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Wireless sensor network (WSN) is widely used in environmental conditions where the systems depend on sensing and monitoring approach. Water pollution monitoring system depends on a network of wireless sensing nodes which communicate together depending on a specific topological order. The nodes distributed in a harsh environment to detect the polluted zones within the WSN range based on the sensed data. WSN exposes several malicious attacks as a consequence of its presence in such open environment, so additional techniques are needed alongside with the existing cryptography approach. In this paper an enhanced trust model based on the use of radial base artificial neural network (RBANN) is presented to predict the future behavior of each node based on its weighted direct and indirect behaviors, in order to provide a comprehensive trust model that helps to detect and eliminate malicious nodes within the WSN. The proposed model considered the limited power, storage and processing capabilities of the system.

Wireless sensor network;security;Artificial neural network;trust rate;malicious node;trust model;threat

WoS

Wireless sensor network applications range from industrial automation and control, agricultural and environmental protection, to surveillance and medicine. In most applications, data are highly sensitive and must be protected from any type of attack and abuse. Security challenges in wireless sensor networks are mainly defined by the power and computing resources of sensor devices, memory size, quality of radio channels and susceptibility to physical capture. In this article, an embedded sensor node microcontroller designed to support sensor network applications with severe security demands is presented. It features a low power 16-bitprocessor core supported by a number of hardware accelerators designed to perform complex operations required by advanced crypto algorithms. The microcontroller integrates an embedded Flash and an 8-channel 12-bit analog-to-digital converter making it a good solution for low-power sensor nodes. The article discusses the most important security topics in wireless sensor networks and presents the architecture of the proposed hardware solution. Furthermore, it gives details on the chip implementation, verification and hardware evaluation. Finally, the chip power dissipation and performance figures are estimated and analyzed.

sensor node;security;cryptography;processor;system-on-chip

WoS

Wireless sensor network(WSN) contains many specially distributed sensors which collect information for people to analyze appointed objects in real-time. WSN is deployed widely in many fields, such as fire detection and remote health care monitoring. User authentication is an important part for the communication of WSN. In 2014, Jiang et al. and Choi et al. proposed their authentication schemes for WSN, respectively. However, we find some weaknesses in them. Jiang et al.'s scheme cannot resist the De-Synchronization attack, the off-line guessing attack and the user forgery attack. Besides, it does not keep the character of strong forward security. Choi et al.'s scheme is under the off-line password guessing attack and the user impersonation attack without user anonymity. We present an improved authentication scheme and prove it to be secure with the formal security model. Also, we analyze the concrete secure characters and the performance of our scheme. Through comparison with some recent schemes, our scheme is more practical and fit for applications.

Wireless sensor network;Off-line guessing attack;Formal proof;Smart card

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Wireless sensor networks (WSNs) are a collection of several small and inexpensive battery-powered nodes, commonly used to monitor regions of interests and to collect data from the environment. Several issues exist in routing data packets through WSN, but the most crucial problem is energy. There are a number of routing approaches in WSNs that address the issue of energy by the use of different energy-efficient methods. This paper, presents a brief summary of routing and related issues in WSNs. The most recent energy-efficient data routing approaches are reviewed and categorized based on their aims and methodologies. The traditional battery based energy sources for sensor nodes and the conventional energy harvesting mechanisms that are widely used to in energy replenishment in WSN are reviewed. Then a new emerging energy harvesting technology that uses piezoelectric nanogenerators to supply power to nanosensor; the type of sensors that cannot be charged by conventional energy harvesters are explained. The energy consumption reduction routing strategies in WSN are also discussed. Furthermore, comparisons of the variety of energy harvesting mechanisms and battery power routing protocols that have been discussed are presented, eliciting their advantages, disadvantages and their specific feature. Finally, a highlight of the challenges and future works in this research domain is presented.

Energy harvesting;Battery power;Routing;Piezoelectric nanogenerators;Sensor nodes

WoS

Wireless Sensor Networks (WSNs) are a growing subset of the emerging Internet of Things (IoT). WSNs reduce the cost of deployment over wired alternatives; consequently, use is increasing in home automation, critical infrastructure, smart metering, and security solutions. Few published works evaluate the security of proprietary WSN protocols due to the lack of low-cost and effective research tools. One such protocol is ITU-T G. 9959-based Z-Wave, which maintains wide acceptance within the IoT market. Concurrently, the use of software-defined radios (SDRs) is experiencing significant growth due to lowcost and open-source platforms. Using SDRs, network security professionals are able to evaluate WSNs and identify avenues of attack which historically required large investments in RF equipment and specialized skill sets. Recent work introduces Scapy-radio, a generic SDR-based wireless monitor/injection tool, designed to simplify the development of penetration testing capabilities for wireless networks. Other works demonstrate methods for fingerprinting transceivers for the IEEE 802.11b and IEEE 802.15.4 standards by analyzing packet reception rates when preamble lengths are manipulated. This work significantly expands Scapy-radio, providing broad support for the Z-Wave protocol using the low-cost HackRF SDR to investigate cooperative and non-cooperative fingerprinting techniques. Specifically, this work demonstrates transceiver type fingerprinting through experimental analysis of packet reception with respect to preamble length across eight devices from five manufactures, utilizing the two most widely-used Z-Wave transceivers. Furthermore, this work presents EZ-Wave, a set of Z-Wave network reconnaissance tools capable of network discovery and enumeration, device fingerprinting, and gathering device status information. Herein this work successfully demonstrates methods for conducting network reconnaissance on a Z-Wave Home Area Network and transceiver type fingerprinting through preamble manipulation with greater than 99% accuracy.

internet of things;wireless sensor networks;Z-Wave;transceiver fingerprinting;software-defined radios

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Wireless sensor networks (WSNs) are characterized by localized interactions, that is, protocols are often based on message exchanges within a node's direct radio range. We recognize that for these protocols to work effectively, nodes must have consistent information about their shared neighborhoods. Different types of faults, however, can affect this information, severely impacting a protocol's performance. We factor this problem out of existing WSN protocols and argue that a notion of neighborhood view consistency (NVC) can be embedded within existing designs to improve their performance. To this end, we study the problem from both a theoretical and a system perspective. We prove that the problem cannot be solved in an asynchronous system using any of Chandra and Toueg's failure detectors. Because of this, we introduce a new software device called pseudocrash failure detector (PCD), study its properties, and identify necessary and sufficient conditions for solving NVC with PCDs. We prove that, in the presence of transient faults, NVC is impossible to solve with any PCDs, thus define two weaker specifications of the problem. We develop a global algorithm that satisfies both specifications in the presence of unidirectional links, and a localized algorithm that solves the weakest specification in networks of bidirectional links. We implement the latter atop two different WSN operating systems, integrate our implementations with four different WSN protocols, and run extensive micro-benchmarks and full-stack experiments on a real 90-node WSN testbed. Our results show that the performance significantly improves for NVC-equipped protocols; for example, the Collection Tree Protocol (CTP) halves energy consumption with higher data delivery.

Wireless sensor networks;localized interactions;neighborhoods;fault-tolerance;consistency;views;transient faults;pseudocrashes

WoS

Wireless sensor networks (WSNs) are susceptible to many security threats and are specifically prone to physical node capture in which the adversary can easily launch the so-called insider attacks such as node compromise, bypassing the traditional security mechanisms based on cryptography primitives. So, the compromised nodes can be modified to misbehave and disrupt the entire network and can successfully perform the authentication process with their neighbors, which have no way to distinguish fraudulent nodes from trustworthy ones. Trust and reputation systems have been recently suggested as a powerful tools and an attractive complement to cryptography-based schemes in securing WSNs. They provide ability to detect and isolate both faulty and malicious nodes. Considerable research has been done on modeling and managing trust and reputation. However, trust topic issue in WSNs remains an open and challenging field. In this paper, we propose a Risk-aware Reputation-based Trust (RaRTrust) model for WSNs. Our novel framework uses both reputation and risk to evaluate trustworthiness of a sensor node. Risk evaluation is used to deal with the dramatic spoiling of nodes, which makes RaRTrust robust to on-off attack and differ from other trust models based only on reputation. This paper contributes to model the risk as opinion of short-term trustworthiness combining with traditional reputation evaluation to derive trustworthiness in WSNs.

Wireless sensor networks;Network security;Trust management;Reputation evaluation;Risk evaluation

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Wireless Sensor Networks (WSNs) consists of large number of spatially distributed configurable sensors, to meet the requirements of industrial, military, precision agriculture and health monitoring applications with ease of implementation and maintenance cost. Transmission of data requires both energy and quality of service (QoS) aware routing to ensure efficient use of the sensors and effective access of the gathered information. Design of WSNs considering its issues is challenging task and leads to complex algorithm design which are difficult to analyze by analytical methods and by physical measurements. Deploying test-beds supposes a huge effort. In deed Computer aided simulation is the feasible approach for analysis of WSNs. We addressed different types of simulators along with their key features and their applicability for simulation in numerous application areas.

WSN;QoS;Simulators;Emulator;Performance parameters

WoS

Wireless sensor networks (WSNs) contain multiple nodes of the same configuration and type. The biggest challenge nowadays is to communicate with heterogeneous nodes of different WSNs. To communicate with distinct networks, an application requires generic middleware. This middleware should be able to translate the requests for contrary WSNs. Most of the wireless nodes use the TinyOS or Contiki operating systems. These operating systems vary in their architecture, configuration and programming model. An application cannot communicate with heterogeneous networks because of their divergent nature. In this paper, we design and implement TinyCO (a generic middleware model for WSNs), which overcomes these challenges. TinyCO is a general-purpose service-oriented middleware model. This middleware model can identify the heterogeneous networks based on TinyOS and Contiki. It allows applications to communicate with these networks using a generic request. This middleware interprets the given input into signatures of the underlying networks. This proposed middleware is implemented in Java and tested on TelosB motes.

wireless sensor networks;middleware;heterogeneous network;interoperability;service-oriented architecture

WoS

Wireless sensor networks (WSNs) have become increasingly popular in many applications across a broad range of fields. Securing WSNs poses unique challenges mainly due to their resource constraints. Traditional public key cryptography (PKC) for instance is considered to be too computationally expensive for direct implementation in WSNs. Elliptic curve cryptography (ECC) allows one to reach the same level of security as traditional PKC using smaller key sizes. In this paper, a key distribution protocol was designed to securely provide authenticated motes with secret system keys using ECC based cryptographic functions. The designed scheme met the minimum requirements for a key distribution scheme to be considered secure and efficient in WSNs.

wireless sensor networks;key distribution;authentication;network security;elliptic curve cryptography

WoS

Wireless sensor networks (WSNs) have been widely used in different fields, such as battle field, environment monitoring, and intrusion detection, where amount of nodes are deployed. There are many factors make sensor nodes being more vulnerable to be attacked and compromised. In order to address the issue, many different schemes and methods are proposed. Trust evaluation and trust management play an important role in detecting the malicious nodes. In this paper, we propose a trust management system for clustered WSNs monitoring the sensor nodes' behaviors and evaluating their trust values. This system employs a hash algorithm for generating identify labels for sensor nodes to distinguish external attackers from normal nodes and dynamically manages the trust value of each node to detect the compromised nodes based on the trust evaluating model, which is based on beta density function. The simulation results show that our scheme can detect the malicious nodes quickly, which prevents clustered WSNs from external attacks and internal compromised nodes' attacks. Copyright (c) 2015 John Wiley & Sons, Ltd.

trust management;trust evaluation;wireless sensor networks;network security

WoS

Wireless sensor networks (WSNs) have been widely used in structural health monitoring (SHM) for their attractive features such as low cost, high efficiency, and flexibility. The optimal wireless sensor placement in SHM has much difference with traditional tethered sensors. This paper presents a new method to extract the optimal wireless sensor configuration for SHM An objective function that is a trade-off, between the linear dependence of identified mode shapes and the connectivity of WSNs is proposed. A discrete firefly algorithm (DFA) that is based on the basic firefly algorithm (FA) with continuous variable is developed to solve this complicated optimization problem. Some improvements like the one-dimensional binary coding system, the Hamming distance and a parthenogenesis movement scheme are introduced to make the underlying concept of FA applicable in OWSP. A numerical experiment using a long-span suspension bridge demonstrates that the DFA can find the optimal wireless sensor configuration with high dependence of identified mode shapes and good connectivity of the WSN. The effectiveness of the proposed method is validated.

structural health monitoring;optimal sensor placement;firefly algorithm;wireless sensor network;modal assurance criterion

WoS

Wireless sensor networks (WSNs) have emerged as an important research paradigm since the last decade, thereby motivating researches to take up new theoretical and practical challenges. WSNs need to be provided with efficient security features generally due to their deployment in inaccessible terrain and also communication being in the wireless domain. Therefore the question of providing security to such networks arises but the major constraints are the limited resources present in the sensor nodes. Prior importance is given to the energy parameter as it is the most vital component of the sensor nodes. So the objective of any intrusion detection framework would be to design robust mechanisms capable of handling attacks in energy efficient manner. Intrusion detection is used in WSNs because of their ability to detect unknown attacks and finding means to thwart them for preserving energy. Therefore energy efficient intrusion detection has become a significant research area for researchers. Keeping this in mind, we survey the major topics of energy efficient intrusion detection in WSNs. The survey work presents topics such as the fundamentals of intrusion detection techniques, as well as the various energy saving mechanisms used in different architectural models. The earlier achievements in energy efficient intrusion detection in WSNs are also summarized and existing problems are discussed. We also give an insight into the possible directions for future work in intrusion detection by highlighting open research areas.

Anomaly based detection;intrusion detection system;intrusion prevention;signature based detection;wireless sensor network

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Wireless sensor networks are already employed in numerous applications including military, industry, and health. Among the several inherent limitations in wireless sensor network, security is a critical concern. The declared security functions of wireless devices should be well verified. In this study, a security testing method based on security levels is proposed for wireless sensor networks. In addition, an experimental security testing platform for WIA-PA-based wireless sensor networks is implemented. The test results show that the platform is a feasible platform for assessing device security levels in wireless sensor networks.

Distributed networks;sensor networks;security;testing;verification

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Wireless sensor networks are commonly used for critical security tasks such as intrusion or tamper detection, so they must be protected. Based on previous research, in this paper, we present a kind of routing protocol based on node convergence degree and the trust value which is named BCDTV. We focus on the security routing algorithm design and work process, including the election of cluster head and the establishment of cluster, the collection and transmission of the sensing information of wireless sensor networks. Simulation results show that the protocol can prevent some malicious behaviour of malicious nodes effectively.

wireless sensor networks;convergence degree;trust value;security routing

WoS

Wireless Sensor Networks are installed in hostile areas. The security issues in wireless sensor networks are very important. Getting secure links between nodes is a challenging problem in WSNs. They are more vulnerable to security attacks than wired networks. In order to protect the sensitive data in WSN can be protected using secret keys to encrypt the exchanged messages between communicating nodes. Key management is essential for many security services such as confidentiality and authentication. The symmetric or asymmetric key cryptography or Trusted-server schemes are used to solve this problem. Asymmetric key cryptography increases network security but it increases computational, memory, and energy overhead. Symmetric key cryptography provides less security and it is efficient key management scheme. Trusted server schemes use key management server. Because there is usually no trusted infrastructure it is not very suitable for sensor networks. In this paper, we have proposed Mobile Agent (MA) Based Key Distribution (MAKD). In MAKD, Mobile Agents are used for dissemination of public keys and update of shared keys. Each sensor node constructs different symmetric keys with its neighbors, and communication security is achieved by data encryption and mutual authentication with these keys. Simulation results show that MAKD is scalable and with less communication overhead.

Wireless Sensor Networks;Mobile Agents;key management;cryptography

WoS

Wireless Sensor Networks are installed in hostile areas. The security issues in wireless sensor networks are very important. Getting secure links between nodes is a challenging problem in WSNs. They are more vulnerable to security attacks than wired networks. In order to protect the sensitive data in WSN can be protected using secret keys to encrypt the exchanged messages between communicating nodes. Key management is essential for many security services such as confidentiality and authentication. The symmetric or asymmetric key cryptography or Trusted-server schemes are used to solve this problem. Asymmetric key cryptography increases network security but it increases computational, memory, and energy overhead. Symmetric key cryptography provides less security and it is efficient key management scheme. Trusted server schemes use key management server. Because there is usually no trusted infrastructure it is not very suitable for sensor networks. In this paper, we have proposed Mobile Agent (MA) Based Key Distribution (MAKD). In MAKD, Mobile Agents are used for dissemination of public keys and update of shared keys. Each sensor node constructs different symmetric keys with its neighbors, and communication security is achieved by data encryption and mutual authentication with these keys. Simulation results show that MAKD is scalable and with less memory overhead.

Wireless Sensor Networks;Mobile Agents;key management;cryptography

WoS

Wireless sensor networks based-structural health monitoring is being widely researched. To make a better structural health monitoring, real-time acquisition of structural responses is indispensable. However, the data, which is large in number especially when they are of moving structures, are difficult to be measured, and the adaptation of wireless sensor networks further limits structural health monitoring within the capacity of radio frequency. In this study, cochlea-inspired artificial filter bank was developed as a technological way to efficiently acquire dynamic responses at a wireless sensor networks based-structural health monitoring. The cochlea-inspired artificial filter bank developed in this article was enabled to acquire valid dynamic responses of compressed size around the frequency range of interest by simulating raw data to the full regarding to time and frequency of dynamic responses. In addition, the digitalized cochlea-inspired artificial filter bank was also found to fix the disadvantages of analogue filters by its easy and efficient development of logics, optimization, design of software, and real-time autonomous execution. Finally, the cochleainspired artificial filter bank makes it possible to compress and reduce the vast amount of real-time dynamic responses usually obtained by means of a uniform rate of sample, into a manageable size. It is thus expected to open up a new paradigm in the Wireless sensor networks based-structural health monitoring of civil structures by facilitating an efficient measurement and management of data base.

Cochlear-inspired Artificial Filter Bank (CAFB);Band-pass filter Optimizing Algorithm (BOA);Peak-picking Algorithm (PPA);Reconstruction Error (RE);Compressive Ratio (CR);Structural Health Monitoring (SHM);Data Compressing

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Wireless technologies combined with advanced computing are changing industrial communications. Industrial wireless networks can improve the monitoring and the control of the entire system by jointly exploiting massively interacting communication and distributed computing paradigms. In this paper, we develop a wireless cloud platform for supporting critical data publishing and distributed sensing of the surrounding environment. The cloud system is designed as a self-contained network that interacts with devices exploiting the time synchronized channel hopping protocol (TSCH), supported by WirelessHART (IEC 62591). The cloud platform augments industry-standard networking functions as it handles the delivery (or publishing) of latency and throughput-critical data by implementing a cooperative-multihop forwarding scheme. In addition, it supports distributed sensing functions through consensus-based algorithms. Experimental activities are presented to show the feasibility of the approach in two real industrial plant sites representative of typical indoor and outdoor environments. Validation of cooperative forwarding schemes shows substantial improvements compared with standard industrial solutions. Distributed sensing functions are developed to enable the autonomous identification of recurring cochannel interference patterns.

Consensus-based distributed estimation;cooperative communication;dense cloud networks;industrial Internet of Things;industrial wireless sensor networks (IWSNs);interference detection;sensor-cloud networking

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With a large number of scientific literature, it has been difficult to search for a set of relevant articles and to rank them. In this work, we propose a generalized network analysis approach (called N-star ranking model) for sorting them based on . The ranking of the result is considered in the mutual relationships between another classes: keyword, publication, citation. From the model, we propose two ranks for this problem: the Universal-Publication rank - (UP rank) and Topic-Publication rank (TP rank). We also study two simple ranks based on citation counting (RCC rank) and content matching (RCM rank). We propose the metrics for ranking comparison and analysis on two criteria value and order. We have conducted the experimentations for confirming the predictions and studying the features of the ranks. The results show that the proposed ranks are very impressive for the given problem since they consider the query/topic, the content of publication and the citations in the ranking model.

Scientific search engine;Scientific recommendation system;Keyword-based query;Scientific topic ranking;PageRank;N-star ranking system

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With a national maternal mortality rate of 401 per 100,000 live births, it is clear that becoming a mother in Togo carries significant risk. In order to inform the scale-up of maternal health services, this qualitative baseline evaluation explored barriers to maternal and reproductive health in the Kozah district of northern Togo through semi-structured interviews with 21 community stake-holders and focus group discussions with four groups of six mothers. Inter-related factors including financial means, distance from health posts, gender roles, cultural beliefs, and patient-provider relations all influence women's care-seeking behavior. Lack of financial means renders the cost of crucial maternal health services prohibitive, and husbands' resistance to family planning and health-care financing compounds the challenges women face meeting essential maternal health needs. Our findings suggest that waiving user fees, providing facility-based delivery free of cost, improving transportation options, and fostering trust in and access to health centers could significantly improve maternal health in the Kozah district.

maternal health;Togo;qualitative

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With a shift in focus from genes to cells, systems approach is not only revolutionizing cell biology, but is also providing impetus for clinical medicine to shift from a reductionistic to a holistic approach for efficient disease management. This inevitably brings into focus one of the longest unbroken healthcare systems in the world, namely ayurveda, the medical system indigenous to Indian subcontinent. A distinctive feature of ayurveda is its systems approach to health and disease. Through the theoretical framework of vata, pitta and kapha, ayurveda offers a new paradigm for understanding the human system as a networked functional entity wherein system properties are integral components. An open-minded dialogue between the cell-centric systems biology and organism-centric ayurveda can open new exciting vistas for research beneficial to both sciences, which could leave a major imprint on clinical practice.

Ayurveda;kapha;pitta;systems approach;tridosha;vata

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With a United States-based sample of 326 sexual minority men, the present study tested hypotheses derived from objectification theory (Fredrickson & Roberts, 1997), minority stress theory (e.g., Meyer, 2003), and prior research regarding men and body image (e.g., McCreary & Sasse, 2000). Specifically, we examined a path model wherein objectification constructs (internalized standards of attractiveness, body surveillance, body dissatisfaction, and drive for muscularity) and a minority stress variable (internalized heterosexism) were direct and indirect predictors of intention to use anabolic-androgenic steroids (AAS) and compulsive exercise. Results of the path model yielded adequate fit to the data. Regarding direct links, internalized heterosexism was correlated positively with internalized standards of attractiveness and related positively to body dissatisfaction, internalized standards of attractiveness related positively to drive for muscularity and body surveillance, and drive for muscularity related positively with intention to use AAS and compulsive exercise; internalized standards of attractiveness yielded a significant and positive indirect link to intention to use AAS through drive for muscularity. Implications of our findings, regarding the application and limitations of the objectification theory framework for research and practice with sexual minority men, are further discussed.

gay men;objectification;sexual minority men;internalized heterosexism;body image

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With advances in both medical imaging and computer programming, two-dimensional axial images can be processed into other reformatted views (sagittal and coronal) and three-dimensional (3D) virtual models that represent a patients' own anatomy. This processed digital information can be analyzed in detail by orthopedic surgeons to perform patient-specific orthopedic procedures. The use of 3D printing is rising and has become more prevalent in medical applications over the last decade as surgeons and researchers are increasingly utilizing the technology's flexibility in manufacturing objects. 3D printing is a type of manufacturing process in which materials such as plastic or metal are deposited in layers to create a 3D object from a digital model. This additive manufacturing method has the advantage of fabricating objects with complex freeform geometry, which is impossible using traditional subtractive manufacturing methods. Specifically in surgical applications, the 3D printing techniques can not only generate models that give a better understanding of the complex anatomy and pathology of the patients and aid in education and surgical training, but can also produce patient-specific surgical guides or even custom implants that are tailor-made to the surgical requirements. As the clinical workflow of the 3D printing technology continues to evolve, orthopedic surgeons should embrace the latest knowledge of the technology and incorporate it into their clinical practice for patient-specific orthopedic applications. This paper is written to help orthopedic surgeons stay up-to-date on the emerging 3D technology, starting from the acquisition of clinical imaging to 3D printing for patient-specific applications in orthopedics. It 1) presents the necessary steps to prepare the medical images that are required for 3D printing, 2) reviews the current applications of 3D printing in patient-specific orthopedic procedures, 3) discusses the potential advantages and limitations of 3D-printed custom orthopedic implants, and 4) suggests the directions for future development. The 3D printing technology has been reported to be beneficial in patient-specific orthopedics, such as in the creation of anatomic models for surgical planning, education and surgical training, patient-specific instruments, and 3D-printed custom implants. Besides being anatomically conformed to a patient's surgical requirement, 3D-printed implants can be fabricated with scaffold lattices that may facilitate osteointegration and reduce implant stiffness. However, limitations including high cost of the implants, the lead time in manufacturing, and lack of intraoperative flexibility need to be addressed. New biomimetic materials have been investigated for use in 3D printing. To increase utilization of 3D printing technology in orthopedics, an all-in-one computer platform should be developed for easy planning and seamless communications among different care providers. Further studies are needed to investigate the real clinical efficacy of 3D printings in orthopedic applications.

3D printing;patient-specific orthopedics;custom implants;patient-specific instrument;image processing

WoS

With advances in DNA sequencing technology, it is increasingly common and tractable to informatically look for genes of interest in the genomic databases of parasitic organisms and infer cellular states. Assignment of a putative gene function based on homology to functionally characterized genes in other organisms, though powerful, relies on the implicit assumption of functional homology, i.e. that orthology indicates conserved function. Eukaryotes reveal a dazzling array of cellular features and structural organization, suggesting a concomitant diversity in their underlying molecular machinery. Significantly, examples of novel functions for pre-existing or new paralogues are not uncommon. Do these examples undermine the basic assumption of functional homology, especially in parasitic protists, which are often highly derived? Here we examine the extent to which functional homology exists between organisms spanning the eukaryotic lineage. By comparing membrane trafficking proteins between parasitic protists and traditional model organisms, where direct functional evidence is available, we find that function is indeed largely conserved between orthologues, albeit with significant adaptation arising from the unique biological features within each lineage. (C) 2016 Elsevier B.V. All rights reserved.

Membrane-trafficking;Protist;Parasite;Genomics;Functional homology;Endomembrane

WoS

With advances in technology, frequent pattern mining has been used widely in our daily lives. By using this technology, one can obtain interesting or useful information that would help one make decisions and apply judgment. For example, marketplace managers mine transaction data to obtain information that can help improve services, understand customer buying habits, determine a suitable scheme for placement of goods to increase profits, or for medical and biotechnology applications. However, the rate at which data is generated is very rapid, leading to problems caused by Big Data. Therefore, many researchers have studied distributed, parallel and cloud computing technology to select the best among them. However, data mining uses multiple computing nodes, which requires the transmission of a considerable amount of data in a network environment. The available network bandwidth is limited when many different tasks are being transmitted at the same time and many servers are working in the same network segment. This results in poor transmission, causing severe transfer delay, either internal or external to the network. Thus, we propose the fast and distributed mining algorithm for discovering frequent patterns in congested networks (FDMCN) algorithm, which is based on CARM. The main purpose is to reduce FP-tree transmission such that only a portion of the information is required for mining using computing nodes. The results of empirical evaluation under various simulation conditions show that the proposed method FDMCN delivers excellent performance in terms of execution efficiency and scalability when compared with the PSWS algorithm.

Data mining;Frequent pattern mining;Congested networks;Distributed computing

WoS

With aging, skin undergoes progressive structural and functional degeneration that leaves it prone to a wide variety of bothersome and even serious conditions and diseases. As skin conditions and diseases may affect all ages from cradle to grave, a disproportionate burden will clearly fall on the elderly and may significantly impact on quality of life (QoL). With a reduced ability of the skin to regenerate, the elderly are at an increased risk of skin breakdowns from even the simplest insults. It is therefore vital that skin care in the late adulthood is seen as a priority among both clinicians and caregivers. The scientific literature on diagnosing and assessing age-related skin conditions and diseases is vast; however, when it comes to preventive care and treatment, the scientific data available is less profound, and the recommendations are often based on personal experience, opinions or at best on consensus documents rather than on scientific data retrieved from controlled clinical trials. In addition to the absence of the scientific data, the imprecise terminology to describe the topical products, as well as the lack of understanding the essence of the vehicle, contributes to vague and often unhelpfully product recommendations. This paper aims to elucidate some basic principles of skincare, the choice of skincare products and their regulatory status. The paper discusses adherence to topical therapies, percutaneous absorption in the elderly, and skin surface pH and skin care. Lastly, it also discusses skin care principles in selected age related skin conditions and diseases.

Skin care;Aging;Administration topical;Aged

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With an ever-increasing accessibility to different multimedia contents in real-time, it is difficult for users to identify the proper resources from such a vast number of choices. By utilizing the user's context while consuming diverse multimedia contents, we can identify different personal preferences and settings. However, there is a need to reinforce the recommendation process in a systematic way, with context-adaptive information. The contributions of this paper are twofold. First, we propose a framework, called RecAm, which enables the collection of contextual information and the delivery of resulted recommendation by adapting the user's environment using Ambient Intelligent (AmI) Interfaces. Second, we propose a recommendation model that establishes a bridge between the multimedia resources, user joint preferences, and the detected contextual information. Hence, we obtain a comprehensive view of the user's context, as well as provide a personalized environment to deliver the feedback. We demonstrate the feasibility of RecAm with two prototypes applications that use contextual information for recommendations. The offline experiment conducted shows the improvement of delivering personalized recommendations based on the user's context on two real-world datasets.

Context media search;Context-aware recommendation;Collaborative context;Context awareness;Ambient intelligent

WoS

With an experimental design, we assess the reliability of eyewitness identification. After viewing a staged nonviolent crime, subjects heard a confederate provide an inaccurate description of the criminal. Subjects were then randomly placed in one of several experimental conditions, and their ability to identify the criminal was assessed. While subjects were highly confident in their ability to accurately identify the perpetrator, their ability to provide accurate information about the perpetrator was relatively low. All of the following were shown to significantly impact the probability that our eyewitnesses could provide accurate eyewitness information: length of time between the subject witnessing the crime and being asked to identify the perpetrator; the subjects' physical distance from the witnessed crime; the content of the photo lineup (whether or not the criminal was included); and prelineup instructions provided to the eyewitness. Similar to prior research, our results highlight the dangerous fallibility of eyewitness identification, particularly for co-witness contamination.

eyewitness identification;postevent contamination;prelineup instructions

WoS

With an increase in the survival rate and shift in the age composition of women, menopause is emerging as one of the major health issues in the sociology of health. Thanks to demographic transition, a sizeable number of women will now spend one-third to half of their life as post-menopausal. The present paper focuses upon the prevailing discourses on women's menopausal health in the Indian setting. It suggests that though women's health beliefs, behaviour and coping patterns in the Indian context differ from their Western counterparts, huge similarities are found in sociocultural and medical discourses on menopause. In most of these discourses women are marginalised and seen as inferior to men. However, the epidemiological studies on women's menopausal health in India suggest that menopause is a normal life event where menstruation ceases; it is not associated with the bio-psycho-social morbidity paradigm as prevalent in the West.

menopause;gender;medicalisation;biomedical;sociology of health;sociocultural;menopausal health

WoS

With an increasing amount of volatile renewable electrical energy, the balancing of demand and supply becomes more and more demanding. Demand response is one of the emerging tools in this new landscape. Targeting service sector buildings, we investigated a tariff driven demand response model as a means to shave electrical peak loads and thus reducing grid balancing energy. In this paper is presented a software framework for load shifting which uses a tariff signal for the electric energy as minimization target. The framework can be used both on top of an existing building management system to shift heat generation towards low-tariff times, as well as to simulate load shifting for different buildings, heat pumps and storage configurations. Its modular architecture allows us to easily replace optimizers, weather data providers or building management system adapters. Our results show that even with the current TOU tariff system, up to 34% of cost savings and up to 20% reduction in energy consumption can be achieved. With Sub-MPC, a modifiedMPCoptimizer, we could reduce computing times by a factor 50, while only slightly affecting the quality of the optimization. With an increasing amount of volatile renewable electrical energy, the balancing of demand and supply becomes more and more demanding. Demand response is one of the emerging tools in this new landscape. Targeting service sector buildings, we investigated a tariff driven demand response model as a means to shave electrical peak loads and thus reducing grid balancing energy. In this paper is presented a software framework for load shifting which uses a tariff signal for the electric energy as minimization target. The framework can be used both on top of an existing building management system to shift heat generation towards low-tariff times, as well as to simulate load shifting for different buildings, heat pumps and storage configurations. Its modular architecture allows us to easily replace optimizers, weather data providers or building management system adapters. Our results show that even with the current TOU tariff system, up to 34 % of cost savings and up to 20 % reduction in energy consumption can be achieved. With Sub-MPC, a modified MPC optimizer, we could reduce computing times by a factor 50, while only slightly affecting the quality of the optimization.

ICT in buildings and housing;Building energy operating systems;Heating devices and energy networks;Demand response;Dynamic electricity prices;Load shifting;Simulation;Building automation

WoS

With an increasing number of wind turbines being erected offshore, there is a need for cost-effective, predictive, and proactive maintenance. A large fraction of wind turbine downtime is due to bearing failures, particularly in the generator and gearbox. One way of assessing impending problems is to install vibration sensors in key positions on these subassemblies. Such equipment can be costly and requires sophisticated software for analysis of the data. An alternative approach, which does not require extra sensors, is investigated in this paper. This involves monitoring the power output of a variable-speed wind turbine generator and processing the data using a wavelet in order to extract the strength of particular frequency components, characteristic of faults. This has been done for doubly fed induction generators (DFIGs), commonly used in modern variable-speed wind turbines. The technique is first validated on a test rig under controlled fault conditions and then is applied to two operational wind turbine DFIGs where generator shaft misalignment was detected. For one of these turbines, the technique detected a problem 3 months before a bearing failure was recorded.

Condition monitoring;electrical generator;signal processing;wind energy;wind turbines

WoS

With an insightful policy, rainwater harvesting (RWH) can be promoted as a core adaptation strategy for achieving global water security, reaching the Millennium Development Goals (MDGs) and sustaining water resources. The microbial and chemical quality of RWH samples collected from tanks in a sustainable housing development in Kleinmond, South Africa, were monitored. Results indicated that the tank water quality was within all the chemical standards (cations and anions) analysed for potable water. However, the counts of the indicator organisms, for example, total coliforms and Escherichia coli, exceeded the guidelines stipulated by the Department of Water Affairs and Forestry (1996). The microbial analysis results thus indicate that the tank water was not fit for potable use without treatment. A social research project was then conducted to describe, amongst others, the condition of the tank and the users' knowledge of the RWH system. In addition, demographic data, viz., gender, household size and employment status, etc., were gathered in order to provide a socioeconomic background description of the study population. Data were gathered by means of face-to-face interviews with 68 respondents. Generally, RWH was used for washing clothes and for cleaning inside and outside the houses. This study noted that without acceptance and necessary training to maintain and use the tank optimally, it is possible that social development projects, such as the one in Kleinmond, will not be sustainable.

domestic rainwater harvesting;microbial and chemical quality;social perception;acceptance

WoS

With climate change high on the political agenda, weather has emerged as an important issue in travel behavioural research and urban planning. While various studies demonstrate profound effects of weather on travel behaviours, limited attention has been paid to subjective weather experiences and the psychological mechanisms that may (partially) underlie these effects. This paper integrates theoretical insights on outdoor thermal comfort, weather perceptions and emotional experiences in the context of travel behaviour. Drawing on unique panel travel diary data for 945 Greater Rotterdam respondents (The Netherlands), this paper aims to investigate how and to what extent weather conditions affect transport mode choices, outdoor thermal perceptions and emotional travel experiences. Our findings point out that observed dry, calm, sunny and warm but not too hot weather conditions stimulate cycling over other transport modes and - via mechanisms of thermal and mechanical comfort - lead to more pleasant emotions during travel. Overall, public transport users have less pleasant emotional experiences than users of other transport modes, while active mode users appear most weather sensitive. The theoretical contributions and empirical findings are discussed in the context of climate change and climate-sensitive urban planning. (C) 2016 Elsevier Ltd. All rights reserved.

Weather;Thermal comfort;Transport mode choice;Emotion;Netherlands

WoS

With climate change, extreme heat (EH) events are increasing, so it is important to understand who is vulnerable to heat-associated morbidity. We determined the association between EH and hospitalizations for all natural causes; cardiovascular, respiratory, and renal diseases; diabetes mellitus; and acute myocardial infarction in Michigan, USA, at different intensities and durations. We assessed confounding by ozone and how individual characteristics and health insurance payer (a proxy for income) modified these associations. We obtained Michigan Inpatient Database, National Climatic Data Center, and US Environmental Protection Agency ozone data for May-September, 2000-2009 for three Michigan counties. We employed a case-crossover design and modeled EH as an indicator for temperature above the 95th, 97th, or 99th percentile thresholds for 1, 2, 3, or 4 days. We examined effect modification by patient age, race, sex, and health insurance payer and pooled the county results. Among non-whites, the pooled odds ratio for hospitalization on EH (97th percentile threshold) vs. non-EH days for renal diseases was 1.37 (95 % CI = 1.13-1.66), which increased with increasing EH intensity, but was null among whites (OR = 1.00, 95 % CI = 0.81, 1.25). We observed a null association between EH and cardiovascular hospitalization. EH (99th percentile threshold) was associated with myocardial infarction hospitalizations. Confounding by ozone was minimal. EH was associated with hospitalizations for renal disease among non-whites. This information on vulnerability to heat-associated morbidity helps characterize the public health burden of EH and target interventions including patient education.

Hospitalization;Temperature;Morbidity;Heat wave;Heat

WoS

With cloud computing technology becoming more mature, it is essential to combine the big data processing tool Hadoop with the Infrastructure as a Service (IaaS) cloud platform. In this study, we first propose a new Dynamic Hadoop Cluster on IaaS (DHCI) architecture, which includes four key modules: monitoring, scheduling, Virtual Machine (VM) management, and VM migration modules. The load of both physical hosts and VMs is collected by the monitoring module and can be used to design resource scheduling and data locality solutions. Second, we present a simple load feedback-based resource scheduling scheme. The resource allocation can be avoided on overburdened physical hosts or the strong scalability of virtual cluster can be achieved by fluctuating the number of VMs. To improve the flexibility, we adopt the separated deployment of the computation and storage VMs in the DHCI architecture, which negatively impacts the data locality. Third, we reuse the method of VM migration and propose a dynamic migration-based data locality scheme using parallel computing entropy. We migrate the computation nodes to different host(s) or rack(s) where the corresponding storage nodes are deployed to satisfy the requirement of data locality. We evaluate our solutions in a realistic scenario based on OpenStack. Substantial experimental results demonstrate the effectiveness of our solutions that contribute to balance the workload and performance improvement, even under heavy-loaded cloud system conditions.

Hadoop;resource scheduling;data locality;Infrastructure as a Service (Iaas);OpenStack

WoS

With continuous development of science and technology, actual data integration and operating path also change greatly. To better improve transmission accuracy of overall data information, and guarantee optimal establishment of computer network security system, accuracy of overall system can improve fundamentally and more efficient computer security treatment measures can be established only when efficient network model operates. This paper simply analyzes the connotation of computer network security risk assessment model, intensively interprets the principle of fuzzy theory and composition of neural network model and finally discusses neural network model of fuzzy theory and fusion system of computer network security. This paper aims to verify system security performance through effective data analysis.

Fuzzy theory;Neural network model;Computer;Network security;Application

WoS

With degradation in quality of life, threat of brain disorders has become a serious concern from past few decades. Dementia is one such abnormality which includes a group of symptoms that deteriorate cognitive functions of the brain. The use of neuroimaging techniques has revealed the abnormal anatomy of Corpus callosum (CC) for diagnosing various brain disorders. This paper focuses on classification of magnetic resonance (MR) images of dementia using CC features. CC is segmented from each mid-sagittal brain MR image using K-means clustering algorithm and then used for feature extraction. Significant features between demented and normal groups are identified using statistical analysis. Depending upon the statistical significance, hybrid feature vectors are designed for male and female dataset. Support vector machine (SVM) and Back propagation neural network (BPNN) classifiers are trained and tested using the designed feature vectors. Considering the sexual dimorphism of CC structure, feature classification is performed separately for male and female data. This paper reports the highest classification accuracy of 97% for male data and 95% for female data.

Back Propagation Neural Network;Corpus Callosum;Dementia;Magnetic Resonance Imaging;Support Vector Machine.

WoS

With deterioration of the electromagnetic environment, microcontroller unit (MCU) electromagnetic susceptibility (EMS) to transient burst interference has become a focus of academia and enterprise. Most electromagnetic compatibility (EMC) studies of MCUs have not taken the effects of aging into account. However, component aging can degrade the physical parameters of an MCU and change its immunity to EMI. This paper proposes a time-equivalent interval accelerated aging methodology combining DC electrical and high temperature stresses. The test results show variations in susceptibility to electrical fast transients (EFT) burst revealing increasing susceptibility. The reasons for MCU immunity drifts in the aging process are discussed. (C) 2016 Elsevier Ltd. All rights reserved.

Microcontroller;Susceptibility;EFT burst;Accelerated aging

WoS

With developments and innovations in technology, new materials and methods have enabled architects and engineers to plan and construct large-scale facilities. However, these developments may also result in serious problems which include budget overruns, completion delays and distress on the part of the facility owner. To avoid these problems, many types of delivery systems which contain force account system, design-bid-build system, design-build system, Construction Management at Risk (CMAR) system and so on have been employed in the world construction market. But every system could not be a complete one because of its own inherit limit. In the midst of the systems, CMAR system is the finally changed delivery one among the systems and has many merits to construct and manage the facilities. In Korea, CMAR system had been introduced conceptually, but it have not been applied to public construction market yet. Therefore, to promote the application of CMAR system in the Korean public construction market, a review of construction delivery systems was conducted with a focus on CMAR systems which were descriptively analyzed. It is suggested that specialized construction management services, streamlined bidding and contracting regulations, and reasonable allotment of contract risk are essential tools for successful construction projects.

CMAR;contract management;construction delivery systems;liability;risk

WoS

With Donald Trump the Republican nominee and Hillary Clinton the Democratic nominee for the 2016 U.S. Presidential election, speculations of why Trump resonates with many Americans are widespread - as are suppositions of whether, independent of party identification, people might vote for Hillary Clinton. The present study, using a sample of American adults (n = 406), investigated whether two ideological beliefs, namely, right-wing authoritarianism (RWA) and social dominance orientation (SDO) uniquely predicted Trump support and voting intentions for Clinton. Cognitive ability as a predictor of RWA and SDO was also tested. Path analyses, controlling for political party identification, revealed that higher RWA and SDO uniquely predicted more favorable attitudes of Trump, greater intentions to vote for Trump, and lower intentions to vote for Clinton. Lower cognitive ability predicted greater RWA and SDO and indirectly predicted more favorable Trump attitudes, greater intentions to vote for Trump and lower intentions to vote for Clinton. (C) 2016 Elsevier Ltd. All rights reserved.

Authoritarianism;Ideological beliefs;Right-wing authoritarianism;Social dominance orientation;Cognitive ability;Voting;Political psychology

WoS

With emerging Network Functions Virtualization (NFV) and Software Defined Networking (SDN) paradigms in Network Management (NM), new network devices and features can immediately become available. Available network resources and services can be altered and optimized in real time to gain the maximum benefit. However, this requires real time analytics information sent to SDN controllers rather than traditional manual offline or batch analytics which deliver outputs in hourly or monthly in NM Systems. As a result, real time analytic is becoming a critical element for NM. In this paper, we describe a configuration free (i.e., non-parametric) streaming data anomaly detection analytic engine for automatic NM system development. We describe the design principles, innovative algorithm design, architecture and implementation of the engine in relation to streaming data and mobile NM. Finally, we present use cases and evaluation results.

Anomaly detection;streaming analytic;machine learning;network management system

WoS

with ever increasing load and insufficient growth of generation and transmission capacities, the operating constraints of modern integrated power system are increasing. It has led to ever increasing dynamic problems of low frequency oscillations in the system that needs to be detected and damped out quickly and efficiently. In electrical power networks small oscillations appear from time to time. These oscillations concern the quantities determining the equilibrium point of the system, and following which, system stability and system behaviors are influenced. The objective of our study is to check the static stability of the high voltage power to small perturbations of electrical network. In this context, after linearizing the system, power system stabilizer (PSS) has so far been extensively utilized to mitigate these problems. This paper presents a novel and efficient approach for the optimal tuning of power system stabilizer parameters (PSS) using a genetic algorithm (GA) with the eigenvalue-based objective function. The proposed approach is implemented and examined in a system with a single machine connected to an infinite bus via a transmission line. The results of this technique have been verified by eigenvalue analysis and time-domain simulations. The obtained results were evaluated and compared with ones obtained by ordinary GAs. Eigenvalue analysis and nonlinear system simulations demonstrated the effectiveness of the proposed approach in damping the electromechanical oscillations and enhancing the system dynamic stability.

genetic algorithms;objective optimization;single machine (SIMB);power system stabilizer;modal analysis

WoS

With existing programming tools, writing high-performance simulation code is labor intensive and requires sacrificing readability and portability. The alternative is to prototype simulations in a high-level language like Matlab, thereby sacrificing performance. The Matlab programming model naturally describes the behavior of an entire physical system using the language of linear algebra. However, simulations also manipulate individual geometric elements, which are best represented using linked data structures like meshes. Translating between the linked data structures and linear algebra comes at significant cost, both to the programmer and to the machine. High-performance implementations avoid the cost by rephrasing the computation in terms of linked or index data structures, leaving the code complicated and monolithic, often increasing its size by an order of magnitude. In this article, we present Simit, a new language for physical simulations that lets the programmer view the system both as a linked data structure in the form of a hypergraph and as a set of global vectors, matrices, and tensors depending on what is convenient at any given time. Simit provides a novel assembly construct that makes it conceptually easy and computationally efficient to move between the two abstractions. Using the information provided by the assembly construct, the compiler generates efficient in-place computation on the graph. We demonstrate that Simit is easy to use: a Simit program is typically shorter than a Matlab program; that it is high performance: a Simit program running sequentially on a CPU performs comparably to hand-optimized simulations; and that it is portable: Simit programs can be compiled for GPUs with no change to the program, delivering 4 to 20x speedups over our optimized CPU code.

Graph;matrix;tensor;simulation

WoS

With expectations for resource efficiency and climate change adaptation in the construction industry, there is an increasing need for contractors to implement sustainable practices. Such action will burden contractors with additional costs that will lower their economic performance. There are few research studies on how sustainability relates to a firm's competitiveness. This paper represents an empirical study of the relationship between sustainability performance and business competitiveness of international construction contractors. An inverse U-shape relationship between contractors' sustainability performance and their international revenue, and a U-shape relationship between contractors' sustainability performance and their international revenue growth was discovered. The findings can help international contractors have a better understanding of the relationship between sustainability performance and business competitiveness, evaluate their current position in the relationship, optimize their resource allocation on sustainable development and integrate sustainability into their strategic planning. Therefore, contractors with high sustainability performance can expect higher international revenue growth, and sustainability performance is likely to become an opportunity for competitive advantage in the international construction market. (C) 2015 Elsevier Ltd. All rights reserved.

Sustainability performance;Business competitiveness;Construction industry;Contractor;International revenue

WoS

With global climate and environment deterioration, the desertification is getting worse and the phenomenon of wind-sand flow frequently occurs in many areas. Hangers of suspension bridges may suffer the impact from wind-sand flow and be damaged. In this study, the riding-type hangers with four strands which are the commonly used hanger of long-span suspension bridges are taken as an example to investigate the influence of wind-sand flow on the hangers. The aerodynamic interference effect can occur among the four strands under the action of wind-sand flow. In order to explore the influence of wind-sand flow on the hangers, the wind-sand flow field around the riding-type hangers of a long-span suspension bridge is simulated within the FLUENT software on the basis of the numerical simulation of computational fluid dynamics. The pressure and velocity contour, aerostatic coefficients and forces produced by the wind-sand flow under different wind attack angle and volume fractions of sand phase are analyzed from the simulation. Results indicate that the forces exerted by the wind-sand flow on riding-type hangers are greater than the forces exerted only by wind. In the wind and wind-sand flow field, the drag and lift coefficients of the front two strands of hangers exhibit minor changes with increasing wind attack angle, whereas those of the back two strands increase first and then decrease to a small value. The volume fraction of the sand phase has an insignificant effect on the drag and lift coefficients, but has a significant effect on the force exerted on the hanger, and the force exerted on the hangers multiplies when the volume fraction of the sand phase multiplies. The results lay a theoretical foundation for the corrosion fatigue analysis of riding-type hangers for large-span suspension bridges under the action of wind-sand flow.

suspension bridge;riding-type hanger;wind-sand flow;aerodynamic coefficient;CFD;aerodynamic interactions

WoS

With government's response to child abuse and neglect seen as one of the most daunting challenges for public policy and law, legislative reform on this issue struggles to adequately protect children while preserving the integrity of family. The authors utilize the Child Abuse Prevention and Treatment Act (CAPTA) as an example of the funding and policy challenges in reforming federal child welfare law, as well as a lens through which advocates can locate both conventional and unconventional tools to move forward. CAPTA is examined as an important but weak and flawed federal statute. Authors present an array of opportunities to improve CAPTA during the next reauthorization cycle. Noting exemplary successes, in other recent and related legislation reforms, are suggested for CAPTA to more effectively address ongoing challenges of child welfare.

Child Advocacy;Child Welfare Reform;CAPTA;Child Welfare Finance Reform;Child Abuse and Neglect;Revenue-Neutral;Oversight;Enforcement;State Compliance

WoS

With growing Electronic Design Automation (EDA) industry, automated analog circuit design is now a feasible solution for the demand to exploit a span of nonlinear circuit behaviors from devices to circuits with the flexibility to optimize numerous competing continuous-valued performance specifications. In order to meet desired specifications, state-of art EDA tools are employed which depend upon more efficient and effective optimization techniques to suffice the cost of designing complex analog systems. In this paper, a hybrid metaheuristic based on PSO and SA is presented to design one of the most prominent design specifications, i.e. gains of a two-stage CMOS operational amplifier circuit and a simple operational transconductance amplifier circuit subject to a variety of design conditions and constraints. Here convergence of PSO is improved by advancing through local solutions using SA to achieve quality global optimum solution. Experimental results are compared with other standard optimization techniques to show performance of proposed hybrid metaheuristic in terms of optimization quality and robustness.

Electronic Design Automation;Particle Swarm Optimization (PSO);Simulated Annealing (SA)

WoS

With growing population in urban areas, the problem of lacking space is becoming more prominent. Thus, the development of underground space has increasingly gained attention as a viable solution. Social aspects, such as social behavior and attitudes toward underground spaces could act as both facilitators and inhibitors toward the adoption of underground spaces. Here we review, present and discuss the major social parameters associated with working in underground spaces. Our research overview identified three major themes that pervade existing literature: attitudes and perception; social behavior; and the impact of environmental attributes of underground spaces. Yet, we also notice that the social and cultural elements associated with underground spaces have remained largely unexplored, with previous research being of more of a qualitative character and, to some extent, outdated. We thus subsequently identified the major unexplored themes and present an organized, systematic research program for a more holistic and quantifiable understanding of the interaction between social behavior and underground spaces. We end by discussing how this research program can be integrated with other disciplines, including engineering, design and health. (C) 2016 Published by Elsevier Ltd.

Underground;Social behavior;Attitudes;Perceived control;Identity;Criminal behavior;Architecture

WoS

With high and growing supply of Database-as-a-Service solutions from cloud platform vendors, many enterprises still show moderate to low demand for them. Even though migration to a DaaS solution might result in a significantly reduced bill for IT maintenance, data security and privacy issues are among the reasons of low popularity of these services. Such a migration is also often only justified if it could be done seamlessly, with as few changes to the system as possible. Transparent Data Encryption could help, but solutions for TDE shipped with major database systems are limited to securing only data-at-rest, and appear to be useless if the machine could be physically accessed by the adversary, which is a probable risk when hosting in the cloud. This paper proposes a different approach to TDE, which takes into account cloud-specific risks, extends encryption to cover data-in-use and partly data-in-motion, and is capable of executing large subsets of SQL including heavy relational operations, complex operations over attributes, and transactions.

query processing;relational databases;data security;data privacy

WoS

With higher rate of depletion of the non-renewable fuels, the quest for an appropriate alternative fuel has gathered great momentum. Though diesel engines are the most trusted power sources in the transportation industry, due to stringent emission norms and rapid depletion of petroleum resources there has been a continuous effort to use alternative fuels. Hydrogen is one of the best alternatives for conventional fuels. Hydrogen has its own benefits and limitations in its use as a conventional fuel in automotive engine system. In the present investigation, hydrogen-enriched air is used as intake charge in a diesel engine adopting exhaust gas recirculation (EGR) technique with hydrogen flow rate at 201/min. Experiments are conducted in a single-cylinder, four-stroke, water-cooled, direct-injection diesel engine coupled to an electrical generator. Performance parameters such as specific energy consumption, brake thermal efficiency are determined and emissions such as oxides of nitrogen, hydrocarbon, carbon monoxide, particulate matter, smoke and exhaust gas temperature are measured. Usage of hydrogen in dual fuel mode with EGR technique results in lowered smoke level, particulate and NO, emissions. (C) 2007 Elsevier Ltd. All rights reserved.

exhaust gas recirculation (EGR);hydrogen;enrichment;performance;emissions

WoS

With hip fracture and dementia increasing in incidence in the global ageing population, there is a need for the development of specific procedures targeting optimal treatment outcomes for these patients. This paper looks primarily at the factors that limit access to subacute rehabilitation services as a growing body of evidence suggests that access to timely inpatient rehabilitation increases functional outcomes for patients both with dementia and without. Information was gathered by searching electronic data bases (SCOPUS, Medline, CINAHL, Health Source Nursing/Academic Addition, Psychinfo and the Cochrane Library) for relevant articles using the search terms dementia OR Alzheimer* AND hip fracture AND subacute rehabilitation OR convalescence for the period 2005-2015. Abstracts were scanned to identify articles discussing eligibility and access. A total of nine papers were identified that directly addressed this topic. Other papers discussing success or failure of rehabilitation and improved models of care were also reviewed. Barriers to access discussed in the literature include information management, management of comorbidities, attitudes, resource availability, and the quality of evidence and education. By identifying these factors we can identify strategic points of intervention across the trajectory of prevention, treatment and rehabilitation that may improve outcomes for this growing group of vulnerable patients. Emerging best practice for these patients is also discussed.

dementia;hip fracture;subacute rehabilitation;health service structure;health service delivery

WoS

With increased use of forensic memory analysis, the soundness of memory acquisition becomes more important. We therefore present a black box analysis technique in which memory contents are constantly changed via our payload application with a traceable access pattern. This way, given the correctness of a memory acquisition procedure, we can evaluate its atomicity and one aspect of integrity as defined by Vomel and Freiling (2012). We evaluated our approach on several memory acquisition techniques represented by 12 memory acquisition tools using a Windows 7 64-bit operating system running on a i5-2400 with 2 GiB RAM. We found user-mode memory acquisition software (ProcDump, Windows Task Manager), which suspend the process during memory acquisition, to provide perfect atomicity and integrity for snapshots of process memory. Cold-boot attacks (memimage, msramdump), virtualization (VirtualBox) and emulation (QEMU) all deliver perfect atomicity and integrity of full physical system memory snapshots. Kernel level software acquisition tools (FTK Imager, DumpIt, win64dd, WinPmem) exhibit memory smear from concurrent system activity reducing their atomicity. There integrity is reduced by running within the imaged memory space, hence overwriting part of the memory contents to be acquired. The least amount of atomicity is exhibited by a DMA attack (inception using IEEE 1394). Further, even if DMA is performed completely in hardware, integrity violations with respect to the point in time of the acquisition let this method appear inferior to all other methods. Our evaluation methodology is generalizable to examine further memory acquisition procedures on other operating systems and platforms. (C) 2016 The Authors. Published by Elsevier Ltd on behalf of DFRWS.

Memory acquisition;Atomicity;Memory forensics;Integrity;Forensic tool testing

WoS

With increasing altitude, solar UV-B radiation is enhanced. Based on the phenomenon of male-biased sex ratio of Populus cathayana Rehder in high altitude alpine area, we hypothesized that males have a faster and more sophisticated responsive mechanism to high UV-B radiation than that of females. Our previous studies have shown sexually different responses to high UV-B radiation were existed in P. cathayana at the morphological, physiological, and transcriptomic levels. However, the responses at the proteomic level remain unclear. In this study, an isobaric tag for relative and absolute quantification (iTRAQ)-based quantitative proteome analysis was performed in P. cathayana females and males. A total of 2,405 proteins were identified, with 331 proteins defined as differentially expressed proteins (DEPs). Among of these, 79 and 138 DEPs were decreased and 47 and 107 DEPs were increased under high solar UV-B radiation in females and males, respectively. A bioinformatics analysis categorized the common responsive proteins in the sexes as related to carbohydrate and energy metabolism, translation/transcription/post-transcriptional modification, photosynthesis, and redox reactions. The responsive proteins that showed differences in sex were mainly those involved in amino acid metabolism, stress response, and translation/transcription/post-transcriptional modification. This study provides proteomic profiles that poplars responding to solar UV-B radiation, and it also provides new insights into differentially sex-related responses to UV-B radiation.

dioecious;plant proteomics;UV-B radiation;sexual difference;poplar

WoS

With increasing demand for energy and advances in exploration and development technologies, more attention is being devoted to exploration and development of deep oil and gas reservoirs. The Nanpu Sag contains huge reserves in deep oil and gas reservoirs and is a promising area. In this paper, the physico-chemical and mechanical properties of hard brittle shales from the Shahejie Formation in the Nanpu Sag in the Bohai Bay Basin of northern China were investigated using a variety of methods, including x-ray diffraction analysis, cation exchange capacity (CEC) analysis, contact angle measurements, scanning electron microscope observations, immersion experiments, ultrasonic testing and mechanical testing. The effects of the physico-chemical properties of the shales on wellbore instability were observed, and the effects of hydration of the shales on wellbore instability were also examined. The results show that the major mineral constituents of the investigated shales are quartz and clay minerals. The clay mineral contents range from 25.33% to 52.03%, and the quartz contents range from 20.03% to 46.45%. The clay minerals do not include montmorillonite, but large amounts of mixed-layer illite/smectite were observed. The CEC values of the shales range from 90 to 210 mmol kg(-1), indicating that the shales are partly hydrated. The wettability of the shales is strongly water-wetted, indicating that water would enter the shales due to the capillary effect. Hydration of hard brittle shales can generate cracks, leading to changes in microstructure and increases in the acoustic value, which could generate damage in the shales and reduce their strength. With increasing hydration time, the shale hydration effect gradually becomes stronger, causing an increase in the range of the acoustic travel time and decreases in the ranges of cohesion and internal friction angles. For the hard brittle shales of the Nanpu Sag, drilling fluid systems should aim to enhance sealing ability, decrease drilling fluid filter loss and increase the amount of clay-hydration inhibitor used.

Nanpu Sag;Shahejie Formation;hard brittle shale;physico-chemical properties;mechanical properties

WoS

With increasing global demand for energy resources, shale gas has been paid considerable attention in recent years. Nanopore geometry is the basis for all microscopic rock physics and petrophysical numerical experiments for shale. At present, nano digital cores can be acquired via thin section reconstruction,. nanometer-scale x-ray computed tomography (nano-CT), and focused ion beam and scanning electron microscopy (FIB-SEM). FIB-SEM detects nanoscale pores in the xy-plane with a resolution of up to 0.8 nm voxel(-1), and it is usually provides higher resolution than nano-CT. The main workload associated with FIB-SEM is the need to recut the sample many times and scan every section, with these then being overlaid to create a threedimensional (3D) pore model. Each cutting distance can be ascertained, but this cannot be controlled. precisely because of the fundamental limits of focused ion beams. Many interpolation methods can be used to fit the anisotropy resolution. However, these methods can also alter the geometry of the pores. Nanopores that are close to the limiting resolution are particularly susceptible to stretching. Linear interpolation is likely to lengthen the pores in the low-resolution direction. The subsequent calculation of sensitive physical attributes will be affected by geometric alterations. Through foundational work in the compressive sensing (CS) method, we present a reconstruction workflow for maintaining the pore shape using prior knowledge and reliable information. The images are reassembled with equal distance, so the nanoscale structures can have a resolution of unity in three dimensions.

compressive sensing;nanopore reconstruction;FIB-SEM image processing

WoS

With increasing modernization and urbanization of Asia, much of the future focus of the obesity epidemic will be in the Asian region. Low testosterone levels are frequently encountered in obese men who do not otherwise have a recognizable hypothalamic-pituitary-testicular (HPT) axis pathology. Moderate obesity predominantly decreases total testosterone due to insulin resistance-associated reductions in sex hormone binding globulin. More severe obesity is additionally associated with reductions in free testosterone levels due to suppression of the HPT axis. Low testosterone by itself leads to increasing adiposity, creating a self-perpetuating cycle of metabolic complications. Obesity-associated hypotestosteronemia is a functional, non-permanent state, which can be reversible, but this requires substantial weight loss. While testosterone treatment can lead to moderate reductions in fat mass, obesity by itself, in the absence of symptomatic androgen deficiency, is not an established indication for testosterone therapy. Testosterone therapy may lead to a worsening of untreated sleep apnea and compromise fertility. Whether testosterone therapy augments diet- and exercise-induced weight loss requires evaluation in adequately designed randomized controlled clinical trials.

androgens;hypogonadism;obesity;testosterone;weight loss

WoS

With increasing rates of cancer patients undergoing radiation therapy, the treatment itself can cause patients significant amounts of anxiety and distress. This can be attributed to the diagnosis of the disease, lack of knowledge of what radiation therapy is, expectations and management of side effects, and the lack of knowledge of supportive care for patients and their families. Providing patients with effective educational tools to meet the informational needs of cancer patients undergoing radiation therapy can empower patients and allow them to participate in treatment decision-making and their own healthcare. This discussion paper will evaluate several studies on the psychological impact of cancer patients undergoing radiation therapy and how video material can effectively meet the informational and educational needs of this patient population group.

Radiotherapy;Informational/Educational needs;Supportive care needs;Video material

WoS

With increasingly strict requirements for control speed and system performance, the unavoidable time delay becomes a serious problem. Fractional-order feedback is constantly adopted in control engineering due to its advantages, such as robustness, strong de-noising ability and better control performance. In this paper, the dynamical characteristics of an autonomous Duffing oscillator under fractional-order feedback coupling with time delay are investigated. At first, the first-order approximate analytical solution is obtained by the averaging method. The equivalent stiffness and equivalent damping coefficients are defined by the feedback coefficient, fractional order and time delay. It is found that the fractional-order feedback coupling with time delay has the functions of both delayed velocity feedback and delayed displacement feedback simultaneously. Then, the comparison between the analytical solution and the numerical one verifies the correctness and satisfactory precision of the approximately analytical solution under three parameter conditions respectively. The effects of the feedback coefficient, fractional order and nonlinear stiffness coefficient on the complex dynamical behaviors are analyzed, including the locations of bifurcation points, the stabilities of the periodic solutions, the existence ranges of the periodic solutions, the stability of zero solution and the stability switch times. It is found that the increase of fractional order could make the delay-amplitude curves of periodic solutions shift rightwards, but the stabilities of the periodic solutions and the stability switch times of zero solution cannot be changed. The decrease of the feedback coefficient makes the amplitudes and ranges of the periodic solutions become larger, and induces the stability switch times of zero solution to decrease, but the stabilities of the periodic solutions keep unchanged. The sign of the nonlinear stiffness coefficient determines the stabilities and the bending directions of delay-amplitude curves of periodic solutions, but the bifurcation points, the stability of zero solution and the stability switch times are not changed. It could be concluded that the primary system parameters have important influences on the dynamical behavior of Duffing oscillator, and the results are very helpful to design, analyze or control this kind of system. The analysis procedure and conclusions could provide a reference for the study on the similar fractional-order dynamic systems with time delays.

fractional-order derivative;Duffing oscillator;time delay;averaging method

WoS

With information becoming a first-class citizen on the Internet, information-centric networking (ICN) is considered as a promising direction for the future Internet. Named data networking (NDN) is a prominent example of emerging ICN architectures. Unfortunately, NDN is vulnerable to various attacks targeting its in-network caching mechanism. In this paper, we focus on the false-locality pollution attack, in which an adversary repeatedly requests a number of unpopular data objects to waste the precious cache space on the NDN router and to reduce normal users' hit ratios. With simulation experiments, we show that such an attack can cause considerable damage to the NDN network. To detect and mitigate such an attack, we introduce an algorithm that exploits the diversity of the Interest traversing paths within an Internet service provider's point-of-presence network. We also propose inexpensive methodologies based on the probabilistic counting and Bloom filter techniques to implement the algorithm on an NDN router. The experimental results indicate that our proposed algorithm is effective in thwarting false-locality pollution. We also experiment with strategies that the adversary may utilize against our antipollution algorithm and demonstrate that such strategies are either ineffective or impractical in the real world.

Future Internet architecture;cache pollution attack;network security

WoS

With integrative trend of world economy, drastic competition in the market, commercial intercourse in the future will emphasize more and more on convenience. Thus strengthening the comprehensive transportation network of research and practice has become the mainstream. This paper describes the development of an intelligent traffic control and dispatch system.

Intelligent Traffic Control;Dispatch System;Integrated Transportation Network

WoS

With introducing demand response aggregator (DRA) in smart paradigm, small customers can actively participate in price and incentive-based demand response programs. This new matter can significantly affect many factors of power system such as transmission network security. Accordingly, it is notably useful to define an adjusted framework for transmission expansion planning in smart environment. A long-term market simulation is performed using a tri-level iterative framework to find the best expansion decisions for transmission company (TransCo) in a pool-based market. The TransCo's investment decisions are made by a merchant approach consistent with transmission network security and smart environment. The effects of smart environment on future network configuration, strategic bidding of generators in the market operation, and contingency analysis are considered during planning process. The effectiveness of proposed method is examined on the IEEE 24-bus system with one DRA, one TransCo, and two generation companies under the independent system operator's supervision. Copyright (c) 2016 John Wiley & Sons, Ltd.

demand response aggregator (DRA);merchant transmission expansion planning (TEP);long term market simulation;smart grid

WoS

With its relatively small key size, elliptic-curve cryptography (ECC) is considered as the public-key cryptographic algorithm of choice for wireless sensor networks (WSNs). In this work, we implemented ECC in the frequency domain, that is,by using the number theoretic transform, and without using hardware multiplier support, on the constrained MSP430 microcontroller widely used in WSNs. Our 169-bit ECC implementation uses Edwards curves and performs scalar point multiplication in only 1.97 and 0.98s for multiplication of random and fixed points, respectively. Unlike many implementations in literature, our implementation does not use hardware multiplier support, which makes it desirable for low-power applications on constrained WSN platforms. To our knowledge, this study presents the first ever software implementation of ECC in the frequency domain on a constrained low-power microcontroller without hardware multiplier support. Copyright (C) 2016 John Wiley & Sons, Ltd.

wireless sensor networks;WSN;elliptic-curve cryptography;ECC;point multiplication;NAF;comb method;number theoretic transform;NTT;frequency domain;finite field multiplication;MSP430;low-power

WoS

With larger-scale of railway construction in China, there are more and more larger-scale tunnel projects in process. Tunnel engineering constructions are very difficult, high risk, and there are many unpredictable factors that may cause safety issues, such as landslides, roof caving and water bursts, threatening the construction personnel's safety. The personnel positioning tracking systems have been studied and applied preliminarily in railway tunnel construction. It is important to know how many people are underground, and workers must sign in/out one by one at tunnel entrances when they come in or leave; a process that is time-consuming and sometimes irritating to those who line up and must exit one-by-one to sign in. Active Radio Frequency Identification (RFID) systems can respond to transponders on the personnel's helmets or jackets to quickly identify workers coming and going without stopping to sign in and out. It can also alert management when a person enters without a transponder. Indoor moving target recognition and tracking in Internet of Things is a popular research and application topic in recent years. This paper proposes an indoor moving target recognition and tracking method based on RFID and Charge Coupled Device (CCD) collaborative information fusion. First, RFID technique and the proposed extended virtual reference elimination (extended virtual reference elimination) approach are used to recognize and to coarsely locate the target. Second, based on the coarse localization results, the monitoring/sleeping control of different CCDs will be realized. Subsequently, the background-difference method is used to detect the target in CCD monitoring image and realize precise localization with multiple angle of view fusion. Finally, with weighted average of the two localization results, the moving target location is obtained. The method combines the advantages of RFID fast recognition and localization and CCD precise localization. The experiment results indicate that the proposed collaborative information fusion method can effectively improve the accuracy and real-time performance of indoor moving target tracking.

Internet of Things;RFID technology;CCD image processing;collaborative information fusion;extended virtual reference elimination (extended VIRE)

WoS

With literally hundreds of electric motor manufacturers from which to choose, sorting through options to find the best value can be a daunting task. This paper draws on the author's forty-plus years of experience to share practical methods for comparing motors before purchase. Interwoven into the paper are suggestions and techniques for improving designs of motors already in service. Areas of interest include electrical windings, bearings, rotor designs, ventilation and balancing.

Electric motor;enclosure;Stator;Rotor;Ventilation

WoS

With location-based social network (LBSN) flourishing, location check-in records offer us sufficient information resource to do relative mining. Among locations visited by a user, those attracting relatively more visits from that user can serve as a support for further mining and improvement for location-based services. Therefore, great significance lies in the partition for visited locations based on a user's visiting frequency. The aim of our paper is to partition locations for individual users by utilizing classification in machine learning, categorizing the location for a user once he or she makes initial check-in there. After feature extraction for each initial check-in record, we evaluate the contribution of three feature categories. The results show the contribution of different feature categories varies in classification, where social features appear to offer the least contribution. At last, we do a final test on the whole sample, comparing the results with two baselines based on majority voting respectively. The results largely outperform the baselines in general, demonstrating the effectiveness of classification. (C) 2017 Elsevier B.V. All rights reserved.

Location-based social network;Classification;Prediction

WoS

With minimal information on sexual health provision during mass-gathering events, our aim was to describe the use of sexual health, contraceptive, sex worker and sexual assault services during the London 2012 Olympics. We analysed data from five sources. One contraceptive service provider reported a 10% increase in attendance during the main Games, while emergency contraception prescriptions rose during the main Olympics, compared to the week before, but were similar or lower than at the beginning and end of the summer period. A health telephone advice line reported a 16% fall in sexual health-related calls during the main Olympics, but a 33% increase subsequently. London sexual assault referral centres reported that 1.8% of sexual assaults were Olympics-linked. A service for sex workers reported that 16% started working in the sex industry and 7% moved to London to work during the Olympics. Fifty-eight per cent and 45% of sex workers reported fewer clients and an increase in police crack-downs, respectively. Our results show a change in activity across these services during the 2012 summer, which may be associated with the Olympics. Our data are a guide to other services when anticipating changes in service activity and planning staffing for mass-gathering events.

Olympic;London 2012;sexual assault referral centre;telephone advice line;contraception;sex worker;sexual health;mass-gathering event

WoS

With new advances in computer hardware and software, users now have widespread accessibility to multicore devices inside personal computers making it feasible for fast indoor airflow simulations. Some exciting preliminary results of a cross-platform parallel computing framework OpenCL using specific hardware were reported. However, those results are largely based on two hypotheses: 1. OpenCL code on all devices will generate the same results; 2. On the same device, running in parallel with multiple processors will be faster than running in sequential with a single processor. This study attempted to evaluate these two hypotheses by systematically studying the accuracy and computing speed of OpenCL for indoor airflow simulations. A Fast Fluid Dynamics (FFD) code was selected as an exemplar indoor airflow simulation program. To compare the cross-platform ability of OpenCL, the evaluation was performed using four Graphics Processing Units (GPUs) and five Central Processing Units (CPUs) from three manufacturers, with different degrees of computing capability and mounted on two operating systems. The test subjects were evaluated using four case studies consisting of various indoor airflows. A sequential FFD code programmed in C and a Computational Fluid Dynamics (CFD) program were first used to perform the case studies and generate numerical benchmarks. The comparison of the numerical simulation results with experimental data showed that CFD and FFD can predict the studied flows with averaged relative errors of 9.99% and 11.30%, respectively. Afterwards, the accuracy and speedup of the OpenCL code was compared with numerical benchmarks. Although the OpenCL code on the CPUs generated identical numerical results, the OpenCL results from the GPUs were slightly dissimilar. This is likely due to varying interpretations, by the manufactures, of an Institute of Electrical and Electronics Engineers standard. Depending on the hardware, the speedups of the OpenCL code varied from 0.7 to 4.2 times on the CPUs and 5.1-129.3 times on the GPUs. The slowdown of computing speed happened when running OpenCL on a two-core CPU in a Windows Operating System using the Boot Camp on a Mac computer. Finally, a separate study on the relationship between speedup and global work size showed that a speedup of 1139 can be achieved when using an AMD FirePro W8100 GPU.

FFD;OpenCL;parallel computing;indoor airflow simulation

WoS

With newer complex multi-core systems, it is important to understand an application's runtime behavior to be able to debug its execution, detect possible problems and bottlenecks and finally identify potential root causes. Execution traces usually contain precise data about an application execution. Their analysis and abstraction at multiple levels can provide valuable information and insights about an application's runtime behavior. However, with multiple abstraction levels, it becomes increasingly difficult to find the exact location of detected performance or security problems. Tracing tools provide various analysis views to help users to understand their application problems. However, these pre-defined views are often not sufficient to reveal all analysis aspects of the underlying application. A declarative approach that enables users to specify and build their own custom analysis and views based on their knowledge, requirements and problems can be more useful and effective. In this paper, we propose a generic declarative trace analysis framework to analyze, comprehend and visualize execution traces. This enhanced framework builds custom analyses based on a specified modeled state, extracted from a system execution trace and stored in a special purpose database. The proposed solution enables users to first define their different analysis models based on their application and requirements, then visualize these models in many alternate representations (Gantt chart, XY chart, etc.), and finally filter the data to get some highlights or detect some potential patterns. Several sample applications with different operating systems are shown, using trace events gathered from Linux and Windows, at the kernel and user-space levels.

Software debugging;Declarative debugging;Execution trace analysis

WoS

With one operational amplifier (op-amp) in negative feedback, the traditional zero potential circuit could access one element in the two-dimensional (2-D) resistive sensor array with the shared row-column fashion but it suffered from the crosstalk problem for the non-scanned elements' bypass currents, which were injected into array's non-scanned electrodes from zero potential. Firstly, for suppressing the crosstalk problem, we designed a novel improved zero potential circuit with one more op-amp in negative feedback to sample the total bypass current and calculate the precision resistance of the element being tested (EBT) with it. The improved setting non-scanned-electrode zero potential circuit (S-NSE-ZPC) was given as an example for analyzing and verifying the performance of the improved zero potential circuit. Secondly, in the S-NSE-ZPC and the improved S-NSE-ZPC, the effects of different parameters of the resistive sensor arrays and their readout circuits on the EBT's measurement accuracy were simulated with the NI Multisim 12. Thirdly, part features of the improved circuit were verified with the experiments of a prototype circuit. Followed, the results were discussed and the conclusions were given. The experiment results show that the improved circuit, though it requires one more op-amp, one more resistor and one more sampling channel, can access the EBT in the 2-D resistive sensor array more accurately.

the 2-D resistive sensor array;zero potential circuit;improved zero potential circuit;measurement;crosstalk

WoS

With over 10 million git repositories, GitHub is becoming one of the most important sources of software artifacts on the Internet. Researchers mine the information stored in GitHub's event logs to understand how its users employ the site to collaborate on software, but so far there have been no studies describing the quality and properties of the available GitHub data. We document the results of an empirical study aimed at understanding the characteristics of the repositories and users in GitHub; we see how users take advantage of GitHub's main features and how their activity is tracked on GitHub and related datasets to point out misalignment between the real and mined data. Our results indicate that while GitHub is a rich source of data on software development, mining GitHub for research purposes should take various potential perils into consideration. For example, we show that the majority of the projects are personal and inactive, and that almost 40 % of all pull requests do not appear as merged even though they were. Also, approximately half of GitHub's registered users do not have public activity, while the activity of GitHub users in repositories is not always easy to pinpoint. We use our identified perils to see if they can pose validity threats; we review selected papers from the MSR 2014 Mining Challenge and see if there are potential impacts to consider. We provide a set of recommendations for software engineering researchers on how to approach the data in GitHub.

Mining software repositories;git;GitHub;Code reviews

WoS

With participation in high school sports rising, the number of injuries sustained by high school athletes have also increased. This study sought to investigate the attributes of sports injuries and the common injury sites for male and female athletes to determine if certain muscles should be strengthened to prevent injuries in high school athletes. This project utilizes AnNA (anatomical network analysis) to show the relationships between the musculoskeletal system and high school sports injuries. An injury was defined as trauma to the musculoskeletal system. The study focused on the synovial joints of the human body and did not include head injuries. To do this we collected information from three data sets to develop three anatomical networks. The results showed that the articulation sites with the highest degree of muscle and bone account for the highest incidences of sports injury, most common injury site in female athletes was the ankle, but the most common injury site varied in male athletes. The results also showed that the anatomical differences between men and women account for the different injury sites. We hypothesize that strengthening the gastrocnemius muscle would help prevent injuries to knees and ankles, but further studies would need to be conducted.

anatomical network analysis;musculoskeletal;articulation;sports injury;synovial joints

WoS

With promising results in recent treatment trials for Alzheimer's disease (AD), it becomes increasingly important to distinguish AD at early stages from other causes for cognitive impairment. However, existing diagnostic methods are either invasive (lumbar punctures, PET) or inaccurate Magnetic Resonance Imaging (MRI). This study investigates the potential of neuropsychological testing (NPT) to specifically identify those patients with possible AD among a sample of 158 patients with Mild Cognitive Impairment (MCI) or dementia for various causes. Patients were divided into an early stage and a late stage group according to their Mini Mental State Examination (MMSE) score and labeled as AD or non-AD patients based on a post-mortem validated threshold of the ratio between total tau and beta amyloid in the cerebrospinal fluid (CSF; Total tau/Ab (1-42) ratio, TB ratio). All patients completed the established Consortium to Establish a Registry for Alzheimer's Disease-Neuropsychological Assessment Battery (CERAD-NAB) test battery and two additional newly-developed neuropsychological tests (recollection and verbal comprehension) that aimed at carving out specific Alzheimer-typical deficits. Based on these test results, an underlying AD (pathologically increased TB ratio) was predicted with a machine learning algorithm. To this end, the algorithm was trained in each case on all patients except the one to predict (leave-one-out validation). In the total group, 82% of the patients could be correctly identified as AD or non-AD. In the early group with small general cognitive impairment, classification accuracy was increased to 89%. NPT thus seems to be capable of discriminating between AD patients and patients with cognitive impairment due to other neurodegenerative or vascular causes with a high accuracy, and may be used for screening in clinical routine and drug studies, especially in the early course of this disease.

Alzheimer's disease;MCI;total tau to A beta(1-42)ratio;neuropsychological testing;dementia;machine learning

WoS

With rail transit construction developing by leaps and bounds in China, the traditional project management model has shown discomfort. Informatization management, the modern concept of project management, provides a new management model for rail transit construction management and becomes an effective way to change the shortcomings of traditional project management. This paper bases on the analysis of the characteristics and requirements of the rail transit construction management, presents the informatization management system based on integrated management thoughts and analyses its overall frame and operation mechanism virtual reality, decision support and dynamic control. Then, it proposes to strengthen the constructions in three aspects including the organizational and institutional, runtime environment of informatization platform and informatization technology to ensure the informatization management system of rail transit construction running safely and smoothly.

Rail transit construction;Informatization management system;Informatization-plat;Integrate

WoS

With rapid development of mobile technologies, people can easily obtain surrounding information through their mobile devices. Meanwhile, weather forecasting information is important for many people in the daily life. Most of current weather information systems only illustrate the basic weather information, such as the temperature and the precipitation probability, by a simple text-based or graphic-based presentation without involving too much environmental information. To integrate weather information with ambient intelligence, this paper aims at showing our implementation experience about how to realize our ambient mesoscale weather forecasting system (AMWFS). With an augmented reality presentation in the system, a more intuitive navigation interface provides users a new way of accessing weather information.

Weather forecasting;Ambient intelligence;Mesoscale weather;Augmented reality

WoS

With rapid growth in population, it becomes difficult to control the huge amount of residual materials generated from enormous industrial activities. The residuals that are not recycled, reclaimed or reused constitute the wastes only to get released to the environment. As some of the wastes cannot be assimilated by the environment, those can become hazardous for the environment quality and ensure pollution. This paper expresses the concern on two such industrial wastes, used plastic water bottles and fly ash. The present study emphasizes on the reuse of used waste plastic water bottles in the Civil Engineering applications and in this regard, it discusses the previous work by Dutta and Mandal (2013). Two different type plastic water bottles, having different diameter and tensile stiffness, were chosen to prepare perforated cells of different heights wrapped with jute geotextile from inner side so that fine infill materials cannot escape from the perforations. Laboratory strain controlled compression tests were carried out on the cells rested over a rigid base and filled with compacted fly ash or stone aggregates. Test results showed significant load carrying capacity of the composite cells with fly ash as infill material. Though fine fly ash appeared to be an effective infill material, use of coarse stone aggregates as infill material produced better load carrying capacity of the composite cells. It was also observed that with reduction in cell height over the rigid base, load carrying capacity of the composite cells got increased. The study confirmed that plastic bottles with suitable infill material can act as an ideal compression member. (C) 2016 The Authors. Published by Elsevier B.V.

Waste plastic bottle;Fly ash;Cell;Jute geotextile;Infill material;Stone aggregates;Load carrying capacity

WoS

With rapid socioeconomic development, water pollution emergency has become increasingly common and could potentially harm the environment and human health, especially heavy metal pollution. In this paper, we investigate the Cd pollution emergency that occurred in the Pearl River network, China, in 2005, and we build a migration and transformation model for heavy metals to simulate the spatiotemporal distribution of Cd concentrations under various scenarios of Cd pollution emergency in Foshan City. Moreover, human health hazard and carcinogenic risk for local residents of Foshan City were evaluated. The primary conclusions were as follows: (1) the number of carcinogen-affected people per year under scenario 1 reached 254.41 when the frequency was 0.1 year/time; specifically, the number of people with cancer per year in the area of the Datang, Lubao, and Nanbian waterworks was 189.36 accounting for 74% of the total number per year; (2) at the frequency of 5 years/time, the Lubao waterwork is the only one in extremely high- or high-risk grade, while besides it, the risk grade in the Datang, Nanbian, Xinan, Shitang, and Jianlibao waterworks is in the extremely high or high grade when the frequency is 0.1 year/time; (3) when Cd pollution accidents with the same level occurs again, Cd concentration decreases to a low level in the water only if the migration distance of Cd is at least 40-50 km. Based on the health risk assessment of Cd pollution, this study gives the recommendation that the distance should keep above 50 km in tidal river network of the Pearl River Delta between those factories existing the possibility of heavy metal pollution and the drinking water source. Only then can the public protect themselves from hazardous effects of higher levels of heavy metal.

Foshan City;Heavy metal;Cd pollution emergency;Scenario simulation;Health risk assessment;Risk grade

WoS

With rapid urbanization, highly accurate and semantically rich virtualization of building assets in 3D become more critical for supporting various applications, including urban planning, emergency response and location-based services. Many research efforts have been conducted to automatically reconstruct building models at city-scale from remotely sensed data. However, developing a fully-automated photogrammetric computer vision system enabling the massive generation of highly accurate building models still remains a challenging task. One the most challenging task for 3D building model reconstruction is to regularize the noises introduced in the boundary of building object retrieved from a raw data with lack of knowledge on its true shape. This paper proposes a data-driven modeling approach to reconstruct 3D rooftop models at city-scale from airborne laser scanning (ALS) data. The focus of the proposed method is to implicitly derive the shape regularity of 3D building rooftops from given noisy information of building boundary in a progressive manner. This study covers a full chain of 3D building modeling from low level processing to realistic 3D building rooftop modeling. In the element clustering step, building-labeled point clouds are clustered into homogeneous groups by applying height similarity and plane similarity. Based on segmented clusters, linear modeling cues including outer boundaries, intersection lines, and step lines are extracted. Topology elements among the modeling cues are recovered by the Binary Space Partitioning (BSP) technique. The regularity of the building rooftop model is achieved by an implicit regularization process in the framework of Minimum Description Length (MDL) combined with Hypothesize and Test (HAT). The parameters governing the MDL optimization are automatically estimated based on Min-Max optimization and Entropy-based weighting method. The performance of the proposed method is tested over the International Society for Photogrammetry and Remote Sensing (ISPRS) benchmark datasets. The results show that the proposed method can robustly produce accurate regularized 3D building rooftop models.

3D building rooftop modeling;building reconstruction;regularization;airborne laser scanning data;minimum description length

WoS

With rapidly growing Internet traffic, energy efficient operation of IP over WDM networks with sleep enabled routers is of increasing interest. However, for network security and to provide guaranteed communications, it would still be desirable to ensure that a certain fraction of the bandwidth is assured through routers which cannot be put to sleep using software control. This paper presents an energy-minimized IP over WDM network using a mixture of sleep-enabled and non-sleep-enabled router cards where a certain percentage of the network bandwidth is guaranteed to the offered traffic. Such a mixed configuration is also motivated by the fact that there will always be some traffic demand between each node pair at any time even though the traffic between node pairs may fluctuate to very low levels. This implies a need for some non-sleeping router cards at any time. Another motivation for this mixed configuration is because in the course of migration from today's networks with non-sleep-enabled cards to future networks with sleep-enabled cards, the non-sleep-enabled network devices will not be quickly abandoned but will be gradually replaced. This also causes a network situation with the mixed router card types. To design an IP over WDM network where both sleep-enabled and non-sleep-enabled router cards are used, we propose a mixed integer linear programming (MILP) model which jointly minimizes the energy consumption of all the router cards while guaranteeing a secured fractional bandwidth for all the node pairs. Modified MILPs with subsequent port-channel association are also proposed along with efficient heuristic algorithms which perform almost as well as the joint MILP approaches. The performance of these approaches is studied through simulations on a wide variety of networks.

Energy-minimized design;guaranteed network bandwidth;IP over WDM;lightpath bypass;non-sleep-enabled;router cards;sleep-enabled

WoS

With recent advancements, micro-object contactless conveyers are becoming an essential part of the biomedical sector. They help avoid any infection and damage that can occur due to external contact. In this context, a smart micro-conveyor is devised. It is a Field Programmable Gate Array (FPGA)-based system that employs a smart surface for conveyance along with an OmniVision complementary metal-oxide-semiconductor (CMOS) HD camera for micro-object position detection and tracking. A specific FPGA-based hardware design and VHSIC (Very High Speed Integrated Circuit) Hardware Description Language (VHDL) implementation are realized. It is done without employing any Nios processor or System on a Programmable Chip (SOPC) builder based Central Processing Unit (CPU) core. It keeps the system efficient in terms of resource utilization and power consumption. The micro-object positioning status is captured with an embedded FPGA-based camera driver and it is communicated to the Image Processing, Decision Making and Command (IPDC) module. The IPDC is programmed in C++ and can run on a Personal Computer (PC) or on any appropriate embedded system. The IPDC decisions are sent back to the FPGA, which pilots the smart surface accordingly. In this way, an automated closed-loop system is employed to convey the micro-object towards a desired location. The devised system architecture and implementation principle is described. Its functionality is also verified. Results have confirmed the proper functionality of the developed system, along with its outperformance compared to other solutions.

Field Programmable Gate Array (FPGA);VHSIC Hardware Description Language (VHDL);camera driver;embedded design;micro-conveyor;image processing;C plus plus programming

WoS

With reference to a distributed architecture consisting of sensor nodes connected by wireless links in an arbitrary network topology, we consider a segment-oriented implementation of the single address space paradigm of memory reference. In our approach, applications consist of active entities called components, which are distributed in the network nodes. A component accesses a given segment by presenting a handle for this segment. A handle is a form of pointer protected cryptographically. Handles allow an effective implementation of communications between components, and key replacement. The number of messages generated by the execution of the communication primitives is independent of the network size. The key replacement mechanism is well suited to reliable application rekeying over an unreliable network.

cryptographic key;key replacement;protected pointer;single address space;symmetric-key cryptography;wireless sensor network

WoS

With requirement of household heat metering, variable-flow heating network is future trend, but it's difficult to heating according to users' demand because of hydraulic disorder, which is caused mainly by individual user's regulation. Self-operated pressure difference control valve (SPDCV) is widely used in heating system to solve this problem. This paper concentrates on effect of users' flow reduction on other non-regulated users' flow with constant pressure difference of heating network (CPDHN) and constant pressure difference of the end user (CPDE), and change of pressure diagram. Equal pressure drop of parallel user based on Kirchhoff's voltage law is used to theoretical model, and influencing law of users' regulation is obtained. The results are as follow: (1) user's pressure drop is larger than design pressure drop with CPDHN, and is less than design pressure drop with CPDE when any user's flow is reduced; (2) the front non-regulated. users' flow is increased little, and the middle ones take second place, and the back non-regulated users' flow is increased greatly when any user's flow is reduced with CPDHN; (3) the front non-regulated users' flow is reduced greatly, and the middle ones take second place, and the back non-regulated users' flow keep constant when any user's flow is reduced with CPDE. The conclusion can be got that CPDHN is better than CPDE with any user's flow reduction.

Heating network;Hydraulic condition;Self-operated pressure difference control valve

WoS

With respect to automotive safety, the driver plays a crucial role. Stress level, tiredness, and distraction of the driver are therefore of high interest. In this paper, a driver state detection system based on cellular neural networks (CNNs) to monitor the driver's stress level is presented. We propose to include a capacitive-based wireless hand detection (position and touch) sensor for a steering wheel utilizing ink-jet printed sensor mats as an input sensor in order to improve the performance. A driving simulator platform providing a realistic virtual traffic environment is utilized to conduct a study with 22 participants for the evaluation of the proposed system. Each participant is driving in two different scenarios, each representing one of the two no-stress/stress driver states. A "threefold" cross validation is applied to evaluate our concept. The subject dependence is considered carefully by separating the training and testing data. Furthermore, the CNN approach is benchmarked against other state-of-the-art machine learning techniques. The results show a significant improvement combining sensor inputs from different driver inherent domains, giving a total related detection accuracy of 92%. Besides that, this paper shows that in case of including the capacitive hand detection sensor, the accuracy increases by 10%. These findings indicate that adding a subject-independent sensor, such as the proposed capacitive hand detection sensor, can significantly improve the detection performance.

Artificial neural networks;automotive applications;capacitive sensors;cellular neural networks (CNNs);ink-jet printing

WoS

With respect to the current vulnerable climatic condition, water quality has become a matter of the highest worldwide concern. Rainwater harvesting is the most acceptable solution for overcoming this problem. Among various rainwater harvesting systems, green roof rainwater harvesting is a significant tool for improving the standard of living for rapidly growing populations in the whole world, in terms of both water demand and protecting the environment from pollution. This paper assesses the water quality parameter (dissolved oxygen (DO), pH, conductivity, and temperature) of rainwater harvesting from green roofs in humid tropic center under tropical climate conditions. It shows that the values of electric conductivity are always within Class I according to Interim National Water Quality Standards (INWQS) and Water Quality Index (WQI). Depletions of DO and pH values were observed for the green roof runoff, and the runoff quality ranged between Class I and III under INWQS and WQI. Lower value of pH indicates that harvested rainwater from green roofs is more acidic than the standard neutral value. Harvested water must be processed through general water treatment methods like filtration, disinfection, and through reverse osmosis storage tank. The indoor temperatures are always within an acceptable range.

Rainwater harvesting;Green roofs;MSMA SME;Water quality parameter;Water treatment;INWQS and WQI

WoS

With security and surveillance, there is an increasing need to process image data efficiently and effectively either at source or in a large data network. Whilst a Field-Programmable Gate Array has been seen as a key technology for enabling this, the design process has been viewed as problematic in terms of the time and effort needed for implementation and verification. The work here proposes a different approach of using optimized FPGA-based soft-core processors which allows the user to exploit the task and data level parallelism to achieve the quality of dedicated FPGA implementations whilst reducing design time. The paper also reports some preliminary progress on the design flow to program the structure. An implementation for a Histogram of Gradients algorithm is also reported which shows that a performance of 328 fps can be achieved with this design approach, whilst avoiding the long design time, verification and debugging steps associated with conventional FPGA implementations.

Image processing;FPGAs;Heterogeneous multi-core architecture

WoS

With shape memory function of new smart material, the magnetic control properties of magnetic shape memory alloy could be used to fabricate intelligent actuators for vibration control of reticulated shell structure. The major performance parameters of the microstructure of the materials has been considered in the functional relationship between the magnetic field and strain model of traditional magnetic shape memory alloys(MSMA). But the magnetic field of MSMA do not considered, induced strain and pre-pressure, ambient temperature and other factors, which is a mutual restraint relationship and coupling. Selected Ni53Mn25Ga22, in this paper, as the material for the research on deformation under the action of temperature, magnetic field, pressure coupling effect, and according to the test data designed a MSMA actuator drive.

Reticulated shell structure;Magnetic shape memory alloy;Magnetic field;Coupling effects;Actuator drive

WoS

With shape memory function of new smart material, the magnetic control properties of magnetic shape memory alloy could be used to fabricate intelligent actuators for vibration control of structures. In order to study its magnetic properties, this text selected Ni53Mn25Ga22 as the material for the research and development of actuator drive, And two MSMA test specimens were prepared for the experimental study under the coupled action of the temperature, preload pressure and magnetic field. The results showed that the strain of MSMA induced by magnetic field decreased with the increase of the preload pressure at constant magnetic field. The deformation performance was best when the magnetic induction intensity was about 0.5T. And the constitutive relations were fitted for the actuator production to lay the foundation for later.

Magnetic Shape Memory Alloy;the magnetic characteristics;magnetic field;coupled action;preload pressure

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With simple access interfaces and flexible billing models, cloud storage has become an attractive solution to simplify the storage management for both enterprises and individual users. However, traditional file systems with extensive optimizations for local disk-based storage backend can not fully exploit the inherent features of the cloud to obtain desirable performance. In this paper, we present the design, implementation, and evaluation of Coral, a cloud based file system that strikes a balance between performance and monetary cost. Unlike previous studies that treat cloud storage as just a normal backend of existing networked file systems, Coral is designed to address several key issues in optimizing cloud-based file systems such as the data layout, block management, and billing model. With carefully designed data structures and algorithms, such as identifying semantically correlated data blocks, kd-tree based caching policy with self-adaptive thrashing prevention, effective data layout, and optimal garbage collection, Coral achieves good performance and cost savings under various workloads as demonstrated by extensive evaluations.

Cloud storage;file systems;cost optimization;cache;Billing model

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With smart grid, the power supply will shift from the 1: N tree structure with centralized power plants to the M:N structure with various kinds of distributed energy resources based on renewable energy, batteries, and so on. Deregulation of the electricity market will yield a truly competitive market, where anyone can become a power seller or buyer, which will necessitate a real-time multiseller-multibuyer power trading system. However, it is difficult to realize such a system without centralized control, because of the additional trade complexity created by a large number of sellers, including ordinary homes. In this paper, the authors propose a novel distributed power cooperation algorithm that maximizes each home's welfare based on local information. The proposed algorithm enables each home to calculate the same electricity market price from only local household information, to trade, and to maximize all members' satisfaction in smart grid by balancing consumption against supply. The authors formulate a distributed optimization problem and logically prove that the authors' algorithm can obtain the same optimal user welfare as the global optimal approach but within a much shorter time. (C) 2016 American Society of Civil Engineers.

Smart grid;Social welfare;Power trading;Distributed;Cooperative algorithm;Convex optimization;Real-time optimization

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With sufficient drug exposure, some individuals develop transient psychotic symptoms referred to as 'substance-induced psychosis' (SIP), which closely resemble the symptoms observed in schizophrenia spectrum disorders. The comparability in psychotic presentation between SIP and the schizophrenias suggests that similar underlying neural deficits may contribute to the emergence of psychosis across these disorders. Only a small number of studies have investigated structural alterations in SIP, and all have been limited to volumetric imaging methods, with none controlling for the effects of chronic drug exposure. To investigate white matter abnormalities associated with SIP, diffusion tensor imaging was employed in a group of individuals with cocaine-associated psychosis (CAP; n = 24) and a cocaine-dependent non-psychotic (CDN) group (n = 43). Tract-based spatial statistics was used to investigate group differences in white matter diffusion parameters. The CAP group showed significantly lower fractional anisotropy values than the CDN group (p < 0.05) in voxels within white matter tracts of fronto-temporal, fronto-thalamic and interhemispheric pathways. The greatest differences in white matter integrity were present in the corpus callosum, corona radiata, bilateral superior longitudinal fasciculi and bilateral inferior longitudinal fasciculi. Additionally, the CAP group had voxels of significantly higher radial diffusivity in a subset of the previously mentioned pathways. These results are the first description of white matter integrity abnormalities in a SIP sample and indicate that differences in these pathways may be a shared factor in the expression of different forms of psychosis.

cocaine-associated psychosis;diffusion tensor imaging;psychosis;substance-induced psychosis;TBSS;white matter

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With symbolic computation and Hirota method, analytic two-soliton solutions for the coupled nonlinear Schrodinger (CNLS) equations, which describe the propagation of spatial solitons in an AlGaAs slab waveguide, are derived. Two types of coefficient constraints of the CNLS equations to distinguish the elastic and inelastic interactions between spatial solitons are obtained for the first time in this paper. Asymptotic analysis is made to investigate the spatial soliton interactions. The inelastic interactions are studied under the obtained coefficient constraints of the CNLS equations. The influences of parameters for the obtained soliton solutions are discussed. All-optical switching and soliton amplification are studied based on the dynamic properties of inelastic interactions between spatial solitons. Numerical simulations are in good agreement with the analytic results. The presented results have applications in the design of birefringence-managed switching architecture.

Spatial soliton;Soliton interactions;All-optical switching;Soliton amplification;Symbolic computation

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With symbolic computation, Bell-polynomial scheme and bilinear method are applied to a two-dimensional Korteweg-de Vries (KdV) model, which is firstly proposed with Lax pair generating technique. Bell-polynomial expression with one auxiliary independent variable is derived and transformed into bilinear form. According to the coupled two-field conditions between the primary and replica fields, Bell-polynomial-typed Backlund transformations (BTs) are constructed and converted into the bilinear ones. Finally, soliton solutions of the two-dimensional KdV model are obtained (via solving the bilinear representation and BT, respectively) and compared. Such associated integrable properties as bilinear representation, BT (especially auxiliary-independent-variable-involved Bell-polynomial-typed ones constructed in this paper) and soliton solutions (especially the multi-soliton ones) may be useful for further study on other two-dimensional KdV and KdV-typed models. (C) 2014 Elsevier Inc. All rights reserved.

Bell polynomials;Bell-polynomial-typed Backlund transformation;Two-dimensional Korteweg-de Vries model;Bilinear method;Symbolic computation

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With symbolic computation, this paper investigates some integrable properties of a two-dimensional generalization of the Korteweg-de Vries equation, i.e., the Bogoyavlensky-Konoplechenko model, which can govern the interaction of a Riemann wave propagating along the -axis and a long wave propagating along the -axis. Within the framework of Bell-polynomial manipulations, Bell-polynomial expressions are firstly given, which then are cast into bilinear forms. The -soliton solutions in the form of an th-order polynomial in the exponentials and in terms of the Wronskian determinant are, respectively, constructed with the Hirota bilinear method and Wronskian technique. Bilinear Backlund transformation is also derived with the achievement of a family of explicit solutions.

Bogoyavlensky-Konoplechenko model;Bell-polynomial manipulation;N-soliton solution;Bilinear Backlund transformation;Wronskian solution;Symbolic computation

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With symbolic computation, two classes of lump solutions to the dimensionally reduced equations in (2+1)-dimensions are derived, respectively, by searching for positive quadratic function solutions to the associated bilinear equations. To guarantee analyticity and rational localization of the lumps, two sets of sufficient and necessary conditions are presented on the parameters involved in the solutions. Localized characteristics and energy distribution of the lump solutions are also analyzed and illustrated.

Lump solution;Dimensionally reduced Hirota bilinear equation;Lump dynamics;Symbolic computation

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With the 1812 Constitution Spain entered the official history of liberal constitutionalism, being one of its proclamations the equality of all citizens of all Spanish dominions. However, this idea of an equality apparently within reach of all habitants of its territories, did not go beyond its formal character. Its contents did not correct the various forms of exclusion as, for instance, the exclusion for racial motives. The debates at the Cortes de Cadiz reflect the influences of the racial theories then dominating science and, thus, the development of constitutional principles. The idea of citizenship as embodied in the 1812 Constitution was limited by the racial prejudice that impregnated 19th century law and, in present-day law, still exists.

Constitution 1812;citizenship;equality;racial discrimination;Cadiz Parliament;castes;race;negroes;mulattos

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With the acceleration development of the Internet of Things and big data, the importance of high-performance mass data retrieval is gradually highlighted. Cloud computing is the distributed data calculation model that is suitable for big data, and has been widely used. In this paper, firstly, the technology of cloud computing is introduced. Secondly, retrieval technology of mass data is analyzed, finally a high-performance retrieval method of mass data based on Hadoop is proposed. The architecture of this method is composed of HDFS, MapReduce, and Hive, and is divided into four layers from bottom to top: access layer, interface layer, management layer and storage layer.

Cloud Computing;Mass Data;Retrieve;Hadoop Hierarchical Model;Distributed Computing

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With the advance of the World-Wide Web (WWW) technology, people can easily share content on the Web, including geospatial data and web services. Thus, the "big geospatial data management" issues start attracting attention. Among the big geospatial data issues, this research focuses on discovering distributed geospatial resources. As resources are scattered on the WWW, users cannot find resources of their interests efficiently. While the WWW has Web search engines addressing web resource discovery issues, we envision that the geospatial Web (i.e., GeoWeb) also requires GeoWeb search engines. To realize a GeoWeb search engine, one of the first steps is to proactively discover GeoWeb resources on the WWW. Hence, in this study, we propose the GeoWeb Crawler, an extensible Web crawling framework that can find various types of GeoWeb resources, such as Open Geospatial Consortium (OGC) web services, Keyhole Markup Language (KML) and Environmental Systems Research Institute, Inc (ESRI) Shapefiles. In addition, we apply the distributed computing concept to promote the performance of the GeoWeb Crawler. The result shows that for 10 targeted resources types, the GeoWeb Crawler discovered 7351 geospatial services and 194,003 datasets. As a result, the proposed GeoWeb Crawler framework is proven to be extensible and scalable to provide a comprehensive index of GeoWeb.

Geospatial Web;resource discovery;Web crawler;Open Geospatial Consortium

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With the advanced materials industry, makes this especially machinery manufacturing industry has witnessed rapid development and become one of the very important part, therefore, material engineering colleges focus on the development has also become one of the disciplines. Train and improve their practical ability to adapt to the needs of society has become an important part of college students training, this thesis explores the materials engineering students' professional training system establishment, the students presented material class materials processing skills training methods Manufacturing engineering training through high students' practical ability and engineering sense.

Materials Engineering;Jewelry Materials;Engineering Training;Training System

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With the advancement in technologies, the power requirement around the globe is tremendously increasing, putting extra loads on grids. The existing grids cannot bear that load and also do not provide the interface with Distributed Renewable Energy Sources (DRES). Building new lines and substations alone do not serve the purpose of overcoming energy shortfall. Thus a major transformation in electricity infrastructure is need of the hour to meet the ever growing demands of electricity. Converting current power management system to a smart autonomic system is pertinent to achieve an increasing amount of renewable energy generation. This paper presents a comprehensive review of advances in control of smart grids. Various robust and adaptive strategies are spotlighted with a detailed description of control of overloads and power smart grids. Also, power generation, storage and management techniques and development of operational schedule of sources and loads are elaborated. Recently reported systems and Information and Communication Technologies (ICT) techniques in smart grid are highlighted. Renewable energy has potential to eliminate the current electricity crisis in Pakistan's energy sector. The solar, wind, hydro and biogas/biomass are the alternative energy resources found abundantly in the country, which have tremendous potential to offer environment-friendly energy solutions. This in-depth study reveals that a lot of opportunities and potential of smart grid technology exist in developing countries like Pakistan that need to be exploited so as to cope with energy crisis.

Smart grid control;Power management;Operational schedule

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With the advancement of internet, computer network security has brought serious concerns. Intrusion detection is an important topic in network security framework. To address the effectiveness and efficiency problem with traditional intrusion detection models, we present an intrusion detection method based on deep leaning. The deep belief network (DBN) constructed via the stacked Boltzmann machine model (RBM) is selected. Firstly, combining numeralization of symbolic features and numeric features normalization are used to processing network log features. In addition, extreme learning machine (ELM) was applied into the learning process of DBN. Compared with traditional DBN, the experimental results on the NSL KDD dataset demonstrate that intrusion detection based on IDBN has double training speed compared to DBN, while achieving a reliable detection rate.

intrusion detection;deep neural network;stacked boltzmann machine model

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