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Traditional handoff algorithms based on stochastic and heuristic models perform poorly as they do not account for the rapid changes in the radio environments. Adaptive handoff algorithms are being developed to solve this problem with a corresponding tradeoff in terms of computational complexity. This paper suggests a location-aware handoff decision algorithm. The performance of the traditional and proposed handoff algorithm in a cellular digital packet data network (CDPD) are compared using simulations. The results indicate that the location-aware algorithm performs better than the traditional handoff algorithm.

['Wiklom Teerapabkajorndet', 'Prashant Krishnamurthy']

Comparison of performance of location-aware and traditional handoff-decision algorithms in CDPD networks

Multi-level Particle Filter Fusion of Features and Cues for Audio-Visual Person Tracking.

['Keni Bernardin', 'Tobias Gehrig', 'Rainer Stiefelhagen']

Multi-level Particle Filter Fusion of Features and Cues for Audio-Visual Person Tracking.

Quality and Reliability Engineering International#R##N#Early View (Online Version of Record published before inclusion in an issue)

['Fu-Kwun Wang', 'C. K. Huang', 'Yeneneh Tamirat']

Implementing EWMA Yield Index for Simple Linear Profiles with One-sided Specifications in Product Acceptance Determination

Based on the Field Theory , this study postulates that the cognitive processes involved in making decisions to share information on social media platforms could be dynamically affected by network features and the contextual environment. The field effect is exerted by the reach and richness of network features, which virtually form a psychological pressure on one’s perception of the sharing situation. A research model is developed, in which the effects of extrinsic and intrinsic motivators on information-sharing continuance are moderated by the network features of social media platforms. A global sample from content contributors in two major social media platform contexts, experience-socialization (ES) platforms ( N  = 568) and intelligence-proliferation (IP) platforms ( N  = 653), were collected through the participatory research method. By using partial least-square analysis, the moderating effects of network features on cognitive-sharing processes under the two contexts were confirmed. For contributors on ES platforms, network features negatively moderate community identification and perceived enjoyment toward information sharing. By contrast, for contributors on IP platforms, network features negatively moderate the effects of perceived usefulness and altruistic tendencies on their intention to share, but self-efficacy for sharing is positively induced. The conceptualization of network features and refined knowledge about the situational and contextual effects of social media platforms are useful for further studies on social behaviors and may ultimately benefit platform providers in their attempts to promote information-sharing continuance.

['Shari S. C. Shang', 'Ya-Ling Wu', 'Eldon Y. Li']

Field Effects of Social Media Platforms on Information Sharing Continuance: Do Reach and Richness Matter?

IT infrastructure is a crucial part in most of today''s business operations. High availability and reliability, and short response times to outages are essential. Thus a high amount of tool support and automation in risk management is desirable to decrease outages. We propose a new approach for calculating the root cause for an observed failure in an IT infrastructure. Our approach is based on Abduction in Markov Logic Networks. Abduction aims to find an explanation for a given observation in the light of some background knowledge. In failure diagnosis, the explanation corresponds to the root cause, the observation to the failure of a component, and the background knowledge to the dependency graph extended by potential risks. We apply a method to extend a Markov Logic Network in order to conduct abductive reasoning, which is not naturally supported in this formalism. Our approach exhibits a high amount of reusability and enables users without specific knowledge of a concrete infrastructure to gain viable insights in the case of an incident. We implemented the method in a tool and illustrate its suitability for root cause analysis by applying it to a sample scenario.

['Joerg Schoenfisch', 'Janno von Stülpnagel', 'Jens Ortmann', 'Christian Meilicke', 'Heiner Stuckenschmidt']

Root Cause Analysis through Abduction in Markov Logic Networks

Advanced building materials are nowadays an active research domain. The integration of traditional materials and technologies in the field of electronics, photonics and computer science are leading to a new class of smart components that provide advanced functionalities and enable original applications. The LUMENTILE H2020 EU funded Project aims at the integration of existing and state-of-the-art technologies in the domain of large area electronic circuits, LED based lighting, embedded systems and communication. These technologies are blended with advancements in the manufacturing of ceramic tiles to obtain a new building component that can be managed as a common tile, while providing the possibility to self-illuminate and to sense the neighbor environment by means of dedicated sensors. The applications of these new material and technologies include indoor and outdoor architectural design, smart environments (also targeting improved safety and security issues), smart and high-efficiency lighting and art installations. State-of-the-art advancements are expected in the field of large area circuits and successful integration of heterogeneous materials, mainly focusing on ceramics and electronics.

['Tullio Facchinetti', 'Guido Benetti', 'Alessandro Tramonte', 'Luca Carraro', 'Mauro Benedetti', 'Enrico Maria Randone', 'Marcello Simonetta', 'Giorgio Capelli', 'Guido Giuliani']

Luminous Tiles: A New Smart Device for Buildings and Architectures

The Phytophthora Genome Initiative (PGI) is a distributed collaboration to study the genome and evolution of a particularly destructive group of plant pathogenic oomycete, with the goal of understanding the mechanisms of infection and resistance. NCGR provides informatics support for the collaboration as well as a centralized data repository. In the pilot phase of the project, several investigators prepared Phytophthora infestans and Phytophthora sojae EST and Phytophthora sojae BAC libraries and sent them to another laboratory for sequencing. Data from sequencing reactions were transferred to NCGR for analysis and curation. An analysis pipeline transforms raw data by performing simple analyses (i.e., vector removal and similarity searching) that are stored and can be retrieved by investigators using a web browser. Here we describe the database and access tools, provide an overview of the data therein and outline future plans. This resource has provided a unique opportunity for the distributed, collaborative study of a genus from which relatively little sequence data are available. Results may lead to insight into how better to control these pathogens. The homepage of PGI can be accessed at http:www.ncgr.org/pgi , with database access through the database access hyperlink.

['Mark Waugh', 'Peter Hraber', 'Jennifer W. Weller', 'Yihe Wu', 'Guanghong Chen', 'Jeff T. Inman', 'Donald Kiphart', 'Bruno W. S. Sobral']

The phytophthora genome initiative database: informatics and analysis for distributed pathogenomic research.

In this paper, we propose a novel method, called random subspace method (RSM) based on tensor (Tensor-RS), for face recognition. Different from the traditional RSM which treats each pixel (or feature) of the face image as a sampling unit, thus ignores the spatial information within the face image, the proposed Tensor-RS regards each small image region as a sampling unit and obtains spatial information within small image regions by using reshaping image and executing tensor-based feature extraction method. More specifically, an original whole face image is first partitioned into some sub-images to improve the robustness to facial variations, and then each sub-image is reshaped into a new matrix whose each row corresponds to a vectorized small sub-image region. After that, based on these rearranged newly formed matrices, an incomplete random sampling by row vectors rather than by features (or feature projections) is applied. Finally, tensor subspace method, which can effectively extract the spatial information within the same row (or column) vector, is used to extract useful features. Extensive experiments on four standard face databases (AR, Yale, Extended Yale B and CMU PIE) demonstrate that the proposed Tensor-RS method significantly outperforms state-of-the-art methods.

['Yulian Zhu', 'Jing Xue']

Face recognition based on random subspace method and tensor subspace analysis

This paper proposes the online reconfiguration of active distribution networks. The control of the active/reactive output power of distributed generation (DG) units combined with the control of remote controlled switches are employed in order to minimize DG curtailment, alleviate lines congestion, and mitigate voltage rise issues due to DG integration. Convex relaxations of the ac power flow equations and mixed integer linear disjunctive formulations are adopted to the optimization model in order to obtain fast and optimal solutions using standard branch and bound solvers. The computation burden of the optimization procedure is drastically reduced by exploiting the assessment of switching actions, which is performed using multiple load/generation scenarios. The effectiveness of the proposed optimization model is verified using different distribution test systems.

['Nikolaos C. Koutsoukis', 'Dimitris O. Siagkas', 'Pavlos S. Georgilakis', 'Nikos D. Hatziargyriou']

Online Reconfiguration of Active Distribution Networks for Maximum Integration of Distributed Generation

word and language operations on trajectories provide a general framework for the study of properties of sequential insertion and deletion operations. A trajectory gives a syntactical constraint on the scattered insertion (deletion) of a word into(from) another one, with an intuitive geometrical interpretation. Moreover, deletion on trajectories is an inverse of the shuffle on trajectories. These operations are a natural generalization of many binary word operations like catenation, quotient, insertion, deletion, shuffle, etc. Besides they were shown to be useful, e.g. in concurrent processes modelling and recently in biocomputing area.We begin with the study of algebraic properties of the deletion on trajectories. Then we focus on three standard decision problems concerning linear language equations with one variable, involving the above mentioned operations. We generalize previous results and obtain a sequence of new ones. Particularly, we characterize the class of binary word operations for which the validity of such a language equation is (un)decidable, for regular and context-free operands.

['Lila Kari', 'Petr Sosík']

Aspects of shuffle and deletion on trajectories

This paper presents a reflection about function construction through well-founded recursion in the type theory known as Calculus of Inductive Constructions. It shows the expressive power of this calculus when dealing with concepts as accesibility and noetherianity among others. The properties of the General Recursion Scheme ([2]) and its relation with Structural Recursion in inductive types are analyzed. As a consequence, a methodology arises which is illustrated with some examples.We use the INRIA's compiler of the Calculus of Inductive Constructions: Coq[6].

['José Luis Freire', 'Enrique Xavier Garcés Freire', 'Antonio Martínez Blanco']

On recursive functions and well-founded relations in the calculus of constructions

We develop three parametric models for electroencephalography (EEG) to estimate current sources that are spatially distributed on a line. We assume a realistic head model and solve the EEG forward problem using the boundary element method (BEM). We present the models with increasing degrees of freedom, provide the forward solutions, and derive the maximum-likelihood estimates as well as Crameacuter-Rao bounds of the unknown source parameters. A series of experiments are conducted to evaluate the applicability of the proposed models. We use numerical examples to demonstrate the usefulness of our line-source models in estimating extended sources. We also apply our models to the real EEG data of N20 response that is known to have an extended source. We observe that the line-source models explain the N20 measurements better than the dipole model

['Nannan Cao', 'Imam Samil Yetik', 'Arye Nehorai', 'Carlos H. Muravchik', 'Jens Haueisen']

Estimating Parametric Line-Source Models With Electroencephalography

This paper analyzes approaches investigating success drivers of mergers and acquisitions (M&A) in the software industry. The literature review covers a classification of research pa-pers in the generic and software industry-specific M&A research discipline. The results ac-centuate that the impact of success factors depends on the research context and that many factors have not been examined thus far with respect to the software industry. Correspondingly, the resulting areas for research are pointed out. Thereof, the investigation of software industry-specific factors, in particular, seems to contribute to the analysis of variance in M&A performance.

['Markus Schief', 'Peter Buxmann', 'Dirk Schiereck']

Mergers and Acquisitions in the Software Industry – Research Results in the Area of Success Determinants

The inherently weak reliability behavior of the ring architecture has led network designers to consider various design choices to improve network reliability. We assess the impact of provisions such as node bypass, secondary ring and concentrator trees on network reliability. For this reason, we develop closed-form expressions for the reliability and the mean time-to-failure of the double counter-rotating ring architecture. For our comparisons we adopt the 2-terminal, and the all-terminal reliability criteria. Our network reliability expressions are valid for any time-to-failure distributions of links and nodes. >

['Dimitris Logothetis', 'Kishor S. Trivedi']

Reliability analysis of the double counter-rotating ring with concentrator attachments

Model Checking an OSEK/VDX-Based Operating System for Automobile Safety Analysis

['Yunja Choi']

Model Checking an OSEK/VDX-Based Operating System for Automobile Safety Analysis

A central problem in built-in self test (BIST) is how to efficiently generate a small set of test vectors that detect all targeted faults. We propose a novel solution that uses linear algebraic concepts to partition the vector space of tests into subspaces (clusters). A subspace is defined by a compact set of basis vectors. We give an algorithm to compute sets of basis vectors defining the clusters. We also describe a low-cost logic circuit based on Gray codes that reproduces the subspaces from these basis vectors. Experimental results are presented which show that this approach reduces on-chip hardware overhead and test application time, while also guaranteeing full fault coverage.

['R. Das', 'Igor L. Markov', 'John P. Hayes']

On-Chip Test Generation Using Linear Subspaces

Objective#R##N#Healthcare communities have identified a significant need for disease-specific information. Disease-specific ontologies are useful in assisting the retrieval of disease-relevant information from various sources. However, building these ontologies is labor intensive. Our goal is to develop a system for an automated generation of disease-pertinent concepts from a popular knowledge resource for the building of disease-specific ontologies.#R##N#Methods#R##N#A pipeline system was developed with an initial focus of generating disease-specific treatment vocabularies. It was comprised of the components of disease-specific citation retrieval, predication extraction, treatment predication extraction, treatment concept extraction, and relevance ranking. A semantic schema was developed to support the extraction of treatment predications and concepts. Four ranking approaches (i.e., occurrence, interest, degree centrality, and weighted degree centrality) were proposed to measure the relevance of treatment concepts to the disease of interest. We measured the performance of four ranks in terms of the mean precision at the top 100 concepts with five diseases, as well as the precision-recall curves against two reference vocabularies. The performance of the system was also compared to two baseline approaches.#R##N#Results#R##N#The pipeline system achieved a mean precision of 0.80 for the top 100 concepts with the ranking by interest. There were no significant different among the four ranks (p = 0.53). However, the pipeline-based system had significantly better performance than the two baselines.#R##N#Conclusions#R##N#The pipeline system can be useful for an automated generation of disease-relevant treatment concepts from the biomedical literature.

['Liqin Wang', 'Guilherme Del Fiol', 'Bruce E. Bray', 'Peter J. Haug']

Generating disease-pertinent treatment vocabularies from MEDLINE citations

Expanding the coverage of Communications Standards [Welcome Message]

['Robert S. Fish']

Expanding the coverage of Communications Standards [Welcome Message]

We characterize and compute the maximal admissible positively invariant set for asymptotically stable constrained switching linear systems. Motivated by practical problems found, e.g., in obstacle avoidance, power electronics and nonlinear switching systems, in our setting the constraint set is formed by a finite number of polynomial inequalities. First, we observe that the so-called Veronese lifting allows to represent the constraint set as a polyhedral set. Next, by exploiting the fact that the lifted system dynamics remains linear, we establish a method based on reachability computations to characterize and compute the maximal admissible invariant set, which coincides with the domain of attraction when the system is asymptotically stable. After developing the necessary theoretical background, we propose algorithmic procedures for its exact computation, based on linear or semidefinite programs. The approach is illustrated in several numerical examples.

['Nikolaos Athanasopoulos', 'Raphaël M. Jungers']

Computing the Domain of Attraction of Switching Systems Subject to Non-Convex Constraints

Intrusion detection is an effective mechanism to dealing with the attacks in computer networks. Pattern recognition techniques have been used for network intrusion detection for more than a decade. Almost all of such intrusion detection systems (IDSs) use an individual classifier to distinguish normal behavior patterns from attack signatures. Moreover these systems have a high false alarm rate and high cost. In this paper, a hierarchical classifier combiner is proposed to detect network intrusions based on the fusion of multiple well-known and efficient classifiers. The KDDCUP99 dataset is used to train and test the classifiers. The overall performance in terms of the overall error rate, average cost and the false alarm rate is investigated and discussed. Also, the performance of the proposed approach is compared with the performance of the most common non- hierarchical combination approaches as well as individual classifiers.

['Morteza Analoui', 'Behrouz Minaei Bidgoli', 'Mohammad Hossein Rezvani']

Hierarchical Classifier Combination and Its Application in Networks Intrusion Detection

Efficient utilization of distributed generation (DG) resources in a microgrid requires coordinated control, which can be realized using multiagent-based system model. The coordinated control requires information exchange among the distributed agents, which can be implemented using either periodic or need-based aperiodic data transmission. For reducing the data communication requirements among the agents, an aperiodic self-triggered communication-based coordinated control is proposed. Centralized as well as distributed self-triggered coordinated control is implemented. The performance evaluation results show that self-triggered aperiodic communication requires lower data rates, while delivering the same performance as that of periodic sampled data control.

['Muhammad Tahir', 'Sudip K. Mazumder']

Self-Triggered Communication Enabled Control of Distributed Generation in Microgrids

Passive RFID tags provide a promising way to create wireless and battery-free heart rate monitors. However, the reliability of these tags is limited in the presence of common noise sources in their environment. In this paper, we propose an algorithm to improve the beat detection for RFID based heart rate monitors in noisy environments. To achieve this, a logistic regression model is first employed to determine data points that have a very high probability of being actual heart beats. These data points are then used as features to remove the ambiguity in detection of other heart beats. The algorithm is trained using features from a single heart rate measurement and the obtained parameters are used for determining various other heart rates. Using our algorithm, we achieve an F1-score of 0.98 for correct heart beat detection, and completely eliminate an error of over 75% in mean heart rate calculation.

['Shrenik Vora', 'Timothy P. Kurzweg']

Modified logistic regression algorithm for accurate determination of heart beats from noisy passive RFID tag data

Ground-based observations at millimeter (mm) and submillimeter (submm) wavelengths were collected at the atmospheric radiation measurement program site at Barrow, AK, during the Arctic winter by a new 25-channel radiometer. A weighting function analysis is presented to demonstrate the enhanced sensitivity of mm- and submm-wave (50-400 GHz) radiometers to low vapor and liquid water contents with respect to conventional instruments such as the ones operating at centimeter (cm) wavelengths (20-30 GHz). In addition, based on measurements, we carried out a quantitative analysis of mm- and submm-wavelength sensitivity, yielding improvement factors from 1.5 to 69 for precipitable water vapor (PWV) and 3 to 4 for liquid water path (LWP) when compared to 20-30 GHz radiometers. Furthermore, using a simulated data set, we evaluate the effect of hydrometeor scattering: given the conditions occurring during the experiment, the scattering contribution is within the instrumental noise for most, but not all, of the considered channels. With the same data set, we demonstrate that in the dry conditions of the Arctic, a simple linear regression yields satisfactory results when applied on selected mm- and submm-wave channels. For a dual-channel combination, the expected accuracy is ~0.23 (0.007) mm for PWV (LWP), when using mm- and submm-wavelengths, whereas it is 0.37 (0.012) mm using cm-wave channels. When the retrieval is applied to real observations, the accuracy is found in agreement with theoretical expectations.

['Domenico Cimini', 'Ed R. Westwater', 'Albin J. Gasiewski', 'Marian Klein', 'V. Ye Leuski', 'James C. Liljegren']

Ground-Based Millimeter- and Submillimeter-Wave Observations of Low Vapor and Liquid Water Contents

This paper describes an approach for object-based image retrieval based on classes of objects in images. In this approach, contours of objects are extracted from images and are represented under a scheme which satisfies scale, rotation and translation invariance. Classifier learning techniques are used to classify objects in images into different classes. Image similarity calculation is performed based on class information of objects. Experimental results show that the method is effective and efficient.

['Linhui Jia', 'Leslie J. Kitchen']

Classification-driven object-based image retrieval

We estimate the n-gram entropies of natural language texts in word-length representation and nd that these are sensitive to text language and genre. We attribute this sensitivity to changes in the probability distribution of the lengths of single words and emphasize the crucial role of the uniformity of probabilities of having words with length between ve and ten. Furthermore, comparison with the entropies of shued data reveals the impact of word length correlations on the estimated n-gram entropies.

['Maria Kalimeri', 'Vassilios Constantoudis', 'Constantinos Papadimitriou', 'Konstantinos Karamanos', 'F. K. Diakonos', 'Harris Papageorgiou']

Entropy analysis of word-length series of natural language texts: Effects of text language and genre

Automobiles provide a convenient form of transportation, and the number of automobiles in the world has been increasing rapidly, from 193 million in 1970 to more than 796 million in recent years [1]. However, automobiles have created a number of serious problems, such as accidents, traffic congestion, and air pollution, among which traffic accidents are one of the most serious and urgent problems threatening the safety of automobile users.

['Youjun Choi', 'Sang Ik Han', 'Seung-Hyun Kong', 'Hyunwoo Ko']

Driver Status Monitoring Systems for Smart Vehicles Using Physiological Sensors: A safety enhancement system from automobile manufacturers

Quorum consensus protocols execute requests in parallel and proceed once K out of N responses are received. The performance of a system depends on the value of K, the distributions of the quorum response delays, and on the use of system resources by the N concurrent requests. An analytic approximation is given for the delay to achieve the quorum, which also accounts for the contention and delay caused by the (N - K) delayed responses. Compared to simulation results, our approximation gives reasonable accuracy; about 5% in most cases. Our method is shown to be rapid and scalable.

['Tariq Omari', 'Salem Derisavi', 'Greg Franks', 'C. Murray Woodside']

Performance Modeling of a Quorum Pattern in Layered Service Systems

This paper considers the support of real-time applications to mobile hosts in an integrated services packet network. We have proposed a service model for mobile hosts that can support adaptive applications which can withstand a wide range of available bandwidth, as well as applications which require mobility independent service guarantees. We describe an admission control scheme and a reservation protocol for implementing this service model. Our admission control scheme achieves high utilization of network resources.

['Anup Talukdar', 'B. R. Badrinath', 'Arup Acharya']

On accommodating mobile hosts in an integrated services packet network

Genomic studies and high-throughput experiments often produce large lists of candidate genes among which only a small fraction are truly relevant to the disease, phenotype or biological process of interest. Gene prioritization tackles this problem by ranking candidate genes by profiling candidates across multiple genomic data sources and integrating this heterogeneous information into a global ranking. We describe an extended version of our gene prioritization method, Endeavour, now available for six species and integrating 75 data sources. The performance (Area Under the Curve) of Endeavour on cross-validation benchmarks using ‘gold standard’ gene sets varies from 88% (for human phenotypes) to 95% (for worm gene function). In addition, we have also validated our approach using a time-stamped benchmark derived from the Human Phenotype Ontology, which provides a setting close to prospective validation. With this benchmark, using 3854 novel gene–phenotype associations, we observe a performance of 82%. Altogether, our results indicate that this extended version of Endeavour efficiently prioritizes candidate genes. The Endeavour web server is freely available at https://endeavour.esat.kuleuven.be/.

['Léon-Charles Tranchevent', 'Amin Ardeshirdavani', 'Sarah Elshal', 'Daniel Alcaide', 'Jan Aerts', 'Didier Auboeuf', 'Yves Moreau']

Candidate gene prioritization with Endeavour

The focus of this research is to model and solve a large-scale service network design problem involving express package delivery. The objective is to find the cost minimizing movement of packages from their origins to their destinations, given very tight service windows, limited package sort capacity, and a finite number of ground vehicles and aircraft. We have developed a model for large scale transportation service network design problems with time windows. With the use of route-based decision variables, we capture complex cost structures and operating regulations and policies. The poor linear programming bounds limit our ability to solve the problem, so we strengthen our linear programming relaxation by adding valid inequalities. By exploiting problem structure using a specialized network representation and applying a series of novel problem reduction methods, we achieve dramatic decreases in problem size without compromising optimality of the model. Our solution optimization approach synthesizes column and row generation optimization techniques and heuristics to generate solutions to an express package delivery application containing hundreds of thousands of constraints and billions of variables, using only a small fraction of the constraint matrix. The results are potential savings in annual operating costs of tens of millions of dollars, reductions in the fleet size required, dramatic decreases in the time required to develop operating plans, and scenario analysis capabilities for planners and analysts. Through this and additional computational experiments, we conclude that, although state-of-the-art integer programming methods can work well for relatively small, uncongested service network design problems, they must be used in concert with heuristics to be effective for large-scale, congested problems encountered in practice.

['Daeki Kim', 'Cynthia Barnhart', 'Keith A. Ware', 'Gregory A. Reinhardt']

Multimodal Express Package Delivery: a Service Network Design Application

OFDM system suffers from significant performance degradation due to phase noise. Many phase noise analysis methods have been proposed in the literature showing its effect as a loss in the ratio of the signal power to the statistical average of the intercarrier interference (ICI). It would be more desirable, however, to predict phase noise effect on bit error rate (BER) directly. In this paper, by investigating the phase noise properties and the impacts caused by phase noise on an OFDM system, we derive approximate closed-form expressions for BER performance in AWGN channels with BPSK and QPSK modulations. In general, it is impossible to get such expression for multipath Rayleigh fading channels. Hence we establish upper and lower bounds for the degradation caused by phase noise, which give insightful view of the system performance. Simulation results show that the proposed simple analytical forms are quite accurate for different phase noise levels, which lead to the conclusion that a phase noise mitigation mechanism is needed to obtain acceptable performance in OFDM systems.

['Pan Liu', 'Yeheskel Bar-Ness']

Closed-Form Expressions for BER Performance in OFDM Systems with Phase Noise

In this paper we study the problem of partitioning a convex polygon P of n vertices into m polygons of equal area and perimeter. We give an algorithm for m = 2 that runs in O ( n ) time, and an algorithm for m = 2 k , where k is an integer, that runs in O ( ( 2 n ) k ) time. These are the first algorithms to solve this problem.

['Bogdan Armaselu', 'Ovidiu Daescu']

Algorithms for fair partitioning of convex polygons

Maintaining the attitude of a spacecraft precisely aligned to a given orientation is crucial for commercial and scientific space missions. The problem becomes challenging when on/off thrusters are employed instead of momentum exchange devices due to, e.g., wheel failures or power limitations. In this case, the attitude control system must enforce an oscillating motion about the setpoint, so as to minimize the switching frequency of the actuators, while guaranteeing a predefined pointing accuracy and rejecting the external disturbances. This paper develops a three-axis attitude control scheme for this problem, accounting for the limitations imposed by the thruster technology. The proposed technique is able to track both the period and the phase of periodic oscillations along the rotational axes, which is instrumental to minimize the switching frequency in the presence of input coupling. Two simulation case studies of a geostationary mission and a low Earth orbit mission are reported, showing that the proposed controller can effectively deal with both constant and time-varying disturbance torques.

['Mirko Leomanni', 'Andrea Garulli', 'Antonio Giannitrapani', 'Francesco Farina', 'Fabrizio Scortecci']

Minimum Switching Thruster Control for Spacecraft Precision Pointing

In this paper, we propose a novel sealed-bid auction framework to address the problem of dynamic spectrum allocation in cognitive radio (CR) networks. We design an optimal auction mechanism that maximizes the moderator’s expected utility, when the spectrum is not available with certainty. We assume that the moderator employs collaborative spectrum sensing in order to make a reliable inference about spectrum availability. Due to the presence of a collision cost whenever the moderator makes an erroneous inference, and a sensing cost at each CR, we investigate feasibility conditions that guarantee a non-negative utility at the moderator. Since the moderator fuses CRs’ sensing decisions to obtain a global inference regarding spectrum availability, we propose a novel strategy-proof fusion rule that encourages the CRs to simultaneously reveal truthful sensing decisions, along with truthful valuations to the moderator. We also present tight theoretical bounds on instantaneous network throughput achieved by our auction mechanism. Numerical examples are presented to provide insights into the performance of the proposed auction under different scenarios.

['V. Sriram Siddhardh Nadendla', 'Swastik Brahma', 'Pramod K. Varshney']

Optimal Spectrum Auction Design With 2-D Truthful Revelations Under Uncertain Spectrum Availability

The mapping of regulatory guidelines with organizational processes is an important aspect of a regulatory-compliance management system. Automating this mapping process can greatly improve the overall compliance process. Currently, there is research on mapping between different entities such as ontology mapping, sentence similarity, semantic similarity and regulation-requirement mapping. However, there has not been adequate research on the automation of the mapping process between regulatory guidelines and organizational processes. In this paper, we explain how Natural Language Processing and Semantic Web technologies can be applied in this area. In particular, we explain how we can take advantage of the structures of regulation-ontology and the process-ontology in order to compute the similarity between a regulatory guideline and a process. Our methodology is validated using a case study in the Pharmaceutical industry, which has shown promising results.

['Krishna Sapkota', 'Arantza Aldea', 'Muhammad Younas', 'David A. Duce', 'René Bañares-Alcántara']

Automating the semantic mapping between regulatory guidelines and organizational processes

Mashup applications for business can lead to better business insights, marketing opportunities, and may provide opportunity to monetize the value locked in business data. To enable necessary experimentation with mashups by domain experts, we describe a development and runtime framework that exposes data level abstractions in the form of templates and automates the programming details associated with plumbing for mashups. The framework also provides runtime support to manage security, reliability, and other business application related enterprise IT concerns.

['Vijay K. Naik']

A Framework for Business Mashup Applications

A correctly designed dynamic programming algorithm can be used as a fitness function to permit the evolution of maze-like levels for use in games. This study compares multiple representations for evolvable mazes including direct, as well as positive and negative indirect representations. The first direct representation simply specifies, with a binary gene, which squares of a grid are obstructed. The second paints the maze grid and passage is allowed only between colors that are the same or adjacent in a rainbow. The positive and negative representations are developmental and evolve directions for adding barriers or digging “tunnels.” These representations are tested with a design space of fitness functions that automatically generate levels with controllable properties. Fitness function design is the most difficult part of automatic level generation and this study gives a simple framework for designing fitness functions that permits substantial control over the character of the mazes that evolve. This technique relies on using checkpoints within the maze to characterize the connectivity and path lengths within the level. Called checkpoint-based fitness, these fitness functions are built on a menu of properties that can be rewarded. The choice of which qualities are rewarded, in turn, specifies within broad limits the characteristics of the mazes to be evolved. Three of the representations are found to benefit from a technique called sparse initialization in which a maze starts mostly empty and variation operators fill in details while increasing fitness. Different representations are found to produce mazes with very different appearances, even when the same fitness function is used. The example fitness functions designed around dynamic programming with checkpoints are found to permit substantial control over the properties of the evolved mazes.

['Daniel Ashlock', 'Colin Lee', 'Cameron McGuinness']

Search-Based Procedural Generation of Maze-Like Levels

We introduce an efficient method for computing Montgomery products of polynomials in the frequency domain. The discrete Fourier transform (DFT) based method originally proposed for integer multiplication provides an extremely efficient method with the best asymptotic complexity, i.e. O(mlogmloglogm), for multiplication of m-bit integers or (m–1)st degree polynomials. However, the original DFT method bears significant overhead due to the conversions between the time and the frequency domains which makes it impractical for short operands as used in many applications. In this work, we introduce DFT modular multiplication which performs the entire modular multiplication (including the reduction step) in the frequency domain, and thus eliminates costly back and forth conversions. We show that, especially in computationally constrained platforms, multiplication of finite field elements may be achieved more efficiently in the frequency domain than in the time domain for operand sizes relevant to elliptic curve cryptography (ECC). To the best of our knowledge, this is the first work that proposes the use of frequency domain arithmetic for ECC and shows that it can be efficient.

['Selcuk Baktir', 'Berk Sunar']

Finite field polynomial multiplication in the frequency domain with application to elliptic curve cryptography

With the increasing complexity of Web service management in highly dynamic environments, service providers must participate to the self-adaptation process as they are aware of the capabilities and requirements of their executing services. However, defining additional adaptation policies demands a greater effort. A primary condition to reuse other providers' policies is to understand the information specifying a service behavior. Despite several efforts, a common self-management syntax and semantic was not achieved. In this paper, we propose an ontology-based categorization of autonomic service metadata, which will be used not only for policy discovery and integration, but also for the composition of self-adaptive Web services. We, then, propose to semantically annotate providers' policies. This allows providers to discover and reuse policies based on their semantic meaning. Finally, we propose a framework for the discovery, matching, and integration of providers' policies.

['Haithem Mezni', 'Mokhtar Sellami']

AWS-Ont: An Ontology for the Self-Management of Service-Based Systems

Learning sounding gestures

['Amalia De Götzen', 'Luca Mion', 'Federico Avanzini', 'Stefania Serafin']

Learning sounding gestures

We consider strongly secure communication over a discrete memoryless multiple access wiretap channel with two transmitters - no degradation or symmetry assumptions are made on the channel. Our main result is that any rate pair known to be achievable with a random coding like proof, is also achievable with a low-complexity polar coding scheme. Moreover, if the rate pair is known to be achievable without time-sharing, then time-sharing is not needed in our polar coding scheme as well. Our proof technique relies on rate-splitting and different cooperative jamming strategies. Specifically, our coding scheme combines several point-to-point codes that either aim at secretly conveying a message to the legitimate receiver or at performing cooperative jamming. Each point-to-point code relies on a chaining construction to be able to deal with an arbitrary channel and strong secrecy. We assess reliability and strong secrecy through a detailed analysis of the dependencies between the random variables involved in the scheme.

['Remi A. Chou', 'Aylin Yener']

Polar coding for the multiple access wiretap channel via rate-splitting and cooperative jamming

VODUM: A Topic Model Unifying Viewpoint, Topic and Opinion Discovery

['Thibaut Thonet', 'Guillaume Cabanac', 'Mohand Boughanem', 'Karen Pinel-Sauvagnat']

VODUM: A Topic Model Unifying Viewpoint, Topic and Opinion Discovery

The probabilistic self-organizing map (PRSOM) is an improved version of the Kohonen classical model (SOM) that appeared in the late 1990’s. In the last years, the interest of probabilistic methods, especially in the fields of clustering and classification has increased, and the PRSOM has been successfully employed in many technological uses, such as: pattern recognition, speech recognition, data compression, medical diagnosis, etc. Mathematically, the PRSOM gives an estimation of the density probability function of a set of samples. And this estimation depends on the parameters given by the architecture of the model. Therefore, the main problem of this model, that we try to approach in this paper, is the architecture choice (the number of neurons and the initialization parameters). In summary, in the present paper, we describe a recent approach of PRSOM trying to find a solution to the problem below. For that, we propose an architecture optimization model that is a mixed integer nonlinear optimization model under linear constraints, resolved by the genetic algorithm. Then to prove the efficiency of the proposed model, we chose to apply it on a speech compression technique based on the determination of the optimal codebook, and finally, we give an implementation and an evaluation of the proposed method that we compare with the results of the classical model.

['Zakariae En-Naimani', 'Mohamed Lazaar', 'Mohamed Ettaouil']

Architecture Optimization Model for the Probabilistic Self-Organizing Maps and Speech Compression

A wheelchair is a mandatory device for people with mobility problems. Typical wheelchairs maneuvered by muscular forces are physically demanding in various conditions, e.g., uphill or step. For this purpose, electric wheelchairs have been developed and commercialized for enhancement of the maneuverability and safety of people with muscular weakness. Such systems involve complete human-machine interaction, and thus it is necessary to accurately observe the physical state and the environmental condition in real-time. For this reasoning, a sensor-fusion method and a decision making algorithm for the complete observation of both the physical states of the wheelchair and the intention of a user are introduced in this paper. The physical states to be observed include the wheel speed, the pitch angle and the external forces, which are the most important physical quantities for the control of a power-assisted wheelchair (PAW) system in daily-life conditions. The estimated physical quantities are further processed in real-time in order to detect the environmental conditions and the intentional motions by the human operator. The proposed methods are all verified by experiments in this paper.

['Sehoon Oh', 'Kyoungchul Kong']

Operation condition recognition for the control of power-assisted wheelchair

The authors investigate the re-engineering of time-critical applications using an integration of refinement and transformational techniques. The approach is uniform in the sense that one is able to combined both reverse and forward engineering within the same formal model. The approach is based on designing a wide-spectrum language which is equipped with a specification statement and concrete constructs to cope with concurrency and real-time aspects. The language is an extension of Dijksua's guarded command language with the specification statement taken as a formula expressed in interval temporal logic (ITL). An ITL semantics for WSL is given together with a set of algebraic laws and refinement rules. Reverse engineering is achieved by applying various algebraic laws to produce a structured code (written in WSL) from the original one preserving its semantic equivalence. Such a transformation is done semi-automatically using an extension to MA. The resulting code is considered as an intermediate representation which can then be analysed and used as a basis to construct a higher level of abstraction of the original system. Calculating ITL semantics for the intermediate representation serves as a requirement specification of the original code and is subsequently used as the starting point to forward engineer the system by successive applications of the available refinement calculus. The semantics (an In formula) is produced automatically with the help of the PVS+ toolkit.

['Hussein Zedan', 'Hongji Yang']

A sound and practical approach to the re-engineering of time-critical systems

Value-at-risk (VaR) is a popular measure for quantifying the market risk that a financial institution faces into a single number. Owing to the complexity of financial markets, the risks associated with a portfolio varies over time. Consequently, advanced methods of VaR estimation use parametric conditional models of portfolio volatility (e.g. generalized autoregressive heteroscedasticity (GARCH) models) to adapt risk estimation to changing market conditions. However, more flexible semi-parametric methods that adapt to the highly flexible underlying data distribution are better suited for accurate VaR estimation. In this paper, we consider VaR estimation by using probabilistic fuzzy systems (PFSs). A PFS is a semi-parametric method that combines a linguistic description of the system behaviour with statistical properties of the data. Therefore, they provide the potential to adapt estimations of probability density to the linguistic framework of the modeller. We study two approaches to designing probabilistic fuzzy VaR models and compare their performances with the performance of a GARCH model. It is found that statistical back testing always accepts PFS models after tuning, whereas GARCH models may be rejected. Copyright © 2009 John Wiley & Sons, Ltd.

['Rui Jorge Almeida', 'Uzay Kaymak']

Probabilistic fuzzy systems in value-at-risk estimation

The research question this report addresses is: how, and to what extent, those directly involved with the design, development and employment of a specific black box algorithm can be certain that it is not unlawfully discriminating (directly and/or indirectly) against particular persons with protected characteristics (e.g. gender, race and ethnicity)?

['Steffen Staab', 'Sophie Stalla-Bourdillon', 'Laura Carmichael']

Observing and Recommending from a Social Web with Biases

The first objective of this paper is to introduce a nonlinear system to model the heart rate (HR) response during and after treadmill walking exercise. The model is a feedback interconnected system that has components to describe the central and peripheral local responses to exercise and their interactions. The parameters of the model were experimentally identified from subjects walking on a treadmill at different speeds. The stability of the obtained nonlinear model was mathematically proven. The modeling results demonstrate that the proposed model can be useful in examining the cardiovascular response to exercise. Based on the nonlinear model, the second objective is to present a computer-controlled treadmill system for the regulation of HR during treadmill exercise. The proposed nonlinear controller consists of feedforward and feedback components. The designed control system was experimentally verified and the results demonstrated that the proposed computer-controlled treadmill system regulated the HR of the experimental subjects according to two different exercising HR profiles, indicating that it can play an important role in the design of exercise protocols for individuals.

['Teddy M. Cheng', 'Andrey V. Savkin', 'Branko G. Celler', 'Steven W. Su', 'Lu Wang']

Nonlinear Modeling and Control of Human Heart Rate Response During Exercise With Various Work Load Intensities

Commercial off-the-shelf (COTS) products are increasingly being used in software development. In COTS-based development, selecting appropriate COTS is the most crucial phase. This paper explores the evolution of COTS selection practices, and surveys eighteen of the most significant COTS selection approaches. The paper traces how each approach contributed to the improvement of current COTS selection practices, and then compares them .The paper also highlights some open research issues relevant to the selection process, and concludes with a discussion of possible future directions to address these issues

['Abdallah Mohamed', 'Guenther Ruhe', 'Armin Eberlein']

COTS Selection: Past, Present, and Future

Although Object Orientation is emphasized in software engineering education, few have attempted to alleviate the initial learning curve associated with an inexperienced audience in non-computer science disciplines. The authors propose a Problem-Based Learning curriculum centered on game development to deliver basic Object-Oriented programming concepts in an interactive and engaging manner. Class activities occur within the context of the Object-Oriented Rational Unified Process. One of the most significant contributions of this paper lies in the design of class modules containing tasks intended to educate students on Object-Oriented Software Engineering in an incremental and self-actuated way.

['Jungwoo Ryoo', 'Frederico T. Fonseca', 'David S. Janzen']

Teaching Object-Oriented Software Engineering through Problem-Based Learning in the Context of Game Design

Decentralized Multi-UAV Flight Autonomy for Moving Convoys Search and Track

['Wei Meng', 'Zhirong He', 'Rong Su', 'Pradeep K. Yadav', 'Rodney Teo', 'Lihua Xie']

Decentralized Multi-UAV Flight Autonomy for Moving Convoys Search and Track

This paper evaluates the secure energy efficiency (SEE) of a cooperative network subject to partial secrecy requirements, implemented through a fractional equivocation parameter $\theta \in (0, 1]$ that allows partial secrecy when $\theta . We assume that only the channel state information (CSI) of the legitimate channel is available, while the CSI with respect to the eavesdropper is unknown. Then, we propose a CSI-aided decode-and-forward (DF) scheme, in which the transmitter uses the available CSI in order to choose between direct and cooperative paths. Moreover, the relay employs either repetition coding (CSI-RC), i.e. , source and relay use the same codebook, or parallel coding (CSI-PC), when different codebooks are used. By resorting to the Dinkelbach algorithm, we propose a joint power allocation scheme, which also optimizes $\theta $ to maximize the SEE. Our schemes are compared with the traditional DF, amplify-and-forward, and cooperative jamming (CJ). In most scenarios, CSI-RC performs best in terms of SEE. Nevertheless, we observe that CSI-PC achieves the highest SEE when $\theta \rightarrow 1$ and if the relay is close to either the transmitter or the receiver. Moreover, CJ also stands out to maximize the SEE if the relay is placed closer to the eavesdropper. In addition, the influence of $\theta $ in the system performance is evaluated, showing that a joint $\theta $ and power optimization considerably improves the SEE.

['Jamil Farhat', 'Glauber Gomes de Oliveira Brante', 'Richard Demo Souza', 'Joao Luiz Rebelatto']

Energy Efficiency of Repetition Coding and Parallel Coding Relaying Under Partial Secrecy Regime

A Stacking Gated Neural Architecture for Implicit Discourse Relation Classification.

['Lianhui Qin', 'Zhisong Zhang', 'Hai Zhao']

A Stacking Gated Neural Architecture for Implicit Discourse Relation Classification.

In an attempt to reduce the number of operand memory references, many RISC machines have thirty-two or more general-purpose registers (e.g., MIPS, ARM, Spectrum, 88K). Without special compiler optimizations, such as inlining or interprocedural register allocation, it is rare that a compiler will use a majority of these registers for a function. This paper explores the possibility of using some of these registers to hold branch target addresses and the corresponding instruction at each branch target. To evaluate the effectiveness of this scheme, two machines were designed and emulated. One machine had thirty-two general-purpose registers used for data references, while the other machine had sixteen data registers and sixteen registers used for branching. The results show that using registers for branching can effectively reduce the cost of transfers of control.

['Jack W. Davidson', 'David B. Whalley']

Reducing the cost of branches by using registers

Generation of software from modeling languages such as UML and domain specific languages (DSLs) has become an important paradigm in software engineering. In this contribution, we present some positions on software development in a model based, generative manner based on home grown DSLs as well as the UML. This includes development of DSLs as well as development of models in these languages in order to generate executable code, test cases or models in different languages. Development of formal DSLs contains concepts of metamodels or grammars (syntax), context conditions (static analysis and quality assurance) as well as possibilities to define the semantics of a language. The growing number and complexity of DSLs is addressed by concepts for the modular and compositional development of languages and their tools. Moreover, we introduce approaches to code generation and model transformation. Finally, we give an overview of the relevance of DSLs for various steps of software development processes.

['Bernhard Rumpe', 'Martin Schindler', 'Steven Völkel', 'Ingo Weisemöller']

Generative software development

This paper presents a power factor corrected (PFC) bridgeless (BL) buck-boost converter-fed brushless direct current (BLDC) motor drive as a cost-effective solution for low-power applications. An approach of speed control of the BLDC motor by controlling the dc link voltage of the voltage source inverter (VSI) is used with a single voltage sensor. This facilitates the operation of VSI at fundamental frequency switching by using the electronic commutation of the BLDC motor which offers reduced switching losses. A BL configuration of the buck-boost converter is proposed which offers the elimination of the diode bridge rectifier, thus reducing the conduction losses associated with it. A PFC BL buck-boost converter is designed to operate in discontinuous inductor current mode (DICM) to provide an inherent PFC at ac mains. The performance of the proposed drive is evaluated over a wide range of speed control and varying supply voltages (universal ac mains at 90-265 V) with improved power quality at ac mains. The obtained power quality indices are within the acceptable limits of international power quality standards such as the IEC 61000-3-2. The performance of the proposed drive is simulated in MATLAB/Simulink environment, and the obtained results are validated experimentally on a developed prototype of the drive.

['Vashist Bist', 'Bhim Singh']

An Adjustable-Speed PFC Bridgeless Buck–Boost Converter-Fed BLDC Motor Drive

We describe how techniques from computer graphics are used to visualize pool fire data and computer radiative effects from pool fires. The basic tools are ray casting and accurate line integration using the RADCAL program. Example images in the visible and infrared band are shown which give qualitative insights about the fire data. Examples are given of irradiation calculations and novel methods to visualize the results of irradiation calculations.

['Holly E. Rushmeier', 'Anthony Hamins', 'Mun-Young Choi']

Case study: volume rendering of pool fire data

The translation efficiency of most Saccharomyces cerevisiae genes remains fairly constant across poor and rich growth media. This observation has led us to revisit the available data and to examine the potential utility of a protein abundance predictor in reinterpreting existing mRNA expression data. Our predictor is based on large-scale data of mRNA levels, the tRNA adaptation index, and the evolutionary rate. It attains a correlation of 0.76 with experimentally determined protein abundance levels on unseen data and successfully cross-predicts protein abundance levels in another yeast species (Schizosaccharomyces pombe). The predicted abundance levels of proteins in known S. cerevisiae complexes, and of interacting proteins, are significantly more coherent than their corresponding mRNA expression levels. Analysis of gene expression measurement experiments using the predicted protein abundance levels yields new insights that are not readily discernable when clustering the corresponding mRNA expression levels. Comparing protein abundance levels across poor and rich media, we find a general trend for homeostatic regulation where transcription and translation change in a reciprocal manner. This phenomenon is more prominent near origins of replications. Our analysis shows that in parallel to the adaptation occurring at the tRNA level via the codon bias, proteins do undergo a complementary adaptation at the amino acid level to further increase their abundance.

['Tamir Tuller', 'Martin Kupiec', 'Eytan Ruppin']

Determinants of Protein Abundance and Translation Efficiency in S. cerevisiae

Open source software (OSS) development is considered an effective approach to ensuring acceptable levels of software quality. One facet of quality improvement involves the detection of potential relationship between defect density and other open source software metrics. This paper presents an empirical study of the relationship between defect density and download number, software size and developer number as three popular repository metrics. This relationship is explored by examining forty-four randomly selected open source software projects retrieved from SourceForge.net. By applying simple and multiple linear regression analysis, the results reveal a statistically significant relationship between defect density and number of developers and software size jointly. However, despite theoretical expectations, no significant relationship was found between defect density and number of downloads in OSS projects.

['Cobra Rahmani', 'Deepak Khazanchi']

A Study on Defect Density of Open Source Software

Responsible programming

['Vinton G. Cerf']

Responsible programming

A prefix normal word is a binary word with the property that no substring has more 1s than the prefix of the same length. This class of words is important in the context of binary jumbled pattern matching. In this paper we present an efficient algorithm for exhaustively listing the prefix normal words with a fixed length. The algorithm is based on the fact that the language of prefix normal words is a bubble language, a class of binary languages with the property that, for any word w in the language, exchanging the first occurrence of 01 by 10 in w results in another word in the language. We prove that each prefix normal word is produced in O(n) amortized time, and conjecture, based on experimental evidence, that the true amortized running time is O(log(n)).

['Péter Burcsi', 'Gabriele Fici', 'Zsuzsanna Lipták', 'Frank Ruskey', 'Joe Sawada']

On Combinatorial Generation of Prefix Normal Words

Motivation: Gene expression profiling using RNA-seq is a powerful technique for screening RNA species’ landscapes and their dynamics in an unbiased way. While several advanced methods exist for differential expression analysis of RNA-seq data, proper tools to anal.yze RNA-seq time-course have not been proposed. Results: In this study, we use RNA-seq to measure gene expression during the early human T helper 17 (Th17) cell differentiation and T-cell activation (Th0). To quantify Th17-specific gene expression dynamics, we present a novel statistical methodology, DyNB, for analyzing timecourse RNA-seq data. We use non-parametric Gaussian processes to model temporal correlation in gene expression and combine that with negative binomial likelihood for the count data. To account for experiment-specific biases in gene expression dynamics, such as differences in cell differentiation efficiencies, we propose a method to rescale the dynamics between replicated measurements. We develop an MCMC sampling method to make inference of differential expression dynamics between conditions. DyNB identifies several known and novel genes involved in Th17 differentiation. Analysis of differentiation efficiencies revealed consistent patterns in gene expression dynamics between different cultures. We use qRT-PCR to validate differential expression and differentiation efficiencies for selected genes. Comparison of the results with those obtained via traditional timepoint-wise analysis shows that time-course analysis together with time rescaling between cultures identifies differentially expressed genes which would not otherwise be detected. Availability: An implementation of the proposed computational methods will be available at http://research.ics.aalto.fi/csb/software/ Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

['Tarmo Äijö', 'Vincent Butty', 'Zhi Jane Chen', 'Verna Salo', 'Subhash Tripathi', 'Christopher B. Burge', 'Riitta Lahesmaa', 'Harri Lähdesmäki']

Methods for time series analysis of RNA-seq data with application to human Th17 cell differentiation

Ambient Intelligence (AmI) promises future environments that support the well-being of their inhabitants through comfort and assistive environments. For the elderly users, Ambient Assisted Living (AAL) scenarios are targeting safe and independent living at home. Especially the integration of home automation components, such as intelligent light, window, and climate controls seem promising for such scenarios. In this paper, we present a new development method that is based on a detailed three-dimensional model and show how the model can be used for designing and evaluating assistive environments. Such a system has been developed and deployed. We present an architectural foundation of how Universal Remote Console technology can be applied to synchronize the virtual environment model with the real world. Furthermore, we extend previous work on Dual Reality by introducing the concept of Synchronized Realities that includes the synchronization between remote AmI environments. We will discuss application scenarios and show two demonstrators that we have implemented based on the proposed development method.

['Christoph Stahl', 'Jochen Frey', 'Jan Alexandersson', 'Boris Brandherm']

Synchronized Realities

Context : In this paper we present an exploratory study on the insights of organizations into the perceived value of their software projects. Our study is based on the notion that quantifying and qualifying project size, cost, duration and defects needs to be done in relation with stakeholder satisfaction and perceived value. Objectives : We expect that bringing perceived value into the equation will help in increasing the impact such organizations deliver. Method : In order to find out whether our approach is practically feasible in an industrial setting, we performed an exploratory study in a Belgian telecom company. Results : In this study we evaluate 22 software projects that were delivered during one release. Fifty-three (53) key stakeholders provide stakeholder satisfaction and perceived value measurements in 103 completed surveys. Conclusions : We conclude that a focus on shortening overall project duration , and improving communication on intermediate progress improved stakeholder satisfaction and perceived value . Our study does not provide any evidence that steering on costs helped to improve these.

['Hennie Huijgens', 'Arie van Deursen', 'Rini van Solingen']

An exploratory study on the effects of perceived value and stakeholder satisfaction on software projects

We suggest a method of inspecting the latent space of stock market data using genetic programming. Given black box patterns and (stock, day) tuples a relation matrix is constructed. Applying a low-rank matrix factorization technique to the relation matrix induces a latent vector space. By manipulating the latent vector representations of black box patterns, the geometry of the latent space can be examined. Genetic programming constructs a tree representation corresponding to an arbitrary latent vector representation, allowing us to interpret the result of the inspection.

['Sungjoo Ha', 'Sangyeop Lee', 'Byung-Ro Moon']

Inspecting the Latent Space of Stock Market Data with Genetic Programming

We propose a robust wavelet domain method for noise filtering in medical images. The proposed method adapts itself to various types of image noise as well as to the preference of the medical expert; a single parameter can be used to balance the preservation of (expert-dependent) relevant details against the degree of noise reduction. The algorithm exploits generally valid knowledge about the correlation of significant image features across the resolution scales to perform a preliminary coefficient classification. This preliminary coefficient classification is used to empirically estimate the statistical distributions of the coefficients that represent useful image features on the one hand and mainly noise on the other. The adaptation to the spatial context in the image is achieved by using a wavelet domain indicator of the local spatial activity. The proposed method is of low complexity, both in its implementation and execution time. The results demonstrate its usefulness for noise suppression in medical ultrasound and magnetic resonance imaging. In these applications, the proposed method clearly outperforms single-resolution spatially adaptive algorithms, in terms of quantitative performance measures as well as in terms of visual quality of the images.

['Aleksandra Pizurica', 'Wilfried Philips', 'Ignace Lemahieu', 'Marc Acheroy']

A versatile wavelet domain noise filtration technique for medical imaging

We present a novel approach for multi-channel operation (MCO) in vehicular communication systems, which allows for efficient utilization of the available bandwidth by asynchronous channel switching and enables dynamic service provisioning and usage by means of service advertisements. The proposed solution – Service-Actuated Multi-Channel Operation (SAMCO) – provides a logic that controls the prioritization of services and the timing of channel switching. It takes into account users preferences to decide on the consumption of a particular service if several concurrent services are available. SAMCO employs a novel channel load estimation scheme that, in addition to measuring the load on the channel at the physical layer, exploits the information contained in service advertisements. We perform simulations and use platooning as an example of a service with particularly stringent requirements to show that SAMCO can support service prioritization, continuity of service for high-priority services, and graceful degradation for low-priority services. Furthermore, by limiting the admission to services in high load scenarios, we show that SAMCO effectively controls the channel load and thereby complements congestion control mechanisms. Finally, we discuss the extensions needed in currently standardized solutions to implement SAMCO.

['Mate Boban', 'Andreas Festag']

Service-actuated multi-channel operation for vehicular communications

In this paper we report on an ethnographic study of a small software house to discuss the practical work of software testing. Through use of two rich descriptions, we discuss that "rigour' in systems integration testing necessarily has to be organisationally defined. Getting requirements "right', defining "good' test scenarios and ensuring "proper' test coverage are activities that need to be pragmatically achieved taking account of organisational realities and constraints such as: the dynamics of customer relationships; using limited effort in an effective way; timing software releases; and creating a market. We discuss how these organisational realities shape (1) requirements testing; (2) test coverage; (3) test automation; and (4) test scenario design.

['David B. Martin 0001', 'John Rooksby', 'Mark Rouncefield', 'Ian Sommerville']

'Good' Organisational Reasons for 'Bad' Software Testing: An Ethnographic Study of Testing in a Small Software Company

The correct inference of gene regulatory networks for the understanding of the intricacies of the complex biological regulations remains an intriguing task for researchers. With the availability of large dimensional microarray data, relationships among thousands of genes can be simultaneously extracted. Among the prevalent models of reverse engineering genetic networks, S-system is considered to be an efficient mathematical tool. In this paper, Bat algorithm, based on the echolocation of bats, has been used to optimize the S-system model parameters. A decoupled S-system has been implemented to reduce the complexity of the algorithm. Initially, the proposed method has been successfully tested on an artificial network with and without the presence of noise. Based on the fact that a real-life genetic network is sparsely connected, a novel Accumulative Cardinality based decoupled S-system has been proposed. The cardinality has been varied from zero up to a maximum value, and this model has been implemented for the reconstruction of the DNA SOS repair network of Escherichia coli. The obtained results have shown significant improvements in the detection of a greater number of true regulations, and in the minimization of false detections compared to other existing methods.

['Sudip Mandal', 'Abhinandan Khan', 'Goutam Saha', 'Rajat Kumar Pal']

Reverse engineering of gene regulatory networks based on S-systems and Bat algorithm

The current generation of young people indulges in more media multitasking behavior (e.g., instant messaging while watching videos) in their everyday lives than older generations. Concerns have been raised about how this might affect their attentional functioning, as previous studies have indicated that extensive media multitasking in everyday life may be associated with decreased attentional control. In the current study, 149 adolescents and young adults (aged 13–24 years) performed speech-listening and reading tasks that required maintaining attention in the presence of distractor stimuli in the other modality or dividing attention between two concurrent tasks. Brain activity during task performance was measured using functional magnetic resonance imaging (fMRI). We studied the relationship between self-reported daily media multitasking (MMT), task performance and brain activity during task performance. The results showed that in the presence of distractor stimuli, a higher MMT score was associated with worse performance and increased brain activity in right prefrontal regions. The level of performance during divided attention did not depend on MMT. This suggests that daily media multitasking is associated with behavioral distractibility and increased recruitment of brain areas involved in attentional and inhibitory control, and that media multitasking in everyday life does not translate to performance benefits in multitasking in laboratory settings.

['M. Moisala', 'Viljami R. Salmela', 'Lauri Hietajärvi', 'Eeva Salo', 'Synnöve Carlson', 'Oili Salonen', 'Kirsti Lonka', 'Kai Hakkarainen', 'Katariina Salmela-Aro', 'K. Alho']

Media multitasking is associated with distractibility and increased prefrontal activity in adolescents and young adults

In this paper, we study the problem of half-duplex active eavesdropping in fast-fading channels. The active eavesdropper is a more powerful adversary than the classical eavesdropper. It can choose between two functional modes: eavesdropping the transmission between the legitimate parties (Ex mode), and jamming it (Jx mode)-the active eavesdropper cannot function in full duplex mode. We consider a conservative scenario, when the active eavesdropper can choose its strategy based on the legitimate transmitter-receiver pair's strategy, and thus, the transmitter and legitimate receiver have to plan for the worst. We show that conventional physical-layer secrecy approaches perform poorly (if at all), and we introduce a novel encoding scheme, based on very limited and unsecured feedback-the Block-Markov Wyner encoding scheme-which outperforms any schemes currently available.

['George T. Amariucai', 'Shuangqing Wei']

Half-Duplex Active Eavesdropping in Fast-Fading Channels: A Block-Markov Wyner Secrecy Encoding Scheme

Grid computing has proven to be a solution for big workflow execution, especially in Bioinformatics. However, grid nature itself introduces overheads that make its use in many cases an unfeasible solution if considering wall-time. Different heuristics such as list scheduling, agglomeration and replication are available for optimizing workflow execution. In particular, the replication heuristics have been previously used in heterogeneous environments with good results. In this work, we analyze their use for workflow scheduling on Grid infrastructures. In particular, we study its applications to an intree workflow, generated by the distribution of the CD-HIT application. The experiments were conducted on a testbed made of resources from two different grids and results show a significant reduction of the workflow execution time.

['José Luis Vázquez-Poletti', 'Eduardo Huedo', 'Rubén S. Montero', 'Ignacio Martín Llorente']

CD-HIT Workflow Execution on Grids Using Replication Heuristics

This paper presents a new approach to image segmentation, based on the conditional random fields (CRF) modeling and AdaBoost. In the proposed segmentation algorithm, the discriminating characteristics are first learned online using a training machine, and then the learnt characteristics are used to improve the region segmentation. The proposed algorithm is devised to include any kind of features even if they have different semantics, and to learn the difference of regions by selecting and combining only a few discriminating features among them. These novel properties are accomplished by a new Gibbs energy derived from CRF, AdaBoost, and probabilistic interpretation of its strong classifier. Experimental results on various images show the effectiveness of the proposed method.

['Hyung Il Koo', 'Nam Ik Cho']

Boosting image segmentation

A reconfigurable network architecture applied to spiking neural networks is presented. For hardware platforms for neural networks that implement some degree of realism of interest to neuroscientists, connectivity between neurons can be a major limitation. Recent data indicates that neurons in the brain form clusters of connections. Through the combination of this data and a routing scheme that uses a hybrid of short-range direct connectivity and an AER (Address Event Representation) network, the presented architecture aims to provide a useful amount of inter-neuron connectivity. A connection-centric design can provide opportunities for NoCs such as optimising power, bandwidth or introducing redundancy. A method of mapping a network to the architecture is discussed, along with results of optimal hardware specifications for a given set of network parameters.

['Robin Emery', 'Alexandre Yakovlev', 'E. Graeme Chester']

Connection-centric network for spiking neural networks

As networking technology advances, more advanced message services are provided. Users may have one or more different message accounts and devices. Before sending messages, the sender must make sure which message service the receipt currently uses. Any misjudgement may delay the time when the messages are received. To make users be able to receive messages anytime and anywhere with any kind of devices, we propose a Ubiquitous and Unified Multimedia Messaging (UMM) platform. The UMM platform integrates different message services and provides a more efficient way for message delivery. Our design does not modify the existing protocols of message services and need not involve the network operators. An analytical model is proposed to evaluate the performance of the implemented platform. Our study shows that with a large number of message services the user subscribes and long message processing time in the network, the delayed message probability can be limited within 1.5%. This performance is considered satisfactory.

['Phone Lin', 'Shan-Hung Wu', 'Chung-Min Chen', 'Ching-Feng Liang']

Implementation and performance evaluation for a ubiquitous and unified multimedia messaging platform

We examine the use of a paper-based checklist during 48 simulated trauma resuscitations to inform the design of digital cognitive aids for safety-critical medical teamwork. Our analysis focused on team communication and interaction behaviors as physician leaders led resuscitations and administered the checklist. We found that the checklist increased the amount of communication between the leader and the team, but did not compromise the leader's interactions with the environment. In addition, we observed several changes in team dynamics: the checklist facilitated collaborative decision making and process reflections, but it also made some team members reactive rather than proactive. As the push toward digitizing medical work continues, we expect that paper checklists will soon be replaced by their digital counterparts. Designing interactive cognitive aids for medical domains, however, poses many challenges. Our results offer directions for how these tools could be designed to support medical work in increasingly digital environments.

['Zhan Zhang', 'Aleksandra Sarcevic', 'Maria Yala', 'Randall S. Burd']

Informing Digital Cognitive Aids Design for Emergency Medical Work by Understanding Paper Checklist Use

We develop a theory of local errors for the explicit and implicit tau-leaping methods for simulating stochastic chemical systems, and we prove that these methods are first-order consistent. Our theory provides local error formulae that could serve as the basis for future stepsize control techniques. We prove that, for the special case of systems with linear propensity functions, both tau-leaping methods are first-order convergent in all moments. We provide a stiff stability analysis of the mean of both leaping methods, and we confirm that the implicit method is unconditionally stable in the mean for stable systems. Finally, we give some theoretical and numerical examples to illustrate these results.

['Muruhan Rathinam', 'Linda R. Petzold', 'Yang Cao', 'Daniel T. Gillespie']

Consistency and Stability of Tau-Leaping Schemes for Chemical Reaction Systems

Location and mapping are fundamental problems for a mobile robot to implement a series of high-level applications. Traditional solutions to Simultaneous Location and Mapping (SLAM) are probabilistic reasoning. This paper proposes an analytic solution to 3D visual SLAM with a Time-of-Flight (TOF) camera. According to the visual registration, 3D visual SLAM problem is decomposed into such steps as environment sensing, data matching, motion estimation, as well as location update and registration of new landmarks. First, TOF range camera enables the robot to capture images of distance and intensity of a scene. Scale-Invariant feature transform (SIFT) algorithms for visual feature extraction is applied to the captured intensity images. These visual features combined with the corresponding distance information give a full measurement of 3D landmarks. Then, the process of data association and match is developed through SIFT and the Iterative Closest Point (ICP) to minimize the relative and global error in SLAM process, while obtaining motion estimation. Finally, based on the visual theory of structure from motion (SFM), an analytic solution to location and mapping is presented to 3D Visual SLAM, instead of conventional probabilistic reasoning. We provide 3D visual SLAM experimental results from simulation and the indoor environment. It turns out that the proposed scheme is feasible.

['Xu HaiXia', 'Zhou Wei', 'Zhu Jiang']

3D visual SLAM with a Time-of-Flight camera

The oracle problem is a crucial part in current research on software testing. In many situations available solutions like partial oracles can be used, however the suitability of a specific oracle depends on the application to be tested. Moreover, the inputs have a considerable impact on the effectiveness of the testing strategy. Therefore selecting an appropriate oracle as well as adequate inputs is essential in order to yield satisfying results.    In the present paper an approach is described that uses Mutation Analysis to assess testing strategies, which implies the determination of suitable inputs and the evaluation of partial oracles. The approach is illustrated using Metamorphic Relations as partial oracles for imaging software.

['René Just', 'Franz Schweiggert']

Evaluating Testing Strategies for Imaging Software by Means of Mutation Analysis

In this paper we study the Forest Wrapping Problem (FWP) which can be stated as follows: given a connected graph G = (V, E), with |V| = n, let ?0 be a partition of G into K (not necessarily connected) components, find a connected partition ?* of G that wraps ?0 and has maximum number of components.The Forest Wrapping problem is NP-complete on grid graphs while is solvable in O(n log n) time on ladder graphs. We provide a two-phase O(n2) time algorithm for solving FWP on outerplanar graphs.

['Isabella Lari', 'Federica Ricca', 'Andrea Scozzari']

The Forest Wrapping Problem on Outerplanar Graphs

Verifying security requirements of the firmware in contemporary system-on-chip (SoC) designs is a critical challenge. There are two main difficulties in addressing this problem. Security properties like confidentiality and integrity cannot be specified with commonly-used property specification schemes like assertion-based verification/linear temporal logic (LTL). Second, firmware interacts closely with other hardware and firmware which may be untrusted/malicious and their behavior has to be correctly modelled for the verification to be sound and complete. In this paper, we propose an approach to verify firmware security properties using symbolic execution. We introduce a property specification language for information flow properties of firmware which intuitively captures the requirements of confidentiality and integrity. We also propose an algorithm based on symbolic execution to verify these properties. Evaluation on a commercial SoC design uncovered a complex security bug missed by simulation-based testing.

['Pramod Subramanyan', 'Sharad Malik', 'Hareesh Khattri', 'Abhranil Maiti', 'Jason Fung']

Verifying information flow properties of firmware using symbolic execution

Construction and number of self-dual skew codes over $\mathbb{F}_{p^2}$

['Delphine Boucher']

Construction and number of self-dual skew codes over $\mathbb{F}_{p^2}$

Computational methods and tools that can efficiently and effectively analyze the temporal changes in dynamic complex relational networks enable us to gain significant insights regarding the entity relations and their evolution. This article introduces a new class of dynamic graph patterns, referred to as coevolving relational motifs (CRMs), which are designed to identify recurring sets of entities whose relations change in a consistent way over time. CRMs can provide evidence to the existence of, possibly unknown, coordination mechanisms by identifying the relational motifs that evolve in a similar and highly conserved fashion. We developed an algorithm to efficiently analyze the frequent relational changes between the entities of the dynamic networks and capture all frequent coevolutions as CRMs. Our algorithm follows a depth-first exploration of the frequent CRM lattice and incorporates canonical labeling for redundancy elimination. Experimental results based on multiple real world dynamic networks show that the method is able to efficiently identify CRMs. In addition, a qualitative analysis of the results shows that the discovered patterns can be used as features to characterize the dynamic network.

['Rezwan Ahmed', 'George Karypis']

Algorithms for Mining the Coevolving Relational Motifs in Dynamic Networks

Auxiliary Training Information Assisted Visual Recognition

['Qilin Zhang', 'Gang Hua', 'Wei Liu', 'Zicheng Liu', 'Zhengyou Zhang']

Auxiliary Training Information Assisted Visual Recognition

This brief considers a class of delayed full-range (FR) cellular neural networks (CNNs) with uncertain interconnections between neurons modeled by means of intervalized matrices. Using mathematical tools from the theory of differential inclusions, a fundamental result on global robust stability of standard (S) CNNs is extended to prove global robust exponential stability for the corresponding class (same interconnection weights and inputs) of FR-CNNs. The result is of theoretical interest since, in general, the equivalence between the dynamical behavior of FR-CNNs and S-CNNs is not guaranteed.

['M. Di Marco', 'M. Grazzini', 'Luca Pancioni']

Global Robust Stability Criteria for Interval Delayed Full-Range Cellular Neural Networks

The key nodes in network play the critical role in system recovery and survival. Many traditional key nodes selection algorithms utilize the characters of the physical topology to find the key nodes. But they can hardly succeed in the mobile ad hoc network due to the mobility nature of the network. In this paper we propose a social-aware Kcore selection algorithm to work in the Pocket Switched Network. The social view of the network suggests the social position of the mobile nodes can help to find the key nodes in the Pocket Switched Network. The S-Kcore selection algorithm is designed to exploit the nodes' social features to improve the performance in data communication. Experiments use the NS2 shows S-Kcore selection algorithm workable in the Pocket Switched Network. Furthermore, with the social behavior information, those key nodes are more suitable to represent and improve the whole network's performance.

['Ming Li', 'Longxiang Gao', 'Wanlei Zhou']

S-Kcore: A Social-aware Kcore Decomposition Algorithm in Pocket Switched Networks

Logical Foundation for Logic Programming Based on First Order Linear Temporal Logic.

['Regimantas Pliuskevicius']

Logical Foundation for Logic Programming Based on First Order Linear Temporal Logic.

Recommendation systems have been widely used by commercial service providers for giving suggestions to users based on their previous behaviors. While a large portion of users faithfully express their opinions, some malicious users add noisy ratings in order to change the overall ratings of a specific group of items. The presence of noise can add bias to recommendations, leading to instabilities in estimation and prediction. Although the robustness of different recommendation systems has been extensively studied, designing a robust recommendation system remains a significant challenge as detecting malicious users is computationally expensive. In this work, we propose Chiron, a fast and robust hybrid recommendation system that is not only faster than most state-of-the-art methods, but is also resistant to manipulation by malicious users.

['Saber Shokat Fadaee', 'Hossein Azari Soufiani', 'Ravi Sundaram']

Chiron: A Robust Recommendation System

Internet of Things (IoT) becomes an inevitable technology for ICT convergence. It gathers information from various objects and provides intelligent services through analyzing the information. To collect surrounding information, IoT employs a sensor network, which is a low-power wireless communication network with numerous sensor nodes. Sensor nodes in conventional sensor networks have short transmission range. However, it is required a sensor network with long transmission range as well as low transmission power consumption for various IoT services. Long transmission range of IoT devices affects transmission environment. Lots of sensor nodes (i.e., IoT devices) in the long range sensor network transmit data to a given gateway node in order to deliver data to a network server. The gateway node can experience serious traffic load to relay the data. It causes to drop transmission efficiency. Therefore, for efficient data transmission, a network architecture and a data transmission method for long range IoT services are necessary. This paper proposes the network and data transmission architecture for the long range sensor networks. The proposed network architecture is based on oneM2M IoT standard. It has Infrastructure Node (IN), Middle Node (MN) and Application Service Node (ASN) as network elements. In the proposed method, IN employs cloned MNs to reduce the traffic load at the MN, which is the gateway. ASN delivers data through MN or cloned MNs to the IN. Through the load balancing by the proposed method at the MN, the efficient data transmission for IoT services in long range sensor networks can be provided. The performance of the proposed method is validated by the computer simulation.

['Dae-Young Kim', 'Minwoo Jung']

Data Transmission and Network Architecture in Long Range Low Power Sensor Networks for IoT

We describe a collaborative project between our research group and a small west-coast business to apply machine learning techniques to a document processing task. This experience suggests two key points: (1) even as machine learning and artificial intelligence matures, there are many business applications that have not yet exploited these techniques; and (2) academically well-established machine learning techniques have much to offer both in terms of flexibility and economic benefit.

['Scott A. Wallace', 'Bhadresh Patel', 'Landon Kryger', 'Susan Seley']

Machine Learning to Improve a Document Pipeline.

A compact wide-frequency-range quadrature sinusoid signal generator tailored to on-chip impedance spectroscopy instrumentation applications is described. Using a new hybrid structure, it provides seven orders of frequency-tuning range (1 mHz to 10 kHz) appropriate for impedance characterization of many sensor materials. The signal generator exhibits very accurate frequency tuning through digital control, and the new structure inherently guarantees good phase and amplitude matching between sine and cosine outputs across the supported frequency range. The circuit has been fabricated in a 0.5-mum CMOS process and occupies 1 mm 2 . It consumes only 60 muA with a 3-V supply. Measurements show that the phase mismatch is less than 0.8 deg and that the amplitude mismatch is less than 3%. The total harmonic distortion is below 0.6% over the seven-order frequency range.

['Chao Yang', 'Andrew J. Mason']

Fully Integrated Seven-Order Frequency-Range Quadrature Sinusoid Signal Generator

A nonlinear supervised learning model, the Specialized Mappings Architecture (SMA), is described and applied to the estimation of human body pose from monocular images. The SMA consists of several specialized forward mapping functions and an inverse mapping function. Each specialized function maps certain domains of the input space (image features) onto the output space (body pose parameters). The key algorithmic problems faced are those of learning the specialized domains and mapping functions in an optimal way, as well as performing inference given inputs and knowledge of the inverse function. Solutions to these problems employ the EM algorithm and alternating choices of conditional independence assumptions. Performance of the approach is evaluated with synthetic and real video sequences of human motion.

['Rómer Rosales', 'Stan Sclaroff']

Learning Body Pose via Specialized Maps

The routing in communication networks is typically a multicriteria decision making (MCDM) problem. However, setting the parameters of most used MCDM methods to fit the preferences of a decision maker is often a difficult task. A Russian doll method able to choose the best multicriteria solution according to a context defined beforehand is proposed. This context is given by a set of nested boxes in the criteria space, the shapes of which can be established from objective facts such as technical standards, technical specifications, etc. This kind of method is well suited for self-adaptive systems because it is designed to be able to give pertinent results without interaction with a decision maker, whatever the Pareto front. The Russian doll multicriteria decision method is used with a reinforcement learning to optimize the routing in a mobile ad-hoc network. The results on a case study show that the routing can be finely controlled because of the possibility to include as much parameters as desired to adjust the search of the best solution on Pareto fronts a priori unknown. These results are clearly better than those obtained with the optimization of a weighted sum or the minimization of a Chebyshev distance to a reference point.

['Alain Petrowski', 'Farouk Aissanou', 'Ilham Benyahia', 'Sebastien Houcke']

Multicriteria reinforcement learning based on a Russian doll method for network routing

A method for retrieval of leaf area index (LAI) using ENVISAT Advanced Synthetic Aperture Radar vertical/horizontal (VV/HH) polarization ratio was derived for boreal forests. Five alternating polarization single-look complex images of the test site were acquired in summer 2003. The swath range from IS1-IS6 was studied. The VV/HH polarization ratio correlated quite well with the ground truth LAI values. The mean error of the LAI estimates was 0.27 for the test site with mixed forest when data from all images and stands were used without separating between species (or swaths). The respective mean LAI estimation error was 0.3 for Norway spruce (Picea abies (L.) Karst.) and 0.07 for Scots pine (Pinus sylvestris L.) dominated stands.

['Terhikki Manninen', 'Pauline Stenberg', 'Miina Rautiainen', 'Pekka Voipio', 'Heikki Smolander']

Leaf area index estimation of boreal forest using ENVISAT ASAR

A conceptual model for complaint management systems is introduced in this paper. Complaint management systems comprise proactive and interactive parts. In this paper, the primary model and its elements were developed through literature review. Afterwards, based on the model, the performance of the tax affairs organisation with regards to voice of customer was surveyed and analysed. Evidences gathered from case study, at this stage, helped modifications in the primary model. Academics as well as tax affairs experts were then interviewed to evaluate the model. Existing models of customer complain management systems only focus on dealing with complaints. However, this paper takes a more comprehensive approach to design a model which deals with causes of complaints and also attenuating the potential for complaints. Proactive-interactive complaint management model is capable to deal with causes of complaint - prevention - even before a complaint is made. This will help organisations reduce costs of losing customer and of course higher profitability.

['Atefeh Atlikhan', 'Amir Albadvi', 'Amir Hossein Ghapanchi']

A conceptual model for proactive-interactive customer complaint management systems

Process and workflow technology have traditionally not allowed for the specification of, nor run-time enforcement of, real-time requirements, despite the fact that time-to-market and other real-time constraints are more stringent than ever. Without specification of timing constraints, process designers cannot effectively reason about real-time constraints on process programs and the efficacy of their process programs in satisfying those constraints. Furthermore, without executable semantics for those timing specifications, such reasoning might not be applicable to the process as actually executed. We seek to support reasoning about the real-time requirements of software processes. In this paper, we describe work in which we have added real-time specifications to a process programming language, and in which we have added deadline timers and task scheduling to enforce the real-time requirements of processes.

['Aaron G. Cass', 'Leon J. Osterweil']

Applying Real-Time Scheduling Techniques to Software Processes: A Position Paper

Parameterized Matching: Solutions and Extensions.

['Juan Mendivelso', 'Yoan J. Pinzon']

Parameterized Matching: Solutions and Extensions.

Providing QoS guarantees to the applications in a multi-institutional Grid is a challenging task. Although advance reservations (ARs) can provide QoS guarantees for the applications, they often seriously degrade system performance for resource owners. In this paper, we present a framework for AR based resource sharing that not only provides QoS guarantees for the applications but also ensures high utilization of the resources. This paper focuses on the application-to-resource mapping component of the framework as our results show that traditional mapping algorithms used with best effort jobs do not perform well for ARs. The paper proposes a set of algorithms for mapping ARs and investigates their performance in detail. The paper then presents a novel algorithm that outperforms a number of other algorithms in almost every respect for a wide range of workload parameters. Rigorous experimentation proves the efficacy of our algorithm and brings important insights into the dynamics of the system.

['Umar Farooq', 'Shikharesh Majumdar', 'Eric W. Parsons']

A Framework to Achieve Guaranteed QoS for Applications and High System Performance in Multi-Institutional Grid Computing

The definition of the rough integral Pawlak proposed is improved. New notions are proposed, which are respectively the rough integral on a constant interval and the roughly integral upper limit function, and so on. By comparing with the definite integral of real functions, the properties of rough integrals are analyzed. Giving the concept of mean value of discrete functions, the mean value method for rough integration is derived. At the same time, the intermediate value theorem of rough integration is proposed and its geometric significance is analyzed, which provides a dependable theoretical tool for rough integral operation, etc.. Conclusions including the existence theorem of rough primitives and the fundamental formula of rough calculus are proposed. By the representative of discrete functions, the method of computing a primitive is given, by which basic formulas for rough integration in common use are derived, and the method of rough direct integration is obtained. There is also the method of rough integration by parts for rough integrals which is like that of definite integrals. Thus the recurrence formula for rough integration is deduced, in which the integrand of the rough integral is in the shape of the product of a rough power function and a rough exponential function. It is pointed out that integration by substitution is not applicable for rough integral operation.

['Yun Wang', 'Jinmei Wang', 'Yanyong Guan']

The Theory and Application of Rough Integration in Rough Function Model

A pure vulnerability market is one in which each discrete vulnerability is a unit of trade with a price assigned to it by the buyer, seller, and demand. In such a market, exclusivity of knowledge is a key factor in overall value, thus when a vulnerability becomes public knowledge, it loses its value. Other factors also come into play, such as the affected product's popularity, the vulnerability's security impact, and the exploit's ease and efficacy. Vulnerabilities in this market retain their peak value when very few people know about them; value decreases through events such as vendor notification, information leaks, independent rediscovery, or accidental discovery of the vulnerability due to attack activity in the wild. Because it's difficult to certify and appraise information exclusivity, many buyers contractually obligate vulnerability reporters to exclusivity agreements to ensure that their information is exclusive to the best of their knowledge. Very few buyers are interested in nonexclusive information.

['David McKinney']

Vulnerability Bazaar