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An Environment to Foster Scientific Collaborations

['Tatiana P. V. Alves', 'Marcos R. S. Borges', 'Adriana Santarosa Vivacqua']

An Environment to Foster Scientific Collaborations

Corrigendum to ‘‘Solving mixed model sequencing problem in assembly lines with serial workstations with work overload minimisation and interruption rules’’ [Eur. J. Oper. Res. 210 (2011) 495–513]

['Joaquín Bautista', 'Alberto Cano']

Corrigendum to ‘‘Solving mixed model sequencing problem in assembly lines with serial workstations with work overload minimisation and interruption rules’’ [Eur. J. Oper. Res. 210 (2011) 495–513]

We discuss a novel sampling theorem on the sphere developed by McEwen & Wiaux recently through an association between the sphere and the torus. To represent a band-limited signal exactly, this new sampling theorem requires less than half the number of samples of other equiangular sampling theorems on the sphere, such as the canonical Driscoll & Healy sampling theorem. A reduction in the number of samples required to represent a band-limited signal on the sphere has important implications for compressive sensing, both in terms of the dimensionality and sparsity of signals. We illustrate the impact of this property with an inpainting problem on the sphere, where we show superior reconstruction performance when adopting the new sampling theorem.

['Jason D. McEwen', 'Gilles Puy', 'Jean-Philippe Thiran', 'Pierre Vandergheynst', 'Dimitri Van De Ville', 'Yves Wiaux']

Sampling theorems and compressive sensing on the sphere

In view of the necessity of activity analysis on Gbps-scale 3D Tele-Immersive (3DTI) content bundle and petabyte-scale 3DTI recordings, this work proposes and verifies the feasibility of replacing high-latency intrusive analysis with light-weighted metadata-based analysis. For real-time in-session use case, result shows that metadata-based analysis module, when personalized with user's body index, can achieve accuracies in 90 percentile on classifying various activity classes. For offline cross-session use case, we propose a hybrid analysis scheme which combines the advantages of intrusive analysis (i.e., conventional activity analysis on content level) and metadata-based analysis and achieves high accuracy with low computation latency.

['Shannon Chen', 'Aahdar Jain', 'Zhenhuan Gao', 'Klara Nahrstedt', 'Ahsan Arefin', 'Raoul Rivas']

Metadata-Based Activity Analysis in 3D Tele-Immersion

The adaptation module is a Radial Basis Function Neural Network (RBF-NN) that can be connected to the output of any recognition system and its aim is to examine the output of the writer-independent system and produce a more correct output vector close to the desired response. The proposed adaptation module is built using an incremental training named GA-AM algorithm (Growing-Adjustment Adaptation Module). Two adaptation strategies are applied : Growing and Adjustment. The growing criteria are based on the estimation of the significance of the new input and the significance of the nearest unit compared to the input. The adjustment consists of the update of two specific units (nearest and desired contributor) parameters using the standard LMS gradient descent to decrease the error at each time no new unit is allocated. This new training algorithm is evaluated by the adaptation of two handwriting recognition systems. The results, reported according to the cumulative error, show that the GA-AM algorithm leads to decreasing the classification error and to instantly adapting the recognition system to a specific user's handwriting. Performance comparison of GA-AM training algorithm with two other adaptation strategies, based on four writer-dependent datasets, are presented.

['Lobna Haddad', 'Tarek M. Hamdani', 'Adel M. Alimi']

Improved Neural Based Writer Adaptation for On-Line Recognition Systems

Fetal development is noninvasively assessed by measuring the size of different structures in ultrasound (US) images. The reliability of these measurements is dependent upon the identification of the correct anatomical viewing plane, each of which contains different fetal structures. However, the automatic classification of the anatomical planes in fetal US images is challenging due to a number of factors, such as low signal-to-noise-ratios and the small size of the fetus. Current approaches for plane classification are limited to simpler subsets of the problem: only classifying planes within specific body regions or using temporal information from videos. In this paper, we propose a new general method for the classification of anatomical planes in fetal US images. Our method trains two convolutional neural networks to learn the best US and saliency features. The fusion of these features overcomes the challenges associated with US fetal imaging by emphasising the salient features within US images that best discriminate different planes. Our method achieved higher classification accuracy than a state-of-the-art baseline for 12 of the 13 different planes found in a clinical dataset of fetal US images.

['Ashnil Kumar', 'Pradeeba Sridar', 'Ann Quinton', 'R. Krishna Kumar', 'Dagan Feng', 'Ralph Nanan', 'Jinman Kim']

Plane identification in fetal ultrasound images using saliency maps and convolutional neural networks

There is a growing awareness in enterprises about the need for adequate Knowledge Management (KM) in the organisation as a key factor to sustainable competitive success of enterprises. As working patterns are rapidly changing and more flexible organisational structures are emerging, the individual "knowledge workers" have to keep track of information and knowledge in a fast evolving world characterised by information overload. What is required are generic and general purpose approaches that allow users to record a variety of knowledge together with its association to relevant information sources and to share it with colleagues in an intuitive way. An approach to this problem, using conceptual structures combined with the use of ontologies is proposed and discussed and an example of its application to the sharing of research knowledge in a University is presented.

['Andrew Slade', 'Albert Bokma']

Conceptual approaches for personal and corporate information and knowledge management

Spectral Learning for Expressive Interactive Ensemble Music Performance.

['Guangyu Xia', 'Yun Wang', 'Roger B. Dannenberg', 'Geoffrey J. Gordon']

Spectral Learning for Expressive Interactive Ensemble Music Performance.

Mobile web-services often use location information for service customisation. Most such services operate on the user’s physical/geographical location. Unfortunately, such common forms of location carry little context information. In the CoolTown project at HP Labs, we have addressed this deficiency by defined an orthogonal form of location – Semantic location. Use of this form of location can also help lower the risk of invasion of privacy.

['Salil Pradhan']

Semantic Location

This article is motivated by the recent recognition that channel fading for new wireless applications is not always well described by traditional models used for mobile communication systems. In particular, fading data collected for vehicleto- vehicle and wireless sensor network applications has motivated new models for conditions in which channel fading statistics can be worse than Rayleigh. We review the use of statistical channel models, describe our example applications, and provide both measured and modeling results for these severe fading conditions.

['David W. Matolak', 'Jeff Frolik']

Worse-than-Rayleigh fading: Experimental results and theoretical models

An Ambient Intelligent Agent with Awareness of Human Task Execution.

['Fiemke Both', 'Mark Hoogendoorn', 'Andy van der Mee', 'Michael de Vos']

An Ambient Intelligent Agent with Awareness of Human Task Execution.

We will demonstrate the ModelTalker Voice Recorder (MT Voice Recorder) -- an interface system that lets individuals record and bank a speech database for the creation of a synthetic voice. The system guides users through an automatic calibration process that sets pitch, amplitude, and silence. The system then prompts users with both visual (text-based) and auditory prompts. Each recording is screened for pitch, amplitude and pronunciation and users are given immediate feedback on the acceptability of each recording. Users can then rerecord an unacceptable utterance. Recordings are automatically labeled and saved and a speech database is created from these recordings. The system's intention is to make the process of recording a corpus of utterances relatively easy for those inexperienced in linguistic analysis. Ultimately, the recorded corpus and the resulting speech database is used for concatenative synthetic speech, thus allowing individuals at home or in clinics to create a synthetic voice in their own voice. The interface may prove useful for other purposes as well. The system facilitates the recording and labeling of large corpora of speech, making it useful for speech and linguistic research, and it provides immediate feedback on pronunciation, thus making it useful as a clinical learning tool.

['Debra Yarrington', 'John Gray', 'Christopher A. Pennington', 'H. Timothy Bunnell', 'Allegra Cornaglia', 'Jason Lilley', 'Kyoko Nagao', 'James B. Polikoff']

ModelTalker Voice Recorder---An Interface System for Recording a Corpus of Speech for Synthesis

A Chaotic Substitution Based Image Encryption Using APA-transformation

['Musheer Ahmad', 'Akshay Chopra', 'Prakhar Jain', 'Shahzad Alam']

A Chaotic Substitution Based Image Encryption Using APA-transformation

Real-world data are often prepared for purposes other than data mining and machine learning and, therefore, are represented by primitive attributes. When data representation is primitive, preprocessing data before looking for patterns becomes necessary. If lack of domain experts prevents the use of highly informative attributes, patterns are hard to uncover due to complex attribute interactions. This article suggests a new use of MFE3/GA to restructure the primitive data representation by means of capturing and compacting hidden information into new features in order to highlight them to the learner. Empirical results on Poker Hand data set show that the new use successfully improves learning this concept by means of data reduction, generation of a smaller decision tree classifier, and accuracy improvement.

['Leila Shila Shafti', 'Eduardo Pérez']

Data Reduction by Genetic Algorithms and Non-Algebraic Feature Construction: A Case Study

Fast Point Multiplication Formulae on Elliptic Curves of Weierstrass Form.

['Rongquan Feng', 'Zilong Wang', 'Hongfeng Wu']

Fast Point Multiplication Formulae on Elliptic Curves of Weierstrass Form.

In this letter, pioneering experimental results of passive synthetic aperture radar (SAR) imaging are presented. The classical active SAR radar operates in monostatic geometry. The SAR sensor presented in this letter is a passive radar utilizing commercial Digital Video Broadcasting—Terrestrial transmitters as illuminators of opportunity. It works in a bistatic configuration, where the receiver is placed on a moving platform and the transmitter is placed on the ground and is stationary. The imaged scenes are stationary surfaces on Earth such as agriculture or urban areas, buildings, etc. In this letter, pioneering results of signal processing verified by a measurement campaign are presented. In the experiment, two synchronized passive radar receivers were mounted on a small airborne platform. The main goal of the presented experiment was to verify the possibility of ground imaging using passive SAR technology and validate previously presented theoretical results.

['D. Gromek', 'Krzysztof Kulpa', 'Piotr Samczynski']

Experimental Results of Passive SAR Imaging Using DVB-T Illuminators of Opportunity

Note on the path-following approach of equilibrium programming

['A.J.J. Talman', 'G. van der Laan']

Note on the path-following approach of equilibrium programming

In this paper, we study the problem of designing the optimal sensing time and power allocation strategy, in order to maximize the ergodic throughput of a cognitive radio that employs simultaneous multiband spectrum sensing and operates under: (i) the wideband sensing-based spectrum sharing (WSSS) scheme and (ii) the wideband opportunistic spectrum access (WOSA) scheme. In our analysis, we consider both average transmit and interference power constraints for the two schemes, so that to effectively protect the primary users from harmful interference, propose an algorithm that acquires the optimal sensing time and power allocation strategy under imperfect spectrum sensing and discuss the effect of the average transmit and interference power constraints on the optimal sensing time. Finally, simulation results are provided, in order to compare the two schemes and validate our theoretical analysis.

['Stergios Stotas', 'Arumugam Nallanathan']

Sensing Time and Power Allocation Optimization in Wideband Cognitive Radio Networks

Background#R##N#Light/dark cycles are probably the most important environmental signals that regulate plant development. Light is essential for photosynthesis, but an excess, in combination with the unavoidable presence of atmospheric oxygen inside the chloroplast, leads to excessive reactive oxygen species production. Among the defense mechanisms that activate plants to cope with environmental stress situations, it is worth noting the ascorbate-glutathione cycle, a complex metabolic pathway in which a variety of photochemical, chemical and enzymatic steps are involved.

['Edelmira Valero', 'Hermenegilda Macià', 'Ildefonso M. De la Fuente', 'José-Antonio Hernández', 'María-Isabel González-Sánchez', 'Francisco García-Carmona']

Modeling the ascorbate-glutathione cycle in chloroplasts under light/dark conditions.

Losing talented IT employees, the most critical strategic resource in IT, during a major organizational change can be catastrophic to the overall performance of the IS organization. This paper develops a multi-layered communicative-tension model of change-induced collective voluntary turnover from a historical case study analysis. A major organizational change at a healthcare insurance firm’s IT unit reveals the presence of three primary communicative tensions: alignment-autonomy, stability-change and expression-suppression. A group of employees, dissatisfied with the negative communicative practices employed by their managers in the midst of these communicative tensions, left the organization. A communicative-tension model of change-induced collective voluntary turnover complements and extends upon prior collective voluntary turnover research by accounting for the organizational change context and broader relational dynamics. This study offers practitioners important insights on how to manage communicative tensions during an IS organizational change to improve IT talent retention.

['Rennie Naidoo']

A communicative-tension model of change-induced collective voluntary turnover in IT

Publisher Summary This chapter discusses a complete framework for the parallelization of nested loops by applying tiling transformation and automatically generating MPI code that allows for an advanced scheduling scheme. In particular, under advanced scheduling scheme two separate techniques are considered: first, the application of a suitable tiling transformation, and second, the overlapping of computation and communication when executing the parallel program. As far as the choice of a scheduling-efficient tiling transformation is concerned, the data dependencies of the initial algorithm are taken into account and an appropriate transformation matrix is automatically generated according to a well-established theory. On the other hand, overlapping computation with communication partly hides the communication overhead and allows for more efficient processor utilization. The chapter discusses a tool that automatically generates MPI code and supports arbitrary tiling transformations, as well as both communication schemes, e.g., the conventional receive-compute-send scheme and the overlapping one.

['Nikolaos Drosinos', 'Georgios I. Goumas', 'Maria Athanasaki', 'Nectarios Koziris']

Delivering high performance to parallel applications using advanced scheduling

System-Level Considerations on Design of 3D NAND Flash Memories

['Chao Sun', 'Ken Takeuchi']

System-Level Considerations on Design of 3D NAND Flash Memories

As video on demand systems gain popularity, it seems likely that the desire to serve a high number of customers from limited network resources could lead to a degradation of the end- users' perceived quality. Quality-oriented adaptation scheme (QOAS) balances the need for high quality with increased network utilization when streaming multimedia. QOAS requires client-side monitoring of some transmission-related parameters, grading of the end-user's quality and feedback that informs the server about the received quality. In response to this feedback, the server adjusts the streaming process in order to maximize the end-user perceived quality in the current conditions. This paper studies the effect of delivery latency and feedback frequency on quality-oriented adaptive multimedia streaming. It also shows how high end-user perceived quality is maintained in the presence of different types of background traffic while recording a significant increase in link utilization and a very low loss rate.

['Gabriel-Miro Muntean']

Effect of Delivery Latency, Feedback Frequency and Network Load on Adaptive Multimedia Streaming

Program performance may be improved by efficiently programming some key sections of the software. We present a methodology for converting selected portions of source code into automatically scalable multithreaded routines, without forcing programmers to concentrate on parallel programming issues. These developed routines can be reused across various projects, operating systems and system architectures. To support this methodology two separate but tightly coupled tools have been developed -PARSA/sup (TM)/ software development environment (SDE) and the ThreadMan/sup (TM)/ thread manager. The SDE addresses programming issues by allowing a graphical object based approach to develop multithreaded routines that abstracts the users from parallel programming. ThreadMan manages the software developed using SDE. ThreadMan is a user-level thread manager that automatically spawns and schedules threads at runtime. Two examples have been developed using this methodology to demonstrate that there is virtually no degradation in performance when compared to sequential code, in a single processor system and scalability is achieved as the number of processors is increased.

['Vijay Murthi', 'David Levine', 'Behrooz Shirazi', 'Jeff Marquis']

A tool based methodology for development of automatically scalable and reusable parallel code

The key issue in motion estimation and tracking an object over a fieqwnce of images is establishing correspondpncp betwen the features of the object in the different images of t hr sequence. For range image spquences, this problem translates into finding a match between the surface segments in a pair of ranRe images of the scene. This paper considers the problem of establishing rorrespondences hetwn surlaces in a sequence oi range images. N'e prpaent a novel procedure for finding correspondence and show the results an real range image sequences. h graph search procedur~ forms the basis lar the algorithm that computes the rorr~spondcnce bvtwwn surfaces. The solutinn usen grometrical and topological information derived from th~ sr~nes to direct t h~ search procedure. Fundamental ta our strategy to match features over a seqrlence of ranw images is a hypergraph representation of the scenes. Two scenPs arr modcled as hyp~rgraphs and the hyperedges are matched using a suh-graph isomorphism algorithm. The hietarrhicd rrprrsentalion of hypergraphs not only rrdures the search space significantly, brtt also facilitates the encoding of the topological and geometrical information. R~rth~r. we present a sub-hypcrgrap h isomorphism pror~di~rp to ~~tahlish the corr~spond~nces between the surfar~ patchrs and drrnonstrate the al~orit hrn an different typ~s of tral ranp imagt. spquences. We present res~lfts tha~ show that the algorithm is robust and performs well in prPaPncP of occlusions and incorrect segmentations. The key issue in motion stir nation and tracking an object owr a SequPncP of images is establishing correspondcnce between the features of the object in the different ima~es of the sequence. Fn this paper we deal with the tracking of objerts in a sequence of range images to estimate t hc motion of the camera (range smsor) in the environment. Rangc irnap;es sense the surfacr of the objects, so it is natural to use stirface a~grnents as the features of interest: this translates the tracking of objects into finding a matrh h~rw~cn the surface segments in a pair of ranRe images of I hp scenp. This paper considers the finding OF correspondences between aurfac~a in a sequence of range image<. Finding rnrrespondenrp or a matrh bptween features is not isolat~d to ohject tracking, but ia also centrd to other computer vision tasks ~ncEuding navigation. ohjerl recognition, target tracking, and map building, We present a novel procedi~r~ for estabIishing correspondence and slrow tho rcsults on real range image sequences. h graph search procedure forms the hnqis far the alprit hrn that computes t hc correspondence betwwn surfaces. The solution uses geometrical and topolo~ical information derived From the scenes to direct the search procedure. In general, the input to the matching algorithm is the output from a s~grnentation al~orithm that partitions the image into surface srgments. The performance of the matching depends greatly on the results or the segmentation algorithms. Incnrrpct s~grn~ntatinn causes poor estimation of the surface parameters and aff~ctfi the performance of the match in^ algoritlim. We address this iasuc and obtain a ~olotion that is rohusr and able to handle occli~sinns of fiurfaces, noisr in data, and incorrect segmentation from a segment ation alaorit hm. In the present implementation,

['Bikash Sabata', 'J. K. Aggarwal']

CORRESPONDENCE OF SURFACES IN A SEQUENCE OF RANGE IMAGES FOR MOTION ESTIMATION AND TRACKING

With the explosion of high-throughput data, an effective integrative analysis is needed to decipher the knowledge accumulated in multiple studies. However, batch effects, patient heterogeneity, and disease complexity all complicate the integration of data from different sources. Here we introduce TOMAS, a novel meta-analysis framework that transforms the challenging meta-analysis problem into a set of standard analysis problems that can be solved efficiently. This framework utilizes techniques based on both p-values and effect sizes to identify differentially expressed genes and their expression change on a genome-scale. The computed statistics allow for topology-aware pathway analysis of the given phenotypes, where topological information of genes is taken into consideration. We compare TOMAS with four meta-analysis approaches, as well as with three dedicated pathway analysis approaches that employ multiple datasets (MetaPath). The eight approaches have been tested on 609 samples from 9 Alzheimer's studies conducted in independent labs for different sets of patients and tissues. We demonstrate that the topology based meta-analysis framework overcomes noise and bias to identify pathways that are known to be implicated in Alzheimer's disease. While presented here in a genomic data analysis application, the proposed framework is sufficiently general to be applied in other research areas.

['Tin Nguyen', 'Diana Diaz', 'Sorin Draghici']

TOMAS: A novel TOpology-aware Meta-Analysis approach applied to System biology

There is an ongoing debate regarding the role of object orientation in the introductory programming sequence. While the pendulum swings to and fro between the "objects first" and "back to basics" extremes, there is general agreement that object-oriented programming is central to modern software development and therefore integral to a computer science curriculum. Developing effective approaches to teach these principles raises challenges that have been exacerbated by the use of Java or C++ as the first instructional language. In this paper, we recommend Python as an excellent choice for teaching an object-oriented CS1. Although often viewed as a "scripting" language, Python is a fully object-oriented language with a consistent object model and a rich set of built-in classes. Based upon our experiences, we describe aspects of the language that help support a balanced introduction to object orientation in CS1. We also discuss the downstream effects on our students' transition to Java and C++ in subsequent courses.

['Michael H. Goldwasser', 'David Letscher']

Teaching an object-oriented CS1 -: with Python

Extracting Spatial Entities and Relations in Korean Text.

['Bogyum Kim', 'Jae Sung Lee']

Extracting Spatial Entities and Relations in Korean Text.

The authors propose a framework for a broad class of data mining algorithms for understanding existing databases: functional and approximate dependency inference, minimal key inference, example relation generation and normal form tests. We point out that the common data centric step of these algorithms is the discovery of agree sets. A set-oriented approach for discovering agree sets from database relations based on SQL queries is proposed. Experiments have been performed in order to compare the proposed approach with a data mining approach. We also present a novel way to extract approximate functional dependencies having minimal errors from agree sets.

['Stéphane Lopes', 'Jean-Marc Petit', 'Lotfi Lakhal']

A framework for understanding existing databases

A theory of security that is based on specification languages for communicating processes and the formal testing semantics for such languages is developed. The DeNicola-Hennessy theory of testing semantics for processes as presented by M. Hennessy (Algebraic Theory of Processes, MIT Press, Cambridge, MA, 1988) is reviewed in some detail. The theory is then applied to the analysis of certain information flows. >

['Dale M. Johnson', 'F.J. Thayer']

Security properties consistent with the testing semantics for communicating processes

Errors, inconsistences, incompletenesses and ambiguities in the requirements specification are major reasons for the failure of IT projects. Since the new major version 2 of the UML, the suitability of activity diagrams for modeling requirements has increased significantly. UML 2 activity diagrams are based upon a completely reengineered metamodel including many new features and an improved semantic precision. We provide a formal syntax and operational semantics for activity diagrams to allow for fully executable models. Inspired by the scenario-based language of live sequence charts, some extensions for activity diagrams are proposed including a distinction between possible and mandatory behavior. The proposed semantics paves the way for formal reasoning and tool development that allows for early prototyping and validation by simulation.

['Christoph Knieke', 'Michaela Huhn', 'Malte Lochau']

Executable Requirements Specification: Formal Semantics of Live Activity Diagrams

Although electrical muscle stimulation (EMS) has been used in various haptic interfaces, haptic sense induced by EMS does not satisfactorily provide the full spectrum of haptic events. It is difficult to convey certain haptic sensations accurately through EMS. In this study, we aim to create the haptic sensation of the stiffness of an object by using muscle contraction induced by EMS. To simulate varying degrees of stiffness or elasticity of different objects, we must vary the displayed force depending on the displacement. To generate a haptic sensation corresponding to the force applied on the hand, we measure the generated force at the hand when electric stimulation is applied to a particular muscle. Once we have a model of the relationship between the applied electric stimulation and the generated force, we can determine the intensity of the electric stimulation required to simulate the target stiffness. In this study, we develop a haptic force display system that renders different levels of stiffness using EMS. We analyze the performance of our system by measuring the perceived stiffness in human experiments. The experimental results show a positive correlation between the target stiffness and perceived stiffness.

['Yuichi Kurita', 'Takaaki Ishikawa', 'Toshio Tsuji']

Stiffness Display by Muscle Contraction Via Electric Muscle Stimulation

Medical illustrations are in essence drawings/paintings of measured accuracy, depicting subtleties without ambiguities. Though often highly representational ("realistic-looking"), the main purpose of such illustrations is to communicate information and not necessarily to look real. In medical subjects, there are four instances where good illustration is the best (and possibly the only) medium to use; this is the case where: (1) Areas of reference exist physiologically but not gross anatomically; (2) Superimposing one structure upon another gives related information; (3) Section views show instruments in place in body cavities, etc; (4) Eliminating much visual garbage from a photo can produce a simpler explanation. In this lecture I will describe current traditional and digital illustration techniques that medical illustrator uses almost everyday to create the feel of traditional imagery in the digital age. Follow a step by step presentation that starts as traditional line art sketch and is then brought to life with color and style on the computer screen using glazes, airbrush, "wet" paintbrush, and more. I will also describe how medical illustrators would benefit from using illustrative visualization systems, including research and development requirements and ongoing collaborations between the computer graphics/visualization and medical illustrators communities.

['Bill Andrews']

Introduction to "Perceptual Principles in Medical Illustration" Some Course 6 presentations are available on the introduction citation page

In this letter, we consider D-STTD (Double Space Time Transmit Diversity) with an adaptive modulation (AM) scheme. The simple criteria for AM are proposed according to linear receivers and the corresponding AM schemes are derived to minimize bit error rate under the constraint of the total data rate and total transmit power. The D-STTD system using the proposed AM scheme requires low computational complexity and small feedback information. The performance of D-STTD system using the proposed scheme is improved by 7 dB or more in signal to noise ratio corresponding to 10/sup -4/ bit error rate.

['Jaesang Ham', 'Seijoon Shim', 'Kyeongyeon Kim', 'Chungyong Lee']

A simplified adaptive modulation scheme for D-STTD systems with linear receivers

This paper studies the intelligent controller design problem based on fuzzy approach for the stabilization of nonlinear ship's lift feedback fin stabilizing systems. The fuzzy controller is designed by using Mamdani and Takagi-Sugeno (T-S) fuzzy control methods. For the T-S fuzzy control approach, the considered nonlinear plant is represented by a T-S fuzzy model. Then, the parallel distributed compensation technique is used to design a model-based fuzzy controller. The main idea of the PDC fuzzy controller is to derive linear controller so as to compensate each fuzzy rule of the T-S fuzzy model. Furthermore, the stability conditions derived in this paper are in term of the linear matrix inequalities which can be solved by convex optimal programming algorithm. Finally, the simulation results of a ship's lift feedback fin stabilizing system are provided to show that the proposed fuzzy controller design methods are effective.

['Wen-Jer Chang', 'Feng-Ling Hsu']

Mamdani and Takagi-Sugeno fuzzy controller design for ship fin stabilizing systems

The IPv4+4 architecture presented provides an evolutionary approach to the extension of IPv4 address space. It builds on the existence of network address translators (NATs) and private address realms. During and after the transition from IPv4 to IPv4+4 there is no need to change routers, only NATs and end-hosts. End-to-end address transparency is regained incrementally as deployment progresses. The transition process is simple and it provides incentives for networks with both private and public addresses to upgrade and increase transparent reachability. Early implementation experiences are also included.

['Zoltán Turányi', 'András Gergely Valkó']

IPv4+4

We study the stability of a vector field associated to a nearly-integrable Hamiltonian dynamical system to which a dissipation is added. Such a system is governed by two parameters, namely the perturbing and dissipative parameters, and it depends on a drift function. Assuming that the frequency of motion satisfies some resonance assumption, we investigate the stability of the dynamics, and precisely the variation of the action variables associated to the conservative model. According to the structure of the vector field, one can find linear and long-term stability times, which are established under smallness conditions of the parameters. We also provide some applications to concrete examples, which exhibit a linear or long-term stability behavior.

['Christoph Lhotka', 'Alessandra Celletti']

Stability of nearly-integrable systems with dissipation

Universally Composable Disk Encryption Schemes.

['Ivan Damgård', 'Kasper Dupont']

Universally Composable Disk Encryption Schemes.

Abstract#R##N##R##N#We construct a recursive ultrapower F/U such that F/U is a tame 1-model in the sense of [6, §3] and FU is existentially incomplete in the models of II2 arithmetic. This enables us to answer in the negative a question about closure with respect to recursive fibers of certain special semirings Γ of isols termed tame models by Barback. Erik Ellentuck had conjuctured that all such semirings enjoy the closure property in question. Our result is that while many do, some do not.

['Thomas G. McLaughlin']

Existentially Incomplete Tame Models and a Conjecture of Ellentuck

MiddLog is an extensible and configurable logging framework based on middleware technologies that exposes its services as web services, allowing its users to send log information as SOAP messages. It includes a set of components that are deployed on an application server, performing analysis and recordings of application events at a log file, in a dynamic and transparent way. MiddLog extension capability enables developers to augment its services by aggregating new features or creating new components and inserting them into its infrastructure.

['Marcelo Pitanga Alves', 'Paulo F. Pires', 'Flávia Coimbra Delicato', 'Maria Luiza Machado Campos']

MiddLog: a web service approach for application logging

Cloud computing, a paradigm shift that offer computing resources in a pay-as-you-go manner, is expected to minimize service operators' cost without sacrificing the performance of services. However, it is much harder to guarantee the performance of cloud applications due to the complex architecture of cloud, the interaction between co-deployed applications and the unpredictability of workload. Some research work has reported that existed cloud is not performing as satisfactorily as expected. How to guarantee the stable performance of cloud applications turns into a major concern of both the cloud providers and the service providers. In this paper, we present an approach to guarantee the performance of cloud applications based on a performance model. Extracted from actual runtime monitoring data using data mining techniques, the model can be leveraged to direct how to adjust the resource provision strategy under a given performance requirement. A monitoring framework is implemented for collecting runtime monitoring data on a real cloud which provides PaaS service.

['Jin Shao', 'Qianxiang Wang']

A Performance Guarantee Approach for Cloud Applications Based on Monitoring

We propose a novel method for single-channel microphone localization inside a known room. Unlike other approaches, we take advantage of the room reverberation, which enables us to use only a single fixed loudspeaker to localize the microphone. Our method uses an echo labeling approach that associates the echoes to the correct walls. Echo labeling leverages the properties of the Euclidean distance matrices formed from the distances between the virtual sources and the microphone. Experiments performed in a real lecture room verify the effectiveness of the proposed localization algorithm.

['Reza Parhizkar', 'Ivan Dokmanic', 'Martin Vetterli']

SINGLE-CHANNEL INDOOR MICROPHONE LOCALIZATION

This special focus issue on research data networks starts with a collection of articles describing a large initiative in the US that will use electronic health record data for patient-centered outcomes research in a privacy-preserving manner. This type of research will include observational and interventional studies. PCORnet, funded by the Patient-Centered Outcomes Research Institute (PCORI), leverages investments of several agencies such as the NIH, AHRQ, and FDA, as well as institutional support from healthcare systems to build a ‘network-of-networks' aimed at helping researchers answer questions that matter most to patients and their caregivers.#N##N#An editorial by leaders of the NIH ( See page 576 ) embodies the excitement that has permeated the biomedical science, health services research, and informatics communities around the big challenge of connecting highly diverse systems into a national network. Taken together, the 11 clinical data research networks (CDRNs) and the 18 patient-powered research …

['Lucila Ohno-Machado']

Networking the country to promote health and scientific discovery

As the industry moves to personalization and mobility, users expect their applications to be location savvy, and relevant to their lives in increasing detail. While we can pinpoint a user at a location within 700 meters with just their IP address, and within a meter with their GPS-enabled mobile phone, we fall short when it comes to understanding their geographic context. A person's geographic context includes their current and previous location, the things that surround them, their activity in a given place, as well as their thoughts and feelings in that place. Understanding this context allows us to personalize their experience and refine their interactions with an application, on a hyper-local level.

['Vanessa Murdock', 'Gary Gale']

Computational geography

Pattern matching is an important operation in various applications such as computer and network security, bioinformatics, image processing, among many others. Aho-Corasick (AC) algorithm is a multiple patterns matching algorithm commonly used for such applications. In order to meet the highly demanding performance requirements imposed on these applications, achieving high performance for AC algorithm is crucial. In this paper, we present a high performance parallel implementation of AC algorithm on a Graphic Processing Unit (GPU) which efficiently utilizes the high degree of on-chip parallelism and the memory hierarchy of the GPU so that the aggregate performance (or throughput) of the GPU can be maximized. For this purpose our approach carefully places and caches the input text data and the reference pattern data used for pattern matching in the on-chip shared memories and the texture caches of the GPU. Furthermore, it efficiently schedules the off-chip global memory loads and the shared memory stores in order to minimize the overheads in loading the input data to the shared memories and also to minimize the shared memory bank conflicts. The proposed approach leads to a significant cut-down of the effective memory access latencies and leads to impressive performance improvements. Experimental results on Nvidia GeForce GTX 285 GPU show that our approach delivers up to 127Gbps throughput performance and up to 222-times speedup compared with a serial version running on 2.2Ghz Core2Duo Intel processor.

['Nhat-Phuong Tran', 'Myungho Lee', 'Sugwon Hong', 'Jaeyoung Choi']

High Throughput Parallel Implementation of Aho-Corasick Algorithm on a GPU

Process variation may lead to chip fail because of the property variation of its data path and clock network. We consider the problem of finding an optimal clock schedule, which has not only the minimal clock period but also the maximal tolerant to process variation. Clock skew scheduling is modelled as a constraint difference system, which can be solved by graph theory. The basic traditional algorithm has the vulnerability that the skew value is near to the skew constraint boundary. The parametric shortest path algorithm inserts unified margin value in the skew constraint with loss of circuit performance. We present a novel approach that can maximize the safe margin during clock skew scheduling, which is evaluated by center error square index. Experimental results show that our incremental slack distribution algorithm has the optimal clock skew scheduling result with more safe margin and has more robust tolerant to process variation.

['Xinjie Wei', 'Yici Cai', 'Xianlong Hong']

Clock Skew Scheduling Under Process Variations

Mental, mathematical, and moral facts are difficult to accommodate within an overall worldview due to the peculiar kinds of properties inherent to them. In this paper I argue that a significant class of social entities also presents us with an ontological puzzle that has thus far not been addressed satisfactorily. This puzzle relates to the location of certain social entities. Where, for instance, are organizations located? Where their members are, or where their designated offices are? Organizations depend on their members for their existence, but the members of an organization can be where the organization is not. The designated office of an organization, however, need be little more than a mailbox. I argue that the problem can be solved by conceptualizing the relation between social entities and non-social entities as one of constitution, a relation of unity without identity. Constituted objects have properties that cannot be reduced to properties of the constituting objects. Thus, my attempt to solve the Location Problem results in an argument in favor of a kind of non-reductive materialism about the social.

['Frank Hindriks']

The location problem in social ontology

In this paper, we focus on a new type of emerging learning games: Social Learning Games (SLG). We define SLG as games that enhance learning by offering educational contents according to a learning scenario and by supporting a community that offers condition for social learning. Leaning upon this analysis, we propose a model of SLG, which relies on five components: decision-making, contextual discussions, social capital, educational feedback and dashboard. We highlight the learning possibilities offered by this design approach, such as stimulating learners throughout decision-making process and cultivating learners' engagement in the game. This theoretical contribution has been integrated into a Social Learning Game called CIBUS dedicated to the field of entrepreneurship. We present the specific structure of the learning scenario that allows the regulation of the progress of the learners in the game, by giving freedom in the participation in the community. Finally, we explain how the design approaches we propose allow supporting three levels of learning involved in the game: individual, within the group, and within the community.

['Elise Lavoué']

Towards social learning games

In this paper a novel approach to assessing the threat of network intrusions is proposed. Unlike the present approaches which assess the attack threat either from a backward perspective (how probable a security state can be reached) or from the perspective of the attacks themselves (how much an attack would cause damage to the network), this approach assesses the attack threat from a forwarding perspective (how probable it would be the precursor of future attacks). First, to every attack type and some attack scenarios, their probabilities of having following attacks(PFAs) are calculated by a data mining algorithm. Then the threats of real time intrusions are assessed by these probabilities. The result of the threat assessment can help identify the intrusion alerts which would be the best evidence for the coming attacks from tremendous amount of intrusion alerts, thus this approach can be used for intrusion prediction. The approach is validated by DARPA 2000 and DARPA 1999 intrusion detection evaluation datasets.

['Zhitang Li', 'Jie Lei', 'Li Wang', 'Dong Li']

Assessing Attack Threat by the Probability of Following Attacks

Mind wandering (MW) is a ubiquitous phenomenon that has a negative influence on performance and productivity in many contexts. We propose that intelligent interfaces should have some mechanism to detect and respond to MW in real-time. Towards this end, we developed an interface that automatically detects MW from eye-gaze during computerized reading. When MW is detected, the interface intervenes by asking just-in-time questions and encouraging re-reading as needed. After multiple rounds of iterative refinement, we summatively compared the interface to a yoked control condition in a randomized control trial with 104 participants. Preliminary results suggest that the system was successful in correcting comprehension deficits attributed to MW, thereby highlighting the potential for intelligent interfaces that improve performance by "attending to attention."

["Sidney K. D'Mello", 'Kristopher Kopp', 'Robert Bixler', 'Nigel Bosch']

Attending to Attention: Detecting and Combating Mind Wandering during Computerized Reading

Transparent (Holographic) Proofs

['László Babai']

Transparent (Holographic) Proofs

High spectral efficiency modulation is key to addressing the optical network capacity challenge. Typical implementations of transmitters for advanced modulation formats use high-resolution silicon digital-to-analog converters, complemented by high bandwidth linear amplifiers to drive the electro-optic modulator. To overcome the limitations of this setup, both in speed and complexity, Bell Labs has proposed and realized an alternative approach based on a multi-level driver which operates at symbol rates up to 50 GBaud with swings up to 2×2 volts, sufficient to drive various common electro-optic modulators (Vπ ∼3–4 V). Over the past two years, multi-level drivers have enabled various Bell Labs optical system experiments relying on the high signal quality achieved and the rate flexibility offered. The circuit architecture, its main features, and the various system experiments are summarized.

['J. Godin', 'Agnieszka Konzykowska', 'Jean-Yves Dupuy', 'M. Riet', 'Virginie Nodjiadjim', 'Filipe Jorge', 'Gabriel Charlet', 'Oriol Bertran-Pardo', 'Jeremie Renaudier', 'Haik Mardoyan', 'A.H. Gnauck', 'Peter J. Winzer']

High speed multi-level drivers for spectrally efficient optical transmission systems

In this paper, roadway departure risk while cornering is assessed using probabilistic methods. Sensitivity analysis conducted through Sobol' indices lead to the selection of the parameters that are modeled by random variables. Then structural reliability methods are applied to compute a risk indicator. Importance measure of several parameters are studied to define the quantities that must be statistically determined for an accurate risk assessment at the entrance of the curve. This study is a part of the french national road safety project SARI, and involves several partners for the implementation of a roadway departure warning system.

['Guillaume Rey', 'David Clair', 'Michel Fogli', 'Frédéric Bernardin']

Towards a probabilistic alert procedure of roadway departure

Documents our efforts to develop a scalable low-cost and high-performance network infrastructure for a novel distributed automation system-minifactory. The resulting communication system (AAA-Net) relies on a suite of low-latency protocols carried by a commercial 100 Mb Fast Ethernet network. In addition to documenting the operation of this network system and its associated protocols we offer a brief comparison to the currently available commercial field network systems, and present experimental verification of the performance delivered by AAA-Net under typical and extreme operating conditions.

['Shinji Kume', 'Alfred A. Rizzi']

A high-performance network infrastructure and protocols for distributed automation

The auto/cross correlation of L2 functions are constrained by certain bounds which may often be used to advantage. These bounds apply to all the common cross correlation functions used for registration purposes (called ``deterministic'' correlation functions in this paper, as opposed to stochastic correlation based on non-L2 functions). It is shown that the envelopes of deterministic autocorrelations have essentially a cosine-like behavior but with jump discontinuities at points where the normalized relative displacement is the reciprocal of an integer. Several inequalities extending these results are given. It is shown how these can be applied toward obtaining improved registration algorithms.

['V. N. Dvornychenko']

Bounds on (Deterministic) Correlation Functions with Application to Registration

These large-volume mesh models face challenge in rendering, storing, and transmission for the further geometrical reconstruction. This paper presents a feature extraction based mesh simplification method to get a topology preserved simple mesh model. Sequence of mesh simplification is controlled on the basis of geometrical feature sensitivity, which results in coarse mesh in the flat region and fine mesh around the areas of crease and corner. This algorithm helps to decrease the size of the simplified file by largely simplifying flat area and helps to preserve the geometric feature at large-scale simplification.

['Lirong Wang', 'Jinzhu Li', 'Ichiro Hagiwara']

A Topology Preserved Mesh Simplification Algorithm

We present an original information theoretic measure of heart motion based on the Shannon's differential entropy (SDE), which allows heart wall motion abnormality detection. Based on functional images, which are subject to noise and segmentation inaccuracies, heart wall motion analysis is acknowledged as a difficult problem, and as such, incorporation of prior knowledge is crucial for improving accuracy. Given incomplete, noisy data and a dynamic model, the Kalman filter, a well-known recursive Bayesian filter, is devised in this study to the estimation of the left ventricular (LV) cavity points. However, due to similarity between the statistical information of normal and abnormal heart motions, detecting and classifying abnormality is a challenging problem, which we investigate with a global measure based on the SDE. We further derive two other possible information theoretic abnormality detection criteria, one is based on Renyi entropy and the other on Fisher information. The proposed methods analyze wall motion quantitatively by constructing distributions of the normalized radial distance estimates of the LV cavity. Using 269 × 20 segmented LV cavities of short-axis MRI obtained from 30 subjects, the experimental analysis demonstrates that the proposed SDE criterion can lead to a significant improvement over other features that are prevalent in the literature related to the LV cavity, namely, mean radial displacement and mean radial velocity.

['Kumaradevan Punithakumar', 'Ismail Ben Ayed', 'Ian G. Ross', 'Ali Islam', 'Jaron Chong', 'Shuo Li']

Detection of Left Ventricular Motion Abnormality Via Information Measures and Bayesian Filtering

Stream Cipher Operation Modes with Improved Security against Generic Collision Attacks.

['Matthias Hamann', 'Matthias Krause']

Stream Cipher Operation Modes with Improved Security against Generic Collision Attacks.

We present a new approach for the development of hypertext information systems that avoids a number of traditional hypermedia authoring problems, and facilitates the maintenance of links and the reuse of information resources. The model is set-based, and integrates features from object-oriented software design models. This helps authors to make a comprehensive (and comprehensible) design before starting an implementation. We also briefly describe an authoring system that implements this model, and which uses an existing relational database system to store documents, links and meta-information.

['Koen Hendrikx', 'Hendrik Olivié', 'Erik Duval']

Object-oriented hypertext design: authoring for reuse

In this paper, we explore the possibility to use 2D pattern spectra as suitable feature vectors in galaxy classification tasks. The focus is on separating mergers from projected galaxies in a data set extracted from the Sloan Digital Sky Survey Data Release 7. Local pattern spectra are built in parallel and are based on an object segmentation obtained by filtering a max-tree structure that preserves faint structures. A set of pattern spectra using size and Hu's and Flusser's image invariant moments information is computed for every segmented galaxy. The C4.5 tree classifier with bagging gives the best classification result. Mergers and projected galaxies are classified with a precision of about 80%.

['Ugo Moschini', 'Paul Teeninga', 'Scott Trager', 'Michael Wilkinson']

Parallel 2D Local Pattern Spectra of Invariant Moments for Galaxy Classification

Based on the Moment Generating Function (MGF), we derive closed form expressions for the Average Symbol Error Probability (ASEP) and the outage probability of the adaptive Decode and Forward (DF) relaying over independent and identical (i.i.d) Generalized-K channels for BPSK modulated signals. This kind of channel model includes jointly multipath fading and shadowing. It is very versatile and accurately approximates many of the commonly used channel models as Nakagami-m, Log-Normal distributions. Simulation results are discussed and proved to be in good agreement with our theoretical analysis.

['Ali Dziri', 'Didier Le Ruyet', 'Daniel Roviras', 'Michel Terre']

Closed form of performance analysis of decode and forward relaying over the Generalized-K channels

In this paper, we present an approach to attackon the Xen hypervisor utilizing return-oriented programming(ROP). It modifies the data in the hypervisor that controlswhether a VM is privileged or not and thus can escalatethe privilege of an unprivileged domain (domU) at runtime. As ROP technique makes use of existed code to implementattack, not modifying or injecting any code, it canbypass the integrity protections that base on code measurement. By constructing such kind of attack at the virtualizationlayer, it can motivate further research work towardspreventing or detecting ROP attack on the hypervisor.

['Baozeng Ding', 'Yanjun Wu', 'Yeping He', 'Shuo Tian', 'Bei Guan', 'Guowei Wu']

Return-Oriented Programming Attack on the Xen Hypervisor

The challenges of managing energy efficiency and performance in SoC designs often results in sleepless nights searching for a solution. Today processors have to deliver more computational power, while maintaining flexibility and delivering the lowest power envelope simultaneously. These requirements are fundamentally contradictory in nature. This paradox keeps designers up at night trying to develop the perfect tradeoff between energy efficiency, flexibility and performance. This session will discuss some of the latest and most advanced techniques in power and performance management. Topics will include clocking, controlling idle and active power, optimizing data pipelines, hardware accelerators, advancements in microprocessor architecture and utilizing optimized libraries, mfg process, tools and design flow to ensure optimal power and performance ratios.

['Krisztián Flautner']

Optimize your power and performance yields and regain those sleepless nights

With requirements of spiraling data rates and limited spectrum availability, there is an increased interest in mm-wave beamformer-based communications for 5G. For upcoming cellular networks, the critical point is to exploit the increased number of employable antennas at both Tx and Rx to: 1) combat increased path loss; 2) tackle higher interference due to higher user density; and 3) handle multipath effects in frequency selective channels. Toward this, a multi-beam spatiotemporal superresolution beamforming framework is proposed in this paper as a promising candidate to design beampatterns that mitigate/suppress co-channel interference and deliver massive gain in the desired directions. Initially, channel and signal models suitable for the mm-wave MIMO system are presented using the manifold vectors of both Tx and Rx antenna arrays. Based on these models, a novel subspace-based channel estimator is employed, which estimates delays, directions, velocities, and fading coefficients of the desired signal paths. This information is then exploited by the proposed spatiotemporal beamformer to provide a massive array gain that combats path loss without increasing the number of antenna array elements and to be tolerant to the near-far problem in a high interference environment. The performance of the proposed channel estimator and beamformer is examined using computer simulation studies.

['Vidhya Sridhar', 'Thibaud Gabillard', 'Athanassios Manikas']

Spatiotemporal-MIMO Channel Estimator and Beamformer for 5G

Reaching a power efficiency of 1mW/Gb/s has proven difficult for wireline transceivers operating at tens of gigabits per second. At 40Gb/s, recent receivers consume from 150mW [1] to 1W [2]. This paper describes a receiver that achieves a tenfold reduction in power and an efficiency of 0.35mW/Gb/s.

['Abishek Manian', 'Behzad Razavi']

23.8 A 40Gb/s 14mW CMOS wireline receiver

We have created software that shows a musician accurately, in real time, the pitch of the notes he or she is playing or singing. This is useful as a teaching aid for beginners and also for studying refinements of sound production such as vibrato.

['Philip McLeod', 'Geoff Wyvill']

Visualization of musical pitch

We apply a sequential experiment design procedure to the problem of signal selection for radar target classification. Radar waveforms are designed to discriminate between targets possessing a doubly spread reflectivity function that are observed in clutter. The waveforms minimize decision time by maximizing the discrimination information in the echo signal. Each waveform selected maximizes the Kullback-Leibler (1951) information number that measures the dissimilarity between the observed target and the alternative targets. We discuss in details two scenarios. In the first scenario, the target environment is assumed fixed during illumination. In this case, the optimal waveform selection strategy leads to a fixed library of waveforms. During actual classification, the sequence in which the waveforms are selected from the library is determined from the noise to clutter power in the range-Doppler support of the targets. In the second scenario, the target environment changes between pulse transmissions. In this case, the maximum discrimination information is obtained by a repeated transmission of a single waveform designed from the reflectivity function of the targets. We show that our choice of signals can produce significant gains in detection performance.

['Sameh M. Sowelam', 'Ahmed H. Tewfik']

Waveform selection in radar target classification

We describe a snake-type method for shape registration in 2D and 3D, by fitting a given polygonal template to an acquired image or volume data. The snake aspires to fit itself to the data in a shape which is locally As-Similar-As-Possible (ASAP) to the template. Our ASAP regulating force is based on the Moving Least Squares (MLS) similarity deformation. Combining this force with the traditional internal and external forces associated with a snake leads to a powerful and robust registration algorithm, capable of extracting precise shape information from image data.

['Zohar Levi', 'Craig Gotsman']

D-Snake: Image Registration by As-Similar-As-Possible Template Deformation

Differential evolution (DE) mutates solution vectors by the weighted difference of other vectors using arithmetic operations. As these operations cannot be directly extended to discrete combinatorial space, DE algorithms have been traditionally applied to optimization problems where the search space is continuous. In this paper, we use JADE, a self-adaptive DE algorithm, for winner determination in combinatorial auctions (CAs) where users place bids on combinations of items. To adapt JADE to discrete optimization, we use a rank-based representation schema that produces only feasible solutions and a regeneration operation that constricts the problem search space. It is shown that JADE compares favorably to a local stochastic search algorithm, Casanova, and a genetic algorithm based approach, SGA.

['Jingqiao Zhang', 'Viswanath Avasarala', 'Arthur C. Sanderson', 'Tracy Mullen']

Differential evolution for discrete optimization: An experimental study on Combinatorial Auction problems

The microblogging service Twitter is in the process of being appropriated for conversational interaction and is starting to be used for collaboration, as well. In order to determine how well Twitter supports user-touser exchanges, what people are using Twitter for, and what usage or design modifications would make it (more) usable as a tool for collaboration, this study analyzes a corpus of naturally-occurring public Twitter messages (tweets), focusing on the functions and uses of the @ sign and the coherence of exchanges. The findings reveal a surprising degree of conversationality, facilitated especially by the use of @ as a marker of addressivity, and shed light on the limitations of Twitter’s current design for collaborative use.

['Courtenay Honeycutt', 'Susan C. Herring']

Beyond Microblogging: Conversation and Collaboration via Twitter

Most mobile application displays use LCDs (liquid crystal displays). Such panels have various problems, including decreases in transmission and saturation. We propose an algorithm to solve these problems by using data processing without panel replacement. In general, the subtle problems in color adjustment processing are skin color conversion and color saturation. The human skin tone is a color that is typically remembered; viewers feel awkward when skin tone is converted to an unnatural color. This paper proposes as a solution a skin protection algorithm that detects human skin color tone and prevents skin color from changing. Moreover, the paper introduces an adaptive quadratic curve that reproduces natural appearances more vividly without color saturation. In addition, the system does not use field-to-field processing but pixel-to-pixel processing in real time so that incoming image display color can be controlled without interference from neighboring pixels.

['Jooyoung Ha', 'Sungmok Lee', 'Taeeung Kim', 'Wontae Choi', 'Bongsoon Kang']

A New Approach to Color Adjustment for Mobile Application Displays with a Skin Protection Algorithm on a CIE1931 Diagram

The challenge of modernizing the current force of military combat systems is one of competing priorities. While planning for future capability requirements and modernization efforts, military acquisition program managers must also consider the immediate demands from the field as the United States is engaged on multiple fronts. These competing demands, along with the challenge of managing large groups of complex systems, motivate the need for an expedient and repeatable systems engineering process. The U.S. Army's Program Executive Office for Ground Combat Systems developed such an approach to support analysis of acquisition programs to meet future capability needs. This paper describes the systems engineering approach and illustrates its usefulness.

['Kimberly M. Welch', 'Craig R. Lawton']

Applying system of systems and systems engineering to the military modernization challenge

We consider the problem of refining an abstract task plan into a motion trajectory. Task and motion planning is a hard problem that is essential to long-horizon mobile manipulation. Many approaches divide the problem into two steps: a search for a task plan and task plan refinement to find a feasible trajectory. We apply sequential quadratic programming to jointly optimize over the parameters in a task plan (e.g., trajectories, grasps, put down locations). We provide two modifications that make our formulation more suitable to task and motion planning. We show how to use movement primitives to reuse previous solutions (and so save optimization effort) without trapping the algorithm in a poor basin of attraction. We also derive an early convergence criterion that lets us quickly detect unsatisfiable constraints so we can re-initialize their variables. We present experiments in a navigation amongst movable objects domain and show substantial improvement in cost over a backtracking refinement algorithm.

['Dylan Hadfield-Menell', 'Christopher Lin', 'Rohan Chitnis', 'Stuart J. Russell', 'Pieter Abbeel']

Sequential quadratic programming for task plan optimization

There is significant interest today in integrating additive manufacturing (AM) and topology optimization (TO). However, TO often leads to designs that are not AM friendly. For example, topologically optimized designs may require significant amount of support structures before they can be additively manufactured, resulting in increased fabrication and clean-up costs.#R##N##R##N#In this paper, we propose a TO methodology that will lead to designs requiring significantly reduced support structures. Towards this end, the concept of ‘support structure topological sensitivity’ is introduced. This is combined with performance sensitivity to result in a TO framework that maximizes performance, subject to support structure constraints. The robustness and efficiency of the proposed method is demonstrated through numerical experiments, and validated through fused deposition modeling, a popular AM process.

['Amir M. Mirzendehdel', 'Krishnan Suresh']

Support structure constrained topology optimization for additive manufacturing

In this paper we propose a new method for displaying touch sensation by controlling suction pressure. We discovered a tactile illusion that pulling skin through a hole with suction pressure causes a feeling as if a stick is pushing the skin. This illusion is considered to be caused by the insensitivity of our mechanoreceptors to signs of stress (negative or positive) that are sensitive to the strain energy. Our tactile display is based on the key concept of this illusion and that of "multi-primitive stimulation." We show that a simple structure of a sparse stimulator array produces various tactile sensations from a sharp edge to a smooth plane surface.

['Yasutoshi Makino', 'Naoya Asamura', 'Hiroyuki Shinoda']

Multi primitive tactile display based on suction pressure control

Considers a slotted ring in which simultaneous transmission of messages by different stations is allowed, a property referred to as spatial reuse. Ring networks with spatial reuse can achieve significantly higher throughput than standard token rings but they also introduce the possibility of starvation for some nodes on the ring. To alleviate this problem, various policies have been suggested in the literature. The present objective is to characterize the node throughputs achievable by general transmission policies in ring networks with spatial reuse and then to evaluate the throughput trade-off for a class of policies that has been proposed in the literature in order to avoid starvation. Specifically, the authors study a policy that is based on the idea of allocating transmission quotas to the nodes. Each node is guaranteed transmission of his quota within a specified interval. The authors show that by appropriately allocating the quotas, policies that satisfy general optimality criteria-in particular criteria related to fairness-can be designed. They also study the asymptotic behavior of the quota policy when either the quotas or the number of nodes increase. >

['Leonidas Georgiadis', 'Roch Guérin', 'Israel Cidon']

Throughput properties of fair policies in ring networks

Several gene selection methods have been proposed to identify sets of genes re- lated to a particular disease or to a particular functional status of the tissue. An open problem with gene selection methods consists in evaluating their perfor- mance; since we usually know only a smell subset of the genes involved in the onset of a status, and many times no relevant genes are known "a priori". We propose an artificial system, based on modeling gene expression signatures, to generate synthetic gene expression data for validating gene selection methods. Comparison between gene selection methods using data generated through the artificial model are performed and preliminary results are reported.

['Francesca Ruffino']

GENE EXPRESSION DATA MODELING AND VALIDATION OF GENE SELECTION METHODS

Using a simple finite integral representation for the bivariate Rayleigh (1889) cumulative distribution function previously discovered by the authors, we present expressions for the outage probability and average error probability performances of a dual selective diversity system with correlated slow Rayleigh fading either in closed form (in particular for binary differential phase-shift keying) or in terms of a single integral with finite limits and an integrand composed of elementary (exponential and trigonometric) functions. Because of their simple form, these expressions readily allow numerical evaluation for cases of practical interest. The results are also extended to the case of slow Nakagami-m fading using an alternate representation of the generalized Marcum (1950) Q-function.

['Marvin K. Simon', 'Mohamed-Slim Alouini']

A unified performance analysis of digital communication with dual selective combining diversity over correlated Rayleigh and Nakagami-m fading channels

Issues around climate change are being examined globally across various disciplines and informed decisions at community levels are required within wider national responses. Research addressing decision support for managing the possible impacts on human communities has to date been limited. As climate science knowledge and government policy changes, information must be updated for dissemination to regional implementers. Traditional knowledge repositories for decision support however work on static models, expensive to update in dynamic fields. This paper describes a process for developing a sustainable knowledge repository for decision support that can assist local policy development in climate change applications. An ontology guaranteeing the semantic integrity of the repository is a central feature. Using a semantic wiki approach the semantic integrity of the knowledge base is combined with the update of emergent findings from multiple stakeholders. Both methodological and practical aspects for developing an information framework to support climate change decision makers are addressed.

['Shah Jahan Miah', 'John Grant Gammack']

A Sustainable Knowledge Repository for Decision Support in Climate Change Adaptation

Real-Time 3D Lettering with a 2D Font Engine

['Sebastian Heise', 'Jörn Loviscach']

Real-Time 3D Lettering with a 2D Font Engine

We address instance-based learning from a perceptual organization standpoint and present methods for dimensionality estimation, manifold learning and function approximation. Under our approach, manifolds in high-dimensional spaces are inferred by estimating geometric relationships among the input instances. Unlike conventional manifold learning, we do not perform dimensionality reduction, but instead perform all operations in the original input space. For this purpose we employ a novel formulation of tensor voting, which allows an N-D implementation. Tensor voting is a perceptual organization framework that has mostly been applied to computer vision problems. Analyzing the estimated local structure at the inputs, we are able to obtain reliable dimensionality estimates at each instance, instead of a global estimate for the entire data set. Moreover, these local dimensionality and structure estimates enable us to measure geodesic distances and perform nonlinear interpolation for data sets with varying density, outliers, perturbation and intersections, that cannot be handled by state-of-the-art methods. Quantitative results on the estimation of local manifold structure using ground truth data are presented. In addition, we compare our approach with several leading methods for manifold learning at the task of measuring geodesic distances. Finally, we show competitive function approximation results on real data.

['Philippos Mordohai', 'Gérard G. Medioni']

Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting

In this paper we analyze functional correlation of the attenuation of protection current/potential in cathodic protection (CP) systems over the time. Our aim is to define protection current/potential function in correlation to CP system exploitation time, based on long term measurements of the current/potential. Correlation of the attenuation of the protective current/potential over the time period is established by comparison of the experimental data and data obtained from our analytical model. The analytical model allows prediction of the changes in the changes in the current/potential over the time and thus prediction and verification of the CP. Our data are collected for cathodic protection PCCP (Prestressed Concrete Cylinder Pipe) in desert conditions. Usage of our model for the attenuation of protective current/potential over time of exploitation of a CP system significantly simplifies operational procedures and saves on time, equipment and measurements. Application of proposed mathematical model, make it is possible, without long-lasting measurements, reliably envisage evolution in time of a cathodic protection system.

['Adnan Muharemovic', 'Narcis Behlilovic', 'Irfan Turkovic']

Functional relationship between cathodic protection current/potential and duration of system deployment in desert conditions

Kinship verification is an interesting and challenging problem in human face analysis, which has received increasing interests in computer vision and biometrics in recent years. This paper presents a neighborhood repulsed correlation metric learning (NRCML) method for kinship verification via facial image analysis. Most existing metric learning based kinship verification methods are developed with the Euclidian similarity metric, which is not powerful enough to measure the similarity of face samples, especially when they are captured in wild conditions. Motivated by the fact that the correlation similarity metric can better handle face variations than the Euclidian similarity metric, we propose a NRCML method by using the correlation similarity measure where the kin relation of facial images can be better highlighted. Since negative kinship samples are usually less than positive samples, we automatically identify the most discriminative negative samples in the training set to learn the distance metric so that the most discriminative encoded by negative samples can better exploited. Experimental results show the efficacy of the proposed approach.

['Haibin Yan']

Kinship verification using neighborhood repulsed correlation metric learning

As interest in the concepts and methods of software engineering increases, many companies, particularly in aerospace, find it difficult to acquire software developers with the desired skills. The option of full-time, company-based training is discussed with suggestions for implementation. Lessons learned from the actual implementation of such a program are discussed along with possible directions for future evolution.

['James P. McGill']

The Software Engineering Shortage: A Third Choice

A clutter (V, E) packs if the smallest number of vertices needed to intersect all the edges (i.e. a minimum transversal) is equal to the maximum number of pairwise disjoint edges (i.e. a maximum matching). This terminology is due to Seymour 1977. A clutter is minimally nonpacking if it does not pack but all its minors pack. An m x n 0,1 matrix is minimally nonpacking if it is the edge-vertex incidence matrix of a minimally nonpacking clutter. Minimally nonpacking matrices can be viewed as the counterpart for the set covering problem of minimally imperfect matrices for the set packing problem. This paper proves several properties of minimally nonpacking clutters and matrices.

['Gérard Cornuéjols', 'Bertrand Guenin', 'François Margot']

The Packing Property

The Viterbi algorithm (VA) is the maximum likelihood decoding algorithm for convolutionally encoded data. Improvements in the performance of a concatenated coding system that uses VA decoding (inner decoder) can be obtained when, in addition to the standard VA output, an indicator of the reliability of the VA decision is delivered to the outer stage of processing. Two different approaches of extending the VA are considered. In the first approach, the VA is extended with a soft output (SOVA) unit that calculates reliability values for each of the decoded output information symbols. In the second approach, coding gains are obtained by delivering a list of the L best estimates of the transmitted data sequence, namely the list Viterbi decoding algorithm (LVA). Our main interest is to evaluate the LVA and the SOVA in comparison with each other, determine suitable applications for both algorithms and to construct extended versions of the LVA and the SOVA with low complexity that perform the task of the other algorithm. We define a list output VA using the output symbol reliability information of the SOVA to generate a list of size L and that also has a lower complexity than the regular LVA for a long list size. We evaluate the list-SOVA in comparison to the LVA. Further, we introduce a low complexity soft symbol output viterbi algorithm that accepts the (short) list output of the LVA and calculates for each of the decoded information bits a reliability value. The complexity and the performance of the soft-LVA (LVA and soft decoding unit) is a function of the list size L. The performance of the soft-LVA and the SOVA are compared in a concatenated coding system. A new software implementation of the iterative serial version of the LVA is also included. >

['Christiane Gabriele Nill', 'Carl-Erik Sundberg']

List and soft symbol output Viterbi algorithms: extensions and comparisons

Adaptive Fuzzy Function Approximation for Multi-agent Reinforcement Learning.

['Cheng Wu', 'Waleed Meleis']

Adaptive Fuzzy Function Approximation for Multi-agent Reinforcement Learning.

EWCDM: An Efficient, Beyond-Birthday Secure, Nonce-Misuse Resistant MAC

['Benoît Cogliati', 'Yannick Seurin']

EWCDM: An Efficient, Beyond-Birthday Secure, Nonce-Misuse Resistant MAC

This paper addresses the problem of energy-efficiency (EE) within an underlay cognitive radio (CR) network where primary users (PUs) and secondary users (SUs) utilize two types of multicarrier modulation: orthogonal frequency-division multiplexing (OFDM) and filter bank based multicarrier (FBMC). The problem of non-cooperative SU downlink energy-efficiency is investigated using a game theoretic approach. We reformulate the EE optimization problem as a non-cooperative power allocation game (NPAG). A distributed power control algorithm is proposed to find the optimal power allocation strategy for each secondary base station on each subcarrier. The proposed non-cooperative game is demonstrated to reach a Nash-equilibrium (NE) point. Simulation analyses are then provided in order to validate the efficiency of our proposed distributed algorithm and also to highlight the advantages of using FBMC as a modulation technique if compared to OFDM.

['Juwendo Denis', 'Mylene Pischella', 'Didier Le Ruyet']

Optimal energy-efficient power allocation for asynchronous cognitive radio networks using FBMC/OFDM

We study the problem of computing an exact motion plan for the snakeboard by exploiting its kinematic controllability properties and its decoupling vector fields. Decoupling vector fields allow us to treat the underactuated dynamic system as a kinematic one, and rest-to-rest paths are the concatenation of integral curves of the decoupling vector fields. These paths can then be time-scaled according to actuator limits to yield fast trajectories. Switches between decoupling vector fields must occur at zero velocity, so to find fast trajectories, we wish to find paths minimizing the number of switches. In this paper we solve the minimum switch path planning problem for the snakeboard. We consider two problems: (1) finding motion plans achieving a desired position and orientation of the body of the snakeboard, and (2) the full problem of motion planning for all five configuration variables of the snakeboard. The first problem is solved in closed form by geometric considerations, while the second problem is solved by a numerical approach with guaranteed convergence. We present a complete characterization of the snakeboard's optimal paths in terms of the number of switches.

['Stefano Iannitti', 'Kevin M. Lynch']

Exact minimum control switch motion planning for the snakeboard

Geocoding of traffic-related events from Twitter.

['Juan Camilo Forero Salazar', 'Miguel Torres Ruiz', 'A Clodoveu Davis', 'Marco Moreno-Ibarra']

Geocoding of traffic-related events from Twitter.

Is There HCI in IDTV? - An Exploratory Study on Their Words.

['Samuel B. Buchdid', 'Maria Cecília Calani Baranauskas']

Is There HCI in IDTV? - An Exploratory Study on Their Words.

We study the problem of (off-line) broadcast scheduling in minimizing total flow time and propose a dynamic programming approach to compute an optimal broadcast schedule. Suppose the broadcast server has k pages and the last page request arrives at time n. The optimal schedule can be computed in O(k3(n+k)k−1) time for the case that the server has a single broadcast channel. For m channels case, i.e., the server can broadcast m different pages at a time where m < k, the optimal schedule can be computed in O(nk−m) time when k and m are constants. Note that this broadcast scheduling problem is NP-hard when k is a variable and will take O(nk−m+1) time when k is fixed and m ≥ 1 with the straightforward implementation of the dynamic programming approach.

['Wun-Tat Chan', 'Francis Y. L. Chin', 'Yong Zhang', 'Hong Zhu', 'Hong Shen', 'Prudence W. H. Wong']

A dynamic programming approach of finding an optimal broadcast schedule in minimizing total flow time

Cloud-based Web applications powered by new technologies such as Asynchronous Javascript and XML (Ajax) place a significant burden on network operators and enterprises to effectively manage traffic. Despite increase of their popularity, we have little understanding of characteristics of these cloud applications. Part of the problem is that there exists no systematic way to generate their workloads, observe their network behavior today and keep track of the changing trends of these applications. This paper focuses on addressing these issues by developing a tool, called AJAXTRACKER, that automatically mimics a human interaction with a cloud application and collects associated network traces. These traces can further be post-processed to understand various characteristics of these applications and those characteristics can be fed into a classifier to identify new traffic for a particular application in a passive trace. The tool also can be used by service providers to automatically generate relevant workloads to monitor and test specific applications.

['Myungjin Lee', 'Ramana Rao Kompella', 'Sumeet Singh']

AjaxTracker: active measurement system for high-fidelity characterization of AJAX applications

Induction motors fed through variable speed drives (VSD) are widely used in different industrial processes. Nowadays, the industry demands the integration of smart sensors to improve the fault detection in order to reduce cost, maintenance and power consumption. Induction motors can develop one or more faults at the same time that can be produce severe damages. The combined fault identification in induction motors is a demanding task, but it has been rarely considered in spite of being a common situation, because it is difficult to identify two or more faults simultaneously. This work presents a smart sensor for online detection of simple and multiple-combined faults in induction motors fed through a VSD in a wide frequency range covering low frequencies from 3 Hz and high frequencies up to 60 Hz based on a primary sensor being a commercially available current clamp or a hall-effect sensor. The proposed smart sensor implements a methodology based on the fast Fourier transform (FFT), RMS calculation and artificial neural networks (ANN), which are processed online using digital hardware signal processing based on field programmable gate array (FPGA).

['Armando G. Garcia-Ramirez', 'Roque Alfredo Osornio-Rios', 'David Granados-Lieberman', 'Arturo Garcia-Perez', 'Rene de Jesus Romero-Troncoso']

Smart Sensor for Online Detection of Multiple-Combined Faults in VSD-Fed Induction Motors

There are many advantages to deploying mobile devices in eHealth systems. However; security is still an issue: in particular authentication and user privacy. In this paper we propose a novel architecture that integrates 3GPP UMTS mobile technology with Web services. This will help address authentication and privacy concern within eHealth environment. The architecture makes use of the Generic Authentication Architecture from the 3GPP and the Single Sign-On system to authenticate mobile users to a Health Authentication Server to give access to various eHealth Service Providers. The Platform for Privacy Preferences Project is thus used to manage privacy in the system.

['Kalid Elmufti', 'Dasun Weerasinghe', 'Muttukrishnan Rajarajan', 'Veselin Rakocevic', 'Sanowar H. Khan']

Privacy in Mobile Web Services eHealth

In this paper, we present an efficient and simple solution to the parallelization of discrete integration programs of ordinary differential equations (ODE). The main technique used is known as loop tiling. To avoid the overhead due to code complexity and border effects, we introduce redundant tasks and we use non parallelepiped tiles. Thanks both to cache reuse (×4:3) and coarse granularity (×24:5), the speedup using 25 processors over the non-tiled sequential implementation is larger than 106.We also present the draft of a fuzzy methodology to optimize the tile size and we illustrate it using real measurements for the communication cost and the execution time. In particular, we observe that the model of communication latencies over a Myrinet network is not as simple as is usually reported.

['Fabrice Rastello', 'Thierry Dauxois']

Efficient tiling for an ODE discrete integration program: redundant tasks instead of trapezoidal shaped-tiles

As networks become more and more complicated and applications more and more demanding, a very common network topology for state-of-the-art multimedia applications supporting emerging user - centric frameworks is a heterogeneous wired/wireless architecture. A network architecture solution for indoor/outdoor heterogeneous networking applications, to support both multimedia and sensor applications suitable for such frameworks is proposed in this paper. Furthermore, an integrated DRM system architecture is proposed for the protection of intellectual property, characterized by its interoperability aspect.

['Tasos Fragopoulos', 'Antonis Athanasopoulos', 'Artemios Vogiatzis', 'Evangelos Topalis', 'John V. Gialelis', 'Stavros Koubias']

Security and DRM in indoor/outdoor heterogeneous networking applications for user - centric frameworks

Attention operators based on 2D image cues (such as color, texture) are well known and discussed extensively in the vision literature but are not ideally suited for robotic applications. In such contexts it is the 3D structure of scene elements that makes them interesting or not. We show how a bottom-up exploration mechanism that fuses 2D saliency-based conspicuity with spatial abstraction resulting from the coherent plane estimation and stereo line detection is well suited for typical indoor robotics tasks. This spatial abstraction is performed by a joint probabilistic model which takes the interaction of stereo line detection and 3D supporting plane estimation into consideration. By maximizing the probability of the joint model, our method facilitates reduction of false-positive stereo line detection and refines the estimation of supporting surface simultaneously. Experiments demonstrate that our approach provides more accurate and plausible attention.

['Kai Zhou', 'Andreas Richtsfeld', 'Michael Zillich', 'Markus Vincze']

Coherent spatial abstraction and stereo line detection for robotic visual attention

Experience shows that different text classification methods can give different results. We look here at a way of combining the results of two or more different classification methods using an evidential approach. The specific methods we have been experimenting with in our group include the support vector machine, kNN (nearest neighbors), kNN model-based approach (kNNM), and Rocchio methods, but the analysis and methods apply to any methods. We review these learning methods briefly, and then we describe our method for combining the classifiers. In a previous study, we suggested that the combination could be done using evidential operations and that using only two focal points in the mass functions gives good results. However, there are conditions under which we should choose to use more focal points. We assess some aspects of this choice from an reasoning perspective and suggest a refinement of the approach.

['David A. Bell', 'Jiwen Guan', 'Yaxin Bi']

On combining classifier mass functions for text categorization