title: Counter-forensics in machine learning based forgery detection

text: With the powerful image editing tools available today, it is very easy to create forgeries without leaving visible traces. Boundaries between host image and forgery can be concealed, illumination changed, and so on, in a naive form of counter-forensics. For this reason, most modern techniques for forgery detection rely on the statistical distribution of micro-patterns, enhanced through high-level filtering, and summarized in some image descriptor used for the final classification. In this work we propose a strategy to modify the forged image at the level of micro-patterns to fool a state-of-the-art forgery detector. Then, we investigate on the effectiveness of the proposed strategy as a function of the level of knowledge on the forgery detection algorithm. Experiments show this approach to be quite effective especially if a good prior knowledge on the detector is available.


title: A Multimodal, Full-Surround Vehicular Testbed for Naturalistic Studies and Benchmarking: Design, Calibration and Deployment

text: Recent progress in autonomous and semiautonomous driving has been made possible in part through an assortment of sensors that provide the intelligent agent with an enhanced perception of its surroundings. It has been clear for quite some while now that for intelligent vehicles to function effectively in all situations and conditions, a fusion of different sensor technologies is essential. Consequently, the availability of synchronized multi-sensory data streams are necessary to promote the development of fusion based algorithms for low, mid and high level semantic tasks. In this paper, we provide a comprehensive description of our heavily sensorized, panoramic testbed capable of providing high quality data from a slew of synchronized and calibrated sensors such as cameras, LIDARs, radars, and the IMU/GPS. The vehicle has recorded over 100 hours of real world data for a very diverse set of weather, traffic and daylight conditions. All captured data is accurately calibrated and synchronized using timestamps, and stored safely in high performance servers mounted inside the vehicle itself. Details on the testbed instrumentation, sensor layout, sensor outputs, calibration and synchronization are described in this paper.


title: Prototypical Networks for Few-shot Learning

text: We propose Prototypical Networks for the problem of few-shot classification, where a classifier must generalize to new classes not seen in the training set, given only a small number of examples of each new class. Prototypical Networks learn a metric space in which classification can be performed by computing distances to prototype representations of each class. Compared to recent approaches for few-shot learning, they reflect a simpler inductive bias that is beneficial in this limited-data regime, and achieve excellent results. We provide an analysis showing that some simple design decisions can yield substantial improvements over recent approaches involving complicated architectural choices and meta-learning. We further extend Prototypical Networks to zero-shot learning and achieve state-ofthe-art results on the CU-Birds dataset.


title: Prozessmodellierung in eGovernment-Projekten mit der eEPK

text: Im Rahmen der Informationssystemgestaltung unterscheiden sich die Projektbeteiligten insbesondere hinsichtlich ihrer Anforderungen an die Inhalte und Repräsentationsformen der für die Anwendungssystemund Organisationsgestaltung verwendeten Modellen. Die multiperspektivische Modellierung stellt einen viel versprechenden Ansatz dar, um diesem Umstand durch die Bereitstellung perspektivenspezifischer Sichten auf Informationsmodelle gerecht zu werden. Der Beitrag stellt eine Erweiterung ereignisgesteuerter Prozessketten durch Konfigurationsmechanismen vor, welche die Erstellung und Nutzung von Perspektiven auf Prozessmodelle unterstützt. 1 Perspektiven auf Prozessmodelle Die wissenschaftliche Diskussion über die Qualität von Prozessmodellen wurde in den letzten Jahren wesentlich durch die Entwicklung von allgemeinen Modellierungsempfehlungen, welche auf die syntaktische Korrektheit der Modelle und der Einhaltung der Grundsätze ordnungsmäßiger Modellierung bei der Erstellung von Prozessmodellen abzielen [BRS95; Ro96; BRU00], geprägt. Ein dominierendes Kriterium, das die Qualität von Prozessmodellen determiniert, ist dabei die Entsprechung der Modellkonzeption und -repräsentation mit den Anforderungen der jeweiligen Modellnutzergruppe [RS99, S. 25f.; Be02, S. 28ff.; RSD03, S. 49]. So werden z. B. innerhalb eines prozessbasierten Reorganisationsprojektes diese Modellnutzergruppen durch die verschiedenen organisatorischen Rollen der Projektteilnehmer bestimmt. Ein Sachbearbeiter benötigt hierbei lediglich die für ihn relevanten Prozessmodelle und deren Schnittstellen. Aus der Sicht des Managers der zu reorganisierenden Unternehmung sollten die Modelle in aggregierter Form vorliegen und durch erweiterte visuelle Merkmale, wie z. B. ansprechender Farboder Symboldarstellung, gekennzeichnet sein. Einem Anwendungsentwickler sollten sehr detaillierte Modelle vorgelegt werden, damit sich die aus der Reorganisation ergebenden Konsequenzen im Anwendungssystem berücksichtigt werden können. Die verschiedenen Anforderungen der Nutzergruppen resultieren aus den Differenzen ihrer subjektabhängigen Vorstellungswelten und den daraus resultierenden Problemlösungsansätzen [Be01a; Be02, S. 30ff.]. Ein Ansatz zur expliziten Vermittlung zwischen diesen Vorstellungswelten findet sich in der Bereitstellung von anforderungsgerechten Perspektiven wieder [Fr94, S. 36f.]. Perspektiven werden dadurch determiniert, welcher Modellierungszweck verfolgt wird, welche organisatorische Rolle die Nutzer einnehmen und welche persönlichen Präferenzen bzgl. der Modellkonzeption und -repräsentation bestehen [Be02, S. 38ff., RSD03, S. 49]. Die Entwicklung und Bereitstellung perspektivenspezifischer Modelle wird unter dem Begriff der multiperspektivischen Informationsmodellierung diskutiert [Fi92; RS99, S. 25f.; RSD03, S. 52]. Soll den Anforderungen mehrerer Nutzergruppen entsprochen werden, d. h. sollen mehrere Perspektiven berücksichtigt werden, ergeben sich für den Modellersteller zwei Alternativen. Modelle könnten einerseits für unterschiedliche Perspektiven redundant vorgehalten werden. Nachteile dieser Vorgehensweise sind die üblichen, mit Redundanzen verbundenen Zusatzaufwände wie erhöhter Pflegeaufwand und Gefahr von Inkonsistenzen. Andererseits kann ein Gesamtmodell derartig erstellt werden, dass es die für sämtliche Perspektiven relevanten Elemente redundanzfrei enthält. Den einzelnen Vertretern der Perspektiven werden die für sie relevanten Modelle bereitgestellt, indem ihnen eine View auf das Gesamtmodell zur Verfügung gestellt wird, die das Gesamtmodell um die nicht relevanten Inhalte reduziert. Die Maßnahmen, welche vom Modellierer zur Erstellung dieser Views durchgeführt werden müssen, können hierbei durchaus zu einer komplexen Aufgabe werden. Im Folgenden wird anhand ereignisgesteuerter Prozessketten (EPKs) [KNS92] die Umsetzung der zweiten Variante diskutiert. Dabei wird in Abschnitt 2 zunächst eine metamodellbasierte Formalisierung der EPK vorgenommen, um eine konzeptionelle Basis für die multiperspektivische Erweiterung der Modellierungstechnik durch Konfigurationsmechanismen zu schaffen. Darauf aufbauend werden in Abschnitt 3 die notwendigen Erweiterungen der Modellierungstechnik vorgenommen. Abschnitt 4 behandelt die Problematik und Notwendigkeit von Konsistenzsicherungsmechanismen, die bei der Verwendung der Konfigurationsmechanismen auftreten können. Nach einem Praxisbeispiel in Abschnitt 5 schließt der Beitrag mit einem Ausblick in Abschnitt 6. 2 Metamodellbasierte Formalisierung der EPK Das hier vorgestellte Verfahren zur Erstellung multiperspektivischer ereignisgesteuerter Prozessketten basiert auf der Manipulation von Modellstrukturen durch die Anwendung von Konfigurationsmechanismen. Da hierbei die strukturellen Veränderungen auf Ebene der Sprachspezifikation sowie deren Auswirkungen auf die Struktur der Modelle im Zentrum der Betrachtung stehen, empfiehlt es sich, die Sprache der EPK formalisiert darzustellen. Dies kann wiederum durch Informationsmodelle – sogenannte sprachorientierte Metamodelle – erfolgen [St96, S. 24ff.]. Als Notationsform eignen sich insbesondere Struktursprachen wie das Entity-Relationship-Modell [Ch76]. Ein erweiterter Dialekt dieser Modellierungssprache wird im vorliegenden Beitrag zur Metamodellierung verwendet. 2 Das zentrale Element der EPK Sprache ist das Prozesselement (vgl. Abbildung 1). Alle am Prozessgraphen beteiligten Knoten werden als Spezialisierung dieses Elements mo1 Der Begriff EPK wird im Folgenden synonym zur erweiterten ereignisgesteuerten Prozesskette (eEPK) verwendet, die neben der Ablauflogik die Annotation von benötigten Ressourcen erlaubt. 2 Es handelt sich hierbei um einen Dialekt, der die perspektivenabhängige Modifikation von Sprachen erlaubt (vgl. ausführlich [Be02, S. 77ff.]). delliert. Hierzu gehören die Elemente Prozessfunktion, Prozessereignis und Operator (vgl. Spezialisierung des Entitytyps Prozesselement). Eine Prozessfunktion beschreibt eine Aktivität innerhalb eines Prozesses. Diese Aktivitäten werden beim Eintreten eines oder einer Kombination von Ereignissen ausgeführt und führen nach ihrer Beendigung selbst wieder zu dem Eintreten von Ereignissen. Somit kann ein Ereignis als Zustandswechsel interpretiert werden. Die notwendige Kombination der Ereignisse für die Ausführung einer Aktivität sowie die Definition der Menge der eintretenden Ereignisse nach erfolgreicher Ausführung werden über die Operatoren definiert. Hierdurch lassen sich parallele Prozessstränge und deren Wiederzusammenführung im Prozessmodell abbilden. Prozessfunktion Operator Prozessereignis Prozesselement D,T (0,n) (0,n) Ressource (0,n) (0,n) D,P Organisationseinheit Fachbegriff Anwendungssystemtyp Vorgänger/ Nachfolger PERessourcenZuO (0,n) ProzessRessourcenBeziehungstyp Typ PRBeziehungstyphierarchie


title: Decoding of EEG Signals Using Deep Long Short-Term Memory Network in Face Recognition Task

text: The paper proposes a novel approach to classify the human memory response involved in the face recognition task by the utilization of event related potentials. Electroencephalographic signals are acquired when a subject engages himself/herself in familiar or unfamiliar face recognition tasks. The signals are analyzed through source Iocalization using eLORETA and artifact removal by ICA from a set of channels corresponding to those selected sources, with an ultimate aim to classify the EEG responses of familiar and unfamiliar faces. The EEG responses of the two different classes (familiar and unfamiliar face recognition)are distinguished by analyzing the Event Related Potential signals that reveal the existence of large N250 and P600 signals during familiar face recognition.The paper introduces a novel LSTM classifier network which is designed to classify the ERP signals to fulfill the prime objective of this work. The first layer of the novel LSTM network evaluates the spatial and local temporal correlations between the obtained samples of local EEG time-windows. The second layer of this network models the temporal correlations between the time-windows. An attention mechanism has been introduced in each layer of the proposed model to compute the contribution of each EEG time-window in face recognition task. Performance analysis reveals that the proposed LSTM classifier with attention mechanism outperforms the efficiency of the conventional LSTM and other classifiers with a significantly large margin. Moreover, source Iocalization using eLORETA shows the involvement of inferior temporal and frontal lobes during familiar face recognition and pre-frontal lobe during unfamiliar face recognition. Thus, the present research outcome can be used in criminal investigation, where meticulous differentiation of familiar and unfamiliar face detection by criminals can be performed from their acquired brain responses.


title: Algorithmic Prediction of Health-Care Costs

text: The rising cost of health care is one of the world’s most important problems. Accordingly, predicting such costs with accuracy is a significant first step in addressing this problem. Since the 1980s, there has been research on the predictive modeling of medical costs based on (health insurance) claims data using heuristic rules and regression methods. These methods, however, have not been appropriately validated using populations that the methods have not seen. We utilize modern data-mining methods, specifically classification trees and clustering algorithms, along with claims data from over 800,000 insured individuals over three years, to provide rigorously validated predictions of health-care costs in the third year, based on medical and cost data from the first two years. We quantify the accuracy of our predictions using unseen (out-of-sample) data from over 200,000 members. The key findings are: (a) our data-mining methods provide accurate predictions of medical costs and represent a powerful tool for prediction of health-care costs, (b) the pattern of past cost data is a strong predictor of future costs, and (c) medical information only contributes to accurate prediction of medical costs of high-cost members.


title: Extensive Benchmark and Survey of Modeling Methods for Scene Background Initialization

text: Scene background initialization is the process by which a method tries to recover the background image of a video without foreground objects in it. Having a clear understanding about which approach is more robust and/or more suited to a given scenario is of great interest to many end users or practitioners. The aim of this paper is to provide an extensive survey of scene background initialization methods as well as a novel benchmarking framework. The proposed framework involves several evaluation metrics and state-of-the-art methods, as well as the largest video data set ever made for this purpose. The data set consists of several camera-captured videos that: 1) span categories focused on various background initialization challenges; 2) are obtained with different cameras of different lengths, frame rates, spatial resolutions, lighting conditions, and levels of compression; and 3) contain indoor and outdoor scenes. The wide variety of our data set prevents our analysis from favoring a certain family of background initialization methods over others. Our evaluation framework allows us to quantitatively identify solved and unsolved issues related to scene background initialization. We also identify scenarios for which state-of-the-art methods systematically fail.


title: PUMA: Planning Under Uncertainty with Macro-Actions

text: Planning in large, partially observable domains is challenging, especially when a long-horizon lookahead is necessary to obtain a good policy. Traditional POMDP planners that plan a different potential action for each future observation can be prohibitively expensive when planning many steps ahead. An efficient solution for planning far into the future in fully observable domains is to use temporallyextended sequences of actions, or “macro-actions.” In this paper, we present a POMDP algorithm for planning under uncertainty with macro-actions (PUMA) that automatically constructs and evaluates open-loop macro-actions within forward-search planning, where the planner branches on observations only at the end of each macro-action. Additionally, we show how to incrementally refine the plan over time, resulting in an anytime algorithm that provably converges to an ǫ-optimal policy. In experiments on several large POMDP problems which require a long horizon lookahead, PUMA outperforms existing state-of-the art solvers. Most partially observable Markov decision process (POMDP) planners select actions conditioned on the prior observation at each timestep: we refer to such planners as fully-conditional. When good performance relies on considering different possible observations far into the future, both online and offline fully-conditional planners typically struggle. An extreme alternative is unconditional (or “openloop”) planning where a sequence of actions is fixed and does not depend on the observations that will be received during execution. While open-loop planning can be extremely fast and perform surprisingly well in certain domains, acting well in most real-world domains requires plans where at least some action choices are conditional on the obtained observations. This paper focuses on the significant subset of POMDP domains, including scientific exploration, target surveillance, and chronic care management, where it is possible to act well by planning using conditional sequences of openloop, fixed-length action chains, or “macro-actions.” We call this approach semi-conditional planning, in that actions are chosen based on the received observations only at the end of each macro-action. Copyright c © 2010, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. For a discussion of using open-loop planning for multi-robot tag for open-loop planning see Yu et al. (2005). We demonstrate that for certain domains, planning with macro-actions can offer performance close to fullyconditional planning at a dramatically reduced computational cost. In comparison to prior macro-action work, where a domain expert often hand-coded a good set of macro-actions for each problem, we present a technique for automatically constructing finite-length open-loop macroactions. Our approach uses sub-goal states based on immediate reward and potential information gain. We then describe how to incrementally refine an initial macro-action plan by incorporating successively shorter macro-actions. We combine these two contributions in a forward-search algorithm for planning under uncertainty with macro-actions (PUMA). PUMA is an anytime algorithm which guarantees eventual convergence to an ǫ-optimal policy, even in domains that may require close to fully-conditional plans. PUMA outperforms a state-of-the-art POMDP planner both in terms of plan quality and computational cost on two large simulated POMDP problems. However, semiconditional planning does not yield an advantage in all domains, and we provide preliminary experimental analysis towards determining a priori when planning in a semiconditional manner will be helpful. However, even in domains that are not well suited to semi-conditional planning, our anytime improvement allows PUMA to still eventually compute a good policy, suggesting that PUMA may be viable as a generic planner for large POMDP problems.


title: Revising Perceptual Linear Prediction (PLP)

text: Mel Frequency Cepstral Coefficients (MFCC) and Perceptual Linear Prediction (PLP) are the most popular acoustic features used in speech recognition. Often it depends on the task, which of the two methods leads to a better performance. In this work we develop acoustic features that combine the advantages of MFCC and PLP. Based on the observation that the techniques have many similarities, we revise the processing steps of PLP. In particular, the filter-bank, the equal-loudness pre-emphasis and the input for the linear prediction are improved. It is shown for a broadcast news transcription task and a corpus of children’s speech that the new variant of PLP performs better than both MFCC and conventional PLP for a wide range of clean and noisy acoustic conditions.


title: Multi-speaker modeling and speaker adaptation for DNN-based TTS synthesis

text: In DNN-based TTS synthesis, DNNs hidden layers can be viewed as deep transformation for linguistic features and the output layers as representation of acoustic space to regress the transformed linguistic features to acoustic parameters. The deep-layered architectures of DNN can not only represent highly-complex transformation compactly, but also take advantage of huge amount of training data. In this paper, we propose an approach to model multiple speakers TTS with a general DNN, where the same hidden layers are shared among different speakers while the output layers are composed of speaker-dependent nodes explaining the target of each speaker. The experimental results show that our approach can significantly improve the quality of synthesized speech objectively and subjectively, comparing with speech synthesized from the individual, speaker-dependent DNN-based TTS. We further transfer the hidden layers for a new speaker with limited training data and the resultant synthesized speech of the new speaker can also achieve a good quality in term of naturalness and speaker similarity.


title: Classroom Response Systems: A Review of the Literature.

text: As the frequency with which Classroom Response Systems (CRSs) are used is increasing, it becomes more and more important to define the affordances and limitations of these tools. Currently existing literature is largely either anecdotal or focuses on comparing CRS and non-CRS environments that are unequal in other aspects as well. In addition, the literature primarily describes situations in which the CRS is used to provide an individual as opposed to a group response. This article points to the need for a concerted research effort, one that rigorously explores conditions of use across diverse settings and pedagogies.


title: An energy-efficient dual sampling SAR ADC with reduced capacitive DAC

text: This paper presents an energy-efficient SAR ADC which adopts reduced MSB cycling step with dual sampling of the analog signal. By sampling and holding the analog signal asymmetrically at both input sides of comparator, the MSB cycling step can be hidden by hold mode. Benefits from this technique, not only the total capacitance of DAC is reduced by half, but also the average switching energy is reduced by 68% compared with conventional SAR ADC. Moreover, switching energy distribution is more uniform over entire output code compared with previous works.


title: The impact of pretend play on children's development: a review of the evidence.

text: Pretend play has been claimed to be crucial to children's healthy development. Here we examine evidence for this position versus 2 alternatives: Pretend play is 1 of many routes to positive developments (equifinality), and pretend play is an epiphenomenon of other factors that drive development. Evidence from several domains is considered. For language, narrative, and emotion regulation, the research conducted to date is consistent with all 3 positions but insufficient to draw conclusions. For executive function and social skills, existing research leans against the crucial causal position but is insufficient to differentiate the other 2. For reasoning, equifinality is definitely supported, ruling out a crucially causal position but still leaving open the possibility that pretend play is epiphenomenal. For problem solving, there is no compelling evidence that pretend play helps or is even a correlate. For creativity, intelligence, conservation, and theory of mind, inconsistent correlational results from sound studies and nonreplication with masked experimenters are problematic for a causal position, and some good studies favor an epiphenomenon position in which child, adult, and environment characteristics that go along with play are the true causal agents. We end by considering epiphenomenalism more deeply and discussing implications for preschool settings and further research in this domain. Our take-away message is that existing evidence does not support strong causal claims about the unique importance of pretend play for development and that much more and better research is essential for clarifying its possible role.


title: Adversarial Examples: Attacks on Machine Learning-based Malware Visualization Detection Methods

text: As the threat of malicious software (malware) becomes urgently serious, automatic malware detection techniques have received increasing attention recently, where the machine learning (ML)-based visualization detection plays a significant role. However, this leads to a fundamental problem whether such detection methods can be robust enough against various potential attacks. Even though ML algorithms show superiority to conventional ones in malware detection in terms of high efficiency and accuracy, this paper demonstrates that such ML-based malware detection methods are vulnerable to adversarial examples (AE) attacks. We propose the first AE-based attack framework, named Adversarial Texture Malware Perturbation Attacks (ATMPA), based on the gradient descent or L-norm optimization method. By introducing tiny perturbations on the transformed dataset, ML-based malware detection methods completely fail. The experimental results on the MS BIG malware dataset show that a small interference can reduce the detection rate of convolutional neural network (CNN), support vector machine (SVM) and random forest(RF)-based malware detectors down to 0 and the attack transferability can achieve up to 88.7% and 74.1% on average in different ML-based detection methods.


title: Block Chain based Searchable Symmetric Encryption

text: The mechanism for traditional Searchable Symmetric Encryption is pay-then-use. That is to say, if a user wants to search some documents that contain special keywords, he needs to pay to the server firstly, then he can enjoy search service. Under this situation, these kinds of things will happen: After the user paying the service fees, the server may either disappear because of the poor management or returning nothing. As a result, the money that the user paid cannot be brought back quickly. Another case is that the server may return incorrect document sets to the user in order to save his own cost. Once such events happen, it needs the arbitration institution to mediate which will cost a long time. Besides, to settle the disputes the user has to pay to the arbitration institution. Ideally, we deeply hope that when the user realizes the server has a tendency to cheat in the task of searching, he can immediately and automatically withdraw his money to safeguard his right. However, the existing SSE protocols cannot satisfy this demand. To solve this dilemma, we find a compromised method by introducing the block chain into SSE. Our scheme achieves three goals stated below. Firstly, when the server does not return any thing to user after he gets the search token, the user can get some compensation from the server, because the server can infer some important information from the Index and this token. Besides, the user also doesn’t pay the service charge. Secondly, if the documents that the server returns are false, the server cannot receive service fees, meanwhile, he will be punished. Lastly, when the user receives some bitcoin from server at the beginning, he may terminate the protocol. Under this situation, the server is a victim. In order to prevent such thing from happening, the server will broadcast a transaction to redeem his pledge after an appointed time. ∗Corresponding author Email addresses: tianhb@mail.sysu.edu.cn (Haibo Tian), isszhfg@mail.sysu.edu.cn (Fangguo Zhang ) Preprint submitted to Elsevier April 26, 2017


title: Ionospheric Time-Delay Algorithm for Single-Frequency GPS Users

text: The goal in designing an ionospheric time-delay correctionalgorithm for the single-frequency global positioning system userwas to include the main features of the complex behavior of theionosphere, yet require a minimum of coefficients and usercomputational time, while still yielding an rms correction of at least50 percent. The algorithm designed for this purpose, andimplemented in the GPS satellites, requires only eight coefficientssent as part of the satellite message, contains numerousapproximations designed to reduce user computationalrequirements, yet preserves the essential elements required to obtaingroup delay values along multiple satellite viewing directions.


title: Weighted Similarity Schemes for High Scalability in User-Based Collaborative Filtering

text: Similarity-based algorithms, often referred to as memory-based collaborative filtering techniques, are one of the most successful methods in recommendation systems. When explicit ratings are available, similarity is usually defined using similarity functions, such as the Pearson correlation coefficient, cosine similarity or mean square difference. These metrics assume similarity is a symmetric criterion. Therefore, two users have equal impact on each other in recommending new items. In this paper, we introduce new weighting schemes that allow us to consider new features in finding similarities between users. These weighting schemes, first, transform symmetric similarity to asymmetric similarity by considering the number of ratings given by users on non-common items. Second, they take into account the habit effects of users are regarded on rating items by measuring the proximity of the number of repetitions for each rate on common rated items. Experiments on two datasets were implemented and compared to other similarity measures. The results show that adding weighted schemes to traditional similarity measures These authors contributed equally to this work as the first author. P. Pirasteh · D. Hwang Department of Computer Engineering, Yeungnam University, Gyeongsan, Republic of Korea P. Pirasteh e-mail: parivash63@gmail.com D. Hwang e-mail: dosamhwang@gmail.com J. E. Jung ( ) Department of Computer Engineering, Chung-Ang University, Seoul, Republic of Korea e-mail: ontology.society@gmail.com significantly improve the results obtained from traditional similarity measures.


title: Optimization tool for direct water cooling system of high power IGBT modules

text: Thermal management of power electronic devices is essential for reliable system performance especially at high power levels. Since even the most efficient electronic circuit becomes hot because of ohmic losses, it is clear that cooling is needed in electronics and even more as the power increases. One of the most important activities in the thermal management and reliability improvement is the cooling system design. As industries are developing smaller power devices with higher power densities, optimized design of cooling systems with minimum thermal resistance and pressure drop become important issue for thermal design engineers. This paper aims to present a user friendly optimization tool for direct water cooling system of a high power module which enables the cooling system designer to identify the optimized solution depending on customer load profiles and available pump power. CFD simulations are implemented to find best solution for each scenario.


title: BER Analysis of MIMO-OFDM System using Alamouti STBC and MRC Diversity Scheme over Rayleigh Multipath Channel

text: Commons Attribution-Noncommercial 3.0 Unported License http://creativecommons.org/licenses/by-nc/3.0/), permitting all non commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Global Journal of Researches in Engineering Electrical and Electronics Engineering Volume 13 Issue 13 Version 1.0 Year 2013 Type: Double Blind Peer Reviewed International Research Journal Publisher: Global Journals Inc. (USA) Online ISSN: 2249-4596 & Print ISSN: 0975-5861


title: A passivity based Cartesian impedance controller for flexible joint robots - part I: torque feedback and gravity compensation

text: In this paper a novel approach to the Cartesian impedance control problem for robots with flexible joints is presented. The proposed controller structure is based on simple physical considerations, which are motivating the extension of classical position feedback by an additional feedback of the joint torques. The torque feedback action can be interpreted as a scaling of the apparent motor inertia. Furthermore the problem of gravity compensation is addressed. Finally, it is shown that the closed loop system can be seen as a feedback interconnection of passive systems. Based on this passivity property a proof of asymptotic stability is presented.


title: A unified approach for motion and force control of robot manipulators: The operational space formulation

text: A framework for the analysis and control of manipulator systems with respect to the dynamic behavior of their end-effectors is developed. First, issues related to the description of end-effector tasks that involve constrained motion and active force control are discussed. The fundamentals of the operational space formulation are then presented, and the unified approach for motion and force control is developed. The extension of this formulation to redundant manipulator systems is also presented, constructing the end-effector equations of motion and describing their behavior with respect to joint forces. These results are used in the development of a new and systematic approach for dealing with the problems arising at kinematic singularities. At a singular configuration, the manipulator is treated as a mechanism that is redundant with respect to the motion of the end-effector in the subspace of operational space orthogonal to the singular direction.


title: A passivity based Cartesian impedance controller for flexible joint robots - part II: full state feedback, impedance design and experiments

text: The paper presents a Cartesian impedance controller for flexible joint robots based on the feedback of the complete state of the system, namely the motor position, the joint torque and their derivatives. The approach is applied to a quite general robot model, in which also a damping element is considered in parallel to the joint stiffness. Since passivity and asymptotic stability of the controller hold also for varying damping matrices, some possibilities of designing those gain matrices (depending on the actual inertia matrix) are addressed. The passivity of the controller relies on the usage of only motor side measurements for the position feedback. A method is introduced, which provides the exact desired link side stiffness based on this motor position information. Experimental results are validating the proposed controller.


title: Nonlinear Systems Analysis

text: THIS IS a completely rewritten version of the first edition which appeared in 1978. At that time the book gave a good overview of the main body of nonlinear systems and control theory, except for nonlinear optimal control theory. The emphasis was very much on the analysis of systems (in openor closed-loop configuration), instead of on the actual design of controllers. Most attention was being focused on stability issues, both from the input-output and the state-space point of view. Highlights in this theory were the concepts of input-output stability including Popov's criterion and the circle criterion (see also Desoer and Vidyasagar, 1975), the theory of Lyapunov stability, and perhaps the method of describing functions. Since the appearance of the first edition, geometric nonlinear control theory has become a prevailing trend. (In fact these developments were already initiated at the beginning of the seventies.) Geometric nonlinear control theory started as a successful approach to deal with basic system-theoretic questions in the state-space formulation of nonlinear control systems, such as controllability and observability properties and minimal realization theory. It gained strong impetus at the beginning of the eighties by the systematic study of nonlinear (state) feedback for various synthesis problems; also stimulated by the geometric approach to linear control theory of Wonham and Morse and Basile and Marro: In particular the Lie bracket conditions for controllability and feedback linearizability have become popular and powerful tools in nonlinear control. The books by Isidori (1989) and Nijmeijer and Van der Schaft (1990) are clear exponents of the achievements of geometric nonlinear control theory. In the last couple of years one can witness some developments which can be looked at as attempts to bridge the gap between nonlinear systems and control theory as put forward in the first edition of the present book on the one hand, and geometric nonlinear control theory on the other hand. Indeed, in nonlinear adaptive control as well as in nonlinear robust control (including nonlinear ~-cont ro l ) there is much need for the kind of stability concepts as exposed in the first edition of the book, while at the same time geometric nonlinear control theory offers an underlying structural framework. In particular passivity, and more generally, dissipativity concepts turn out to be extremely useful in these areas, especially within the context of the control of physical systems. Also, there has been recently some rapprochement between nonlinear input-output theory and (geometric) state-space theory. In my opinion these converging developments are very important and indeed offer promising perspectives for a truly nonlinear control design. In the present second edition Professor Vidyasagar has made an admirable attempt to include at least an introduction to geometric nonlinear control theory in an additional chapter of the book. In fact, this new chapter deals with the perhaps most 'useful' parts of geometric nonlinear control theory such as controllability, feedback linearization and input-output linearization. The other most noticeable differences with the first edition are the inclusion of some


title: On a New Generation of Torque Controlled Light-Weight Robots

text: The paper describes the recent design and development efforts in DLR ́s robotics lab towards the second generation of light-weight robots. The design of the lightweight mechanics, integrated sensors and electronics is outlined. The fully sensorized joint, with motor and link position sensors as well as joint torque sensors enables the implementation of effective vibration damping and advanced control strategies for compliant manipulation. The mechatronic approach incorporates a tight collaboration between mechanics, electronics and controller design as well. Thus we hope, that important steps towards a new generation of service and personal robots have been achieved.


title: Compact Zigzag-Shaped-Slit Microstrip Antenna With Circular Defected Ground Structure for Wireless Applications

text: In this letter, a compact zigzag-shaped-slit rectangular microstrip patch antenna with circular defected ground structure (DGS) is designed for wireless applications. The probe-fed antenna consisting of a zigzag-shaped slit, dual T-shaped slits on either sides of a rectangular patch, and circular dumbbell-shaped defected ground plane is optimized. The antenna was able to generate three separate resonances to cover both the 2.45/5.28-GHz WLAN bands and the 3.5-GHz WiMAX bands while maintaining a small overall size of 40 ×28 ×3.175 mm3. The return-loss impedance bandwidth values are enhanced significantly for three resonant frequencies. The designed antenna is characterized with better radiation patterns and potentially stable gain around 4-6 dBi over the working bands. Good agreement was obtained between measurements and simulations.


title: FIRST EXPERIMENTAL INVESTIGATIONS ON WHEEL-WALKING FOR IMPROVING TRIPLE-BOGIE ROVER LOCOMOTION PERFORMANCES

text: Deployment actuators of a triple-bogie rover locomotion platform can be used to perform Wheel-Walking (WW) manoeuvres. How WW could affect the traversing capabilities of rovers is a recurrent debate in the planetary robotics community. The Automation and Robotics Section of ESTEC has initiated a long term project to evaluate the performance of WW manoeuvres in different scenarios. This paper presents the first experimental results on this project, obtained during the test campaign run on November 2014 at the Planetary Robotics Lab (PRL) of ESTEC, and shows the performance analysis made when comparing WW with standard rolling. The PRL rover prototype ExoTeR was used to test three different scenarios: entrapment in loose soil, up-slope traverse and lander egressing. WW locomotion showed increased capabilities in all scenarios and proved its relevance and advantages for planetary exploration missions.


title: ISO 9241-11 Revised: What Have We Learnt About Usability Since 1998?

text: A revision is currently being undertaken of ISO 9241-11, published in 1998 to provide guidance on usability. ISO-9241-11 defines usability in terms of effectiveness, efficiency and satisfaction in a particular context of use. The intention was to emphasise that usability is an outcome of interaction rather than a property of a product. This is now widely accepted. However, the standard also places emphasis on usability measurement and it is now appreciated that there is more to usability evaluation than measurement. Other developments include an increasing awareness of the importance of the individual user's emotional experience as discretionary usage of complex consumer products and use of the World Wide Web have became more widespread. From an organisational perspective, it is now appreciated that usability plays an important role in managing the potentials risks that can arise from inappropriate outcomes of interaction. The revision of ISO 9241-11 takes account of these issues and other feedback.


title: Aerodynamic Design Optimization Studies of a Blended-Wing-Body Aircraft

text: Abstract The blended-wing body is an aircraft configuration that has the potential to be more efficient than conventional large transport aircraft configurations with the same capability. However, the design of the blended-wing is challenging due to the tight coupling between aerodynamic performance, trim, and stability. Other design challenges include the nature and number of the design variables involved, and the transonic flow conditions. To address these issues, we perform a series of aerodynamic shape optimization studies using Reynolds-averaged Navier–Stokes computational fluid dynamics with a Spalart–Allmaras turbulence model. A gradient-based optimization algorithm is used in conjunction with a discrete adjoint method that computes the derivatives of the aerodynamic forces. A total of 273 design variables—twist, airfoil shape, sweep, chord, and span—are considered. The drag coefficient at the cruise condition is minimized subject to lift, trim, static margin, and center plane bending moment constraints. The studies investigate the impact of the various constraints and design variables on optimized blended-wing-body configurations. The lowest drag among the trimmed and stable configurations is obtained by enforcing a 1% static margin constraint, resulting in a nearly elliptical spanwise lift distribution. Trim and static stability are investigated at both onand off-design flight conditions. The single-point designs are relatively robust to the flight conditions, but further robustness is achieved through a multi-point optimization.


title: Group-Sensitive Triplet Embedding for Vehicle Reidentification

text: The widespread use of surveillance cameras toward smart and safe cities poses the critical but challenging problem of vehicle reidentification (Re-ID). The state-of-the-art research work performed vehicle Re-ID relying on deep metric learning with a triplet network. However, most existing methods basically ignore the impact of intraclass variance-incorporated embedding on the performance of vehicle reidentification, in which robust fine-grained features for large-scale vehicle Re-ID have not been fully studied. In this paper, we propose a deep metric learning method, group-sensitive-triplet embedding (GS-TRE), to recognize and retrieve vehicles, in which intraclass variance is elegantly modeled by incorporating an intermediate representation “group” between samples and each individual vehicle in the triplet network learning. To capture the intraclass variance attributes of each individual vehicle, we utilize an online grouping method to partition samples within each vehicle ID into a few groups, and build up the triplet samples at multiple granularities across different vehicle IDs as well as different groups within the same vehicle ID to learn fine-grained features. In particular, we construct a large-scale vehicle database “PKU-Vehicle,” consisting of 10 million vehicle images captured by different surveillance cameras in several cities, to evaluate the vehicle Re-ID performance in real-world video surveillance applications. Extensive experiments over benchmark datasets VehicleID, VeRI, and CompCar have shown that the proposed GS-TRE significantly outperforms the state-of-the-art approaches for vehicle Re-ID.


title: Integrating technology in the classroom: a visual conceptualization of teachers' knowledge, goals and beliefs

text: In this paper, we devise a diagrammatic conceptualization to describe and represent the complex interplay of a teacher’s knowledge (K), goals (G) and beliefs (B) in leveraging technology effectively in the classroom. The degree of coherency between the KGB region and the affordances of the technology serves as an indicator of the teachers’ developmental progression through the initiation, implementation and maturation phases of using technology in the classroom. In our study, two teachers with differing knowledge, goals and beliefs are studied as they integrated GroupScribbles technology in their classroom lessons over a period of 1 year. Our findings reveal that the transition between the teacher’s developmental states (as indicated by coherency diagrams) is nonlinear, and thus the importance of ensuring high coherency right at the initiation stage. Support for the teacher from other teachers and researchers remains an important factor in developing the teacher’s competency to leverage the technology successfully. The stability of the KGB region further ensures smooth progression of the teacher’s effective integration of technology in the classroom.


title: EvalVid - A Framework for Video Transmission and Quality Evaluation

text: With EvalVid we present a complete framework and tool-set for evaluation of the quality of video transmitted over a real or simu lated communication network. Besides measuring QoS parameters of the underlyin g network, like loss rates, delays, and jitter, we support also a subjective vide o quality evaluation of the received video based on the frame-by-frame PSNR calcula tion. The tool-set has a modular construction, making it possible to exchange b oth the network and the codec. We present here its application for MPEG-4 as exam ple. EvalVid is targeted for researchers who want to evaluate their network designs or setups in terms of user perceived video quality. The tool-set is publi cly available [11].


title: Design and control of an actuated thumb exoskeleton for hand rehabilitation following stroke

text: Chronic hand impairment is common following stroke. This paper presents an actuated thumb exoskeleton (ATX) to facilitate research in hand rehabilitation therapy. The ATX presented in this work permits independent bi-directional actuation in each of the 5 degrees-of-freedom (DOF) of the thumb using a mechanism that has 5 active DOF and 3 passive DOF. The ATX is able to provide considerable joint torques for the user while still allowing backdrivability through flexible shaft transmission. A prototype has been built and experiments were conducted to evaluate the closed-loop position control. Further improvement and future work are discussed.


title: Robotic Cutting : Mechanics and Control of Knife Motion

text: Effectiveness of cutting is measured by the ability to achieve material fracture with smooth knife movements. The work performed by the knife overcomes the material toughness, acts against the blade-material friction, and generates shape deformation. This paper studies how to control a 2-DOF robotic arm equipped with a force/torque sensor to cut through an object in a sequence of three moves: press, push, and slice. For each move, a separate control strategy in the Cartesian space is designed to incorporate contact and/or force constraints while following some prescribed trajectory. Experiments conducted over several types of natural foods have demonstrated smooth motions like would be commanded by a human hand.


title: Pravastatin in elderly individuals at risk of vascular disease (PROSPER): a randomised controlled trial

text:
BACKGROUND
Although statins reduce coronary and cerebrovascular morbidity and mortality in middle-aged individuals, their efficacy and safety in elderly people is not fully established. Our aim was to test the benefits of pravastatin treatment in an elderly cohort of men and women with, or at high risk of developing, cardiovascular disease and stroke.

METHODS
We did a randomised controlled trial in which we assigned 5804 men (n=2804) and women (n=3000) aged 70-82 years with a history of, or risk factors for, vascular disease to pravastatin (40 mg per day; n=2891) or placebo (n=2913). Baseline cholesterol concentrations ranged from 4.0 mmol/L to 9.0 mmol/L. Follow-up was 3.2 years on average and our primary endpoint was a composite of coronary death, non-fatal myocardial infarction, and fatal or non-fatal stroke. Analysis was by intention-to-treat.

FINDINGS
Pravastatin lowered LDL cholesterol concentrations by 34% and reduced the incidence of the primary endpoint to 408 events compared with 473 on placebo (hazard ratio 0.85, 95% CI 0.74-0.97, p=0.014). Coronary heart disease death and non-fatal myocardial infarction risk was also reduced (0.81, 0.69-0.94, p=0.006). Stroke risk was unaffected (1.03, 0.81-1.31, p=0.8), but the hazard ratio for transient ischaemic attack was 0.75 (0.55-1.00, p=0.051). New cancer diagnoses were more frequent on pravastatin than on placebo (1.25, 1.04-1.51, p=0.020). However, incorporation of this finding in a meta-analysis of all pravastatin and all statin trials showed no overall increase in risk. Mortality from coronary disease fell by 24% (p=0.043) in the pravastatin group. Pravastatin had no significant effect on cognitive function or disability.

INTERPRETATION
Pravastatin given for 3 years reduced the risk of coronary disease in elderly individuals. PROSPER therefore extends to elderly individuals the treatment strategy currently used in middle aged people.


title: A framework for evaluating quality-driven self-adaptive software systems

text: Over the past decade the dynamic capabilities of self-adaptive software-intensive systems have proliferated and improved significantly. To advance the field of self-adaptive and self-managing systems further and to leverage the benefits of self-adaptation, we need to develop methods and tools to assess and possibly certify adaptation properties of self-adaptive systems, not only at design time but also, and especially, at run-time. In this paper we propose a framework for evaluating quality-driven self-adaptive software systems. Our framework is based on a survey of self-adaptive system papers and a set of adaptation properties derived from control theory properties. We also establish a mapping between these properties and software quality attributes. Thus, corresponding software quality metrics can then be used to assess adaptation properties.


title: A multimodal adaptive session manager for physical rehabilitation exercising

text: Physical exercising is an essential part of any rehabilitation plan. The subject must be committed to a daily exercising routine, as well as to a frequent contact with the therapist. Rehabilitation plans can be quite expensive and time-consuming. On the other hand, tele-rehabilitation systems can be really helpful and efficient for both subjects and therapists. In this paper, we present ReAdapt, an adaptive module for a tele-rehabilitation system that takes into consideration the progress and performance of the exercising utilizing multisensing data and adjusts the session difficulty resulting to a personalized session. Multimodal data such as speech, facial expressions and body motion are being collected during the exercising and feed the system to decide on the exercise and session difficulty. We formulate the problem as a Markov Decision Process and apply a Reinforcement Learning algorithm to train and evaluate the system on simulated data.


title: Environmental influence in the brain, human welfare and mental health

text: The developing human brain is shaped by environmental exposures—for better or worse. Many exposures relevant to mental health are genuinely social in nature or believed to have social subcomponents, even those related to more complex societal or area-level influences. The nature of how these social experiences are embedded into the environment may be crucial. Here we review select neuroscience evidence on the neural correlates of adverse and protective social exposures in their environmental context, focusing on human neuroimaging data and supporting cellular and molecular studies in laboratory animals. We also propose the inclusion of innovative methods in social neuroscience research that may provide new and ecologically more valid insight into the social-environmental risk architecture of the human brain.


title: Compact Rep-Rate GW Pulsed Generator Based on Forming Line With Built-In High-Coupling Transformer

text: In this paper, a compact rep-rate GW pulsed power generator is developed. First, its three key subsystems are theoretically analyzed, engineering designed, and experimentally investigated, respectively. The emphases are put on these four problems: the theoretical analysis of the voltage distribution across the conical secondary windings of the high-coupling transformer, the investigation of the high energy storage density dielectric used in the pulse forming line, the choice of the gas flow velocity of the gas blowing system, and theoretical analysis of the passive stability of the pulsed power generator operated in rep-rate mode. Second, the developed pulsed power generator is described in detail. It has a 0.2-m diameter, a 1.0-m length, and a 20- Ω wave impedance. Across a 100- Ω resistive dummy load, it can steadily operate at a 300-kV output voltage in 50-Hz rep-rate and 250 kV in 150 Hz without gas blowing system. The average power is ~ 1 kW. Finally, the pulsed power generator is applied to drive a relativistic backward-wave oscillator, generating a high-power microwave with peak output power of 200 MW and duration (full-width at half-maximum) of 5 ns in 150-Hz rep-rate. These efforts set a good foundation for the development of a compact rep-rate pulsed power generator and show a promising application for the future.


title: Myanmar Spell Checker

text: Natural Language Processing (NLP) is one of the most important research area carried out in the world of Human Language. For every language, spell checker is an essential component of many of Office Automation Systems and Machine Translation Systems. In this paper, we develop a Myanmar Spell Checker System which can handle Typographic errors, Sequence errors, Phonetic errors, and Context errors. A Myanmar Text Corpus is created for developing Myanmar Spell checker. To check Typographic Errors, corpus look up approach is applied. Myanmar3 Unicode is applied in this system so that it can automatically reorder the character sequence. A compound misused word detection algorithm is proposed for Phonetic Errors checking and Bayesian Classifier is applied for Context Errors checking. In this system, Levenshtein Distance Algorithm is applied to improve users’ efficiency by providing a suggestion list for misspelled Myanmar Words. We provide evaluation results of the system and our approach can handle various types of Myanmar spell errors.


title: A Supervised Named-Entity Extraction System for Medical Text

text: TOKEN LEMMA POS Chunk Capitalized Token Class Dependency Sem Group Doc Type Section CUI TUI SemGroup UMLS Categ LEXIQUE SG LEXIQUE CUI DISO TOKEN ANAT TOKEN Wiki Gold label Nails nail NNS B-NP Capitalized Word ROOT DIS heent B-C1 B-T023 B-ANAT B DISO B-ANAT B-C0027342 1 1 – O : : : O – Punct P ANAT DIS heent – – – O O O 0 0 – O No no DT B-NP Capitalized Word NMOD #NA DIS heent – – – O O O 0 0 – O bed bed NN I-NP – Word NMOD #NA DIS heent – – – O O O 1 1 – B-DISORDER abnormalities abnormality NNS I-NP – Word NMOD DISO DIS heent – – – O O O 1 0 – I-DISORDER , , , O – Punct P #NA DIS heent – – – O O O 0 0 – O lunulas lunula NNS B-NP – Word AMOD #NA DIS heent – – – O O O 0 0 – O present present JJ B-ADJP – Word APPO #NA DIS heent – – – O O O 1 1 – O , , , O – Punct P ANAT DIS heent – – – O O O 0 0 – O no no DT B-NP – Word NMOD DISO DIS heent – – – O O O 0 0 – O splinters splinter NNS I-NP – Word ROOT DIS heent B-C2 C3 B-T037 B-DISO O O O 1 0 B-DISO B-DISORDER , , , I-NP – Punct P DISO DIS heent – – – O O O 0 0 – O pulses pulse NNS I-NP – Word COORD DISO DIS heent – – – O B-PHYS B-C0391850 0 0 – O I Lexical and morphological features (e.g., capitalization, lemma)


title: Dual-Transfer Face Sketch–Photo Synthesis

text: Recognizing the identity of a sketched face from a face photograph dataset is a critical yet challenging task in many applications, not least law enforcement and criminal investigations. An intelligent sketched face identification system would rely on automatic face sketch synthesis from photographs, thereby avoiding the cost of artists manually drawing sketches. However, conventional face sketch–photo synthesis methods tend to generate sketches that are consistent with the artists’drawing styles. Identity-specific information is often overlooked, leading to unsatisfactory identity verification and recognition performance. In this paper, we discuss the reasons why conventional methods fail to recover identity-specific information. Then, we propose a novel dual-transfer face sketch–photo synthesis framework composed of an inter-domain transfer process and an intra-domain transfer process. In the inter-domain transfer, a regressor of the test photograph with respect to the training photographs is learned and transferred to the sketch domain, ensuring the recovery of common facial structures during synthesis. In the intra-domain transfer, a mapping characterizing the relationship between photographs and sketches is learned and transferred across different identities, such that the loss of identity-specific information is suppressed during synthesis. The fusion of information recovered by the two processes is straightforward by virtue of an ad hoc information splitting strategy. We employ both linear and nonlinear formulations to instantiate the proposed framework. Experiments on The Chinese University of Hong Kong face sketch database demonstrate that compared to the current state-of-the-art the proposed framework produces more identifiable facial structures and yields higher face recognition performance in both the photo and sketch domains.


title: Skin microbiota: overview and role in the skin diseases acne vulgaris and rosacea.

text: As the first barrier to environmental exposures, human skin has developed an integrated immune system to protect the inner body from chemical, physical or microbial insults. Microorganisms inhabiting superficial skin layers are known as skin microbiota and include bacteria, viruses, archaea and fungi. The microbiota composition is crucial in the instruction and support of the skin's immune system. Changes in microbiota can be due to individual, environmental or behavioral factors, such as age, climate, hygiene or antibiotic consumption, which can cause dysbiosis. The contribution of skin microbiota to disease development is known in atopic dermatitis, where there is an increase in Staphylococcus aureus. Culture-independent studies have enabled more accurate descriptions of this complex interplay. Microbial imbalance is associated with the development of various diseases. This review focuses on microbial imbalances in acne vulgaris and rosacea.


title: Eliminating Tight Coupling using Subscriptions Subgrouping in Structured Overlays

text: An advertisement and matching subscription are tightly coupled to activate a single publication routing path in content-based publish/subscribe systems. Due to this tight coupling, instantaneous updates in routing tables are required to generate alternative paths for dynamic routing. This poses serious challenges in offering scalable and robust dynamic routing in cyclic overlays when network conditions like link congestion is detected. We propose, OctopiA, a distributed publish/subscribe system for content-based dynamic routing in structured cyclic overlays. OctopiA uses a novel concept of subscription subgrouping to divide subscriptions into disjoint sets, called subscription subgroups, to eliminate tight coupling. While aiming at deployment in data center networks, OctopiA generates routing paths of minimum lengths. We use a homogeneous clustering approach with a bit-vector to realize subscription subgrouping and offer inter-cluster dynamic routing without requiring updates in routing tables. Experiments on a cluster testbed with real world data show that OctopiA reduces the number of saved advertisements in routing tables by 93%, subscription broadcast delay by 33%, static and dynamic publication delivery delays by 25% and 54%, respectively.


title: Virtual Reality as an Innovative Setting for Simulations in Education

text: The increasingly widespread use of simulations in education underlines the fact that these teaching tools compared to other methods or media allow students to approach and experience new topics in a more realistic way. This realism enhances their learning and understanding of complex subjects. So far it has been difficult to interactively simulate three-dimensional dynamic learning content. In this field, the continuing development of Virtual Reality (VR) offers new opportunities for educators to convey a wide variety of subjects. It is the aim of this paper to characterize the nature of Virtual Reality as an educational setting for simulations, and to show that Studierstube, our multi-user collaborative Virtual Environment, comprises the necessary features for applying VR-techniques to educational purposes. We further discuss the general applicability of VR to various fields of education and demonstrate its specific application as a tool for teaching elementary three-dimensional geometry.


title: Causal discovery and inference: concepts and recent methodological advances

text: This paper aims to give a broad coverage of central concepts and principles involved in automated causal inference and emerging approaches to causal discovery from i.i.d data and from time series. After reviewing concepts including manipulations, causal models, sample predictive modeling, causal predictive modeling, and structural equation models, we present the constraint-based approach to causal discovery, which relies on the conditional independence relationships in the data, and discuss the assumptions underlying its validity. We then focus on causal discovery based on structural equations models, in which a key issue is the identifiability of the causal structure implied by appropriately defined structural equation models: in the two-variable case, under what conditions (and why) is the causal direction between the two variables identifiable? We show that the independence between the error term and causes, together with appropriate structural constraints on the structural equation, makes it possible. Next, we report some recent advances in causal discovery from time series. Assuming that the causal relations are linear with nonGaussian noise, we mention two problems which are traditionally difficult to solve, namely causal discovery from subsampled data and that in the presence of confounding time series. Finally, we list a number of open questions in the field of causal discovery and inference.


title: Learning to Reason With Adaptive Computation

text: Multi-hop inference is necessary for machine learning systems to successfully solve tasks such as Recognising Textual Entailment and Machine Reading. In this work, we demonstrate the effectiveness of adaptive computation for learning the number of inference steps required for examples of different complexity and that learning the correct number of inference steps is difficult. We introduce the first model involving Adaptive Computation Time which provides a small performance benefit on top of a similar model without an adaptive component as well as enabling considerable insight into the reasoning process of the model.


title: Alignment of Monophonic and Polyphonic Music to a Score

text: Music alignmentis the associationof eventsin a score with pointsin the time axisof an audio signal. Thesignal is thus segmentedaccording to theeventsin thescore. We proposea new methodology for automaticalignmentbasedon dynamic time warping, where the spectral peak structure is usedto computethe local distance, enhancedby a modelof attacks andof silence. Themethodologycancopewith performances consider eddifficult to align, like polyphonicmusic,trills, fast sequences, or multi-instrumentmusic.An optimisationof the representationof thealignmentpathmakesthemethodapplicableto long soundfiles, so that unit databasescan be fully automaticallysegmentedand labeled. On 708 sequencesof synthesisedmusic,weachievedanaverageoffsetof 18msand an error rateof 2.5%.


title: Adaptive Mixtures of Local Experts

text: We present a new supervised learning procedure for systems composed of many separate networks, each of which learns to handle a subset of the complete set of training cases. The new procedure can be viewed either as a modular version of a multilayer supervised network, or as an associative version of competitive learning. It therefore provides a new link between these two apparently different approaches. We demonstrate that the learning procedure divides up a vowel discrimination task into appropriate subtasks, each of which can be solved by a very simple expert network.


title: Bayesian Methods for Mixtures of Experts

text: Tony Robinson Cambridge University Engineering Department Cambridge CB2 1PZ England. Tel: [+44] 1223 332815 ajr@eng.cam.ac.uk We present a Bayesian framework for inferring the parameters of a mixture of experts model based on ensemble learning by variational free energy minimisation. The Bayesian approach avoids the over-fitting and noise level under-estimation problems of traditional maximum likelihood inference. We demonstrate these methods on artificial problems and sunspot time series prediction.


title: Neural Networks and the Bias/Variance Dilemma

text: Feedforward neural networks trained by error backpropagation are examples of nonparametric regression estimators. We present a tutorial on nonparametric inference and its relation to neural networks, and we use the statistical viewpoint to highlight strengths and weaknesses of neural models. We illustrate the main points with some recognition experiments involving artificial data as well as handwritten numerals. In way of conclusion, we suggest that current-generation feedforward neural networks are largely inadequate for difficult problems in machine perception and machine learning, regardless of parallel-versus-serial hardware or other implementation issues. Furthermore, we suggest that the fundamental challenges in neural modeling are about representation rather than learning per se. This last point is supported by additional experiments with handwritten numerals.


title: The variational approximation for Bayesian inference

text: The influence of this Thomas Bayes' work was immense. It was from here that "Bayesian" ideas first spread through the mathematical world, as Bayes's own article was ignored until 1780 and played no important role in scientific debate until the 20th century. It was also this article of Laplace's that introduced the mathematical techniques for the asymptotic analysis of posterior distributions that are still employed today. And it was here that the earliest example of optimum estimation can be found, the derivation and characterization of an estimator that minimized a particular measure of posterior expected loss. After more than two centuries, we mathematicians, statisticians cannot only recognize our roots in this masterpiece of our science, we can still learn from it.


title: A multi-objective artificial bee colony algorithm

text: This work presents a multi-objective optimization method based on the artificial bee colony, called the MOABC, for optimizing problems with multiple objectives. The MOABC uses a grid-based approach to adaptively assess the Pareto frontmaintained in an external archive. The external archive is used to control the flying behaviours of the individuals and structuring the bee colony. The employed bees adjust their trajectories based on the non-dominated solutionsmaintained in the external archive. On the other hand, the onlooker bees select the food sources advertised by the employed bees to update their positions. The qualities of these food sources are computed based on the Pareto dominance notion. The scout bees are used by the MOABC to get rid of food sources with poor qualities. The proposed algorithm was evaluated on a set of standard test problems in comparison with other state-of-the-art algorithms. Experimental results indicate that the proposed approach is competitive compared to other algorithms considered in this work. © 2011 Elsevier B.V. All rights reserved.


title: Refining Geometry from Depth Sensors using IR Shading Images

text: We propose a method to refine geometry of 3D meshes from a consumer level depth camera, e.g. Kinect, by exploiting shading cues captured from an infrared (IR) camera. A major benefit to using an IR camera instead of an RGB camera is that the IR images captured are narrow band images that filter out most undesired ambient light, which makes our system robust against natural indoor illumination. Moreover, for many natural objects with colorful textures in the visible spectrum, the subjects appear to have a uniform albedo in the IR spectrum. Based on our analyses on the IR projector light of the Kinect, we define a near light source IR shading model that describes the captured intensity as a function of surface normals, albedo, lighting direction, and distance between light source and surface points. To resolve the ambiguity in our model between the normals and distances, we utilize an initial 3D mesh from the Kinect fusion and multi-view information to reliably estimate surface details that were not captured and reconstructed by the Kinect fusion. Our approach directly operates on the mesh model for geometry refinement. We ran experiments on our algorithm for geometries captured by both the Kinect I and Kinect II, as the depth acquisition in Kinect I is based on a structured-light technique and that of the Kinect II is based on a time-of-flight technology. The effectiveness of our approach is demonstrated through several challenging real-world examples. We have also performed a user study to evaluate the quality of the mesh models before and after our refinements.


title: Receptive fields of single neurones in the cat's striate cortex.

text: In the central nervous system the visual pathway from retina to striate cortex provides an opportunity to observe and compare single unit responses at several distinct levels. Patterns of light stimuli most effective in influencing units at one level may no longer be the most effective at the next. From differences in responses at successive stages in the pathway one may hope to gain some understanding of the part each stage plays in visual perception. By shining small spots of light on the light-adapted cat retina Kuffler (1953) showed that ganglion cells have concentric receptive fields, with an 'on' centre and an 'off ' periphery, or vice versa. The 'on' and 'off' areas within a receptive field were found to be mutually antagonistic, and a spot restricted to the centre of the field was more effective than one covering the whole receptive field (Barlow, FitzHugh & Kuffler, 1957). In the freely moving lightadapted cat it was found that the great majority of cortical cells studied gave little or no response to light stimuli covering most of the animal's visual field, whereas small spots shone in a restricted retinal region often evoked brisk responses (Hubel, 1959). A moving spot of light often produced stronger responses than a stationary one, and sometimes a moving spot gave more activation for one direction than for the opposite. The present investigation, made in acute preparations, includes a study of receptive fields of cells in the cat's striate cortex. Receptive fields of the cells considered in this paper were divided into separate excitatory and inhibitory ('on' and 'off') areas. In this respect they resembled retinal ganglion-cell receptive fields. However, the shape and arrangement of excitatory and inhibitory areas differed strikingly from the concentric pattern found in retinal ganglion cells. An attempt was made to correlate responses to moving stimuli


title: A handheld mirror simulation

text: We present the design and construction of a handheld mirror simulation device. The perception of the world reflected through a mirror depends on the viewer's position with respect to the mirror and the 3-D geometry of the world. In order to simulate a real mirror on a computer screen, images of the observed world, consistent with the viewer's position, must be synthesized and displayed in realtime. Our system is build around a LCD screen manipulated by the user, a single camera fixed on the screen, and a tracking device. The continuous input video stream and tracker data is used to synthesize, in real-time, a continuous video stream displayed on the LCD screen. The synthesized video stream is a close approximation of what the user would see on the screen surface if it were a real mirror. Our system provides a generic interface for applications involving rich, first-person interaction, such as the Virtual Daguerreotype.


title: Magic decorator: automatic material suggestion for indoor digital scenes

text: Assigning textures and materials within 3D scenes is a tedious and labor-intensive task. In this paper, we present Magic Decorator, a system that automatically generates material suggestions for 3D indoor scenes. To achieve this goal, we introduce local material rules, which describe typical material patterns for a small group of objects or parts, and global aesthetic rules, which account for the harmony among the entire set of colors in a specific scene. Both rules are obtained from collections of indoor scene images. We cast the problem of material suggestion as a combinatorial optimization considering both local material and global aesthetic rules. We have tested our system on various complex indoor scenes. A user study indicates that our system can automatically and efficiently produce a series of visually plausible material suggestions which are comparable to those produced by artists.


title: Efficiency Degradation in Wideband Power Amplifiers

text: This paper addresses the efficiency degradation observed in wideband power amplifiers. It starts by presenting a detailed explanation that relates this observed performance degradation with the terminations at baseband. Then, a comparison between two implemented power amplifiers with the same fundamental and harmonic terminations, but with different baseband networks is presented, showing that an optimized bias network design can improve the observed efficiency degradation.


title: Generating Keyword Queries for Natural Language Queries to Alleviate Lexical Chasm Problem

text: In recent years, the task of reformulating natural language queries has received considerable attention from both industry and academic communities. Because of the lexical chasm problem between natural language queries and web documents, if we directly use natural language queries as inputs for retrieval, the results are usually unsatisfactory. In this work, we formulated the task as a translation problem to convert natural language queries into keyword queries. Since the nature language queries users input are diverse and multi-faceted, general encoder-decoder models cannot effectively handle low-frequency words and out-of-vocabulary words. We propose a novel encoder-decoder method with two decoders: the pointer decoder firstly extracts query terms directly from the source text via copying mechanism, then the generator decoder generates query terms using two attention modules simultaneously considering the source text and extracted query terms. For evaluation and training, we also proposed a semi-automatic method to construct a large-scale dataset about natural language query-keyword query pairs. Experimental results on this dataset demonstrated that our model could achieve better performance than the previous state-of-the-art methods.


title: Customizing Computational Methods for Visual Analytics with Big Data

text: The volume of available data has been growing exponentially, increasing data problem's complexity and obscurity. In response, visual analytics (VA) has gained attention, yet its solutions haven't scaled well for big data. Computational methods can improve VA's scalability by giving users compact, meaningful information about the input data. However, the significant computation time these methods require hinders real-time interactive visualization of big data. By addressing crucial discrepancies between these methods and VA regarding precision and convergence, researchers have proposed ways to customize them for VA. These approaches, which include low-precision computation and iteration-level interactive visualization, ensure real-time interactive VA for big data.


title: EW-SHOT L EARNING

text: A recent approach to few-shot classification called matching networks has demonstrated the benefits of coupling metric learning with a training procedure that mimics test. This approach relies on an attention scheme that forms a distribution over all points in the support set, scaling poorly with its size. We propose a more streamlined approach, prototypical networks, that learns a metric space in which few-shot classification can be performed by computing Euclidean distances to prototype representations of each class, rather than individual points. Our method is competitive with state-of-the-art few-shot classification approaches while being much simpler and more scalable with the size of the support set. We empirically demonstrate the performance of our approach on the Omniglot and miniImageNet datasets. We further demonstrate that a similar idea can be used for zero-shot learning, where each class is described by a set of attributes, and achieve state-ofthe-art results on the Caltech UCSD bird dataset.


title: Setting Lower Bounds on Truthfulness

text: We present general techniques for proving inapproximability results for several paradigmatic truthful multidimensional mechanism design problems. In particular, we demonstrate the strength of our techniques by exhibiting a lower bound of 2 − 1 m for the scheduling problem with m unrelated machines (formulated as a mechanism design problem in the seminal paper of Nisan and Ronen on Algorithmic Mechanism Design). Our lower bound applies to truthful randomized mechanisms, regardless of any computational assumptions on the running time of these mechanisms. Moreover, it holds even for the wider class of truthfulness-in-expectation mechanisms. This lower bound nearly matches the known 1.58606 randomized truthful upper bound for the case of two machines (a non-truthful FPTAS exists). Recently, Daskalakis and Weinberg [17] show that there is a polynomial-time 2approximately optimal Bayesian mechanism for makespan minimization for unrelated machines. We complement this result by showing an appropriate lower bound of 1.25 for deterministic incentive compatible Bayesian mechanisms. We then show an application of our techniques to the workload-minimization problem in networks. We prove our lower bounds for this problem in the inter-domain routing setting presented by Feigenbaum, Papadimitriou, Sami, and Shenker. Finally, we discuss several notions of non-utilitarian fairness (Max-Min fairness, Min-Max fairness, and envy minimization) and show how our techniques can be used to prove lower bounds for these notions. No lower bounds for truthful mechanisms in multidimensional probabilistic settings were previously known.1 ∗Computer Science Department, Technion, Haifa, Israel. ahumu@yahoo.com. †School of Computer Science and Engineering, Hebrew University, Jerusalem, Israel. schapiram@huji.ac.il. The current paper supersedes "Setting Lower Bounds on Truthfulness" that appeared as an extended abstract in the Proceedings of the 18th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA07), pages 1143-1152, 2007. The current version includes a new lower bound result for Bayesian Incentive compatible Mechanisms.


title: A d–q Voltage Droop Control Method With Dynamically Phase-Shifted Phase-Locked Loop for Inverter Paralleling Without Any Communication Between Individual Inverters

text: This paper presents a modified droop control method for equal load sharing of parallel-connected inverters, without any communication between individual inverters. Droop in <italic>d</italic>- and <italic>q</italic>-axis voltages are given depending upon <italic>d</italic>- and <italic>q</italic>-axis currents, respectively. Each inverter works in the voltage control mode, where it controls the filter capacitor voltage. Voltage references of each inverter come from <italic>d</italic>- and <italic>q</italic>-axis voltage droops. This <italic>d</italic>- and <italic>q</italic> -axis voltage droops force the parallel-connected inverters to share equal current and hence equal active and reactive power. A dynamically phase-shifted phase-locked loop (PLL) technique is locally designed for generating phase reference of each inverter. The phase angle between filter capacitor voltage vector and <italic>d</italic>-axis is dynamically adjusted with the change in <italic>q</italic>-axis inverter current to generate the phase reference of each inverter. The strategy has been verified with simulations and experiments and results are presented in this paper.


title: A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning

text: Insertion is a challenging haptic and visual control problem with significant practical value for manufacturing. Existing approaches in the model-based robotics community can be highly effective when task geometry is known, but are complex and cumbersome to implement, and must be tailored to each individual problem by a qualified engineer. Within the learning community there is a long history of insertion research, but existing approaches are typically either too sample-inefficient to run on real robots, or assume access to high-level object features, e.g. socket pose. In this paper we show that relatively minor modifications to an off-the-shelf Deep-RL algorithm (DDPG), combined with a small number of human demonstrations, allows the robot to quickly learn to solve these tasks efficiently and robustly. Our approach requires no modeling or simulation, no parameterized search or alignment behaviors, no vision system aside from raw images, and no reward shaping. We evaluate our approach on a narrowclearance peg-insertion task and a deformable clip-insertion task, both of which include variability in the socket position. Our results show that these tasks can be solved reliably on the real robot in less than 10 minutes of interaction time, and that the resulting policies are robust to variance in the socket position and orientation.


title: LTE in the sky: trading off propagation benefits with interference costs for aerial nodes

text: The popularity of unmanned aerial vehicles has exploded over the last few years, urgently demanding solutions to transfer large amounts of data from the UAV to the ground. Conversely, a control channel to the UAV is desired, in order to safely operate these vehicles remotely. This article analyzes the use of LTE for realizing this downlink data and uplink control. By means of measurements and simulations, we study the impact of interference and path loss when transmitting data to and from the UAV. Two scenarios are considered in which UAVs act as either base stations transmitting in downlink or UEs transmitting in uplink, and their impact on the respective downlink and uplink performance of an LTE ground network is analyzed. Both measurements and simulations are used to quantify such impact for a range of scenarios with varying altitude, distance from the base station, or UAV density. The measurement sets show that signal-to-interference ratio decreases up to 7 dB for UAVs at 150 m compared to ground users. Simulation results show that a UAV density of 10/km2 gives an average degradation of the signal-to-interference ratio of more than 6 dB. It is concluded that interference is going to be a major limiting factor when LTE enabled UAVs are introduced, and that strong technical solutions will have to be found.


title: Scattered data modeling

text: A variety of methods for modeling scattered data are discussed, with an emphasis on two types of data: volumetric and spherical. To demonstrate the performance of the various methods, results from an empirical study using trivariate scattered data are presented. The author's objective is to provide information to aid in selecting a type of method or to form the basis for customizing a method for a particular application.<<ETX>>


title: Benign Osteoblastoma Involving Maxilla: A Case Report and Review of the Literature

text: Background. Osteoblastoma is a rare benign tumor. This tumor is characterized by osteoid and bone formation with the presence of numerous osteoblasts. The lesion is more frequently seen in long bones and rarely involves maxilla and mandible. Due to its clinical and histological similarity with other bone tumors such as osteoid osteoma and fibro-osseous lesions, osteoblastoma presents a diagnostic dilemma. Case Report. Very few cases of osteoblastomas involving maxillofacial region have been reported in the literature. This case report involves osteoblastoma involving right maxilla in an 18-year-old male patient. Following detailed clinical examination, radiological interpretation, and histopathological diagnosis, surgical excision was performed. The patient was followed up for a period of 3 years and was disease free. Summary and Conclusion. Benign osteoblastoma involving jaw bones is a rare tumor. There is a close resemblance of this tumor with other lesions such as fibro-osseous lesions and odontogenic tumors and thus faces a diagnostic challenge. Surgical excision with a long-term follow-up gives good prognosis to this lesion-Benign Osteoblastoma.


title: Almost Optimal Exploration in Multi-Armed Bandits

text: We study the problem of exploration in stochastic Multi-Armed Bandits. Even in the simplest setting of identifying the best arm, there remains a logarithmic multiplicative gap between the known lower and upper bounds for the number of arm pulls required for the task. This extra logarithmic factor is quite meaningful in nowadays large-scale applications. We present two novel, parameterfree algorithms for identifying the best arm, in two di↵erent settings: given a target confidence and given a target budget of arm pulls, for which we prove upper bounds whose gap from the lower bound is only doublylogarithmic in the problem parameters. We corroborate our theoretical results with experiments demonstrating that our algorithm outperforms the state-of-the-art and scales better as the size of the problem increases.


title: Buck-boost converter fed BLDC motor drive for solar PV array based water pumping

text: Solar photovoltaic (SPV) array based water pumping is receiving wide attention now a days because the everlasting solar energy is the best alternative to the conventional energy sources. This paper deals with the utilization of a buck-boost converter in solar PV array based water pumping as an intermediate DC-DC converter between a solar PV array and a voltage source inverter (VSI) in order to achieve the maximum efficiency of the solar PV array and the soft starting of the permanent magnet brushless DC (BLDC) motor by proper control. Consisting of a least number of components and single switch, the buck-boost converter exhibits very good conversion efficiency. Moreover, buck-boost DC-DC converter topology is the only one allowing follow-up of the PV array maximum power point (MPP) regardless of temperature, irradiance, and connected load. A BLDC motor is employed to drive a centrifugal type of water pump because its load characteristic is well matched to the maximum power locus of the PV generator. The transient, dynamic and steady state behaviors of the proposed solar PV array powered buck-boost converter fed BLDC motor driven water pumping system are evaluated under the rapid and slowly varying atmospheric conditions using the sim-power-system toolboxes of the MATLAB/Simulink environment.


title: Event detection from social media: 5W1H analysis on big data

text: Increasing number of social media content shared across the globe in real time creates a fascinating area of research. For most events, social media users act as collective sensors by sharing important information about events of any scale. Due to its real time nature, social media is much quicker to respond to such events relative to conventional news media. This paper proposes an event detection system which provides 5W1H (What, Where, When, Why, Who, How) analysis for each detected event. We make use of a myriad of techniques such as anomaly detection, named entity recognition, automatic summary generation, user link analysis. Our experimental results for the system indicate a faster event detection performance compared to conventional news sources. Event analysis results are also in line with the corresponding news articles about detected events.


title: Persistence and periodicity in a dynamic proximity network

text: The topology of social networks can be understood as being inherently dynamic, with edges having a distinct position in time. Most characterizations of dynamic networks discretize time by converting temporal information into a sequence of network “snapshots” for further analysis. Here we study a highly resolved data set of a dynamic proximity network of 66 individuals. We show that the topology of this network evolves over a very broad distribution of time scales, that its behavior is characterized by strong periodicities driven by external calendar cycles, and that the conversion of inherently continuous-time data into a sequence of snapshots can produce highly biased estimates of network structure. We suggest that dynamic social networks exhibit a natural time scale ∆nat, and that the best conversion of such dynamic data to a discrete sequence of networks is done at this natural rate.


title: Metal-oxide-semiconductor field-effect transistor with a vacuum channel.

text: High-speed electronic devices rely on short carrier transport times, which are usually achieved by decreasing the channel length and/or increasing the carrier velocity. Ideally, the carriers enter into a ballistic transport regime in which they are not scattered. However, it is difficult to achieve ballistic transport in a solid-state medium because the high electric fields used to increase the carrier velocity also increase scattering. Vacuum is an ideal medium for ballistic transport, but vacuum electronic devices commonly suffer from low emission currents and high operating voltages. Here, we report the fabrication of a low-voltage field-effect transistor with a vertical vacuum channel (channel length of ~20 nm) etched into a metal-oxide-semiconductor substrate. We measure a transconductance of 20 nS µm(-1), an on/off ratio of 500 and a turn-on gate voltage of 0.5 V under ambient conditions. Coulombic repulsion in the two-dimensional electron system at the interface between the oxide and the metal or the semiconductor reduces the energy barrier to electron emission, leading to a high emission current density (~1 × 10(5) A cm(-2)) under a bias of only 1 V. The emission of two-dimensional electron systems into vacuum channels could enable a new class of low-power, high-speed transistors.


title: Privacy attitudes and privacy behaviour: A review of current research on the privacy paradox phenomenon

text: Do people really care about their privacy? Surveys show that privacy is a primary concern for citizens in the digital age. On the other hand, individuals reveal personal information for relatively small rewards, often just for drawing the attention of peers in an online social network. This inconsistency of privacy attitudes and privacy behavior is often referred to as the “privacy paradox”. In this paper, we present the results of a review of research literature on the privacy paradox. We analyze studies that provide evidence of a paradoxical dichotomy between attitudes and behavior and studies that challenge the existence of such a phenomenon. The diverse research results are explained by the diversity in research methods, the different contexts and the different conceptualizations of the privacy paradox. We also present several interpretations of the privacy paradox, stemming from social theory, psychology, behavioral economics and, in one case, from quantum theory. We conclude that current research has improved our understanding of the privacy paradox phenomenon. It is, however, a complex phenomenon that requires extensive further research. Thus, we call for synthetic studies to be based on comprehensive theoretical models that take into account the diversity of personal information and the diversity of privacy concerns. We suggest that future studies should use evidence of actual behavior rather than self-reported behavior.


title: GraphBuilder: scalable graph ETL framework

text: Graph abstraction is essential for many applications from finding a shortest path to executing complex machine learning (ML) algorithms like collaborative filtering. Graph construction from raw data for various applications is becoming challenging, due to exponential growth in data, as well as the need for large scale graph processing. Since graph construction is a data-parallel problem, MapReduce is well-suited for this task. We developed GraphBuilder, a scalable framework for graph Extract-Transform-Load (ETL), to offload many of the complexities of graph construction, including graph formation, tabulation, transformation, partitioning, output formatting, and serialization. GraphBuilder is written in Java, for ease of programming, and it scales using the MapReduce model. In this paper, we describe the motivation for GraphBuilder, its architecture, MapReduce algorithms, and performance evaluation of the framework. Since large graphs should be partitioned over a cluster for storing and processing and partitioning methods have significant performance impacts, we develop several graph partitioning methods and evaluate their performance. We also open source the framework at https://01.org/graphbuilder/.


title: Convolutional neural networks for SAR image segmentation

text: Segmentation of Synthetic Aperture Radar (SAR) images has several uses, but it is a difficult task due to a number of properties related to SAR images. In this article we show how Convolutional Neural Networks (CNNs) can easily be trained for SAR image segmentation with good results. Besides this contribution we also suggest a new way to do pixel wise annotation of SAR images that replaces a human expert manual segmentation process, which is both slow and troublesome. Our method for annotation relies on 3D CAD models of objects and scene, and converts these to labels for all pixels in a SAR image. Our algorithms are evaluated on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset which was released by the Defence Advanced Research Projects Agency during the 1990s. The method is not restricted to the type of targets imaged in MSTAR but can easily be extended to any SAR data where prior information about scene geometries can be estimated.


title: Analysis and implementation of software rejuvenation in cluster systems

text: Several recent studies have reported the phenomenon of "software aging", one in which the state of a software system degrades with time. This may eventually lead to performance degradation of the software or crash/hang failure or both. "Software rejuvenation" is a pro-active technique aimed to prevent unexpected or unplanned outages due to aging. The basic idea is to stop the running software, clean its internal state and restart it. In this paper, we discuss software rejuvenation as applied to cluster systems. This is both an innovative and an efficient way to improve cluster system availability and productivity. Using Stochastic Reward Nets (SRNs), we model and analyze cluster systems which employ software rejuvenation. For our proposed time-based rejuvenation policy, we determine the optimal rejuvenation interval based on system availability and cost. We also introduce a new rejuvenation policy based on prediction and show that it can dramatically increase system availability and reduce downtime cost. These models are very general and can capture a multitude of cluster system characteristics, failure behavior and performability measures, which we are just beginning to explore. We then briefly describe an implementation of a software rejuvenation system that performs periodic and predictive rejuvenation, and show some empirical data from systems that exhibit aging


title: Predicting Rare Events In Temporal Domains

text: Temporal data mining aims at finding patterns in historical data. Our work proposes an approach to extract temporal patterns from data to predict the occurrence of target events, such as computer attacks on host networks, or fraudulent transactions in financial institutions. Our problem formulation exhibits two major challenges: 1) we assume events being characterized by categorical features and displaying uneven inter-arrival times; such an assumption falls outside the scope of classical time-series analysis, 2) we assume target events are highly infrequent; predictive techniques must deal with the class-imbalance problem. We propose an efficient algorithm that tackles the challenges above by transforming the event prediction problem into a search for all frequent eventsets preceding target events. The class imbalance problem is overcome by a search for patterns on the minority class exclusively; the discrimination power of patterns is then validated against other classes. Patterns are then combined into a rule-based model for prediction. Our experimental analysis indicates the types of event sequences where target events can be accurately predicted.