title: Visualizing reference patterns for solving memory leaks in Java

abstract: Many Java programmers believe they do not have to worry about memory management because of automatic garbage collection. In fact, many Java programs run out of memory unexpectedly after performing a number of operations. A memory leak in Java is caused when an object that is no longer needed cannot be reclaimed because another object is still referring to it. Memory leaks can be difficult to solve, since the complexity of most programs prevents us from manually verifying the validity of every reference. ::: ::: In this paper we show a new methodology for finding the causes of memory leaks. We have identified a basic memory leak scenario which fits many important cases. In this scenario, we allow the programmer to identify a period of time in which temporary objects are expected to be created and released. Using this information we are able to identify objects that persist beyond this period and the references which are holding on to them. Scaling this methodology to real-world systems brings additional challenges. We propose a novel combination of visual syntax and reference pattern extraction to manage this additional complexity. We also describe how these techniques can be applied to a wider class of memory problems, including the exploration of large data structures. These techniques have been implemented and have been proven successful on large projects.


title: Evolutionary developments of advanced PWR nuclear fuels and cladding materials

abstract: Abstract The evolutionary developments of advanced PWR fuels and cladding materials are explained with outstanding design features of nuclear fuel assembly components and zirconium-base cladding materials. The advanced PWR fuel and cladding materials development processes are also provided along with verification tests, which can be used as guidelines for newcomers planning to develop an advanced fuel for the first time. The up-to-date advanced fuels with the advanced cladding materials may provide a high level of economic utilization and reliable performance even under current and upcoming aggressive operating conditions. To be specific, nuclear fuel vendors may achieve high fuel burnup capability of between 45,000 and 65,000 MWD/MTU batch average, overpower thermal margin of as much as 15% and longer cycle length up to 24 months on the one hand and fuel failure rates of around 10 −6 on the other hand. However, there is still a need for better understanding of grid-to-rod fretting wear mechanisms leading to major PWR fuel defects in the world and subsequently a driving force for developing innovative spacer grid designs with zero fretting wear-induced fuel failure.


title: Web Design Attributes in Building User Trust, Satisfaction, and Loyalty for a High Uncertainty Avoidance Culture

abstract: In this study, we attempt to evaluate the user preferences for web design attributes (i.e., typography, color, content quality, interactivity, and navigation) to determine the trust, satisfaction, and loyalty for uncertainty avoidance cultures. Content quality and navigation have been observed as strong factors in building user trust with e-commerce websites. In contrast, interactivity, color, and typography have been observed as strong determinants of user satisfaction. The most relevant and interesting finding is related to typography, which has been rarely discussed in e-commerce literature. A questionnaire was designed to collect data to corroborate the proposed model and hypotheses. Furthermore, the partial least-squares method was adopted to analyze the collected data from the students who participated in the test ( $n$ = 558). Finally, the results of this study provide strong support to the proposed model and hypotheses. Therefore, all the web design attributes were observed as important design features to develop user trust and satisfaction for uncertainty avoidance cultures. Although both factors seem to be relevant, the relationship between trust and loyalty was observed to be stronger than between satisfaction and loyalty; thus, trust seems to be a stronger determinant of loyalty for risk/high uncertainty avoidance cultures.


title: Designing structurally-sound ornamental curve networks

abstract: We present a computational tool for designing ornamental curve networks---structurally-sound physical surfaces with user-controlled aesthetics. In contrast to approaches that leverage texture synthesis for creating decorative surface patterns, our method relies on user-defined spline curves as central design primitives. More specifically, we build on the physically-inspired metaphor of an embedded elastic curve that can move on a smooth surface, deform, and connect with other curves. We formalize this idea as a globally coupled energy-minimization problem, discretized with piece-wise linear curves that are optimized in the parametric space of a smooth surface. Building on this technical core, we propose a set of interactive design and editing tools that we demonstrate on manually-created layouts and semi-automated deformable packings. In order to prevent excessive compliance, we furthermore propose a structural analysis tool that uses eigenanalysis to identify potentially large deformations between geodesically-close curves and guide the user in strengthening the corresponding regions. We used our approach to create a variety of designs in simulation, validated with a set of 3D-printed physical prototypes.


title: A Wireline Piston Core Barrel for Sampling Cohesionless Sand and Gravel Below the Water Table

abstract: A coring device has been developed to obtain long and minimally disturbed samples of saturated cohesionless sand and gravel. The coring device, which includes a wireline and piston, was developed specifically for use during hollow-stem auger drilling but it also offers possibilities for cable tool and rotary drilling. The core barrel consists of an inner liner made of inexpensive aluminum or plastic tubing, a piston for core recovery, and an exterior steel housing that protects the liner when the core barrel is driven into the aquifer. The core barrel, which is approximately 1.6m (5.6 feet) long, is advanced ahead of the lead auger by hammering at the surface on drill rods that are attached to the core barrel. After the sampler has been driven 1.5m (5 feet), the drill rods are detached and a wireline is used to hoist the core barrel, with the sample contained in the aluminum or plastic liner, to the surface. A vacuum developed by the piston during the coring operation provides good recovery of both the sediment and aquifer fluids contained in the sediment. In the field the sample tubes can be easily split along their length for on-site inspection or they can be capped with the pore water fluids inside and transported to the laboratory. The cores are 5cm (2 inches) in diameter by 1.5m (5 feet) long. Core acquisition to depths of 35m (115 feet), with a recovery greater than 90 percent, has become routine in University of Waterloo aquifer studies. A large diameter (12.7cm [5 inch]) version has also been used successfully. Nearly continuous sample sequences from sand and gravel aquifers have been obtained for studies of sedimentology, hydraulic conductivity, hydrogeochemistry and microbiology.


title: 1P = IW?ACE

abstract: In this paper, it is proven that when both randomization and interaction are allowed, the proofs that can be verified in polynomial time are exactly those proofs that can be generated with polynomial space.


title: Minimum Complexity Echo State Network

abstract: Reservoir computing (RC) refers to a new class of state-space models with a fixed state transition structure (the reservoir) and an adaptable readout form the state space. The reservoir is supposed to be sufficiently complex so as to capture a large number of features of the input stream that can be exploited by the reservoir-to-output readout mapping. The field of RC has been growing rapidly with many successful applications. However, RC has been criticized for not being principled enough. Reservoir construction is largely driven by a series of randomized model-building stages, with both researchers and practitioners having to rely on a series of trials and errors. To initialize a systematic study of the field, we concentrate on one of the most popular classes of RC methods, namely echo state network, and ask: What is the minimal complexity of reservoir construction for obtaining competitive models and what is the memory capacity (MC) of such simplified reservoirs? On a number of widely used time series benchmarks of different origin and characteristics, as well as by conducting a theoretical analysis we show that a simple deterministically constructed cycle reservoir is comparable to the standard echo state network methodology. The (short-term) of linear cyclic reservoirs can be made arbitrarily close to the proved optimal value.


The effects of physical and hormonal treatments on dormancy breaking and the changes in seed coat ultrastructure of Delonix


title: KLEE: Unassisted and Automatic Generation of High-Coverage Tests for Complex Systems Programs

abstract: We present a new symbolic execution tool, KLEE, capable of automatically generating tests that achieve high coverage on a diverse set of complex and environmentally-intensive programs. We used KLEE to thoroughly check all 89 stand-alone programs in the GNU COREUTILS utility suite, which form the core user-level environment installed on millions of Unix systems, and arguably are the single most heavily tested set of open-source programs in existence. KLEE-generated tests achieve high line coverage -- on average over 90% per tool (median: over 94%) -- and significantly beat the coverage of the developers' own hand-written test suite. When we did the same for 75 equivalent tools in the BUSYBOX embedded system suite, results were even better, including 100% coverage on 31 of them. ::: ::: We also used KLEE as a bug finding tool, applying it to 452 applications (over 430K total lines of code), where it found 56 serious bugs, including three in COREUTILS that had been missed for over 15 years. Finally, we used KLEE to crosscheck purportedly identical BUSYBOX and COREUTILS utilities, finding functional correctness errors and a myriad of inconsistencies.


title: A better approximation ratio for the vertex cover problem

abstract: We reduce the approximation factor for the vertex cover to 2 − Θ (1/slogn) (instead of the previous 2 − Θ ln ln n/2ln n obtained by Bar-Yehuda and Even [1985] and Monien and Speckenmeyer [1985]). The improvement of the vanishing factor comes as an application of the recent results of Arora et al. [2004] that improved the approximation factor of the sparsest cut and balanced cut problems. In particular, we use the existence of two big and well-separated sets of nodes in the solution of the semidefinite relaxation for balanced cut, proven by Arora et al. [2004]. We observe that a solution of the semidefinite relaxation for vertex cover, when strengthened with the triangle inequalities, can be transformed into a solution of a balanced cut problem, and therefore the existence of big well-separated sets in the sense of Arora et al. [2004] translates into the existence of a big independent set.


title: A physically-based night sky model

abstract: This paper presents a physically-based model of the night sky for realistic image synthesis. We model both the direct appearance of the night sky and the illumination coming from the Moon, the stars, the zodiacal light, and the atmosphere. To accurately predict the appearance of night scenes we use physically-based astronomical data, both for position and radiometry. The Moon is simulated as a geometric model illuminated by the Sun, using recently measured elevation and albedo maps, as well as a specialized BRDF. For visible stars, we include the position, magnitude, and temperature of the star, while for the Milky Way and other nebulae we use a processed photograph. Zodiacal light due to scattering in the dust covering the solar system, galactic light, and airglow due to light emission of the atmosphere are simulated from measured data. We couple these components with an accurate simulation of the atmosphere. To demonstrate our model, we show a variety of night scenes rendered with a Monte Carlo ray tracer.


title: Review of Research on Vehicles Aerodynamic Drag Reduction Methods

abstract: Recent spikes in fuel prices and concern regarding greenhouse gas emissions, automotive design engineers are faced with the immediate task of introducing more efficient aerodynamic designs vehicles. The aerodynamic drags of a road vehicle is responsible for a large part of the vehicle’s fuel consumption and contribute up to 50% of the total vehicle fuel consumption at highway speeds. Review on the research performance of active and passive flow control on the vehicle aerodynamic drag reduction is reported in this paper. This review intends to provide information on the current approaches and their efficiency in reducing pressure drag of ground vehicles. The review mainly focuses on the methods employed to prevent or delay air flow separation at the rear end of vehicle. Researches carried out by a number of researchers with regard to active and passive flow controls method on vehicle and their effect on aerodynamic drag in terms of drag coefficient (CD) was highlighted. Passive methods i.e. Vortex Generator (VG), spoiler and splitter and active flow controls i.e. steady blowing, suction and air jet are among the methods had been reviewed. In addition several attempts to couple these flow control methods were also reviewed. Several aspects of aerodynamic drag that need for further investigation as to assist for vehicles aerodynamic design and for practical reasons were highlighted. Progressive research on active flow control was observed due to its flexibility for wide range of application without body shape modification.


title: Three-phase Medium Voltage DC Fast Charger based on Single-stage Soft-switching Topology

abstract: This paper presents a 350kW, high-efficiency, three-phase 4.16kV-AC medium voltage(MV) isolated power converter that can be used as a MV DC fast charger for battery electric vehicles using SOOV battery packs and is interoperable with legacy vehicles with 400V battery packs. The proposed high power quality (PF$\geq 0.98$, THD $\leq 5\%$) charging system comprises of three identical power modules, one for each phase with their outputs connected in parallel to deliver the charging power. The converter uses variable switching frequency and a combination of single and double phase shifts to achieve the dual control objective of UPF and ZVS over the entire operating range while minimizing the device current and maintaining the charging current constant. Design guidelines of input and output filters, high frequency tranformer and switching frequency range selection have been presented. Simulation results validate the proposed charging station design and operation.


title: Effect of Online Reviews on Consumer Purchase Behavior

abstract: In order to understand the effect of online reviews on consumer purchase behavior, more than 400 Taobao shops’ online reviews are collected. Based on S-O-R model (Stimulus-Organism-Response Model), this paper studies the influence on consumer purchase behavior according to online reviews of experience goods from a new perspective of consumer learning. Using SPSS 19.0 software for data analysis and assumptions, statistical results show that the positive reviews, describing rating, picture reviews, appended reviews and cumulative reviews have an effect on consumer purchase behavior. The moderate reviews, negative reviews, logistics rating and service rating are not significant in the results. Finally, this paper puts forward suggestions and summary.


title: MOOCs: So Many Learners, So Much Potential ...

abstract: Massive open online courses (MOOCs) have exploded onto the scene, promising to satisfy a worldwide thirst for a high-quality, personalized, and free education. This article explores where MOOCs fit within the e-learning and Artificial Intelligence in Education (AIED) landscape.


A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities


title: RankME: Reliable Human Ratings for Natural Language Generation

abstract: Human evaluation for natural language generation (NLG) often suffers from inconsistent user ratings. While previous research tends to attribute this problem to individual user preferences, we show that the quality of human judgements can also be improved by experimental design. We present a novel rank-based magnitude estimation method (RankME), which combines the use of continuous scales and relative assessments. We show that RankME significantly improves the reliability and consistency of human ratings compared to traditional evaluation methods. In addition, we show that it is possible to evaluate NLG systems according to multiple, distinct criteria, which is important for error analysis. Finally, we demonstrate that RankME, in combination with Bayesian estimation of system quality, is a cost-effective alternative for ranking multiple NLG systems.


title: Comparison of FaaS Orchestration Systems

abstract: Since the appearance of Amazon Lambda in 2014, all major cloud providers have embraced the "Function as a Service" (FaaS) model, because of its enormous potential for a wide variety of applications. As expected (and also desired), the competition is fierce in the serverless world, and includes aspects such as the run-time support for the orchestration of serverless functions. In this regard, the three major production services are currently Amazon Step Functions (December 2016), Azure Durable Functions (June 2017), and IBM Composer (October 2017), still young and experimental projects with a long way ahead. In this article, we will compare and analyze these three serverless orchestration systems under a common evaluation framework. We will study their architectures, programming and billing models, and their effective support for parallel execution, among others. Through a series of experiments, we will also evaluate the run-time overhead of the different infrastructures for different types of workflows.


title: Deep Hierarchical Network With Line Segment Learning for Quantitative Analysis of Facial Palsy

abstract: We propose the deep hierarchical network (DHN) for the quantitative analysis of facial palsy. Facial palsy, also known as Bell’s palsy, is the most common type of facial nerve palsy that results in the loss of muscle control in the affected facial regions. Typical symptoms include facial deformity and facial expression dysfunction. To the best of our best knowledge, all approaches for the automatic detection of facial palsy consider hand-crafted features. This paper reports the first deep-learning-based approach developed for the real-time quantitative analysis of facial palsy. The proposed DHN consists of three component networks: the first detects the subject’s face, the second detects the facial landmarks and line segments on the detected face, and the third detects the local palsy regions. The first component network is built on the YOLO2 detector. The second component network is developed on a fused network architecture that incorporates a line segment learning network for locating the facial landmarks and line segments. The third component network is developed on an object detection network with the line-segment-embedded input that combines the landmarked region and the line segments detected by the second component network. The novelties of this research include: 1) the modification of a state-of-the-art edge detector for extracting the facial line segments; 2) the embedding of the line segment learning for the detection of facial landmarks and local palsy regions; 3) the quantitative description of the facial palsy syndrome intensity; and 4) the release of the first clinically labeled database, the YouTube Facial Palsy (YFP) database. The making of the YFP database solves the issue that previous methods were all evaluated on proprietary databases, making the comparison of different methods extremely difficult. The YFP database includes 32 videos of 21 patients collected from YouTube and labeled by clinic specialists. To enhance the robustness against facial expression variations, we include the CK+ facial expression database in the training. We show that the proposed DHN not only just detects the local palsy regions but also captures the intensity of the facial palsy syndrome over time, enabling the quantitative description of the syndrome. The experiments show that the proposed approach offers an accurate and efficient real-time solution for facial palsy analysis.


title: When Social Bots Attack: Modeling Susceptibility of Users in Online Social Networks

abstract: Social bots are automatic or semi-automatic computer programs that mimic humans and/or human behavior in online social networks. Social bots can attack users (targets) in online social networks to pursue a variety of latent goals, such as to spread information or to influence targets. Without a deep understanding of the nature of such attacks or the susceptibility of users, the potential of social media as an instrument for facilitating discourse or democratic processes is in jeopardy. In this paper, we study data from the Social Bot Challenge 2011 - an experiment conducted by the WebEcologyProject during 2011 - in which three teams implemented a number of social bots that aimed to influence user behavior on Twitter. Using this data, we aim to develop models to (i) identify susceptible users among a set of targets and (ii) predict users’ level of susceptibility. We explore the predictiveness of three different groups of features (network, behavioral and linguistic features) for these tasks. Our results suggest that susceptible users tend to use Twitter for a conversational purpose and tend to be more open and social since they communicate with many different users, use more social words and show more affection than non-susceptible users.


title: CRISPR Screens Uncover Genes that Regulate Target Cell Sensitivity to the Morphogen Sonic Hedgehog

abstract: Summary To uncover regulatory mechanisms in Hedgehog (Hh) signaling, we conducted genome-wide screens to identify positive and negative pathway components and validated top hits using multiple signaling and differentiation assays in two different cell types. Most positive regulators identified in our screens, including Rab34 , Pdcl , and Tubd1 , were involved in ciliary functions, confirming the central role for primary cilia in Hh signaling. Negative regulators identified included Megf8 , Mgrn1 , and an unannotated gene encoding a tetraspan protein we named Atthog . The function of these negative regulators converged on Smoothened (SMO), an oncoprotein that transduces the Hh signal across the membrane. In the absence of Atthog , SMO was stabilized at the cell surface and concentrated in the ciliary membrane, boosting cell sensitivity to the ligand Sonic Hedgehog (SHH) and consequently altering SHH-guided neural cell-fate decisions. Thus, we uncovered genes that modify the interpretation of morphogen signals by regulating protein-trafficking events in target cells.


title: A Large Public Corpus of Web Tables containing Time and Context Metadata

abstract: The Web contains vast amounts of HTML tables. Most of these tables are used for layout purposes, but a small subset of the tables is relational, meaning that they contain structured data describing a set of entities [2]. As these relational Web tables cover a very wide range of different topics, there is a growing body of research investigating the utility of Web table data for completing cross-domain knowledge bases [6], for extending arbitrary tables with additional attributes [7, 4], as well as for translating data values [5]. The existing research shows the potentials of Web tables. However, comparing the performance of the different systems is difficult as up till now each system is evaluated using a different corpus of Web tables and as most of the corpora are owned by large search engine companies and are thus not accessible to the public. In this poster, we present a large public corpus of Web tables which contains over 233 million tables and has been extracted from the July 2015 version of the CommonCrawl. By publishing the corpus as well as all tools that we used to extract it from the crawled data, we intend to provide a common ground for evaluating Web table systems. The main difference of the corpus compared to an earlier corpus that we extracted from the 2012 version of the CommonCrawl as well as the corpus extracted by Eberius et al. [3] from the 2014 version of the CommonCrawl is that the current corpus contains a richer set of metadata for each table. This metadata includes table-specific information such as table orientation, table caption, header row, and key column, but also context information such as the text before and after the table, the title of the HTML page, as well as timestamp information that was found before and after the table. The context information can be useful for recovering the semantics of a table [7]. The timestamp information is crucial for fusing time-depended data, such as alternative population numbers for a city [8].


title: Conversations in context: a Twitter case for social media systems design

abstract: Conversations are the lifeblood of collaborative communities. Social media like microblogging tool Twitter have great potential for supporting these conversations. However, just studying the role of these media from a tool perspective is not sufficient. To fully unlock their power, they need to examined from a socio-technical perspective. We introduce a socio-technical context framework which can be used to analyze the role of systems of tools supporting goal-oriented conversations. Central to this framework is the communicative workflow loop, which is grounded in the Language/Action Perspective. We show how socio-technical conversation contexts can be used to match the communicative requirements of collaborative communities with enabling tool functionalities. This social media systems design process is illustrated with a case on Twitter.


title: Magnetically Isolated Gate Driver With Leakage Inductance Immunity

abstract: This letter presents the design of a magnetically isolated gate driver with high immunity to leakage inductance. The proposed gate driver (PGD) is developed based on a bipolar totem-pole gate driver (noninverting) located on the secondary side of the coupling transformer. It is able to drive a MOSFET/IGBT from standard CMOS to TTL output and down to LSTTL level. It also achieves large duty cycle ratio and small input to output delay and provides reliable isolation. In this letter, the PGD is analyzed and verified experimentally. The design guidelines are also provided including design considerations.


title: The Association between SNPs and a Quantitative Trait: Power Calculation

abstract: A power calculation for a study with a quantitative outcome requires information on the outcome distribution under the alternative hypothesis. Researchers face challenges when they concisely specify alternative distributions in genetic studies because power depends on genotype frequencies and the average effect of each genotype. In GWAS, investigators evaluate hundreds of thousands of associations; therefore it is unrealistic to specify gene frequencies and gene effects for each test and some simplification is needed. Software packages are available to calculate power, but many of them have limited flexibility and / or may have a steep learning curve. In this review, we describe to researchers and graduate students the essentials of a power calculation for testing for an association between a quantitative trait and genotypes. In addition, we provide them with the codes of the different available software packages—free and commercial—to calculate this power. The calculations can be carried out using virtually any computer language that computes the cumulative distribution function of a non-central F-distribution.


title: Video abstraction using density-based clustering algorithm

abstract: The exponential growth in the number of surveillance videos makes the search and retrieval of their contents an extensive, time-consuming, and tedious task. Video abstraction is a general solution to alleviate this problem by generating a short and concise version of the original video. The existing abstraction approaches have commonly relied on global characteristics of visual content and neglected the local details of video frames. This paper presents an enhanced video abstraction approach called Density-based Surveillance video abstraction (DbSva) to generate a static short-length video. The novelty of DbSva is (a) to integrate the advantages of both the global and local features of video contents by fusion and (b) to employ the DENsity-based CLUstEring algorithm (DENCLUE) to significantly improve the quality of abstract videos. Utilizing fusion and the DENCLUE algorithm resulted in the extraction of more informative parts of the videos and increased the robustness of the proposed approach to handle large-scale and noisy videos with no further tuning of the input parameters. A number of qualitative and quantitative experiments support the effectiveness of the proposed approach in generating higher-quality abstract videos compared to the other approaches.


title: Community Computing: Comparisons between Rural and Urban Societies Using Mobile Phone Data

abstract: We present a comparative analysis of the behavioral dynamics of rural and urban societies using four years of mobile phone data from all 1.4M subscribers within a small country. We use information from communication logs and top up denominations to characterize attributes such as socioeconomic status and region. We show that rural and urban communities differ dramatically not only in terms of personal network topologies, but also in terms of inferred behavioral characteristics such as travel. We confirm the hypothesis for behavioral adaptation, demonstrating that individuals change their patterns of communication to increase the similarity with their new social environment. To our knowledge, this is the first comprehensive comparison between regional groups of this size.


title: Developing Web Services Choreography Standards – The Case of REST vs. SOAP 1

abstract: This paper presents a case study of the development of standards in the area of cross-organizational workflows based on web services. We discuss two opposing types of standards: those based on SOAP, with tightly coupled designs similar to remote procedure calls, and those based on REST, with loosely coupled designs similar to the navigating of web links. We illustrate the standardization process, clarify the technical underpinnings of the conflict, and analyze the interests of stakeholders. The decision criteria for each group of stakeholders are discussed. Finally, we present implications for both the workflow and the wider Internet communities.


Tutorial : Image Segmentation


title: Performance analysis of the IEEE 802.1 ethernet audio/video bridging standard

abstract: Switched Ethernet is widely used for all kinds of applications. However, for demanding multimedia streaming applications in a fully-loaded network, legacy Ethernet is not the best choice due to its limited Quality-of-Service (QoS) support. The new specification of the IEEE 802.1 Audio/Video Bridging (AVB) standard, an extension to legacy Ethernet, provides the QoS features needed for multimedia streaming: Time synchronized low latency streaming services and bandwidth reservation on Layer-2. In this work, we study and analyze the AVB standard based on a simulation approach to verify the specified constraints and to determine the feasibility of the mechanisms in a switched Ethernet network. We use the simulation tool OMNeT++ and extend the existing INET-framework to support all the required protocols specified in the IEEE 802.1 AVB standard.


title: Behavior-based Malware Detection with Quantitative Data Flow Analysis

abstract: We study the usefulness of quantitative data flow analyses for behavior-based malware detection. To this end, we propose a generic model to represent system behavior, i.e. traces of system calls, as sequences of quantifiable data flows that together form a Quantitative Data Flow Graph (QDFG). We operationalize this model in four different ways for highly accurate, robust, and efficient malware detection. We do so by both identifying patterns of known malicious behavior in unknown QDFGs and by profiling malware with graph metrics over QDFGs. Using large data sets, we demonstrate that quantitative data flow analysis yields better detection effectiveness than non-quantitative analysis.


title: Low-Power CMOS Equalizer Design for 20-Gb/s Systems

abstract: The power consumption of wireline circuits has become increasingly more critical as the pin count and data rate rise. This paper describes a power scaling methodology and a new half-rate speculative architecture for decision-feedback equalizers (DFEs) to relax the speed-power trade-offs. Designed in 90-nm CMOS technology, a 20-Gb/s prototype consisting of a linear equalizer and a one-tap DFE compensates for the loss of an 18-in FR4 trace while drawing 40 mW from a 1-V supply.


A Clustering Approach to Unsupervised Attack Detection in Collaborative Recommender Systems


title: Implementing a Rating-Based Item-to-Item in SQL

abstract: User personalization and profiling is key to many succesful Web sites. Consider that there is considerable free content on the Web, but comparatively few tools to help us organize or mine such content for specific purposes. One solution is to ask users to rate resources so that they can help each other find better content: we call this rating-based collaborative filtering. This paper presents a database-driven approach to item-to-item collaborative filtering which is both easy to implement and can support a full range of applications.


title: Ins/gps integration architectures

abstract: Abstract : An inertial navigation system (INS) exhibits relatively low noise from second to second, but tends to drift over time. Typical aircraft inertial navigation errors grow at rates between 1 and 10 nmi/h (1.8 to 18 km/h) of operation. In contrast, Global Positioning System (GPS) errors are relatively noisy from second to second, but exhibit no long-term drift. Using both of these systems is superior to using either alone. Integrating the information from each sensor results in a navigation system that operates like a drift-free INS. There are further benefits to be gained depending on the level at which the information is combined. This presentation will focus on integration architectures, including loosely coupled, tightly coupled, and deeply integrated configurations. (Deep integration is trademarked by Draper Laboratory.) The advantages and disadvantages of each level of integration will be listed. Examples of current and future systems will be cited.


title: A 3.6kW single-ended resonant inverter for induction heating applications

abstract: The single-ended (SE) resonant inverter is a type of class E parallel resonant inverter and popularly used in many IH applications due to its lower cost structure and relatively high efficiency. However its maximum power rating should be limited because the resonant voltage of SE resonant inverter increases as its power increases. Consequently the maximum power rating of SE resonant inverter should be limited up to around 2kW. This paper proposes an interleaved single-ended resonant inverter for the induction heating applications. The proposed inverter can provide two times higher output power than the conventional single-ended resonant inverter by the alternative operation of two inverters. A burst mode control enhances the power control range from very light load to full load and can improve efficiency.


Proposed New N-Multilevel Family of Topologies for T-Type Inverter


title: Data Streams and Data Stream Management Systems and Languages

abstract: The massive usage of data streams dates back to artificial satellite information processing systems and to their commercial application in the early 1970s, such as in telecommunications switching, land monitoring, meteorological surveillance, etc. Today they are extensively used in monitoring systems applications based on wired and wireless sensor networks, in social networks, and in the Internet of Things [20]. The main functional goals of data stream management systems (DSMSs) are as follows: (a) results must be pushed to the output promptly and eagerly while input tuples continue to arrive and (b) because of the unbounded and massive nature of data streams, all past tuples cannot be memorized for future use. Only synopses can be kept in memory and the rest must be discarded.


title: M2RML: Multidimensional to RDF Mapping Language

abstract: This research is about design and implementation of a middleware between an RDF application (as a client) and an OLAP server which manages multidimensional data. At the heart of the middleware is a software layer which accepts a query from the client and returns as the answer an RDF dataset. This software is an implementation of a mapping language from multidimensional data to RDF, or M2RML. The RDF dataset is a 'slice' of the data cube as defined in the W3C's RDF Data Cube Vocabulary. The limitations of the Data Cube Vocabulary are discussed, and options to overcome these limitations are proposed.


title: Extracellular vesicles as an emerging mechanism of cell-to-cell communication

abstract: The concept that extracellular vesicles may act as paracrine/endocrine effectors is based on the evidence that they are able to transport bioactive molecules between cells, either within a defined microenvironment or remotely, by entering the biologic fluids. Extracellular vesicles, including exosomes and microvesicles, may deliver lipids and various functional transcripts, released from the cell of origin, to target cells. Since extracellular vesicles contain defined patterns of mRNA, microRNA, long non-coding RNA, and occasionally genomic DNA, they may transfer genetic information which induces transient or persistent phenotypic changes in recipient cells. In this review, we will discuss potential physiologic and pathological implications of extracellular vesicles, as well as the diagnostic and therapeutic opportunities that they may provide.


title: Normative curves of fetal nasal bone length for the ethnic Chinese population

abstract: Objective ::: The purpose of this study is to determine the association between fetal nasal bone length (NBL) and gestational age (GA), biparietal diameter (BPD) and head circumference (HC) in women undergoing prenatal assessments and Down syndrome screening.


title: Computer analysis of Van Gogh's complementary colours

abstract: Traditionally, the analysis of visual arts is performed by human art experts only. The availability of advanced artificial intelligence techniques makes it possible to support art experts in their judgement of visual art. In this article currently available image-analysis techniques are applied. Our aim is (1) to determine how successful the usage of complementary colours was in the oeuvre of Vincent Van Gogh and (2) whether this characteristic may make his paintings identifiable in time. It is commonly acknowledged that, especially in his French period, Van Gogh started employing complementary colours to emphasize contours of objects or parts of scenes. This article proposes a new method called MECOCO to measure complementary-colour usage in a painting by combining an opponent-colour space representation with Gabor filtering. To achieve the aim, (1) we defined a novel measure called the opponency value that quantifies the usage of complementary-colour transitions in a painting and (2) we studied Van Gogh's painting style. MECOCO's analysis of a dataset of 145 digitised and colour-calibrated oil-on-canvas paintings confirms the global transition pattern of complementary colours in Van Gogh's paintings as generally acknowledged by art experts. In addition, MECOCO also provides an objective and quantifiable way to support the analysis of colours in individual paintings.


title: Communication through coherence with inter-areal delays

abstract: The communication-through-coherence (CTC) hypothesis proposes that anatomical connections are dynamically rendered effective or ineffective through the presence or absence of rhythmic synchronization, in particular in the gamma and beta bands. The original CTC statement proposed that uni-directional communication is due to rhythmic entrainment with an inter-areal delay and a resulting non-zero phase relation, whereas bi-directional communication is due to zero-phase synchronization. Recent studies found that inter-areal gamma-band synchronization entails a non-zero phase lag. We therefore modify the CTC hypothesis and propose that bi-directional cortical communication is realized separately for the two directions by uni-directional CTC mechanisms entailing delays in both directions. We review evidence suggesting that inter-areal influences in the feedforward and feedback directions are segregated both anatomically and spectrally.


title: Face Alignment at 3000 FPS via Regressing Local Binary Features

abstract: This paper presents a highly efficient, very accurate regression approach for face alignment. Our approach has two novel components: a set of local binary features, and a locality principle for learning those features. The locality principle guides us to learn a set of highly discriminative local binary features for each facial landmark independently. The obtained local binary features are used to jointly learn a linear regression for the final output. Our approach achieves the state-of-the-art results when tested on the current most challenging benchmarks. Furthermore, because extracting and regressing local binary features is computationally very cheap, our system is much faster than previous methods. It achieves over 3, 000 fps on a desktop or 300 fps on a mobile phone for locating a few dozens of landmarks.


title: Antibacterial activity of large-area monolayer graphene film manipulated by charge transfer

abstract: Graphene has attracted increasing attention for potential applications in biotechnology due to its excellent electronic property and biocompatibility. Here we use both Gram-positive Staphylococcus aureus (S. aureus) and Gram-negative Escherichia coli (E. coli) to investigate the antibacterial actions of large-area monolayer graphene film on conductor Cu, semiconductor Ge and insulator SiO2. The results show that the graphene films on Cu and Ge can surprisingly inhibit the growth of both bacteria, especially the former. However, the proliferation of both bacteria cannot be significantly restricted by the graphene film on SiO2. The morphology of S. aureus and E. coli on graphene films further confirms that the direct contact of both bacteria with graphene on Cu and Ge can cause membrane damage and destroy membrane integrity, while no evident membrane destruction is induced by graphene on SiO2. From the viewpoint of charge transfer, a plausible mechanism is proposed here to explain this phenomenon. This study may provide new insights for the better understanding of antibacterial actions of graphene film and for the better designing of graphene-based antibiotics or other biomedical applications.


An Introduction to Genetic Algorithms and Evolution


title: SmartAuth: dynamic context fingerprinting for continuous user authentication

abstract: As recent incidents have shown, weak passwords are a severe security risk for authenticating users and granting access to protected resources. Additionally, strong passwords score low on usability, especially on mobile devices. In this work, we present SmartAuth, a scalable context-aware authentication framework built on top of OpenAM, a state-of-practice identity and access management suite. It uses adaptive and dynamic context fingerprinting based on Hoeffding trees to continuously ascertain whether a user's identity is authentic or not, and it respects privacy preferences by adopting consent-driven use of context information. We assess our approach from both an offensive and defensive security perspective. Our results show that dynamic context fingerprinting has good potential for a zero-interaction authentication scheme, with a minimal performance overhead compared to traditional authentication schemes.


title: A Review on Recent Advances in Doppler Radar Sensors for Noncontact Healthcare Monitoring

abstract: This paper reviews recent advances in biomedical and healthcare applications of Doppler radar that remotely detects heartbeat and respiration of a human subject. In the last decade, new front-end architectures, baseband signal processing methods, and system-level integrations have been proposed by many researchers in this field to improve the detection accuracy and robustness. The advantages of noncontact detection have drawn interests in various applications, such as energy smart home, baby monitor, cardiopulmonary activity assessment, and tumor tracking. While many of the reported systems were bench-top prototypes for concept verification, several portable systems and integrated radar chips have been demonstrated. This paper reviews different architectures, baseband signal processing, and system implementations. Validations of this technology in a clinical environment will also be discussed.


title: A Molecular Phylogeny of Reptiles

abstract: The classical phylogeny of living reptiles pairs crocodilians with birds, tuataras with squamates, and places turtles at the base of the tree. New evidence from two nuclear genes, and analyses of mitochondrial DNA and 22 additional nuclear genes, join crocodilians with turtles and place squamates at the base of the tree. Morphological and paleontological evidence for this molecular phylogeny is unclear. Molecular time estimates support a Triassic origin for the major groups of living reptiles.


title: Waveguide slot antennas for circularly polarized radiated field

abstract: We present a new waveguide slot configuration able to radiate a circular polarization with a very low axial ratio. This configuration is mainly intended as a circularly polarized radiating element to be used in an array. Both left-hand and right-hand circular polarization can be independently obtained and therefore this configuration could be used to realize a polarization agile antenna. The proposed configuration consists of two very closely spaced radiating slots, so a specialized method of moments code has been developed to analyze, in a very effective way, the near-field interaction between such slots. Our method of moments code has been validated against a commercial finite-element method code, and then used to design a number of different circularly polarized radiating elements.


title: Identifying the Intent of a User Query Using Support Vector Machines

abstract: In this paper we introduce a high-precision query classification method to identify the intent of a user query given that it has been seen in the past based on informational, navigational, and transactional categorization. We propose using three vector representations of queries which, using support vector machines, allow past queries to be classified by user's intents. The queries have been represented as vectors using two factors drawn from click-through data: the time users take to review the documents they select and the popularity (quantity of preferences) of the selected documents. Experimental results show that time is the factor that yields higher precision in classification. The experiments shown in this work illustrate that the proposed classifiers can effectively identify the intent of past queries with high-precision.


title: A brain computer interface for smart home control

abstract: The aim of this study is to control home devices using a non invasive brain computer interface (BCI). The Electroencephalographic signals (EEG) recorded from the brain activity using the Emotiv EPOCH headset are interfaced with the help of mouse emulator to a graphical user interface (GUI) on the computer screen. The user will use this GUI to control various devices in a smart home. This application will be very useful especially for people with special needs.


title: X-band antenna design for Indonesian ground surveillance man pack radar

abstract: In this paper, an X Band antenna for ground surveillance manpack radar was designed with 15 × 38 cm dimension using RT/Duroid 5880 substrate. The array consisted of 64 patches antenna with a carved slit to obtain a horizontal polarization. The gap between antenna feed were evaluated and the results are that that antenna gain and side lobe level will decrease as the gap became larger. This design has 200 MHz bandwidth with gain of 25.2 dB and side lobe level of −22.7 dB.


title: Social Exchange in Organizations: Perceived Organizational Support, Leader-Member Exchange, and Employee Reciprocity

abstract: Whether Leader-Member Exchange (LMX) is a unidimensional or a multidimensional construct was assessed through the development and validation of a multidimensional measure. Item analysis involving 302 working students, followed by construct and criterion-related validation using 249 employees representing two organizations resulted in a multidimensional LMX scale. The results provided support for the affect, loyalty, and contribution dimensions identified by Dienesch and Liden (1986), as well as a fourth dimension, professional respect.


title: Detection and Classification of a Moving Object in a Video Stream

abstract: In this paper we present a new method for detecting and classifying moving objects into humans and vehicles from a video surveillance scene. In this approach, the moving objects are firstly detected from the background using a background subtraction technique. Background subtraction algorithms are implemented in a MATLAB environment. A comparison for all the algorithms was made to determine which background subtraction algorithm performs better with the proposed classifying algorithm. The algorithms were then tested using more than a video and many frames of the video was tested. Secondly, edge detection of moving objects was performed using Canny or Prewitt operations, while bounding boxes were implemented over the moving objects. Edge detection and bounding boxes were used before the classification step to simplify the classification. Finally, classifying the moving object into humans and vehicles was accomplished by finding the height-width ratio of the bounding box around the moving object in each frame and estimating the speed of the moving object from two consecutive frames in the video stream. The results found were fairly good and the wrong classification was due to the bounding boxes not correctly covering the moving objects. The background subtraction step and the classification step were tested using different video sequences. A comparison was made between the combination of each background subtraction technique and the classification algorithm; the false classification results are given. Although the proposed classification algorithm in this paper is simple and easy to be implemented, the results obtained are very satisfactory and the accuracy is very good


Analyzing the Impact of Service Accessibility Enhancement on Urban Energy Efficiency Based on GIS Network Analysis


title: Mentally simulated movements in virtual reality : does Fitts ' s law hold in motor imagery ?

abstract: This study was designed to investigate mentally simulated actions in a virtual reality environment. Naive human subjects (n = 15) were instructed to imagine themselves walking in a three-dimensional virtual environment toward gates of different apparent widths placed at three different apparent distances. Each subject performed nine blocks of six trials in a randomised order. The response time (reaction time and mental walking time) was measured as the duration between an acoustic go signal and a motor signal produced by the subject. There was a combined effect on response time of both gate width and distance. Response time increased for decreasing apparent gate widths when the gate was placed at different distances. These results support the notion that mentally simulated actions are governed by central motor rules.


title: CRF-CNN: Modeling Structured Information in Human Pose Estimation

abstract: Deep convolutional neural networks (CNN) have achieved great success. On the other hand, modeling structural information has been proved critical in many vision problems. It is of great interest to integrate them effectively. In a classical neural network, there is no message passing between neurons in the same layer. In this paper, we propose a CRF-CNN framework which can simultaneously model structural information in both output and hidden feature layers in a probabilistic way, and it is applied to human pose estimation. A message passing scheme is proposed, so that in various layers each body joint receives messages from all the others in an efficient way. Such message passing can be implemented with convolution between features maps in the same layer, and it is also integrated with feedforward propagation in neural networks. Finally, a neural network implementation of end-to-end learning CRF-CNN is provided. Its effectiveness is demonstrated through experiments on two benchmark datasets.


title: Smart traffic lights switching and traffic density calculation using video processing

abstract: Congestion in traffic is a serious problem nowadays. Although it seems to pervade everywhere, mega cities are the ones most affected by it. And it's ever increasing nature makes it imperative to know the road traffic density in real time for better signal control and effective traffic management. There can be different causes of congestion in traffic like insufficient capacity, unrestrained demand, large Red Light delays etc. While insufficient capacity and unrestrained demand are somewhere interrelated, the delay of respective light is hard coded and not dependent on traffic. Therefore the need for simulating and optimizing traffic control to better accommodate this increasing demand arises. In recent years, video monitoring and surveillance systems have been widely used in traffic management for traveler's information, ramp metering and updates in real time. The traffic density estimation and vehicle classification can also be achieved using video monitoring systems. This paper presents the method to use live video feed from the cameras at traffic junctions for real time traffic density calculation using video and image processing. It also focuses on the algorithm for switching the traffic lights according to vehicle density on road, thereby aiming at reducing the traffic congestion on roads which will help lower the number of accidents. In turn it will provide safe transit to people and reduce fuel consumption and waiting time. It will also provide significant data which will help in future road planning and analysis. In further stages multiple traffic lights can be synchronized with each other with an aim of even less traffic congestion and free flow of traffic.


title: Problematic Internet use in Chinese adolescents and its relation to psychosomatic symptoms and life satisfaction

abstract: BackgroundProblematic Internet use (PIU) is a growing problem in Chinese adolescents. Little is known about associations of PIU with physical and psychological health. This study was designed to investigate the prevalence of PIU and to test the relationships between PIU and psychosomatic symptoms and life satisfaction among adolescents in mainland China.MethodsA cross-sectional survey was conducted comprising a large representative sample of 17 599 students in eight cities of China. PIU was assessed by the 20-item Young Internet Addiction Test (YIAT). The Multidimensional Sub-health Questionnaire of Adolescents and the Multidimensional Students' Life Satisfaction Scale were administered to obtain information on psychosomatic symptoms and life satisfaction. Demographics and Internet usage patterns were also collected. Logistic regression was used to assess the effects of PIU on psychosomatic symptoms and life satisfaction.ResultsApproximately 8.1% of subjects showed PIU. Adolescents with PIU were associated with males, high school students, urban, eastern and western areas, upper self-report family economy, service type mostly used for entertainment and relieving loneliness and more frequency of Internet use. Compared with normal Internet users, adolescents with PIU were more likely to suffer from psychosomatic symptoms (P < 0.001), including lack of physical energy (P < 0.001), physiological dysfunction (P < 0.001), weakened immunity (P < 0.001), emotional symptoms (P < 0.001), behavioural symptoms (P < 0.001) and social adaptation problems (P < 0.001). Adolescents with PIU had lower scores on total and all dimensions of life satisfaction (all P < 0.001). Adjusted for the demographic and Internet-related factors, there was positive significant relationship between PIU and psychosomatic symptoms, but negatively related to life satisfaction.ConclusionsPIU is common among Chinese students, and PIU was significantly associated with psychosomatic symptoms and life satisfaction. Effective measures are needed to prevent the spread of this problem and interventions to prevent the effects of PIU on psychosomatic symptoms and life satisfaction should be conducted as early as possible.


title: Automatic Scheme Selection for Toolkit Hex Meshing

abstract: Current hexahedral mesh generation techniques rely on a set of meshing tools, which when combined with geometry decomposition leads to an adequate mesh generation process. Of these tools, sweeping tends to be the workhorse algorithm, accounting for at least 50% of most meshing applications. Constraints which must be met for a volume to be sweepable are derived, and it is proven that these constraints are necessary but not sufficient conditions for sweepability. This paper also describes a new algorithm for detecting extruded or sweepable geometries. This algorithm, based on these constraints, uses topological and local geometric information, and is more robust than feature recognition-based algorithms. A method for computing sweep dependencies in volume assemblies is also given. The auto sweep detect and sweep grouping algorithms have been used to reduce interactive user time required to generate all-hexahedral meshes by filtering out non-sweepable volumes needing further decomposition and by allowing concurrent meshing of independent sweep groups. Parts of the auto sweep detect algorithm have also been used to identify independent sweep paths, for use in volume-based interval assignment.


title: Convolutional neural networks for text hashing

abstract: Hashing, as a popular approximate nearest neighbor search, has been widely used for large-scale similarity search. Recently, a spectrum of machine learning methods are utilized to learn similarity-preserving binary codes. However, most of them directly encode the explicit features, keywords, which fail to preserve the accurate semantic similarities in binary code beyond keyword matching, especially on short texts. Here we propose a novel text hashing framework with convolutional neural networks. In particular, we first embed the keyword features into compact binary code with a locality preserving constraint. Meanwhile word features and position features are together fed into a convolutional network to learn the implicit features which are further incorporated with the explicit features to fit the pretrained binary code. Such base method can be successfully accomplished without any external tags/labels, and other three model variations are designed to integrate tags/labels. Experimental results show the superiority of our proposed approach over several state-of-the-art hashing methods when tested on one short text dataset as well as one normal text dataset.


title: Digital Beamforming on Receive: Techniques and Optimization Strategies for High-Resolution Wide-Swath SAR Imaging

abstract: Synthetic Aperture Radar (SAR) is a well-proven imaging technique for remote sensing of the Earth. However, conventional SAR systems are not capable of fulfilling the increasing demands for improved spatial resolution and wider swath coverage. To overcome these inherent limitations, several innovative techniques have been suggested which employ multiple receive-apertures to gather additional information along the synthetic aperture. These digital beamforming (DBF) on receive techniques are reviewed with particular emphasis on the multi-aperture signal processing in azimuth and a multi-aperture reconstruction algorithm is presented that allows for the unambiguous recovery of the Doppler spectrum. The impact of Doppler aliasing is investigated and an analytic expression for the residual azimuth ambiguities is derived. Further, the influence of the processing on the signal-to-noise ratio (SNR) is analyzed, resulting in a pulse repetition frequency (PRF) dependent factor describing the SNR scaling of the multi-aperture beamforming network. The focus is then turned to a complete high-resolution wide-swath SAR system design example which demonstrates the intricate connection between multi-aperture azimuth processing and the system architecture. In this regard, alternative processing approaches are compared with the multi-aperture reconstruction algorithm. In a next step, optimization strategies are discussed as pattern tapering, prebeamshaping-on-receive, and modified processing algorithms. In this context, the analytic expressions for both the residual ambiguities and the SNR scaling factor are generalized to cascaded beamforming networks. The suggested techniques can moreover be extended in many ways. Examples discussed are a combination with ScanSAR burst mode operation and the transfer to multistatic sparse array configurations.


title: Scientific Skills as Core Competences in Medical Education: What do medical students think?

abstract: Background: Scientific excellence is one of the most fundamental underpinnings of medical education and its relevance is unquestionable. To be involved in research activities enhances students' critical thinking and problem-solving capacities, which are mandatory competences for new achievements in patient care and consequently to the improvement of clinical practice. Purposes: This work aimed to study the relevance given by Portuguese medical students to a core of scientific skills, and their judgment about their own ability to execute those skills. Methods: A cross-sectional study was conducted on students attending the first, fourth and sixth years of medical course in the same period. An assessment istrument, exploring the importance given by Portuguese medical students to scientific skills in high school, to clinical practice and to their own ability to execute them, was designed, adapted and applied specifically to this study. Results: Students' perceptions were associated with gender, academic year...


title: Performance Analysis of a Two-Diode model of PV cell for PV based generation in MATLAB

abstract: The increase in concern for carbon emission and reduction in natural resources for conventional power generation, the renewable energy based generation such as Wind, Photovoltaic (PV), and Fuel cell has gained importance. Out of which the PV based generation has gained significance due to availability of abundant sunlight. As the Solar power conversion is a low efficient conversion process, accurate and reliable, modeling of solar cell is important. Due to the non-linear nature of diode based PV model, the accurate design of PV cell is a difficult task. A built-in model of PV cell is available in Simscape, Simelectronics library, Matlab. The equivalent circuit parameters have to be computed from data sheet and incorporated into the model. However it acts as a stiff source when implemented with a MPPT controller. Henceforth, to overcome this drawback, in this paper a two-diode model of PV cell is implemented in Matlab Simulink with reduced four required parameters along with similar configuration of the built-in model. This model allows incorporation of MPPT controller. The I–V and P-V characteristics of these two models are investigated under different insolation levels. A PV based generation system feeding a DC load is designed and investigated using these two models and further implemented with MPPT based on P&O technique.


title: Extracting Cylinders in Full 3D Data Using a Random Sampling Method and the Gaussian Image

abstract: Abstract This paper presents a new method for extractingcylinders from an unorganized set of 3D points. Theoriginality of this approach is to separate the ex-traction problem into two distinct steps. The ﬁrststep consists in extracting a constrained plane in theGaussian image. This yields a subset of 3D pointsalong with a direction. In the second step, cylindersof known direction are extracted in the correspond-ing subset of points. Robustness is achieved by theuse of a random sampling method in both steps.Experimental results showing the extraction ofpipes in digitized industrial environments are pre-sented. 1 Introduction The main principle of as-built CAD modeling andreverse engineering is to ﬁnd a set of geometricprimitives properly describing 3D data correspond-ing to a real scene. The 3D scene is typically pro-vided by a range scanner. Since several views areusually needed, the data often consist of a set ofregistered and merged range images. In the worstcase, the structure of each range image has beenlost and the 3D data therefore consist of an unor-ganized set of 3D points. Obviously, for real data,the scanning process also introduces noise on thepoints. Moreover, when dealing with large digitizedindustrial scenes, the density of data points is notuniform [7, 5]. However, the geometric primitivespresent in the scene are usually surfaces or curvesof simple types, such as planes, cylinders, cones,spheres or tori.Geometric primitive extraction is an importantproblem of model-based vision. An interestinggeneral framework for geometric primitive extrac-tion was described in [13, 14], generalizing theRANSAC method [2]. In their approach, the ex-traction of a primitive is performed using randomsampling over the set of points. Each sample con-tains exactly the minimum number of points neces-sary to deﬁne an instance of the primitive — e.g.,three points for a plane, four points for a sphere.The extraction is then performed using an generaloptimization process, i.e. by iteratively consider-ing the primitive deﬁned by a random sample andchoosing the primitivemaximizing a merit function.This process therefore requires a method for deﬁn-ing the primitive instance from every minimum setof points. It is straightforward for algebraic surfacesof ordergiven points, since it amounts to thecomputation of a determinant (see the ’exact ﬁt’ in[11]). In 3D, this includes the cases of the plane, thesphere and the quadric — using three, four and nineVMV 2001 Stuttgart, Germany, November 21–23, 2001


title: Multi-sensorial virtual reality and augmented human food interaction

abstract: In the field of virtual reality (VR) research, media technologies to create a realistic feeling of being present in a real/virtual world by duplicating multi-sensory information have been studied over a long period. Recently, technologies for multi-sensory feedbacks achieved a major breakthrough by utilizing cross-modal interactions. By changing sensory stimuli through only one modality using these technologies, the impression from our experience can be modified significantly. These novel technologies have a great potential in changing our food consumption experience and behavior. For example, "MetaCookie" is a flavor augmentation system that enables us to change the perceived taste of a cookie by overlaying visual and olfactory information onto a real cookie. "Augmented Satiety" is a system that enables us to control the perception of satiety and food intake implicitly by changing the apparent volume of food with augmented reality and computer vision techniques. This paper introduces such novel techniques that augment our eating experience by using multimodal VR techniques and discusses the future of Human Food Interaction.


title: Matching Convolutional Neural Networks without Priors about Data

abstract: We propose an extension of Convolutional Neural Networks (CNNs) to graph-structured data, including strided convolutions and data augmentation on graphs. Our method matches the accuracy of state-of-the-art CNNs when applied on images, without any prior about their 2D regular structure. On fMRI data, we obtain a significant gain in accuracy compared with existing graph-based alternatives.


title: The ABC Ontology and Model

abstract: This paper describes the latest version of the ABC metadata model. This model has been developed within the Harmony international digital library project to provide a common conceptual model to facilitate interoperability between metadata vocabularies from different domains. This updated ABC model is the result of collaboration with the CIMI consortium whereby earlier versions of the ABC model were applied to metadata descriptions of complex objects provided by CIMI museums and libraries. The result is a metadata model with more logically grounded time and entity semantics. Based on this model we have been able to build a metadata repository of RDF descriptions and a search interface which is capable of more sophisticated queries than less-expressive, object-centric metadata models will allow.


title: Phocomelia and additional anomalies in two sisters

abstract: Two daughters of non-consanguineous normal parents had phocomelia of both lower extremities with 4-toed feet. The older sister also had phocomelia of the left upper extremity with 5 finger rays; she died immediately after birth. Autopsy disclosed a congenital diaphragmatic hernia, common mesentery and agenesis of the gallbladder, and normal female genitalia. In addition, the younger sister showed a bony skull defect, diastasis recti, agenesis of the uterus and agenesis or atresia of the vagina, hypoplasia of the sacrum and hypo/dysplasia of the pelvic bones. Her growth and mental development were normal. The patterns of anomalies of the two sisters do not fit into any of the syndromes featuring phocomelia; there was no prenatal exposure to thalidomide or any other possible teratogen.


title: Forest change detection from Sentinel-1 and ALOS-2 satellite images

abstract: This research presents the performance of the recently launched C-band Sentinel-1 and L-band ALOS-2 satellite missions for detecting forest clear-cuts and thinning in the winter season in coniferous and deciduous forests within Estonia. SAR data were acquired from September 2014 to April 2015 to analyze the cross-polarized backscatter dynamics over 76 stands before and after the logging event. Both clear-cuts and thinning treatments were considered with stand size ranging from 0.11–6.44 ha and compared to the in situ reference data. The results show that the accuracy of logging detection is influenced by the weather conditions as well as the size of the stand. Both Sentinel-1 and ALOS-2 provide reliable forest clear-cut monitoring and are suitable for an operational change detection service for forest stands larger than 0.5 ha.


title: The Planar Hamiltonian Circuit Problem is NP-Complete

abstract: We consider the problem of determining whether a planar, cubic, triply-connected graph G has a Hamiltonian circuit. We show that this problem is NP-complete. Hence the Hamiltonian circuit problem for this class of graphs, or any larger class containing all such graphs, is probably computationally intractable.


title: Robust high capacity audio steganography using modulo operator

abstract: A secure audio steganography technique is introduced in this paper. Here modulo operator is used for hiding target string. The embedding as well as extracting process is of two steps which provides more robustness in this method. During preprocessing the hexadecimal equivalent of target string is calculated by taking four bits at a time. That increases capacity of cover media. Modulo operator is used during embedding and the adjustment is done in such a way so that the distortion becomes less which increases imperceptibility. The quality of experimental result is analyzed by SNR and also compared with standard LSB and HLLAS technique. Bits per sample is also calculated which shows more efficiency of the proposed technique.


title: Composition of a New Process to Meet Agile Needs Using Method Engineering

abstract: The need of developing a new software engineering process to allow the quick prototyping of some robotic applications and meet the requests by some companies for a development process that was shorter than PASSI, gave us the opportunity of applying our studies on the assembling of a new SEP by reusing parts (called method fragments) from other processes. In this paper we discuss our approach that, starting from the method engineering paradigm, adapts and extends it considering specific agent-oriented issues like the multi-agent system meta-model. The final result of our experiment (Agile PASSI) is presented together with the requirements that motivated its structure.


title: Direct Manipulation Interfaces

abstract: Direct manipulation has been lauded as a good form of interface design, and some interfaces that have this property have been well received by users. In this article we seek a cognitive account of both the advantages and disadvantages of direct manipulation interfaces. We identify two underlying phenomena that give rise to the feeling of directness. One deals with the information processing distance between the user's intentions and the facilities provided by the machine. Reduction of this distance makes the interface feel direct by reducing the effort required of the user to accomplish goals. The second phenomenon concerns the relation between the input and output vocabularies of the interface language. In particular, direct manipulation requires that the system provide representations of objects that behave as if they are the objects themselves. This provides the feeling of directness of manipulation.


title: Mechanics of the Human Hamstring Muscles during Sprinting

abstract: PURPOSE ::: An understanding of hamstring mechanics during sprinting is important for elucidating why these muscles are so vulnerable to acute strain-type injury. The purpose of this study was twofold: first, to quantify the biomechanical load (specifically, musculotendon strain, velocity, force, power, and work) experienced by the hamstrings across a full stride cycle; and second, to determine how these parameters differ for each hamstring muscle (i.e., semimembranosus (SM), semitendinosus (ST), biceps femoris long head (BF), biceps femoris short head (BF)). ::: ::: ::: METHODS ::: Full-body kinematics and ground reaction force data were recorded simultaneously from seven subjects while sprinting on an indoor running track. Experimental data were integrated with a three-dimensional musculoskeletal computer model comprised of 12 body segments and 92 musculotendon structures. The model was used in conjunction with an optimization algorithm to calculate musculotendon strain, velocity, force, power, and work for the hamstrings. ::: ::: ::: RESULTS ::: SM, ST, and BF all reached peak strain, produced peak force, and formed much negative work (energy absorption) during terminal swing. The biomechanical load differed for each hamstring muscle: BF exhibited the largest peak strain, ST displayed the greatest lengthening velocity, and SM produced the highest peak force, absorbed and generated the most power, and performed the largest amount of positive and negative work. ::: ::: ::: CONCLUSIONS ::: As peak musculotendon force and strain for BF, ST, and SM occurred around the same time during terminal swing, it is suggested that this period in the stride cycle may be when the biarticular hamstrings are at greatest injury risk. On this basis, hamstring injury prevention or rehabilitation programs should preferentially target strengthening exercises that involve eccentric contractions performed with high loads at longer musculotendon lengths.


An Optimum Modified Bit Plane Splicing LSB Algorithm for Secret Data Hiding


title: The American Sign Language Lexicon Video Dataset

abstract: The lack of a written representation for American sign language (ASL) makes it difficult to do something as commonplace as looking up an unknown word in a dictionary. The majority of printed dictionaries organize ASL signs (represented in drawings or pictures) based on their nearest English translation; so unless one already knows the meaning of a sign, dictionary look-up is not a simple proposition. In this paper we introduce the ASL lexicon video dataset, a large and expanding public dataset containing video sequences of thousands of distinct ASL signs, as well as annotations of those sequences, including start/end frames and class label of every sign. This dataset is being created as part of a project to develop a computer vision system that allows users to look up the meaning of an ASL sign. At the same time, the dataset can be useful for benchmarking a variety of computer vision and machine learning methods designed for learning and/or indexing a large number of visual classes, and especially approaches for analyzing gestures and human communication.


title: An Empirical Examination of the Effects of Web Personalization at Different Stages of Decision Making

abstract: Personalization agents are incorporated in many Web sites to tailor content and interfaces for individual users. In contrast to the proliferation of personalized Web services worldwide, empirical research on the effects of Web personalization is scant. How does exposure to personalized offers affect subsequent product consideration and choice outcome? Drawing on literature in human-computer interaction (HCI) and user behavior, this research examines the effect of three major elements of Web personalization strategies on users' information processing through different decision-making stages: personalized content quality, feature overlapping among alternatives, and personalized message framing. These elements can be manipulated by a firm during implemention of its personalization strategy. A study using a personalized ringtone download Web site was conducted. The findings provide empirical evidence of the effects of Web personalization. In particular, when users are forming their consideration sets, the age...


title: Robust photometric stereo via low-rank matrix completion and recovery

abstract: We present a new approach to robustly solve photometric stereo problems. We cast the problem of recovering surface normals from multiple lighting conditions as a problem of recovering a low-rank matrix with both missing entries and corrupted entries, which model all types of non-Lambertian effects such as shadows and specularities. Unlike previous approaches that use Least-Squares or heuristic robust techniques, our method uses advanced convex optimization techniques that are guaranteed to find the correct low-rank matrix by simultaneously fixing its missing and erroneous entries. Extensive experimental results demonstrate that our method achieves unprecedentedly accurate estimates of surface normals in the presence of significant amount of shadows and specularities. The new technique can be used to improve virtually any photometric stereo method including uncalibrated photometric stereo.


The incidence of dermatophytes in Denmark.


title: Which Factors Explain Employees ’ Adherence to Information Security Policies ? An Empirical Study

abstract: Research in socio-technical factors in computer security has traditionally focused on employees and their work practice within the premises of the organization. However, with universal access to computing and the diverse means of connecting such devices to each another and to the global Internet, work carried out has shifted outside one central physical location to encompass a variety of possible points-of-access that include homes, modern cafes, and public libraries. Given the ubiquity of wireless devices used for last-hop access to the Internet from home, we look at the security of home wireless networks. In this work, we identify the variables that affect the decision of home wireless network users to implement security features on their networks. Our study is based on the protection motivation theory. A survey was conducted on 189 home users to identify and characterize predictors that differentiate between users who secure their home wireless networks and those who don’t. Results of the analysis identified the following variables as significant: perceived severity, response efficacy, self efficacy, and response cost.


title: Approximation Trees: Statistical Stability in Model Distillation

abstract: This paper examines the stability of learned explanations for black-box predictions via model distillation with decision trees. One approach to intelligibility in machine learning is to use an understandable `student' model to mimic the output of an accurate `teacher'. Here, we consider the use of regression trees as a student model, in which nodes of the tree can be used as `explanations' for particular predictions, and the whole structure of the tree can be used as a global representation of the resulting function. However, individual trees are sensitive to the particular data sets used to train them, and an interpretation of a student model may be suspect if small changes in the training data have a large effect on it. In this context, access to outcomes from a teacher helps to stabilize the greedy splitting strategy by generating a much larger corpus of training examples than was originally available. We develop tests to ensure that enough examples are generated at each split so that the same splitting rule would be chosen with high probability were the tree to be re trained. Further, we develop a stopping rule to indicate how deep the tree should be built based on recent results on the variability of Random Forests when these are used as the teacher. We provide concrete examples of these procedures on the CAD-MDD and COMPAS data sets.


Andromeda : Observation-Level and Parametric Interaction for Exploratory Data Analysis


title: Network Analysis on Safety Culture and Worker‘s Behaviour: A Forest of All Minimum Spanning Trees

abstract: In this paper safety culture and worker’s are considered, all together, as a complex system and ::: statistically represented in the form of correlation network among their characteristics. We show that the current practice, based on a minimal spanning tree (MST), to filter the information contained in the network is not robust.A robust filter based on the forest of all possible MSTs is then proposed and used to analyze the network. For practical purpose, an algorithm will be provided to find the forest.The advantages of the proposed filter compared to the MST-based filter will be illustrated first before we use it in the case of Malaysia manufacturing industry. Some important results that will be useful for the management will be highlighted.


title: Program obfuscation: a quantitative approach

abstract: Despite the recent advances in the theory underlying obfuscation, there still is a need to evaluate the quality of practical obfuscating transformations more quickly and easily. This paper presents the first steps toward a comprehensive evaluation suite consisting of a number of deobfuscating transformations and complexity metrics that can be readily applied on existing and future transformations in the domain of binary obfuscation. In particular, a framework based on software complexity metrics measuring four program properties: code, control flow, data and data flow is suggested. A number of well-known obfuscating and deobfuscating transformations are evaluated based upon their impact on a set of complexity metrics. This enables us to quantitatively evaluate the potency of the (de)obfuscating transformations.


title: Data Extraction for Deep Web Using WordNet

abstract: Our survey shows that the techniques used in data extraction from deep webs need to be improved to achieve the efficiency and accuracy of automatic wrappers. Further investigations indicate that the development of a lightweight ontological technique using existing lexical database for English (WordNet) is able to check the similarity of data records and detect the correct data region with higher precision using the semantic properties of these data records. The advantages of this method are that it can extract three types of data records, namely, single-section data records, multiple-section data records, and loosely structured data records, and it also provides options for aligning iterative and disjunctive data items. Experimental results show that our technique is robust and performs better than the existing state-of-the-art wrappers. Tests also show that our wrapper is able to extract data records from multilingual web pages and that it is domain independent.


title: A Comparison between Concept Maps, Mind Maps, Conceptual Diagrams, and Visual Metaphors as Complementary Tools for Knowledge Construction and Sharing

abstract: In this article, Novak's concept mapping technique is compared to three other types of visualization formats, namely mind maps, conceptual diagrams, and visual metaphors. The application parameters and the respective advantages and disadvantages of each format for learning and knowledge sharing are reviewed and discussed. It is argued that the combination of these four visualization types can play to the strength of each one. The article then provides real-life examples from such a use in undergraduate and graduate university teaching. The results provide first indications that the different visualization formats can be used in complementary ways to enhance motivation, attention, understanding and recall. The implications for a complementary use of these visualization formats in class room and meeting contexts are discussed and a future research agenda in this domain is articulated.


title: A social tag clustering method based on common co-occurrence group similarity

abstract: Social tagging systems are widely applied in Web 2.0. Many users use these systems to create, organize, manage, and share Internet resources freely. However, many ambiguous and uncontrolled tags produced by social tagging systems not only worsen users’ experience, but also restrict resources’ retrieval efficiency. Tag clustering can aggregate tags with similar semantics together, and help mitigate the above problems. In this paper, we first present a common co-occurrence group similarity based approach, which employs the ternary relation among users, resources, and tags to measure the semantic relevance between tags. Then we propose a spectral clustering method to address the high dimensionality and sparsity of the annotating data. Finally, experimental results show that the proposed method is useful and efficient.


title: Internet Addiction: Metasynthesis of 1996-2006 Quantitative Research

abstract: Abstract This study reports the results of a meta-analysis of empirical studies on Internet addiction published in academic journals for the period 1996–2006. The analysis showed that previous studies have utilized inconsistent criteria to define Internet addicts, applied recruiting methods that may cause serious sampling bias, and examined data using primarily exploratory rather than confirmatory data analysis techniques to investigate the degree of association rather than causal relationships among variables. Recommendations are provided on how researchers can strengthen this growing field of research.


title: Cutting circles and polygons from area-minimizing rectangles

abstract: A set of circles, rectangles, and convex polygons are to be cut from rectangular design plates to be produced, or from a set of stocked rectangles of known geometric dimensions. The objective is to minimize the area of the design rectangles. The design plates are subject to lower and upper bounds of their widths and lengths. The objects are free of any orientation restrictions. If all nested objects fit into one design or stocked plate the problem is formulated and solved as a nonconvex nonlinear programming problem. If the number of objects cannot be cut from a single plate, additional integer variables are needed to represent the allocation problem leading to a nonconvex mixed integer nonlinear optimization problem. This is the first time that circles and arbitrary convex polygons are treated simultaneously in this context. We present exact mathematical programming solutions to both the design and allocation problem. For small number of objects to be cut we compute globally optimal solutions. One key idea in the developed NLP and MINLP models is to use separating hyperplanes to ensure that rectangles and polygons do not overlap with each other or with the circles. Another important idea used when dealing with several resource rectangles is to develop a model formulation which connects the binary variables only to the variables representing the center of the circles or the vertices of the polytopes but not to the non-overlap or shape constraints. We support the solution process by symmetry breaking constraints. In addition we compute lower bounds, which are constructed by a relaxed model in which each polygon is replaced by the largest circle fitting into that polygon. We have successfully applied several solution techniques to solve this problem among them the Branch&Reduce Optimization Navigator (BARON) and the LindoGlobal solver called from GAMS, and, as described in Rebennack et al. [21], a column enumeration approach in which the columns represent the assignments. Good feasible solutions are computed within seconds or minutes usually during preprocessing. In most cases they turn out to be globally optimal. For up to 10 circles, we prove global optimality up to a gap of the order of 10-8 in short time. Cases with a modest number of objects, for instance, 6 circles and 3 rectangles, are also solved in short time to global optimality. For test instances involving non-rectangular polygons it is difficult to obtain small gaps. In such cases we are content to obtain gaps of the order of 10%.


title: Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation

abstract: Unsupervised domain adaptation has caught appealing attentions as it facilitates the unlabeled target learning by borrowing existing well-established source domain knowledge. Recent practice on domain adaptation manages to extract effective features by incorporating the pseudo labels for the target domain to better solve cross-domain distribution divergences. However, existing approaches separate target label optimization and domain-invariant feature learning as different steps. To address that issue, we develop a novel Graph Adaptive Knowledge Transfer (GAKT) model to jointly optimize target labels and domain-free features in a unified framework. Specifically, semi-supervised knowledge adaptation and label propagation on target data are coupled to benefit each other, and hence the marginal and conditional disparities across different domains will be better alleviated. Experimental evaluation on two cross-domain visual datasets demonstrates the effectiveness of our designed approach on facilitating the unlabeled target task learning, compared to the state-of-the-art domain adaptation approaches.


title: MeSH Up: effective MeSH text classification for improved document retrieval

abstract: Motivation: Controlled vocabularies such as the Medical Subject Headings (MeSH) thesaurus and the Gene Ontology (GO) provide an efficient way of accessing and organizing biomedical information by reducing the ambiguity inherent to free-text data. Different methods of automating the assignment of MeSH concepts have been proposed to replace manual annotation, but they are either limited to a small subset of MeSH or have only been compared with a limited number of other systems. ::: ::: Results: We compare the performance of six MeSH classification systems [MetaMap, EAGL, a language and a vector space model-based approach, a K-Nearest Neighbor (KNN) approach and MTI] in terms of reproducing and complementing manual MeSH annotations. A KNN system clearly outperforms the other published approaches and scales well with large amounts of text using the full MeSH thesaurus. Our measurements demonstrate to what extent manual MeSH annotations can be reproduced and how they can be complemented by automatic annotations. We also show that a statistically significant improvement can be obtained in information retrieval (IR) when the text of a user's query is automatically annotated with MeSH concepts, compared to using the original textual query alone. ::: ::: Conclusions: The annotation of biomedical texts using controlled vocabularies such as MeSH can be automated to improve text-only IR. Furthermore, the automatic MeSH annotation system we propose is highly scalable and it generates improvements in IR comparable with those observed for manual annotations. ::: ::: Contact: trieschn@ewi.utwente.nl ::: ::: Supplementary information: Supplementary data are available at Bioinformatics online.


title: Lead user analyses for the development of new industrial products

abstract: Recently, a "lead user" concept has been proposed for new product development in fields subject to rapid change von Hippel [von Hippel, E. 1986. Lead users: A source of novel product concepts. Management Sci.32 791-805.]. In this paper we integrate market research within this lead user methodology and report a test of it in the rapidly evolving field of computer-aided systems for the design of printed circuit boards PC-CAD. In the test, lead users were successfully identified and proved to have unique and useful data regarding both new product needs and solutions responsive to those needs. New product concepts generated on the basis of lead user data were found to be strongly preferred by a representative sample of PC-CAD users. We discuss strengths and weaknesses of this first empirical test of the lead user methodology, and suggest directions for future research.


title: Resource-constrained reasoning using a reasoner composition approach

abstract: To increase the interoperability and accessibility of data in sensor-rich systems, there has been a recent proliferation of the use of Semantic Web technologies in sensor-rich systems. Quite a range of such applications have emerged, such as hazard monitoring and rescue, context-aware computing, environmental monitoring, field studies, internet of things, and so on. These systems often assume a centralized paradigm for data processing, which does not always hold in reality especially when the systems are deployed in a hostile environment. At runtime, the infrastructure of systems deployed in such an environment is also prone to interference or damage, causing part of the infrastructure to have limited network connection or even to be detached from the rest. A solution to such a problem would be to push the intelligence, such as semantic reasoning, down to the device layer. A key enabler for such a solution is to run semantic reasoning on resourceconstrained devices. This paper shows how reasoner composition (i.e. to automatically adjust a reasoning approach to preserve only a “well-suited” amount of reasoning for a given ontology) can achieve resource-efficient semantic reasoning. Two novel reasoner composition algorithms are introduced and implemented. Evaluation indicates that the reasoner composition algorithms greatly reduce the resources required for OWL reasoning, potentially facilitating greater semantic reasoning on sensor devices.


title: LabelMe video: Building a video database with human annotations

abstract: Currently, video analysis algorithms suffer from lack of information regarding the objects present, their interactions, as well as from missing comprehensive annotated video databases for benchmarking. We designed an online and openly accessible video annotation system that allows anyone with a browser and internet access to efficiently annotate object category, shape, motion, and activity information in real-world videos. The annotations are also complemented with knowledge from static image databases to infer occlusion and depth information. Using this system, we have built a scalable video database composed of diverse video samples and paired with human-guided annotations. We complement this paper demonstrating potential uses of this database by studying motion statistics as well as cause-effect motion relationships between objects.


Cognitive Engineering: Issues in User-Centered System Design