title: Toward a homogenization of academic social sites: a longitudinal study of profiles in Academia.edu, Google Scholar Citations and ResearchGate

abstract: Purpose ::: ::: ::: ::: ::: The purpose of this paper is to analyze the distribution of profiles from academic social networking sites according to disciplines, academic statuses and gender, and detect possible biases with regard to the real staff distribution. In this way, it intends to know whether these academic places tend to become specialized sites or, on the contrary, there is a homogenization process. ::: ::: ::: ::: ::: Design/methodology/approach ::: ::: ::: ::: ::: To this purpose, the evolution of profiles of one organization (Consejo Superior de Investigaciones Cientificas) in three major academic social sites (Academia.edu, Google Scholar Citations and ResearchGate) through six quarterly samples since April 2014 to September 2015 are tracked. ::: ::: ::: ::: ::: Findings ::: ::: ::: ::: ::: Longitudinal results show important disciplinary biases but with strong increase of new profiles form different areas. They also suggest that these virtual spaces are gaining more stability and they tend toward a equilibrate environment. ::: ::: ::: ::: ::: Originality/value ::: ::: ::: ::: ::: This is the first longitudinal study of profiles from three major academic social networking sites and it allows to shed light on the future of these platforms’ populations.


Dynamic Programming Treatment of the Travelling Salesman Problem


title: Psychological Stress and Disease

abstract: A cosmetic composition for use in the treatment of hair. The cosmetic composition contains a conditioning agent and the improvement resides in the conditioning agent being a mixture of (i) a silicone polyether and (ii) an amine functional siloxane polymer. The amine functional siloxane polymer has the formula:R3-z'QzSiO[R2'SiO]x[R'QSiO]ySiQzR3-z'.A method of treating hair is also described in which the mixture is applied to hair for the purpose of improving wet and dry combing and imparting durable conditioning benefits to the hair.


title: Sparse submodular probabilistic PCA

abstract: We propose a novel approach for sparse probabilistic principal component analysis, that combines a low rank representation for the latent factors and loadings with a novel sparse variational inference approach for estimating distributions of latent variables subject to sparse support constraints. Inference and parameter estimation for the resulting model is achieved via expectation maximization with a novel variational inference method for the E-step that induces sparsity. We show that this inference problem can be reduced to discrete optimal support selection. The discrete optimization is submodular, hence, greedy selection is guaranteed to achieve 1-1/e fraction of the optimal. Empirical studies indicate eectiveness of the proposed approach for the recovery of a parsimonious decomposition as compared to established baseline methods. We also evaluate our method against state-of-the-art methods on high dimensional fMRI data, and show that the method performs as well as or better than other methods.


title: From Big Data to Big Projects: A Step-by-Step Roadmap

abstract: While technologies to build and run big data projects have started to mature and proliferate over the last couple of years, exploiting all potentials of big data is still at a relatively early stage. In fact, building effective big data projects inside organizations is hindered by the lack of a clear data-driven and analytical roadmap to move businesses and organizations from an opinion-operated era where humans skills are a necessity to a data-driven and smart era where big data analytics plays a major role in discovering unexpected insights in the oceans of data routinely generated or collected. This paper provides a solid and well-founded methodology for organizations to build big data projects and reap the most rewards out of their data. It covers all aspects of big data project implementation, from data collection to final project evaluation. In each stage of the process, we introduce different sets of platforms and tools in order to assist IT professionals and managers in gaining a comprehensive understanding of the methods and technologies involved and in making the best use of them. We also complete the picture by illustrating the process through different real-world big data projects implementations.


title: Mining process models with non-free-choice constructs

abstract: Process mining aims at extracting information from event logs to capture the business process as it is being executed. Process mining is particularly useful in situations where events are recorded but there is no system enforcing people to work in a particular way. Consider for example a hospital where the diagnosis and treatment activities are recorded in the hospital information system, but where health-care professionals determine the "careflow." Many process mining approaches have been proposed in recent years. However, in spite of many researchers' persistent efforts, there are still several challenging problems to be solved. In this paper, we focus on mining non-free-choice constructs, i.e., situations where there is a mixture of choice and synchronization. Although most real-life processes exhibit non-free-choice behavior, existing algorithms are unable to adequately deal with such constructs. Using a Petri-net-based representation, we will show that there are two kinds of causal dependencies between tasks, i.e., explicit and implicit ones. We propose an algorithm that is able to deal with both kinds of dependencies. The algorithm has been implemented in the ProM framework and experimental results shows that the algorithm indeed significantly improves existing process mining techniques.


title: Instantaneously Trained Neural Networks

abstract: This paper presents a review of instantaneously trained neural networks (ITNNs). These networks trade learning time for size and, in the basic model, a new hidden node is created for each training sample. Various versions of the corner-classification family of ITNNs, which have found applications in artificial intelligence (AI), are described. Implementation issues are also considered.


title: A Novel 3D Cell Array Architecture for Terra-Bit NAND Flash Memory

abstract: A novel 3D flash cell array architecture, called "hybrid 3D", is proposed to provide the distinctive low address selection method of stacked channels, suitable for conventional NAND page operation. The strings are composed of GAA type selector and double gate type cells, and their key characters were verified independently. The GAA selectors showed excellent and uniform switching character, and double gate MANOS cells were expected to provide enough program window and acceptable reliability for MLC. Extendibility of hybrid 3D was rigorously estimated within the acceptable range of channel stacking and word line scaling, where 2 Tb NAND flash memory would be available just by 16 channel stacks.


title: Simultaneous Wireless Information and Power Transfer in Modern Communication Systems

abstract: Energy harvesting for wireless communication networks is a new paradigm that allows terminals to recharge their batteries from external energy sources in the surrounding environment. A promising energy harvesting technology is wireless power transfer where terminals harvest energy from electromagnetic radiation. Thereby, the energy may be harvested opportunistically from ambient electromagnetic sources or from sources that intentionally transmit electromagnetic energy for energy harvesting purposes. A particularly interesting and challenging scenario arises when sources perform simultaneous wireless information and power transfer (SWIPT), as strong signals not only increase power transfer but also interference. This article provides an overview of SWIPT systems with a particular focus on the hardware realization of rectenna circuits and practical techniques that achieve SWIPT in the domains of time, power, antennas, and space. The article also discusses the benefits of a potential integration of SWIPT technologies in modern communication networks in the context of resource allocation and cooperative cognitive radio networks.


title: Identifying Cell Subpopulations and Their Genetic Drivers from Single-Cell RNA-Seq Data Using a Biclustering Approach

abstract: Single-cell RNA-Seq (scRNA-Seq) has attracted much attention recently because it allows unprecedented resolution into cellular activity; the technology, therefore, has been widely applied in studying cell heterogeneity such as the heterogeneity among embryonic cells at varied developmental stages or cells of different cancer types or subtypes. A pertinent question in such analyses is to identify cell subpopulations as well as their associated genetic drivers. Consequently, a multitude of approaches have been developed for clustering or biclustering analysis of scRNA-Seq data. In this article, we present a fast and simple iterative biclustering approach called "BiSNN-Walk" based on the existing SNN-Cliq algorithm. One of BiSNN-Walk's differentiating features is that it returns a ranked list of clusters, which may serve as an indicator of a cluster's reliability. Another important feature is that BiSNN-Walk ranks genes in a gene cluster according to their level of affiliation to the associated cell cluster, making the result more biologically interpretable. We also introduce an entropy-based measure for choosing a highly clusterable similarity matrix as our starting point among a wide selection to facilitate the efficient operation of our algorithm. We applied BiSNN-Walk to three large scRNA-Seq studies, where we demonstrated that BiSNN-Walk was able to retain and sometimes improve the cell clustering ability of SNN-Cliq. We were able to obtain biologically sensible gene clusters in terms of GO term enrichment. In addition, we saw that there was significant overlap in top characteristic genes for clusters corresponding to similar cell states, further demonstrating the fidelity of our gene clusters.


title: A Study for Texture Feature Extraction of High-Resolution Satellite Images Based on a Direction Measure and Gray Level Co-Occurrence Matrix Fusion Algorithm

abstract: To address the problem of image texture feature extraction, a direction measure statistic that is based on the directionality of image texture is constructed, and a new method of texture feature extraction, which is based on the direction measure and a gray level co-occurrence matrix (GLCM) fusion algorithm, is proposed in this paper. This method applies the GLCM to extract the texture feature value of an image and integrates the weight factor that is introduced by the direction measure to obtain the final texture feature of an image. A set of classification experiments for the high-resolution remote sensing images were performed by using support vector machine (SVM) classifier with the direction measure and gray level co-occurrence matrix fusion algorithm. Both qualitative and quantitative approaches were applied to assess the classification results. The experimental results demonstrated that texture feature extraction based on the fusion algorithm achieved a better image recognition, and the accuracy of classification based on this method has been significantly improved.


title: 'Learning to live with OCD is a little mantra I often repeat': understanding the lived experience of obsessive-compulsive disorder (OCD) in the contemporary therapeutic context.

abstract: Objectives ::: While there has been an abundance of quantitative studies that examine the clinical features and treatment modalities of obsessive-compulsive disorder (OCD), only a few qualitative research studies examining the experience of OCD have been documented. Our objectives were to explore and understand psychosocial aspects of OCD and to provide qualitative accounts of the condition and its treatment rather than concentrating on its psychopathology. We also wanted to locate the role cognitive behavioural therapy (CBT) played in the condition for our participants. ::: ::: Design ::: Data for the study came from a series of nine semi-structured interviews carried out with individuals who self-identified as having OCD. Participants were recruited through two leading UK-based OCD charities. ::: ::: Methods ::: We used interpretative phenomenological analysis (IPA) to analyse the accounts and participants gave feedback as to the validity of the themes in early stages of analysis. ::: ::: Results ::: We report two superordinate themes – Having OCD (with subordinate themes ‘wanting to be normal and fit it’, ‘failing at life’ and ‘loving and hating OCD’) and The Impact of Therapy (with subordinate themes of ‘wanting therapy’, ‘finding the roots’ and ‘a better self’). ::: ::: Conclusions ::: Having OCD as a condition meant that individuals experienced a sense of overwhelming personal failure matched against age appropriate life cycle goals. This crisis of the self was bolstered by public and self-stigma about the condition. While clinical diagnosis and therapeutic interventions were significant, participants reported dialectical tensions experienced with OCD, pointing to the complexity of psychological functioning in the condition. ::: ::: Practitioner Points ::: Participants experienced a ‘deficit identity’ as a result of OCD, impacting on self-esteem and self-confidence. ::: While participants valued a medical diagnosis of OCD, there was ambivalence in ‘letting go’ of OCD behaviours. ::: Some participants experienced CBT as an intervention which prevented them telling their OCD story. ::: Participants valued the therapeutic relationship, especially in understanding and talking through the origins of OCD.


title: ENVELOP Antenna: A Class of Very Low Profile UWB Directive Antennas for Radar and Communication Diversity Applications

abstract: In this paper we present the concept of new electrically narrow very low profile (ENVELOP) directive antennas for low frequency radars and diversity communication applications. The basic structure consists of a short TEM horn combined with an inductive loop antenna. The proposed antenna height is 0.063 where is the minimum operating wavelength and has good matching and radiation characteristics over more than an octave. It is based on the principle of crossed electric and magnetic dipoles with a TEM horn as the electric dipole and a sheet loop as the magnetic dipole. However, unlike the standard structures, the proposed structure is designed to enhance the radiation in a direction perpendicular to the TEM horn axis. This limits the maximum pattern bandwidth to about one octave but allows the antenna height along the direction of maximum radiation to be very small which is very important for airborne radars and in low frequency military communications that require conformal antennas. Three different variations of the basic structure are also presented which offer improved pattern characteristics and/or pattern and polarization diversity. Two antennas were fabricated and measured. The measured results agreed well with the simulation results and both showed that the antenna can operate over 1-2 GHz with consistent radiation pattern, low dispersion and input impedance matching performance.


title: Surface area determination via NMR: fluid and frequency effects

abstract: Recently, the use of NMR spin-lattice relaxation measurements has been proposed as a tool for the determination of specific surface area. The use of this approach, which has several advantages and disadvantages as compared to conventional methods, was demonstrated using relaxation measurements of water at 20 MHz for two materials with similar surface chemistry. In principle, the surface-enhanced spin-lattice relaxation rate is a function of proton frequency, fluid, temperature and surface chemistry. In this paper, we describe relaxation measurements at 303 K using a range of fluids (water, methanol, ethanol, cyclohexane) at two proton frequencies (20 and 300 MHz) for a series of samples with different surface areas from three different porous solid groups (controlled pore glass, mixed ester cellulose membranes and carbon blacks). Surface area of samples studied were in the range of 4.4 to 179.0 m2/g. A three-fold increase in the sensitivity of the surface area determination is noted when the frequency is decreased from 300 to 20 MHz. In general, surface area sensitivity increases with fluid type as (cyclohexane ⪡ water < methanol < ethanol).


title: CubTile: a multi-touch cubic interface

abstract: On the one hand, multitouch tactile interfaces offer many advantages and are more and more widespread. Their use as 3D application interfaces are rather limited though, since they offer large horizontal flat projection surfaces that are not suited to many kinds of 3D operations. On the other hand, despite the many propositions that have been made over the past years, no single interface has proven to tackle the numerous specificities related to the 3D interaction constraints. Through the CubTile device proposal, our preliminary work tries to bring the strengths related to multitouch tactile surfaces into a device aimed at 3D interactions. Consisting in a medium-sized cube where 5 out of 6 sides are multitouch, our prototype senses several fingers, offers interaction redundancy and lets a user handle 3D manipulation thanks to single handed and bimanual input.


title: Revealing the 'real' me, searching for the 'actual' you: Presentations of self on an internet dating site

abstract: This paper considers the presentation of self on an internet dating site. Thirty men and thirty women were interviewed about their online dating experiences. They were asked about how they constructed their profiles and how they viewed other individuals’ profiles. What types of presentations of self led to more successful offline romantic relationships were also investigated. Additionally, gender differences were examined. In line with previous research on presentation of self online, individuals were quite strategic in their online presentations. However, important differences between initiating a relationship on an internet dating site and other spaces (online and offline) included the type of self disclosed as well as the depth of breadth of information individuals self-disclosed about themselves before any one-on-one conversations took place.


title: Monet: A User-Oriented Behavior-Based Malware Variants Detection System for Android

abstract: Android, the most popular mobile OS, has around 78% of the mobile market share. Due to its popularity, it attracts many malware attacks. In fact, people have discovered around 1 million new malware samples per quarter, and it was reported that over 98% of these new malware samples are in fact “ derivatives ” (or variants) from existing malware families. In this paper, we first show that runtime behaviors of malware’s core functionalities are in fact similar within a malware family. Hence, we propose a framework to combine “ runtime behavior ” with “ static structures ” to detect malware variants. We present the design and implementation of Monet, which has a client and a backend server module. The client module is a lightweight, in-device app for behavior monitoring and signature generation, and we realize this using two novel interception techniques. The backend server is responsible for large scale malware detection. We collect 3723 malware samples and top 500 benign apps to carry out extensive experiments of detecting malware variants and defending against malware transformation. Our experiments show that Monet can achieve around 99% accuracy in detecting malware variants. Furthermore, it can defend against ten different obfuscation and transformation techniques, while only incurs around 7% performance overhead and about 3% battery overhead. More importantly, Monet will automatically alert users with intrusion details so to prevent further malicious behaviors.


title: Calculated and measured brachytherapy dosimetry parameters in water for the Xoft Axxent X-Ray Source: An electronic brachytherapy sourcea)

abstract: A new x-ray source, the model S700 Axxent trade mark sign X-Ray Source (Source), has been developed by Xoft Inc. for electronic brachytherapy. Unlike brachytherapy sources containing radionuclides, this Source may be turned on and off at will and may be operated at variable currents and voltages to change the dose rate and penetration properties. The in-water dosimetry parameters for this electronic brachytherapy source have been determined from measurements and calculations at 40, 45, and 50 kV settings. Monte Carlo simulations of radiation transport utilized the MCNP5 code and the EPDL97-based mcplib04 cross-section library. Inter-tube consistency was assessed for 20 different Sources, measured with a PTW 34013 ionization chamber. As the Source is intended to be used for a maximum of ten treatment fractions, tube stability was also assessed. Photon spectra were measured using a high-purity germanium (HPGe) detector, and calculated using MCNP. Parameters used in the two-dimensional (2D) brachytherapy dosimetry formalism were determined. While the Source was characterized as a point due to the small anode size, <1 mm, use of the one-dimensional (1D) brachytherapy dosimetry formalism is not recommended due to polar anisotropy. Consequently, 1D brachytherapy dosimetry parameters were not sought. Calculated point-source model radial dose functions atmore » g{sub P}(5) were 0.20, 0.24, and 0.29 for the 40, 45, and 50 kV voltage settings, respectively. For 1<r<7 cm, measured point-source model radial dose functions were typically within 4% of calculated results. Calculated values for F(r,{theta}) for all operating voltages were within 15% of unity along the distal end ({theta}=0 deg. ), and ranged from F(1 cm,160 deg. )=0.2 to F(15 cm,175 deg. )=0.4 towards the catheter proximal end. For all three operating voltages using the PTW chamber, measured dependence of output as a function of azimuthal angle, {psi}, was typically on average {+-}3% for 0 deg. {<=}{psi}{<=}360 deg. . Excluding an energy response function, measurements of normalized photon energy spectra were made for three operating voltages, and were typically within 2% agreement with the normalized Monte Carlo calculated spectra. In general, the model S700 Source exhibited depth dose behavior similar to low-energy photon-emitting low dose rate sources {sup 125}I and {sup 103}Pd, yet with capability for variable and much higher dose rates and subsequently adjustable penetration capabilities. This paper presents the calculated and measured in-water brachytherapy dosimetry parameters for the model S700 Source at the aforementioned three operating voltages.« less


title: An online HDP-HMM for joint action segmentation and classification in motion capture data

abstract: Since its inception, action recognition research has mainly focused on recognizing actions from closed, predefined sets of classes. Conversely, the problem of recognizing actions from open, possibly incremental sets of classes is still largely unexplored. In this paper, we propose a novel online method based on the “sticky” hierarchical Dirichlet process and the hidden Markov model [11, 5]. This approach, labelled as the online HDP-HMM, provides joint segmentation and classification of actions while a) processing the data in an online, recursive manner, b) discovering new classes as they occur, and c) adjusting its parameters over the streaming data. In a set of experiments, we have applied the online HDP-HMM to recognize actions from motion capture data from the TUM kitchen dataset, a challenging dataset of manipulation actions in a kitchen [12]. The results show significant accuracy in action classification, time segmentation and determination of the number of action classes.


title: Stash: have your scratchpad and cache it too

abstract: Heterogeneous systems employ specialization for energy efficiency. Since data movement is expected to be a dominant consumer of energy, these systems employ specialized memories (e.g., scratchpads and FIFOs) for better efficiency for targeted data. These memory structures, however, tend to exist in local address spaces, incurring significant performance and energy penalties due to inefficient data movement between the global and private spaces. We propose an efficient heterogeneous memory system where specialized memory components are tightly coupled in a unified and coherent address space. This paper applies these ideas to a system with CPUs and GPUs with scratchpads and caches. We introduce a new memory organization, stash, that combines the benefits of caches and scratchpads without incurring their downsides. Like a scratchpad, the stash is directly addressed (without tags and TLB accesses) and provides compact storage. Like a cache, the stash is globally addressable and visible, providing implicit data movement and increased data reuse. We show that the stash provides better performance and energy than a cache and a scratchpad, while enabling new use cases for heterogeneous systems. For 4 microbenchmarks, which exploit new use cases (e.g., reuse across GPU compute kernels), compared to scratchpads and caches, the stash reduces execution cycles by an average of 27% and 13% respectively and energy by an average of 53% and 35%. For 7 current GPU applications, which are not designed to exploit the new features of the stash, compared to scratchpads and caches, the stash reduces cycles by 10% and 12% on average (max 22% and 31%) respectively, and energy by 16% and 32% on average (max 30% and 51%).


title: Development of whole-body humanoid “pneumat-BS” with pneumatic musculoskeletal system

abstract: The human musculoskeletal system is supposed to play an important role in doing various static and dynamic tasks. From this standpoint, some musculoskeletal humanoid robots have been developed in recent years. However, existing musculoskeletal robots did not have upper body with several DOFs to balance their bodies statically or did not have enough power to perform dynamic tasks. We think the musculoskeletal structure has two significant properties: whole-body flexibility and whole-body coordination. Using these two properties can enable us to make robots' performance better than before. In this study, we developed a humanoid robot with a musculoskeletal system that is driven by pneumatic artificial muscles. To demonstrate the robot's capability in static and dynamic tasks, we conducted two experiments. As a static task, we conducted a standing experiment using a simple feedback control and evaluated the stability by applying an impulse to the robot. As a dynamic task, we conducted a walking experiment using a feedforward controller with human muscle activation patterns and confirmed that the robot was able to perform the dynamic task.


title: Quantum cognition: a new theoretical approach to psychology

abstract: What type of probability theory best describes the way humans make judgments under uncertainty and decisions under conflict? Although rational models of cognition have become prominent and have achieved much success, they adhere to the laws of classical probability theory despite the fact that human reasoning does not always conform to these laws. For this reason we have seen the recent emergence of models based on an alternative probabilistic framework drawn from quantum theory. These quantum models show promise in addressing cognitive phenomena that have proven recalcitrant to modeling by means of classical probability theory. This review compares and contrasts probabilistic models based on Bayesian or classical versus quantum principles, and highlights the advantages and disadvantages of each approach.


title: Implementing IT Service Management: A systematic literature review

abstract: Author's version of an article in the journal: International Journal of Information Management. Also available from the publisher at: http://dx.doi.org/10.1016/j.ijinfomgt.2013.01.004


title: A 0.5V 4Mb logic-process compatible embedded resistive RAM (ReRAM) in 65nm CMOS using low-voltage current-mode sensing scheme with 45ns random read time

abstract: Numerous low-supply-voltage (V DD ) mobile chips, such as energy-harvesting-powered devices and biomedical applications, require low-V DD on-chip nonvolatile memory (NVM) for low-power active-mode access and power-off data storage. However, conventional NVMs cannot achieve low-V DD operation due to insufficient write voltage generated by charge-pumped (CP) circuits at a low V DD , and a lack of low-V DD current-mode sense amplifiers (CSA) [1–4] to overcome read issues in reduced sensing margins, degraded speeds, and insufficient voltage headroom (VHR). Resistive RAM (ReRAM) [4–6] is a promising memory with the advantages of short write time, low write-voltage, and reduced write power compared to Flash and other NVMs. Using a low-V DD CP with relaxed output voltage/current requirements for write operations, ReRAM is a good candidate for on-chip low-V DD NVM if a low-V DD CSA is provided, particularly for frequent-read-seldom-write applications. We develop a body-drain-driven CSA (BDD-CSA) with dynamic BL bias voltage (V BL ) and small VHR for larger sensing margins to achieve a lower V DDmin , faster read speed, and better tolerance of read cell current (I CELL ) and BL leakage current (I BL-LEAK ) variations compared to conventional CSAs. A fabricated 65nm 4Mb ReRAM macro using the BDD-CSA and our CMOS-logic-compatible ReRAM cell [7] achieves 0.5V V DDmin . The BDD-CSA achieves 0.32V V DDmin .


title: Neural Network Bottleneck Features for Language Identifica tion

abstract: This paper presents the application of Neural Network Bottleneck (BN) features in Language Identification (LID). BN f eatures are generally used for Large Vocabulary Speech Recognition in conjunction with conventional acoustic features, s uch as MFCC or PLP. We compare the BN features to several common types of acoustic features used in the state-of-the-art LID systems. The test set is from DARPA RATS (Robust Automatic Transcription of Speech) program, which seeks to advance state-of-the-art detection capabilities on audio from hig hly degraded radio communication channels. On this type of noisy data, we show that in average, the BN features provide a 45% relative improvement in the Cavgor Equal Error Rate (EER) metrics across several test duration conditions, with resp ect to our single best acoustic features. Index Terms: language identification, noisy speech, robust feature extraction


title: Cross-Architecture Bug Search in Binary Executables

abstract: With the general availability of closed-source software for various CPU architectures, there is a need to identify security-critical vulnerabilities at the binary level to perform a vulnerability assessment. Unfortunately, existing bug finding methods fall short in that they i) require source code, ii) only work on a single architecture (typically x86), or iii) rely on dynamic analysis, which is inherently difficult for embedded devices. In this paper, we propose a system to derive bug signatures for known bugs. We then use these signatures to find bugs in binaries that have been deployed on different CPU architectures (e.g., x86 vs. MIPS). The variety of CPU architectures imposes many challenges, such as the incomparability of instruction set architectures between the CPU models. We solve this by first translating the binary code to an intermediate representation, resulting in assignment formulas with input and output variables. We then sample concrete inputs to observe the I/O behavior of basic blocks, which grasps their semantics. Finally, we use the I/O behavior to find code parts that behave similarly to the bug signature, effectively revealing code parts that contain the bug. We have designed and implemented a tool for cross architecture bug search in executables. Our prototype currently supports three instruction set architectures (x86, ARM, and MIPS) and can find vulnerabilities in buggy binary code for any of these architectures. We show that we can find Heart bleed vulnerabilities, regardless of the underlying software instruction set. Similarly, we apply our method to find backdoors in closed source firmware images of MIPS- and ARM-based routers.


3 D Shape Segmentation and Labeling via Extreme Learning Machine


title: On the Role of Correlation and Abstraction in Cross-Modal Multimedia Retrieval

abstract: The problem of cross-modal retrieval from multimedia repositories is considered. This problem addresses the design of retrieval systems that support queries across content modalities, for example, using an image to search for texts. A mathematical formulation is proposed, equating the design of cross-modal retrieval systems to that of isomorphic feature spaces for different content modalities. Two hypotheses are then investigated regarding the fundamental attributes of these spaces. The first is that low-level cross-modal correlations should be accounted for. The second is that the space should enable semantic abstraction. Three new solutions to the cross-modal retrieval problem are then derived from these hypotheses: correlation matching (CM), an unsupervised method which models cross-modal correlations, semantic matching (SM), a supervised technique that relies on semantic representation, and semantic correlation matching (SCM), which combines both. An extensive evaluation of retrieval performance is conducted to test the validity of the hypotheses. All approaches are shown successful for text retrieval in response to image queries and vice versa. It is concluded that both hypotheses hold, in a complementary form, although evidence in favor of the abstraction hypothesis is stronger than that for correlation.


title: LaneQuest: An Accurate and Energy-Efficient Lane Detection System

abstract: Current outdoor localization techniques fail to provide the required accuracy for estimating the car's lane. In this paper, we present LaneQuest: a system that leverages the ubiquitous and low-energy inertial sensors available in commodity smart-phones to provide an accurate estimate of the car's current lane. LaneQuest leverages hints from the phone sensors about the surrounding environment to detect the car's lane. For example, a car making a right turn most probably will be in the right-most lane, a car passing by a pothole will be in a specific lane, and the car's angular velocity when driving through a curve reflects its lane. Our investigation shows that there are amble opportunities in the environment, i.e. lane “anchors”, that provide cues about the car's lane. To handle the ambiguous location, sensors noise, and fuzzy lane anchors; LaneQuest employs a novel probabilistic lane estimation algorithm. Furthermore, it uses an unsupervised crowd-sourcing approach to learn the position and lane-span distribution of the different lane-level anchors. Our evaluation results from implementation on different android devices and 260Km driving traces by 13 drivers in different cities shows that LaneQuest can detect the different lane-level anchors with an average precision and recall of more than 90%. This leads to an accurate detection of the exact car's lane position 80% of the time, increasing to 89% of the time to within one lane. This comes with a low-energy footprint, allowing LaneQuest to be implemented on the energy-constrained mobile devices.


title: Association between low plasma vitamin E concentration and progression of early cortical lens opacities.

abstract: The authors evaluated the association between plasma vitamin E content and progression of eye lens opacities. A total of 410 hypercholesterolemic eastern Finnish men participated in the study from January 1990 to September 1993 in Kuopio, Finland. Lens opacities were classified three times at 18-month intervals using the Lens Opacities Classification System II. A low plasma vitamin E level (lowest quartile) was associated with a 3.7-fold excess risk (95% confidence interval 1.2-11.8) of the progression of early cortical lens opacities compared with the highest quartile (p = 0.028). In addition, the number of cigarettes smoked daily was a significant predictor of the progression of cortical lens opacity (relative risk = 1.06 per cigarette, 95% confidence interval 1.003-1.12). The progression of nuclear lens opacities was not associated with either the plasma vitamin E content or smoking. The data suggest that low plasma vitamin E content may be associated with increased risk of the progression of early cortical lens opacity.


title: A Broadband Horizontally Polarized Omnidirectional Antenna for VHF Application

abstract: A novel broadband horizontally polarized (HP) omnidirectional antenna is proposed for meteor-burst communication system in VHF. The proposed antenna is composed of three bowtie dipoles, which are concentrically placed to form a loop antenna. The bowtie dipole is shorted at the terminal by folded elements in order to reduce antenna size. The bowtie dipoles are fed by a three-way power divider. A slotted line balun is employed to achieve broadband impedance matching and realize balanced-to-unbalanced transformation. The designed HP omnidirectional antenna exhibits a fractional bandwidth of 24.7% with VSWR < 2 ranging from 39 to 50 MHz. Uniform omnidirectional radiation patterns in the azimuth plane with HP have been obtained. The loop antenna provides a relatively low gain of no more than 1.5 dBi. Therefore, a two-element HP antenna array is developed to enhance its gain. In order to reduce longitudinal dimension of the array, the two loop antenna elements are placed in reverse and employ differential feeding method to realize in-phase current. Both the simulation and measured results are used to verify the design approach.


title: Modelling of physical systems for the design and control of mechatronic systems Job

abstract: Mechatronic design requires that a mechanical system and its control system be designed as an integrated system. This contribution covers the background and tools for modelling and simulation of physical systems and their controllers, with parameters that are directly related to the real-world system. The theory will be illustrated with examples of typical mechatronic systems such as servo systems and a mobile robot. Hands-on experience is realised by means of exercises with the 20-sim software package (a demo version is freely available on the Internet). ::: ::: In mechatronics, where a controlled system has to be designed as a whole, it is advantageous that model structure and parameters are directly related to physical components. In addition, it is desired that (sub-)models be reusable. Common block-diagram- or equation-based simulation packages hardly support these features. The energy-based approach towards modelling of physical systems allows the construction of reusable and easily extendible models. This contribution starts with an overview of mechatronic design problems and the various ways to solve such problems. A few examples will be discussed that show the use of such a tool in various stages of the design. The examples include a typical mechatronic system with a flexible transmission and a mobile robot. The energy-based approach towards modelling is treated in some detail. This will give the reader sufficient insight in order to exercise it with the aid of modelling and simulation software (20-sim). Such a tool allows high level input of models in the form of iconic diagrams, equations, block diagrams or bond graphs and supports efficient symbolic and numerical analysis as well as simulation and visualisation. Components in various physical domains (e.g. mechanical or electrical) can easily be selected from a library and combined into a process that can be controlled by block-diagram-based (digital) controllers. ::: ::: This contribution is based on object-oriented modelling: each object is determined by constitutive relations at the one hand and its interface, the power and signal ports to and from the outside world, at the other hand. Other realizations of an object may contain different or more detailed descriptions, but as long as the interface (number and type of ports) is identical, they can be exchanged in a straightforward manner. This allows top–down modelling as well as bottom–up modelling. Straightforward interconnection of (empty) submodels supports the actual decision process of modelling, not just model input and output manipulation. Empty submodel types may be filled with specific descriptions with various degrees of complexity (models can be polymorphic) to support evolutionary and iterative modelling and design approaches. Additionally, submodels may be constructed from other submodels in hierarchical structures. ::: ::: An introduction to the design of controllers based on these models is also given. Modelling and controller design as well as the use of 20-sim may be exercised in hands-on experience assignments, available at the Internet (http://www.ce.utwente.nl/IFACBrief/). A demonstration copy of 20-sim that allows the reader to use the ideas presented in this contribution may be downloaded from the Internet (http://www.20sim.com).


title: Survey of Research on Software Clones

abstract: Summary. This report summarizes my overview talk on software clone detection research. It first discusses the notion of software redundancy, cloning, duplication, and similarity. Then, it describes various categorizations of clone types, empirical studies on the root causes for cloning, current opinions and wisdom of consequences of cloning, empirical studies on the evolution of clones, ways to remove, to avoid, and to detect them, empirical evaluations of existing automatic clone detector performance (such as recall, precision, time and space consumption) and their fitness for a particular purpose, benchmarks for clone detector evaluations, presentation issues, and last but not least application of clone detection in other related fields. After each summary of a subarea, I am listing open research questions.


title: Canine low-grade intra-orbital myxosarcoma: case report

abstract: OBJECTIVE ::: The aim of this study was to evaluate important clinical, morphological, histopathological, histochemical, and immunohistochemical characteristics in order to establish the diagnosis and prognosis of a low-grade intra-orbital myxosarcoma. ::: ::: ::: ANIMAL STUDIED ::: A mongrel dog presented a 2-year history of a neoplastic mass behind the right eye. ::: ::: ::: RESULTS ::: The neoplasm presented a mesenchymal spindle and stellate cell proliferation with an abundant myxoid matrix, moderate anisocariosis, and a low mitotic index. It stained positive for vimentin, moderately positive for periodic acid-Schiff, and negative for Gomori trichrome stain and α-smooth muscle actin. ::: ::: ::: CONCLUSIONS ::: One year following surgical excision, the patient remains disease free. The histological findings established a diagnosis of a rare canine intra-orbital low-grade myxosarcoma.


title: Teacher Retention and Attrition: Views of Early Career Teachers

abstract: The provision and maintenance of quality teachers in the profession is a pressing issue. Concerns have been raised that teacher experience and knowledge may be lost to the profession through attrition and retirement (Ramsey, 2000; Ingersoll, 2001; Williams, 2002; McGaw, 2003; Lonsdale and Ingvarson, 2003; Skilbeck and Connell, 2003, 2004). Teacher attrition comes at a cost to individual teachers and to the community (Korthagen, 2004; Connell, 2007; Rinke, 2007; Buchanan, 2009; 2010; Schuck, Aubusson, Buchanan and Russell, 2012). Hence there is a need to investigate the experiences of early career teachers (ECTs) to consider how these experiences influence ECTs' decisions about staying in or leaving the profession. For teacher educators, knowing about ECTs' experiences provides insights that enable them to enhance teacher education programs and better prepare teachers for their first years of teaching. This paper reports on an aspect of a large-scale longitudinal study on early career teachers' decisions to remain in or leave the profession. The overarching research question was: Why do some early career teachers choose to remain in the profession and why do others choose to leave? This paper describes and analyses the experiences of teachers participating in the study and highlights implications for teacher retention.


title: A 1-V PTAT current reference circuit with 0.05%/V current sensitivity to VDD

abstract: This paper presents a CMOS PTAT current reference circuit which is robust against process and supply voltage variations over a wide voltage and temperature range, i.e. from 0.9 V to 2.5 V and from −40° C to 125° C, respectively. Two implementations of the same circuit were designed for comparison: the first one uses core transistors (1.1 V), while the second one employs IO transistors (2.5 V). The circuit uses a PMOS version of a conventional PTAT current generator with a PMOS self-cascode MOSFET and a PMOS feedback amplifier to enhance the circuit performance. Simulation results have shown a PTAT current sensitivity to the supply voltage of 2.9%/V @ 27° C (from 0.9 V to 1.5 V) and of 0.05%/V @ 27° C (from 1 V to 2.5 V) for core and IO transistors implementations, respectively, and a nearly constant current spread over temperature, with a maximum variation of 10% (3σ) for both ones.


title: The Rational Unified Process Made Easy: A Practitioner's Guide to the RUP

abstract: "Per Kroll and Philippe Kruchten are especially well suited to explain the RUP...because they have been the central forces inside Rational Software behind the creation of the RUP and its delivery to projects around the world."--From the Foreword by Grady BoochThis book is a comprehensive guide to modern software development practices, as embodied in the Rational Unified Process, or RUP. With the help of this book's practical advice and insight, software practitioners will learn how to tackle challenging development projects--small and large--using an iterative and risk-driven development approach with a proven track record.The Rational Unified Process Made Easy will teach you the key points involved in planning and managing iterative projects, the fundamentals of component design and software architecture, and the proper employment of use cases. All team members--from project managers to analysts, from developers to testers--will learn how to immediately apply the RUP to their work. You will learn that the RUP is a flexible, versatile process framework that can be tailored to suit the needs of development projects of all types and sizes.Key topics covered include: How to use the RUP to develop iteratively, adopt an architecture-centric approach, mitigate risk, and verify software quality Tasks associated with the four phases of the RUP: Inception, Elaboration, Construction, and Transition Roles and responsibilities of project managers, architects, analysts, developers, testers, and process engineers in a RUP project Incrementally adopting the RUP with minimal risk Common patterns for failure with the RUP--and how to avoid themUse this book to get quickly up to speed with the RUP, so you can easily employ the significant power of this process to increase the productivity of your team.0321166094B03062003


title: The asymptotic decider: resolving the ambiguity in marching cubes

abstract: A method for computing isovalue or contour surfaces of a trivariate function is discussed. The input data are values of the trivariate function, F/sub ijk/, at the cuberille grid points (x/sub i/, y/sub j/, z/sub k/), and the output of a collection of triangles representing the surface consisting of all points where F(x,y,z) is a constant value. The method is a modification that is intended to correct a problem with a previous method. >


title: BoardPUF: Physical Unclonable Functions for Printed Circuit Board Authentication

abstract: Physical Unclonable Functions (PUFs) are cryptographic primitives that can be used to generate volatile secret keys for cryptographic operations and enable low-cost authentication of integrated circuits. Existing PUF designs mainly exploit variation effects on silicon and hence are not readily applicable for the authentication of printed circuit boards (PCBs). To tackle the above problem, in this paper, we propose a novel PUF device that is able to generate unique and stable IDs for individual PCB, namely BoardPUF. To be specific, we embed a number of capacitors in the internal layer of PCBs and utilize their variations for key generation. Then, by integrating a cryptographic primitive (e.g. hash function) into BoardPUF, we can effectively perform PCB authentication in a challenge-response manner. Our experimental results on fabricated boards demonstrate the efficacy of BoardPUF.


title: S-WOLF: Semantic Workplace Learning Framework

abstract: Workplace learning can be conceived as the set of processes related to learning and training activities at work. Typically, workplace learning includes formal, informal, and non-formal learning activities. Having a control on the whole learning process of each worker is a complex task. Indeed we have to align individual learning paths, real workers' needs (for instance in terms of tasks or projects to accomplish), career plans, and other organizational needs to activate virtuous knowledge flows. In order to accomplish this complex task a comprehensive framework is needed. This paper provides the definition of the aforementioned framework by exploiting semantic technologies in order to model (by means of Ontologies), represent, extract, and share knowledge within organizations. Although the proposed framework allows a wide range of workplace learning experiences, it mainly focuses on informal learning, on the ways it can be sustained by exploiting organizational resources, and on the capability of linking individual and organizational learning in the context of a widely accepted knowledge flow model like socialization, externalization, composition, and internalization.


title: Context-aware application scheduling in mobile systems: what will users do and not do next?

abstract: Usage patterns of mobile devices depend on a variety of factors such as time, location, and previous actions. Hence, context-awareness can be the key to make mobile systems to become personalized and situation dependent in managing their resources. We first reveal new findings from our own Android user experiment: (i) the launching probabilities of applications follow Zipf's law, and (ii) inter-running and running times of applications conform to log-normal distributions. We also find context-dependency in application usage patterns, for which we classify contexts in a personalized manner with unsupervised learning methods. Using the knowledge acquired, we develop a novel context-aware application scheduling framework, CAS that adaptively unloads and preloads background applications in a timely manner. Our trace-driven simulations with 96 user traces demonstrate the benefits of CAS over existing algorithms. We also verify the practicality of CAS by implementing it on the Android platform.


title: Ten principles of good interdisciplinary team work

abstract: Interdisciplinary team work is increasingly prevalent, supported by policies and practices that bring care closer to the patient and challenge traditional professional boundaries. To date, there has been a great deal of emphasis on the processes of team work, and in some cases, outcomes. This study draws on two sources of knowledge to identify the attributes of a good interdisciplinary team; a published systematic review of the literature on interdisciplinary team work, and the perceptions of over 253 staff from 11 community rehabilitation and intermediate care teams in the UK. These data sources were merged using qualitative content analysis to arrive at a framework that identifies characteristics and proposes ten competencies that support effective interdisciplinary team work. Ten characteristics underpinning effective interdisciplinary team work were identified: positive leadership and management attributes; communication strategies and structures; personal rewards, training and development; appropriate resources and procedures; appropriate skill mix; supportive team climate; individual characteristics that support interdisciplinary team work; clarity of vision; quality and outcomes of care; and respecting and understanding roles. We propose competency statements that an effective interdisciplinary team functioning at a high level should demonstrate.


title: MobiByte: An Application Development Model for Mobile Cloud Computing

abstract: Mobile cloud computing presents an effective solution to overcome smartphone constraints, such as limited computational power, storage, and energy. As the traditional mobile application development models do not support computation offloading, mobile cloud computing requires novel application development models that can facilitate the development of cloud enabled mobile applications. This paper presents a mobile cloud application development model, named MobiByte, to enhance mobile device applications' performance, energy efficiency, and execution support. MobiByte is a context-aware application model that uses multiple data offloading techniques to support a wide range of applications. The proposed model is validated using prototype applications and detailed results are presented. Moreover, MobiByte is compared with the most recent application models with a conclusion that it outperforms the existing application models in many aspects like energy efficiency, performance, generality, context awareness, and privacy.


title: Binary stereo matching

abstract: In this paper, we propose a novel binary-based cost computation and aggregation approach for stereo matching problem. The cost volume is constructed through bitwise operations on a series of binary strings. Then this approach is combined with traditional winner-take-all strategy, resulting in a new local stereo matching algorithm called binary stereo matching (BSM). Since core algorithm of BSM is based on binary and integer computations, it has a higher computational efficiency than previous methods. Experimental results on Middlebury benchmark show that BSM has comparable performance with state-of-the-art local stereo methods in terms of both quality and speed. Furthermore, experiments on images with radiometric differences demonstrate that BSM is more robust than previous methods under these changes, which is common under real illumination.


title: Towards decision support for disclosing data: Closed or open data?

abstract: The disclosure of open government data is a complex activity that may create public value yet might also encounter risks, such as the misinterpretation and misuse of data. While politicians support data release and assume that the positive value of open data will dominate, many governmental organizations are reluctant to open their data, as they are afraid of the dark side. The objective of this paper is to provide a decision-making model that assists in trade-offs between the pros and cons of open data. Data disclosure is dependent on the type of data (e.g. its sensitivity, structure and quality) and the context (e.g. organizational policies, legislation and the political influences). Based on the literature and fifteen in-depth interviews with public sector officials and data archivists, this paper identifies contextual and dataset-related variables which influence a trade- off. A decision-making model is presented capturing trade-offs, and in this way providing guidance for weighing the creation of public value and the risks. The model can be used for decision-making to open or not to open data. It is likely that the decision regarding which data should be opened or closed will shift over time.


title: Age-related hearing impairment—a risk factor and frailty marker for dementia and AD

abstract: Age-related hearing impairment (ARHI, also known as presbycusis) is potentially a reversible risk factor for dementia and Alzheimer disease (AD). Social isolation, loneliness, poor verbal communication, and cognitive reserve depletion might causally link ARHI with cognitive impairment. ARHI is an important frailty marker, and several factors related to physical frailty could be associated with cognitive impairment. Such factors include inflammatory markers and vascular factors, which might also directly contribute to ARHI. Randomized controlled trials of potential interventions, and larger population-based studies, could facilitate further understanding of the interplay between cognitive impairment, ARHI and frailty in older age. Deficits in both peripheral hearing and central auditory processing (CAP) can contribute to ARHI. Impairments in peripheral hearing and CAP have been linked to accelerated cognitive decline, incident cognitive impairment and AD; moreover, CAP dysfunction is common in mild cognitive impairment (MCI) and AD. Assessment of CAP dysfunction in people with ARHI might, therefore, aid identification of older individuals with increased risk of MCI and AD.


title: Electronic Word of Mouth and Knowledge Sharing on Social Network Sites: A Social Capital Perspective

abstract: Social network sites (SNSs) have attracted millions of users who interact with each other and with companies. However, few studies have examined the impact of knowledge sharing through electronic word of mouth (eWOM) in the context of SNSs. This paper investigates the relationship among the use of SNSs, users' social capital, knowledge sharing, and eWOM. The results show that the intensity of use of SNSs is positively related to trust and identification which have a positive effect on eWOM quality. In addition, eWOM quality has a positive effect on knowledge sharing. Female users feel more strongly about eWOM quality when they trust others, or when they perceive that they belong to their SNS community when they use their SNS. Furthermore, female users feel more strongly about knowledge sharing when they perceive that eWOM quality is good. This study provides the theoretical framework of the relationship between eWOM and knowledge sharing on SNSs from the perspective of social capital. Practitioners could use this study as a rationale to utilize SNSs internally for organizational use, and externally for marketing purposes.


title: Analysis and optimization of a modular stator core with segmental teeth and solid back iron for pm electric machines

abstract: Compared with conventional overlapping windings, nonoverlapping windings offer an exclusive advantage of short end-windings, which leads to less copper loss, shorter axial length, and higher slot fill factor particularly when used with segmental stator core. However, it is not so easy to manufacture the stator with nonoverlapping windings, especially when a high slot fill factor with low cost is required. In most existing methods, laminated segments are connected directly to form a complete stator core, so-called laminated-joint core. This requires precise mechanical assembles, and usually results in restrict process with expensive equipments. The goal of this paper is to propose a new segmental stator structure without laminated-joint, where the laminated tooth modules are coupled with a solid back iron. In this paper, existing manufacturing methods of segmental stator core will be reviewed and analyzed. Subsequently, several models are developed and improved, step by step, to achieve the best target, especially taking the iron losses as an evaluation criterion. Some techniques to reduce iron losses in the solid back iron will be proposed and compared. Some practical issues for manufacturing the proposed segmental stator core are discussed. Influence of subsidiary air gap on the iron losses will also be analyzed. And, cost evaluation of the proposed method, as well as the realistic shapes of laminations-solid-joints, is presented.


title: A smart home system based on sensor technology

abstract: This paper presents a new approach to utilize technology in a practical and meaningful manner within a smart home system that can be widely deployed into residential settings. In the modern world, people are rapidly turning to technology as a fast and cost-effective way of improving quality of daily living. This primary goal is to address the needs of the end user by employing networked low-power sensors sensitive to the environment, so it can be altered to their liking. The proposed system consists of following steps: direct environment sensing, collecting and analyzing data and then allowing user to customize the settings and initiate specific commands. This research will present the design and implementation of a practical and simple smart home system, which can be further extended. The system is based on: group of sensors, Raspberry Pi device as a server system and Bluetooth as a communication protocol. These devices can be easily controlled via user-friendly interface for Android phones. The main advantage of the proposed system is that it is a sensible, secure and easily configurable system that provides end users with a neat home automation solution.


title: Exercise in Cardiovascular Disease Cardiovascular Effects of Exercise Training Molecular Mechanisms

abstract: In the natural habitat of our ancestors, physical activity was not a preventive intervention but a matter of survival. In this hostile environment with scarce food and ubiquitous dangers, human genes were selected to optimize aerobic metabolic pathways and conserve energy for potential future famines.1 Cardiac and vascular functions were continuously challenged by intermittent bouts of high-intensity physical activity and adapted to meet the metabolic demands of the working skeletal muscle under these conditions. When speaking about molecular cardiovascular effects of exercise, we should keep in mind that most of the changes from baseline are probably a return to normal values. The statistical average of physical activity in Western societies is so much below the levels normal for our genetic background that sedentary lifestyle in combination with excess food intake has surpassed smoking as the No. 1 preventable cause of death in the United States.2 Physical activity has been shown to have beneficial effects on glucose metabolism, skeletal muscle function, ventilator muscle strength, bone stability, locomotor coordination, psychological well-being, and other organ functions. However, in the context of this review, we will focus entirely on important molecular effects on the cardiovascular system. The aim of this review is to provide a bird’s-eye view on what is known and unknown about the physiological and biochemical mechanisms involved in mediating exercise-induced cardiovascular effects. The resulting map is surprisingly detailed in some areas (ie, endothelial function), whereas other areas, such as direct cardiac training effects in heart failure, are still incompletely understood. For practical purposes, we have decided to use primarily an anatomic approach to present key data on exercise effects on cardiac and vascular function. For the cardiac effects, the left ventricle and the cardiac valves will be described separately; for the vascular effects, we will follow the arterial vascular tree, addressing changes in the aorta, the large conduit arteries, the resistance vessels, and the microcirculation before turning our attention toward the venous and the pulmonary circulation (Figure 1). Cardiac Effects of Exercise


title: Layers of Interpretation: On Grammar and Compositionality

abstract: With the recent resurgence of interest in semantic annotation of corpora for improved semantic parsing, we observe a tendency which we view as ill-advised, to conflate sentence meaning and speaker meaning into a single mapping, whether done by annotators or by a parser. We argue instead for the more traditional hypothesis that sentence meaning, but not speaker meaning, is compositional, and accordingly that NLP systems would benefit from reusable, automatically derivable, taskindependent semantic representations which target sentence meaning, in order to capture exactly the information in the linguistic signal itself. We further argue that compositional construction of such sentence meaning representations affords better consistency, more comprehensiveness, greater scalability, and less duplication of effort for each new NLP application. For concreteness, we describe one well-tested grammar-based method for producing sentence meaning representations which is efficient for annotators, and which exhibits many of the above benefits. We then report on a small inter-annotator agreement study to quantify the consistency of semantic representations produced via this grammar-based method.


title: AI assisted ethics

abstract: The growing number of `smart' instruments, those equipped with AI, has raised concerns because these instruments make autonomous decisions; that is, they act beyond the guidelines provided them by programmers. Hence, the question the makers and users of smart instrument (e.g., driver-less cars) face is how to ensure that these instruments will not engage in unethical conduct (not to be conflated with illegal conduct). The article suggests that to proceed we need a new kind of AI program--oversight programs--that will monitor, audit, and hold operational AI programs accountable.


title: Introduction: Changing Business Systems in the Netherlands in the Twentieth Century

abstract: The organization of economic activities differs among countries and over time. Differences between nations have been highlighted in academic discussions about national business systems and the varieties of capitalism. This group of articles about the Dutch business system contributes to these debates by offering new empirical research from the perspective of a small, open economy and highlighting changes that have occurred during the second half of the twentieth century. While they discuss developments in the Netherlands, the articles also explore general themes, including corporate governance, cartels, and the organization of multinational companies. While the articles show that business systems are in constant flux, comparisons between the Dutch and U.S. systems seem to suggest that each moves at a different pace. A particularly striking aspect of the Dutch stories is the large impact of developments abroad.


title: Encouraging information security behaviors in organizations: Role of penalties, pressures and perceived effectiveness

abstract: Secure management of information systems is crucially important in information intensive organizations. Although most organizations have long been using security technologies, it is well known that technology tools alone are not sufficient. Thus, the area of end-user security behaviors in organizations has gained an increased attention. In information security observing end-user security behaviors is challenging. Moreover, recent studies have shown that the end users have divergent security views. The inability to monitor employee IT security behaviors and divergent views regarding security policies, in our view, provide a setting where the principal agent paradigm applies. In this paper, we develop and test a theoretical model of the incentive effects of penalties, pressures and perceived effectiveness of employee actions that enhances our understanding of employee compliance to information security policies. Based on 312 employee responses from 77 organizations, we empirically validate and test the model. Our findings suggest that security behaviors can be influenced by both intrinsic and extrinsic motivators. Pressures exerted by subjective norms and peer behaviors influence employee information security behaviors. Intrinsic motivation of employee perceived effectiveness of their actions was also found to play an important role in security policy compliance intentions. In analyzing the penalties, certainty of detection was found to be significant while surprisingly, severity of punishment was found to have a negative effect on security behavior intentions. We discuss the implications of our findings for theory and practice.


title: Fertility, Politics, and Religion 1 Running head: FERTILITY, POLITICS, AND RELIGION Forthcoming in Psychological Science The Fluctuating Female Vote: Politics, Religion, and the Ovulatory Cycle

abstract: Each month, many women experience an ovulatory cycle that regulates fertility. Although research has found that this cycle influences women’s mating preferences, we proposed that it might also change women’s political and religious views. Building on theory suggesting that political and religious orientation are linked to reproductive goals, we tested how fertility influenced women’s politics, religiosity, and voting in the 2012 U.S. presidential election. In two studies with large and diverse samples, ovulation had drastically different effects on single women and women in committed relationships. Ovulation led single women to become more liberal, less religious, and more likely to vote for Barack Obama. In contrast, ovulation led women in committed relationships to become more conservative, more religious, and more likely to vote for Mitt Romney. In addition, ovulation-induced changes in political orientation mediated women’s voting behavior. Overall, the ovulatory cycle not only influences women’s poli...


Named entity recognition : a local grammar-based approach


title: Nanoparticle Properties, Behavior, Fate in Aquatic Systems and Characterization Methods

abstract: The global demand for a wide variety of applications based on engineered nanoparticles (ENPs)has expanded the worldwide industrial scale production and inevitably released these materials into the environment. The increasing existence of NPs and its impact towards human health and the environment especially the aquatic system has sparked a great concern among both the scientific community and the public. It is therefore crucial to gain an in depth understanding of the properties the manufactured nanoparticles possess along with the various transformations they undergo that determine their behaviour and mobility. This review begins by addressing the fundamental physicochemical aspects of manufactured oxide nanoparticles with detailed attention given specifically to ZnO as a representative example in a separated section. The literature collected is summarized and focused on the essential point of view to evaluate their occurrence, fate and transport in the natural aquatic environment as a result of their interactions with other nanoparticles or natural colloids. Key methods and principles of nanoparticle characterization are also presented.


EVALUATION OF PROMISING FABA BEAN (Vicia faba L.) GENOTYPES FOR AGRONOMIC AND SEED TECHNOLOGY CHARACTERS IN NORTH EGYPT


Design and Implementation of Focused Web Crawler Using Genetic Algorithm


title: FPGA based floating-point library for CORDIC algorithms

abstract: Computation of floating-point transcendental functions has a relevant importance in a wide variety of scientific applications, where the area cost, error and latency are important requirements to be attended. This paper describes a flexible FPGA implementation of a parameterizable floating-point library for computing sine, cosine, arctangent and exponential functions using the CORDIC algorithm. The novelty of the proposed architecture is that by sharing the same resources the CORDIC algorithm can be used in two operation modes, allowing it to compute the sine, cosine or arctangent functions. Additionally, in case of the exponential function, the architectures change automatically between the CORDIC or a Taylor approach, which helps to improve the precision characteristics of the circuit, specifically for small input values after the argument reduction. Synthesis of the circuits and an experimental analysis of the errors have demonstrated the correctness and effectiveness of the implemented cores and allow the designer to choose, for general-purpose applications, a suitable bit-width representation and number of iterations of the CORDIC algorithm.


title: API 541 5th edition - Revisions, updates and improvements

abstract: API 541 5th edition was written by a taskforce composed of users, consultants and manufacturers to provide a common performance standard to cover the minimum requirements for form-wound squirrel-cage induction motors 375 kW (500 HP) and larger. The Standard is designed to outline the requirements of all aspects of an induction machine. When compared to earlier editions, this revision has enhancements making it easier to purchase and specify a more durable machine. This edition has new requirements in the areas of frame vibration and insulation tests; plus improved sections concerning dynamic analysis and thermal withstand capabilities. The Standard is used in conjunction with the extensively modified data sheets.


Experiments in Candidate Phrase Selection for Financial Named Entity Extraction - A Demo


title: Towards building large-scale distributed systems for twitter sentiment analysis

abstract: In recent years, social networks have become very popular. Twitter, a micro-blogging service, is estimated to have about 200 million registered users and these users create approximately 65 million tweets a day. Twitter users usually show their opinion about topics of their interest. The challenge is that each tweet is limited in 140 characters, and is hence very short. It may contain slang and misspelled words. Thus, it is difficult to apply traditional NLP techniques which are designed for working with formal languages, into Twitter domain. Another challenge is that the total volume of tweets is extremely high, and it takes a long time to process. In this paper, we describe a large-scale distributed system for real-time Twitter sentiment analysis. Our system consists of two components: a lexicon builder and a sentiment classifier. These two components are capable of running on a large-scale distributed system since they are implemented using a MapReduce framework and a distributed database model. Thus, our lexicon builder and sentiment classifier are scalable with the number of machines and the size of data. The experiments also show that our lexicon has a good quality in opinion extraction, and the accuracy of the sentiment classifier can be improved by combining the lexicon with a machine learning technique.


title: On the usability of deep networks for object-based image analysis

abstract: As computer vision before, remote sensing has been radically changed by the introduction of Convolution Neural Networks. Land cover use, object detection and scene understanding in aerial images rely more and more on deep learning to achieve new state-of-the-art results. Recent architectures such as Fully Convolutional Networks (Long et al., 2015) can even produce pixel level annotations for semantic mapping. In this work, we show how to use such deep networks to detect, segment and classify different varieties of wheeled vehicles in aerial images from the ISPRS Potsdam dataset. This allows us to tackle object detection and classification on a complex dataset made up of visually similar classes, and to demonstrate the relevance of such a subclass modeling approach. Especially, we want to show that deep learning is also suitable for object-oriented analysis of Earth Observation data. First, we train a FCN variant on the ISPRS Potsdam dataset and show how the learnt semantic maps can be used to extract precise segmentation of vehicles, which allow us studying the repartition of vehicles in the city. Second, we train a CNN to perform vehicle classification on the VEDAI (Razakarivony and Jurie, 2016) dataset, and transfer its knowledge to classify candidate segmented vehicles on the Potsdam dataset.


title: Transferring Landmark Annotations for Cross-Dataset Face Alignment

abstract: Dataset bias is a well known problem in object recognition domain. This issue, nonetheless, is rarely explored in face alignment research. In this study, we show that dataset plays an integral part of face alignment performance. Specifically, owing to face alignment dataset bias, training on one database and testing on another or unseen domain would lead to poor performance. Creating an unbiased dataset through combining various existing databases, however, is non-trivial as one has to exhaustively re-label the landmarks for standardisation. In this work, we propose a simple and yet effective method to bridge the disparate annotation spaces between databases, making datasets fusion possible. We show extensive results on combining various popular databases (LFW, AFLW, LFPW, HELEN) for improved cross-dataset and unseen data alignment.


title: Sex and Violence in the Slasher Horror Film: A Content Analysis of Gender Differences in the Depiction of Violence By

abstract: The slasher horror film has been the subject of frequent criticism based on the assumption that female characters in these films are more likely to be the victims of serious, graphic violence that is juxtaposed with explicit sexual imagery. The purpose of this study was to address limitations inherent in previous analyses of slasher films and examine whether gender differences exist in the nature of violent presentations. A content analysis of several indicators of violent and sexual content was conducted using a random sample of 50 slasher films that were released in North America between 1960 and 2007. Findings suggested that there are several significant gender differences in the nature of violent presentations found in slasher films. In general, female characters were more likely to be victims of less serious and graphic forms of violence, but were also significantly more likely to be victimized in scenes involving a concomitant presentation of sex and violence.


title: Blinky blocks: a physical ensemble programming platform

abstract: A major impediment to understanding programmable matter is the lack of an existing system with sufficiently many modules of sufficient capabilities. In this paper we describe the requirements of physically distributed ensembles and discuss the use of the distributed programming language Meld to program ensembles of these units. We demonstrate a new system designed to meet these requirements called Blinky Blocks and discuss the hardware design we used to create 100 of these modules.


Community-Based Question Answering via Asymmetric Multi-Faceted Ranking Network Learning.


title: A novel 3D ear reconstruction method using a single image

abstract: To achieve denser 3D ear model from less controlled 2D image, we explore a 3D Ear Morphable Model (3DEMM) for 3D ear reconstruction using a single 2D ear image. Considering the unique structure of ear, we propose a novel dense corresponding method. The proposed method can overcome the shortcoming of optical flow based method and achieve pixel level dense correspondences based on physiological features of ear without choosing a reference ear. Novel 3D ear shape can be recovered from a single ear image based on the proposed 3D ear morphable model. Extensive experimental results have shown that our proposed method can obtain denser 3D ear model with lower cost and higher efficiency than existing methods.


title: A quasi-passive compliant stance control Knee-Ankle-Foot Orthosis

abstract: In this paper, we present the design of a novel quasi-passive stance-control orthosis that implements a natural amount of knee compliance during the weight acceptance phase and potentially the entire stance phase of the gait, and allows for free motion during the rest of the gait. We explain that the unaffected knee behaves close to a linear torsional spring in stance and hypothesize that an assistive device that places a linear spring of appropriate stiffness in parallel with the knee can help restore the natural behavior of the joint in stance. We present the design of a friction-based latching mechanism and a control algorithm that engages the spring in parallel with the knee in stance and disengages it during the swing phase of gait, and explain how this module is implemented into a brace in order to create a novel class of compliant stance control orthosis. The device is quasi-passive in that a small actuator serves to lock and unlock the spring module, but the device otherwise requires no actuation and very little power, computation, and control to operate.


title: A simulation approach to evaluating design decisions in MapReduce setups

abstract: MapReduce has emerged as a model of choice for supporting modern data-intensive applications. The model is easy-to-use and promising in reducing time-to-solution. It is also a key enabler for cloud computing, which provides transparent and flexible access to a large number of compute, storage and networking resources. Setting up and operating a large MapReduce cluster entails careful evaluation of various design choices and run-time parameters to achieve high efficiency. However, this design space has not been explored in detail. In this paper, we adopt a simulation approach to systematically understanding the performance of MapReduce setups. The resulting simulator, MRPerf, captures such aspects of these setups as node, rack and network configurations, disk parameters and performance, data layout and application I/O characteristics, among others, and uses this information to predict expected application performance. Specifically, we use MRPerf to explore the effect of several component inter-connect topologies, data locality, and software and hardware failures on overall application performance. MR-Perf allows us to quantify the effect of these factors, and thus can serve as a tool for optimizing existing MapReduce setups as well as designing new ones.


title: Bioinspired Grippers for Natural Curved Surface Perching

abstract: Perching and climbing as animals do is useful to aerial robots for extending mission life and for interacting with the physical world because flight is energetically costly. This paper presents the design and modeling of a claw or spine based gripper for perching on rough, curved surfaces. Drawing inspiration from the opposed grip techniques found in animals, we focus on the design considerations associated with surface geometry and preload. A model elucidates the relationship between these variables, and a mechanism demonstrates the effectiveness of the opposed grip technique.


title: Computer-assisted animation of line and paint in Disney's Paperman

abstract: We present a system which allows animators to combine CG animation's strengths -- temporal coherence, spatial stability, and precise control -- with traditional animation's expressive and pleasing line-based aesthetic. Our process begins as an ordinary 3D CG animation, but later steps occur in a light-weight and responsive 2D environment, where an artist can draw lines which the system can then automatically move through time using vector fields derived from the 3D animation, thereby maximizing the benefits of both environments. Unlike with an automated "toon-shader", the final look was directly in the hands of the artists in a familiar workflow, allowing their artistry and creative power to be fully utilized. This process was developed during production of the short film Paperman at Walt Disney Animation Studios, but its application is extensible to other styles of animation as well.


title: A discriminative CNN video representation for event detection

abstract: In this paper, we propose a discriminative video representation for event detection over a large scale video dataset when only limited hardware resources are available. The focus of this paper is to effectively leverage deep Convolutional Neural Networks (CNNs) to advance event detection, where only frame level static descriptors can be extracted by the existing CNN toolkits. This paper makes two contributions to the inference of CNN video representation. First, while average pooling and max pooling have long been the standard approaches to aggregating frame level static features, we show that performance can be significantly improved by taking advantage of an appropriate encoding method. Second, we propose using a set of latent concept descriptors as the frame descriptor, which enriches visual information while keeping it computationally affordable. The integration of the two contributions results in a new state-of-the-art performance in event detection over the largest video datasets. Compared to improved Dense Trajectories, which has been recognized as the best video representation for event detection, our new representation improves the Mean Average Precision (mAP) from 27.6% to 36.8% for the TRECVID MEDTest 14 dataset and from 34.0% to 44.6% for the TRECVID MEDTest 13 dataset.


title: A Highly Backdrivable, Lightweight Knee Actuator for Investigating Gait in Stroke

abstract: Many of those who survive a stroke develop a gait disability known as stiff-knee gait (SKG). Characterized by reduced knee flexion angle during swing, people with SKG walk with poor energy efficiency and asymmetry due to the compensatory mechanisms required to clear the foot. Previous modeling studies have shown that knee flexion activity directly before the foot leaves the ground, and this should result in improved knee flexion angle during swing. The goal of this research is to physically test this hypothesis using robotic intervention. We developed a device that is capable of assisting knee flexion torque before swing but feels imperceptible (transparent) for the rest of the gait cycle. This device uses sheathed Bowden cable to control the deflection of a compliant torsional spring in a configuration known as a Series Elastic Remote Knee Actuator (SERKA). In this investigation, we describe the design and evaluation of SERKA, which includes a pilot experiment on stroke subjects. SERKA could supply a substantial torque (12 N· m) in less than 20 ms, with a maximum torque of 41 N·m. The device resisted knee flexion imperceptibly when desired, at less than 1 N·m rms torque during normal gait. With the remote location of the actuator, the user experiences a mass of only 1.2 kg on the knee. We found that the device was capable of increasing both peak knee flexion angle and velocity during gait in stroke subjects. Thus, the SERKA is a valid experimental device that selectively alters knee kinetics and kinematics in gait after stroke.


title: PUBCRAWL: Protecting Users and Businesses from CRAWLers

abstract: Web crawlers are automated tools that browse the web to retrieve and analyze information. Although crawlers are useful tools that help users to find content on the web, they may also be malicious. Unfortunately, unauthorized (malicious) crawlers are increasingly becoming a threat for service providers because they typically collect information that attackers can abuse for spamming, phishing, or targeted attacks. In particular, social networking sites are frequent targets of malicious crawling, and there were recent cases of scraped data sold on the black market and used for blackmailing. ::: ::: In this paper, we introduce PUBCRAWL, a novel approach for the detection and containment of crawlers. Our detection is based on the observation that crawler traffic significantly differs from user traffic, even when many users are hidden behind a single proxy. Moreover, we present the first technique for crawler campaign attribution that discovers synchronized traffic coming from multiple hosts. Finally, we introduce a containment strategy that leverages our detection results to efficiently block crawlers while minimizing the impact on legitimate users. Our experimental results in a large, well-known social networking site (receiving tens of millions of requests per day) demonstrate that PUBCRAWL can distinguish between crawlers and users with high accuracy. We have completed our technology transfer, and the social networking site is currently running PUB-CRAWL in production.


title: Support Vector Guided Dictionary Learning

abstract: Discriminative dictionary learning aims to learn a dictionary from training samples to enhance the discriminative capability of their coding vectors. Several discrimination terms have been proposed by assessing the prediction loss (e.g., logistic regression) or class separation criterion (e.g., Fisher discrimination criterion) on the coding vectors. In this paper, we provide a new insight on discriminative dictionary learning. Specifically, we formulate the discrimination term as the weighted summation of the squared distances between all pairs of coding vectors. The discrimination term in the state-of-the-art Fisher discrimination dictionary learning (FDDL) method can be explained as a special case of our model, where the weights are simply determined by the numbers of samples of each class. We then propose a parameterization method to adaptively determine the weight of each coding vector pair, which leads to a support vector guided dictionary learning (SVGDL) model. Compared with FDDL, SVGDL can adaptively assign different weights to different pairs of coding vectors. More importantly, SVGDL automatically selects only a few critical pairs to assign non-zero weights, resulting in better generalization ability for pattern recognition tasks. The experimental results on a series of benchmark databases show that SVGDL outperforms many state-of-the-art discriminative dictionary learning methods.


title: Powerful and consistent analysis of likert-type ratingscales

abstract: Likert-type scales are used extensively during usability evaluations, and more generally evaluations of interactive experiences, to obtain quantified data regarding attitudes, behaviors, and judgments of participants. Very often this data is analyzed using parametric statistics like the Student t-test or ANOVAs. These methods are chosen to ensure higher statistical power of the test (which is necessary in this field of research and practice where sample sizes are often small), or because of the lack of software to handle multi-factorial designs nonparametrically. With this paper we present to the HCI audience new developments from the field of medical statistics that enable analyzing multiple factor designs nonparametrically. We demonstrate the necessity of this approach by showing the errors in the parametric treatment of nonparametric data in experiments of the size typically reported in HCI research. We also provide a practical resource for researchers and practitioners who wish to use these new methods.


title: Connectionist Models and Their Properties

abstract: Much of the progress in the fields constituting cognitive science has been based upon the use of explicit information processing models, almost exclusively patterned after conventional serial computers. An extension of these ideas to massively parallel, connectionist models appears to offer a number of advantages. After a preliminary discussion, this paper introduces a general connectionist model and considers how it might be used in cognitive science. Among the issues addressed are: stability and noise-sensitivity, distributed decision-making, time and sequence problems, and the representation of complex concepts.


title: A Survey of Online Experiment Design with the Stochastic Multi-Armed Bandit

abstract: Adaptive and sequential experiment design is a well-studied area in numerous domains. We survey and synthesize the work of the online statistical learning paradigm referred to as multi-armed bandits integrating the existing research as a resource for a certain class of online experiments. We first explore the traditional stochastic model of a multi-armed bandit, then explore a taxonomic scheme of complications to that model, for each complication relating it to a specific requirement or consideration of the experiment design context. Finally, at the end of the paper, we present a table of known upper-bounds of regret for all studied algorithms providing both perspectives for future theoretical work and a decision-making tool for practitioners looking for theoretical guarantees.


title: Testing malware detectors

abstract: In today's interconnected world, malware, such as worms and viruses, can cause havoc. A malware detector (commonly known as virus scanner) attempts to identify malware. In spite of the importance of malware detectors, there is a dearth of testing techniques for evaluating them. We present a technique based on program obfuscation for generating tests for malware detectors. Our technique is geared towards evaluating the resilience of malware detectors to various obfuscation transformations commonly used by hackers to disguise malware. We also demonstrate that a hacker can leverage a malware detector's weakness in handling obfuscation transformations and can extract the signature used by a detector for a specific malware. We evaluate three widely-used commercial virus scanners using our techniques and discover that the resilience of these scanners to various obfuscations is very poor.


Legal Translation and Functionalist Approaches : a Contradiction in Terms ?


title: The Effect of Mulligan Mobilization Technique in Older Adults with Neck Pain: A Randomized Controlled, Double-Blind Study

abstract: Background ::: The purpose of this study was to examine the effect of Mulligan mobilization technique (MMT) on pain, range of motion (ROM), functional level, kinesiophobia, depression, and quality of life (QoL) in older adults with neck pain (NP). ::: ::: ::: Methods ::: Forty-two older adults with NP were included in the study, and they were randomly divided into two groups: traditional physiotherapy (TP) group and traditional physiotherapy-Mulligan mobilization (TPMM) group. Treatment program was scheduled for 10 sessions. Participants were assessed in terms of pain, ROM, functional level, kinesiophobia, depression, and QoL both pre- and posttreatment. ::: ::: ::: Results ::: Pain, ROM, functional level, kinesiophobia, depression, and QoL improved in both groups following treatment (p < 0.05). When comparing effects of these two treatment programs, it was observed that the TPMM group had a better outcome (p < 0.05) in terms of ROM, kinesiophobia, depression, and QoL. ::: ::: ::: Conclusion ::: In older adults with NP, MMT has been found to have significant effects on pain, ROM, functional level, kinesiophobia, depression, and QoL as long as it is performed by a specialist. "This trial is registered with NCT03507907".


title: A design and implementation of active network socket programming

abstract: The concept of programmable nodes and active networks introduces programmability into communication networks. Code and data can be sent and modified on their routes to the destinations. Various research groups have designed and implemented their own design platforms. Each design has its own benefits and drawbacks. Moreover, there exists an interoperability problem among platforms. As a result, we introduce a concept that is similar to network socket programming. We intentionally establish a set of simple interfaces for programming active applications. This set of interfaces, known as active network socket programming (ANSP), will be working on top of all other execution environments in the future. Therefore, the ANSP offers a concept that is similar to "write once, run everywhere". It is an open programming model that active applications can work on all execution environments. It solves the heterogeneity within active networks. This is especially useful when active applications need to access all regions within a heterogeneous network to deploy a special service at critical points or to monitor the performance of the entire networks. Instead of introducing a new platform, our approach provides a thin, transparent layer on top of existing environments that can be easily installed for all active applications.


title: A fast and robust point tracking algorithm

abstract: We present an algorithm that efficiently tracks a predefined set of landmark points in a time sequence of images. The algorithm iteratively optimizes the correspondences between the point measurements in the images, while allowing for spurious and missing point measurements. This trajectory based approach hypothesizes missing points by interpolation. Spurious measurements are either left our because they do not form the optimal correspondences or are removed afterwards if they have the smoothness or other constraint exceed its predetermined maximum.


title: A hierarchical multiscale and multiangle system for human face detection in a complex background using gravity-center template

abstract: Abstract This paper presents a novel faster search scheme of gravity-center template matching compared with the traditional search method in an image for human face detection, which significantly saves the time consumed in rough detection of human faces in a mosaic image. Besides, the system is able to detect rather slanted faces (−25°∼25°) and faces with much horizontal rotating angles (−45°∼45°) and vertical rotating angles (−30°∼30°), which are in various sizes and at unknown locations in an unconstrained background. A specially defined recognition rate of 86.7% has been reached for such faces.


title: Dual Switches DC/DC Converter With Three-Winding-Coupled Inductor and Charge Pump

abstract: In order to obtain a high step-up voltage gain, high-efficiency converter, this paper proposed a dual switches dc/dc converter with three-winding-coupled inductor and charge pump. The proposed converter composed of dual switches structure, three-winding-coupled inductor, and charge pump. This combination facilitates realization of high step-up voltage gain with a low voltage/current stress on the power switches. Meanwhile, the voltage across the diodes is low and the diode reverse-recovery problem is alleviated by the leakage inductance of the three-winding-coupled inductor. Taking all these into consideration, the efficiency can be high. This paper illustrated the operation principle of the proposed converter; discussed the effect of leakage inductance on voltage gain; the conditions of zero current shutting off of the diodes are illustrated; the voltage and current stress of the power devices are shown; a comparison between the performance of the proposed converter and previous high step-up converters was conducted. Finally, a prototype rated at 500 W has been established, and the experimental results verify the correctness of the analysis.