title: Bias in computer systems

abstract: From an analysis of actual cases, three categories of bias in computer systems have been developed: preexisting, technical, and emergent. Preexisting bias has its roots in social institutions, practices, and attitudes. Technical bias arises from technical constraints of considerations. Emergent bias arises in a context of use. Although others have pointed to bias inparticular computer systems and have noted the general problem, we know of no comparable work that examines this phenomenon comprehensively and which offers a framework for understanding and remedying it. We conclude by suggesting that freedom from bias should by counted amoung the select set of criteria—including reliability, accuracy, and efficiency—according to which the quality of systems in use in society should be judged.


title: Why eve and mallory love android: an analysis of android SSL (in)security

abstract: Many Android apps have a legitimate need to communicate over the Internet and are then responsible for protecting potentially sensitive data during transit. This paper seeks to better understand the potential security threats posed by benign Android apps that use the SSL/TLS protocols to protect data they transmit. Since the lack of visual security indicators for SSL/TLS usage and the inadequate use of SSL/TLS can be exploited to launch Man-in-the-Middle (MITM) attacks, an analysis of 13,500 popular free apps downloaded from Google's Play Market is presented. We introduce MalloDroid, a tool to detect potential vulnerability against MITM attacks. Our analysis revealed that 1,074 (8.0%) of the apps examined contain SSL/TLS code that is potentially vulnerable to MITM attacks. Various forms of SSL/TLS misuse were discovered during a further manual audit of 100 selected apps that allowed us to successfully launch MITM attacks against 41 apps and gather a large variety of sensitive data. Furthermore, an online survey was conducted to evaluate users' perceptions of certificate warnings and HTTPS visual security indicators in Android's browser, showing that half of the 754 participating users were not able to correctly judge whether their browser session was protected by SSL/TLS or not. We conclude by considering the implications of these findings and discuss several countermeasures with which these problems could be alleviated.


Improving Sub-Phone Modeling for Better Native Language Identification with Non-Native English Speech


title: The formal specification for the inventory system using Z language

abstract: Formal methods use mathematical notations to precisely express requirements specification. The formal specification removes ambiguity which is inherently present in natural language specification.Formal specification also addresses the software reliability. In this paper, we present the formal specification for the inventory system by using Z language.Based from the scenario of the inventory system, we present the Unified Modeling Language (UML) specification by means of use case diagram and class diagram.We then present the Z schema based from the UML specification. We also show the consistency between UML specification and ::: Z schema for this inventory system.The Z schema can effectively improve system reliability and reduce defect in developing the system.


title: 10 kV and 15 kV silicon carbide power MOSFETs for next-generation energy conversion and transmission systems

abstract: Advanced high-voltage (10 kV-15 kV) silicon carbide (SiC) power MOSFETs described in this paper have the potential to significantly impact the system performance, size, weight, high-temperature reliability, and cost of next-generation energy conversion and transmission systems. In this paper, we report our recently developed 10 kV/20 A SiC MOSFETs with a chip size of 8.1 × 8.1 mm2 and a specific on-resistance (RON, SP) of 100 MΩ-cm2 at 25 °C. We also developed 15 kV/10 A SiC power MOSFETs with a chip size of 8 × 8 mm2 and a RON, SP of 204 mQ cm2 at 25 °C. To our knowledge, this 15 kV SiC MOSFET is the highest voltage rated unipolar power switch. Compared to the commercial 6.5 kV Silicon (Si) IGBTs, these 10 kV and 15 kV SiC MOSFETs exhibit extremely low switching losses even when they are switched at 2-3× higher voltage. The benefits of using these 10 kV and 15 kV SiC MOSFETs include simplifying from multilevel to two-level topology and removing the need for time-interleaving by improving the switching frequency from a few hundred Hz for Si based systems to ≥ 10 kHz for hard-switched SiC based systems.


title: Hardware architecture for high-accuracy real-time pedestrian detection with CoHOG features

abstract: Co-occurrence histograms of oriented gradients (CoHOG) is a powerful feature descriptor for pedestrian detection. However, its calculation cost is large because the feature vector for the CoHOG descriptor is very high-dimensional. In this paper, in order to achieve real-time detection on embedded systems, we propose a novel hardware architecture for the CoHOG feature extraction. Our architecture exploits high degree of fine-grained parallelism and adopts an efficient histogram generator combined with a linear SVM classifier. The proposed architecture is implemented on a Xilinx Virtex-5 FPGA and it achieves real-time pedestrian detection on 38 fps 320×240 video. That is more than 100 times faster than the execution on a state-of-the-art Intel CPU.


title: Automatic Prediction of Impressions in Time and across Varying Context: Personality, Attractiveness and Likeability

abstract: In this paper, we propose a novel multimodal framework for automatically predicting the impressions of extroversion , agreeableness , conscientiousness , neuroticism , openness , attractiveness and likeability continuously in time and across varying situational contexts. Differently from the existing works, we obtain visual-only and audio-only annotations continuously in time for the same set of subjects, for the first time in the literature, and compare them to their audio-visual annotations. We propose a time-continuous prediction approach that learns the temporal relationships rather than treating each time instant separately. Our experiments show that the best prediction results are obtained when regression models are learned from audio-visual annotations and visual cues, and from audio-visual annotations and visual cues combined with audio cues at the decision level. Continuously generated annotations have the potential to provide insight into better understanding which impressions can be formed and predicted more dynamically, varying with situational context, and which ones appear to be more static and stable over time.


title: FORM FOLLOWS FLOW: A Material-driven Computational Workflow For Digital Fabrication of Large-Scale Hierarchically Structured Objects

abstract: In the natural world shape and matter are structured through growth and adaptation, resulting in highly tunable and hierarchically structured constructs, which exhibit excellent mechanical properties. Conventional digital design tools and processes however display little integration between shape formation and materialization resulting in the disassociation between shape and matter. This paper proposes a framework and an application for the integration of shape and matter by implementing a novel material-driven manufacturing platform and computational workflow to derive large-scale hierarchically structured objects. The workflow is comprised of material-driven methods and techniques such as environmentally informed property variation, material-based hierarchical structuring, and hydration-guided shape formation. The platform is composed of a custom multi-barrel deposition head attached to a robotic positioning system. Components are physically form-found by digitally distributing natural polymer gels with functionally graded properties informed by desired structural and environmental performance. In this approach, properties such as material viscosity, deposition velocity, and nozzle pressure drive the printing of two-dimensional patterns induced into three-dimensional shapes by natural evaporation. The workflow associates material, environmental and manufacturing considerations with virtual design modeling tools, challenging traditional design workflows, prioritizing process over product and flow over form.


title: Anatomy and Physiology of the Aging Neck

abstract: INTRODUCTIONNeck rejuvenation and contouring procedurescontinue to expand and evolve, with a multitudeof techniques designed to address the clinicalconsequences related to aging. Patients presentwith concerns regarding the aged appearance oftheirneck,oftencausedbychangesinskinquality,fat accumulation, muscle tone, sun damage, orchanges after weight gain or loss.


title: 122 GHz radar sensor based on a monostatic SiGe-BiCMOS IC with an on-chip antenna

abstract: In this paper, a short range monostatic radar sensor operating at 122 GHz is presented. The millimeter-wave frontend, including the on-chip antenna, is based on an integrated circuit realized in SiGe BiCMOS technology. The setup of the radar sensor is introduced and measurement results for FMCW modulation demonstrate the performance of the radar frontend.


title: The DSM Diagnostic Criteria for Gender Identity Disorder in Adolescents and Adults

abstract: Apart from some general issues related to the Gender Identity Disorder (GID) diagnosis, such as whether it should stay in the DSM-V or not, a number of problems specifically relate to the current criteria of the GID diagnosis for adolescents and adults. These problems concern the confusion caused by similarities and differences of the terms transsexualism and GID, the inability of the current criteria to capture the whole spectrum of gender variance phenomena, the potential risk of unnecessary physically invasive examinations to rule out intersex conditions (disorders of sex development), the necessity of the D criterion (distress and impairment), and the fact that the diagnosis still applies to those who already had hormonal and surgical treatment. If the diagnosis should not be deleted from the DSM, most of the criticism could be addressed in the DSM-V if the diagnosis would be renamed, the criteria would be adjusted in wording, and made more stringent. However, this would imply that the diagnosis would still be dichotomous and similar to earlier DSM versions. Another option is to follow a more dimensional approach, allowing for different degrees of gender dysphoria depending on the number of indicators. Considering the strong resistance against sexuality related specifiers, and the relative difficulty assessing sexual orientation in individuals pursuing hormonal and surgical interventions to change physical sex characteristics, it should be investigated whether other potentially relevant specifiers (e.g., onset age) are more appropriate.


title: Impaired TNFα-induced A20 expression in E1A/Ras-transformed cells

abstract: : Tumour necrosis factor (TNF) is capable of activating the cell death pathway, and has been implicated in killingtransformed cells. However, TNF also activates survival signals, including NF-kB activation and the subsequent expression of anti-apoptotic genes, leading to protection against TNF toxicity.


title: Global rank-invariant set normalization (GRSN) to reduce systematic distortions in microarray data

abstract: Background ::: Microarray technology has become very popular for globally evaluating gene expression in biological samples. However, non-linear variation associated with the technology can make data interpretation unreliable. Therefore, methods to correct this kind of technical variation are critical. Here we consider a method to reduce this type of variation applied after three common procedures for processing microarray data: MAS 5.0, RMA, and dChip®.


title: FlexRAN: A Flexible and Programmable Platform for Software-Defined Radio Access Networks

abstract: Although the radio access network (RAN) part of mobile networks offers a significant opportunity for benefiting from the use of SDN ideas, this opportunity is largely untapped due to the lack of a software-defined RAN (SD-RAN) platform. We fill this void with FlexRAN, a flexible and programmable SD-RAN platform that separates the RAN control and data planes through a new, custom-tailored southbound API. Aided by virtualized control functions and control delegation features, FlexRAN provides a flexible control plane designed with support for real-time RAN control applications, flexibility to realize various degrees of coordination among RAN infrastructure entities, and programmability to adapt control over time and easier evolution to the future following SDN/NFV principles. We implement FlexRAN as an extension to a modified version of the OpenAirInterface LTE platform, with evaluation results indicating the feasibility of using FlexRAN under the stringent time constraints posed by the RAN. To demonstrate the effectiveness of FlexRAN as an SD-RAN platform and highlight its applicability for a diverse set of use cases, we present three network services deployed over FlexRAN focusing on interference management, mobile edge computing and RAN sharing.


title: When participants do the capturing: the role of media in diary studies

abstract: In this paper, we investigate how the choice of media for capture and access affects the diary study method. The diary study is a method of understanding participant behavior and intent in situ that minimizes the effects of observers on participants. We first situate diary studies within a framework of field studies and review related literature. We then report on three diary studies we conducted that involve photographs, audio recordings, location information and tangible artifacts. We then analyze our findings, specifically addressing the following questions: How do context information and episodic memory prompts captured by participants vary with media? In what way do different media "jog" memory? How do different media affect the diary study process? These questions are particularly important for diary studies because they can be especially useful as compared to other methods when a participant intends to do an action but does not or when actions are particularly difficult to sense. We also built and tested a tool based on participant and researcher frustrations with the method. Our contribution includes suggested modifications to traditional diary techniques that enable annotation and review of captured media; a new variation on the diary study appropriate for researchers using digital capture media; and a lightweight tool to support it, motivated by past work and findings from our studies.


title: Uncertain Fate of Fair Sampling in Quantum Annealing

abstract: Recently, it was demonstrated both theoretically and experimentally on the D-Wave quantum annealer that transverse-field quantum annealing does not find all ground states with equal probability. In particular, it was proposed that more complex driver Hamiltonians beyond transverse fields might mitigate this shortcoming. Here, we investigate the mechanisms of (un)fair sampling in quantum annealing. While higher-order terms can improve the sampling for selected small problems, we present multiple counterexamples where driver Hamiltonians that go beyond transverse fields do not remove the sampling bias. Using perturbation theory we explain why this is the case. In addition, we present large-scale quantum Monte Carlo simulations for spin glasses with known degeneracy in two space dimensions and demonstrate that the fair-sampling performance of quadratic driver terms is comparable to standard transverse-field drivers. Our results suggest that quantum annealing machines are not well suited for sampling applications, unless post-processing techniques to improve the sampling are applied.


Assessing the effects of gami fi cation in the classroom : A longitudinal study on intrinsic motivation , social comparison , satisfaction , effort , and academic performance


title: Progress in carbon dioxide separation and capture: A review

abstract: This article reviews the progress made in CO2 separation and capture research and engineering. Various technologies, such as absorption, adsorption, and membrane separation, are thoroughly discussed. New concepts such as chemical-looping combustion and hydrate-based separation are also introduced briefly. Future directions are suggested. Sequestration methods, such as forestation, ocean fertilization and mineral carbonation techniques are also covered. Underground injection and direct ocean dump are not covered.


title: Comparing semiliterate and illiterate users' ability to transition from audio+text to text-only interaction

abstract: Multimodal interfaces with little or no text have been shown to be useful for users with low literacy. However, this research has not differentiated between the needs of the fully illiterate and semiliterate - those who have basic literacy but cannot read and write fluently. Text offers a fast and unambiguous mode of interaction for literate users and the exposure to text may allow for incidental improvement of reading skills. We conducted two studies that explore how semiliterate users with very little education might benefit from a combination of text and audio as compared to illiterate and literate users. Results show that semiliterate users reduced their use of audio support even during the first hour of use and over several hours this reduction was accompanied by a gain in visual word recognition; illiterate users showed no similar improvement. Semiliterate users should thus be treated differently from illiterate users in interface design.


D Mesh Segmentation Methodologies for CAD applications


More Efficient Topic Modelling Through a Noun Only Approach


title: Decomposing technical efficiency and scale elasticity in two-stage network DEA

abstract: The constant returns to scale assumption maintained by neoclassical theorists for justifying the black-box structure of production technology in long run does not necessarily allow one to infer that there are no scale benefits available in its sub-technologies. Most of real-life production technologies are multi-stage in nature, and the sources of increasing returns lie in the sub-technologies. It is, therefore, imperative to estimate the scale economies of a firm not only for the network technology but also for the sub-technologies. To accomplish this, two approaches are suggested in this contribution, based on the premise concerning whether a network technology construct considers allocative inefficiency. The first approach, which is ours, makes use of a single network technology for two interdependent sub-technologies. The second approach, which is due to Kao and Hwang (2011), however, assumes complete allocative efficiency by considering two independent sub-technology frontiers, one for each sub-technology. The distinction between these two approaches is important from a policy point of view since the network efficiencies revealed from these two approaches have distinctive causative factors that do not permit them to be used interchangeably.


title: ProvDB: A System for Lifecycle Management of Collaborative Analysis Workflows

abstract: As data-driven methods are becoming pervasive in a wide variety of disciplines, there is an urgent need to develop scalable and sustainable tools to simplify the process of data science, to make it easier to keep track of the analyses being performed and datasets being generated, and to enable introspection of the workflows. In this paper, we describe our vision of a unified provenance and metadata management system to support lifecycle management of complex collaborative data science workflows. We argue that a large amount of information about the analysis processes and data artifacts can, and should be, captured in a semi-passive manner; and we show that querying and analyzing this information can not only simplify bookkeeping and debugging tasks for data analysts but can also enable a rich new set of capabilities like identifying flaws in the data science process itself. It can also significantly reduce the time spent in fixing post-deployment problems through automated analysis and monitoring. We have implemented an initial prototype of our system, called ProvDB, on top of git (a version control system) and Neo4j (a graph database), and we describe its key features and capabilities.


title: Pathophysiology of major depressive disorder: mechanisms involved in etiology are not associated with clinical progression

abstract: Meta-analyses support the involvement of different pathophysiological mechanisms (inflammation, hypothalamic-pituitary (HPA)-axis, neurotrophic growth and vitamin D) in major depressive disorder (MDD). However, it remains unknown whether dysregulations in these mechanisms are more pronounced when MDD progresses toward multiple episodes and/or chronicity. We hypothesized that four central pathophysiological mechanisms of MDD are not only involved in etiology, but also associated with clinical disease progression. Therefore, we expected to find increasingly more dysregulation across consecutive stages of MDD progression. The sample from the Netherlands Study of Depression and Anxiety (18-65 years) consisted of 230 controls and 2333 participants assigned to a clinical staging model categorizing MDD in eight stages (0, 1A, 1B, 2, 3A, 3B, 3C and 4), from familial risk at MDD (stage 0) to chronic MDD (stage 4). Analyses of covariance examined whether pathophysiological mechanism markers (interleukin (IL)-6, C-reactive protein (CRP), cortisol, brain-derived neurotrophic factor and vitamin D) showed a linear trend across controls, those at risk for MDD (stages 0, 1A and 1B), and those with full-threshold MDD (stages 2, 3A, 3B, 3C and 4). Subsequently, pathophysiological differences across separate stages within those at risk and with full-threshold MDD were examined. A linear increase of inflammatory markers (CRP P=0.026; IL-6 P=0.090), cortisol (P=0.025) and decrease of vitamin D (P<0.001) was found across the entire sample (for example, from controls to those at risk and those with full-threshold MDD). Significant trends of dysregulations across stages were present in analyses focusing on at-risk individuals (IL-6 P=0.050; cortisol P=0.008; vitamin D P<0.001); however, no linear trends were found in dysregulations for any of the mechanisms across more progressive stages of full-threshold MDD. Our results support that the examined pathophysiological mechanisms are involved in MDD's etiology. These same mechanisms, however, are less important in clinical progression from first to later MDD episodes and toward chronicity.


title: VIGILANCE: THE IMPORTANCE OF THE ELICITED OBSERVING RATE.

abstract: Observing may be elicited by regularly repeated events that occasionally become signals. Such events were presented at rates of either 5 per minute or 30 per minute, and signals averaged 15 per hour during an 80-minute vigil. Observers missed about 10 percent of the signals with the low event rate and about 70 percent of the signals with the high event rate. The experiment supports a decisiontheory approach to observing behavior.


title: A Modelling Language for Discourse Analysis in Humanities: Definition, Design, Validation and First Experiences

abstract: Due to humanities generally produce knowledge in textual formats (e.g. narrative conclusions or reports), a properly management of the humanities corpus needs methods for conceptualizing and extracting information from textual sources. Discourse analysis techniques allow extracting information in terms of the connection between discourse structure and elements of the reality referred in the text, as well as the inferential dimension. This semantic information is not available following other extraction methods from texts. In order to formalize the discourse analysis application for textual sources in humanities, a modelling language has been defined and initially validated with humanities specialists, showing the discourse structure and the semantic and inferential aspects extracted.


title: Model Order Reduction By MixedMathematical Methods

abstract: In this paper, a mixed method mathematical technique is proposed for finding reduced order model of Single-Input Single-Output (SISO) system. The model reduction of large scale systems is achieved by using Pade approximation and utilizing the characteristics of the higher order system which is maintained in the reduced model. The denominator polynomial of the reduced model is determined by the characteristic equation which retains the basic characteristics of the original system, and the coefficients of the numerator polynomial are obtained by using the Pade approximation technique.


title: DESIGN FOR OPTIMAL PERFORMANCE OF 3-RPS PARALLEL MANIPULATOR USING EVOLUTIONARY ALGORITHMS

abstract: This paper presents an optimal kinematic design for a general type of 3-RPS spatial parallel manipulator based on multi-objective optimization. The objective functions considered are Global Conditi...


title: Relative age effect in Spanish association football: Its extent and implications for wasted potential

abstract: Abstract Spain is one of the largest and most successful powers in international youth football, but this success has not extended to the national team. This lack of continued success seems to indicate a loss of potential. The relative age effect has been detected in football in many countries. Understanding the extent of this bias in the youth teams of Spanish elite clubs may help to improve selection processes and reduce the waste of potential. Comparisons between players from: the Spanish Professional Football League, all age categories of these clubs' youth teams, the Under-17 to Under-21 national teams, the national team, and the Spanish population, show a constant tendency to under-represent players from the later months of the selection year at all age groups of youth and Under-17 to Under-21 national teams. Professional and national team players show a similar but diminished behaviour that weakens with ageing, which suggests that talent identification and selection processes can be improved to hel...


title: A Survey on NoSQL Stores

abstract: Recent demands for storing and querying big data have revealed various shortcomings of traditional relational database systems. This, in turn, has led to the emergence of a new kind of complementary nonrelational data store, named as NoSQL. This survey mainly aims at elucidating the design decisions of NoSQL stores with regard to the four nonorthogonal design principles of distributed database systems: data model, consistency model, data partitioning, and the CAP theorem. For each principle, its available strategies and corresponding features, strengths, and drawbacks are explained. Furthermore, various implementations of each strategy are exemplified and crystallized through a collection of representative academic and industrial NoSQL technologies. Finally, we disclose some existing challenges in developing effective NoSQL stores, which need attention of the research community, application designers, and architects.


title: Finite Element Modelling of Thermoplastic Matrix Composite Gas Cylinders

abstract: Continuous glass/polypropylene (GF/PP) commingled fiber tapes were employed to produce wrapped pressure gas vessels for domestic applications by using filament winding. The vessel structural-wall was built using a hybrid solution consisting in a very thin steel liner over wrapped by the filament wounded GF/PP commingled fiber tape layers. FEM analysis was used to evaluate if the composite gas pressure vessel based on the hybrid solution (steel liner + glass fiber reinforced thermoplastic) is capable to withstand the following pressure requirements: the metallic liner, alone, a minimum burst pressure of 4MPa and whole hybrid composite vessel minima internal test and burst pressures of 3 MPa and 6.75 MPa, respectively. Finally, gas pressure vessel prototypes manufactured in industrial cycle conditions were submitted to burst pressure tests to prove that they accomplish all European standard strength requirements.


title: Optimal Boundaries for Poisson Mesh Merging

abstract: Existing Poisson mesh editing techniques mainly focus on designing schemes to propagate deformation from a given boundary condition to a region of interest. Although solving the Poisson system in the least-squares sense distributes the distortion errors over the entire region of interest, large deformation in the boundary condition might still lead to severely distorted results. We propose to optimize the boundary condition (the merging boundary) for Poisson mesh merging. The user needs only to casually mark a source region and a target region. Our algorithm automatically searches for an optimal boundary condition within the marked regions such that the change of the found boundary during merging is minimal in terms of similarity transformation. Experimental results demonstrate that our merging tool is easy to use and produces visually better merging results than unoptimized techniques.


title: Blockchain technology, bitcoin, and Ethereum: A brief overview

abstract: The blockchain technology is a relatively new approach in the field of information technologies. As one of its first implementations, bitcoin as a cryptocurrency has gained a lot of attention. Together with Ethereum, blockchain implementation with focus on smart contracts, they represent the very core of modern cryptocurrency development. This paper is meant to give a brief introduction to these topics.


title: CortexNet: a Generic Network Family for Robust Visual Temporal Representations

abstract: In the past five years we have observed the rise of incredibly well performing feed-forward neural networks trained supervisedly for vision related tasks. These models have achieved super-human performance on object recognition, localisation, and detection in still images. However, there is a need to identify the best strategy to employ these networks with temporal visual inputs and obtain a robust and stable representation of video data. Inspired by the human visual system, we propose a deep neural network family, CortexNet, which features not only bottom-up feed-forward connections, but also it models the abundant top-down feedback and lateral connections, which are present in our visual cortex. We introduce two training schemes - the unsupervised MatchNet and weakly supervised TempoNet modes - where a network learns how to correctly anticipate a subsequent frame in a video clip or the identity of its predominant subject, by learning egomotion clues and how to automatically track several objects in the current scene. Find the project website at this https URL.


title: A Novel Topology Optimization Approach using Conditional Deep Learning

abstract: In this study, a novel topology optimization approach based on conditional Wasserstein generative adversarial networks (CWGAN) is developed to replicate the conventional topology optimization algorithms in an extremely computationally inexpensive way. CWGAN consists of a generator and a discriminator, both of which are deep convolutional neural networks (CNN). The limited samples of data, quasi-optimal planar structures, needed for training purposes are generated using the conventional topology optimization algorithms. With CWGANs, the topology optimization conditions can be set to a required value before generating samples. CWGAN truncates the global design space by introducing an equality constraint by the designer. The results are validated by generating an optimized planar structure using the conventional algorithms with the same settings. A proof of concept is presented which is known to be the first such illustration of fusion of CWGANs and topology optimization.


title: Memory for Music in Alzheimer’s Disease: Unforgettable?

abstract: The notion that memory for music can be preserved in patients with Alzheimer’s Disease (AD) has been raised by a number of case studies. In this paper, we review the current research examining musical memory in patients with AD. In keeping with models of memory described in the non-musical domain, we propose that various forms of musical memory exist, and may be differentially impaired in AD, reflecting the pattern of neuropathological changes associated with the condition. Our synthesis of this literature reveals a dissociation between explicit and implicit musical memory functions. Implicit, specifically procedural musical memory, or the ability to play a musical instrument, can be spared in musicians with AD. In contrast, explicit musical memory, or the recognition of familiar or unfamiliar melodies, is typically impaired. Thus, the notion that music is unforgettable in AD is not wholly supported. Rather, it appears that the ability to play a musical instrument may be unforgettable in some musicians with AD.


title: Parallel greedy algorithms for packing unequal circles into a strip or a rectangle

abstract: Given a finite set of circles of different sizes we study the strip packing problem (SPP) as well as the Knapsack Problem (KP). The SPP asks for a placement of all circles within a rectangular strip of fixed width so that the variable length of the strip is minimized. The KP requires packing of a subset of the circles in a given rectangle so that the wasted area is minimized. To solve these problems some greedy algorithms were developed which enhance the algorithms proposed by Huang et al. (J Oper Res Soc 56:539–548, 2005). Furthermore, the new greedy algorithms were parallelized using a master slave approach. The resulting parallel methods were tested using the instances introduced by Stoyan and Yaskov (Eur J Oper Res 156:590–600, 2004). Additionally, two sets of 128 instances each for the SPP and for the KP were generated and results for these new instances are also reported.


title: HeartSense: smart phones to estimate blood pressure from photoplethysmography

abstract: In this paper we propose to demonstrate a smart phone application, that estimates human blood pressure (BP) values from photoplethysmography (PPG) signal using Windkessel model. PPG signal is extracted from a video sequence of a user's index fingertip, acquired using smart phone camera. A set of time domain PPG features are used to estimate different lumped parameters of Windkessel model to simulate arterial BP. Under most of the cases, the application estimates systolic and diastolic BP values, within a range of ±10% of clinical measurement.


title: Feature-based factorized Bilinear Similarity Model for Cold-Start Top-n Item Recommendation

abstract: Recommending new items to existing users has remained a challenging problem due to absence of user's past preferences for these items. The user personalized non-collaborative methods based on item features can be used to address this item cold-start problem. These methods rely on similarities between the target item and user's previous preferred items. While computing similarities based on item features, these methods overlook the interactions among the features of the items and consider them independently. Modeling interactions among features can be helpful as some features, when considered together, provide a stronger signal on the relevance of an item when compared to case where features are considered independently. To address this important issue, in this work we introduce the Feature-based factorized Bilinear Similarity Model (FBSM), which learns factorized bilinear similarity model for TOP-n recommendation of new items, given the information about items preferred by users in past as well as the features of these items. We carry out extensive empirical evaluations on benchmark datasets, and we find that the proposed FBSM approach improves upon traditional non-collaborative methods in terms of recommendation performance. Moreover, the proposed approach also learns insightful interactions among item features from data, which lead to deep understanding on how these interactions contribute to personalized recommendation.


title: Multi-Head Attention for End-to-End Neural Machine Translation

abstract: Inspired by the recent success of Google’s Transformer model works have been done on borrowing the novel idea of multi-head attention to various applications under different architectures. Albeit latest works have adopted this idea using an end-to-end recurrent model on speech recognition and voice search, making use of a similar model on machine translation has not been attempted yet. In this work, we examine multi-head attention under the attention-based recurrent encoder-decoder frame-work, and conduct detailed analysis on the positional response of multiple heads. Through leveraging the essence of multi-head attention, we are capable of attaining a state-of-the-art result on IWSLT’ 15 with 28.48 tokenized BLEU and 53.86% TER, which gives a 0.17 gain in BLEU and 0.37% reduction in TER. Similarly we achieve 25.58 tokenized BLEU and 55.03% TER on WMT’16, which provide a 0.40 gain in BLEU and 0.32% reduction in TER to the baseline model respectively. To the best of our knowledge, this is the first work1 that evaluates the concept of multi-head attention in an end-to-end recurrent network on machine translation tasks.


title: Providing social protection to mobile populations: symbiotic relationships between migrants and welfare institutions

abstract: ABSTRACTStudies on migration and social protection have shown that a lack of access to formal welfare in receiving countries leads migrants to rely on their informal social networks for support. This paper argues that such clear-cut dichotomies between formal and informal social protection systems ignore the manners in which both welfare-state institutions and migrants work together at the interstices of the formal and informal to cater to national and transnational social protection needs. Based on empirical data collected during 14 months of multi-sited and partially matched-sample ethnography with Sudanese families across the Netherlands and Sudan, this paper investigates how migrants sometimes enter into symbiotic relationships with different welfare-state institutions, such as municipal offices, non-governmental organisations and other immigration institutions, which in turn rely on the support of these migrants to provide social protection to people who would otherwise escape their purview. While th...


title: Finding shell company accounts using anomaly detection

abstract: Money laundering refers to activities pertaining to hiding the true income, evading taxes, or converting illegally earned money for normal use. These activities are often performed through shell companies that masquerade as real companies but where actual the purpose is to launder money. Shell companies are used in all the three phases of money laundering, namely, placement, layering, and integration, often simultaneously. In this paper, we aim to identify shell companies. We propose to use only bank transactions since that is easily available. In particular, we look at all incoming and outgoing transactions from a particular bank account along with its various attributes, and use anomaly detection techniques to identify the accounts that pertain to shell companies. Our aim is to create an initial list of potential shell company candidates which can be investigated by financial experts later. Due to lack of real data, we propose a banking transactions simulator (BTS) to simulate both honest as well as shell company transactions by studying a host of actual real-world fraud cases. We apply anomaly detection algorithms to detect candidate shell companies. Results indicate that we are able to identify the shell companies with a high degree of precision and recall.1


title: Substrate Integrated Waveguide Filter With Improved Stopband Performance for Satellite Ground Terminal

abstract: In this paper, patent pending substrate integrated waveguide (SIW) bandpass filters with moderate fractional bandwidth and improved stopband performance are proposed and demonstrated for a Ka-band satellite ground terminal. Nonphysical cross-coupling provided by higher order modes in the oversized SIW cavities is used to generate the finite transmission zeros far away from the passband for improved stopband performance. Different input/output topologies of the filter are discussed for wide stopband applications. Design considerations including the design approach, filter configuration, and tolerance analysis are addressed. Two fourth-order filters with a passband of 19.2-21.2 GHz are fabricated on a single-layer Rogers RT/Duroid 6002 substrate using linear arrays of metallized via-holes by a standard printed circuit board process. Measured results of the two filters agree very well with simulated results, showing the in-band insertion loss is 0.9 dB or better, and the stopband attenuation in the frequency band of 29.5-30 GHz is better than 50 dB. Measurements over a temperature range of -20degC to +40degC show the passband remains almost unchanged.


Approximate Algorithms for the 0/1 Knapsack Problem


title: Ambient Assisted Living for Improvement of Health and Quality of Life—A Special Issue of the Journal of Informatics

abstract: The demographic change with respect to the ageing of the population has been a worldwide trend[...]


title: Brain regions involved in the retrieval of spatial and episodic details associated with a familiar environment: An fMRI study

abstract: Functional magnetic resonance imaging (fMRI) was used to compare brain activity during the retrieval of coarse- and fine-grained spatial details and episodic details associated with a familiar environment. Long-time Toronto residents compared pairs of landmarks based on their absolute geographic locations (requiring either coarse or fine discriminations) or based on previous visits to those landmarks (requiring episodic details). An ROI analysis of the hippocampus showed that all three conditions activated the hippocampus bilaterally. Fine-grained spatial judgments recruited an additional region of the right posterior hippocampus, while episodic judgments recruited an additional region of the right anterior hippocampus, and a more extensive region along the length of the left hippocampus. To examine whole-brain patterns of activity, Partial Least Squares (PLS) analysis was used to identify sets of brain regions whose activity covaried with the three conditions. All three comparison judgments recruited the default mode network including the posterior cingulate/retrosplenial cortex, middle frontal gyrus, hippocampus, and precuneus. Fine-grained spatial judgments also recruited additional regions of the precuneus, parahippocampal cortex and the supramarginal gyrus. Episodic judgments recruited the posterior cingulate and medial frontal lobes as well as the angular gyrus. These results are discussed in terms of their implications for theories of hippocampal function and spatial and episodic memory.


title: Cultural Understanding Cultural Comparisons of Beliefs and Values: Applying the Grid-Group Approach to the World Values Survey

abstract: The goal of our research is to enrich quantitative cross-cultural studies by employing concepts of grid and group, which were first developed within anthropology and more recently deployed in a broader range of social sciences. The grid-group approach has until now not been subjected to large-scale quantitative empirical investigation, thus limiting its use in cross-cultural research. In order to carry out such an investigation, we develop individual-level indices for measuring grid and group, using data from the World Values Survey, and then investigate the collective or cohort level by taking a country or a city as a main cohort proxy and make comparisons across different cultures. We establish a number of results that suggest the usefulness of grid and group in quantitative studies: (a) grid and group variables exhibit significantly less variance within societies than between societies, (b) the characterizations of societies derived from the indices coincide with findings in the ethnographic literature, and (c) grid and group are statistically related to a society’s socioeconomic conditions and geographic location. We hope our results will further stimulate the formulation of empirically testable propositions using cultural indices. This article examines cultural differences across countries by using the grid-group framework. The grid-group framework is a well-known cultural representation framework in cultural anthropology. It is a typology of social environments created by anthropologist Mary Douglas (1970, 1982) that has been adapted, modifi ed, and


title: Formalization, User Strategy And Interaction Design: Users? Behaviour With Discourse Tagging Semantics

abstract: When authors publish their interpretations of the ideas, opinions, claims or rebuttals in the literature, they are drawing on a repertoire of well understood moves, contributing to an extended discourse. Readers also bring their own perspective to documents, interpreting them in the light of their own research interests, and initiating, for instance, new connections that may not have been intended by authors. Collaborative, social, tagging holds promise as an approach to mediating these processes via the Web, but may lack the discourse dimension that is fundamental to the articulation of interpretations. We therefore take a hybrid semiformal approach to add structure to freeform folksonomies. Our experience demonstrates that this particular brand of tagging requires tools designed specifically for this sensemaking task by providing enough support to initiate the annotation, while not overwhelming users with suggestions. We describe a tool called ClaimSpotter that aims at supporting this tradeoff, through a novel combination of system-initiated tag recommendations, Web interface design, and an expanded conception of how tags can be both expressed, and semantically linked. We then report a detailed study which analysed the tool’s usability and the tag structures created, contributing to our understanding of the implications of adding structure to collaborative tagging.


title: Syringomyelia and Bone Malformations in the Setting of Hypertrichosis Cubiti (Hairy Elbow Syndrome)

abstract: INTRODUCTION ::: The hypertrichosis cubiti also named "hairy elbow syndrome" is a benign anomaly which occurs as an isolated sign but sometime it may be associated with others abnormalities including short stature, facial dysmorphism, developmental delay and bone anomalies. ::: ::: ::: CASE REPORT ::: The Authors report on a girl 8 years old, who showed a classical hypertrichosis cubiti, tufts of peluria in the thoraco lumbar region, moderate scoliosis and bilateral large big toes. In correspondence with the tufts of spinal peluria the MRI displayed areas of syringomyelia. ::: ::: ::: CONCLUSION ::: A review of the cases of hypertrichosis cubiti associated to spine and bone anomalies is reported. This is the first report of the association of hypertrichosis cubiti with syringomyelia and large big toes. The presence of peluria in the elbow and/or in the thoraco lumbar region may be a clue of malformations of spine and bone. In conclusion the HC may be a simply aesthetic, benign anomaly, but may be also a clue of malformations affecting many organs including the spine and skeletal tissue.


title: Skip-connection convolutional neural network for still image crowd counting

abstract: In recent years, crowd counting in still images has attracted many research interests due to its applications in public safety. However, it remains a challenging task for reasons of perspective and scale variations. In this paper, we propose an effective Skip-connection Convolutional Neural Network (SCNN) for crowd counting to overcome the issue of scale variations. The proposed SCNN architecture consists of several multi-scale units to extract multi-scale features. Each multi-scale unit including three convolutional layers builds connections between the input and each convolutional layer. In addition, we propose a scale-related training method to improve the accuracy and robustness of crowd counting. We evaluate our method on three crowd counting benchmarks. Experimental results verify the efficiency of the proposed method, and it achieves superior performance compared with other methods.


title: Equisolid Fisheye Stereovision Calibration and Point Cloud Computation

abstract: This paper deals with dense 3D point cloud computation of urban environments around a vehicle. The idea is to use two fisheye views to get 3D coordinates of the surrounding scene's points. The first contribution of this paper is the adaptation of an omnidirectional stereovision self-calibration algorithm to an equisolid fisheye projection model. The second contribution is the description of a new epipolar matching based on a scan-circle principle and a dynamic programming technique adapted for fisheye images. The method is validated using both synthetic images for which ground truth is available and real images of an urban scene.


title: Towards Elasticity in Distributed File Systems

abstract: In IaaS Cloud Computing platforms, elasticity offers to users the possibility to adjust the number of resources tithe current workload, taking into account peak (high activity) and trough (low activity) periods by powering down/up someresources. This elasticity principally consists in dynamically starting/stopping Virtual Machines to increase/reduce the computing capacities. In this paper, we study the problem of storage resources elasticity using a Distributed File System (DFS). Indeed, the main DFSes that are used today, like Glister, HDFS or Lustre, focus on data access performance and transient fault tolerance, but they do not take into account intentional and dynamic removal/addition of resources. We propose an algorithm that provides an initial data placement and adapts the resources of a DFS to the workload of a platform maintaining good data access performance. This algorithm takes into account an estimated popularity of the data stored on the DFS to distribute the workload using the least resources. Our simulations on top of SimGrid show that we could improve HDFS' performances by up to 41% while using less resources (up to 63%). Then, we introduce our solutions that adapt the replication factor of each data to their popularity, allowing more parallel accesses when needed and easing the removal of resources when some data have few concurrent accesses. The simulations show we could either reduce the number of used resources (up to 35%) or increase performances (up to 54%).


title: Solving the n-Queens Problem Using a Tuned Hybrid Imperialist Competitive Algorithm

abstract: The n queens problem is a classical combinatorial optimization problem which has been proved to be NP hard. The goal is to place n non attacking queens on an n×n chessboard. In this paper, the Imperialist Competitive Algorithm (ICA), which is a recent evolutionary metaheuristic method, has been applied for solving the n queens problem. As another variation, the ICA was combined with a local search method, resulting the Hybrid ICA (HICA). Since, the parameters of heuristic and metaheuristic algorithms have a great influence on the performance of the search, parameter tuning is used for handling the problems in an efficient manner. Hence, a TOPSIS based parameters tuning is proposed, which not only considers the number of Fitness Function Evaluations (FFE), but also aims to minimize the running time of the presented heuristics. In order to, investigate the performance of the suggested approach, a computational analysis on the n queens problem was performed. Extensive experimental results showed that the proposed HICA outperformed the basic ICA in terms of average runtimes and average number of FFE. The developed algorithms were also compared to the Cooperative PSO (CPSO) algorithm, which is currently the best algorithm in the literature for finding the first valid solution to the n queens problem, and the results showed that the HICA dominates the CPSO by evaluating the fitness function fewer times.


title: FATORES MOTIVACIONAIS E DESEMPENHO NO FUTEBOL

abstract: This study aimed to verify what were the motivational factors that made teenagers to choose ADUFSM soccer school, and to verify the difference among the groups, the performance and gain scores at soccer basis. The sample comprised 32 persons, 10 to 16 years old, that practice soccer at ADUFSM. The sample was divided in four groups. The motivational factors inventory (MFI) was applied in the beginning of the semester. It was verified, through descriptive statistics, that the stronger motivation for the subjects involvement with soccer was to develop skills (78%), followed by excitation and challenge (72%); affiliation (70%) and aptitude (68%). The performance level evaluation in three different phases was done through soccer basis analytical matrix (SBAM), always in game situation. Five observations per subject were made for each base listed in SBAM, and the execution mistakes were identifies. Initially, an ANOVA was used to deal with the data; later, a post-hoc test. The results showed that learning occurred and that there was a significant difference favoring GF10 in the learning gain scores after the treatment.


title: Buying or browsing ? An exploration of shopping orientations and online purchase intention

abstract: Consumer selection of retail patronage mode has been widely researched by marketing scholars. Several researchers have segmented consumers by shopping orientation. However, few have applied such methods to the Internet shopper. Despite the widespread belief that Internet shoppers are primarily motivated by convenience, the authors show empirically that consumers' fundamental shopping orientations have no significant impact on their proclivity to purchase products online. Factors that are more likely to influence purchase intention include product type, prior purchase, and, to a lesser extent, gender.


title: Wireless Body Area Network Security and Privacy Issue in E-Healthcare

abstract: Wireless Body Area Network (WBAN) is a collection of wireless sensor nodes which can be placed within the body or outside the body of a human or a living person which in result observes or monitors the functionality and adjoining situations of the body. Utilizing a Wireless Body Area Network, the patient encounters a greater physical versatility and is never again constrained to remain in the hospital. As the Wireless Body Area Network sensor devices is being utilized for gathering the sensitive data and possibly will run into antagonistic situations, they require complicated and very secure security medium or structure to avoid the vitriolic communications within the system. These devices represent various security and privacy protection of touchy and private patient medical data. The medical records of patients are a significant and an unsolved situation due to which a changing or exploitation to the system is possible. In this research paper, we first present an overview of WBAN, how they utilized for healthcare monitoring, its architecture then highlight major security and privacy requirements and assaults at different network layer in a WBAN and we finally talk about various cryptographic algorithms and laws for providing solution of security and privacy in WBAN.


title: Changes in Marketing Process Management Employing TMS: Establishment of Toyota Sales Marketing System ∗

abstract: The purpose of the total marketing system (TMS) is to aid changes in marketing process management by correctly identifying customer demands, conducting proper business and sales activities and implementing customer science to contribute to merchandise development. As an example of application study using science SQC, the author established the Toyota sales marketing system (TSMS), an intelligent customer information network system, to improve the repeat customer ratio for Toyota vehicles. The achievements of the present study are currently being applied at Netz Chiba and other Toyota dealers.


title: Optimized link state routing protocol for ad hoc networks

abstract: In this paper we propose and discuss an optimized link state routing protocol, named OLSR, for mobile wireless networks. The protocol is based on the link state algorithm and it is proactive (or table-driven) in nature. It employs periodic exchange of messages to maintain topology information of the network at each node. OLSR is an optimization over a pure link state protocol as it compacts the size of information sent in the messages, and furthermore, reduces the number of retransmissions to flood these messages in an entire network. For this purpose, the protocol uses the multipoint relaying technique to efficiently and economically flood its control messages. It provides optimal routes in terms of number of hops, which are immediately available when needed. The proposed protocol is best suitable for large and dense ad hoc networks.


title: Machine learning techniques for web intrusion detection — A comparison

abstract: The rapid development of web applications has created many security problems related to intrusions not just on computer, network systems, but also on web applications themselves. In Web Intrusion Systems (WIS), most techniques used nowadays are not able to deal with the dynamic and complex nature of cyber-attacks on web applications and related issues. However, web intrusion techniques based on machine learning approaches with statistical analysis of data enable autonomous detect intrusive and non-intrusive traffic with low false-positive errors. In this paper, we present the survey of various machine learning techniques used to build WIS. In addition, we develop the experimental framework for comparative analysis of some machine learning techniques applying on the well-known benchmark data set - CSIC 2010 HTTP [13].


title: Entrepreneurship theory and the poverty of historicism

abstract: Purpose. The author applies methodological concepts from The poverty of historicism to contemporary research in the area of entrepreneurship. The aims are to explain why current theoretic models do not adequately explain entrepreneurial phenomena and to present outlines of a distinct entrepreneurship research paradigm. Design/methodology/approach. The author examines the essay from the perspective of a historian and then summarizes its concepts. Next, the author reviews the current state of entrepreneurship research and theory and applies concepts from the essay to its contemporary challenges. Finally, the author presents five implications. Findings. The five implications are that entrepreneurship research should include designs that predict failure, strive to develop theory that is distinct from other areas, emphasize novel arrangements of empirical elements that are also novel, utilize nonparametric statistics and case studies more fully, and push for a paradigmatic shift. Originality/value. The contribution of this article is useful to entrepreneurship scholars interested in developing and distinguishing their research area in a substantial and lasting way alongside other established research areas in the domain of business studies.


title: Real-time large-scale dense RGB-D SLAM with volumetric fusion

abstract: We present a new simultaneous localization and mapping (SLAM) system capable of producing high-quality globally consistent surface reconstructions over hundreds of meters in real time with only a low-cost commodity RGB-D sensor. By using a fused volumetric surface reconstruction we achieve a much higher quality map over what would be achieved using raw RGB-D point clouds. In this paper we highlight three key techniques associated with applying a volumetric fusion-based mapping system to the SLAM problem in real time. First, the use of a GPU-based 3D cyclical buffer trick to efficiently extend dense every-frame volumetric fusion of depth maps to function over an unbounded spatial region. Second, overcoming camera pose estimation limitations in a wide variety of environments by combining both dense geometric and photometric camera pose constraints. Third, efficiently updating the dense map according to place recognition and subsequent loop closure constraints by the use of an ‘as-rigid-as-possible’ space deformation. We present results on a wide variety of aspects of the system and show through evaluation on de facto standard RGB-D benchmarks that our system performs strongly in terms of trajectory estimation, map quality and computational performance in comparison to other state-of-the-art systems.


title: Coded computation over heterogeneous clusters

abstract: In large-scale distributed computing clusters, such as Amazon EC2, there are several types of "system noise" that can result in major degradation of performance: system failures, bottlenecks due to limited communication bandwidth, latency due to straggler nodes, etc. On the other hand, these systems enjoy abundance of computing and storage redundancy. There have been recent results that demonstrate the impact of coding for efficient utilization of computation and storage redundancy to alleviate the effect of stragglers and communication bottlenecks in homogeneous clusters. In this paper, we focus on general heterogeneous distributed computing clusters consisting of a variety of computing machines with different capabilities. We propose a coding framework for speeding up distributed computing in heterogeneous clusters by trading redundancy for reducing the latency of computation. In particular, we propose Heterogeneous Coded Matrix Multiplication (HCMM) algorithm for performing distributed matrix multiplication over heterogeneous clusters that is provably asymptotically optimal. Moreover, we show that HCMM is unboundedly faster than uncoded schemes. We also provide numerical results demonstrating significant speedups of up to 90% and 35% for HCMM in comparison to the "uncoded" and "coded homogeneous" schemes, respectively. Furthermore, we carry out real experiments over Amazon EC2 clusters, where HCMM is found to be up to 17% faster than the uncoded scheme. In our worst case experiments with artificial stragglers, HCMM provides speedups of up to 12x over the uncoded scheme. Furthermore, we provide a generalization of the problem of optimal load allocation for heterogeneous clusters to scenarios with budget constraints. In the end, we discuss about the decoding complexity and describe how LDPC codes can be combined with HCMM in order to control the complexity of decoding.


title: Parametric font and image definition and generation

abstract: The demand for high graphic arts quality publications particularly in the areas of education and technology increases steadily. The associated use of computer controlled photocomposition systems can be likewise expected to accelerate. Considering the high cost of currently available systems, we were motivated to investigate alternative approaches, both from a hardware and a software point of view. We conducted experiments with a high resolution electron beam recorder controlled by a small computer containing 8K words of 16 bits each, and running at about 500K cycles per second. The recorder can address a raster grid 16,384 square, and can draw both horizontal and vertical vectors, but the vectors must be no greater than four rasters apart to obtain proper shading. This paper concerns itself primarily with the software implementation, as constrained by the given hardware configuration.


title: Tumor-specific usage of alternative transcription start sites in colorectal cancer identified by genome-wide exon array analysis

abstract: BackgroundApproximately half of all human genes use alternative transcription start sites (TSSs) to control mRNA levels and broaden the transcriptional output in healthy tissues. Aberrant expression patterns promoting carcinogenesis, however, may arise from alternative promoter usage.ResultsBy profiling 108 colorectal samples using exon arrays, we identified nine genes (TCF12, OSBPL1A, TRAK1, ANK3, CHEK1, UGP2, LMO7, ACSL5, and SCIN) showing tumor-specific alternative TSS usage in both adenoma and cancer samples relative to normal mucosa. Analysis of independent exon array data sets corroborated these findings. Additionally, we confirmed the observed patterns for selected mRNAs using quantitative real-time reverse-transcription PCR. Interestingly, for some of the genes, the tumor-specific TSS usage was not restricted to colorectal cancer. A comprehensive survey of the nine genes in lung, bladder, liver, prostate, gastric, and brain cancer revealed significantly altered mRNA isoform ratios for CHEK1, OSBPL1A, and TCF12 in a subset of these cancer types.To identify the mechanism responsible for the shift in alternative TSS usage, we antagonized the Wnt-signaling pathway in DLD1 and Ls174T colorectal cancer cell lines, which remarkably led to a shift in the preferred TSS for both OSBPL1A and TRAK1. This indicated a regulatory role of the Wnt pathway in selecting TSS, possibly also involving TP53 and SOX9, as their transcription binding sites were enriched in the promoters of the tumor preferred isoforms together with their mRNA levels being increased in tumor samples.Finally, to evaluate the prognostic impact of the altered TSS usage, immunohistochemistry was used to show deregulation of the total protein levels of both TCF12 and OSBPL1A, corresponding to the mRNA levels observed. Furthermore, the level of nuclear TCF12 had a significant correlation to progression free survival in a cohort of 248 stage II colorectal cancer samples.ConclusionsAlternative TSS usage in colorectal adenoma and cancer samples has been shown for nine genes, and OSBPL1A and TRAK1 were found to be regulated in vitro by Wnt signaling. TCF12 protein expression was upregulated in cancer samples and correlated with progression free survival.


title: Calibration of p Values for Testing Precise Null Hypotheses

abstract: P values are the most commonly used tool to measure evidence against a hypothesis or hypothesized model. Unfortunately, they are often incorrectly viewed as an error probability for rejection of the hypothesis or, even worse, as the posterior probability that the hypothesis is true. The fact that these interpretations can be completely misleading when testing precise hypotheses is first reviewed, through consideration of two revealing simulations. Then two calibrations of a ρ value are developed, the first being interpretable as odds and the second as either a (conditional) frequentist error probability or as the posterior probability of the hypothesis.


title: CNN based approach for activity recognition using a wrist-worn accelerometer

abstract: In recent years, significant advancements have taken place in human activity recognition using various machine learning approaches. However, feature engineering have dominated conventional methods involving the difficult process of optimal feature selection. This problem has been mitigated by using a novel methodology based on deep learning framework which automatically extracts the useful features and reduces the computational cost. As a proof of concept, we have attempted to design a generalized model for recognition of three fundamental movements of the human forearm performed in daily life where data is collected from four different subjects using a single wrist worn accelerometer sensor. The validation of the proposed model is done with different pre-processing and noisy data condition which is evaluated using three possible methods. The results show that our proposed methodology achieves an average recognition rate of 99.8% as opposed to conventional methods based on K-means clustering, linear discriminant analysis and support vector machine.


A SEMI-ANALYTICAL METHOD FOR THE DESIGN OF COIL-SYSTEMS FOR HOMOGENEOUS MAGNETO- STATIC FIELD GENERATION


title: Frequent Pattern Mining on Message Passing Multiprocessor Systems

abstract: Extraction of frequent patterns in transaction-oriented database is crucial to several data mining tasks such as association rule generation, time series analysis, classification, etc. Most of these mining tasks require multiple passes over the database and if the database size is large, which is usually the case, scalable high performance solutions involving multiple processors are required. This paper presents an efficient scalable parallel algorithm for mining frequent patterns on parallel shared nothing platforms. The proposed algorithm is based on one of the best known sequential techniques referred to as Frequent Pattern (FP) Growth algorithm. Unlike most of the earlier parallel approaches based on different variants of the Apriori Algorithm, the algorithm presented in this paper does not explicitly result in having entire counting data structure duplicated on each processor. Furthermore, the proposed algorithm introduces minimum communication (and hence synchronization) overheads by efficiently partitioning the list of frequent elements list over processors. The experimental results show scalable performance over different machine and problem sizes. The comparison of implementation results with existing parallel approaches show significant gains in the speedup. On an 8-processor machine, we report an average speedup of 6 for different problem sizes.


title: Evaluations of the Effects of Extremely Low-Frequency Electromagnetic Fields on Growth and Antibiotic Susceptibility of Escherichia coli and Pseudomonas aeruginosa

abstract: We aimed to investigate the effects of exposure to extremely low-frequency electromagnetic fields (2 mT; 50 Hz) on the growth rate and antibiotic sensitivity of E. coli ATCC 25922 and P. aeruginosa ATCC 27853. The electromagnetic field treatment significantly influenced the growth rate of both strains when incubated in the presence of subinhibitory concentrations of kanamycin (1 μg/mL) and amikacin (0.5 μg/mL), respectively. In particular, at 4, 6, and 8 h of incubation the number of cells was significantly decreased in bacteria exposed to electromagnetic field when compared with the control. Additionally, at 24 h of incubation, the percentage of cells increased (P. aeruginosa∼42%; E. coli∼5%) in treated groups with respect to control groups suggesting a progressive adaptive response. By contrast, no remarkable differences were found in the antibiotic susceptibility and on the growth rate of both bacteria comparing exposed groups with control groups.


title: Detecting duplicate bug reports with software engineering domain knowledge

abstract: Bug deduplication, ie, recognizing bug reports that refer to the same problem, is a challenging task in the software-engineering life cycle. Researchers have proposed several methods primarily relying on information-retrieval techniques. Our work motivated by the intuition that domain knowledge can provide the relevant context to enhance effectiveness, attempts to improve the use of information retrieval by augmenting with software-engineering knowledge. In our previous work, we proposed the software-literature-context method for using software-engineering literature as a source of contextual information to detect duplicates. If bug reports relate to similar subjects, they have a better chance of being duplicates. Our method, being largely automated, has a potential to substantially decrease the level of manual effort involved in conventional techniques with a minor trade-off in accuracy. ::: ::: In this study, we extend our work by demonstrating that domain-specific features can be applied across projects than project-specific features demonstrated previously while still maintaining performance. We also introduce a hierarchy-of-context to capture the software-engineering knowledge in the realms of contextual space to produce performance gains. We also highlight the importance of domain-specific contextual features through cross-domain contexts: adding context improved accuracy; Kappa scores improved by at least 3.8% to 10.8% per project.


title: 99.3% Efficient three-phase buck-type all-SiC SWISS Rectifier for DC distribution systems

abstract: DC power distribution systems for data centers, industrial applications and residential areas are expected to provide higher efficiency, reliability and lower cost compared to ac systems. Accordingly they have been an important research topic in recent years. In these applications an efficient power factor correction rectifier, supplying a dc distribution bus from the conventional three-phase ac mains is typically required. This paper analyzes the three-phase buck-type unity power factor SWISS Rectifier showing that its input current THD can be improved significantly by interleaving. The dc output filter is implemented using a current compensated Integrated Common Mode Coupled Inductor which ensures equal current sharing between interleaved half bridges and provides common mode inductance. Based on the analysis an high efficient 8 kW, 4 kW dm−3 (64 Win−3) lab-scale prototype converter is designed using SiC MOSFETS. Measurements taken on a hardware prototype confirm a full power efficiency of 99.16 % and a peak efficiency of 99.26 %.


title: Pattern classification by a condensed neural network

abstract: Neural networks have come to the fore as potent pattern classifiers. More amenable to parallel computation, they are much faster than the nearest neighbor classifier (NN), which, however, has distinctly outperformed them in several applications. The purpose of this study is to investigate a condensed neural network that combines the classification speed of neural networks and the low error rate of the nearest neighbor classifier. This condensed network is a fast, accurate classifier of simple architecture and function: it consists of a set of generalized perceptrons that draw maximal hyperspherical boundaries centered on patterns of memory units, each circumscribing reference patterns of a single category. The generalized perceptrons carry out classification, assisted by sporadic nearest neighbor matching to patterns of a small reference set. We compare the condensed network to a high performance neural network pattern classifier (Kohonen) and to NN in experiments on hand-printed character recognition.


title: SecReach: Secure Reachability Computation on Encrypted Location Check-in Data

abstract: Reachability, which answers whether one person is reachable from another through a sequence of contacts within a period of time, is of great importance in many domains such as social behavior analysis. Recently, with the prevalence of various location-based services (LBSs), a great amount of spatiotemporal location check-in data is generated by individual GPS-equipped mobile devices and collected by LBS companies, which stimulates research on reachability queries in these location check-in datasets. Meanwhile, a growing trend is for LBS companies to use scalable and cost-effective clouds to collect, store, and analyze data, which makes it necessary to encrypt location check-in data before outsourcing due to privacy concerns. In this paper, for the first time, we propose a scheme, SecReach, to securely evaluate reachability queries on encrypted location check-in data by using somewhat homomorphic encryption (SWHE). We prove that our scheme is secure against a semi-honest cloud server. We also present a proof-of-concept implementation using the state-of-the-art SWHE library (i.e., HElib), which shows the efficiency and feasibility of our scheme.


title: Demand Estimation and Assortment Optimization Under Substitution: Methodology and Application

abstract: Assortment planning at a retailer entails both selecting the set of products to be carried and setting inventory levels for each product. We study an assortment planning model in which consumers might accept substitutes when their favorite product is unavailable. We develop an algorithmic process to help retailers compute the best assortment for each store. First, we present a procedure for estimating the parameters of substitution behavior and demand for products in each store, including the products that have not been previously carried in that store. Second, we propose an iterative optimization heuristic for solving the assortment planning problem. In a computational study, we find that its solutions, on average, are within 0.5% of the optimal solution. Third, we establish new structural properties (based on the heuristic solution) that relate the products included in the assortment and their inventory levels to product characteristics such as gross margin, case-pack sizes, and demand variability. We applied our method at Albert Heijn, a supermarket chain in The Netherlands. Comparing the recommendations of our system with the existing assortments suggests a more than 50% increase in profits.


title: The functional significance of mu rhythms: Translating “seeing” and “hearing” into “doing”

abstract: Existing evidence indicates that mu and other alpha-like rhythms are independent phenomena because of differences in source generation, sensitivity to sensory events, bilateral coherence, frequency, and power. Although mu suppression and enhancement echo sensorimotor processing in frontoparietal networks, they are also sensitive to cognitive and affective influences and likely reflect more than an idling brain state. Mu rhythms are present at early stages of human development and in other mammalian species. They exhibit adaptive and dynamically changing properties, including frequency acceleration and posterior-to-anterior shifts in focus. Furthermore, individuals can learn to control mu rhythms volitionally in a very short period of time. This raises questions about the mu rhythm’s open neural architecture and ability to respond to cognitive, affective, and motor imagery, implying an even greater developmental and functional role than has previously been ascribed to it. Recent studies have suggested that mu rhythms reflect downstream modulation of motor cortex by prefrontal mirror neurons, i.e., cells that may play a critical role in imitation learning and the ability to understand the actions of others. It is proposed that mu rhythms represent an important information processing function that links perception and action — specifically, the transformation of ‘‘seeing’’ and ‘‘hearing’’ into ‘‘doing.’’ In a broader context, this transformation function results from an entrainment/gating mechanism in which multiple alpha networks (visual-, auditory-, and somatosensory-centered domains), typically producing rhythmic oscillations in a locally independent manner, become coupled and entrained. A global or Fdiffuse and distributed alpha system_ comes into existence when these independent sources of alpha become coherently engaged in transforming perception to action. D 2005 Elsevier B.V. All rights reserved. Theme: Neural basis of behavior Topic: Biological rhythms


title: Molecular mechanisms of metal hyperaccumulation in plants

abstract: Metal hyperaccumulator plants accumulate and detoxify extraordinarily high concentrations of metal ions in their shoots. Metal hyperaccumulation is a fascinating phenomenon, which has interested scientists for over a century. Hyperaccumulators constitute an exceptional biological material for understanding mechanisms regulating plant metal homeostasis as well as plant adaptation to extreme metallic environments. Our understanding of metal hyperaccumulation physiology has recently increased as a result of the development of molecular tools. This review presents key aspects of our current understanding of plant metal - in particular cadmium (Cd), nickel (Ni) and zinc (Zn) - hyperaccumulation. © The Authors (2009).


title: Decision Support System in Healthcare Industry

abstract: In this paper we propose Decision support system implementation for health care system with the use of decision support system. The system integrates the input data from relevant sources into an autonomous data warehouse, while the client frontend ensures adequate output presentation to the user so as reveal significant details and dependencies. Applying the system as an “on –the –fly” decision–support facility for the policy–makers has resulted in significant acceleration of planning procedure, raised the overall awareness with respect to the underlying methodology and, ultimately, enabled more efficient academic administration.


title: Less Is More: Towards Compact CNNs

abstract: To attain a favorable performance on large-scale datasets, convolutional neural networks (CNNs) are usually designed to have very high capacity involving millions of parameters. In this work, we aim at optimizing the number of neurons in a network, thus the number of parameters. We show that, by incorporating sparse constraints into the objective function, it is possible to decimate the number of neurons during the training stage. As a result, the number of parameters and the memory footprint of the neural network are also reduced, which is also desirable at the test time. We evaluated our method on several well-known CNN structures including AlexNet, and VGG over different datasets including ImageNet. Extensive experimental results demonstrate that our method leads to compact networks. Taking first fully connected layer as an example, our compact CNN contains only \(30\,\%\) of the original neurons without any degradation of the top-1 classification accuracy.


Analysis of the Genetic Phylogeny of Multifocal Prostate Cancer Identifies Multiple Independent Clonal Expansions in Neoplastic and Morphologically Normal Prostate Tissue


title: Rigid dietary control, flexible dietary control, and intuitive eating: Evidence for their differential relationship to disordered eating and body image concerns

abstract: This study aimed to replicate and extend from Tylka, Calogero, and Danielsdottir (2015) findings by examining the relationship between rigid control, flexible control, and intuitive eating on various indices of disordered eating (i.e., binge eating, disinhibition) and body image concerns (i.e., shape and weight over-evaluation, body checking, and weight-related exercise motivations). This study also examined whether the relationship between intuitive eating and outcomes was mediated by dichotomous thinking and body appreciation. Analysing data from a sample of 372 men and women recruited through the community, this study found that, in contrast to rigid dietary control, intuitive eating uniquely and consistently predicted lower levels of disordered eating and body image concerns. This intuitive eating-disordered eating relationship was mediated by low levels of dichotomous thinking and the intuitive eating-body image relationship was mediated by high levels of body appreciation. Flexible control predicted higher levels of body image concerns and lower levels of disordered eating only when rigid control was accounted for. Findings suggest that until the adaptive properties of flexible control are further elucidated, it may be beneficial to promote intuitive eating within public health approaches to eating disorder prevention. In addition to this, particular emphasis should also be made toward promoting body acceptance and eradicating a dichotomous thinking style around food and eating.


title: Full-duplex Bluetooth Low Energy (BLE) compatible Backscatter communication system for mobile devices

abstract: We present the first demonstration of a monostatic full-duplex backscatter system having a carrier source co-located with a commercial Bluetooth chipset. The system permits the co-location and simultaneous operation of a commercial Bluetooth chipset with a carrier source, enabling the use of specially designed BLE-Backscatter tags to send data to the commercial Bluetooth chipset with no software modifications. This demonstration shows the potential for reusing the wireless chipsets in future full-duplex devices as readers for backscatter tags and other backscatter-based devices. Using a directional coupler-based carrier cancellation implementation, we achieve carrier suppression of 50 dB. In an over-the-air experiment using a dipole antenna with 2.1 dBi gain, we observe a read range of 3 meters with an 88% packet success rate at a carrier power of +33.9 dBm.


title: EzMail: using information visualization techniques to help manage email

abstract: Originally designed as a messaging application, email is now used for a wide range of functions. Email clients however have not progressed correspondingly to support users with email management. This work describes the design of EzMail, an email visualization tool that runs in conjunction with an email client and creates a multi-view interface to assist with email management. Our primary focus is to group and visualize messages as components of threads to provide contextual information and conversational history. We have developed visualizations for individual messages, message properties, and messages in a thread. Message annotation is incorporated, along with a capability for replying simultaneously to several messages. A small user survey and a user study provided information regarding users' management of their messages and threads, and a comparative evaluation of EzMail with respect to Microsoft Outlook.


title: A practical model for traffic forecasting based on big data, machine-learning, and network KPIs

abstract: Traffic forecasting plays an important role in improving network quality and energy saving of mobile networks. In 5G, traffic forecasting directly influences the self-organizing network (SON) in managing and controlling the network effectively. Especially, long-term traffic forecasting can provide a detailed pattern of future traffic, besides permitting more time for planning and optimizing. Most of the traffic forecasting models used the history of traffic, while the utilization of another network KPIs (key performance indicators) for traffic forecasting is limited. Therefore, the authors propose here a practical platform and process for traffic forecasting, based on big data, machine-learning (ML), and network KPIs that are flexible to forecast accurately different statistical traffic characteristics of different types of cells (GSM, 3G, 4G) for both long- and short-term forecasting. The performance of the proposed model was evaluated by applying it to a real dataset that collected KPIs of more than 6000 cells of a real network during the years, 2016 and 2017.


title: Adaptive Fuzzy Neural Network Control for a Constrained Robot Using Impedance Learning

abstract: This paper investigates adaptive fuzzy neural network (NN) control using impedance learning for a constrained robot, subject to unknown system dynamics, the effect of state constraints, and the uncertain compliant environment with which the robot comes into contact. A fuzzy NN learning algorithm is developed to identify the uncertain plant model. The prominent feature of the fuzzy NN is that there is no need to get the prior knowledge about the uncertainty and a sufficient amount of observed data. Also, impedance learning is introduced to tackle the interaction between the robot and its environment, so that the robot follows a desired destination generated by impedance learning. A barrier Lyapunov function is used to address the effect of state constraints. With the proposed control, the stability of the closed-loop system is achieved via Lyapunov’s stability theory, and the tracking performance is guaranteed under the condition of state constraints and uncertainty. Some simulation studies are carried out to illustrate the effectiveness of the proposed scheme.


title: Web Content Extraction by Integrating Textual and Visual Importance of Web Pages

abstract: Web page has huge information and the information in the Web pages is useful in real world applications. The additional contents in the Web page like links, footers, headers and advertisements may cause the content extraction to be complicated. Irrelevant content in the Web page is treated as noisy content. A method is necessary to extract the informative content and discard the noisy content from Web pages. An integration of textual and visual importance is used to extract the informative content from Web pages. Initially a Web page is converted in to DOM (Document Object Model) tree. For each node in the DOM tree, textual and visual importance is calculated. Textual importance and visual importance is combined to form hybrid density. Density sum is calculated and used in content extraction algorithm to extract the informative content from Web pages. Performance of Web content extraction is obtained by calculating precision, recall, f-measure and accuracy. KeywordsContent Extraction, Web content Mining, DOM tree, Vision based Page Segmentation.


title: Towards Neural Theorem Proving at Scale

abstract: Neural models combining representation learning and reasoning in an end-to-end trainable manner are receiving increasing interest. However, their use is severely limited by their computational complexity, which renders them unusable on real world datasets. We focus on the Neural Theorem Prover (NTP) model proposed by Rockt{\"{a}}schel and Riedel (2017), a continuous relaxation of the Prolog backward chaining algorithm where unification between terms is replaced by the similarity between their embedding representations. For answering a given query, this model needs to consider all possible proof paths, and then aggregate results - this quickly becomes infeasible even for small Knowledge Bases (KBs). We observe that we can accurately approximate the inference process in this model by considering only proof paths associated with the highest proof scores. This enables inference and learning on previously impracticable KBs.


title: Differentially Private Publication of Sparse Data

abstract: The problem of privately releasing data is to provide a version of a dataset without revealing sensitive information about the individuals who contribute to the data. The model of differential privacy allows such private release while providing strong guarantees on the output. A basic mechanism achieves differential privacy by adding noise to the frequency counts in the contingency tables (or, a subset of the count data cube) derived from the dataset. However, when the dataset is sparse in its underlying space, as is the case for most multi-attribute relations, then the effect of adding noise is to vastly increase the size of the published data: it implicitly creates a huge number of dummy data points to mask the true data, making it almost impossible to work with. ::: We present techniques to overcome this roadblock and allow efficient private release of sparse data, while maintaining the guarantees of differential privacy. Our approach is to release a compact summary of the noisy data. Generating the noisy data and then summarizing it would still be very costly, so we show how to shortcut this step, and instead directly generate the summary from the input data, without materializing the vast intermediate noisy data. We instantiate this outline for a variety of sampling and filtering methods, and show how to use the resulting summary for approximate, private, query answering. Our experimental study shows that this is an effective, practical solution, with comparable and occasionally improved utility over the costly materialization approach.


title: Supervised Noun Phrase Coreference Research: The First Fifteen Years

abstract: The research focus of computational coreference resolution has exhibited a shift from heuristic approaches to machine learning approaches in the past decade. This paper surveys the major milestones in supervised coreference research since its inception fifteen years ago.


title: An empirical study of online consumer review spam: A design science approach

abstract: Because of the sheer volume of consumer reviews posted to the Internet, a manual approach for the detection and analysis of fake reviews is not practical. However, automated detection of fake reviews is a very challenging research problem given the fact that fake reviews could just look like legitimate reviews. Guided by the design science research methodology, one of the main contributions of our research work is the development of a novel methodology and an instantiation which can effectively detect untruthful consumer reviews. The results of our experiment confirm that the proposed methodology outperforms other well-known baseline methods for detecting untruthful reviews collected from amazon.com. Above all, the designed artifacts enable us to conduct an econometric analysis to examine the impact of fake reviews on product sales. To the best of our knowledge, this is the first empirical study conducted to analyze the economic impact of fake consumer reviews.


title: Classification of brain MRI using SVM and KNN classifier

abstract: The classification of the brain MRI is an important task. In this paper, the automatic approach to the classification of brain tumor into malignant Vs. benign and low grade Vs. high grade glioma is present. This method employs GLCM technique to extract the texture features from images and stored as a feature vector. The extracted features were classified using supervised SVM and KNN algorithm. The proposed system is applied on the 251 images (85 malignant and 166 benign) of clinical database and 80 images (50 low grade glioma and 30 high grade glioma) of brats 2012 training database. The accuracy of the proposed system is 96% and 86% for SVM and KNN respectively for clinical database and 85% and 72.50% for SVM and KNN respectively for Brats database.


Infliximab improves bone metabolism and bone mineral density in rheumatoid arthritis and ankylosing spondylitis: a prospective 2-year study


title: Business Intelligence from Social Media: A Study from the VAST Box Office Challenge

abstract: With over 16 million tweets per hour, 600 new blog posts per minute, and 400 million active users on Facebook, businesses have begun searching for ways to turn real-time consumer-based posts into actionable intelligence. The goal is to extract information from this noisy, unstructured data and use it for trend analysis and prediction. Current practices support the idea that visual analytics (VA) can help enable the effective analysis of such data. However, empirical evidence demonstrating the effectiveness of a VA solution is still lacking. A proposed VA toolkit extracts data from Bitly and Twitter to predict movie revenue and ratings. Results from the 2013 VAST Box Office Challenge demonstrate the benefit of an interactive environment for predictive analysis, compared to a purely statistical modeling approach. The VA approach used by the toolkit is generalizable to other domains involving social media data, such as sales forecasting and advertisement analysis.


title: Incorporating simulation and implementation into teaching computer organization and architecture

abstract: This paper describes the motivation, the realization, and the experience of incorporating simulation and hardware implementation into teaching computer organization and architecture to computer science students. It demonstrates that learning by doing has helped students to truly understand how a computer is constructed and how it really works in practice. Correlated with textbook material, a set of simulation and implementation projects were created on the basis of the work that students had done in previous homework and laboratory activities. Students can thus use these designs as building blocks for completing more complex projects at a later time. The projects cover a wide range of topics from simple adders up to ALU's and CPU's. These processors operate in a virtual manner on certain short assembly-language programs. Specifically, this paper shares the experience of using simulation tools (Alterareg Quartus II) and reconfigurable hardware prototyping platforms (Alterareg UP2 development boards)


A Case Study on Learning a Unified Encoder of Relations


Order Independent Transparency with Per-Pixel Linked Lists


title: Adaptive linear step-up procedures that control the false discovery rate

abstract: The linear step-up multiple testing procedure controls the false discovery rate at the desired level q for independent and positively dependent test statistics. When all null hypotheses are true, and the test statistics are independent and continuous, the bound is sharp. When some of the null hypotheses are not true, the procedure is conservative by a factor which is the proportion m-sub-0/m of the true null hypotheses among the hypotheses. We provide a new two-stage procedure in which the linear step-up procedure is used in stage one to estimate m-sub-0, providing a new level q′ which is used in the linear step-up procedure in the second stage. We prove that a general form of the two-stage procedure controls the false discovery rate at the desired level q. This framework enables us to study analytically the properties of other procedures that exist in the literature. A simulation study is presented that shows that two-stage adaptive procedures improve in power over the original procedure, mainly because they provide tighter control of the false discovery rate. We further study the performance of the current suggestions, some variations of the procedures, and previous suggestions, in the case where the test statistics are positively dependent, a case for which the original procedure controls the false discovery rate. In the setting studied here the newly proposed two-stage procedure is the only one that controls the false discovery rate. The procedures are illustrated with two examples of biological importance. Copyright 2006, Oxford University Press.