title: A note on the least square fitting of ellipses

abstract: Rosin, P.L., A note on the least squares fitting of ellipses, Pattern Recognition Letters 14 (1993) 799-808. The characteristics of two normalisations for the general conic equation are investigated for use in least squares fitting: either setting F= 1 or A + C= 1. The normalisations vary in three main areas: curvature bias, singularities, transformational invariance. It is shown that setting F= 1 is the more appropriate for ellipse fitting since it is less heavily curvature biased. Setting A + C= 1 produces more eccentric conics, resulting either in over-elongated ellipses or hyperbolae. Although the F= 1 normalisation is less well suited than the A + C= 1 normalisation with respect to singularities and transformational invariance both these problems are solved by normalising the data, shifting it so that it is centred on the origin before fitting, and then re-expressing the fit in the original frame of reference.


title: Sensitivity of Double-Gate and FinFET Devices to Process Variations

abstract: We investigate the manufacturability of 20-nm double-gate and FinFET devices in integrated circuits by projecting process tolerances. Two important factors affecting the sensitivity of device electrical parameters to physical variations were quantitatively considered. The quantum effect was computed using the density gradient method and the sensitivity of threshold voltage to random dopant fluctuation was studied by Monte Carlo simulation. Our results show the 3/spl sigma/ value of V/sub T/ variation caused by discrete impurity fluctuation can be greater than 100%. Thus, engineering the work function of gate materials and maintaining a nearly intrinsic channel is more desirable. Based on a design with an intrinsic channel and ideal gate work function, we analyzed the sensitivity of device electrical parameters to several important physical fluctuations such as the variations in gate length, body thickness, and gate dielectric thickness. We found that quantum effects have great impact on the performance of devices. As a result, the device electrical behavior is sensitive to small variations of body thickness. The effect dominates over the effects produced by other physical fluctuations. To achieve a relative variation of electrical parameters comparable to present practice in industry, we face a challenge of fin width control (less than /spl sim/1 nm 3/spl sigma/ value of variation) for the 20-nm FinFET devices. The constraint of the gate length variation is about 10/spl sim/15%. We estimate a tolerance of 1/spl sim/2 /spl Aring/ 3/spl sigma/ value of oxide thickness variation and up to 30% front-back oxide thickness mismatch.


title: C.: Adaptive content presentation for the Web

abstract: In this chapter we describe techniques for adaptive presentation of content on the Web. We first describe techniques to select and structure the content deemed to be most relevant for the current user in the current interaction context. We then illustrate approaches that deal with the problem of how to adaptively deliver this content.


title: Babble Noise: Modeling, Analysis, and Applications

abstract: Speech babble is one of the most challenging noise interference for all speech systems. Here, a systematic approach to model its underlying structure is proposed to further the existing knowledge of speech processing in noisy environments. This paper establishes a working foundation for the analysis and modeling of babble speech. We first address the underlying model for multiple speaker babble speech - considering the number of conversations versus the number of speakers contributing to babble. Next, based on this model, we develop an algorithm to detect the range of the number of speakers within an unknown babble speech sequence. Evaluation is performed using 110 h of data from the Switchboard corpus. The number of simultaneous conversations ranges from one to nine, or one to 18 subjects speaking. A speaker conversation stream detection rate in excess of 80% is achieved with a speaker window size of plusmn1 speakers. Finally, the problem of in-set/out-of-set speaker recognition is considered in the context of interfering babble speech noise. Results are shown for test durations from 2-8 s, with babble speaker groups ranging from two to nine subjects. It is shown that by choosing the correct number of speakers in the background babble an overall average performance gain of 6.44% equal error rate can be obtained. This study represents effectively the first effort in developing an overall model for speech babble, and with this, contributions are made for speech system robustness in noise.


title: SimCC-AT: A Method to Compute Similarity of Scientific Papers with Automatic Parameter Tuning

abstract: In this paper, we propose SimCC-AT (similarity based on content and citations with automatic parameter tuning) to compute the similarity of scientific papers. As in SimCC, the state-of-the-art method, we exploit a notion of a contribution score in similarity computation. SimCC-AT utilizes an automatic weighting scheme based on SVMrank and thus requires only a smaller number of experiments for parameter tuning than SimCC. Furthermore, our experimental results with a real-world dataset show that the accuracy of SimCC-AT is dramatically higher than that of other existing methods and is comparable to that of SimCC.


title: Understanding network failures in data centers: measurement, analysis, and implications

abstract: We present the first large-scale analysis of failures in a data center network. Through our analysis, we seek to answer several fundamental questions: which devices/links are most unreliable, what causes failures, how do failures impact network traffic and how effective is network redundancy? We answer these questions using multiple data sources commonly collected by network operators. The key findings of our study are that (1) data center networks show high reliability, (2) commodity switches such as ToRs and AggS are highly reliable, (3) load balancers dominate in terms of failure occurrences with many short-lived software related faults,(4) failures have potential to cause loss of many small packets such as keep alive messages and ACKs, and (5) network redundancy is only 40% effective in reducing the median impact of failure.


title: Crawler Mechanism with Circular Section to Realize a Sideling Motion

abstract: In this paper, a novel crawler mechanism for a sideling motion is presented. The crawler mechanism has a circular section and has active rolling axes at the center of the circles. Conventional crawler mechanism can convey heavy weigh, however they can not move to side. And previous crawler unit sinks into the soft ground when it whole body is inclined during moving. The proposed design solves this drawback by means of a circular section. An actual prototype model has been developed to illustrate the concept and to perform preliminary motion experiments, through which the basic performance of the Crawler Vehicle with this proposed Omni-Crawler mechanism was confirmed. An prototype has been developed to illustrate the concept. Motion experiments, with a test vehicle are also presented.


title: A wearable capacitive sensing system with phase-dependent classifier for locomotion mode recognition

abstract: Locomotion mode recognition is one of the most important aspects for the control of motion rehabilitation systems, e.g. lower-limb prostheses and exoskeletons. In this paper, we propose a capacitance based sensing system for recognizing human locomotion modes. The proposed system includes two rings as sensing front-ends of body capacitance, two sensing circuits for processing the signals and the gait event detection system. The deformation of muscles can be reflected by the changes of capacitance signals. To validate the developed prototype, nine locomotion modes are monitored and ten channels of capacitance signals are collected for locomotion mode recognition. With the combination of capacitive sensing approach and phase-dependent classification method, satisfactory recognition results are obtained.


title: The precise control of manipulators with high joint-friction using base force / torque sensing q

abstract: Joint friction is a major problem in accurate robot position control, particularly during low-speed, small-amplitude tasks. This paper proposes a simple, practical, and effective method to compensate for joint friction, using a six-axis force/torque sensor mounted under the manipulator. From these measurements, joint torques are estimated and used in a torque controller, which virtually eliminates friction and gravity effects, providing high-precision motion control even for small motions at low speed. The method does not require complex analytical friction models. The method also does not require expensive and unreliable internal joint-torque sensors. Experimental results demonstrate the effectiveness and practicality of the method for an electrical PUMA and hydraulic Schilling Titan II manipulator.


title: Accelerometer-based hand gesture recognition using feature weighted naïve bayesian classifiers and dynamic time warping

abstract: Accelerometer-based gesture recognition is a major area of interest in human-computer interaction. In this paper, we compare two approaches: naive Bayesian classification with feature separability weighting [1] and dynamic time warping [2]. Algorithms based on these two approaches are introduced and the results are compared. We evaluate both algorithms with four gesture types and five samples from five different people. The gesture identification accuracy for Bayesian classification and dynamic time warping are 97% and 95%, respectively.


title: Using high resolution UAV thermal imagery to assess the variability in the water status of five fruit tree species within a commercial orchard

abstract: This paper deals with the assessment of heterogeneity in water status in a commercial orchard, as a prerequisite for precision irrigation management. Remote sensing-derived indicators could be suitable for mapping water stress over large areas, and recent studies have demonstrated that high resolution airborne thermal imagery enables the assessment of discontinuous canopies as pure tree crowns can be targeted, thus eliminating the background effects. Airborne campaigns were conducted over a drip-irrigated com- mercial orchard in Southwestern Spain composed of five different orchard tree crops. An unmanned aerial vehicle with a thermal camera onboard was flown three times during the day on 8 July 2010, at 9, 11 and 13 h (local time). Stem water potential was measured at the same time of the flights. In some irrigation units, irrigation was stopped prior to the measurement date to induce water deficits for comparative purposes. Several approaches for using the thermal data were proposed. Daily evolution of the differential between canopy and air temperature (Tc - Ta) was compared to tree water status. The slope of the evolution of Tc - Ta with time was well correlated with water status and is proposed as a novel indicator linked with the stomatal behavior. The Crop Water Stress Index (CWSI) was calculated with the temperature data from the 13.00 h flight using an empirical approach for defining the upper and lower limits of Tc - Ta. The assessment of variability


title: Utilizing QR Code and Mobile Phones for Blinds and Visually Impaired People

abstract: In this paper a barcode-based system to help the visually impaired and blind people identify objects in the environment is introduced. The system is based on the idea of utilizing QR codes (two-dimensional barcode) affixed to an object and scanned using a camera phone equipped with QR reader software. The reader decodes the barcode to a URL and directs the phone's browser to fetch an audio file from the Web that contains a verbal description of the object. Our proposed system is expected to be useful in real-time interaction with different environments and to further illustrate the potential of our work, two scenarios are presented.


title: 3D Human Pose Estimation from Deep Multi-View 2D Pose

abstract: Human pose estimation - the process of recognizing a human's limb positions and orientations in a video - has many important applications including surveillance, diagnosis of movement disorders, and computer animation. While deep learning has lead to great advances in 2D and 3D pose estimation from single video sources, the problem of estimating 3D human pose from multiple video sensors with overlapping fields of view has received less attention. When the application allows use of multiple cameras, 3D human pose estimates may be greatly improved through fusion of multi-view pose estimates and observation of limbs that are fully or partially occluded in some views. Past approaches to multi-view 3D pose estimation have used probabilistic graphical models to reason over constraints, including per-image pose estimates, temporal smoothness, and limb length. In this paper, we present a pipeline for multi-view 3D pose estimation of multiple individuals which combines a state-of-art 2D pose detector with a factor graph of 3D limb constraints optimized with belief propagation. We evaluate our results on the TUM-Campus and Shelf datasets for multi-person 3D pose estimation and show that our system significantly out-performs the previous state-of-the-art with a simpler model of limb dependency.


title: Conditional Video Generation Using Action-Appearance Captions

abstract: The field of automatic video generation has received a boost thanks to the recent Generative Adversarial Networks (GANs). However, most existing methods cannot control the contents of the generated video using a text caption, losing their usefulness to a large extent. This particularly affects human videos due to their great variety of actions and appearances. This paper presents Conditional Flow and Texture GAN (CFT-GAN), a GAN-based video generation method from action-appearance captions. We propose a novel way of generating video by encoding a caption (e.g.,"a man in blue jeans is playing golf") in a two-stage generation pipeline. Our CFT-GAN uses such caption to generate an optical flow (action) and a texture (appearance) for each frame. As a result, the output video reflects the content specified in the caption in a plausible way. Moreover, to train our method, we constructed a new dataset for human video generation with captions. We evaluated the proposed method qualitatively and quantitatively via an ablation study and a user study. The results demonstrate that CFT-GAN is able to successfully generate videos containing the action and appearances indicated in the captions.


title: Effects of Anabolic Androgenic Steroids on the Reproductive System of Athletes and Recreational Users: A Systematic Review and Meta-Analysis

abstract: Background ::: Anabolic androgenic steroids (AAS) are testosterone derivatives used by athletes and recreational users to improve athletic performance and/or enhance appearance. Anabolic androgenic steroids use may have serious and potentially irreversible adverse effects on different organs and systems, including the reproductive system.


title: Analysis of the performance-influencing factors of virtualization platforms

abstract: Nowadays, virtualization solutions are gaining increasing importance. By enabling the sharing of physical resources, thus making resource usage more efficient, they promise energy and cost savings. Additionally, virtualization is the key enabling technology for Cloud Computing and server consolidation. However, the effects of sharing resources on system performance are not yet well-understood. This makes performance prediction and performance management of services deployed in such dynamic systems very challenging. Because of the large variety of virtualization solutions, a generic approach to predict the performance influences of virtualization platforms is highly desirable. In this paper, we present a hierarchical model capturing the major performance-relevant factors of virtualization platforms. We then propose a general methodology to quantify the influence of the identified factors based on an empirical approach using benchmarks. Finally, we present a case study of Citrix XenServer 5.5, a state-of-the-art virtualization platform.


Software Testing Techniques


title: Joint multi-feature spatial context for scene recognition in the semantic manifold

abstract: In the semantic multinomial framework patches and images are modeled as points in a semantic probability simplex. Patch theme models are learned resorting to weak supervision via image labels, which leads the problem of scene categories co-occurring in this semantic space. Fortunately, each category has its own co-occurrence patterns that are consistent across the images in that category. Thus, discovering and modeling these patterns is critical to improve the recognition performance in this representation. In this paper, we observe that not only global co-occurrences at the image-level are important, but also different regions have different category co-occurrence patterns. We exploit local contextual relations to address the problem of discovering consistent co-occurrence patterns and removing noisy ones. Our hypothesis is that a less noisy semantic representation, would greatly help the classifier to model consistent co-occurrences and discriminate better between scene categories. An important advantage of modeling features in a semantic space is that this space is feature independent. Thus, we can combine multiple features and spatial neighbors in the same common space, and formulate the problem as minimizing a context-dependent energy. Experimental results show that exploiting different types of contextual relations consistently improves the recognition accuracy. In particular, larger datasets benefit more from the proposed method, leading to very competitive performance.


title: First Blood The Story Of Fort Sumter

abstract: Thank you very much for reading first blood the story of fort sumter. As you may know, people have look hundreds times for their chosen novels like this first blood the story of fort sumter, but end up in harmful downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they cope with some malicious virus inside their desktop computer. first blood the story of fort sumter is available in our book collection an online access to it is set as public so you can get it instantly. Our books collection hosts in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the first blood the story of fort sumter is universally compatible with any devices to read.


title: A new computing environment for collective privacy protection from constrained healthcare devices to IoT cloud services

abstract: The Internet of healthcare things is essentially a new model that changes the way of the delivery and management of healthcare services. It utilizes digital sensors and cloud computing to present a quality healthcare service outside of the classical hospital environment. This resulted in the emergence of a new class of online web 4.0 services, which are termed “cloud healthcare services”. Cloud healthcare services offer a straightforward opportunity for patients to communicate with healthcare professionals and utilize their personal IoHT devices to obtain timely and accurate medical guidance and decisions. The personal IoHT devices integrate sensed health data at a central cloud healthcare service to extract useful health insights for wellness and preventive care strategies. However, the present practices for cloud healthcare services rely on a centralized approach, where patients’ health data are collected and stored on servers, located at remote locations, which might be functioning under data privacy laws somewhat different from the ones applied where the service is running. Promoting a privacy respecting cloud services encourages patients to actively participate in these healthcare services and to routinely provide an accurate and precious health data about themselves. With the emergence of fog computing paradigm, privacy protection can now be enforced at the edge of the patient’s network regardless of the location of service providers. In this paper, a framework for cloud healthcare recommender service is presented. We depicted the personal gateways at the patients’ side act as intermediate nodes (called fog nodes) between IoHT devices and cloud healthcare services. A fog-based middleware will be hosted on these fog nodes for an efficient aggregation of patients generated health data while maintaining the privacy and the confidentiality of their health profiles. The proposed middleware executes a two-stage concealment process that utilizes the hierarchical nature of IoHT devices. This will unburden the constrained IoHT devices from performing intensive privacy preserving processes. At that, the patients will be empowered with a tool to control the privacy of their health data by enabling them to release their health data in a concealed form. The further processing at the cloud healthcare service continues over the concealed data by applying the proposed protocols. The proposed solution was integrated into a scenario related to preserving the privacy of the patients’ health data when utilized by a cloud healthcare recommender service to generate health insights. Our approach induces a straightforward solution with accurate results, which are beneficial to both patients and service providers.


title: High-Frequency, High-Power Resonant Inverter With eGaN FET for Wireless Power Transfer

abstract: This letter presents a high-power resonant inverter using an enhancement mode gallium nitride (eGaN) device with magnetic resonant coupling (MRC) coils at 13.56 MHz for wireless power transfer (WPT). The power inverter driving the transmitting coils is based on a class $\Phi _2$ inverter, a single-switch topology with low switch-voltage stress, and fast transient response. The implementation utilizes a recently available eGaN device in a low-inductance package that is compatible with operation in the 10 s of MHz switching frequency. In this letter, we present experimental measurements of the inverter in a WPT application and characterize the system performance over various distances and operating conditions. Before using MRC coils, we evaluated the performance of the class $\Phi _2$ inverter with the eGaN FET. It delivered 1.3-kW output to a 50- $\Omega$ load with an efficiency of 95% when a 280-V input voltage was applied. For WPT operation, we added the open-type four-coil unit with a diameter of 300 mm to deliver power over 270-mm distance. With the addition of MRC coils, the class $\Phi _2$ inverter provided 823-W output power with 87% efficiency over 270-mm distance between coils.


title: Design of Bearingless Flux-Switching Permanent-Magnet Motor

abstract: In this paper, a novel E-core bearingless flux-switching permanent-magnet (BFSPM) motor is presented to overcome the shortcomings of rotor permanent-magnet-type bearingless motors. The basic structure and the operation principle are first described. In addition, the mathematical models of radial suspension forces and torque are deduced. Finally, based on the finite-element analysis, the optimization design of the 6/10 E-core BFSPM motor has been proposed to reduce torque ripple and increase suspension forces. The research results show that the torque ripple is significantly reduced by around 34%, whereas the suspension forces of the E-core BFSPM motor are increased by around 4% with the optimized parameters.


title: RISC I: A Reduced Instruction Set VLSI Computer

abstract: The Reduced Instruction Set Computer (RISC) Project investigates an alternative to the general trend toward computers with increasingly complex instruction sets: With a proper set of instructions and a corresponding architectural design, a machine with a high effective throughput can be achieved. The simplicity of the instruction set and addressing modes allows most instructions to execute in a single machine cycle, and the simplicity of each instruction guarantees a short cycle time. In addition, such a machine should have a much shorter design time. This paper presents the architecture of RISC I and its novel hardware support scheme for procedure call/return. Overlapping sets of register banks that can pass parameters directly to subroutines are largely responsible for the excellent performance of RISC I. Static and dynamic comparisons between this new architecture and more traditional machines are given. Although instructions are simpler, the average length of programs was found not to exceed programs for DEC VAX 11 by more than a factor of 2. Preliminary benchmarks demonstrate the performance advantages of RISC. It appears possible to build a single chip computer faster than VAX 11/780.


title: A synchronous charge extraction piezoelectric energy harvesting circuit based on precision active control peak detection with supplement energy

abstract: This paper proposes a cooperative power harvesting system. The system can harvest power from ambient vibration energy source with supplement thermal energy. It employs the Synchronous Charge Extraction (SCE) structure while a high-precision active peak detector is designed to control the switch, which consumes less power and is powered by thermoelectric power generation circuit. As a result, the energy harvesting efficiency of the piezoelectric energy harvesting circuit is improved by about 41.9%. The proposed circuit avoids the traditional rectifier bridge structure and outputs a stable DC voltage.


title: Meaning, communication, music: towards a revised communication model

abstract: Purpose – If an information retrieval system is going to be of value to the user then it must give meaning to the information which matches the meaning given to it by the user. The meaning given to music varies according to who is interpreting it – the author/composer, the performer, cataloguer or the listener – and this affects how music is organized and retrieved. This paper aims to examine the meaning of music, how meaning is communicated and suggests this may affect music retrieval.Design/methodology/approach – Musicology is used to define music and examine its functions leading to a discussion of how music has been organised and described. Various ways of establishing the meaning of music are reviewed, focussing on established musical analysis techniques. It is suggested that traditional methods are of limited use with digitised popular music. A discussion of semiotics and a review of semiotic analysis in western art music leads to a discussion of semiotics of popular music and examines ideas of Midd...


title: Eye-movement strategies in developmental prosopagnosia and “super” face recognition

abstract: Developmental prosopagnosia (DP) is a cognitive condition characterized by a severe deficit in face recognition. Few investigations have examined whether impairments at the early stages of processing may underpin the condition, and it is also unknown whether DP is simply the "bottom end" of the typical face-processing spectrum. To address these issues, we monitored the eye-movements of DPs, typical perceivers, and "super recognizers" (SRs) while they viewed a set of static images displaying people engaged in naturalistic social scenarios. Three key findings emerged: (a) Individuals with more severe prosopagnosia spent less time examining the internal facial region, (b) as observed in acquired prosopagnosia, some DPs spent less time examining the eyes and more time examining the mouth than controls, and (c) SRs spent more time examining the nose-a measure that also correlated with face recognition ability in controls. These findings support previous suggestions that DP is a heterogeneous condition, but suggest that at least the most severe cases represent a group of individuals that qualitatively differ from the typical population. While SRs seem to merely be those at the "top end" of normal, this work identifies the nose as a critical region for successful face recognition.


title: A review of argumentation for the Social Semantic Web

abstract: Argumentation represents the study of views and opinions that humans express with the goal of reaching a conclusion through logical reasoning. Since the 1950's, several models have been proposed to capture the essence of informal argumentation in different settings. With the emergence of the Web, and then the Semantic Web, this modeling shifted towards ontologies, while from the development perspective, we witnessed an important increase in Web 2.0 human-centered collaborative deliberation tools. Through a review of more than 150 scholarly papers, this article provides a comprehensive and comparative overview of approaches to modeling argumentation for the Social Semantic Web. We start from theoretical foundational models and investigate how they have influenced Social Web tools. We also look into Semantic Web argumentation models. Finally we end with Social Web tools for argumentation, including online applications combining Web 2.0 and Semantic Web technologies, following the path to a global World Wide Argument Web.


title: Use of learning, game theory and optimization as biomimetic approaches for Self-Organization in macro-femtocell coexistence

abstract: In this paper, we present the use of several Biomimetic approaches for Self Organization (SO) in heterogeneous scenarios where macrocell and femtocell networks coexist. Mainly these approaches are categorized in indirect biomimetics and direct biomimetics. Under indirect biomimetics we discuss 1) emerging paradigms in learning theory and 2) game theory for their potential to enable SO solutions in heterogeneous networks. By means of numerical results we demonstrate the pros and cons of these indirect biomimetic approaches for designing SO in macro-femto coexistence scenarios. Furthermore, we demonstrate the use of direct biomimetic approaches for designing SO by exploiting one to one mapping between a natural SO system and our system model for heterogeneous networks based on Outdoor Fixed Relays (OFR). Numerical results show that the proposed analytical solution can enhance wireless backhaul capacity of the OFR based femtocells by adapting the macro base station (BS) antenna tilts in a distributed and self organizing manner.


title: Red Media, Blue Media: Evidence of Ideological Selectivity in Media Use

abstract: We show that the demand for news varies with the perceived affinity of the news organization to the consumer’s political preferences. In an experimental setting, conservatives and Republicans preferred to read news reports attributed to Fox News and to avoid news from CNN and NPR. Democrats and liberals exhibited exactly the opposite syndrome—dividing their attention equally between CNN and NPR, but avoiding Fox News. This pattern of selective exposure based on partisan affinity held not only for news coverage of controversial issues but also for relatively ‘‘soft’’ subjects such as crime and travel. The tendency to select news based on anticipated agreement was also strengthened among more politically engaged partisans. Overall, these results suggest that the further proliferation of new media and enhanced media choices may contribute to the further polarization of the news audience.


title: Automatic Adaptation of Annotations

abstract: Manually annotated corpora are indispensable resources, yet for many annotation tasks, such as the creation of treebanks, there exist multiple corpora with different and incompatible annotation guidelines. This leads to an inefficient use of human expertise, but it could be remedied by integrating knowledge across corpora with different annotation guidelines. In this article we describe the problem of annotation adaptation and the intrinsic principles of the solutions, and present a series of successively enhanced models that can automatically adapt the divergence between different annotation formats. ::: ::: We evaluate our algorithms on the tasks of Chinese word segmentation and dependency parsing. For word segmentation, where there are no universal segmentation guidelines because of the lack of morphology in Chinese, we perform annotation adaptation from the much larger People's Daily corpus to the smaller but more popular Penn Chinese Treebank. For dependency parsing, we perform annotation adaptation from the Penn Chinese Treebank to a semantics-oriented Dependency Treebank, which is annotated using significantly different annotation guidelines. In both experiments, automatic annotation adaptation brings significant improvement, achieving state-of-the-art performance despite the use of purely local features in training.


title: Learning Regular Expressions for the Extraction of Product Attributes from E-commerce Microdata

abstract: A large number of e-commerce websites have started to markup their products using standards such as Microdata, Microformats, and RDFa. However, the markup is mostly not as fine-grained as desirable for applications and mostly consists of free text properties. This paper discusses the challenges that arise in the task of matching descriptions of electronic products from several thousand e-shops that offer Microdata markup. Specifically, our goal is to extract product attributes from product offers, by means of regular expressions, in order to build well structured product specifications. For this purpose we present a technique for learning regular expressions. We evaluate our attribute extraction approach using 1.9 million product offers from 9,240 e-shops which we extracted from the Common Crawl 2012, a large public Web corpus. Our results show that with our approach we are able to reach a similar matching quality as with manually defined regular expressions.


title: Bufadienolides (lucibufagins) from an ecologically aberrant firefly (Ellychnia corrusca)

abstract: The winter firefly (Ellychnia corrusca) is common throughout the eastern United States and Canada. It is notable among fireflies (Coleoptera: Lampyridae) for its adult activity during the winter and early spring months, and for its lack of a light-producing organ. Multiple lines of evidence suggest that E. corrusca is chemically protected, specifically its unusual phenology which results in prolonged exposure to predators, its aposematic coloration, its reflex bleeding upon disturbance, and its relatedness to toxic firefly genera. Chemical investigation of this species revealed the presence of large quantities (>500 μg/beetle) of steroidal pyrones known as lucibufagins. The structures of these lucibufagins were determined using 1D and 2D NMR spectroscopy along with UHPLC-HRMS. Four of these compounds were previously detected in fireflies of the genus Photinus, while the remaining four, which contain a highly modified D-ring of the steroid core, are previously unknown. Analysis of reflex bleeding showed that the hemolymph contained the lucibufagins and that it was primarily released via a band of cuticular pores along the costal margin of the elytra. In addition, our analysis of the eggs, larva, and pupa established that all immature stages possess lucibufagins, thus representing the first instance of a firefly species for which all life stages have been investigated chemically.


title: Symptomatic ectopic pancreas relieved by surgical excision.

abstract: It is clear that hetereotopic pancreatic tissue not associated with pancreatitis, mucosal ulceration or bleeding can produce symptoms, and as such requires removal. Many benign intramural tumors are asymptomatic and are discovered only at autopsy. The majority of the tumors discovered clinically ae symptomatic; therefore, operative removal of the lesion for relief of symptoms rather than for diagnosis or prophylaxis is generally acceptable to the patient, physician and surgeon. It would seem that, in these patients, radical therapy is the nonoperative choice, while operation leads to rapid recovery and a symptom-free postconvalescent life style.


title: A general design method for band-pass post filters in rectangular waveguide and substrate integrated waveguide

abstract: This paper presents an efficient design approach for band-pass post filters in waveguides, based on mode-matching technique. With this technique, the characteristics of symmetrical cylindrical post arrangements in the cross-section of the considered waveguides can be analyzed accurately and quickly. Importantly, the approach is applicable to post filters in waveguide but can be extended to Substrate Integrated Waveguide (SIW) technologies. The fast computations provide accurate relationships for the K factors as a function of the post radii and the distances between posts, and allow analyzing the influence of machining tolerances on the filter performance. The computations are used to choose reasonable posts for designing band-pass filters, while the error analysis helps to judge whether a given machining precision is sufficient. The approach is applied to a Chebyshev band-pass post filter and a band-pass SIW filter with a center frequency of 10.5 GHz and a fractional bandwidth of 9.52% with verification via full-wave simulations using HFSS and measurements on manufactured prototypes.


Role of Software Agents in E-Commerce


title: Tweetchain: An Alternative to Blockchain for Crowd-Based Applications

abstract: The assurance of information in the crowdsourcing domain cannot be committed to a single party, but should be distributed over the crowd. Blockchain is an infrastructure allowing this, because transactions are broadcast to the entire community and verified by miners. A node (or a coalition of nodes) with high computational power can play the role of miner to verify and approve transactions by computing the proof of work. Miners follows a highest-fee-first-served policy, so that a provider of a Blockchain-based application has to pay a non-negligible fee per transaction, to increase the likelihood that the application proceeds. This makes Blockchain not suitable for small-value transactions often occurring in the crowdsourcing paradigm. To overcome this drawback, in this paper we propose an alternative to Blockchain, leveraging an online social network (we choose Twitter to provide a proof of concept). Our protocol works by building a meshed chain of public posts to ensure transaction security instead of proof of work, and no trustworthiness assumption is required for the social network provider.


title: Qualitative research in health care: Assessing quality in qualitative research

abstract: This is the first in a series of three articles ::: ::: In the past decade, qualitative methods have become more commonplace in areas such as health services research and health technology assessment, and there has been a corresponding rise in the reporting of qualitative research studies in medical and related journals.1 Interest in these methods and their wider exposure in health research has led to necessary scrutiny of qualitative research. Researchers from other traditions are increasingly concerned to understand qualitative methods and, most importantly, to examine the claims researchers make about the findings obtained from these methods. ::: ::: The status of all forms of research depends on the quality of the methods used. In qualitative research, concern about assessing quality has manifested itself recently in the proliferation of guidelines for doing and judging qualitative work.2–5 Users and funders of research have had an important role in developing these guidelines as they become increasingly familiar with qualitative methods, but require some means of assessing their quality and of distinguishing “good” and “poor” quality research. However, the issue of “quality” in qualitative research is part of a much larger and contested debate about the nature of the knowledge produced by qualitative research, whether its quality can legitimately be judged, and, if so, how. This paper cannot do full justice to this wider epistemological debate. Rather it outlines two views of how qualitative methods might be judged and argues that qualitative research can be assessed according to two broad criteria: validity and relevance. ::: ::: #### Summary points ::: ::: Qualitative methods are now widely used and increasingly accepted in health research, but quality in qualitative research is a mystery to many health services researchers ::: ::: There is considerable debate over the nature of the knowledge produced by such methods and how such research should be judged ::: ::: Antirealists argue …


A Java-based topology optimization program with web access: nodal design variable approach


title: Capacitive driven-right-leg grounding in Indirect-contact ECG measurement

abstract: For the reduction of common-mode noise level in Indirect-contact ECG (IDC-ECG) measurement, a driven-right-leg grounding method was applied to the IDC-ECG. Because the IDC-ECG does not require any direct contact between the electrodes and the human skin, it is adequate for un-constraining long-term ECG measurement at home and its various applications are now under development. However, larger 60 Hz noise induced by power line appears in IDC-ECG than in conventional ECG, that is a restriction of IDC-ECG application. In this study, the driven-right-leg ground which has been used in conventional direct-contact ECG, was adapted to the IDC-ECG measurement, by feedback of the inversion of amplified common-mode noise to the body through the conductive textile laid on the chair seat. It was shown that the level of 60Hz power line noise was reduced to about -40 dB when the driven-right-leg gain was 1000.


title: Frozen in Time: How Disney Gender-Stereotypes Its Most Powerful Princess

abstract: Disney’s animated feature Frozen (2013) received acclaim for presenting a powerful heroine, Elsa, who is independent of men. Elsa’s avoidance of male suitors, however, could be a result of her protective father’s admonition not to “let them in” in order for her to be a “good girl.” In addition, Elsa’s power threatens emasculation of any potential suitor suggesting that power and romance are mutually exclusive. While some might consider a princess’s focus on power to be refreshing, it is significant that the audience does not see a woman attaining a balance between exercising authority and a relationship. Instead, power is a substitute for romance. Furthermore, despite Elsa’s seemingly triumphant liberation celebrated in Let It Go, selfless love rather than independence is the key to others’ approval of her as queen. Regardless of the need for novel female characters, Elsa is just a variation on the archetypal power-hungry female villain whose lust for power replaces lust for any person, and who threatens the patriarchal status quo. The only twist is that she finds redemption through gender-stereotypical compassion.


title: IEEE 802.11p: Towards an International Standard for Wireless Access in Vehicular Environments

abstract: Vehicular environments impose a set of new requirements on today's wireless communication systems. Vehicular safety communications applications cannot tolerate long connection establishment delays before being enabled to communicate with other vehicles encountered on the road. Similarly, non-safety applications also demand efficient connection setup with roadside stations providing services (e.g. digital map update) because of the limited time it takes for a car to drive through the coverage area. Additionally, the rapidly moving vehicles and complex roadway environment present challenges at the PHY level. The IEEE 802.11 standard body is currently working on a new amendment, IEEE 802.1 lp, to address these concerns. This document is named wireless access in vehicular environment, also known as WAVE. As of writing, the draft document for IEEE 802.11p is making progress and moving closer towards acceptance by the general IEEE 802.11 working group. It is projected to pass letter ballot in the first half of 2008. This paper provides an overview of the latest draft proposed for IEEE 802.11p. It is intended to provide an insight into the reasoning and approaches behind the document.


title: CPW to stripline transitions in LTCC for millimeter-wave applications

abstract: A novel additional intermediate ground plane structure is proposed in this paper to improve the RF performance of the grounded coplanar waveguide (GCPW) to stripline vertical transition. The ground plane is placed in an inner layer to reduce the distance between the upper and lower grounds, making the approximate impedance of GCPW close to 50 /spl Omega/. Meanwhile, with another additional pad in the inner layer, the inductive effect of the transition can be compensated and improvement has been achieved from 55 GHz to 70 GHz. The presented design was simulated and validated by measurements.


CHAPTER 7 Grounded Theory as an Emergent Method


title: Deep learning for 2D scan matching and loop closure

abstract: Although 2D LiDAR based Simultaneous Localization and Mapping (SLAM) is a relatively mature topic nowadays, the loop closure problem remains challenging due to the lack of distinctive features in 2D LiDAR range scans. Existing research can be roughly divided into correlation based approaches e.g. scan-to-submap matching and feature based methods e.g. bag-of-words (BoW). In this paper, we solve loop closure detection and relative pose transformation using 2D LiDAR within an end-to-end Deep Learning framework. The algorithm is verified with simulation data and on an Unmanned Aerial Vehicle (UAV) flying in indoor environment. The loop detection ConvNet alone achieves an accuracy of 98.2% in loop closure detection. With a verification step using the scan matching ConvNet, the false positive rate drops to around 0.001%. The proposed approach processes 6000 pairs of raw LiDAR scans per second on a Nvidia GTX1080 GPU.


title: North-Holland A typology of cutting and packing problems

abstract: Abstract Cutting and packing problems appear under various names in literature, e.g. cutting stock or trim loss problem, bin or strip packing problem, vehicle, pallet or container loading problem, nesting problem, knapsack problem etc. The paper develops a consistent and systematic approach for a comprehensive typology integrating the various kinds of problems. The typology is founded on the basic logical structure of cutting and packing problems. The purpose is to unify the different use of notions in the literature and to concentrate further research on special types of problems.


title: DBLP - Some Lessons Learned

abstract: The DBLP Computer Science Bibliography evolved from an early small experimental Web server to a popular service for the computer science community. Many design decisions and details of the public XML-records behind DBLP never were documented. This paper is a review of the evolution of DBLP. The main perspective is data modeling. In DBLP persons play a central role, our discussion of person names may be applicable to many other data bases. All DBLP data are available for your own experiments. You may either download the complete set, or use a simple XML-based API described in an online appendix.


title: PIXHAWK: A micro aerial vehicle design for autonomous flight using onboard computer vision

abstract: We describe a novel quadrotor Micro Air Vehicle (MAV) system that is designed to use computer vision algorithms within the flight control loop. The main contribution is a MAV system that is able to run both the vision-based flight control and stereo-vision-based obstacle detection parallelly on an embedded computer onboard the MAV. The system design features the integration of a powerful onboard computer and the synchronization of IMU-Vision measurements by hardware timestamping which allows tight integration of IMU measurements into the computer vision pipeline. We evaluate the accuracy of marker-based visual pose estimation for flight control and demonstrate marker-based autonomous flight including obstacle detection using stereo vision. We also show the benefits of our IMU-Vision synchronization for egomotion estimation in additional experiments where we use the synchronized measurements for pose estimation using the 2pt+gravity formulation of the PnP problem.


title: A review of enterprise content management (ECM): Growth and maturation of ECM from the year 2001 to 2011

abstract: Managing information and content in organisations can be a challenging task hence the implementation of the Enterprise Content Management (ECM) systems. ECM can be classified as integrated approach to information management. The ECM concept has received much attention from the practitioners and vendors perspective but ECM research is still an emerging field in Information Systems (IS) research. ECM research is approximately more than one decade but it only received little consideration from scholars and a lot of attention from industries. This paper will provide an in-depth review of the ECM literature mainly its implementation and the benefits associated with it. When looking at the four ECM dimensions, research indicates that the majority of the literature focuses on content mainly on the information and system views. However, ECM research still lacks consistency and well accepted definitions as it is a concept that is still evolving. Most of the literature consists of case studies and most frequent contribution in field studies with a promising trend towards contributing theory. This is a comprehensive analysis of the ECM literature across a number of sources and offers an important insight about the directions of the ECM research.


Cryptanalytic attacks on DES block cipher


The effects of speaking rate manipulations on the perception of voicing contrasts


title: Deformable models

abstract: We develop physically-based models of deformable curves, surfaces, and solids for use in computer graphics. Our deformable models are governed by the mechanical laws of continuous bodies whose shapes can change over time. These laws, expressed in the form of dynamic differential equations, unify the description of shape and motion. By solving the equations numerically we are able to create realistic animations involving the interaction of deformable models with various applied forces, ambient media, and impenetrable obstacles in a simulated physical world. We develop deformable models capable of perfectly elastic behavior and more general inelastic behavior, including viscoelasticity, plasticity, and fracture.


Bullying Detection


title: Read-Proof Hardware from Protective Coatings

abstract: In cryptography it is assumed that adversaries only have black box access to the secret keys of honest parties. In real life, however, the black box approach is not sufficient because attackers have access to many physical means that enable them to derive information on the secret keys. In order to limit the attacker’s ability to read out secret information, the concept of Algorithmic Tamper Proof (ATP) security is needed as put forth by Gennaro, Lysyanskaya, Malkin, Micali and Rabin. An essential component to achieve ATP security is read-proof hardware. In this paper, we develop an implementation of read-proof hardware that is resistant against invasive attacks. The construction is based on a hardware and a cryptographic part. The hardware consists of a protective coating that contains a lot of randomness. By performing measurements on the coating a fingerprint is derived. The cryptographic part consists of a Fuzzy Extractor that turns this fingerprint into a secure key. Hence no key is present in the non-volatile memory of the device. It is only constructed at the time when needed, and deleted afterwards. A practical implementation of the hardware and the cryptographic part is given. Finally, experimental evidence is given that an invasive attack on an IC equipped with this coating, reveals only a small amount of information on the key.


title: Local Stereo Matching with Segmentation-based Outlier Rejection

abstract: We present a new window-based stereo matching algorithm which focuses on robust outlier rejection during aggregation. The main difficulty for window-based methods lies in determining the best window shape and size for each pixel. Working from the assumption that depth discontinuities occur at colour boundaries, we segment the reference image and consider all window pixels outside the image segment that contains the pixel under consideration as outliers and greatly reduce their weight in the aggregation process. We developed a variation on the recursive moving average implementation to keep processing times independent from window size. Together with a robust matching cost and the combination of the left and right disparity maps, this gives us a robust local algorithm that approximates the quality of global techniques without sacrificing the speed and simplicity of window-based aggregation.


title: Arcs, Angles, or Areas: Individual Data Encodings in Pie and Donut Charts

abstract: Pie and donut charts have been a hotly debated topic in the visualization community for some time now. Even though pie charts have been around for over 200 years, our understanding of the perceptual factors used to read data in them is still limited. Data is encoded in pie and donut charts in three ways: arc length, center angle, and segment area. For our first study, we designed variations of pie charts to test the importance of individual encodings for reading accuracy. In our second study, we varied the inner radius of a donut chart from a filled pie to a thin outline to test the impact of removing the central angle. Both studies point to angle being the least important visual cue for both charts, and the donut chart being as accurate as the traditional pie chart.


title: Physical reconfiguration of an origami-inspired deployable microstrip patch antenna array

abstract: The physical reconfiguration and deployment of a 2×2 corporate-fed microstrip patch antenna array is investigated. The origami-inspired antenna array reconfigures structurally using a Miura-ori fold pattern to deploy to/from a compact folded state from/to a flat state. The impact of folding on the electromagnetic performance is evaluated across a range of physical states to study the impact of physical reconfiguration. In particular, the input impedance and beamforming capabilities are used to characterize the performance as a function of the primary folding parameter. These performance metrics are impacted by a feed network that extends across the folds and the beamforming capabilities that are impacted by the changing element spacing and orientation. Results from simulation and a fabricated structure are provided for a 2.4 GHz design.


Smart Home Energy Management System Based on Raspberry Pi Using Iot


title: Language play in a second language: Social media as contexts for emerging Sociopragmatic competence

abstract: The aim of this study is to gain insights into students’ language use on social media as part of the specific linguistic activities of second language (L2) learning, including development of sociopragmatic competence. Two Facebook groups were introduced in different English-as-L2 classes that were part of an international collaborative project comprising secondary schools in Colombia, Finland, Sweden and Taiwan. The study is theoretically grounded in sociocultural perspectives on learning, and the methods involve logging the students’ linguistic interactions in the social media groups. The analysis of the empirical material explored how the students framed the activities by different types of keying in their choice of linguistic repertoires. The findings show that the social media context offered a casual space for communication in which the students, by attentively attuning to the local coordinated framing, used diverse linguistic repertoires to play with the language. In instances of upkeyed framings, the language play was not only used with pragmatic intentions, but also as a means for various socializing purposes. In conclusion, it is suggested that language play on social media can be seen as a valuable activity in developing sociopragmatic competence to prepare students for L2 use outside of school.


title: Six Sigma Quality Management System and Design of Risk-based Statistical Quality Control.

abstract: Six sigma concepts provide a quality management system (QMS) with many useful tools for managing quality in medical laboratories. This Six Sigma QMS is driven by the quality required for the intended use of a test. The most useful form for this quality requirement is the allowable total error. Calculation of a sigma-metric provides the best predictor of risk for an analytical examination process, as well as a design parameter for selecting the statistical quality control (SQC) procedure necessary to detect medically important errors. Simple point estimates of sigma at medical decision concentrations are sufficient for laboratory applications.


Commentary on “Nondegloving technique for Peyronie's disease with penile prosthesis implantation and double dorsal-ventral patch graft”


title: Spectral K-Way Ratio-Cut Partitioning and Clustering

abstract: Recent research on partitioning has focussed on the ratio-cut cost metric which maintains a balance between the sizes of the edges cut and the sizes of the partitions without fixing the size of the partitions a priori. Iterative approaches and spectral approaches to two-way ratio-cut partitioning have yielded higher quality partitioning results. In this paper we develop a spectral approach to multiway ratio-cut partitioning which provides a generalization of the ratio-cut cost metric to k-way partitioning and a lower bound on this cost metric. Our approach involves finding the k smallest eigenvalue/eigenvector pairs of the Laplacian of the graph. The eigenvectors provide an embedding of the graph's n vertices into a k-dimensional subspace. We devise a time and space efficient clustering heuristic to coerce the points in the embedding into k partitions. Advancement over the current work is evidenced by the results of experiments on the standard benchmarks.


title: User acceptance of mobile Internet: Implication for convergence technologies

abstract: Using the Technology Acceptance Model as a conceptual framework and a method of structural equation modeling, this study analyzes the consumer attitude toward Wi-Bro drawing data from 515 consumers. Individuals' responses to questions about whether they use/accept Wi-Bro were collected and combined with various factors modified from the Technology Acceptance Model. The result of this study show that users' perceptions are significantly associated with their motivation to use Wi-Bro. Specifically, perceived quality and perceived availability are found to have significant effect on users' extrinsic and intrinsic motivation. These new factors are found to be Wi-Bro-specific factors, playing as enhancing factors to attitudes and intention.


title: Abnormal Processing of Affective Words by Psychopaths

abstract: We tested the hypothesis that psychopathy is associated with abnormal processing of affective verbal material. Criminal psychopaths and nonpsychopaths, defined by the Psychopathy Checklist, performed a lexical decision task (“Is it a word or not”) while we recorded reaction time and eventrelated potentials in response to letter-strings consisting of affective and neutral words and pronounceable nonwords. On the assumption that they do not make efficient use of affective information, our primary prediction was that psychopaths would show less behavioral and eventrelated potential differentiation between affective and neutral words than would nonpsychopaths. The results were in accordance with this prediction. The lexical decisions of nonpsychopaths were significantly faster, and relevant event-related potential components were significantly larger, to affective words than to neutral words. In sharp contrast, psychopaths failed to show reaction lime facilitation or larger amplitude event-related potentials to affective words. We suggest that psychopaths extract less information from affective words than do other individuals. Possible implications of these and related findings for understanding the behavior of psychopaths are discussed.


title: Labeling complicated objects: multi-view multi-instance multi-label learning

abstract: Multi-Instance Multi-Label (MIML) is a learning framework where an example is associated with multiple labels and represented by a set of feature vectors (multiple instances). In the formalization of MIML learning, instances come from a single source (single view). To leverage multiple information sources (multi-view), we develop a multi-view MIML framework based on hierarchical Bayesian Network, and derive an effective learning algorithm based on variational inference. The model can naturally deal with examples in which some views could be absent (partial examples). On multi-view datasets, it is shown that our method is better than other multi-view and single-view approaches particularly in the presence of partial examples. On single-view benchmarks, extensive evaluation shows that our method is highly competitive or better than other MIML approaches on labeling examples and instances. Moreover, our method can effectively handle datasets with a large number of labels.


Assessing the Corpus Size vs. Similarity Trade-off for Word Embeddings in Clinical NLP.


title: An Empirical Study of Investigating Mobile Applications Development Challenges

abstract: Context: mobile application development is rapidly evolving with substantial economic and scientific interest. One of the primary reasons for mobile application development failure is the increasing number of mobile platforms; some organizations endorse mobile application development before understanding the associated development challenges of each target platform. Objective: the objective of this paper is to identify the challenges of native, web, and hybrid mobile applications, which can undermine the successful development of such applications. Method: we adopted a two-phase research approach: at first, the challenges were identified via a systematic literature review (SLR); and then, the identified challenges were validated through conducting interviews with practitioners. Results: through both research approaches, we identified nine challenges vital to the success of mobile application development and four additional challenges from interviews not reported in the literature. A comparison of the challenges (native, web, and hybrid) identified in SLR indicates that there are slightly more differences than similarities between the challenges. On the other hand, the challenges (native, web, and hybrid) identified in interviews indicates that there are more similarities than differences between the challenges. Our results show a weak negative correlation between the ranks obtained from the SLR and the interviews ( $[rs(9) = -.034]$ , $p = 0.932$ ). The results obtained from our t-test (i.e., $t = 0.868, p = 0.402 > 0.05$ ) depicts that there is no significant difference between the findings of SLR and interviews. Conclusions: mobile application development organizations should try to address the identified challenges when developing mobile applications (native, web, or hybrid) to increase the probability of mobile application success.


title: Book organization checking algorithm using image segmentation and OCR

abstract: Organizing and rearranging library books in appropriate order requires attention and care of librarians. The book indexing and organizing algorithm will detect misplaced library books and suggest a proper position to the user. It can be implemented in a smartphone or a server or an autonomous embedded system. It first segments the captured image to find proper tag area in the book. Then crops that tag area and process that with OCR to detect string. From the string, it is possible to determine if a book is on the right shelf or row.


title: Targeting inter set write variation to improve the lifetime of non-volatile cache using fellow sets

abstract: High density and low static power exhibited by nonvolatile technologies (NVM) have made them popular candidates in the memory hierarchy, including caches. Writes within a cache set are governed by the access pattern as well as replacement policies, leading to a large write variation. This variation is of concern as it leads to early breakdown of the NVM cells due to large writes thus reducing the effective lifetime. This paper presents a technique to improve the lifetime of non-volatile caches by reducing the inter-set write variation. Our policy partitions the cache sets into groups called fellow groups. Every set has two logical parts: Normal and Reserved. Sets within a fellow group can use the reserved parts from their fellow sets to distribute the writes uniformly. Experimental results using full system simulation show that the proposed technique shows significant reduction in inter-set write variation over the baseline and existing technique.


title: Prediction of Bond Wire Fatigue of IGBTs in a PV Inverter Under a Long-Term Operation

abstract: Bond wire fatigue is one of the dominant failure mechanisms in IGBT modules. However, the bond wire lifetime is not easily predictable and measurable to date due to several challenges. To overcome this challenge, this paper proposes a Monte Carlo based analysis method to predict the lifetime consumption of bond wires in a Photovoltaic (PV) inverter under long-term operation. The parameter distributions of IGBTs due to manufacturing variation and the annual stress profiles due to intermittent nature of solar irradiance and ambient temperature are taken into consideration. The proposed method enables a more realistic lifetime prediction with a specified confidence level compared to the state-of-the-art approaches. A study case on IGBT modules in a 10 kW three-phase PV inverter demonstrates the procedure and the results of the analysis. Finally, the lifetime distribution of bond wires permits to estimate the risk of unreliability of a single IGBT in a Photovoltaic (PV) inverter.


title: Agricultural robots—system analysis and economic feasibility

abstract: This paper focuses on the economic feasibility of applying autonomous robotic vehicles compared to conventional systems in three different applications: robotic weeding in high value crops (particularly sugar beet), crop scouting in cereals and grass cutting on golf courses. The comparison was based on a systems analysis and an individual economic feasibility study for each of the three applications. The results showed that in all three scenarios, the robotic applications are more economically feasible than the conventional systems. The high cost of real time kinematics Global Positioning System (RTK-GPS) and the small capacity of the vehicles are the main parameters that increase the cost of the robotic systems.


A Generative Attentional Neural Network Model for Dialogue Act Classification


title: Image Enhancement of Low-light Scenes with Near-infrared Flash Images

abstract: We present a novel technique for enhancing an image captured in low light by using near-infrared flash images. The main idea is to combine a color image with near-infrared flash images captured at the same time without causing any interference with the color image. In this work, near-infrared flash images are effectively used for removing annoying effects that are commonly observed in images of dimly lit environments, namely, image noise and motion blur. Our denoising method uses a pair of color and near-infrared flash images captured simultaneously. Therefore it is applicable to dynamic scenes, whereas existing methods assume stationary scenes and require a pair of flash and no-flash color images captured sequentially. Our deblurring method utilizes a set of near-infrared flash images captured during the exposure time of a single color image and directly acquires a motion blur kernel based on optical flow. We implemented a multispectral imaging system and confirmed the effectiveness of our technique through experiments using real images.


title: Multiple Object Tracking: A Literature Review

abstract: Multiple Object Tracking (MOT) is an important computer vision problem which has gained increasing attention due to its academic and commercial potential. Although different kinds of approaches have been proposed to tackle this problem, it still remains challenging due to factors like abrupt appearance changes and severe object occlusions. In this work, we contribute the first comprehensive and most recent review on this problem. We inspect the recent advances in various aspects and propose some interesting directions for future research. To the best of our knowledge, there has not been any extensive review on this topic in the community. We endeavor to provide a thorough review on the development of this problem in recent decades. The main contributions of this review are fourfold: 1) Key aspects in a multiple object tracking system, including formulation, categorization, key principles, evaluation of an MOT are discussed. 2) Instead of enumerating individual works, we discuss existing approaches according to various aspects, in each of which methods are divided into different groups and each group is discussed in detail for the principles, advances and drawbacks. 3) We examine experiments of existing publications and summarize results on popular datasets to provide quantitative comparisons. We also point to some interesting discoveries by analyzing these results. 4) We provide a discussion about issues of MOT research, as well as some interesting directions which could possibly become potential research effort in the future.


title: Hand shape based biometric authentication system using radon transform and collaborative representation based classification

abstract: Biometric authentication systems are used to identify individuals based on their unique physiological and behavioral characteristics for access control and security enhancement. In this paper, we propose a novel method of authentication using hand images by collaborative representation based classification (CRC). The contour or hand shape of a query image is extracted by morphological operations and its radon transform is computed along an optimal direction to produce unique one-dimensional feature vector. The feature vector of the query image is then coded over similarly processed training samples from all subjects (or classes) and identified as a member of the class which produces the least reconstruction residual by regularized least square (RLS) instantiation of collaborative representation. Extensive experiments were conducted on a database of 300 images employing two different mathematical operators for dimensionality reduction of acquired feature vector.


title: On extracting feature models from product descriptions

abstract: In product line engineering, domain analysis is the process of analyzing related products to identify their common and variable features. This process is generally carried out by experts on the basis of existing product descriptions, which are expressed in a more or less structured way. Modeling and reasoning about product descriptions are error-prone and time consuming tasks. Feature models (FMs) constitute popular means to specify product commonalities and variabilities in a compact way, and to provide automated support to the domain analysis process. This paper aims at easing the transition from product descriptions expressed in a tabular format to FMs accurately representing them. This process is parameterized through a dedicated language and high-level directives (e.g., products/features scoping). We guarantee that the resulting FM represents the set of legal feature combinations supported by the considered products and has a readable tree hierarchy together with variability information. We report on our experiments based on public data and characterize the properties of the derived FMs.


title: Potential immune escape mechanisms underlying the distinct clinical outcome of immune checkpoint blockades in small cell lung cancer

abstract: Small cell lung cancer (SCLC) is one of the deadliest cancer types in the world. Despite the high response rate to frontline platinum-containing doublets, relapse is inevitable for the majority of patients and the prognosis is poor. Topotecan, which has limited efficacy, has remained the standard second-line therapy for approximately three decades. Although SCLC has a high mutation burden, the clinical efficacy of immune checkpoint blockades (ICBs) in SCLC is far less pronounced than that in non-small cell lung cancer (NSCLC). Only atezolizumab in combination with chemotherapy improved overall survival over chemotherapy alone in the phase III CheckMate 133 trial and has recently received FDA approval as first-line therapy. Most studies concerning ICBs in SCLC are limited to early-phase studies and found that ICBs were not superior to traditional chemotherapy. Why is there such a large difference between SCLC and NSCLC? In this review, comparative analyses of previous studies indicate that SCLC is even more immunodeficient than NSCLC and the potential immune escape mechanisms in SCLC may involve the low expression of PD-L1 and the downregulation of major histocompability complex (MHC) molecules and regulatory chemokines. In consideration of these immune dysfunctions, we speculate that chemotherapy and radiotherapy prior to immunotherapy, the combination of ICBs with antiangiogenic treatment, and selecting tumor mutation burden in combination with PD-L1 expression as biomarkers could be promising strategies to improve the clinical efficacy of immunotherapy for SCLC.


title: Frame-Semantic Parsing

abstract: Frame semantics is a linguistic theory that has been instantiated for English in the FrameNet lexicon. We solve the problem of frame-semantic parsing using a two-stage statistical model that takes lexical targets i.e., content words and phrases in their sentential contexts and predicts frame-semantic structures. Given a target in context, the first stage disambiguates it to a semantic frame. This model uses latent variables and semi-supervised learning to improve frame disambiguation for targets unseen at training time. The second stage finds the target's locally expressed semantic arguments. At inference time, a fast exact dual decomposition algorithm collectively predicts all the arguments of a frame at once in order to respect declaratively stated linguistic constraints, resulting in qualitatively better structures than nave local predictors. Both components are feature-based and discriminatively trained on a small set of annotated frame-semantic parses. On the SemEval 2007 benchmark data set, the approach, along with a heuristic identifier of frame-evoking targets, outperforms the prior state of the art by significant margins. Additionally, we present experiments on the much larger FrameNet 1.5 data set. We have released our frame-semantic parser as open-source software.


title: Does the benefit of testing depend on lag, and if so, why? Evaluating the elaborative retrieval hypothesis

abstract: Despite the voluminous literatures on testing effects and lag effects, surprisingly few studies have examined whether testing and lag effects interact, and no prior research has directly investigated why this might be the case. To this end, in the present research we evaluated the elaborative retrieval hypothesis (ERH) as a possible explanation for why testing effects depend on lag. Elaborative retrieval involves the activation of cue-related information during the long-term memory search for the target. If the target is successfully retrieved, this additional information is encoded with the cue–target pair to yield a more elaborated memory trace that enhances target access on a later memory test. The ERH states that the degree of elaborative retrieval during practice is greater when testing takes place after a long rather than a short lag (whereas elaborative retrieval during restudy is minimal at either lag). Across two experiments, final-test performance was greater following practice testing than following restudy only, and this memorial advantage was greater with long-lag than with short-lag practice. The final test also included novel cue conditions used to diagnose the degree of elaborative retrieval during practice. The overall pattern of performance in these conditions provided consistent evidence for the ERH, with more extensive elaborative retrieval during long- than during short-lag practice testing.


title: Decoding the cognitive map: ensemble hippocampal sequences and decision making

abstract: Tolman proposed that complex animal behavior is mediated by the cognitive map, an integrative learning system that allows animals to reconfigure previous experience in order to compute predictions about the future. The discovery of place cells in the rodent hippocampus immediately suggested a plausible neural mechanism to fulfill the ‘map’ component of Tolman's theory. Recent work examining hippocampal representations occurring at fast time scales suggests that these sequences might be important for supporting the inferential mental operations associated with the cognitive map function. New findings that hippocampal sequences play an important causal role in mediating adaptive behavior on a moment-by-moment basis suggest specific neural processes that may underlie Tolman's cognitive map framework.


title: Stochastic Fractal Search : A powerful metaheuristic algorithm

abstract: Evolutionary Algorithms (EAs) are well-known terms in many science fields. EAs usually interfere with science problems when common mathematical methods are unable to provide a good solution or finding the exact solution requires an unreasonable amount of time. Nowadays, many EA methods have been proposed and developed. Most of them imitate natural behavior, such as swarm animal movement. In this paper, inspired by the natural phenomenon of growth, a new metaheuristic algorithm is presented that uses a mathematic concept called the fractal. Using the diffusion property which is seen regularly in random fractals, the particles in the new algorithm explore the search space more efficiently. To verify the performance of our approach, both the constrained and unconstrained standard benchmark functions are employed. Some classic functions including unimodal and multimodal functions, as well as some modern hard functions, are employed as unconstrained benchmark functions; On the other hand, some well-known engineering design optimization problems commonly used in the literature are considered as constrained benchmark functions. Numerical results and comparisons with other state of the art stochastic algorithms are also provided. Considering both convergence and accuracy simultaneously, experimental results prove that the proposed method performs significantly better than other previous well-known metaheuristic algorithms in terms of avoiding getting stuck in local minimums, and finding the global minimum.


title: Web Application Migration with Closure Reconstruction

abstract: Due to its high portability and simplicity, web application (app) based on HTML/JavaScript/CSS has been widely used for various smart-device platforms. To take advantage of its wide platform pool, a new idea called app migration has been proposed for the web platform. Web app migration is a framework to serialize a web app running on a device and restore it in another device to continue its execution. In JavaScript semantics, one of the language features that does not allow easy app migration is a closure. A JavaScript function can access variables defined in its outer function even if the execution of the outer function is terminated. It is allowed because the inner function is created as a closure such that it contains the outer function's environment. This feature is widely used in web app development because it is the most common way to implement data encapsulation in web programming. Closures are not easy to serialize because environments can be shared by a number of closures and environments can be created in a nested way. In this paper, we propose a novel approach to fully serialize closures. We created mechanisms to extract information from a closure's environment through the JavaScript engine and to serialize the information in a proper order so that the original relationship between closures and environments can be restored properly. We implemented our mechanism on the WebKit browser and successfully migrated Octane benchmarks and seven real web apps which heavily exploit closures. We also show that our mechanism works correctly even for some extreme, closure-heavy cases.


title: Powered Hip Exoskeletons Can Reduce the User's Hip and Ankle Muscle Activations During Walking

abstract: In this paper, we study the human locomotor adaptation to the action of a powered exoskeleton providing assistive torque at the user's hip during walking. To this end, we propose a controller that provides the user's hip with a fraction of the nominal torque profile, adapted to the specific gait features of the user from Winter's reference data . The assistive controller has been implemented on the ALEX II exoskeleton and tested on ten healthy subjects. Experimental results show that when assisted by the exoskeleton, users can reduce the muscle effort compared to free walking. Despite providing assistance only to the hip joint, both hip and ankle muscles significantly reduced their activation, indicating a clear tradeoff between hip and ankle strategy to propel walking.


title: Too Far to See? Not Really! --- Pedestrian Detection with Scale-aware Localization Policy

abstract: A major bottleneck of pedestrian detection lies on the sharp performance deterioration in the presence of small-size pedestrians that are relatively far from the camera. Motivated by the observation that pedestrians of disparate spatial scales exhibit distinct visual appearances, we propose in this paper an active pedestrian detector that explicitly operates over multiple-layer neuronal representations of the input still image. More specifically, convolutional neural nets such as ResNet and faster R-CNNs are exploited to provide a rich and discriminative hierarchy of feature representations as well as initial pedestrian proposals. Here each pedestrian observation of distinct size could be best characterized in terms of the ResNet feature representation at a certain layer of the hierarchy; Meanwhile, initial pedestrian proposals are attained by faster R-CNNs techniques, i.e. region proposal network and follow-up region of interesting pooling layer employed right after the specific ResNet convolutional layer of interest, to produce joint predictions on the bounding-box proposals' locations and categories (i.e. pedestrian or not). This is engaged as input to our active detector where for each initial pedestrian proposal, a sequence of coordinate transformation actions is carried out to determine its proper x-y 2D location and layer of feature representation, or eventually terminated as being background. Empirically our approach is demonstrated to produce overall lower detection errors on widely-used benchmarks, and it works particularly well with far-scale pedestrians. For example, compared with 60.51% log-average miss rate of the state-of-the-art MS-CNN for far-scale pedestrians (those below 80 pixels in bounding-box height) of the Caltech benchmark, the miss rate of our approach is 41.85%, with a notable reduction of 18.68%.


title: Dr. Inventor Framework: Extracting Structured Information from Scientific Publications

abstract: Even if research communities and publishing houses are putting increasing efforts in delivering scientific articles as structured texts, nowadays a considerable part of on-line scientific literature is still available in layout-oriented data formats, like PDF, lacking any explicit structural or semantic information. As a consequence the bootstrap of textual analysis of scientific papers is often a time-consuming activity. We present the first version of the Dr. Inventor Framework, a publicly available collection of scientific text mining components useful to prevent or at least mitigate this problem. Thanks to the integration and the customization of several text mining tools and on-line services, the Dr. Inventor Framework is able to analyze scientific publications both in plain text and PDF format, making explicit and easily accessible core aspects of their structure and semantics. The facilities implemented by the Framework include the extraction of structured textual contents, the discursive characterization of sentences, the identifications of the structural elements of both papers header and bibliographic entries and the generation of graph based representations of text excerpts. The Framework is distributed as a Java library. We describe in detail the scientific mining facilities included in the Framework and present two use cases where the Framework is respectively exploited to boost scientific creativity and to generate RDF graphs from scientific publications.


title: Cyberattack Detection using Deep Generative Models with Variational Inference

abstract: Recent years have witnessed a rise in the frequency and intensity of cyberattacks targeted at critical infrastructure systems. This study designs a versatile, data-driven cyberattack detection platform for infrastructure systems cybersecurity, with a special demonstration in water sector. A deep generative model with variational inference autonomously learns normal system behavior and detects attacks as they occur. The model can process the natural data in its raw form and automatically discover and learn its representations, hence augmenting system knowledge discovery and reducing the need for laborious human engineering and domain expertise. The proposed model is applied to a simulated cyberattack detection problem involving a drinking water distribution system subject to programmable logic controller hacks, malicious actuator activation, and deception attacks. The model is only provided with observations of the system, such as pump pressure and tank water level reads, and is blind to the internal structures and workings of the water distribution system. The simulated attacks are manifested in the model's generated reproduction probability plot, indicating its ability to discern the attacks. There is, however, need for improvements in reducing false alarms, especially by optimizing detection thresholds. Altogether, the results indicate ability of the model in distinguishing attacks and their repercussions from normal system operation in water distribution systems, and the promise it holds for cyberattack detection in other domains.


title: AUTOMATIC CORRESPONDENCE FOR 3 D MODELING : AN EXTENSIVE REVIEW

abstract: To generate a 3D computer model of a free-form object, multiple range images (point clouds) covering its entire surface are acquired from different viewpoints. These views are then aligned in a common coordinate basis by minimizing the distance error between their corresponding points. Establishing correspondences automatically is an inherently challenging problem due to the lack of any type of information other than the geometrical information extracted from the point clouds. Existing "automatic" correspondence techniques achieve automatism at the expense of other important specifications namely, applicability to free-form objects, accuracy, efficiency, robustness to resolution and surface sampling, robustness to overlap, robustness to noise and finally their applicability to simultaneous multiview correspondence. There is also a lack of a review paper that describes and critically analyzes these techniques. In this paper, we present such an extensive review and carry out the analysis of each technique according to the above listed indispensable criteria. Our analysis shows that none of these techniques fully meets these criteria and that there is still a need for the development of practical automatic correspondence algorithms.


title: Analysis and design of a high-efficiency multistage Doherty power amplifier for wireless communications

abstract: A comprehensive analysis of a multistage Doherty amplifier, which can be used to achieve higher efficiency at a lower output power level compared to the classical Doherty amplifier, is presented. Generalized design equations that explain the operation of a three-stage Doherty amplifier, which can be easily extended to an N-stage Doherty amplifier, are derived. In addition, the optimum device periphery, which minimizes AM-AM distortion for perfect Doherty amplifier operation, is analyzed. For the first time, a multistage Doherty power amplifier that meets wide-band code-division multiple-access (WCDMA) requirements is demonstrated. The designed power amplifier exhibits a power-added efficiency (PAE) of 42% at 6-dB output power backoff and 27% at 12-dB output power backoff. These PAEs are more than 2/spl times/ and 7/spl times/ better, respectively, than that of a single-stage linear power amplifier at the same output power backoff levels. The power amplifier is capable of delivering up to 33 dBm of output power, and has a maximum adjacent channel power leakage ratio of -35 and -47 dBc at 5- and 10-MHz offset, respectively. To the best of the authors' knowledge, these represent the best reported results of a Doherty amplifier for WCDMA application in the 1.95-GHz band to date.


title: Android UI Deception Revisited: Attacks and Defenses

abstract: App-based deception attacks are increasingly a problem on mobile devices and they are used to steal passwords, credit card numbers, text messages, etc. Current versions of Android are susceptible to these attacks. Recently, Bianchi et al. proposed a novel solution “What the App is That” that included a host-based system to identify apps to users via a security indicator and help assure them that their input goes to the identified apps [7]. Unfortunately, we found that the solution has a significant side channel vulnerability as well as susceptibility to clickjacking that allow non-privileged malware to completely compromise the defenses, and successfully steal passwords or other keyboard input. We discuss the vulnerabilities found, propose possible defenses, and then evaluate the defenses against different types of UI deception attacks.


title: Characteristics of Higher-level Languages for Software Architecture

abstract: Abstract : As the size and complexity of software systems increases, the design and specification of overall system structure-or software architecture-emerges as a central concern. Architectural issues include the gross organization of the system, protocols for communication and data access, assignment of functionality to design elements, and selection among design alternatives. Currently system designers have at their disposal two primary ways of defining software architecture: they can use the modularization facilities of existing programming languages and module interconnection languages; or they can describe their designs using informal diagrams and idiomatic phrases (such as 'client-server organization'). In this paper we explain why neither alternative is adequate. We consider the nature of architectural description as it is performed informally by systems designers. Then we show that regularities in these descriptions can form the basis for architectural description languages. Next we identify specific properties that such languages should have. Finally, we illustrate how current notations fail to satisfy those properties.


title: Discovering Parallel Text from the World Wide Web

abstract: Parallel corpus is a rich linguistic resource for various multilingual text management tasks, including cross-lingual text retrieval, multilingual computational linguistics and multilingual text mining. Constructing a parallel corpus requires effective alignment of parallel documents. In this paper, we develop a parallel page identification system for identifying and aligning parallel documents from the World Wide Web. The system crawls the Web to fetch potentially parallel multilingual Web documents using a Web spider. To determine the parallelism between potential document pairs, two modules are developed. First, a filename comparison module is used to check filename resemblance. Second, a content analysis module is used to measure the semantic similarity. The experiment conducted to a multilingual Web site shows the effectiveness of the system.


title: QuAC : Question Answering in Context

abstract: We present QuAC, a dataset for Question Answering in Context that contains 14K information-seeking QA dialogs (100K questions in total). The dialogs involve two crowd workers: (1) a student who poses a sequence of freeform questions to learn as much as possible about a hidden Wikipedia text, and (2) a teacher who answers the questions by providing short excerpts from the text. QuAC introduces challenges not found in existing machine comprehension datasets: its questions are often more open-ended, unanswerable, or only meaningful within the dialog context, as we show in a detailed qualitative evaluation. We also report results for a number of reference models, including a recently state-of-the-art reading comprehension architecture extended to model dialog context. Our best model underperforms humans by 20 F1, suggesting that there is significant room for future work on this data. Dataset, baseline, and leaderboard available at this http URL


title: Cost Sensitive Credit Card Fraud Detection Using Bayes Minimum Risk

abstract: Credit card fraud is a growing problem that affects card holders around the world. Fraud detection has been an interesting topic in machine learning. Nevertheless, current state of the art credit card fraud detection algorithms miss to include the real costs of credit card fraud as a measure to evaluate algorithms. In this paper a new comparison measure that realistically represents the monetary gains and losses due to fraud detection is proposed. Moreover, using the proposed cost measure a cost sensitive method based on Bayes minimum risk is presented. This method is compared with state of the art algorithms and shows improvements up to 23% measured by cost. The results of this paper are based on real life transactional data provided by a large European card processing company.


title: Empathy Is a Protective Factor of Burnout in Physicians: New Neuro-Phenomenological Hypotheses Regarding Empathy and Sympathy in Care Relationship

abstract: Burnout is a multidimensional work-related syndrome that is characterized by emotional exhaustion, depersonalization – or cynicism – and diminution of personal accomplishment. Burnout particularly affects physicians. In medicine as well as other professions, burnout occurrence depends on personal, developmental-psychodynamic, professional and environmental factors. Recently, it has been proposed to specifically define burnout in physicians as “pathology of care relationship”. That is, burnout would arise, among the above-mentioned factors, from the specificity of the care relationship as it develops between the physician and the patient. Accordingly, experimental studies and theoretical approaches have suggested that burnout and empathy, which is one of the most important skills in physicians, are closely linked. However, the nature of the relation between burnout and empathy remains not yet understood, as reflected in the variety of theoretical and contradictory hypotheses attempting to causally relate these two phenomena. Firstly, we here question the epistemological problem concerning the modality of the burnout-empathy link. Secondly, we hypothesize that considering the multidimensional features of both burnout and empathy, on one hand, and on the other hand, the distinction between empathy and sympathy enables to overcome these contradictions and, consequently, gives a better understanding of the relationship between burnout and empathy in physicians. Thirdly, we propose that clarifying the link between burnout, empathy and sympathy would enable developing specific training in medical students and continuous professional formation in senior physicians and would potentially contribute to the prevention of burnout in medical care.


Multiple instance regression


title: A Dataset for Lane Instance Segmentation in Urban Environments

abstract: Autonomous vehicles require knowledge of the surrounding road layout, which can be predicted by state-of-the-art CNNs. This work addresses the current lack of data for determining lane instances, which are needed for various driving manoeuvres. The main issue is the time-consuming manual labelling process, typically applied per image. We notice that driving the car is itself a form of annotation. Therefore, we propose a semi-automated method that allows for efficient labelling of image sequences by utilising an estimated road plane in 3D based on where the car has driven and projecting labels from this plane into all images of the sequence. The average labelling time per image is reduced to 5 seconds and only an inexpensive dash-cam is required for data capture. We are releasing a dataset of 24,000 images and additionally show experimental semantic segmentation and instance segmentation results.