Automating Content Extraction of HTML Documents. Web pages often contain clutter (such as unnecessary images and extraneous links) around the body of an article that distracts a user from actual content. Extraction of "useful and relevant" content from web pages has many applications, including cell phone and PDA browsing, speech rendering for the visually impaired, and text summarization. Most approaches to making content more readable involve changing font size or removing HTML and data components such as images, which takes away from a webpage's inherent look and feel. Unlike "Content Reformatting," which aims to reproduce the entire webpage in a more convenient form, our solution directly addresses "Content Extraction." We have developed a framework that employs an easily extensible set of techniques. It incorporates advantages of previous work on content extraction. Our key insight is to work with DOM trees, a W3C specified interface that allows programs to dynamically access document structure, rather than with raw HTML markup. We have implemented our approach in a publicly available Web proxy to extract content from HTML web pages. This proxy can be used both centrally, administered for groups of users, as well as by individuals for personal browsers. We have also, after receiving feedback from users about the proxy, created a revised version with improved performance and accessibility in mind.

Question: How to extract content from HTML documents?


Transactional events. Concurrent programs require high-level abstractions in order to manage complexity and enable compositional reasoning. In this paper, we introduce a novel concurrency abstraction, dubbed transactional events, which combines first-class synchronous messagepassing events with all-or-nothing transactions. This combination enables simple solutions to interesting problems in concurrent programming. For example, guarded synchronous receive can be implemented as an abstract transactional event, whereas in other languages it requires a non-abstract, non-modular protocol. Likewise, three-way rendezvous can also be implemented as an abstract transactional event, which is impossible using first-class events alone. Both solutions are easy to code and easy to reason about.The expressive power of transactional events arises from a sequencing combinator whose semantics enforces an all-or-nothing transactional property - either both of the constituent events synchronize in sequence or neither of them synchronizes. This sequencing combinator, along with a non-deterministic choice combinator, gives transactional events the compositional structure of a monad-with-plus. We provide a formal semantics for and a preliminary implementation of transactional events.

Question: What is the difference between a monad and a monad with plus?


A Framework for Analysis of Road Accidents. The road accident data analysis use data mining and machine learning techniques, focusing on identifying factors that affect the severity of an accident. There are a variety of reasons that contribute to accidents. Some of them are internal to the driver but many are external. For example, adverse weather conditions like fog, rainfall or snowfall cause partial visibility and it may become difficult as well as risky to drive on such roads. It is expected that the findings from this paper would help civic authorities to take proactive actions on likely crash prone weather and traffic conditions.

Question: What is the weather conditions that cause road accidents?


Object based Information Extraction from High Resolution Satellite Imagery using eCognition. High resolution images offer rich contextual information, including spatial, spectral and contextual information. In order to extract the information from these high resolution images, we need to utilize the spatial and contextual information of an object and its surroundings. If pixel based approaches are applied to extract information from such remotely sensed data, only spectral information is used. Thereby, in Pixel based approaches, information extraction is based exclusively on the gray level thresholding methods. To extract the certain features only from high resolution satellite imagery, this situation becomes worse. To overcome this situation an object-oriented approach is implemented. This paper demonstrated the concept of objectoriented information extraction from high resolution satellite imagery using eCognition software, allows the classification of remotely-sensed data based on different object features, such as spatial, spectral, and contextual information. Thus with the object based approach, information is extracted on the basis of meaningful image objects rather than individual gray values of pixels. The test area has different discrimination, assigned to different classes by this approach: Agriculture, built-ups, forest and water. The Multiresolution segmentation and the nearest neighbour (NN) classification approaches are used and overall accuracy is assessed. The overall accuracy reaches to 97.30% thus making it an efficient and practical approach for information extraction.

Question: What is the object-oriented approach?


A Web Service Discovery Approach Based on Common Topic Groups Extraction. Web services have attracted much attention from distributed application designers and developers because of their roles in abstraction and interoperability among heterogeneous software systems, and a growing number of distributed software applications have been published as Web services on the Internet. Faced with the increasing numbers of Web services and service users, researchers in the services computing field have attempted to address a challenging issue, i.e., how to quickly find the suitable ones according to user queries. Many previous studies have been reported towards this direction. In this paper, a novel Web service discovery approach based on topic models is presented. The proposed approach mines common topic groups from the service-topic distribution matrix generated by topic modeling, and the extracted common topic groups can then be leveraged to match user queries to relevant Web services, so as to make a better trade-off between the accuracy of service discovery and the number of candidate Web services. Experiment results conducted on two publicly-available data sets demonstrate that, compared with several widely used approaches, the proposed approach can maintain the performance of service discovery at an elevated level by greatly decreasing the number of candidate Web services, thus leading to faster response time.

Question: What is a topic model?


An Extended Model of Cybercrime Investigations. A comprehensive model of cybercrime investigations is important for standardising terminology, defining requirements, and supporting the development of new techniques and tools for investigators. In this paper a model of investigations is presented which combines the existing models, generalises them, and extends them by explicitly addressing certain activities not included in them. Unlike previous models, this model explicitly represents the information flows in an investigation and captures the full scope of an investigation, rather than only the processing of evidence. The results of an evaluation of the model by practicing cybercrime investigators are presented. This new model is compared to some important existing models and applied to a real investigation.

Question: What is a model of cybercrime investigations?


SPARTan: Scalable PARAFAC2 for Large & Sparse Data. In exploratory tensor mining, a common problem is how to analyze a set of variables across a set of subjects whose observations do not align naturally. For example, when modeling medical features across a set of patients, the number and duration of treatments may vary widely in time, meaning there is no meaningful way to align their clinical records across time points for analysis purposes. To handle such data, the state-of-the-art tensor model is the so-called PARAFAC2, which yields interpretable and robust output and can naturally handle sparse data. However, its main limitation up to now has been the lack of efficient algorithms that can handle large-scale datasets.  In this work, we fill this gap by developing a scalable method to compute the PARAFAC2 decomposition of large and sparse datasets, called SPARTan. Our method exploits special structure within PARAFAC2, leading to a novel algorithmic reformulation that is both faster (in absolute time) and more memory-efficient than prior work. We evaluate SPARTan on both synthetic and real datasets, showing 22X performance gains over the best previous implementation and also handling larger problem instances for which the baseline fails. Furthermore, we are able to apply SPARTan to the mining of temporally-evolving phenotypes on data taken from real and medically complex pediatric patients. The clinical meaningfulness of the phenotypes identified in this process, as well as their temporal evolution over time for several patients, have been endorsed by clinical experts.

Question: What is the scalability of the spartan algorithm?


Physician Burnout and Well-Being: A Systematic Review and Framework for Action.. BACKGROUND Physician burnout in the United States has reached epidemic proportions and is rising rapidly, although burnout in other occupations is stable. Its negative impact is far reaching and includes harm to the burned-out physician, as well as patients, coworkers, family members, close friends, and healthcare organizations.   OBJECTIVE The purpose of this review is to provide an accurate, current summary of what is known about physician burnout and to develop a framework to reverse its current negative impact, decrease its prevalence, and implement effective organizational and personal interventions.   DATA SOURCES I completed a comprehensive MEDLINE search of the medical literature from January 1, 2000, through December 28, 2016, related to medical student and physician burnout, stress, depression, suicide ideation, suicide, resiliency, wellness, and well-being. In addition, I selectively reviewed secondary articles, books addressing the relevant issues, and oral presentations at national professional meetings since 2013.   STUDY SELECTION Healthcare organizations within the United States were studied.   RESULTS The literature review is presented in 5 sections covering the basics of defining and measuring burnout; its impact, incidence, and causes; and interventions and remediation strategies.   CONCLUSIONS All US medical students, physicians in training, and practicing physicians are at significant risk of burnout. Its prevalence now exceeds 50%. Burnout is the unintended net result of multiple, highly disruptive changes in society at large, the medical profession, and the healthcare system. Both individual and organizational strategies have been only partially successful in mitigating burnout and in developing resiliency and well-being among physicians. Two highly effective strategies are aligning personal and organizational values and enabling physicians to devote 20% of their

Question: What is the prevalence of burnout in the united states?


A COMPARISON OF ENTERPRISE ARCHITECTURE FRAMEWORKS. An Enterprise Architecture Framework (EAF) maps all of the software development processes within the enterprise and how they relate and interact to fulfill the enterprise's mission. It provides organizations with the ability to understand and analyze weaknesses or inconsistencies to be identified and addressed. There are a number of already established EAF in use today; some of these frameworks were developed for very specific areas, whereas others have broader functionality. This study provides a comparison of several frameworks that can then be used for guidance in the selection of an EAF that meets the needed criteria.

Question: What is an enterprise architecture framework?


Efficient Spectral Feature Selection with Minimum Redundancy. Spectral feature selection identifies relevant features by measuring their capability of preserving sample similarity. It provides a powerful framework for both supervised and unsupervised feature selection, and has been proven to be effective in many real-world applications. One common drawback associated with most existing spectral feature selection algorithms is that they evaluate features individually and cannot identify redundant features. Since redundant features can have significant adverse effect on learning performance, it is necessary to address this limitation for spectral feature selection. To this end, we propose a novel spectral feature selection algorithm to handle feature redundancy, adopting an embedded model. The algorithm is derived from a formulation based on a sparse multi-output regression with a L2;1-norm constraint. We conduct theoretical analysis on the properties of its optimal solutions, paving the way for designing an efficient path-following solver. Extensive experiments show that the proposed algorithm can do well in both selecting relevant features and removing redundancy.

Question: How to select relevant features?


Analyzing features for activity recognition. Human activity is one of the most important ingredients of context information. In wearable computing scenarios, activities such as walking, standing and sitting can be inferred from data provided by body-worn acceleration sensors. In such settings, most approaches use a single set of features, regardless of which activity to be recognized. In this paper we show that recognition rates can be improved by careful selection of individual features for each activity. We present a systematic analysis of features computed from a real-world data set and show how the choice of feature and the window length over which the feature is computed affects the recognition rates for different activities. Finally, we give a recommendation of suitable features and window lengths for a set of common activities.

Question: What is the best way to recognize activities?


Education 4.0 for tall thin engineer in a data driven society. The rise of digital technology creates disruptive innovation, new opportunities in communication, it transforms industrial production and it changes the way we work, learn and live. That leads to the fourth Industrial Revolution, which changes the working world enormously. New skills, future-ready curricula, new learning and training concepts as well as the flexibility in education are necessary. To deliver that, it needs a fourth revolution in the educational system with a strong active presence and most important Artificial Intelligence (AI) driven features for better performance. Education 4.0 needs also a strong partnership between industry and academicals environment in the formation of human resources for Industry 4.0. We present in this paper our answers of education regarding the challenges of fourth revolution in Industry and the seven AI driven didactic methods identified for the University of Future.

Question: What is the fourth industrial revolution?


Scap: stream-oriented network traffic capture and analysis for high-speed networks. Many network monitoring applications must analyze traffic beyond the network layer to allow for connection-oriented analysis, and achieve resilience to evasion attempts based on TCP segmentation. However, existing network traffic capture frameworks provide applications with just raw packets, and leave complex operations like flow tracking and TCP stream reassembly to application developers. This gap leads to increased application complexity, longer development time, and most importantly, reduced performance due to excessive data copies between the packet capture subsystem and the stream processing module. This paper presents the Stream capture library (Scap), a network monitoring framework built from the ground up for stream-oriented traffic processing. Based on a kernel module that directly handles flow tracking and TCP stream reassembly, Scap delivers to user-level applications flow-level statistics and reassembled streams by minimizing data movement operations and discarding uninteresting traffic at early stages, while it inherently supports parallel processing on multi-core architectures, and uses advanced capabilities of modern network cards. Our experimental evaluation shows that Scap can capture all streams for traffic rates two times higher than other stream reassembly libraries, and can process more than five times higher traffic loads when eight cores are used for parallel stream processing in a pattern matching application.

Question: What is a stream-oriented network traffic capture and analysis for high-speed networks?


Secondary confessions: the influence (or lack thereof) of incentive size and scientific expert testimony on jurors' perceptions of informant testimony.. The goal of this research was to determine whether the size of the incentive (none, small, medium, or large, in terms of sentence reduction) a jailhouse informant receives for testifying, as well as scientific expert testimony regarding the fundamental attribution error, would influence mock juror decision-making in a criminal trial involving a secondary confession. Participants read a murder trial transcript involving informant testimony in which incentive size and expert testimony were manipulated and then provided verdict judgments, made attributions for the informant's decision to testify, and rated the informant and expert on a number of dimensions. Neither expert testimony nor size of incentive had a direct influence on verdicts. However, contrary to previous research on the influence of incentives on jurors' perceptions of secondary confessions, the presence of an incentive did influence verdict decisions, informant ratings, and attributional responses. Results imply that jury-eligible community members may be becoming aware of the issues with informant testimony as a function of incentive but that they are insensitive to the size of the incentive, and expert testimony may not sensitize them to the limitations of such testimony.

Question: What is the influence of incentive size on jurors' perceptions of informant testimony?


Adaptive Linked Data-Driven Web Components: Building Flexible and Reusable Semantic Web Interfaces - Building Flexible and Reusable Semantic Web Interfaces. Due to the increasing amount of Linked Data openly published on the Web, user-facing Linked Data Applications (LDAs) are gaining momentum. One of the major entrance barriers for Web developers to contribute to this wave of LDAs is the required knowledge of Semantic Web (SW) technologies such as the RDF data model and SPARQL query language. This paper presents an adaptive componentbased approach together with its open source implementation for creating flexible and reusable SW interfaces driven by Linked Data. Linked Data-driven (LD-R) Web components abstract the complexity of the underlying SW technologies in order to allow reuse of existing Web components in LDAs, enabling Web developers who are not experts in SW to develop interfaces that view, edit and browse Linked Data. In addition to the modularity provided by the LD-R components, the proposed RDF-based configuration method allows application assemblers to reshape their user interface for different use cases, by either reusing existing shared configurations or by creating their proprietary configurations.

Question: What is the difference between a linked data interface and a linked data application?


Micro-Doppler effect in radar: phenomenon, model, and simulation study. When, in addition to the constant Doppler frequency shift induced by the bulk motion of a radar target, the target or any structure on the target undergoes micro-motion dynamics, such as mechanical vibrations or rotations, the micro-motion dynamics induce Doppler modulations on the returned signal, referred to as the micro-Doppler effect. We introduce the micro-Doppler phenomenon in radar, develop a model of Doppler modulations, derive formulas of micro-Doppler induced by targets with vibration, rotation, tumbling and coning motions, and verify them by simulation studies, analyze time-varying micro-Doppler features using high-resolution time-frequency transforms, and demonstrate the micro-Doppler effect observed in real radar data.

Question: What is the micro-Doppler effect?


Suicidal decapitation using a tractor loader: a case report and review of the literature.. In forensic practice, decapitated bodies are predominantly associated with decapitation by wheels of trains or with postmortem dismemberment following homicide. In the suicidal context, decapitation accounts for less than 1% of total suicide. Apart from decapitation by trains, other encountered methods involve suicidal hanging and vehicle-assisted ligature suicide. Reported here is a unique case of suicidal decapitation in a 45-year-old man using a tractor loader at the foot of a silo, on his farm. The head was recovered in the loader and there were several impact spots from the loader as well as blood on the silo wall. The autopsy revealed a complete decapitation wound with the severance plane located between the third and fourth cervical vertebra. A 1.5 cm wide abrasion on the anterior part of the neck and abrasions under the chin were noted. This very unique case of intentional suicidal decapitation is the first reported case of a planned system intended to create decapitation outside the unique case of homemade guillotine and the more common decapitation by train.

Question: What is the first reported case of suicidal decapitation?


A direct scattering model for tracking vehicles with high-resolution radars. In advanced driver assistance systems and autonomous driving, reliable environment perception and object tracking based on radar is fundamental. High-resolution radar sensors often provide multiple measurements per object. Since in this case traditional point tracking algorithms are not applicable any more, novel approaches for extended object tracking emerged in the last few years. However, they are primarily designed for lidar applications or omit the additional Doppler information of radars. Classical radar based tracking methods using the Doppler information are mostly designed for point tracking of parallel traffic. The measurement model presented in this paper is developed to track vehicles of approximately rectangular shape in arbitrary traffic scenarios including parallel and cross traffic. In addition to the kinematic state, it allows to determine and track the geometric state of the object. Using the Doppler information is an important component in the model. Furthermore, it neither requires measurement preprocessing, data clustering, nor explicit data association. For object tracking, a Rao-Blackwellized particle filter (RBPF) adapted to the measurement model is presented.

Question: What is the measurement model for tracking vehicles with high-resolution radars?


Second screen applications and tablet users: constellation, awareness, experience, and interest. This study investigates how tablet users incorporate multiple media in their television viewing experience. Three patterns are found: (a) only focusing on television, (b) confounding television viewing with other screen media (e.g. laptop, tablet) and (c) confounding television viewing with various media, including print and screen media. Furthermore, we question how the incorporation of screen media in this experience affects the practice of engaging in digital commentary on television content. Also, we inquire the uptake and interest in so-called 'second screen applications'. These applications allow extensions of the primary screen experience on secondary screens (e.g. tablet). The results, based on a sample of 260 tablet users, indicate that there is only a modest uptake and interest in using secondary screens to digitally share opinions. However, the use of second screen interaction with television content is not discarded: although there is still little awareness and experience, we notice a moderate interest in these apps.

Question: How does the incorporation of screen media in this experience affect the practice of engaging in digital commentary on television content?


3D People Tracking with Gaussian Process Dynamical Models. We advocate the use of Gaussian Process Dynamical Models (GPDMs) for learning human pose and motion priors for 3D people tracking. A GPDM provides a lowdimensional embedding of human motion data, with a density function that gives higher probability to poses and motions close to the training data. With Bayesian model averaging a GPDM can be learned from relatively small amounts of data, and it generalizes gracefully to motions outside the training set. Here we modify the GPDM to permit learning from motions with significant stylistic variation. The resulting priors are effective for tracking a range of human walking styles, despite weak and noisy image measurements and significant occlusions.

Question: What is a GPDM?


Towards Deep Neural Network Architectures Robust to Adversarial Examples. Recent work has shown deep neural networks (DNNs) to be highly susceptible to well-designed, small perturbations at the input layer, or so-called adversarial examples. Taking images as an example, such distortions are often imperceptible, but can result in 100% mis-classification for a state of the art DNN. We study the structure of adversarial examples and explore network topology, pre-processing and training strategies to improve the robustness of DNNs. We perform various experiments to assess the removability of adversarial examples by corrupting with additional noise and pre-processing with denoising autoencoders (DAEs). We find that DAEs can remove substantial amounts of the adversarial noise. However, when stacking the DAE with the original DNN, the resulting network can again be attacked by new adversarial examples with even smaller distortion. As a solution, we propose Deep Contractive Network, a model with a new end-to-end training procedure that includes a smoothness penalty inspired by the contractive autoencoder (CAE). This increases the network robustness to adversarial examples, without a significant performance penalty.

Question: What is the canadian military?


A Soft Robotic Orthosis for Wrist Rehabilitation 1. In the United States about 795,000 people suffer from a stroke each year [1]. Of those who survive the stroke, the majority experience paralysis on one side of their body, a condition known as hemiparesis. Physical therapy has been shown to restore functionality of the paretic limbs, especially when done early and often [2]. However, the effectiveness of therapy is limited by the availability of therapists and the amount of practice that patients do on their own. Robot-assisted therapy has been explored as a means of guiding patients through the time-intensive exercise regimes that most therapy techniques prescribe. Several wearable, robotic orthoses for the hand and wrist have been developed and are still being developed today [3]. However, few of these existing solutions allow for any significant range of motion, and those that do only offer one degree of freedom. The assisted degree of freedom is almost always flexion/extension, despite the fact that supination/ pronation is crucial in nearly all activities of daily living. In addition, current devices are often large, heavy, and uncomfortable for the wearer, presenting significant deterrents to practice. This paper presents a soft wearable device for the wrist that provides motion-specific assistance with rehabilitation for hemiparetic stroke patients at home. Unlike conventional robotassisted rehabilitation, this pneumatically actuated orthosis is portable, soft, and lightweight, making it more suitable for use outside of the clinic. In addition, this device supports all the degrees of freedom of the wrist, including supination and pronation, which are critical to many tasks.

Question: What is the difference between a soft robotic orthosis and a conventional robotic orthosis?


An Efficient Finger-Knuckle-Print Based Recognition System Fusing SIFT and SURF Matching Scores. This paper presents a novel combination of local-local information for an efficient finger-knuckle-print (FKP) based recognition system which is robust to scale and rotation. The non-uniform brightness of the FKP due to relatively curvature surface is corrected and texture is enhanced. The local features of the enhanced FKP are extracted using the scale invariant feature transform (SIFT) and the speeded up robust features (SURF). Corresponding features of the enrolled and the query FKPs are matched using nearest-neighbour-ratio method and then the derived SIFT and SURF matching scores are fused using weighted sum rule. The proposed system is evaluated using PolyU FKP database of 7920 images for both identification mode and verification mode. It is observed that the system performs with CRR of 100% and EER of 0.215%. Further, it is evaluated against various scales and rotations of the query image and is found to be robust for query images downscaled upto 60% and for any orientation of query image.

Question: What is the purpose of the paper?


Mining Online Reviews for Predicting Sales Performance: A Case Study in the Movie Domain. Posting reviews online has become an increasingly popular way for people to express opinions and sentiments toward the products bought or services received. Analyzing the large volume of online reviews available would produce useful actionable knowledge that could be of economic values to vendors and other interested parties. In this paper, we conduct a case study in the movie domain, and tackle the problem of mining reviews for predicting product sales performance. Our analysis shows that both the sentiments expressed in the reviews and the quality of the reviews have a significant impact on the future sales performance of products in question. For the sentiment factor, we propose Sentiment PLSA (S-PLSA), in which a review is considered as a document generated by a number of hidden sentiment factors, in order to capture the complex nature of sentiments. Training an S-PLSA model enables us to obtain a succinct summary of the sentiment information embedded in the reviews. Based on S-PLSFA, we propose ARSA, an Autoregressive Sentiment-Aware model for sales prediction. We then seek to further improve the accuracy of prediction by considering the quality factor, with a focus on predicting the quality of a review in the absence of user-supplied indicators, and present ARSQA, an Autoregressive Sentiment and Quality Aware model, to utilize sentiments and quality for predicting product sales performance. Extensive experiments conducted on a large movie data set confirm the effectiveness of the proposed approach.

Question: How to predict sales performance of a product?


Multi-style Generative Network for Real-Time Transfer. Despite the rapid progress in style transfer, existing approaches using feed-forward generative network for multistyle or arbitrary-style transfer are usually compromised of image quality and model flexibility. We find it is fundamentally difficult to achieve comprehensive style modeling using 1-dimensional style embedding. Motivated by this, we introduce CoMatch Layer that learns to match the second order feature statistics with the target styles. With the CoMatch Layer, we build a Multi-style Generative Network (MSGNet), which achieves real-time performance. In addition, we employ an specific strategy of upsampled convolution which avoids checkerboard artifacts caused by fractionallystrided convolution. Our method has achieved superior image quality comparing to state-of-the-art approaches. The proposed MSG-Net as a general approach for real-time style transfer is compatible with most existing techniques including content-style interpolation, color-preserving, spatial control and brush stroke size control. MSG-Net is the first to achieve real-time brush-size control in a purely feedforward manner for style transfer. Our implementations and pre-trained models for Torch, PyTorch and MXNet frameworks will be publicly available1.

Question: What is the first large-scale Canadian peacekeeping mission?


Mechanical Design and Modeling of an Omni-directional RoboCup Player. Abstract. This paper covers the mechanical design process of an omni-directional mobile robot developed for the Ohio University RoboCup team player. It covers each design iteration, detailing what we learned from each phase. In addition, the kinematics of the final design is derived, and its inverse Jacobian matrix for the design is presented. The dynamic equations of motion for the final design is derived in a symbolic form, assuming that no slip occurs on the wheel in the spin direction. Finally, a simulation example demonstrates simple independent PID wheel control for the complex coupled nonlinear dynamic system.

Question: How to design a robot?


Giving too much social support: social overload on social networking sites. Received: 20 July 2012 Revised: 18 February 2013 2nd Revision: 28 June 2013 3rd Revision: 20 September 2013 4th Revision: 7 November 2013 Accepted: 1 February 2014 Abstract As the number of messages and social relationships embedded in social networking sites (SNS) increases, the amount of social information demanding a reaction from individuals increases as well. We observe that, as a consequence, SNS users feel they are giving too much social support to other SNS users. Drawing on social support theory (SST), we call this negative association with SNS usage 'social overload' and develop a latent variable to measure it. We then identify the theoretical antecedents and consequences of social overload and evaluate the social overload model empirically using interviews with 12 and a survey of 571 Facebook users. The results show that extent of usage, number of friends, subjective social support norms, and type of relationship (online-only vs offline friends) are factors that directly contribute to social overload while age has only an indirect effect. The psychological and behavioral consequences of social overload include feelings of SNS exhaustion by users, low levels of user satisfaction, and a high intention to reduce or even stop using SNS. The resulting theoretical implications for SST and SNS acceptance research are discussed and practical implications for organizations, SNS providers, and SNS users are drawn. European Journal of Information Systems advance online publication, 4 March 2014; doi:10.1057/ejis.2014.3; corrected online 11 March 2014

Question: How much social support do you give to other people?


Information Systems Success: The Quest for the Dependent Variable. A large number of studies have been conducted during the last decade and a half attempting to identify those factors that contribute to information systems success. However, the dependent variable in these studies—I/S success —has been an elusive one to define. Different researchers have addressed different aspects of success, making comparisons difficult and the prospect of building a cumulative tradition for I/S research similarly elusive. To organize this diverse research, as well as to present a more integrated view of the concept of I/S success, a comprehensive taxonomy is introduced. This taxonomy posits six major dimensions or categories of I/S success—SYSTEM OUALITY, INFORMATION QUALITY, USE, USER SATISFACTION, INDIVIDUAL IMPACT, and ORGANIZATIONAL IMPACT. Using these dimensions, both conceptual and empirical studies are then reviewed (a total of 180 articles are cited) and organized according to the dimensions of the taxonomy. Finally, the many aspects of I/S success are drawn together into a descriptive model and its implications for future I/S research are discussed.

Question: What is the dependent variable in information systems research?


Internet addiction among Norwegian adults: a stratified probability sample study.. Most Norwegians are Internet users. We conducted a stratified probability sample study (Norway, 2007, age-group 16-74 years, N= 3,399, response rate 35.3%, 87.1% Internet users) to assess the prevalence of Internet addiction and at-risk Internet use by the Young Diagnostic Questionnaire (YDQ). The prevalence of Internet addiction (YDQ score 5-8) was 1.0% and an additional 5.2% were at-risk Internet users (YDQ score 3-4). Internet addiction and at-risk Internet use was strongly dependent on gender and age with highest prevalences among young males (16-29 years 4.1% and 19.0%, 30-39 years 3.3% and 10.7%). Logistic regression showed that male gender, young age, university level education, and an unsatisfactory financial situation were factors positively associated with "problematic Internet use" (at-risk and addicted use combined). Time spent on the Internet and prevalence of self-reported sleeping disorders, depression, and other psychological impairments increased linearly with YDQ score. Problematic Internet use clearly affects the lives of many people.

Question: What is the prevalence of internet addiction in Norway?


Training RNN simulated vehicle controllers using the SVD and evolutionary algorithms. We describe an approach to creating a controller for The Open Car Racing Simulator (TORCS), based on The Simulated Car Racing Championship (SCRC) client, using unsupervised evolutionary learning for recurrent neural networks. Our method of training the recurrent neural network controllers relies on combining the components of the singular value decomposition of two different neural network connection matrices.

Question: How to train a recurrent neural network?


An analysis of unreliability and asymmetry in low-power wireless links. Experimental studies have demonstrated that the behavior of real links in low-power wireless networks (such as wireless sensor networks) deviates to a large extent from the ideal binary model used in several simulation studies. In particular, there is a large transitional region in wireless link quality that is characterized by significant levels of unreliability and asymmetry, significantly impacting the performance of higher-layer protocols. We provide a comprehensive analysis of the root causes of unreliability and asymmetry. In particular, we derive expressions for the distribution, expectation, and variance of the packet reception rate as a function of distance, as well as for the location and extent of the transitional region. These expressions incorporate important environmental and radio parameters such as the path loss exponent and shadowing variance of the channel, and the modulation, encoding, and hardware variance of the radios.

Question: What is the distribution of the packet reception rate?


Linear codes over F2+uF2+vF2+uvF2. In this work, we investigate linear codes over the ring F2 + uF2 + vF2 + uvF2. We first analyze the structure of the ring and then define linear codes over this ring which turns out to be a ring that is not finite chain or principal ideal contrary to the rings that have hitherto been studied in coding theory. Lee weights and Gray maps for these codes are defined by extending on those introduced in works such as Betsumiya et al. (Discret Math 275:43–65, 2004) and Dougherty et al. (IEEE Trans Inf 45:32–45, 1999). We then characterize the F2 +uF2 +vF2 +uvF2-linearity of binary codes under the Gray map and give a main class of binary codes as an example of F2 + uF2 + vF2 + uvF2-linear codes. The duals and the complete weight enumerators for F2 + uF2 + vF2 + uvF2-linear codes are also defined after which MacWilliams-like identities for complete and Lee weight enumerators as well as for the ideal decompositions of linear codes over F2 + uF2 + vF2 + uvF2 are obtained.

Question: What is the ring F2 + uF2 + vF2 + uvF2?


Electromagnetic Two-Dimensional Scanner Using Radial Magnetic Field. In this paper, we present the design, fabrication, and measurement results of a two-dimensional electromagnetic scanning micromirror actuated by radial magnetic field. The scanner is realized by combining a gimbaled single-crystal-silicon micromirror with a single turn electroplated metal coil, with a concentric permanent magnet assembly composed of two concentric permanent magnets and an iron yoke. The proposed scanner utilizes the radial magnetic field rather than using a lateral magnetic field oriented 45deg to the horizontal and vertical scan axes to achieve a biaxial magnetic actuation. The single turn coil fabricated with electroplated copper achieves a nominal resistance of 1.2 Omega. A two-dimensional scanner with mirror size of 1.5 mm in diameter was fabricated. Maximum optical scan angle of 8.8deg in horizontal direction and 8.3deg in vertical direction were achieved. Forced actuation of the gimbal at 60 Hz and resonant actuation of the micromirror at 19.1-19.7 kHz provide slow vertical scan and fast horizontal scan, respectively. The proposed scanner can be used in raster scanning laser display systems and other scanner applications.

Question: What is the difference between a radial and a lateral magnetic field?


Cardiac arrhythmia detection from ECG combining convolutional and long short-term memory networks. Objectives: Atrial fibrillation (AF) is a common heart rhythm disorder associated with deadly and debilitating consequences including heart failure, stroke, poor mental health, reduced quality of life and death. Having an automatic system that diagnoses various types of cardiac arrhythmias would assist cardiologists to initiate appropriate preventive measures and to improve the analysis of cardiac disease. To this end, this paper introduces a new approach to detect and classify automatically cardiac arrhythmias in electrocardiograms (ECG) recordings. Methods: The proposed approach used a combination of Convolution Neural Networks (CNNs) and a sequence of Long Short-Term Memory (LSTM) units, with pooling, dropout and normalization techniques to improve their accuracy. The network predicted a classification at every 18th input sample and we selected the final prediction for classification. Results were cross-validated on the Physionet Challenge 2017 training dataset, which contains 8,528 single lead ECG recordings lasting from 9s to just over 60s. Results: Using the proposed structure and no explicit feature selection, 10-fold stratified cross-validation gave an overall F-measure of 0.83.10±0.015 on the held-out test data (mean ± standard deviation over all folds) and 0.80 on the hidden dataset of the Challenge entry server.

Question: How to detect cardiac arrhythmias from ECG?


Air-ground localization and map augmentation using monocular dense reconstruction. We propose a new method for the localization of a Micro Aerial Vehicle (MAV) with respect to a ground robot. We solve the problem of registering the 3D maps computed by the robots using different sensors: a dense 3D reconstruction from the MAV monocular camera is aligned with the map computed from the depth sensor on the ground robot. Once aligned, the dense reconstruction from the MAV is used to augment the map computed by the ground robot, by extending it with the information conveyed by the aerial views. The overall approach is novel, as it builds on recent developments in live dense reconstruction from moving cameras to address the problem of air-ground localization. The core of our contribution is constituted by a novel algorithm integrating dense reconstructions from monocular views, Monte Carlo localization, and an iterative pose refinement. In spite of the radically different vantage points from which the maps are acquired, the proposed method achieves high accuracy whereas appearance-based, state-of-the-art approaches fail. Experimental validation in indoor and outdoor scenarios reported an accuracy in position estimation of 0.08 meters and real time performance. This demonstrates that our new approach effectively overcomes the limitations imposed by the difference in sensors and vantage points that negatively affect previous techniques relying on matching visual features.

Question: How accurate is the localization of a micro aerial vehicle?


Adversarial Text Generation Without Reinforcement Learning. Generative Adversarial Networks (GANs) have experienced a recent surge in popularity, performing competitively in a variety of tasks, especially in computer vision. However, GAN training has shown limited success in natural language processing. This is largely because sequences of text are discrete, and thus gradients cannot propagate from the discriminator to the generator. Recent solutions use reinforcement learning to propagate approximate gradients to the generator, but this is inefficient to train. We propose to utilize an autoencoder to learn a low-dimensional representation of sentences. A GAN is then trained to generate its own vectors in this space, which decode to realistic utterances. We report both random and interpolated samples from the generator. Visualization of sentence vectors indicate our model correctly learns the latent space of the autoencoder. Both human ratings and BLEU scores show that our model generates realistic text against competitive baselines.

Question: How do adversarial networks work?


Learning Bayesian Belief Network Classifiers: Algorithms and System. This paper investigates the methods for learning Bayesian belief network (BN) based predictive models for classification. Our primary interests are in the unrestricted Bayesian network and Bayesian multi-net based classifiers. We present our algorithms for learning these classifiers and also the methods for fighting the overfitting problem. A natural method for feature subset selection is also studied. Using a set of standard classification problems, we empirically evaluate the performance of various BN based classifiers. The results show that the proposed BN and Bayes multi-net classifiers are competitive with (or superior to) the best known classifiers, based on both BN and other formalisms; and that the computational time for learning and using these classifiers is relatively small. We also briefly introduce our BN classifier learning system – BN PowerPredictor. We argue that BN based classifiers deserve more attention in the data mining community.

Question: What is a Bayesian belief network?


Designing for collaborative creative problem solving. Collaborative creativity is traditionally supported by formal techniques, such as brainstorming. These techniques improve the idea-generation process by creating group synergies, but also suffer from a number of negative effects. Current electronic tools to support collaborative creativity overcome some of these problems, but introduce new ones, by either losing the benefits of face-to-face communication or the immediacy of simultaneous contribution. Using an interactive environment as a test bed, we are investigating how collaborative creativity can be supported electronically while maintaining face-to-face communication. What are the design-factors influencing such a system? We have designed a brainstorming application that uses an interactive table and a large wall display, and compared the results of using it to traditional paper-based brainstorming in a user study with 30 participants. From the considerations that went into the design and the observations during the study we derive a number of design guidelines for collaborative systems in interactive environments.

Question: What are the design-factors influencing such a system?


Modeling Visual Attention via Selective Tuning. A model for aspects of visual attention based on the concept of selective tuning is presented. It provides for a solution to the problems of selection in an image, information routing through the visual processing hierarchy and task-specific attentional bias. The central thesis is that attention acts to optimize the search procedure inherent in a solution to vision. It does so by selectively tuning the visual processing network which is accomplished by a top-down hierarchy of winner-take-all processes embedded within the visual processing pyramid. Comparisons to other major computational models of attention and to the relevant neurobiology are included in detail throughout the paper. The model has been implemented; several examples of its performance are shown. This model is a hypothesis for primate visual attention, but it also outperforms existing computational solutions for attention in machine vision and is highly appropriate to solving the problem in a robot vision system.

Question: What is the model for aspects of visual attention based on the concept of selective tuning?


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

Question: What is the difference between polynomial time and polynomial space?


Design of High Performance Permanent-Magnet Synchronous Wind Generators. This paper is devoted to the analysis and design of high performance permanent-magnet synchronous wind generators (PSWGs). A systematic and sequential methodology for the design of PMSGs is proposed with a high performance wind generator as a design model. Aiming at high induced voltage, low harmonic distortion as well as high generator efficiency, optimal generator parameters such as pole-arc to pole-pitch ratio and stator-slot-shoes dimension, etc. are determined with the proposed technique using Maxwell 2-D, Matlab software and the Taguchi method. The proposed double three-phase and six-phase winding configurations, which consist of six windings in the stator, can provide evenly distributed current for versatile applications regarding the voltage and current demands for practical consideration. Specifically, windings are connected in series to increase the output voltage at low wind speed, and in parallel during high wind speed to generate electricity even when either one winding fails, thereby enhancing the reliability as well. A PMSG is designed and implemented based on the proposed method. When the simulation is performed with a 6 Ω load, the output power for the double three-phase winding and six-phase winding are correspondingly 10.64 and 11.13 kW. In addition, 24 Ω load experiments show that the efficiencies of double three-phase winding and six-phase winding are 96.56% and 98.54%, respectively, verifying the proposed high performance operation. OPEN ACCESS Energies 2014, 7 7106

Question: What is the design of high performance permanent-magnet synchronous wind generators?


An extended set of Haar-like features for rapid object detection. Recently Viola et al. [5] have introduced a rapid object detection scheme based on a boosted cascade of simple features. In this paper we introduce a novel set of rotated haar-like features, which significantly enrich this basic set of simple haar-like features and which can also be calculated very efficiently. At a given hit rate our sample face detector shows off on average a 10% lower false alarm rate by means of using these additional rotated features. We also present a novel post optimization procedure for a given boosted cascade improving on average the false alarm rate further by 12.5%. Using both enhancements the number of false detections is only 24 at a hit rate of 82.3% on the CMU face set [7].

Question: What is a haar-like feature?


DC Motor Drive with P, PI, and Particle Swarm Optimization Speed Controllers. This paper implements a Particle Swarm Optimization (PSO) speed controller for controlling the speed of DC motor. Also traditional Proportional (P), Proportional-Integral (PI) controller have been developed and simulated using MATLAB/SIMULINK. The simulation results indicate that the PI controller has big overshoot, sensitivity to controller gains. The optimization with particle swarm verified the reduction of oscillations as well as improve the steady state error, rise time and overshot in speed response. The simulation results confirmed the system is less sensitive to gain.

Question: How to control the speed of DC motor?


A public key cryptosystem and a signature scheme based on discrete logarithms. A new signature scheme is proposed, together with an implementation of the Diffie-Hellman key distribution scheme that achieves a public key cryptosystem. The security of both systems relies on the difficulty of computing discrete logarithms over finite fields.

Question: What is a signature scheme based on discrete logarithms?


A survey of point-based POMDP solvers. The past decade has seen a significant breakthrough in research on solving partially observable Markov decision processes (POMDPs). Where past solvers could not scale beyond perhaps a dozen states, modern solvers can handle complex domains with many thousands of states. This breakthrough was mainly due to the idea of restricting value function computations to a finite subset of the belief space, permitting only local value updates for this subset. This approach, known as point-based value iteration, avoids the exponential growth of the value function, and is thus applicable for domains with longer horizons, even with relatively large state spaces. Many extensions were suggested to this basic idea, focusing on various aspects of the algorithm—mainly the selection of the belief space subset, and the order of value function updates. In this survey, we walk the reader through the fundamentals of point-based value iteration, explaining the main concepts and ideas. Then, we survey the major extensions to the basic algorithm, discussing their merits. Finally, we include an extensive empirical analysis using well known benchmarks, in order to shed light on the strengths and limitations of the various approaches.

Question: What is a point-based POMDP solver?


Blind Source Separation in nonminimum-phase systems based on filter decomposition. This paper focuses on the causality problem in the task of Blind Source Separation (BSS) of speech signals in nonminimum-phase mixing channels. We propose a new algorithm for solving this problem using filter decomposition approach. Our proposed algorithm uses an integrated cost function in which independence criterion is defined in frequency-domain. The parameters of demixing system are derived in time-domain, so the algorithm has the benefits of both time and frequency-domain approaches. Compared to the previous work in this framework, our proposed algorithm is the extension of filter decomposition idea in multi-channel blind deconvolution to the problem of blind source separation of speech signals. The proposed method is capable of dealing with both minimum-phase and nonminimum-phase mixing situations. Simulation results show considerable improvement in separating speech signals specially when the mixing system is nonminimum-phase.

Question: How to separate speech signals in nonminimum-phase mixing channels?


The Beta Generalized Exponential Distribution. We introduce the beta generalized exponential distribution that includes the beta exponential and generalized exponential distributions as special cases. We provide a comprehensive mathematical treatment of this distribution. We derive the moment generating function and the rth moment thus generalizing some results in the literature. Expressions for the density, moment generating function and rth moment of the order statistics also are obtained. We discuss estimation of the parameters by maximum likelihood and provide the information matrix. We observe in one application to real data set that this model is quite flexible and can be used quite effectively in analyzing positive data in place of the beta exponential and generalized exponential distributions. keywords: Beta exponential distribution, Information matrix, Generalized exponential distribution, Maximum likelihood estimation.

Question: What is the beta generalized exponential distribution?


Low-power 4-2 and 5-2 compressors. This paper explores various low power higher order compressors such as 4-2 and 5-2 compressor units. These compressors are building blocks for binary multipliers. Various circuit architectures for 4-2 compressors are compared with respect to their delay and power consumption. The different circuits are simulated using HSPICE. A new circuit for a 5-2 compressor is then presented which is 12% faster and consumes 37% less power.

Question: What is a 4-2 compressor?


Gesture control of drone using a motion controller. In this study, we present our implementation of using a motion controller to control the motion of a drone via simple human gestures. We have used the Leap as the motion controller and the Parrot AR DRONE 2.0 for this implementation. The Parrot AR DRONE is an off the shelf quad rotor having an on board Wi-Fi system. The AR DRONE is connected to the ground station via Wi-Fi and the Leap is connected to the ground station via USB port. The LEAP Motion Controller recognizes the hand gestures and relays it on to the ground station. The ground station runs ROS (Robot Operating System) in Linux which is used as the platform for this implementation. Python is the programming language used for interaction with the AR DRONE in order to convey the simple hand gestures. In our implementation, we have written python codes to interpret the hand gestures captured by the LEAP, and transmit them in order to control the motion of the AR DRONE via these gestures.

Question: How to control a drone using gestures?


Notions of Video Game Addiction and Their Relation to Self-Reported Addiction Among Players of World of Warcraft. In this study, 438 players of the online video game, World of Warcraft, completed a survey about video game addiction and answered an open-ended question about behaviors they considered characteristic of video game addiction. Responses were coded and correlated with players' self-reports of being addicted to games and scores on a modified video game addiction scale. The behaviors most frequently mentioned as characteristic of addiction included playing a lot and games' interfering with other activities, especially socializing or work. Few players mentioned such signs of addiction as withdrawal symptoms or tolerance, and some thought it was not possible to become addicted to video games. Self-reported addiction to video games correlated positively with perceptions that video game addiction involved playing a lot or playing to escape problems, and correlated negatively with perceptions that addiction involved games' interfering with other activities or not being able to stop play. Implications for assessment are discussed.

Question: What are the most common signs of video game addiction?


The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations.. In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators.

Question: What is the difference between a moderator and a mediator?


Revisiting The American Voter on Twitter. The American Voter - a seminal work in political science - uncovered the multifaceted nature of voting behavior which has been corroborated in electoral research for decades since. In this paper, we leverage The American Voter as an analysis framework in the realm of computational political science, employing the factors of party, personality, and policy to structure the analysis of public discourse on online social media during the 2016 U.S. presidential primaries. Our analysis of 50 million tweets reveals the continuing importance of these three factors; our understanding is also enriched by the application of sentiment analysis techniques. The overwhelmingly negative sentiment of conversations surrounding 10 major presidential candidates reveals more "crosstalk" from Democratic leaning users towards Republican candidates, and less vice-versa. We uncover the lack of moderation as the most discussed personality dimension during this campaign season, as the political field becomes more extreme - Clinton and Rubio are perceived as moderate, while Trump, Sanders, and Cruz are not. While the most discussed issues are foreign policy and immigration, Republicans tweet more about abortion than Democrats who tweet more about gay rights than Republicans. Finally, we illustrate the importance of multifaceted political discourse analysis by applying regression to quantify the impact of party, personality, and policy on national polls.

Question: What is the most discussed issue on twitter during the 2016 presidential election?


Discriminative and consistent similarities in instance-level Multiple Instance Learning. In this paper we present a bottom-up method to instance-level Multiple Instance Learning (MIL) that learns to discover positive instances with globally constrained reasoning about local pairwise similarities. We discover positive instances by optimizing for a ranking such that positive (top rank) instances are highly and consistently similar to each other and dissimilar to negative instances. Our approach takes advantage of a discriminative notion of pairwise similarity coupled with a structural cue in the form of a consistency metric that measures the quality of each similarity. We learn a similarity function for every pair of instances in positive bags by how similarly they differ from instances in negative bags, the only certain labels in MIL. Our experiments demonstrate that our method consistently outperforms state-of-the-art MIL methods both at bag-level and instance-level predictions in standard benchmarks, image category recognition, and text categorization datasets.

Question: What is the discriminative notion of pairwise similarity coupled with a structural cue in the form of a consistency metric?


Reinforcement learning of clothing assistance with a dual-arm robot. This study aims at robotic clothing assistance as it is yet an open field for robotics despite it is one of the basic and important assistance activities in daily life of elderly as well as disabled people. The clothing assistance is a challenging problem since robots must interact with non-rigid clothes generally represented in a high-dimensional space, and with the assisted person whose posture can vary during the assistance. Thus, the robot is required to manage two difficulties to perform the task of the clothing assistance: 1) handling of non-rigid materials and 2) adaptation of the assisting movements to the assisted person's posture. To overcome these difficulties, we propose to use reinforcement learning with the cloth's state which is low-dimensionally represented in topology coordinates, and with the reward defined in the low-dimensional coordinates. With our developed experimental system, for T-shirt clothing assistance, including an anthropomorphic dual-arm robot and a soft mannequin, we demonstrate the robot quickly learns a suitable arm motion for putting the mannequin's head into a T-shirt.

Question: How does reinforcement learning work?


Energy-Efficient Multiple-Precision Floating-Point Multiplier for Embedded Applications. Floating-point (FP) multipliers are the main energy consumers in many modern embedded digital signal processing (DSP) and multimedia systems. For lossy applications, minimizing the precision of FP multiplication operations under the acceptable accuracy loss is a well-known approach for reducing the energy consumption of FP multipliers. This paper proposes a multiple-precision FP multiplier to efficiently trade the energy consumption with the output quality. The proposed FP multiplier can perform lowprecision multiplication that generates 8−, 14−, 20−, or 26bit mantissa product through an iterative and truncated modified Booth multiplier. Energy saving for lowprecision multiplication is achieved by partially suppressing the computation of mantissa multiplier. In addition, the proposed multiplier allows the bitwidth of mantissa in the multiplicand, multiplier, and output product to be dynamically changed when it performs different FP multiplication operations to further reduce energy consumption. Experimental results show that the proposed multiplier can achieve 59 %, 71 %, 73 %, and 82 % energy saving under 0.1 %, 1 %, 5 %, and 11 % accuracy loss, respectively, for the RGB-to-YUV & YUV-to-RGB conversion when compared to the conventional IEEE single-precision multiplier. In addition, the results also exhibit that the proposed multiplier can obtain more energy reduction than previous multipleprecision iterative FP multipliers.

Question: What is the energy consumption of a floating point multiplier?


Open Information Extraction with Meta-pattern Discovery in Biomedical Literature. Biomedical open information extraction (BioOpenIE) is a novel paradigm to automatically extract structured information from unstructured text with no or little supervision. It does not require any pre-specified relation types but aims to extract all the relation tuples from the corpus. A major challenge for open information extraction (OpenIE) is that it produces massive surface-name formed relation tuples that cannot be directly used for downstream applications. We propose a novel framework CPIE (Clause+Pattern-guided Information Extraction) that incorporates clause extraction and meta-pattern discovery to extract structured relation tuples with little supervision. Compared with previous OpenIE methods, CPIE produces massive but more structured output that can be directly used for downstream applications. We first detect short clauses from input sentences. Then we extract quality textual patterns and perform synonymous pattern grouping to identify relation types. Last, we obtain the corresponding relation tuples by matching each quality pattern in the text. Experiments show that CPIE achieves the highest precision in comparison with state-of-the-art OpenIE baselines, and also keeps the distinctiveness and simplicity of the extracted relation tuples. CPIE shows great potential in effectively dealing with real-world biomedical literature with complicated sentence structures and rich information.

Question: What is the difference between open information extraction and clause extraction?


A 0.3 GHz to 1.4 GHz N-path mixer-based code-domain RX with TX self-interference rejection. A code-domain N-path RX is proposed based on PN-code modulated LO pulses for concurrent reception of two code-modulated signals. Additionally, a combination of Walsh-Function and PN sequence is proposed to translate in-band TX self-interference (SI) to out-of-band at N-path RX output enabling frequency filtering for high SI rejection. A 0.3 GHz–1.4 GHz 65-nm CMOS implementation has 35 dB gain for desired signals and concurrently receives two RX signals while rejecting mismatched spreading codes at RF input. Proposed TX SI mitigation approach results in 38.5 dB rejection for −11.8dBm 1.46 Mb/s QPSK modulated SI at RX input. The RX achieves 23.7dBm OP1dB for in-band SI, while consuming ∼35mW and occupies 0.31mm2.

Question: What is a code-domain N-path mixer-based RX?


Identification of extract method refactoring opportunities for the decomposition of methods. The extraction of a code fragment into a separate method is one of the most widely performed refactoring activities, since it allows the decomposition of large and complex methods and can be used in combination with other code transformations for fixing a variety of design problems. Despite the significance of Extract Method refactoring towards code quality improvement, there is limited support for the identification of code fragments with distinct functionality that could be extracted into new methods. The goal of our approach is to automatically identify Extract Method refactoring opportunities which are related with the complete computation of a given variable (complete computation slice) and the statements affecting the state of a given object (object state slice). Moreover, a set of rules regarding the preservation of existing odule decomposition dependences is proposed that exclude refactoring opportunities corresponding to slices whose extraction could possibly cause a change in program behavior. The proposed approach has been evaluated regarding its ability to capture slices of code implementing a distinct functionality, its ability to resolve existing design flaws, its impact on the cohesion of the decomposed and extracted methods, and its ability to preserve program behavior. Moreover, precision and recall have been computed employing the refactoring depe opportunities found by in

Question: How to extract a method from a method?


Taming the beast: Free and open-source massive point cloud web visualization. Powered by WebGL, some renderers have recently become available for the visualization of point cloud data over the web, for example Plasio or Potree. We have extended Potree to be able to visualize massive point clouds and we have successfully used it with the second national Lidar survey of the Netherlands, AHN2, with 640 billion points. In addition to the visualization, the publicly available service at http://ahn2.pointclouds.nl/ also features a multi-resolution download tool, a geographic name search bar, a measurement toolkit, a 2D orientation map with field of view depiction, a demo mode and the tuning of the visualization parameters. Potree relies on reorganizing the point cloud data into an multi-resolution octree data structure. However, this reorganization is very time consuming for massive data sets. Hence, we have used a divide and conquer approach to decrease the octree creation time. To achieve such performance improvement we divided the entire space into smaller cells, generated an octree for each of them in a distributed manner and then we merged them into a single massive octree. The merging is possible because the extent of all the nodes of the octrees is known and fixed. All the developed tools are free and open-source (FOSS) and they can be used to visualize over the web other massive point clouds.

Question: How to tame the beast?


Design & construction of a Vertical Axis Wind Turbine. A wind turbine is a device that converts kinetic energy from the wind into electrical power. Vertical Axis Wind Turbine (VAWT) is one type of wind turbine where the main rotor shaft is set vertically and it can capture wind from any direction. The aim of this work is to develop a theoretical model for the design and performance of Darrieus type vertical axis wind turbine for small scale energy applications. A small 3 bladed turbine (prototype) is constructed and investigated the performance for low wind velocity. The model is based on NACA 0018 airfoil & light wood is used as blade material. The full scale Vertical Axis Wind Turbine is made for 36 inch height, 24 inch diameter, blade cord length is 3.937 inch & blade height is 24 inch. A 100 watt 24 volt brushless DC motor is used to measure output power. The whirling speed of blade & electric power output for the corresponding speed is measured through Tachometer & Wattmeter. The power curves show the relation between the rotational wind speed of the turbine and the power produced for a range of wind speeds. This approach indicates to develop vertical axis wind turbine with better performance to meet the increasing power demand.

Question: What is the vertical axis wind turbine?


Production and structural elucidation of exopolysaccharide from endophytic Pestalotiopsis sp. BC55.. There is a little information on exopolysaccharide production by endophytic fungi. In this investigation endophytic Pestalotiopsis sp. BC55 was used for optimization of exopolysaccharide production. One variable at a time method and response surface methodology were adopted to find out the best culture conditions and medium compositions for maximum exopolysaccharide production. The organism produced maximum exopolysaccharide (4.320 ± 0.022 g/l EPS) in 250 ml Erlenmeyer flask containing 75 ml potato dextrose broth supplemented with (g%/l) glucose, 7.66; urea, 0.29; CaCl2, 0.05 with medium pH 6.93; after 3.76 days of incubation at 24°C. Exopolysaccharide [EPS (EP-I)] produced by this organism have Mw ∼2×10(5)Da with a melting point range of 122-124°C. Structural elucidation of the EPS (PS-I) was carried out after a series of experiments. Result indicated the presence of only (1→3)-linked β-d-glucopyranosyl moiety. The structure of the repeating unit was established as - →3)-β-d-Glcp-(1→.

Question: What is the structure of exopolysaccharide produced by endophytic fungus?


Beyond blacklists: learning to detect malicious web sites from suspicious URLs. Malicious Web sites are a cornerstone of Internet criminal activities. As a result, there has been broad interest in developing systems to prevent the end user from visiting such sites. In this paper, we describe an approach to this problem based on automated URL classification, using statistical methods to discover the tell-tale lexical and host-based properties of malicious Web site URLs. These methods are able to learn highly predictive models by extracting and automatically analyzing tens of thousands of features potentially indicative of suspicious URLs. The resulting classifiers obtain 95-99% accuracy, detecting large numbers of malicious Web sites from their URLs, with only modest false positives.

Question: What is the tell-tale lexical and host-based properties of malicious web sites?


NailTactors: eyes-free spatial output using a nail-mounted tactor array. This paper investigates the feasibility of using a nail-mounted array of tactors, NailTactors, as an eyes-free output device. By rim-attached eccentric-rotating-mass (ERM) vibrators to artificial nails, miniature high-resolution tactile displays were realized as an eyes-free output device. To understand how to deliver rich signals to users for valid signal perception, three user studies were conducted. The results suggest that users can not only recognized absolute and relative directional cues, but also recognized numerical characters in EdgeWrite format with an overall 89% recognition rate. Experiments also identified the optimal placement of ERM actuators for maximizing information transfer.

Question: How to deliver rich signals to users for valid signal perception?


Synchromesh Torque Estimation in an Electric Vehicle's Clutchless Automated Manual Transmission Using Unknown Input Observer. This paper studies the estimation of the frictional torque of the synchromesh during the gear shifting operation in an electric vehicle equipped with a clutchless automated manual transmission (AMT). The clutchless drivetrain of the electric vehicle is discussed and the dynamical model of the powertrain from the electric traction motor to the synchromesh system of a two-speed AMT is developed. In order to estimate the frictional torque of the synchromesh, which is indeed an unknown input to the dynamical system, it is assumed to be generated by a fictitious autonomous system. Thereafter, the augmented state- space representation of the actual and fictitious state variables, which forms the basis for the observer design, is provided and the observability of this augmented system is discussed. A deterministic Luenberger observer and a stochastic Kalman-Bucy filter are designed in order to estimate the frictional torque of the synchromesh. The estimation is based on the measuring angular velocities of the electric motor and synchro ring together with the known electromagnetic torque of the traction motor. The performance of the observers is assessed experimentally by means of a test rig. The results demonstrate the satisfactory performance of the stochastic observer when the system encounters process and measurement noise which are likely to happen in practice.

Question: How to estimate the frictional torque of the synchromesh?


SHORTEST PATHS FOR THE REEDS-SHEPP CAR : A WORKED OUT EXAMPLE OF THE USE OF GEOMETRIC TECHNIQUES IN NONLINEAR OPTIMAL CONTROL. We illustrate the use of the techniques of modern geometric optimal control theory by studying the shortest paths for a model of a car that can move forwards and backwards. This problem was discussed in recent work by Reeds and Shepp who showed, by special methods, (a) that shortest path motion could always be achieved by means of trajectories of a special kind, namely, concatenations of at most five pieces, each of which is either a straight line or a circle, and (b) that these concatenations can be classified into 48 three-parameter families. We show how these results fit in a much more general framework, and can be discovered and proved by applying in a systematic way the techniques of Optimal Control Theory. It turns out that the "classical" optimal control tools developed in the 1960's, such as the Pontryagin Maximum Principle and theorems on the existence of optimal trajectories, are helpful to go part of the way and get some information on the shortest paths, but do not suffice to get the full result. On the other hand, when these classical techniques are combined with the use of a more recently developed body of theory, namely, geometric methods based on the Lie algebraic analysis of trajectories, then one can recover the full power of the Reeds-Shepp results, and in fact slightly improve upon them by lowering their 48 to a 46.

Question: What is the shortest path for a car?


Counterfactual Fairness. Machine learning can impact people with legal or ethical consequences when it is used to automate decisions in areas such as insurance, lending, hiring, and predictive policing. In many of these scenarios, previous decisions have been made that are unfairly biased against certain subpopulations, for example those of a particular race, gender, or sexual orientation. Since this past data may be biased, machine learning predictors must account for this to avoid perpetuating or creating discriminatory practices. In this paper, we develop a framework for modeling fairness using tools from causal inference. Our definition of counterfactual fairness captures the intuition that a decision is fair towards an individual if it the same in (a) the actual world and (b) a counterfactual world where the individual belonged to a different demographic group. We demonstrate our framework on a real-world problem of fair prediction of success in law school.

Question: What is a counterfactual world?


Contactless vital signs measurement for self-service healthcare kiosk in intelligent building. Contactless healthcare system is becoming a new trend to solve the existing healthcare system limitations. High flexibility and accessibility are the main advantages of contactless measurements. In this paper, we proposed a contactless healthcare kiosk for intelligent building application. The Remote Imaging Photoplethysmography (rIPPG) based framework to measure multiple human's vital signs, including pulse rate (PR), respiratory rate (RR), and systolic blood pressure (SBP) was developed to fulfill the performance requirement with a personal computer. Our experimental results show the Mean Absolute Error (MAE) of each measured parameters are 1.7 BPM, 0.41 BPM and 8.15 mmHg for PR, RR, and SBP respectively compared with clinical apparatus. These statistical numbers show the feasibility of using the contactless based system to measure numerous vital signs and also meet the requirements of standard healthcare device.

Question: How to measure multiple vital signs?


Parameterized Models for Facial Animation. Parameterized models can produce realistic, manipulable images of human faces— with a surprisingly small number of parameters.

Question: What is a parameterized model?


Sliding spotlight SAR processing for TerraSAR-X using a new formulation of the extended chirp scaling algorithm. This paper describes the sliding spotlight algorithm and the processing strategy to be applied for TerraSAR-X. The steering spotlight geometry is analysed. Analysis of scene size and resolution demonstrates the particularities of this mode. The Doppler frequencies for individual targets and for a whole sliding spotlight scene are analyzed and the result shows the applicability of azimuth subaperture processing to sliding spotlight data. A description of the Extended Chirp Scaling Algorithm for sliding spotlight is presented.

Question: What is the sliding spotlight SAR processing?


Teaching cryptography with open-source software. Cryptography has become an important topic in undergraduate curricula in mathematics and computer science, not just for its intrinsic interest---``about the most fun you can have with mathematics''\cite{ferg04, but for its current standing as the basis for almost all computer security. From wireless networking to secure email to password protection, cryptographic methods are used to secure information, to protect users, and to protect data.  At Victoria University, cryptography has been taught as part of a mathematics and computer science degree for several years. The students all have had at least a year of tertiary mathematics, and some exposure to a computer algebra system (Maple). However, the cost of Maple, and the current licensing agreement, means that students are unable to experiment with the software away from the computer laboratories at the University. For this reason we have decided to investigate the use of open-source computer algebra systems Maxima and Axiom. Although not as full-featured and powerful as the commercial systems Maple and Mathematica, we show they are in fact admirably suited for a subject such as cryptography. In some ways Maxima and Axiom even surpass Maple and Mathematica. Student response to the introduction of these systems has been very positive.

Question: What is cryptography?


Prader-Willi syndrome: a review of clinical, genetic, and endocrine findings. INTRODUCTION Prader-Willi syndrome (PWS) is a multisystemic complex genetic disorder caused by lack of expression of genes on the paternally inherited chromosome 15q11.2-q13 region. There are three main genetic subtypes in PWS: paternal 15q11-q13 deletion (65-75 % of cases), maternal uniparental disomy 15 (20-30 % of cases), and imprinting defect (1-3 %). DNA methylation analysis is the only technique that will diagnose PWS in all three molecular genetic classes and differentiate PWS from Angelman syndrome. Clinical manifestations change with age with hypotonia and a poor suck resulting in failure to thrive during infancy. As the individual ages, other features such as short stature, food seeking with excessive weight gain, developmental delay, cognitive disability and behavioral problems become evident. The phenotype is likely due to hypothalamic dysfunction, which is responsible for hyperphagia, temperature instability, high pain threshold, hypersomnia and multiple endocrine abnormalities including growth hormone and thyroid-stimulating hormone deficiencies, hypogonadism and central adrenal insufficiency. Obesity and its complications are the major causes of morbidity and mortality in PWS.   METHODS An extensive review of the literature was performed and interpreted within the context of clinical practice and frequently asked questions from referring physicians and families to include the current status of the cause and diagnosis of the clinical, genetics and endocrine findings in PWS.   CONCLUSIONS Updated information regarding the early diagnosis and management of individuals with Prader-Willi syndrome is important for all physicians and will be helpful in anticipating and managing or modifying complications associated with this rare obesity-related disorder.

Question: What is the cause of Prader-Willi syndrome?


Medicinal strategies in the treatment of obesity. When prevention fails, medicinal treatment of obesity may become a necessity. Any strategic medicinal development must recognize that obesity is a chronic, stigmatized and costly disease that is increasing in prevalence. Because obesity can rarely be cured, treatment strategies are effective only as long as they are used, and combined therapy may be more effective than monotherapy. For a drug to have significant impact on body weight it must ultimately reduce energy intake, increase energy expenditure, or both. Currently approved drugs for long-term treatment of obesity include sibutramine, which inhibits food intake, and orlistat, which blocks fat digestion.

Question: What is the difference between medicinal strategies in the treatment of obesity?


Periodically Controlled Hybrid Systems Verifying A Controller for An Autonomous Vehicle. This paper introduces Periodically Controlled Hybrid Automata (PCHA) for describing a class of hybrid control systems. In a PCHA, control actions occur roughly periodically while internal and input actions, may occur in the interim changing the discrete-state or the setpoint. Based on periodicity and subtangential conditions, a new sufficient condition for verifying invariance of PCHAs is presented. This technique is used in verifying safety of the planner-controller subsystem of an autonomous ground vehicle, and in deriving geometric properties of planner generated paths that can be followed safely by the controller under environmental uncertainties.

Question: How to verify the safety of a controller for an autonomous vehicle?


Evolutionary algorithm in Forex trade strategy generation. This paper shows an evolutionary algorithm application to generate profitable strategies to trade futures contracts on foreign exchange market (Forex). Strategy model in approach is based on two decision trees, responsible for taking the decisions of opening long or short positions on Euro/US Dollar currency pair. Trees take into consideration only technical analysis indicators, which are connected by logic operators to identify border values of these indicators for taking profitable decision(s). We have tested the efficiency of presented approach on learning and test time-frames of various characteristics.

Question: What is an evolutionary algorithm?


Orthogonal least squares methods and their application to non-linear system identification. This article maybe used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. Identification algorithms based on the well-known linear least squares methods of gaussian elimination, Cholesky decomposition, classical Gram-Schmidt, modified Gram-Schmidt, Householder transformation, Givens method, and singular value decomposition are reviewed. The classical Gram-Schmidt, modified Gram-Schmidt,and Householder transformation algorithms are then extended to combine structure determination, or which terms to include in the model, and parameter estimation in a very simple and efficient manner for a class of multivariable discrete-time non-linear stochastic systems which are linear in the parameters.

Question: What is the difference between the classical Gram-Schmidt, modified Gram-Schmidt, and Householder transformation algorithms?


General 3D modelling of novel objects from a single view. In this paper we present a method for building models for grasping from a single 3D snapshot of a scene composed of objects of daily use in human living environments. We employ fast shape estimation, probabilistic model fitting and verification methods capable of dealing with different kinds of symmetries, and combine these with a triangular mesh of the parts that have no other representation to model previously unseen objects of arbitrary shape. Our approach is enhanced by the information given by the geometric clues about different parts of objects which serve as prior information for the selection of the appropriate reconstruction method. While we designed our system for grasping based on single view 3D data, its generality allows us to also use the combination of multiple views. We present two application scenarios that require complete geometric models: grasp planning and locating objects in camera images.

Question: How to build a 3D model from a single view?


Design and analysis of a hybrid energy harvester for self-powered sensor. This paper presents a slightly different concept of energy harvesting method as compared to the conventional energy harvesters. The new energy harvester of interest is known as Hybrid Energy Harvester (HEH). It comprises of the Piezoelectric and Magnetostrictive/Electromagnetic transducers integrated into a system. Theoretically, the hybrid energy harvester device developed is targeted to expand the vibration bandwidth as compared to the standalone energy harvesters, hence higher output power will be generated. To develop the hybrid energy harvester, mathematical models of each respective transducers are formulated, then simulations are carried out using the MATLAB/Simulink analysis tool. Next, a macro-scale prototype device is designed, fabricated and validated. From the experimental characterizations, it is unveiled that the maximum open circuit output voltage produced by the hybrid energy harvester is 6.23 V at a resonant frequency of 59.6 Hz.

Question: What is a hybrid energy harvester?


Vehicle Guidance for an Autonomous Vehicle. This paper describes the vehicle guidance system of an autonomous vehicle. This system is part of the control structure of the vehicle and consists of a path generator, a motion planning algorithm and a sensor fusion module. A stereo vision sensor and a DGPS sensor are used as position sensors. The trajectory for the vehicle motion is generated in a rst step by using only information from a digital map. Object-detecting sensors such as the stereo vision sensor, three laserscanner and a radar sensor observe the vehicle environment and report detected objects to the sensor fusion module. This information is used to dynamically update the planned vehicle trajectory to the nal vehicle motion.

Question: What is a vehicle guidance system?


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

Question: What is the name of the robot?


Review: Graph Databases. This paper covers NOSQL databases. With the increase in net users and applications it is important to understand graph databases, the future of tomorrow's data storage and management. Basic architecture of some graph databases has been discussed to know their working and how data is stored in the form of nodes and relationships. KeywordsNOSQL databases, Neo4j, JENA, DEX, InfoGrid, FlockDB.

Question: What is the future of data storage and management?


Reflection Removal Using Low-Rank Matrix Completion. The images taken through glass often capture a target transmitted scene as well as undesired reflected scenes. In this paper, we propose a low-rank matrix completion algorithm to remove reflection artifacts automatically from multiple glass images taken at slightly different camera locations. We assume that the transmitted scenes are more dominant than the reflected scenes in typical glass images. We first warp the multiple glass images to a reference image, where the gradients are consistent in the transmission images while the gradients are varying across the reflection images. Based on this observation, we compute a gradient reliability such that the pixels belonging to the salient edges of the transmission image are assigned high reliability. Then we suppress the gradients of the reflection images and recover the gradients of the transmission images only, by solving a low-rank matrix completion problem in gradient domain. We reconstruct an original transmission image using the resulting optimal gradient map. Experimental results show that the proposed algorithm removes the reflection artifacts from glass images faithfully and outperforms the existing algorithms on typical glass images.

Question: How to remove reflection artifacts from glass images?


ToneTrack: Leveraging Frequency-Agile Radios for Time-Based Indoor Wireless Localization. Indoor localization of mobile devices and tags has received much attention recently, with encouraging fine-grained localization results available with enough line-of-sight coverage and hardware infrastructure. Some of the most promising techniques analyze the time-of-arrival of incoming signals, but the limited bandwidth available to most wireless transmissions fundamentally constrains their resolution. Frequency-agile wireless networks utilize bandwidths of varying sizes and locations in a wireless band to efficiently share the wireless medium between users. ToneTrack is an indoor location system that achieves sub-meter accuracy with minimal hardware and antennas, by leveraging frequency-agile wireless networks to increase the effective bandwidth. Our novel signal combination algorithm combines time-of-arrival data from different transmissions as a mobile device hops across different channels, approaching time resolutions previously not possible with a single narrowband channel. ToneTrack's novel channel combination and spectrum identification algorithms together with the triangle inequality scheme yield superior results even in non-line-of-sight scenarios with one to two walls separating client and APs and also in the case where the direct path from mobile client to an AP is completely blocked. We implement ToneTrack on the WARP hardware radio platform and use six of them served as APs to localize Wi-Fi clients in an indoor testbed over one floor of an office building. Experimental results show that ToneTrack can achieve a median 90 cm accuracy when 20 MHz bandwidth APs overhear three packets from adjacent channels.

Question: How does tone track work?


Caring for a child with autism spectrum disorder and parents' quality of life: application of the CarerQol.. This study describes the impact of caregiving on parents of children with autism spectrum disorders (ASDs). Secondly, we investigate construct validation of the care-related quality of life instrument (CarerQol) measuring impact of caregiving. Primary caregivers of children with ASDs were included. Many parents experienced considerable problems combining daily activities with care, had financial problems or suffered from depressive mood. Validity tests showed that a higher impact of caring on the CarerQol was positively associated with higher subjective burden and lower family quality of life. Most of the associations between CarerQol scores and background characteristics confirmed previous research. The CarerQol validly measures the impact of caregiving for children with ASDs on caregivers in our sample. The CarerQol may therefore be useful for including parent outcomes in research on ASDs.

Question: What is the impact of caring for a child with autism spectrum disorder on parents?


Simple and strong : Twisted silver painted nylon artificial muscle actuated by Joule heating. Highly oriented nylon and polyethylene fibres shrink in length when heated and expand in diameter. By twisting and then coiling monofilaments of these materials to form helical springs, the anisotropic thermal expansion has recently been shown to enable tensile actuation of up to 49% upon heating. Joule heating, by passing a current through a conductive coating on the surface of the filament, is a convenient method of controlling actuation. In previously reported work this has been done using highly flexible carbon nanotube sheets or commercially available silver coated fibres. In this work silver paint is used as the Joule heating element at the surface of the muscle. Up to 29% linear actuation is observed with energy and power densities reaching 840 kJ m (528 J kg) and 1.1 kW kg (operating at 0.1 Hz, 4% strain, 1.4 kg load). This simple coating method is readily accessible and can be applied to any polymer filament. Effective use of this technique relies on uniform coating to avoid temperature gradients.

Question: How does this work?


Emotion recognition in human-computer interaction. In this paper, we outline the approach we have developed to construct an emotion-recognising system. It is based on guidance from psychological studies of emotion, as well as from the nature of emotion in its interaction with attention. A neural network architecture is constructed to be able to handle the fusion of different modalities (facial features, prosody and lexical content in speech). Results from the network are given and their implications discussed, as are implications for future direction for the research.

Question: What is the approach to emotion recognition in human-computer interaction?