The social role of social media: the case of Chennai rains-2015. Social media has altered the way individuals communicate in present scenario. Individuals feel more connected on Facebook and Twitter with greater communication freedom to chat, share pictures, and videos. Hence, social media is widely employed by various companies to promote their product and services and establish better customer relationships. Owing to the increasing popularity of these social media platforms, their usage is also expanding significantly. Various studies have discussed the importance of social media in the corporate world for effective marketing communication, customer relationships, and firm performance, but no studies have focused on the social role of social media, i.e., in disaster resilience in India. Various academicians and practitioners have advocated the importance and use of social media in disaster resilience. This article focuses on the role that social media can play during the time of natural disasters, with the help of the recent case of Chennai floods in India. This study provides a better understanding about the role social media can play in natural disaster resilience in Indian context.

Question: What is the role of social media in disaster resilience?


Electrostatic adhesive brakes for high spatial resolution refreshable 2.5D tactile shape displays. We investigate the mechanism, design, modeling and fabrication of a scalable high resolution, low cost and lightweight refreshable 2.5D tactile pin array controlled by electrostatic adhesive brakes. By replacing linear actuators in motorized shape displays with a high voltage solid-state circuit that can be fabricated with printable electronics techniques, we can decrease the cost and complexity of such devices. Electrostatic adhesive brakes, made by patterning interdigital electrodes on high dielectric constant thin films, are used to hold metal pins' positions and provide contact force to the user's fingertip. We present designs of two high resolution brake modules which are 1.7 mm pitch with 0.8 mm width pins and 4 mm pitch with 1.58 mm width pins with a maximum measured dynamic loading force of 76.3 gf and static loading force of 28 gf on an individual pin (for the later size). A small demonstration of 4 × 2 pin array with a 4 mm pitch size within a row and 2.5 mm pitch size between the rows, using 1.58 mm width pins, was created. We also characterized the refresh time to be 37.5 ms for each brake, which enables refreshable actuated pin displays.

Question: What is the refresh time of a refreshable pin display?


The New Algorithms of Weighted Association Rules based on Apriori and FP-Growth Methods. In order to improve the frequent itemsets generated layer-wise efficiency, the paper uses the Apriori property to reduce the search space. FP-grow algorithm for mining frequent pattern steps mainly is divided into two steps: FP-tree and FP-tree to construct a recursive mining. Algorithm FP-Growth is to avoid the high cost of candidate itemsets generation, fewer, more efficient scanning. The paper puts forward the new algorithms of weighted association rules based on Apriori and FP-Growth methods. In the same support, this method is the most effective and stable maximum frequent itemsets mining capacity and minimum execution time. Through theoretical analysis and experimental simulation of the performance of the algorithm is discussed, it is proved that the algorithm is feasible and effective.

Question: What is the new algorithms of weighted association rules based on Apriori and FP-Growth methods?


Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks. Recognizing arbitrary multi-character text in unconstrained natural photographs is a hard problem. In this paper, we address an equally hard sub-problem in this domain viz. recognizing arbitrary multi-digit numbers from Street View imagery. Traditional approaches to solve this problem typically separate out the localization, segmentation, and recognition steps. In this paper we propose a unified approach that integrates these three steps via the use of a deep convolutional neural network that operates directly on the image pixels. We employ the DistBelief (Dean et al., 2012) implementation of deep neural networks in order to train large, distributed neural networks on high quality images. We find that the performance of this approach increases with the depth of the convolutional network, with the best performance occurring in the deepest architecture we trained, with eleven hidden layers. We evaluate this approach on the publicly available SVHN dataset and achieve over 96% accuracy in recognizing complete street numbers. We show that on a per-digit recognition task, we improve upon the state-of-the-art and achieve 97.84% accuracy. We also evaluate this approach on an even more challenging dataset generated from Street View imagery containing several tens of millions of street number annotations and achieve over 90% accuracy. Our evaluations further indicate that at specific operating thresholds, the performance of the proposed system is comparable to that of human operators. To date, our system has helped us extract close to 100 million physical street numbers from Street View imagery worldwide.

Question: What is the best way to recognize multi-digit numbers from street view imagery?


Quality Traits of "Cannabidiol Oils": Cannabinoids Content, Terpene Fingerprint and Oxidation Stability of European Commercially Available Preparations. Cannabidiol (CBD)-based oil preparations are becoming extremely popular, as CBD has been shown to have beneficial effects on human health. CBD-based oil preparations are not unambiguously regulated under the European legislation, as CBD is not considered as a controlled substance. This means that companies can produce and distribute CBD products derived from non-psychoactive hemp varieties, providing an easy access to this extremely advantageous cannabinoid. This leaves consumers with no legal quality guarantees. The objective of this project was to assess the quality of 14 CBD oils commercially available in European countries. An in-depth chemical profiling of cannabinoids, terpenes and oxidation products was conducted by means of GC-MS and HPLC-Q-Exactive-Orbitrap-MS in order to improve knowledge regarding the characteristics of CBD oils. Nine out of the 14 samples studied had concentrations that differed notably from the declared amount, while the remaining five preserved CBD within optimal limits. Our results highlighted a wide variability in cannabinoids profile that justifies the need for strict and standardized regulations. In addition, the terpenes fingerprint may serve as an indicator of the quality of hemp varieties, while the lipid oxidation products profile could contribute in evaluation of the stability of the oil used as milieu for CBD rich extracts.

Question: What is the difference between CBD and THC?


The digital platform: a research agenda. As digital platforms are transforming almost every industry today, they are slowly finding their way into the mainstream information systems (IS) literature. Digital platforms are a challenging research object because of their distributed nature and intertwinement with institutions, markets and technologies. New research challenges arise as a result of the exponentially growing scale of platform innovation, the increasing complexity of platform architectures, and the spread of digital platforms to many different industries. This paper develops a research agenda for digital platforms research in IS. We recommend researchers seek to (1) advance conceptual clarity by providing clear definitions that specify the unit of analysis, degree of digitality and the sociotechnical nature of digital platforms; (2) define the proper scoping of digital platform concepts by studying platforms on different architectural levels and in different industry settings; and (3) advance methodological rigour by employing embedded case studies, longitudinal studies, design research, data-driven modelling and visualization techniques. Considering current developments in the business domain, we suggest six questions for further research: (1) Are platforms here to stay?; (2) How should platforms be designed?; (3) How do digital platforms transform industries?; (4) How can data-driven approaches inform digital platforms research?; (5) How should researchers develop theory for digital platforms?; and (6) How do digital platforms affect everyday life?

Question: What is a digital platform?


Friend or Foe: Cyberbullying in Social Network Sites. As the use of social media technologies proliferates in organizations, it is important to understand the nefarious behaviors, such as cyberbullying, that may accompany such technology use and how to discourage these behaviors. We draw from neutralization theory and the criminological theory of general deterrence to develop and empirically test a research model to explain why cyberbullying may occur and how the behavior may be discouraged. We created a research model of three second-order formative constructs to examine their predictive influence on intentions to cyberbully. We used PLS- SEM to analyze the responses of 174 Facebook users in two different cyberbullying scenarios. Our model suggests that neutralization techniques enable cyberbullying behavior and while sanction certainty is an important deterrent, sanction severity appears ineffective. We discuss the theoretical and practical implications of our model and results.

Question: What is cyberbullying?


Cascaded Attention based Unsupervised Information Distillation for Compressive Summarization. When people recall and digest what they have read for writing summaries, the important content is more likely to attract their attention. Inspired by this observation, we propose a cascaded attention based unsupervised model to estimate the salience information from the text for compressive multi-document summarization. The attention weights are learned automatically by an unsupervised data reconstruction framework which can capture the sentence salience. By adding sparsity constraints on the number of output vectors, we can generate condensed information which can be treated as word salience. Fine-grained and coarse-grained sentence compression strategies are incorporated to produce compressive summaries. Experiments on some benchmark data sets show that our framework achieves better results than the state-of-the-art methods.

Question: What is the cascaded attention based unsupervised model?


AI-Assisted Game Debugging with Cicero. We present Cicero, a mixed-initiative application for prototyping two-dimensional sprite-based games across different genres such as shooters, puzzles, and action games. Cicero provides a host of features which can offer assistance in different stages of the game development process. Noteworthy features include AI agents for gameplay simulation, a game mechanics recommender system, a playtrace aggregator, heatmap-based game analysis, a sequential replay mechanism, and a query system that allows searching for particular interaction patterns. In order to evaluate the efficacy and usefulness of the different features of Cicero, we conducted a user study in which we compared how users perform in game debugging tasks with different kinds of assistance.

Question: What is the name of the game?


Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning. Very deep convolutional networks have been central to the largest advances in image recognition performance in recent years. One example is the Inception architecture that has been shown to achieve very good performance at relatively low computational cost. Recently, the introduction of residual connections in conjunction with a more traditional architecture has yielded state-of-the-art performance in the 2015 ILSVRC challenge; its performance was similar to the latest generation Inception-v3 network. This raises the question of whether there are any benefit in combining the Inception architecture with residual connections. Here we give clear empirical evidence that training with residual connections accelerates the training of Inception networks significantly. There is also some evidence of residual Inception networks outperforming similarly expensive Inception networks without residual connections by a thin margin. We also present several new streamlined architectures for both residual and non-residual Inception networks. These variations improve the single-frame recognition performance on the ILSVRC 2012 classification task significantly. We further demonstrate how proper activation scaling stabilizes the training of very wide residual Inception networks. With an ensemble of three residual and one Inception-v4, we achieve 3.08% top-5 error on the test set of the ImageNet classification (CLS) challenge.

Question: What is the impact of residual connections on learning?


Airway management and smoke inhalation injury in the burn patient.. Smoke inhalation injury, a unique form of acute lung injury, greatly increases the occurrence of postburn morbidity and mortality. In addition to early intubation for upper-airway protection, subsequent critical care of patients who have this injury should be directed at maintaining distal airway patency. High-frequency ventilation, inhaled heparin, and aggressive pulmonary toilet are among the therapies available. Even so, immunosuppression, intubation, and airway damage predispose these patients to pneumonia and other complications.

Question: What is the treatment for smoke inhalation injury?


A theory of biological pattern formation. One of the elementary processes in morphogenesis is the formation of a spatial pattern of tissue structures, starting from almost homogeneous tissue. It will be shown that relatively simple molecular mechanisms based on auto- and cross catalysis can account for a primary pattern of morphogens to determine pattern formation of the tissue. The theory is based on short range activation, long range inhibition, and a distinction between activator and inhibitor concentrations on one hand, and the densities of their sources on the other. While source density is expected to change slowly, e.g. as an effect of cell differentiation, the concentration of activators and inhibitors can change rapidly to establish the primary pattern; this results from auto- and cross catalytic effects on the sources, spreading by diffusion or other mechanisms, and degradation. Employing an approximative equation, a criterium is derived for models, which lead to a striking pattern, starting from an even distribution of morphogens, and assuming a shallow source gradient. The polarity of the pattern depends on the direction of the source gradient, but can be rather independent of other features of source distribution. Models are proposed which explain size regulation (constant proportion of the parts of the pattern irrespective of total size). Depending on the choice of constants, aperiodic patterns, implying a one-to-one correlation between morphogen concentration and position in the tissue, or nearly periodic patterns can be obtained. The theory can be applied not only to multicellular tissues, but also to intracellular differentiation, e.g. of polar cells. The theory permits various molecular interpretations. One of the simplest models involves bimolecular activation and monomolecular inhibition. Source gradients may be substituted by, or added to, sink gradients, e.g. of degrading enzymes. Inhibitors can be substituted by substances required for, and de

Question: What is the difference between aperiodic and periodic patterns?


A Lightweight Semantic Web-based Approach for Data Annotation on IoT Gateways. Internet of Things (IoT) applications rely on networks composed of set of heterogeneous sensors and smart devices, which have the capability to constantly, observe the surroundings and gather data. This heterogeneity is reflected on raw data gathered by such type of systems. Consequently, the task of high-level IoT applications to interpret such data and detect events in the real world is more complex. Moreover, data heterogeneity leads to the lack of interoperability between IoT applications. Semantic Web (SW) technologies have been widely adopted to model and integrate data from different sources on the web; extending them to the IoT domain can be used to mitigate the aforementioned challenges. Semantically annotating IoT data is a fundamental step toward developing smarter and interoperable IoT applications. However, this type of process requires a large amount of computing resources, especially in scenarios where a large number of sensors is expected to be involved such as smart city. To address these challenges, we propose a lightweight semantic annotation approach that can be implemented on resource-constrained IoT gateways connected to a limited number of sensors. To evaluate the feasibility of the proposed approach, we have carried out a set of experimentations using a middleware prototype implementation. Several benchmarks are considered such as: Data size, response time, and resource utilization. c © 2017 The Authors. Published by Elsevier B.V. .

Question: What is the size of the data?


Expressing emotion through posture and gesture Introduction. Introduction Emotion and its physical expression are an integral part of social interaction, informing others about how we are feeling and affecting social outcomes (Vosk, Forehand, and Figueroa 1983). Studies on the physical expression of emotion can be traced back to the 19th century with Darwin's seminal book "The Expression of the Emotions in Man and Animals" that reveals the key role of facial expressions and body movement in communicating status and emotion (Darwin 1872).

Question: What is the role of facial expressions in social interaction?


Happiness Economics , Eudaimonia and Positive Psychology : From Happiness Economics to Flourishing Economics. A remarkable current development, happiness economics focuses on the relevance of people's happiness in economic analyses. As this theory has been criticised for relying on an incomplete notion of happiness, this paper intends to support it with richer philosophical and psychological foundations. Specifically, it suggests that happiness economics should be based on Aristotle's philosophical eudaimonia concept and on a modified version of 'positive psychology' that stresses human beings' relational nature. First, this analysis describes happiness economics and its shortcomings. Next, it introduces Aristotle's eudaimonia and takes a look at positive psychology with this lens, elaborating on the need to develop a new approach that goes beyond the economics of happiness: the economics of flourishing. Finally, the paper specifies some possible socio-economic objectives of a eudaimonic economics of happiness.

Question: What is the difference between happiness economics and flourishing economics?


Tooth structure removal associated with various preparation designs for anterior teeth.. STATEMENT OF PROBLEM The conservation of sound tooth structure helps preserve tooth vitality and reduce postoperative sensitivity. Innovative preparation designs, like those for porcelain laminate veneers, are much less invasive than conventional complete-coverage crown preparations. However, no study has quantified the amount of tooth structure removed during these preparations.   PURPOSE The purpose of this study was to quantify and compare the amount of tooth structure removed when various innovative and conventional tooth preparation designs were completed on different teeth.   MATERIAL AND METHOD . A new comprehensive tooth preparation design classification system was introduced. Typodont resin teeth representing the maxillary left central incisor, maxillary left canine, and mandibular left central incisor were prepared with the following designs: partial (V1), traditional (V2), extended (V3), and complete (V4) porcelain laminate veneer preparations; resin-bonded retainer preparation with grooves (A1) and with wing/grooves (A2); all-ceramic crown preparation with 0.8 mm axial reduction and tapering chamfer finish line (F1), all-ceramic crown preparation with 1.0 mm axial reduction and rounded shoulder finish line (F2), and metal-ceramic crown with 1.4 mm axial reduction and facial shoulder finish line (F3). After tooth preparations (10 per group), the crown was separated from the root at the CEJ. The removed coronal tooth structure was measured with gravimetric analysis. Means and standard deviations for tooth structure removal with different preparation designs were calculated and analyzed with analysis of variance at a significance level of P<.05.   RESULTS Significant differences in the amount of tooth structure removal were noted between preparation designs. Ceramic veneers and resin-bonded prosthesis retainers were the least invasive preparation designs, removing appro

Question: What is the difference between a porcelain laminate veneer and a resin-bonded prosthesis?


A Digital Input Controller for Audio Class-D Amplifiers with 100W 0.004% THD+N and 113dB DR. A digital input controller for audio class-D amplifiers is presented. The controller utilizes specially configured integrated DAC and power stage feedback loop to suppress distortion components coming from power-stage switching with digital input capability. The class-D amplifier system with the controller and an existing power stage achieves 113dB DR, 0.0018% THD+N with 10W output power, and 0.004% THD+N with 100W output power into 4Omega load

Question: What is a digital input controller for audio class-D amplifiers?


Being overweight has limited effect on SCARF osteotomy outcome for hallux valgus correction. The purpose of this study was to investigate the association between body mass index (BMI) and the results of SCARF osteotomy of the first metatarsal for hallux valgus (HV) correction, as the literature on this is scant. This prospective study was carried out between 2011 and 2015. One hundred and thirty-three patients diagnosed with moderate to severe HV underwent a SCARF corrective osteotomy. We divided the patients into two groups according to their BMI: normal and overweight. Postoperative follow-up was two years. All patients were examined twice by two medical doctors simultaneously: pre-operatively and post-operatively at two years' follow-up. Data collected included biometrical records, X-rays [HV angle (HVA), intermetatarsal angle (IMA), American Orthopaedic Foot and Ankle Society Hallux Metatarsophalangeal Index (AOFAS-HMI) and visual analogue scale (VAS) for pain and satisfaction]. There was a significant difference between patient age (p = 0.001), age at onset (p < 0.001) and AOFAS-HMI (p = 0.035) at follow-up. Other parameters were similar in both groups. Regardless of BMI, the radiological outcome was comparable. Despite a significant difference in AOFAS-HMI results, pain and satisfaction level were similar. The authors agreed that high BMI has protective role in the prevalence of HV.

Question: What is the effect of BMI on the outcome of SCARF osteotomy for hallux valgus correction?


JM: An R Package for the Joint Modelling of Longitudinal and Time-to-Event Data. In longitudinal studies measurements are often collected on different types of outcomes for each subject. These may include several longitudinally measured responses (such as blood values relevant to the medical condition under study) and the time at which an event of particular interest occurs (e.g., death, development of a disease or dropout from the study). These outcomes are often separately analyzed; however, in many instances, a joint modeling approach is either required or may produce a better insight into the mechanisms that underlie the phenomenon under study. In this paper we present the R package JM that fits joint models for longitudinal and time-to-event data.

Question: What is a joint model?


Design and optimization of thermo-mechanical reliability in wafer level packaging. Article history: Received 4 July 2009 Received in revised form 16 November 2009 Available online 29 January 2010 0026-2714/$ see front matter 2009 Elsevier Ltd. A doi:10.1016/j.microrel.2009.11.010 * Corresponding author. Address: Department of M University, P.O. Box 10028, Beaumont, TX 77710, USA +1 409 880 8121. E-mail address: xuejun.fan@lamar.edu (X.J. Fan). In this paper, a variety of wafer level packaging (WLP) structures, including both fan-in and fan-out WLPs, are investigated for solder joint thermo-mechanical reliability performance, from a structural design point of view. The effects of redistribution layer (RDL), bump structural design/material selection, polymer-cored ball application, and PCB design/material selection are studied. The investigation focuses on four different WLP technologies: standard WLP (ball on I/O WLP), ball on polymer WLP without under bump metallurgy (UBM) layer, ball on polymer WLP with UBM layer, and encapsulated copper post WLP. Ball on I/O WLP, in which solder balls are directly attached to the metal pads on silicon wafer, is used as a benchmark for the analysis. 3-D finite element modeling is performed to investigate the effects of WLP structures, UBM layer, polymer film material properties (in ball on polymer WLP), and encapsulated epoxy material properties (in copper post WLP). Both ball on polymer and copper post WLPs have shown great reliability improvement in thermal cycling. For ball on polymer WLP structures, polymer film between silicon and solder balls creates a 'cushion' effect to reduce the stresses in solder joints. Such cushion effect can be achieved either by an extremely compliant film or a 'hard' film with a large coefficient of thermal expansion. Encapsulated copper post WLP shows the best thermo-mechanical performance among the four WLP structures. Furthermore, for a fan-out WLP, it has been found that the critical solder ball

Question: What is the difference between a fan-in and fan-out WLP?


Learning Context for Text Categorization. This paper describes our work which is based on discovering context for text document categorization. The document categorization approach is derived from a combination of a learning paradigm known as relation extraction and an technique known as context discovery. We demonstrate the effectiveness of our categorization approach using reuters 21578 dataset and synthetic real world data from sports domain. Our experimental results indicate that the learned context greatly improves the categorization performance as compared to traditional categorization approaches.

Question: What is the context discovery technique?


How Data Breaches Ruin Firm Reputation on Social Media! - Insights from a Sentiment-based Event Study. Data breach events are heavily discussed in social media. Data breaches, which imply the loss of personal sensitive data, have negative consequences on the affected firms such as loss of market value, loss of customers and reputational damage. In the digital era, wherein ensuring information security is extremely demanding and the dissemination of information occurs at a very high speed, protecting corporate reputation has become a challenging task. While several studies have provided empirical evidence of the financial consequences of data breaches, little attention has been dedicated to the link between data breaches and reputational risk. To address this research gap, we have measured the reputational effect of data breaches based on social media content by applying a novel approach, the sentiment-based event study. The empirical results provide strong evidence that data breach events deteriorate the reputation of companies involved in such incidents.

Question: How does a data breach affect a firm's reputation?


Roombots—Towards decentralized reconfiguration with self-reconfiguring modular robotic metamodules. This paper presents our work towards a decentralized reconfiguration strategy for self-reconfiguring modular robots, assembling furniture-like structures from Roombots (RB) metamodules. We explore how reconfiguration by locomotion from a configuration A to a configuration B can be controlled in a distributed fashion. This is done using Roombots metamodules—two Roombots modules connected serially—that use broadcast signals, lookup tables of their movement space, assumptions about their neighborhood, and connections to a structured surface to collectively build desired structures without the need of a centralized planner.

Question: How can a robot build a house?


Coupled semi-supervised learning for information extraction. We consider the problem of semi-supervised learning to extract categories (e.g., academic fields, athletes) and relations (e.g., PlaysSport(athlete, sport)) from web pages, starting with a handful of labeled training examples of each category or relation, plus hundreds of millions of unlabeled web documents. Semi-supervised training using only a few labeled examples is typically unreliable because the learning task is underconstrained. This paper pursues the thesis that much greater accuracy can be achieved by further constraining the learning task, by coupling the semi-supervised training of many extractors for different categories and relations. We characterize several ways in which the training of category and relation extractors can be coupled, and present experimental results demonstrating significantly improved accuracy as a result.

Question: What is semi-supervised learning?


Seed priming to alleviate salinity stress in germinating seeds.. Salinity is one of the major abiotic stresses that affect crop production in arid and semiarid areas. Seed germination and seedling growth are the stages most sensitive to salinity. Salt stress causes adverse physiological and biochemical changes in germinating seeds. It can affect the seed germination and stand establishment through osmotic stress, ion-specific effects and oxidative stress. The salinity delays or prevents the seed germination through various factors, such as a reduction in water availability, changes in the mobilization of stored reserves and affecting the structural organization of proteins. Various techniques can improve emergence and stand establishment under salt conditions. One of the most frequently utilized is seed priming. The process of seed priming involves prior exposure to an abiotic stress, making a seed more resistant to future exposure. Seed priming stimulates the pre-germination metabolic processes and makes the seed ready for radicle protrusion. It increases the antioxidant system activity and the repair of membranes. These changes promote seed vigor during germination and emergence under salinity stress. The aim of this paper is to review the recent literature on the response of plants to seed priming under salinity stress. The mechanism of the effect of salinity on seed germination is discussed and the seed priming process is summarized. Physiological, biochemical and molecular changes induced by priming that lead to seed enhancement are covered. Plants' responses to some priming agents under salinity stress are reported based on the best available data. For a great number of crops, little information exists and further research is needed.

Question: What is the mechanism of the effect of salinity on seed germination?


Classification of benign and malignant tumors in histopathology images. Breast cancer leads the list of cancer that act on women worldwide. It starts when cells in the breast begin to build up beyond control. These cells normally create a tumour that can usually be seen on an x-ray or felt as a lump. Analysing and grading the tumour will take up much of a pathologist time. Pathologists have been largely diagnosing disease the same way for the past years, by manually reviewing images under a microscope. Thus, to help the pathologists improve accuracy and significantly change the way breast cancer been diagnosed, this paper presents an automated classification program. BreakHis dataset was used which build of 7909 breast tumor images gathered from 82 patients. This system is developed in order to categorize the cancer cells into two classes of cancer which are benign and malignant. The classification system compared different types of feature extractors using k-nearest neighbours classifier to efficiently observe the performance of the classification system. An extensive set of experiments showed that the overall accuracy rates range from 83% to 86%.

Question: What is the classification of benign and malignant tumors in histopathology images?


Ring-Light Photometric Stereo. We propose a novel algorithm for uncalibrated photometric stereo. While most of previous methods rely on various assumptions on scene properties, we exploit constraints in lighting configurations. We first derive an ambiguous reconstruction by requiring lights to lie on a view centered cone. This reconstruction is upgraded to Euclidean by constraints derived from lights of equal intensity and multiple view geometry. Compared to previous methods, our algorithm deals with more general data and achieves high accuracy. Another advantage of our method is that we can model weak perspective effects of lighting, while previous methods often assume orthographical illumination. We use both synthetic and real data to evaluate our algorithm. We further build a hardware prototype to demonstrate our approach.

Question: How to build a ring-light photometric stereo system?


Sliding mode control strategy for three-phase DVR employing twelve-switch voltage source converter. In this study, a new method is proposed for the suppression of voltage amplitude fluctuations on the load terminals. Moreover, the voltage harmonics on the load terminals are effectively reduced below the defined limits in the IEEE-519 standard. In the studied topology, a twelve-switch three-phase voltage source converter is used for effective control on the zero-sequence components due to the unbalanced voltages or single phase voltage sags. In order to obtain a fast dynamic response, sliding mode control strategy is used to control the system. The existence condition of the sliding mode is presented. The performance of the closed-loop system is verified with cases of voltage sag and utility voltage harmonics. The overall system is explained in detail and verified by using MATLAB/Simulink.

Question: How to suppress voltage amplitude fluctuations on the load terminals?


Design and Evaluation of Visual Interpenetration Cues in Virtual Grasping. We present design and impact studies of visual feedback for virtual grasping. The studies suggest new or updated guidelines for feedback. Recent grasping techniques incorporate visual cues to help resolve undesirable visual or performance artifacts encountered after real fingers enter a virtual object. Prior guidelines about such visuals are based largely on other interaction types and provide inconsistent and potentially-misleading information when applied to grasping. We address this with a two-stage study. In the first stage, users adjusted parameters of various feedback types, including some novel aspects, to identify promising settings and to give insight into preferences regarding the parameters. In the next stage, the tuned feedback techniques were evaluated in terms of objective performance (finger penetration, release time, and precision) and subjective rankings (visual quality, perceived behavior impact, and overall preference). Additionally, subjects commented on the techniques while reviewing them in a final session. Performance wise, the most promising techniques directly reveal penetrating hand configuration in some way. Subjectively, subjects appreciated visual cues about interpenetration or grasp force, and color changes are most promising. The results enable selection of the best cues based on understanding the relevant tradeoffs and reasonable parameter values. The results also provide a needed basis for more focused studies of specific visual cues and for choosing conditions in comparisons to other feedback modes, such as haptic, audio, or multimodal. Considering results, we propose that 3D interaction guidelines must be updated to capture the importance of interpenetration cues, possible performance benefits of direct representations, and tradeoffs involved in cue selection.

Question: What is the difference between a virtual and a real object?


Collaboratively crowdsourcing workflows with turkomatic. Preparing complex jobs for crowdsourcing marketplaces requires careful attention to workflow design, the process of decomposing jobs into multiple tasks, which are solved by multiple workers. Can the crowd help design such workflows? This paper presents Turkomatic, a tool that recruits crowd workers to aid requesters in planning and solving complex jobs. While workers decompose and solve tasks, requesters can view the status of worker-designed workflows in real time; intervene to change tasks and solutions; and request new solutions to subtasks from the crowd. These features lower the threshold for crowd employers to request complex work. During two evaluations, we found that allowing the crowd to plan without requester supervision is partially successful, but that requester intervention during workflow planning and execution improves quality substantially. We argue that Turkomatic's collaborative approach can be more successful than the conventional workflow design process and discuss implications for the design of collaborative crowd planning systems.

Question: How can we design a crowdsourcing system that allows requesters to intervene during workflow planning and execution?


Algorithmic motion planning in robotics. A survey is presented of an approach to motion planning that emphasizes object-oriented, exact, and discrete (or combinatorial) algorithmic techniques in which worst-case asymptotically efficient solutions are being sought. Following a statement of the problem, motion planning in static and known environments is treated. The discussion covers general solutions, lower bounds, the projection method, the retraction method, the expanded obstacles, the single-component approach, and a mobile convex object moving in a 2D polygonal space. Variants of the motion-planning problem are then considered, namely, optimal motion planning, adaptive and exploratory motion planning, motion planning in the presence of moving obstacles, constrained motion planning, motion planning with uncertainty, and general task planning.<<ETX>>

Question: What is the difference between the projection and retraction methods?


The obstacle-restriction method for robot obstacle avoidance in difficult environments. This paper addresses the obstacle avoidance problem in difficult scenarios that usually are dense, complex and cluttered. The proposal is a method called the obstacle-restriction. At each iteration of the control cycle, this method addresses the obstacle avoidance in two steps. First there is procedure to compute instantaneous subgoals in the obstacle structure (obtained by the sensors). The second step associates a motion restriction to each obstacle, which are managed next to compute the most promising motion direction. The advantage of this technique is that it avoids common limitations of previous obstacle avoidance methods, improving their navigation performance in difficult scenarios. Furthermore, we obtain similar results to the recent methods that achieve navigation in troublesome scenarios. However, the new method improves their behavior in open spaces. The performance of this method is illustrated with experimental results obtained with a robotic wheelchair vehicle.

Question: What is the obstacle-restriction method for robot obstacle avoidance in difficult environments?


Algorithms for the Assignment and Transiortation Troblems*. In this paper we presen algorithms for the solution of the general assignment and transportation problems. In Section 1, a statement of the algorithm for the assignment problem appears, along with a proof for the correctness of the algorithm. The remarks which constitute the proof are incorporated parenthetically into the statement of the algorithm. Following this appears a discussion of certain theoretical aspects of the problem. In Section 2, the algorithm is generalized to one for the transportation problem. The algorithm of that section is stated as concisely as possible, with theoretical remarks omitted.

Question: What is the algorithm for the assignment problem?


Weakly Supervised Affordance Detection. Localizing functional regions of objects or affordances is an important aspect of scene understanding and relevant for many robotics applications. In this work, we introduce a pixel-wise annotated affordance dataset of 3090 images containing 9916 object instances. Since parts of an object can have multiple affordances, we address this by a convolutional neural network for multilabel affordance segmentation. We also propose an approach to train the network from very few keypoint annotations. Our approach achieves a higher affordance detection accuracy than other weakly supervised methods that also rely on keypoint annotations or image annotations as weak supervision.

Question: What is a weakly supervised approach?


The James-Lange theory of emotions: a critical examination and an alternative theory. By Walter B. Cannon, 1927..

Question: What is the James-Lange theory of emotions?


EKG-based key agreement in Body Sensor Networks. Preserving a person's privacy in an efficient manner is very important for critical, life-saving infrastructures like body sensor networks (BSN). This paper presents a novel key agreement scheme which allows two sensors in a BSN to agree to a common key generated using electrocardiogram (EKG) signals. This EKG-based key agreement (EKA) scheme aims to bring the "plug-n-play" paradigm to BSN security whereby simply deploying sensors on the subject can enable secure communication, without requiring any form of initialization such as pre-deployment. Analysis of the scheme based on real EKG data (obtained from MIT PhysioBank database) shows that keys resulting from EKA are: random, time variant, can be generated based on short-duration EKG measurements, identical for a given subject and different for separate individuals.

Question: How does the EKG-based key agreement work?


An Active Pixel Sensor Fabricated Using CMOS / CCD Process Technology. Paul P. K. Lee, Russell C. Gee*, R. Michael Guidash, T-H. Lee, and Eric R. Fossum* Microelectronics Technology Division, Eastman Kodak Company 1669 Lake Avenue, Rochester, New York 14650-2008 Tel: (716) 477-2869, Fax: (716) 477-4947, Internet: ppklee@Kodak.COM *Jet Propulsion Laboratory, California Institute of Technology 4800 Oak Grove Drive, Pasadena, CA 91109 Abstract This paper describes the integration of the active pixel sensor (APS) architecture normally fabricated in conventional complementary metal oxide semiconductor (CMOS) technology with a pinned photodiode (PPD) device using a mixed process technology. This new technology allows mix and match of CMOS and high performance charged coupled device (CCD) modules. The PPD [1] becomes the photoactive element in an XYaddressable area array with each pixel containing active devices for the transfer, readout and reset functions. It is a standard photo-sensitive element, available in a high performance true two-phase CCD technology developed previously for CCD-based image sensors [2]. An n-well 2-μm CMOS technology was combined with the CCD process to provide the best features from both. A Design of Experiment approach was used with Technology Computer Aided Design (TCAD) tools to develop and optimize the new mixed process technology without sacrificing any CCD performance while minimizing impact to the CMOS device characteristics [3]. By replacing polysilicon photocapacitor or photogate in conventional APS with the pinned photodiode, deficiencies in poor blue response and high dark current are minimized [4].

Question: What is the difference between a CMOS and a CCD?


Development environments for autonomous mobile robots: A survey. Robotic Development Environments (RDEs) have come to play an increasingly important role in robotics research in general, and for the development of architectures for mobile robots in particular. Yet, no systematic evaluation of available RDEs has been performed; establishing a comprehensive list of evaluation criteria targeted at robotics applications is desirable that can subsequently be used to compare their strengths and weaknesses. Moreover, there are no practical evaluations of the usability and impact of a large selection of RDEs that provides researchers with the information necessary to select an RDE most suited to their needs, nor identifies trends in RDE research that suggest directions for future RDE development. This survey addresses the above by selecting and describing nine open source, freely available RDEs for mobile robots, evaluating and comparing them from various points of view. First, based on previous work concerning agent systems, a conceptual framework of four broad categories is established, encompassing the characteristics and capabilities that an RDE supports. Then, a practical evaluation of RDE usability in designing, implementing, and executing robot architectures is presented. Finally, the impact of specific RDEs on the field of robotics is addressed by providing a list of published applications and research projects that give concrete examples of areas in which systems have been used. The comprehensive evaluation and comparison of the nine RDEs concludes with suggestions of how to use the results of this survey and a brief discussion of future trends in RDE design.

Question: What is the difference between a robot and a robot?


Being John Malkovich. Given a photo of person A, we seek a photo of person B with similar pose and expression. Solving this problem enables a form of puppetry, in which one person appears to control the face of another. When deployed on a webcam-equipped computer, our approach enables a user to control another person's face in real-time. This image-retrievalinspired approach employs a fully-automated pipeline of face analysis techniques, and is extremely general—we can puppet anyone directly from their photo collection or videos in which they appear. We show several examples using images and videos of celebrities from the Internet.

Question: How does this work?


101companies: A Community Project on Software Technologies and Software Languages. 101companies is a community project in computer science (or software science) with the objective of developing a free, structured, wiki-accessible knowledge resource including an open-source repository for different stakeholders with interests in software technologies, software languages, and technological spaces; notably: teachers and learners in software engineering or software languages as well as software developers, software technologists, and ontologists. The present paper introduces the 101companies Project. In fact, the present paper is effectively a call for contributions to the project and a call for applications of the project in research and education.

Question: What is a wiki?


A Deep Network with Visual Text Composition Behavior. While natural languages are compositional, how state-of-the-art neural models achieve compositionality is still unclear. We propose a deep network, which not only achieves competitive accuracy for text classification, but also exhibits compositional behavior. That is, while creating hierarchical representations of a piece of text, such as a sentence, the lower layers of the network distribute their layer-specific attention weights to individual words. In contrast, the higher layers compose meaningful phrases and clauses, whose lengths increase as the networks get deeper until fully composing the sentence.

Question: How does a deep network achieve compositionality?


Characterization studies of fluorine-induced corrosion crystal defects on microchip Al bondpads using X-ray photoelectron spectroscopy. In wafer fabrication, Fluorine (F) contamination may cause F-induced corrosion and defects on microchip Al bondpad, resulting in bondpad discoloration or non-stick on pad (NSOP). In the previous paper [1], the authors studied the F-induced corrosion and defects, characterized the composition of the "flower-like" defects and determined the binding energy of Al fluoride [AlF6]3- using X-ray Photoelectron Spectroscopy (XPS) and Time of Flight Secondary Ion Mass Spectrometry (TOF-SIMS) techniques. In this paper, we further studied F-induced corrosion and defects, and characterized the composition of the "crystal-like" defects using XPS. The experimental results showed that the major component of the "crystal-like" defect was Al fluoride of AlF3. The percentages of the components of the "crystal-like" defects on the affected bondpad are: Al (22.2%), Al2O3 (5.4%), AlF3(70.0%) and [AlF6]3- (2.4%). During high-resolution fitting, the binding energies of Al (72.8eV)Al2O3 (74.5eV), AlF3 (76.3eV) and [AlF6]3- (78.7eV) were used.

Question: What is the composition of the "crystal-like" defects?


A Survey of Algorithms for Keyword Search on Graph Data. In this chapter, we survey methods that perform keyword search on graph data. Keyword search provides a simple but user-friendly interface to retrieve information from complicated data structures. Since many real life datasets are represented by trees and graphs, keyword search has become an attractive mechanism for data of a variety of types. In this survey, we discuss methods of keyword search on schema graphs, which are abstract representation for XML data and relational data, and methods of keyword search on schema-free graphs. In our discussion, we focus on three major challenges of keyword search on graphs. First, what is the semantics of keyword search on graphs, or, what qualifies as an answer to a keyword search; second, what constitutes a good answer, or, how to rank the answers; third, how to perform keyword search efficiently. We also discuss some unresolved challenges and propose some new research directions

Question: What is the semantics of keyword search on graphs?


Design and implementation of embedded Web server based on arm and Linux. This paper achieves the design of an embedded Web server, which takes ARM920T-S3c2410s chip as its core and Linux as its operating system. This is because Linux can be reduced and transplanted. The method used to transplant Web server Boa on the embedded Linux platform is also discussed in detail, and through CGI technology functions of dynamic Web page is successfully realized. Relevant experiments show that after the Web server is embedded into the network video monitoring system, dynamic page interaction can be achieved between the Web server and the embedded system via the browser in the Windows environment.

Question: How to design an embedded Web server?


Action-Reaction: Forecasting the Dynamics of Human Interaction. Forecasting human activities from visual evidence is an emerging area of research which aims to allow computational systems to make predictions about unseen human actions. We explore the task of activity forecasting in the context of dual-agent interactions to understand how the actions of one person can be used to predict the actions of another. We model dual-agent interactions as an optimal control problem, where the actions of the initiating agent induce a cost topology over the space of reactive poses – a space in which the reactive agent plans an optimal pose trajectory. The technique developed in this work employs a kernel-based reinforcement learning approximation of the soft maximum value function to deal with the high-dimensional nature of human motion and applies a mean-shift procedure over a continuous cost function to infer a smooth reaction sequence. Experimental results show that our proposed method is able to properly model human interactions in a high dimensional space of human poses. When compared to several baseline models, results show that our method is able to generate highly plausible simulations of human interaction.

Question: What is the optimal control problem?


Cache Games -- Bringing Access-Based Cache Attacks on AES to Practice. Side channel attacks on cryptographic systems exploit information gained from physical implementations rather than theoretical weaknesses of a scheme. In recent years, major achievements were made for the class of so called access-driven cache attacks. Such attacks exploit the leakage of the memory locations accessed by a victim process. In this paper we consider the AES block cipher and present an attack which is capable of recovering the full secret key in almost real time for AES-128, requiring only a very limited number of observed encryptions. Unlike previous attacks, we do not require any information about the plaintext (such as its distribution, etc.). Moreover, for the first time, we also show how the plaintext can be recovered without having access to the cipher text at all. It is the first working attack on AES implementations using compressed tables. There, no efficient techniques to identify the beginning of AES rounds is known, which is the fundamental assumption underlying previous attacks. We have a fully working implementation of our attack which is able to recover AES keys after observing as little as 100 encryptions. It works against the OpenS SL 0.9.8n implementation of AES on Linux systems. Our spy process does not require any special privileges beyond those of a standard Linux user. A contribution of probably independent interest is a denial of service attack on the task scheduler of current Linux systems (CFS), which allows one to observe (on average) every single memory access of a victim process.

Question: What is the size of the cache in a modern computer?


Communication-efficient algorithms for statistical optimization. We study two communication-efficient algorithms for distributed statistical optimization on large-scale data. The first algorithm is an averaging method that distributes the N data samples evenly to m machines, performs separate minimization on each subset, and then averages the estimates. We provide a sharp analysis of this average mixture algorithm, showing that under a reasonable set of conditions, the combined parameter achieves mean-squared error that decays as O(N-1 + (N/m)-2). Whenever m ≤ √N, this guarantee matches the best possible rate achievable by a centralized algorithm with access to all N samples. The second algorithm is a novel method, based on an appropriate form of bootstrap. Requiring only a single round of communication, it has mean-squared error that decays as O(N-1 + (N/m)-3), and so is more robust to the amount of parallelization.

Question: What is the best known rate for the average mixture algorithm?


A Security approach for Data Migration in Cloud Computing. Cloud computing is a new paradigm that combines several computing concepts and technologies of the Internet creating a platform for more agile and cost-effective business applications and IT infrastructure. The adoption of Cloud computing has been increasing for some time and the maturity of the market is steadily growing. Security is the question most consistently raised as consumers look to move their data and applications to the cloud. I justify the importance and motivation of security in the migration of legacy systems and I carry out an approach related to security in migration processes to cloud with the aim of finding the needs, concerns, requirements, aspects, opportunities and benefits of security in the migration process of legacy systems.

Question: What is the motivation of security in migration processes to cloud?


Human Action Recognition Using Multi-Velocity STIPs and Motion Energy Orientation Histogram. Local image features in space-time or spatio-temporal interest points provide compact and abstract representations of patterns in a video sequence. In this paper, we present a novel human action recognition method based on multi-velocity spatio-temporal interest points (MVSTIPs) and a novel local descriptor called motion energy (ME) orientation histogram (MEOH). The MVSTIP detection includes three steps: first, filtering video frames with multi-direction ME filters at different speeds to detect significant changes at the pixel level; thereafter, a surround suppression model is employed to rectify the ME deviation caused by the camera motion and complicated backgrounds (e.g., dynamic texture); finally, MVSTIPs are obtained with local maximum filters at multispeeds. After detection, we develop MEOH descriptor to capture the motion features in local regions around interest points. The performance of the proposed method is evaluated on KTH, Weizmann, and UCF sports human action datasets. Results show that our method is robust to both simple and complex backgrounds and the method is superior to other methods that are based on local features.

Question: What is the difference between a local feature and a global feature?


Estimation of Primary Quantization Matrix in Double Compressed JPEG Images. In this report, we present a method for estimation of primary quantization matrix from a double compressed JPEG image. We first identify characteristic features that occur in DCT histograms of individual coefficients due to double compression. Then, we present 3 different approaches that estimate the original quantization matrix from double compressed images. Finally, most successful of them Neural Network classifier is discussed and its performance and reliability is evaluated in a series of experiments on various databases of double compressed images. It is also explained in this paper, how double compression detection techniques and primary quantization matrix estimators can be used in steganalysis of JPEG files and in digital forensic analysis for detection of digital forgeries.

Question: How to estimate the primary quantization matrix in double compressed JPEG images?


Extensional Versus Intuitive Reasoning : The Conjunction Fallacy in Probability Judgment. Perhaps the simplest and the most basic qualitative law of probability is the conjunction rule: The probability of a conjunction, P(A&B), cannot exceed the probabilities of its constituents, P(A) and .P(B), because the extension (or the possibility set) of the conjunction is included in the extension of its constituents. Judgments under uncertainty, however, are often mediated by intuitive heuristics that are not bound by the conjunction rule. A conjunction can be more representative than one of its constituents, and instances of a specific category can be easier to imagine or to retrieve than instances of a more inclusive category. The representativeness and availability heuristics therefore can make a conjunction appear more probable than one of its constituents. This phenomenon is demonstrated in a variety of contexts including estimation of word frequency, personality judgment, medical prognosis, decision under risk, suspicion of criminal acts, and political forecasting. Systematic violations of the conjunction rule are observed in judgments of lay people and of experts in both between-subjects and within-subjects comparisons. Alternative interpretations of the conjunction fallacy are discussed and attempts to combat it are explored.

Question: What is the conjunction fallacy?


Comparison of different methods to cancel offset capacitance in capacitive displacement sensors. This paper presents a comparative study of the power consumption of two methods to cancel the offset capacitance in high-resolution capacitive displacement sensors. One method is applied based on correlated-double-sampling (CDS) technique and the other method is applied using oversampling technique. The analytical comparison predicts similar power consumption, if the same resolution for the same conversion time need to be reached. Experimental results with implementations of the two methods confirmed the analytical prediction.

Question: What is the difference between the two methods?


Agile Software Development: The Business of Innovation. T he rise and fall of the dot-com-driven Internet economy shouldn't distract us from seeing that the business environment continues to change at a dramatically increasing pace. To thrive in this turbulent environment, we must confront the business need for relentless innovation and forge the future workforce culture. Agile software development approaches such as Extreme Programming , Crystal methods, Lean Development, Scrum, Adaptive Software Development (ASD), and others view change from a perspective that mirrors today's turbulent business and technology environment. In a recent study of more than 200 software development projects, QSM Associates' Michael Mah reported that the researchers couldn't find nearly half of the projects' original plans to measure against. Why? Conforming to plan was no longer the primary goal; instead, satisfying customers—at the time of delivery , not at project initiation—took precedence. In many projects we review, major changes in the requirements, scope, and technology that are outside the development team's control often occur within a project's life span. Accepting that Barry Boehm's life cycle cost differentials theory—the cost of change grows through the software's development life cycle—remains valid, the question today is not how to stop change early in a project but how to better handle inevitable changes throughout its life cycle. Traditional approaches assumed that if we just tried hard enough, we could anticipate the complete set of requirements early and reduce cost by eliminating change. Today, eliminating change early means being unresponsive to business con-ditions—in other words, business failure. Similarly, traditional process manage-ment—by continuous measurement, error identification, and process refine-ments—strove to drive variations out of processes. This approach assumes that variations are the result of errors. Today, while process problems certainly caus

Question: What is the cost of change?


Question: What is simulated annealing?


Corn Disease Identification from Leaf Images Using Convolutional Neural Networks. Plant diseases are one of the major factors that can negatively impact crop yields. Therefore, we want to create an automated system that can identify plant diseases as easily as possible. Our research goal is to help crop growers who might not be experts in plant pathology be able to identify diseases as soon as they occur in order to minimize the spread of disease and the damage to the crops. We propose a very light-weight convolutional neural network architecture that is trained to classify images of corn leaves into one of the four categories: common rust disease, northern leaf blight disease, gray leaf spot disease, or healthy. The dataset used is the PlantVillage dataset taken from plantvillage.org. The dataset consists of 8506 images of corn leaves from 4 categories. We evaluated our model using 5-fold cross-validation, and we achieves an accuracy of 97.09 % on average. The result of our model is slightly worse than the performance of other well-known CNNs architectures, but the complexity of our architecture is much lower, making it more suitable for real-time inferences on resource-constrained devices such as smartphones.

Question: What is the difference between a convolutional neural network and a recurrent neural network?


GIST: A Model for Design and Management of Content and Interactivity of Customer-Centric Web Sites. Customer-centric Web-based systems, such as ecommerce Web sites, or sites that support customer relationship management (CRM) activities, are themselves information systems, but their design and maintenance need to follow vastly different approaches from the traditional systems lifecycle approach. Based on marketing frameworks that are applicable to the online world, and following design science principles, we develop a model to guide the design and the continuous management of such sites. The model makes extensive use of current technologies for tracking the customers and their behaviors, and combines elements of data mining and statistical analyses. A case study based on a financial services Web site is used to provide a preliminary validation and design evaluation of our approach. The case study showed considerable measured improvement in the effectiveness of the company's Web site. In addition, it also highlighted an important benefit of the our approach: the identification of previously unknown or unexpected segments of visitors. This finding can lead to promising new business opportunities.

Question: What is a customer-centric Web site?


2395-1621 Hand Gesture Recognition Using Flex Sensors. ARTICLE INFO In this system an electro-mechanical robot is designed and controlled using hand gesture in real time. The system is designed on microcontroller platform using Keil and MPLAB tools. Hand gesture recognition is done on the principle of resistance change sensed through flex sensor. These sensors are integrated in a hand gloves from which input to the system is given. The designed system is divided into two sections as transmitter and receiver. The transmitter section will be in hand gloves from which the data is sensed and processed through PIC16F7487 and send serially to the receiver section. RF technology is used to transmit the data at the receiver section at the frequency of 2.4 GHz. ARM 7 (LPC2148) processor is used to receive the data. Here from the received data, the character is predicted and matched with the closet character from which the character is identified and displayed on LCD. The various case studies is prepared for the designed system and tested in real time. The proposed system can be used for the various applications such as in unmanned machines, industries, handicapped personnel etc. Keywords— a Sensor gloves, flex sensors, PIC controller, ARM processor etc Article History Received:20 th September 2015 Received in revised form :

Question: What is the difference between a sensor glove and a sensor glove?


Massively Parallel A* Search on a GPU. A* search is a fundamental topic in artificial intelligence. Recently, the general purpose computation on graphics processing units (GPGPU) has been widely used to accelerate numerous computational tasks. In this paper, we propose the first parallel variant of the A* search algorithm such that the search process of an agent can be accelerated by a single GPU processor in a massively parallel fashion. Our experiments have demonstrated that the GPU-accelerated A* search is efficient in solving multiple real-world search tasks, including combinatorial optimization problems, pathfinding and game solving. Compared to the traditional sequential CPU-based A* implementation, our GPU-based A* algorithm can achieve a significant speedup by up to 45x on largescale search problems.

Question: What is the first parallel variant of the A* search algorithm?


Extensibility, Safety and Performance in the SPIN Operating System. This paper describes the motivation architecture and performance of SPIN an extensible operating system SPIN provides an extension infrastructure together with a core set of extensible services that allow applica tions to safely change the operating system s interface and implementation Extensions allow an application to specialize the underlying operating system in order to achieve a particular level of performance and function ality SPIN uses language and link time mechanisms to inexpensively export ne grained interfaces to operat ing system services Extensions are written in a type safe language and are dynamically linked into the op erating system kernel This approach o ers extensions rapid access to system services while protecting the op erating system code executing within the kernel address space SPIN and its extensions are written in Modula and run on DEC Alpha workstations

Question: What is the motivation architecture of SPIN?


Unseen Noise Estimation Using Separable Deep Auto Encoder for Speech Enhancement. Unseen noise estimation is a key yet challenging step to make a speech enhancement algorithm work in adverse environments. At worst, the only prior knowledge we know about the encountered noise is that it is different from the involved speech. Therefore, by subtracting the components which cannot be adequately represented by a well defined speech model, the noises can be estimated and removed. Given the good performance of deep learning in signal representation, a deep auto encoder (DAE) is employed in this work for accurately modeling the clean speech spectrum. In the subsequent stage of speech enhancement, an extra DAE is introduced to represent the residual part obtained by subtracting the estimated clean speech spectrum (by using the pre-trained DAE) from the noisy speech spectrum. By adjusting the estimated clean speech spectrum and the unknown parameters of the noise DAE, one can reach a stationary point to minimize the total reconstruction error of the noisy speech spectrum. The enhanced speech signal is thus obtained by transforming the estimated clean speech spectrum back into time domain. The above proposed technique is called separable deep auto encoder (SDAE). Given the under-determined nature of the above optimization problem, the clean speech reconstruction is confined in the convex hull spanned by a pre-trained speech dictionary. New learning algorithms are investigated to respect the non-negativity of the parameters in the SDAE. Experimental results on TIMIT with 20 noise types at various noise levels demonstrate the superiority of the proposed method over the conventional baselines.

Question: How to estimate the noise in speech?


Skipping Refinement. We introduce skipping refinement, a new notion of correctness for reasoning about optimized reactive systems. Reasoning about reactive systems using refinement involves defining an abstract, highlevel specification system and a concrete, low-level implementation system. One then shows that every behavior allowed by the implementation is also allowed by the specification. Due to the difference in abstraction levels, it is often the case that the implementation requires many steps to match one step of the specification, hence, it is quite useful for refinement to directly account for stuttering. Some optimized implementations, however, can actually take multiple specification steps at once. For example, a memory controller can buffer the commands to the memory and at a later time simultaneously update multiple memory locations, thereby skipping several observable states of the abstract specification, which only updates one memory location at a time. We introduce skipping simulation refinement and provide a sound and complete characterization consisting of "local" proof rules that are amenable to mechanization and automated verification. We present case studies that highlight the applicability of skipping refinement: a JVM-inspired stack machine, a simple memory controller and a scalar to vector compiler transformation. Our experimental results demonstrate that current model-checking and automated theorem proving tools have difficultly automatically analyzing these systems using existing notions of correctness, but they can analyze the systems if we use skipping refinement.

Question: What is a memory controller?


The longitudinal relationship of personality traits and disorders.. Personality disorders are presumed to be stable because of underlying stable and maladaptive personality traits, but while previous research has demonstrated a link between personality traits and personality disorders cross-sectionally, personality disorders and personality traits have not been linked longitudinally. This study explores the extent to which relevant personality traits are stable in individuals diagnosed with 4 personality disorders (schizotypal, borderline, avoidant, and obsessive-compulsive personality disorders) and examines the assumption that these personality disorders are stable by virtue of stable personality traits. This assumption was tested via the estimation of a series of latent longitudinal models that evaluated whether changes in relevant personality traits lead to subsequent changes in personality disorders. In addition to offering large consistency estimates for personality traits and personality disorders, the results demonstrate significant cross-lagged relationships between trait change and later disorder change for 3 of the 4 personality disorders studied.

Question: What personality traits are stable in individuals diagnosed with personality disorders?


Stabilization and Path Following of a Spherical Robot. In this paper, we present a spherical mobile robot BYQ_III, for planetary surface exploration and security tasks. The driving torque for the rolling robot is generated by a new type of mechanism equipped with a counter-pendulum. This robot is nonholonomic in nature, and underactuated. In this paper, the three-dimensional (3-D) nonlinear dynamic model is developed, then decoupled to the longitudinal and lateral motions by linearization. Two sliding-mode controllers are proposed to asymptotically stabilize the tracking errors in lean angle and spinning angular velocity, respectively, and indirectly to stabilize the desired path curvature, because the robot steers only by leaning itself to a predefined angle. For the task of path following, a path curvature controller, based on a geometrical notion, is employed. The stability and performance analyses are performed, and also the effectiveness of the controllers is shown by numerical simulations. To the best of author's knowledge, similar results could not be obtained in the previous spherical robot control system based on the dynamics. The work is of significance in understanding and developing this type of planning and controlling motions of nonholonomic systems.

Question: How to stabilize a spherical robot?


Empirical studies of software engineering: a roadmap. In this article we summarize the strengths and weaknesses of empirical research in software engineering. We argue that in order to improve the current situation we must create better studies and draw more credible interpretations from them. We finally present a roadmap for this improvement, which includes a general structure for software empirical studies and concrete steps for achieving these goals: designing better studies, collecting data more effectively, and involving others in our empirical enterprises.

Question: What is the roadmap for empirical studies of software engineering?


Algebraic Distance on Graphs. Measuring the connection strength between a pair of vertices in a graph is one of the most important concerns in many graph applications. Simple measures such as edge weights may not be sufficient for capturing the effects associated with short paths of lengths greater than one. In this paper, we consider an iterative process that smooths an associated value for nearby vertices, and we present a measure of the local connection strength (called the algebraic distance, see [25]) based on this process. The proposed measure is attractive in that the process is simple, linear, and easily parallelized. An analysis of the convergence property of the process reveals that the local neighborhoods play an important role in determining the connectivity between vertices. We demonstrate the practical effectiveness of the proposed measure through several combinatorial optimization problems on graphs and hypergraphs.

Question: What is the algebraic distance?


Getting plugged in: an overview of internet addiction.. Internet addiction is not formally recognised as a clinical disorder by the WHO despite increasing evidence that excessive internet use can interfere with daily life and work. There is increasing pressure from Psychologists for Internet addiction to be recognised. This article explores the prevalence, symptoms and management of Internet addiction and the consequences of ignoring the ever growing concerns from public figures and institutions.

Question: What is the prevalence of internet addiction?


Evaluation on State of Charge Estimation of Batteries With Adaptive Extended Kalman Filter by Experiment Approach. An accurate State-of-Charge (SoC) estimation plays a significant role in battery systems used in electric vehicles due to the arduous operation environments and the requirement of ensuring safe and reliable operations of batteries. Among the conventional methods to estimate SoC, the Coulomb counting method is widely used, but its accuracy is limited due to the accumulated error. Another commonly used method is model-based online iterative estimation with the Kalman filters, which improves the estimation accuracy in some extent. To improve the performance of Kalman filters in SoC estimation, the adaptive extended Kalman filter (AEKF), which employs the covariance matching approach, is applied in this paper. First, we built an implementation flowchart of the AEKF for a general system. Second, we built an online open-circuit voltage (OCV) estimation approach with the AEKF algorithm so that we can then get the SoC estimate by looking up the OCV-SoC table. Third, we proposed a robust online model-based SoC estimation approach with the AEKF algorithm. Finally, an evaluation on the SoC estimation approaches is performed by the experiment approach from the aspects of SoC estimation accuracy and robustness. The results indicate that the proposed online SoC estimation with the AEKF algorithm performs optimally, and for different error initial values, the maximum SoC estimation error is less than 2% with close-loop state estimation characteristics.

Question: How to estimate the state of charge of a battery?


Machine Learning Applied to Cyber Operations.

Question: What is machine learning?


Understanding the Metropolis-Hastings Algorithm. Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at http://www.jstor.org/journals/astata.html. Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission.

Question: How to use JSTOR?


Process reengineering in the public sector : learning some private sector lessons. The possible applicability of business process reengineering (BPR) to organisations in the public sector is explored through analysis of the central issues in BPR and the emerging experience of organisations which have recently implemented it. In particular, the paper suggests that success of reengineering may depend critically on the strategic capability of the organisation prior to undertaking the effort. For that reason well-performing organisations are more likely to improve performance by means of BPR than are weak ones. Yet, in the public sector, it tends to be badly performing agencies which are most encouraged to undertake BPR. Knowing and understanding the reasons for success or failure of BPR in private organisations can prepare public sector managers for undertaking the effort, but each reengineering initiative must be tailored to the specific needs and circumstances of the individual agency. Public sector managers should use the widest possible definition of 'value' when analysing value-added in process reengineering and should be especially sensitive to the way in which 'value' in the public sector is differently interpreted by major stakeholders. During this learning process, public sector agencies would be well advised to be conservative in estimating gains from BPR. © 1997 Elsevier Science Ltd

Question: What is the difference between public and private sector?


A restart CMA evolution strategy with increasing population size. In this paper we introduce a restart-CMA-evolution strategy, where the population size is increased for each restart (IPOP). By increasing the population size the search characteristic becomes more global after each restart. The IPOP-CMA-ES is evaluated on the test suit of 25 functions designed for the special session on real-parameter optimization of CEC 2005. Its performance is compared to a local restart strategy with constant small population size. On unimodal functions the performance is similar. On multi-modal functions the local restart strategy significantly outperforms IPOP in 4 test cases whereas IPOP performs significantly better in 29 out of 60 tested cases.

Question: What is the restart CMA evolution strategy?


Dynamic Cascades for Face Detection. In this paper, we propose a novel method, called "dynamic cascade", for training an efficient face detector on massive data sets. There are three key contributions. The first is a new cascade algorithm called "dynamic cascade ", which can train cascade classifiers on massive data sets and only requires a small number of training parameters. The second is the introduction of a new kind of weak classifier, called "Bayesian stump", for training boost classifiers. It produces more stable boost classifiers with fewer features. Moreover, we propose a strategy for using our dynamic cascade algorithm with multiple sets of features to further improve the detection performance without significant increase in the detector's computational cost. Experimental results show that all the new techniques effectively improve the detection performance. Finally, we provide the first large standard data set for face detection, so that future researches on the topic can be compared on the same training and testing set.

Question: How to train a face detector on massive data sets?


A 3D Morphable Model Learnt from 10,000 Faces. We present Large Scale Facial Model (LSFM) - a 3D Morphable Model (3DMM) automatically constructed from 9,663 distinct facial identities. To the best of our knowledge LSFM is the largest-scale Morphable Model ever constructed, containing statistical information from a huge variety of the human population. To build such a large model we introduce a novel fully automated and robust Morphable Model construction pipeline. The dataset that LSFM is trained on includes rich demographic information about each subject, allowing for the construction of not only a global 3DMM but also models tailored for specific age, gender or ethnicity groups. As an application example, we utilise the proposed model to perform age classification from 3D shape alone. Furthermore, we perform a systematic analysis of the constructed 3DMMs that showcases their quality and descriptive power. The presented extensive qualitative and quantitative evaluations reveal that the proposed 3DMM achieves state-of-the-art results, outperforming existing models by a large margin. Finally, for the benefit of the research community, we make publicly available the source code of the proposed automatic 3DMM construction pipeline. In addition, the constructed global 3DMM and a variety of bespoke models tailored by age, gender and ethnicity are available on application to researchers involved in medically oriented research.

Question: What is the largest morphable model ever constructed?


Position Paper: Physical Unclonable Functions for IoT Security. Devices in the Internet of Things (IoT) introduce unique security challenges due to their operating conditions and device limitations. Existing security solutions based on classical cryptography have significant drawbacks in IoT devices, primarily due to the possibility of physical and side channel attacks. As an alternative approach, this position paper advocates the use of physical unclonable functions (PUFs) as a security primitive for developing security solutions for IoT devices. Preliminary work on developing a PUF based mutual authentication protocol is also presented.

Question: What is a physical unclonable function?


Combining Gradient and Albedo Data for Rotation Invariant Classification of 3D Surface Texture. We present a new texture classification scheme which is invariant to surface-rotation. Many texture classification approaches have been presented in the past that are image-rotation invariant, However, image rotation is not necessarily the same as surface rotation. We have therefore developed a classifier that uses invariants that are derived from surface properties rather than image properties. Previously we developed a scheme that used surface gradient (normal) fields estimated using photometric stereo. In this paper we augment these data with albedo information and an also employ an additional feature set: the radial spectrum. We used 30 real textures to test the new classifier. A classification accuracy of 91% was achieved when albedo and gradient 1D polar and radial features were combined. The best performance was also achieved by using 2D albedo and gradient spectra. The classification accuracy is 99%.

Question: How do you combine gradient and albedo data for rotation invariant classification of 3D surface texture?


Multiband Handset Antenna Combining a PIFA, Slots, and Ground Plane Modes. A multiband handset antenna combining a PIFA and multiple slots on a ground plane is presented. It is shown by means of simulations that the slots on the ground plane have a double function: to tune the ground plane resonance at low frequencies (f ¿ 900 MHz) and to act as parasitic radiators at high frequencies (f ¿ 1800 MHz). A prototype is designed and built featuring a behavior suitable for low frequencies (GSM850 and GSM900) and for high frequencies spanning from DCS1800 to Bluetooth, and including, for instance, PCS1900, UMTS2000, and other possible systems. Reflection coefficient, efficiency, and radiation patterns are measured and compared with a design without slots to prove the advantages of the slotted ground plane. The component effect is investigated to determine critical areas where the placement is not recommended. Besides, the effect of the slot of the ground plane on SAR is investigated, by discussing the effect of the ground plane and slot modes for two phone positions. The total antenna volume of the proposed design is 40 × 15 × 6 mm3.

Question: What is the volume of the antenna?


Significant Triples : Adjective + Noun + Verb Combinations. We investigate the identification and, to some extent, the classification of collocational word groups that consist of an adjectival modifier (A), an accusative object noun (N), and a verb (V) by means of parsing a newspaper corpus with a lexicalized probabilistic grammar.1 Data triples are extracted from the resulting Viterbi parses and subsequently evaluated by means of a statistical association measure. The extraction results are then compared to predefined descriptive classes of ANV-triples. We also use a decision tree algorithm to classify part of the data obtained, on the basis of a small set of manually classified examples. Much of the candidate data is lexicographically relevant: the triples include idiomatic combinations (e.g. (sich) eine goldene Nase verdienen, 'get rich', lit. 'earn oneself a golden nose'), combinations of N+V and N+A collocations (e.g. (eine) klare Absage erteilen, 'refuse resolutely', lit. 'give a clear refusal'), next to cases where N+V or N+A collocations are found, in combination with other (not necessarily collocational) context partners. To extract such data from text corpora, a grammar is needed that captures verb+object relations: simple pattern matching on part-of-speech shapes is not sufficient. Statistical tools then allow to order the data in a way useful for subsequent manual selection by lexicographers. 1This work has been carried out in the context of the Transferbereich 32: Automatische Exzerption, a DFG-funded project aiming at the creation of support tools for the corpus-based updating of printed dictionaries in lexicography, carried out in cooperation with the publishers Langenscheidt KG and Duden BIFAB AG.

Question: What is a lexicographic grammar?


Time-Varying Copula Models for Financial Time Series. We perform an analysis of the potential time inhomogeneity in the dependence between multiple financial time series. To this end, we use the framework of copula theory and tackle the question of whether dependencies in such a case can be assumed constant throughout time or rather have to be modeled in a time-inhomogeneous way. We focus on parametric copula models and suitable inference techniques in the context of a special copula-based multivariate time series model. A recent result due to Chan et al. (2009) is used to derive the joint limiting distribution of local maximum-likelihood estimators on overlapping samples. By restricting the overlap to be fixed, we establish the limiting law of the maximum of the estimator series. Based on the limiting distributions, we develop statistical homogeneity tests, and investigate their local power properties. A Monte Carlo simulation study demonstrates that bootstrapped variance estimates are needed in finite samples. Empirical analyses on real-world financial data finally confirm that time-varying parameters are an exception rather than the rule.

Question: What is the difference between a copula and a joint distribution?


An effect analysis of industry 4.0 to higher education. From history to the present day, especially in the field of technology is provided a wide range of developments. The most important of these developments has achieved the realization of the industrial revolution, has led to play a leading role in the production is done by human beings. The effects on production of industry 4.0 emerging with this mind is very important. The qualified employees should be trained to make the necessary preparations for the company in this period, it is experiencing the fourth industrial revolution. Therefore, the impacts on higher education of industry 4.0 are examined in this paper. The importance in education of industry 4.0 has revealed with statistical data presented in this study.

Question: What is the importance of industry 4.0 in higher education?


Joint learning of ontology and semantic parser from text. Semantic parsing methods are used for capturing and representing semantic meaning of text. Meaning representation capturing all the concepts in the text may not always be available or may not be sufficiently complete. Ontologies provide a structured and reasoning-capable way to model the content of a collection of texts. In this work, we present a novel approach to joint learning of ontology and semantic parser from text. The method is based on semi-automatic induction of a context-free grammar from semantically annotated text. The grammar parses the text into semantic trees. Both, the grammar and the semantic trees are used to learn the ontology on several levels – classes, instances, taxonomic and non-taxonomic relations. The approach was evaluated on the first sentences of Wikipedia pages describing people.

Question: What is the first sentence of a wikipedia page about a person?


Vision-Based Gesture Recognition: A Review. The use of gesture as a natural interface serves as a motivating force for research in modeling, analyzing and recognition of gestures. In particular, human computer intelligent interaction needs vision-based gesture recognition, which involves many interdisciplinary studies. A survey on recent vision-based gesture recognition approaches is given in this paper. We shall review methods of static hand posture and temporal gesture recognition. Several application systems of gesture recognition are also described in this paper. We conclude with some thoughts about future research directions.

Question: What is the difference between static hand posture and temporal gesture recognition?


Inferring causal impact using Bayesian structural time-series models. An important problem in econometrics and marketing is to infer the causal impact that a designed market intervention has exerted on an outcome metric over time. In order to allocate a given budget optimally, for example, an advertiser must determine the incremental contributions that different advertising campaigns have made to web searches, product installs, or sales. This paper proposes to infer causal impact on the basis of a diffusion-regression state-space model that predicts the counterfactual market response that would have occurred had no intervention taken place. In contrast to classical difference-in-differences schemes, state-space models make it possible to (i) infer the temporal evolution of attributable impact, (ii) incorporate empirical priors on the parameters in a fully Bayesian treatment, and (iii) flexibly accommodate multiple sources of variation, including the time-varying influence of contemporaneous covariates, i.e., synthetic controls. Using a Markov chain Monte Carlo algorithm for posterior inference, we illustrate the statistical properties of our approach on synthetic data. We then demonstrate its practical utility by evaluating the effect of an online advertising campaign on search-related site visits. We discuss the strengths and limitations of our approach in improving the accuracy of causal attribution, power analyses, and principled budget allocation.

Question: How to infer causal impact using Bayesian structural time-series models.


Long Text Generation via Adversarial Training with Leaked Information. Automatically generating coherent and semantically meaningful text has many applications in machine translation, dialogue systems, image captioning, etc. Recently, by combining with policy gradient, Generative Adversarial Nets (GAN) that use a discriminative model to guide the training of the generative model as a reinforcement learning policy has shown promising results in text generation. However, the scalar guiding signal is only available after the entire text has been generated and lacks intermediate information about text structure during the generative process. As such, it limits its success when the length of the generated text samples is long (more than 20 words). In this paper, we propose a new framework, called LeakGAN, to address the problem for long text generation. We allow the discriminative net to leak its own high-level extracted features to the generative net to further help the guidance. The generator incorporates such informative signals into all generation steps through an additional MANAGER module, which takes the extracted features of current generated words and outputs a latent vector to guide the WORKER module for next-word generation. Our extensive experiments on synthetic data and various realworld tasks with Turing test demonstrate that LeakGAN is highly effective in long text generation and also improves the performance in short text generation scenarios. More importantly, without any supervision, LeakGAN would be able to implicitly learn sentence structures only through the interaction between MANAGER and WORKER.

Question: How to generate long text?


Polygraph: automatically generating signatures for polymorphic worms. It is widely believed that content-signature-based intrusion detection systems (IDS) are easily evaded by polymorphic worms, which vary their payload on every infection attempt. In this paper, we present Polygraph, a signature generation system that successfully produces signatures that match polymorphic worms. Polygraph generates signatures that consist of multiple disjoint content substrings. In doing so, Polygraph leverages our insight that for a real-world exploit to function properly, multiple invariant substrings must often be present in all variants of a payload; these substrings typically correspond to protocol framing, return addresses, and in some cases, poorly obfuscated code. We contribute a definition of the polymorphic signature generation problem; propose classes of signature suited for matching polymorphic worm payloads; and present algorithms for automatic generation of signatures in these classes. Our evaluation of these algorithms on a range of polymorphic worms demonstrates that Polygraph produces signatures for polymorphic worms that exhibit low false negatives and false positives.

Question: What is a polymorphic worm?


Corporate social responsibility and bank customer satisfaction A research agenda. Purpose – The purpose of this paper is to explore the relationship between corporate social responsibility (CSR) and customer outcomes. Design/methodology/approach – This paper reviews the literature on CSR effects and satisfaction, noting gaps in the literature. Findings – A series of propositions is put forward to guide future research endeavours. Research limitations/implications – By understanding the likely impact on customer satisfaction of CSR initiatives vis-à-vis customer-centric initiatives, the academic research community can assist managers to understand how to best allocate company resources in situations of low customer satisfaction. Such endeavours are managerially relevant and topical. Researchers seeking to test the propositions put forward in this paper would be able to gain links with, and possibly attract funding from, banks to conduct their research. Such endeavours may assist researchers to redefine the stakeholder view by placing customers at the centre of a network of stakeholders. Practical implications – An understanding of how to best allocate company resources to increase the proportion of satisfied customers will allow bank marketers to reduce customer churn and hence increase market share and profits. Originality/value – Researchers have not previously conducted a comparative analysis of the effects of different CSR initiatives on customer satisfaction, nor considered whether more customer-centric initiatives are likely to be more effective in increasing the proportion of satisfied customers.

Question: What is the relationship between corporate social responsibility and customer satisfaction?


Description of Luciola aquatilis sp. nov., a new aquatic firefly (Coleoptera: Lampyridae: Luciolinae) from Thailand. A new species of aquatic firefly belonging to Luciola Laporte is described and illustrated based on external morphology of both males and females, and the genitalia of males. Luciola aquatilis sp. nov., a common firefly in Thailand was formerly commonly misidentified as Luciola brahmina Bourgeois. Other Luciola species that resemble L. aquatilis are discussed, as well as past confusion concerning their taxonomic affinities.

Question: What is the common name of the firefly?