Modelling, Visualising and Summarising Documents with a Single Convolutional Neural Network. Capturing the compositional process which maps the meaning of words to that of documents is a central challenge for researchers in Natural Language Processing and Information Retrieval. We introduce a model that is able to represent the meaning of documents by embedding them in a low dimensional vector space, while preserving distinctions of word and sentence order crucial for capturing nuanced semantics. Our model is based on an extended Dynamic Convolution Neural Network, which learns convolution filters at both the sentence and document level, hierarchically learning to capture and compose low level lexical features into high level semantic concepts. We demonstrate the effectiveness of this model on a range of document modelling tasks, achieving strong results with no feature engineering and with a more compact model. Inspired by recent advances in visualising deep convolution networks for computer vision, we present a novel visualisation technique for our document networks which not only provides insight into their learning process, but also can be interpreted to produce a compelling automatic summarisation system for texts.

Question: What is a convolutional neural network?


EigenTrustp++: Attack resilient trust management. This paper argues that trust and reputation models should take into account not only direct experiences (local trust) and experiences from the circle of "friends", but also be attack resilient by design in the presence of dishonest feedbacks and sparse network connectivity. We first revisit EigenTrust, one of the most popular reputation systems to date, and identify the inherent vulnerabilities of EigenTrust in terms of its local trust vector, its global aggregation of local trust values, and its eigenvector based reputation propagating model. Then we present EigenTrust++, an attack resilient trust management scheme. EigenTrust++ extends the eigenvector based reputation propagating model, the core of EigenTrust, and counters each of vulnerabilities identified with alternative methods that are by design more resilient to dishonest feedbacks and sparse network connectivity under four known attack models. We conduct extensive experimental evaluation on EigenTrust++, and show that EigenTrust++ can significantly outperform EigenTrust in terms of both performance and attack resilience in the presence of dishonest feedbacks and sparse network connectivity against four representative attack models.

Question: What is the eigenvector based reputation propagating model?


A Gradient-Based Comparison Measure for Visual analysis of Multifield Data. We introduce a multifield comparison measure for scalar fields that helps in studying relations between them. The comparison measure is insensitive to noise in the scalar fields and to noise in their gradients. Further, it can be computed robustly and efficiently. Results from the visual analysis of various data sets from climate science and combustion applications demonstrate the effective use of the measure.

Question: What is a multifield comparison measure?


Critiquing-based recommenders: survey and emerging trends. Critiquing-based recommender systems elicit users' feedback, called critiques, which they made on the recommended items. This conversational style of interaction is in contract to the standard model where users receive recommendations in a single interaction. Through the use of the critiquing feedback, the recommender systems are able to more accurately learn the users' profiles, and therefore suggest better recommendations in the subsequent rounds. Critiquing-based recommenders have been widely studied in knowledge-, content-, and preference-based recommenders and are beginning to be tried in several online websites, such as MovieLens. This article examines the motivation and development of the subject area, and offers a detailed survey of the state of the art concerning the design of critiquing interfaces and development of algorithms for critiquing generation. With the help of categorization analysis, the survey reveals three principal branches of critiquing based recommender systems, using respectively natural language based, system-suggested, and user-initiated critiques. Representative example systems will be presented and analyzed for each branch, and their respective pros and cons will be discussed. Subsequently, a hybrid framework is developed to unify the advantages of different methods and overcome their respective limitations. Empirical findings from user studies are further presented, indicating how hybrid critiquing supports could effectively enable end-users to achieve more confident decisions. Finally, the article will point out several future trends to boost the advance of critiquing-based recommenders.

Question: What is the difference between critiquing-based recommender systems and standard recommender systems?


Measuring the effectiveness of answers in Yahoo! Answers. Purpose – This study investigates the ways in which effectiveness of answers in Yahoo! Answers, one of the largest community question answering sites (CQAs), is related to question types and answerer reputation. Effective answers are defined as those that are detailed, readable, superior in quality, and contributed promptly. Five question types that were studied include factoid, list, definition, complex interactive, and opinion. Answerer reputation refers to the past track record of answerers in the community. Design/Methodology/Approach – The dataset comprises 1,459 answers posted in Yahoo! Answers in response to 464 questions that were distributed across the five question types. The analysis was done using factorial analysis of variance. Findings – The results indicate that factoid, definition and opinion questions were comparable in attracting high quality as well as readable answers. Although reputed answerers generally fared better in offering detailed and high quality answers, novices were found to submit more readable responses. Moreover, novices were more prompt in answering factoid, list and definition questions. Originality/value – By analyzing variations in answer effectiveness with a twin-focus on question types and answerer reputation, this study explores a strand of CQA research that has hitherto received limited attention. The findings offer insights to users and designers of CQAs.

Question: What is the difference between a factoid and a definition question?


On Divergences and Informations in Statistics and Information Theory. The paper deals with the f-divergences of Csiszar generalizing the discrimination information of Kullback, the total variation distance, the Hellinger divergence, and the Pearson divergence. All basic properties of f-divergences including relations to the decision errors are proved in a new manner replacing the classical Jensen inequality by a new generalized Taylor expansion of convex functions. Some new properties are proved too, e.g., relations to the statistical sufficiency and deficiency. The generalized Taylor expansion also shows very easily that all f-divergences are average statistical informations (differences between prior and posterior Bayes errors) mutually differing only in the weights imposed on various prior distributions. The statistical information introduced by De Groot and the classical information of Shannon are shown to be extremal cases corresponding to alpha=0 and alpha=1 in the class of the so-called Arimoto alpha-informations introduced in this paper for 0<alpha<1 by means of the Arimoto alpha-entropies. Some new examples of f-divergences are introduced as well, namely, the Shannon divergences and the Arimoto alpha-divergences leading for alphauarr1 to the Shannon divergences. Square roots of all these divergences are shown to be metrics satisfying the triangle inequality. The last section introduces statistical tests and estimators based on the minimal f-divergence with the empirical distribution achieved in the families of hypothetic distributions. For the Kullback divergence this leads to the classical likelihood ratio test and estimator

Question: What is the difference between the total variation distance and the Hellinger divergence?


Clustering and projected clustering with adaptive neighbors. Many clustering methods partition the data groups based on the input data similarity matrix. Thus, the clustering results highly depend on the data similarity learning. Because the similarity measurement and data clustering are often conducted in two separated steps, the learned data similarity may not be the optimal one for data clustering and lead to the suboptimal results. In this paper, we propose a novel clustering model to learn the data similarity matrix and clustering structure simultaneously. Our new model learns the data similarity matrix by assigning the adaptive and optimal neighbors for each data point based on the local distances. Meanwhile, the new rank constraint is imposed to the Laplacian matrix of the data similarity matrix, such that the connected components in the resulted similarity matrix are exactly equal to the cluster number. We derive an efficient algorithm to optimize the proposed challenging problem, and show the theoretical analysis on the connections between our method and the K-means clustering, and spectral clustering. We also further extend the new clustering model for the projected clustering to handle the high-dimensional data. Extensive empirical results on both synthetic data and real-world benchmark data sets show that our new clustering methods consistently outperforms the related clustering approaches.

Question: What is the difference between clustering and projected clustering?


Fast Algorithms for Mining Association Rules in Large Databases.

Question: What is the difference between a database and a database management system?


Top Rank Supervised Binary Coding for Visual Search. In recent years, binary coding techniques are becoming increasingly popular because of their high efficiency in handling large-scale computer vision applications. It has been demonstrated that supervised binary coding techniques that leverage supervised information can significantly enhance the coding quality, and hence greatly benefit visual search tasks. Typically, a modern binary coding method seeks to learn a group of coding functions which compress data samples into binary codes. However, few methods pursued the coding functions such that the precision at the top of a ranking list according to Hamming distances of the generated binary codes is optimized. In this paper, we propose a novel supervised binary coding approach, namely Top Rank Supervised Binary Coding (Top-RSBC), which explicitly focuses on optimizing the precision of top positions in a Hamming-distance ranking list towards preserving the supervision information. The core idea is to train the disciplined coding functions, by which the mistakes at the top of a Hamming-distance ranking list are penalized more than those at the bottom. To solve such coding functions, we relax the original discrete optimization objective with a continuous surrogate, and derive a stochastic gradient descent to optimize the surrogate objective. To further reduce the training time cost, we also design an online learning algorithm to optimize the surrogate objective more efficiently. Empirical studies based upon three benchmark image datasets demonstrate that the proposed binary coding approach achieves superior image search accuracy over the state-of-the-arts.

Question: What is the top rank of the canadian military?


Active Imitation Learning via Reduction to I.I.D. Active Learning. In standard passive imitation learning, the goal is to learn a target policy by passively observing full execution trajectories of it. Unfortunately, generating such trajectories can require substantial expert effort and be impractical in some cases. In this paper, we consider active imitation learning with the goal of reducing this effort by querying the expert about the desired action at individual states, which are selected based on answers to past queries and the learner's interactions with an environment simulator. We introduce a new approach based on reducing active imitation learning to i.i.d. active learning, which can leverage progress in the i.i.d. setting. Our first contribution, is to analyze reductions for both non-stationary and stationary policies, showing that the label complexity (number of queries) of active imitation learning can be substantially less than passive learning. Our second contribution, is to introduce a practical algorithm inspired by the reductions, which is shown to be highly effective in four test domains compared to a number of alternatives.

Question: What is the label complexity of active imitation learning?


Diffusion of innovations in service organizations: systematic review and recommendations.. This article summarizes an extensive literature review addressing the question, How can we spread and sustain innovations in health service delivery and organization? It considers both content (defining and measuring the diffusion of innovation in organizations) and process (reviewing the literature in a systematic and reproducible way). This article discusses (1) a parsimonious and evidence-based model for considering the diffusion of innovations in health service organizations, (2) clear knowledge gaps where further research should be focused, and (3) a robust and transferable methodology for systematically reviewing health service policy and management. Both the model and the method should be tested more widely in a range of contexts.

Question: How can we spread and sustain innovations in health service delivery and organization?


Round-Robin Arbiter Design and Generation. In this paper, we introduce a Round-robin Arbiter Generator (RAG) tool. The RAG tool can generate a design for a Bus Arbiter (BA). The BA is able to handle the exact number of bus masters for both on-chip and off-chip buses. RAG can also generate a distributed and parallel hierarchical Switch Arbiter (SA). The first contribution of this paper is the automated generation of a round-robin token passing BA to reduce time spent on arbiter design. The generated arbiter is fair, fast, and has a low and predictable worst-case wait time. The second contribution of this paper is the design and integration of a distributed fast arbiter, e.g., for a terabit switch, based on 2x2 and 4x4 switch arbiters (SAs). Using a .25µ TSMC standard cell library from LEDA Systems [10, 14], we show the arbitration time of a 256x256 SA for a terabit switch and demonstrate that the SA generated by RAG meets the time constraint to achieve approximately six terabits of throughput in a typical network switch design. Furthermore, our generated SA performs better than the Ping-Pong Arbiter and Programmable Priority Encoder by a factor of 1.9X and 2.4X, respectively.

Question: What is a terabit switch?


Realization of a composite right/left-handed leaky-wave antenna with circular polarization. A leaky-wave antenna (LWA) with circular polarization based on the composite right/left-handed (CRLH) substrate integrated waveguide (SIW) is investigated and presented. Series interdigital capacitors have been introduced into the circuit by etching the slots on the waveguide surface achieving a CRLH functionality. Two symmetrical leaky traveling-wave transmission lines with orthogonal polarizations are placed side-by-side and excited with 90° phase difference generating a pure circular polarization mode. The main beam of this antenna can be steered continuously by varying the frequency while maintaining a low axial ratio (below 3 dB) within the main beam direction. The performance of this LWA is verified through both full-wave simulation and measurement of a fabricated prototype showing a good agreement.

Question: What is a leaky-wave antenna?


Domain Modelling in Computational Persuasion for Behaviour Change in Healthcare. The aim of behaviour change is to help people to change aspects of their behaviour for the better (e.g., to decrease calorie intake, to drink in moderation, to take more exercise, to complete a course of antibiotics once started, etc.). In current persuasion technology for behaviour change, the emphasis is on helping people to explore their issues (e.g., through questionnaires or game playing) or to remember to follow a behaviour change plan (e.g., diaries and email reminders). However, recent developments in computational persuasion are leading to an argument-centric approach to persuasion that can potentially be harnessed in behaviour change applications. In this paper, we review developments in computational persuasion, and then focus on domain modelling as a key component. We present a multi-dimensional approach to domain modelling. At the core of this proposal is an ontology which provides a representation of key factors, in particular kinds of belief, which we have identified in the behaviour change literature as being important in diverse behaviour change initiatives. Our proposal for domain modelling is intended to facilitate the acquisition and representation of the arguments that can be used in persuasion dialogues, together with meta-level information about them which can be used by the persuader to make strategic choices of argument to present.

Question: What is domain modelling?


The Parable of Google Flu: Traps in Big Data Analysis. In February 2013, Google Flu Trends (GFT) made headlines but not for a reason that Google executives or the creators of the flu tracking system would have hoped. Nature reported that GFT was predicting more than double the proportion of doctor visits for influenza-like illness (ILI) than the Centers for Disease Control and Prevention (CDC), which bases its estimates on surveillance reports from laboratories across the United States (1, 2). This happened despite the fact that GFT was built to predict CDC reports. Given that GFT is often held up as an exemplary use of big data (3, 4), what lessons can we draw from this error?

Question: What is the difference between GFT and CDC?


3-D Deep Learning Approach for Remote Sensing Image Classification. Recently, a variety of approaches have been enriching the field of remote sensing (RS) image processing and analysis. Unfortunately, existing methods remain limited to the rich spatiospectral content of today's large data sets. It would seem intriguing to resort to deep learning (DL)-based approaches at this stage with regard to their ability to offer accurate semantic interpretation of the data. However, the specificity introduced by the coexistence of spectral and spatial content in the RS data sets widens the scope of the challenges presented to adapt DL methods to these contexts. Therefore, the aim of this paper is first to explore the performance of DL architectures for the RS hyperspectral data set classification and second to introduce a new 3-D DL approach that enables a joint spectral and spatial information process. A set of 3-D schemes is proposed and evaluated. Experimental results based on well-known hyperspectral data sets demonstrate that the proposed method is able to achieve a better classification rate than state-of-the-art methods with lower computational costs.

Question: What is the difference between a hyperspectral data set and a remote sensing image?


Job insecurity and organizational citizenship behavior: exploring curvilinear and moderated relationships.. This article examined a curvilinear relationship between job insecurity and organizational citizenship behavior (OCB). Drawing from social exchange theory and research on personal control, we developed and tested an explanation for employees' reactions to job insecurity based on their conceptualization of their social exchange relationship with the organization at different levels of job insecurity. Using data from 244 Chinese employees and 102 supervisory ratings of OCB, we found support for a U-shaped relationship between job insecurity and OCB. Moreover, 2 factors--psychological capital and subordinate-supervisor guanxi--moderated the curvilinear relationship, such that the curvilinear relationship is more pronounced among those with lower psychological capital or less positive subordinate-supervisor guanxi.

Question: What is the curvilinear relationship between job insecurity and organizational citizenship behavior?


A High Step-Down Transformerless Single-Stage Single-Switch AC/DC Converter. This paper presents a high step-down tranformerless single-stage single-switch ac/dc converter suitable for universal line applications (90-270 Vrms) . The topology integrates a buck-type power-factor correction (PFC) cell with a buck-boost dc/dc cell and part of the input power is coupled to the output directly after the first power processing. With this direct power transfer feature and sharing capacitor voltages, the converter is able to achieve efficient power conversion, high power factor, low voltage stress on intermediate bus (less than 130 V) and low output voltage without a high step-down transformer. The absence of transformer reduces the component counts and cost of the converter. Unlike most of the boost-type PFC cell, the main switch of the proposed converter only handles the peak inductor current of dc/dc cell rather than the superposition of both inductor currents. Detailed analysis and design procedures of the proposed circuit are given and verified by experimental results.

Question: What is a high step-down transformerless single-stage single-switch ac/dc converter?


A Study on Knowledge , Perceptions and Attitudes about Screening and Diagnosis of Diabetes in Saudi Population. Introduction: Timely screening and treatment of diabetes can considerably reduce associated health adverse effects. The purpose of the study was to evaluate the knowledge about diabetes and perceptions and attitude about screening and early diagnosis of diabetes among the population. Methods: A cross-sectional questionnaire-based study conducted among non-diabetes adult people attending primary health care centers in Jeddah, Saudi Arabia. Participants' knowledge about diabetes risk factors and complications and perceptions and attitude regarding screening and early diagnosis of diabetes was assessed and different scores were calculated. Results: Total 202 patients were included: mean (SD) age was 38.19 (13.25) years and 55.0% were females. Knowledge about diabetes risk factors and complications was 60.41%84.77% and 44.67%-67.51%, respectively, depending on the item. Perceptions about screening and early diagnosis showed that 81.19% believed that screening tests exist and 75.14% believed that it is possible to diagnose diabetes before complication stage; while 84.16% believed that early diagnosis increases treatment efficacy, decreases incidence of complications (83.66%), and allows early treatment (83.66%). Regarding attitude, 86.14% agreed to undergo diabetes screening if advised by the physician and 60.40% would do on their own initiative. Linear regression showed a positive correlation of attitude score with knowledge about diabetes risk factors (OR=1.87; p<0.0001) and complications (OR=1.46; p<0.0001); perception about feasibility of screening (OR=1.93; p<0.0001) and benefits of early diagnosis (OR=1.69; p<0.0001). Conclusions: The improvement of knowledge about diabetes risk factors and complications as well as the perception about feasibility and benefits of screening are prerequisites for the promotion of diabetes screening among the population.

Question: What is the difference between knowledge and perception?


The Behavioural Paths to Wellbeing : An Exploratory Study to Distinguish Between Hedonic and Eudaimonic Wellbeing From an Activity Perspective. Hedonic wellbeing and eudaimonic wellbeing are two prevailing approaches to wellbeing. However, remarkably little research has distinguished them from an activity perspective; the knowledge of behavioural paths for achieving these two wellbeings is poor. This study first clarified the behavioural contents of the two approaches through a bottom-up method and then analysed the representativeness of activities to indicate to what extent activities contributed to wellness. We found that the paths to hedonic wellbeing and eudaimonic wellbeing overlapped and differed from each other. Furthermore, this study explained why hedonic activity differed from eudaimonic activity by analysing activity characteristics. We found that people reported higher frequency, sensory experience, and affective experience in hedonic activity, whereas they reported higher intellectual experience, behavioural experience, and spiritual experience in eudaimonic activity. Finally, we explored the behavioural pattern of wellbeing pursuit in both an unthreatening situation and a threatening situation. We found that the overlap between the two approaches increased in the threatening situation. Moreover, people in the threatening situation tended to score lower on all characteristics except frequency relative to those in the unthreatening situation. It seemed that the behavioural pattern in the threatening situation was less effective than its equivalent in the unthreatening situation.

Question: What is the difference between hedonic and eudaimonic wellbeing?


Cooperation and Competition. Some time ago, in the garden of a friend's house, my 5-year-old son and his chum were struggling over possession of a water hose. (They were in conflict.) Each wanted to use it first to water the garden. (They had a competitive orientation.) Each was trying to tug it away from the other and both were crying. Each was very frustrated, and neither was able to use the hose to sprinkle the flowers as he'd desired. After reaching a deadlock in this tug-of-war, they began to punch one another and call each other names. (As a result of their competitive approach, the conflict took a destructive course for both of them—producing frustration, crying, and violence.) Now imagine a different scenario. The garden consists mainly of two sections, flowers and vegetables. Each kid wants to use the hose first. Let's suppose they want to resolve their conflict amicably. (They have a cooperative orientation.) One says to the other, "Let's flip a coin to see who uses the hose first." (A fair procedure for resolving the conflict is suggested.) The other agrees and suggests that the loser be given the right to select which section of the garden he waters. They both agree to the suggestion. (A cooperative, win-win agreement is reached.) Their agreements are implemented and both kids feel happy and good about one another. (These are common effects of a cooperative or constructive approach to a conflict.) As this example illustrates, whether the participants in a conflict have a cooperative orientation or a competitive one is decisive in determining its course and outcomes. This chapter is concerned with understanding the processes involved in cooperation and competition, their effects, and the factors that contribute to developing a cooperative or competitive relationship. It is important to understand the nature of cooperation and competition since almost all conflicts are mixed-motive, containing elements of both cooperation and competition.

Question: What is the difference between cooperation and competition?


Understanding Technology Adoption : Theory and Future Directions for Informal Learning. How and why individuals adopt innovations has motivated a great deal of research. This article examines individuals' computing adoption processes through the lenses of three adoption theories: Rogers's innovation diffusion theory, the Concerns-Based Adoption Model, the Technology Acceptance Model, and the United Theory of Acceptance and Use of Technology. Incorporating all three models, this article suggests technology adoption is a complex, inherently social, developmental process; individuals construct unique yet malleable perceptions of technology that influence their adoption decisions. Thus, successfully facilitating technology adoption must address cognitive, emotional, and contextual concerns. This article also focuses specific attention on adoption theory outside of a formal organization and the implications of adoption theory on informal environments. For a crime against the gods—the specifics of which are variously reported—he was condemned to an eternity at hard labor. And frustrating labor at that. For his assignment was to roll a great boulder to the top of a hill. Only every time Sisyphus, by the greatest of exertion and toil, attained the summit, the darn thing rolled back down again.

Question: What is the difference between the technology adoption model and the technology acceptance model?


A novel integrated dielectric-and-conductive ink 3D printing technique for fabrication of microwave devices. In this work a novel combination of printed electronics using conductive nanoparticle ink together with 3D printing of dielectric material is presented as one integrated process. This allows fabrication of complicated 3D electromagnetic (EM) structures such as wide range of different antennas and microwave devices to simultaneously include printing of conductive nanoparticle ink within 3D dielectric configurations. Characterization of conductive ink and polymer based substrate has been done to ensure proper RF, electric, thermal and mechanical performance of both substrate and the ink. A meander line dipole antenna on a V-shaped substrate is printed and tested to demonstrate the efficiency and accuracy of proposed technique. The goal in this paper is to provide a low cost, environmentally friendly integrated process for the fabrication of geometrically complicated 3D electromagnetic structures.

Question: What is the goal of this paper?


Beyond the Turing Test. SPRING 2016 3 Alan Turing's renowned test on intelligence, commonly known as the Turing test, is an inescapable signpost in AI. To people outside the field, the test — which hinges on the ability of machines to fool people into thinking that they (the machines) are people — is practically synonymous with the quest to create machine intelligence. Within the field, the test is widely recognized as a pioneering landmark, but also is now seen as a distraction, designed over half a century ago, and too crude to really measure intelligence. Intelligence is, after all, a multidimensional variable, and no one test could possibly ever be definitive truly to measure it. Moreover, the original test, at least in its standard implementations, has turned out to be highly gameable, arguably an exercise in deception rather than a true measure of anything especially correlated with intelligence. The much ballyhooed 2015 Turing test winner Eugene Goostman, for instance, pretends to be a thirteen-year-old foreigner and proceeds mainly by ducking questions and returning canned one-liners; it cannot see, it cannot think, and it is certainly a long way from genuine artificial general intelligence. Our hope is to see a new suite of tests, part of what we have

Question: What is the Turing test?


Complexity of vehicle routing and scheduling problems. The complexity of a class of vehicle routing and scheduling problems is investigated. We review known NP-hardness results and compile the results on the worst-case performance of approximation algorithms. Some directions for future research are suggested. The presentation is based on two discussion sessions during the Workshop to Investigate Future Directions in Routing and Scheduling of Vehicles and Crews, held at the University of Maryland at College Park, June 4-6, 1979.

Question: What is the complexity of vehicle routing and scheduling problems?


Evaluation of direct attacks to fingerprint verification systems. The vulnerabilities of fingerprint-based recognition systems to direct attacks with and without the cooperation of the user are studied. Two different systems, one minutiae-based and one ridge feature-based, are evaluated on a database of real and fake fingerprints. Based on the fingerprint images quality and on the results achieved on different operational scenarios, we obtain a number of statistically significant observations regarding the robustness of the systems.

Question: What is the minutiae-based fingerprint recognition system?


Subjective Probability : A Judgment of Representativeness. This paper explores a heuristic-representativeness-according to which the subjective probability of an event, or a sample, is determined by the degree to which it: (i) is similar in essential characteristics to its parent population; and (ii) reflects the salient features of the process by which it is generated. This heuristic is explicated in a series of empirical examples demonstrating predictable and systematic errors in the evaluation of uncertain events. In particular, since sample size does not represent any property of the population, it is expected to have little or no effect on judgment of likelihood. This prediction is confirmed in studies showing that subjective sampling distributions and posterior probability judgments are determined by the most salient characteristic of the sample (e.g., proportion, mean) without regard to the size of the sample. The present heuristic approach is contrasted with the normative (Bayesian) approach to the analysis of the judgment of uncertainty.

Question: What is the probability of a coin landing heads?


Regions, Periods, Activities: Uncovering Urban Dynamics via Cross-Modal Representation Learning. With the ever-increasing urbanization process, systematically modeling people's activities in the urban space is being recognized as a crucial socioeconomic task. This task was nearly impossible years ago due to the lack of reliable data sources, yet the emergence of geo-tagged social media (GTSM) data sheds new light on it. Recently, there have been fruitful studies on discovering geographical topics from GTSM data. However, their high computational costs and strong distributional assumptions about the latent topics hinder them from fully unleashing the power of GTSM. To bridge the gap, we present CrossMap, a novel crossmodal representation learning method that uncovers urban dynamics with massive GTSM data. CrossMap first employs an accelerated mode seeking procedure to detect spatiotemporal hotspots underlying people's activities. Those detected hotspots not only address spatiotemporal variations, but also largely alleviate the sparsity of the GTSM data. With the detected hotspots, CrossMap then jointly embeds all spatial, temporal, and textual units into the same space using two different strategies: one is reconstructionbased and the other is graph-based. Both strategies capture the correlations among the units by encoding their cooccurrence and neighborhood relationships, and learn lowdimensional representations to preserve such correlations. Our experiments demonstrate that CrossMap not only significantly outperforms state-of-the-art methods for activity recovery and classification, but also achieves much better efficiency.

Question: What is the difference between a hotspot and a cluster?


Striatal Plasticity and Basal Ganglia Circuit Function. The dorsal striatum, which consists of the caudate and putamen, is the gateway to the basal ganglia. It receives convergent excitatory afferents from cortex and thalamus and forms the origin of the direct and indirect pathways, which are distinct basal ganglia circuits involved in motor control. It is also a major site of activity-dependent synaptic plasticity. Striatal plasticity alters the transfer of information throughout basal ganglia circuits and may represent a key neural substrate for adaptive motor control and procedural memory. Here, we review current understanding of synaptic plasticity in the striatum and its role in the physiology and pathophysiology of basal ganglia function.

Question: What is the role of the striatum in motor control?


A single-layer folded substrate integrated waveguide (SIW) filter. A novel single-layer folded filter using the substrate integrated waveguide (SIW) technique is presented in this paper. A prototype at X-band for the proposed filter has been fabricated using standard printed-circuit-board (PCB) process, and is measured with a vector network analyzer (VNA). The measured results show the proposed filter has a narrow band-pass bandwidth, small insert loss and good frequency selective performances. The proposed filter has a compact size and it is suitable for designing microwave and millimeter-wave circuits.

Question: What is a single-layer folded filter?


Implementing Intelligent Traffic Control System for Congestion Control, Ambulance Clearance, and Stolen Vehicle Detection. This paper presents an intelligent traffic control system to pass emergency vehicles smoothly. Each individual vehicle is equipped with special radio frequency identification (RFID) tag (placed at a strategic location), which makes it impossible to remove or destroy. We use RFID reader, NSK EDK-125-TTL, and PIC16F877A system-on-chip to read the RFID tags attached to the vehicle. It counts number of vehicles that passes on a particular path during a specified duration. It also determines the network congestion, and hence the green light duration for that path. If the RFID-tag-read belongs to the stolen vehicle, then a message is sent using GSM SIM300 to the police control room. In addition, when an ambulance is approaching the junction, it will communicate to the traffic controller in the junction to turn ON the green light. This module uses ZigBee modules on CC2500 and PIC16F877A system-on-chip for wireless communications between the ambulance and traffic controller. The prototype was tested under different combinations of inputs in our wireless communication laboratory and experimental results were found as expected.

Question: How to implement an intelligent traffic control system for congestion control, ambulance clearance, and stolen vehicle detection?


Are image quality metrics adequate to evaluate the quality of geometric objects?. Geometric objects are often represented by many millions of triangles or polygons, which limits the ease with which they can be transmitted and displayed electronically. This has led to the development of many algorithms for simplifying geometric models, and to the recognition that metrics are required to evaluate their success. The goal is to create computer graphic renderings of the object that do not appear to be degraded to a human observer. The perceptual evaluation of simplified objects is a new topic. One approach has been to use image-based metrics to predict the perceived degradation of simplified 3-D models 1 Since that 2-D images of 3-D objects can have significantly different perceived quality, depending on the direction of the illumination, 2 2-D measures of image quality may not adequately capture the perceived quality of 3-D objects. To address this question, we conducted experiments in which we explicitly compared the perceived quality of animated 3-D objects and their corresponding 2-D still image projections. Our results suggest that 2-D judgements do not provide a good predictor of 3-D image quality, and identify a need to develop "object quality metrics."

Question: What is the difference between 2-D and 3-D?


Sexual Conflict in Human Mating. Despite interdependent reproductive fates that favor cooperation, males and females exhibit many psychological and behavioral footprints of sexually antagonistic coevolution. These include strategies of deception, sexual exploitation, and sexual infidelity as well as anti-exploitation defenses such as commitment skepticism and emotions such as sexual regret and jealousy. Sexual conflict pervades the mating arena prior to sexual consummation, after a mating relationship has formed, and in the aftermath of a breakup. It also permeates many other social relationships in forms such as daughter-guarding, conflict in opposite-sex friendships, and workplace sexual harassment. As such, sexual conflict constitutes not a narrow or occasional flashpoint but rather persistent threads that run through our intensely group-living species.

Question: What is sexual conflict?


Dynamic topic models. A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the natural parameters of the multinomial distributions that represent the topics. Variational approximations based on Kalman filters and nonparametric wavelet regression are developed to carry out approximate posterior inference over the latent topics. In addition to giving quantitative, predictive models of a sequential corpus, dynamic topic models provide a qualitative window into the contents of a large document collection. The models are demonstrated by analyzing the OCR'ed archives of the journal Science from 1880 through 2000.

Question: What is a dynamic topic model?


Efficient tracing of failed nodes in sensor networks. In sensor networks, nodes commonly rely on each other to route messages to a base station. Although this practice conserves power it can obscure the cause of a measurement outage in a portion of the network. For example, when a base station ceases to receive measurements from a region of nodes it can't immediately determine whether this is because of the destruction of all the nodes in that region (due to an enemy attack, for example) or merely the result of the failure of a few nodes bearing much of the routing load. Previous solutions to this problem typically consist of re-running the route-discovery protocol, a process that can be quite expensive in terms of the number of messages that must be exchanged. We demonstrate that the topology of the network can be efficiently conveyed to the base station allowing for the quick tracing of the identities of the failed nodes with moderate communication overhead. Our algorithms work in conjunction with the existing functions of the network, requiring the nodes to send no additional messages.

Question: How to trace the failed nodes in a sensor network?


Teaching-Learning-Based Optimization: An optimization method for continuous non-linear large scale problems. An efficient optimization method called 'Teaching–Learning-Based Optimization (TLBO)' is proposed in this paper for large scale non-linear optimization problems for finding the global solutions. The proposed method is based on the effect of the influence of a teacher on the output of learners in a class. The basic philosophy of the method is explained in detail. The effectiveness of the method is tested on many benchmark problems with different characteristics and the results are compared with other population based methods. 2011 Elsevier Inc. All rights reserved.

Question: What is the basic philosophy of the method?


Interactive Graph Cuts for Optimal Boundary and Region Segmentation of Objects in N-D Images. In this paper we describe a new technique for general purpose interactive segmentation of N-dimensional images . The user marks certain pixels as "object" or "background" to provide hard constraints for segmentation. Additional soft constraints incorporate both boundary and region information. Graph cuts are used to find the globally optimal segmentation of the N-dimensional image. The obtained solution gives the best balance of boundary and region properties among all segmentations satisfying the constraints . The topology of our segmentation is unrestricted and both "object" and "background" segments may consist of several isolated parts. Some experimental results are present ed in the context of photo/video editing and medical image segmentation. We also demonstrate an interesting Gestalt example. A fast implementation of our segmentation method is possible via a new max-flow algorithm in [2].

Question: How to segment an image?


ZooKeeper: Wait-free Coordination for Internet-scale Systems. In this paper, we describe ZooKeeper, a service for coordinating processes of distributed applications. Since ZooKeeper is part of critical infrastructure, ZooKeeper aims to provide a simple and high performance kernel for building more complex coordination primitives at the client. It incorporates elements from group messaging, shared registers, and distributed lock services in a replicated, centralized service. The interface exposed by ZooKeeper has the wait-free aspects of shared registers with an event-driven mechanism similar to cache invalidations of distributed file systems to provide a simple, yet powerful coordination service. The ZooKeeper interface enables a high-performance service implementation. In addition to the wait-free property, ZooKeeper provides a per client guarantee of FIFO execution of requests and linearizability for all requests that change the ZooKeeper state. These design decisions enable the implementation of a high performance processing pipeline with read requests being satisfied by local servers. We show for the target workloads, 2:1 to 100:1 read to write ratio, that ZooKeeper can handle tens to hundreds of thousands of transactions per second. This performance allows ZooKeeper to be used extensively by client applications.

Question: What is the ZooKeeper interface?


Accuracy of Ultrasound-Guided Genicular Nerve Block: A Cadaveric Study.. BACKGROUND Genicular nerve block has recently emerged as a novel alternative treatment in chronic knee pain. The needle placement for genicular nerve injection is made under fluoroscopic guidance with reference to bony landmarks.   OBJECTIVE To investigate the anatomic landmarks for medial genicular nerve branches and to determine the accuracy of ultrasound-guided genicular nerve block in a cadaveric model.   STUDY DESIGN Cadaveric accuracy study.   SETTING University hospital anatomy laboratory.   METHODS Ten cadaveric knee specimens without surgery or major procedures were used in the study. The anatomic location of the superior medial genicular nerve (SMGN) and the inferior medial genicular nerve (IMGN) was examined using 4 knee dissections. The determined anatomical sites of the genicular nerves in the remaining 6 knee specimens were injected with 0.5 mL red ink under ultrasound guidance. The knee specimens were subsequently dissected to assess for accuracy. If the nerve was dyed with red ink, it was considered accurate placement. All other locations were considered inaccurate.   RESULTS The course of the SMGN is that it curves around the femur shaft and passes between the adductor magnus tendon and the femoral medial epicondyle, then descends approximately one cm anterior to the adductor tubercle. The IMGN is situated horizontally around the tibial medial epicondyle and passes beneath the medial collateral ligament at the midpoint between the tibial medial epicondyle and the tibial insertion of the medial collateral ligament. The adductor tubercle for the SMGN and the medial collateral ligament for the IMGN were determined as anatomic landmarks for ultrasound. The bony cortex one cm anterior to the peak of the adductor tubercle and the bony cortex at the midpoint between the peak of the tibial medial epicondyle and the initial fibers inserting on the tibia of the medial collateral ligament

Question: What is the accuracy of ultrasound-guided genicular nerve block?


Translational Recommender Networks. Representing relationships as translations in vector space lives at the heart of many neural embedding models such as word embeddings and knowledge graph embeddings. In this work, we study the connections of this translational principle with collaborative €ltering algorithms. We propose Translational Recommender Networks (TransRec), a new aŠentive neural architecture that utilizes the translational principle to model the relationships between user and item pairs. Our model employs a neural aŠention mechanism over a Latent Relational Aˆentive Memory (LRAM) module to learn the latent relations between user-item pairs that best explains the interaction. By exploiting adaptive user-item speci€c translations in vector space, our model also alleviates the geometric inƒexibility problem of other metric learning algorithms while enabling greater modeling capability and €ne-grained €Šing of users and items in vector space. Œe proposed architecture not only demonstrates the state-of-the-art performance across multiple recommendation benchmarks but also boasts of improved interpretability. ‹alitative studies over the LRAM module shows evidence that our proposed model is able to infer and encode explicit sentiment, temporal and aŠribute information despite being only trained on implicit feedback. As such, this ascertains the ability of TransRec to uncover hidden relational structure within implicit datasets.

Question: What is the state of the art in collaborative filtering?


Fundamental analysis for visible-light communication system using LED lights. White LED offers advantageous properties such as high brightness, reliability, lower power consumption and long lifetime. White LEDs are expected to serve in the next generation of lamps. An indoor visible-light communication system utilizing white LED lights has been proposed from our laboratory. In the proposed system, these devices are used not only for illuminating rooms but also for an optical wireless communication system. Generally, plural lights are installed in our room. So, their optical path difference must be considered. In this paper, we discuss about the influence of interference and reflection. Based on numerical analyses, we show that the system is expected to be the indoor communication of the next generation.

Question: What is the optical path difference?


Bandwidth-Enhanced Low-Profile Cavity-Backed Slot Antenna by Using Hybrid SIW Cavity Modes. A bandwidth enhanced method of a low-profile substrate integrated waveguide (SIW) cavity-backed slot antenna is presented in this paper. Bandwidth enhancement is achieved by simultaneously exciting two hybrid modes in the SIW-backed cavity and merging them within the required frequency range. These two hybrid modes, whose dominant fields are located in different half parts of the SIW cavity, are two different combinations of the and resonances. This design method has been validated by experiments. Compared with those of a previously presented SIW cavity-backed slot antenna, fractional impedance bandwidth of the proposed antenna is enhanced from 1.4% to 6.3%, its gain and radiation efficiency are also slightly improved to 6.0 dBi and 90%, and its SIW cavity size is reduced about 30%. The proposed antenna exhibits low cross polarization level and high front to back ratio. It still retains advantages of low-profile, low fabrication cost, and easy integration with planar circuits.

Question: How to design a low-profile cavity-backed slot antenna?


Analysis of dynamically scheduled tile algorithms for dense linear algebra on multicore architectures. The objective of this paper is to analyze the dynamic scheduling of dense linear algebra algorithms on shared-memory, multicore architectures. Current numerical libraries, e.g., LAPACK, show clear limitations on such emerging systems mainly due to their coarse granularity tasks. Thus, many numerical algorithms need to be redesigned to better fit the architectural design of the multicore platform. The PLASMA library (Parallel Linear Algebra for Scalable Multi-core Architectures) developed at the University of Tennessee tackles this challenge by using tile algorithms to achieve a finer task granularity. These tile algorithms can then be represented by Directed Acyclic Graphs (DAGs), where nodes are the tasks and edges are the dependencies between the tasks. The paramount key to achieve high performance is to implement a runtime environment to efficiently schedule the DAG across the multicore platform. This paper studies the impact on the overall performance of some parameters, both at the level of the scheduler, e.g., window size and locality, and the algorithms, e.g., Left Looking (LL) and Right Looking (RL) variants. The conclusion of this study claims that some commonly accepted rules for dense linear algebra algorithms may need to be revisited.

Question: What is the impact of the window size and locality on the overall performance of the tile algorithms?


changepoint: An R Package for Changepoint Analysis. One of the key challenges in changepoint analysis is the ability to detect multiple changes within a given time series or sequence. The changepoint package has been developed to provide users with a choice of multiple changepoint search methods to use in conjunction with a given changepoint method and in particular provides an implementation of the recently proposed PELT algorithm. This article describes the search methods which are implemented in the package as well as some of the available test statistics whilst highlighting their application with simulated and practical examples. Particular emphasis is placed on the PELT algorithm and how results differ from the binary segmentation approach.

Question: What is a changepoint?


What Does This Imply? Examining the Impact of Implicitness on the Perception of Hate Speech.

Question: What does this imply?


Question: What is the mask r-cnn?


The New DLR Flight Dynamics Library Gertjan Looye. An overview of the new Modelica Flight Dynamics Library of the German Aerospace Center DLR is given. This library is intended for construction of multi-disciplinary flight dynamics models of rigid and flexible flight vehicles. The environment models provide the functionality to cover on-ground operations up to flight at high speeds and high altitudes. The resulting models may be used in various fields and stages of the aircraft development process, like flight control law design, as well as for real-time flight simulation.

Question: What is the new DLR Flight Dynamics Library?


ACCIDENT AVOIDANCE AND DETECTION ON HIGHWAYS. Technological approaches for detecting and monitoring fatigue levels of driver fatigue continue to emerge and many are now in the development, validation testing, or early implementation stages. Previous studies have reviewed available fatigue detection and prediction technologies and methodologies. As the name indicates this project is about advanced technologies in cars for making it more intelligent and interactive for avoiding accidents on roads. By using ARM7 this system becomes more efficient, reliable & effective. There are very less number of systems implemented on human behaviour detection in or with cars. In this paper, we describe a real-time online safety prototype that controls the vehicle speed under driver fatigue. The purpose of such a model is to advance a system to detect fatigue symptoms in drivers and control the speed of vehicle to avoid accidents. The main components of the system consist of number of real time sensors like gas, eye blink, alcohol, fuel, impact sensors and a software interface with GPS and Google Maps APIs for location.

Question: How to detect driver fatigue?


Tribeca: A Stream Database Manager for Network Traffic Analysis. High speed computer and telephone networks carry large amounts of data and signalling traffic. The engineers who build and maintain these networks use a combination of hardware and software tools to monitor the stream of network traffic. Some of these tools operate directly on the live network; others record data on magnetic tape for later offline analysis by software. Most analysis tasks require tens to hundreds of gigabytes of data. Traffic analysis applications include protocol performance analysis, conformance testing, error monitoring and fraud detection.

Question: What is a stream database manager?


Self-Attentive Feature-Level Fusion for Multimodal Emotion Detection. Multimodal emotion recognition is the task of detecting emotions present in user-generated multimedia content. Such resources contain complementary information in multiple modalities. A stiff challenge often faced is the complexity associated with feature-level fusion of these heterogeneous modes. In this paper, we propose a new feature-level fusion method based on self-attention mechanism. We also compare it with traditional fusion methods such as concatenation, outer-product, etc. Analyzed using textual and speech (audio) modalities, our results suggest that the proposed fusion method outperforms others in the context of utterance-level emotion recognition in videos.

Question: How to fuse multimodal emotion detection?


Time Expression Recognition Using a Constituent-based Tagging Scheme. Wefind from four datasets that time expressions are formed by loose structure and the words used to express time information can differentiate time expressions from common text. The findings drive us to design a learning method named TOMN to model time expressions. TOMN defines a constituent-based tagging scheme named TOMN scheme with four tags, namely T, O, M, and N, indicating the constituents of time expression, namely Time token,Modifier,Numeral, and the words Outside time expression. In modeling, TOMN assigns a word with a TOMN tag under conditional random fields with minimal features. Essentially, our constituent-based TOMN scheme overcomes the problem of inconsistent tag assignment that is caused by the conventional position-based tagging schemes (e.g., BIO scheme and BILOU scheme). Experiments show that TOMN is equally or more effective than state-of-the-art methods on various datasets, and much more robust on cross-datasets. Moreover, our analysis can explain many empirical observations in other works about time expression recognition and named entity recognition. ACM Reference Format: Xiaoshi Zhong and Erik Cambria. 2018. Time Expression Recognition Using a Constituent-based Tagging Scheme. In Proceedings of The Web Conference 2018 (WWW'18). ACM, New York, NY, USA, 10 pages. https://doi.org/10. 1145/3178876.3185997

Question: What is the time expression recognition?


Simulated annealing: Practice versus theory. Simulated annealing (SA) presents an optimization technique with several striking positive and negative features. Perhaps its most salient feature, statistically promising to deliver an optimal solution, in current practice is often spurned to use instead modified faster algorithms, "simulated quenching" (SQ). Using the author's Adaptive Simulated Annealing (ASA) code, some examples are given which demonstrate how SQ can be much faster than SA without sacrificing accuracy.

Question: What is simulated annealing?


Discovering Texture Regularity as a Higher-Order Correspondence Problem. Understanding texture regularity in real images is a challenging computer vision task. We propose a higher-order feature matching algorithm to discover the lattices of near-regular textures in real images. The underlying lattice of a near-regular texture identifies all of the texels as well as the global topology among the texels. A key contribution of this paper is to formulate lattice-finding as a correspondence problem. The algorithm finds a plausible lattice by iteratively proposing texels and assigning neighbors between the texels. Our matching algorithm seeks assignments that maximize both pair-wise visual similarity and higher-order geometric consistency. We approximate the optimal assignment using a recently developed spectral method. We successfully discover the lattices of a diverse set of unsegmented, real-world textures with significant geometric warping and large appearance variation among

Question: What is a higher-order correspondence problem?


User Acceptance of Hedonic Information Technologies: A Perceived Value Perspective. Hedonic information technologies do not focus on productivity-oriented applications, but rather, on lifestyle-augmentation and entertainment. As such users of hedonic IT are provided with benefits related to general enjoyment as opposed to gains in organizational efficiency. The main purpose of this study is to investigate this burgeoning phenomenon by measuring several value drivers for downloading mobile phone ringtones. Hypothesis testing was performed with PLS techniques applied to data collected from 119 ringtone users. Results confirmed that the overall value of hedonic IT is a third-order construct, which successfully predicted behavioral usage intentions and positive word of mouth.

Question: What is the purpose of this study?


Message-Locked Encryption for Lock-Dependent Messages. Motivated by the problem of avoiding duplication in storage systems, Bellare, Keelveedhi, and Ristenpart have recently put forward the notion of Message-Locked Encryption (MLE) schemes which subsumes convergent encryption and its variants. Such schemes do not rely on permanent secret keys, but rather encrypt messages using keys derived from the messages themselves. We strengthen the notions of security proposed by Bellare et al. by considering plaintext distributions that may depend on the public parameters of the schemes. We refer to such inputs as lock-dependent messages. We construct two schemes that satisfy our new notions of security for message-locked encryption with lock-dependent messages. Our main construction deviates from the approach of Bellare et al. by avoiding the use of ciphertext components derived deterministically from the messages. We design a fully randomized scheme that supports an equality-testing algorithm defined on the ciphertexts. Our second construction has a deterministic ciphertext component that enables more efficient equality testing. Security for lock-dependent messages still holds under computational assumptions on the message distributions produced by the attacker. In both of our schemes the overhead in the length of the ciphertext is only additive and independent of the message length.

Question: What is the difference between a message-locked encryption scheme and a convergent encryption scheme?


Point cloud labeling using 3D Convolutional Neural Network. In this paper, we tackle the labeling problem for 3D point clouds. We introduce a 3D point cloud labeling scheme based on 3D Convolutional Neural Network. Our approach minimizes the prior knowledge of the labeling problem and does not require a segmentation step or hand-crafted features as most previous approaches did. Particularly, we present solutions for large data handling during the training and testing process. Experiments performed on the urban point cloud dataset containing 7 categories of objects show the robustness of our approach.

Question: What is the 3D point cloud labeling scheme based on 3D Convolutional Neural Network?


Driver Drowsiness Detection System. Sleepiness or fatigue in drivers driving for long hours is the major cause of accidents on highways worldwide. The International statistics shows that a large number of road accidents are caused by driver fatigue. Therefore, a system that can detect oncoming driver fatigue and issue timely warning could help in preventing many accidents, and consequently save money and reduce personal suffering. The authors have made an attempt to design a system that uses video camera that points directly towards the driver"s face in order to detect fatigue. If the fatigue is detected a warning signal is issued to alert the driver. The authors have worked on the video files recorded by the camera. Video file is converted into frames.Once the eyes are located from each frame, by determining the energy value of each frame one can determine whether the eyes are open or close. A particular condition is set for the energy values of open and close eyes. If the average of the energy value for 5 consecutive frames falls in a given condition then the driver will be detected as drowsy and issues a warning signal. The algorithm is proposed, implemented, tested, and found working satisfactorily.

Question: How to detect drowsiness in drivers?


Restructuring speech representations using a pitch-adaptive time-frequency smoothing and an instantaneous-frequency-based F0 extraction: Possible role of a repetitive structure in sounds. A set of simple new procedures has been developed to enable the real-time manipulation of speech parameters. The proposed method uses pitch-adaptive spectral analysis combined with a surface reconstruction method in the time± frequency region. The method also consists of a fundamental frequency (F0) extraction using instantaneous frequency calculation based on a new concept called `fundamentalness'. The proposed procedures preserve the details of time± frequency surfaces while almost perfectly removing ®ne structures due to signal periodicity. This close-to-perfect elimination of interferences and smooth F0 trajectory allow for over 600% manipulation of such speech parameters as pitch, vocal tract length, and speaking rate, while maintaining high reproductive quality. Ó 1999 Elsevier Science B.V. All rights reserved.

Question: How to extract the F0 from a speech signal?


Pravastatin in elderly individuals at risk of vascular disease (PROSPER): a randomised controlled trial. BACKGROUND Although statins reduce coronary and cerebrovascular morbidity and mortality in middle-aged individuals, their efficacy and safety in elderly people is not fully established. Our aim was to test the benefits of pravastatin treatment in an elderly cohort of men and women with, or at high risk of developing, cardiovascular disease and stroke.   METHODS We did a randomised controlled trial in which we assigned 5804 men (n=2804) and women (n=3000) aged 70-82 years with a history of, or risk factors for, vascular disease to pravastatin (40 mg per day; n=2891) or placebo (n=2913). Baseline cholesterol concentrations ranged from 4.0 mmol/L to 9.0 mmol/L. Follow-up was 3.2 years on average and our primary endpoint was a composite of coronary death, non-fatal myocardial infarction, and fatal or non-fatal stroke. Analysis was by intention-to-treat.   FINDINGS Pravastatin lowered LDL cholesterol concentrations by 34% and reduced the incidence of the primary endpoint to 408 events compared with 473 on placebo (hazard ratio 0.85, 95% CI 0.74-0.97, p=0.014). Coronary heart disease death and non-fatal myocardial infarction risk was also reduced (0.81, 0.69-0.94, p=0.006). Stroke risk was unaffected (1.03, 0.81-1.31, p=0.8), but the hazard ratio for transient ischaemic attack was 0.75 (0.55-1.00, p=0.051). New cancer diagnoses were more frequent on pravastatin than on placebo (1.25, 1.04-1.51, p=0.020). However, incorporation of this finding in a meta-analysis of all pravastatin and all statin trials showed no overall increase in risk. Mortality from coronary disease fell by 24% (p=0.043) in the pravastatin group. Pravastatin had no significant effect on cognitive function or disability.   INTERPRETATION Pravastatin given for 3 years reduced the risk of coronary disease in elderly individuals. PROSPER therefore extends to elderly individuals the treatment strategy cur

Question: What is the effect of pravastatin on elderly individuals?


A viability theory for digital businesses: Exploring the evolutionary changes of revenue mechanisms to support managerial decisions. The ongoing integration of Information Technology (IT) into various areas of our lives has led to a plethora of digital products and services. To survive competition in the long run, these offerings not only have to keep up with constant technological developments, but also have to adapt from a business point of view. Managers of these digital businesses have to especially focus on the design and evolution of their business' revenue mechanisms to ensure the viability of their offerings. The related decisions are not trivial, as managers have to be aware of the relevant contextual factors and have to react quickly to changes in the environment. This paper proposes a viability theory for digital businesses described by 17 propositions that may guide managers in the design of revenue mechanisms and thereby support the evolution as well as the viability of a digital business.

Question: What is a viability theory for digital businesses?


Perspectives and Visions of Computer Science Education in Primary and Secondary (K-12) Schools. In view of the recent developments in many countries, for example, in the USA and in the UK, it appears that computer science education (CSE) in primary or secondary schools (K-12) has reached a significant turning point, shifting its focus from ICT-oriented to rigorous computer science concepts. The goal of this special issue is to offer a publication platform for soundly based in-depth experiences that have been made around the world with concepts, approaches, or initiatives that aim at supporting this shift. For this purpose, the article format was kept as large as possible, enabling the authors to explain many facets of their concepts and experiences in detail. Regarding the structure of the articles, we had encouraged the authors to lean on the Darmstadt Model, a category system that was developed to support the development, improvement, and investigation of K-12 CSE across regional or national boundaries. This model could serve as a unifying framework that might provide a proper structure for a well-founded critical discussion about the future of K-12 CSE. Curriculum designers or policy stakeholders, who have to decide, which approach an upcoming national initiative should follow, could benefit from this discussion as well as researchers who are investigating K12 CSE in any regard. With this goal in mind, we have selected six extensive and two short case studies from the UK, New Zealand, USA/Israel, France, Sweden, Georgia (USA), Russia, and Italy that provide an in-depth analysis of K-12 CSE in their respective country or state.

Question: What is the difference between a curriculum and a curriculum framework?


Parsing as Language Modeling. We recast syntactic parsing as a language modeling problem and use recent advances in neural network language modeling to achieve a new state of the art for constituency Penn Treebank parsing — 93.8 F1 on section 23, using 2-21 as training, 24 as development, plus tri-training. When trees are converted to Stanford dependencies, UAS and LAS are 95.9% and 94.1%.

Question: What is the state of the art for constituency parsing?


Design And Application Guide For High Speed MOSFET Gate Drive Circuits By. The main purpose of this paper is to demonstrate a systematic approach to design high performance gate drive circuits for high speed switching applications. It is an informative collection of topics offering a "one-stop-shopping" to solve the most common design challenges. Thus it should be of interest to power electronics engineers at all levels of experience. The most popular circuit solutions and their performance are analyzed, including the effect of parasitic components, transient and extreme operating conditions. The discussion builds from simple to more complex problems starting with an overview of MOSFET technology and switching operation. Design procedure for ground referenced and high side gate drive circuits, AC coupled and transformer isolated solutions are described in great details. A special chapter deals with the gate drive requirements of the MOSFETs in synchronous rectifier applications. Several, step-by-step numerical design examples complement the paper.

Question: What is the purpose of this paper?


Stakeholder Identification in the Requirements Engineering Process. Adequate, timely and effective consultation of relevant stakeholders is of paramount importance in the requirements engineering process. However, the thorny issue of making sure that all relevant stakeholders are consulted has received less attention than other areas which depend on it, such as scenario-based requirements, involving users in development, negotiating between different viewpoints and so on. The literature suggests examples of stakeholders, and categories of stakeholder, but does not provide help in identifying stakeholders for a specific system. In this paper, we discuss current work in stakeholder identification, propose an approach to identifying relevant stakeholders for a specific system, and propose future directions for the work. 1. What is a ÔstakeholderÕ? There is a large body of literature in the strategic management area which discusses organisations in terms of a stakeholder model. Stakeholder analysis, it is claimed, can be used to analyse an organisationÕs performance and determine its future strategic direction. An oft-quoted definition of ÔstakeholderÕ, taken from a key reference in this literature is: ÔA stakeholder in an organisation is (by definition) any group or individual who can affect or is affected by the achievement of the organisationÕs objectives.Õ [10] A much broader definition, which has also been attributed to Freeman, is that a stakeholder is Ôanything influencing or influenced byÕ the firm, but it has been claimed that this definition is problematic because it leads to the identification of a very broad set of stakeholders. It is important to distinguish between influencers and stakeholders because while some potential stakeholders may indeed be both stakeholders and influencers, some who have a real stake in an enterprise may have no influence, e.g. a job applicant, while some influencers may have no stake, e.g. the media [8]. Information systems (IS)

Question: What is a stakeholder?


Pilot Contamination and Precoding in Multi-Cell TDD Systems. This paper considers a multi-cell multiple antenna system with precoding used at the base stations for downlink transmission. Channel state information (CSI) is essential for precoding at the base stations. An effective technique for obtaining this CSI is time-division duplex (TDD) operation where uplink training in conjunction with reciprocity simultaneously provides the base stations with downlink as well as uplink channel estimates. This paper mathematically characterizes the impact that uplink training has on the performance of such multi-cell multiple antenna systems. When non-orthogonal training sequences are used for uplink training, the paper shows that the precoding matrix used by the base station in one cell becomes corrupted by the channel between that base station and the users in other cells in an undesirable manner. This paper analyzes this fundamental problem of pilot contamination in multi-cell systems. Furthermore, it develops a new multi-cell MMSE-based precoding method that mitigates this problem. In addition to being linear, this precoding method has a simple closed-form expression that results from an intuitive optimization. Numerical results show significant performance gains compared to certain popular single-cell precoding methods.

Question: How does pilot contamination affect the performance of multi-cell TDD systems?


Elliptic Curve Multiset Hash. A homomorphic, or incremental, multiset hash function, associates a hash value to arbitrary collections of objects (with possible repetitions) in such a way that the hash of the union of two collections is easy to compute from the hashes of the two collections themselves: it is simply their sum under a suitable group operation. In particular, hash values of large collections can be computed incrementally and/or in parallel. Homomorphic hashing is thus a very useful primitive with applications ranging from database integrity verification to streaming set/multiset comparison and network coding. Unfortunately, constructions of homomorphic hash functions in the literature are hampered by two main drawbacks: they tend to be much longer than usual hash functions at the same security level (e.g. to achieve a collision resistance of 2, they are several thousand bits long, as opposed to 256 bits for usual hash functions), and they are also quite slow. In this paper, we introduce the Elliptic Curve Multiset Hash (ECMH), which combines a usual bit string-valued hash function like BLAKE2 with an efficient encoding into binary elliptic curves to overcome both difficulties. On the one hand, the size of ECMH digests is essentially optimal: 2m-bit hash values provideO(2) collision resistance. On the other hand, we demonstrate a highly-efficient software implementation of ECMH, which our thorough empirical evaluation shows to be capable of processing over 3 million set elements per second on a 4 GHz Intel Haswell machine at the 128-bit security level— many times faster than previous practical methods. While incremental hashing based on elliptic curves has been considered previously [1], the proposed method was less efficient, susceptible to timing attacks, and potentially patent-encumbered [2], and no practical implementation was demonstrated.

Question: What is a homomorphic hash function?


Two-Stream Neural Networks for Tampered Face Detection. We propose a two-stream network for face tampering detection. We train GoogLeNet to detect tampering artifacts in a face classification stream, and train a patch based triplet network to leverage features capturing local noise residuals and camera characteristics as a second stream. In addition, we use two different online face swaping applications to create a new dataset that consists of 2010 tampered images, each of which contains a tampered face. We evaluate the proposed two-stream network on our newly collected dataset. Experimental results demonstrate the effectness of our method.

Question: How to detect tampered faces?


Design of an endoluminal NOTES robotic system. Natural orifice transluminal endoscopic surgery, or NOTES, allows for exceedingly minimally invasive surgery but has high requirements for the dexterity and force capabilities of the tools. An overview of the ViaCath System is presented. This system is a first generation teleoperated robot for endoluminal surgery and consists of a master console with haptic interfaces, slave drive mechanisms, and 6 degree-of-freedom, long-shafted flexible instruments that run alongside a standard gastroscope or colonoscope. The system was validated through animal studies. It was discovered that the devices were difficult to introduce into the GI tract and manipulation forces were insufficient. The design of a second generation system is outlined with improvements to the instrument articulation section and a steerable overtube. Results of basic evaluation tests performed on the tools are also presented.

Question: What is the design of an endoluminal NOTES robotic system?


Semantic image retrieval system based on object relationships. Semantic-based image retrieval has recently become popular as an avenue to improve retrieval accuracy. The "semantic gap" between the visual features and the high-level semantic features could be narrowed down by utilizing this kind of retrieval method. However, most of the current methods of semantic-based image retrieval utilize visual semantic features and do not consider spatial relationships. We build a system for content-based image retrieval from image collections on the web and tackle the challenges of distinguishing between images that contain similar objects, in order to capture the semantic meaning of a search query. In order to do so, we utilize a combination of segmentation into objects as well as the relationships of these objects with each other.

Question: What is the semantic gap?


Impossibility of Distributed Consensus with One Faulty Process. The consensus problem involves an asynchronous system of processes, some of which may be unreliable. The problem is for the reliable processes to agree on a binary value. In this paper, it is shown that every protocol for this problem has the possibility of nontermination, even with only one faulty process. By way of contrast, solutions are known for the synchronous case, the "Byzantine Generals" problem.

Question: What is the Byzantine Generals problem?


A path decomposition approach for computing blocking probabilities in wavelength-routing networks. We study a class of circuit-switched wavelength-routing networks with fixed or alternate routing and with random wavelength allocation. We present an iterative path decomposition algorithm to evaluate accurately and efficiently the blocking performance of such networks with and without wavelength converters. Our iterative algorithm analyzes the original network by decomposing it into single-path subsystems. These subsystems are analyzed in isolation, and the individual results are appropriately combined to obtain a solution for the overall network. To analyze individual subsystems, we first construct an exact Markov process that captures the behavior of a path in terms of wavelength use. We also obtain an approximate Markov process which has a closed-form solution that can be computed efficiently for short paths. We then develop an iterative algorithm to analyze approximately arbitrarily long paths. The path decomposition approach naturally captures the correlation of both link loads and link blocking events. Our algorithm represents a simple and computationally efficient solution to the difficult problem of computing call-blocking probabilities in wavelength-routing networks. We also demonstrate how our analytical techniques can be applied to gain insight into the problem of converter placement in wavelength-routing networks.

Question: What is the path decomposition approach for computing blocking probabilities in wavelength-routing networks?


Using BabelNet to Improve OOV Coverage in SMT. Out-of-vocabulary words (OOVs) are a ubiquitous and difficult problem in statistical machine translation (SMT). This paper studies different strategies of using BabelNet to alleviate the negative impact brought about by OOVs. BabelNet is a multilingual encyclopedic dictionary and a semantic network, which not only includes lexicographic and encyclopedic terms, but connects concepts and named entities in a very large network of semantic relations. By taking advantage of the knowledge in BabelNet, three different methods – using direct training data, domain-adaptation techniques and the BabelNet API – are proposed in this paper to obtain translations for OOVs to improve system performance. Experimental results on English–Polish and English–Chinese language pairs show that domain adaptation can better utilize BabelNet knowledge and performs better than other methods. The results also demonstrate that BabelNet is a really useful tool for improving translation performance of SMT systems.

Question: How to use BabelNet to improve OOV coverage in SMT?


CBSA: content-based soft annotation for multimodal image retrieval using Bayes point machines. We propose a content-based soft annotation (CBSA) procedure for providing images with semantical labels. The annotation procedure starts with labeling a small set of training images, each with one single semantical label (e.g., forest, animal, or sky). An ensemble of binary classifiers is then trained for predicting label membership for images. The trained ensemble is applied to each individual image to give the image multiple soft labels, and each label is associated with a label membership factor. To select a base binary-classifier for CBSA, we experiment with two learning methods, Support Vector Machines (SVMs) and Bayes Point Machines (BPMs, and compare their class-prediction accuracy. Our empirical study on a 116-category 25K-image set shows that the BPM-based ensemble provides better annotation quality than the SVM-based ensemble for supporting multimodal image retrievals.

Question: What is the content-based soft annotation procedure?


Animal-inspired design and aerodynamic stabilization of a hexapedal millirobot. The VelociRoACH is a 10 cm long, 30 gram hexapedal millirobot capable of running at 2.7 m/s, making it the fastest legged robot built to date, relative to scale. We present the design by dynamic similarity technique and the locomotion adaptations which have allowed for this highly dynamic performance. In addition, we demonstrate that rotational dynamics become critical for stability as the scale of a robotic system is reduced. We present a new method of experimental dynamic tuning for legged millirobots, aimed at finding stable limit cycles with minimal rotational energy. By implementing an aerodynamic rotational damper, we further reduced the rotational energy in the system, and demonstrated that stable limit cycles with lower rotational energy are more robust to disturbances. This method increased the stability of the system without detracting from forward speed.

Question: What is the fastest legged robot?


Logic BIST for large industrial designs: real issues and case studies. to Abstract This paper discusses practical issues involved in app ing logic built-in self-test (BIST) to four large industria designs. These multi-clock designs, ranging in size fr 200K to 800K gates, pose significant challenges to log BIST methodology, flow, and tools. The paper presents process of generating a BIST-compliant core along with t logic BIST controller for at-speed testing. Comparativ data on fault grades and area overhead between autom test pattern generation (ATPG) and logic BIST a reported. The experimental results demonstrate that w automation of the proposed solutions, logic BIST c achieve test quality approaching that of ATPG with min mal area overhead and few changes to the design flow.

Question: What is the area overhead of logic BIST?


Cross-Modal Multistep Fusion Network With Co-Attention for Visual Question Answering. Visual question answering (VQA) is receiving increasing attention from researchers in both the computer vision and natural language processing fields. There are two key components in the VQA task: feature extraction and multi-modal fusion. For feature extraction, we introduce a novel co-attention scheme by combining Sentence-guide Word Attention (SWA) and Question-guide Image Attention in a unified framework. To be specific, the textual attention SWA relies on the semantics of the whole question sentence to calculate contributions of different question words for text representation. For the multi-modal fusion, we propose a "Cross-modal Multistep Fusion (CMF)" network to generate multistep features and achieve multiple interactions for two modalities, rather than focusing on modeling complex interactions between two modals like most current feature fusion methods. To avoid the linear increase of the computational cost, we share the parameters for each step in the CMF. Extensive experiments demonstrate that the proposed method can achieve competitive or better performance than the state of the art.

Question: What is the difference between the visual question answering and visual question answering?


Dual-Transfer Face Sketch–Photo Synthesis. Recognizing the identity of a sketched face from a face photograph dataset is a critical yet challenging task in many applications, not least law enforcement and criminal investigations. An intelligent sketched face identification system would rely on automatic face sketch synthesis from photographs, thereby avoiding the cost of artists manually drawing sketches. However, conventional face sketch–photo synthesis methods tend to generate sketches that are consistent with the artists'drawing styles. Identity-specific information is often overlooked, leading to unsatisfactory identity verification and recognition performance. In this paper, we discuss the reasons why conventional methods fail to recover identity-specific information. Then, we propose a novel dual-transfer face sketch–photo synthesis framework composed of an inter-domain transfer process and an intra-domain transfer process. In the inter-domain transfer, a regressor of the test photograph with respect to the training photographs is learned and transferred to the sketch domain, ensuring the recovery of common facial structures during synthesis. In the intra-domain transfer, a mapping characterizing the relationship between photographs and sketches is learned and transferred across different identities, such that the loss of identity-specific information is suppressed during synthesis. The fusion of information recovered by the two processes is straightforward by virtue of an ad hoc information splitting strategy. We employ both linear and nonlinear formulations to instantiate the proposed framework. Experiments on The Chinese University of Hong Kong face sketch database demonstrate that compared to the current state-of-the-art the proposed framework produces more identifiable facial structures and yields higher face recognition performance in both the photo and sketch domains.

Question: How to synthesize a face sketch from a face photograph?


Guided-wave and leakage characteristics of substrate integrated waveguide. The substrate integrated waveguide (SIW) technique makes it possible that a complete circuit including planar circuitry, transitions, and rectangular waveguides are fabricated in planar form using a standard printed circuit board or other planar processing techniques. In this paper, guided wave and modes characteristics of such an SIW periodic structure are studied in detail for the first time. A numerical multimode calibration procedure is proposed and developed with a commercial software package on the basis of a full-wave finite-element method for the accurate extraction of complex propagation constants of the SIW structure. Two different lengths of the SIW are numerically simulated under multimode excitation. By means of our proposed technique, the complex propagation constant of each SIW mode can accurately be extracted and the electromagnetic bandstop phenomena of periodic structures are also investigated. Experiments are made to validate our proposed technique. Simple design rules are provided and discussed.

Question: What is the guided wave and leakage characteristics of substrate integrated waveguide?


Simulator sickness in virtual display gaming: a comparison of stereoscopic and non-stereoscopic situations. In this paper we compare simulator sickness symptoms produced by racing game in three different conditions. In the first experiment the participants played the Need for Speed car racing game with an ordinary 17" display and in the second and third experiments they used a head-worn virtual display for the game playing. The difference between experiments 2 and 3 was in the use of stereoscopy, as in the third experiment the car racing game was seen in stereoscopic three-dimensions. Our results indicated that there were no significant differences in sickness symptoms when we compared the ordinary display and the virtual display in non-stereoscopic mode. In stereoscopic condition the eye strain and disorientation symptoms were significantly elevated compared to the ordinary display. We conclude that using a virtual display as an accessory in a mobile device is a viable alternative, because the non-stereoscopic virtual display did not produce significantly more sickness symptoms compared to ordinary game playing.

Question: What is the difference between stereoscopic and non-stereoscopic virtual display gaming?


The NASD Securities Observation , News Analysis & Regulation System ( SONAR ). The Securities Observation, News Analysis, and Regulation (SONAR) system was developed by NASD to monitor the Nasdaq, Over the Counter (OTC), and Nasdaq-Liffe (futures) stock markets for potential insider trading and fraud through misrepresentation. SONAR has been in operational use at NASD since December 2001, processing approximately 10,000 news wires stories and SEC filings, evaluating price/volume models for 25,000 securities, and generating 50-60 alerts (or "breaks") per day for review by several groups of regulatory analysts and investigators. In addition, SONAR has greatly expanded surveillance coverage to new areas of the market and increased accuracy significantly over an earlier break detection system. SONAR makes use of several AI and statistical techniques, including NLP text mining, statistical regression, rule-based inference, uncertainty, and fuzzy matching. Sonar combines these enabling technologies in a system designed to deliver a steady stream of high-quality breaks to the analysts for further investigation. Additional components including visualization, text search agents, and flexible displays add to the system's utility. Finally, SONAR is designed as a knowledge-based system. Domain knowledge is maintained by knowledge engineers working closely with the regulatory analysts. In this way, SONAR is adaptable to new market conditions, data sources, and regulatory concerns.

Question: What is the NASD Securities Observation, News Analysis & Regulation System (SONAR)?


MOBA: a New Arena for Game AI. Games have always been popular testbeds for Artificial Intelligence (AI). In the last decade, we have seen the rise of the Multiple Online Battle Arena (MOBA) games, which are the most played games nowadays. In spite of this, there are few works that explore MOBA as a testbed for AI Research. In this paper we present and discuss the main features and opportunities offered by MOBA games to Game AI Research. We describe the various challenges faced along the game and also propose a discrete model that can be used to better understand and explore the game. With this, we aim to encourage the use of MOBA as a novel research platform for Game AI.

Question: What is a MOBA?


Beyond data warehousing: what's next in business intelligence?. During the last ten years the approach to business management has deeply changed, and companies have understood the importance of enforcing achievement of the goals defined by their strategy through metrics-driven management. The DW process, though supporting bottom-up extraction of information from data, fails in top-down enforcing the company strategy. A new approach to BI, called Business Performance Management (BPM), is emerging from this framework: it includes DW but it also requires a reactive component capable of monitoring the time-critical operational processes to allow tactical and operational decision-makers to tune their actions according to the company strategy. The aim of this paper is to encourage the research community to acknowledge the coming of a second era in BI, to propose a general architecture for BPM, and to lay the premises for investigating the most challenging of the related issues.

Question: What is the difference between business intelligence and business performance management?


A Spiking Neural Network Based Cortex-Like Mechanism and Application to Facial Expression Recognition. In this paper, we present a quantitative, highly structured cortex-simulated model, which can be simply described as feedforward, hierarchical simulation of ventral stream of visual cortex using biologically plausible, computationally convenient spiking neural network system. The motivation comes directly from recent pioneering works on detailed functional decomposition analysis of the feedforward pathway of the ventral stream of visual cortex and developments on artificial spiking neural networks (SNNs). By combining the logical structure of the cortical hierarchy and computing power of the spiking neuron model, a practical framework has been presented. As a proof of principle, we demonstrate our system on several facial expression recognition tasks. The proposed cortical-like feedforward hierarchy framework has the merit of capability of dealing with complicated pattern recognition problems, suggesting that, by combining the cognitive models with modern neurocomputational approaches, the neurosystematic approach to the study of cortex-like mechanism has the potential to extend our knowledge of brain mechanisms underlying the cognitive analysis and to advance theoretical models of how we recognize face or, more specifically, perceive other people's facial expression in a rich, dynamic, and complex environment, providing a new starting point for improved models of visual cortex-like mechanism.

Question: What is a spiking neural network?


An Approach for Factory-Wide Control Utilizing Virtual Metrology. In the semiconductor manufacturing industry, market demands and technology trends drive manufacturers towards increases in wafer size and decreases in device size. Application of factory-wide advanced process control (APC) techniques down to the wafer-to-wafer (W2W) level control capability is becoming the only choice to cope with the demanding situation. However, one of the main limitations in undertaking W2W control is the nonavailability of timely metrology data at the wafer level. Recently virtual metrology (VM) techniques have been proposed to provide timely wafer level metrology data; they have the potential to be used in realizing W2W control. In this paper, the VM approach to W2W control on factory level is described. VM for an individual process is realized by utilizing the preprocess metrology and the process data from the underlying tools that is generally collected in real time for fault detection purposes. The VM implementation for factory-wide run-to-run control brings unique opportunities and issues to the forefront such as dealing with expected lower quality of VM data, coordination between VM modules of cascading processes for better prediction quality, flexibility of the factory-wide controller to accommodate lower quality VM data, dynamic adjustments to the target values of individual processes by the factory-wide controller when using VM data, and dealing with metrology delays at the factory level. Near and long-term solutions are presented to address these issues in order to allow VM to be used today and become an integral part of the factory-wide APC solution for W2W control.

Question: What is virtual metrology?


Common method biases in behavioral research: a critical review of the literature and recommended remedies.. Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.

Question: How to control for method biases in behavioral research?