Textual Spatial Cosine Similarity. When dealing with document similarity many methods exist today, like cosine similarity. More complex methods are also available based on the semantic analysis of textual information, which are computationally expensive and rarely used in the real time feeding of content as in enterprisewide search environments. To address these real-time constraints, we developed a new measure of document similarity called Textual Spatial Cosine Similarity, which is able to detect similitude at the semantic level using word placement information contained in the document. We will see in this paper that two degenerate cases exist for this model, which coincide with Cosine Similarity on one side and with a paraphrasing detection model to the other.

Question: What is the difference between cosine similarity and textual spatial cosine similarity?


Parameterized Pattern Matching: Algorithms and Applications. The problem of finding sections of code that either are identical or are related by the systematic renaming of variables or constants can be modeled in terms of parameterized strings ( p-strings) and parameterized matches ( p-matches). P-strings are strings over two alphabets, one of which represents parameters. Two p-strings are a parameterized match ( p-match) if one p-string is obtained by renaming the parameters of the other by a one-to-one function. In this paper, we investigate parameterized pattern matching via parameterized suffix trees (p-suffix trees). We give two algorithms for constructing p-suffix trees: one (eager) that runs in linear time for fixed alphabets, and another that uses auxiliary data structures and runs in O(n log(n)) time for variable alphabets, where n is input length. We show that using a p-suffix tree for a pattern p-string P, it is possible to search for all p-matches of P within a text p-string T in space linear in |P| and time linear in |T | for fixed alphabets, or O( |T | log(min( |P|, _)) time and O( |P|) space for variable alphabets, where _ is the sum of the alphabet sizes. The simpler p-suffix tree construction algorithm eager has been implemented, and experiments show it to be practical. Since it runs faster than predicted by the above worst-case bound, we reanalyze the algorithm and show that eager runs in time O(min(t |S |+m(t, S) | t>0) log _)), where for an input p-string S, m(t, S) is the number of maximal p-matches of length at least t that occur within S, and _ is the sum of the alphabet sizes. Experiments with the author's program dup (B. Baker, in ``Comput. Sci. Statist.,'' Vol. 24, 1992) for finding all maximal p-matches within a p-string have found m(t, S) to be less than |S | in practice unless t is small. ] 1996 Academic Press, Inc.

Question: What is the author's name?


Transfer Learning Improves Supervised Image Segmentation Across Imaging Protocols. The variation between images obtained with different scanners or different imaging protocols presents a major challenge in automatic segmentation of biomedical images. This variation especially hampers the application of otherwise successful supervised-learning techniques which, in order to perform well, often require a large amount of labeled training data that is exactly representative of the target data. We therefore propose to use transfer learning for image segmentation. Transfer-learning techniques can cope with differences in distributions between training and target data, and therefore may improve performance over supervised learning for segmentation across scanners and scan protocols. We present four transfer classifiers that can train a classification scheme with only a small amount of representative training data, in addition to a larger amount of other training data with slightly different characteristics. The performance of the four transfer classifiers was compared to that of standard supervised classification on two magnetic resonance imaging brain-segmentation tasks with multi-site data: white matter, gray matter, and cerebrospinal fluid segmentation; and white-matter-/MS-lesion segmentation. The experiments showed that when there is only a small amount of representative training data available, transfer learning can greatly outperform common supervised-learning approaches, minimizing classification errors by up to 60%.

Question: What is transfer learning?


Business intelligence and analytics: From big data to big impact.

Question: What is business intelligence and analytics?


Jerk-bounded manipulator trajectory planning: design for real-time applications. An online method for obtaining smooth, jerk-bounded trajectories has been developed and implemented. Jerk limitation is important in industrial robot applications, since it results in improved path tracking and reduced wear on the robot. The method described herein uses a concatenation of fifth-order polynomials to provide a smooth trajectory between two way points. The trajectory approximates a linear segment with parabolic blends trajectory. A sine wave template is used to calculate the end conditions (control points) for ramps from zero acceleration to nonzero acceleration. Joining these control points with quintic polynomials results in a controlled quintic trajectory that does not oscillate, and is near time optimal for the jerk and acceleration limits specified. The method requires only the computation of the quintic control points, up to a maximum of eight points per trajectory way point. This provides hard bounds for online motion algorithm computation time. A method for blending these straight-line trajectories over a series of way points is also discussed. Simulations and experimental results on an industrial robot are presented.

Question: How to design a robot trajectory?


A Systematic Literature Review: Code Bad Smells in Java Source Code. Code smell is an indication of a software designing problem. The presence of code smells can have a severe impact on the software quality. Smells basically refers to the structure of the code which violates few of the design principals and so has negative effect on the quality of the software. Larger the source code, more is its presence. Software needs to be reliable, robust and easily maintainable so that it can minimize the cost of its development as well as maintenance. Smells may increase the chances of failure of the system during maintenance. A SLR has been performed based on the search of digital libraries that includes the publications since 1999 to 2016. 60 research papers are deeply analyzed that are most relevant. The objective of this paper is to provide an extensive overview of existing research in the field of bad smells, identify the detection techniques and correlation between the detection techniques, in addition to find the name of the code smells that need more attention in detection approaches. This SLR identified that code clone (code smell) receives most research attention. Our findings also show that very few papers report on the impact of code bad smells. Most of the papers focused on the detection techniques and tools. A significant correlation between detection techniques has been calculated. There are four code smells that are not yet detected are Primitive Obsession, Inappropriate Intimacy, Incomplete library class and Comments.

Question: What is a systematic literature review?


Indian Sign Language gesture classification as single or double handed gestures. The development of a sign language recognition system can have a great impact on the daily lives of humans with hearing disabilities. Recognizing gestures from the Indian Sign Language (ISL) with a camera can be difficult due to complexity of various gestures. The motivation behind the paper is to develop an approach to successfully classify gestures in the ISL under ambiguous conditions from static images. A novel approach involving the decomposition of gestures into single handed or double handed gesture has been presented in this paper. Classifying gesture into these subcategories simplifies the process of gesture recognition in the ISL due to presence of lesser number of gestures in each subcategory. Various approaches making use of Histogram of Gradients (HOG) features and geometric descriptors using KNN and SVM classifiers were tried on a dataset consisting of images of all 26 English alphabets present in the ISL under variable background. HOG features when classified with Support Vector Machine were found to be the most efficient approach resulting in an accuracy of 94.23%.

Question: How to classify gestures in the Indian Sign Language?


A Communication-Optimal Framework for Contracting Distributed Tensors. Tensor contractions are extremely compute intensive generalized matrix multiplication operations encountered in many computational science fields, such as quantum chemistry and nuclear physics. Unlike distributed matrix multiplication, which has been extensively studied, limited work has been done in understanding distributed tensor contractions. In this paper, we characterize distributed tensor contraction algorithms on torus networks. We develop a framework with three fundamental communication operators to generate communication-efficient contraction algorithms for arbitrary tensor contractions. We show that for a given amount of memory per processor, the framework is communication optimal for all tensor contractions. We demonstrate performance and scalability of the framework on up to 262,144 cores on a Blue Gene/Q supercomputer.

Question: What is a tensor contraction?


End-to-End Sound Source Separation Conditioned On Instrument Labels. Can we perform an end-to-end sound source separation (SSS) with a variable number of sources using a deep learning model? This paper presents an extension of the WaveU-Net [1] model which allows end-to-end monaural source separation with a non-fixed number of sources. Furthermore, we propose multiplicative conditioning with instrument labels at the bottleneck of the Wave-U-Net and show its effect on the separation results. This approach can be further extended to other types of conditioning such as audio-visual SSS and score-informed SSS.

Question: How to perform end-to-end sound source separation with a variable number of sources?


3-D Modeling of Tomato Canopies Using a High-Resolution Portable Scanning Lidar for Extracting Structural Information. In the present study, an attempt was made to produce a precise 3D image of a tomato canopy using a portable high-resolution scanning lidar. The tomato canopy was scanned by the lidar from three positions surrounding it. Through the scanning, the point cloud data of the canopy were obtained and they were co-registered. Then, points corresponding to leaves were extracted and converted into polygon images. From the polygon images, leaf areas were accurately estimated with a mean absolute percent error of 4.6%. Vertical profile of leaf area density (LAD) and leaf area index (LAI) could be also estimated by summing up each leaf area derived from the polygon images. Leaf inclination angle could be also estimated from the 3-D polygon image. It was shown that leaf inclination angles had different values at each part of a leaf.

Question: How to extract leaf area from a 3D point cloud?


LegUp: high-level synthesis for FPGA-based processor/accelerator systems. In this paper, we introduce a new open source high-level synthesis tool called LegUp that allows software techniques to be used for hardware design. LegUp accepts a standard C program as input and automatically compiles the program to a hybrid architecture containing an FPGA-based MIPS soft processor and custom hardware accelerators that communicate through a standard bus interface. Results show that the tool produces hardware solutions of comparable quality to a commercial high-level synthesis tool.

Question: What is a high-level synthesis tool?


Feature selection via sensitivity analysis of SVM probabilistic outputs. Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) learning. Like most feature-selection methods, the proposed method ranks all features in decreasing order of importance so that more relevant features can be identified. It uses a novel criterion based on the probabilistic outputs of SVM. This criterion, termed Feature-based Sensitivity of Posterior Probabilities (FSPP), evaluates the importance of a specific feature by computing the aggregate value, over the feature space, of the absolute difference of the probabilistic outputs of SVM with and without the feature. The exact form of this criterion is not easily computable and approximation is needed. Four approximations, FSPP1-FSPP4, are proposed for this purpose. The first two approximations evaluate the criterion by randomly permuting the values of the feature among samples of the training data. They differ in their choices of the mapping function from standard SVM output to its probabilistic output: FSPP1 uses a simple threshold function while FSPP2 uses a sigmoid function. The second two directly approximate the criterion but differ in the smoothness assumptions of criterion with respect to the features. The performance of these approximations, used in an overall feature-selection scheme, is then evaluated on various artificial problems and real-world problems, including datasets from the recent Neural Information Processing Systems (NIPS) feature selection competition. FSPP1-3 show good performance consistently with FSPP2 being the best overall by a slight margin. The performance of FSPP2 is competitive with some of the best performing feature-selection methods in the literature on the datasets that we have tested. Its associated computations are modest and hence it is suitable as a feature-selection method for SV

Question: What is the difference between feature selection and feature extraction?


Wireless health monitoring system for patients. eHealth is the provision of healthcare with the inclusion of telecommunication techniques. This project looks at the construction of a simple device that will be capable of transferring the data of a patient's vital signs to a remote device wirelessly. The necessity of this project is to alleviate the difficulty that is encountered by medical experts in monitoring multiple patients simultaneously. This project will enable them to observe patients without having to be physically present at their bedside, be it in the hospital or in their home. A patient's body temperature, heart rate and electrocardiography (ECG) are transferred wirelessly through an agent such as Bluetooth technology.

Question: What is the necessity of this project?


Community detection using a neighborhood strength driven Label Propagation Algorithm. Studies of community structure and evolution in large social networks require a fast and accurate algorithm for community detection. As the size of analyzed communities grows, complexity of the community detection algorithm needs to be kept close to linear. The Label Propagation Algorithm (LPA) has the benefits of nearly-linear running time and easy implementation, thus it forms a good basis for efficient community detection methods. In this paper, we propose new update rule and label propagation criterion in LPA to improve both its computational efficiency and the quality of communities that it detects. The speed is optimized by avoiding unnecessary updates performed by the original algorithm. This change reduces significantly (by order of magnitude for large networks) the number of iterations that the algorithm executes. We also evaluate our generalization of the LPA update rule that takes into account, with varying strength, connections to the neighborhood of a node considering a new label. Experiments on computer generated networks and a wide range of social networks show that our new rule improves the quality of the detected communities compared to those found by the original LPA. The benefit of considering positive neighborhood strength is pronounced especially on real-world networks containing sufficiently large fraction of nodes with high clustering coefficient.

Question: What is a neighborhood strength driven label propagation algorithm?


Problems in dealing with missing data and informative censoring in clinical trials. Acommon problem in clinical trials is the missing data that occurs when patients do not complete the study and drop out without further measurements. Missing data cause the usual statistical analysis of complete or all available data to be subject to bias. There are no universally applicable methods for handling missing data. We recommend the following: (1) Report reasons for dropouts and proportions for each treatment group; (2) Conduct sensitivity analyses to encompass different scenarios of assumptions and discuss consistency or discrepancy among them; (3) Pay attention to minimize the chance of dropouts at the design stage and during trial monitoring; (4) Collect post-dropout data on the primary endpoints, if at all possible; and (5) Consider the dropout event itself an important endpoint in studies with many.

Question: What is the difference between informative censoring and missing data?


Structural Models of Corporate Bond Pricing : An Empirical Analysis. This article empirically tests five structural models of corporate bond pricing: those of Merton (1974), Geske (1977), Longstaff and Schwartz (1995), Leland and Toft (1996), and Collin-Dufresne and Goldstein (2001). We implement the models using a sample of 182 bond prices from firms with simple capital structures during the period 1986–1997. The conventional wisdom is that structural models do not generate spreads as high as those seen in the bond market, and true to expectations, we find that the predicted spreads in our implementation of the Merton model are too low. However, most of the other structural models predict spreads that are too high on average. Nevertheless, accuracy is a problem, as the newer models tend to severely overstate the credit risk of firms with high leverage or volatility and yet suffer from a spread underprediction problem with safer bonds. The Leland and Toft model is an exception in that it overpredicts spreads on most bonds, particularly those with high coupons. More accurate structural models must avoid features that increase the credit risk on the riskier bonds while scarcely affecting the spreads of the safest bonds.

Question: What is the difference between a structural model and a parametric model?


A Hybrid Word-Character Model for Abstractive Summarization. Automatic abstractive text summarization is an important and challenging research topic of natural language processing. Among many widely used languages, the Chinese language has a special property that a Chinese character contains rich information comparable to a word. Existing Chinese text summarization methods, either adopt totally character-based or word-based representations, fail to fully exploit the information carried by both representations. To accurately capture the essence of articles, we propose a hybrid word-character approach (HWC) which preserves the advantages of both wordbased and character-based representations. We evaluate the advantage of the proposed HWC approach by applying it to two existing methods, and discover that it generates state-of-the-art performance with a margin of 24 ROUGE points on a widely used dataset LCSTS. In addition, we find an issue contained in the LCSTS dataset and offer a script to remove overlapping pairs (a summary and a short text) to create a clean dataset for the community. The proposed HWC approach also generates the best performance on the new, clean LCSTS dataset.

Question: What is the difference between a hybrid word-character model and a character-based model?


Patterns, Causes, and Consequences of Anthropocene Defaunation. Anthropocene defaunation, the global extinction of faunal species and populations and the decline in abundance of individuals within populations, has been predominantly documented in terrestrial ecosystems, but indicators suggest defaunation has been more severe in freshwater ecosystems. Marine defaunation is in a more incipient stage, yet pronounced effects are already apparent and its rapid acceleration seems likely. Defaunation now impacts the planet's wildlife with profound cascading consequences, ranging from local to global coextinctions of interacting species to the loss of ecological services critical for humanity. Slowing defaunation will require aggressively reducing animal overexploitation and habitat destruction; mitigating climate disruption; and stabilizing the impacts of human population growth and uneven resource consumption. Given its omnipresence, defaunation should receive status of major global environmental change and should be addressed with the same urgency as deforestation, pollution, and climatic change. Global action is needed to prevent defaunation's current trajectory from catalyzing the planet's sixth major extinction. 333 Review in Advance first posted online on August 26, 2016. (Changes may still occur before final publication online and in print.) Changes may still occur before final publication online and in print A nn u. R ev . E co l. E vo l. Sy st . 2 01 6. 47 . D ow nl oa de d fr om w w w .a nn ua lr ev ie w s. or g A cc es s pr ov id ed b y U ni ve rs ity o f C al if or ni a Sa nt a B ar ba ra o n 10 /2 0/ 16 . F or p er so na l u se o nl y. ES47CH15-Dirzo ARI 19 August 2016 14:55

Question: What is the sixth major extinction?


The RB and p 53 pathways in cancer. The life history of cancer cells encompasses a series of genetic missteps in which normal cells are progressively transformed into tumor cells that invade surrounding tissues and become malignant. Most prominent among the regulators disrupted in cancer cells are two tumor suppressors, the retinoblastoma protein (RB) and the p53 transcription factor. Here, we discuss interconnecting signaling pathways controlled by RB and p53, attempting to explain their potentially universal involvement in the etiology of cancer. Pinpointing the various ways by which the functions of RB and p53 are subverted in individual tumors should provide a rational basis for developing more refined tumor-specific therapies.

Question: What is the RB and p53 pathways?


Versatile low power media access for wireless sensor networks. We propose B-MAC, a carrier sense media access protocol for wireless sensor networks that provides a flexible interface to obtain ultra low power operation, effective collision avoidance, and high channel utilization. To achieve low power operation, B-MAC employs an adaptive preamble sampling scheme to reduce duty cycle and minimize idle listening. B-MAC supports on-the-fly reconfiguration and provides bidirectional interfaces for system services to optimize performance, whether it be for throughput, latency, or power conservation. We build an analytical model of a class of sensor network applications. We use the model to show the effect of changing B-MAC's parameters and predict the behavior of sensor network applications. By comparing B-MAC to conventional 802.11-inspired protocols, specifically SMAC, we develop an experimental characterization of B-MAC over a wide range of network conditions. We show that B-MAC's flexibility results in better packet delivery rates, throughput, latency, and energy consumption than S-MAC. By deploying a real world monitoring application with multihop networking, we validate our protocol design and model. Our results illustrate the need for flexible protocols to effectively realize energy efficient sensor network applications.

Question: What is the difference between a sensor network and a wireless sensor network?


Colostrum avoidance, prelacteal feeding and late breast-feeding initiation in rural Northern Ethiopia.. OBJECTIVE To identify specific cultural and behavioural factors that might be influenced to increase colostrum feeding in a rural village in Northern Ethiopia to improve infant health.   DESIGN Background interviews were conducted with six community health workers and two traditional birth attendants. A semi-structured tape-recorded interview was conducted with twenty mothers, most with children under the age of 5 years. Variables were: parental age and education; mother's ethnicity; number of live births and children's age; breast-feeding from birth through to weaning; availability and use of formula; and descriptions of colostrum v. other stages of breast milk. Participant interviews were conducted in Amharic and translated into English.   SETTING Kossoye, a rural Amhara village with high prevalence rates of stunting: inappropriate neonatal feeding is thought to be a factor.   SUBJECTS Women (20-60 years of age) reporting at least one live birth (range: 1-8, mean: ∼4).   RESULTS Colostrum (inger) and breast milk (yetut wotet) were seen as different substances. Colostrum was said to cause abdominal problems, but discarding a portion was sufficient to mitigate this effect. Almost all (nineteen of twenty) women breast-fed and twelve (63 %) reported ritual prelacteal feeding. A majority (fifteen of nineteen, 79 %) reported discarding colostrum and breast-feeding within 24 h of birth. Prelacteal feeding emerged as an additional factor to be targeted through educational intervention.   CONCLUSIONS To maximize neonatal health and growth, we recommend culturally tailored education delivered by community health advocates and traditional health practitioners that promotes immediate colostrum feeding and discourages prelacteal feeding.

Question: What is the difference between colostrum and breast milk?


Observations on periorbital and midface aging.. BACKGROUND Many of the anatomical changes of facial aging are still poorly understood. This study looked at the aging process in individuals linearly over time, focusing on aspects of periorbital aging and the upper midface.   METHODS The author compared photographs of patients' friends and relatives taken 10 to 50 years before with closely matched recent follow-up pictures. The best-matching old and recent pictures were equally sized and superimposed in the computer. The images were then assembled into GIF animations, which automate the fading of one image into the other and back again indefinitely.   RESULTS The following findings were new to the author: (1) the border of the pigmented lid skin and thicker cheek skin (the lid-cheek junction) is remarkably stable in position over time, becoming more visible by contrast, not by vertical descent as is commonly assumed. (2) Orbicularis wrinkles on the cheek and moles and other markers on the upper midface were also stable over decades. (3) With aging, there can be a distinct change in the shape of the upper eyelid. The young upper lid frequently has a medially biased peak. The upper lid peak becomes more central in the older lid. This article addresses these three issues. No evidence was seen here for descent of the globe in the orbit.   CONCLUSIONS There seems to be very little ptosis (inferior descent) of the lid-cheek junction or of the upper midface. These findings suggest that vertical descent of skin, and by association, subcutaneous tissue, is not necessarily a major component of aging in those areas. In addition, the arc of the upper lid changes shape in a characteristic way in some patients. Other known changes of the periorbital area are visualized.

Question: How do you know if you are aging?


Procedural Generation of Parcels in Urban Modeling. We present a method for interactive procedural generation of parcels within the urban modeling pipeline. Our approach performs a partitioning of the interior of city blocks using user-specified subdivision attributes and style parameters. Moreover, our method is both robust and persistent in the sense of being able to map individual parcels from before an edit operation to after an edit operation this enables transferring most, if not all, customizations despite small to large-scale interactive editing operations. The guidelines guarantee that the resulting subdivisions are functionally and geometrically plausible for subsequent building modeling and construction. Our results include visual and statistical comparisons that demonstrate how the parcel configurations created by our method can closely resemble those found in real-world cities of a large variety of styles. By directly addressing the block subdivision problem, we intend to increase the editability and realism of the urban modeling pipeline and to become a standard in parcel generation for future urban modeling methods.

Question: How to generate parcels in urban modeling?


Street-to-shop: Cross-scenario clothing retrieval via parts alignment and auxiliary set. We address a cross-scenario clothing retrieval problem- given a daily human photo captured in general environment, e.g., on street, finding similar clothing in online shops, where the photos are captured more professionally and with clean background. There are large discrepancies between daily photo scenario and online shopping scenario. We first propose to alleviate the human pose discrepancy by locating 30 human parts detected by a well trained human detector. Then, founded on part features, we propose a two-step calculation to obtain more reliable one-to-many similarities between the query daily photo and online shopping photos: 1) the within-scenario one-to-many similarities between a query daily photo and an extra auxiliary set are derived by direct sparse reconstruction; 2) by a cross-scenario many-to-many similarity transfer matrix inferred offline from the auxiliary set and the online shopping set, the reliable cross-scenario one-to-many similarities between the query daily photo and all online shopping photos are obtained.

Question: How to find similar clothing in online shops?


The Airport Gate Assignment Problem: Mathematical Model and a Tabu Search Algorithm. In this paper, we consider an Airport Gate Assignment Problem that dynamically assigns airport gates to scheduled ights based on passengers' daily origin and destination ow data. The objective of the problem is to minimize the overall connection times that passengers walk to catch their connection ights. We formulate this problem as a mixed 0-1 quadratic integer programming problem and then reformulate it as a mixed 0-1 integer problem with a linear objective function and constraints. We design a simple tabu search meta-heuristic to solve the problem. The algorithm exploits the special properties of di erent types of neighborhood moves, and create highly e ective candidate list strategies. We also address issues of tabu short term memory, dynamic tabu tenure, aspiration rule, and various intensi cation and diversi cation strategies. Preliminary computational experiments are conducted and the results are presented and analyzed.

Question: What is the airport gate assignment problem?


T REE-STRUCTURED DECODING WITH DOUBLY-RECURRENT NEURAL NETWORKS. We propose a neural network architecture for generating tree-structured objects from encoded representations. The core of the method is a doubly recurrent neural network model comprised of separate width and depth recurrences that are combined inside each cell (node) to generate an output. The topology of the tree is modeled explicitly together with the content. That is, in response to an encoded vector representation, co-evolving recurrences are used to realize the associated tree and the labels for the nodes in the tree. We test this architecture in an encoderdecoder framework, where we train a network to encode a sentence as a vector, and then generate a tree structure from it. The experimental results show the effectiveness of this architecture at recovering latent tree structure in sequences and at mapping sentences to simple functional programs.

Question: What is a neural network architecture for generating tree-structured objects from encoded representations?


Reader-Aware Multi-Document Summarization: An Enhanced Model and The First Dataset. We investigate the problem of readeraware multi-document summarization (RA-MDS) and introduce a new dataset for this problem. To tackle RA-MDS, we extend a variational auto-encodes (VAEs) based MDS framework by jointly considering news documents and reader comments. To conduct evaluation for summarization performance, we prepare a new dataset. We describe the methods for data collection, aspect annotation, and summary writing as well as scrutinizing by experts. Experimental results show that reader comments can improve the summarization performance, which also demonstrates the usefulness of the proposed dataset. The annotated dataset for RA-MDS is available online1.

Question: What is the first dataset for reader-aware multi-document summarization?


MySpace and Facebook: Applying the Uses and Gratifications Theory to Exploring Friend-Networking Sites. The increased use of the Internet as a new tool in communication has changed the way people interact. This fact is even more evident in the recent development and use of friend-networking sites. However, no research has evaluated these sites and their impact on college students. Therefore, the present study was conducted to evaluate: (a) why people use these friend-networking sites, (b) what the characteristics are of the typical college user, and (c) what uses and gratifications are met by using these sites. Results indicated that the vast majority of college students are using these friend-networking sites for a significant portion of their day for reasons such as making new friends and locating old friends. Additionally, both men and women of traditional college age are equally engaging in this form of online communication with this result holding true for nearly all ethnic groups. Finally, results showed that many uses and gratifications are met by users (e.g., "keeping in touch with friends"). Results are discussed in light of the impact that friend-networking sites have on communication and social needs of college students.

Question: What are the uses and gratifications of using the friend-networking sites?


Linking Data to Ontologies. Many organizations nowadays face the problem of accessing existing data sources by means of flexible mechanisms that are both powerful and efficient. Ontologies are widely considered as a suitable formal tool for sophisticated data access. The ontology expresses the domain of interest of the information system at a high level of abstraction, and the relationship between data at the sources and instances of concepts and roles in the ontology is expressed by means of mappings. In this paper we present a solution to the problem of designing effective systems for ontology-based data access. Our solution is based on three main ingredients. First, we present a new ontology language, based on Description Logics, that is particularly suited to reason with large amounts of instances. The second ingredient is a novel mapping language that is able to deal with the so-called impedance mismatch problem, i.e., the problem arising from the difference between the basic elements managed by the sources, namely data, and the elements managed by the ontology, namely objects. The third ingredient is the query answering method, that combines reasoning at the level of the ontology with specific mechanisms for both taking into account the mappings and efficiently accessing the data at the sources.

Question: What is the ontology language based on Description Logics?


True upper bounds for Bermudan products via non-nested Monte. We present a generic non-nested Monte Carlo procedure for computing true upper bounds for Bermudan products, given an approximation of the Snell envelope. The pleonastic "true" stresses that, by construction, the estimator is biased above the Snell envelope. The key idea is a regression estimator for the Doob martingale part of the approximative Snell envelope, which preserves the martingale property. The so constructed martingale can be employed for computing tight dual upper bounds without nested simulation. In general, this martingale can also be used as a control variate for simulation of conditional expectations. In this context, we develop a variance reduced version of the nested primal-dual estimator (Andersen and Broadie, 2004). Numerical experiments indicate the efficiency of the proposed algorithms.

Question: How to compute tight upper bounds for Bermudan products?


PaperVis: Literature Review Made Easy. Reviewing literatures for a certain research field is always important for academics. One could use Google-like information seeking tools, but oftentimes he/she would end up obtaining too many possibly related papers, as well as the papers in the associated citation network. During such a process, a user may easily get lost after following a few links for searching or cross-referencing. It is also difficult for the user to identify relevant/important papers from the resulting huge collection of papers. Our work, called PaperVis, endeavors to provide a user-friendly interface to help users quickly grasp the intrinsic complex citation-reference structures among a specific group of papers. We modify the existing Radial Space Filling (RSF) and Bullseye View techniques to arrange involved papers as a node-link graph that better depicts the relationships among them while saving the screen space at the same time. PaperVis applies visual cues to present node attributes and their transitions among interactions, and it categorizes papers into semantically meaningful hierarchies to facilitate ensuing literature exploration. We conduct experiments on the InfoVis 2004 Contest Dataset to demonstrate the effectiveness of PaperVis.

Question: How to find relevant papers?


Visual Tracking via Boolean Map Representations. In this paper, we present a simple yet effective Boolean map based representation that exploits connectivity cues for visual tracking. We describe a target object with histogram of oriented gradients and raw color features, of which each one is characterized by a set of Boolean maps generated by uniformly thresholding their values. The Boolean maps effectively encode multi-scale connectivity cues of the target with different granularities. The fine-grained Boolean maps capture spatially structural details that are effective for precise target localization while the coarse-grained ones encode global shape information that are robust to large target appearance variations. Finally, all the Boolean maps form together a robust representation that can be approximated by an explicit feature map of the intersection kernel, which is fed into a logistic regression classifier with online update, and the target location is estimated within a particle filter framework. The proposed representation scheme is computationally efficient and facilitates achieving favorable performance in terms of accuracy and robustness against the state-of-the-art tracking methods on a large benchmark dataset of 50 image sequences.

Question: What is a Boolean map?


You Can Run but You Can't Read: Preventing Disclosure Exploits in Executable Code. Code reuse attacks allow an adversary to impose malicious behavior on an otherwise benign program. To mitigate such attacks, a common approach is to disguise the address or content of code snippets by means of randomization or rewriting, leaving the adversary with no choice but guessing. However, disclosure attacks allow an adversary to scan a process - even remotely - and enable her to read executable memory on-the-fly, thereby allowing the just-in time assembly of exploits on the target site. In this paper, we propose an approach that fundamentally thwarts the root cause of memory disclosure exploits by preventing the inadvertent reading of code while the code itself can still be executed. We introduce a new primitive we call Execute-no-Read (XnR) which ensures that code can still be executed by the processor, but at the same time code cannot be read as data. This ultimately forfeits the self-disassembly which is necessary for just-in-time code reuse attacks (JIT-ROP) to work. To the best of our knowledge, XnR is the first approach to prevent memory disclosure attacks of executable code and JIT-ROP attacks in general. Despite the lack of hardware support for XnR in contemporary Intel x86 and ARM processors, our software emulations for Linux and Windows have a run-time overhead of only 2.2% and 3.4%, respectively.

Question: How can I prevent disclosure exploits in executable code?


Learning to Decode for Future Success. We introduce a general strategy for improving neural sequence generation by incorporating knowledge about the future. Our decoder combines a standard sequence decoder with a 'soothsayer' prediction function Q that estimates the outcome in the future of generating a word in the present. Our model draws on the same intuitions as reinforcement learning, but is both simpler and higher performing, avoiding known problems with the use of reinforcement learning in tasks with enormous search spaces like sequence generation. We demonstrate our model by incorporating Q functions that incrementally predict what the future BLEU or ROUGE score of the completed sequence will be, its future length, and the backwards probability of the source given the future target sequence. Experimental results show that future prediction yields improved performance in abstractive summarization and conversational response generation and the state-of-the-art in machine translation, while also enabling the decoder to generate outputs that have specific properties.

Question: How to improve neural sequence generation?


The effect of substrate noise on VCO performance. This study characterizes the effect of substrate noise on a standard component of the RF front end: the voltage controlled oscillator (VCO), as well as evaluating the effect of VCO bias current and guard rings on noise performance. Frequency effects of substrate noise are also examined through the study of VCOs at three different center frequencies: 900 MHz, 2.4 GHz, and 5.2 GHz. Substrate noise is a serious problem that continues to plague mixed-signal designs. Components of the RF frontend are particularly sensitive to substrate noise as the effectiveness of standard isolation techniques degrades at higher frequencies. This study has shown that the phase noise of a VCO is adversely affected by substrate noise. In the extreme, the VCO can lock to the substrate noise. Guard rings can effectively attenuate substrate noise at lower frequencies. For example, at 900 MHz, as much as 25 dB of isolation is observed. At 5.2 GHz, the isolation reduces to 10 dB. Furthermore, the use of guard rings can improve the response of the VCO to injection locking.

Question: What is the effect of substrate noise on VCO performance?


CatchTartan: Representing and Summarizing Dynamic Multicontextual Behaviors. Representing and summarizing human behaviors with rich contexts facilitates behavioral sciences and user-oriented services. Traditional behavioral modeling represents a behavior as a tuple in which each element is one contextual factor of one type, and the tensor-based summaries look for high-order dense blocks by clustering the values (including timestamps) in each dimension. However, the human behaviors are multicontextual and dynamic: (1) each behavior takes place within multiple contexts in a few dimensions, which requires the representation to enable non-value and set-values for each dimension; (2) many behavior collections, such as tweets or papers, evolve over time. In this paper, we represent the behavioral data as a two-level matrix (temporal-behaviors by dimensional-values) and propose a novel representation for behavioral summary called Tartan that includes a set of dimensions, the values in each dimension, a list of consecutive time slices and the behaviors in each slice. We further develop a propagation method CatchTartan to catch the dynamic multicontextual patterns from the temporal multidimensional data in a principled and scalable way: it determines the meaningfulness of updating every element in the Tartan by minimizing the encoding cost in a compression manner. CatchTartan outperforms the baselines on both the accuracy and speed. We apply CatchTartan to four Twitter datasets up to 10 million tweets and the DBLP data, providing comprehensive summaries for the events, human life and scientific development.

Question: What is the tartan?


Autonomous boids. The classical work of bird-like objects of Reynolds [1] simulates polarized motion of groups of oriented particles, bird-like objects, or simply boids. To do this, three steering vectors are introduced. Cohesion is the tendency of boids to stay in the center of the flock, alignment smoothes their velocities to similar values, and separation helps them to avoid mutual collisions. If no impetus is introduced the boids wander somewhat

Question: What is the classical work of bird-like objects of Reynolds?


Procedural City Layout Generation Based on Urban Land Use Models. Training and simulation applications in virtual worlds require significant amounts of urban environments. Procedural generation is an efficient way to create such models. Existing approaches for procedural modelling of cities aim at facilitating the work of urban planners and artists, but either require expert knowledge or external input data to generate results that resemble real-life cities, or they have long computation times, and thus are unsuitable for non-experts such as training instructors. We propose a method that procedurally creates layouts of structurally plausible cities from high-level, intuitive user input such as city size, location and historic background. The resulting layouts consist of different kinds of city districts which are arranged using constraints derived from established models of urban land use. Our approach avoids the need for external expert engagement in the creation process, and allows for the generation of large city layouts in seconds, making it significantly faster than comparable agent-based software and thus supporting the needs of non-expert creators of virtual cities for many applications.

Question: How to create a city layout?


Design and Implementation of an FPGA-Based Real-Time Face Recognition System. Face recognition systems play a vital role in many applications including surveillance, biometrics and security. In this work, we present a {\textit complete} real-time face recognition system consisting of a face detection, a recognition and a down sampling module using an FPGA. Our system provides an end-to-end solution for face recognition, it receives video input from a camera, detects the locations of the face(s) using the Viola-Jones algorithm, subsequently recognizes each face using the Eigenface algorithm, and outputs the results to a display. Experimental results show that our complete face recognition system operates at 45 frames per second on a Virtex-5 FPGA.

Question: What is an FPGA?


Using Neural Networks to Generate Inferential Roles for Natural Language. Neural networks have long been used to study linguistic phenomena spanning the domains of phonology, morphology, syntax, and semantics. Of these domains, semantics is somewhat unique in that there is little clarity concerning what a model needs to be able to do in order to provide an account of how the meanings of complex linguistic expressions, such as sentences, are understood. We argue that one thing such models need to be able to do is generate predictions about which further sentences are likely to follow from a given sentence; these define the sentence's "inferential role." We then show that it is possible to train a tree-structured neural network model to generate very simple examples of such inferential roles using the recently released Stanford Natural Language Inference (SNLI) dataset. On an empirical front, we evaluate the performance of this model by reporting entailment prediction accuracies on a set of test sentences not present in the training data. We also report the results of a simple study that compares human plausibility ratings for both human-generated and model-generated entailments for a random selection of sentences in this test set. On a more theoretical front, we argue in favor of a revision to some common assumptions about semantics: understanding a linguistic expression is not only a matter of mapping it onto a representation that somehow constitutes its meaning; rather, understanding a linguistic expression is mainly a matter of being able to draw certain inferences. Inference should accordingly be at the core of any model of semantic cognition.

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


Block-Matching Convolutional Neural Network for Image Denoising. There are two main streams in up-to-date image denoising algorithms: non-local self similarity (NSS) prior based methods and convolutional neural network (CNN) based methods. The NSS based methods are favorable on images with regular and repetitive patterns while the CNN based methods perform better on irregular structures. In this paper, we propose a blockmatching convolutional neural network (BMCNN) method that combines NSS prior and CNN. Initially, similar local patches in the input image are integrated into a 3D block. In order to prevent the noise from messing up the block matching, we first apply an existing denoising algorithm on the noisy image. The denoised image is employed as a pilot signal for the block matching, and then denoising function for the block is learned by a CNN structure. Experimental results show that the proposed BMCNN algorithm achieves state-of-the-art performance. In detail, BMCNN can restore both repetitive and irregular structures.

Question: What is the state-of-the-art image denoising algorithm?


Election Analysis and Prediction of Election Results with Twitter.

Question: How to predict election results with twitter?


Good features to track. No feature-based vision system can work unless good features can be identi ed and tracked from frame to frame. Although tracking itself is by and large a solved problem, selecting features that can be tracked well and correspond to physical points in the world is still hard. We propose a feature selection criterion that is optimal by construction because it is based on how the tracker works, and a feature monitoring method that can detect occlusions, disocclusions, and features that do not correspond to points in the world. These methods are based on a new tracking algorithm that extends previous Newton-Raphson style search methods to work under a ne image transformations. We test performance with several simulations and experiments.

Question: How to track features in a video?


DynamicFusion: Reconstruction and tracking of non-rigid scenes in real-time. We present the first dense SLAM system capable of reconstructing non-rigidly deforming scenes in real-time, by fusing together RGBD scans captured from commodity sensors. Our DynamicFusion approach reconstructs scene geometry whilst simultaneously estimating a dense volumetric 6D motion field that warps the estimated geometry into a live frame. Like KinectFusion, our system produces increasingly denoised, detailed, and complete reconstructions as more measurements are fused, and displays the updated model in real time. Because we do not require a template or other prior scene model, the approach is applicable to a wide range of moving objects and scenes.

Question: What is the dynamic fusion?


FPGA Implementations of the AES Masked Against Power Analysis Attacks. Power analysis attacks are a serious treat for implementations of modern cryptographic algorithms. Masking is a particularly appealing countermeasure against such attacks since it increases the security to a well quantifiable level and can be implemented without modifying the underlying technology. Its main drawback is the performance overhead it implies. For example, due to prohibitive memory costs, the straightforward application of masking to the AES algorithm, with precomputed tables, is hardly practical. In this paper, we exploit both the increased size of state-of-the-art reconfigurable hardware devices and previous optimization techniques to minimize the memory occupation of software S-boxes, in order to provide an efficient FPGA implementation of the AES algorithm, masked against side-channel attacks. We describe two high throughput architectures, based on 32-bit and 128-bit datapaths that are suitable for Xilinx Virtex-5 devices. In this way, we demonstrate the possibility to efficiently combine technological advances with algorithmic optimizations in this context.

Question: What is the size of the AES state?


Synthesizing tests for detecting atomicity violations. Using thread-safe libraries can help programmers avoid the complexities of multithreading. However, designing libraries that guarantee thread-safety can be challenging. Detecting and eliminating atomicity violations when methods in the libraries are invoked concurrently is vital in building reliable client applications that use the libraries. While there are dynamic analyses to detect atomicity violations, these techniques are critically dependent on effective multithreaded tests. Unfortunately, designing such tests is non-trivial. In this paper, we design a novel and scalable approach for synthesizing multithreaded tests that help detect atomicity violations. The input to the approach is the implementation of the library and a sequential seed testsuite that invokes every method in the library with random parameters. We analyze the execution of the sequential tests, generate variable lock dependencies and construct a set of three accesses which when interleaved suitably in a multithreaded execution can cause an atomicity violation. Subsequently, we identify pairs of method invocations that correspond to these accesses and invoke them concurrently from distinct threads with appropriate objects to help expose atomicity violations. We have incorporated these ideas in our tool, named Intruder, and applied it on multiple open-source Java multithreaded libraries. Intruder is able to synthesize 40 multithreaded tests across nine classes in less than two minutes to detect 79 harmful atomicity violations, including previously unknown violations in thread-safe classes. We also demonstrate the effectiveness of Intruder by comparing the results with other approaches designed for synthesizing multithreaded tests.

Question: How to detect atomicity violations in multithreaded libraries?


G3D: A gaming action dataset and real time action recognition evaluation framework. In this paper a novel evaluation framework for measuring the performance of real-time action recognition methods is presented. The evaluation framework will extend the time-based event detection metric to model multiple distinct action classes. The proposed metric provides more accurate indications of the performance of action recognition algorithms for games and other similar applications since it takes into consideration restrictions related to time and consecutive repetitions. Furthermore, a new dataset, G3D for real-time action recognition in gaming containing synchronised video, depth and skeleton data is provided. Our results indicate the need of an advanced metric especially designed for games and other similar real-time applications.

Question: What is a gaming action dataset?


A Bayesian framework for word segmentation: Exploring the effects of context. Since the experiments of Saffran et al. [Saffran, J., Aslin, R., & Newport, E. (1996). Statistical learning in 8-month-old infants. Science, 274, 1926-1928], there has been a great deal of interest in the question of how statistical regularities in the speech stream might be used by infants to begin to identify individual words. In this work, we use computational modeling to explore the effects of different assumptions the learner might make regarding the nature of words--in particular, how these assumptions affect the kinds of words that are segmented from a corpus of transcribed child-directed speech. We develop several models within a Bayesian ideal observer framework, and use them to examine the consequences of assuming either that words are independent units, or units that help to predict other units. We show through empirical and theoretical results that the assumption of independence causes the learner to undersegment the corpus, with many two- and three-word sequences (e.g. what's that, do you, in the house) misidentified as individual words. In contrast, when the learner assumes that words are predictive, the resulting segmentation is far more accurate. These results indicate that taking context into account is important for a statistical word segmentation strategy to be successful, and raise the possibility that even young infants may be able to exploit more subtle statistical patterns than have usually been considered.

Question: What is the Bayesian ideal observer?


Exploring commonalities across participants in the neural representation of objects.. The question of whether the neural encodings of objects are similar across different people is one of the key questions in cognitive neuroscience. This article examines the commonalities in the internal representation of objects, as measured with fMRI, across individuals in two complementary ways. First, we examine the commonalities in the internal representation of objects across people at the level of interobject distances, derived from whole brain fMRI data, and second, at the level of spatially localized anatomical brain regions that contain sufficient information for identification of object categories, without making the assumption that their voxel patterns are spatially matched in a common space. We examine the commonalities in internal representation of objects on 3T fMRI data collected while participants viewed line drawings depicting various tools and dwellings. This exploratory study revealed the extent to which the representation of individual concepts, and their mutual similarity, is shared across participants.

Question: What is the commonalities in the neural representation of objects?


Brain-computer interface research at the Wadsworth Center.. Studies at the Wadsworth Center over the past 14 years have shown that people with or without motor disabilities can learn to control the amplitude of mu or beta rhythms in electroencephalographic (EEG) activity recorded from the scalp over sensorimotor cortex and can use that control to move a cursor on a computer screen in one or two dimensions. This EEG-based brain-computer interface (BCI) could provide a new augmentative communication technology for those who are totally paralyzed or have other severe motor impairments. Present research focuses on improving the speed and accuracy of BCI communication.

Question: What is the Wadsworth Center?


Adaptive Binary Search Trees Jonathan Carlyle Derryberry. A ubiquitous problem in the field of algorithms and data structures is that of searching for an element from an ordered universe. The simple yet powerful binary search tree (BST) model provides a rich family of solutions to this problem. Although BSTs require Ω(lg n) time per operation in the worst case, various adaptive BST algorithms are capable of exploiting patterns in the sequence of queries to achieve tighter, input-sensitive, bounds that can be o(lg n) in many cases. This thesis furthers our understanding of what is achievable in the BST model along two directions. First, we make progress in improving instance-specific lower bounds in the BST model. In particular, we introduce a framework for generating lower bounds on the cost that any BST algorithm must pay to execute a query sequence, and we show that this framework generalizes previous lower bounds. This suggests that the optimal lower bound in the framework is a good candidate for being tight to within a constant factor of the optimal BST algorithm for each input. Further, we show that lower bounds in this framework are also valid lower bounds for instances of the partial-sums problem in a restricted model of computation, which suggests that augmented BSTs may be the most efficient way of maintaining sums over ranges of an array when the entries of the array can be updated throughout time. Second, we improve the input-sensitive upper bounds that are known to be achievable in the BST model by introducing two new BST algorithms, skip-splay and cache-splay. These two algorithms are the first BSTs that are known to have running times that have nontrivial competitiveness to Iacono's Unified Bound, which is a generalization of the dynamic finger and working set bounds. Skip-splay is a simple algorithm that is nearly identical to splaying, and it achieves a running time that is within additive O(lg lg n) per operation of the Unified Bound. Cache-splay is

Question: What is the running time of the unified bound?


Modeling Social Perception of Faces [Social Sciences]. The face is our primary source of visual information for identifying people and reading their emotional and mental states. With the exception of prosopagnosics (who are unable to recognize faces) and those suffering from such disorders of social cognition as autism, people are extremely adept at these two tasks. However, our cognitive powers in this regard come at the price of reading too much into the human face. The face is often treated as a window into a person's true nature. Given the agreement in social perception of faces, this paper discusses that it should be possible to model this perception.

Question: What is the price of reading too much into the human face?


Empirical evidence in global software engineering: a systematic review. Recognized as one of the trends of the 21st century, globalization of the world economies brought significant changes to nearly all industries, and in particular it includes software development. Many companies started global software engineering (GSE) to benefit from cheaper, faster and better development of software systems, products and services. However, empirical studies indicate that achieving these benefits is not an easy task. Here, we report our findings from investigating empirical evidence in GSE-related research literature. By conducting a systematic review we observe that the GSE field is still immature. The amount of empirical studies is relatively small. The majority of the studies represent problem-oriented reports focusing on different aspects of GSE management rather than in-depth analysis of solutions for example in terms of useful practices or techniques. Companies are still driven by cost reduction strategies, and at the same time, the most frequently discussed recommendations indicate a necessity of investments in travelling and socialization. Thus, at the same time as development goes global there is an ambition to minimize geographical, temporal and cultural separation. These are normally integral parts of cross-border collaboration. In summary, the systematic review results in several descriptive classifications of the papers on empirical studies in GSE and also reports on some best practices identified from literature.

Question: What is the best practice in software engineering?


Long-Term Treatment with High-Dose Thiamine in Parkinson Disease: An Open-Label Pilot Study.. OBJECTIVES To investigate the potential clinical, restorative, and neuroprotective effects of long-term treatment with thiamine in Parkinson disease (PD).   DESIGN Observational open-label pilot study.   SETTING Outpatient neurologic rehabilitation clinic.   PATIENTS AND METHODS Starting in June 2012, we have recruited 50 patients with PD (33 men and 17 women; mean age, 70.4 ± 12.9 years; mean disease duration, 7.3 ± 6.7 years). All the patients were assessed at baseline with the Unified Parkinson's Disease Rating Scale (UPDRS) and the Fatigue Severity Scale (FSS) and began treatment with 100 mg of thiamine administered intramuscularly twice a week, without any change to personal therapy. All the patients were re-evaluated after 1 month and then every 3 months during treatment.   RESULTS Thiamine treatment led to significant improvement of motor and nonmotor symptoms: mean UPDRS scores (parts I-IV) improved from 38.55 ± 15.24 to 18.16 ± 15.08 (p = 2.4 × 10(-14), t test for paired data) within 3 months and remained stable over time; motor UPDRS part III score improved from 22.01 ± 8.57 to 9.92 ± 8.66 (p = 3.1 × 10(-22)). Some patients with a milder phenotype had complete clinical recovery. FSS scores, in six patients who had fatigue, improved from 53.00 ± 8.17 to 23.60 ± 7.77 (p < 0.0001, t test for paired data). Follow-up duration ranged from 95 to 831 days (mean, 291.6 ± 207.2 days).   CONCLUSIONS Administration of parenteral high-dose thiamine was effective in reversing PD motor and nonmotor symptoms. The clinical improvement was stable over time in all the patients. From our clinical evidence, we hypothesize that a dysfunction of thiamine-dependent metabolic processes could cause selective neural damage in the centers typically affected by this disease and might be a fundamental molecular event provoking neurodegeneration. Thiamine could have both restorative and neuropr

Question: What is the difference between a pilot study and an open-label study?


Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam. Uncertainty computation in deep learning is essential to design robust and reliable systems. Variational inference (VI) is a promising approach for such computation, but requires more effort to implement and execute compared to maximumlikelihood methods. In this paper, we propose new natural-gradient algorithms to reduce such efforts for Gaussian mean-field VI. Our algorithms can be implemented within the Adam optimizer by perturbing the network weights during gradient evaluations, and uncertainty estimates can be cheaply obtained by using the vector that adapts the learning rate. This requires lower memory, computation, and implementation effort than existing VI methods, while obtaining uncertainty estimates of comparable quality. Our empirical results confirm this and further suggest that the weight-perturbation in our algorithm could be useful for exploration in reinforcement learning and stochastic optimization.

Question: How to implement Bayesian deep learning?


Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients.. OBJECTIVE To ascertain the current burden of adverse drug reactions (ADRs) through a prospective analysis of all admissions to hospital.   DESIGN Prospective observational study.   SETTING Two large general hospitals in Merseyside, England.   PARTICIPANTS 18 820 patients aged > 16 years admitted over six months and assessed for cause of admission.   MAIN OUTCOME MEASURES Prevalence of admissions due to an ADR, length of stay, avoidability, and outcome.   RESULTS There were 1225 admissions related to an ADR, giving a prevalence of 6.5%, with the ADR directly leading to the admission in 80% of cases. The median bed stay was eight days, accounting for 4% of the hospital bed capacity. The projected annual cost of such admissions to the NHS is 466m pounds sterling (706m Euros, 847m dollars). The overall fatality was 0.15%. Most reactions were either definitely or possibly avoidable. Drugs most commonly implicated in causing these admissions included low dose aspirin, diuretics, warfarin, and non-steroidal anti-inflammatory drugs other than aspirin, the most common reaction being gastrointestinal bleeding.   CONCLUSION The burden of ADRs on the NHS is high, accounting for considerable morbidity, mortality, and extra costs. Although many of the implicated drugs have proved benefit, measures need to be put into place to reduce the burden of ADRs and thereby further improve the benefit:harm ratio of the drugs.

Question: What is the burden of adverse drug reactions on the NHS?


A survey of traffic sign recognition. Advanced Driver Assistance Systems (ADAS) refer to various high-tech in-vehicle systems that are designed to increase road traffic safety by helping drivers gain better awareness of the road and its potential hazards as well as other drivers around them. The design of traffic sign recognition, one important subsystem of ADAS, has been a challenge problem for many years and hence become an important and active research topic in the area of intelligent transport systems. The realization of a real-time traffic sign recognition system is usually divided into three stages: detection, tracking and classification. This paper introduces the main difficulties in road sign recognition and briefly surveys the state-of-the-art technologies in this field with further discussions on the potential trend of development of road sign recognition.

Question: What is the state of the art in road sign recognition?


Multiple description-DASH: Pragmatic video streaming maximizing end-users' quality of experience. Over the past few years, adaptive bitrate streaming protocols, such as DASH, have risen to enhance the End-Users' experience towards video consumption over the Internet. Current methods perform a smoother playback (i.e., fewer re-buffering states) trading off with quality fluctuations due to the client-server link state. The proposed work goes a step further and introduces an innovative lightweight streaming solution by taking advantage of bandwidth aggregation over multiple paths using multiple content sources at the same time. This pragmatic evolving approach outperforms the QoE delivered by current DASH-based or P2P-based solutions and leverages the scope of action made available to the media delivery chain actors. The proposed solution has been implemented and is compared to a DASH-based approach used in most existing VoD use-cases through a first set of experiments. Results demonstrate the strong advantages in terms of quality delivered at the End-User's side and buffer occupancy. Discussion on the necessary trade-offs is also tackled.

Question: What is the difference between DASH and P2P?


Impact Analysis of Flow Shaping in Ethernet-AVB/TSN and AFDX from Network Calculus and Simulation Perspective. Ethernet-AVB/TSN (Audio Video Bridging/Time-Sensitive Networking) and AFDX (Avionics Full DupleX switched Ethernet) are switched Ethernet technologies, which are both candidates for real-time communication in the context of transportation systems. AFDX implements a fixed priority scheduling strategy with two priority levels. Ethernet-AVB/TSN supports a similar fixed priority scheduling with an additional Credit-Based Shaper (CBS) mechanism. Besides, TSN can support time-triggered scheduling strategy. One direct effect of CBS mechanism is to increase the delay of its flows while decreasing the delay of other priority ones. The former effect can be seen as the shaping restriction and the latter effect can be seen as the shaping benefit from CBS. The goal of this paper is to investigate the impact of CBS on different priority flows, especially on the intermediate priority ones, as well as the effect of CBS bandwidth allocation. It is based on a performance comparison of AVB/TSN and AFDX by simulation in an automotive case study. Furthermore, the shaping benefit is modeled based on integral operation from network calculus perspective. Combing with the analysis of shaping restriction and shaping benefit, some configuration suggestions on the setting of CBS bandwidth are given. Results show that the effect of CBS depends on flow loads and CBS configurations. A larger load of high priority flows in AVB tends to a better performance for the intermediate priority flows when compared with AFDX. Shaping benefit can be explained and calculated according to the changing from the permitted maximum burst.

Question: What is the difference between AVB/TSN and AFDX?


Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life.. Two studies examined violent video game effects on aggression-related variables. Study 1 found that real-life violent video game play was positively related to aggressive behavior and delinquency. The relation was stronger for individuals who are characteristically aggressive and for men. Academic achievement was negatively related to overall amount of time spent playing video games. In Study 2, laboratory exposure to a graphically violent video game increased aggressive thoughts and behavior. In both studies, men had a more hostile view of the world than did women. The results from both studies are consistent with the General Affective Aggression Model, which predicts that exposure to violent video games will increase aggressive behavior in both the short term (e.g., laboratory aggression) and the long term (e.g., delinquency).

Question: What is the general affective aggression model?


A 95% Efficient Normally-Off GaN-on-Si HEMT Hybrid-IC Boost-Converter with 425-W Output Power at 1 MHz. A 2:1 351 V hard-switched boost converter was constructed using high-voltage GaN high-electron-mobility transistors grown on Si substrates and GaN Schottky diodes grown on Sapphire substrates. The high speed and low on-resistance of the GaN devices enables extremely fast switching times and low losses, resulting in a high conversion efficiency of 95% with 425-W output power at 1 MHz. The boost converter has a power density of 175 W/in3. To our knowledge, these results are the best reported on GaN devices, and the highest for 1MHz switching.

Question: What is the highest power density of a transistor?


Sketches by Paul the Robot. In this paper we describe Paul, a robotic installation that produces observational sketches of people. The sketches produced have been considered of interest by fine art professionals in recent art fairs and exhibitions, as well as by the public at large. We identify factors that may account for the perceived qualities of the produced sketches. A technical overview of the system is also presented.

Question: What is a robot?


Optimal dimensioning of active cell balancing architectures. This paper presents an approach to optimal dimensioning of active cell balancing architectures, which are of increasing relevance in Electrical Energy Storages (EESs) for Electric Vehicles (EVs) or stationary applications such as smart grids. Active cell balancing equalizes the state of charge of cells within a battery pack via charge transfers, increasing the effective capacity and lifetime. While optimization approaches have been introduced into the design process of several aspects of EESs, active cell balancing architectures have, until now, not been systematically optimized in terms of their components. Therefore, this paper analyzes existing architectures to develop design metrics for energy dissipation, installation volume, and balancing current. Based on these design metrics, a methodology to efficiently obtain Pareto-optimal configurations for a wide range of inductors and transistors at different balancing currents is developed. Our methodology is then applied to a case study, optimizing two state-of-the-art architectures using realistic balancing algorithms. The results give evidence of the applicability of systematic optimization in the domain of cell balancing, leading to higher energy efficiencies with minimized installation space.

Question: How to design an active cell balancing architecture?


Constructions from Dots and Lines. Marko A. Rodriguez is graph systems architect at AT&T Interactive. He can be reached at marko<at>markorodriguez.com. Peter Neubauer is chief operating officer of Neo Technology. He can be reached at peter.neubauer<at>neotechnology.com A graph is a data structure composed of dots (i.e., vertices) and lines (i.e., edges). The dots and lines of a graph can be organized into intricate arrangements. A graph's ability to denote objects and their relationships to one another allows for a surprisingly large number of things to be modeled as graphs. From the dependencies that link software packages to the wood beams that provide the framing to a house, most anything has a corresponding graph representation. However, just because it is possible to represent something as a graph does not necessarily mean that its graph representation will be useful. If a modeler can leverage the plethora of tools and algorithms that store and process graphs, then such a mapping is worthwhile. This article explores the world of graphs in computing and exposes situations in which graphical models are beneficial.

Question: What is a graph?


Optimizing Soft Real-Time Scheduling Performance for Virtual Machines with SRT-Xen. Multimedia applications are an important part of today's Internet. However, currently most virtualization solutions, including Xen, lack adequate support for soft real-time tasks. Soft real-time applications, e.g. media workloads, are impeded by components of virtualization, such as the increase of scheduling latency. This paper focuses on improving scheduling scheme to support soft real-time workloads in virtualization systems. In this paper, we present an enhanced scheduler SRT-Xen. SRT-Xen can promote the soft real-time domain's performance compared with Xen's existing scheduling. It focuses on not only bringing a new realtime-friendly scheduling framework with corresponding strategies but also improving the management of the virtual CPUs' queuing in order to implement a fair scheduling mechanism for both real-time and non-real-time tasks. Finally, we use PESQ (Perceptual Evaluation of Speech Quality) and other benchmarks to evaluate and compare SRT-Xen with some other works. The results show that SRT-Xen supports soft real-time domains well without penalizing non-real-time ones.

Question: What is the difference between soft real-time and hard real-time?


ColorBars: increasing data rate of LED-to-camera communication using color shift keying. LED-to-camera communication allows LEDs deployed for illumination purposes to modulate and transmit data which can be received by camera sensors available in mobile devices like smartphones, wearable smart-glasses etc. Such communication has a unique property that a user can visually identify a transmitter (i.e. LED) and specifically receive information from the transmitter. It can support a variety of novel applications such as augmented reality through mobile devices, navigation using smart signs, fine-grained location specific advertisement etc. However, the achievable data rate in current LED-to-camera communication techniques remains very low (≈ 12 bytes per second) to support any practical application. In this paper, we present ColorBars, an LED-to-camera communication system that utilizes Color Shift Keying (CSK) to modulate data using different colors transmitted by the LED. It exploits the increasing popularity of Tri-LEDs (RGB) that can emit a wide range of colors. We show that commodity cameras can efficiently and accurately demodulate the color symbols. ColorBars ensures flicker-free and reliable communication even in the presence of inter-frame loss and diversity of rolling shutter cameras. We implement ColorBars on embedded platform and evaluate it with Android and iOS smartphones as receivers. Our evaluation shows that ColorBars can achieve a data rate of 5.2 Kbps on Nexus 5 and 2.5 Kbps on iPhone 5S, which is significantly higher than previous approaches. It is also shown that lower CSK modulations (e.g. 4 and 8 CSK) provide extremely low symbol error rates (< 10--3), making them a desirable choice for reliable LED-to-camera communication.

Question: How does color shift keying work?


Building upon RouteFlow : a SDN development experience. RouteFlow is a platform for providing virtual IP routing services in OpenFlow networks. During the first year of development, we came across some use cases that might be interesting pursuing in addition to a number of lessons learned worth sharing. In this paper, we will discuss identified requirements and architectural and implementation changes made to shape RouteFlow into a more robust solution for Software Defined networking (SDN). This paper addresses topics of interest to the SDN community, such as development issues involving layered applications on top of network controllers, ease of configuration, and network visualization. In addition, we will present the first publicly known use case with multiple, heterogeneous OpenFlow controllers to implement a centralized routing control function, demonstrating how IP routing as a service can be provided for different network domains under a single central control. Finally, performance comparisons and a real testbed were used as means of validating the implementation.

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


PowerPlay: Training an Increasingly General Problem Solver by Continually Searching for the Simplest Still Unsolvable Problem. Most of computer science focuses on automatically solving given computational problems. I focus on automatically inventing or discovering problems in a way inspired by the playful behavior of animals and humans, to train a more and more general problem solver from scratch in an unsupervised fashion. Consider the infinite set of all computable descriptions of tasks with possibly computable solutions. Given a general problem-solving architecture, at any given time, the novel algorithmic framework PowerPlay (Schmidhuber, 2011) searches the space of possible pairs of new tasks and modifications of the current problem solver, until it finds a more powerful problem solver that provably solves all previously learned tasks plus the new one, while the unmodified predecessor does not. Newly invented tasks may require to achieve a wow-effect by making previously learned skills more efficient such that they require less time and space. New skills may (partially) re-use previously learned skills. The greedy search of typical PowerPlay variants uses time-optimal program search to order candidate pairs of tasks and solver modifications by their conditional computational (time and space) complexity, given the stored experience so far. The new task and its corresponding task-solving skill are those first found and validated. This biases the search toward pairs that can be described compactly and validated quickly. The computational costs of validating new tasks need not grow with task repertoire size. Standard problem solver architectures of personal computers or neural networks tend to generalize by solving numerous tasks outside the self-invented training set; PowerPlay's ongoing search for novelty keeps breaking the generalization abilities of its present solver. This is related to Gödel's sequence of increasingly powerful formal theories based on adding

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Analysis on robust H∞ performance and stability for linear systems with interval time-varying state delays via some new augmented Lyapunov-Krasovskii functional. In this paper, the problem ofH1 performance and stability analysis for linear systems with interval time-varying delays is considered. First, by constructing a newly augmented Lyapunov–Krasovskii functional which has not been proposed yet, an improvedH1 performance criterion with the framework of linear matrix inequalities (LMIs) is introduced. Next, the result and method are extended to the problem of a delay-dependent stability criterion. Finally, numerical examples are given to show the superiority of proposed method. 2013 Elsevier Inc. All rights reserved.

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Analysis and Control of Multiphase Inductively Coupled Resonant Converter for Wireless Electric Vehicle Charger Applications. In this paper, an inductively coupled multiphase resonant converter is presented for wireless electric vehicle charging applications. As an alternative to the traditional frequency and phase shift control methods, a hybrid phase-frequency control strategy is implemented to improve the system efficiency. A theoretical analysis of the proposed system is carried out considering a wide battery state-of-charging range. In order to confirm the proposed converter and control technique, a laboratory prototype wireless charger is designed using 8-in air-gap coreless transformer and rectifier. The proposed control is compared with the conventional control methods for various load conditions at the different power levels. In comparison results, the proposed hybrid control methodology demonstrates the efficiency improvements of 1.1% at the heaviest load condition and 5.7% at the lightest load condition.

Question: How to control the inductor current of a resonant converter?


RDF-4X: a scalable solution for RDF quads store in the cloud. Resource Description Framework (RDF) represents a flexible and concise model for representing the metadata of resources on the web. Over the past years, with the increasing amount of RDF data, efficient and scalable RDF data management has become a fundamental challenge to achieve the Semantic Web vision. However, multiple approaches for RDF storage have been suggested, ranging from simple triple stores to more advanced techniques like vertical partitioning on the predicates or centralized approaches. Unfortunately, it is still a challenge to store a huge quantity of RDF quads due, in part, to the query processing for RDF data. This paper proposes a scalable solution for RDF data management that uses Apache Accumulo. We focus on introducing storage methods and indexing techniques that scale to billions of quads across multiple nodes, while providing fast and easy access to the data through conventional query mechanisms such as SPARQL. Our performance evaluation shows that in most cases our approach works well against large RDF datasets.

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The economic costs of pain in the United States.. UNLABELLED In 2008, according to the Medical Expenditure Panel Survey (MEPS), about 100 million adults in the United States were affected by chronic pain, including joint pain or arthritis. Pain is costly to the nation because it requires medical treatment and complicates treatment for other ailments. Also, pain lowers worker productivity. Using the 2008 MEPS, we estimated 1) the portion of total U.S. health care costs attributable to pain; and 2) the annual costs of pain associated with lower worker productivity. We found that the total costs ranged from $560 to $635 billion in 2010 dollars. The additional health care costs due to pain ranged from $261 to $300 billion. This represents an increase in annual per person health care costs ranging from $261 to $300 compared to a base of about $4,250 for persons without pain. The value of lost productivity due to pain ranged from $299 to $335 billion. We found that the annual cost of pain was greater than the annual costs of heart disease ($309 billion), cancer ($243 billion), and diabetes ($188 billion). Our estimates are conservative because they do not include costs associated with pain for nursing home residents, children, military personnel, and persons who are incarcerated.   PERSPECTIVE This study estimates that the national cost of pain ranges from $560 to $635 billion, larger than the cost of the nation's priority health conditions. Because of its economic toll on society, the nation should invest in research, education, and training to advocate the successful treatment, management, and prevention of pain.

Question: How much is the cost of pain in the united states?


Evaluation of Attention and Relaxation Levels of Archers in Shooting Process using Brain Wave Signal Analysis Algorithms. * Archer's capability of attention and relaxation control during shooting process was evaluated using EEG technology. Attention and meditation algorithms were used to represent the levels of mental concentration and relaxation levels. Elite, mid-level, and novice archers were tested for short and long distance shootings in the archery field. Single channel EEG was recorded on the forehead (Fp1) during the shooting process, and attention and meditation levels were computed by real time. Four types of variations were defined based on the increasing and decreasing patterns of attention and meditation levels during shooting process. Elite archers showed increases in both attention and relaxation while mid-level archers showed increased attention but decreased relaxation. Elite archers also showed higher levels of attention at the release than mid-level and novice archers. Levels of attention and relaxation and their variation patterns were useful to categorize archers and to provide feedback in training.

Question: How to categorize archers?


Should one compute the Temporal Difference fix point or minimize the Bellman Residual? The unified oblique projection view. We investigate projection methods, for evaluating a linear approximation of the value function of a policy in a Markov Decision Process context. We consider two popular approaches, the one-step Temporal Difference fix-point computation (TD(0)) and the Bellman Residual (BR) minimization. We describe examples, where each method outperforms the other. We highlight a simple relation between the objective function they minimize, and show that while BR enjoys a performance guarantee, TD(0) does not in general. We then propose a unified view in terms of oblique projections of the Bellman equation, which substantially simplifies and extends the characterization of Schoknecht (2002) and the recent analysis of Yu & Bertsekas (2008). Eventually, we describe some simulations that suggest that if the TD(0) solution is usually slightly better than the BR solution, its inherent numerical instability makes it very bad in some cases, and thus worse on average.

Question: What is the unified oblique projection view?


Developing and validating an instrument for measuring user-perceived web quality. Many of the instruments to measure information and system quality were developed in the context of mainframe and PC-based technologies of yesteryears. With the proliferation of the Internet and World Wide Web applications, users are increasingly interfacing and interacting with web-based applications. It is, therefore, important to develop new instruments and scales, which are directly targeted to these new interfaces and applications. In this article, we report on the development of an instrument that captures key characteristics of web site quality from the userâ€TMs perspective. The 25item instrument measures four dimensions of web quality: specific content, content quality, appearance and technical adequacy. While improvements are possible, the instrument exhibits excellent psychometric properties. The instrument would be useful to organizations and web designers as it provides an aggregate measure of web quality, and to researchers in related web research. a 1, b Purchase Export Previous article Next article Check if you have access through your login credentials or your institution.

Question: What is the difference between a web site and a web application?


Multiple asynchronous stimulus- and task-dependent hierarchies (STDH) within the visual brain's parallel processing systems.. Results from a variety of sources, some many years old, lead ineluctably to a re-appraisal of the twin strategies of hierarchical and parallel processing used by the brain to construct an image of the visual world. Contrary to common supposition, there are at least three 'feed-forward' anatomical hierarchies that reach the primary visual cortex (V1) and the specialized visual areas outside it, in parallel. These anatomical hierarchies do not conform to the temporal order with which visual signals reach the specialized visual areas through V1. Furthermore, neither the anatomical hierarchies nor the temporal order of activation through V1 predict the perceptual hierarchies. The latter shows that we see (and become aware of) different visual attributes at different times, with colour leading form (orientation) and directional visual motion, even though signals from fast-moving, high-contrast stimuli are among the earliest to reach the visual cortex (of area V5). Parallel processing, on the other hand, is much more ubiquitous than commonly supposed but is subject to a barely noticed but fundamental aspect of brain operations, namely that different parallel systems operate asynchronously with respect to each other and reach perceptual endpoints at different times. This re-assessment leads to the conclusion that the visual brain is constituted of multiple, parallel and asynchronously operating task- and stimulus-dependent hierarchies (STDH); which of these parallel anatomical hierarchies have temporal and perceptual precedence at any given moment is stimulus and task related, and dependent on the visual brain's ability to undertake multiple operations asynchronously.

Question: What is the visual brain?


A MapReduce Implementation of C 4 . 5 Decision Tree Algorithm. Recent years have witness the development of cloud computing and the big data era, which brings up challenges to traditional decision tree algorithms. First, as the size of dataset becomes extremely big, the process of building a decision tree can be quite time consuming. Second, because the data cannot fit in memory any more, some computation must be moved to the external storage and therefore increases the I/O cost. To this end, we propose to implement a typical decision tree algorithm, C4.5, using MapReduce programming model. Specifically, we transform the traditional algorithm into a series of Map and Reduce procedures. Besides, we design some data structures to minimize the communication cost. We also conduct extensive experiments on a massive dataset. The results indicate that our algorithm exhibits both time efficiency and scalability.

Question: What is a MapReduce implementation of C4.5?


The Parallel Knowledge Gradient Method for Batch Bayesian Optimization. In many applications of black-box optimization, one can evaluate multiple points simultaneously, e.g. when evaluating the performances of several different neural networks in a parallel computing environment. In this paper, we develop a novel batch Bayesian optimization algorithm — the parallel knowledge gradient method. By construction, this method provides the one-step Bayes optimal batch of points to sample. We provide an efficient strategy for computing this Bayes-optimal batch of points, and we demonstrate that the parallel knowledge gradient method finds global optima significantly faster than previous batch Bayesian optimization algorithms on both synthetic test functions and when tuning hyperparameters of practical machine learning algorithms, especially when function evaluations are noisy.

Question: How to find the global optimum of a function?


On the number of response regions of deep feed forward networks with piece-wise linear activations. This paper explores the complexity of deep feedforward networks with linear presynaptic couplings and rectified linear activations. This is a contribution to the growing body of work contrasting the representational power of deep and shallow network architectures. In particular, we offer a framework for comparing deep and shallow models that belong to the family of piecewise linear functions based on computational geometry. We look at a deep rectifier multi-layer perceptron (MLP) with linear outputs units and compare it with a single layer version of the model. In the asymptotic regime, when the number of inputs stays constant, if the shallow model has kn hidden units and n0 inputs, then the number of linear regions is O(k0n0). For a k layer model with n hidden units on each layer it is Ω(bn/n0c n0). The number bn/n0c grows faster than k0 when n tends to infinity or when k tends to infinity and n ≥ 2n0. Additionally, even when k is small, if we restrict n to be 2n0, we can show that a deep model has considerably more linear regions that a shallow one. We consider this as a first step towards understanding the complexity of these models and specifically towards providing suitable mathematical tools for future analysis.

Question: What is the complexity of deep feedforward networks with piece-wise linear activations?


Literature Review of Teamwork Models. Both human collaboration and software agent collaboration have been thoroughly studied, but there is relatively little research on hybrid human-agent teamwork. Some research has identified the roles that agents could play in hybrid teams: supporting individual team members, being a teammate, or supporting the team as a whole [99]. Some other work [57] has investigated trust concepts as the fundamental building block for effective human-agent teamwork or posited the types of shared knowledge that promote mutual understanding between cooperating humans and agents [9, 68]. However, many of the facets of human agent teamwork models, such as communication protocols for forming mutual intelligibility, performing team monitoring to assess progress, forming joint goals, addressing task interdependencies in hybrid teamwork are still unexplored. In this report, we address the following questions: 1. what factors affect human team task performance and cognition? 2. how can agent coordination mechanisms be adapted for human-agent teams? 3. with current technologies, what roles can agents successfully fill in hybrid human-agent teams? 4. what are the barriers to human-agent interaction?

Question: What factors affect human team task performance and cognition?