A Database for Handwritten Text Recognition Research. We propose in this correspondence a new method to perform two-class clustering of 2-D data in a quick and automatic way by preserving certain features of the input data. The method is analytical, deterministic, unsupervised, automatic, and noniterative. The computation time is of order n if the data size is n, and hence much faster than any other method which requires the computation of an n-by-n dissimilarity matrix. Furthermore, the proposed method does not have the trouble of guessing initial values. This new approach is thus more suitable for fast automatic hierarchical clustering or any other fields requiring fast automatic two-class clustering of 2-D data. The method can be extended to cluster data in higher dimensional space. A 3-D example is included.

Question: What is a database for handwritten text recognition research?


Identifying Analogies Across Domains. Identifying analogies across domains without supervision is an important task for artificial intelligence. Recent advances in cross domain image mapping have concentrated on translating images across domains. Although the progress made is impressive, the visual fidelity many times does not suffice for identifying the matching sample from the other domain. In this paper, we tackle this very task of finding exact analogies between datasets i.e. for every image from domain A find an analogous image in domain B. We present a matching-by-synthesis approach: AN-GAN, and show that it outperforms current techniques. We further show that the cross-domain mapping task can be broken into two parts: domain alignment and learning the mapping function. The tasks can be iteratively solved, and as the alignment is improved, the unsupervised translation function reaches quality comparable to full supervision.

Question: What is the difference between cross domain image mapping and cross domain image translation?


Point & Teleport Locomotion Technique for Virtual Reality. With the increasing popularity of virtual reality (VR) and new devices getting available with relatively lower costs, more and more video games have been developed recently. Most of these games use first person interaction techniques since it is more natural for Head Mounted Displays (HMDs). One of the most widely used interaction technique in VR video games is locomotion that is used to move user's viewpoint in virtual environments. Locomotion is an important component of video games since it can have a strong influence on user experience. In this study, a new locomotion technique we called "Point & Teleport" is described and compared with two commonly used VR locomotion techniques of walk-in-place and joystick. In this technique, users simply point where they want to be in virtual world and they are teleported to that position. As a major advantage, it is not expected to introduce motion sickness since it does not involve any visible translational motion. In this study, two VR experiments were designed and performed to analyze the Point & Teleport technique. In the first experiment, Point & Teleport was compared with walk-in-place and joystick locomotion techniques. In the second experiment, a direction component was added to the Point & Teleport technique so that the users could specify their desired orientation as well. 16 users took part in both experiments. Results indicated that Point & Teleport is a fun and user friendly locomotion method whereas the additional direction component degraded the user experience.

Question: What is the point and teleport locomotion technique?


Calcium currents in hair cells isolated from semicircular canals of the frog.. L-type and R-type Ca(2+) currents were detected in frog semicircular canal hair cells. The former was noninactivating and nifedipine-sensitive (5 microM); the latter, partially inactivated, was resistant to omega-conotoxin GVIA (5 microM), omega-conotoxin MVIIC (5 microM), and omega-agatoxin IVA (0.4 microM), but was sensitive to mibefradil (10 microM). Both currents were sensitive to Ni(2+) and Cd(2+) (>10 microM). In some cells the L-type current amplitude increased almost twofold upon repetitive stimulation, whereas the R-type current remained unaffected. Eventually, run-down occurred for both currents, but was prevented by the protease inhibitor calpastatin. The R-type current peak component ran down first, without changing its plateau, suggesting that two channel types generate the R-type current. This peak component appeared at -40 mV, reached a maximal value at -30 mV, and became undetectable for voltages > or =0 mV, suggestive of a novel transient current: its inactivation was indeed reversibly removed when Ba(2+) was the charge carrier. The L-type current and the R-type current plateau were appreciable at -60 mV and peaked at -20 mV: the former current did not reverse for voltages up to +60 mV, the latter reversed between +30 and +60 mV due to an outward Cs(+) current flowing through the same Ca(2+) channel. The physiological role of these currents on hair cell function is discussed.

Question: What is the physiological role of the Ca(2+) currents in hair cells?


CellSDN : Software-Defined Cellular Networks. Existing cellular networks suffer from inflexible and expen sive equipment, complex control-plane protocols, and vend orspecific configuration interfaces. In this paper, we argue th at software defined networking (SDN) can simplify the design and management of cellular data networks, while enabling new services. However, supporting many subscribers, frequent mobility, fine-grained measurement and control, and real-time adaptation introduces new scalability challeng es that future SDN architectures should address. As a first step , we present a software-defined cellular network architectur that (i) allows controller applications to express policie s based on the attributes of subscribers, rather than network addre sses and locations, (ii) enables real-time, fine-grained contro l via a local agent on each switch, and (iii) extends switches to support features like deep packet inspection and header com pression to meet the needs of cellular data services, (iv) su pports flexible "slicing" of network resources based on the at tributes of subscribers, rather than the packet header field s, and flexible "slicing" of base stations and radio resources b y having the controller to handle radio resource management, admission control and mobility in each slice.

Question: What is a software-defined cellular network?


Brain Activity during Simulated Deception: An Event-Related Functional Magnetic Resonance Study. TheGuilty Knowledge Test (GKT) has been used extensively to model deception. An association between the brain evoked response potentials and lying on the GKT suggests that deception may be associated with changes in other measures of brain activity such as regional blood flow that could be anatomically localized with event-related functional magnetic resonance imaging (fMRI). Blood oxygenation level-dependent fMRI contrasts between deceptive and truthful responses were measured with a 4 Tesla scanner in 18 participants performing the GKT and analyzed using statistical parametric mapping. Increased activity in the anterior cingulate cortex (ACC), the superior frontal gyrus (SFG), and the left premotor, motor, and anterior parietal cortex was specifically associated with deceptive responses. The results indicate that: (a) cognitive differences between deception and truth have neural correlates detectable by fMRI, (b) inhibition of the truthful response may be a basic component of intentional deception, and (c) ACC and SFG are components of the basic neural circuitry for deception.

Question: What is the difference between truth and deception?


Semi-supervised Learning by Entropy Minimization. We consider the semi-supervised learning problem, where a decision rule is to be learned from labeled and unlabeled data. In this framework, we motivate minimum entropy regularization, which enables to incorporate unlabeled data in the standard supervised learning. Our approach includes other approaches to the semi-supervised problem as particular or limiting cases. A series of experiments illustrates that the proposed solutions benefit from unlabeled data. The method challenges mixture models when the data are sampled from the distribution class spanned by the generative model. The performances are definitely in favor of minimum entropy regularization when generative models are misspecified, and the weighting of unlabeled data provides robustness to the violation of the "cluster assumption". Finally, we also illustrate that the method can also be far superior to manifold learning in high dimension spaces.

Question: What is the semi-supervised learning problem?


Outlier detection by active learning. Most existing approaches to outlier detection are based on density estimation methods. There are two notable issues with these methods: one is the lack of explanation for outlier flagging decisions, and the other is the relatively high computational requirement. In this paper, we present a novel approach to outlier detection based on classification, in an attempt to address both of these issues. Our approach isbased on two key ideas. First, we present a simple reduction of outlier detection to classification, via a procedure that involves applying classification to a labeled data set containing artificially generated examples that play the role of potential outliers. Once the task has been reduced to classification, we then invoke a selective sampling mechanism based on active learning to the reduced classification problem. We empirically evaluate the proposed approach using a number of data sets, and find that our method is superior to other methods based on the same reduction to classification, but using standard classification methods. We also show that it is competitive to the state-of-the-art outlier detection methods in the literature based on density estimation, while significantly improving the computational complexity and explanatory power.

Question: What is the difference between density estimation and classification?


Relations among children's social goals, implicit personality theories, and responses to social failure.. Two studies examined children's thought patterns in relation to their responses to social challenge. In Study 1, 4th and 5th graders tried out for a pen pal club under either a performance goal (stressing the evaluative nature of the tryout) or a learning goal (emphasizing the potential learning opportunities). In their behavior and attributions following rejection, children who were focused on a performance goal reacted with more helplessness, whereas children given a learning goal displayed a more mastery-oriented response. Study 2 found that in response to hypothetical socially challenging situations, 4th, 5th, and 6th graders who believed personality was nonmalleable (entity theorists) vs. malleable (incremental theorists) were more likely to endorse performance goals. Together, these studies indicate that children's goals in social situations are associated with their responses to social failure and are predicted by their implicit theories about their personality.

Question: What is the difference between a performance goal and a learning goal?


ITIL as common practice reference model for IT service management: formal assessment and implications for practice. Due to enhanced focus on the customer in the planning, development and delivery of information services, IT service management has become increasingly important. These days IT management is focussing particularly on the de facto standard ITIL (IT Infrastructure Library) for implementing IT service management. In doing this, deficits of the ITIL reference model are often being overlooked, the benefits are merely assumed and misunderstandings spread. This results in uncertainties, unfulfilled expectations and problems in the execution of ITIL transformation projects. Against this background the article critically assesses the ITIL reference model. A formal analysis of the model on the basis of established criteria according to the principles for proper modelling is undertaken and implications for IT management are deduced from this. Four case studies of ITIL transformation projects conducted for this purpose, as well as an analysis of the ITIL documents, serve as basis for the assessment.

Question: What is the ITIL reference model?


Comparative Metagenomics Reveals Host Specific Metavirulomes and Horizontal Gene Transfer Elements in the Chicken Cecum Microbiome. BACKGROUND The complex microbiome of the ceca of chickens plays an important role in nutrient utilization, growth and well-being of these animals. Since we have a very limited understanding of the capabilities of most species present in the cecum, we investigated the role of the microbiome by comparative analyses of both the microbial community structure and functional gene content using random sample pyrosequencing. The overall goal of this study was to characterize the chicken cecal microbiome using a pathogen-free chicken and one that had been challenged with Campylobacter jejuni.   METHODOLOGY/PRINCIPAL FINDINGS Comparative metagenomic pyrosequencing was used to generate 55,364,266 bases of random sampled pyrosequence data from two chicken cecal samples. SSU rDNA gene tags and environmental gene tags (EGTs) were identified using SEED subsystems-based annotations. The distribution of phylotypes and EGTs detected within each cecal sample were primarily from the Firmicutes, Bacteroidetes and Proteobacteria, consistent with previous SSU rDNA libraries of the chicken cecum. Carbohydrate metabolism and virulence genes are major components of the EGT content of both of these microbiomes. A comparison of the twelve major pathways in the SEED Virulence Subsystem (metavirulome) represented in the chicken cecum, mouse cecum and human fecal microbiomes showed that the metavirulomes differed between these microbiomes and the metavirulomes clustered by host environment. The chicken cecum microbiomes had the broadest range of EGTs within the SEED Conjugative Transposon Subsystem, however the mouse cecum microbiomes showed a greater abundance of EGTs in this subsystem. Gene assemblies (32 contigs) from one microbiome sample were predominately from the Bacteroidetes, and seven of these showed sequence similarity to transposases, whereas the remainin

Question: What is the chicken cecum microbiome?


Multipath TCP path schedulers for streaming video. Modern internet traffic is heavily composed of some form of video communication. In addition, video streaming is slowly replacing regular phone connections. Given that most video transport utilizes Video over Hypertext Transfer Protocol/Transmission Control Protocol (HTTP/TCP), it is important to understand TCP performance in transporting video streams. Recently, multipath transport protocols have allowed video streaming over multiple paths to become a reality. In this paper, we investigate packet scheduling disciplines for injecting video stream packets into multiple paths at the video server. We study video streaming performance when subjected to these schedulers in conjunction with various TCP variants. We utilize network performance measures, as well as video quality metrics, to characterize the performance and interactions between network and application layers of video streams for various network scenarios.

Question: What is the difference between multipath TCP and TCP?


Dynamic tire friction models for vehicle traction control. In this paper we derive a dynamic friction force model for road/tire interaction for ground vehicles. The model is based on a similar dynamic friction model for contact developed previously for contact-point friction problems, called the LuGre model [4]. We show that the dynamic LuGre friction model is able to accurately capture velocity and road/surface dependence of the tire friction force.

Question: What is the LuGre model?


Positive and negative emotional verbal stimuli elicit activity in the left amygdala.. The human amygdala's involvement in negative emotion is well established, but relatively little is known regarding its role in positive emotion. Here we examined the neural response to emotionally positive, negative, and neutral words using fMRI. Relative to neutral words, positive and negative emotional words elicited greater activity in the left amygdala. Positive but not negative words elicited activity in dorsal and ventral striatal regions which have been linked in previous neuroimaging studies to reward and positive affect, including caudate, putamen, globus pallidus, and accumbens. These findings provide the first direct evidence that the amygdala is involved in emotional reactions elicited by both positive and negative emotional words, and further indicate that positive words additionally activate brain regions related to reward.

Question: What is the amygdala?


SciMATE: A Novel MapReduce-Like Framework for Multiple Scientific Data Formats. Despite the popularity of MapReduce, there are several obstacles to applying it for developing scientific data analysis applications. Current MapReduce implementations require that data be loaded into specialized file systems, like the Hadoop Distributed File System (HDFS), whereas with rapidly growing size of scientific datasets, reloading data in another file system or format is not feasible. We present a framework that allows scientific data in different formats to be processed with a MapReduce like API. Our system is referred to as SciMATE, and is based on the MATE system developed at Ohio State. SciMATE is developed as a customizable system, which can be adapted to support processing on any of the scientific data formats. We have demonstrated the functionality of our system by creating instances that can be processing NetCDF and HDF5 formats as well as flat-files. We have also implemented three popular data mining applications and have evaluated their execution with each of the three instances of our system.

Question: SciMATE: A Novel MapReduce-Like Framework for Multiple Scientific Data Formats. Despite the popularity of MapReduce, there are several obstacles to applying it for developing scientific data analysis applications. Current MapReduce implementations require that data be loaded into specialized file systems, like the Hadoop Distributed File


Detecting Display Energy Hotspots in Android Apps. Energy consumption of mobile apps has become an important consideration as the underlying devices are constrained by battery capacity. Display represents a significant portion of an app's energy consumption. However, developers lack techniques to identify the user interfaces in their apps for which energy needs to be improved. In this paper, we present a technique for detecting display energy hotspots - user interfaces of a mobile app whose energy consumption is greater than optimal. Our technique leverages display power modeling and automated display transformation techniques to detect these hotspots and prioritize them for developers. In an evaluation on a set of popular Android apps, our technique was very accurate in both predicting energy consumption and ranking the display energy hotspots. Our approach was also able to detect display energy hotspots in 398 Android market apps, showing its effectiveness and the pervasiveness of the problem. These results indicate that our approach represents a potentially useful technique for helping developers to detect energy related problems and reduce the energy consumption of their mobile apps.

Question: How to detect display energy hotspots in android apps?


An insight into imbalanced Big Data classification: outcomes and challenges. BigData applications are emerging during the last years, and researchers frommany disciplines are aware of the high advantages related to the knowledge extraction from this type of problem. However, traditional learning approaches cannot be directly applied due to scalability issues. To overcome this issue, the MapReduce framework has arisen as a "de facto" solution. Basically, it carries out a "divide-andconquer" distributed procedure in a fault-tolerant way to adapt for commodity hardware.Being still a recent discipline, few research has been conducted on imbalanced classification for Big Data. The reasons behind this are mainly the difficulties in adapting standard techniques to the MapReduce programming style. Additionally, inner problems of imbalanced data, namely lack of data and small disjuncts, are accentuated during the data partitioning to fit theMapReduce programming style. This paper is designed under three main pillars. First, to present the first outcomes for imbalanced classification in Big Data problems, introducing the current B Alberto Fernández alberto@decsai.ugr.es Sara del Río srio@decsai.ugr.es Nitesh V. Chawla nchawla@nd.edu Francisco Herrera herrera@decsai.ugr.es 1 Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain 2 Department of Computer Science and Engineering, 384 Fitzpatrick Hall, University of Notre Dame, Notre Dame, IN 46556, USA 3 Interdisciplinary Center for Network Science and Applications, 384 Nieuwland Hall of Science, University of Notre Dame, Notre Dame, IN 46556, USA research state of this area. Second, to analyze the behavior of standard pre-processing techniques in this particular framework. Finally, taking into account the experimental results obtained throughout this work, we will carry out a discussion on the challenges and future directions for the topic.

Question: What is the state of the art in imbalanced classification for Big Data?


UWB antenna for brain stroke and brain tumour detection. UWB Pentagon antenna is designed to detect brain stroke and brain tumour. It is operating at a band from 3.3568– 12.604 GHz in free space and from 3.818 to 9.16 GHz on the normal head model. The antenna has dimensions of 44×30mm2. It is fabricated on FR4-substrate with relative permittivity 4.4 and thickness 1.5mm. The antenna is simulated on the CST Microwave Studio and measured using the network analyser. There is a good agreement between the measured and simulated results of the return loss of the antenna on human's head and head phantom.

Question: How does the antenna work?


Feeding State Modulates Behavioral Choice and Processing of Prey Stimuli in the Zebrafish Tectum. Animals use the sense of vision to scan their environment, respond to threats, and locate food sources. The neural computations underlying the selection of a particular behavior, such as escape or approach, require flexibility to balance potential costs and benefits for survival. For example, avoiding novel visual objects reduces predation risk but negatively affects foraging success. Zebrafish larvae approach small, moving objects ("prey") and avoid large, looming objects ("predators"). We found that this binary classification of objects by size is strongly influenced by feeding state. Hunger shifts behavioral decisions from avoidance to approach and recruits additional prey-responsive neurons in the tectum, the main visual processing center. Both behavior and tectal function are modulated by signals from the hypothalamic-pituitary-interrenal axis and the serotonergic system. Our study has revealed a neuroendocrine mechanism that modulates the perception of food and the willingness to take risks in foraging decisions.

Question: How does the hypothalamic-pituitary-interrenal axis modulate the perception of food and the willingness to take risks in foraging decisions?


MAPLSC: A novel multi-class classifier for medical diagnosis. Analysis of clinical records contributes to the Traditional Chinese Medicine (TCM) experience expansion and techniques promotion. More than two diagnostic classes (diagnostic syndromes) in the clinical records raise a popular data mining problem: multi-value classification. In this paper, we propose a novel multi-class classifier, named Multiple Asymmetric Partial Least Squares Classifier (MAPLSC). MAPLSC attempts to be robust facing imbalanced data distribution in the multi-value classification. Elaborated comparisons with other seven state-of-the-art methods on two TCM clinical datasets and four public microarray datasets demonstrate MAPLSC's remarkable improvements.

Question: What is a multi-value classifier?


RELIABLE ISLANDING DETECTION WITH ACTIVE MV NETWORK MANAGEMENT. Active management of distribution networks and different controllable resources will play a key role in future Smart Grids. This paper proposes that centralized active network management functionalities at MV level could also include an algorithm which in real time confirms reliable islanding detection with local measurements based passive method. The proposed algorithm continuously ensures that there is such reactive power unbalance, so that the operation point remains constantly outside the non-detection zone of the used passive islanding detection method. The effect of recent grid code requirements on the proposed scheme, like the P/f -droop control of DG units, has been also considered.

Question: How to detect reliable islanding?


A Locality Aware Convolutional Neural Networks Accelerator. The advantages of Convolutional Neural Networks (CNNs) with respect to traditional methods for visual pattern recognition have changed the field of machine vision. The main issue that hinders broad adoption of this technique is the massive computing workload in CNN that prevents real-time implementation on low-power embedded platforms. Recently, several dedicated solutions have been proposed to improve the energy efficiency and throughput, nevertheless the huge amount of data transfer involved in the processing is still a challenging issue. This work proposes a new CNN accelerator exploiting a novel memory access scheme which significantly improves data locality in CNN related processing. With this scheme, external memory access is reduced by 50% while achieving similar or even better throughput. The accelerator is implemented using 28nm CMOS technology. Implementation results show that the accelerator achieves a performance of 102GOp/s @800MHz while consuming 0.303mm2 in silicon area. Power simulation shows that the dynamic power of the accelerator is 68mW. Its flexibility is demonstrated by running various different CNN benchmarks.

Question: What is the size of the accelerator?


RHex: A Biologically Inspired Hexapod Runner. RHex is an untethered, compliant leg hexapod robot that travels at better than one body length per second over terrain few other robots can negotiate at all. Inspired by biomechanics insights into arthropod locomotion, RHex uses a clock excited alternating tripod gait to walk and run in a highly maneuverable and robust manner. We present empirical data establishing that RHex exhibits a dynamical ("bouncing") gait—its mass center moves in a manner ∗This work was supported in part by DARPA/SPAWAR under contract N66001-00-C-8026. Portions of the material reported here were first presented in a conference paper appearing in the collection (Altendorfer et al., 2000). 208 Altendorfer et al. well approximated by trajectories from a Spring Loaded Inverted Pendulum (SLIP)—characteristic of a large and diverse group of running animals, when its central clock, body mass, and leg stiffnesses are appropriately tuned. The SLIP template can function as a useful control guide in developing more complex autonomous locomotion behaviors such as registration via visual servoing, local exploration via visual odometry, obstacle avoidance, and, eventually, global mapping and localization.

Question: What is a SLIP?


Validation, verification, and testing techniques throughout the life cycle of a simulation study. Life cycle validation, verification, and testing (VV&T) is extremely important for the success of a simulation study. This paper surveys current software VV&T techniques and current simulation model VV&T techniques and describes how they can all be applied throughout the life cycle of a simulation study. The processes and credibility assessment stages of the life cycle are described and the applicability of the VV&T techniques for each stage is stated.

Question: What is the life cycle of a simulation study?


Trimming and Improving Skip-thought Vectors. The skip-thought model has been proven to be effective at learning sentence representations and capturing sentence semantics. In this paper, we propose a suite of techniques to trim and improve it. First, we validate a hypothesis that, given a current sentence, inferring the previous and inferring the next sentence provide similar supervision power, therefore only one decoder for predicting the next sentence is preserved in our trimmed skip-thought model. Second, we present a connection layer between encoder and decoder to help the model to generalize better on semantic relatedness tasks. Third, we found that a good word embedding initialization is also essential for learning better sentence representations. We train our model unsupervised on a large corpus with contiguous sentences, and then evaluate the trained model on 7 supervised tasks, which includes semantic relatedness, paraphrase detection, and text classification benchmarks. We empirically show that, our proposed model is a faster, lighter-weight and equally powerful alternative to the original skip-thought model.

Question: How to trim and improve skip-thought vectors?


Automatic design of low power CMOS buffer-chain circuit using differential evolutionary algorithm and particle swarm optimization. PSO and DE algorithms and its variants are used for the optimization of a buffer-chain circuit and the results of all the algorithms are compared in this literature. By testing these algorithms on different mathematical benchmark functions the best parameter values of buffer chain circuit are obtained in such a way that it reduces the error between simulated output and optimized output, hence giving the best circuit performance. Evolutionary algorithms are better in performance and speed than the classical methods. 130nm CMOS technology has been used in this work. With the help of these parameter values the circuit simulator gives the values of power consumption, symmetry, rise time and fall time, which are almost closer to the desired specification of the buffer chain circuit.

Question: How to design a buffer chain circuit?


Indoor optical wireless communication: potential and state-of-the-art. In recent years, interest in optical wireless (OW) as a promising complementary technology for RF technology has gained new momentum fueled by significant deployments in solid state lighting technology. This article aims at reviewing and summarizing recent advancements in OW communication, with the main focus on indoor deployment scenarios. This includes a discussion of challenges, potential applications, state of the art, and prospects. Related issues covered in this article are duplex transmission, multiple access, MAC protocols, and link capacity improvements.

Question: What is the state of the art in indoor optical wireless communication?


A Review of Information Quality Research - Develop a Research Agenda. Recognizing the substantial development of information quality research, this review article analyzes three major aspects of information quality research: information quality assessment, information quality management and contextual information quality. Information quality assessment is analyzed by three components: information quality problem, dimension and assessment methodology. Information quality management is analyzed from three perspectives: quality management, information management and knowledge management. Following an overview of contextual information quality, this article analyzes information quality research in the context of information system and decision making. The analyzing results reveal the potential research streams and current research limitations of information quality. Aiming at bridging the research gaps, we conclude by providing the research issues for future information quality research and implications for empirical applications.

Question: What is the difference between information quality assessment, information quality management and contextual information quality?


Stochastic Gradient Boosting. Gradient boosting constructs additive regression models by sequentially tting a simple parameterized function (base learner) to current \pseudo"{residuals by least{squares at each iteration. The pseudo{residuals are the gradient of the loss functional being minimized, with respect to the model values at each training data point, evaluated at the current step. It is shown that both the approximation accuracy and execution speed of gradient boosting can be substantially improved by incorporating randomization into the procedure. Speci cally, at each iteration a subsample of the training data is drawn at random (without replacement) from the full training data set. This randomly selected subsample is then used in place of the full sample to t the base learner and compute the model update for the current iteration. This randomized approach also increases robustness against overcapacity of the base learner. 1 Gradient Boosting In the function estimation problem one has a system consisting of a random \output" or \response" variable y and a set of random \input" or \explanatory" variables x = fx1; ; xng. Given a \training" sample fyi;xig N 1 of known (y;x){values, the goal is to nd a function F (x) that maps x to y, such that over the joint distribution of all (y;x){values, the expected value of some speci ed loss function (y; F (x)) is minimized F (x) = argmin F (x) Ey;x (y; F (x)): (1) Boosting approximates F (x) by an \additive" expansion of the form

Question: What is a gradient boosting algorithm?


Laboratory Experiments for Tsunamis Generated by Underwater Landslides: Comparison with Numerical Modeling. Three-dimensional experiments and fully nonlinear computations are performed at the University of Rhode Island, to investigate tsunami generation by underwater landslides. Each experiment consists of a solid landslide of idealized smooth shape sliding over a plane slope. Surface elevations are measured using very accurate gages placed at strategic locations. Gage calibration is performed using a newly developed automated system. Landslide acceleration is measured with a micro-accelerometer. The repeatability of experiments is first investigated, and then by varying the initial depth of the landslide, different conditions of wave non-linearity and dispersion are generated and compared. The principle of numerical modeling, using an earlier developed model, is briefly explained. One application is presented and results compared to experiments. The agreement of computations with the latter is quite good. In the model, horizontal velocities are found quite non-uniform over depth above the moving landslide. This would preclude using a long wave model for such landslide tsunami wave generation.

Question: What is the difference between a numerical model and an experiment?


Spine dynamics as a computational resource in spine-driven quadruped locomotion. Recent results suggest that compliance and non-linearity in physical bodies of soft robots may not be disadvantageous properties with respect to control, but rather of advantage. In the context of morphological computation one could see such complex structures as potential computational resources. In this study, we implement and exploit this view point in a spine-driven quadruped robot called Kitty by using its flexible spine as a computational resource. The spine is an actuated multi-joint structure consisting of a sequence of soft silicone blocks. Its complex dynamics are captured by a set of force sensors and used to construct a closed-loop to drive the motor commands. We use simple static, linear readout weights to combine the sensor values to generate multiple gait patterns (bounding, trotting, turning behavior). In addition, we demonstrate the robustness of the setup by applying strong external perturbations in form of additional loads. The system is able to fully recover to its nominal gait patterns (which are encoded in the linear readout weights) after the perturbation has vanished.

Question: What is a spine-driven quadruped robot?


Detection of small objects from high-resolution panchromatic satellite imagery based on supervised image segmentation. A new concept for the detection of small objects from modular optoelectronic multispectral scanner (MOMS-02) high spatial resolution panchromatic satellite imagery is presented. We combine supervised shape classification with unsupervised image segmentation in an iterative procedure which allows a target-oriented search for specific object shapes.

Question: How do you detect small objects from high-resolution panchromatic satellite imagery?


Accurate Singular Values of Bidiagonal Matrices. C Abstract om puting the singular valu es of a bidiagonal m atrix is the fin al phase of the stan dard algo-w rithm for the singular valu e decom position of a general m atrix. We present a ne w algorithm hich com putes all the singular valu es of a bidiagonal m atrix to high relative accuracy indepen-p dent of their m agn itudes. In contrast, the stan dard algorithm for bidiagonal m atrice s m ay com ute sm all singular valu es with no relative accuracy at all. Num erical experim ents sh ow th at K the new algorithm is com parable in speed to the stan dard algorithm , an d frequently faster. The stan dard algorithm for com puting the singular valu e decom position (SVD) of a gen-1 eral real m atrix A has two phases [7]:) Com pute orthogonal m atrices P an d Q su ch that B = P AQ is in bidiagonal form , i.e. 1 1 1 T 1. 2 has nonzero entries only on its diagonal an d first su perdiagonal) Com pute orthogonal m atrices P an d Q su ch that Σ = P BQ is diagonal an d nonnega-t i 2 2 2 T 2 ive. The diagonal entries σ of Σ are the singular values of A. We will take them to be-sorted in decreasing order: σ ≥ σ. The colum ns of Q = Q Q are the right singular vec i i + 1 1 2 t 1 2 ors, an d the colum ns of P= P P are the left singular vectors. n This process takes O (n) operations, where n is the dim ension of A. This is true eve 3 though Phase 2 is iterative, since it converges quickly in practice. The error an alysis o f this r u com bined procedure has a widely accepted conclusion [8], an d provided neither overflow no nderflow occurs m ay be su m m arized as follows: The com puted singular valu es σ differ from the true singular valu es of A by no m ore t 1 i han p (n). ε. A , where A = σ is the 2-norm of A, ε is the m ach ine precision, an d p (n) is a T slowly growing function of the dim ension n …

Question: What is the difference between the singular values and the singular vectors?


Comparisons of randomization and K-degree anonymization schemes for privacy preserving social network publishing. Many applications of social networks require identity and/or relationship anonymity due to the sensitive, stigmatizing, or confidential nature of user identities and their behaviors. Recent work showed that the simple technique of anonymizing graphs by replacing the identifying information of the nodes with random ids does not guarantee privacy since the identification of the nodes can be seriously jeopardized by applying background based attacks. In this paper, we investigate how well an edge based graph randomization approach can protect node identities and sensitive links. We quantify both identity disclosure and link disclosure when adversaries have one specific type of background knowledge (i.e., knowing the degrees of target individuals). We also conduct empirical comparisons with the recently proposed K-degree anonymization schemes in terms of both utility and risks of privacy disclosures.

Question: How well does the k-degree anonymization scheme protect node identities?


Classification for Fraud Detection with Social Network Analysis. Worldwide fraud conducts to big losses to states' treasuries and to private companies. Because of that, motivations to detect and fight fraud are high, but despite continuous efforts, it is far from being accomplished. The problems faced when trying to characterize fraud activities are many, with the specificities of fraud on each business domain leading the list. Despite the differences, building a classifier for fraud detection almost always requires to deal with unbalanced datasets, since fraudulent records are usually in a small number when compared with the nonfraudulent ones. This work describes two types of techniques to deal with fraud detection: techniques at a preprocessing level where the goal is to balance the dataset, and techniques at a processing level where the objective is to apply different errors costs to fraudulent and non-fraudulent cases. Besides that, as organizations and people more often do associations in order to commit fraud, is proposed a new method to make use of that information to improve the training of classifiers for fraud detection. In particular, this new method identifies patterns among the social networks for fraudulent organizations, and uses them to enrich the description of its entity. The enriched data will then be used jointly with balancing techniques to produce a better classifier to identify fraud.

Question: How to detect fraud?


Testing the significance of a correlation with nonnormal data: comparison of Pearson, Spearman, transformation, and resampling approaches.. It is well known that when data are nonnormally distributed, a test of the significance of Pearson's r may inflate Type I error rates and reduce power. Statistics textbooks and the simulation literature provide several alternatives to Pearson's correlation. However, the relative performance of these alternatives has been unclear. Two simulation studies were conducted to compare 12 methods, including Pearson, Spearman's rank-order, transformation, and resampling approaches. With most sample sizes (n ≥ 20), Type I and Type II error rates were minimized by transforming the data to a normal shape prior to assessing the Pearson correlation. Among transformation approaches, a general purpose rank-based inverse normal transformation (i.e., transformation to rankit scores) was most beneficial. However, when samples were both small (n ≤ 10) and extremely nonnormal, the permutation test often outperformed other alternatives, including various bootstrap tests.

Question: What is the difference between Pearson, Spearman, transformation, and resampling approaches?


FELICS - Fair Evaluation of Lightweight Cryptographic Systems. In this paper we introduce FELICS, a free and open-source benchmarking framework designed for fair and consistent evaluation of software implementations of lightweight cryptographic primitives for embedded devices. The framework is very flexible thanks to its modular structure, which allows for an easy integration of new metrics, target devices and evaluation scenarios. It consists of two modules that can currently asses the performance of lightweight block and stream ciphers on three widely used microcontrollers: 8-bit AVR, 16-bit MSP and 32-bit ARM. The metrics extracted are execution time, RAM consumption and binary code size. FELICS has a simple user interface and is intended to be used by cipher designers to compare new primitives with the state of the art. The extracted metrics are very detailed and assist embedded software engineers in selecting the best cipher to match the requirements of a particular application. The tool aims to increase the transparency and trust in benchmarking results of lightweight primitives and facilitates a fair comparison between different primitives using the same evaluation conditions.

Question: What is a lightweight cryptographic primitive?


Learning Rapid-Temporal Adaptations. A hallmark of human intelligence and cognition is its flexibility. One of the longstanding goals in AI research is to replicate this flexibility in a learning machine. In this work we describe a mechanism by which artificial neural networks can learn rapid-temporal adaptation – the ability to adapt quickly to new environments or tasks – that we call adaptive neurons. Adaptive neurons modify their activations with task-specific values retrieved from a working memory. On standard metalearning and few-shot learning benchmarks in both vision and language domains, models augmented with adaptive neurons achieve state-of-the-art results.

Question: What is the metalearning benchmark?


Microcontroller Based Wireless Temperature And Heart Beat Read-Out. In this paper, we propose a Simple Wireless transmission System using common approach Sensor Platform called The wireless based Patient Sensor platform (WSP, Sensor Node) which has remote access capability. The goals of the WSP are to establish: Standard sensor node (System on module), a common software .The proposed platform architecture (Sensor Node) offers flexibility, easy customization for different vital parameter collecting and sending. An prototype has been established based on wireless communication channel. Wireless lan (IEEE .802.15.4)) has been used as communication channel on our prototype (Sensor node). Desire sensor information (vital parameter) can be viewed remotely, and also vital parameter can be adjusted to meet demand.

Question: What is the difference between a sensor node and a sensor platform?


Attention estimation by simultaneous analysis of viewer and view. This paper introduces a system for estimating the attention of a driver wearing a first person view camera using salient objects to improve gaze estimation. A challenging data set of pedestrians crossing intersections has been captured using Google Glass worn by a driver. A challenge unique to first person view from cars is that the interior of the car can take up a large part of the image. The proposed system automatically filters out the dashboard of the car, along with other parts of the instrumentation. The remaining area is used as a region of interest for a pedestrian detector. Two cameras looking at the driver are used to determine the direction of the driver's gaze, by examining the eye corners and the center of the iris. This coarse gaze estimation is then linked to the detected pedestrians to determine which pedestrian the driver is focused on at any given time.

Question: How to estimate the attention of a driver wearing a first person view camera?


Reliable Client Accounting for P2P-Infrastructure Hybrids. Content distribution networks (CDNs) have started to adopt hybrid designs, which employ both dedicated edge servers and resources contributed by clients. Hybrid designs combine many of the advantages of infrastructurebased and peer-to-peer systems, but they also present new challenges. This paper identifies reliable client accounting as one such challenge. Operators of hybrid CDNs are accountable to their customers (i.e., content providers) for the CDN's performance. Therefore, they need to offer reliable quality of service and a detailed account of content served. Service quality and accurate accounting, however, depend in part on interactions among untrusted clients. Using the Akamai NetSession client network in a case study, we demonstrate that a small number of malicious clients used in a clever attack could cause significant accounting inaccuracies. We present a method for providing reliable accounting of client interactions in hybrid CDNs. The proposed method leverages the unique characteristics of hybrid systems to limit the loss of accounting accuracy and service quality caused by faulty or compromised clients. We also describe RCA, a system that applies this method to a commercial hybrid content-distribution network. Using trace-driven simulations, we show that RCA can detect and mitigate a variety of attacks, at the expense of a moderate increase in logging overhead.

Question: What is a hybrid CDN?


Counterintuitive Behavior of Social Systems. This paper addresses several social concerns: population trends; quality of urban life; policies for urban growth; and the unexpected, ineffective, or detrimental results often generated by government programs. Society becomes frustrated as repeated attacks on deficiencies in social systems lead only to worse symptoms. Legislation is debated and passed with great hope, but many programs prove to be ineffective. Results are often far short of expectations. Because dynamic behavior of social systems is not understood, government programs often cause exactly the reverse of desired results. The field of system dynamics now can explain how such contrary results happen. Fundamental reasons cause people to misjudge behavior of social systems. Orderly processes in creating human judgment and intuition lead people to wrong decisions when faced with complex and highly interacting systems. Until we reach a much better public understanding of social systems, attempts to develop corrective programs for social troubles will continue to be disappointing. This paper cautions against continuing to depend on the same past approaches that have led to present feelings of frustration. New methods developed over the last 30 years will lead to a better understanding of social systems and thereby to more effective policies for guiding the future. 1 Updated March, 1995. This paper was first copyrighted © 1971 by Jay W. Forrester. It is based on testimony for the Subcommittee on Urban Growth of the Committee on Banking and Currency, U.S. House of Representatives, on October 7, 1970. The original text appeared in the January, 1971, issue of the Technology Review published by the Alumni Association of the Massachusetts Institute of Technology. All figures are taken from World Dynamics by Jay W. Forrester, Productivity Press, Portland, Oregon. 2 Germeshausen Professor Emeritus and Senior Lecturer, Massachusetts Institute of Technology, Cambridge, MA,

Question: What is the population of canada?


Detection of covert attacks on cyber-physical systems by extending the system dynamics with an auxiliary system. Securing cyber-physical systems is vital for our modern society since they are widely used in critical infrastructure like power grid control and water distribution. One of the most sophisticated attacks on these systems is the covert attack, where an attacker changes the system inputs and disguises his influence on the system outputs by changing them accordingly. In this paper an approach to detect such an attack by extending the original system with a switched auxiliary system is proposed. Furthermore, a detection system using a switched Luenberger observer is presented. The effectiveness of the proposed method is illustrated by a simulation example.

Question: How to detect covert attacks on cyber-physical systems?


We don't need another hero.. Everybody loves the stories of heroes like Martin Luther King, Jr., Mother Teresa, and Gandhi. But the heroic model of moral leadership usually doesn't work in the corporate world. Modesty and restraint are largely responsible for the achievements of the most effective moral leaders in business. The author, a specialist in business ethics, says the quiet leaders he has studied follow four basic rules in meeting ethical challenges and making decisions. The rules constitute an important resource for executives who want to encourage the development of such leaders among their middle managers. The first rule is "Put things off till tomorrow." The passage of time allows turbulent waters to calm and lets leaders' moral instincts emerge. "Pick your battles" means that quiet leaders don't waste political capital on fights they can't win; they save it for occasions when they really want to fight. "Bend the rules, don't break them" sounds easier than it is--bending the rules in order to resolve a complicated situation requires imagination, discipline, restraint, flexibility, and entrepreneurship. The fourth rule, "Find a compromise," reflects the author's finding that quiet leaders try not to see situations as polarized tests of ethical principles. These individuals work hard to craft compromises that are "good enough"--responsible and workable enough--to satisfy themselves, their companies, and their customers. The vast majority of difficult problems are solved through the consistent striving of people working far from the limelight. Their quiet approach to leadership doesn't inspire, thrill, or provide story lines for uplifting TV shows. But the unglamorous efforts of quiet leaders make a tremendous difference every day in the corporate world.

Question: What is the difference between a hero and a quiet leader?


ADDITIVE LOGISTIC REGRESSION : A STATISTICAL VIEW OF BOOSTING. Boosting is one of the most important recent developments in classification methodology. Boosting works by sequentially applying a classification algorithm to reweighted versions of the training data and then taking a weighted majority vote of the sequence of classifiers thus produced. For many classification algorithms, this simple strategy results in dramatic improvements in performance. We show that this seemingly mysterious phenomenon can be understood in terms of well-known statistical principles, namely additive modeling and maximum likelihood. For the two-class problem, boosting can be viewed as an approximation to additive modeling on the logistic scale using maximum Bernoulli likelihood as a criterion. We develop more direct approximations and show that they exhibit nearly identical results to boosting. Direct multiclass generalizations based on multinomial likelihood are derived that exhibit performance comparable to other recently proposed multiclass generalizations of boosting in most situations, and far superior in some. We suggest a minor modification to boosting that can reduce computation, often by factors of 10 to 50. Finally, we apply these insights to produce an alternative formulation of boosting decision trees. This approach, based on best-first truncated tree induction, often leads to better performance, and can provide interpretable descriptions of the aggregate decision rule. It is also much faster computationally, making it more suitable to large-scale data mining applications.

Question: What is boosting?


The many faces of publish/subscribe. Well adapted to the loosely coupled nature of distributed interaction in large-scale applications, the publish/subscribe communication paradigm has recently received increasing attention. With systems based on the publish/subscribe interaction scheme, subscribers register their interest in an event, or a pattern of events, and are subsequently asynchronously notified of events generated by publishers. Many variants of the paradigm have recently been proposed, each variant being specifically adapted to some given application or network model. This paper factors out the common denominator underlying these variants: full decoupling of the communicating entities in time, space, and synchronization. We use these three decoupling dimensions to better identify commonalities and divergences with traditional interaction paradigms. The many variations on the theme of publish/subscribe are classified and synthesized. In particular, their respective benefits and shortcomings are discussed both in terms of interfaces and implementations.

Question: What is the difference between publish/subscribe and event-driven programming?


DRAM errors in the wild: a large-scale field study. Errors in dynamic random access memory (DRAM) are a common form of hardware failure in modern compute clusters. Failures are costly both in terms of hardware replacement costs and service disruption. While a large body of work exists on DRAM in laboratory conditions, little has been reported on real DRAM failures in large production clusters. In this paper, we analyze measurements of memory errors in a large fleet of commodity servers over a period of 2.5 years. The collected data covers multiple vendors, DRAM capacities and technologies, and comprises many millions of DIMM days.  The goal of this paper is to answer questions such as the following: How common are memory errors in practice? What are their statistical properties? How are they affected by external factors, such as temperature and utilization, and by chip-specific factors, such as chip density, memory technology and DIMM age?  We find that DRAM error behavior in the field differs in many key aspects from commonly held assumptions. For example, we observe DRAM error rates that are orders of magnitude higher than previously reported, with 25,000 to 70,000 errors per billion device hours per Mbit and more than 8% of DIMMs affected by errors per year. We provide strong evidence that memory errors are dominated by hard errors, rather than soft errors, which previous work suspects to be the dominant error mode. We find that temperature, known to strongly impact DIMM error rates in lab conditions, has a surprisingly small effect on error behavior in the field, when taking all other factors into account. Finally, unlike commonly feared, we don't observe any indication that newer generations of DIMMs have worse error behavior.

Question: How common are memory errors in practice?


Hand segmentation for hand-object interaction from depth map. Hand segmentation for hand-object interaction is a necessary preprocessing step in many applications such as augmented reality, medical application, and human-robot interaction. However, typical methods are based on color information which is not robust to objects with skin color, skin pigment difference, and light condition variations. Thus, we propose hand segmentation method for hand-object interaction using only a depth map. It is challenging because of the small depth difference between a hand and objects during an interaction. To overcome this challenge, we propose the two-stage random decision forest (RDF) method consisting of detecting hands and segmenting hands. To validate the proposed method, we demonstrate results on the publicly available dataset of hand segmentation for hand-object interaction. The proposed method achieves high accuracy in short processing time comparing to the other state-of-the-art methods.

Question: How to segment a hand from a depth map?


Sample Preparation on Micro-Electrode-Dot-Array Digital Microfluidic Biochips. Sample preparation in digital microfluidics refers to the generation of droplets with target concentrations for onchip biochemical applications. In recent years, digital microfluidic biochips (DMFBs) have been adopted as a platform for sample preparation. However, there remain one major problem associated with sample preparation on a conventional DMFB. For conventional DMFBs, only a (1:1) mixing/splitting model can be used, leading to an increase in the number of fluidic operations required for sample preparation. To overcome the drawback, we adopt a next generation DMFB platform, referred to as micro-electrode-dot-array (MEDA), for sample preparation. We propose the first sample preparation method that exploits the MEDA-specific advantages of fine-grained control of droplet sizes and real-time droplet sensing. Experimental demonstration using a fabricated MEDA biochip and simulation results highlight the effectiveness of the proposed sample-preparation method.

Question: How to prepare a sample for a biochip?


Introduction to E-commerce Learning Objectives. ● To understand the complexity of e-commerce and its many facets. ● To explore how e-business and e-commerce fit together. ● To identify the impact of e-commerce. ● To recognise the benefits and limitations of e-commerce. ● To use classification frameworks for analysing e-commerce. ● To identify the main barriers to the growth and development of e-commerce in organisations.  Even today, some considerable time after the so called 'dot com/Internet revolution', electronic commerce (e-commerce) remains a relatively new, emerging and constantly changing area of business management and information technology. There has been and continues to be much publicity and discussion about e-commerce. Library catalogues and shelves are filled with books and articles on the subject. However, there remains a sense of confusion, suspicion and misunderstanding surrounding the area, which has been exacerbated by the different contexts in which electronic commerce is used, coupled with the myriad related buzzwords and acronyms. This book aims to consolidate the major themes that have arisen from the new area of electronic commerce and to provide an understanding of its application and importance to management. In order to understand electronic commerce it is important to identify the different terms that are used, and to assess their origin and usage. According to the editor-in-chief of International Journal of Electronic Commerce , Vladimir Zwass, 'Electronic commerce is sharing business information , maintaining business relationships and conducting business transactions by means of telecommunications networks'. 1 He maintains that in its purest form, electronic commerce has existed for over 40 years, originating from the electronic transmission of messages during the Berlin airlift in 1948. 2 From this, electronic data interchange (EDI) was the next stage of e-commerce development. In the 1960s a cooperative effort between industry grou

Question: What is the difference between electronic commerce and electronic data interchange?


Battery-Draining-Denial-of-Service Attack on Bluetooth Devices. We extend the Xen virtual machine monitor with the ability to host a hundred of virtual machines on a single physical node. Similarly to a demand paging of virtual memory, we page out idle virtual machines making them available on demand. Paging is transparent. An idle virtual machine remains fully operational. It is able to respond to external events with a delay comparable to a delay under a medium load. To achieve desired degree of consolidation, we identify and leave in memory only a minimal working set of pages required to maintain the illusion of running VM and respond to external events. To keep the number of active pages small without harming performance dramatically, we build a correspondence between every event and its working set. Reducing a working set further, we implement a copy-on-write page sharing across virtual machines running on the same host. To decrease resources occupied by a virtual machine's file system, we implement a copy-on-write storage and golden imaging.

Question: What is the size of the virtual machine monitor?


A Generic Coordinate Descent Framework for Learning from Implicit Feedback. In recent years, interest in recommender research has shifted from explicit feedback towards implicit feedback data. A diversity of complex models has been proposed for a wide variety of applications. Despite this, learning from implicit feedback is still computationally challenging. So far, most work relies on stochastic gradient descent (SGD) solvers which are easy to derive, but in practice challenging to apply, especially for tasks with many items. For the simple matrix factorization model, an efficient coordinate descent (CD) solver has been previously proposed. However, efficient CD approaches have not been derived for more complex models. In this paper, we provide a new framework for deriving efficient CD algorithms for complex recommender models. We identify and introduce the property of k-separable models. We show that k-separability is a sufficient property to allow efficient optimization of implicit recommender problems with CD. We illustrate this framework on a variety of state-of-the-art models including factorization machines and Tucker decomposition. To summarize, our work provides the theory and building blocks to derive efficient implicit CD algorithms for complex recommender models.

Question: What is the difference between a matrix factorization model and a factorization machine model?


Context-aware query suggestion by mining click-through and session data. Query suggestion plays an important role in improving the usability of search engines. Although some recently proposed methods can make meaningful query suggestions by mining query patterns from search logs, none of them are context-aware - they do not take into account the immediately preceding queries as context in query suggestion. In this paper, we propose a novel context-aware query suggestion approach which is in two steps. In the offine model-learning step, to address data sparseness, queries are summarized into concepts by clustering a click-through bipartite. Then, from session data a concept sequence suffix tree is constructed as the query suggestion model. In the online query suggestion step, a user's search context is captured by mapping the query sequence submitted by the user to a sequence of concepts. By looking up the context in the concept sequence sufix tree, our approach suggests queries to the user in a context-aware manner. We test our approach on a large-scale search log of a commercial search engine containing 1:8 billion search queries, 2:6 billion clicks, and 840 million query sessions. The experimental results clearly show that our approach outperforms two baseline methods in both coverage and quality of suggestions.

Question: What is the context-aware query suggestion approach?


Aneka Cloud Application Platform and Its Integration with Windows Azure. Aneka is an Application Platform-as-a-Service (Aneka PaaS) for Cloud Computing. It acts as a framework for building customized applications and deploying them on either public or private Clouds. One of the key features of Aneka is its support for provisioning resources on different public Cloud providers such as Amazon EC2, Windows Azure and GoGrid. In this chapter, we will present Aneka platform and its integration with one of the public Cloud infrastructures, Windows Azure, which enables the usage of Windows Azure Compute Service as a resource provider of Aneka PaaS. The integration of the two platforms will allow users to leverage the power of Windows Azure Platform for Aneka Cloud Computing, employing a large number of compute instances to run their applications in parallel. Furthermore, customers of the Windows Azure platform can benefit from the integration with Aneka PaaS by embracing the advanced features of Aneka in terms of multiple programming models, scheduling and management services, application execution services, accounting and pricing services and dynamic provisioning services. Finally, in addition to the Windows Azure Platform we will illustrate in this chapter the integration of Aneka PaaS with other public Cloud platforms such as Amazon EC2 and GoGrid, and virtual machine management platforms such as Xen Server. The new support of provisioning resources on Windows Azure once again proves the adaptability, extensibility and flexibility of Aneka.

Question: What is the cloud computing platform?


Image-guided full waveform inversion. Multiple problems, including high computational cost, spurious local minima, and solutions with no geologic sense, have prevented widespread application of full waveform inversion (FWI), especially FWI of seismic reflections. These problems are fundamentally related to a large number of model parameters and to the absence of low frequencies in recorded seismograms. Instead of inverting for all the parameters in a dense model, image-guided full waveform inversion inverts for a sparse model space that contains far fewer parameters. We represent a model with a sparse set of values, and from these values, we use image-guided interpolation (IGI) and its adjoint operator to compute finelyand uniformly-sampled models that can fit recorded data in FWI. Because of this sparse representation, image-guided FWI updates more blocky models, and this blockiness in the model space mitigates the absence of low frequencies in recorded data. Moreover, IGI honors imaged structures, so image-guided FWI built in this way yields models that are geologically sensible.

Question: What is image-guided full waveform inversion?


Improved Option Pricing Using Artificial Neural Networks and Bootstrap Methods. A hybrid neural network is used to predict the difference between the conventional option-pricing model and observed intraday option prices for stock index option futures. Confidence intervals derived with bootstrap methods are used in a trading strategy that only allows trades outside the estimated range of spurious model fits to be executed. Whilst hybrid neural network option pricing models can improve predictions they have bias. The hybrid option-pricing bias can be reduced with bootstrap methods. A modified bootstrap predictor is indexed by a parameter that allows the predictor to range from a pure bootstrap predictor, to a hybrid predictor, and finally the bagging predictor. The modified bootstrap predictor outperforms the hybrid and bagging predictors. Greatly improved performance was observed on the boundary of the training set and where only sparse training data exists. Finally, bootstrap bias estimates were studied.

Question: What is the modified bootstrap predictor?


Personalized recommendation engine using HADOOP. More and more E-commerce Websites provide products with different prices which made it hard for consumers to find the products and services they want. In order to overcome this data overload, personalized recommendation engines are used to suggest products and to provide consumers with relevant data to help them decide which products to purchase. Recommendation engines are highly computational and hence ideal for the Hadoop Platform. This system aims at building a book recommendation engine which uses item or user based recommendation from Mahout for recommending books. It will analyze the data and give suggestions based on what similar users did and on the past transaction history of the user.

Question: What is the Hadoop platform?


Development and validation of measures of social phobia scrutiny fear and social interaction anxiety.. The development and validation of the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) two companion measures for assessing social phobia fears is described. The SPS assesses fear of being scrutinised during routine activities (eating, drinking, writing, etc.), while the SIAS assesses fear of more general social interaction, the scales corresponding to the DSM-III-R descriptions of Social Phobia--Circumscribed and Generalised types, respectively. Both scales were shown to possess high levels of internal consistency and test-retest reliability. They discriminated between social phobia, agoraphobia and simple phobia samples, and between social phobia and normal samples. The scales correlated well with established measures of social anxiety, but were found to have low or non-significant (partial) correlations with established measures of depression, state and trait anxiety, locus of control, and social desirability. The scales were found to change with treatment and to remain stable in the face of no-treatment. It appears that these scales are valid, useful, and easily scored measures for clinical and research applications, and that they represent an improvement over existing measures of social phobia.

Question: What is social phobia?


A Privacy Preservation Model for Facebook-Style Social Network Systems. Recent years have seen unprecedented growth in the popularity of social network systems, with Facebook being an archetypical example. The access control paradigm behind the privacy preservation mechanism of Facebook is distinctly different from such existing access control paradigms as Discretionary Access Control, Role-Based Access Control, Capability Systems, and Trust Management Systems. This work takes a first step in deepening the understanding of this access control paradigm, by proposing an access control model that formalizes and generalizes the privacy preservation mechanism of Facebook. The model can be instantiated into a family of Facebook-style social network systems, each with a recognizably different access control mechanism, so that Facebook is but one instantiation of the model. We also demonstrate that the model can be instantiated to express policies that are not currently supported by Facebook but possess rich and natural social significance. This work thus delineates the design space of privacy preservation mechanisms for Facebook-style social network systems, and lays out a formal framework for policy analysis in these systems.

Question: What is the privacy preservation mechanism of facebook?


Evaluation of object-oriented design patterns in game development. The use of object-oriented design patterns in game development is being evaluated in this paper. Games' quick evolution, demands great flexibility, code reusability and low maintenance costs. Games usually differentiate between versions, in respect of changes of the same type (additional animation, terrains etc). Consequently, the application of design patterns in them can be beneficial regarding maintainability. In order to investigate the benefits of using design patterns, a qualitative and a quantitative evaluation of open source projects is being performed. For the quantitative evaluation, the projects are being analyzed by reverse engineering techniques and software metrics are calculated. 2006 Elsevier B.V. All rights reserved.

Question: What is the benefit of using design patterns in game development?


Frontal fibrosing alopecia: a clinical review of 36 patients.. BACKGROUND Frontal fibrosing alopecia (FFA) is a primary lymphocytic cicatricial alopecia with a distinctive clinical pattern of progressive frontotemporal hairline recession. Currently, there are no evidence-based studies to guide treatment for patients with FFA; thus, treatment options vary among clinicians.   OBJECTIVES We report clinical findings and treatment outcomes of 36 patients with FFA, the largest cohort to date. Further, we report the first evidence-based study of the efficacy of hydroxychloroquine in FFA using a quantitative clinical score, the Lichen Planopilaris Activity Index (LPPAI).   METHODS A retrospective case note review was performed of 36 adult patients with FFA. Data were collected on demographics and clinical findings. Treatment responses to hydroxychloroquine, doxycycline and mycophenolate mofetil were assessed using the LPPAI. Adverse events were monitored.   RESULTS Most patients in our cohort were female (97%), white (92%) and postmenopausal (83%). Apart from hairline recession, 75% also reported eyebrow loss. Scalp pruritus (67%) and perifollicular erythema (86%) were the most common presenting symptom and sign, respectively. A statistically significant reduction in signs and symptoms in subjects treated with hydroxychloroquine (P < 0·05) was found at both 6- and 12-month follow up.   CONCLUSIONS In FFA, hairline recession, scalp pruritus, perifollicular erythema and eyebrow loss are common at presentation. Despite the limitations of a retrospective review, our data reveal that hydroxychloroquine is significantly effective in reducing signs and symptoms of FFA after both 6 and 12 months of treatment. However, the lack of a significant reduction in signs and symptoms between 6 and 12 months indicates that the maximal benefits of hydroxychloroquine are evident within the first 6 months of use.

Question: What is the largest cohort of patients with frontal fibrosing alopecia?


Elliptic operator for shape analysis. Many shape analysis methods treat the geometry of an object as a metric space that can be captured by the Laplace-Beltrami operator. In this paper, we propose to adapt a classical operator from quantum mechanics to the field of shape analysis where we suggest to integrate a scalar function through a unified elliptical Hamiltonian operator. We study the addition of a potential function to the Laplacian as a generator for dual spaces in which shape processing is performed. Then, we evaluate the resulting spectral basis for different applications such as mesh compression and shape matching. The suggested operator is shown to produce better functional spaces to operate with, as demonstrated by the proposed framework that outperforms existing spectral methods, for example, when applied to shape matching benchmarks.

Question: What is the elliptic operator for shape analysis?


Clinical spinal instability and low back pain.. Clinical instability is an important cause of low back pain. Although there is some controversy concerning its definition, it is most widely believed that the loss of normal pattern of spinal motion causes pain and/or neurologic dysfunction. The stabilizing system of the spine may be divided into three subsystems: (1) the spinal column; (2) the spinal muscles; and (3) the neural control unit. A large number of biomechanical studies of the spinal column have provided insight into the role of the various components of the spinal column in providing spinal stability. The neutral zone was found to be a more sensitive parameter than the range of motion in documenting the effects of mechanical destabilization of the spine caused by injury and restabilization of the spine by osteophyle formation, fusion or muscle stabilization. Clinical studies indicate that the application of an external fixator to the painful segment of the spine can significantly reduce the pain. Results of an in vitro simulation of the study found that it was most probably the decrease in the neutral zone, which was responsible for pain reduction. A hypothesis relating the neutral zone to pain has been presented. The spinal muscles provide significant stability to the spine as shown by both in vitro experiments and mathematical models. Concerning the role of neuromuscular control system, increased body sway has been found in patients with low back pain, indicating a less efficient muscle control system with decreased ability to provide the needed spinal stability.

Question: What is the role of the spinal muscles in providing spinal stability?


The feeling of effort during mental activity. The feeling of effort is familiar to most, if not all, humans. Prior research shows that the feeling of effort shapes judgments (e.g., of agency) and decisions (e.g., to quit the current task) in various ways, but the proximal causes of the feeling of effort are not well understood. In this research, I address these proximal causes. In particular, I conducted two preregistered experiments in which participants performed a difficult vs. easy cognitive task, while I measured effort-related phenomenology (feeling of effort) and physiology (pupil dilation) on a moment-to-moment basis. In both experiments, difficult tasks increased the feeling of effort; however, this effect could not be explained by concurrent increases in physiological effort. To explain these findings, I suggest that the feeling of effort during mental activity stems from the decision to exert physiological effort, rather than from physiological effort itself.

Question: What is the feeling of effort?


Overview of rotary steerable system and its control methods. Rotary steerable system (RSS) is a new technique of drilling technology adopted in directional drilling. Compared with conventional directional drilling, RSS has the ability to improve the drilling efficiency, reduce the drilling risk and decrease the drilling cost at the same time. This paper summaries the fundamental structure, classification, directional principle and development process of RSS; and gives detail analysis of the control methods in RSS. According to these summaries and analyses, the advantages and disadvantages of RSS at present are given, and some key suggestions about this technique and the related control methods are also proposed in this paper.

Question: What is the difference between rotary steerable system and directional drilling?


A five level cascaded H-bridge inverter based on space vector pulse width modulation technique. Multilevel inverters brought a tremendous revolution in high power superior performance industrial drive applications. Minimizing harmonic distortion is a challenging issue for power electronic drive. This problem can be solved by developing suitable modulation technique. There are number of modulation techniques established in the last decade. Among them, the space vector pulse width modulation (SVPWM) is extensively used because of their easier digital realization, better DC bus utilization and lower THD. Conventional SVPWM requires different number of logical computations of on time calculations and different number of lookup table for each triangle due to having their different number of switching states. In this paper, a simple SVPWM is presented where proposed only four logical computations of on time calculation, four active switching states and four lookup table for each triangle. Five level cascaded h-bridge inverter (CHBI) based on SVPWM technique are modeled and analyzed by using MATLAB/Simulink and origin 6.1 with a passive R-L load that can be extended to any level. These results are compared with other lower levels of inverter and with previous established results. From these results, five level CHBI based on SVPWM shows better performance compared to others in terms of THD.

Question: What is a space vector pulse width modulation?


Resuming the discussion of AMSTAR: What can (should) be made better?. BACKGROUND Evidence syntheses, and in particular systematic reviews (SRs), have become one of the cornerstones of evidence-based health care. The Assessment of Multiple Systematic Reviews (AMSTAR) tool has become the most widely used tool for investigating the methodological quality of SRs and is currently undergoing revision. The objective of this paper is to present insights, challenges and potential solutions from the point of view of a group of assessors, while referring to earlier methodological discussions and debates with respect to AMSTAR.   DISCUSSION One major drawback of AMSTAR is that it relies heavily on reporting quality rather than on methodological quality. This can be found in several items. Furthermore, it should be acknowledged that there are now new methods and procedures that did not exist when AMSTAR was developed. For example, the note to item 1 should now refer to the International Prospective Register of Ongoing Systematic Reviews (PROSPERO). Furthermore, item 3 should consider the definition of hand-searching, as the process of reviewing conference proceedings using the search function (e.g. in Microsoft Word or in a PDF file) does not meet the definition set out by the Cochrane Collaboration. Moreover, methods for assessing the quality of the body of evidence have evolved since AMSTAR was developed and should be incorporated into a revised AMSTAR tool. Potential solutions are presented for each AMSTAR item with the aim of allowing a more thorough assessment of SRs. As the AMSTAR tool is currently undergoing further development, our paper hopes to add to preceding discussions and papers regarding this tool and stimulate further discussion.

Question: What is the definition of hand-searching?


Parallel tree-ensemble algorithms for GPUs using CUDA. We present two new parallel implementations of the tree-ensemble algorithms Random Forest (RF) and Extremely randomized trees (ERT) for emerging many-core platforms, e.g., contemporary graphics cards suitable for general-purpose computing (GPGPU). Random Forest and Extremely randomized trees are ensemble learners for classification and regression. They operate by constructing a multitude of decision trees at training time and outputting a prediction by comparing the outputs of the individual trees. Thanks to the inherent parallelism of the task, an obvious platform for its computation is to employ contemporary GPUs with a large number of processing cores. Previous parallel algorithms for Random Forests in the literature are either designed for traditional multi-core CPU platforms or early history GPUs with simpler hardware architecture and relatively few number of cores. The new parallel algorithms are designed for contemporary GPUs with a large number of cores and take into account aspects of the newer hardware architectures as memory hierarchy and thread scheduling. They are implemented using the C/C++ language and the CUDA interface for best possible performance on NVidia-based GPUs. An experimental study comparing with the most important previous solutions for CPU and GPU platforms shows significant improvement for the new implementations, often with several magnitudes.

Question: What is the difference between parallel algorithms for Random Forest and Extremely randomized trees?


Sphinx-4: a flexible open source framework for speech recognition. Sphinx-4 is a flexible, modular and pluggable framework to he lp foster new innovations in the core research of hidden Mark ov model (HMM) recognition systems. The design of Sphinx-4 is b a ed on patterns that have emerged from the design of past sys tems as well as new requirements based on areas that researchers c urr ntly want to explore. To exercise this framework, and to pr vide researchers with a "research-ready" system, Sphinx-4 also includes several implementations of both simple and stateofhe-art techniques. The framework and the implementations are all f reely available via open source.

Question: What is the name of the framework?


Markov Chain Monte Carlo with People. Many formal models of cognition implicitly use subjective probability distributions to capture the assumptions of human learners. Most applications of these models determine these distributions indirectly. We propose a method for directly determining the assumptions of human learners by sampling from subjective probability distributions. Using a correspondence between a model of human choice and Markov chain Monte Carlo (MCMC), we describe a method for sampling from the distributions over objects that people associate with different categories. In our task, subjects choose whether to accept or reject a proposed change to an object. The task is constructed so that these decisions follow an MCMC acceptance rule, defining a Markov chain for which the stationary distribution is the category distribution. We test this procedure for both artificial categories acquired in the laboratory, and natural categories acquired from experience.

Question: What is a Markov chain?


An Improved Lexicographical Sort Algorithm of Copy-move Forgery Detection. As a technique for digital image tampering, copy-move forgery is frequently used. In this paper, an improved lexicographical sort algorithm based on discrete cosine transform (DCT) is developed to detect copy-move forgery. Firstly, the image is split into 8*8 blocks, and the image data undergoes a DCT. Then the DCT coefficients were grouped to reduce the dimension according to the frequency property. Finally, the distance of eigenvectors, instead of the DCT coefficients, was taken as the eigenvalue to fulfill the block matching. Experiments results showed that the false matching ratio of the proposed algorithm was reduced while the detecting ability was maintained.

Question: What is the improved lexicographical sort algorithm based on discrete cosine transform?


Ultrawideband Metasurface Lenses Based on Off-Shifted Opposite Layers. Metasurfaces have demonstrated to be a low-cost solution for the development of directive antennas at high frequency. One of the opportunities of metasurfaces is the possibility to produce planar lenses. However, these lenses usually present a narrow band of operation. This limitation on bandwidth is more restrictive when the required range of refractive index is high. Here, we present a novel implementation of metasurfaces with low dispersion that can be employed for the design of ultrawideband planar lenses. The implementation consists of two mirrored metasurfaces that are displaced exactly a half unit cell. This displacement produces two effects: It increases the equivalent refractive index of the fundamental mode and flattens its frequency dependence.

Question: What is a metasurface?


A Technique for Data Deduplication using Q-Gram Concept with Support Vector Machine. Several systems that rely on consistent data to offer high quality services, such as digital libraries and e-commerce brokers, may be affected by the existence of duplicates, quasi-replicas, or near-duplicate entries in their repositories. Because of that, there have been significant investments from private and government organizations in developing methods for removing replicas from its data repositories.In this paper, we have proposed accordingly. In the previous work, duplicate record detection was done using three different similarity measures and neural network. In the previous work, we have generated feature vector based on similarity measures and then, neural network was used to find the duplicate records. In this paper, we have developed Q-gram concept with support vector machine for deduplication process. The similarity function, which we are used Dice coefficient,Damerau–Levenshtein distance,Tversky index for similarity measurement. Finally, support vector machine is used for testing whether data record is duplicate or not. A set of data generated from some similarity measures are used as the input to the proposed system. There are two processes which characterize the proposed deduplication technique, the training phase and the testing phase the experimental results showed that the proposed deduplication technique has higher accuracy than the existing method. The accuracy obtained for the proposed deduplication 88%.

Question: What is the accuracy of the proposed deduplication technique?


Field-Robot-Based Agriculture : " RemoteFarming . 1 " and " BoniRob-Apps. Based on the autonomous field robot BoniRob, which was developed for plant phenotyping, the authors have created an enhanced platform BoniRob (V2). The design of BoniRob (V2) considers two main improvements: At first the robustness for continuous outdoor use is increased and secondly the robot now makes available a reusable platform that can serve for multiple agricultural purposes. The combination of the platform BoniRob (V2) and application modules ("BoniRob-Apps") is comparable to the classical combination of a tractor and an implement. In order to demonstrate this new concept, the authors have implemented three BoniRob-Apps, which can be integrated in BoniRob (V2) via defined mechanical, electrical and logical interfaces. The research project RemoteFarming.1 goes even beyond the accomplishment of a specific task by a robot and demonstrates the integration of the BoniRob (V2) platform into agricultural processes. For that purpose innovative agricultural engineering is combined with webbased communication technologies. The target is to develop a robotic mechanical weed control system which integrates a human user as remote worker in the process. The robotic weed control system is used for intra row weed treatment in carrots at BBCH-scales 10 to 20 in organic farming. This task is today conducted by hand. Introduction In recent years a variety of field robot prototypes have been proposed. They cover several applications, such as scouting and sampling, precise variable rate application of pesticides and fertilizers as well as autonomous weeding [1][2]. However, until now there is no commercial application of autonomous field operation in agriculture available. This is partly due to open issues regarding safety and legal requirements of autonomous operations [3].Another problem of the presented prototypes for autonomous field robots is their conception as single-purpose robots, despite there be

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


Towards Ontology Learning from Folksonomies. A folksonomy refers to a collection of user-defined tags with which users describe contents published on the Web. With the flourish of Web 2.0, folksonomies have become an important mean to develop the Semantic Web. Because tags in folksonomies are authored freely, there is a need to understand the structure and semantics of these tags in various applications. In this paper, we propose a learning approach to create an ontology that captures the hierarchical semantic structure of folksonomies. Our experimental results on two different genres of real world data sets show that our method can effectively learn the ontology structure from the folksonomies.

Question: What is a folksonomy?


Facebook in higher education promotes social but not academic engagement. Although there is evidence that academically successful students are engaged with their studies, it has proved difficult to define student engagement clearly. Student engagement is commonly construed as having two dimensions, social and academic. The rapid adoption of social media and digital technologies has ensured increasing interest in using them for improving student engagement. This paper examines Facebook usage among a first year psychology student cohort and reports that although the majority of students (94%) had Facebook accounts and spent an average of one hour per day on Facebook, usage was found to be predominantly social. Personality factors influenced usage patterns, with more conscientious students tending to use Facebook less than less conscientious students. This paper argues that, rather than promoting social engagement in a way that might increase academic engagement, it appears that Facebook is more likely to operate as a distracting influence.

Question: What is the difference between social and academic engagement?


Noise-contrastive estimation: A new estimation principle for unnormalized statistical models. We present a new estimation principle for parameterized statistical models. The idea is to perform nonlinear logistic regression to discriminate between the observed data and some artificially generated noise, using the model log-density function in the regression nonlinearity. We show that this leads to a consistent (convergent) estimator of the parameters, and analyze the asymptotic variance. In particular, the method is shown to directly work for unnormalized models, i.e. models where the density function does not integrate to one. The normalization constant can be estimated just like any other parameter. For a tractable ICA model, we compare the method with other estimation methods that can be used to learn unnormalized models, including score matching, contrastive divergence, and maximum-likelihood where the normalization constant is estimated with importance sampling. Simulations show that noise-contrastive estimation offers the best trade-off between computational and statistical efficiency. The method is then applied to the modeling of natural images: We show that the method can successfully estimate a large-scale two-layer model and a Markov random field.

Question: How to estimate the normalization constant of an unnormalized model?


Design of a Novel Broadband Skeletal Discone Antenna With a Compact Configuration. A novel broadband skeletal discone antenna with a compact configuration is proposed in this letter. The antenna consists of three components including a circular metal disc, a small upside-down cone, and a skeletal cone. The operating principle of this antenna is investigated by simulation, and the corresponding simulated results are also demonstrated in this letter. According to the simulation, the antenna was fabricated and followed by the measurement. The comparison between the simulated and measured results is made for validating the design strategy. Although some discrepancies can be obviously found at some discrete frequencies, both the simulated and measured results indicate that this antenna is capable of operating in the frequency range of 400 MHz to almost 16.4 GHz with VSWR below 2.5, while maintaining stable omnidirectional radiation. Meanwhile, this antenna also has a distinct advantage over the traditional discone antenna for its compact configuration, which makes it a more competitive candidate for applications as wireless communication.

Question: What is the operating principle of this antenna?


Lifelong Multi-Agent Path Finding for Online Pickup and Delivery Tasks. The multi-agent path-finding (MAPF) problem has recently received a lot of attention. However, it does not capture important characteristics of many real-world domains, such as automated warehouses, where agents are constantly engaged with new tasks. In this paper, we therefore study a lifelong version of the MAPF problem, called the multiagent pickup and delivery (MAPD) problem. In the MAPD problem, agents have to attend to a stream of delivery tasks in an online setting. One agent has to be assigned to each delivery task. This agent has to first move to a given pickup location and then to a given delivery location while avoiding collisions with other agents. We present two decoupled MAPD algorithms, Token Passing (TP) and Token Passing with Task Swaps (TPTS). Theoretically, we show that they solve all well-formed MAPD instances, a realistic subclass of MAPD instances. Experimentally, we compare them against a centralized strawman MAPD algorithm without this guarantee in a simulated warehouse system. TP can easily be extended to a fully distributed MAPD algorithm and is the best choice when real-time computation is of primary concern since it remains efficient for MAPD instances with hundreds of agents and tasks. TPTS requires limited communication among agents and balances well between TP and the centralized MAPD algorithm.

Question: What is the difference between a centralized and a distributed algorithm?