Gaze estimation method based on an aspherical model of the cornea: surface of revolution about the optical axis of the eye. A novel gaze estimation method based on a novel aspherical model of the cornea is proposed in this paper. The model is a surface of revolution about the optical axis of the eye. The calculation method is explained on the basis of the model. A prototype system for estimating the point of gaze (POG) has been developed using this method. The proposed method has been found to be more accurate than the gaze estimation method based on a spherical model of the cornea.

Question: How to estimate the point of gaze?


Neural Networks for Open Domain Targeted Sentiment. Open domain targeted sentiment is the joint information extraction task that finds target mentions together with the sentiment towards each mention from a text corpus. The task is typically modeled as a sequence labeling problem, and solved using state-of-the-art labelers such as CRF. We empirically study the effect of word embeddings and automatic feature combinations on the task by extending a CRF baseline using neural networks, which have demonstrated large potentials for sentiment analysis. Results show that the neural model can give better results by significantly increasing the recall. In addition, we propose a novel integration of neural and discrete features, which combines their relative advantages, leading to significantly higher results compared to both baselines.

Question: What is the effect of neural networks on open domain targeted sentiment?


Design of new intelligent street light control system. In China, the methods of time-control, optical-control and time-optical-control are in common used to control street lamp, particularly in small and medium-sized cities. But due to the backward lighting control and administrative method, the precision is bad, and the result of work is also poor. Through many kinds of sensor combination sense environment's change, the multi-sensor exhibition can combinatory logically control the new intelligent street light controller system. And based on the degree of illumination control fixed time, in the automatic foundation fixed time, according to the multi-sensing exhibition survey data's special combination change, to control the street light nimbly; the system can also realize the automatic timing control, by pre-installing time to control street light switch and ultimately to control the street light time. Simultaneously the system can also realize the automatic sunshine control, which may act according to the actual determination of the sunlight degree of illumination and the degree of illumination control criterion and automatically control street light. On the basis of the merits of the regular control and the optical control, a new street smart controller is designed, with dual functions including timing control and automatic photoelectric control. It allows street lamps automatically lit in the evening, lighting the road for a few hours (adjustable time). After 0:00, when few vehicles or pedestrians go past, it turn off automatically. And terminal controller has wake-up function. After the street light turn out automatically, when the vehicles or pedestrians are going through, street light will be waken up by terminal controller. When the vehicles or pedestrians go past, the lights are off automatically. Design of new intelligent street light control system does not only achieve energy-saving power but also extend the service life of lighting equipment. Moreover, i

Question: What is the difference between the time-control and the time-optical-control?


BING: Binarized Normed Gradients for Objectness Estimation at 300fps. Training a generic objectness measure to produce a small set of candidate object windows, has been shown to speed up the classical sliding window object detection paradigm. We observe that generic objects with well-defined closed boundary can be discriminated by looking at the norm of gradients, with a suitable resizing of their corresponding image windows in to a small fixed size. Based on this observation and computational reasons, we propose to resize the window to 8 × 8 and use the norm of the gradients as a simple 64D feature to describe it, for explicitly training a generic objectness measure. We further show how the binarized version of this feature, namely binarized normed gradients (BING), can be used for efficient objectness estimation, which requires only a few atomic operations (e.g. ADD, BITWISE SHIFT, etc.). Experiments on the challenging PASCAL VOC 2007 dataset show that our method efficiently (300fps on a single laptop CPU) generates a small set of category-independent, high quality object windows, yielding 96.2% object detection rate (DR) with 1, 000 proposals. Increasing the numbers of proposals and color spaces for computing BING features, our performance can be further improved to 99.5% DR.

Question: What is the size of the windows?


Extended Kalman filter based grid synchronization in the presence of voltage unbalance for smart grid. In this paper, grid synchronization for gird-connected power generation systems in the presence of voltage unbalance and frequency variation is considered. A new extended Kalman filter based synchronization algorithm is proposed to track the phase angle of the utility network. Instead of processing the three-phase voltage signal in the abc natural reference frame and resorting to the symmetrical component transformation as in the traditional way, the proposed algorithm separates the positive and negative sequences in the transformed αβ stationary reference frame. Based on the obtained expressions in αβ domain, an EKF is developed to track both the in-phase and quadrature sinusoidal signals together with the unknown frequency. An estimate of the phase angle of the positive sequence is then obtained. As a by-product, estimates of phase angle of negative sequence and grid frequency are also computed. Compared to the commonly used scheme, the proposed algorithm has a simplified structure. The good performance is supported by computer simulations.

Question: How to synchronize a grid in the presence of voltage unbalance?


A Survey Paper on PID Control System. This paper concentrates on the work done on the PID control system specially on time delaying systems like network control systems. The different works which have already been done are summarised here like gain margin, phase margin methods. The absolute focal point on time delayed systemare the delays induced by network and the packet losses. This survey paper covers the study on such methods that compensates these

Question: What is PID control system?


Media and children's aggression, fear, and altruism.. Noting that the social and emotional experiences of American children today often heavily involve electronic media, Barbara Wilson takes a close look at how exposure to screen media affects children's well-being and development. She concludes that media influence on children depends more on the type of content that children find attractive than on the sheer amount of time they spend in front of the screen. Wilson begins by reviewing evidence on the link between media and children's emotions. She points out that children can learn about the nature and causes of different emotions from watching the emotional experiences of media characters and that they often experience empathy with those characters. Although research on the long-term effects of media exposure on children's emotional skill development is limited, a good deal of evidence shows that media exposure can contribute to children's fears and anxieties. Both fictional and news programming can cause lasting emotional upset, though the themes that upset children differ according to a child's age. Wilson also explores how media exposure affects children's social development. Strong evidence shows that violent television programming contributes to children's aggressive behavior. And a growing body of work indicates that playing violent video games can have the same harmful effect. Yet if children spend time with educational programs and situation comedies targeted to youth, media exposure can have more prosocial effects by increasing children's altruism, cooperation, and even tolerance for others. Wilson also shows that children's susceptibility to media influence can vary according to their gender, their age, how realistic they perceive the media to be, and how much they identify with characters and people on the screen. She concludes with guidelines to help parents enhance the positive effects of the media while minimizing the risks associated with certain ty

Question: How can media influence children's emotions?


Fast algorithms for mining association rules.

Question: What is an association rule?


Design of Permanent Magnet-Assisted Synchronous Reluctance Motors Made Easy. Electric motor design is a multi-variable problem which involves geometric dimensions of the stator and rotor. Presenting a unique solution for a family of optimization criteria has always been a challenge for motor designers. Several numerical tools such as finite element methods (FEM) have been developed to perform a precise analysis and predict the outcome of the design. However, limits in parametric analysis as well as mathematical and computational burden on numerical tools usually prohibit the designer in obtaining a unique solution for the design problem. These limits and demands in optimized solutions motivate the designer to use analytical models in order to perform a comprehensive parametric design. An accurate analytical model is crucial for this purpose. In this paper, an analytical model for permanent magnet assisted synchronous reluctance motor (PMa- SynRM) with four flux barriers and one cutout per pole is developed. Flux densities are found in the air gap, in the cutouts, and in the flux barriers; thus, the back-EMF developed by the permanent magnets is derived. Equations for the d-axis and the q-axis inductances are also obtained. Electromagnetic torque is finally derived using the co-energy method. The developed analytical model highlights the contribution of the reluctance variation and permanent magnets on the developed torque. Simulation results are obtained using both Matlab and Ansoft/Maxwell packages. These outcomes are supported by the experimental results obtained from a laboratory test bed.

Question: How to design a permanent magnet-assisted synchronous reluctance motor?


Functional Search-based Testing from State Machines. The application of metaheuristic search techniques in test data generation has been extensively investigated in recent years. Most studies, however, have concentrated on the application of such techniques in structural testing. The use of search-based techniques in functional testing is less frequent, the main cause being the implicit nature of the specification. This paper investigates the use of search-based techniques for functional testing, having the specification in form of a state machine. Its purpose is to generate input data for chosen paths in a state machine, so that the parameter values provided to the methods satisfy the corresponding guards and trigger the desired transitions. A general form of a fitness function for an individual path is presented and this approach is empirically evaluated using three search techniques: simulated annealing, genetic algorithms and particle swarm optimization.

Question: What is the purpose of this paper?


Optimized rate matching architecture for a LTE-Advanced FPGA-based PHY. In this paper we present an optimized rate matching architecture for a LTE-Advanced FPGA-based physical layer. Since LTE-Advanced can reach up to rates of 1 Gbps in downlink, and since rate matching is in that critical path, it is very important that the design of the hardware architecture be efficient enough to allow this high data rate with little resources as possible. If not well planned, implementations on FPGAs can be quite challenging, limiting the choices of speed grades and FPGAs sizes capable of supporting such requirements. We propose efficient hardware architecture for the LTE-Advanced rate matching generic procedure; occupying only 218 slices and 9 block RAMs and performing in frequencies greater than 400 MHz in a FPGA-based solution.

Question: What is the LTE-Advanced rate matching generic procedure?


Selecting Coherent and Relevant Plots in Large Scatterplot Matrices. The scatterplot matrix (SPLOM) is a well-established technique to visually explore high-dimensional data sets. It is characterized by the number of scatterplots (plots) of which it consists of. Unfortunately, this number quadratically grows with the number of the data set's dimensions. Thus, a SPLOM scales very poorly. Consequently, the usefulness of SPLOMs is restricted to a small number of dimensions. For this, several approaches already exist to explore such "small" SPLOMs. Those approaches address the scalability problem just indirectly and without solving it. Therefore, we introduce a new greedy approach to manage "large" SPLOMs with more than hundred dimensions. We establish a combined visualization and interaction scheme that produces intuitively interpretable SPLOMs by combining known quality measures, a pre-process reordering, and a perception-based abstraction. With this scheme, the user can interactively find large amounts of relevant plots in large SPLOMs.

Question: How to select coherent and relevant plots in large scatterplot matrices?


Exact clothing retrieval approach based on deep neural network. In recent years, the trend of shopping for clothing on an onscreen character has been raising. Unfortunately, clothes that appear on screen could be difficult to track down, much less to purchase directly. It is a challenging task to find out exactly what the clothing in a TV show is from massive amounts of clothing items in online clothing retails due to the clearly noticeable visual discrepancies of the same clothing in video and in online shop photos. In order to tackle the problem, we adopt the deep neural network to learn recognizable clothing-specific feature for finding the exact clothing item in the video scenario among a large collection of online shop images. The experiments shows the clothing-specific feature is more effective in retrieval task and color filtering improve the retrieval performance.

Question: What is the deep neural network?


Trusted Click: Overcoming Security issues of NFV in the Cloud. Network Function Virtualization has received a large amount of research and recent efforts have been made to further leverage the cloud to enhance NFV. However, since there are privacy and security issues with using cloud computing, work has been done to allow for operating on encrypted data, which introduces a large amount of overhead in both computation and data, while only providing a limited set of operations, since these encryption schemes are not fully homomorphic. We propose using trusted computing to circumvent these limitations by having hardware enforce data privacy and provide guaranteed computation. Prior work has shown that Intel's Software Guard Extensions can be used to protect the state of network functions, but there are still questions about the usability of SGX in arbitrary NFV applications and the performance of SGX in these applications. We extend prior work to show how SGX can be used in network deployments by extending the Click modular router to perform secure packet processing with SGX. We also present a performance evaluation of SGX on real hardware to show that processing inside of SGX has a negligible performance impact, compared to performing the same processing outside of SGX.

Question: How can I use trusted computing to protect my data?


A parameterized cell design for high-Q, variable width and spacing spiral inductors. The on-chip planar spiral inductors having variable width (W) and spacing (S) across their turns are known to exhibit higher quality factors (Q). In this paper, we present an efficient parameterized cell (pcell) design in cadence using SKILL scripts for automatic layout generation of these complex, high-Q, variable W&S spiral inductors comprising of single ended and symmetric structures with rectangular, hexagonal, octagonal and circular spirals. Electromagnetic simulations are performed on the inductor layouts generated using the developed pcells. The constant W&S and variable W&S spiral inductor structures are fabricated in a 0.18 μm silicon on insulator process. Measurements show ~25% improvement in the quality factor of variable W%S spiral inductors compared to their constant W&S counterparts and also validates the proper operation of the developed inductor parameterized cells. The presented variable W&S inductor pcell significantly reduces the layout design time of RF circuit designers and also helps in the design automation of these complex inductor structures to boost their own performance and the RF circuits as well.

Question: What is the quality factor of a spiral inductor?


Optimal estimation of the mean function based on discretely sampled functional data: Phase transition. The problem of estimating the mean of random functions based on discretely sampled data arises naturally in functional data analysis. In this paper, we study optimal estimation of the mean function under both common and independent designs. Minimax rates of convergence are established and easily implementable rateoptimal estimators are introduced. The analysis reveals interesting and different phase transition phenomena in the two cases. Under the common design, the sampling frequency solely determines the optimal rate of convergence when it is relatively small and the sampling frequency has no effect on the optimal rate when it is large. On the other hand, under the independent design, the optimal rate of convergence is determined jointly by the sampling frequency and the number of curves when the sampling frequency is relatively small. When it is large, the sampling frequency has no effect on the optimal rate. Another interesting contrast between the two settings is that smoothing is necessary under the independent design, while, somewhat surprisingly, it is not essential under the common design.

Question: How to estimate the mean of a random function based on discretely sampled data?


Building Lifecycle Management System for Enhanced Closed Loop Collaboration. In the past few years, the architecture, engineering and construction (AEC) industry has carried out efforts to develop BIM (Building Information Modelling) facilitating tools and standards for enhanced collaborative working and information sharing. Lessons learnt from other industries and tools such as PLM (Product Lifecycle Management) – established tool in manufacturing to manage the engineering change process – revealed interesting potential to manage more efficiently the building design and construction processes. Nonetheless, one of the remaining challenges consists in closing the information loop between multiple building lifecycle phases, e.g. by capturing information from middle-of-life processes (i.e., use and maintenance) to re-use it in end-of-life processes (e.g., to guide disposal decision making). Our research addresses this lack of closed-loop system in the AEC industry by proposing an open and interoperable Web-based building lifecycle management system. This paper gives (i) an overview of the requirement engineering process that has been set up to integrate efforts, standards and directives of both the AEC and PLM industries, and (ii) first proofs-of-concept of our system implemented on two distinct campus.

Question: What is the building lifecycle management system for enhanced closed loop collaboration?


Mathematical Models for Natural Gas Forecasting. It is vital for natural gas Local Distribution Companies (LDCs) to forecast their customers' natural gas demand accurately. A significant error on a single very cold day can cost the customers of the LDC millions of dollars. This paper looks at the financial implication of forecasting natural gas, the nature of natural gas forecasting, the factors that impact natural gas consumption, and describes a survey of mathematical techniques and practices used to model natural gas demand. Many of the techniques used in this paper currently are implemented in a software GasDay , which is currently used by 24 LDCs throughout the United States, forecasting about 20% of the total U.S. residential, commercial, and industrial consumption. Results of GasDay's forecasting performance also is presented.

Question: What is the financial implication of forecasting natural gas?


Routing, scheduling and channel assignment in Wireless Mesh Networks: Optimization models and algorithms. Wireless Mesh networks (WMNs) can partially replace the wired backbone of traditional wireless access networks and, similarly, they require to carefully plan radio resource assignment in order to provide the same quality guarantees to traffic flows. In this paper we study the radio resource assignment optimization problem in Wireless Mesh Networks assuming a time division multiple access (TDMA) scheme, a dynamic power control able to vary emitted power slot-by-slot, and a rate adaptation mechanism that sets transmission rates according to the signalto-interference-and-noise ratio (SINR). The proposed optimization framework includes routing, scheduling and channel assignment. Quality requirements of traffic demands are expressed in terms of minimum bandwidth and modeled with constraints defining the number of information units (packets) that must be delivered per frame. We consider an alternative problem formulation where decision variables represent compatible sets of links active in the same slot and channel, called configurations. We propose a two phases solution approach where a set of configurations is first selected to meet traffic requirements along the best available paths, and then configurations are assigned to channels according to device characteristics and constraints. The optimization goal is to minimize the number of used slots, which is directly related to the global resource allocation efficiency. We provide a lower bound of the optimal solution solving the continuous relaxation of problem formulation. Moreover, we propose a heuristic approach to determine practical integer solutions (upper bound). Since configuration variables are exponentially many, our solution approaches are based on the Column Generation technique. In order to assess the effectiveness of the proposed algorithms we show the numerical results obtained on a set of realistic-siz

Question: What is the size of the canadian military?


Networks versus markets in international trade. I propose a network/search view of international trade in differentiated products. I present evidence that supports the view that proximity and common language/colonial ties are more important for differentiated products than for products traded on organized exchanges in matching international buyers and sellers, and that search barriers to trade are higher for differentiated than for homogeneous products. I also discuss alternative explanations for the findings.

Question: What is the difference between a network and a market?


DTAM: Dense tracking and mapping in real-time. DTAM is a system for real-time camera tracking and reconstruction which relies not on feature extraction but dense, every pixel methods. As a single hand-held RGB camera flies over a static scene, we estimate detailed textured depth maps at selected keyframes to produce a surface patchwork with millions of vertices. We use the hundreds of images available in a video stream to improve the quality of a simple photometric data term, and minimise a global spatially regularised energy functional in a novel non-convex optimisation framework. Interleaved, we track the camera's 6DOF motion precisely by frame-rate whole image alignment against the entire dense model. Our algorithms are highly parallelisable throughout and DTAM achieves real-time performance using current commodity GPU hardware. We demonstrate that a dense model permits superior tracking performance under rapid motion compared to a state of the art method using features; and also show the additional usefulness of the dense model for real-time scene interaction in a physics-enhanced augmented reality application.

Question: What is a dense model?


A hybrid feature selection scheme for unsupervised learning and its application in bearing fault diagnosis. With the development of the condition-based maintenance techniques and the consequent requirement for good machine learning methods, new challenges arise in unsupervised learning. In the real-world situations, due to the relevant features that could exhibit the real machine condition are often unknown as priori, condition monitoring systems based on unimportant features, e.g. noise, might suffer high falsealarm rates, especially when the characteristics of failures are costly or difficult to learn. Therefore, it is important to select the most representative features for unsupervised learning in fault diagnostics. In this paper, a hybrid feature selection scheme (HFS) for unsupervised learning is proposed to improve the robustness and the accuracy of fault diagnostics. It provides a general framework of the feature selection based on significance evaluation and similarity measurement with respect to the multiple clustering solutions. The effectiveness of the proposed HFS method is demonstrated by a bearing fault diagnostics application and comparison with other features selection methods. 2011 Elsevier Ltd. All rights reserved.

Question: What is the bearing fault diagnosis application?


Back propagation neural network with adaptive differential evolution algorithm for time series forecasting. The back propagation neural network (BPNN) can easily fall into the local minimum point in time series forecasting. A hybrid approach that combines the adaptive differential evolution (ADE) algorithm with BPNN, called ADE–BPNN, is designed to improve the forecasting accuracy of BPNN. ADE is first applied to search for the global initial connection weights and thresholds of BPNN. Then, BPNN is employed to thoroughly search for the optimal weights and thresholds. Two comparative real-life series data sets are used to verify the feasibility and effectiveness of the hybrid method. The proposed ADE–BPNN can effectively improve forecasting accuracy relative to basic BPNN, autoregressive integrated moving average model (ARIMA), and other hybrid models. 2014 Elsevier Ltd. All rights reserved.

Question: What is the difference between the back propagation neural network and the adaptive differential evolution algorithm?


Genotyping by Sequencing for SNP-Based Linkage Analysis and Identification of QTLs Linked to Fruit Quality Traits in Japanese Plum (Prunus salicina Lindl.). Marker-assisted selection (MAS) in stone fruit (Prunus species) breeding is currently difficult to achieve due to the polygenic nature of the most relevant agronomic traits linked to fruit quality. Genotyping by sequencing (GBS), however, provides a large quantity of useful data suitable for fine mapping using Single Nucleotide Polymorphisms (SNPs) from a reference genome. In this study, GBS was used to genotype 272 seedlings of three F1 Japanese plum (Prunus salicina Lindl) progenies derived from crossing "98-99" (as a common female parent) with "Angeleno," "September King," and "September Queen" as male parents. Raw sequences were aligned to the Peach genome v1, and 42,909 filtered SNPs were obtained after sequence alignment. In addition, 153 seedlings from the "98-99" × "Angeleno" cross were used to develop a genetic map for each parent. A total of 981 SNPs were mapped (479 for "98-99" and 502 for "Angeleno"), covering a genetic distance of 688.8 and 647.03 cM, respectively. Fifty five seedlings from this progeny were phenotyped for different fruit quality traits including ripening time, fruit weight, fruit shape, chlorophyll index, skin color, flesh color, over color, firmness, and soluble solids content in the years 2015 and 2016. Linkage-based QTL analysis allowed the identification of genomic regions significantly associated with ripening time (LG4 of both parents and both phenotyping years), fruit skin color (LG3 and LG4 of both parents and both years), chlorophyll degradation index (LG3 of both parents in 2015) and fruit weight (LG7 of both parents in 2016). These results represent a promising situation for GBS in the identification of SNP variants associated to fruit quality traits, potentially applicable in breeding programs through MAS, in a highly heterozygous crop species such as Japanese plum.

Question: What is the difference between a SNP and a QTL?


Automatic labeling hierarchical topics. Recently, statistical topic modeling has been widely applied in text mining and knowledge management due to its powerful ability. A topic, as a probability distribution over words, is usually difficult to be understood. A common, major challenge in applying such topic models to other knowledge management problem is to accurately interpret the meaning of each topic. Topic labeling, as a major interpreting method, has attracted significant attention recently. However, previous works simply treat topics individually without considering the hierarchical relation among topics, and less attention has been paid to creating a good hierarchical topic descriptors for a hierarchy of topics. In this paper, we propose two effective algorithms that automatically assign concise labels to each topic in a hierarchy by exploiting sibling and parent-child relations among topics. The experimental results show that the inter-topic relation is effective in boosting topic labeling accuracy and the proposed algorithms can generate meaningful topic labels that are useful for interpreting the hierarchical topics.

Question: What is a topic?


ClothCap: seamless 4D clothing capture and retargeting. Designing and simulating realistic clothing is challenging. Previous methods addressing the capture of clothing from 3D scans have been limited to single garments and simple motions, lack detail, or require specialized texture patterns. Here we address the problem of capturing regular clothing on fully dressed people in motion. People typically wear multiple pieces of clothing at a time. To estimate the shape of such clothing, track it over time, and render it believably, each garment must be segmented from the others and the body. Our ClothCap approach uses a new multi-part 3D model of clothed bodies, automatically segments each piece of clothing, estimates the minimally clothed body shape and pose under the clothing, and tracks the 3D deformations of the clothing over time. We estimate the garments and their motion from 4D scans; that is, high-resolution 3D scans of the subject in motion at 60 fps. ClothCap is able to capture a clothed person in motion, extract their clothing, and retarget the clothing to new body shapes; this provides a step towards virtual try-on.

Question: How does clothcap work?


Survey on Fraud Detection Techniques Using Data Mining. Now a days, fraud is a million dollar business and every year it is increasing more and more. In a crime survey in 2009, tells that close to 30% of the company's worldwide reported falling victim to fraud in the past year. Fraud involves individual or in a form of groups who intentionally act secretly to rob another of something of worth, for their own profit. Fraud is as against the humanity and it is unlimited variety of different forms. So in this paper, we introduce different methods and techniques to tackle the fraud and how to prevent the fraud into the organization, businesses, and hospital and insurance companies. Fraud prevention is a continuing battle. Many website owners must continually fight against many kinds of crime ranging from stealing identity theft and credit cards and many other types of fraud related to that. Internet Fraud is also very popular, where fraudster can steal the credit card number and buy thing from the different websites.

Question: What is the difference between fraud and identity theft?


Detection and Discrimination of Open-Phase Fault in Permanent Magnet Synchronous Motor Drive System. Open-phase fault in permanent magnet synchronous motor (PMSM) drive system occurs as the phase winding is disconnected or one leg of the inverter bridge fails. It may generate large electromagnetic torque ripple and serious mechanical vibration. Therefore, a rapid fault detection method is greatly required to identify this fault at early stage and prevent damage to the system. This paper develops a method of the open-phase fault detection and discrimination for the PMSM drive system based on the zero-sequence voltage components, in which the discrimination of the fault types, namely internal stator winding failure and switches failure of the inverter is realized. Then, appropriate fault-tolerant measures may be taken according to the different fault types. The experimental platform is established, and the experimental results verify the effectiveness of the proposed method, showing that not only the open-phase fault can be rapidly detected, but also the fault type can be effectively discriminated.

Question: How to detect open-phase fault in PMSM drive system?


Designing game-based learning environments for elementary science education: A narrative-centered learning perspective. Game-based learning environments hold significant promise for STEM education, yet they are enormously complex. CRYSTAL ISLAND: UNCHARTED DISCOVERY, is a gamebased learning environment designed for upper elementary science education that has been under development in our laboratory for the past four years. This article discusses curricular and narrative interaction design requirements, presents the design of the CRYSTAL ISLAND learning environment, and describes its evolution through a series of pilots and field tests. Additionally, a classroom integration study was conducted to initiate a shift towards ecological validity. Results indicated that CRYSTAL ISLAND produced significant learning gains on both science content and problem-solving measures. Importantly, gains were consistent for gender across studies. This finding is key in light of past studies that revealed disproportionate participation by boys within game-based learning environments.

Question: How does a game-based learning environment for elementary science education work?


Has the Internet become indispensable?. As was empirically demonstrated in [3], "the adoption rate of the Internet has exceeded that of earlier mass communication technologies by several magnitudes," making it an "irreversible" innovation. Studies have also shown that for the generation of U.S.-based youth that grew up with the Internet, it is gradually displacing television as their main source of entertainment, communication, and education [6]. Here, we explore how the Internet has become indispensable to people in their daily lives and develop a conceptual model allowing us to address the associated research questions. The idea is that the Internet has become so embedded in the daily fabric of people's lives that they simply cannot live without it. How is the Internet indispensable and in what ways? For which groups of people is it indispensable, for what tasks, and how has BY DONNA L. HOFFMAN, THOMAS P. NOVAK, AND ALLADI VENKATESH

Question: How has the internet become indispensable?


Learning to Discover Social Circles in Ego Networks. Our personal social networks are big and cluttered, and currently there is no good way to organize them. Social networking sites allow users to manually categorize their friends into social circles (e.g. 'circles' on Google+, and 'lists' on Facebook and Twitter), however they are laborious to construct and must be updated whenever a user's network grows. We define a novel machine learning task of identifying users' social circles. We pose the problem as a node clustering problem on a user's ego-network, a network of connections between her friends. We develop a model for detecting circles that combines network structure as well as user profile information. For each circle we learn its members and the circle-specific user profile similarity metric. Modeling node membership to multiple circles allows us to detect overlapping as well as hierarchically nested circles. Experiments show that our model accurately identifies circles on a diverse set of data from Facebook, Google+, and Twitter for all of which we obtain hand-labeled ground-truth.

Question: How to detect social circles in ego networks?


A versatile FMCW Radar System Simulator for Millimeter-Wave Applications. For the successful design of low-cost and high-performance radar systems accurate and efficient system simulation is a key requirement. In this paper we present a new versatile simulation environment for frequency-modulated continuous-wave radar systems. Besides common hardware simulation it covers integrated system simulation and concept analysis from signal synthesis to baseband. It includes a flexible scenario generator, accurate noise modeling, and efficiently delivers simulation data for development and testing of signal processing algorithms. A comparison of simulations and measurement results for an integrated 77-GHz radar prototype shows the capabilities of the simulator on two different scenarios.

Question: What is a versatile FMCW Radar System Simulator for Millimeter-Wave Applications?


Orthogonal nonnegative matrix t-factorizations for clustering. Currently, most research on nonnegative matrix factorization (NMF)focus on 2-factor $X=FG^T$ factorization. We provide a systematicanalysis of 3-factor $X=FSG^T$ NMF. While it unconstrained 3-factor NMF is equivalent to it unconstrained 2-factor NMF, itconstrained 3-factor NMF brings new features to it constrained 2-factor NMF. We study the orthogonality constraint because it leadsto rigorous clustering interpretation. We provide new rules for updating $F,S, G$ and prove the convergenceof these algorithms. Experiments on 5 datasets and a real world casestudy are performed to show the capability of bi-orthogonal 3-factorNMF on simultaneously clustering rows and columns of the input datamatrix. We provide a new approach of evaluating the quality ofclustering on words using class aggregate distribution andmulti-peak distribution. We also provide an overview of various NMF extensions andexamine their relationships.

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


Consideration on successive interference canceller (SIC) receiver at cell-edge users for non-orthogonal multiple access (NOMA) with SU-MIMO. Non-orthogonal multiple access (NOMA) utilizing transmit power difference and advanced successive interference canceller (SIC) receivers has been considered as a candidate radio access technology for future wireless communication systems. Single-user multiple-input multiple-output (SU-MIMO) is one of the key technologies in Long-Term-Evolution (LTE) systems. Thus, it has been proved to combine with NOMA for further system performance improvement. In previous studies, SIC receiver is adopted at cell center users (UEs), while SIC processing is not taken into account at cell-edge UEs, considering the feasibility of UE receiver and control signaling overhead. However, it may put limitation on the performance of NOMA. To further enhance the performance of NOMA with SU-MIMO, advanced receiver can be considered at cell-edge UEs. In this paper, we investigate the impact of applying the SIC receiver at cell-edge UEs in downlink NOMA with SU-MIMO. The detail SIC detection schemes at cell-edge UE will be discussed, including ideal SIC processing and non-ideal SIC processing. The simulation results show that performance gains of NOMA can be improved with SIC processing at cell-edge UEs. It indicates that more advanced receiver can be considered for cell-edge UE to achieve upper-bound performance.

Question: What is the impact of applying the SIC receiver at cell-edge UEs in downlink NOMA with SU-MIMO?


RCV1: A New Benchmark Collection for Text Categorization Research. Reuters Corpus Volume I (RCV1) is an archive of over 800,000 manually categorized newswire stories recently made available by Reuters, Ltd. for research purposes. Use of this data for research on text categorization requires a detailed understanding of the real world constraints under which the data was produced. Drawing on interviews with Reuters personnel and access to Reuters documentation, we describe the coding policy and quality control procedures used in producing the RCV1 data, the intended semantics of the hierarchical category taxonomies, and the corrections necessary to remove errorful data. We refer to the original data as RCV1-v1, and the corrected data as RCV1-v2. We benchmark several widely used supervised learning methods on RCV1-v2, illustrating the collection's properties, suggesting new directions for research, and providing baseline results for future studies. We make available detailed, per-category experimental results, as well as corrected versions of the category assignments and taxonomy structures, via online appendices.

Question: What is the size of the Reuters corpus?


Degradation of mechanical properties of class-H winding insulation. Thermal ageing is one of the key factors that result in insulation degradation leading to lower dielectric strength and thereafter occurrence of partial discharge in high voltage machines. However, in low voltage high current machines, the occurrence of partial discharge is minimal and degradation of dielectric strength alone will not cause the breakdown of the insulation. This paper hypothesizes that the breakdown of insulation in low voltage/high current machines occur as a result of insulation cracking among other factors. In this paper, it is shown that thermal degradation leads to degradation of mechanical properties of Polyamide-imide insulation, particularly reduction of the ultimate tensile strength and leads to enhanced brittleness. It follows that once a crack in the insulation is formed, the breakdown strength at the point of cracking will be lower. Multiple such cracks may lead to the formation of a breakdown path thereafter leading to aggravated heating and further accelerated deterioration of the insulation. In this paper, the methodology for testing the mechanical properties of insulation material is presented. A model to account for the variation of such properties due to thermal degradation is developed.

Question: What is the difference between thermal ageing and thermal degradation?


A lane detection algorithm based on reliable lane markings. This paper proposes a robust and effective vision-based lane detection approach. First, two binary images are obtained from the region of interest of gray-scale images. The obtained binary images are merged by a novel neighborhood AND operator and then transformed to a bird's eye view (BEV) via inverse perspective mapping. Then, gaussian probability density functions are fit to the left and right regions of a histogram image acquired from the BEV. Finally, a polynomial lane model is estimated from the identified regions. Experimental results show that the proposed method accurately detects lanes in complex situations including worn-out and curved lanes.

Question: What is a polynomial lane model?


High performance CAN/FlexRay gateway design for in-vehicle network. A gateway in in-vehicle network (IVN) is an indispensable component as a conversion device between different communication protocols. Due to meet more complex network for IVN, how to improving the performance of gateway is more important. In this paper, a high efficient of CAN/FlexRay gateway using hardware/software (HW/SW) co-design method is proposed which is implemented with Xilinx FPGA system. The CAN controller and FlexRay controller are designed by SW and HW, respectively. The interface of HW and SW are used AXI-bus. The convert module is evaluated by a cost function. In addition, a transceiver PCB for connecting between the proposed gateway and external CAN/FlexRay-based ECUs is implemented. Experimental results show that the proposed gateway system can reduce at most 94.7% on execution time with related works which is more suited for IVN.

Question: How to improve the performance of gateway?


Recursive Neural Networks for Learning Logical Semantics. Supervised recursive neural network models (RNNs) for sent ence meaning have been successful in an array of sophisticated language tasks , but it remains an open question whether they can learn compositional semantic gra mm rs that support logical deduction. We address this question directly by for the first time evaluating whether each of two classes of neural model — plain RNNs and re cursive neural tensor networks (RNTNs) — can correctly learn relationship such as entailment and contradiction between pairs of sentences, where we have generated controlled data sets of sentences from a logical grammar. Our first exper iment evaluates whether these models can learn the basic algebra of logical r elations involved. Our second and third experiments extend this evaluation to c omplex recursive structures and sentences involving quantification. We find t hat he plain RNN achieves only mixed results on all three experiments, where as the stronger RNTN model generalizes well in every setting and appears capable of learning suitable representations for natural language logical inference.

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


Women's use of cosmetics: psychosocial correlates and consequences.. Synopsis Few systematic studies have examined individual differences in women's use of facial make-up or the possible psychosocial effects of such use. In the present investigation, the researchers developed several measures of the amount and the situational and temporal patterning of cosmetics use. Among forty-two female college students, differential use was associated with a number of selected personality variables-public self-consciousness, public body-consciousness, social anxiety, and various body-image factors. Through the imagery-induction of cosmetics use and non-use conditions, cosmetics users' self-evaluative responses were studied. In a variety of imagined situations, subjects reported being more self-confident and sociable when wearing as opposed to not wearing their customary cosmetics. Findings were discussed in the context of the role of cosmetics in self-image enhancement and social impression management.

Question: What are the psychosocial effects of cosmetics use?


Which phoneme-to-viseme maps best improve visual-only computer lip-reading?. A critical assumption of all current visual speech recognition systems is that there are visual speech units called visemes which can be mapped to units of acoustic speech, the phonemes. Despite there being a number of published maps it is infrequent to see the effectiveness of these tested, particularly on visual-only lip-reading (many works use audio-visual speech). Here we examine 120 mappings and consider if any are stable across talkers. We show a method for devising maps based on phoneme confusions from an automated lip-reading system, and we present new mappings that show improvements for individual talkers.

Question: Which phoneme-to-viseme maps improve visual-only computer lip-reading?


String Alignment with Substitution, Insertion, Deletion, Squashing and Expansion Operations. Let X and Y be any two strings of finite length. The problem of transforming X to Y using the edit operations of substitution, deletion, and insertion has been extensively studied in the literature. The problem can be solved in quadratic time if the edit operations are extended to include the operation of transposition of adjacent characters, and is NP-complete if the characters can be edited repeatedly. In this paper we consider the problem of transforming X to Y when the set of edit operations is extended to include the squashing and expansion operations. Whereas in the squashing operation two (or more) contiguous characters of X can be transformed into a single character of Y, in the expansion operation a single character in X may be expanded into two or more contiguous characters of Y. These operations are typically found in the recognition of cursive script. A quadratic time solution to the problem has been presented. This solution is optimal for the infinite-alphabet case. The strategy to compute the sequence of edit operations is also presented.

Question: What is the quadratic time solution to the problem?


Performance analysis and security dependence of on paper digital signature using random and critical content. The content of physical paper documents is a major concern, after the development of modern scanning and printing technologies. The tendency for the document fraud has been growing and the paper-based documents require authenticating the sender identity and ensuring the content integrity. This paper presents a reliable and simple method for authenticating the content of a paper document by implementing an on paper digital signature. This method randomly selects the words at random positions of the document along with critical content and creates on paper digital signature. This method employs an online document verification system and the unauthorized access is denied by the user authentication mechanism. Performance analysis and security dependence on the system is also studied in this paper.

Question: What is the content of the paper document?


The PeerRank Method for Peer Assessment. We propose the PeerRank method for peer assessment. This constructs a grade for an agent based on the grades proposed by the agents evaluating the agent. Since the grade of an agent is a measure of their ability to grade correctly, the PeerRank method weights grades by the grades of the grading agent. The PeerRank method also provides an incentive for agents to grade correctly. As the grades of an agent depend on the grades of the grading agents, and as these grades themselves depend on the grades of other agents, we define the PeerRank method by a fixed point equation similar to the PageRank method for ranking web-pages.

Question: What is the peer rank method?


Optimized, Direct Sale of Privacy in Personal-Data Marketplaces. Very recently, we are witnessing the emergence of a number of start-ups that enables individuals to sell their private data directly to brokers and businesses. While this new paradigm may shift the balance of power between individuals and companies that harvest data, it raises some practical, fundamental questions for users of these services: how they should decide which data must be vended and which data protected, and what a good deal is. In this work, we investigate a mechanism that aims at helping users address these questions. The investigated mechanism relies on a hard-privacy model and allows users to share partial or complete profile data with broker companies in exchange for an economic reward. The theoretical analysis of the trade-off between privacy and money posed by such mechanism is the object of this work. We adopt a generic measure of privacy although part of our analysis focuses on some important examples of Bregman divergences. We find a parametric solution to the problem of optimal exchange of privacy for money, and obtain a closed-form expression and characterize the trade-off between profile-disclosure risk and economic reward for several interesting cases.

Question: How to sell privacy?


A Case for Hardware Protection of Guest VMs from Compromised Hypervisors in Cloud Computing. Cloud computing, enabled by virtualization technologies, is becoming a mainstream computing model. Many companies are starting to utilize the infrastructure-as-a-service (IaaS) cloud computing model, leasing guest virtual machines (VMs) from the infrastructure providers for economic reasons: to reduce their operating costs and to increase the flexibility of their own infrastructures. Yet, many companies may be hesitant to move to cloud computing due to security concerns. An integral part of any virtualization technology is the all-powerful hyper visor. A hyper visor is a system management software layer which can access all resources of the platform. Much research has been done on using hyper visors to monitor guest VMs for malicious code and on hardening hyper visors to make them more secure. There is, however, another threat which has not been addressed by researchers -- that of compromised or malicious hyper visors that can extract sensitive or confidential data from guest VMs. Consequently, we propose that a new research direction needs to be undertaken to tackle this threat. We further propose that new hardware mechanisms in the multi core microprocessors are a viable way of providing protections for the guest VMs from the hyper visor, while still allowing the hyper visor to flexibly manage the resources of the physical platform.

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


Feature-based attention influences motion processing gain in macaque visual cortex. Changes in neural responses based on spatial attention have been demonstrated in many areas of visual cortex, indicating that the neural correlate of attention is an enhanced response to stimuli at an attended location and reduced responses to stimuli elsewhere. Here we demonstrate non-spatial, feature-based attentional modulation of visual motion processing, and show that attention increases the gain of direction-selective neurons in visual cortical area MT without narrowing the direction-tuning curves. These findings place important constraints on the neural mechanisms of attention and we propose to unify the effects of spatial location, direction of motion and other features of the attended stimuli in a 'feature similarity gain model' of attention.

Question: How does attention influence motion processing gain in macaque visual cortex?


Project massive: self-regulation and problematic use of online gaming. A longitudinal design was employed to collect three waves of survey data over a 14 month period from 2790 online gamers. Respondents were asked questions about their gaming activity, motivations, personality, social and emotional environment, and the effect gaming has had on their lives. Prospective analysis was used to establish causal and temporal linkages among the repeatedly measured factors. While the data provide some indication that a player's reasons for playing do influence the development of problematic usage, these effects are overshadowed by the central importance of self-regulation in managing both the timing and amount of play. An individual's level of self-regulatory activity is shown to be very important in allowing them to avoid negative outcomes like problematic use. The role of depression is also discussed. With responsible use, online gaming appears to be a healthy recreational activity that provides millions of people with hours of social entertainment and adaptive diversion. However, failure to manage play behavior can lead to feelings of dependency.

Question: What is the role of depression in online gaming?


Broadband Bent Triangular Omnidirectional Antenna for RF Energy Harvesting. In this letter, a broadband bent triangular omnidirectional antenna is presented for RF energy harvesting. The antenna has a bandwidth for VSWR ≤ 2 from 850 MHz to 1.94 GHz. The antenna is designed to receive both horizontal and vertical polarized waves and has a stable radiation pattern over the entire bandwidth. Antenna has also been optimized for energy harvesting application and it is designed for 100 Ω input impedance to provide a passive voltage amplification and impedance matching to the rectifier. A peak efficiency of 60% and 17% is obtained for a load of 500 Ω at 980 and 1800 MHz, respectively. At a cell site while harvesting all bands simultaneously a voltage of 3.76 V for open circuit and 1.38 V across a load of 4.3 k Ω is obtained at a distance of 25 m using an array of two elements of the rectenna.

Question: What is the bandwidth of the antenna?


MIMO Radar with Widely Separated Antennas. MIMO (multiple-input multiple-output) radar refers to an architecture that employs multiple, spatially distributed transmitters and receivers. While, in a general sense, MIMO radar can be viewed as a type of multistatic radar, the separate nomenclature suggests unique features that set MIMO radar apart from the multistatic radar literature and that have a close relation to MIMO communications. This article reviews some recent work on MIMO radar with widely separated antennas. Widely separated transmit/receive antennas capture the spatial diversity of the target's radar cross section (RCS). Unique features of MIMO radar are explained and illustrated by examples. It is shown that with noncoherent processing, a target's RCS spatial variations can be exploited to obtain a diversity gain for target detection and for estimation of various parameters, such as angle of arrival and Doppler. For target location, it is shown that coherent processing can provide a resolution far exceeding that supported by the radar's waveform.

Question: What is the difference between MIMO radar and multistatic radar?


The Development Process of the Semantic Web and Web Ontology. This paper deals with the semantic web and web ontology. The existing ontology development processes are not catered towards casual web ontology development, a notion analogous to standard web page development. Ontologies have become common on the World-Wide Web[2]. Key features of this process include easy and rapid creation of ontological skeletons, searching and linking to existing ontologies and a natural language-based technique to improve presentation of ontologies[6]. Ontologies, however, vary greatly in size, scope and semantics. They can range from generic upper-level ontologies to domain-specific schemas. The success of the Semantic Web is based on the existance of numerous distributed ontologies, using which users can annotate their data, thereby enabling shared machine readable content. This paper elaborates the stages in a casual ontology development process. Key wordsToolkits; ontology; semantic web; language-based; web ontology.

Question: What is the development process of the semantic web?


RUNNING HEAD : THE SOCIAL ORIENTATION HYPOTHESIS-1The Origin of Cultural Differences in Cognition : The Social Orientation Hypothesis. A large body of research documents cognitive differences between Westerners and East Asians. Westerners tend to be more analytic and East Asians tend to be more holistic. These findings have often been explained as being due to corresponding differences in social orientation. Westerners are more independent and Easterners are more interdependent. However, comparisons of the cognitive tendencies of Westerners and East Asians do not allow us to rule out alternative explanations for the cognitive differences, such as linguistic and genetic differences, as well as cultural differences other than social orientation. In this review we summarize recent developments that provide stronger support for the social-orientation hypothesis. Keywordsculture; cross-cultural differences; within-culture differences; reasoning; independence/interdependence; holistic/analytic cognition RUNNING HEAD: THE SOCIAL ORIENTATION HYPOTHESIS 3 Cultural psychologists have consistently found different patterns of thinking and perception in different societies, with some cultures demonstrating a more analytic pattern and others a more holistic pattern (see Table 1). Analytic cognition is characterized by taxonomic and rule-based categorization of objects, a narrow focus in visual attention, dispositional bias in causal attribution, and the use of formal logic in reasoning. In contrast, holistic cognition is characterized by thematic and familyresemblance-based categorization of objects, a focus on contextual information and relationships in visual attention, an emphasis on situational causes in attribution, and dialecticism (Nisbett, Peng, Choi, & Norenzayan, 2001). What unites the elements of the analytic style is a tendency to focus on a single dimension or aspect—whether in categorizing objects or evaluating arguments—and a tendency to disentangle phenomena from

Question: What is the origin of cultural differences in cognition?


A Model for Competence and Integrity in Variable Payoff Games. Agents often have to trust one another when engaging in joint actions. In many cases, no single design team has the authority to assure that agents cooperate. Trust is required when agents hold potentially different values or conflicting goals. This paper presents a framework and some initial experiments for decomposing agent reputation within a multi-agent society into two characteristics: competence and integrity. The framework models competence as the probability of successfully carrying out an intended action. Integrity is modeled as a rational commitment to maintaining a reputation, based on the agent's assessment of the game's discount rate. We show that a simple, one-level-deep recursive model—given accurate knowledge of self and the other agent's competence and integrity (commitment to reputation)—outperforms titfor-tat and other standard strategies in evolutionary round-robin iterated prisoner's dilemma tournaments. This indicates that the approach taken here warrants further investigation using more realistic and complex strategies.

Question: How do you model trust?


The Mediator complex: a central integrator of transcription. The RNA polymerase II (Pol II) enzyme transcribes all protein-coding and most non-coding RNA genes and is globally regulated by Mediator — a large, conformationally flexible protein complex with a variable subunit composition (for example, a four-subunit cyclin-dependent kinase 8 module can reversibly associate with it). These biochemical characteristics are fundamentally important for Mediator's ability to control various processes that are important for transcription, including the organization of chromatin architecture and the regulation of Pol II pre-initiation, initiation, re-initiation, pausing and elongation. Although Mediator exists in all eukaryotes, a variety of Mediator functions seem to be specific to metazoans, which is indicative of more diverse regulatory requirements.

Question: What is the mediator complex?


Android Forensics: Simplifying Cell Phone Examinations.. It is hardly appropriate to call the devices many use to receive the occasional phone call a telephone any more. The capability of these devices is growing, as is the number of people utilizing them. By the end of 2009, 46.3% of mobile phones in use in the United States were reported to be smart phones (AdMob, 2010). With the increased availability of these powerful devices, there is also a potential increase for criminals to use this technology as well. Criminals could use smart phones for a number of activities such as committing fraud over e-mail, harassment through text messages, trafficking of child pornography, communications related to narcotics, etc. The data stored on smart phones could be extremely useful to analysts through the course of an investigation. Indeed, mobile devices are already showing themselves to have a large volume of probative information that is linked to an individual with just basic call history, contact, and text message data; smart phones contain even more useful information, such as e-mail, browser history, and chat logs. Mobile devices probably have more probative information that can be linked to an individual per byte examined than most computers -and this data is harder to acquire in a forensically proper fashion. Part of the problem lies in the plethora of cell phones available today and a general lack of hardware, software, and/or interface standardization within the industry. These differences range from the media on which data is stored and the file system to the operating system and the effectiveness of certain tools. Even different model cell phones made by the same manufacture may require different data cables and software to access the phone's information. The good news is there are numerous people in the field working on making smart phone forensics easier. Already there is material available on how to conduct an examination on Blackberry phones and a growing numb

Question: What is the difference between a smart phone and a regular phone?


Digital dentistry: an overview of recent developments for CAD/CAM generated restorations. As in many other industries, production stages are increasingly becoming automated in dental technology. As the price of dental laboratory work has become a major factor in treatment planning and therapy, automation could enable more competitive production in high-wage areas like Western Europe and the USA. Advances in computer technology now enable cost-effective production of individual pieces. Dental restorations produced with computer assistance have become more common in recent years. Most dental companies have access to CAD/CAM procedures, either in the dental practice, the dental laboratory or in the form of production centres. The many benefits associated with CAD/CAM generated dental restorations include: the access to new, almost defect-free, industrially prefabricated and controlled materials; an increase in quality and reproducibility and also data storage commensurate with a standardised chain of production; an improvement in precision and planning, as well as an increase in efficiency. As a result of continual developments in computer hardware and software, new methods of production and new treatment concepts are to be expected, which will enable an additional reduction in costs. Dentists, who will be confronted with these techniques in the future, require certain basic knowledge if they are to benefit from these new procedures. This article gives an overview of CAD/CAM-technologies and systems available for dentistry today.

Question: What is the difference between CAD/CAM and CAM?


Offensive Language Detection Using Multi-level Classification. Text messaging through the Internet or cellular phones has become a major medium of personal and commercial communication. In the same time, flames (such as rants, taunts, and squalid phrases) are offensive/abusive phrases which might attack or offend the users for a variety of reasons. An automatic discriminative software with a sensitivity parameter for flame or abusive language detection would be a useful tool. Although a human could recognize these sorts of useless annoying texts among the useful ones, it is not an easy task for computer programs. In this paper, we describe an automatic flame detection method which extracts features at different conceptual levels and applies multilevel classification for flame detection. While the system is taking advantage of a variety of statistical models and rule-based patterns, there is an auxiliary weighted pattern repository which improves accuracy by matching the text to its graded entries.

Question: How to detect flame in text?


Conceptualizing Context for Pervasive Advertising. Profile-driven personalization based on socio-demographics is currently regarded as the most convenient base for successful personalized advertising. However, signs point to the dormant power of context recognition: Advertising systems that can adapt to the situational context of a consumer will rapidly gain importance. While technologies that can sense the environment are increasingly advanced, questions such as what to sense and how to adapt to a consumer's context are largely unanswered. In this chapter, we analyze the purchase context of a retail outlet and conceptualize it such that adaptive pervasive advertising applications really deliver on their potential: showing the right message at the right time to the right recipient. full version published as: Bauer, Christine & Spiekermann, Sarah (2011). Conceptualizing Context for Pervasive Advertising. In Müller, Jörg, Alt, Florian, & Michelis, Daniel (Eds.), Pervasive Advertising (pp. 159-183). London: Springer.

Question: What is the context of a retail outlet?


When Morality Opposes Justice : Conservatives Have Moral Intuitions that Liberals may not Recognize. Researchers in moral psychology and social justice have agreed that morality is about matters of harm, rights, and justice. On this definition of morality, conservative opposition to social justice programs appears to be immoral, and has been explained as a product of various non-moral processes such as system justification or social dominance orientation. In this article we argue that, from an anthropological perspective, the moral domain is usually much broader, encompassing many more aspects of social life and valuing institutions as much or more than individuals. We present theoretical and empirical reasons for believing that there are five psychological systems that provide the foundations for the world s many moralities. The five foundations are psychological preparations for detecting and reacting emotionally to issues related to harm/care, fairness/reciprocity, ingroup/loyalty, authority/respect, and purity/sanctity. Political liberals have moral intuitions primarily based upon the first two foundations, and therefore misunderstand the moral motivations of political conservatives, who generally rely upon all five foundations.

Question: What is the difference between liberals and conservatives?


Experimental Analysis of a UAV-Based Wireless Power Transfer Localization System. Sensors deployed in remote locations provide unprecedented amounts of data, but powering these sensors over long periods remains a challenge. In this paper, we develop and present a UAV-based wireless power transfer system. We discuss design considerations and present our system that allows a UAV to fly to remote locations to charge hard to access sensors. We analyze the impact of different materials on the wireless power transfer system. Since GPS does not provide sufficient accuracy, we develop and experimentally characterize a relative localization algorithm based on sensing the magnetic field of the power transfer system and optical flow that allows the UAV to localize the sensor with an average error of 15 cm to enable the transfer of on average 4.2 W . These results overcome some of the practical challenges associated with wirelessly charging sensors with a UAV and show that UAVs with wireless power transfer systems can greatly extend the life of remotely deployed sensors.

Question: How to localize a UAV?


Approximation by exponential sums revisited ✩. Article history: Received 15 May 2009 Accepted 15 August 2009 Available online 2 September 2009 Communicated by Ginette Saracco

Question: How large is the canadian military?


Benchmarks as Limits to Arbitrage : Understanding the Low Volatility Anomaly ∗. Over the past 41 years, high volatility and high beta stocks have substantially underperformed low volatility and low beta stocks in U.S. markets. We propose an explanation that combines the average investor's preference for risk and the typical institutional investor's mandate to maximize the ratio of excess returns and tracking error relative to a fixed benchmark (the information ratio) without resorting to leverage. Models of delegated asset management show that such mandates discourage arbitrage activity in both high alpha, low beta stocks and low alpha, high beta stocks. This explanation is consistent with several aspects of the low volatility anomaly including why it has strengthened in recent years even as institutional investors have become more dominant.

Question: What is the low volatility anomaly?


A hybrid data analytic approach to predict college graduation status and its determinative factors. Purpose – The prediction of graduation rates of college students has become increasingly important to colleges and universities across the USA and the world. Graduation rates, also referred to as completion rates, directly impact university rankings and represent a measurement of institutional performance and student success. In recent years, there has been a concerted effort by federal and state governments to increase the transparency and accountability of institutions, making "graduation rates" an important and challenging university goal. In line with this, the main purpose of this paper is to propose a hybrid data analytic approach which can be flexibly implemented not only in the USA but also at various colleges across the world which would help predict the graduation status of undergraduate students due to its generic nature. It is also aimed at providing a means of determining and ranking the critical factors of graduation status. Design/methodology/approach – This study focuses on developing a novel hybrid data analytic approach to predict the degree completion of undergraduate students at a four-year public university in the USA. Via the deployment of the proposed methodology, the data were analyzed using three popular data mining classifications methods (i.e. decision trees, artificial neural networks, and support vector machines) to develop predictive degree completion models. Finally, a sensitivity analysis is performed to identify the relative importance of each predictor factor driving the graduation. Findings – The sensitivity analysis of the most critical factors in predicting graduation rates is determined to be fall-term grade-point average, housing status (on campus or commuter), and which high school the student attended. The least influential factors of graduation status are ethnicity, whether or not a student had work study, and whether or not a

Question: What is the most important factor in predicting graduation rates?


FCNN: Fourier Convolutional Neural Networks. The Fourier domain is used in computer vision and machine learning as image analysis tasks in the Fourier domain are analogous to spatial domain methods but are achieved using different operations. Convolutional Neural Networks (CNNs) use machine learning to achieve state-of-the-art results with respect to many computer vision tasks. One of the main limiting aspects of CNNs is the computational cost of updating a large number of convolution parameters. Further, in the spatial domain, larger images take exponentially longer than smaller image to train on CNNs due to the operations involved in convolution methods. Consequently, CNNs are often not a viable solution for large image computer vision tasks. In this paper a Fourier Convolution Neural Network (FCNN) is proposed whereby training is conducted entirely within the Fourier domain. The advantage offered is that there is a significant speed up in training time without loss of effectiveness. Using the proposed approach larger images can therefore be processed within viable computation time. The FCNN is fully described and evaluated. The evaluation was conducted using the benchmark Cifar10 and MNIST datasets, and a bespoke fundus retina image dataset. The results demonstrate that convolution in the Fourier domain gives a significant speed up without adversely affecting accuracy. For simplicity the proposed FCNN concept is presented in the context of a basic CNN architecture, however, the FCNN concept has the potential to improve the speed of any neural network system involving convolution.

Question: What is Fourier Convolutional Neural Network?


Data mining in metric space: an empirical analysis of supervised learning performance criteria. Many criteria can be used to evaluate the performance of supervised learning. Different criteria are appropriate in different settings, and it is not always clear which criteria to use. A further complication is that learning methods that perform well on one criterion may not perform well on other criteria. For example, SVMs and boosting are designed to optimize accuracy, whereas neural nets typically optimize squared error or cross entropy. We conducted an empirical study using a variety of learning methods (SVMs, neural nets, k-nearest neighbor, bagged and boosted trees, and boosted stumps) to compare nine boolean classification performance metrics: Accuracy, Lift, F-Score, Area under the ROC Curve, Average Precision, Precision/Recall Break-Even Point, Squared Error, Cross Entropy, and Probability Calibration. Multidimensional scaling (MDS) shows that these metrics span a low dimensional manifold. The three metrics that are appropriate when predictions are interpreted as probabilities: squared error, cross entropy, and calibration, lay in one part of metric space far away from metrics that depend on the relative order of the predicted values: ROC area, average precision, break-even point, and lift. In between them fall two metrics that depend on comparing predictions to a threshold: accuracy and F-score. As expected, maximum margin methods such as SVMs and boosted trees have excellent performance on metrics like accuracy, but perform poorly on probability metrics such as squared error. What was not expected was that the margin methods have excellent performance on ordering metrics such as ROC area and average precision. We introduce a new metric, SAR, that combines squared error, accuracy, and ROC area into one metric. MDS and correlation analysis shows that SAR is centrally located and correlates well with other metrics, suggesting that it is a good general purpose met

Question: What is the difference between accuracy, lift, and ROC area?


Finding surprising patterns in a time series database in linear time and space. The problem of finding a specified pattern in a time series database (i.e. query by content) has received much attention and is now a relatively mature field. In contrast, the important problem of enumerating all surprising or interesting patterns has received far less attention. This problem requires a meaningful definition of "surprise", and an efficient search technique. All previous attempts at finding surprising patterns in time series use a very limited notion of surprise, and/or do not scale to massive datasets. To overcome these limitations we introduce a novel technique that defines a pattern surprising if the frequency of its occurrence differs substantially from that expected by chance, given some previously seen data.

Question: What is a pattern surprising?


TruSpy: Cache Side-Channel Information Leakage from the Secure World on ARM Devices. As smart, embedded devices are increasingly integrated into our daily life, the security of these devices has become a major concern. The ARM processor family, which powers more than 60% of embedded devices, introduced TrustZone technology to offer security protection via an isolated execution environment called secure world. Caches in TrustZone-enabled processors are extended with a nonsecure (NS) bit to indicate whether a cache line is used by the secure world or the normal world. This cache design improves system performance by eliminating the need to perform cache flush during world switches; however, it also enables cache contention between the two worlds. In this work, we present TruSpy, the first study of timingbased cache side-channel information leakage of TrustZone. Our proposed attack exploits the cache contention between normal world and secure world to recover secret information from secure world. Two attacks are proposed in TruSpy, namely, the normal world OS attack and the normal world Android app attack. In the OS-based attack, the attacker is able to access virtual-to-physical address translation and high precision timers. In the Android app-based attack, these tools are unavailable to the attacker, so we devise a novel method that uses the expected channel statistics to allocate memory for cache probing. We also show how an attacker might use the less accurate performance event interface as a timer. Using the T-table based AES implementation in OpenSSL 1.0.1f as an example, we demonstrate that it is possible for a normal world attacker to steal a fine-grained secret from the secure world using a timing-based cache side-channel. We can recover the full AES encryption key via either the OS-based attack or the Android app-based attack. Since our zero permission TruSpy attack is based on the cache design in TrustZone enabled ARM processors, it poses a significant threa

Question: What is the size of the canadian military?


A decision cognizant Kullback-Leibler divergence. In decision making systems involving multiple classifiers there is the need to assess classifier (in)congruence, that is to gauge the degree of agreement between their outputs. A commonly used measure for this purpose is the Kullback-Leibler (KL) divergence. We propose a variant of the KL divergence, named decision cognizant Kullback-Leibler divergence (DC-KL), to reduce the contribution of the minority classes, which obscure the true degree of classifier incongruence. We investigate the properties of the novel divergence measure analytically and by simulation studies. The proposed measure is demonstrated to be more robust to minority class clutter. Its sensitivity to estimation noise is also shown to be considerably lower than that of the classical KL divergence. These properties render the DC-KL divergence a much better statistic for discriminating between classifier congruence and incongruence in pattern recognition systems.

Question: What is the Kullback-Leibler divergence?


Satellite alerts track deforestation in real time. A satellite-based alert system could prove a potent weapon in the fight against deforestation. As few as eight hours after it detects that trees are being cut down, the system will send out e-mails warning that an area is endangered. That rapid response could enable environmental managers to catch illegal loggers before they damage large swathes of forest. " It's going to be very, very helpful, " says Brian Zutta Salazar, a remote-sensing scientist at the Peruvian Ministry of the Environment in Lima. Satellites are already valuable tools for monitoring deforestation; in recent decades, they have delivered consistent data on forest change over large and often remote areas. One such effort, the Real Time System for Detection of Deforestation, or DETER, has helped Brazil's government to reduce its deforestation rate by almost 80% since 2004, by alerting the country's environmental police to large-scale forest clearing. But DETER and other existing alert systems can be relatively slow to yield useful information. They use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra satellite, which at its top resolution produces images with pixels covering an area 250 metres on each side, roughly equivalent to 10 football pitches. This is too big to spot small changes in land cover, so it can take computer programs that process MODIS data weeks or even months to detect that a forest is being cleared. " By the time MODIS picks up on it, it's almost too late, " says Peter Ellis, a forest-carbon scientist at the Nature Conservancy, a conservation group in Arlington, Virginia. Seeking to provide a sharper view, geographer Matthew Hansen of the University of Maryland in College Park and his colleagues published maps showing year-to-year changes in global forest cover from 2000 to 2012 (M. C. Hansen et al. Science 342, 850–853; 2013). The researchers relied on data from NASA's two active Landsat satelli

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


NOBLE – Flexible concept recognition for large-scale biomedical natural language processing. Natural language processing (NLP) applications are increasingly important in biomedical data analysis, knowledge engineering, and decision support. Concept recognition is an important component task for NLP pipelines, and can be either general-purpose or domain-specific. We describe a novel, flexible, and general-purpose concept recognition component for NLP pipelines, and compare its speed and accuracy against five commonly used alternatives on both a biological and clinical corpus. NOBLE Coder implements a general algorithm for matching terms to concepts from an arbitrary vocabulary set. The system's matching options can be configured individually or in combination to yield specific system behavior for a variety of NLP tasks. The software is open source, freely available, and easily integrated into UIMA or GATE. We benchmarked speed and accuracy of the system against the CRAFT and ShARe corpora as reference standards and compared it to MMTx, MGrep, Concept Mapper, cTAKES Dictionary Lookup Annotator, and cTAKES Fast Dictionary Lookup Annotator. We describe key advantages of the NOBLE Coder system and associated tools, including its greedy algorithm, configurable matching strategies, and multiple terminology input formats. These features provide unique functionality when compared with existing alternatives, including state-of-the-art systems. On two benchmarking tasks, NOBLE's performance exceeded commonly used alternatives, performing almost as well as the most advanced systems. Error analysis revealed differences in error profiles among systems. NOBLE Coder is comparable to other widely used concept recognition systems in terms of accuracy and speed. Advantages of NOBLE Coder include its interactive terminology builder tool, ease of configuration, and adaptability to various domains and tasks. NOBLE provides a term-to-concept matching system suitable for general concept re

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


Changes in structural and functional connectivity among resting-state networks across the human lifespan. At rest, the brain's sensorimotor and higher cognitive systems engage in organized patterns of correlated activity forming resting-state networks. An important empirical question is how functional connectivity and structural connectivity within and between resting-state networks change with age. In this study we use network modeling techniques to identify significant changes in network organization across the human lifespan. The results of this study demonstrate that whole-brain functional and structural connectivity both exhibit reorganization with age. On average, functional connections within resting-state networks weaken in magnitude while connections between resting-state networks tend to increase. These changes can be localized to a small subset of functional connections that exhibit systematic changes across the lifespan. Collectively, changes in functional connectivity are also manifest at a system-wide level, as components of the control, default mode, saliency/ventral attention, dorsal attention, and visual networks become less functionally cohesive, as evidenced by decreased component modularity. Paralleling this functional reorganization is a decrease in the density and weight of anatomical white-matter connections. Hub regions are particularly affected by these changes, and the capacity of those regions to communicate with other regions exhibits a lifelong pattern of decline. Finally, the relationship between functional connectivity and structural connectivity also appears to change with age; functional connectivity along multi-step structural paths tends to be stronger in older subjects than in younger subjects. Overall, our analysis points to age-related changes in inter-regional communication unfolding within and between resting-state networks.

Question: How do changes in functional connectivity and structural connectivity across the human lifespan?


Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey. This paper represents energy efficient routing protocols in WSN. It is a collection of sensor nodes with a set of limited Processor and limited memory unit embedded in it. Reliable routing of packets from the sensor node to its base station is the most important task for the networks. The routing protocols applied for the other networks cannot be used here due to its battery powered nodes This paper gives an overview of the different routing strategies used in wireless sensor networks and gives a brief working model of energy efficient routing protocols in WSN. It also shows the comparison of these different routing protocols based on metrics such as mobility support, stability, issues and latency.

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


Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogram-based model, the FM has an intrinsic limitation-no spatial information is taken into account. This causes the FM model to work only on well-defined images with low levels of noise; unfortunately, this is often not the the case due to artifacts such as partial volume effect and bias field distortion. Under these conditions, FM model-based methods produce unreliable results. Here, the authors propose a novel hidden Markov random field (HMRF) model, which is a stochastic process generated by a MRF whose state sequence cannot be observed directly but which can be indirectly estimated through observations. Mathematically, it can be shown that the FM model is a degenerate version of the HMRF model. The advantage of the HMRF model derives from the way in which the spatial information is encoded through the mutual influences of neighboring sites. Although MRF modeling has been employed in MR image segmentation by other researchers, most reported methods are limited to using MRF as a general prior in an FM model-based approach. To fit the HMRF model, an EM algorithm is used. The authors show that by incorporating both the HMRF model and the EM algorithm into a HMRF-EM framework, an accurate and robust segmentation can be achieved. More importantly, the HMRF-EM framework can easily be combined with other techniques. As an example, the authors show how the bias field correction algorithm of Guillemaud and Brady (1997) can be incorporated into this framework to achieve a three-dimensional fully automated approach for brain MR image segmentation.

Question: How to segment brain MR images through a hidden Markov random field model and the expectation-maximization algorithm.


Measurement of carotid blood pressure and local pulse wave velocity changes during cuff induced hyperemia. We present a prototype design of dual element photoplethysmograph (PPG) probe along with associated measurement system for carotid local pulse wave velocity (PWV) evaluation in a non-invasive and continuous manner. The PPG probe consists of two identical sensing modules placed 23 mm apart. Simultaneously measured blood pulse waveforms from these arterial sites were processed and the pulse transit time delay was resolved using the developed application-specific software. The ability of developed PPG probe and associated measurement system to detect acute changes in carotid local PWV due to blood pressure (BP) variations was experimentally validated by an in-vivo study. Intra-subject carotid BP elevation was achieved by an upper arm cuff based occlusion, which offered a controlled way of local PWV escalation. The elevated carotid BP values were also recorded by a calibrated pressure tonometer prior to the study, and was used as a reference. A significant increment (1.0 – 2.6 m/s) in local PWV was observed and was proportional to the BP increment induced by the occlusive reactive hyperemia. Study results demonstrated the feasibility of real-time signal acquisition and reliable local PWV evaluation under normal and elevated BP conditions using the developed measurement system.

Question: How to measure carotid blood pressure?


Social Dominance An Intergroup Theory of Social Hierarchy and Oppression. Social dominance : an intergroup theory of social hierarchy and oppression / Jim Sidanius, Felicia Pratto. p. cm. Includes bibliographical references and index.

Question: What is the intergroup theory of social hierarchy and oppression?


Exploring the Interconnectedness of Cryptocurrencies using Correlation Networks. Correlation networks were used to detect characteristics which, although fixed over time, have an important influence on the evolution of prices over time. Potentially important features were identified using the websites and whitepapers of cryptocurrencies with the largest userbases. These were assessed using two datasets to enhance robustness: one with fourteen cryptocurrencies beginning from 9 November 2017, and a subset with nine cryptocurrencies starting 9 September 2016, both ending 6 March 2018. Separately analysing the subset of cryptocurrencies raised the number of data points from 115 to 537, and improved robustness to changes in relationships over time. Excluding USD Tether, the results showed a positive association between different cryptocurrencies that was statistically significant. Robust, strong positive associations were observed for six cryptocurrencies where one was a fork of the other; Bitcoin / Bitcoin Cash was an exception. There was evidence for the existence of a group of cryptocurrencies particularly associated with Cardano, and a separate group correlated with Ethereum. The data was not consistent with a token's functionality or creation mechanism being the dominant determinants of the evolution of prices over time but did suggest that factors other than speculation contributed to the price.

Question: What is the difference between a fork and a hard fork?


Factorized graph matching. Graph matching plays a central role in solving correspondence problems in computer vision. Graph matching problems that incorporate pair-wise constraints can be cast as a quadratic assignment problem (QAP). Unfortunately, QAP is NP-hard and many algorithms have been proposed to solve different relaxations. This paper presents factorized graph matching (FGM), a novel framework for interpreting and optimizing graph matching problems. In this work we show that the affinity matrix can be factorized as a Kronecker product of smaller matrices. There are three main benefits of using this factorization in graph matching: (1) There is no need to compute the costly (in space and time) pair-wise affinity matrix; (2) The factorization provides a taxonomy for graph matching and reveals the connection among several methods; (3) Using the factorization we derive a new approximation of the original problem that improves state-of-the-art algorithms in graph matching. Experimental results in synthetic and real databases illustrate the benefits of FGM. The code is available at http://humansensing.cs.cmu.edu/fgm.

Question: What is the connection between graph matching and quadratic assignment problem?


An architecture for scalable, universal speech recognition. This thesis describes MultiSphinx, a concurrent architecture for scalable, low-latency automatic speech recognition. We first consider the problem of constructing a universal "core" speech recognizer on top of which domain and task specific adaptation layers can be constructed. We then show that when this problem is restricted to that of expanding the search space from a "core" vocabulary to a superset of this vocabulary across multiple passes of search, it allows us to effectively "factor" a recognizer into components of roughly equal complexity. We present simple but effective algorithms for constructing the reduced vocabulary and associated statistical language model from an existing system. Finally, we describe the MultiSphinx decoder architecture, which allows multiple passes of recognition to operate concurrently and incrementally, either in multiple threads in the same process, or across multiple processes on separate machines, and which allows the best possible partial results, including confidence scores, to be obtained at any time during the recognition process.

Question: What is the architecture of speech recognition?


Autonomous decision-making: a data mining approach. The researchers and practitioners of today create models, algorithms, functions, and other constructs defined in abstract spaces. The research of the future will likely be data driven. Symbolic and numeric data that are becoming available in large volumes will define the need for new data analysis techniques and tools. Data mining is an emerging area of computational intelligence that offers new theories, techniques, and tools for analysis of large data sets. In this paper, a novel approach for autonomous decision-making is developed based on the rough set theory of data mining. The approach has been tested on a medical data set for patients with lung abnormalities referred to as solitary pulmonary nodules (SPNs). The two independent algorithms developed in this paper either generate an accurate diagnosis or make no decision. The methodology discussed in the paper depart from the developments in data mining as well as current medical literature, thus creating a variable approach for autonomous decision-making.

Question: What is the rough set theory of data mining?


Culture, corruption, suicide, happiness and global social media use: a cross-cultural perspective. This study was conducted to answer this simple question: 'Can cultural values explain global social media use?' Along with cultural dimensions introduced by past studies we also added several demographic, socio-economic and personality variables into this study that generated quite interesting findings. We found that there are low levels of suicide, more happiness and more corruption in societies that use social media heavily. We also observed that GDP per capita and median age are negatively related with social media use. Self-esteem stood out as important variable related to social media use intensity along with emotional expressiveness, openness and conscientiousness. Contrary to the common view, nation-level social capital achievement was negatively related with social media use and there was absolutely no relationship between high-context and low-context communication characteristics and local social media use. Some other findings also indicated that conservative and collectivistic countries use social media more often than do individualistic and developed countries. Schwartz's cultural dimensions and the results of the GLOBE study accounted for a considerable amount of variation in country-level social media use where Hofstede and Trompenaars' cultural dimensions were insignificant. Since most of the cultural values failed to explain the intensity of social media use, we also developed a cross-cultural online communication framework called cross-cultural self and others' worth.

Question: What is the relationship between social media use and suicide?