Scalable production of large quantities of defect-free few-layer graphene by shear exfoliation in liquids.. To progress from the laboratory to commercial applications, it will be necessary to develop industrially scalable methods to produce large quantities of defect-free graphene. Here we show that high-shear mixing of graphite in suitable stabilizing liquids results in large-scale exfoliation to give dispersions of graphene nanosheets. X-ray photoelectron spectroscopy and Raman spectroscopy show the exfoliated flakes to be unoxidized and free of basal-plane defects. We have developed a simple model that shows exfoliation to occur once the local shear rate exceeds 10(4) s(-1). By fully characterizing the scaling behaviour of the graphene production rate, we show that exfoliation can be achieved in liquid volumes from hundreds of millilitres up to hundreds of litres and beyond. The graphene produced by this method performs well in applications from composites to conductive coatings. This method can be applied to exfoliate BN, MoS2 and a range of other layered crystals.

Question: How to exfoliate graphite in liquids?


The HAWKwood Database. We present a database consisting of wood pile images, which can be used as a benchmark to evaluate the performance of wood pile detection and surveying algorithms. We distinguish six database categories which can be used for different types of algorithms. Images of real and synthetic scenes are provided, which consist of 7655 images divided into 354 data sets. Depending on the category the data sets either include ground truth data or forestry specific measurements with which algorithms may be compared.

Question: What is the database for?


Unsupervised detection of surface defects: A two-step approach. In this paper, we focus on the problem of finding anomalies in surface images. Despite enormous research efforts and advances, it still remains a big challenge to be solved. This paper proposes a unified approach for defect detection. Our proposed method consists of two phases: (1) global estimation and (2) local refinement. First, we roughly estimate defects by applying a spectral-based approach in a global manner. We then locally refine the estimated region based on the distributions of pixel intensities derived from defect and defect-free regions. Experimental results show that the proposed method outperforms the previous defect detection methods and gives robust results even in noisy surface defect images.

Question: How to detect defects in surface images?


Removal Mechanism in Chemical Mechanical Polishing : Theory and Modeling. The abrasion mechanism in solid-solid contact mode of the chemical mechanical polishing (CMP) process is investigated in detail. Based on assumptions of plastic contact over wafer-abrasive and pad-abrasive interfaces, the normal distribution of abrasive size and an assumed periodic roughness of pad surface, a novel model is developed for material removal in CMP. The basic model is = removed, where is the density of wafer, the number of active abrasives, and removed the volume of material removed by a single abrasive. The model proposed integrates process parameters including pressure and velocity and other important input parameters including the wafer hardness, pad hardness, pad roughness, abrasive size, and abrasive geometry into the same formulation to predict the material removal rate ( ). An interface between the chemical effect and mechanical effect has been constructed through a fitting parameter , a "dynamical" hardness value of the wafer surface, in the model. It reflects the influences of chemicals on the mechanical material removal. The fluid effect in the current model is attributed to the number of active abrasives. It is found that the nonlinear down pressure dependence of material removal rate is related to a probability density function of the abrasive size and the elastic deformation of the pad. Compared with experimental results, the model accurately predicts . With further verification of the model, a better understanding of the fundamental mechanism involved in material removal in the CMP process, particularly different roles played by the consumables and their interactions, can be obtained.

Question: What is the removal mechanism in chemical mechanical polishing?


Algebraic feature extraction of image for recognition. The extraction of image features is one of the fundamental tasks in image recognition . Up until now, there have been several kinds of features to be used for the purpose of image recognition as follows: (1) visual features ; (2) statistical features of pixel ; (3) transform coefficient features . In addition, there is another kind of feature which the author believes is very useful, i.e . (4) algebraic features which represent intrinsic attributions of an image . Singular Values (SV) of image are this kind of feature . In this paper, we prove that SV feature vector has some important properties of algebraic and geometric invariance, and insensitiveness to noise . These properties are very useful for the description and recognition of images . As an example, SV feature vector is used for the problem of recognizing human facial images . In this paper, using SV feature vector samples of facial images, a normal pattern Bayes classification model based on Sammon s optimal descriminant plane is constructed . The experimental result shows that SV feature vector has good performance of class separation . Image recognition Algebraic feature extraction Singular value feature Facial image recognition Discrinlinant vector Dimensionality reduction

Question: What is the difference between a feature vector and a discriminant vector?


Defending against Internet worms: a signature-based approach. With the capability of infecting hundreds of thousands of hosts, worms represent a major threat to the Internet. The defense against Internet worms is largely an open problem. This paper investigates two important problems. Can a localized defense system detect new worms that were not seen before and moreover, capture the attack packets? How to identify polymorphic worms from the normal background traffic? We have two major contributions here. The first contribution is the design of a novel double-honeypot system, which is able to automatically detect new worms and isolate the attack traffic. The second contribution is the proposal of a new type of position-aware distribution signatures (PADS), which fit in the gap between the traditional signatures and the anomaly-based systems. We propose two algorithms based on expectation-maximization (EM) and Gibbs sampling for efficient computation of PADS from polymorphic worm samples. The new signature is capable of handling certain polymorphic worms. Our experiments show that the algorithms accurately separate new variants of the MSBlaster worm from the normal-traffic background.

Question: How to defend against Internet worms?


Algorithmic improvements for fast concurrent Cuckoo hashing. Fast concurrent hash tables are an increasingly important building block as we scale systems to greater numbers of cores and threads. This paper presents the design, implementation, and evaluation of a high-throughput and memory-efficient concurrent hash table that supports multiple readers and writers. The design arises from careful attention to systems-level optimizations such as minimizing critical section length and reducing interprocessor coherence traffic through algorithm re-engineering. As part of the architectural basis for this engineering, we include a discussion of our experience and results adopting Intel's recent hardware transactional memory (HTM) support to this critical building block. We find that naively allowing concurrent access using a coarse-grained lock on existing data structures reduces overall performance with more threads. While HTM mitigates this slowdown somewhat, it does not eliminate it. Algorithmic optimizations that benefit both HTM and designs for fine-grained locking are needed to achieve high performance.  Our performance results demonstrate that our new hash table design---based around optimistic cuckoo hashing---outperforms other optimized concurrent hash tables by up to 2.5x for write-heavy workloads, even while using substantially less memory for small key-value items. On a 16-core machine, our hash table executes almost 40 million insert and more than 70 million lookup operations per second.

Question: What is optimistic cuckoo hashing?


Stemming Algorithms: A Comparative Study and their Analysis. Stemming is an approach used to reduce a word to its stem or root form and is used widely in information retrieval tasks to increase the recall rate and give us most relevant results. There are number of ways to perform stemming ranging from manual to automatic methods, from language specific to language independent each having its own advantage over the other. This paper represents a comparative study of various available stemming alternatives widely used to enhance the effectiveness and efficiency of information retrieval.

Question: What is a comparative study?


IccTA: Detecting Inter-Component Privacy Leaks in Android Apps. Shake Them All is a popular "Wallpaper" application exceeding millions of downloads on Google Play. At installation, this application is given permission to (1) access the Internet (for updating wallpapers) and (2) use the device microphone (to change background following noise changes). With these permissions, the application could silently record user conversations and upload them remotely. To give more confidence about how Shake Them All actually processes what it records, it is necessary to build a precise analysis tool that tracks the flow of any sensitive data from its source point to any sink, especially if those are in different components.  Since Android applications may leak private data carelessly or maliciously, we propose IccTA, a static taint analyzer to detect privacy leaks among components in Android applications. IccTA goes beyond state-of-the-art approaches by supporting inter-component detection. By propagating context information among components, IccTA improves the precision of the analysis. IccTA outperforms existing tools on two benchmarks for ICC-leak detectors: DroidBench and ICC-Bench. Moreover, our approach detects 534 ICC leaks in 108 apps from MalGenome and 2,395 ICC leaks in 337 apps in a set of 15,000 Google Play apps.

Question: How to detect inter-component privacy leaks in android apps?


Assessing Suicide Risk and Emotional Distress in Chinese Social Media: A Text Mining and Machine Learning Study. BACKGROUND Early identification and intervention are imperative for suicide prevention. However, at-risk people often neither seek help nor take professional assessment. A tool to automatically assess their risk levels in natural settings can increase the opportunity for early intervention.   OBJECTIVE The aim of this study was to explore whether computerized language analysis methods can be utilized to assess one's suicide risk and emotional distress in Chinese social media.   METHODS A Web-based survey of Chinese social media (ie, Weibo) users was conducted to measure their suicide risk factors including suicide probability, Weibo suicide communication (WSC), depression, anxiety, and stress levels. Participants' Weibo posts published in the public domain were also downloaded with their consent. The Weibo posts were parsed and fitted into Simplified Chinese-Linguistic Inquiry and Word Count (SC-LIWC) categories. The associations between SC-LIWC features and the 5 suicide risk factors were examined by logistic regression. Furthermore, the support vector machine (SVM) model was applied based on the language features to automatically classify whether a Weibo user exhibited any of the 5 risk factors.   RESULTS A total of 974 Weibo users participated in the survey. Those with high suicide probability were marked by a higher usage of pronoun (odds ratio, OR=1.18, P=.001), prepend words (OR=1.49, P=.02), multifunction words (OR=1.12, P=.04), a lower usage of verb (OR=0.78, P<.001), and a greater total word count (OR=1.007, P=.008). Second-person plural was positively associated with severe depression (OR=8.36, P=.01) and stress (OR=11, P=.005), whereas work-related words were negatively associated with WSC (OR=0.71, P=.008), severe depression (OR=0.56, P=.005), and anxiety (OR=0.77, P=.02). Inconsistently, third-person plural was found to be negatively associat

Question: What is the difference between a pronoun and a prepend word?


Open Logo Detection Challenge. Existing logo detection benchmarks consider artificial deployment scenarios by assuming that large training data with fine-grained bounding box annotations for each class are available for model training. Such assumptions are often invalid in realistic logo detection scenarios where new logo classes come progressively and require to be detected with little or none budget for exhaustively labelling fine-grained training data for every new class. Existing benchmarks are thus unable to evaluate the true performance of a logo detection method in realistic and open deployments. In this work, we introduce a more realistic and challenging logo detection setting, called Open Logo Detection. Specifically, this new setting assumes fine-grained labelling only on a small proportion of logo classes whilst the remaining classes have no labelled training data to simulate the open deployment. We further create an open logo detection benchmark, called QMUL-OpenLogo, to promote the investigation of this new challenge. QMUL-OpenLogo contains 27,083 images from 352 logo classes, built by aggregating/refining 7 existing datasets and establishing an open logo detection evaluation protocol. To address this challenge, we propose a Context Adversarial Learning (CAL) approach to synthesising training data with coherent logo instance appearance against diverse background context for enabling more effective optimisation of contemporary deep learning detection models. Experiments show the performance advantage of CAL over existing state-of-the-art alternative methods on the more realistic and challenging open logo benchmark. The QMUL-OpenLogo benchmark is publicly available at https://qmul-openlogo.github.io/.

Question: What is the open logo detection challenge?


An agent-based decision support system for wholesale electricity market. Application software has been developed for analyzing and understanding a dynamic price change in the US wholesale power market. Traders can use the software as an effective decision-making tool by modeling and simulating a power market. The software uses different features of a decision support system by creating a framework for assessing new trading strategies in a competitive electricity trading environment. The practicality of the software is confirmed by comparing its estimation accuracy with those of other methods (e.g., neural network and genetic algorithm). The software has been applied to a data set regarding the California electricity crisis in order to examine whether the learning (convergence) speed of traders is different between the two periods (before and during the crisis). Such an application confirms the validity of the proposed software. © 2007 Elsevier B.V. All rights reserved.

Question: What is an agent-based decision support system for wholesale electricity market?


DeepLoco: dynamic locomotion skills using hierarchical deep reinforcement learning. Learning physics-based locomotion skills is a difficult problem, leading to solutions that typically exploit prior knowledge of various forms. In this paper we aim to learn a variety of environment-aware locomotion skills with a limited amount of prior knowledge. We adopt a two-level hierarchical control framework. First, low-level controllers are learned that operate at a fine timescale and which achieve robust walking gaits that satisfy stepping-target and style objectives. Second, high-level controllers are then learned which plan at the timescale of steps by invoking desired step targets for the low-level controller. The high-level controller makes decisions directly based on high-dimensional inputs, including terrain maps or other suitable representations of the surroundings. Both levels of the control policy are trained using deep reinforcement learning. Results are demonstrated on a simulated 3D biped. Low-level controllers are learned for a variety of motion styles and demonstrate robustness with respect to force-based disturbances, terrain variations, and style interpolation. High-level controllers are demonstrated that are capable of following trails through terrains, dribbling a soccer ball towards a target location, and navigating through static or dynamic obstacles.

Question: What is a biped?


A new approach for sparse matrix vector product on NVIDIA GPUs. The sparse matrix vector product (SpMV) is a key operation in engineering and scientific computing and, hence, it has been subjected to intense research for a long time. The irregular computations involved in SpMV make its optimization challenging. Therefore, enormous effort has been devoted to devise data formats to store the sparse matrix with the ultimate aim of maximizing the performance. Graphics Processing Units (GPUs) have recently emerged as platforms that yield outstanding acceleration factors. SpMV implementations for NVIDIA GPUs have already appeared on the scene. This work proposes and evaluates a new implementation of SpMV for NVIDIA GPUs based on a new format, ELLPACK-R, that allows storage of the sparse matrix in a regular manner. A comparative evaluation against a variety of storage formats previously proposed has been carried out based on a representative set of test matrices. The results show that, although the performance strongly depends on the specific pattern of the matrix, the implementation based on ELLPACK-R achieves higher overall performance. Moreover, a comparison with standard state-of-the-art superscalar processors reveals that significant speedup factors are achieved with GPUs. Copyright 2010 John Wiley & Sons, Ltd.

Question: What is the new approach for sparse matrix vector product on NVIDIA GPUs?


Using Smart Sensor Strings for Continuous Monitoring of Temperature Stratification in Large Water Bodies. A "smart" thermistor string for continuous long-term temperature profiling in large water bodies is described allowing highly matched yet low-cost spatial and temporal temperature measurements. The sensor uses the three-wire SDI-12 communications standard to enable a low-powered radio or data logger on supporting buoys to command measurements and retrieve high-resolution temperature data in digital form. Each "smart" temperature sensor integrates a thermistor element, measurement circuitry, power control, calibration coefficient storage, temperature computation, and data communications. Multiple addressable sensors at discrete vertical depths are deployed along a three-wire cable that provides power and allows data transfer at regular intervals. Circuit, manufacturing, and automated calibration techniques allow temperature measurements with a resolution of plusmn0.003degC, and with intersensor matching of plusmn0.006degC. The low cost of each sensor is achieved by using poor tolerance thermistor and circuit components in conjunction with a 15-bit charge-balance analog-to-digital converter. Sensor inaccuracies and temperature coefficients are corrected by a two-point calibration procedure made possible by a standard-curve generator within the sensor, based upon the method of finite differences. This two-point calibration process allows in-field sensor string calibration in stratified water bodies and provides a means to correct for long-term calibration drift without having to return the string to a laboratory

Question: How do you measure temperature in stratified water bodies?


Cancer statistics in China, 2015.. With increasing incidence and mortality, cancer is the leading cause of death in China and is a major public health problem. Because of China's massive population (1.37 billion), previous national incidence and mortality estimates have been limited to small samples of the population using data from the 1990s or based on a specific year. With high-quality data from an additional number of population-based registries now available through the National Central Cancer Registry of China, the authors analyzed data from 72 local, population-based cancer registries (2009-2011), representing 6.5% of the population, to estimate the number of new cases and cancer deaths for 2015. Data from 22 registries were used for trend analyses (2000-2011). The results indicated that an estimated 4292,000 new cancer cases and 2814,000 cancer deaths would occur in China in 2015, with lung cancer being the most common incident cancer and the leading cause of cancer death. Stomach, esophageal, and liver cancers were also commonly diagnosed and were identified as leading causes of cancer death. Residents of rural areas had significantly higher age-standardized (Segi population) incidence and mortality rates for all cancers combined than urban residents (213.6 per 100,000 vs 191.5 per 100,000 for incidence; 149.0 per 100,000 vs 109.5 per 100,000 for mortality, respectively). For all cancers combined, the incidence rates were stable during 2000 through 2011 for males (+0.2% per year; P = .1), whereas they increased significantly (+2.2% per year; P < .05) among females. In contrast, the mortality rates since 2006 have decreased significantly for both males (-1.4% per year; P < .05) and females (-1.1% per year; P < .05). Many of the estimated cancer cases and deaths can be prevented through reducing the prevalence of risk factors, while increasing the effectiveness of clinical care delivery, particularly for those living in rural areas and in disadvantaged popula

Question: What is the leading cause of cancer death in China?


Fourier Transform Decoding of Non-Binary LDPC Codes. Binary low-density parity-check (LDPC) codes have recently emerged as a promising alternative to turbo codes and have been shown to achieve excellent coding gains in AWGN channels. Non-binary LDPC codes have demonstrated improved performance over binary LDPC codes but their decoding is computationally intensive. Fourier transform decoding can reduce the decoding complexity but has a number of problems which can be avoided by implementing this algorithm in the log domain. In this paper Fourier transform decoding of non-binary LDPC codes in the log domain is described. The computational complexity and performance of this algorithm is then discussed. Differential evolution is then used to search for optimal binary and non-binary LDPC codes and it is shown by simulation that non-binary LDPC codes are superior.

Question: What is the computational complexity of Fourier transform decoding?


V-Clip: Fast and Robust Polyhedral Collision Detection. This article presents the Voronoi-clip, or V-Clip, collision detection alogrithm for polyhedral objects specified by a boundary representation. V-Clip tracks the closest pair of features between convex polyhedra, using an approach reminiscent of the Lin-Canny closest features algorithm. V-Clip is an improvement over the latter in several respects. Coding complexity is reduced, and robustness is significantly improved; the implementation has no numerical tolerances and does not exhibit cycling problems. The algorithm also handles penetrating polyhedra, and can therefore be used to detect collisions between nonvconvex polyhedra described as hierarchies of convex pieces. The article presents the theoretical principles of V-Clip, and gives a pseudocode description of the algorithm. It also documents various test that compare V-Clip, Lin-Canny, and the Enhanced GJK algorithm, a simplex-based algorithm that is widely used for the same application. The results show V-Clip to be a strong contender in this field, comparing favorably with the other algorithms in most of the tests, in term of both performance and robustness.

Question: What is the difference between the Lin-Canny and the Enhanced GJK algorithms?


Research challenges in legal-rule and QoS-aware cloud service brokerage. The ICT industry and specifically critical sectors, such as healthcare, transportation, energy and government, require as mandatory the compliance of ICT systems and services with legislation and regulation, as well as with standards. In the era of cloud computing, this compliance management issue is exacerbated by the distributed nature of the system and by the limited control that customers have on the services. Today, the cloud industry is aware of this problem (as evidenced by the compliance program of many cloud service providers), and the research community is addressing the many facets of the legal-rule compliance checking and quality assurance problem. Cloud service brokerage plays an important role in legislation compliance and QoS management of cloud services. In this paper we discuss our experience in designing a legal-rule and QoS-aware cloud service broker, and we explore relate research issues. Specifically we provide three main contributions to the literature: first, we describe the detailed design architecture of the legal-rule and QoS-aware broker. Second, we discuss our design choices which rely on the state of the art solutions available in literature. We cover four main research areas: cloud broker service deployment, seamless cloud service migration, cloud service monitoring, and legal rule compliance checking. Finally, from the literature review in these research areas, we identify and discuss research challenges.

Question: What is the state of the art in legal-rule and QoS-aware cloud service brokerage?


THE X-BAR THEORY OF PHRASE STRUCTURE. X-bar theory is widely regarded as a substantive theory of phrase structure properties in natural languages. In this paper we will demonstrate that a formalization of its content reveals very little substance in its claims. We state and discuss six conditions that encapsulate the claims of X-bar theory: Lexicality — each nonterminal is a projection of a preterminal; Succession — each X dominates an X for all n ≥ 0; Uniformity — all maximal projections have the same bar-level; Maximality — all non-heads are maximal projections; Centrality — the start symbol is a maximal projection; and Optionality — all and only non-heads are optional. We then consider recent proposals to 'eliminate' base components from transformational grammars and to reinterpret X-bar theory as a set of universal constraints holding for all languages at D-structure, arguing that this strategy fails. We show that, as constraints on phrase structure rule systems, the X-bar conditions have hardly any effect on the descriptive power of grammars, and that the principles with the most chance of making some descriptive difference are the least adhered to in practice. Finally, we reconstruct X-bar theory in a way that makes no reference to the notion of bar-level but instead makes the notion 'head of' the central one.∗

Question: What is the x-bar theory of phrase structure?


Decentralized Decision Making in the Game of Tic-tac-toe. Traditionally, the game of Tic-tac-toe is a pencil and paper game played by two people who take turn to place their pieces on a 3times3 grid with the objective of being the first player to fill a horizontal, vertical, or diagonal row with their pieces. What if instead of having one person playing against another, one person plays against a team of nine players, each of whom is responsible for one cell in the 3times3 grid? In this new way of playing the game, the team has to coordinate its players, who are acting independently based on their limited information. In this paper, we present a solution that can be extended to the case where two such teams play against each other, and also to other board games. Essentially, the solution uses a decentralized decision making, which at first seems to complicate the solution. However, surprisingly, we show that in this mode, an equivalent level of decision making ability comes from simple components that reduce system complexity

Question: What is a decentralized decision making?


A Hybrid Ant Colony Optimization Algorithm for Path Planning of Robot in Dynamic Environment. Ant colony optimization and artificial potential field were used respectively as global path planning and local path planning methods in this paper. Some modifications were made to accommodate ant colony optimization to path planning. Pheromone generated by ant colony optimization was also utilized to prevent artificial potential field from getting local minimum. Simulation results showed that the hybrid algorithm could satisfy the real-time demand. The comparison between ant colony optimization and genetic algorithm was also made in this paper.

Question: What is the hybrid ant colony optimization algorithm?


Docker Cluster Management for the Cloud - Survey Results and Own Solution. Docker provides a good basis to run composite applications in the cloud, especially if those are not cloud-aware, or cloud-native. However, Docker concentrates on managing containers on one host, but SaaS providers need a container management solution for multiple hosts. Therefore, a number of tools emerged that claim to solve the problem. This paper classifies the solutions, maps them to requirements from a case study and identifies gaps and integration requirements. We close some of these gaps with our own integration components and tool enhancements, resulting in the currently most complete management suite.

Question: What is docker cluster management for the cloud?


Moving Right Along: A Computational Model of Metaphoric Reasoning about Events. This paper describes the results of an implemented computational model that cashes out the belief that metaphor interpretation is grounded in embodied primitives. The speci c task addressed is the interpretation of simple causal narratives in the domains of Politics and Economics. The stories are taken from newspaper articles in these domains. When presented with a preparsed version of these narratives as input, the system described is able to generate commonsense inferences consistent with the input.

Question: What is a computational model of metaphoric reasoning about events?


Comparisons of waist circumferences measured at 4 sites.. BACKGROUND Waist circumference (WC) is now accepted as a practical measure of adipose tissue distribution. Four body sites for WC measurements are commonly used, as follows: immediately below the lowest ribs (WC1), the narrowest waist (WC2), the midpoint between the lowest rib and the iliac crest (WC3), and immediately above the iliac crest (WC4).   OBJECTIVE We sought to compare the magnitude and reliability of WC measured at these 4 sites in males and females.   DESIGN WC was measured at each site 1 time in all subjects [49 males and 62 females, aged 7-83 y, with a body mass index (in kg/m(2)) of 9-43] and 3 times in a subgroup (n = 93) by one experienced observer using a heavy-duty inelastic tape. Body fat was measured in a subgroup (n = 74) with the use of dual-energy X-ray absorptiometry.   RESULTS The mean values of WC were WC2 < WC1 < WC3 < WC4 (P < 0.01) in females and WC2 < WC1, WC3, and WC4 (P < 0.01) in males. For all 4 sites, measurement reproducibility was high, with intraclass correlation (r) values > 0.99. WC values were significantly correlated with fatness; correlations with trunk fat were higher than correlations with total body fat in both sexes.   CONCLUSIONS WC values at the 4 commonly used anatomic sites differ in magnitude depending on sex, are highly reproducible, and are correlated with total body and trunk adiposity in a sex-dependent manner. These observations have implications for the use of WC measurements in clinical practice and patient-oriented research.

Question: What is the difference between the 4 sites?


Metagenes and molecular pattern discovery using matrix factorization.. We describe here the use of nonnegative matrix factorization (NMF), an algorithm based on decomposition by parts that can reduce the dimension of expression data from thousands of genes to a handful of metagenes. Coupled with a model selection mechanism, adapted to work for any stochastic clustering algorithm, NMF is an efficient method for identification of distinct molecular patterns and provides a powerful method for class discovery. We demonstrate the ability of NMF to recover meaningful biological information from cancer-related microarray data. NMF appears to have advantages over other methods such as hierarchical clustering or self-organizing maps. We found it less sensitive to a priori selection of genes or initial conditions and able to detect alternative or context-dependent patterns of gene expression in complex biological systems. This ability, similar to semantic polysemy in text, provides a general method for robust molecular pattern discovery.

Question: What is the difference between nonnegative matrix factorization and hierarchical clustering?


Optical Character Recognition. 72  Abstract— The Optical Character Recognition is a mobile application. It uses smart mobile phones of android platform. This paper combines the functionality of Optical Character Recognition and speech synthesizer. The objective is to develop user friendly application which performs image to speech conversion system using android phones. The OCR takes image as the input, gets text from that image and then converts it into speech. This system can be useful in various applications like banking, legal industry, other industries, and home and office automation. It mainly designed for people who are unable to read any type of text documents. In this paper, the character recognition method is presented by using OCR technology and android phone with higher quality camera.

Question: What is the objective of this paper?


An integrated 122GHz differential frequency doubler with 37GHz bandwidth in 130 nm SiGe BiCMOS technology. This paper describes an integrated frequency multiplier, implemented as a Gilbert cell based frequency doubler in a 130 nm SiGe BiCMOS technology. The circuit demonstrates a 3 dB bandwidth of 97–134GHz with peak output power of 1 dBm for 1 dBm input power. The fundamental suppression, measured at the single-ended output, is better than 21 dBc while the frequency doubler consumes 69mW from a 3.3V supply. The doubler is preceded by a differential amplifier functioning as an active balun to generate a differential signal for the Gilbert cell.

Question: What is a Gilbert cell?


English Language Learners and Academic Achievement : Revisiting the Threshold Hypothesis. This nonexperimental study explored the predictive strength of English proficiency levels on academic achievement of middle school students in a sample of 17,470 native English-speaking (NES) students, 558 English language learners (current ELLs), and 500 redesignated fluent English proficient students (former ELLs). Results of multilevel analyses indicated that after controlling for relevant studentand school-level characteristics, former ELLs significantly outperformed current ELL and NES students in reading (effect sizes: 1.07 and 0.52) and mathematics (effect sizes: 0.86 and 0.42). The results support Cummins's (1979, 2000) lower level threshold hypothesis predicting that upon reaching adequate proficiency in the language of schooling and testing, ELLs would no longer experience academic disadvantages. Refinements for the theory and directions for future research are discussed.

Question: What is the threshold hypothesis?


WILDSENSING: Design and deployment of a sustainable sensor network for wildlife monitoring. The increasing adoption of wireless sensor network technology in a variety of applications, from agricultural to volcanic monitoring, has demonstrated their ability to gather data with unprecedented sensing capabilities and deliver it to a remote user. However, a key issue remains how to maintain these sensor network deployments over increasingly prolonged deployments. In this article, we present the challenges that were faced in maintaining continual operation of an automated wildlife monitoring system over a one-year period. This system analyzed the social colocation patterns of European badgers (Meles meles) residing in a dense woodland environment using a hybrid RFID-WSN approach. We describe the stages of the evolutionary development, from implementation, deployment, and testing, to various iterations of software optimization, followed by hardware enhancements, which in turn triggered the need for further software optimization. We highlight the main lessons learned: the need to factor in the maintenance costs while designing the system; to consider carefully software and hardware interactions; the importance of rapid prototyping for initial deployment (this was key to our success); and the need for continuous interaction with domain scientists which allows for unexpected optimizations.

Question: How to maintain a sensor network over a year?


Rethinking Feelings: An fMRI Study of the Cognitive Regulation of Emotion. The ability to cognitively regulate emotional responses to aversive events is important for mental and physical health. Little is known, however, about neural bases of the cognitive control of emotion. The present study employed functional magnetic resonance imaging to examine the neural systems used to reappraise highly negative scenes in unemotional terms. Reappraisal of highly negative scenes reduced subjective experience of negative affect. Neural correlates of reappraisal were increased activation of the lateral and medial prefrontal regions and decreased activation of the amygdala and medial orbito-frontal cortex. These findings support the hypothesis that prefrontal cortex is involved in constructing reappraisal strategies that can modulate activity in multiple emotion-processing systems.

Question: What is the neural basis of reappraisal?


MIMO radar theory and experimental results. The continuing progress of Moore's law has enabled the development of radar systems that simultaneously transmit and receive multiple coded waveforms from multiple phase centers and to process them in ways that have been unavailable in the past. The signals available for processing from these multiple-input multiple-output (MIMO) radar systems appear as spatial samples corresponding to the convolution of the transmit and receive aperture phase centers. The samples provide the ability to excite and measure the channel that consists of the transmit/receive propagation paths, the target and incidental scattering or clutter. These signals may be processed and combined to form an adaptive coherent transmit beam, or to search an extended area with high resolution in a single dwell. Adaptively combining the received data provides the effect of adaptively controlling the transmit beamshape and the spatial extent provides improved track-while-scan accuracy. This paper describes the theory behind the improved surveillance radar performance and illustrates this with measurements from experimental MIMO radars.

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


A 1.2V 64Gb 341GB/S HBM2 stacked DRAM with spiral point-to-point TSV structure and improved bank group data control. With the recent increasing interest in big data and artificial intelligence, there is an emerging demand for high-performance memory system with large density and high data-bandwidth. However, conventional DIMM-type memory has difficulty achieving more than 50GB/s due to its limited pin count and signal integrity issues. High-bandwidth memory (HBM) DRAM, with TSV technology and wide IOs, is a prominent solution to this problem, but it still has many limitations: including power consumption and reliability. This paper presents a power-efficient structure of TSVs with reliability and a cost-effective HBM DRAM core architecture.

Question: What is the difference between HBM and DDR4?


Forecasting stock price directional movements using technical indicators: Investigating window size effects on one-step-ahead forecasting. Accurate forecasting of directional changes in stock prices is important for algorithmic trading and investment management. Technical analysis has been successfully used in financial forecasting and recently researchers have explored the optimization of parameters for technical indicators. This study investigates the relationship between the window size used for calculating technical indicators and the accuracy of one-step-ahead (variable steps) forecasting. The directions of the future price movements are predicted using technical analysis and machine learning algorithms. Results show a correlation between window size and forecasting step size for the Support Vector Machines approach but not for the other approaches.

Question: What is the relationship between window size and forecasting step size?


Pixelwise View Selection for Unstructured Multi-View Stereo. This work presents a Multi-View Stereo system for robust and efficient dense modeling from unstructured image collections. Our core contributions are the joint estimation of depth and normal information, pixelwise view selection using photometric and geometric priors, and a multi-view geometric consistency term for the simultaneous refinement and image-based depth and normal fusion. Experiments on benchmarks and large-scale Internet photo collections demonstrate stateof-the-art performance in terms of accuracy, completeness, and efficiency. Fig. 1. Reconstructions for Louvre, Todai-ji, Paris Opera, and Astronomical Clock.

Question: What is the largest image collection?


A Machine Learning Based Intrusion Detection System for Software Defined 5G Network. As an inevitable trend of future 5G networks, Software Defined architecture has many advantages in providing centralized control and flexible resource management. But it is also confronted with various security challenges and potential threats with emerging services and technologies. As the focus of network security, Intrusion Detection Systems (IDS) are usually deployed separately without collaboration. They are also unable to detect novel attacks with limited intelligent abilities, which are hard to meet the needs of software defined 5G. In this paper, we propose an intelligent intrusion system taking the advances of software defined technology and artificial intelligence based on Software Defined 5G architecture. It flexibly combines security function modules which are adaptively invoked under centralized management and control with a globle view. It can also deal with unknown intrusions by using machine learning algorithms. Evaluation results prove that the intelligent intrusion detection system achieves a better performance.

Question: What is the difference between a software defined network and a software defined 5G network?


A Context-Aware Security Architecture for Emerging Applications. We describe an approach to building security services for context-aware environments. Specifically, we focus on the design of security services that incorporate the use of security-relevant "context" to provide flexible access control and policy enforcement. We previously presented a generalized access control model that makes significant use of contextual information in policy definition. This document provides a concrete realization of such a model by presenting a system-level service architecture, as well as early implementation experience with the framework. Through our context-aware security services, our system architecture offers enhanced authentication services, more flexible access control and a security subsystem that can adapt itself based on current conditions in the environment. We discuss our architecture and implementation and show how it can be used to secure several sample applications.

Question: What is a context-aware security architecture?


Design and Implementation of a 40-kV, 20-kJ/s Capacitor Charger for Pulsed-Power Application. This paper presents the design and implementation of a 40-kV, 20-kJ/s high-voltage capacitor charger based on a series/parallel resonant converter. The inclusion of the parallel resonant capacitor component in this circuit results in the production of a trapezoidal resonant current, which reduces conduction loss. This capacitor is practically realized as a part of the balancing network of the high-voltage rectifiers in the secondary side of the circuit. Particular attention in this paper is paid to the high-voltage transformer, which must be carefully designed to provide the required functionality without negative impact on the resonant circuit. A PSpice simulation has been used to prove that the proposed control method for the circuit is valid. This is supported with the experimental results, which verify that the operation of the circuit is as expected and that the converter is able to meet all the design criteria with an efficiency of up to 96%.

Question: How to design a high-voltage capacitor charger?


Application Design for Wearable Computing. The confluence of decades of computer science and computer engineering research in multimodal interaction (e.g., speech and gesture recognition), machine learning (e.g., classification and feature extraction), software (e.g., web browsers, distributed agents), electronics (e.g., energy-efficient microprocessors, head-mounted displays), design methodology in user-centered design, and rapid prototyping have enabled a new class of computers—wearable computers. The lecture takes the viewpoint of a potential designer or researcher in wearable computing. Designing wearable computers requires attention to many different factors because of the computer's closeness to the body and its use while performing other tasks. For the purposes of discussion, we have created the UCAMP framework, which consists of the following factors: user, corporal, attention, manipulation, and perception. Each of these factors and their importance is described. A number of example prototypes developed by the authors, as well as by other researchers, are used to illustrate these concepts. Wearable computers have established their first foothold in several application domains, such as vehicle and aircraft maintenance and manufacturing, inspection, language translation, and other areas. The lecture continues by describing the next step in the evolution of wearable computers, namely, context awareness. Context-aware computing takes into account a user's state and surroundings, and the mobile computer modifies its behavior based on this information. A user's context can be quite rich, consisting of attributes such as physical location, physiological state, personal history, daily behavioral patterns, and so forth. If a human assistant were given such context, he or she would make decisions in a proactive fashion, anticipating user needs, and acting as a proactive assistant. The goal is to enable mobile computers to play an analogous role, exploiting context inf

Question: What is the difference between a wearable computer and a mobile computer?


Novel compact spider microstrip antenna with new Defected Ground Structure. Two novel Defected Ground Structures (DGS) were first proposed, which have better results than that of the dumbbell (published shape). Using the general model of DGS, its equivalent parameters were extracted. The two new proposed shapes of DGS were then used to design a novel compact spider microstrip antenna to minimize its area. The size of the developed antenna was reduced to about 90.5% of that of the conventional one. This antenna with two different novel shapes of DGS was designed and simulated by using the ready-made software package Zeland-IE3D. Finally, it was fabricated by using thin film and photolithographic technique and measured by using vector network analyzer. Good agreements were found between the simulated and measured results.

Question: What is the size of the antenna?


Culture and Institutions. A growing body of empirical work measuring different types of cultural traits has shown that culture matters for a variety of economic outcomes. This paper focuses on one specific aspect of the relevance of culture: its relationship to institutions. We review work with a theoretical, empirical, and historical bent to assess the presence of a two-way causal effect between culture and institutions. 1 We thank Benjamin Friedman and Andrei Shleifer for useful conversations and Janet Currie, Steven Durlauf, and six anonymous referees for excellent comments.

Question: What is the relationship between culture and institutions?


A Polymer-Based Capacitive Sensing Array for Normal and Shear Force Measurement. In this work, we present the development of a polymer-based capacitive sensing array. The proposed device is capable of measuring normal and shear forces, and can be easily realized by using micromachining techniques and flexible printed circuit board (FPCB) technologies. The sensing array consists of a polydimethlysiloxane (PDMS) structure and a FPCB. Each shear sensing element comprises four capacitive sensing cells arranged in a 2 × 2 array, and each capacitive sensing cell has two sensing electrodes and a common floating electrode. The sensing electrodes as well as the metal interconnect for signal scanning are implemented on the FPCB, while the floating electrodes are patterned on the PDMS structure. This design can effectively reduce the complexity of the capacitive structures, and thus makes the device highly manufacturable. The characteristics of the devices with different dimensions were measured and discussed. A scanning circuit was also designed and implemented. The measured maximum sensitivity is 1.67%/mN. The minimum resolvable force is 26 mN measured by the scanning circuit. The capacitance distributions induced by normal and shear forces were also successfully captured by the sensing array.

Question: What is the minimum resolvable force?


From categories to subcategories: Large-scale image classification with partial class label refinement. The number of digital images is growing extremely rapidly, and so is the need for their classification. But, as more images of pre-defined categories become available, they also become more diverse and cover finer semantic differences. Ultimately, the categories themselves need to be divided into subcategories to account for that semantic refinement. Image classification in general has improved significantly over the last few years, but it still requires a massive amount of manually annotated data. Subdividing categories into subcategories multiples the number of labels, aggravating the annotation problem. Hence, we can expect the annotations to be refined only for a subset of the already labeled data, and exploit coarser labeled data to improve classification. In this work, we investigate how coarse category labels can be used to improve the classification of subcategories. To this end, we adopt the framework of Random Forests and propose a regularized objective function that takes into account relations between categories and subcategories. Compared to approaches that disregard the extra coarse labeled data, we achieve a relative improvement in subcategory classification accuracy of up to 22% in our large-scale image classification experiments.

Question: How to classify subcategories?


Erasure coded storage systems for cloud storage — challenges and opportunities. Erasure coded storage schemes offer a promising future for cloud storage. Highlights of erasure coded storage systems are that these offer the same level of fault tolerance as that of replication, at lower storage footprints. In the big data era, cloud storage systems based on data replication are of dubious usability due to 200% storage overhead in data replication systems. This has prompted storage service providers to use erasure coded storage as an alternative to replication. Refinements are required in various aspects of erasure coded storage systems to make it a real contender against data replication based storage systems. Streamlining huge bandwidth requirements during the recovery of failed nodes, inefficient update operations, effect of topology in recovery and consistency requirements of erasure coded storage systems, are some areas which need attention. This paper presents an in-depth study on the challenges faced, and research pursued in some of these areas. The survey shows that more research is required to improve erasure coded storage system from being bandwidth crunchers to efficient storage systems. Another challenge that has emerged from the study is the requirement of elaborate research for upgrading the erasure coded storage systems from being mere archival storage systems by providing better update methods. Provision of multiple level consistency in erasure coded storage is yet another research opportunity identified in this work. A brief introduction to open source libraries available for erasure coded storage is also presented in the paper.

Question: What is the difference between erasure coding and replication?


Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation. This paper presents a novel unsupervised domain adaptation framework, called Synergistic Image and Feature Adaptation (SIFA), to effectively tackle the problem of domain shift. Domain adaptation has become an important and hot topic in recent studies on deep learning, aiming to recover performance degradation when applying the neural networks to new testing domains. Our proposed SIFA is an elegant learning diagram which presents synergistic fusion of adaptations from both image and feature perspectives. In particular, we simultaneously transform the appearance of images across domains and enhance domain-invariance of the extracted features towards the segmentation task. The feature encoder layers are shared by both perspectives to grasp their mutual benefits during the end-to-end learning procedure. Without using any annotation from the target domain, the learning of our unified model is guided by adversarial losses, with multiple discriminators employed from various aspects. We have extensively validated our method with a challenging application of crossmodality medical image segmentation of cardiac structures. Experimental results demonstrate that our SIFA model recovers the degraded performance from 17.2% to 73.0%, and outperforms the state-of-the-art methods by a significant margin.

Question: What is the name of the paper?


Eliminative Materialism and the Propositional Attitudes. Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use.

Question: What is the difference between eliminative materialism and propositional attitudes?


Potassium Incorporation for Enhanced Performance and Stability of Fully Inorganic Cesium Lead Halide Perovskite Solar Cells.. Thermally unstable nature of hybrid organic-inorganic perovskites has been a major obstacle to fabricating the long-term operational device. A cesium lead halide perovskite has been suggested as an alternative light absorber, due to its superb thermal stability. However, the phase instability and poor performance are hindering the further progress. Here, cesium lead halide perovskite solar cells with enhanced performance and stability are demonstrated via incorporating potassium cations. Based on Cs0.925K0.075PbI2Br, the planar-architecture device achieves a power conversion efficiency of 10.0%, which is a remarkable record in the field of inorganic perovskite solar cells. In addition, the device shows an extended operational lifetime against air. Our research will stimulate the development of cesium lead halide perovskite materials for next-generation photovoltaics.

Question: What is the phase stability of hybrid organic-inorganic perovskites?


SemEval-2017 Task 7: Detection and Interpretation of English Puns. Apun is a form of wordplay in which aword suggests two or more meanings by exploiting polysemy, homonymy, or phonological similarity to another word, for an intended humorous or rhetorical effect. Though a recurrent and expected feature in many discourse types, puns stymie traditional approaches to computational lexical semantics because they violate their one-sense-percontext assumption. This paper describes the first competitive evaluation for the automatic detection, location, and interpretation of puns. We describe the motivation for these tasks, the evaluation methods, and the manually annotated data set. Finally, we present an overview and discussion of the participating systems' methodologies, resources, and results.

Question: What is the first competitive evaluation for the automatic detection, location, and interpretation of puns?


Zero moment point-measurements from a human walker wearing robot feet as shoes. The anthropomorphic biped robot Bip is equipped with sensors for measuring the ground/feet forces in order to localize the center of pressure (CoP) and zero moment point (ZMP). This paper focuses on experimental results regarding the evolution of the ground contact forces, obtained from a human walker wearing the robot feet as shoes. First, one determines the influence of heavy and rigid metallic shoes on the gait of the subject, during experiments carried out on flat ground. Second, the evolution of the contact forces is studied while walking on parallel planes with different elevations (stairs), then one addresses the case where the feet are supported by two nonparallel planes (uneven terrain). The corresponding analysis is founded on the concepts of virtual supporting surface and pseudo-CoP-ZMP introduced in a companion paper, discussing the theoretical aspects of CoP and ZMP (Sardain and Bessonnet, 2004). Beyond the academic contribution, the data analyzed in this paper could constitute an incitement to design truly anthropomorphic feet, for Bip as well as for other biped robots, because all the current robot feet are functionally rather poor.

Question: What is the influence of heavy and rigid metallic shoes on the gait of the subject?


Learning from examples to improve code completion systems. The suggestions made by current IDE's code completion features are based exclusively on static type system of the programming language. As a result, often proposals are made which are irrelevant for a particular working context. Also, these suggestions are ordered alphabetically rather than by their relevance in a particular context. In this paper, we present intelligent code completion systems that learn from existing code repositories. We have implemented three such systems, each using the information contained in repositories in a different way. We perform a large-scale quantitative evaluation of these systems, integrate the best performing one into Eclipse, and evaluate the latter also by a user study. Our experiments give evidence that intelligent code completion systems which learn from examples significantly outperform mainstream code completion systems in terms of the relevance of their suggestions and thus have the potential to enhance developers' productivity.

Question: What is the potential of intelligent code completion systems?


Persistent Point Feature Histograms for 3 D Point Clouds. This paper proposes a novel way of characterizing the local geometry of 3D points, using persistent feature histograms. The relationships between the neighbors of a point are analyzed and the resulted values are stored in a 16-bin histogram. The histograms are pose and point cloud density invariant and cope well with noisy datasets. We show that geometric primitives have unique signatures in this feature space, preserved even in the presence of additive noise. To extract a compact subset of points which characterizes a point cloud dataset, we perform an in-depth analysis of all point feature histograms using different distance metrics. Preliminary results show that point clouds can be roughly segmented based on the uniqueness of geometric primitives feature histograms. We validate our approach on datasets acquired from laser sensors in indoor (kitchen) environments.

Question: What is a persistent feature histogram?


The evolution to 4G cellular systems: LTE-Advanced. This paper provides an in-depth view on the technologies being considered for Long Term Evolution-Advanced (LTE-Advanced). First, the evolution from third generation (3G) to fourth generation (4G) is described in terms of performance requirements and main characteristics. The new network architecture developed by the Third Generation Partnership Project (3GPP), which supports the integration of current and future radio access technologies, is highlighted. Then, the main technologies for LTE-Advanced are explained, together with possible improvements, their associated challenges, and some approaches that have been considered to tackle those challenges.

Question: What is LTE-Advanced?


On Detecting Clustered Anomalies Using SCiForest. Detecting local clustered anomalies is an intricate problem for many existing anomaly detection methods. Distance-based and density-based methods are inherently restricted by their basic assumptions—anomalies are either far from normal points or being sparse. Clustered anomalies are able to avoid detection since they defy these assumptions by being dense and, in many cases, in close proximity to normal instances. In this paper, without using any density or distance measure, we propose a new method called SCiForest to detect clustered anomalies. SCiForest separates clustered anomalies from normal points effectively even when clustered anomalies are very close to normal points. It maintains the ability of existing methods to detect scattered anomalies, and it has superior time and space complexities against existing distance-based and density-based methods.

Question: How does SCiForest detect clustered anomalies?


FlowQA: Grasping Flow in History for Conversational Machine Comprehension. Conversational machine comprehension requires a deep understanding of the conversation history. To enable traditional, single-turn models to encode the history comprehensively, we introduce FLOW, a mechanism that can incorporate intermediate representations generated during the process of answering previous questions, through an alternating parallel processing structure. Compared to shallow approaches that concatenate previous questions/answers as input, FLOW integrates the latent semantics of the conversation history more deeply. Our model, FLOWQA, shows superior performance on two recently proposed conversational challenges (+7.2% F1 on CoQA and +4.0% on QuAC). The effectiveness of FLOW also shows in other tasks. By reducing sequential instruction understanding to conversational machine comprehension, FLOWQA outperforms the best models on all three domains in SCONE, with +1.8% to +4.4% improvement in accuracy.

Question: What is the best model for conversational machine comprehension?


Digital Media and Symptoms of Attention-Deficit/Hyperactivity Disorder in Adolescents.. In many regards, this trial represents the best of evidence-based quality improvement efforts—the improvement in health outcomes is often greater than what would have been expected from the individual components alone. An outcome of the trial by Wang et al is the proof that effective stroke interventions can be implemented in China where the burden of stroke is the highest in the world. Trials like this one leave a lasting legacy because the coaching and follow-up and the demonstration that data collection can lead to better outcomes with practice change will leave each of the intervention hospitals with a platform of good-quality stroke care and a mechanism to keep improving. Similar to the challenge of providing a novel drug to patients after a trial ends, a new dilemma that arises for the trialists is how to get the nonintervention hospitals up to the same level of care as the intervention hospitals. A major challenge is the sustainability of these kinds of interventions. Intensive quality improvement is just not practical for long periods; lower level embedded improvement needs to be built into the culture of a hospital, written into job descriptions, and identified as a deliverable in employment contracts to make continuous improvement possible and likely. In addition, the finer details of the intervention must be made available to others. A "teach the teacher" model may apply in distributing this kind of intervention widely. Overall, this randomized clinical trial by Wang et al has achieved its broad objective of both providing both stroke evidence and implanting practice change in 20 hospitals. The challenge now is to sustain that level of quality improvement at these hospitals, and expand this approach to other centers providing care for patients with acute stroke.

Question: What is the best way to improve the quality of care for stroke patients?


A topological hierarchy for functions on triangulated surfaces. We combine topological and geometric methods to construct a multiresolution representation for a function over a two-dimensional domain. In a preprocessing stage, we create the Morse-Smale complex of the function and progressively simplify its topology by cancelling pairs of critical points. Based on a simple notion of dependency among these cancellations, we construct a hierarchical data structure supporting traversal and reconstruction operations similarly to traditional geometry-based representations. We use this data structure to extract topologically valid approximations that satisfy error bounds provided at runtime.

Question: What is a topological hierarchy for functions on triangulated surfaces?


Role of self-care in management of diabetes mellitus. Diabetes mellitus (DM) is a chronic progressive metabolic disorder characterized by hyperglycemia mainly due to absolute (Type 1 DM) or relative (Type 2 DM) deficiency of insulin hormone. World Health Organization estimates that more than 346 million people worldwide have DM. This number is likely to more than double by 2030 without any intervention. The needs of diabetic patients are not only limited to adequate glycemic control but also correspond with preventing complications; disability limitation and rehabilitation. There are seven essential self-care behaviors in people with diabetes which predict good outcomes namely healthy eating, being physically active, monitoring of blood sugar, compliant with medications, good problem-solving skills, healthy coping skills and risk-reduction behaviors. All these seven behaviors have been found to be positively correlated with good glycemic control, reduction of complications and improvement in quality of life. Individuals with diabetes have been shown to make a dramatic impact on the progression and development of their disease by participating in their own care. Despite this fact, compliance or adherence to these activities has been found to be low, especially when looking at long-term changes. Though multiple demographic, socio-economic and social support factors can be considered as positive contributors in facilitating self-care activities in diabetic patients, role of clinicians in promoting self-care is vital and has to be emphasized. Realizing the multi-faceted nature of the problem, a systematic, multi-pronged and an integrated approach is required for promoting self-care practices among diabetic patients to avert any long-term complications.

Question: What is the role of clinicians in promoting self-care?


Autonomous semantic mapping for robots performing everyday manipulation tasks in kitchen environments. In this work we report about our efforts to equip service robots with the capability to acquire 3D semantic maps. The robot autonomously explores indoor environments through the calculation of next best view poses, from which it assembles point clouds containing spatial and registered visual information. We apply various segmentation methods in order to generate initial hypotheses for furniture drawers and doors. The acquisition of the final semantic map makes use of the robot's proprioceptive capabilities and is carried out through the robot's interaction with the environment. We evaluated the proposed integrated approach in the real kitchen in our laboratory by measuring the quality of the generated map in terms of the map's applicability for the task at hand (e.g. resolving counter candidates by our knowledge processing system).

Question: What is the quality of the generated map?


Zero-bias autoencoders and the benefits of co-adapting features. Regularized training of an autoencoder typically results in hidden unit biases that take on large negative values. We show that negative biases are a natural result of using a hidden layer whose responsibility is to both represent the input data and act as a selection mechanism that ensures sparsity of the representation. We then show that negative biases impede the learning of data distributions whose intrinsic dimensionality is high. We also propose a new activation function that decouples the two roles of the hidden layer and that allows us to learn representations on data with very high intrinsic dimensionality, where standard autoencoders typically fail. Since the decoupled activation function acts like an implicit regularizer, the model can be trained by minimizing the reconstruction error of training data, without requiring any additional regularization.

Question: What is the difference between a zero-bias autoencoder and a regularized autoencoder?


CommonSense: Collaborative learning of scene semantics by robots and humans. The recent introduction of robots to everyday scenarios has revealed new opportunities for collaboration and social interaction between robots and people. However, high level interaction will require semantic understanding of the environment. In this paper, we advocate that co-existence of assistive robots and humans can be leveraged to enhance the semantic understanding of the shared environment, and improve situation awareness. We propose a probabilistic framework that combines human activity sensor data generated by smart wearables with low level localisation data generated by robots. Based on this low level information and leveraging colocation events between a user and a robot, it can reason about semantic information and track humans and robots across different rooms. The proposed system relies on two-way sharing of information between the robot and the user. In the first phase, user activities indicative of room utility are inferred from consumer wearable devices and shared with the robot, enabling it to gradually build a semantic map of the environment. This will enable natural language interaction and high-level tasks for both assistive and co-working robots. In a second phase, via colocation events, the robot is able to share semantic information with the user, by labelling raw user data with semantic information about room type. Over time, the labelled data is used for training an Hidden Markov Model for room-level localisation, effectively making the user independent from the robot.

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


A wireless electrocardiogram detection for personal health monitoring. The current paper presents low-power analog integrated circuits (ICs) for wireless electrocardiogram (ECG) detection in personal health monitoring. Considering the power-efficient communication in the body sensor network (BSN), the required low-power analog ICs are developed for a healthcare system through miniaturization and system integration. The proposed system comprises the design and implementation with three subsystems, namely, (1) the ECG acquisition node, (2) the protocol for standard IEEE 802.15.4 ZigBee system, and (3) the radio frequency (RF) transmitter circuits. A preamplifier, a low-pass filter, and a successive-approximation analog-to-digital converter (SA-ADC) are integrated to detect an ECG signal. For high integration, the ZigBee protocol is adopted for wireless communication. To transmit the ECG signal through wireless communication, a quadrature voltage-controlled oscillator and a 2.4 GHz low-IF transmitter with a power amplifier and up-conversion mixer are also developed. In the receiver, a 2.4 GHz fully integrated CMOS radio-frequency front-end with a low-noise amplifier, and a quadrature mixer is proposed. The low-power wireless bio-signal acquisition SoC (WBSA-SoC) has been implemented in TSMC 0.18-μm standard CMOS process. The measurement results on the human body reveal that the ECG signals can be acquired effectively by the proposed SoC.

Question: What is the size of the canadian military?


Identifying Exoplanets with Deep Learning : A Five-planet Resonant Chain around Kepler-80 and an Eighth Planet around Kepler-90. NASA's Kepler Space Telescope was designed to determine the frequency of Earth-sized planets orbiting Sun-like stars, but these planets are on the very edge of the mission's detection sensitivity. Accurately determining the occurrence rate of these planets will require automatically and accurately assessing the likelihood that individual candidates are indeed planets, even at low signal-to-noise ratios. We present a method for classifying potential planet signals using deep learning, a class of machine learning algorithms that have recently become state-of-theart in a wide variety of tasks. We train a deep convolutional neural network to predict whether a given signal is a transiting exoplanet or a false positive caused by astrophysical or instrumental phenomena. Our model is highly effective at ranking individual candidates by the likelihood that they are indeed planets: 98.8% of the time it ranks plausible planet signals higher than false-positive signals in our test set. We apply our model to a new set of candidate signals that we identified in a search of known Kepler multi-planet systems. We statistically validate two new planets that are identified with high confidence by our model. One of these planets is part of a five-planet resonant chain around Kepler-80, with an orbital period closely matching the prediction by three-body Laplace relations. The other planet orbits Kepler-90, a star that was previously known to host seven transiting planets. Our discovery of an eighth planet brings Kepler-90 into a tie with our Sun as the star known to host the most planets.

Question: What is the probability of a false positive?


Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach. Unsupervised domain adaptation (uDA) models focus on pairwise adaptation settings where there is a single, labeled, source and a single target domain. However, in many real-world settings one seeks to adapt to multiple, but somewhat similar, target domains. Applying pairwise adaptation approaches to this setting may be suboptimal, as they fail to leverage shared information among multiple domains. In this work we propose an information theoretic approach for domain adaptation in the novel context of multiple target domains with unlabeled instances and one source domain with labeled instances. Our model aims to find a shared latent space common to all domains, while simultaneously accounting for the remaining private, domainspecific factors. Disentanglement of shared and private information is accomplished using a unified information-theoretic approach, which also serves to establish a stronger link between the latent representations and the observed data. The resulting model, accompanied by an efficient optimization algorithm, allows simultaneous adaptation from a single source to multiple target domains. We test our approach on three challenging publicly-available datasets, showing that it outperforms several popular domain adaptation methods.

Question: How does unsupervised multi-target domain adaptation work?


Information Extraction Supported Question Answering. This paper discusses the use of our information extraction (IE) system, Textract, in the questionanswering (QA) track of the recently held TREC-8 tests. One of our major objectives is to examine how IE can help IR (Information Retrieval) in applications like QA. Our study shows: (i) IE can provide solid support for QA; (ii ) low-level IE like Named Entity tagging is often a necessary component in handling most types of questions; (iii ) a robust natural language shallow parser provides a structural basis for handling questions; (iv) high-level domain independent IE, i.e. extraction of multiple relationships and general events, is expected to bring about a breakthrough in QA.

Question: What is the name of the information extraction system?


Induction of pluripotent stem cells from fibroblast cultures. Clinical application of embryonic stem (ES) cells faces difficulties regarding use of embryos, as well as tissue rejection after implantation. One way to circumvent these issues is to generate pluripotent stem cells directly from somatic cells. Somatic cells can be reprogrammed to an embryonic-like state by the injection of a nucleus into an enucleated oocyte or by fusion with ES cells. However, little is known about the mechanisms underlying these processes. We have recently shown that the combination of four transcription factors can generate ES-like pluripotent stem cells directly from mouse fibroblast cultures. The cells, named induced pluripotent stem (iPS) cells, can be differentiated into three germ layers and committed to chimeric mice. Here we describe detailed methods and tips for the generation of iPS cells.

Question: How to generate iPS cells?


A systematic analysis of performance measures for classification tasks. Article history: Received 14 February 2008 Received in revised form 21 November 2008 Accepted 6 March 2009 Available online 8 May 2009

Question: What is the history of the article?


Knowing Yourself: Improving Video Caption via In-depth Recap. Generating natural language descriptions for videos (a.k.a video captioning) has attracted much research attention in recent years, and a lot of models have been proposed to improve the caption performance. However, due to the rapid progress in dataset expansion and feature representation, newly proposed caption models have been evaluated on different settings, which makes it unclear about the contributions from either features or models. Therefore, in this work we aim to gain a deep understanding about "where are we" for the current development of video captioning. First, we carry out extensive experiments to identify the contribution from different components in video captioning task and make fair comparison among several state-of-the-art video caption models. Second, we discover that these state-of-the-art models are complementary so that we could benefit from "wisdom of the crowd" through ensembling and reranking. Finally, we give a preliminary answer to the question "how far are we from the human-level performance in general'' via a series of carefully designed experiments. In summary, our caption models achieve the state-of-the-art performance on the MSR-VTT 2017 challenge, and it is comparable with the average human-level performance on current caption metrics. However, our analysis also shows that we still have a long way to go, such as further improving the generalization ability of current caption models.

Question: What is the state-of-the-art performance on the MSR-VTT 2017 challenge?


Finite Automata and Their Decision Problems. Finite automata are considered in this paper a s instruments for classifying finite tapes. Each onetape automaton defines a set of tapes, a two-tape automaton defines a set of pairs of tapes, et cetera. The structure of the defined sets is studied. Various generalizations of the notion of an automaton are introduced and their relation to the classical automata is determined. Some decision problems concerning automata are shown to be solvable by effective algorithms; others turn out to be unsolvable by algorithms.

Question: What is a finite automata?


Engineering for Predictive Modeling using Reinforcement Learning. Feature engineering is a crucial step in the process of predictive modeling. It involves the transformation of given feature space, typically using mathematical functions, with the objective of reducing the modeling error for a given target. However, there is no well-defined basis for performing effective feature engineering. It involves domain knowledge, intuition, and most of all, a lengthy process of trial and error. The human attention involved in overseeing this process significantly influences the cost of model generation. We present a new framework to automate feature engineering. It is based on performance driven exploration of a transformation graph, which systematically and compactly enumerates the space of given options. A highly efficient exploration strategy is derived through reinforcement learning on past examples.

Question: What is a transformation graph?


A Survey of Definitions and Models of Exploratory Search. Exploratory search has an unclear and open-ended definition. The complexity of the task and the difficulty of defining this activity are reflected in the limits of existing evaluation methods for exploratory search systems. In order to improve them, we intend to design an evaluation method based on a user-centered model of exploratory search. In this work, we identified and defined the characteristics of exploratory search and used them as an information seeking model evaluation grid. We tested this analytic grid on two information seeking models: Ellis' and Marchionini's models. The results show that Marchonini's model does not match our evaluation method's requirements whereas on the other hand Ellis' model could be adapted to better suit exploratory search.

Question: What is the difference between exploratory search and information seeking?


Learning partial differential equations via data discovery and sparse optimization.. We investigate the problem of learning an evolution equation directly from some given data. This work develops a learning algorithm to identify the terms in the underlying partial differential equations and to approximate the coefficients of the terms only using data. The algorithm uses sparse optimization in order to perform feature selection and parameter estimation. The features are data driven in the sense that they are constructed using nonlinear algebraic equations on the spatial derivatives of the data. Several numerical experiments show the proposed method's robustness to data noise and size, its ability to capture the true features of the data, and its capability of performing additional analytics. Examples include shock equations, pattern formation, fluid flow and turbulence, and oscillatory convection.

Question: What is the difference between a partial differential equation and a differential equation?


A variable splitting augmented Lagrangian approach to linear spectral unmixing. This paper presents a new linear hyperspectral unmixing method of the minimum volume class, termed simplex identification via split augmented Lagrangian (SISAL). Following Craig's seminal ideas, hyperspectral linear unmixing amounts to finding the minimum volume simplex containing the hyperspectral vectors. This is a nonconvex optimization problem with convex constraints. In the proposed approach, the positivity constraints, forcing the spectral vectors to belong to the convex hull of the endmember signatures, are replaced by soft constraints. The obtained problem is solved by a sequence of augmented Lagrangian optimizations. The resulting algorithm is very fast and able so solve problems far beyond the reach of the current state-of-the art algorithms. The effectiveness of SISAL is illustrated with simulated data.

Question: What is the minimum volume simplex?


Valuation of IT Investments Using Real Options Theory. Real Options Theory is often applied to the valuation of IT investments. The application of Real Options Theory is generally accompanied by a monetary valuation of real options through option pricing models which in turn are based on restrictive assumptions and thus subject to criticism. Therefore, this paper analyzes the application of option pricing models for the valuation of IT investments. A structured literature review reveals the types of IT investments which are valuated with Real Options Theory in scientific literature. These types of IT investments are further investigated and their main characteristics are compared to the restrictive assumptions of traditional option pricing models. This analysis serves as a basis for further discussion on how the identified papers address these assumptions. The results show that a lot of papers do not account for critical assumptions, although it is known that the assumptions are not fulfilled. Moreover, the type of IT investment determines the criticality of the assumptions. Additionally, several extensions or adaptions of traditional option pricing models can be found which provide the possibility of relaxing critical assumptions. Researchers can profit from the results derived in this paper in two ways: First, which assumptions can be critical for various types of IT investments are demonstrated. Second, extensions of option pricing models that relax critical assumptions are introduced.

Question: What is the difference between real options and option pricing models?


Wave-front Transformation with Gradient Metasurfaces. Relying on abrupt phase discontinuities, metasurfaces characterized by a transversely inhomogeneous surface impedance profile have been recently explored as an ultrathin platform to generate arbitrary wave fronts over subwavelength thicknesses. Here, we outline fundamental limitations of passive gradient metasurfaces in molding the impinging wave and show that local phase compensation is essentially insufficient to realize arbitrary wave manipulation, but full-wave designs should be considered. These findings represent a critical step towards realistic and highly efficient conformal wave manipulation beyond the scope of ray optics, enabling unprecedented nanoscale light molding.

Question: How can we manipulate the wavefront of light?


Employing Aesthetic Principles for Automatic Photo Book Layout. Photos are a common way of preserving our personal memories. The visual souvenir of a personal event is often composed into a photo collage or the pages of a photo album. Today we find many tools to help users creating such compositions by different tools for authoring photo compositions. Some template-based approaches generate nice presentations, however, come mostly with limited design variations. Creating complex and fancy designs for, e.g., a personal photo book, still demands design and composition skills to achieve results that are really pleasing to the eye – skills which many users simply lack. Professional designers instead would follow general design principles such as spatial layout rules, symmetry, balance among the element as well color schemes and harmony. In this paper, we propose an approach to deliver principles of design and composition to the end user by embedding it into an automatic composition application. We identify and analyze common design and composition principles and transfer these to the automatic creation of pleasant photo compositions by employing genetic algorithms. In contrast to other approaches, we strictly base our design system on common design principles, consider additional media types besides text in the photo book and specifically take the content of photos into account. Our approach is both implemented in a web-based rich media application and a tool for the automatic transformation from blogs into photo books.

Question: What is a photo book?


The Measurement of Web-Customer Satisfaction: An Expectation and Disconfirmation Approach.

Question: What is the measurement of web-customer satisfaction?


Dynamic Programming and Optimal Control. This is an updated version of Chapter 4 of the author's Dynamic Programming and Optimal Control, Vol. II, 4th Edition, Athena Scientific, 2012. It includes new material, and it is substantially revised and expanded (it has more than doubled in size). The new material aims to provide a unified treatment of several models, all of which lack the contractive structure that is characteristic of the discounted problems of Chapters 1 and 2: positive and negative cost models, deterministic optimal control (including adaptive DP), stochastic shortest path models, and risk-sensitive models. Here is a summary of the new material:

Question: What is the new material?


A Compact Dual-Polarized Printed Dipole Antenna With High Isolation for Wideband Base Station Applications. A compact dual-polarized printed dipole antenna for wideband base station applications is presented in this communication. The proposed dipole antenna is etched on three assembled substrates. Four horizontal triangular patches are introduced to form two dipoles in two orthogonal polarizations. Two integrated baluns connected with 50 Ω SMA launchers are used to excite the dipole antenna. The proposed dipole antenna achieves a more compact size than many reported wideband printed dipole and magneto-electric dipole antennas. Both simulated and measured results show that the proposed antenna has a port isolation higher than 35 dB over 52% impendence bandwidth (VSWR <; 1.5). Moreover, stable radiation pattern with a peak gain of 7 dBi - 8.6 dBi is obtained within the operating band. The proposed dipole antenna is suitable as an array element and can be used for wideband base station antennas in the next generation IMT-advanced communications.

Question: What is a compact dual-polarized printed dipole antenna?


Dielectric properties estimation of normal and malignant skin tissues at millimeter-wave frequencies using effective medium theory. Millimeter-wave reflectometry can be used as a non-invasive method for early detection of skin cancers. Less penetration and higher resolution are only some reasons to use mm-waves for skin cancer diagnosis. The dielectric parameters data of human skin at mm-wave frequencies are not widely addressed in the literature due to the expensive instruments and the complicated structure of human skin. Available dielectric properties of cancerous tissues in the literature are for other tissues rather than skin and are restricted to the frequencies below 20 GHz. In this paper, dielectric properties of healthy and malignant skin tissues were estimated in the range of 20-100 GHz by applying the effective medium theory. A stratified skin model and some skin tumors were presented. The possibility of mm-wave reflectometry for detection of skin cancers has also been studied. The results of this paper can be used as a theoretical basis for taking further steps in skin cancer research.

Question: What is the difference between normal and malignant skin tissues?


FLEXIBLE GENERATION OF SEMANTIC 3 D BUILDING MODELS. The paper presents a new 3D semantic building model dedicated to urban development. It provides the following special semantic features: storeys, passages, opening objects, and building variants, modelling different levels of detail and design respectively temporal variants. The model also includes a parametric part supporting easy generation of buildings and building variants in the urban design phase. In order to make the powerful tools of the CA(A)D world accessible to city modeling, a toolbox is being developed for transformation of IFC data. These extensions and addition facilitate multiple utilization of city models and thus enhance sustainability of modeling.

Question: What is a semantic building model?


Hand Gesture Recognition using Sign Language. Sign Language is mostly used by deaf and dumb people. In order to improve the man machine interaction, sign language can be used as a way for communicating with machines. Most of the applications which enable sign language processing are using data gloves and other devices for interacting with computers. This restricts the freedom of users. So to avoid this, this system we capture live video stream through normal webcam and pass it as input and process this video to detect human gestures . These gestures can be signs represented in any sign language like American Sign Language (ASL), Indian Sign Language(ISL) etc. By processing these signs, this system can make an efficient system for searching using signs. In future this method of searching can be implemented in many areas such as railway station for searching the details of any trains, etc. Searching uses signs can play a major role in searching technique because the latest existing technique of searching is based on voice. But this may not work properly because each person has a different pronunciation. This system can overcome the drawbacks of the current available searching technique and thus can make every person under an umbrella of searching.

Question: How to detect hand gestures using sign language?


Differential privacy for location pattern mining. One main concern for individuals to participate in the data collection of personal location history records is the disclosure of their location and related information when a user queries for statistical or pattern mining results derived from these records. In this paper, we investigate how the privacy goal that the inclusion of one's location history in a statistical database with location pattern mining capabilities does not substantially increase one's privacy risk. In particular, we propose a differentially private pattern mining algorithm for interesting geographic location discovery using a region quadtree spatial decomposition to preprocess the location points followed by applying a density-based clustering algorithm. A differentially private region quadtree is used for both de-noising the spatial domain and identifying the likely geographic regions containing the interesting locations. Then, a differential privacy mechanism is applied to the algorithm outputs, namely: the interesting regions and their corresponding stay point counts. The quadtree spatial decomposition enables one to obtain a localized reduced sensitivity to achieve the differential privacy goal and accurate outputs. Experimental results on synthetic datasets are used to show the feasibility of the proposed privacy preserving location pattern mining algorithm.

Question: What is a differentially private pattern mining algorithm?


Fast Road Sign Detection Using Hough Transform for Assisted Driving of Road Vehicles. A system for real-time traffic sign detection is described in this paper. The system uses restricted Hough transform for circumferences in order to detect circular signs, and for straight lines for triangular ones. Some results obtained from a set of real road images captured under both normal and adverse weather conditions are presented as well in order to illustrate the robustness of the detection system. The average processing time is 30 ms per frame, what makes the system a good approach to work in real time conditions.

Question: What is the average processing time per frame?


The art of UHF RFID antenna design: impedance-matching and size-reduction techniques. Radio-frequency identification technology, based on the reader/tag paradigm, is quickly permeating several aspects of everyday life. The electromagnetic research mainly concerns the design of tag antennas having high efficiency and small size, and suited to complex impedance matching to the embedded electronics. Starting from the available but fragmented open literature, this paper presents a homogeneous survey of relevant methodologies for the design of UHF passive tag antennas. Particular care is taken to illustrate, within a common framework, the basic concepts of the most-used design layouts. The design techniques are illustrated by means of many noncommercial examples.

Question: What is the size of the canadian military?


A case study of user participation in the information systems development process. There are many in the information systems discipline who believe that user participation is necessary for successful systems development. However, it has been suggested that this belief is neither grounded in theory nor substantiated by research data. This may indicate that researchers have not addressed fully the underlying complexity of the concept. If so, this is indicative of a deficiency in understanding user participation in information systems development as it occurs in organizations. In order to enhance the extant understanding of participative information systems development, the present study adopts a qualitative, case-based approach to research so as to provide an in-depth description of the complex social nature of the phenomenon as manifested in one organization. The results of the study illustrate that a high degree of direct and indirect user participation did not guarantee the successful implementation and use of information systems in the organization studied. Such participatory development practices did, however, result in the development of systems that adequately captured user requirements and hence satisfied user informational needs. It was clear that despite the perceived negative impact, which the new systems would have on user work-related roles and activities, the existence of an organization-wide participative policy, and associated participative structures, coupled with a favorable organization culture, generated a participatory development climate that was conducive to the successful development of information systems, while not guaranteeing it. That said, the central conclusion of this study was that user dissatisfaction with developed systems centered on the poor management of change in the organization.

Question: What is the difference between user participation and user satisfaction?


Advanced algorithms for neural networks: a C++ sourcebook.

Question: What is a neural network?