Combination therapy : Synergism between natural plant extracts and antibiotics against infectious diseases. Antibiotics are one of the most important weapons in fighting bacterial infections and have greatly benefited the health‐related quality of human life since their introduction. However, over the past few decades these health benefits are under threat as many commonly used antibiotics have become less and less effective against certain illnesses not only because many of them produce toxic reactions but also due to emergence of drug resistant bacteria. Resistance development is an even bigger problem since the bacterial resistance is often not restricted to the specific antibiotic prescribed, but generally extends to other compounds of the same class. Bacterial resistance and its rapid increase is a major concern of global public health and is emerging as one of the most significant challenges to human health. Treating bacterial infections by antibiotics is beneficial but their indiscriminate use has led to an alarming resistance among microorganisms as well as led to re-emergence of old infectious diseases. One approach to treat infectious diseases is the use of plant extracts individually and /or as an alternative approach is the use of combination of antibiotics with plant extracts. This latter approach i.e. combination therapy or synergistic therapy; against resistant microorganisms may lead to new ways of treating infectious diseases and probably this represents a potential area for further future investigations. Combination therapy is helpful and useful for patients with serious infections caused by drug resistant pathogens. The present review describes in detail, the observed synergy between natural extracts and standard antibiotics combating bacterial and fungal infections. The mode of action of combination therapy significantly differs from that of the same drugs acting individually; therefore the selection of an appropriate combination is crucial and e

Question: What is the difference between combination therapy and synergistic therapy?


Labor Costs and Foreign Direct Investment : A Panel VAR Approach. This paper examines the endogenous interaction between labor costs and Foreign Direct Investment (FDI) in the OECD countries via the Panel VAR approach under system GMM estimates for the period 1995–2009. The available data allows identifying the relevance of the components of labor costs, and allows a detailed analysis across different sectors. Empirical findings have revealed that sectoral composition of FDI and the decomposition of labor costs play a significant role in investigating the dynamic association between labor costs and FDI. Further, results suggest that labor market policies should focus on productivity-enhancing tools in addition to price hindering tools.

Question: What is the relationship between labor costs and foreign direct investment?


Dependency-Based Open Information Extraction. Building shallow semantic representations from text corpora is the first step to perform more complex tasks such as text entailment, enrichment of knowledge bases, or question answering. Open Information Extraction (OIE) is a recent unsupervised strategy to extract billions of basic assertions from massive corpora, which can be considered as being a shallow semantic representation of those corpora. In this paper, we propose a new multilingual OIE system based on robust and fast rule-based dependency parsing. It permits to extract more precise assertions (verb-based triples) from text than state of the art OIE systems, keeping a crucial property of those systems: scaling to Web-size document collections.

Question: What is a dependency-based open information extraction?


Automatic Stance Detection Using End-to-End Memory Networks. We present an effective end-to-end memory network model that jointly (i) predicts whether a given document can be considered as relevant evidence for a given claim, and (ii) extracts snippets of evidence that can be used to reason about the factuality of the target claim. Our model combines the advantages of convolutional and recurrent neural networks as part of a memory network. We further introduce a similarity matrix at the inference level of the memory network in order to extract snippets of evidence for input claims more accurately. Our experiments on a public benchmark dataset, FakeNewsChallenge, demonstrate the effectiveness of our approach.

Question: How does the memory network work?


Inverted 'V--Y' advancement medial epicanthoplasty.. The presence of an epicanthal fold is a distinctive anatomic feature of the Asian population. Epicanthoplasty can be very helpful in resolving the above problematic anatomy and may produce a more aesthetic appearance. The goal of this report is to describe a modification in the traditional operative methods related to medial epicanthoplasty, to minimise scar appearance and maximise normal appearance. An inverse triangular flap of skin is based on the semilunar skin, which is elevated and retracted within the line of the normal eyelid. The design of four key points is crucial to this epicanthoplasty. A total of 62 patients were performed with this method; 42 of this group underwent simultaneous double-eyelid plasty. Most of the patients obtained satisfactory results aesthetically followed from 6 months to 4 years postoperation. There was no recurrence of the epicanthal fold. As many as 38 patients were followed by interview and photographs were taken at the same time. The rest of the patients were followed up through telephone. No patients complained about visible scarring in the epicanthal area. As many as 60 patients obtained satisfactory results aesthetically, two patients complained about the median canthal asymmetry. The result indicates the reliability and feasibility of epicanthoplasty.

Question: How to perform epicanthoplasty?


Fast Training of Convolutional Networks through FFTs. Convolutional networks are one of the most widely employed architectures in computer vision and machine learning. In order to leverage their ability to learn complex functions, large amounts of data are required for training. Training a large convolutional network to produce state-of-the-art results can take weeks, even when using modern GPUs. Producing labels using a trained network can also be costly when dealing with web-scale datasets. In this work, we present a simple algorithm which accelerates training and inference by a significant factor, and can yield improvements of over an order of magnitude compared to existing state-of-the-art implementations. This is done by computing convolutions as pointwise products in the Fourier domain while reusing the same transformed feature map many times. The algorithm is implemented on a GPU architecture and addresses a number of related challenges.

Question: How to accelerate training of convolutional networks?


Next generation data systems and knowledge products to support agricultural producers and science-based policy decision making. Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions. This paper presents a framework for the use of farm-level and landscape-scale models and data to provide analysis that could be used in NextGen knowledge products, such as mobile applications or personal computer data analysis and visualization software. We describe two analytical tools - AgBiz Logic and TOA-MD - that demonstrate the current capability of farmlevel and landscape-scale models. The use of these tools is explored with a case study of an oilseed crop, Camelina sativa, which could be used to produce jet aviation fuel. We conclude with a discussion of innovations needed to facilitate the use of farm and policy-level models to generate data and analysis for improved knowledge products.

Question: What is the canadian military?


ICDAR2017 Competition on Handwritten Text Recognition on the READ Dataset. This paper describes the fourth edition of the Handwritten Text Recognition (HTR) competition that was prepared this time in the context of the International Conference on Document Analysis and Recognition (ICDAR) 2017. Previous editions of this competition were conducted, first, with datasets from the tranScriptorium project in ICFHR 2014, and ICDAR 2015, and then, with datasets from the "Recognition and Enrichment of Archival Documents (READ)" European project in ICFHR 2016. This competition aims to bring together researchers working on off-line HTR and provides them a suitable benchmark to compare their techniques on the task of transcribing typical and difficult historical handwritten documents. The competition proposed for ICDAR 2017 aims at introducing a usual scenario for some collections in which there exist transcripts at page level for many pages useful for training, but these transcripts are not aligned with line images. Two tracks with different conditions on the use of training data were proposed. Most of the data comes from the Alfred Escher Letter Collection. But handwritten images were drawn from other German collections written by several hands.

Question: What is the ICDAR2017 competition?


Predicting Stock Price Direction using Support Vector Machines. Support Vector Machine is a machine learning technique used in recent studies to forecast stock prices. This study uses daily closing prices for 34 technology stocks to calculate price volatility and momentum for individual stocks and for the overall sector. These are used as parameters to the SVM model. The model attempts to predict whether a stock price sometime in the future will be higher or lower than it is on a given day. We find little predictive ability in the short-run but definite predictive ability in the long-run.

Question: What is a support vector machine?


Parenting stress in mothers and fathers of toddlers with autism spectrum disorders: associations with child characteristics.. Elevated parenting stress is observed among mothers of older children with autism spectrum disorders (ASD), but little is known about parents of young newly-diagnosed children. Associations between child behavior and parenting stress were examined in mothers and fathers of 54 toddlers with ASD (mean age = 26.9 months). Parents reported elevated parenting stress. Deficits/delays in children's social relatedness were associated with overall parenting stress, parent-child relationship problems, and distress for mothers and fathers. Regulatory problems were associated with maternal stress, whereas externalizing behaviors were associated with paternal stress. Cognitive functioning, communication deficits, and atypical behaviors were not uniquely associated with parenting stress. Clinical assessment of parental stress, acknowledging differences in parenting experiences for mothers and fathers of young children with ASD, is needed.

Question: What is the difference between parenting stress in mothers and fathers of toddlers with autism spectrum disorders?


Violent Scenes Detection Using Mid-Level Violence Clustering. This work proposes a novel system for Violent Scenes Detection, which is based on the combination of visual and audio features with machine learning at segment-level. Multiple Kernel Learning is applied so that multimodality of videos can be maximized. In particular, Mid-level Violence Clustering is proposed in order for mid-level concepts to be implicitly learned, without using manually tagged annotations. Finally a violence-score for each shot is calculated. The whole system is trained ona dataset from MediaEval 2013 Affect Task and evaluated by its official metric. The obtained results outperformed its best score.

Question: How to detect violent scenes in videos?


Hand sign language recognition for Bangla alphabet using Support Vector Machine. The sign language considered as the main language for deaf and dumb people. So, a translator is needed when a normal person wants to talk with a deaf or dumb person. In this paper, we present a framework for recognizing Bangla Sign Language (BSL) using Support Vector Machine. The Bangla hand sign alphabets for both vowels and consonants have been used to train and test the recognition system. Bangla sign alphabets are recognized by analyzing its shape and comparing its features that differentiates each sign. In proposed system, hand signs are first converted to HSV color space from RGB image. Then Gabor filters are used to acquire desired hand sign features. Since feature vector obtained using Gabor filter is in a high dimension, to reduce the dimensionality a nonlinear dimensionality reduction technique that is Kernel PCA has been used. Lastly, Support Vector Machine (SVM) is employed for classification of candidate features. The experimental results show that our proposed method outperforms the existing work on Bengali hand sign recognition.

Question: How to recognize hand sign language using Support Vector Machine?


Detection of SQL injection and XSS attacks in three tier web applications. Web applications are used on a large scale worldwide, which handles sensitive personal data of users. With web application that maintains data ranging from as simple as telephone number to as important as bank account information, security is a prime point of concern. With hackers aimed to breakthrough this security using various attacks, we are focusing on SQL injection attacks and XSS attacks. SQL injection attack is very common attack that manipulates the data passing through web application to the database servers through web servers in such a way that it alters or reveals database contents. While Cross Site Scripting (XSS) attacks focuses more on view of the web application and tries to trick users that leads to security breach. We are considering three tier web applications with static and dynamic behavior, for security. Static and dynamic mapping model is created to detect anomalies in the class of SQL Injection and XSS attacks.

Question: What is SQL injection?


Algorithms for Unevenly Spaced Time Series : Moving Averages and Other Rolling Operators. This paper describes algorithms for efficiently calculating certain rolling time series operators for unevenly spaced data. In particular, we show how to calculate simple moving averages (SMAs), exponential moving averages (EMAs), and related operators in linear time with respect to the number of observations in a time series. A web appendix provides an implementation of these algorithms in the programming language C and a package (forthcoming) for the statistical software R.

Question: How to calculate moving averages for unevenly spaced data?


Innocent by association: early recognition of legitimate users. This paper presents the design and implementation of Souche, a system that recognizes legitimate users early in online services. This early recognition contributes to both usability and security. Souche leverages social connections established over time. Legitimate users help identify other legitimate users through an implicit vouching process, strategically controlled within vouching trees. Souche is lightweight and fully transparent to users. In our evaluation on a real dataset of several hundred million users, Souche can efficiently identify 85% of legitimate users early, while reducing the percentage of falsely admitted malicious users from 44% to 2.4%. Our evaluation further indicates that Souche is robust in the presence of compromised accounts. It is generally applicable to enhance usability and security for a wide class of online services.

Question: How can we identify legitimate users early?


CVSS Attack Graphs. Attack models and attack graphs are efficient tools to describe and analyse attack scenarios aimed at computer networks. More precisely, attack graphs give all possible scenarios for an attacker to reach a certain goal, exploiting vulnerabilities of the targeted network. Nevertheless they give no information about the damages induced by these attacks, nor about the probability of exploitation of these scenarios. In this paper, we propose to combine attack graphs and CVSS framework, in order to add damage and exploitability probability information. Then, we define a notion of risk for each attack scenario, which is based on quantitative information added to attack graphs.

Question: What is the CVSS attack graph?


The evolutionary impact of invasive species.. Since the Age of Exploration began, there has been a drastic breaching of biogeographic barriers that previously had isolated the continental biotas for millions of years. We explore the nature of these recent biotic exchanges and their consequences on evolutionary processes. The direct evidence of evolutionary consequences of the biotic rearrangements is of variable quality, but the results of trajectories are becoming clear as the number of studies increases. There are examples of invasive species altering the evolutionary pathway of native species by competitive exclusion, niche displacement, hybridization, introgression, predation, and ultimately extinction. Invaders themselves evolve in response to their interactions with natives, as well as in response to the new abiotic environment. Flexibility in behavior, and mutualistic interactions, can aid in the success of invaders in their new environment.

Question: What are the evolutionary consequences of invasive species?


Interactive Visual Exploration of a Large Spatio-temporal Dataset: Reflections on a Geovisualization Mashup.. Exploratory visual analysis is useful for the preliminary investigation of large structured, multifaceted spatio-temporal datasets. This process requires the selection and aggregation of records by time, space and attribute, the ability to transform data and the flexibility to apply appropriate visual encodings and interactions. We propose an approach inspired by geographical 'mashups' in which freely-available functionality and data are loosely but flexibly combined using de facto exchange standards. Our case study combines MySQL, PHP and the LandSerf GIS to allow Google Earth to be used for visual synthesis and interaction with encodings described in KML. This approach is applied to the exploration of a log of 1.42 million requests made of a mobile directory service. Novel combinations of interaction and visual encoding are developed including spatial 'tag clouds', 'tag maps', 'data dials' and multi-scale density surfaces. Four aspects of the approach are informally evaluated: the visual encodings employed, their success in the visual exploration of the dataset, the specific tools used and the 'mashup' approach. Preliminary findings will be beneficial to others considering using mashups for visualization. The specific techniques developed may be more widely applied to offer insights into the structure of multifarious spatio-temporal data of the type explored here.

Question: What is a mashup?


The adoption of hyped technologies: a qualitative study. The introduction of new consumer technology is often greeted with declarations that the way people conduct their lives will be changed instantly. In some cases, this might create hype surrounding a specific technology. This article investigates the adoption of hyped technology, a special case that is absent in the adoption literature. The study employs a consumer research perspective, specifically the theory of consumption values (TCV), to understand the underlying motives for adopting the technology. In its original form, TCV entails five values that influence consumer behavior: functional, social, epistemic, emotional and conditional. The values catch the intrinsic and extrinsic motives influencing behavior. Using a qualitative approach that includes three focus groups and 60 one-on-one interviews, the results of the study show that emotional, epistemic and social values influence the adoption of hyped technologies. Contrary to expectations, functional value, which is similar to the widely used information system constructs of perceived usefulness and relative advantage, has little impact on the adoption of technologies that are surrounded with significant hype. Using the findings of the study, this article proposes a model for investigating and understanding the adoption of hyped technologies. This article contributes to the literature by (1) focusing on the phenomenon of hyped technology, (2) introducing TCV, a consumer research-based theoretical framework, to enhance the understanding of technology adoption, and (3) proposing a parsimonious model explaining the adoption of hyped technology.

Question: What is the difference between hyped and normal technologies?


Perceptual Generative Adversarial Networks for Small Object Detection. Detecting small objects is notoriously challenging due to their low resolution and noisy representation. Existing object detection pipelines usually detect small objects through learning representations of all the objects at multiple scales. However, the performance gain of such ad hoc architectures is usually limited to pay off the computational cost. In this work, we address the small object detection problem by developing a single architecture that internally lifts representations of small objects to super-resolved ones, achieving similar characteristics as large objects and thus more discriminative for detection. For this purpose, we propose a new Perceptual Generative Adversarial Network (Perceptual GAN) model that improves small object detection through narrowing representation difference of small objects from the large ones. Specifically, its generator learns to transfer perceived poor representations of the small objects to super-resolved ones that are similar enough to real large objects to fool a competing discriminator. Meanwhile its discriminator competes with the generator to identify the generated representation and imposes an additional perceptual requirement - generated representations of small objects must be beneficial for detection purpose - on the generator. Extensive evaluations on the challenging Tsinghua-Tencent 100K [45] and the Caltech [9] benchmark well demonstrate the superiority of Perceptual GAN in detecting small objects, including traffic signs and pedestrians, over well-established state-of-the-arts.

Question: What is the smallest object that can be detected?


Neural personalized response generation as domain adaptation. One of the most crucial problem on training personalized response generation models for conversational robots is the lack of large scale personal conversation data. To address the problem, we propose a two-phase approach, namely initialization then adaptation, to first pre-train an optimized RNN encoder-decoder model (LTS model) in a large scale conversational data for general response generation and then fine-tune the model in a small scale personal conversation data to generate personalized responses. For evaluation, we propose a novel human aided method, which can be seen as a quasi-Turing test, to evaluate the performance of the personalized response generation models. Experimental results show that the proposed personalized response generation model outperforms the state-of-the-art approaches to language model personalization and persona-based neural conversation generation on the automatic evaluation, offline human judgment and the quasi-Turing test.

Question: How to generate personalized responses for conversational robots?


Human error analysis of commercial aviation accidents: application of the Human Factors Analysis and Classification system (HFACS).. BACKGROUND The Human Factors Analysis and Classification System (HFACS) is a general human error framework originally developed and tested within the U.S. military as a tool for investigating and analyzing the human causes of aviation accidents. Based on Reason's (1990) model of latent and active failures, HFACS addresses human error at all levels of the system, including the condition of aircrew and organizational factors. The purpose of the present study was to assess the utility of the HFACS framework as an error analysis and classification tool outside the military.   METHODS The HFACS framework was used to analyze human error data associated with aircrew-related commercial aviation accidents that occurred between January 1990 and December 1996 using database records maintained by the NTSB and the FAA.   RESULTS Investigators were able to reliably accommodate all the human causal factors associated with the commercial aviation accidents examined in this study using the HFACS system. In addition, the classification of data using HFACS highlighted several critical safety issues in need of intervention research.   CONCLUSION These results demonstrate that the HFACS framework can be a viable tool for use within the civil aviation arena. However, additional research is needed to examine its applicability to areas outside the flight deck, such as aircraft maintenance and air traffic control domains.

Question: What is the purpose of this study?


A Slacker Coherence Protocol for Pull-based Monitoring of On-line Data Sources �. An increasing number of online applications operate on data from disparate, and often wide-spread, data sources. This paper studies the design of a system for the automated monitoring of on-line data sources. In this system a number of ad-hoc data warehouses, which maintain client-specified views, are interposed between clients and data sources. We present a model of coherence, referred to here as slacker coherence, to address the freshness problem in the context of pull-based protocols. We experimentally examine various techniques for estimating update rates and polling adaptively. We also look at the impact on the coherence model performance of the request scheduling algorithm at the source.

Question: What is a slacker coherence protocol?


Compression of multiple depth maps for IBR. Image-based rendering techniques include those with geometry and those without. Geometric information in the form of a depth map aligned with the image holds a lot of promise for IBR due to the several methods available to capture it. It can improve the quality of generated views using a limited number of views. Compression of light fields or multiple images has attracted a lot of attention in the past. Compression of multiple depth maps of the same scene has not been explored much in the literature. We propose a method for compressing multiple depth maps in this paper using geometric proxy. Different quality of rendering and compression ratio can be achieved by varying different parameters. Experiments show the effectiveness of the compression technique on several model data.

Question: How to compress multiple depth maps?


Functional Specialization for Semantic and Phonological Processing in the Left Inferior Prefrontal Cortex. Neuroimaging and neuropsychological studies have implicated left inferior prefrontal cortex (LIPC) in both semantic and phonological processing. In this study, functional magnetic resonance imaging was used to examine whether separate LIPC regions participate in each of these types of processing. Performance of a semantic decision task resulted in extensive LIPC activation compared to a perceptual control task. Phonological processing of words and pseudowords in a syllable-counting task resulted in activation of the dorsal aspect of the left inferior frontal gyrus near the inferior frontal sulcus (BA 44/45) compared to a perceptual control task, with greater activation for nonwords compared to words. In a direct comparison of semantic and phonological tasks, semantic processing preferentially activated the ventral aspect of the left inferior frontal gyrus (BA 47/45). A review of the literature demonstrated a similar distinction between left prefrontal regions involved in semantic processing and phonological/lexical processing. The results suggest that a distinct region in the left inferior frontal cortex is involved in semantic processing, whereas other regions may subserve phonological processes engaged during both semantic and phonological tasks.

Question: What is the difference between semantic and phonological processing?


Advanced universal remote controller for home automation and security. There has been inconvenience in controlling each digital home appliance which requires its own remote controller. In this paper, we present an advanced universal remote controller (URC) with the total solution for home automation and security. All kinds of home appliances can be controlled with the URC, which can be also connected to a PC dealing with Internet as well. To use the URC, we need several receivers with wired or wireless communication methods to be connected to all appliances. The receivers have many channels and IDs to control many appliances at the same time and to support multi-zone services. In addition, we propose a PC-based interface for end-users to use the URC conveniently. With the proposed URC, we can easily construct a ubiquitous home automation and security environment with the total solution. Furthermore, this solution can be applied to the automated control of all kinds of appliances installed within buildings for companies, schools, hospitals, and so on.

Question: What is the total solution for home automation and security?


Document Image Quality Assessment: A Brief Survey. To maintain, control and enhance the quality of document images and minimize the negative impact of degradations on various analysis and processing systems, it is critical to understand the types and sources of degradations and develop reliable methods for estimating the levels of degradations. This paper provides a brief survey of research on the topic of document image quality assessment. We first present a detailed analysis of the types and sources of document degradations. We then review techniques for document image degradation modeling. Finally, we discuss objective measures and subjective experiments that are used to characterize document image quality.

Question: What is the difference between a document and a document image?


On the economic significance of ransomware campaigns: A Bitcoin transactions perspective. Bitcoin cryptocurrency system enables users to transact securely and pseudo-anonymously by using an arbitrary number of aliases (Bitcoin addresses). Cybercriminals exploit these characteristics to commit immutable and presumably untraceable monetary fraud, especially via ransomware; a type of malware that encrypts files of the infected system and demands ransom for decryption. In this paper, we present our comprehensive study on all recent ransomware and report the economic impact of such ransomware from the Bitcoin payment perspective. We also present a lightweight framework to identify, collect, and analyze Bitcoin addresses managed by the same user or group of users (cybercriminals, in this case), which includes a novel approach for classifying a payment as ransom. To verify the correctness of our framework, we compared our findings on CryptoLocker ransomware with the results presented in the literature. Our results align with the results found in the previous works except for the final valuation in USD. The reason for this discrepancy is that we used the average Bitcoin price on the day of each ransom payment whereas the authors of the previous studies used the Bitcoin price on the day of their evaluation. Furthermore, for each investigated ransomware, we provide a holistic view of its genesis, development, the process of infection and execution, and characteristic of ransom demands. Finally, we also release our dataset that contains a detailed transaction history of all the Bitcoin addresses we identified for each ransomware.

Question: What is the economic impact of ransomware?


Multi-level direction of autonomous creatures for real-time virtual environments. There have been several recent efforts to build behavior-based autonomous creatures. While competent autonomous action is highly desirable, there is an important need to integrate autonomy with "directability". In this paper we discuss the problem of building autonomous animated creatures for interactive virtual environments which are also capable of being directed at multiple levels. We present an approach to control which allows an external entity to "direct" an autonomous creature at the motivational level, the task level, and the direct motor level. We also detail a layered architecture and a general behavioral model for perception and action-selection which incorporates explicit support for multi-level direction. These ideas have been implemented and used to develop several autonomous animated creatures.

Question: How to build a multi-level directed creature?


Feature Generating Networks for Zero-Shot Learning. Suffering from the extreme training data imbalance between seen and unseen classes, most of existing state-of-the-art approaches fail to achieve satisfactory results for the challenging generalized zero-shot learning task. To circumvent the need for labeled examples of unseen classes, we propose a novel generative adversarial network (GAN) that synthesizes CNN features conditioned on class-level semantic information, offering a shortcut directly from a semantic descriptor of a class to a class-conditional feature distribution. Our proposed approach, pairing a Wasserstein GAN with a classification loss, is able to generate sufficiently discriminative CNN features to train softmax classifiers or any multimodal embedding method. Our experimental results demonstrate a significant boost in accuracy over the state of the art on five challenging datasets - CUB, FLO, SUN, AWA and ImageNet - in both the zero-shot learning and generalized zero-shot learning settings.

Question: What is zero-shot learning?


Remote Sensing for Crop Management. Scientists with the Agricultural Research Service (ARS) and various government agencies and private institutions have provided a great deal of fundamental information relating spectral reflectance and thermal emittance properties of soils and crops to their agronomic and biophysical characteristics. This knowledge has facilitated the development and use of various remote sensing methods for non-destructive monitoring of plant growth and development and for the detection of many environmental stresses which limit plant productivity. Coupled with rapid advances in computing and positionlocating technologies, remote sensing from ground-, air-, and space-based platforms is now capable of providing detailed spatial and temporal information on plant response to their local environment that is needed for site specific agricultural management approaches. This manuscript, which emphasizes contributions by ARS researchers, reviews the biophysical basis of remote sensing; examines approaches that have been developed, refined, and tested for management of water, nutrients, and pests in agricultural crops; and assesses the role of remote sensing in yield prediction. It concludes with a discussion of challenges facing remote sensing in the future. Introduction Agricultural production strategies have changed dramatically over the past decade. Many of these changes have been driven by economic decisions to reduce inputs and maximize profits and by environmental guidelines mandating more efficient and safer use of agricultural chemicals. However, growers now have a heightened sensitivity to concerns over the quality, nutritional value, and safety of agricultural products. They are selecting cultivars and adjusting planting dates to accommodate anticipated patterns in weather, e.g., El Niño or La Niña events (Jones et al., 2000). They are also relying on biotechnological innovations for suppressing pests, e.g., insect protected (Bt) and Roundup® re

Question: What is the role of remote sensing in crop management?


Modeling ITIL Business Motivation Model in ArchiMate. According to Enterprise Architecture (EA) approaches, organizations have motivational concepts that are used to model the motivations that underlie its design or change, which represent the organization's Business Motivation Model (BMM). Likewise, this BMM is also present in the organizations who provide IT services. ITIL has become a reference for IT service providers, but is commonly modeled as a process-oriented approach to IT Service Management, often disregarding the remaining EA domains or its motivational elements. Conversely, we believe that like EA, ITIL has an important motivation model that should be formally represented.

Question: What is the motivation model of ITIL?


Using the SLEUTH urban growth model to simulate the impacts of future policy scenarios on urban land use in the Tehran metropolitan area in Iran. The SLEUTH model, based on the Cellular Automata (CA), can be applied to city development simulation in metropolitan areas. In this study the SLEUTH model was used to model the urban expansion and predict the future possible behavior of the urban growth in Tehran. The fundamental data were five Landsat TM and ETM images of 1988, 1992, 1998, 2001 and 2010. Three scenarios were designed to simulate the spatial pattern. The first scenario assumed historical urbanization mode would persist and the only limitations for development were height and slope. The second one was a compact scenario which makes the growth mostly internal and limited the expansion of suburban areas. The last scenario proposed a polycentric urban structure which let the little patches * Corresponding author. Tel.: +98 912 3572913 E-mail address: shaghayegh.kargozar@yahoo.com

Question: What is the future of the urban growth in Tehran?


A Foray into Conficker's Logic and Rendezvous Points. We present an in depth static analysis of the Conficker worm, primarily through the exploration of the client-side binary logic. In this paper, we summarize various aspects of the inner workings of binary variants A and B,1 which were the first in a chain of recent revisions aimed to keep this epidemic resistant to ongoing eradication attempts. These first two variants have combined to produce a multi-million node population of infected hosts, whose true main purpose has yet to be fully understood. We further validate aspects of our analysis through in-situ network analyses, and discuss some attribution links about its origins.

Question: What is the purpose of the conficker worm?


Plans and resource-bounded practical reasoning. An architecture for a rational agent must allow for means end reason ing for the weighing of competing alternatives and for interactions between these two forms of reasoning Such an architecture must also address the problem of resource boundedness We sketch a solution of the rst problem that points the way to a solution of the second In particular we present a high level speci cation of the practical reasoning component of an archi tecture for a resource bounded rational agent In this architecture a major role of the agent s plans is to constrain the amount of further practical reasoning she must perform Bratman Israel and Pollack

Question: What is a resource bounded rational agent?


Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability. Kernel method has been developed as one of the standard approaches for nonlinear learning, which however, does not scale to large data set due to its quadratic complexity in the number of samples. A number of kernel approximation methods have thus been proposed in the recent years, among which the random features method gains much popularity due to its simplicity and direct reduction of nonlinear problem to a linear one. Different random feature functions have since been proposed to approximate a variety of kernel functions. Among them the Random Binning (RB) feature, proposed in the first random-feature paper [21], has drawn much less attention than the Random Fourier (RF) feature proposed also in [21]. In this work, we observe that the RB features, with right choice of optimization solver, could be orders-of-magnitude more efficient than other random features and kernel approximation methods under the same requirement of accuracy. We thus propose the first analysis of RB from the perspective of optimization, which by interpreting RB as a Randomized Block Coordinate Descent in the infinite-dimensional space, gives a faster convergence rate compared to that of other random features. In particular, we show that by drawing R random grids with at least κ number of non-empty bins per grid in expectation, RB method achieves a convergence rate of O(1/κ R)), which not only sharpens its O(1/√R) rate from Monte Carlo analysis, but also shows a κ times speedup over other random features under the same analysis framework. In addition, we demonstrate another advantage of RB in the L1-regularized setting, where unlike other random features, a RB-based Coordinate Descent solver can be parallelized with guaranteed speedup proportional to κ. Our extensive experiments demonstrate the superior performance of the RB features over other random features and kernel approximation methods.

Question: What is the difference between random binning and random fourier?


Simultaneous Localization and Mapping for Forest Harvesters. A real-time SLAM (simultaneous localization and mapping) approach to harvester localization and tree map generation in forest environments is presented in this paper. The method combines 2D laser localization and mapping with GPS information to form global tree maps. Building an incremental map while also using it for localization is the only way a mobile robot can navigate in large outdoor environments. Until recently SLAM has only been confined to small-scale, mostly indoor, environments. We try to addresses the issues of scale for practical implementations of SLAM in extensive outdoor environments. Presented algorithms are tested in real outdoor environments using an all-terrain vehicle equipped with the navigation sensors and a DGPS receiver.

Question: What is the difference between a laser and a GPS?


Fractional Order ControlA Tutorial. Many real dynamic systems are better characterized using a non-integer order dynamic model based on fractional calculus or, differentiation or integration of noninteger order. Traditional calculus is based on integer order differentiation and integration. The concept of fractional calculus has tremendous potential to change the way we see, model, and control the nature around us. Denying fractional derivatives is like saying that zero, fractional, or irrational numbers do not exist. In this paper, we offer a tutorial on fractional calculus in controls. Basic definitions of fractional calculus, fractional order dynamic systems and controls are presented first. Then, fractional order PID controllers are introduced which may make fractional order controllers ubiquitous in industry. Additionally, several typical known fractional order controllers are introduced and commented. Numerical methods for simulating fractional order systems are given in detail so that a beginner can get started quickly. Discretization techniques for fractional order operators are introduced in some details too. Both digital and analog realization methods of fractional order operators are introduced. Finally, remarks on future research efforts in fractional order control are given.

Question: What is fractional calculus?


A fractional open circuit voltage based maximum power point tracker for photovoltaic arrays. In this paper a fractional open circuit voltage based maximum power point tracker (MPPT) for photovoltaic (PV) arrays is proposed. The fractional open circuit voltage based MPPT utilizes the fact that the PV array voltage corresponding to the maximum power exhibits a linear dependence with respect to array open circuit voltage for different irradiation and temperature levels. This method is the simplest of all the MPPT methods described in the literature. The main disadvantage of this method is that the PV array is disconnected from the load after regular intervals for the sampling of the array voltage. This results in power loss. Another disadvantage is that if the duration between two successive samplings of the array voltage, called the sampling period, is too long, there is a considerable loss. This is because the output voltage of the PV array follows the unchanged reference during one sampling period. Once a maximum power point (MPP) is tracked and a change in irradiation occurs between two successive samplings, then the new MPP is not tracked until the next sampling of the PV array voltage. This paper proposes an MPPT circuit in which the sampling interval of the PV array voltage, and the sampling period have been shortened. The sample and hold circuit, which samples and holds the MPP voltage, has also been simplified. The proposed circuit does not utilize expensive microcontroller or a digital signal processor and is thus suitable for low cost photovoltaic applications.

Question: What is a fractional open circuit voltage based maximum power point tracker?


Convex Formulations for Fair Principal Component Analysis. Though there is a growing literature on fairness for supervised learning, incorporating fairness into unsupervised learning has been less well-studied. This paper studies fairness in the context of principal component analysis (PCA). We first define fairness for dimensionality reduction, and our definition can be interpreted as saying a reduction is fair if information about a protected class (e.g., race or gender) cannot be inferred from the dimensionality-reduced data points. Next, we develop convex optimization formulations that can improve the fairness (with respect to our definition) of PCA and kernel PCA. These formulations are semidefinite programs, and we demonstrate their effectiveness using several datasets. We conclude by showing how our approach can be used to perform a fair (with respect to age) clustering of health data that may be used to set health insurance rates.

Question: How can we improve the fairness of PCA?


CHAPTER 12 WORKFLOW ENGINE FOR CLOUDS. A workflow models a process as consisting of a series of steps that simplifies the complexity of execution and management of applications. Scientific workflows in domains such as high-energy physics and life sciences utilize distributed resources in order to access, manage, and process a large amount of data from a higher level. Processing and managing such large amounts of data require the use of a distributed collection of computation and storage facilities. These resources are often limited in supply and are shared among many competing users. The recent progress in virtualization technologies and the rapid growth of cloud computing services have opened a new paradigm in distributed computing for utilizing existing (and often cheaper) resource pools for ondemand and scalable scientific computing. Scientific Workflow Management Systems (WfMS) need to adapt to this new paradigm in order to leverage the benefits of cloud services. Cloud services vary in the levels of abstraction and hence the type of service they present to application users. Infrastructure virtualization enables providers such as Amazon to offer virtual hardware for use in computeand dataintensive workflow applications. Platform-as-a-Service (PaaS) clouds expose a higher-level development and runtime environment for building and deploying workflow applications on cloud infrastructures. Such services may also expose domain-specific concepts for rapid-application development. Further up in the cloud stack are Software-as-a-Service providers who offer end users with

Question: What is the difference between cloud computing and cloud services?


Target Detection in SFCW Ground Penetrating Radar with C3 Algorithm and Hough Transform based on GPRMAX Simulation and Experimental Data. We perform target detection in B-scan images obtained using stepped frequency continuous wave (SFCW) ground-penetrating radar (GPR) simulation with Matlab and the open-source software for electromagnetic propagation simulation gprMax and using experimental data from measurements available on the Web. We perform hyperbola detection and target depth estimation using the Hough transform. Additionally, we reduce the complexity of Hough transform using the Column-Connection Clustering (C3) algorithm. The results show that gprMax can be used with SFCW modulated signals, besides its use with conventional impulse signals (impulse GPR). The proposed combination of C3 and Hough transform shows very good detection capability. These algorithms are also tested on experimental GPR data available on the Web to show their applicability in real soil conditions. Mean subtraction method and Singular Value Decomposition (SVD) algorithms are used to reduce the effects of the ground reflected wave.

Question: How to detect targets in soil using GPR?


Steady-State Analysis of the Series Resonant Converter. The series resonant converter is analyzed in steady state, and for constant switching frequency the output current and voltage characteristics are found to be ellipses. The converter operating point can then be easily obtained by superimposing a load line on these elliptical characteristics. Peak resonant capacitor voltage and inductor current are also plotted in the output plane and are dependent to first order only on output current. When peak voltage and current are plotted in this manner, the dependence of component stresses on operating point is clearly revealed. The output characteristics are modified to include the effect of transistor and diode voltage drops, and experimental verification is presented.

Question: What is the steady state analysis of the series resonant converter?


Distributed Representation of Subgraphs. Network embeddings have become very popular in learning effective feature representations of networks. Motivated by the recent successes of embeddings in natural language processing, researchers have tried to €nd network embeddings in order to exploit machine learning algorithms for mining tasks like node classi€cation and edge prediction. However, most of the work focuses on €nding distributed representations of nodes, which are inherently ill-suited to tasks such as community detection which are intuitively dependent on subgraphs. Here, we propose Sub2Vec, an unsupervised scalable algorithm to learn feature representations of arbitrary subgraphs. We provide means to characterize similarties between subgraphs and provide theoretical analysis of Sub2Vec and demonstrate that it preserves the so-called local proximity. We also highlight the usability of Sub2Vec by leveraging it for network mining tasks, like community detection. We show that Sub2Vec gets signi€cant gains over stateof-the-art methods and node-embedding methods. In particular, Sub2Vec o'ers an approach to generate a richer vocabulary of features of subgraphs to support representation and reasoning. ACM Reference format: Bijaya Adhikari, Yao Zhang, Naren Ramakrishnan and B. Aditya Prakash. 2016. Distributed Representation of Subgraphs. In Proceedings of ACM Conference, Washington, DC, USA, July 2017 (Conference'17), 9 pages. DOI: 10.1145/nnnnnnn.nnnnnnn

Question: What is the difference between node embedding and subgraph embedding?


High performance work systems: the gap between policy and practice in health care reform.. PURPOSE Studies of high-performing organisations have consistently reported a positive relationship between high performance work systems (HPWS) and performance outcomes. Although many of these studies have been conducted in manufacturing, similar findings of a positive correlation between aspects of HPWS and improved care delivery and patient outcomes have been reported in international health care studies. The purpose of this paper is to bring together the results from a series of studies conducted within Australian health care organisations. First, the authors seek to demonstrate the link found between high performance work systems and organisational performance, including the perceived quality of patient care. Second, the paper aims to show that the hospitals studied do not have the necessary aspects of HPWS in place and that there has been little consideration of HPWS in health system reform.   DESIGN/METHODOLOGY/APPROACH The paper draws on a series of correlation studies using survey data from hospitals in Australia, supplemented by qualitative data collection and analysis. To demonstrate the link between HPWS and perceived quality of care delivery the authors conducted regression analysis with tests of mediation and moderation to analyse survey responses of 201 nurses in a large regional Australian health service and explored HRM and HPWS in detail in three casestudy organisations. To achieve the second aim, the authors surveyed human resource and other senior managers in all Victorian health sector organisations and reviewed policy documents related to health system reform planned for Australia.   FINDINGS The findings suggest that there is a relationship between HPWS and the perceived quality of care that is mediated by human resource management (HRM) outcomes, such as psychological empowerment. It is also found that health care organisations in Australia generally do

Question: What is the relationship between high performance work systems and the perceived quality of care?


Motion planning based on learning models of pedestrian and driver behaviors. Autonomous driving has shown the capability of providing driver convenience and enhancing safety. While introducing autonomous driving into our current traffic system, one significant issue is to make the autonomous vehicle be able to react in the same way as real human drivers. In order to ensure that an autonomous vehicle of the future will perform like human drivers, this paper proposes a vehicle motion planning model, which can represent how drivers control vehicles based on the assessment of traffic environments in the real signalized intersection. The proposed motion planning model comprises functions of pedestrian intention detection, gap detection and vehicle dynamic control. The three functions are constructed based on the analysis of actual data collected from real traffic environments. Finally, this paper demonstrates the performance of the proposed method by comparing the behaviors of our model with the behaviors of real pedestrians and human drivers. The experimental results show that our proposed model can achieve 85% recognition rate for the pedestrian crossing intention. Moreover, the vehicle controlled by the proposed motion planning model and the actual human-driven vehicle are highly similar with respect to the gap acceptance in intersections.

Question: How can we make an autonomous vehicle behave like a human driver?


An Empirical Analysis of Bug Reports and Bug Fixing in Open Source Android Apps. Smartphone platforms and applications (apps) have gained tremendous popularity recently. Due to the novelty of the smartphone platform and tools, and the low barrier to entry for app distribution, apps are prone to errors, which affects user experience and requires frequent bug fixes. An essential step towards correcting this situation is understanding the nature of the bugs and bug-fixing processes associated with smartphone platforms and apps. However, prior empirical bug studies have focused mostly on desktop and server applications. Therefore, in this paper, we perform an in-depth empirical study on bugs in the Google Android smartphone platform and 24 widely-used open-source Android apps from diverse categories such as communication, tools, and media. Our analysis has three main thrusts. First, we define several metrics to understand the quality of bug reports and analyze the bug-fix process, including developer involvement. Second, we show how differences in bug life-cycles can affect the bug-fix process. Third, as Android devices carry significant amounts of security-sensitive information, we perform a study of Android security bugs. We found that, although contributor activity in these projects is generally high, developer involvement decreases in some projects, similarly, while bug-report quality is high, bug triaging is still a problem. Finally, we observe that in Android apps, security bug reports are of higher quality but get fixed slower than non-security bugs. We believe that the findings of our study could potentially benefit both developers and users of Android apps.

Question: What is the difference between a bug report and a bug fix?


Don't fall into a trap: Physical side-channel analysis of ChaCha20-Poly1305. The stream cipher ChaCha20 and the MAC function Poly1305 have been published as IETF RFC 7539. Since then, the industry is starting to use it more often. For example, it has been implemented by Google in their Chrome browser for TLS and also support has been added to OpenSSL, as well as OpenSSH. It is often claimed, that the algorithms are designed to be resistant to side-channel attacks. However, this is only true, if the only observable side-channel is the timing behavior. In this paper, we show that ChaCha20 is susceptible to power and EM side-channel analysis, which also translates to an attack on Poly1305, if used together with ChaCha20 for key generation. As a first countermeasure, we analyze the effectiveness of randomly shuffling the operations of the ChaCha round function.

Question: What is the security of the ChaCha20-Poly1305 combination?


Acquiring linear subspaces for face recognition under variable lighting. Previous work has demonstrated that the image variation of many objects (human faces in particular) under variable lighting can be effectively modeled by low-dimensional linear spaces, even when there are multiple light sources and shadowing. Basis images spanning this space are usually obtained in one of three ways: a large set of images of the object under different lighting conditions is acquired, and principal component analysis (PCA) is used to estimate a subspace. Alternatively, synthetic images are rendered from a 3D model (perhaps reconstructed from images) under point sources and, again, PCA is used to estimate a subspace. Finally, images rendered from a 3D model under diffuse lighting based on spherical harmonics are directly used as basis images. In this paper, we show how to arrange physical lighting so that the acquired images of each object can be directly used as the basis vectors of a low-dimensional linear space and that this subspace is close to those acquired by the other methods. More specifically, there exist configurations of k point light source directions, with k typically ranging from 5 to 9, such that, by taking k images of an object under these single sources, the resulting subspace is an effective representation for recognition under a wide range of lighting conditions. Since the subspace is generated directly from real images, potentially complex and/or brittle intermediate steps such as 3D reconstruction can be completely avoided; nor is it necessary to acquire large numbers of training images or to physically construct complex diffuse (harmonic) light fields. We validate the use of subspaces constructed in this fashion within the context of face recognition.

Question: How to acquire images of objects under different lighting conditions?


Development of a superior frontal–intraparietal network for visuo-spatial working memory. Working memory capacity increases throughout childhood and adolescence, which is important for the development of a wide range of cognitive abilities, including complex reasoning. The spatial-span task, in which subjects retain information about the order and position of a number of objects, is a sensitive task to measure development of spatial working memory. This review considers results from previous neuroimaging studies investigating the neural correlates of this development. Older children and adolescents, with higher capacity, have been found to have higher brain activity in the intraparietal cortex and in the posterior part of the superior frontal sulcus, during the performance of working memory tasks. The structural maturation of white matter has been investigated by diffusion tensor magnetic resonance imaging (DTI). This has revealed several regions in the frontal lobes in which white matter maturation is correlated with the development of working memory. Among these is a superior fronto-parietal white matter region, located close to the grey matter regions that are implicated in the development of working memory. Furthermore, the degree of white matter maturation is positively correlated with the degree of cortical activation in the frontal and parietal regions. This suggests that during childhood and adolescence, there is development of networks related to specific cognitive functions, such as visuo-spatial working memory. These networks not only consist of cortical areas but also the white matter tracts connecting them. For visuo-spatial working memory, this network could consist of the superior frontal and intraparietal cortex.

Question: What is the development of working memory?


Usability Problem Description and the Evaluator Effect in Usability Testing. Previous usability evaluation method (UEM) comparison studies have noted an evaluator effect on problem detection in heuristic evaluation, with evaluators differing in problems found and problem severity judgments. There have been few studies of the evaluator effect in usability testing (UT), task-based testing with end-use rs. UEM comparison studies focus on counting usability problems detected, but we also need to assess the content of usability problem descriptions (UPDs) to more fully mea sure evaluation effectiveness. The goals of this research were to develop UPD gui delines, explore the evaluator effect in UT, and evaluate the usefulness of the guidelines for grading UPD content. Ten guidelines for writing UPDs were developed by consulting usability practitioners through two questionnaires and a card sort. These guidelines are ( briefly): be clear and avoid jargon, describe problem severity, provide backing data, describe problem causes, describe user actions, provide a solution, consider politics and diplomacy, be professional and scientific, describe your methodology, and help the re ader sympathize with the user. A fourth study compared usability reports collect ed from 44 evaluators, both practitioners and graduate students, watching the same 10-minute UT session recording. Three judges measured problem detection for each evaluator a nd graded the reports for following 6 of the UPD guidelines. There was support for existence of an evaluator effect, even when watching prerecorded sessions, with low to moderate individual thoroughness of problem detection across all/severe problems (22%/34%), reliability of problem detection (37%/50%) and reliability of severity judgments (57% for severe ratings). Practiti oners received higher grades averaged across the 6 guidelines than students did, suggesting that the guide lin s may be useful for grading reports. The grades for the guidelines

Question: What is the evaluator effect in usability testing?


Boosted decision trees for word recognition in handwritten document retrieval. Recognition and retrieval of historical handwritten material is an unsolved problem. We propose a novel approach to recognizing and retrieving handwritten manuscripts, based upon word image classification as a key step. Decision trees with normalized pixels as features form the basis of a highly accurate AdaBoost classifier, trained on a corpus of word images that have been resized and sampled at a pyramid of resolutions. To stem problems from the highly skewed distribution of class frequencies, word classes with very few training samples are augmented with stochastically altered versions of the originals. This increases recognition performance substantially. On a standard corpus of 20 pages of handwritten material from the George Washington collection the recognition performance shows a substantial improvement in performance over previous published results (75% vs 65%). Following word recognition, retrieval is done using a language model over the recognized words. Retrieval performance also shows substantially improved results over previously published results on this database. Recognition/retrieval results on a more challenging database of 100 pages from the George Washington collection are also presented.

Question: What is the name of the database?


Sexual arousal patterns of bisexual men.. There has long been controversy about whether bisexual men are substantially sexually aroused by both sexes. We investigated genital and self-reported sexual arousal to male and female sexual stimuli in 30 heterosexual, 33 bisexual, and 38 homosexual men. In general, bisexual men did not have strong genital arousal to both male and female sexual stimuli. Rather, most bisexual men appeared homosexual with respect to genital arousal, although some appeared heterosexual. In contrast, their subjective sexual arousal did conform to a bisexual pattern. Male bisexuality appears primarily to represent a style of interpreting or reporting sexual arousal rather than a distinct pattern of genital sexual arousal.

Question: What is the difference between bisexual and homosexual men?


How to model fake news. Over the past three years it has become evident that fake news is a danger to democracy. However, until now there has been no clear understanding of how to define fake news, much less how to model it. This paper addresses both these issues. A definition of fake news is given, and two approaches for the modelling of fake news and its impact in elections and referendums are introduced. The first approach, based on the idea of a representative voter, is shown to be suitable to obtain a qualitative understanding of phenomena associated with fake news at a macroscopic level. The second approach, based on the idea of an election microstructure, describes the collective behaviour of the electorate by modelling the preferences of individual voters. It is shown through a simulation study that the mere knowledge that pieces of fake news may be in circulation goes a long way towards mitigating the impact of fake news.

Question: How to model fake news?


Active ESD protection for input transistors in a 40-nm CMOS process. This work presents a novel design for input ESD protection. By replacing the protection resistor with an active switch that isolates the input transistors from the pad under ESD stress, the ESD robustness can be greatly improved. The proposed designs were designed and verified in a 40-nm CMOS process using only thin oxide devices, which can successfully pass the typical industry ESD-protection specifications of 2-kV HBM and 200-V MM ESD tests.

Question: What is the difference between a resistor and an active switch?


Letter-based classification of Arabic scripts style in ancient Arabic manuscripts: Preliminary results. Classifying ancient Arabic manuscripts based on handwriting styles is one of the important roles in the field of paleography. Recognizing the style of handwriting in Arabic manuscripts helps in identifying the origin and date of ancient documents. In this paper we proposed using segmented letters from Arabic manuscripts to recognize handwriting style. Both Gabor Filters (GF) and Local Binary Pattern (LBP) are used to extract features from letters. The fused features are sent to Support Vector Machine (SVM) classifier. Experimental results have been implemented using manuscripts images from the Qatar National Library (QNL) and other online datasets. Better results are achieved when both GF and LBP descriptors are combined. The recognized Handwritten Arabic styles are Diwani, Kufic, Naskh, Farsi, Ruq'ah and Thuluth.

Question: What is the difference between diwani and kufic?


100 000 Frames/s 64 × 32 Single-Photon Detector Array for 2-D Imaging and 3-D Ranging. We report on the design and characterization of a multipurpose 64 × 32 CMOS single-photon avalanche diode (SPAD) array. The chip is fabricated in a high-voltage 0.35-μm CMOS technology and consists of 2048 pixels, each combining a very low noise (100 cps at 5-V excess bias) 30-μm SPAD, a prompt avalanche sensing circuit, and digital processing electronics. The array not only delivers two-dimensional intensity information through photon counting in either free-running (down to 10-μs integration time) or time-gated mode, but can also perform smart light demodulation with in-pixel background suppression. The latter feature enables phase-resolved imaging for extracting either three-dimensional depth-resolved images or decay lifetime maps, by measuring the phase shift between a modulated excitation light and the reflected photons. Pixel-level memories enable fully parallel processing and global-shutter readout, preventing motion artifacts (e.g., skew, wobble, motion blur) and partial exposure effects. The array is able to acquire very fast optical events at high frame-rate (up to 100 000 fps) and at single-photon level. Low-noise SPADs ensure high dynamic range (up to 110 dB at 100 fps) with peak photon detection efficiency of almost 50% at 410 nm. The SPAD imager provides different operating modes, thus, enabling both time-domain applications, like fluorescence lifetime imaging (FLIM) and fluorescence correlation spectroscopy, as well as frequency-domain FLIM and lock-in 3-D ranging for automotive vision and lidar.

Question: What is the maximum frame rate of the detector?


The Dysphagia Outcome and Severity Scale. The Dysphagia Outcome and Severity Scale (DOSS) is a simple, easy-to-use, 7-point scale developed to systematically rate the functional severity of dysphagia based on objective assessment and make recommendations for diet level, independence level, and type of nutrition. Intra- and interjudge reliabilities of the DOSS was established by four clinicians on 135 consecutive patients who underwent a modified barium swallow procedure at a large teaching hospital. Patients were assigned a severity level, independence level, and nutritional level based on three areas most associated with final recommendations: oral stage bolus transfer, pharyngeal stage retention, and airway protection. Results indicate high interrater (90%) and intrarater (93%) agreement with this scale. Implications are suggested for use of the DOSS in documenting functional outcomes of swallowing and diet status based on objective assessment.

Question: What is the Dysphagia Outcome and Severity Scale?


Identification of Photovoltaic Source Models. This paper presents a photovoltaic (PV) model estimation method from the PV module data. The model is based on a single-diode model of a PV cell. The cell model of a module is extended to estimate the parameters of arrays. The variation of the parameters with change in temperature and irradiance is also studied. Finally, estimation of the maximum power point from the estimated parameters under varying environmental conditions is presented.

Question: How to identify photovoltaic source models?


A linear regression analysis of the effects of age related pupil dilation change in iris biometrics. Medical studies have shown that average pupil size decreases linearly throughout adult life. Therefore, on average, the longer the time between acquisition of two images of the same iris, the larger the difference in dilation between the two images. Several studies have shown that increased difference in dilation causes an increase in the false nonmatch rate for iris recognition. Thus, increased difference in pupil dilation is one natural mechanism contributing to an iris template aging effect. We present an experimental analysis of the change in genuine match scores in the context of dilation differences due to aging.

Question: What is the age of the iris?


Compact arrays fed by substrate integrated waveguides. In this paper, we compare three different concepts of compact antenna arrays fed by substrate integrated waveguides (SIW). Antenna concepts differ in the type of radiators. Slots represent magnetic linear radiators, patches are electric surface radiators, and Vivaldi slots belong to travelling-wave antennas. Hence, the SIW feeders have to exploit different mechanisms of exciting antenna elements. Impedance and radiation properties of studied antenna arrays have been related to the normalized frequency. Antenna arrays have been mutually compared to show fundamental dependencies of final parameters of the designed antennas on state variables of antennas, on SIW feeder architectures and on related implementation details.

Question: What is the difference between slots, patches and vivaldi slots?


A Differential Covariance Matrix Adaptation Evolutionary Algorithm for real parameter optimization. Hybridization in context to Evolutionary Computation (EC) aims at combining the operators and methodologies from different EC paradigms to form a single algorithm that may enjoy a statistically superior performance on a wide variety of optimization problems. In this article we propose an efficient hybrid evolutionary algorithm that embeds the difference vector-based mutation scheme, the crossover and the selection strategy of Differential Evolution (DE) into another recently developed global optimization algorithm known as Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES). CMA-ES is a stochastic method for real parameter (continuous domain) optimization of non-linear, non-convex functions. The algorithm includes adaptation of covariance matrix which is basically an alternative method of traditional Quasi-Newton method for optimization based on gradient method. The hybrid algorithm, referred by us as Differential Covariance Matrix Adaptation Evolutionary Algorithm (DCMA-EA), turns out to possess a better blending of the explorative and exploitative behaviors as compared to the original DE and original CMAES, through empirical simulations. Though CMA-ES has emerged itself as a very efficient global optimizer, its performance deteriorates when it comes to dealing with complicated fitness landscapes, especially landscapes associated with noisy, hybrid composition functions and many real world optimization problems. In order to improve the overall performance of CMA-ES, the mutation, crossover and selection operators of DE have been incorporated into CMA-ES to synthesize the hybrid algorithm DCMA-EA. We compare DCMA-EA with original DE and CMA-EA, two best known DE-variants: SaDE and JADE, and two state-of-the-art real optimizers: IPOP-CMA-ES (Restart Covariance Matrix Adaptation Evolution Strategy with increasing population size) and DMS-PSO (Dynamic Multi Swarm

Question: What is the difference between a covariance matrix and a correlation matrix?


Approximating Polyhedra with Spheres for Time-Critical Collision Detection. This article presentsa method for approximatingpolyhedralobjects to support a time-critical collision-detectionalgorithm. The approximationsare hierarchies of spheres, and they allow the time-critical algorithm to progressivelyrefine the accuracy of its detection, stopping as needed to maintain the real-time performanceessential for interactive applications.The key to this approachis a preprocessthat automaticallybuilds tightly fitting hierarchies for rigid and articulatedobjects.The preprocessuses medial-axis surfaces, which are skeletal representations of objects. These skeletonsguide an optimizationtechniquethat gives the hierarchies accuracy properties appropriate for collision detection. In a sample application, hierarchies built this way allow the time-criticalcollision-detectionalgorithmto have acceptableaccuracy, improving significantly on that possible with hierarchies built by previous techniques. The performanceof the time-critical algorithmin this application is consistently 10 to 100 times better than a previous collision-detection algorithm, maintaining low latency and a nearIy constant frame rate of 10 frames per second on a conventional graphics workstation. The time-critical algorithm maintains its real-time performanceas objects become more complicated, even as they exceed previouslyreported complexitylevels by a factor of more than 10.

Question: What is a medial-axis surface?


Culture care theory, research, and practice.. Today nurses are facing a world in which they are almost forced to use transculturally-based nursing theories and practices in order to care for people of diverse cultures. The author, who in the mid-50s pioneered the development of the first transcultural nursing theory with a care focus, discusses the relevance, assumptions, and predictions of the culture care theory along with the ethnonursing research method. The author contends that transcultural nursing findings are gradually transforming nursing practice and are providing a new paradigm shift from traditional medical and unicultural practice to multiculturally congruent and specific care modalities. A few research findings are presented to show the importance of being attentive to cultural care diversities and universalities as the major tenets of the theory. In addition, some major contributions of the theory are cited along with major challenges for the immediate future.

Question: What is the author's name?


Solution of the Generalized Noah's Ark Problem.. The phylogenetic diversity (PD) of a set of species is a measure of the evolutionary distance among the species in the collection, based on a phylogenetic tree. Such a tree is composed of a root, internal nodes, and leaves that correspond to the set of taxa under study. With each edge of the tree is associated a non-negative branch length (evolutionary distance). If a particular survival probability is associated with each taxon, the PD measure becomes the expected PD measure. In the Noah's Ark Problem (NAP) introduced by Weitzman (1998), these survival probabilities can be increased at some cost. The problem is to determine how best to allocate a limited amount of resources to maximize the expected PD of the considered species. It is easy to formulate the NAP as a (difficult) nonlinear 0-1 programming problem. The aim of this article is to show that a general version of the NAP (GNAP) can be solved simply and efficiently with any set of edge weights and any set of survival probabilities by using standard mixed-integer linear programming software. The crucial point to move from a nonlinear program in binary variables to a mixed-integer linear program, is to approximate the logarithmic function by the lower envelope of a set of tangents to the curve. Solving the obtained mixed-integer linear program provides not only a near-optimal solution but also an upper bound on the value of the optimal solution. We also applied this approach to a generalization of the nature reserve problem (GNRP) that consists of selecting a set of regions to be conserved so that the expected PD of the set of species present in these regions is maximized. In this case, the survival probabilities of different taxa are not independent of each other. Computational results are presented to illustrate potentialities of the approach. Near-optimal solutions with hypothetical phylogenetic trees comprising about 4000 taxa are obtained in a few seconds or

Question: What is the expected phylogenetic diversity of a set of species?


Image Retargeting Quality Assessment: A Study of Subjective Scores and Objective Metrics. This paper presents the result of a recent large-scale subjective study of image retargeting quality on a collection of images generated by several representative image retargeting methods. Owning to many approaches to image retargeting that have been developed, there is a need for a diverse independent public database of the retargeted images and the corresponding subjective scores to be freely available. We build an image retargeting quality database, in which 171 retargeted images (obtained from 57 natural source images of different contents) were created by several representative image retargeting methods. And the perceptual quality of each image is subjectively rated by at least 30 viewers, meanwhile the mean opinion scores (MOS) were obtained. It is revealed that the subject viewers have arrived at a reasonable agreement on the perceptual quality of the retargeted image. Therefore, the MOS values obtained can be regarded as the ground truth for evaluating the quality metric performances. The database is made publicly available (Image Retargeting Subjective Database, [Online]. Available: http://ivp.ee.cuhk.edu.hk/projects/demo/retargeting/index.html) to the research community in order to further research on the perceptual quality assessment of the retargeted images. Moreover, the built image retargeting database is analyzed from the perspectives of the retargeting scale, the retargeting method, and the source image content. We discuss how to retarget the images according to the scale requirement and the source image attribute information. Furthermore, several publicly available quality metrics for the retargeted images are evaluated on the built database. How to develop an effective quality metric for retargeted images is discussed through a specifically designed subjective testing process. It is demonstrated that the metric performance can be further improved, by fusing t

Question: What is the subject of the paper?


LSTM-Based NeuroCRFs for Named Entity Recognition. Although NeuroCRF, an augmented Conditional Random Fields (CRF) model whose feature function is parameterized as a Feed-Forward Neural Network (FF NN) on word embeddings, has soundly outperformed traditional linear-chain CRF on many sequence labeling tasks, it is held back by the fact that FF NNs have a fixed input length and therefore cannot take advantage of the full input sentence. We propose to address this issue by replacing the FF NN with a Long Short-Term Memory (LSTM) NN, which can summarize an input of arbitrary length into a fixed dimension representation. The resulting model obtains F1=89.28 on WikiNER dataset, a significant improvement over the NeuroCRF baseline's F1=87.58, which is already a highly competitive result.

Question: What is a feed forward neural network?


Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images. Recovering the 3D representation of an object from single-view or multi-view RGB images by deep neural networks has attracted increasing attention in the past few years. Several mainstream works (e.g., 3D-R2N2) use recurrent neural networks (RNNs) to fuse multiple feature maps extracted from input images sequentially. However, when given the same set of input images with different orders, RNN-based approaches are unable to produce consistent reconstruction results. Moreover, due to long-term memory loss, RNNs cannot fully exploit input images to refine reconstruction results. To solve these problems, we propose a novel framework for single-view and multi-view 3D reconstruction, named Pix2Vox. By using a well-designed encoder-decoder, it generates a coarse 3D volume from each input image. Then, a context-aware fusion module is introduced to adaptively select high-quality reconstructions for each part (e.g., table legs) from different coarse 3D volumes to obtain a fused 3D volume. Finally, a refiner further refines the fused 3D volume to generate the final output. Experimental results on the ShapeNet and Pascal 3D+ benchmarks indicate that the proposed Pix2Vox outperforms state-of-the-arts by a large margin. Furthermore, the proposed method is 24 times faster than 3D-R2N2 in terms of backward inference time. The experiments on ShapeNet unseen 3D categories have shown the superior generalization abilities of our method.

Question: How to reconstruct 3D objects from single and multi-view images?


Graph-Level Operations: A High-Level Interface for Graph Visualization Technique Specification. Social networks collected by historians or sociologists typically have a large number of actors and edge attributes. Applying social network analysis (SNA) algorithms to these networks produces additional attributes such as degree, centrality, and clustering coefficients. Understanding the effects of this plethora of attributes is one of the main challenges of multivariate SNA. We present the design of GraphDice, a multivariate network visualization system for exploring the attribute space of edges and actors. GraphDice builds upon the ScatterDice system for its main multidimensional navigation paradigm, and extends it with novel mechanisms to support network exploration in general and SNA tasks in particular. Novel mechanisms include visualization of attributes of interval type and projection of numerical edge attributes to node attributes. We show how these extensions to the original ScatterDice system allow to support complex visual analysis tasks on networks with hundreds of actors and up to 30 attributes, while providing a simple and consistent interface for interacting with network data.

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


MAGAN: Margin Adaptation for Generative Adversarial Networks. We propose a novel training procedure for Generative Adversarial Networks (GANs) to improve stability and performance by using an adaptive hinge loss objective function. We estimate the appropriate hinge loss margin with the expected energy of the target distribution, and derive both a principled criterion for updating the margin and an approximate convergence measure. The resulting training procedure is simple yet robust on a diverse set of datasets. We evaluate the proposed training procedure on the task of unsupervised image generation, noting both qualitative and quantitative performance improvements.

Question: What is a generative adversarial network?


Disclosure , Liquidity , and the Cost of Capital. This paper shows that revealing public information to reduce information asymmetry can reduce a firm's cost of capital by attracting increased demand from large investors due to increased liquidity of its securities. Large firms will disclose more information since they benefit most. Disclosure also reduces the risk bearing capacity available through market makers. If initial information asymmetry is large, reducing it will increase the current price of the security. However, the maximum current price occurs with some asymmetry of information: further reduction of information asymmetry accentuates the undesirable effects of exit from market making. THIS PAPER STUDIES THE causes and consequences of a security's liquidity, especially the effect of future liquidity on the security's current price-equivalently the effect on its required expected rate of return, its cost of capital. Under conditions that we identify, reducing information asymmetry reduces the cost of capital. Under other (less typical) conditions, this reduced information asymmetry can have the opposite effect. We use public disclosure of information as the means of changing information asymmetry, but the points are more general. Our model is related to those of Kyle (1985), Glosten and Milgrom (1985), and Admati and Pfleiderer (1988). They assume that there is unlimited risk bearing capacity devoted to market making, which implies that changes in future liquidity never influence a security's cost of capital.1 In contrast, we develop a model of trade in an illiquid market with limited risk bearing capacity of risk-averse market makers and examine the effects of private information on the incentives of market makers to provide risk bearing *The University of Chicago and the University of Pennsylvania, respectively. Diamond gratefully acknowledges support from NSF grant SES-8896223 and from a gift to the University of Chicago from Dimensional Fund Advisors.

Question: How does disclosure affect the cost of capital?


WeChecker: efficient and precise detection of privilege escalation vulnerabilities in Android apps. Due to the rapid increase of Android apps and their wide usage to handle personal data, a precise and large-scaling checker is in need to validate the apps' permission flow before they are listed on the market. Several tools have been proposed to detect sensitive data leaks in Android apps. But these tools are not applicable to large-scale analysis since they fail to deal with the arbitrary execution orders of different event handlers smartly. Event handlers are invoked by the framework based on the system state, therefore we cannot pre-determine their order of execution. Besides, since all exported components can be invoked by an external app, the execution orders of these components are also arbitrary. A naive way to simulate these two types of arbitrary execution orders yields a permutation of all event handlers in an app. The time complexity is O(n!) where n is the number of event handlers in an app. This leads to a high analysis overhead when n is big. To give an illustration, CHEX [10] found 50.73 entry points of 44 unique class types in an app on average. In this paper we propose an improved static taint analysis to deal with the challenge brought by the arbitrary execution orders without sacrificing the high precision. Our analysis does not need to make permutations and achieves a polynomial time complexity. We also propose to unify the array and map access with object reference by propagating access paths to reduce the number of false positives due to field-insensitivity and over approximation of array access and map access.  We implement a tool, WeChecker, to detect privilege escalation vulnerabilities [7] in Android apps. WeChecker achieves 96% precision and 96% recall in the state-of-the-art test suite DriodBench (for compairson, the precision and recall of FlowDroid [1] are 86% and 93%, respectively). The evaluation of WeChecker on real apps shows that it

Question: What is the state-of-the-art test suite DriodBench?


An Introduction to Logistic Regression Analysis and Reporting. The purpose of this article is to provide researchers, editors, and readers with a set of guidelines for what to expect in an article using logistic regression techniques. Tables, figures, and charts that should be included to comprehensively assess the results and assumptions to be verified are discussed. This article demonstrates the preferred pattern for the application of logistic methods with an illustration of logistic regression applied to a data set in testing a research hypothesis. Recommendations are also offered for appropriate reporting formats of logistic regression results and the minimum observation-to-predictor ratio. The authors evaluated the use and interpretation of logistic regression presented in 8 articles published in The Journal of Educational Research between 1990 and 2000. They found that all 8 studies met or exceeded recommended criteria.

Question: What is logistic regression?


Parsing English into Abstract Meaning Representation Using Syntax-Based Machine Translation. We present a parser for Abstract Meaning Representation (AMR). We treat Englishto-AMR conversion within the framework of string-to-tree, syntax-based machine translation (SBMT). To make this work, we transform the AMR structure into a form suitable for the mechanics of SBMT and useful for modeling. We introduce an AMR-specific language model and add data and features drawn from semantic resources. Our resulting AMR parser significantly improves upon state-of-the-art results.

Question: How to parse english into abstract meaning representation?


Classifying distinct basal cell carcinoma subtype by means of dermatoscopy and reflectance confocal microscopy.. BACKGROUND The current guidelines for the management of basal cell carcinoma (BCC) suggest a different therapeutic approach according to histopathologic subtype. Although dermatoscopic and confocal criteria of BCC have been investigated, no specific studies were performed to evaluate the distinct reflectance confocal microscopy (RCM) aspects of BCC subtypes.   OBJECTIVES To define the specific dermatoscopic and confocal criteria for delineating different BCC subtypes.   METHODS Dermatoscopic and confocal images of histopathologically confirmed BCCs were retrospectively evaluated for the presence of predefined criteria. Frequencies of dermatoscopic and confocal parameters are provided. Univariate and adjusted odds ratios were calculated. Discriminant analyses were performed to define the independent confocal criteria for distinct BCC subtypes.   RESULTS Eighty-eight BCCs were included. Dermatoscopically, superficial BCCs (n=44) were primarily typified by the presence of fine telangiectasia, multiple erosions, leaf-like structures, and revealed cords connected to the epidermis and epidermal streaming upon RCM. Nodular BCCs (n=22) featured the classic dermatoscopic features and well outlined large basaloid islands upon RCM. Infiltrative BCCs (n=22) featured structureless, shiny red areas, fine telangiectasia, and arborizing vessels on dermatoscopy and dark silhouettes upon RCM.   LIMITATIONS The retrospective design.   CONCLUSION Dermatoscopy and confocal microscopy can reliably classify different BCC subtypes.

Question: What is the difference between dermatoscopy and reflectance confocal microscopy?


A Multimodal Analysis of Floor Control in Meetings. The participant in a human-to-human communication who controls the floor bears the burden of moving the communication process along. Change in control of the floor can happen through a number of mechanisms, including interruptions, delegation of the floor, and so on. This paper investigates floor control in multiparty meetings that are both audio and video taped; hence, we analyze patterns of speech (e.g., the use of discourse markers) and visual cues (e.g, eye gaze exchanges) that are often involved in floor control changes. Identifying who has control of the floor provides an important focus for information retrieval and summarization of meetings. Additionally, without understanding who has control of the floor, it is impossible to identify important events such as challenges for the floor. In this paper, we analyze multimodal cues related to floor control in two different meetings involving five participants each.

Question: What is the burden of moving the communication process along?


Humanlike Driving: Empirical Decision-Making System for Autonomous Vehicles. The autonomous vehicle, as an emerging and rapidly growing field, has received extensive attention for its futuristic driving experiences. Although the fast developing depth sensors and machine learning methods have given a huge boost to self-driving research, existing autonomous driving vehicles do meet with several avoidable accidents during their road testings. The major cause is the misunderstanding between self-driving systems and human drivers. To solve this problem, we propose a humanlike driving system in this paper to give autonomous vehicles the ability to make decisions like a human. In our method, a convolutional neural network model is used to detect, recognize, and abstract the information in the input road scene, which is captured by the on-board sensors. And then a decision-making system calculates the specific commands to control the vehicles based on the abstractions. The biggest advantage of our work is that we implement a decision-making system which can well adapt to real-life road conditions, in which a massive number of human drivers exist. In addition, we build our perception system with only the depth information, rather than the unstable RGB data. The experimental results give a good demonstration of the efficiency and robustness of the proposed method.

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


Practical condition synchronization for transactional memory. Few transactional memory implementations allow for condition synchronization among transactions. The problems are many, most notably the lack of consensus about a single appropriate linguistic construct, and the lack of mechanisms that are compatible with hardware transactional memory. In this paper, we introduce a broadly useful mechanism for supporting condition synchronization among transactions. Our mechanism supports a number of linguistic constructs for coordinating transactions, and does so without introducing overhead on in-flight hardware transactions. Experiments show that our mechanisms work well, and that the diversity of linguistic constructs allows programmers to chose the technique that is best suited to a particular application.

Question: What is a transactional memory?


Systematic literature studies: Database searches vs. backward snowballing. Systematic studies of the literature can be done in different ways. In particular, different guidelines propose different first steps in their recommendations, e.g. start with search strings in different databases or start with the reference lists of a starting set of papers.  In software engineering, the main recommended first step is using search strings in a number of databases, while in information systems, snowballing has been recommended as the first step. This paper compares the two different search approaches for conducting literature review studies.  The comparison is conducted by searching for articles addressing "Agile practices in global software engineering". The focus of the paper is on evaluating the two different search approaches.  Despite the differences in the included papers, the conclusions and the patterns found in both studies are quite similar. The strengths and weaknesses of each first step are discussed separately and in comparison with each other.  It is concluded that none of the first steps is outperforming the other, and the choice of guideline to follow, and hence the first step, may be context-specific, i.e. depending on the area of study.

Question: What is the difference between search strings in databases and backward snowballing?