Recent system applications of short-pulse ultra-wideband (UWB) technology. Developed in the early 1960s, time-domain electromagnetics, the study of electromagnetic-wave propagation from a time-domain perspective, has given birth to a fascinating new technology, which today is commonly referred to as ultra-wideband (UWB). It has now been slightly more than 25 years since the 1978 seminal paper of Bennett and Ross, which summarized UWB's early applications. It thus seems appropriate, given the tremendous increase in interest in the technology since the Federal Communications Commission modified its Part 15 rules to accommodate UWB transmissions, to take a look at more recent system applications of this unique technology. This paper provides a brief historical perspective of UWB, discusses recent techniques for the generation and reception of short-pulse electromagnetic waveforms, and examines a number of recently developed UWB systems in the communications, radar, and precision-positioning fields. Finally, a brief assessment of future trends for the technology is provided.

Question: What is the history of ultra-wideband?


Structured Receptive Fields in CNNs. Learning powerful feature representations with CNNs is hard when training data are limited. Pre-training is one way to overcome this, but it requires large datasets sufficiently similar to the target domain. Another option is to design priors into the model, which can range from tuned hyperparameters to fully engineered representations like Scattering Networks. We combine these ideas into structured receptive field networks, a model which has a fixed filter basis and yet retains the flexibility of CNNs. This flexibility is achieved by expressing receptive fields in CNNs as a weighted sum over a fixed basis which is similar in spirit to Scattering Networks. The key difference is that we learn arbitrary effective filter sets from the basis rather than modeling the filters. This approach explicitly connects classical multiscale image analysis with general CNNs. With structured receptive field networks, we improve considerably over unstructured CNNs for small and medium dataset scenarios as well as over Scattering for large datasets. We validate our findings on ILSVRC2012, Cifar-10, Cifar-100 and MNIST. As a realistic small dataset example, we show state-of-the-art classification results on popular 3D MRI brain-disease datasets where pre-training is difficult due to a lack of large public datasets in a similar domain.

Question: What is a structured receptive field network?


Instance Based Clustering of Semantic Web Resources. The original Semantic Web vision was explicit in the need for intelligent autonomous agents that would represent users and help them navigate the Semantic Web. We argue that an essential feature for such agents is the capability to analyse data and learn. In this paper we outline the challenges and issues surrounding the application of clustering algorithms to Semantic Web data. We present several ways to extract instances from a large RDF graph and computing the distance between these. We evaluate our approaches on three different data-sets, one representing a typical relational database to RDF conversion, one based on data from a ontologically rich Semantic Web enabled application, and one consisting of a crawl of FOAF documents; applying both supervised and unsupervised evaluation metrics. Our evaluation did not support choosing a single combination of instance extraction method and similarity metric as superior in all cases, and as expected the behaviour depends greatly on the data being clustered. Instead, we attempt to identify characteristics of data that make particular methods more suitable.

Question: What is the difference between a relational database and a semantic web?


Software-Defined Networking Paradigms in Wireless Networks: A Survey. Software-defined networking (SDN) has generated tremendous interest from both academia and industry. SDN aims at simplifying network management while enabling researchers to experiment with network protocols on deployed networks. This article is a distillation of the state of the art of SDN in the context of wireless networks. We present an overview of the major design trends and highlight key differences between them.

Question: What is the state of the art of software defined networking in wireless networks?


Are leader stereotypes masculine? A meta-analysis of three research paradigms.. This meta-analysis examined the extent to which stereotypes of leaders are culturally masculine. The primary studies fit into 1 of 3 paradigms: (a) In Schein's (1973) think manager-think male paradigm, 40 studies with 51 effect sizes compared the similarity of male and leader stereotypes and the similarity of female and leader stereotypes; (b) in Powell and Butterfield's (1979) agency-communion paradigm, 22 studies with 47 effect sizes compared stereotypes of leaders' agency and communion; and (c) in Shinar's (1975) masculinity-femininity paradigm, 7 studies with 101 effect sizes represented stereotypes of leadership-related occupations on a single masculinity-femininity dimension. Analyses implemented appropriate random and mixed effects models. All 3 paradigms demonstrated overall masculinity of leader stereotypes: (a) In the think manager-think male paradigm, intraclass correlation = .25 for the women-leaders similarity and intraclass correlation = .62 for the men-leaders similarity; (b) in the agency-communion paradigm, g = 1.55, indicating greater agency than communion; and (c) in the masculinity-femininity paradigm, g = 0.92, indicating greater masculinity than the androgynous scale midpoint. Subgroup and meta-regression analyses indicated that this masculine construal of leadership has decreased over time and was greater for male than female research participants. In addition, stereotypes portrayed leaders as less masculine in educational organizations than in other domains and in moderate- than in high-status leader roles. This article considers the relation of these findings to Eagly and Karau's (2002) role congruity theory, which proposed contextual influences on the incongruity between stereotypes of women and leaders. The implications for prejudice against women leaders are also considered.

Question: What is the difference between a leader and a manager?


New trends in gender and mathematics performance: a meta-analysis.. In this article, we use meta-analysis to analyze gender differences in recent studies of mathematics performance. First, we meta-analyzed data from 242 studies published between 1990 and 2007, representing the testing of 1,286,350 people. Overall, d = 0.05, indicating no gender difference, and variance ratio = 1.08, indicating nearly equal male and female variances. Second, we analyzed data from large data sets based on probability sampling of U.S. adolescents over the past 20 years: the National Longitudinal Surveys of Youth, the National Education Longitudinal Study of 1988, the Longitudinal Study of American Youth, and the National Assessment of Educational Progress. Effect sizes for the gender difference ranged between -0.15 and +0.22. Variance ratios ranged from 0.88 to 1.34. Taken together, these findings support the view that males and females perform similarly in mathematics.

Question: What is the variance ratio?


Programming your network at run-time for big data applications. Recent advances of software defined networking and optical switching technology make it possible to program the network stack all the way from physical topology to flow level traffic control. In this paper, we leverage the combination of SDN controller with optical switching to explore the tight integration of application and network control. We particularly study the run-time network configuration for big data applications to jointly optimize application performance and network utilization. We use Hadoop as an example to discuss the integrated network control architecture, job scheduling, topology and routing configuration mechanisms for Hadoop jobs. Our analysis suggests that such an integrated control has great potential to improve application performance with relatively small configuration overhead. We believe our study shows early promise of achieving the long-term goal of tight network and application integration using SDN.

Question: What is the difference between a network controller and a network switch?


Revisit Behavior in Social Media: The Phoenix-R Model and Discoveries. How many listens will an artist receive on a online radio? How about plays on a YouTube video? How many of these visits are new or returning users? Modeling and mining popularity dynamics of social activity has important implications for researchers, content creators and providers. We here investigate the effect of revisits (successive visits from a single user) on content popularity. Using four datasets of social activity, with up to tens of millions media objects (e.g., YouTube videos, Twitter hashtags or LastFM artists), we show the effect of revisits in the popularity evolution of such objects. Secondly, we propose the PHOENIX-R model which captures the popularity dynamics of individual objects. PHOENIX-R has the desired properties of being: (1) parsimonious, being based on the minimum description length principle, and achieving lower root mean squared error than state-of-the-art baselines; (2) applicable, the model is effective for predicting future popularity values of objects.

Question: How many listens will an artist receive on a online radio?


Attribute bagging: improving accuracy of classifier ensembles by using random feature subsets. We present attribute bagging (AB), a technique for improving the accuracy and stability of classi#er ensembles induced using random subsets of features. AB is a wrapper method that can be used with any learning algorithm. It establishes an appropriate attribute subset size and then randomly selects subsets of features, creating projections of the training set on which the ensemble classi#ers are built. The induced classi#ers are then used for voting. This article compares the performance of our AB method with bagging and other algorithms on a hand-pose recognition dataset. It is shown that AB gives consistently better results than bagging, both in accuracy and stability. The performance of ensemble voting in bagging and the AB method as a function of the attribute subset size and the number of voters for both weighted and unweighted voting is tested and discussed. We also demonstrate that ranking the attribute subsets by their classi#cation accuracy and voting using only the best subsets further improves the resulting performance of the ensemble. ? 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

Question: What is the difference between bagging and attribute bagging?


Audio-Visual Person Recognition in Multimedia Data From the Iarpa Janus Program. Currently, datasets that support audio-visual recognition of people in videos are scarce and limited. In this paper, we introduce an expansion of video data from the IARPA Janus program to support this research area. We refer to the expanded set, which adds labels for voice to the already-existing face labels, as the Janus Multimedia dataset. We first describe the speaker labeling process, which involved a combination of automatic and manual criteria. We then discuss two evaluation settings for this data. In the core condition, the voice and face of the labeled individual are present in every video. In the full condition, no such guarantee is made. The power of audiovisual fusion is then shown using these publicly-available videos and labels, showing significant improvement over only recognizing voice or face alone. In addition to this work, several other possible paths for future research with this dataset are discussed.

Question: How to recognize people in videos


The questionable contribution of medical measures to the decline of mortality in the United States in the twentieth century.. Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use.

Question: What is the questionable contribution of medical measures to the decline of mortality in the United States in the twentieth century?


Forensic analysis of video file formats. Video file format standards define only a limited number of mandatory features and leave room for interpretation. Design decisions of device manufacturers and software vendors are thus a fruitful resource for forensic video authentication. This paper explores AVI and MP4-like video streams of mobile phones and digital cameras in detail. We use customized parsers to extract all file format structures of videos from overall 19 digital camera models, 14 mobile phone models, and 6 video editing toolboxes. We report considerable differences in the choice of container formats, audio and video compression algorithms, acquisition parameters, and internal file structure. In combination, such characteristics can help to authenticate digital video files in forensic settings by distinguishing between original and post-processed videos, verifying the purported source of a file, or identifying the true acquisition device model or the processing software used for video processing. a 2014 The Authors. Published by Elsevier Ltd on behalf of DFRWS. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Question: What is the difference between a video file format standard and a video file format standard?


A Wide-Field-of-View Monocentric Light Field Camera. Light field (LF) capture and processing are important in an expanding range of computer vision applications, offering rich textural and depth information and simplification of conventionally complex tasks. Although LF cameras are commercially available, no existing device offers wide field-of-view (FOV) imaging. This is due in part to the limitations of fisheye lenses, for which a fundamentally constrained entrance pupil diameter severely limits depth sensitivity. In this work we describe a novel, compact optical design that couples a monocentric lens with multiple sensors using microlens arrays, allowing LF capture with an unprecedented FOV. Leveraging capabilities of the LF representation, we propose a novel method for efficiently coupling the spherical lens and planar sensors, replacing expensive and bulky fiber bundles. We construct a single-sensor LF camera prototype, rotating the sensor relative to a fixed main lens to emulate a wide-FOV multi-sensor scenario. Finally, we describe a processing toolchain, including a convenient spherical LF parameterization, and demonstrate depth estimation and post-capture refocus for indoor and outdoor panoramas with 15 x 15 x 1600 x 200 pixels (72 MPix) and a 138° FOV.

Question: What is a monocentric lens?


Neurodegenerative Diseases Monitoring ( NDM ) main Challenges , Tendencies , and Enabling Big Data Technologies : A Survey. Evidence-based health monitoring has been recognized in the past few years as a very prominent solution to cope with continuous monitoring of chronic diseases such as neurodegenerative diseases for example: epilepsy. This has reduced the burden and cost for healthcare agencies and has led to efficient disease tracking, diagnosis, and intervention. Monitoring these diseases requires a long and continuous EEG signals recordings, pre-processing, analytics, and visualization. This will require a comprehensive solution to handle the complexity and time sensitivity of continuous monitoring. Several neurodegenerative disease monitoring (NDM) architectures have been proposed in the literature, however, they diverge on different aspects, such as the way they handle the monitoring processes, and the techniques they used to process, classify, and analyze the data. In this paper, we aim to bridge the gap between these existing NDM solutions. We provide first an overview of a standard NDM system, its main components, and requirements. We then survey and classify the exiting NDM solutions features, and characteristics. Afterwards, we provide a thorough evaluation of existing NDM solutions and we discuss the remaining key research challenges that have to be addressed. Finally, we propose and describe a generic NDM framework incorporating new technologies mainly the Cloud and Big Data to efficiently handle data intensive related processes. We aim by this work to serve researchers in this filed with useful information on NDM and provide direction for future research advancements. KeywordsNeurodegenerative Diseases Monitoring, Brain Informatics, Neuro Informatics, Big data, EEG, Seizure Detection

Question: What is the difference between a neurodegenerative disease and a neurodegenerative disease monitoring?


Customer Lifetime Value ( CLV ) Measurement Based on RFM Model. Nowadays companies increasingly derive revenue from the creation and sustenance of long-term relationships with their customers. In such an environment, marketing serves the purpose of maximizing customer lifetime value (CLV) and customer equity, which is the sum of the lifetime values of the company's customers. A frequently-encountered difficulty for companies wishing to measure customer profitability is that management accounting and reporting systems have tended to reflect product profitability rather than customer profitability. But in spite of these difficulties, Companies looking for methods to know how calculate their customers's CLV. In this paper, we used K-Mean clustering approach to determine customers's CLV and segment them based on recency, frequency and monetary (RFM) measures. We also used Discriminant analysis to approve clustering results. Data required applying this method gathered from one branch of an Iranian private bank which is established newly. Finally, in terms of this segmentation, we proposed customer retention strategies for treating with the bank customers.

Question: How to calculate customer lifetime value?


Exploration and Mapping with Autonomous Robot Teams Results from the MAGIC 2010 Competition. The potential impact of autonomous robotics is magnified when those robots are deployed in teams: a team of cooperating robots can greatly increase the effectiveness of a human working alone, making short work of search-and-rescue and reconnaissance tasks. To achieve this potential, however, a number of challenging problems ranging from multi-robot planning, state estimation, object detection, and human-robot interfaces must first be solved. The MAGIC 2010 competition, like the DARPA grand challenges that preceded it, presented a formidable robotics problem designed to foster fundamental advances in these difficult areas. MAGIC asked teams of robots to collaboratively explore and map a 500× 500m area, detect and track benign and dangerous objects, and collaborate with human commanders while respecting their cognitive limits. This paper describes our winning entry in the MAGIC contest, where we fielded a team of 14 autonomous robots supervised by two human operators. While the challenges in MAGIC were diverse, we believe that cooperative multi-robot state estimation is ultimately the critical factor in building a successful system. In this paper, we describe our system and some of the technological advances that we believe were responsible for our success. We also contrast our approach to those of other teams. a)

Question: What is the winning entry in the MAGIC competition?


RoboCup: The Robot World Cup Initiative. The Robot World Cup Initiative (RoboCup) is an attempt to foster AI and intelligent robotics research by providing a standard problem where wide range of technologies can be integrated and examined. The rst RoboCup competition will be held at IJCAI-97, Nagoya. In order for a robot team to actually perform a soccer game, various technologies must be incorporated including: design principles of autonomous agents, multi-agent collaboration, strategy acquisition, real-time reasoning, robotics, and sensor-fusion. Unlike AAAI robot competition, which is tuned for a single heavyduty slow-moving robot, RoboCup is a task for a team of multiple fast-moving robots under a dynamic environment. Although RoboCup's nal target is a world cup with real robots, RoboCup o ers a software platform for research on the software aspects of RoboCup. This paper describes technical challenges involved in RoboCup, rules, and simulation environment.

Question: What is the robot world cup?


Hardware-In-the-Loop Simulation of Electric Vehicle Powertrain System. This paper presents a design procedure of HardwareIn-the-Loop (HIL) for Electric Vehicle powertrain system modeling and simulation. First, simulation is performed in MATLAB/Simulink platform. Then, an Electric Vehicle Powertrain Hardware-In-the-Loop system including BMS (Battery Manage System), MCU (Motor Control Unit) and VMS (vehicle management system) is built based on the dSPACE with MATLAB/Simulink, along with the RTW toolbox (real time workshop). Through this system, the Electric Vehicle Control strategy is simulated and validated, and the results of offline simulation & real time simulation with laboratory prototype are presented. Keywords-Hardware In the Loop; Electric Vehicle; Simulation; dSPACE; DSP

Question: What is the difference between offline and real time simulation?


Women with hyperandrogenism in elite sports: scientific and ethical rationales for regulating.. The recent implementation by some major sports-governing bodies of policies governing eligibility of females with hyperandrogenism to compete in women's sports has raised a lot of attention and is still a controversial issue. This short article addresses two main subjects of controversy: the existing scientific basis supporting performance enhancing of high blood T levels in elite female athletes, and the ethical rationale and considerations about these policies. Given the recently published data about both innate and acquired hyperandrogenic conditions and their prevalence in elite female sports, we claim that the high level of androgens are per se performance enhancing. Regulating women with clinical and biological hyperandrogenism is an invitation to criticism because biological parameters of sex are not neatly divided into only two categories in the real world. It is, however, the responsibility of the sports-governing bodies to do their best to guarantee a level playing field to all athletes. In order not cloud the discussions about the policies on hyperandrogenism in sports, issues of sports eligibility and therapeutic options should always be considered and explained separately, even if they may overlap. Finally, some proposals for refining the existing policies are made in the present article.

Question: What is the difference between the two types of hyperandrogenism?


Towards a Universal Grammar for Natural Language Processing. Universal Dependencies is a recent initiative to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. In this talk, I outline the motivation behind the initiative and explain how the basic design principles follow from these requirements. I then discuss the different components of the annotation standard, including principles for word segmentation, morphological annotation, and syntactic annotation. I conclude with some thoughts on the challenges that lie ahead.

Question: What is the motivation behind the universal grammar for natural language processing?


Design and Analysis of a Low-Profile and Broadband Microstrip Monopolar Patch Antenna. A new microstrip monopolar patch antenna is proposed and analyzed. The antenna has a wide bandwidth and a monopole like radiation pattern. Such antenna is constructed on a circular patch antenna that is shorted concentrically with a set of conductive vias. The antenna is analyzed using a cavity model. The cavity model analysis not only distinguishes each resonating mode and gives a physical insight into each mode of the antenna, but also provides a guideline to design a broadband monopolar patch antenna that utilizes two modes (TM01 and TM02 modes). Both modes provide a monopole like radiation pattern. The proposed antenna has a simple structure with a low profile of 0.024 wavelengths, and yields a wide impedance bandwidth of 18% and a maximum gain of 6 dBi.

Question: What is a monopole like radiation pattern?


Assortment Optimization under the Multinomial Logit Model with Random Choice Parameters. We consider assortment optimization problems under the multinomial logit model, where the parameters of the choice model are random. The randomness in the choice model parameters is motivated by the fact that there are multiple customer segments, each with different preferences for the products, and the segment of each customer is unknown to the firm when the customer makes a purchase. This choice model is also called the mixture-of-logits model. The goal of the firm is to choose an assortment of products to offer that maximizes the expected revenue per customer, across all customer segments. We establish that the problem is NP-complete even when there are just two customer segments. Motivated by this complexity result, we focus on assortments consisting of products with the highest revenues, which we refer to as revenue-ordered assortments. We identify specially structured cases of the problem where revenue-ordered assortments are optimal. When the randomness in the choice model parameters does not follow a special structure, we derive tight approximation guarantees for revenue-ordered assortments. We extend our model to the multi-period capacity allocation problem, and prove that, when restricted to the revenue-ordered assortments, the mixture-of-logits model possesses the nesting-by-fare-order property. This result implies that revenue-ordered assortments can be incorporated into existing revenue management systems through nested protection levels. Numerical experiments show that revenue-ordered assortments perform remarkably well, generally yielding profits that are within a fraction of a percent of the optimal.

Question: What is the multinomial logit model?


Average cost temporal-difference learning. We propose a variant of temporal-di!erence learning that approximates average and di!erential costs of an irreducible aperiodic Markov chain. Approximations are comprised of linear combinations of "xed basis functions whose weights are incrementally updated during a single endless trajectory of the Markov chain. We present a proof of convergence (with probability 1) and a characterization of the limit of convergence. We also provide a bound on the resulting approximation error that exhibits an interesting dependence on the `mixing timea of the Markov chain. The results parallel previous work by the authors, involving approximations of discounted cost-to-go. ! 1999 Elsevier Science Ltd. All rights reserved.

Question: What is the average cost temporal-difference learning?


A systematic review of implementation strategies for assessment, prevention, and management of ICU delirium and their effect on clinical outcomes. INTRODUCTION Despite recommendations from professional societies and patient safety organizations, the majority of ICU patients worldwide are not routinely monitored for delirium, thus preventing timely prevention and management. The purpose of this systematic review is to summarize what types of implementation strategies have been tested to improve ICU clinicians' ability to effectively assess, prevent and treat delirium and to evaluate the effect of these strategies on clinical outcomes.   METHOD We searched PubMed, Embase, PsychINFO, Cochrane and CINAHL (January 2000 and April 2014) for studies on implementation strategies that included delirium-oriented interventions in adult ICU patients. Studies were suitable for inclusion if implementation strategies' efficacy, in terms of a clinical outcome, or process outcome was described.   RESULTS We included 21 studies, all including process measures, while 9 reported both process measures and clinical outcomes. Some individual strategies such as "audit and feedback" and "tailored interventions" may be important to establish clinical outcome improvements, but otherwise robust data on effectiveness of specific implementation strategies were scarce. Successful implementation interventions were frequently reported to change process measures, such as improvements in adherence to delirium screening with up to 92%, but relating process measures to outcome changes was generally not possible. In meta-analyses, reduced mortality and ICU length of stay reduction were statistically more likely with implementation programs that employed more (six or more) rather than less implementation strategies and when a framework was used that either integrated current evidence on pain, agitation and delirium management (PAD) or when a strategy of early awakening, breathing, delirium screening and e

Question: What is the effect of implementation strategies on clinical outcomes?


Fast routing in road networks with transit nodes.. When you drive to somewhere far away, you will leave your current location via one of only a few important traffic junctions. Starting from this informal observation, we developed an algorithmic approach, transit node routing, that allows us to reduce quickest path queries in road networks to a small number of table lookups. For road maps of Western Europe and the United States, our best query times improved over the best previously published figures by two orders of magnitude. This is also more than one million times faster than the best known algorithm for general networks.

Question: What is the fastest algorithm for shortest path queries in road networks?


ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations. We describe PARANMT-50M, a dataset of more than 50 million English-English sentential paraphrase pairs. We generated the pairs automatically by using neural machine translation to translate the nonEnglish side of a large parallel corpus, following Wieting et al. (2017). Our hope is that PARANMT-50M can be a valuable resource for paraphrase generation and can provide a rich source of semantic knowledge to improve downstream natural language understanding tasks. To show its utility, we use PARANMT-50M to train paraphrastic sentence embeddings that outperform all supervised systems on every SemEval semantic textual similarity competition, in addition to showing how it can be used for paraphrase generation.1

Question: What is the size of the dataset?


Leakage Current Elimination of Four-Leg Inverter for Transformerless Three-Phase PV Systems. Eliminating the leakage current is one of the most important issues for transformerless three-phase photovoltaic (PV) systems. In this paper, the leakage current elimination of a three-phase four-leg PV inverter is investigated. With the common-mode loop model established, the generation mechanism of the leakage current is clearly identified. Different typical carrier-based modulation methods and their corresponding common-mode voltages are discussed. A new modulation strategy with Boolean logic function is proposed to achieve the constant common-mode voltage for the leakage current reduction. Finally, the different modulation methods are implemented and tested on the TMS320F28335 DSP +XC3S400 FPGA digital control platform. The experimental results verify the effectiveness of the proposed solution.

Question: How to eliminate the leakage current of a transformerless three-phase PV system?


A Survey on Ambient-Assisted Living Tools for Older Adults. In recent years, we have witnessed a rapid surge in assisted living technologies due to a rapidly aging society. The aging population, the increasing cost of formal health care, the caregiver burden, and the importance that the individuals place on living independently, all motivate development of innovative-assisted living technologies for safe and independent aging. In this survey, we will summarize the emergence of `ambient-assisted living" (AAL) tools for older adults based on ambient intelligence paradigm. We will summarize the state-of-the-art AAL technologies, tools, and techniques, and we will look at current and future challenges.

Question: What is ambient intelligence?


Intelligent Heart Disease Prediction System Using Probabilistic Neural Network. The diagnosis of diseases is a crucial and difficult job in medicine. The recognition of heart disease from diverse features or signs is a multi-layered problem that is not free from false assumptions and is frequently accompanied by hasty effects [1]. Thus an attempt to exploit knowledge and experience of several specialists and clinical screening data of patients composed in databases to assist the diagnosis procedure is regarded as a great challenge. The healthcare industry gathers enormous amounts of heart disease data that unfortunately, are not mined to determine concealed information for effective diagnosing [2]. In this paper, an efficient approach for the intelligent heart disease prediction based on Probabilistic Neural Network (PNN) technique is proposed. Initially, the data set containing 13 medical attributes were obtained from the Cleveland heart disease database. The dataset is clustered with the aid of k-means clustering algorithm. The PNN with radial basis function is trained using the selected data sets. The comparison between existing approaches and proposed approach with respect to accuracy of prediction, sensitivity and specificity is recorded in this paper. The results from experiments returned with diminishing fact that there is considerable improvement in classification and prediction. The proposed PNN works as promising tool for prediction of heart disease.

Question: What is the difference between the existing approaches and proposed approach?


SemEval-2016 Task 7: Determining Sentiment Intensity of English and Arabic Phrases. We present a shared task on automatically determining sentiment intensity of a word or a phrase. The words and phrases are taken from three domains: general English, English Twitter, and Arabic Twitter. The phrases include those composed of negators, modals, and degree adverbs as well as phrases formed by words with opposing polarities. For each of the three domains, we assembled the datasets that include multi-word phrases and their constituent words, both manually annotated for real-valued sentiment intensity scores. The three datasets were presented as the test sets for three separate tasks (each focusing on a specific domain). Five teams submitted nine system outputs for the three tasks. All datasets created for this shared task are freely available to the research community.

Question: What is the sentiment intensity of the following phrases?


Quality driven web services composition. The process-driven composition of Web services is emerging as a promising approach to integrate business applications within and across organizational boundaries. In this approach, individual Web services are federated into composite Web services whose business logic is expressed as a process model. The tasks of this process model are essentially invocations to functionalities offered by the underlying component services. Usually, several component services are able to execute a given task, although with different levels of pricing and quality. In this paper, we advocate that the selection of component services should be carried out during the execution of a composite service, rather than at design-time. In addition, this selection should consider multiple criteria (e.g., price, duration, reliability), and it should take into account global constraints and preferences set by the user (e.g., budget constraints). Accordingly, the paper proposes a global planning approach to optimally select component services during the execution of a composite service. Service selection is formulated as an optimization problem which can be solved using efficient linear programming methods. Experimental results show that this global planning approach outperforms approaches in which the component services are selected individually for each task in a composite service.

Question: What is the difference between a process-driven composition of Web services and a process-driven composition of business applications?


Enhanced Visibility of MoS 2 , MoSe 2 , WSe 2 and Black-Phosphorus : Making Optical Identification of 2 D Semiconductors Easier. We explore the use of Si3N4/Si substrates as a substitute of the standard SiO2/Si substrates employed nowadays to fabricate nanodevices based on 2D materials. We systematically study the visibility of several 2D semiconducting materials that are attracting a great deal of interest in nanoelectronics and optoelectronics: MoS2, MoSe2, WSe2 and black-phosphorus. We find that the use of Si3N4/Si substrates provides an increase of the optical contrast up to a 50%–100% and also the maximum contrast shifts towards wavelength values optimal for human eye detection, making optical identification of 2D semiconductors easier. OPEN ACCESS Electronics 2015, 4 848

Question: What is the maximum contrast shift?


Electrically small omni-directional antenna of circular polarization. A compact omni-directional antenna of circular polarization (CP) is presented for 2.4 GHz WLAN access-point applications. The antenna consists of four bended monopoles and a feeding network simultaneously exciting these four monopoles. The electrical size of the CP antenna is only λ0/5×λ0/5×λ0/13. The impedance bandwidth (|S11|<;-10 dB) is 3.85% (2.392 GHz to 2.486 GHz) and the axial ratio in the azimuth plane is lower than 0.5 dB in the operating band.

Question: What is the size of the antenna?


Damage in the anca-associated vasculitides: long-term data from the European vasculitis study group (EUVAS) therapeutic trials.. OBJECTIVES To describe short-term (up to 12 months) and long-term (up to 7 years) damage in patients with newly diagnosed antineutrophil-cytoplasm antibody-associated vasculitis (AAV).   METHODS Data were combined from six European Vasculitis Study group trials (n=735). Long-term follow-up (LTFU) data available for patients from four trials (n=535). Damage accrued was quantified by the Vasculitis Damage Index (VDI). Sixteen damage items were defined a priori as being potentially treatment-related.   RESULTS VDI data were available for 629 of 735 patients (85.6%) at baseline, at which time 217/629 (34.5%) had ≥1 item of damage and 32 (5.1%) ≥5 items, reflecting disease manifestations prior to diagnosis and trial enrolment. LTFU data were available for 467/535 (87.3%) at a mean of 7.3 years postdiagnosis. 302/535 patients (56.4%) had VDI data at LTFU, with 104/302 (34.4%) having ≥5 items and only 24 (7.9%) no items of damage. At 6 months and LTFU, the most frequent items were proteinuria, impaired glomerular filtration rate, hypertension, nasal crusting, hearing loss and peripheral neuropathy. The frequency of damage, including potentially treatment-related damage, rose over time (p<0.01). At LTFU, the most commonly reported items of treatment-related damage were hypertension (41.5%; 95% CI 35.6 to 47.4%), osteoporosis (14.1%; 9.9 to 18.2%), malignancy (12.6%; 8.6 to 16.6%), and diabetes (10.4%; 6.7 to 14.0%).   CONCLUSIONS In AAV, renal, otolaryngological and treatment-related (cardiovascular, disease, diabetes, osteoporosis and malignancy) damage increases over time, with around one-third of patients having ≥5 items of damage at a mean of 7 years postdiagnosis.

Question: What is the vasculitis damage index?


A Model-Driven Framework to Develop Personalized Health Monitoring. Both distributed healthcare systems and the Internet of Things (IoT) are currently hot topics. The latter is a new computing paradigm to enable advanced capabilities in engineering various applications, including those for healthcare. For such systems, the core social requirement is the privacy/security of the patient information along with the technical requirements (e.g., energy consumption) and capabilities for adaptability and personalization. Typically, the functionality of the systems is predefined by the patient's data collected using sensor networks along with medical instrumentation; then, the data is transferred through the Internet for treatment and decision-making. Therefore, systems creation is indeed challenging. In this paper, we propose a model-driven framework to develop the IoT-based prototype and its reference architecture for personalized health monitoring (PHM) applications. The framework contains a multi-layered structure with feature-based modeling and feature model transformations at the top and the application software generation at the bottom. We have validated the framework using available tools and developed an experimental PHM to test some aspects of the functionality of the reference architecture in real time. The main contribution of the paper is the development of the model-driven computational framework with emphasis on the synergistic effect of security and energy issues.

Question: What is a model-driven framework?


Telomere measurement by quantitative PCR.. It has long been presumed impossible to measure telomeres in vertebrate DNA by PCR amplification with oligonucleotide primers designed to hybridize to the TTAGGG and CCCTAA repeats, because only primer dimer-derived products are expected. Here we present a primer pair that eliminates this problem, allowing simple and rapid measurement of telomeres in a closed tube, fluorescence-based assay. This assay will facilitate investigations of the biology of telomeres and the roles they play in the molecular pathophysiology of diseases and aging.

Question: What is the role of telomeres in the molecular pathophysiology of diseases and aging?


Balancing minimum spanning trees and shortest-path trees. We give a simple algorithm to find a spanning tree that simultaneously approximates a shortest-path tree and a minimum spanning tree. The algorithm provides a continuous tradeoff: given the two trees and aγ>0, the algorithm returns a spanning tree in which the distance between any vertex and the root of the shortest-path tree is at most 1+√2γ times the shortest-path distance, and yet the total weight of the tree is at most 1+√2/γ times the weight of a minimum spanning tree. Our algorithm runs in linear time and obtains the best-possible tradeoff. It can be implemented on a CREW PRAM to run a logarithmic time using one processor per vertex.

Question: What is a CREW PRAM?


PESTO: Parameter EStimation TOolbox. Summary PESTO is a widely applicable and highly customizable toolbox for parameter estimation in MathWorks MATLAB. It offers scalable algorithms for optimization, uncertainty and identifiability analysis, which work in a very generic manner, treating the objective function as a black box. Hence, PESTO can be used for any parameter estimation problem, for which the user can provide a deterministic objective function in MATLAB.   Availability and implementation PESTO is a MATLAB toolbox, freely available under the BSD license. The source code, along with extensive documentation and example code, can be downloaded from https://github.com/ICB-DCM/PESTO/.   Contact jan.hasenauer@helmholtz-muenchen.de.   Supplementary information Supplementary data are available at Bioinformatics online.

Question: What is the source code for PESTO?


Collaborative Filtering with Graph Information: Consistency and Scalable Methods. Low rank matrix completion plays a fundamental role in collaborative filtering applications, the key idea being that the variables lie in a smaller subspace than the ambient space. Often, additional information about the variables is known, and it is reasonable to assume that incorporating this information will lead to better predictions. We tackle the problem of matrix completion when pairwise relationships among variables are known, via a graph. We formulate and derive a highly efficient, conjugate gradient based alternating minimization scheme that solves optimizations with over 55 million observations up to 2 orders of magnitude faster than state-of-the-art (stochastic) gradient-descent based methods. On the theoretical front, we show that such methods generalize weighted nuclear norm formulations, and derive statistical consistency guarantees. We validate our results on both real and synthetic datasets.

Question: What is the difference between a nuclear norm and a weighted nuclear norm?


Image Super-Resolution Using Very Deep Residual Channel Attention Networks. Convolutional neural network (CNN) depth is of crucial importance for image super-resolution (SR). However, we observe that deeper networks for image SR are more difficult to train. The lowresolution inputs and features contain abundant low-frequency information, which is treated equally across channels, hence hindering the representational ability of CNNs. To solve these problems, we propose the very deep residual channel attention networks (RCAN). Specifically, we propose a residual in residual (RIR) structure to form very deep network, which consists of several residual groups with long skip connections. Each residual group contains some residual blocks with short skip connections. Meanwhile, RIR allows abundant low-frequency information to be bypassed through multiple skip connections, making the main network focus on learning high-frequency information. Furthermore, we propose a channel attention mechanism to adaptively rescale channel-wise features by considering interdependencies among channels. Extensive experiments show that our RCAN achieves better accuracy and visual improvements against state-of-the-art methods.

Question: How to train a very deep network for image super-resolution?


ProgTest: An environment for the submission and evaluation of programming assignments based on testing activities. Programming foundations is not an easy subject to be taught — many students have difficulties understanding the abstract concepts of programming and have a wrong view about the programming activity. In order to address these problems, experiences have suggested the integrated teaching of programming concepts and software testing in introductory CS courses. Shortly, the idea is that testing can contribute to enhance the students' capabilities of understanding and analysis. However, such perspective requires tools to provide an adequate feedback to evaluate the students' performance concerning programming and testing activities. In this paper we describe ProgTest — a web-based tool for the submission and automatic evaluation of practical programming assignments based on testing activities. Results from a preliminary validation of ProgTest are also presented. Such results provide evidences on the practical use of ProgTest as a supporting mechanism for the integrated teaching of programming foundations and software testing.

Question: What is a web-based tool for the submission and automatic evaluation of practical programming assignments based on testing activities?


Empirical Evaluation of User Experience in two Adaptive Mobile Application Prototypes. Today's applications such as ubiquitous systems are more and more aware of user's habits and the context of use. The features of products and the context of use will affect the human's experiences and preferences about the use of device. Thus, user experience in user-product interaction has been regarded as an important research topic in the mobile application design area. The purpose of this paper is to clarify how user experience can be evaluated in adaptive mobile applications. The user experience evaluations were performed through interviews and observation while test users were using PDA-based adaptive mobile application prototypes. As a result, this paper presents the analysis of the test methods for further user experience evaluations. CR Categories: J.m [Computer Applications]: Miscellaneous; Experimentation; Human Factors

Question: How can we evaluate user experience in adaptive mobile applications?


Accurate Scale Estimation for Robust Visual Tracking. Robust scale estimation is a challenging problem in visual object tracking. Most existing methods fail to handle large scale variations in complex image sequences. This paper presents a novel approach for robust scale estimation in a tracking-by-detection framework. The proposed approach works by learning discriminative correlation filters based on a scale pyramid representation. We learn separate filters for translation and scale estimation, and show that this improves the performance compared to an exhaustive scale search. Our scale estimation approach is generic as it can be incorporated into any tracking method with no inherent scale estimation. Experiments are performed on 28 benchmark sequences with significant scale variations. Our results show that the proposed approach significantly improves the performance by 18.8% in median distance precision compared to our baseline. Finally, we provide both quantitative and qualitative comparison of our approach with state-of-theart trackers in literature. The proposed method is shown to outperform the best existing tracker by 16.6% in median distance precision, while operating at real-time.

Question: How accurate is the scale estimation?


Containerization and the PaaS Cloud. Containerization is widely discussed as a lightweight virtualization solution. Apart from exhibiting benefits over traditional virtual machines in the cloud, containers are especially relevant for platform-as-a-service (PaaS) clouds to manage and orchestrate applications through containers as an application packaging mechanism. This article discusses the requirements that arise from having to facilitate applications through distributed multicloud platforms.

Question: What is containerization?


From the Test Benches to the First Prototype of the muFly Micro Helicopter. The goal of the European project muFly is to build a fully autonomous micro helicopter, which is comparable to a small bird in size and mass. The rigorous size and mass constraints infer various problems related to energy efficiency, flight stability and overall system design. In this research, aerodynamics and flight dynamics are investigated experimentally to gather information for the design of the helicopter's propulsion group and steering system. Several test benches are designed and built for these investigations. A coaxial rotor test bench is used to measure the thrust and drag torque of different rotor blade designs. The effects of cyclic pitching of the swash plate and the passive stabilizer bar are studied on a test bench measuring rotor forces and moments with a 6–axis force sensor. The gathered knowledge is used to design a first prototype of the muFly helicopter. The prototype is described in terms of rotor configuration, structure, actuator and sensor selection according to the project demands, and a first version of the helicopter is shown. As a safety measure for the flight tests and to analyze the helicopter dynamics, a 6DoF vehicle test bench for tethered helicopter flight is used.

Question: What is the first prototype of the muFly helicopter?


A Tagged Corpus and a Tagger for Urdu. In this paper, we describe a release of a sizeable monolingual Urdu corpus automatically tagged with part-of-speech tags. We extend the work of Jawaid and Bojar (2012) who use three different taggers and then apply a voting scheme to disambiguate among the different choices suggested by each tagger. We run this complex ensemble on a large monolingual corpus and release the tagged corpus. Additionally, we use this data to train a single standalone tagger which will hopefully significantly simplify Urdu processing. The standalone tagger obtains the accuracy of 88.74% on test data.

Question: What is a tagger?


Dyslexia in English as a second language.. This study focused on English as L2 in a group of Norwegian dyslexic 12 year olds, compared to an age and gender matched control group. Norwegian school children learn English from the first grades on. The subjects were assessed with a test battery of verbal and written tasks. First, they were given a comprehension task; second, a model sentence task; third, two pragmatic tasks, and fourth, three tasks of literacy. The verbal tasks were scored according to comprehension, morphology, syntax and semantics, while the literacy tasks were scored by spelling, translation and reading skills. It was hypothesized that the results of the control group and the dyslexia group would differ on all tasks, but that subgrouping the dyslexia group by comprehension skills would show heterogeneity within the dyslexia group. The data analyses confirmed these hypotheses. Significant differences were seen between the dyslexia group and the control group. However, the subgrouping revealed minor differences between the control group and the subgroup with good comprehension skills, and major differences between the control group and the subgroup with poor comprehension skills. Especially morphology and spelling were difficult for the dyslexia group. The results were tentatively discussed within the framework of biological and cognitive models of how to interpret L2 performance in dyslexia, underlining the importance of further research in L2 acquisition in dyslexia.

Question: What is the difference between the control group and the dyslexia group?


On-line Fault Detection of Sensor Measurements. On-line fault detection in sensor networks is of paramount importance due to the convergence of a variety of challenging technological, application, conceptual, and safety related factors. We introduce a taxonomy for classi£cation of faults in sensor networks and the £rst on-line model-based testing technique. The approach is generic in the sense that it can be applied on an arbitrary system of heterogeneous sensors with an arbitrary type of fault model, while it provides a ¤exible tradeoff between accuracy and latency. The key idea is to formulate on-line testing as a set of instances of a non-linear function minimization and consequently apply nonparametric statistical methods to identify the sensors that have the highest probability to be faulty. The optimization is conducted using the Powell nonlinear function minimization method. The effectiveness of the approach is evaluated in the presence of random noise using a system of light sensors.

Question: How to detect faults in sensor networks?


Teleoperation control of Baxter robot using body motion tracking. In this paper, we use Kinect Xbox 360 sensor to implement the motion control of Baxter robot, a semi humanoid robot with limbs of 7 DOF joints with collision avoidance capabilities. Two different methods using vector approach and inverse kinematics approach have been designed to achieve a given task. Primitive experiments have been carried out to verify the effectiveness of the developed methods. Human motions is captured by Kinect sensor and calculated with Processing Software using SimpleOpenNI wrapper for OpenNI and NITE. UDP protocol is adopted to send reference motion to Baxter robot. Python and RosPy script programming kit is used to calculate joint angles of Baxter robot based on vector approach and inverse kinematics approach. The experimental results demonstrate that both of our proposed approaches have achieved satisfactory performance.

Question: How to control a robot using body motion tracking?


Cold-Start Recommendation with Provable Guarantees: A Decoupled Approach. Although the matrix completion paradigm provides an appealing solution to the collaborative filtering problem in recommendation systems, some major issues, such as data sparsity and cold-start problems, still remain open. In particular, when the rating data for a subset of users or items is entirely missing, commonly known as the  cold-start problem, the standard matrix completion methods are inapplicable due the non-uniform sampling of available ratings. In recent years, there has been considerable interest in dealing with cold-start users or items that are principally based on the idea of exploiting other sources of information to compensate for this lack of rating data. In this paper, we propose a novel and general algorithmic framework based on matrix completion that simultaneously exploits the similarity information among users and items to alleviate the cold-start problem. In contrast to existing methods, our proposed recommender algorithm, dubbed DecRec, decouples the following two aspects of the cold-start problem to effectively exploit the side information: (i) the completion of a rating sub-matrix, which is generated by excluding cold-start users/items from the original rating matrix; and (ii) the transduction of knowledge from existing ratings to cold-start items/users using side information. This crucial difference prevents the error propagation of completion and transduction, and also significantly boosts the performance when appropriate side information is incorporated. The recovery error of the proposed algorithm is analyzed theoretically and, to the best of our knowledge, this is the first algorithm that addresses the cold-start problem with provable guarantees on performance. Additionally, we also address the problem where both cold-start user and item challenges are present simultaneously. We conduct thorough experiments on real datasets that complement our theoretical result

Question: What is the cold-start problem?


Apposcopy: semantics-based detection of Android malware through static analysis. We present Apposcopy, a new semantics-based approach for identifying a prevalent class of Android malware that steals private user information. Apposcopy incorporates (i) a high-level language for specifying signatures that describe semantic characteristics of malware families and (ii) a static analysis for deciding if a given application matches a malware signature. The signature matching algorithm of Apposcopy uses a combination of static taint analysis and a new form of program representation called Inter-Component Call Graph to efficiently detect Android applications that have certain control- and data-flow properties. We have evaluated Apposcopy on a corpus of real-world Android applications and show that it can effectively and reliably pinpoint malicious applications that belong to certain malware families.

Question: What is a semantics-based approach for detecting Android malware?


Mining Roles with Multiple Objectives. With the growing adoption of Role-Based Access Control (RBAC) in commercial security and identity management products, how to facilitate the process of migrating a non-RBAC system to an RBAC system has become a problem with significant business impact. Researchers have proposed to use data mining techniques to discover roles to complement the costly top-down approaches for RBAC system construction. An important problem is how to construct RBAC systems with low complexity. In this article, we define the notion of weighted structural complexity measure and propose a role mining algorithm that mines RBAC systems with low structural complexity. Another key problem that has not been adequately addressed by existing role mining approaches is how to discover roles with semantic meanings. In this article, we study the problem in two primary settings with different information availability. When the only information is user-permission relation, we propose to discover roles whose semantic meaning is based on formal concept lattices. We argue that the theory of formal concept analysis provides a solid theoretical foundation for mining roles from a user-permission relation. When user-attribute information is also available, we propose to create roles that can be explained by expressions of user-attributes. Since an expression of attributes describes a real-world concept, the corresponding role represents a real-world concept as well. Furthermore, the algorithms we propose balance the semantic guarantee of roles with system complexity. Finally, we indicate how to create a hybrid approach combining top-down candidate roles. Our experimental results demonstrate the effectiveness of our approaches.

Question: How to construct RBAC systems with low complexity?


Development of humanoid robot HRP-3P. A development of humanoid robot HRP-3P, which is a humanoid robot HRP-3 prototype, is presented in this paper. HRP-3 is under development as the succession humanoid to HRP-2, which we developed in phase two of HRP (humanoid robotics project). One of futures of HRP-3P is that its main mechanical and structural components are designed for protection against dust and water. Another is that node controllers are developed for realization of distributed control system. Real-time communication on Ethernet is also newly developed for communication between main controller and node controllers. In this paper, mechanical features and electrical features are presented with specifications of HRP-3P

Question: What is the main mechanical and structural components of HRP-3P?


Comparison of orthodontic treatment outcomes in adults with skeletal open bite between conventional edgewise treatment and implant-anchored orthodontics.. INTRODUCTION Open bites are known to be difficult malocclusions to treat. Generally, with conventional edgewise treatment, incisor extrusion rather than molar intrusion is observed. Recently, the use of miniscrews as anchorage has markedly increased. In this study, orthodontic treatment outcomes after conventional edgewise treatment and implant-anchored treatment were investigated by cephalometric analysis and several occlusal indexes. In addition, the stability of these patients 2 years after the retention phase was also analyzed.   METHODS Thirty adults (15 for nonimplant treatment [non-IA group] and 15 for implant-anchored treatment [IA group]) were our subjects. Cephalometric analysis, peer assessment rating, discrepancy index, and objective grading system were used.   RESULTS From the cephalometric values in the non-IA group, open-bite patients were generally treated by extrusion of the maxillary and mandibular incisors that resulted in clockwise rotation of the mandibular plane angle. In the IA group, intrusion of the maxillary and mandibular molars that resulted in counterclockwise rotation was noted. Furthermore, in the IA group, the soft-tissue analysis showed decreases in the facial convexity and the inferior labial sulcus angle that resulted in the disappearance of incompetent lips. In the retention phase, extrusion of the mandibular molars was observed in the IA group. From the objective grading system evaluation, significant reductions of overbite in canines and premolars were observed in both groups. Furthermore, less stability was observed in the IA group compared with the non-IA group according to the total objective grading system score.   CONCLUSIONS Ideal occlusion can be achieved in adults with severe open bite with both conventional edgewise and implant-anchored orthodontic treatment. However,

Question: What is the difference between conventional edgewise treatment and implant-anchored orthodontic treatment?


Distributional Clustering of English Words. We describe and experimentally evaluate a method for automatically clustering words according to their distribution in particular syntactic contexts. Deterministic annealing is used to find lowest distortion sets of clusters. As the annealing parameter increases, existing clusters become unstable and subdivide, yielding a hierarchical "soft" clustering of the data. Clusters are used as the basis for class models of word coocurrence, and the models evaluated with respect to held-out test data.

Question: How to cluster words?


DCFont: an end-to-end deep chinese font generation system. Building a complete personalized Chinese font library for an ordinary person is a tough task due to the existence of huge amounts of characters with complicated structures. Yet, existing automatic font generation methods still have many drawbacks. To address the problem, this paper proposes an end-to-end learning system, DCFont, to automatically generate the whole GB2312 font library that consists of 6763 Chinese characters from a small number (e.g., 775) of characters written by the user. Our system has two major advantages. On the one hand, the system works in an end-to-end manner, which means that human interventions during offline training and online generating periods are not required. On the other hand, a novel deep neural network architecture is designed to solve the font feature reconstruction and handwriting synthesis problems through adversarial training, which requires fewer input data but obtains more realistic and high-quality synthesis results compared to other deep learning based approaches. Experimental results verify the superiority of our method against the state of the art.

Question: How to generate a font library?


Excipient-drug interactions in parenteral formulations.. Excipients are added to parenteral formulations to enhance or maintain active ingredient solubility (solubilizers) and/or stability (buffers, antioxidants, chelating agents, cryo- and lyoprotectants). Excipients also are important in parenteral formulations to assure safety (antimicrobial preservatives), minimize pain and irritation upon injection (tonicity agents), and control or prolong drug delivery (polymers). These are all examples of positive or synergistic interactions between excipients and drugs. However, excipients may also produce negative effects such as loss of drug solubility, activity, and/or stability. This review article will highlight documented interactions, both synergistic and antagonistic, between excipients and drugs in parenteral formulations. The reader will gain better understanding and appreciation of the implications of adding formulation ingredients to parenteral drug products.

Question: What is the difference between a synergistic and an antagonistic interaction?


Convolution Kernels on Discrete Structures. We introduce a new method of constructing kernels on sets whose elements are discrete structures like strings, trees and graphs. The method can be applied iteratively to build a kernel on a innnite set from kernels involving generators of the set. The family of kernels generated generalizes the family of radial basis kernels. It can also be used to deene kernels in the form of joint Gibbs probability distributions. Kernels can be built from hidden Markov random elds, generalized regular expressions, pair-HMMs, or ANOVA de-compositions. Uses of the method lead to open problems involving the theory of innnitely divisible positive deenite functions. Fundamentals of this theory and the theory of reproducing kernel Hilbert spaces are reviewed and applied in establishing the validity of the method.

Question: What is a kernel?


Sampled-Point Network for Classification of Deformed Building Element Point Clouds. Search-and-rescue (SAR) robots operating in post-disaster urban areas need to accurately identify physical site information to perform navigation, mapping and manipulation tasks. This can be achieved by acquiring a 3D point cloud of the environment and performing object recognition from the point cloud data. However, this task is complicated by the unstructured environments and potentially-deformed objects encountered during disaster relief operations. Current 3D object recognition methods rely on point cloud input acquired under suitable conditions and do not consider deformations such as outlier noise, bending and truncation. This work introduces a deep learning architecture for 3D class recognition from point clouds of deformed building elements. The classification network, consisting of stacked convolution and average pooling layers applied directly to point coordinates, was trained using point clouds sampled from a database of mesh models. The proposed method achieves robustness to input variability using point sorting, resampling, and rotation normalization techniques. Experimental results on synthetically-deformed object datasets show that the proposed method outperforms the conventional deep learning methods in terms of classification accuracy and computational efficiency.

Question: What is a deep learning architecture for 3D class recognition from point clouds of deformed building elements?


Thoth: Comprehensive Policy Compliance in Data Retrieval Systems. Data retrieval systems process data from many sources, each subject to its own data use policy. Ensuring compliance with these policies despite bugs, misconfiguration, or operator error in a large, complex, and fast evolving system is a major challenge. Thoth provides an efficient, kernel-level compliance layer for data use policies. Declarative policies are attached to the systems' input and output files, key-value tuples, and network connections, and specify the data's integrity and confidentiality requirements. Thoth tracks the flow of data through the system, and enforces policy regardless of bugs, misconfigurations, compromises in application code, or actions by unprivileged operators. Thoth requires minimal changes to an existing system and has modest overhead, as we show using a prototype Thoth-enabled data retrieval system based on the popular Apache Lucene.

Question: What is the name of the data retrieval system?


Protocol Oblivious Forwarding (POF): Software-Defined Networking with Enhanced Programmability. Software-defined networking separates the control and forwarding planes of a network to make it more programmable and application- aware. As one of the initial implementations of SDN, OpenFlow abstracts a forwarding device as a flow table and realizes flow processing by applying the "match-and-act" principle. However, the protocol-dependent nature of OpenFlow still limits the programmability of the forwarding plane. Hence, in this article, we discuss how to leverage protocol-oblivious forwarding (POF) to further enhance the network programmability such that the forwarding plane becomes protocol-independent and can be dynamically reprogrammed to support new protocol stacks seamlessly. We first review the development of OpenFlow and explain the motivations for introducing POF. Then we explain the working principle of POF, discuss our efforts on realizing the POF development ecosystem, and show our implementation of POF-based source routing as a novel use case. Finally, we elaborate on the first WAN-based POF network testbed that includes POF switches located in two cities in China.

Question: What is protocol-oblivious forwarding?


ECG to identify individuals. The electrocardiogram (ECG also called EKG) trace expresses cardiac features that are unique to an individual. The ECG processing followed a logical series of experiments with quantifiable metrics. Data filters were designed based upon the observed noise sources. Fiducial points were identified on the filtered data and extracted digitally for each heartbeat. From the fiducial points, stable features were computed that characterize the uniqueness of an individual. The tests show that the extracted features are independent of sensor location, invariant to the individual's state of anxiety, and unique to an individual. 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Question: How to identify individuals?


Looking good: factors affecting the likelihood of having cosmetic surgery. The present study examined various factors associated with the likelihood of having cosmetic surgery in a community sample of Austrian participants. One-hundred and sixty-eight women and 151 men completed a questionnaire measuring how likely they were to consider common cosmetic procedures. The results showed that women were more likely than men to consider most cosmetic procedures. Path analysis revealed that personal experience of having had cosmetic surgery was a significant predictor of future likelihood, while media exposure (viewing advertisements or television programs, or reading articles about cosmetic surgery) mediated the influence of vicarious experience and sex. These results are discussed in relation to previous work examining the factors associated with the likelihood of having cosmetic surgery.

Question: What factors are associated with the likelihood of having cosmetic surgery?


A 45nm 4Gb 3-Dimensional Double-Stacked Multi-Level NAND Flash Memory with Shared Bitline Structure. Recently, 3-dimensional (3D) memories have regained attention as a potential future memory solution featuring low cost, high density and high performance. We present a 3D double stacked 4Gb MLC NAND flash memory device with shared bitline structure, with a cell size of 0.0021mum2/bit per unit feature area. The device is designed to support 3D stacking and fabricated by S3 and 45nm floating-gate CMOS technologies.

Question: What is the size of a memory cell?


Sexual harassment on the internet. Sexual harassment offline is a well-known, highly prevalent, extensively investigated, and intensively treated social problem. An accepted model classifies sexual harassment behaviors into the categories of gender harassment, unwanted sexual attention, and sexual coercion. Theory and research show that sexual harassment behavior occurs as a product of person × situation characteristics and has substantial personal and organizational costs. This article reviews the available information on sexual harassment in cyberspace, equates this phenomenon with what has been learned about sexual harassment offline, points to specific characteristics of online culture and technology that reinforce the behavior, and proposes ways of promoting prevention.

Question: What is sexual harassment?


PyDial: A Multi-domain Statistical Dialogue System Toolkit. Statistical Spoken Dialogue Systems have been around for many years. However, access to these systems has always been difficult as there is still no publicly available end-to-end system implementation. To alleviate this, we present PyDial, an opensource end-to-end statistical spoken dialogue system toolkit which provides implementations of statistical approaches for all dialogue system modules. Moreover, it has been extended to provide multidomain conversational functionality. It offers easy configuration, easy extensibility, and domain-independent implementations of the respective dialogue system modules. The toolkit is available for download under the Apache 2.0 license.

Question: What is a statistical spoken dialogue system?


Spatial Diversity 24-GHz FMCW Radar With Ground Effect Compensation for Automotive Applications. In automotive radar applications, a realistic road surface can cause multipath reflection, degrade the received power, and reduce detection probability. This paper proposes a one-transmitter–two-receiver (1T2R) 24-GHz frequency-modulation continuous-wave (FMCW) radar architecture with spatial diversity and ground effect compensation for automotive applications. A ray-tracing technique was developed to evaluate the multipath effect of the road surface. In the proposed design, suitable spacing between the two receiving antennas compensated for the multipath effect of the road surface and improved the signal-to-ground clutter ratio of the receivers by a minimum of 20 dB at certain distances. The measurement and calculation results of the proposed radar are in close agreement.

Question: What is the minimum distance between two receiving antennas?


On path planning methods for automotive collision avoidance. There is a strong trend for increasingly sophisticated Advanced Driver Assistance Systems (ADAS) such as Autonomous Emergency Braking (AEB) systems, Lane Keeping Aid (LKA) systems, and indeed autonomous driving. This trend generates a need for online maneuver generation, for which numerous approaches can be found in the large body of work related to path planning and obstacle avoidance. In order to ease the challenge of choosing a method, this paper reports quantitative and qualitative insights about three different path planning methods: a state lattice planner, predictive constraint-based planning, and spline-based search tree. Each method is described, implemented and compared on two specific traffic situations. The paper will not provide a final answer about which method is best. This depends on several factors such as computational constraints and the formulation of maneuver optimality that is appropriate for a given assistance or safety function. Instead, the conclusions will highlight qualitative merits and drawbacks for each method, in order to provide guidance for choosing a method for a specific application.

Question: What is the difference between a state lattice planner, predictive constraint-based planning, and spline-based search tree?


Multiparty Computation from Somewhat Homomorphic Encryption. We propose a general multiparty computation protocol secure against an active adversary corrupting up to n−1 of the n players. The protocol may be used to compute securely arithmetic circuits over any finite field Fpk . Our protocol consists of a preprocessing phase that is both independent of the function to be computed and of the inputs, and a much more efficient online phase where the actual computation takes place. The online phase is unconditionally secure and has total computational (and communication) complexity linear in n, the number of players, where earlier work was quadratic in n. Moreover, the work done by each player is only a small constant factor larger than what one would need to compute the circuit in the clear. We show this is optimal for computation in large fields. In practice, for 3 players, a secure 64-bit multiplication can be done in 0.05 ms. Our preprocessing is based on a somewhat homomorphic cryptosystem. We extend a scheme by Brakerski et al., so that we can perform distributed decryption and handle many values in parallel in one ciphertext. The computational complexity of our preprocessing phase is dominated by the public-key operations, we need O(n/s) operations per secure multiplication where s is a parameter that increases with the security parameter of the cryptosystem. Earlier work in this model needed Ω(n) operations. In practice, the preprocessing prepares a secure 64-bit multiplication for 3 players in about 13 ms.

Question: What is the computational complexity of a secure multiplication?


[Translation and validation for Brazil of the body image scale for adolescents--Offer Self-Image Questionnaire (OSIQ)].. OBJECTIVE To evaluate the semantic and measure equivalence of the body image sub-scale of the Offer Self Image Questionnaire (OSIQ).   METHODS Participants were 386 teenagers, 10 to 18 years old, both sexes, enrolled in a private school (junior and high school age). Translation, back-translation, technique revision and evaluation were conducted. The Portuguese instrument was evaluated for internal consistency, discriminate and concurrent validity.   RESULTS Internal consistency showed values from 0.43 to 0.54 and was able to discriminate all groups studied--the whole population, boys and girls, and boys in early adolescence, by nutritional status (p<0.001; p<0.009; p=0.030; p=0.043, respectively). Concurrent analyses showed significant correlation with anthropometric measures only for girls (r=-0.16 and p=0.021; r=-0.19 and p=0.007), early adolescence (r=-0.23 and p=0.008; r=-0.26 and p=0.003) and intermediate adolescence (r=-0.29 and p=0.010) and the retest confirmed reliability by the coefficient of interclass correlation. Although the instrument has proven its ability to discriminate between the groups studied by nutritional state, other results were less satisfactory. More studies are necessary for full transcultural adaptation, including the application of other comparative scales.   CONCLUSION The body image sub-scale of the OSIQ was translated, but the results are not promising and require more studies.

Question: What is the body image scale for adolescents?


Audio-visual speech recognition using lip movement extracted from side-face images. This paper proposes an audio-visual speech recognition method using lip movement extracted from side-face images to attempt to increase noise-robustness in mobile environments. Although most previous bimodal speech recognition methods use frontal face (lip) images, these methods are not easy for users since they need to hold a device with a camera in front of their face when talking. Our proposed method capturing lip movement using a small camera installed in a handset is more natural, easy and convenient. This method also effectively avoids a decrease of signal-to-noise ratio (SNR) of input speech. Visual features are extracted by optical-flow analysis and combined with audio features in the framework of HMM-based recognition. Phone HMMs are built by the multi-stream HMM technique. Experiments conducted using Japanese connected digit speech contaminated with white noise in various SNR conditions show effectiveness of the proposed method. Recognition accuracy is improved by using the visual information in all SNR conditions, and the best improvement is approximately 6% at 5dB SNR.

Question: How to extract lip movement from side-face images?


A study on the bending mechanism of the flexible ureteroscope. Flexible ureteroscope is increasingly used for urologic treatment today. The key mechanism of the ureteroscope is the bending mechanism. It consists of a bending head and a control lever connected through a set of wire. The lighting and imaging optics as well as the surgical tools all go through the bending head. With the demand for improved performance and reduced size, more research on its design is still needed. In this paper, the modeling and simulation of an ureteroscope are presented, which pave the road for design optimization in the future.

Question: What is the bending mechanism of the flexible ureteroscope?


The spatial and temporal meanings of English prepositions can be independently impaired. English uses the same prepositions to describe both spatial and temporal relationships (e.g., at the corner, at 1:30), and other languages worldwide exhibit similar patterns. These space-time parallelisms have been explained by the Metaphoric Mapping Theory, which maintains that humans have a cognitive predisposition to structure temporal concepts in terms of spatial schemas through the application of a TIME IS SPACE metaphor. Evidence comes from (among other sources) historical investigations showing that languages consistently develop in such a way that expressions that originally have only spatial meanings are gradually extended to take on analogous temporal meanings. It is not clear, however, if the metaphor actively influences the way that modern adults process prepositional meanings during language use. To explore this question, a series of experiments was conducted with four brain-damaged subjects with left perisylvian lesions. Two subjects exhibited the following dissociation: they failed a test that assesses knowledge of the spatial meanings of prepositions, but passed a test that assesses knowledge of the corresponding temporal meanings of the same prepositions. This result suggests that understanding the temporal meanings of prepositions does not necessarily require establishing structural alignments with their spatial correlates. Two other subjects exhibited the opposite dissociation: they performed better on the spatial test than on the temporal test. Overall, these findings support the view that although the spatial and temporal meanings of prepositions are historically linked by virtue of the TIME IS SPACE metaphor, they can be (and may normally be) represented and processed independently of each other in the brains of modern adults.

Question: What is the difference between the spatial and temporal meanings of prepositions?


The Ant System Applied to the Quadratic Assignment Problem. In recent years there has been growing interest in algorithms inspired by the observation of natural phenomena to define computational procedures which can solve complex problems. In this article we introduce a distributed heuristic algorithm which was inspired by the observation of the behavior of ant colonies and we propose its use for the Quadratic Assignment Problem. Finally the results obtained in solving some classical instances of the problem are compared with those obtained from other evolutionary heuristics to evaluate the quality of the system proposed. ^Dipartimento di Scienze dell'Informazione, Università di Bologna, Via Sacchi 3, 47023, Cesena, Italy, EU, maniezzo@csr.unibo.it & Dipartimento di Elettronica e Informazione, Politecnico di Milano, Via Ponzio 34/5, 20133, Milano, Italy, EU, colorni@elet.polimi.it #IRIDIA, Université Libre de Bruxelles, Av. Franklin Roosevelt 50, CP 194/6, 1050 Brussels, Belgium, EU, mdorigo@ulb.ac.be

Question: What is the quadratic assignment problem?


Automatic Verb Classification Based on Statistical Distributions of Argument Structure. Automatic acquisition of lexical knowledge is critical to a wide range of natural language processing tasks. Especially important is knowledge about verbs, which are the primary source of relational information in a sentence-the predicate-argument structure that relates an action or state to its participants (i.e., who did what to whom). In this work, we report on supervised learning experiments to automatically classify three major types of English verbs, based on their argument structure-specifically, the thematic roles they assign to participants. We use linguistically-motivated statistical indicators extracted from large annotated corpora to train the classifier, achieving 69.8 accuracy for a task whose baseline is 34, and whose expert-based upper bound we calculate at 86.5. A detailed analysis of the performance of the algorithm and of its errors confirms that the proposed features capture properties related to the argument structure of the verbs. Our results validate our hypotheses that knowledge about thematic relations is crucial for verb classification, and that it can be gleaned from a corpus by automatic means. We thus demonstrate an effective combination of deeper linguistic knowledge with the robustness and scalability of statistical techniques.

Question: What is the thematic role of the verb?


A Comparative Study of Polar Code Constructions for the AWGN Channel. We present a comparative study of the performance of various polar code constructions in an additive white Gaussian noise (AWGN) channel. A polar code construction is any algorithm that selects K best among N possible polar bit-channels at the design signal-to-noise-ratio (design-SNR) in terms of bit error rate (BER). Optimal polar code construction is hard and therefore many suboptimal polar code constructions have been proposed at different computational complexities. Polar codes are also non-universal meaning the code changes significantly with the design-SNR. However, it is not known which construction algorithm at what design-SNR constructs the best polar codes. We first present a comprehensive survey of all the well-known polar code constructions along with their full implementations. We then propose a heuristic algorithm to find the best design-SNR for constructing best possible polar codes from a given construction algorithm. The proposed algorithm involves a search among several possible design-SNRs. We finally use our algorithm to perform a comparison of different construction algorithms using extensive simulations. We find that all polar code construction algorithms generate equally good polar codes in an AWGN channel, if the design-SNR is optimized. Keywords—Bhattacharyya bounds, bit-channels, Gaussian approximation, polar codes

Question: What is the best polar code construction algorithm?


Supervised Word Sense Disambiguation using Python. In this paper, we discuss the problem of Word Sense Disambigu ation (WSD) and one approach to solving the lexical sample problem. We use training and te st data fromSENSEVAL-3 and implement methods based on Naı̈ve Bayes calculations, cosi ne comparison of word-frequency vectors, decision lists, and Latent Semantic Analysis. We a lso implement a simple classifier combination system that combines these classifiers into one WSD module. We then prove the effectiveness of our WSD module by participating in the M ultilingual Chinese-English Lexical Sample Task from SemEval-2007.

Question: What is the problem of word sense disambiguation?


Model-based dynamic gait generation for a leg-wheel transformable robot. We report on the model-based approach to dynamic trotting and pronking gait generation for a leg-wheel transformable robot. The rolling spring-loaded inverted pendulum (R-SLIP) model served as the template for robot locomotion by programming the robot's motion according to the stable fixed-point trajectories of the model. Two strategies are developed to match the robot leg motions to the virtual model leg: First, using the two active degrees of freedom on each leg to simulate the passive spring effect of the R-SLIP model leg. Second, installing a torsion spring on the leg-wheel module to render the leg-wheel morphology identical to that of the model leg. This model-based approach to dynamic behavior generation for the robot is experimentally evaluated. The robot can successfully generate an R-SLIP-like stable pronking gait with a flight phase.

Question: How to generate a stable pronking gait for a leg-wheel transformable robot?


Internet of Things Approach for Automation of the Complex Industrial Systems. This paper presents the analysis of the Internet of Things (IoT) approach and its application for the development of embedded monitoring and automatic control systems (EMACS) for technological objects and processes that are included in complex industrial systems. The functional structure and main components of EMACS based on IoT approach are given. The examples of IoT applications in design of specialized EMACS for such complex technical objects as gas turbine engines and floating docks are presented. Considerable attention is given to particular qualities of the functional structures, software and hardware implementation as well as multi-level human-machine interfaces of the EMACS for main process parameters. The developed EMACS provide: (a) high precision control of real-time operating processes of gas turbine engines and floating docks, (b) monitoring and automatic control of current technological parameters with high quality indicators, that leads to significant increasing of energy and economic efficiency of both industrial objects.

Question: What is the Internet of Things?


Deep Reinforcement Learning framework for Autonomous Driving. Reinforcement learning is considered to be a strong AI paradigm which can be used to teach machines through interaction with the environment and learning from their mistakes. Despite its perceived utility, it has not yet been successfully applied in automotive applications. Motivated by the successful demonstrations of learning of Atari games and Go by Google DeepMind, we propose a framework for autonomous driving using deep reinforcement learning. This is of particular relevance as it is difficult to pose autonomous driving as a supervised learning problem due to strong interactions with the environment including other vehicles, pedestrians and roadworks. As it is a relatively new area of research for autonomous driving, we provide a short overview of deep reinforcement learning and then describe our proposed framework. It incorporates Recurrent Neural Networks for information integration, enabling the car to handle partially observable scenarios. It also integrates the recent work on attention models to focus on relevant information, thereby reducing the computational complexity for deployment on embedded hardware. The framework was tested in an open source 3D car racing simulator called TORCS. Our simulation results demonstrate learning of autonomous maneuvering in a scenario of complex road curvatures and simple interaction of other vehicles. INTRODUCTION A robot car that drives autonomously is a long-standing goal of Artificial Intelligence. Driving a vehicle is a task that requires high level of skill, attention and experience from a human driver. Although computers are more capable of sustained attention and focus than humans, fully autonomous driving requires a level of intelligence that surpasses that achieved so far by AI agents. The tasks involved in creating an autonomous driving agent can be divided into 3 categories, as shown in Figure 1: 1) Recognition: Identifying components of the surroun

Question: What is the difference between reinforcement learning and supervised learning?


Fast Marine Route Planning for UAV Using Improved Sparse A* Algorithm. This paper focuses on route planning, especially for unmanned aircrafts in marine environment. Firstly, new heuristic information is adopted such as threat-zone, turn maneuver and forbid-zone based on voyage heuristic information. Then, the cost function is normalized to obtain more flexible and reasonable routes. Finally, an improved sparse A* search algorithm is employed to enhance the planning efficiency and reduce the planning time. Experiment results showed that the improved algorithm for aircraft in maritime environment could find a combinational optimum route quickly, which detoured threat-zones, with fewer turn maneuver, totally avoiding forbid-zones, and shorter voyage.

Question: What is the fast marine route planning for unmanned aircrafts?


Byzantine Fault Tolerance, from Theory to Reality. Since its introduction nearly 20 years ago, the Byzantine Generals Problem has been the subject of many papers having the scrutiny of the fault tolerance community. Numerous Byzantine tolerant algorithms and architectures have been proposed. However, this problem is not yet sufficiently understood by those who design, build, and maintain systems with high dependability requirements. Today, there are still many misconceptions relating to Byzantine failure, what makes a system vulnerable, and indeed the very nature and reality of Byzantine faults. This paper revisits the Byzantine problem from a practitioner's perspective. It has the intention to provide the reader with a working appreciation of the Byzantine failure from a practical as well as a theoretical perspective. A discussion of typical failure properties and the difficulties in preventing the associated failure propagation is presented. These are illustrated with real Byzantine failure observations. Finally, various architectural solutions to the Byzantine problem are presented. 1 What You Thought Could Never Happen In English, the phrase "one in a million" is popularly used to describe the highly improbable. The ratio itself is difficult to comprehend. The easiest way to give it reason is to equate it to real-world expectations. For example, the probability of winning the U.K. National Lottery is around one in fourteen million; the probability of getting struck by lightning in the U.S. is around one in six hundred thousand [1]. It is not safe to rely on intuition for reasoning about unfathomably small probabilities (for example, the 1-in-1,000,000,000 maximum failure probability for critical aerospace systems1). It is problematic in two ways: (1) real-world parallels are beyond typical human experience and comprehension; (2) faults that are not recognized, such as Byzantine faults, are incorrectly assumed to occur with zero or very low probability. The lack

Question: What is the probability of getting struck by lightning in the U.S.?


Salt resistance genes revealed by functional metagenomics from brines and moderate-salinity rhizosphere within a hypersaline environment. Hypersaline environments are considered one of the most extreme habitats on earth and microorganisms have developed diverse molecular mechanisms of adaptation to withstand these conditions. The present study was aimed at identifying novel genes from the microbial communities of a moderate-salinity rhizosphere and brine from the Es Trenc saltern (Mallorca, Spain), which could confer increased salt resistance to Escherichia coli. The microbial diversity assessed by pyrosequencing of 16S rRNA gene libraries revealed the presence of communities that are typical in such environments and the remarkable presence of three bacterial groups never revealed as major components of salt brines. Metagenomic libraries from brine and rhizosphere samples, were transferred to the osmosensitive strain E. coli MKH13, and screened for salt resistance. Eleven genes that conferred salt resistance were identified, some encoding for well-known proteins previously related to osmoadaptation such as a glycerol transporter and a proton pump, whereas others encoded proteins not previously related to this function in microorganisms such as DNA/RNA helicases, an endonuclease III (Nth) and hypothetical proteins of unknown function. Furthermore, four of the retrieved genes were cloned and expressed in Bacillus subtilis and they also conferred salt resistance to this bacterium, broadening the spectrum of bacterial species in which these genes can function. This is the first report of salt resistance genes recovered from metagenomes of a hypersaline environment.

Question: What is the function of the genes?


Outlier Detection with Kernel Density Functions. Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel unsupervised algorithm for outlier detection with a solid statistical foundation is proposed. First we modify a nonparametric density estimate with a variable kernel to yield a robust local density estimation. Outliers are then detected by comparing the local density of each point to the local density of its neighbors. Our experiments performed on several simulated data sets have demonstrated that the proposed approach can outperform two widely used outlier detection algorithms (LOF and LOCI).

Question: What is a kernel density function?


Nonparametric Bayesian Models for Joint Analysis of Imagery and Text. Nonparametric Bayesian Models for Joint Analysis of Imagery and Text

Question: What is a nonparametric Bayesian model?