Question: Represent this title from a paper to retrieve its scientific short abstract

Question: A Miniaturized Wideband Three-Section Branch-Line Hybrid With Harmonic Suppression Using Coupled Line and Open-Ended Stubs

In this letter, a wideband three-section branch-line hybrid with harmonic suppression is designed using a novel transmission line model. The proposed topology is constructed using a coupled line, two series transmission lines, and open-ended stubs. The required design equations are obtained by applying even- and odd-mode analysis. To support these equations, a three-section branch-line hybrid working at 0.9 GHz is fabricated and tested. The physical area of the prototype is reduced by 87.7% of the conventional hybrid and the fractional bandwidth is greater than 52%. In addition, the proposed technique can eliminate second harmonic by a level better than 15 dB.

This chapter contains sections titled: Introduction Dipole Basic Characteristics Partial Sleeve, PIFA, and Patch Loops Dielectric Resonator Antennas References


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Question: Connecting Devices to Cookies via Filtering, Feature Engineering, and Boosting

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We present a supervised machine learning system capable of matching internet devices to web cookies through filtering, feature engineering, binary classification, and post processing. The system builds a reasonably sized training and testing data set through filtering and feature engineering. We build 415 features in total. Some of these features were engineered to be O(n) time, stand alone classifiers for this problem. Other features use various natural language processing (NLP) techniques. Meta features are created by ridge regression and Adaboost. Then binary classification through two different gradient boosting (XGBoost with logarithmic loss) models is performed. A post processing pipeline connects devices and cookies in a way that maximizes F_0.5 score. Our machine learning system obtained a private F_0.5 score of 0.849562 for a final rank of 12th/340 on the ICDM 2015: Drawbridge Cross-Device Connections challenge.

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Getting Started Creating and Building a Database Building Up Your Command Library Creating Reports and Labels Variables Writing Simple Programs and Beyond Writing Simple Programs Writing Menu Programs Additional Functions and Commands Advanced Applications Putting It All Together Appendixes Index.


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Question: Efficient Bayesian Network Learning for System Optimization in Reliability Engineering

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We present a new Bayesian network modeling that learns the behavior of an unknown system from real data and can be used for reliability engineering and optimization processes in industrial systems. The suggested approach relies on quantitative criteria for addressing the trade-off between the complexity of a learned model and its prediction accuracy. These criteria are based on measures from Information Theory as they predetermine both the accuracy as well as the complexity of the model. We illustrate the proposed method by a classical example of system reliability engineering. Using computer experiments, we show how in a targeted Bayesian network learning, a tremendous reduction in the model complexity can be accomplished, while maintaining most of the essential information for optimizing the system.

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Partial table of contents: FUNDAMENTALS. Reliability Physics and Failure Mechanisms. Statistical Distributions. MODELLING. The Load-Strength Concept. Intrinsic Reliability - The Generic Case. Extrinsic Reliability. EVALUATION. Lifetesting. Field Failure Data Analysis. Reliability Prediction of Electronic Equipment. ASSURANCE. Reliability Screening: Burn-in. Reliability Indicator Screening. Appendices. Index.


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Question: Energy-Brushes: Interactive Tools for Illustrating Stylized Elemental Dynamics

Dynamic effects such as waves, splashes, fire, smoke, and explosions are an integral part of stylized animations. However, such dynamics are challenging to produce, as manually sketching key-frames requires significant effort and artistic expertise while physical simulation tools lack sufficient expressiveness and user control. We present an interactive interface for designing these elemental dynamics for animated illustrations. Users draw with coarse-scale energy brushes which serve as control gestures to drive detailed flow particles which represent local velocity fields. These fields can convey both realistic and artistic effects based on user specification. This painting metaphor for creating elemental dynamics simplifies the process, providing artistic control, and preserves the fluidity of sketching. Our system is fast, stable, and intuitive. An initial user evaluation shows that even novice users with no prior animation experience can create intriguing dynamics using our system.

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Images, Windows and Operators. Methodical Fundamentals. Algorithmic Fundamentals. Coordinate Transformations and Geometrical Operators. Gray Scale Transformations and Point Operators. Window Functions and Local Operators. Global Operators. Glossary. Index.


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Question: Analyzing students’ performance using multi-criteria classification

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Education is a key factor for achieving long-term economic progress. During the last decades, higher standards in education have become easier to attain due to the availability of knowledge and resources worldwide. With the emergence of new technology enhanced by using data mining it has become easier to dig into data and extract useful knowledge from data. In this research, we use data analytic techniques applied to real case studies to predict students’ performance using their past academic experience. We introduce a new hybrid classification technique which utilize decision tree and fuzzy multi-criteria classification. The technique is used to predict students’ performance based on several criteria such as age, school, address, family size, evaluation in previous grades, and activities. To check the accuracy of the model, our proposed method is compared with other well-known classifiers. This study on existing student data showed that this method is a promising classification tool.

The MADM method based on incomplete decision alternatives information and incomplete decision alternative categories for preference is researched. By means of casebased reasoning, fuzzy processing is done for incomplete decision-making information; an attribute weight determination model based on incomplete information and incomplete program categories for preference is established through the relative overall off-target distance between programs of the same category and the average overall off-target distance between programs of different categories represented by the grey target decisionmaking theory. The example shows the method is effective


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Question: Recurrent Neural Networks for Online Video Popularity Prediction

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In this paper, we address the problem of popularity prediction of online videos shared in social media. We prove that this challenging task can be approached using recently proposed deep neural network architectures. We cast the popularity prediction problem as a classification task and we aim to solve it using only visual cues extracted from videos. To that end, we propose a new method based on a Long-term Recurrent Convolutional Network (LRCN) that incorporates the sequentiality of the information in the model. Results obtained on a dataset of over 37’000 videos published on Facebook show that using our method leads to over 30% improvement in prediction performance over the traditional shallow approaches and can provide valuable insights for content creators.

Why Data Mining is Important: What is Customer-Centric Data Mining? How Data Mining Can Enhance Your Services and Products Data Mining Can Solve Your Most Difficult Problems The Data Mining Process Pillars of the Data Mining Framework: The Information Technology of Business Intelligence The Data in Data Mining The Mathematics of Data Mining Data Mining Techniques: Knowledge Discovery Data Mining Techniques: More Knowledge Discovery Data Mining Techniques: Predictive Models Data Mining Management: Common Reasons Data Mining Projects Fail Overcoming Obstacles Successful Data Mining Project Management Data Mining in Practice--Case Studies: Data Mining in: Customer Service, Retail, Insurance, Financial Services, Health Care and Medicine, Telecommunications, Transportation and Logistics, Energy, and Government Glossary Bibliography Appendixes: Vendor Information "STAT 101" Techniques Listed by Methodology Phase


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Question: A Personalized Markov Clustering and Deep Learning Approach for Arabic Text Categorization.

Text categorization has become a key research field in the NLP community. However, most works in this area are focused on Western languages ignoring other Semitic languages like Arabic. These languages are of immense political and social importance necessitating robust categorization techniques. In this paper, we present a novel three-stage technique to efficiently classify Arabic documents into different categories based on the words they contain. We leverage the significance of root-words in Arabic and incorporate a combination of Markov clustering and Deep Belief Networks to classify Arabic words into separate groups (clusters). Our approach is tested on two public datasets giving a F-Measure of 91.02%.

A. Filippidis, M. Russo, L.C. Jain: Novel Extension of ART2 in Surface Landmine Detection.- M. Blume: An Efficient Mapping of Fuzzy ART onto a Neural Architecture.- M. Blume, D.A. Van Blerkom: Fuzzy ARTMAP Modifications for Intersecting Class Distributions.- A.-H. Tan: Supervised Adaptive Resonance Theory and Rules.- G. Bartfai, R. White: Incremental Learning and Optimization of Hierarchical Clusterings with ART-Based Modular Networks.- C.P. Lim, R.F. Harrison: ART-Based Autonomous Learning Systems: Part I - Architectures and Algorithms.- C.P. Lim, R.F. Harrison: ART-Based Autonomous Learning Systems: Part II - Applications.- T. Serrano-Gotarredona, B. Linares-Barranco: Adaptive Resonance Theory Microchips.


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Question: Learning Accurate, Compact, And Interpretable Tree Annotation

We present an automatic approach to tree annotation in which basic nonterminal symbols are alternately split and merged to maximize the likelihood of a training treebank. Starting with a simple X-bar grammar, we learn a new grammar whose nonterminals are subsymbols of the original nonterminals. In contrast with previous work, we are able to split various terminals to different degrees, as appropriate to the actual complexity in the data. Our grammars automatically learn the kinds of linguistic distinctions exhibited in previous work on manual tree annotation. On the other hand, our grammars are much more compact and substantially more accurate than previous work on automatic annotation. Despite its simplicity, our best grammar achieves an F1 of 90.2% on the Penn Treebank, higher than fully lexicalized systems.

These invited talks discuss the following: STG Decomposition and Its Correctness; Asynchronous Network-On-Chip and its Potential.


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Question: Tracklet Association by Online Target-Specific Metric Learning and Coherent Dynamics Estimation

In this paper, we present a novel method based on online target-specific metric learning and coherent dynamics estimation for tracklet (track fragment) association by network flow optimization in long-term multi-person tracking. Our proposed framework aims to exploit appearance and motion cues to prevent identity switches during tracking and to recover missed detections. Furthermore, target-specific metrics (appearance cue) and motion dynamics (motion cue) are proposed to be learned and estimated online, i.e., during the tracking process. Our approach is effective even when such cues fail to identify or follow the target due to occlusions or object-to-object interactions. We also propose to learn the weights of these two tracking cues to handle the difficult situations, such as severe occlusions and object-to-object interactions effectively. Our method has been validated on several public datasets and the experimental results show that it outperforms several state-of-the-art tracking methods.

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Question: Properties of Dry and Non-contact Electrodes for Wearable Physiological Sensors

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Dry and non-contact electrodes are an important part of building user-friendly wearable body sensor networks for physiological (ECG, EEG, EMG) recording. This paper presents the theory and characterization of several inexpensive and non-irritating electrode materials that implement dry and non-contact sensors, including lead-free PCB solder finish, latex, cotton, silver cloth and solder mask. The noise spectra of the electrodes were measured on a live subject to fully mode all the effects of biological and chemical noise processes at the skin- electrode interface. In addition, exemplary ECG physiological measurements are also presented and compared against the signal from reference clinical wet Ag/AgCl electrodes. Results show that PCB finish can function as a general purpose, low-noise dry electrode. Latex and solder mask also work well as insulated electrodes.

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Biomaterials * Optical Components * Construction Materials * Nuclear Waste Containment * Ceramic Superconductors * Archeologically Significant Articles.


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Question: Highway long short-term memory RNNS for distant speech recognition

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In this paper, we extend the deep long short-term memory (DLSTM) recurrent neural networks by introducing gated direct connections between memory cells in adjacent layers. These direct links, called highway connections, enable unimpeded information flow across different layers and thus alleviate the gradient vanishing problem when building deeper LSTMs. We further introduce the latency-controlled bidirectional LSTMs (BLSTMs) which can exploit the whole history while keeping the latency under control. Efficient algorithms are proposed to train these novel networks using both frame and sequence discriminative criteria. Experiments on the AMI distant speech recognition (DSR) task indicate that we can train deeper LSTMs and achieve better improvement from sequence training with highway LSTMs (HLSTMs). Our novel model obtains $43.9/47.7\%$ WER on AMI (SDM) dev and eval sets, outperforming all previous works. It beats the strong DNN and DLSTM baselines with $15.7\%$ and $5.3\%$ relative improvement respectively.

This work demonstrate algorithm invented for software realization at Windows PC, and demonstrate principles of E1 stream synchronization handling particular for fractional E1 to.


Question: Gut microbial metabolism defines host metabolism: an emerging perspective in obesity and allergic inflammation

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Summary ::: The presence of >100 trillion microorganisms (collectively called gut microbiota) in our large intestine is essential for the maintenance of health. The gut microbiota starts to develop before birth and matures within first three years of life. The Western diet and lifestyle have been implicated in causing an imbalance of gut microbial communities and their metabolites that consequence in disease states, such as obesity and asthma. With more than 13% of the world population currently living with obesity and one out of 10 children diagnosed with asthma, we explore here the recent developments in the biosynthesis and mode of action of the key metabolites in relation to these two chronic inflammatory conditions.

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Danielle Garsin looks at the recent progress that has been made in our understanding of ethanolamine utilization, including the evidence linking ethanolamine utilization to pathogenesis in a diverse range of bacterial pathogens.


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Question: AI Characters and Directors for Interactive Computer Games

represent this abstract from a paper to retrieve its scientific title

For instance, <<['Represent this scientific intro in order to find the title of the paper', 'We propose nested sequential Monte Carlo (NSMC), a methodology to sample from sequences of probability distributions, even where the random variables are high-dimensional. NSMC generalises the SMC framework by requiring only approximate, properly weighted, samples from the SMC proposal distribution, while still resulting in a correct SMC algorithm. Furthermore, NSMC can in itself be used to produce such properly weighted samples. Consequently, one NSMC sampler can be used to construct an efficient high-dimensional proposal distribution for another NSMC sampler, and this nesting of the algorithm can be done to an arbitrary degree. This allows us to consider complex and high-dimensional models using SMC. We show results that motivate the efficacy of our approach on several filtering problems with dimensions in the order of 100 to 1 000.']>>  to "['represent this title from a paper to retrieve its scientific short abstract\nE.g.\n"Investigation on stability of directionally solidified CBr4–C2Cl6 lamellar eutectic by using multiphase field simulation" == "With the multiphase field method, the stability of lamellar basic state is investigated during the directional solidification of eutectic alloy CBr4–C2Cl6. A great number of lamellar patterns observed in experiments are simulated, and a stability diagram for lamellar pattern selections is presented. The simulated growth behaviours of these patterns are found to be qualitatively consistent with Karma et al\'s numerical calculations and experimental results. The formation of the primary instability is attributed to the destabilization of solute boundary layer." != "Paper detailing the temperature and volume fraction effects on the erosion-oxidation of Ni-Cr/WC metal matrix composites."', 'Nested Sequential Monte Carlo Methods']"

We are creating an environment for investigating the role of advanced AI in interactive, story-based computer games. This environment is based on the Unreal Tournament (UT) game engine and the Soar AI engine. Unreal provides a 3D virtual environment, while Soar provides a flexible architecture for developing complex AI characters. This paper describes our progress to date, starting with our game, Haunt 2, which is designed so that complex AI characters will be critical to the success (or failure) of the game. It addresses design issues with constructing a plot for an interactive storytelling environment, creating synthetic characters for that environment, and using a story director agent to tell the story with those characters.

A Helping Hand for Arts, Drama,Music And Film Students! General Tools and Research Information


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Question: Positive Technology: Using Interactive Technologies to Promote Positive Functioning

Abstract It is generally assumed that technology assists individuals in improving the quality of their lives. However, the impact of new technologies and media on well-being and positive functioning is still somewhat controversial. In this paper, we contend that the quality of experience should become the guiding principle in the design and development of new technologies, as well as a primary metric for the evaluation of their applications. The emerging discipline of Positive Psychology provides a useful framework to address this challenge. Positive Psychology is the scientific study of optimal human functioning and flourishing. Instead of drawing on a “disease model” of human behavior, it focuses on factors that enable individuals and communities to thrive and build the best in life. In this paper, we propose the “Positive Technology” approach—the scientific and applied approach to the use of technology for improving the quality of our personal experience through its structuring, augmentation, and/or re...

Tour 1: Preparation for Departure: Who Am I and How Do I Interact With Others? Tour 2: Preparation for Departure: Building Relationships with Basic Listening Skills Tour 3: Departure: Advanced Facilitation Skills Tour 4: Traveling With a Theory: Integration and Personalization Tour 5: Applying Theory: Assessment and Conceptualization Tour 6: Meeting Clients: Treatment Planning, Progress Monitoring, and Documentation Tour 7: Consolidation: Celebrating the Journey and Preparing to Go Separate Ways


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Question: Stacked Square Microstrip Antenna for 4G System

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A single line feed stacked microstrip antenna for 4G system is presented. The proposed antenna with two properly square patches are stacked. The top patch can perform as a driven element is design on 2.44 GHz and lower patch is also design on 2.44 GHz. The performance of proposed antenna for 4G band frequency (2400-2500 MHz). Also gating the improvement of bandwidth (15%) and antenna efficiency (95%) are very high compared to conventional antenna.

This chapter contains sections titled: Introduction Dipole Basic Characteristics Partial Sleeve, PIFA, and Patch Loops Dielectric Resonator Antennas References


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Question: Truth, Justice, and Cake Cutting

Cake cutting is a common metaphor for the division of a heterogeneous divisible good. There are numerous papers that study the problem of fairly dividing a cake; a small number of them also take into account self-interested agents and consequent strategic issues, but these papers focus on fairness and consider a strikingly weak notion of truthfulness. In this paper we investigate the problem of cutting a cake in a way that is truthful and fair, where for the first time our notion of dominant strategy truthfulness is the ubiquitous one in social choice and computer science. We design both deterministic and randomized cake cutting algorithms that are truthful and fair under different assumptions with respect to the valuation functions of the agents.

Introduction Innocence Lost Family Matters In the Gym and Boardroom Higher Learning Coming to America Something Old, Something New Bibliography Index


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Question: Distance metric learning with eigenvalue fine tuning

Distance metric learning focuses on learning one global or multiple local distance functions to draw similar instances close to each other and push away dissimilar ones. Most existing work has to do matrix projection to learn distance functions. In this paper, we present a novel distance function learning model which is based on eigenvalue fine tuning. Our model not only is able to learn the global distance function but also can be easily adopted into local metric learning tasks. From the perspective of dimension reduction, the proposed model can measure how much information has been preserved after feature transformation. Moreover, we connect our model with principal components analysis to improve its performance by introducing the label information. Experimental results have demonstrated the effectiveness of the proposed method.

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Multi instance multi label learning is a framework in which objects are represented as bags of instances and labels are provided at the bag level. Instance annotation is the problem of assigning labels to the instances in a bag given only the bag label. Recently, OR-ed logistic regression (OR-LR) model and an EM based inference method have been proposed for instance annotation. Due to the linear nature of the logistic regression function, OR-LR performance on linearly inseparable data is limited. This paper addresses this problem by proposing a regularized kernel-based extension to the OR-LR framework. Experiments show that the kernel-based OR-LR algorithm achieves a significant improvement in classification accuracy over the linear OR-LR from 3% to 9% on audio bird song and image annotation datasets and two synthetic datasets.


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Question: Adaptive Mobile Robot Navigation and Mapping

The task of building a map of an unknown environment and concurrently using that map to navigate is a central problem in mobile robotics research. This paper addresses the problem of how to perform concurrent mapping and localization (CML) adaptively using sonar. Stochastic mapping is a feature-based approach to CML that generalizes the extended Kalman filter to incorporate vehicle localization and environmental mapping. The authors describe an implementation of stochastic mapping that uses a delayed nearest neighbor data association strategy to initialize new features into the map, match measurements to map features, and delete out-of-date features. The authors introduce a metric for adaptive sensing that is defined in terms of Fisher information and represents the sum of the areas of the error ellipses of the vehicle and feature estimates in the map. Predicted sensor readings and expected dead-reckoning errors are used to estimate the metric for each potential action of the robot, and the action that yi...

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Abstract : Partial contents: Persistent ISR Study Objective, Persistence Defined, Modeling & Simulation, Measures of Effectiveness, Architecture Design Search, Summary.


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Question: Service Quality and Customer Satisfaction: A Case Study of Hotel Industry in Vietnam

The purpose of this study is to empirically examine the relationship between service quality and customer satisfaction in Vietnamese hotels, survey questionnaire was constructed with 23 service quality items covering 5 service quality dimensions based on SERVQUAL model. Data were collected from 432 guests of 33 three-star hotels in Vietnam in 2013. Analysis results indicate that Reliability, Responsiveness, Assurance, and Empathy significantly impact on the customer satisfaction. The study implies that service quality plays an important role as a driver for higher customer satisfaction level in hotel service. Managers would focus on Empathy, Reliability, Responsiveness, and Assurance to achieve high degree of customer satisfaction which leads to customer loyalty and business profit.

A Cross-National Investigation of An Extended Technology Acceptance Model in The Online Shopping Context: A Study Case of Online Apparel Industry Across ASEAN Member States - Technology Acceptance Model (TAM), Online Shopping, ASEAN, Intention.


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Question: Neonatal lung ultrasound exam guidelines

Point-of-care ultrasound (POC-US) is increasingly used especially in emergency and critical-care medicine. It is focused, quick and does not expose patients to ionizing radiation. It encompasses all organ systems and has well-defined indications. Lung ultrasound (LUS) represents one of the most exciting applications in the field of POC-US. It is particularly important to emphasize the role of LUS in neonatology due to the specific pathology inherent in lung immaturity as well as in the particular sensitivity of neonates to repeated radiation exposure. One of the main barriers to the more extensive use of the ultrasound technology is a lack of efficient and attractive training solutions followed by the structured quality-check assurance. In an effort to help bridge this gap, based on the most current literature, we developed creative and intuitive neonatal LUS algorithms. We hope they can serve as a clinical imaging guidelines and a valuable complement to the history and physical exam.

The members of the Guideline Development Group must work in a fantastically well resourced environment where ultrasound scans to diagnose deep vein thrombosis of the leg are …


Question:
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The provided query could be '['Represent this title from a paper to retrieve its scientific short abstract', 'Sequence and peptide-binding motif for a variant of HLA-A*0214 (A*02142) in an HIV-1-resistant individual from the Nairobi Sex Worker cohort']' and the positive '['Represent the abstract for retrieving the scientific paper title', "As part of the ongoing study of natural HIV-1 resistance in the women of the Nairobi Sex Workers' study, we have examined a resistance-associated HLA class I allele at the molecular level. Typing by polymerase chain reaction using sequence-specific primers determined that this molecule is closely related to HLA-A*0214, one of a family of HLA-A2 supertype alleles which correlate with HIV-1 resistance in this population. Direct nucleotide sequencing shows that this molecule differs from A*0214, having a silent nucleotide substitution. We therefore propose to designate it HLA-A*02142. We have determined the peptide-binding motif of HLA-A*0214/02142 by peptide elution and bulk Edman degradative sequencing. The resulting motif, X-[Q,V]-X-X-X-K-X-X-[V,L], includes lysine as an anchor at position 6. The data complement available information on the peptide-binding characteristics of this molecule, and will be of use in identifying antigenic peptides from HIV-1 and other pathogens."]' and the negative '['Represent the abstract for retrieving the scientific paper title', 'One nucleotide substitution at codon 152 of HLA-B*58:01:01:01 results in a novel allele, HLA-B*58:19.']'

Question: Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization

Performance of machine learning algorithms depends critically on identifying a good set of hyperparameters. While recent approaches use Bayesian optimization to adaptively select configurations, we focus on speeding up random search through adaptive resource allocation and early-stopping. We formulate hyperparameter optimization as a pure-exploration non-stochastic infinite-armed bandit problem where a predefined resource like iterations, data samples, or features is allocated to randomly sampled configurations. We introduce a novel algorithm, Hyperband, for this framework and analyze its theoretical properties, providing several desirable guarantees. Furthermore, we compare Hyperband with popular Bayesian optimization methods on a suite of hyperparameter optimization problems. We observe that Hyperband can provide over an order-of-magnitude speedup over our competitor set on a variety of deep-learning and kernel-based learning problems.

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Preliminaries.- An Overview of Empirical Process Optimization.- Elements of Response Surface Methods.- Optimization Of First Order Models.- Experimental Designs For First Order Models.- Analysis and Optimization of Second Order Models.- Experimental Designs for Second Order Models.- Statistical Inference in Process Optimization.- Statistical Inference in First Order RSM Optimization.- Statistical Inference in Second Order RSM Optimization.- Bias Vs. Variance.- Robust Parameter Design and Robust Optimization.- Robust Parameter Design.- Robust Optimization.- Bayesian Approaches in Process Optimization.- to Bayesian Inference.- Bayesian Methods for Process Optimization.- to Optimization of Simulation and Computer Models.- Simulation Optimization.- Kriging and Computer Experiments.- Appendices.- Basics of Linear Regression.- Analysis of Variance.- Matrix Algebra and Optimization Results.- Some Probability Results Used in Bayesian Inference.


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Question: Designing Media Architecture: Tools and Approaches for Addressing the Main Design Challenges

Media Architecture is reaching a level of maturity at which we can identify tools and approaches for addressing the main challenges for HCI practitioners working in this field. While previous influential contributions within Media Architecture have identified challenges for designers and offered case studies of specific approaches, here, we (1) provide guidance on how to tackle the domain-specific challenges of Media Architecture design -- pertaining to the interface, integration, content, context, process, prototyping, and evaluation -- on the basis of the development of numerous installations over the course of seven years, and thorough studies of related work, and (2) present five categories of tools and approaches -- software tools, projection, 3D models, hardware prototyping, and evaluation tools -- developed to address these challenges in practice, exemplified through six concrete examples from real-life cases.

Contents: The Information Society - The Digital Divide - The Digital Practice Perspective - The Digital Practice of Weak Tie Development - The Digital Practice of Maintaining Family Ties via Mobile Phone - The Digital Practice of Maintaining Digital Enclaves - The Digital Practice Perspective and Social Policy: Improving the Social, Cultural, and Civic Quality of the Digital Environment - Conclusion: Smart Mobs, Flash Mobs, Flash Robs and the Revolutionary Potential of the Digital Environment.


Question:
represent this paper title in order to find a scientific intro to what it is about
Given ['Represent this paper title in order to find a scientific intro to what it is about.', 'Shrinking Distance Identifying priorities for territorial integration'], a positive would be ['Represent this abstract from a paper to retrieve its scientific title', '1 The world is not flat! 2 2 A policy framework for territorial integration 4 2.1 Spatially blind “institutions” 6 2.1.1 Progressive taxation 6 2.1.2 Intergovernmental transfers 9 2.1.3 Improving access and quality of education 11 2.1.4 Land market policies 12 2.1.5 Portable pension benefits 12 2.2 Spatially connective “infrastructure” 13 2.2.1 Transport Costs and Spatial concentration 14 2.2.2 Focus on Transport Services 15 2.2.3 Connecting Places with Information flows 16 2.3 Spatially targeted “incentives” 16 2.3.1 Let markets pick the places 17 2.3.2 Coordinating local and national incentive Programs 21 2.3.3 “Know thy Economy” Thinking through the design of incentives 22 3 An “I” for a “D”: Matching policies with country specific challenges 23 4 Implications for EU regional policies 26 4.1 Emphasize spatially blind and connective policies 26 4.2 Focus on international convergence, internal concentration 27 4.3 Assess spatial efficiency equity tradeoffs 29'] & a negative would be ['Represent the abstract for retrieving the scientific paper title', 'Research resources for ESPM C10 / LS C30V. Relationship between human society and the natural environment.']

Question: A 200-245 GHz Balanced Frequency Doubler with Peak Output Power of +2 dBm

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This paper presents a wideband 90 nm SiGe BiCMOS frequency multiplier at 200-245 GHz. The balanced multiplier results in a low first harmonic component, and uses a reflector at the base nodes to reflect the second harmonics to transistors for improved efficiency. The measured output power is > -2 dBm at 200-245 GHz with a peak value of +2 dBm at 224-228 GHz and a conversion gain of -15 dB. To the author's knowledge, this is the highest power wideband doubler at 200-250 GHz.

Preface.Acknowledgements.Glossary of Abbreviations.Glossary of Symbols.1. An Introduction to Optical Communication Systems.2. Principles of Distributed Feedback Semiconductor Laser Diodes: Coupled Wave Theory.3. Structural Impacts on the Solutions of Coupled Wave Equations: An Overview.4. Transfer Matrix Modelling in DFB Semiconductor Lasers.5. Threshold Analysis and Optimization of Various DFB LDs Using the Transfer Matrix Method.6. Above-Threshold Characteristics of DFB Laser Diodes: A TMM Approach.7. Above-Threshold Analysis of Various DFB Lase r Structures Using the TMM.8. Circuit and Transmission-Line Laser Modelling (TLLM) Techniques.9. Analysis of DFB Laser Diode Characteristics Based on the Transmission-Line Modelling (TLLM).10. Wavelength Tunable Optical Filters Based on DFB Laser Structures.11. Other Wavelenght Tunable Optical Filters Based on the DFB Laser Structure.12. Conclusion, Summary and Suggestions.Index.


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Question: Formal Verification of Financial Algorithms

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Many deep issues plaguing today’s financial markets are symptoms of a fundamental problem: The complexity of algorithms underlying modern finance has significantly outpaced the power of traditional tools used to design and regulate them. At Aesthetic Integration, we have pioneered the use of formal verification for analysing the safety and fairness of financial algorithms. With a focus on financial infrastructure (e.g., the matching logics of exchanges and dark pools and FIX connectivity between trading systems), we describe the landscape, and illustrate our Imandra formal verification system on a number of real-world examples. We sketch many open problems and future directions along the way.

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These invited talks discuss the following: STG Decomposition and Its Correctness; Asynchronous Network-On-Chip and its Potential.


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Question: Big Data Validation and Quality Assurance -- Issuses, Challenges, and Needs

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With the fast advance of big data technology and analytics solutions, big data computing and service is becoming a very hot research and application subject in academic research, industry community, and government services. Nevertheless, there are increasing data quality problems resulting in erroneous data costs in enterprises and businesses. Current research seldom discusses how to effectively validate big data to ensure data quality. This paper provides informative discussions for big data validation and quality assurance, including the essential concepts, focuses, and validation process. Moreover, the paper presents a comparison among big data validation tools and several major players in industry are discussed. Furthermore, the primary issues, challenges, and needs are discussed.

How to Think About R&D Quality. Organizing for Quality in R&D. Measuring R&D Quality. Assessing R&D Quality Status. Intellectual Property Management Process Improvement. Implementing Quality in Research: A Case Example. Views and Lessons Learned at the Top. References. Index.


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Question: Sign language to speech conversion

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Human beings interact with each other to convey their ideas, thoughts, and experiences to the people around them. But this is not the case for deaf-mute people. Sign language paves the way for deaf-mute people to communicate. Through sign language, communication is possible for a deaf-mute person without the means of acoustic sounds. The aim behind this work is to develop a system for recognizing the sign language, which provides communication between people with speech impairment and normal people, thereby reducing the communication gap between them. Compared to other gestures (arm, face, head and body), hand gesture plays an important role, as it expresses the user's views in less time. In the current work flex sensor-based gesture recognition module is developed to recognize English alphabets and few words and a Text-to-Speech synthesizer based on HMM is built to convert the corresponding text.

Language, languages and communication learning another language how languages work languages around us.


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Question: Color synesthesia. Insight into perception, emotion, and consciousness

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Purpose of review ::: Synesthesia is an extraordinary perceptual phenomenon, in which individuals experience unusual percepts elicited by the activation of an unrelated sensory modality or by a cognitive process. Emotional reactions are commonly associated. The condition prompted philosophical debates on the nature of perception and impacted the course of art history. It recently generated a considerable interest among neuroscientists, but its clinical significance apparently remains underevaluated. This review focuses on the recent studies regarding variants of color synesthesia, the commonest form of the condition.

Modern conceptions of brain function consider the brain as a "predictive organ," where learned regularities about the world are utilised to facilitate perception of incoming sensory input. Critically, this process hinges on a role for cognitive penetrability. We review a mechanism to explain this process and expand our previous proposals of cognitive penetrability in visual recognition to social vision and visual hallucinations.


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Question: Efficient techniques for dynamic vehicle detection

Fast detection of moving vehicles is crucial for safe autonomous urban driving. We present the vehicle detection algorithm developed for our entry in the Urban Grand Challenge, an autonomous driving race organized by the U.S. Government in 2007. The algorithm provides reliable detection of moving vehicles from a high-speed moving platform using laser range finders. We present the notion of motion evidence, which allows us to overcome the low signal-to-noise ratio that arises during rapid detection of moving vehicles in noisy urban environments. We also present and evaluate an array of optimization techniques that enable accurate detection in real time. Experimental results show empirical validation on data from the most challenging situations presented at the Urban Grand Challenge as well as other urban settings.

A new framework for description and analysis of uncertainty in dynamic systems is briefly described.


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Question: Enhanced Framework for Sentiment Analysis in Text using Distance based Classification Scheme

Social media platform like blogs, social networks and content communities have become valuable resource for mining the sentiments. In fact information gained from the social platform like Facebook and twitter has been expressed to be more important to industries, market, news, public opinion organization and many more. Sentiment analysis in a text is a procedure in which the polarities like positive and negative of a specified text is determined. In this project we are using twitter comments as the text input. The proposed method consists of two phases called testing and training phase. For extracting the features we are using the sentiwordnet. The distance based classifier is used to classify the features. Finally analyses of the sentiments are done by polarities classified by the distance classifier.

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Question: Flying-capacitor boost converter

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This paper introduces the flying-capacitor dc-dc boost converter. In the proposed topology, a high voltage gain ratio and improved conversion efficiency are achieved with low inductor core and copper losses. The input current ripple of the new converter is low while its ripple frequency is high, yielding a low-sized input filter. Furthermore, the voltage stresses on the power switches and diodes of the proposed converter are considerably low. It is shown that the proposed converter can be extended to higher stages to achieve a higher voltage gain ratio at enhanced efficiency. The principle of operation of the new converter is proposed, and the comparison with the conventional boost topology is presented. A complete analysis of this converter in the steady state and small signal operation is performed as well. Simulation results and a design example are also given to demonstrate the effectiveness of the proposed power converter.

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E.g. ['Represent this scientific intro in order to find the title of the paper', 'The Physical Optics (PO) approximation is investigated as tool for analysis of scattering problems involving coated electrically large conducting platforms. The PO-derived current is corrected by including additional terms that account for diffraction phenomena. Numerical example demonstrates usefulness and limitations of the approach and compares results for conducting and coated plate.'] == ["represent this title from a paper to retrieve its scientific short abstract\n\nThe provided query could be 'Nitrogen-doped activated carbon catalyst and application thereof' and the positive 'The invention discloses a nitrogen-doped activated carbon catalyst and application thereof. The preparation method of the nitrogen-doped activated carbon catalyst comprises the following steps: adding a nitrogen-containing compound into water to dissolve to obtain a nitride solution, wherein the nitrogen-containing compound is one or more of ammonia water, ammonia gas, pyridine, pyrrole, imidazole, acrylamide, polyacrylamide and polyvinylpyrrolidone; adding activated carbon into the nitride solution to soak; completely drying the soaked activated carbon, and calcining in nitrogen atmosphere, thereby preparing the nitrogen-doped activated carbon catalyst. The nitrogen-doped activated carbon catalyst disclosed by the invention has very good catalysis property in reaction of catalyzing tetrachloroethane and acetylene to generate trichloro ethylene and chloroethylene and catalyzing tetrachloroethane gas phase cracking to generate trichloro ethylene.' and the negative 'A direct synthesis of high-aspect-ratio microporous zeolite nanosheets and the use of such nanosheets in separation membranes are described.'", 'Physical optics approximation for PEC objects coated with lossy material']

Reduction of switching loss, EMI( electromagnetic interference) and input power factor increase for the switched mode power supply is a matter of great importance Especially in case of battery charger for electrical vehicle requires !ugh power factor and efficiency, so apply power factor correction circuit and the switching method of reduction of switching loss Also battery for using load, isolation of input and output stage is necessary. ::: In this paper show the computer simulation and expenment of isolated single stage single phase AC/DC Full Bridge Boost Converter And introduce to an electrical vehicle system.


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Question: Heterogeneous network-based trust analysis: a survey

Different information sources publish information with different degrees of correctness and originality. False information can often result in considerable damage. Hence, trustworthinessof information is an important issue in this datadriven world economy. Reputation of different agents in a network has been studied earlier in a variety of domains like e-commerce, social sciences, sensor networks, and P2P networks. Recently there has been work in the data mining community on performing trust analysis based on the data provided by multiple information providers for different objects, and such agents and their provided information about data objects form a multi-typed heterogeneous network. The trust analysis under such a framework is considered as heterogeneous network-based trust analysis. This paper will survey heterogeneous network-based trust analysis models and their applications. We would conclude with a summary and some thoughts on future research in the area.

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In this chapter, we propose a systematic architecture on data-driven personalized QoE management. A framework of the QoE management architecture is firstly introduced, which consists of two modules namely (1) training module and (2) control module. We also depict two models for the prediction of user preference, including Bayesian Graphic Model and Context Aware Matrix Factorization Model. A preliminary use case is deployed to demonstrate and evaluate the proposed architecture. Simulation results illustrate the superior performance of proposed architecture compared with traditional water-filling method.


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Question: Mindfulness meditation and substance use in an incarcerated population.

Despite the availability of various substance abuse treatments, alcohol and drug misuse and related negative consequences remain prevalent. Vipassana meditation (VM), a Buddhist mindfulness-based practice, provides an alternative for individuals who do not wish to attend or have not succeeded with traditional addiction treatments. In this study, the authors evaluated the effectiveness of a VM course on substance use and psychosocial outcomes in an incarcerated population. Results indicate that after release from jail, participants in the VM course, as compared with those in a treatment-as-usual control condition, showed significant reductions in alcohol, marijuana, and crack cocaine use. VM participants showed decreases in alcohol-related problems and psychiatric symptoms as well as increases in positive psychosocial outcomes. The utility of mindfulness-based treatments for substance use is discussed.

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Objective ::: The objective of this study was to examine the extent to which poor sleep quality is associated with suicidal ideation among Ethiopian adults.


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Question: Recursive Deep Models for Discourse Parsing

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Text-level discourse parsing remains a challenge: most approaches employ features that fail to capture the intentional, semantic, and syntactic aspects that govern discourse coherence. In this paper, we propose a recursive model for discourse parsing that jointly models distributed representations for clauses, sentences, and entire discourses. The learned representations can to some extent learn the semantic and intentional import of words and larger discourse units automatically,. The proposed framework obtains comparable performance regarding standard discoursing parsing evaluations when compared against current state-of-art systems.

Foundations of Semantic Web Reasoning.- Composing Frameworks and Components for Families of Semantic Web Applications.- Semantic Web Logic Programming Tools.- Web Rules Need Two Kinds of Negation.- Reasoning in Practice.- Towards the Adaptive Semantic Web.- On Reasoning on Time and Location on the Web.- Reasoning about Communicating Agents in the Semantic Web.- Query and Rule-Languages.- A Visual Language for Web Querying and Reasoning.- XML Document Adaptation Queries (XDAQ): An Approach to Adaptation Reasoning Using Web Query Languages.- On Types for XML Query Language Xcerpt.- Integrating Description Logics and Answer Set Programming.- Semantics and Knowledge Representation.- Extracting Mathematical Semantics from Documents.- Reasoning in Attempto Controlled English.- Systematics and Architecture for a Resource Representing Knowledge about Named Entities.


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Question: WYSIWYG NPR: drawing strokes directly on 3D models

We present a system that lets a designer directly annotate a 3D model with strokes, imparting a personal aesthetic to the non-photorealistic rendering of the object. The artist chooses a "brush" style, then draws strokes over the model from one or more viewpoints. When the system renders the scene from any new viewpoint, it adapts the number and placement of the strokes appropriately to maintain the original look.

54. Bits and pieces, 21. A BASIC program to provide a graphical solution of equations for stirred-tank reactors in series.


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Question: Learning for larger datasets with the Gaussian process latent variable model

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In this paper we apply the latest techniques in sparse Gaussian process regression (GPR) to the Gaussian process latent variable model (GPLVM). We review three techniques and discuss how they may be implemented in the context of the GP-LVM. Each approach is then implemented on a well known benchmark data set and compared with earlier attempts to sparsify the model.

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In many data mining applications, the data manifold is of lower dimension than the dimension of the input space. In this paper, it is proposed to take advantage of this additional information in the frame of variational mixtures. The responsibilities computed in the VBE step are constrained according to a discrepancy measure between the Euclidean and the geodesic distance. The methodology is applied to variational Gaussian mixtures as a particular case and outperforms the standard approach, as well as Parzen windows, on both artificial and real data.


Question: Optimistic Optimization of a Deterministic Function without the Knowledge of its Smoothness

We consider a global optimization problem of a deterministic function f in a semi-metric space, given a finite budget of n evaluations. The function f is assumed to be locally smooth (around one of its global maxima) with respect to a semi-metric l We describe two algorithms based on optimistic exploration that use a hierarchical partitioning of the space at all scales. A first contribution is an algorithm, DOO, that requires the knowledge of l. We report a finite-sample performance bound in terms of a measure of the quantity of near-optimal states. We then define a second algorithm, SOO, which does not require the knowledge of the semi-metric l under which f is smooth, and whose performance is almost as good as DOO optimally-fitted.

Preface. 1. On Regularization of Linear Equations on the Basis of Perturbation Theory. 2. Investigation of Bifurcation Points of a Nonlinear Equations. 3. Regularization of Computation of Solutions in a Neighborhood of the Branch Point. 4. Iterations, Interlaced Equations and Lyapunov Conbex Majorants in Nonlinear Analysis. 5. Methods of Representation Theory and Group Analysis in Bifurcation Theory. 6. Singular Differential Equations in Banach Spaces. 7. Steady-State Solutions of the Vlasov-Maxwell System. Appendices. A: Positive solutions of the nonlinear singular boundary value problem of magnetic insulation. References. Index.


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Question: An Interactive Microarray Call-Graph Visualization

In this paper we present an interactive call-graph visualization tool for viewing large programs. Our space-filling grid-based visualization shows the functions of a programs call-graph. The grid view provides an overview of all of the methods, allowing the user to investigate and view subsets of functions, and finally jump to source code for more details on demand. Our tool assists programmers by reducing large call graphs into smaller subgraphs with function relationships that matter for program comprehension. In our benchmarks, we view and explore code relationships in programs with 18,720 functions at interactive frame rates. We provide two use cases with several findings on investigating profile-guided optimizations in C++ and critical sections in concurrent Java programs. Our software visualization tool is Java based and portable across multiple platforms.

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AbstractThe following sections are included:IntroductionThe Information Sharing to Make Use of an ICT SystemThe Evaluation Function of the ICT SystemThe Value Propagation Chain Caused by the ICT SystemActive Use of the Evaluation Function in KPMAn Example of Visualizing the Effect of Risk Distribution on InvestmentSample calculationDiscussionConclusionReferences


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Question: Fast and accurate mining of correlated heavy hitters

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The problem of mining Correlated Heavy Hitters (CHH) from a two-dimensional data stream has been introduced recently, and a deterministic algorithm based on the use of the Misra--Gries algorithm has been proposed by Lahiri et al. to solve it. In this paper we present a new counter-based algorithm for tracking CHHs, formally prove its error bounds and correctness and show, through extensive experimental results, that our algorithm outperforms the Misra--Gries based algorithm with regard to accuracy and speed whilst requiring asymptotically much less space.

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We present a hierarchical tree structure for online maintenance of time-decaying synopses over streaming data. We exemplify such an amnesic behavior over streams of locations taken from numerous moving objects in order to obtain reliable trajectory approximations as well as affordable estimates regarding distinct count spatiotemporal queries.


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Question: Proposal: A Design of E-learning User Authentication System

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The user authentication is very crucial in developing an e-learning system. Emerging standards for distance learning and education influence in a major way the development of e-learning systems. E-learning system must be secured against manipulation from the side of the students and also it protects user's privacy. This paper examines privacy and security issues associated with e-learning. It presents the basic principles behind privacy practices and legislation. Concrete solutions for improving the degree of security achievable are shown. A design of an e-learning user authentication system is introduced. This framework prevents manipulation from the side of the students during learning, thus allowing a reliable control of learning success.


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The query could be '['Represent this title from a paper to retrieve its scientific short abstract', 'Extended glottal LPS with mixed excitation']' and should be close to '['', 'A speech-modelling scheme that is capable of reproducing voiced fricatives, plosives, etc. with good accuracy, as well as purely voiced or unvoided sounds is presented. The scheme results in a speech coder with great ability and flexibility in the source modelling. Since it conserves the timing of the source, it can be interpreted as a waveform model, as well as a speech modelling scheme. The scheme requires input speech recorded under good conditions, and an adequate analog preprocessing. Moreover, the analysis time is on the same order as that of the glottal linear predictive coder. These two major limitations make the scheme suitable for applications such as speech storing, etc. From preliminary experiments the bit rate needed in coding the parameters in this model is estimated at 5 kb/s. >']' but very far from '['Represent this abstract from a paper to retrieve its scientific title!', 'A number of investigators have identified both VOT and F1 cutback as major cues for voicing contrasts. At recent meetings we have presented evidence that sinusoidal analogs to isolated F1‐cutback stimuli are perceived in a relatively discrete fashion with category boundaries corresponding to those found for synthetic speech continua. In contrast to nonspeech analogs to VOT continua (both tone‐onset‐time for stationary and nonstationary stimuli, and noise‐onset‐time for noise‐buzz stimuli), the sinusoidal analogs to F1 cutback exhibit a dependency of the category boundary on spectral frequency. Furthermore, the category boundary locations for the F1‐cutback analogs correspond to the voicing contrast boundary locations for speech stimuli. Our current research examines the perception of the F1‐cutback analog presented in conjunction with various configurations of tone‐onset‐time and noise‐onset‐time continua. In all current conditions, the degree of F1‐cutback analog and the relative onset asynchrony in the ...']'

Question: Personality and Health Care Decision-Making Style

Using the Wisconsin Longitudinal Study Graduate Survey (N = 5,830), a population-based cohort of older adults (most aged 63–66 years), we explored relationships between five factors of personality and four preference types that account for multiple components of the health care decision-making process (information exchange, deliberation, and selection of treatment choice). After adjustment for personal, health, social, and economic factors, we found that increased conscientiousness and openness to experience and decreased agreeableness and neuroticism corresponded to preferring the most active decision-making style compared with the least active. A better understanding of how personality traits relate to patient decision-making styles may help clinicians tailor treatment discussions to the needs and preferences of individual patients.

1. An Introduction to Geographical Information Systems and Participatory Geographical Information Science 2. A Micro-Macro Framework for Participatory Decision Situations 3. Methods and Tools for Participatory Spatial Decision Support 4. Social Behavioural Research Strategies for Investigating the Use of Participatory Geographical Information Systems 5. Collaborative Spatial Decision Making in Primary Health Care Management 6. Transportation Improvement Program Decision Making 7. Collaborative Decision Making About Habitat Restoration 8. Conclusions and Prospects for Future Research


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Question: Compute Pairwise Manhattan Distance and Pearson Correlation Coefficient of Data Points with GPU

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Graphics processing units (GPUs) are powerful computational devices tailored towards the needs of the 3-D gaming industry for high-performance, real-time graphics engines. Nvidia Corporation released a new generation of GPUs designed for general-purpose computing in 2006, and it released a GPU programming language called CUDA in 2007. The DNA microarray technology is a high throughput tool for assaying mRNA abundance in cell samples. In data analysis, scientists often apply hierarchical clustering of the genes, where a fundamental operation is to calculate all pairwise distances. If there are n genes, it takes O(n^2) time. In this work, GPUs and the CUDA language are used to calculate pairwise distances. For Manhattan distance, GPU/CUDA achieves a 40 to 90 times speed-up compared to the central processing unit implementation; for Pearson correlation coefficient, the speed-up is 28 to 38 times.

Overview of SPSS for Windows, James Lyall Research Problems and Questions Measurement and Descriptive Statistics Data Collection Data Entry and Descriptive Statistics for a Class Questionnaire Overview of the High School and Beyond (HSB) Data Set, Checking Data and Descriptive Statistics Selecting and Interpreting Inferential Statistics Cross Tabulation, Chi-square and Phi (or Cramer's V) Associating Variables - Pearson and Spearman.


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Question: Business Process Re-Engineering in Public Administration of Kingdom of Saudi Arabia

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The government of Saudi Arabia is in the phase of transformation. Business process reengineering (BPR) can play a vital role in assessing this conversion. BPR methodologies provide ways to optimize the use of resources while maintaining high-quality services. The aim of this paper is to investigate the introduction of BPR in Saudi Arabia public sector. A framework is proposed to transform change using a knowledge based. The proposed solution is validated through survey. The results of the survey show that Saudi Governmental Agencies acquire the power to implement the BPR successfully especially if it is implemented with knowledge management and the BPR movement started at small scale.

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Introduction Problems and Prospects of Preventing Conflict of Interest in Local Governments in the CEE Countries Chapter 1 The Bulgarian Experience with Building a Framework for the Prevention of Conflict of Interest Situations in Local Governments Chapter 2 The Progress of Regulation of Conflict of Interest in Local Government in Latvia Chapter 3 Difficulties with Implementation of Conflict of Interest Regulation in Polish Local Government Chapter 4 New Ways of Managing Conflict of Interest Problems in Romania Chapter 5 Conflict of Interest in Russian Local Government: Challenges for New Legislation Chapter 6 Waiting for a Conflict of Interest Constitutional Law in Slovakia Index


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Question: Knowledge Based Real Time Monitoring System for Aquaculture Using IoT

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Internet of things is one of the rapidly growing fields for delivering social and economic benefits for emerging and developing economy. The field of IOT is expanding its wings in all the domains like medical, industrial, transportation, education, mining etc. Now-a-days with the advancement in integrated on chip computers like Arduino, Raspberry pi the technology is reaching the ground level with its application in agriculture and aquaculture. Water quality is a critical factor while culturing aquatic organisms. It mainly depends on several parameters like dissolved oxygen, ammonia, pH, temperature, salt, nitrates, carbonates etc. The quality of water is monitored continuously with the help of sensors to ensure growth and survival of aquatic life. The sensed data is transferred to the aqua farmer mobile through cloud. As a result preventive measures can be taken in time to minimize the losses and increase the productivity.

Engaging Customers for More Profitable Business with ARC: a Business Model Creation of Outsourced CRM for Better Customer Centric Brand - Outsourced, Customer Relationship Management, Retail Industries


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Question: AIScale — A coarse grained reconfigurable CNN hardware accelerator

In this paper we propose a novel CNN hardware accelerator, called AlScale, capable of accelerating convolutional, pooling, fully-connected and adding CNN layers. In contrast to most existing solutions, AIScale offers a complete solution to the full CNN acceleration. AIScale is designed as a coarse-grained reconfigurable architecture, which uses rapid, dynamic reconfiguration during the CNN layer processing. Furthermore, a novel algorithm for mapping computations to the available computing resources enables AIScale to achieve higher utilization ratios than some of the previously proposed solutions. Results of the experiments indicate that the AIScale architecture is 1.16 to 2.73 times faster and consumes from 25% to 45% less energy on DRAM data transfers than the previously proposed MIT's Eyeriss CNN accelerator while using an identical number of computing units and having almost identical on-chip RAM memory size.

Fast and accurate simulation of multicore systems requires a parallelized simulator. This paper describes a novel method to build cycle-accurate-capable and parallelizable functional-first simulators of multicore targets.


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Question: Adaptive hierarchical RBF interpolation for creating smooth digital elevation models

This paper presents a fast algorithm for smooth digital elevation model interpolation and approximation from scattered elevation data. The global surface is reconstructed by subdividing it into overlapping local subdomains using a perfectly balanced binary tree. In each tree leaf, a smooth local surface is reconstructed using radial basis functions. Finally a hierarchical blending is done to create the final C1-continuous surface using a family of functions called Partition of Unity. We present two terrain data sets and show that our method is robust since the number of data points in the Partition of Unity blending areas is explicitly specified.

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We apply new methods based on Partial Differential Equations techniques (polysplines) to the visualization of the heart surface.


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Question: Review of shape representation and description techniques

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More and more images have been generated in digital form around the world. There is a growing interest in 1nding images in large collections or from remote databases. In order to 1nd an image, the image has to be described or represented by certain features. Shape is an important visual feature of an image. Searching for images using shape features has attracted much attention. There are many shape representation anddescription techniques in the literature. In this paper, we classify and review these important techniques. We examine implementation procedures for each technique and discuss its advantages and disadvantages. Some recent research results are also included and discussed in this paper. Finally, we identify some promising techniques for image retrieval according to standard principles.

The paper proposes two complementary methods for change analysis and feature extraction: A time evolution analysis of satellite images and using the correlation coefficient together with conditional information.


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Question: Business model metrics: an open repository

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Development of successful business models has become a necessity in turbulent business environments, but compared to research on business modeling tools, attention to the role of metrics in designing business models in literature is limited. Building on existing approaches to business models and performance measurement literature, we develop a generic open repository of metrics related to core business model concepts. We validate and assess the practical value of the repository based on four e-Business model cases. The repository can be utilized in designing business models, specifically for networked enterprises. It is neither complete nor universally applicable, but needs adjustment with each design. Ultimately, with this paper, we hope measurement will become an integral part of the business model innovation discussion.

Three-dimensional structure handling reactions and synthesis property prediction and analysis integrated systems.


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Question: APRIORI-SD: Adapting Association Rule Learning to Subgroup Discovery

This paper presents a subgroup discovery algorithm APRIORI-SD, developed by adapting association rule learning to subgroup discovery. This was achieved by building a classification rule learner APRIORI-C, enhanced with a novel post-processing mechanism, a new quality measure for induced rules (weighted relative accuracy) and using probabilistic classification of instances. Results of APRIORI-SD are similar to the subgroup discovery algorithm CN2-SD while experimental comparisons with CN2, RIPPER and APRIORI-C demonstrate that the subgroup discovery algorithm APRIORI-SD produces substantially smaller rule sets, where individual rules have higher coverage and significance.

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Abstract : Partial contents: Persistent ISR Study Objective, Persistence Defined, Modeling & Simulation, Measures of Effectiveness, Architecture Design Search, Summary.


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Question: Single inductor three-level boost bridgeless PFC rectifier with nature voltage clamp

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A single inductor three-level boost bridgeless PFC rectifier with nature voltage clamp is proposed. In the proposed converter, the operation principle is quite different from other boost bridgeless three-level converters. The charging stage is presented in the low side while the discharging stage in the high side and vice versa. As a result, nature voltage clamp is achieved. And the slow diodes are ‘shared’. They operate not only as rectifying diodes, but also as voltage clamping diodes. Besides, only single inductor is required and the device utilization factor is high. Besides, the common-mode(CM) noise is rather low. First, the operational principle are analyzed in detail. Then the performance evaluation and design consideration are presented. Finally, a 1kW experimental prototype is built. The result shows that the efficiency is above 94% at full load under 90V and the maximum efficiency is 98.4%.

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A zero-voltage-switching (ZVS) Boost converter with DC motor load is proposed. It consists of a ZVS boost converter stage and a ZVS half-bridge converter stage and two stages are merged into a single stage. The ZVS boost converter stage provides a continuous input current and ZVS operation of the power switches. The ZVS half-bridge converter stage provides a high voltage gain in DC Motor Load. The principle of operation and system analysis are presented. Theoretical analysis of the proposed converter wer verified on a Matlab Simulation using operating at 108 kHz switching frequency.


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Question: The Relative Importance of Perceived Ease of Use in IS Adoption: A Study of E-Commerce Adoption

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The technology acceptance model (Davis 1989) is one of the most widely used models of IT adoption. According to TAM, IT adoption is influenced by two perceptions: usefulness and ease-of-use. Research has shown that perceived usefulness (PU) affects intended adoption of IT, but has mostly failed to do so regarding perceived ease of use (PEOU). The basic proposition of this study is that this varying importance of PEOU may be related to the nature of the task. PEOU relates to assessments of the intrinsic characteristics of IT, such as the ease of use, ease of learning, flexibility, and clarity of its interface. PU, on the other hand, is a response to user assessment of its extrinsic, i.e., task-oriented, outcomes: how IT

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Enhancing the Entrepreneurial Spirit!? : Investigating the Entrepreneurship Discourse in Newspapers over Time


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Question: SAGE: whitebox fuzzing for security testing

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SAGE has had a remarkable impact at Microsoft.

This paper expounds the problems of the ob- ject- oriented database- MIS on Borland C++for Windows, and makes researching on currentnature in detail. [


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Question: A look into Twitter hashtag discovery and generation

Twitter is a micro-blogging site that allows users and companies to post brief pieces of information called 'Tweets'. Some of the tweets contain keywords such as 'Hashtags' denoted with a '#', essentially one word summaries of either the topic or emotion of the tweet. The goal of this paper is to examine an approach to perform hashtag discovery on Twitter posts that do not contain user labeled hashtags. The process described in this paper is geared to be as automatic as possible, taking advantage of web information, sentiment analysis, geographic location, basic filtering and classification processes, to generate hashtags for tweets. Hashtags provide users and search queries a fast and simple basis to filter and find information that they are interested in.

Gives an overview of approaches to results presentation by web search engines. Discusses consequences for search engine evaluation and resutls presentation on portals.


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Question: Stroke Controllable Fast Style Transfer with Adaptive Receptive Fields

The Fast Style Transfer methods have been recently proposed to transfer a photograph to an artistic style in real-time. This task involves controlling the stroke size in the stylized results, which remains an open challenge. In this paper, we present a stroke controllable style transfer network that can achieve continuous and spatial stroke size control. By analyzing the factors that influence the stroke size, we propose to explicitly account for the receptive field and the style image scales. We propose a StrokePyramid module to endow the network with adaptive receptive fields, and two training strategies to achieve faster convergence and augment new stroke sizes upon a trained model respectively. By combining the proposed runtime control strategies, our network can achieve continuous changes in stroke sizes and produce distinct stroke sizes in different spatial regions within the same output image.

These invited talks discuss the following: STG Decomposition and Its Correctness; Asynchronous Network-On-Chip and its Potential.


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Question: A predictive model for identifying students with dropout profiles in online courses

Online education often deals with the problem related to the high students’ dropout rate during a course in many areas. There is huge amount of historical data about students in online courses. Hence, a relevant problem on this context is to examine those data, aiming at finding effective mechanisms to understand student profiles, identifying those students with characteristics to drop out at early stage in the course. In this paper, we address this problem by proposing predictive models to provide educational managers with the duty to identify students whom are in the dropout bound. Four classification algorithms with different classification methods were used during the evaluation, in order to find the model with the highest accuracy in prediction the profile of dropouts students. Data for model generation were obtained from two data sources available from University. The results showed the model generated by using SVM algorithm as the most accurate among those selected, with 92.03% of accuracy.

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This research examines the effectiveness of a training intervention program designed to improve strategies for learning from texts and to determine whether the success of this intervention depends ...


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Question: Passive returning mechanism for twisted string actuators

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The twisted string actuator is an actuator that is gaining popularity in various engineering and robotics and applications. However, the fundamental limitation of actuators of this type is the uni-directional action, meaning that the actuator can contract but requires external power to return to its initial state. This paper proposes 2 novel passive extension mechanisms based on buckling effect to solve the uni-directional issue of the twisted string actuator. The proposed mechanisms are mechanically simple and compact and provide a nearly-constant extension force throughout the operation range. The constant force can fully extend the twisted string actuator with minimal loss of force during contraction. The designed mechanisms are evaluated in a series of practical tests, and their performances are compared and discussed.

The present techniques generally relate to apparatus and methods for providing programmable currents for correlated electron switches.


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Question: Exploration of efficient symmetric AES algorithm

Security threats have been a major concern as a result of emergence of technology in every aspect including internet market, computational and communication technologies. To solve this issue effective mechanism of “cryptography” is used to ensure integrity, privacy, availability, authentication, computability, identification and accuracy. Cryptology methods like PKC and SKC are used of data recovery. In this work, we describe exploration of efficient approach of private key architecture that is efficient symmetric AES Algorithm on the basis of attributes: encipherment and Decipherment and degree of security issues essential for safe wired and wireless communication. The work explores efficient private key algorithm based on security of individual system and to improve encipherment and Decipherment time with encipherment/Decipherment performance. The work opens a new direction over cloud security and internet of things.

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The algebraic structure determining the vector-matrix transformation in the discrete vector Boolean space for the analyzing information based on logical operations on associative data.


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Question: Reconfigurable Path Planning for an Autonomous Unmanned Aerial Vehicle

In this paper, we present a motion planning framework for a fully deployed autonomous unmanned aerial vehicle which integrates two sample-based motion planning techniques, Probabilistic Roadmaps and Rapidly Exploring Random Trees. Additionally, we incorporate dynamic reconfigurability into the framework by integrating the motion planners with the control kernel of the UAV in a novel manner with little modification to the original algorithms. The framework has been verified through simulation and in actual flight. Empirical results show that these techniques used with such a framework offer a surprisingly efficient method for dynamically reconfiguring a motion plan based on unforeseen contingencies which may arise during the execution of a plan. The framework is generic and can be used for additional platforms.

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Design of an Isolated Airfoil in an Ideal Incompressible Fluid. Account of Compressibility and Viscosity. Airfoil Design for a Given Range of Angels of Attack. Design of Mechanized Airfoils and Airfoils with Permeable Contour. Design Problems for Airfoils with Partially Given Contour. Airfoil Cascade Design. Aerohydrodynamically Reasonable Velocity Distributions. Regularization and Optimization in Inverse Boundary Value Problems of Hydrodynamics.


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Question: The Cerema pedestrian database: A specific database in adverse weather conditions to evaluate computer vision pedestrian detectors

Nowadays, many pedestrians are victims of road accidents. Several artificial vision solutions, based on pedestrian detection, have therefore been developed to assist drivers and reduce the accident rate. But most of the proposed pedestrian databases make it possible to test detection only in favorable conditions. The main goal of this research is to provide a learning and testing environment for the development of pedestrian detectors able to function under all weather conditions by day and even by night. This paper presents a new database, called Cerema, composed of 10 sets which include normal and degraded conditions (day, night, fog, rain). Image data will include detailed annotations for each set. Two common detectors are used to show the usefulness of our database, which are HOG and Haar. Finally, the results obtained on this new database will be presented to show the impact of adverse weather conditions on these two different detectors.

This paper focuses on describing pedestrian safety at signalized intersections in suburban areas starting with shortcomings of safety indicators and moving through a modeling process. In addition, several other components in the modeling effort are briefly described giving an overview of the entire modeling process. Thus, characterization and understanding of pedestrian safety at suburban intersections can enable better understanding of more effective signal operation and allow further development and evaluation of pedestrian and vehicular control strategies.


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Question: A novel approach to data deduplication over the engineering-oriented cloud systems

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This paper presents a duplication-less storage system over the engineering-oriented cloud computing platforms. Our deduplication storage system, which manages data and duplication over the cloud system, consists of two major components, a front-end deduplication application and a mass storage system as back-end. Hadoop distributed file system HDFS is a common distribution file system on the cloud, which is used with Hadoop database HBase. We use HDFS to build up a mass storage system and employ HBase to build up a fast indexing system. With a deduplication application, a scalable and parallel deduplicated cloud storage system can be effectively built up. We further use VMware to generate a simulated cloud environment. The simulation results demonstrate that our deduplication storage system is sufficiently accurate and efficient for distributed and cooperative data intensive engineering applications.

Data center is an important form of cloud computing, network security of data center is also very important. The firewall has been used widely as an important tool for network security. This paper described a firewall named DC-Firewall for virtual machines in a data center, especially for the virtual machines in a P2P network. Different from previous research, this paper wants to emphasize the importance of distributed model and message control in the study of network security in data centers. The discussion of distributed architecture forms the major concern of the present study. For different topology of P2P network, DC-Firewall used modular design to provide extensibility of architecture. Some useful implications obtained from this system include the architecture of distributed firewalls and message-oriented engine in software defined P2P networks.


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Question: Synaptic patterning and the timescales of cortical dynamics

Neocortical circuits, as large heterogeneous recurrent networks, can potentially operate and process signals at multiple timescales, but appear to be differentially tuned to operate within certain temporal receptive windows. The modular and hierarchical organization of this selectivity mirrors anatomical and physiological relations throughout the cortex and is likely determined by the regional electrochemical composition. Being consistently patterned and actively regulated, the expression of molecules involved in synaptic transmission constitutes the most significant source of laminar and regional variability. Due to their complex kinetics and adaptability, synapses form a natural primary candidate underlying this regional temporal selectivity. The ability of cortical networks to reflect the temporal structure of the sensory environment can thus be regulated by evolutionary and experience-dependent processes.

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Barrels XXIX brought together researchers focusing on the rodent barrel cortex and associated systems. The meeting revolved around three themes: thalamocortical interactions in motor control, touch in rodent, monkey, and humans, and the nature of the multisensory computations the brain makes. Over two days these topics were covered as well as many more presentations that focused on the physiology, behavior, and development of the rodent whisker-to-barrel cortex system.


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Question: Towards quality metrics for OpenStreetMap

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Volunteered Geographic Information (VGI) is currently a "hot topic" in the GIS community. The OpenStreetMap (OSM) project is one of the most popular and well supported examples of VGL Traditional measures of spatial data quality are often not applicable to OSM as in many cases it is not possible to access ground-truth spatial data for all regions mapped by OSM. We investigate to develop measures of quality for OSM which operate in an unsupervised manner without reference to a "trusted" source of ground-truth data. We provide results of analysis of OSM data from several European countries. The results highlight specific quality issues in OSM. Results of comparing OSM with ground-truth data for Ireland are also presented.

The chapter deals with the issue of context definition in ::: adaptive cartography for the flood event.


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Question: Design of a high voltage pulse circuit for exciting ultrasonic transducers

Ultrasonic nondestructive testing with characters of fine resolution and low cost has well been developed and widely applied in modern industrial world. The generation of high voltage pulse to excite the transducer has been a critical challenge in an ultrasonic testing system. In this paper a DC/DC converting circuit with an input of 12V and an output of 300V and -300V independently is introduced, so is a pulse generator with pulse width configured by a FPGA with parameters transmitted through a PCI bus by VC++ program. With different connection of the circuit, a positive unipolar pulse, a negative unipolar pulse, a monocycle bipolar pulse and a 2-cycle bipolar pulse can be generated respectively. Finally some pulse characters which may influence the excitation of the ultrasonic transducer are analyzed, the spectrum signature of each type is presented in the later part of this paper.

A novel approach for the generation of broadband airborne ultrasound by using the thermo-acoustic effect is presented in this contribution. We investigate the applicability of resonance-free thermo-acoustic emitters for generation of very short high pressure airborne ultrasound pulses. A thermoacoustic emitter consisting of a 30 nm thin metallic film on a usual soda-lime glass substrate generates sound pressure values of more than 140 dB at 60 mm distance. The results are compared with conventional piezoelectric airborne ultrasound transducers. Our investigations show the applicability of the thermo-acoustic devices for broadband and high pressure ultrasound emitters using pulse excitation.


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Question: Simple Semi-supervised Dependency Parsing

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We present a simple and effective semisupervised method for training dependency parsers. We focus on the problem of lexical representation, introducing features that incorporate word clusters derived from a large unannotated corpus. We demonstrate the effectiveness of the approach in a series of dependency parsing experiments on the Penn Treebank and Prague Dependency Treebank, and we show that the cluster-based features yield substantial gains in performance across a wide range of conditions. For example, in the case of English unlabeled second-order parsing, we improve from a baseline accuracy of 92.02% to 93.16%, and in the case of Czech unlabeled second-order parsing, we improve from a baseline accuracy of 86.13% to 87.13%. In addition, we demonstrate that our method also improves performance when small amounts of training data are available, and can roughly halve the amount of supervised data required to reach a desired level of performance.


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Question: Radiation pattern measurement system for millimeter-wave antenna fed by contact probe

This paper presents a radiation pattern measurement system in order to evaluate mm-wave antenna fed by contact probe. It reduces the transmission loss by using a waveguide as a revolving arm. Three cut patterns can be measured by changing the orientation of the revolving arm. A differential feeding dipole antenna with a reflection plate was evaluated by using this measurement system. The measurement result of half-power beam width agrees well with the simulation result and the dynamic range is more than 20dB. By covering the possible scatterers in the anechoic chamber by planar electromagnetic absorber, the ripple in the half-power beam width is suppressed below ±0.5dB.

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Previously, we demonstrated the integration of an electrically small EZ antenna with a mesoband high power microwave (HPM) quarter-wave oscillator source. This design was confirmed with both computer modeling and experimental results for an EZ antenna with ka = 0.47. We also have reported results from computer simulations of a dual-band HPM EZ antenna system with resonances near 500 MHz and 1.5 GHz. In this paper we discuss the design of an EZ antenna array fed via the same mesoband source through a radial waveguide designed for handling high power levels.


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Question: A Survey of Definitions and Models of Exploratory Search

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

1. An Introduction to Geographical Information Systems and Participatory Geographical Information Science 2. A Micro-Macro Framework for Participatory Decision Situations 3. Methods and Tools for Participatory Spatial Decision Support 4. Social Behavioural Research Strategies for Investigating the Use of Participatory Geographical Information Systems 5. Collaborative Spatial Decision Making in Primary Health Care Management 6. Transportation Improvement Program Decision Making 7. Collaborative Decision Making About Habitat Restoration 8. Conclusions and Prospects for Future Research