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Question: Induction Heating Appliances: Toward More Flexible Cooking Surfaces

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Efficient energy management in residential areas is a key issue in modern energy systems. In this scenario, induction heating (IH) becomes an alternative to classical heating technologies because of its advantages such as efficiency, quickness, safety, and accurate power control. In this article, the design of modern flexible cooking surfaces featuring IH technology is presented. The main advantages and technical challenges are given, and the design of the inductor system and the power electronic converter is detailed. The feasibility of the proposed system is verified through a laboratory prototype.

Need for Condition Monitoring and Maintenance Management in Industries. Cost Effective Benefits of Condition Monitoring. Condition Monitoring Techniques. Machinery Fault Diagnosis. Vibration Condition Monitoring. Condition Monitoring of Gear Systems. Condition Monitoring of Hydraulic Systems. Condition Monitoring of Pneumatic Systems. Condition Monitoring of Electrical Machinery. Condition Monitoring of Turbomachinery. Wear and Oil Debris Monitoring. Artificial Neural Networks in Condition Monitoring. Infrared Thermography in Condition Monitoring. Expert Systems in Condition Monitoring. Corrosion Monitoring. Environmental Monitoring - Legal Aspects. Cost Effective Benefits of Maintenance. Reliability Centred Maintenance. Total Productive Maintenance. Modern Maintenance Management Techniques.


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Question: Robust C-Loss Kernel Classifiers

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The correntropy-induced loss (C-loss) function has the nice property of being robust to outliers. In this paper, we study the C-loss kernel classifier with the Tikhonov regularization term, which is used to avoid overfitting. After using the half-quadratic optimization algorithm, which converges much faster than the gradient optimization algorithm, we find out that the resulting C-loss kernel classifier is equivalent to an iterative weighted least square support vector machine (LS-SVM). This relationship helps explain the robustness of iterative weighted LS-SVM from the correntropy and density estimation perspectives. On the large-scale data sets which have low-rank Gram matrices, we suggest to use incomplete Cholesky decomposition to speed up the training process. Moreover, we use the representer theorem to improve the sparseness of the resulting C-loss kernel classifier. Experimental results confirm that our methods are more robust to outliers than the existing common classifiers.

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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: Locomotion Modes of an Hybrid Wheel-Legged Robot

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The main objective of this paper is to compare and evaluate the performance of several locomotion modes of an hybrid wheel-legged robot. Each studied locomotion mode is described, compared and evaluated according to the same criteria, which are the gradeability — i.e. the climbing ability — and the power consumption. A hierarchical scheme dedicated to the selection and the control of each locomotion mode is also presented.

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Experimental Studies Were Carried Out With Ejectors Having 2D And Multi Jet Nozzles To Determine If They Could Be Adopted To Drive A Low Speed Tunnel .A Model Tunnel Was Constructed And Results Obtained From Different Ejector Configurations Have Been Compared. ::: ::: The Study Suggests That An Annular Ejector Is Promising As A Candidate Configuration For Further Work Leading To An Application As A Wind Tunnel Drive.


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Question: On the Performance of NOMA-Based Cooperative Relaying Systems Over Rician Fading Channels

Non-orthogonal multiple access (NOMA) is a promising technique for the fifth generation (5G) wireless communications. As users with good channel conditions can serve as relays to enhance the system performance by using successive interference cancellation (SIC), the integration of NOMA and cooperative relaying has recently attracted increasing interests. In this paper, a NOMA-based cooperative relaying system is studied, and an analytical framework is developed to evaluate its performance. Specifically, the performance of NOMA over Rician fading channels is studied, and the exact expression of the average achievable rate is derived. Moreover, we also propose an approximation method to calculate the achievable rate by using the Gauss-Chebyshev Integration. Numerical results confirm that our derived analytical results match well with the Monte Carlo simulations.

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This chapter contains sections titled: Introduction Designing a C/M Scheme: The Gaussian Channel Perspective Wireless Channel: A New Perspective Flat Independent Fading Channel Block-Fading Channel Interference-Limited Channel Conclusions This chapter contains sections titled: References


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Question: Rice disease identification using pattern recognition techniques

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The techniques of machine vision are extensively applied to agricultural science, and it has great perspective especially in the plant protection field, which ultimately leads to crops management. The paper describes a software prototype system for rice disease detection based on the infected images of various rice plants. Images of the infected rice plants are captured by digital camera and processed using image growing, image segmentation techniques to detect infected parts of the plants. Then the infected part of the leaf has been used for the classification purpose using neural network. The methods evolved in this system are both image processing and soft computing technique applied on number of diseased rice plants.

Plant recognition based on digital leaf image has received as particular attention in computer vision and intelligence system, due its important implication in automatic plant identification. Plant species have the unique leaf characteristics such as the shape, texture, margin, and colour, which different each other. This study presents a novel method for automation plant recognition using Generalized Relevance Learning Vector Quantization (GRLVQ). GRLVQ is a competitive based learning algorithm which is integrating features extraction and classification phases. The experimental result shows that GRLVQ has better performance than the predecessor algorithm.


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Question: AN EXHAUSTIVE STUDY ON ASSOCIATION RULE MINING

Association Rule Mining is a data mining method that enables to find out frequent item set, interesting pattern, interesting correlation among set of items in a transactional database or data repositories. This paper establishes the preparatory of basic concept about Association Rule Mining. Broadly, Association Rule Mining can be classified into Apriori, Partitioning, and Frequent Pattern Tree Algorithms. This study is to show the Benefits and Limitations.

PROBLEMS CONNECTED WITH THE USE OF THE CORRELATION COEFFICIENT IN ANALYZING ENGINEERING DATA AND EXAMPLES OF ITS MISUSE ARE DISCUSSED. IN GENERAL, THE USE OF REGRESSION ANALYSIS SERVES THE ENGINEER BETTER. PITFALLS CONNECTED WITH COMPUTER ANALYSIS OF DATA ARE ALSO POINTED OUT. /AUTHOR/


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Question: Feature Selection for Time Series Forecasting: A Case Study

The integration of feature selection techniques within the modeling process of a time series forecaster can improve dealing with some usual important problems in this type of tasks, such as noise reduction, the curse of dimensionality and reducing the complexity of both the problem and the solution. In this paper we show how a convenient combination of feature selection procedures with soft computing techniques can be used to solve satisfactorily a real world problem. The problem is a rather hard one and consists of forecasting the amount of incoming calls for an emergency call center, so that the center managers can make a better resource planning.

Traditional Management and Management Engineering.- Dynamic Supply and Demand Balance Problems.- Linear and Probabilistic Resource Optimization and Allocation Problems.- Forecasting of Time Series.- Business Intelligence and Data Mining.- The Use of Game Theory.- Summary of Some Fundamental Management Engineering Principles.- Concluding Remarks.


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Question: A State-of-the-Art Review on Segmentation Algorithms in Intravascular Ultrasound (IVUS) Images

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Over the past two decades, intravascular ultrasound (IVUS) image segmentation has remained a challenge for researchers while the use of this imaging modality is rapidly growing in catheterization procedures and in research studies. IVUS provides cross-sectional grayscale images of the arterial wall and the extent of atherosclerotic plaques with high spatial resolution in real time. In this paper, we review recently developed image processing methods for the detection of media-adventitia and luminal borders in IVUS images acquired with different transducers operating at frequencies ranging from 20 to 45 MHz. We discuss methodological challenges, lack of diversity in reported datasets, and weaknesses of quantification metrics that make IVUS segmentation still an open problem despite all efforts. In conclusion, we call for a common reference database, validation metrics, and ground-truth definition with which new and existing algorithms could be benchmarked.

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: Distributed Method of Multiplier for Coupled Lagrangian Problems: A Control Approach

In this paper, we propose a method for solving the distributed optimization problem in which the objective function is the sum of separable convex functions with linear constraints. In our approach, the primal variable is partially updated to make the Method of Multiplier algorithm distributed which is based on the suitable scaling of constraint matrix. The algorithm is then viewed as a dynamical system the convergence analysis of which is done using the passivity concepts of nonlinear control theory. The convexity of the function is related to the passivity of the non-linear functions which is in feedback with the positive real linear system.

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One dimensional problems.- The Analytical Behaviour of Solutions.- Finite Difference Schemes for Convection-Diffusion Problems.- Finite Element and Finite Volume Methods.- Discretisations of Reaction-Convection-Diffusion Problems.- Layer-Adapted Meshes.- Two dimensional problems.- The Analytical Behaviour of Solutions.- Reaction-Diffusion Problems.- Convection-Diffusion Problems.


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Question: Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering

A popular recent approach to answering open-domain questions is to first search for question-related passages and then apply reading comprehension models to extract answers. Existing methods usually extract answers from single passages independently. But some questions require a combination of evidence from across different sources to answer correctly. In this paper, we propose two models which make use of multiple passages to generate their answers. Both use an answer-reranking approach which reorders the answer candidates generated by an existing state-of-the-art QA model. We propose two methods, namely, strength-based re-ranking and coverage-based re-ranking, to make use of the aggregated evidence from different passages to better determine the answer. Our models have achieved state-of-the-art results on three public open-domain QA datasets: Quasar-T, SearchQA and the open-domain version of TriviaQA, with about 8 percentage points of improvement over the former two datasets.

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: Learning To Use Formulas To Solve Simple Arithmetic Problems

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Solving simple arithmetic word problems is one of the challenges in Natural Language Understanding. This paper presents a novel method to learn to use formulas to solve simple arithmetic word problems. Our system, analyzes each of the sentences to identify the variables and their attributes; and automatically maps this information into a higher level representation. It then uses that representation to recognize the presence of a formula along with its associated variables. An equation is then generated from the formal description of the formula. In the training phase, it learns to score the pair from the systematically generated higher level representation. It is able to solve 86.07% of the problems in a corpus of standard primary school test questions and beats the state-of-the-art by

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 77-GHz FMCW Radar System Using On-Chip Waveguide Feeders in 65-nm CMOS

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This paper presents a 77-GHz radar system using a transmitter (Tx) and receiver (Rx) integrated with on-chip waveguide feeders in 65-nm CMOS. The newly proposed on-chip waveguide feeder shows the insertion loss of about 2 dB and more than 30% bandwidth. Additionally, both the Tx and Rx are integrated with internal $\times$ 10 frequency multipliers. Therefore, a radar system can be easily implemented without sensitive millimeter-wave packaging technology by mounting the Tx and Rx chips on the waveguide aperture. The interconnections for the low-frequency reference and baseband signals can be realized on the low-cost FR-4 printed circuit board. The radar system shows 9-dBm output power and 13-dB down-conversion gain from the waveguide port.

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: Design of Kernels in Convolutional Neural Networks for Image Classification

Despite the effectiveness of convolutional neural networks (CNNs) for image classification, our understanding of the effect of shape of convolution kernels on learned representations is limited. In this work, we explore and employ the relationship between shape of kernels which define receptive fields (RFs) in CNNs for learning of feature representations and image classification. For this purpose, we present a feature visualization method for visualization of pixel-wise classification score maps of learned features. Motivated by our experimental results, and observations reported in the literature for modeling of visual systems, we propose a novel design of shape of kernels for learning of representations in CNNs.

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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: Delay Tolerant Networking for smart city through drones

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Sensors in future smart cities will continuously monitor the environment in order to prevent critical situations and waste of resources or to offer new services to end users. Likely, the existing networks will not be able to sustain such a traffic without huge investments in the telecommunication infrastructure. One possible solution to overcome these problems is to apply the Delay Tolerant Network (DTN) paradigm, that is to exploit the movement of objects, possibly carrying data toward the final destination. Depending on location of data sources in the area and on paths followed by moving objects some sources could be isolated. In order to fix this issue, we use a drone, flying at proper instant of time over the isolated sources to deliver their data to the final destination. The impact of the presence of a drone as relay of the DTN is investigated accounting for realistic constraints, such as limited drone flight duration.

Ambient Intelligence (AmI) refers to electronic environments that are sensitive and responsive to the presence of people. Ambient intelligence is closely related to the long term vision of an intelligent service system in which technologies are able to automate a platform embedding the required devices for powering context aware, personalized, adaptive and anticipatory services. Ambient intelligence is a vision on the future of consumer electronics, telecommunications and computing that was originally developed in the late 1990s for the time frame 2010-2020.This paper on Vibrant Ambient Intelligence with Agents based Service Oriented Approach focuses on the ambient intelligence environment of managing the traffic congestion control in Coimbatore city through VAISTC4 proposal without crippling the mobility of users using Mobile Internet Protocol Version 6(IPV6). It also discusses on the benefit of coupling service-oriented approach and multi-agent systems towards more appropriate interactions with users.Wi...


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Question: Enhanced Knowledge Management by Synchronizing Mind Maps and Fuzzy Cognitive Maps

This paper presents a conceptual approach to enhance knowledge management by synchronizing mind maps and fuzzy cognitive maps. Using mind maps takes advantage of human creativity, while fuzzy cognitive maps can store and retrieve information expressed in natural language. Applying the concepts of cognitive computing makes it possible to gather and extract relevant information from a data pool. Therefore, this approach is intended to provide a framework that enhances knowledge management. To demonstrate the potential of this framework, a use case concerning the development of a smart city app is presented.

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Question: An Investigation of Customization in ERP System Implementations

This research investigates why certain enterprise resource planning (ERP) system adopters have pursued high levels of software customization during implementation despite the generally accepted best-practice heuristic of limiting customization. Qualitative data from ERP adoption projects and consultants working with ERP implementations have been collected. This study empirically identifies customization drivers and explains their relationship to customization. The results suggest that high customization may occur because of: unnecessary redevelopment of functionality that is available in the ERP system standard, resistance to change based on cultural issues and low project acceptance, insufficient weight given to the implementation team's recommendations, and the implementation team's lack of opposition to customization requests. The results of this study also explain how these problems occur and why they lead to overcustomization.

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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: Recycling zinc oxide varistor blocks for electro-active silicone composites

The recycling process toward the elimination of varistor wastes into new electro-active silicon composites has been investigated. We studied the dependence of the E-J characteristics on the aggregate content in the polymer matrix. Formulations with 40 vol.% metal oxide varistor aggregates in the 100-200 μm range exhibit reliable nonlinear behavior with a switching voltage of 280±30 V/mm. The breakdown voltage of the composite decreases as both filler's diameter and filler's volume fraction increases in the 550-220 V/mm and 440-280 V/mm range, respectively. This paves the way for the valorization of varistors based zinc oxide (ZnO) ceramics.

Piezoelectric sensor can produce voltage when deflected (function as an energy harvester) while piezoelectric actuator can deflect when a voltage is applied. Different device applications have different requirements on the thickness and in-plane geometry of the Lead Zirconate Titanate(PZT) piezoelectric layers and thus have their own processing difficulties. In this paper, PZT-Au-Si cantilever is fabricated by eutectic bonding and dicing process.The properties of lapped PZT ceramics and silicon cantilever is also evaluated. The PZT-Au-Si cantilever applications for both piezoelectric actuators and energy harvesters have been confirmed.


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Question: Traffic accident detection through a hydrodynamic lens

In this paper we present a novel method for automatic traffic accident detection, based on Smoothed Particles Hydrodynamics (SPH). In our method, a motion flow field is obtained from the video through dense optical flow extraction. Then a thermal diffusion process (TDP) is exploited to turn the motion flow field into a coherent motion field. Approximating the moving particles to individuals, their interaction forces, represented as endothermic reactions, are computed using the enthalpy measure, thus obtaining the potential particles of interest. Furthermore, we exploit SPH that accumulates the contribution of each particle in a weighted form, based on a kernel function. The experimental evaluation is conducted on a set of video sequences collected from Youtube, and the obtained results are compared against a state of the art technique.

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This thesis presents an experimental evaluation of the road grip estimator RT3 Curve manufactured by Halliday Technologies Inc. RT3 Curve can be pictured as a small trailer that is coupled behind a ...


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Question: Motivation in online learning: Testing a model of self-determination theory

As high attrition rates becomes a pressing issue of online learning and a major concern of online educators, it is important to investigate online learner motivation, including its antecedents and outcomes. Drawing on Deci and Ryan's self-determination theory, this study proposed and tested a model for online learner motivation in two online certificate programs (N=262). Results from structural equation modeling provided evidence for the mediating effect of need satisfaction between contextual support and motivation/self-determination; however, motivation/self-determination failed to predict learning outcomes. Additionally, this study supported SDT's main theorizing that intrinsic motivation, extrinsic motivation, and amotivation are distinctive constructs, and found that the direct effect and indirect effects of contextual support exerted opposite impacts on learning outcomes. Implications for online learner support were discussed.

Informed by the Cognitive Mediation Model of media learning, this study explores how self-efficacy and information-processing strategies jointly impact the learning of health knowledge. Using survey data (N=1409), the study examines the roles that self-efficacy, motivation of media use, news attention, and elaboration play in acquiring knowledge about swine flu during the 2009 global pandemic crisis. Results support the hypothesized relationships among self-efficacy, motivation, attention to and elaboration of swine flu news, and knowledge about the flu. Implications of the findings to advance the research in mediated cognitive learning are discussed.


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Question: The design and implementation of new Vehicle Black Box using the OBD information

In this paper, the new Vehicle Black Box, which is named E-Black Box (Enhanced Black Box), is designed and developed. The E-Black Box is the combination of all the advantages of previous Black Boxes and Event Data Recorders (EDRs). The E-Black Box communicates with Electronic Control Units (ECUs) to read the status of vehicle via OBD port. It is equipped with camera that records the video in front of the vehicle. As the common vehicle Black Box, the E-Black Box also has Global Positioning System (GPS) for reading the current latitude and longitude of the vehicle point. The 9 Degrees of Freedom (DOF) of inertial sensor, which is incorporated triple-axis gyro senor, triple-axis accelerometer sensor and triple-axis magnetometer sensor, is integrated with E-Black Box to read the velocity, acceleration and orientation of vehicle after which we analyze the stability of vehicle during the travel. After collecting and synchronizing all data, the E-Black Box saves them in Secure Digital (SD) Card.

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This paper introduces the main function and technology of The Video Sync Separator briefly.


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Question: Projective Bundle Adjustment from Arbitrary Initialization Using the Variable Projection Method

Bundle adjustment is used in structure-from-motion pipelines as final refinement stage requiring a sufficiently good initialization to reach a useful local mininum. Starting from an arbitrary initialization almost always gets trapped in a poor minimum. In this work we aim to obtain an initialization-free approach which returns global minima from a large proportion of purely random starting points. Our key inspiration lies in the success of the Variable Projection (VarPro) method for affine factorization problems, which have close to 100 % chance of reaching a global minimum from random initialization. We find empirically that this desirable behaviour does not directly carry over to the projective case, and we consequently design and evaluate strategies to overcome this limitation. Also, by unifying the affine and the projective camera settings, we obtain numerically better conditioned reformulations of original bundle adjustment algorithms.

Introduction. Instruments. Depth and Transverse Resolution. Phase Imaging. Applications. Appendix A: Vector Field Theory for Depth and Transverse Resolution of a CSOM.


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Question: User Interface Development for Interactive Television: Extending a Commercial DTV Platform to the Virtual Channel API

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Abstract We explore the generation of interactive computer graphics at digital set-top boxes in place of the fixed graphics that were embedded to the television video before the broadcast. This direction raises new requirements for user interface development, since the graphics are merged with video at each set-top box dynamically, without the traditional quality control from the television producers. Besides the technical issues, interactive computer graphics for television should be evaluated by television viewers. We employ an animated character in an interactive music television application that was evaluated by consumers, and was developed using the Virtual Channel Control Library, a custom high-level API, that was built using Microsoft Windows and TV technologies.

Introduction to the HyperText Markup Language HTML and Document Design The Design of HTML Document Collections HTML in Detail The Next Generation HTML 3, Stylesheets, and Applets Uniform Resource Locators (URLs) The HTTP Protocol Communication with the Common Gateway Interface CGI Programs and Tools HTML and Web Utilities and Tools Web Developer Resources Real-World Examples Appendices Glossary Index.


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Question: Planar High-efficiency Antenna Array Using New Printed Ridge Gap Waveguide Technology

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High-efficiency millimeter wave antenna array is proposed. A cooperate feeding network is designed using the new printed ridge gap waveguide technology, which is self-packaged with low loss. The feeding network is designed to couple to narrow slots arranged in a planar array that is coupled to printed broadband magnetoelectric (ME) dipoles. An array of $4 \times 4$ ME dipoles is designed. The simulated results are verified with measurements. The measured reflection coefficient is less than −10 dB over 16.5% bandwidth (28.8–34 GHz). The measured antenna gain is higher than 19 dBi, and the cross polarization measured gain is around −35 dB within the main beam. Furthermore, the measured total radiation efficiency is 70%, and the measured aperture efficiency corresponds to 90% at 30.2 GHz.

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


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Question: Interactive multimodal music transcription

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For example, ['Represent the abstract for retrieving the scientific paper title', 'A series of 3-(2H-1,2,4-triazol-5-yl)-1,3-thiazolidin-4-one derivatives (7c–l) was designed and synthesized. Their structures have been elucidated based on analytical and spectral data. They were evaluated for their antibacterial and antifungal activities. Compound 7h showed the highest activity against all tested strains, except P. vulgaris, with MIC 8 μg/mL and 4 μg/mL against S. aureus and C. albicans, respectively. Furthermore, Compounds 7c, 7h, and 7j demonstrated moderate anti-mycobacterium activity. The binding mode of the synthesized thiazolidinones to bacterial MurB enzyme was also studied. Good interactions between the docked compounds to the MurB active site were observed primarily with Asn83, Arg310, Arg188 and Ser82 amino acid residues.'] should be similar to ['Represent this paper title in order to find a scientific intro to what it is about', 'Design, Synthesis, Antimicrobial Evaluation and Molecular Modeling Study of 1,2,4-Triazole-Based 4-Thiazolidinones']

Automatic music transcription has usually been performed as an autonomous task and its evaluation has been made in terms of precision, recall, accuracy, etc. Nevertheless, in this work, assuming that the state of the art is far from being perfect, it is considered as an interactive one, where an expert user is assisted in its work by a transcription tool. In this context, the performance evaluation of the system turns into an assessment of how many user interactions are needed to complete the work. The strategy is that the user interactions can be used by the system to improve its performance in an adaptive way, thus minimizing the workload. Also, a multimodal approach has been implemented, in such a way that different sources of information, like onsets, beats, and meter, are used to detect notes in a musical audio excerpt. The system is focused on monotimbral polyphonic transcription.

Geolocalized photographical pictures realized during urban walkthrough are able to constitute a pertinent research matter for pedestrian emotional and semantical effects perception and representation acknowledgement. Ideoscenic-images manipulation processes analysis enables infra-logical access to visual ambiances recorded with the parameterized camera (framing, point, density…). So-producted knowledge is then integrated in a so-called perlaboration environment for urban planning actors.


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Question: A survey on extractive text summarization

Text Summarization is the process of obtaining salient information from an authentic text document. In this technique, the extracted information is achieved as a summarized report and conferred as a concise summary to the user. It is very crucial for humans to understand and to describe the content of the text. Text Summarization techniques are classified into abstractive and extractive summarization. The extractive summarization technique focuses on choosing how paragraphs, important sentences, etc produces the original documents in precise form. The implication of sentences is determined based on linguistic and statistical features. In this work, a comprehensive review of extractive text summarization process methods has been ascertained. In this paper, the various techniques, populous benchmarking datasets and challenges of extractive summarization have been reviewed. This paper interprets extractive text summarization methods with a less redundant summary, highly adhesive, coherent and depth information.

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The web has become a large knowledge provider for society, allowing people to not just consume information but also produce it. Collaborative documents bring some significant advantages and decentralization, but they also raise questions concerning its quality. In this work, we explore the quality assessment on collaborative documents using these documents' topics. The proposed approach improved in 3.2% the accuracy of quality assesment of Wikipedia content. Then, the main contribution in this paper is an analysis of how we can use topic modelling in order to improve quality prediction performance.


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Question: Design and control of a soft and continuously deformable 2D robotic manipulation system

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In this paper we describe the design, fabrication, control, and experimental validation of a soft and highly compliant 2D manipulator. The arm consists of several body segments actuated using bi-directional fluidic elastomer actuators and is fabricated using a novel composite molding process. We use a cascaded PI and PID computation and novel fluidic drive cylinders to provide closed-loop control of curvature for each soft and highly compliant body segment. Furthermore, we develop algorithms to compute the arm’s forward and inverse kinematics in a manner consistent with piece-wise constant curvature continuum manipulators. These computation and control systems enable this highly compliant robot to autonomously follow trajectories. Experimental results with a robot consisting of six segments show that controlled movement of a soft and highly compliant manipulator is feasible.

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Prototyping and fabrication of nanodevices require subnanometer tolerances and highly accurate sensing and actuation. Improved control on manipulating matter at the nanoscale is of relevance in different fields such as the automotive industry, biotechnology and communication. Limitations of existing nanomanipulation systems include constrained motion of manipulator end-effectors. In the present paper, a new AFM probe design suitable for nanomanipulation is proposed. The design includes a nanomanipulation piezotube that allows actuation and sensing of the tip motion in three directions. In addition, a piezopatch is attached to the cantilever holder for in-situ stiffness tuning needed for manipulating large and sticky nanosamples. Design considerations and path tracking performance of the proposed manipulator are analyzed.Copyright © 2010 by ASME


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Question: Correctly Rounded Arbitrary-Precision Floating-Point Summation

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We present a fast algorithm together with its low-level implementation of correctly rounded arbitrary-precision floating-point summation. The arithmetic is the one used by the GNU MPFR library: radix 2; no subnormals; each variable (each input and the output) has its own precision. We also give a worst-case complexity of this algorithm and describe how the implementation is tested.

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What is a Macro How do Macros Work A Few Short Macros Using the Macro Debugger (Rel 2.2) and STEP Mode Using MacroLearn (Rel 2.2) and Macro Record (Rel 3) Using the Macro Run Keyin Rel 2.2 and 3 The Macro Programming Commands The Art of Range Naming Creating a Macro Library in Rel 2.2 and 3 Togglesand Pop-Ups Self-Modifying Macros The If Command Counters and the For Loop The Print Macros Using String Formulas Day-of-the-Week and Mail Merge Using Multidimensional Worksheets in 3.0 Macros Special Applications and Higher Level Programming.


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Question: Live-fly, large-scale field experimentation for large numbers of fixed-wing UAVs

In this paper, we present extensive advances in live-fly field experimentation capabilities of large numbers of fixed-wing aerial robots, and highlight both the enabling technologies as well as the challenges addressed in such largescale flight operations. We showcase results from recent field tests, including the autonomous launch, flight, and landing of 50 UAVs, which illuminate numerous operational lessons learned and generate rich multi-UAV datasets. We detail the design and open architecture of the testbed, which intentionally leverages low-cost and open-source components, aimed at promoting continued advances and alignment of multi-robot systems research and practice.

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Robotic Sensor Networks composed of robots and wireless sensing devices hold the potential to revolutionize environmental sciences by enabling researchers to collect data across expansive environments, over long, sustained periods of time. We report progress on building such systems for two applications. The first application is on monitoring invasive fish (common carp) in inland lakes. In the second application, the robots act as data mules and collect data from sparsely deployed wireless sensors.


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Question: Clamp-and-Forget: A self-sustainable non-invasive wireless sensor node for smart metering applications

Measuring and managing the power consumption of household appliances, as well as that of industrial machineries, is becoming more and more important to improve the distribution and usage of the electrical energy and to reduce the energy bill. We present the design of a non-invasive wireless current meter which can measure AC current up to 60 A RMS exploiting a small clamp-on inductive sensor. The novelty of the design is a subsystem consisting of a harvesting circuit designed to extract energy from the same current transducer used for measurements. Experiments have been conducted to validate the approach, to assess the accuracy of the sensing system and deviations due to the energy harvester, and to determine the condition which permits us to achieve the energy neutrality and thus, a self-sustainable smart meter.

A packaged self-powered system by hybridizing nanogenerators (PSNGS) is demonstrated. The performance of the PSNGS is tested in a biofluid and used for powering an electronic thermometer. Select waterproof universal connectors are designed and fabricated for energy and signal transmission. This PSNGS and the connectors can significantly advance the development of self-powered implanted medical devices and wearable/portable electronics.


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Question: Genome-wide identification and comparative analysis of the heat shock transcription factor family in Chinese white pear (Pyrus bretschneideri) and five other Rosaceae species

Background ::: Heat shock transcription factors (Hsfs), which act as important transcriptional regulatory proteins in eukaryotes, play a central role in controlling the expression of heat-responsive genes. At present, the genomes of Chinese white pear (‘Dangshansuli’) and five other Rosaceae fruit crops have been fully sequenced. However, information about the Hsfs gene family in these Rosaceae species is limited, and the evolutionary history of the Hsfs gene family also remains unresolved.

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Oryza longistaminata is the only AA-genome Oryza species that is perennial via rhizome production. This undomesticated rice species, which is native to Africa, is hypothesized to be a good candidate for expanding the cultivated rice gene pool. However, its phylogenetic relationships with other Oryza members are still unresolved, and it is underutilized as a genetic resource in the breeding of cultivated rice (Oryza sativa L.). This study therefore genotyped 361 O. longistaminata, 35 cultivated rice, 1 Japonica weedy-type, 25 AA genome and 8 CC genome wild rice accessions by using 67 SSR markers. Genotypic grouping confirmed the distinctness of O. longistaminata from other rice accessions and the sub-differentiation of this population influenced by eco-geographical conditions. The higher genetic diversity within the O. longistaminata population also implies its candidacy as a donor of diverse traits of interest.


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For example, '['Represent the title for retrieving the corresponding scientific abstract', 'Security in software : How software companies work with security during a software development process']' should have a representation like '['represent this abstract from a paper to retrieve its scientific title', 'This study is conducted, due to recent interest in privacy and software security, on how a number of software development companies work during a development process to develop secure software to t ...']' but very far from '['Represent this abstract from a paper to retrieve its scientific title', 'Many IoT devices lack basic security requirements. The small size and limited processing power of many connected devices could inhibit encryption and other robust security measures. People need understanding of limitations of devices due to their size and the approaches for providing security. The challenges for implementing the security of embedded devices and providing end-to-end security are the outcomes of this study.']'.

Question: Design and analysis of cable-connected metallic bellows as Variable Buoyancy Modules

Design of a variable buoyancy system with metallic bellows for underwater applications is presented here. Metallic bellow with a Linear Actuator is proposed as the Variable Buoyancy module. The metallic bellow is approximated as a cylinder and modelled mathematically to study the behavior of the module underwater. The response of the system at different initial orientation and the velocity of the system at different positive buoyancy are studied. The dynamics of the module, when anchored to an underwater platformand the motion characteristics of the module with various buoyancy levels are studied. Two similar modules are then cascaded one above the other and their performance is analyzed with alternative sequence of actuation.

Research on Active Vibration Control System (AVCS) is being carried out to reduce structural vibrations caused by unwanted vibrations in many application areas such as in space, aircraft structures, satellites, automobiles and civil structures (bridges), particularly at low frequencies. In this paper; we have discussed Active Vibration Control technique by using open loop control system. Result from ANSYS and experimental results from FFT analyzer were compared. The experimental results are presented for the cantilever beam excited at one of its natural frequency using active vibration control system. For open loop control system, less reduction were observed and the reasons were discussed for it. Keywords—Piezoelectric(PZT), Active Vibration Control(AVC), Cantilever beam, Actuator, Electro-dynamic shaker,ANSYS, FFT


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Question: A Comparative Study on Machine Learning Classification Models for Activity Recognition

Activity Recognition (AR) systems are machine learning models developed for cell-phones and smart wearables to recognize various real-time human activities such as walking, standing, running and biking. In this paper, the performance (accuracy and computational time) of several well-known supervised and unsupervised learning models including Logistic Regression, Support Vector Machine, K-Nearest Neighbors’, Naive Base, ’Decision Tree’ and Random Forest are examined on a dataset. It is shown that Random Forest model outperforms other models with accuracy over 99 percent. It is shown that PCA significantly improved the performance of Artificial Neural Network with one hidden layer and SVM models in both accuracy and time, while PCA showed to have negative impacts on Random Forest or Decision Tree models by increasing the running time and decreasing the prediction accuracy.

Traditional Management and Management Engineering.- Dynamic Supply and Demand Balance Problems.- Linear and Probabilistic Resource Optimization and Allocation Problems.- Forecasting of Time Series.- Business Intelligence and Data Mining.- The Use of Game Theory.- Summary of Some Fundamental Management Engineering Principles.- Concluding Remarks.


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Question: Irony Detection in Twitter: The Role of Affective Content

Irony has been proven to be pervasive in social media, posing a challenge to sentiment analysis systems. It is a creative linguistic phenomenon where affect-related aspects play a key role. In this work, we address the problem of detecting irony in tweets, casting it as a classification problem. We propose a novel model that explores the use of affective features based on a wide range of lexical resources available for English, reflecting different facets of affect. Classification experiments over different corpora show that affective information helps in distinguishing among ironic and nonironic tweets. Our model outperforms the state of the art in almost all cases.

ABSTRACTIn a recent article, Ma, Dixon, and Hmielowski (2019. Psychological Reactance from Reading Basic Facts on Climate Change: The Role of Prior Views and Political Identification. Environmental...


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Question: Failure mode and effects analysis by data envelopment analysis

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Failure mode and effects analysis (FMEA) is a method that examines potential failures in products or processes and has been used in many quality management systems. One important issue of FMEA is the determination of the risk priorities of failure modes. In this paper we propose an FMEA which uses data envelopment analysis (DEA), a well-known performance measurement tool, to determine the risk priorities of failure modes. The proposed FMEA measures the maximum and minimum risks of each failure mode. The two risks are then geometrically averaged to measure the overall risks of failure modes. The risk priorities are determined in terms of overall risks rather than maximum or minimum risks only. Two numerical examples are provided and examined using the proposed FMEA to show its potential applications and benefits.

Knowledge discovery methods used to find relationships among software engineering data and the extraction of rules have gained increasing importance in recent years. These methods have become necessary for improvements in the quality of the software product and the process. The focus of this paper is a first attempt towards combining strengths of rough set theory and neuro-fuzzy decision trees in classifying software defect data. We compare classification results for four methods: rough sets, neuro-fuzzy decision trees, partial decision trees, rough-neuro-fuzzy decision trees. The analysis of the results include a family-wise 10 fold paired t-test for accuracy and number of rules. The contribution of this paper is the application of a hybrid rough-neuro-fuzzy decision tree method in classifying software defect data.


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Question: Inductive wireless power transfer for electric vehicle dynamic charging

The aim of the paper is to present an overview of inductive wireless power transfer (WPT) technologies for the application of electric vehicles (EVs) wireless charging. The basic principles of this technology are introduced followed by a classification of power electronic architectures and the magnetic coupler design. The advantages and limitations of each technology for EV dynamic charging are discussed. The recent progress, technical issues, challenges and state-of-art researches are introduced. An efficient design of WPT charging system is proposed and studied in VEDECOM institute. The innovative solution is an optimized magnetic coupler associated with the use of new semiconductors components the most challenging EV charging application's requirements.

Abstract With the standardization of communication done, reliable power sources are the main challenge faced by wireless system in industrial automation. While primary cells are suitable power sources, they still require maintenance after several years which increases the total cost of a wireless network. In this paper we analyze the state of the art with primary cells and the standard electronics and show possible approaches to increase the service life of wireless industrial devices.


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Question: Novel in-wheel axial-flux segmented switched reluctance motor

In this paper a novel axial-flux segmented rotor switched reluctance motor (AFSSRM) with a stator sandwiched by two rotors with a particular form of the segments is presented. The machine has magnetic short paths with no flux reversal and the active magnetic parts are made of soft magnetic composites. An in-wheel AFSSRM, specially intended for direct drive of light motorcycles, is designed. Electromagnetic analysis of the AFSSRM is carried out using 3D finite element. Matlab-Simulink simulations of the whole in-wheel AFSSRM drive are used to verify its behavior.

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A directly coupled linear permanent magnet generator of longitudinal flux-type is investigated. The generator will be used for power take-off in a wave energy converter. A combined field- and circ ...


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Question: Automatic Detection of Fake News

The proliferation of misleading information in everyday access media outlets such as social media feeds, news blogs, and online newspapers have made it challenging to identify trustworthy news sources, thus increasing the need for computational tools able to provide insights into the reliability of online content. In this paper, we focus on the automatic identification of fake content in online news. Our contribution is twofold. First, we introduce two novel datasets for the task of fake news detection, covering seven different news domains. We describe the collection, annotation, and validation process in detail and present several exploratory analysis on the identification of linguistic differences in fake and legitimate news content. Second, we conduct a set of learning experiments to build accurate fake news detectors. In addition, we provide comparative analyses of the automatic and manual identification of fake news.

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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: Designing for Deeper Learning in a Blended Computer Science Course for Middle School Students.

The focus of this research was to create and test an introductory computer science course for middle school. Titled “Foundations for Advancing Computational Thinking” (FACT), the course aims to prepare and motivate middle school learners for future engagement with algorithmic problem solving. FACT was also piloted as a seven-week course on Stanford’s OpenEdX MOOC platform for blended in-class learning. Unique aspects of FACT include balanced pedagogical designs that address the cognitive, interpersonal, and intrapersonal aspects of “deeper learning”; a focus on pedagogical strategies for mediating and assessing for transfer from block-based to text-based programming; curricular materials for remedying misperceptions of computing; and “systems of assessments” (including formative and summative quizzes and tests, directed as well as open-ended programming assignments, and a transfer test) to get a comprehensive picture of students’ deeper computational learning. Empirical investigations, accomplished over t...

Teacher Knowledge of LGBT Issues and Student Bullying of LGBT Classmates in Japan: Report of Incidence and Community Based Programs to Address Identified Problems. (Community) Makiko Kasai; International Journal of Psychology


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Question: Corpus-Oriented Grammar Development for Acquiring a Head-Driven Phrase Structure Grammar from the Penn Treebank

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This paper describes a method of semi-automatically acquiring an English HPSG grammar from the Penn Treebank. First, heuristic rules are employed to annotate the treebank with partially-specified derivation trees of HPSG. Lexical entries are automatically extracted from the annotated corpus by inversely applying HPSG schemata to partially-specified derivation trees. Predefined HPSG schemata assure the acquired lexicon to conform to the theoretical formulation of HPSG. Experimental results revealed that this approach enabled us to develop an HPSG grammar with significant robustness at small cost.

I Classification.- 1 Introduction.- 2 Lexical Analysis: A New Approach.- 3 Author's Motivation for a Speech Act Classification.- 4 Description and Explanation of the Method.- 5 Survey of the Resulting Speech Act Classification.- 6 Prospects and Limitations.- 7 References.- II Lexicon Sections.- Directions for Using Lexicon Section I.- 8 Lexicon Section I Semantic Classification of Speech Act Verbs.- Directions for Using Lexicon Section II.- 9 Lexicon Section II Alphabetic Index of Speech Act Verbs.


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Question: Disordered speech recognition using acoustic and sEMG signals.

Parallel isolated word corpora were collected from healthy speakers and individuals with speech impairment due to stroke or cerebral palsy. Surface electromyographic (sEMG) signals were collected for both vocalized and mouthed speech production modes. Pioneering work on disordered speech recognition using the acoustic signal, the sEMG signals, and their fusion are reported. Results indicate that speakerdependent isolated-word recognition from the sEMG signals of articulator muscle groups during vocalized disorderedspeech production was highly effective. However, word recognition accuracy for mouthed speech was much lower, likely related to the fact that some disordered speakers had considerable difficulty producing consistent mouthed speech. Further development of the sEMG-based speech recognition systems is needed to increase usability and robustness.

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A discriminative feature extraction based on Principal component analysis (PCA) and Gaussian mixture models is presented to increase the discrimative capability of modified two dimentional root cepstrum analysis (MTDRC). The exprimental results show that F-ratio tests indicate better separability of phonemes by using discriminative feature extraction than MTDRC.


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Question: An analysis of memory power consumption in database systems

The growing appetite for in-memory computing is increasing memory's share of total server power consumption. However, memory power consumption in database management systems is not well understood. This paper presents an empirical characterization of memory power consumption in database systems, for both analytical and transactional workloads. Our results indicate that memory power optimization will be effective only if it can reduce back-ground power through more aggressive use of low power memory idle states.

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This paper describes an intelligent object model using rough set approach to do data mining on an expanding data set. It also presents the discussion of an example of the traffic control signals.


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Question: Spreadsheet data manipulation using examples

Millions of computer end users need to perform tasks over large spreadsheet data, yet lack the programming knowledge to do such tasks automatically. We present a programming by example methodology that allows end users to automate such repetitive tasks. Our methodology involves designing a domain-specific language and developing a synthesis algorithm that can learn programs in that language from user-provided examples. We present instantiations of this methodology for particular domains of tasks: (a) syntactic transformations of strings using restricted forms of regular expressions, conditionals, and loops, (b) semantic transformations of strings involving lookup in relational tables, and (c) layout transformations on spreadsheet tables. We have implemented this technology as an add-in for the Microsoft Excel Spreadsheet system and have evaluated it successfully over several benchmarks picked from various Excel help forums.

A problem that the writer faced during the course of a actual subject was analyzed, and a viable solution was proposed to settle this problem. Implementation of importing and exporting data of an office document to SQL Server field based on ADO Stream object as well as the ADO Stream object and its main technique were introduced.


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Question: Foundation and methodologies in computer-aided diagnosis systems for breast cancer detection

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Objectives: A modified variable step block backward differentiation formulae (MVS-BBDF) method is introduced in this paper as another alternative way for solving ordinary differential equations (ODEs). Methods: We demonstrated the detailed formulation of the corrector formulae for MVS-BBDF method which is carried out using Maple software. Then, to validate the performance of the introduced method, we applied it to stiff ODEs problem. Findings: The performance of the method in terms of maximum error and number of total steps taken during the computation are compared with the performance of ode15s and ode23s solver in MATLAB. Consequently, the efficiency of MVS-BBDF shows that it is able to outperform both Matlab’s ODE solver since it produces better accuracy and manages to reduce the number of total step.

Objectives ::: There has been continuous development in the area of stereoscopic medical imaging devices, and many stereoscopic imaging devices have been realized and applied in the medical field. In this article, we review past and current trends pertaining to the application stereo-imaging technologies in the medical field.


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Question: Document Clustering Using K-Means, Heuristic K-Means and Fuzzy C-Means

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Document clustering refers to unsupervised classification (categorization) of documents into groups (clusters) in such a way that the documents in a cluster are similar, whereas documents in different clusters are dissimilar. The documents may be web pages, blog posts, news articles, or other text files. This paper presents our experimental work on applying K-means, heuristic K-means and fuzzy C-means algorithms for clustering text documents. We have experimented with different representations (tf, tf.idf & Boolean) and different feature selection schemes (with or without stop word removal & with or without stemming). We ran our implementations on some standard datasets and computed various performance measures for these algorithms. The results indicate that tf.idf representation, and use of stemming obtains better clustering. Moreover, fuzzy clustering produces better results than both K-means and heuristic K-means on almost all datasets, and is a more stable method.

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: A Survey on Load Testing of Large-Scale Software Systems

Many large-scale software systems must service thousands or millions of concurrent requests. These systems must be load tested to ensure that they can function correctly under load (i.e., the rate of the incoming requests). In this paper, we survey the state of load testing research and practice. We compare and contrast current techniques that are used in the three phases of a load test: (1) designing a proper load, (2) executing a load test, and (3) analyzing the results of a load test. This survey will be useful for load testing practitioners and software engineering researchers with interest in the load testing of large-scale software systems.

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


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Question: Related paper recommendation to support online-browsing of research papers

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An online-browsing support system for research papers has been developed that extracts technical terms from a paper and presents links to useful pages such as those explaining the terms. A method to further use the extracted technical terms is proposed to recommend papers to a user that are related to the paper he or she is browsing. Specifically, the proposed method generates a bipartite graph consisting of papers retrieved by the extracted technical terms, which are called related papers, and technical terms appearing in these related papers. It then ranks the related papers using the HITS algorithm for analyzing the bipartite graph and recommends top-ranked papers to the user. The proposed method was compared with other recommendation methods in terms of effectiveness in an experiment.

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Authorware is the leading multimedia development system.It is an excellent tool for interactive multimedia programming,production of multimedia courseware for the use of Authorware The Author conducted research on the production of courseware and put forward his understanding and views.


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Question: Reactive path planning for emergency steering maneuvers on highway roads

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A path planning algorithm is proposed for emergency steering maneuvers on highway roads. A geometric approach is used to generate a graph which is searched to find an optimal path based on a customized cost function. We ensure that the resulted path will be within road boundaries, collision-free and feasible with respect to all kinematic and dynamic constraints of the host vehicle and the surrounding environment. The proposed algorithm is computationally fast and is reactive to all changes on the highway roads. Real-time simulation results in the Hardware-In-the-Loop platform shows the effectiveness of the algorithm in avoiding collision with stationary and moving obstacles on the road.

Precision stopping is an important automated ve- hicle control function that is critical in applications such as precision bus docking and automated truck or bus fuelling. Such applications require specific attention to brake control since the characteristics of a typical pneumatic brake system of a heavy vehicle is inherently nonlinear with large uncertainties. This paper describes the precision stopping problem, details the Indirect Adaptive Robust Control (IARC) design for a bus with pneumatic brake system, and reports the successful implementation of a bus precision docking demonstration.


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Question: A Security Framework in RFID Multi-domain System

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In previous approaches, it's generally assumed that all radio frequency identification (RFID) tags belong to a single RFID domain system (we name this as RFID single domain system). To date, most researches in the RFID single domain system have been on authentication protocols against a variety of attacks. This paper considers the security and privacy problems regarding that RFID tags used by different two or more RFID domains (we name this as RFID multi-domain system). We divided the security and privacy mechanisms in RFID multi-domain system into 3 conceptual parts: RFID forehand system security, RFID backend system security, and RFID inter-domain system security. First, we review RFID forehand and backend system security issues. Second, we present a security framework in RFID multi-domain system. Third, we propose and evaluate authentication and authorization for RFID inter-domain system with a case study

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Question: Age of language acquisition and cortical language organization in multilingual patients undergoing awake brain mapping

OBJECTIVEMost knowledge regarding the anatomical organization of multilingualism is based on aphasiology and functional imaging studies. However, the results have still to be validated by the gold standard approach, namely electrical stimulation mapping (ESM) during awake neurosurgical procedures. In this ESM study the authors describe language representation in a highly specific group of 13 multilingual individuals, focusing on how age of acquisition may influence the cortical organization of language.METHODSThirteen patients who had a high degree of proficiency in multiple languages and were harboring lesions within the dominant, left hemisphere underwent ESM while being operated on under awake conditions. Demographic and language data were recorded in relation to age of language acquisition (for native languages and early- and late-acquired languages), neuropsychological pre- and postoperative language testing, the number and location of language sites, and overlapping distribution in terms of language...

Purpose To assess the utility of a wide range of language measures (phonology, morphology, syntax, and semantics) for the identification of adults with developmental language impairment. Method Mea...


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Question: Richard Thaler and the Rise of Behavioral Economics

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Richard Thaler was awarded the 2017 Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel for his contributions to behavioral economics. In this article, I review and discuss these contributions.

Contents Introduction Culture in Chains: How the Secular and Religious Right Captured America Chapter 1 Manufacturing Common Sense or Cultural Hegemony for Beginners Chapter 2 Foreign Affairs Chapter 3 The American Religious Right and Its Long March through the Institutions Chapter 4 Extinguishing the Enlightenment: The Assault on Knowledge Chapter 5 Lobbies, Corridors and Seats of Power Conclusion Why Undertake This Book? Bibliography


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Question: Parasitic Currents in Structural Paths of YASA Axial Flux PM Machines: Estimation and Tests

This paper evaluates the parasitic currents that can occur in the structural part of some types of yokeless and segmented armature axial flux permanent magnet machines, where the frame-supporting stator floating teeth can originate stray paths. In this paper, these paths are defined and modeled, and the consequent effects (induced electro motive forces and currents) are estimated. The amount of these effects depends on the machine geometry, the magnetic circuit structure, and the winding layout. In this paper, the analysis is performed on two different rating machines, comparing their results. The model is validated by measurements on the corresponding prototypes.

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Introduction.- Analog Signals Conditioning and Discretization.- Selected Methods of Signal Filtration and Separation and their Implementation.- Selected Active Power Filter Control Algorithms.- Digital Signal Processing Circuits for Digital Class D Power Amplifiers.- Conclusion.


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Question: A block-based noise level estimation from X-ray images in SVD domain

Accurate and fast estimation of noise levels from medical images has numerous applications in medical image processing, including image enhancement, image segmentation and feature extraction. In this paper, a block-based noise level estimation algorithm in SVD domain is proposed. The proposed algorithm employs the non-overlapping block image segmentation to estimate homogenous image regions. Each homogenous block is used to obtain an independent noise level estimates in SVD domain. For any particular image, the overall noise level estimate is ascertained by averaging over the set of noise level estimates associated with the homogenous image blocks. In this paper, the optimal size of image segmentation blocks is evaluated systematically over a large dataset of x-ray images. The experimental results show that the proposed method offers numerous advantages over some alternative SVD domain method.

The article introduces the m×n S shape scanning field division method and the arbitrary scanning field division method.


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Question: Nested Sequential Monte Carlo Methods

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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.

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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: A conceptual framework for assessing electronic banking continued use

The development and advancement of electronic banking (e-banking) had raised the level competitiveness in the market for financial products and services. More and more banks and other financial institutions adopted such technology to improve service quality and enhance customer satisfaction and loyalty. Despite the increasing number e-banking users globally, little is known on how this technology can help banks to retain customers. Furthermore, it is only recently that researchers have started to understand the importance of consumers' continued use. Therefore, it is the aim of this paper to propose a framework based on an extensive review of current literature in related areas of e-banking domain and continued use. The main benefits of the proposed framework are towards understanding factors that may influence the e-banking continuance usage.

The author sets out to achieve a better measurement of interorganisational power in distribution channels.


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For instance you may be given '['Represent the title for retrieving the corresponding scientific abstract', 'A New Approach in Bloggers Classification with Hybrid of K-Nearest Neighbor and Artificial Neural Network Algorithms']' and it should match with '['Represent this scientific intro in order to find the title of the paper', 'Blogs are one of the effective tools of web2 which are considered as one of the major module and of social and interactive capabilities in making IT world wonderful for the cyber and virtual living. Two methods were used in this paper: K-Nearest Neighbor (KNN) and Artificial Neural Networks (ANNs). These methods are classified based on Kohkiloye and Boyer Ahmad province bloggers dataset considering input features of each blogger to the other methods and previously provided algorithms as more optimal. Our simulation and experiments not only provide hopeful results but also higher anticipation and classification rate.']' but not with '['Represent this abstract from a paper to retrieve its scientific title', '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.']'.

Question: Control strategies in object manipulation tasks

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The remarkable manipulative skill of the human hand is not the result of rapid sensorimotor processes, nor of fast or powerful effector mechanisms. Rather, the secret lies in the way manual tasks are organized and controlled by the nervous system. At the heart of this organization is prediction. Successful manipulation requires the ability both to predict the motor commands required to grasp, lift, and move objects and to predict the sensory events that arise as a consequence of these commands.

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This paper describes a robots system BeRoSH which incorporates a behaviour-based dynamic cooperation strategy for multiple behaviour-based robots. This behaviour-based dynamic cooperation strategy is realized in two steps: designing the distributed robot's cooperative behavioural attributes according to its abilities, and organizing these behavioural attributes. Through the behaviour design, this strategy allows the dynamic cooperation control to be distributed equally to each robot. In organizing the robots' abilities, the concept of form closure is introduced as the basic strategy. An experimental robot system and experimental results of object transportation and assembly work are also shown.


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Question: Coping with the enemy: Advances in adversary-aware signal processing

This paper is a first attempt to provide a unified framework for studying signal processing problems where designers have to cope with the presence of an adversary, including media forensics, watermarking, adversarial machine learning, biometric spoofing, etc. We focus on the binary decision problem and discuss which strategies the adversary can use to flip the decision output at minimal cost, including blind sensitivity attacks and hill-climbing attacks. As the defender can also play smarter by considering the presence of a rational adversary, we introduce a game-theoretic approach where some advances have been recently made. We conclude by discussing some trends raised by this game-theoretic formulation.

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The 34 papers in this special issue on cognitive sensor networks are devoted to design, theoretical analysis, fabrication, characterization, and experimentation of different cognitive sensors and sensing systems in various areas of engineering applications.


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Question: PET/CT medical image fusion algorithm based on multiwavelet transform

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PET/CT medical image fusion has important clinical significance. As the multiwavelet transform has several particular advantages in comparison with scalar wavelets on image processing, this paper proposes a medical image fusion algorithm based on multiwavelet transform after in-depth study of wavelet theory. The algorithm achieves PET/CT fusion with wavelet coefficients fusion method. Experimental results show that fusion image combines information of the source images, adds more details and texture information, and achieves a good fusion result. Based on the proposed algorithm, we can obtain the best result when using gradient fusion in the low-frequency part and classification fusion in the high-frequency part.

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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: Highly Efficient Leaky-Wave Antenna Array for 28-GHz Millimeter-Wave Terminals

A highly efficient leaky-wave antenna (LWA) array is presented in this paper. The proposed LWA array covers 28-GHz millimeter-wave frequency band and can be useful for 5G terminals. The antenna has been designed to be integrated to a substrate of dimensions 120 mm × 70 mm and occupies a small area of 24.5 mm × 24.5 mm. A dielectric load is used to increase the antenna efficiency. The efficiency of the array varies between 97\% and 98\% within the 28-GHz millimeter-wave band. It has a wide operating bandwidth of 6 GHz (26 - 32 GHz) and a peak gain of 9.1 dBi at 28 GHz. Within the 28-GHz millimeter-wave band the proposed LWA array has stable boresight radiation in the x-z and y-z planes.

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: A Simple Weight Decay Can Improve Generalization

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It has been observed in numerical simulations that a weight decay can improve generalization in a feed-forward neural network. This paper explains why. It is proven that a weight decay has two effects in a linear network. First, it suppresses any irrelevant components of the weight vector by choosing the smallest vector that solves the learning problem. Second, if the size is chosen right, a weight decay can suppress some of the effects of static noise on the targets, which improves generalization quite a lot. It is then shown how to extend these results to networks with hidden layers and non-linear units. Finally the theory is confirmed by some numerical simulations using the data from NetTalk.

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Debugging Of Large-scaled Data Processing Systems Like Supercomputers Is Becoming More Difficult. One Of The Causes Of The Trouble Is A Long Time For Reproducing VlSI's To Change Logic Design. An Automated On-chip Direct Wiring Modification System, Using Focused Ion Beam (FIB) And Laser CVD, Was Developed. It Reduced The Logic Change Period To One Day. The Debugging Time Of The Newest Mainframe Computer M880 Was Shortened By A Few Months.


Question: AutoPart: Parameter-Free Graph Partitioning and Outlier Detection

Graphs arise in numerous applications, such as the analysis of the Web, router networks, social networks, co-citation graphs, etc. Virtually all the popular methods for analyzing such graphs, for example, k-means clustering, METIS graph partitioning and SVD/PCA, require the user to specify various parameters such as the number of clusters, number of partitions and number of principal components. We propose a novel way to group nodes, using information-theoretic principles to choose both the number of such groups and the mapping from nodes to groups. Our algorithm is completely parameter-free, and also scales practically linearly with the problem size. Further, we propose novel algorithms which use this node group structure to get further insights into the data, by finding outliers and computing distances between groups. Finally, we present experiments on multiple synthetic and real-life datasets, where our methods give excellent, intuitive results.

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For instance, <<['Represent this abstract from a paper to retrieve its scientific title', 'Solutions of Lee Smolin Five Great Problems from his book {\\it The Trouble with Physics: the Rise of String Theory, the Fall of a Science, and What Comes Next} are described. This solutions is obtained only from the properties of probability without any ontological hypotheses.']>>  to <<['Represent this paper title in order to find a scientific intro to what it is about', 'Lee Smolin Five Great Problems and Their Solution without Ontological Hypotheses']>>

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


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Question: Improved Radiation Characteristics of Small Antipodal Vivaldi Antenna for Microwave and Millimeter-Wave Imaging Applications

A small antipodal Vivaldi antenna with rectangular slits at sun-shaped configuration and a half elliptical-shaped dielectric lens is designed for microwave and millimeter-wave imaging applications. The slits are developed to extend low end of frequency band and increase antenna gain at lower frequencies, while the lens is applied to this antenna to feature high gain at higher frequencies, high front-to-back ratio, low sidelobe and cross-polarization levels, narrow half-power beamwidth, and modification on E-plane tilt of beam. A prototype of the antenna with small size of 30 × 55 × 0.508 mm3 is fabricated and employed as a part of microwave and millimeter-wave imaging system. Applicability of the proposed antenna for 3-D and 2-D images of targets such as rubber discs and metal rods at different depths inside construction materials including foam and plasterboard sheet-layered structures is demonstrated. High-range resolution images are achieved by applying synthetic aperture radar algorithm.

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Question: Adaptive Object Detection Using Adjacency and Zoom Prediction

State-of-the-art object detection systems rely on an accurate set of region proposals. Several recent methods use a neural network architecture to hypothesize promising object locations. While these approaches are computationally efficient, they rely on fixed image regions as anchors for predictions. In this paper we propose to use a search strategy that adaptively directs computational resources to sub-regions likely to contain objects. Compared to methods based on fixed anchor locations, our approach naturally adapts to cases where object instances are sparse and small. Our approach is comparable in terms of accuracy to the state-of-the-art Faster R-CNN approach while using two orders of magnitude fewer anchors on average. Code is publicly available.

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Question: EURIDICE — IoT applied to logistics using the Intelligent Cargo concept

In an interconnected world, the need to exchange information across domain's boundaries is increasingly common, the concern is rapidly moving towards defining the content that needs to be consumed by numerous and different actors using different platforms and/or software solutions, since the internal processes have been consolidated and optimized. The transport logistics sector is no exception, the main issue in this domain is for ICT applications that allow to tag, monitor and transmit information about the freight along the whole transport chain, thus guaranteeing an efficient communication among the supply chain actors for a prompt intervention and resolution in case of problems and in general to increase the transport efficiency. The paper will present the technical aspects of the solutions developed within the EURIDICE project and will link them to the concrete in-field applications that make the platform a great innovation and a step towards the realization of the Future Internet.

The R&D presented on the communication was developed in the context of the Advanced Ceramics R&D Lab


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Question: A Fast Algorithm for Approximate Quantiles in High Speed Data Streams

We present a fast algorithm for computing approximate quantiles in high speed data streams with deterministic error bounds. For data streams of size N where N is unknown in advance, our algorithm partitions the stream into sub-streams of exponentially increasing size as they arrive. For each sub-stream which has a fixed size, we compute and maintain a multi-level summary structure using a novel algorithm. In order to achieve high speed performance, the algorithm uses simple block-wise merge and sample operations. Overall, our algorithms for fixed-size streams and arbitrary-size streams have a computational cost of O(N log(1/epsivlogepsivN)) and an average per-element update cost of O(log logN) if epsiv is fixed.

Traditional Management and Management Engineering.- Dynamic Supply and Demand Balance Problems.- Linear and Probabilistic Resource Optimization and Allocation Problems.- Forecasting of Time Series.- Business Intelligence and Data Mining.- The Use of Game Theory.- Summary of Some Fundamental Management Engineering Principles.- Concluding Remarks.


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E.g. given '['', 'A Passage-Time Preserving Equivalence for Semi-Markov Processes']' it should be close to '['Represent this abstract from a paper to retrieve its scientific title', 'An equivalence for semi-Markov processes is presented which preserves passage-time distributions between pairs of states in a given set. The equivalence is based upon a state-based aggregation procedure which is O(n2) per state in the worst case.']' but not to '['Represent the abstract for retrieving the scientific paper title', "Stochastic Differential Equations with Jumps in Rd.- Martingale Theory and the Stochastic Integral for Point Processes.- Brownian Motion, Stochastic Integral and Ito's Formula.- Stochastic Differential Equations.- Some Useful Tools in Stochastic Differential Equations.- Stochastic Differential Equations with Non-Lipschitzian Coefficients.- Applications.- How to Use the Stochastic Calculus to Solve SDE.- Linear and Non-linear Filtering.- Option Pricing in a Financial Market and BSDE.- Optimal Consumption by H-J-B Equation and Lagrange Method.- Comparison Theorem and Stochastic Pathwise Control.- Stochastic Population Control and Reflecting SDE.- Maximum Principle for Stochastic Systems with Jumps."]'.

Question: Frequency Reconfigurable Quasi-Yagi Folded Dipole Antenna

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A frequency reconfigurable planar quasi-Yagi antenna with a folded dipole driver element is presented. The center frequency of the antenna is electronically tuned by changing the effective electrical length of the folded dipole driver, which is achieved by employing either varactor diodes or PIN diodes. Two antenna prototypes are designed, fabricated and measured. The first antenna enables continuous tuning from 6 to 6.6 GHz using varactor diodes and the reflection coefficient bandwidth (≤ -10 dB) at each frequency is greater than 15%. The second antenna enables discrete tuning using PIN diodes to operate in either the 5.3-6.6 GHz band or the 6.4-8 GHz band. Similar end-fire radiation patterns with low cross-polarization levels are achieved across the entire tunable frequency range for the two antenna prototypes. Measured results on tuning range, radiation patterns and gain are provided, and these show good agreement with numerical simulations.

This chapter contains sections titled: The Vernier Effect DBR-Type Laser Structures Interferometric Structures Codirectionally Coupled Laser Diodes Combination of Techniques Comparison of Widely Tunable Monolithic Laser Structures This chapter contains sections titled: References


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Question: Predictive-corrective incompressible SPH

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We present a novel, incompressible fluid simulation method based on the Lagrangian Smoothed Particle Hydrodynamics (SPH) model. In our method, incompressibility is enforced by using a prediction-correction scheme to determine the particle pressures. For this, the information about density fluctuations is actively propagated through the fluid and pressure values are updated until the targeted density is satisfied. With this approach, we avoid the computational expenses of solving a pressure Poisson equation, while still being able to use large time steps in the simulation. The achieved results show that our predictive-corrective incompressible SPH (PCISPH) method clearly outperforms the commonly used weakly compressible SPH (WCSPH) model by more than an order of magnitude while the computations are in good agreement with the WCSPH results.

Stohastic description temporally variable subsurface flow spatially variable subsurface flow transport processes in heterogeneous media geostatistical methods and parameter estimation.