Miracle-dz/UniFAR-FTUs huggingface dataset:
MPEG‐4 video transmission over UMTS mobile networks

This paper presents an overview [1] of the MPEG‐4 (Motion Picture Experts Group) coded video file structure and the VOP (Video Object Plane) types followed by classification of errors and introduction of the NEWPRED mechanism in MPEG‐4 for error concealment. An UEP (Unequal Error Protection) scheme is described with a discussion on how the proposed scheme affects the UMTS (Universal Mobile Telecommunications System) network efficiency. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
A Finite State Approach to the Synthesis of Bioengineering Control Systems

The design of devices capable of duplicating the function of human extremities has become increasingly important in science, industry, and medicine. This paper presents an approach to the synthesis of control systems for such machines which results in extremely simple finite state controllers. The technique proposed rests on the definition of a new type of actuator, called a cybernetic actuator, which possesses the property of producing continuous controlled motion from an input which may assume only four distinct states. The application of such actuators to bioengineering systems is illustrated by the design of a control system for an artificial leg.
A user's guide to Sandia's latin hypercube sampling software : LHS UNIX library/standalone version.

This document is a reference guide for the UNIX Library/Standalone version of the Latin Hypercube Sampling Software. This software has been developed to generate Latin hypercube multivariate samples. This version runs on Linux or UNIX platforms. This manual covers the use of the LHS code in a UNIX environment, run either as a standalone program or as a callable library. The underlying code in the UNIX Library/Standalone version of LHS is almost identical to the updated Windows version of LHS released in 1998 (SAND98-0210). However, some modifications were made to customize it for a UNIX environment and as a library that is called from the DAKOTA environment. This manual covers the use of the LHS code as a library and in the standalone mode under UNIX.
SNR estimation for ACM in DVB-RCS satellite systems

• Mitigates slow fading (e.g., Rain fades) • Improves link availability • Provides capacity gains • Dynamically adapts modulation and coding scheme (mode/Mod-Cod subset) • Efficiency relies on accuracy of SNR estimator • Different estimators for DVB-S2 and DVB-RCS analyzed in the literature [Aroumont_2006]
Optimal neural network output feedback control for robot manipulators

A robust neural network output feedback scheme is developed for the joint motion control of robot manipulators without directly measuring joint velocities. A neural network observer is used to estimate the joint velocities. The neural network weights in both the observer and the controller are tuned online, with no off-line learning phase required. No exact knowledge of the robot dynamics is required so that the neural network controller is model-free and so applicable to a class of nonlinear systems which have a similar structure to robot manipulators. Implementation results on a single-link robot are reported to show the performance of the proposed technique.
Segmental GPD training of HMM based speech recognizer

A novel training algorithm, segmental GPD (generalized probabilistic descent) training, for a hidden Markov model (HMM)-based speech recognizer using Viterbi decoding is proposed. This algorithm is based on the principle of minimum recognition error rate in which segmentation and discriminative training are jointly optimized. Various issues related to the special structure of HMM in segmental GPD training are studied. The authors tested this algorithm on two speaker-independent recognition tasks. The first experiment involves English E-set. Segmental GPD training was directly applied to HMM generated from nonoptimal uniform segmentation. A recognition rate of 88.7% was achieved on English E-set with whole word HMM. The second experiment involves the connected digits TI-database. Segmental GPD training was applied to HMM which were already trained using conventional training methods. A string recognition rate of 98.8% was achieved on 10-state word based HMM through segmental GPD training. <<ETX>>
Building Non-Overlapping Polygons For Image Document Layout Analysis Results

Existing Computational Geometry algorithms aren't able to create a tight-fitting contour around document elements. Some of them don't follow the data points close enough, generating overlapping elements, while others, trying to keep close to the contour, break one element into pieces, falling between white spaces. The presented method both follows the contour closely and generates a single shape for a single element. The generation of the shape can be stopped at any time, either when there are no more intersections between layout elements or after a certain time elapsed, the result being valid at any given moment. In association with other algorithms it can offer a fast and clean solution for the problem of finding the non-overlapping areas resulted from the Layout Analysis document processing phase.
GenePrint: Generic and Accurate Physical-Layer Identification for UHF RFID Tags

Physical-layer identification utilizes unique features of wireless devices as their fingerprints, providing authenticity and security guarantee. Prior physical-layer identification techniques on radio frequency identification (RFID) tags require nongeneric equipments and are not fully compatible with existing standards. In this paper, we propose a novel physical-layer identification system, GenePrint, for UHF passive tags. The GenePrint prototype system is implemented by a commercial reader, a USRP-based monitor, and off-the-shelf UHF passive tags. Our solution is generic and completely compatible with the existing standard, EPCglobal C1G2 specification. GenePrint leverages the internal similarity among pulses of tags' RN16 preamble signals to extract a hardware feature as the fingerprint. We conduct extensive experiments on over 10 000 RN16 preamble signals from 150 off-the-shelf RFID tags. The results show that GenePrint achieves a high identification accuracy of 99.68% +. The feature extraction of GenePrint is resilient to various malicious attacks, such as the feature replay attack.
Linear input network based speaker adaptation in the Dialogos system

Describes an activity devoted to experiment linear input networks (LIN) as a speaker adaptation technique for the neural recognition module of the Dialogos(R) system. The LIN technique is experimented with and some variants devoted to reduce the number of estimated parameters are introduced. The obtained results confirm the validity of LIN for speaker adaptation, while the introduced variants are a valid alternative when a reduced model size is important. The potentialities and drawbacks of supervised and unsupervised speaker adaptation are illustrated. Experimentations with a speaker dependent data base collected from real interactions with the Dialogos system are described in detail showing, in both cases, a relevant improvement in comparison with the speaker independent model.
Improved excitation for phonetically-segmented VXC speech coding below 4 kb/s

Techniques for combating two types of distortion that degrade the quality of vector excitation coded (VXC) speech are presented. One degradation, the presence of noiselike components between the intended harmonics in voiced speech segments, is reduced by adaptive comb filtering, controlled by a smoothed pitch estimate. The other degradation arises with front vowel sounds whose second and third formants tend to be attenuated in VXC coders. This is improved by adding high-frequency emphasis to the perceptual weighting when computing the distortion between original and reconstructed speech. It is shown that the first technique can benefit any VXC coder, whereas while the second is applicable specifically when phonetic segmentation is used as a front end to VXC coders. <<ETX>>
Neural network classification of metal surface properties using a dynamic touch sensor

Discusses an application of neural networks to classify signals produced by a dynamic touch sensor, and achieve automated characterization of metal surfaces during machining. Data are first preprocessed and the spectral features are input to a feedforward one-hidden-layer neural network, trained with backpropagation. The classification accuracy was over 90% for most of the surfaces. The authors discuss the experimental setup, the preprocessing, and a critical view of the classification results. <<ETX>>
Reduction of Cogging Torque, Harmonicsin PM BLDC Motor

The Brushless DC Motors are the one in several motors gaining popularity in industrial applications. The main issues with this BLDC motors are cogging torque and harmonics associated with it. Cogging torque is due to the interaction between the permanent magnet of the rotor and the stator slots in permanent magnet machine. The presence of 5th and 7th harmonics in input supply reduces the efficiency of BLDC motor. Many researches are undergoing to reduce the cogging torque and harmonics. Some of the known techniques for reducing the cogging torque are the magnet pole design, skewing, step skewing, and dummy slots in the stator lamination. This paper proposes a method for reducing cogging torque which is a Hybrid method, comprising of both Numerical and Analytical analysis. The design process involves simulating the proposed solution in the MotorSolve FEM and later it is integrated with MATLAB-SIMULINK. The result observed in the proposed system is the reduction of cogging torque and harmonics to a considerable amount.
Improving the Accuracy of Diabetes Classification Using Modified K-Means

This research work has presented different data mining algorithms for efficiently classify the diabetes data. Data mining algorithms have becoming popular in real time applications like e-mail spam classification, intrusion detection system, diabetes mining, etc. The overall goal of this research work is to evaluate the performance of the K-means based data mining algorithms by considering the diabetes data set. As the accuracy rate of traditional K-means algorithm is 76% that means comes up with 24% error rate. So it is required to improve this accuracy rate. To achieve this objective we have modified the pre-processing of data set by using the well-known tool MATLAB. MATLAB has used WEKA machine learning tool as an API (Application programming interface). It has been found that that the Modified K-Means outperforms over the existing machine learning algorithms.
An effective stemmer in Devanagari script

In today's word of internet web search engines are developing the techniques to make the surfing faster. Stemming is a technique used by web search engines for prefix and suffix removal from the derived word. Stemming provides the way to store similar documents together. This research work aims at the development of Hindi stemmer based on Devanagari script for stripping both prefixes as well as suffixes from derived word to provide better stemming than previous stemmers. Proposed stemmer uses the hybrid approach which is the combination of lookup algorithm, suffix stripping algorithm and prefix removal algorithm.
Content Based Image Retrieval Using Clustering

Content-based image retrieval (CBIR) is a widely accepted technique for searching images from large and unlabeled image databases. But users are not satisfied with the traditional information retrieval techniques, because the network and development of multimedia technologies are becoming more popular. So the content based image retrieval (CBIR) are becoming a source of accurate and efficient retrieval. In recent years, various techniques have been implemented to improve the performance of CBIR. Clustering deals with searching a structure in a corpus of unlabeled data. Clustering is an unsupervised method of classification but it is observed that whenever we provide a small amount of supervision to clustering, it improves the clustering performance significantly. In this paper, different clustering techniques are discussed and analysed. Also, we propose a new CBIR system that uses kernel mean shift clustering technique under semi-supervised framework. This method uses only pairwise constraints to train the clustering procedure. This is a non-parametric method, so we are not restricted to specific no of clusters.
A Novel Approach to Search Based Face Annotation (SBFA) Using Weakly Labeled Web Facial Images

This paper introduces a framework of search based face annotation (SBFA) by mining weakly labeled web facial image that are available on www. one challenging part of SBFA scheme is managing most similar web facial images and their weak labels. To avoid this problem, I propose an effective refinement of unsupervised label(RUL) scheme for refining the labels of web facial images. To speed up the proposed system, I also propose a clustering-based approximation algorithm which can improve the scalability.
Lexicon Acquisition for Resource-Poor Languages Using Transductive Learning

We investigate the problem of learning a part-of-speech (POS) lexicon for resource-poor languages. Developing a high-quality lexicon is often the rst step towards building a POS tagger, which is in turn the front-end to many NLP systems. We frame the lexicon acquisition problem as a transductive learning problem, and perform comparisons on three transductive algorithms: Transductive SVMs, Spectral Graph Transducers, and a novel Transductive Clustering method. We test on two datasets: dialectal Arabic (a resource-poor language) and Wall Street Journal with articially limited training data. For dialectal Arabic, we demonstrate that lexicon learning is an important task and leads to signicant improvements in tagging accuracy. For Wall Street Journal, we observe that transductive learning does not necessary lead to improvements in lexicon accuracy and present some preliminary analyses of results.
Developing Metrics for Web Sites

Many different metrics and models have been developed to evaluate a Webs site's attributes as perceived by Internet users. In this paper we focus on users' perceptions of the content and design of Web sites. A Delphi study as well as an exploratory factor analysis are used to generate and merge attributes of Web sites. Different user groups are identified and clustered according to their preferences.
An automated data acquisition system for capturing physiological parameters during animal trials of artificial heart valves

Animal trials form an important phase of any medical device development, especially in the context of implantable devices like artificial heart valves. Monitoring and recording parameters such as physiological pressures and Electrocardiogram (ECG) is essential for assessing the performance of the valve. A dedicated automated data acquisition system was developed for capturing these vital characteristics during implantation, immediately post operative and prior to the explantation of the device. The hardware was designed around the PXI (Pci eXtension for Instrumentation) modular data acquisition chassis and the software was developed using LabVIEW (both National Instruments, USA). A set of transducers was identified, validated and incorporated into the system for converting physical signals to analogue electrical signals. The system was employed in more than fifteen animal experiments and found to be extremely useful for automated data capturing. It provided valuable sets of additional data for many specif.
Phonetic encoding for Bangla and its application to spelling checker , transliteration , cross language information retrieval and name searching

We present a phonetic encoding for Bangla that can be used by spelling checkers, transliteration, name searching application and cross-lingual information retrieval to drastically improve the quality. The complex, and often inconsistent, rules of Bangla word present a significant challenge in producing a proper phonetic code. We propose a phonetic encoding for Bangla, taking into account the various context-sensitive rules, including those involving the large repertoire of conjuncts in Bangla.
How Do Online Citizens Persuade Fellow Voters? Using Twitter During the 2012 Dutch Parliamentary Election Campaign

This article explores how Twitter was used by voters to participate in electoral campaigning during the Dutch election campaign of 2012. New social media networks like Twitter are believed to be efficient tools of communication between electoral candidates and voters during electoral campaign periods. Yet only few studies have been conducted so far to discover in what way the content of online discussions is being used for campaigning. In particular, there have been very few studies of electoral campaigning, which study the content of the social media messages sent by citizens. In order to understand the extent to which citizens utilize Twitter in different forms of electoral campaigning—that is, persuading followers about voting for a particular party or to conduct negative campaigning, we conducted an automated content analysis of a large corpus of tweets collected during the Dutch parliamentary election campaign of 2012. Our findings show that citizens participate significantly in online electoral campaigning on Twitter, whereas they differ from professional users in the style of campaigning. Persuasive campaigning is observed to a lesser extent among citizens than among politicians, while citizens more commonly use negative campaigning. Moreover, qualitative content analysis of campaigning tweets by citizens has revealed that expressions of emotions and opinions make up a large majority of negative tweets, indicating that citizens regard Twitter more as an outlet for expressing discontent than as a medium for negative campaigning.
Inference of central nervous system input and its complexity for interactive arm movement

This dissertation demonstrates a new method for inferring a representation of the motor command, generated by the central nervous system for interactive point-to-point movements. This new tool, the input inference neural network or IINN, allows estimation of the complexity of the motor command. The IINN was applied to experimental data gathered from 7 volunteer subjects who performed point-to-point tasks while interacting with a specially constructed haptic robot. The motor plan inference demonstrates that, for the point-to-point movement tasks executed during experiments, the motor command can be projected onto a low-dimensional manifold. This dimension is estimated to be 4 or 5 and far less than the degrees of freedom available in the arm. It is hypothesized that subjects simplify the problem of adapting to changing environments by projecting the motor control problem onto a motor manifold of low dimension. Reducing the dimension of the movement optimization problem through the development of a motor manifold can explain rapid adaptation to new motor tasks.
Uma arquitetura para negociação de redes virtualizadas na internet do futuro baseada em classes de QoS

Ao longo dos anos a Internet vem se tornando o principal meio de comunicacao, onde muitas empresas e organizacoes a usam como base para os seus servicos, sendo que na maioria dos casos, estas empresas tem varios provedores de Internet (Modelo Multi- Provedor). Entretanto, a Internet atual nao prove garantias de Qualidade de Servico (Quality of Service - QoS). Para contornar esse problema, as empresas realizam um Acordo de Nivel de Servicos (Service Level Agreement - SLA). Dentro desse contexto, esta dissertacao de mestrado tem por objetivo desenvolver uma arquitetura para negociacao de redes virtualizadas na Internet do Futuro utilizando tecnicas de classificacao de trafegos para decidir, a partir dos dados coletados e das politicas de SLA, por qual ISP (Internet Service Provider) enviar os dados de acordo com a classe que os dados se enquadram. Espera-se assim atender aos requisitos de QoS de cada classe de trafego, e diminuir os custos da empresa. Para realizar a validacao da arquitetura proposta, foram efetuados experimentos baseados no protocolo OpenFlow e no emulador Mininet. Os resultados mostraram a eficiencia do modelo desenvolvido, bem como a capacidade do mesmo de cumprir os objetivos definidos. Abstract
A Full Scale Camera Calibration Technique with Automatic Model Selection – Extension and Validation

I am submitting herewith a thesis written by Vitaliy Leonidovich Orekhov entitled “A Full Scale Camera Calibration Technique with Automatic Model Selection – Extension and Validation” I have examined the final electronic copy of this thesis for form and content and recommend that it be accepted in partial fulfillment of the requirements for the degree of Master of Science, with a major in Electrical Engineering.
Automatic Prediction of High-Quality Answers in Community QA

コミュニティ型質問応答サイト(CQA)は，ユーザが自身の状況に応じた情報を得ることができる新たな手段である．しかし投稿された回答の質は様々であるため，その中から良質な回答を選択する方法が求められている．そこで本研究は，まず Yahoo! 知恵袋データにおける良質回答を人手で分析し，その結果に基づいて良質回答自動予測システムを構築した．具体的には，「恋愛相談」「パソコン」「一般教養」「政治」の4つのカテゴリからそれぞれ無作為に50問の質問を抽出し，判定者2名によって手作業で良質回答を決定した．次に，その結果を分析し，良質回答の特徴として「詳しさ」「根拠」「丁寧さ」に基づく機械学習システムを構築した．機械学習システムの評価結果は，「パソコン」と「一般教養」カテゴリでは判定者らを上回った．「恋愛相談」と「政治」カテゴリでは，機械学習システムの評価結果は判定者らとほぼ同じであった．以上の結果から，CQAアーカイブから自動的に良質回答を発見するシステムの可能性が示唆される．
Design and Realization Wilkinson Power Divider at Frequency 2400MHz for Radar S-Band

This paper presents design and realization of 2-way Wilkinson Power Dividers (WPD) at frequency 2400MHz for Radar S-Band. Power dividers in radar S-Band used for divide the output power from oscillator where used for the mixer of transmitter and receiver section. The 2-way WPD used Wilkinson configuration where consist of two quarter-wavelength transmission line (λg/4) and one resistor chip between the both output ports. Design of the 2-way WPD presents by simulation result with ADS2011.10 and have been implemented using Roger Duroid 5880 substrate. The simulation and measurement result contains graph of insertion loss, voltage standing wave ratio (VSWR) or return loss, and isolation between the both output ports. The measurement result of the 2way WPD indicating a good performance than the 2-way power dividers with wideband that currently used and its suitable to use at radar S-band for divide the output power from oscillator.
An update to the sliding DFT

Those properties allow us to create Table 1, listing the appropriate arctan approximation based on the octant location of complex x. So we have to check the signs of Q and I, and see if |Q | > |I |, to determine the octant location and then use the appropriate approximation in Table 1. The maximum angle approximation error is 0.26◦ for all octants. When θ is in the fifth octant, the above algorithm will yield a θ ′ that’s more positive than +π radians. If we need to keep the θ ′ estimate in the range of −π to +π , we can rotate any θ residing in the fifth quadrant +π/4 rad (45◦) by multiplying (I + jQ ) by (1 + j ), placing it in the sixth octant. That multiplication yields new real and imaginary parts defined as