Search results for: Multistage Vector Quantization and Pyramid Vector Quantization.
429 A Sentence-to-Sentence Relation Network for Recognizing Textual Entailment
Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee
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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.Keywords: Deep neural models, natural language inference, recognizing textual entailment, sentence-to-sentence relation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1442428 Exchange Rate Volatility, Its Determinants and Effects on the Manufacturing Sector in Nigeria
Authors: Chimaobi V. Okolo, Onyinye S. Ugwuanyi, Kenneth A. Okpala
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This study evaluated the effect of exchange rate volatility on the manufacturing sector of Nigeria. The flow and stock market theories of exchange rate determination was adopted considering macroeconomic determinants such as balance of trade, trade openness, and net international investment. Furthermore, the influence of changes in parallel exchange rate, official exchange rate and real effective exchange rate was modeled on the manufacturing sector output. Vector autoregression techniques and vector error correction mechanism were adopted to explore the macroeconomic determinants of exchange rate fluctuation in Nigeria and to examine the influence of exchange rate volatility on the manufacturing sector output in Nigeria. The exchange rate showed an unstable and volatile movement in Nigeria. Official exchange rate significantly impacted on the manufacturing sector of Nigeria and shock to previous manufacturing sector output caused 60.76% of the fluctuation in the manufacturing sector output in Nigeria. Trade balance, trade openness and net international investments did not significantly determine exchange rate in Nigeria. However, own shock accounted for about 95% of the variation of exchange rate fluctuation in the short-run and long-run. Among other macroeconomic variables, net international investment accounted for about 2.85% variation of the real effective exchange rate fluctuation in the short-run and in the long-run. Monetary authorities should maintain stability of the exchange rates through proper management so as to encourage local production and government should formulate and implement policies that will develop other sectors of the economy as this will widen the country’s revenue base, reduce our over reliance on oil sector for our foreign exchange earnings and in turn reduce the shocks on our domestic economy.
Keywords: Exchange rate volatility, exchange rate determinants, manufacturing sector, official exchange rate, parallel exchange rate, real effective exchange rate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1912427 New Adaptive Linear Discriminante Analysis for Face Recognition with SVM
Authors: Mehdi Ghayoumi
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We have applied new accelerated algorithm for linear discriminate analysis (LDA) in face recognition with support vector machine. The new algorithm has the advantage of optimal selection of the step size. The gradient descent method and new algorithm has been implemented in software and evaluated on the Yale face database B. The eigenfaces of these approaches have been used to training a KNN. Recognition rate with new algorithm is compared with gradient.Keywords: lda, adaptive, svm, face recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1408426 Impedance of an Encircling Coil due to a Cylindrical Tube with Varying Properties
Authors: Valentina Koliskina
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Change in impedance of an encircling coil is obtained in the present paper for the case where the electric conductivity and magnetic permeability of a metal cylindrical tube depend on the radial coordinate. The system of equations for the vector potential is solved by means of the Fourier cosine transform. The solution is expressed in terms of improper integral containing modified Bessel functions of complex order.Keywords: Eddy currents, magnetic permeability, Besselfunctions
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1760425 Machine Learning Techniques in Bank Credit Analysis
Authors: Fernanda M. Assef, Maria Teresinha A. Steiner
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The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, the best accuracy does not always represent the best technique. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study.
Keywords: Artificial Neural Networks, ANNs, classifier algorithms, credit risk assessment, logistic regression, machine learning, support vector machines.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1258424 Analysis of Filtering in Stochastic Systems on Continuous-Time Memory Observations in the Presence of Anomalous Noises
Authors: S. Rozhkova, O. Rozhkova, A. Harlova, V. Lasukov
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For optimal unbiased filter as mean-square and in the case of functioning anomalous noises in the observation memory channel, we have proved insensitivity of filter to inaccurate knowledge of the anomalous noise intensity matrix and its equivalence to truncated filter plotted only by non anomalous components of an observation vector.
Keywords: Mathematical expectation, filtration, anomalous noise, memory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2040423 Rice cDNA Encoding PROLM is Capable of Rescuing Salt Sensitive Yeast Phenotypes G19 and Axt3K from Salt Stress
Authors: Prasad Senadheera, Younousse Saidi, Frans JM Maathuis
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Rice seed expression (cDNA) library in the Lambda Zap 11® phage constructed from the developing grain 10-20 days after flowering was transformed into yeast for functional complementation assays in three salt sensitive yeast mutants S. cerevisiae strain CY162, G19 and Axt3K. Transformed cells of G19 and Axt3K with pYES vector with cDNA inserts showed enhance tolerance than those with empty pYes vector. Sequencing of the cDNA inserts revealed that they encode for the putative proteins with the sequence homologous to rice putative protein PROLM24 (Os06g31070), a prolamin precursor. Expression of this cDNA did not affect yeast growth in absence of salt. Axt3k and G19 strains expressing the PROLM24 were able to grow upto 400 mM and 600 mM of NaCl respectively. Similarly, Axt3k mutant with PROLM24 expression showed comparatively higher growth rate in the medium with excess LiCl (50 mM). The observation that expression of PROLM24 rescued the salt sensitive phenotypes of G19 and Axt3k indicates the existence of a regulatory system that ameliorates the effect of salt stress in the transformed yeast mutants. However, the exact function of the cDNA sequence, which shows partial sequence homology to yeast UTR1 is not clear. Although UTR1 involved in ferrous uptake and iron homeostasis in yeast cells, there is no evidence to prove its role in Na+ homeostasis in yeast cells. Absence of transmembrane regions in Os06g31070 protein indicates that salt tolerance is achieved not through the direct functional complementation of the mutant genes but through an alternative mechanism.Keywords: Rice seed expression, salt stress, prolamin, salinitytolerance, Oryza sativa
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1897422 Multistage Data Envelopment Analysis Model for Malmquist Productivity Index Using Grey's System Theory to Evaluate Performance of Electric Power Supply Chain in Iran
Authors: Mesbaholdin Salami, Farzad Movahedi Sobhani, Mohammad Sadegh Ghazizadeh
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Evaluation of organizational performance is among the most important measures that help organizations and entities continuously improve their efficiency. Organizations can use the existing data and results from the comparison of units under investigation to obtain an estimation of their performance. The Malmquist Productivity Index (MPI) is an important index in the evaluation of overall productivity, which considers technological developments and technical efficiency at the same time. This article proposed a model based on the multistage MPI, considering limited data (Grey’s theory). This model can evaluate the performance of units using limited and uncertain data in a multistage process. It was applied by the electricity market manager to Iran’s electric power supply chain (EPSC), which contains uncertain data, to evaluate the performance of its actors. Results from solving the model showed an improvement in the accuracy of future performance of the units under investigation, using the Grey’s system theory. This model can be used in all case studies, in which MPI is used and there are limited or uncertain data.
Keywords: Malmquist Index, Grey's Theory, Charnes Cooper & Rhodes (CCR) Model, network data envelopment analysis, Iran electricity power chain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 544421 Image Transmission via Iterative Cellular-Turbo System
Authors: Ersin Gose, Kenan Buyukatak, Onur Osman, Osman N. Ucan
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To compress, improve bit error performance and also enhance 2D images, a new scheme, called Iterative Cellular-Turbo System (IC-TS) is introduced. In IC-TS, the original image is partitioned into 2N quantization levels, where N is denoted as bit planes. Then each of the N-bit-plane is coded by Turbo encoder and transmitted over Additive White Gaussian Noise (AWGN) channel. At the receiver side, bit-planes are re-assembled taking into consideration of neighborhood relationship of pixels in 2-D images. Each of the noisy bit-plane values of the image is evaluated iteratively using IC-TS structure, which is composed of equalization block; Iterative Cellular Image Processing Algorithm (ICIPA) and Turbo decoder. In IC-TS, there is an iterative feedback link between ICIPA and Turbo decoder. ICIPA uses mean and standard deviation of estimated values of each pixel neighborhood. It has extra-ordinary satisfactory results of both Bit Error Rate (BER) and image enhancement performance for less than -1 dB Signal-to-Noise Ratio (SNR) values, compared to traditional turbo coding scheme and 2-D filtering, applied separately. Also, compression can be achieved by using IC-TS systems. In compression, less memory storage is used and data rate is increased up to N-1 times by simply choosing any number of bit slices, sacrificing resolution. Hence, it is concluded that IC-TS system will be a compromising approach in 2-D image transmission, recovery of noisy signals and image compression.
Keywords: Iterative Cellular Image Processing Algorithm (ICIPA), Turbo Coding, Iterative Cellular Turbo System (IC-TS), Image Compression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1803420 Neural Network Based Predictive DTC Algorithm for Induction Motors
Authors: N.Vahdatifar, Ss.Mortazavi, R.Kianinezhad
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In this paper, a Neural Network based predictive DTC algorithm is proposed .This approach is used as an alternative to classical approaches .An appropriate riate Feed - forward network is chosen and based on its value of derivative electromagnetic torque ; optimal stator voltage vector is determined to be applied to the induction motor (by inverter). Moreover, an appropriate torque and flux observer is proposed.Keywords: Neural Networks, Predictive DTC
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1375419 A Bayesian Classification System for Facilitating an Institutional Risk Profile Definition
Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan
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This paper presents an approach for easy creation and classification of institutional risk profiles supporting endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support set up of the most important risk factors. Subsequently, risk profiles employ risk factors classifier and associated configurations to support digital preservation experts with a semi-automatic estimation of endangerment group for file format risk profiles. Our goal is to make use of an expert knowledge base, accuired through a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation of risk factors for a requried dimension for analysis. Using the naive Bayes method, the decision support system recommends to an expert the matching risk profile group for the previously selected institutional risk profile. The proposed methods improve the visibility of risk factor values and the quality of a digital preservation process. The presented approach is designed to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and values of file format risk profiles. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert and to define its profile group. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.Keywords: linked open data, information integration, digital libraries, data mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 714418 Using the Keystrokes Dynamic for Systems of Personal Security
Authors: Gláucya C. Boechat, Jeneffer C. Ferreira, Edson C. B. Carvalho
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This paper presents a boarding on biometric authentication through the Keystrokes Dynamics that it intends to identify a person from its habitual rhythm to type in conventional keyboard. Seven done experiments: verifying amount of prototypes, threshold, features and the variation of the choice of the times of the features vector. The results show that the use of the Keystroke Dynamics is simple and efficient for personal authentication, getting optimum resulted using 90% of the features with 4.44% FRR and 0% FAR.Keywords: Biometrics techniques, Keystroke Dynamics, patternrecognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1729417 Optimal Placement of Processors based on Effective Communication Load
Authors: A. R. Aswatha, T. Basavaraju, N. Bhaskara Rao
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This paper presents a new technique for the optimum placement of processors to minimize the total effective communication load under multi-processor communication dominated environment. This is achieved by placing heavily loaded processors near each other and lightly loaded ones far away from one another in the physical grid locations. The results are mathematically proved for the Algorithms are described.Keywords: Ascending Sort Index Vector, EffectiveCommunication Load, Effective Distance Matrix, OptimalPlacement, Sorting Order.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1339416 A Perceptually Optimized Wavelet Embedded Zero Tree Image Coder
Authors: A. Bajit, M. Nahid, A. Tamtaoui, E. H. Bouyakhf
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In this paper, we propose a Perceptually Optimized Embedded ZeroTree Image Coder (POEZIC) that introduces a perceptual weighting to wavelet transform coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement with respect to the coding quality obtained using the SPIHT algorithm only. The paper also, introduces a new objective quality metric based on a Psychovisual model that integrates the properties of the HVS that plays an important role in our POEZIC quality assessment. Our POEZIC coder is based on a vision model that incorporates various masking effects of human visual system HVS perception. Thus, our coder weights the wavelet coefficients based on that model and attempts to increase the perceptual quality for a given bit rate and observation distance. The perceptual weights for all wavelet subbands are computed based on 1) luminance masking and Contrast masking, 2) the contrast sensitivity function CSF to achieve the perceptual decomposition weighting, 3) the Wavelet Error Sensitivity WES used to reduce the perceptual quantization errors. The new perceptually optimized codec has the same complexity as the original SPIHT techniques. However, the experiments results show that our coder demonstrates very good performance in terms of quality measurement.
Keywords: DWT, linear-phase 9/7 filter, 9/7 Wavelets Error Sensitivity WES, CSF implementation approaches, JND Just Noticeable Difference, Luminance masking, Contrast masking, standard SPIHT, Objective Quality Measure, Probability Score PS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2041415 Multiuser Detection in CDMA Fast Fading Multipath Channel using Heuristic Genetic Algorithms
Authors: Muhammad Naeem, Syed Ismail Shah, Habibullah Jamal
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In this paper, a simple heuristic genetic algorithm is used for Multistage Multiuser detection in fast fading environments. Multipath channels, multiple access interference (MAI) and near far effect cause the performance of the conventional detector to degrade. Heuristic Genetic algorithms, a rapidly growing area of artificial intelligence, uses evolutionary programming for initial search, which not only helps to converge the solution towards near optimal performance efficiently but also at a very low complexity as compared with optimal detector. This holds true for Additive White Gaussian Noise (AWGN) and multipath fading channels. Experimental results are presented to show the superior performance of the proposed techque over the existing methods.Keywords: Genetic Algorithm (GA), Multiple AccessInterference (MAI), Multistage Detectors (MSD), SuccessiveInterference Cancellation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2038414 Performance Analysis of Chrominance Red and Chrominance Blue in JPEG
Authors: Mamta Garg
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While compressing text files is useful, compressing still image files is almost a necessity. A typical image takes up much more storage than a typical text message and without compression images would be extremely clumsy to store and distribute. The amount of information required to store pictures on modern computers is quite large in relation to the amount of bandwidth commonly available to transmit them over the Internet and applications. Image compression addresses the problem of reducing the amount of data required to represent a digital image. Performance of any image compression method can be evaluated by measuring the root-mean-square-error & peak signal to noise ratio. The method of image compression that will be analyzed in this paper is based on the lossy JPEG image compression technique, the most popular compression technique for color images. JPEG compression is able to greatly reduce file size with minimal image degradation by throwing away the least “important" information. In JPEG, both color components are downsampled simultaneously, but in this paper we will compare the results when the compression is done by downsampling the single chroma part. In this paper we will demonstrate more compression ratio is achieved when the chrominance blue is downsampled as compared to downsampling the chrominance red in JPEG compression. But the peak signal to noise ratio is more when the chrominance red is downsampled as compared to downsampling the chrominance blue in JPEG compression. In particular we will use the hats.jpg as a demonstration of JPEG compression using low pass filter and demonstrate that the image is compressed with barely any visual differences with both methods.Keywords: JPEG, Discrete Cosine Transform, Quantization, Color Space Conversion, Image Compression, Peak Signal to Noise Ratio & Compression Ratio.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1669413 Lattice Dynamics of (ND4Br)x(KBr)1-x Mixed Crystals
Authors: Alpana Tiwari, N. K. Gaur
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We have incorporated the translational rotational (TR) coupling effects in the framework of three body force shell model (TSM) to develop an extended TSM (ETSM). The dynamical matrix of ETSM has been applied to compute the phonon frequencies of orientationally disordered mixed crystal (ND4Br)x(KBr)1-x in (q00), (qq0) and (qqq) symmetry directions for compositions 0.10≤x≤0.50 at T=300K.These frequencies are plotted as a function of wave vector k. An unusual acoustic mode softening is found along symmetry directions (q00) and (qq0) as a result of translation-rotation coupling.Keywords: Orientational glass, phonons, TR-coupling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1237412 Computational Assistance of the Research, Using Dynamic Vector Logistics of Processes for Critical Infrastructure Subjects Continuity
Authors: J. Urbánek Jiří, Krahulec Josef, Johanidesová Jitka, F. Urbánek Jiří
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This paper deals with using of prevailing operation system MS Office (SmartArt...) for mathematical models, using DYVELOP (Dynamic Vector Logistics of Processes) method. It serves for crisis situations investigation and modelling within the organizations of critical infrastructure. In first part of paper, it will be introduced entities, operators, and actors of DYVELOP method. It uses just three operators of Boolean algebra and four types of the entities: the Environments, the Process Systems, the Cases, and the Controlling. The Process Systems (PrS) have five “brothers”: Management PrS, Transformation PrS, Logistic PrS, Event PrS and Operation PrS. The Cases have three “sisters”: Process Cell Case, Use Case, and Activity Case. They all need for the controlling of their functions special Ctrl actors, except ENV – it can do without Ctrl. Model´s maps are named the Blazons and they are able mathematically - graphically express the relationships among entities, actors and processes. In second part of this paper, the rich blazons of DYVELOP method will be used for the discovering and modelling of the cycling cases and their phases. The blazons need live PowerPoint presentation for better comprehension of this paper mission. The crisis management of energetic crisis infrastructure organization is obliged to use the cycles for successful coping of crisis situations. Several times cycling of these cases is necessary condition for the encompassment for both emergency events and the mitigation of organization´s damages. Uninterrupted and continuous cycling process brings for crisis management fruitfulness and it is good indicator and controlling actor of organizational continuity and its sustainable development advanced possibilities. The research reliable rules are derived for the safety and reliable continuity of energetic critical infrastructure organization in the crisis situation.Keywords: Blazons, computational assistance, DYVELOP method, critical infrastructure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1627411 A Proposed Optimized and Efficient Intrusion Detection System for Wireless Sensor Network
Authors: Abdulaziz Alsadhan, Naveed Khan
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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion detection system (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw dataset for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle component analysis (PCA), Linear Discriminant Analysis (LDA) and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. This optimal feature subset is used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) are used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.
Keywords: Particle Swarm Optimization (PSO), Principle component analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2748410 Measures and Influence of a Baw Filter on Digital Radio-Communications Signals
Authors: A. Diet, M. Villegas, G. Baudoin
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This work concerns the measurements of a Bulk Acoustic Waves (BAW) emission filter S parameters and compare with prototypes simulated types. Thanks to HP-ADS, a co-simulation of filters- characteristics in a digital radio-communication chain is performed. Four cases of modulation schemes are studied in order to illustrate the impact of the spectral occupation of the modulated signal. Results of simulations and co-simulation are given in terms of Error Vector Measurements to be useful for a general sensibility analysis of 4th/3rd Generation (G.) emitters (wideband QAM and OFDM signals)Keywords: RF architectures, BAW filters.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2766409 Computing Center Conditions for Non-analytic Vector Fields with Constant Angular Speed
Authors: Li Feng
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We investigate the planar quasi-septic non-analytic systems which have a center-focus equilibrium at the origin and whose angular speed is constant. The system could be changed into an analytic system by two transformations, with the help of computer algebra system MATHEMATICA, the conditions of uniform isochronous center are obtained.
Keywords: Non-analytic, center–focus problem, Lyapunov constant, uniform isochronous center.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1294408 Skyline Extraction using a Multistage Edge Filtering
Authors: Byung-Ju Kim, Jong-Jin Shin, Hwa-Jin Nam, Jin-Soo Kim
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Skyline extraction in mountainous images can be used for navigation of vehicles or UAV(unmanned air vehicles), but it is very hard to extract skyline shape because of clutters like clouds, sea lines and field borders in images. We developed the edge-based skyline extraction algorithm using a proposed multistage edge filtering (MEF) technique. In this method, characteristics of clutters in the image are first defined and then the lines classified as clutters are eliminated by stages using the proposed MEF technique. After this processing, we select the last line using skyline measures among the remained lines. This proposed algorithm is robust under severe environments with clutters and has even good performance for infrared sensor images with a low resolution. We tested this proposed algorithm for images obtained in the field by an infrared camera and confirmed that the proposed algorithm produced a better performance and faster processing time than conventional algorithms.Keywords: MEF, mountainous image, navigation, skyline
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1864407 The Control Vector Scheme for Design of Planar Primitive PH curves
Authors: Ching-Shoei Chiang, Sheng-Hsin Tsai, James Chen
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The PH curve can be constructed by given parameters, but the shape of the curve is not so easy to image from the value of the parameters. On the contract, Bézier curve can be constructed by the control polygon, and from the control polygon, we can image the figure of the curve. In this paper, we want to use the hodograph of Bézier curve to construct PH curve by selecting part of the control vectors, and produce other control vectors, so the property of PH curve exists.Keywords: PH curve, hodograph, Bézier curve.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1484406 On Frenet-Serret Invariants of Non-Null Curves in Lorentzian Space L5
Authors: Melih Turgut, José Luis López-Bonilla, Süha Yılmaz
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The aim of this paper is to determine Frenet-Serret invariants of non-null curves in Lorentzian 5-space. First, we define a vector product of four vectors, by this way, we present a method to calculate Frenet-Serret invariants of the non-null curves. Additionally, an algebraic example of presented method is illustrated.
Keywords: Lorentzian 5-space, Frenet-Serret Invariants, Nonnull Curves
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1516405 Development System for Emotion Detection Based on Brain Signals and Facial Images
Authors: Suprijanto, Linda Sari, Vebi Nadhira , IGN. Merthayasa. Farida I.M
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Detection of human emotions has many potential applications. One of application is to quantify attentiveness audience in order evaluate acoustic quality in concern hall. The subjective audio preference that based on from audience is used. To obtain fairness evaluation of acoustic quality, the research proposed system for multimodal emotion detection; one modality based on brain signals that measured using electroencephalogram (EEG) and the second modality is sequences of facial images. In the experiment, an audio signal was customized which consist of normal and disorder sounds. Furthermore, an audio signal was played in order to stimulate positive/negative emotion feedback of volunteers. EEG signal from temporal lobes, i.e. T3 and T4 was used to measured brain response and sequence of facial image was used to monitoring facial expression during volunteer hearing audio signal. On EEG signal, feature was extracted from change information in brain wave, particularly in alpha and beta wave. Feature of facial expression was extracted based on analysis of motion images. We implement an advance optical flow method to detect the most active facial muscle form normal to other emotion expression that represented in vector flow maps. The reduce problem on detection of emotion state, vector flow maps are transformed into compass mapping that represents major directions and velocities of facial movement. The results showed that the power of beta wave is increasing when disorder sound stimulation was given, however for each volunteer was giving different emotion feedback. Based on features derived from facial face images, an optical flow compass mapping was promising to use as additional information to make decision about emotion feedback.
Keywords: Multimodal Emotion Detection, EEG, Facial Image, Optical Flow, compass mapping, Brain Wave
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2279404 Kalman Filter for Bilinear Systems with Application
Authors: Abdullah E. Al-Mazrooei
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In this paper, we present a new kind of the bilinear systems in the form of state space model. The evolution of this system depends on the product of state vector by its self. The well known Lotak Volterra and Lorenz models are special cases of this new model. We also present here a generalization of Kalman filter which is suitable to work with the new bilinear model. An application to real measurements is introduced to illustrate the efficiency of the proposed algorithm.
Keywords: Bilinear systems, state space model, Kalman filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1960403 Synthesis of Filtering in Stochastic Systems on Continuous-Time Memory Observations in the Presence of Anomalous Noises
Authors: S. Rozhkova, O. Rozhkova, A. Harlova, V. Lasukov
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We have conducted the optimal synthesis of rootmean- squared objective filter to estimate the state vector in the case if within the observation channel with memory the anomalous noises with unknown mathematical expectation are complement in the function of the regular noises. The synthesis has been carried out for linear stochastic systems of continuous - time.
Keywords: Mathematical expectation, filtration, anomalous noise, memory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1958402 Spin Coherent State Path Integral for the Interaction of Two-Level System with Time Dependent Non-Uniform Magnetic Field
Authors: Rekik Rima, Aouachria Mekki
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We study the movement of a two-level atom in interaction with time dependent nonuniform magnetic filed using the path integral formalism. The propagator is first written in the standard form by replacing the spin by a unit vector aligned along the polar and azimuthal directions. Then it is determined exactly using perturbation methods. Thus the Rabi formula of the system are deduced.
Keywords: Path integral, Formalism, Propagator, Transition probability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2008401 A Study on the Differential Diagnostic Model for Newborn Hearing Loss Screening
Authors: Chun-Lang Chang
Abstract:
According to the statistics, the prevalence of congenital hearing loss in Taiwan is approximately six thousandths; furthermore, one thousandths of infants have severe hearing impairment. Hearing ability during infancy has significant impact in the development of children-s oral expressions, language maturity, cognitive performance, education ability and social behaviors in the future. Although most children born with hearing impairment have sensorineural hearing loss, almost every child more or less still retains some residual hearing. If provided with a hearing aid or cochlear implant (a bionic ear) timely in addition to hearing speech training, even severely hearing-impaired children can still learn to talk. On the other hand, those who failed to be diagnosed and thus unable to begin hearing and speech rehabilitations on a timely manner might lose an important opportunity to live a complete and healthy life. Eventually, the lack of hearing and speaking ability will affect the development of both mental and physical functions, intelligence, and social adaptability. Not only will this problem result in an irreparable regret to the hearing-impaired child for the life time, but also create a heavy burden for the family and society. Therefore, it is necessary to establish a set of computer-assisted predictive model that can accurately detect and help diagnose newborn hearing loss so that early interventions can be provided timely to eliminate waste of medical resources. This study uses information from the neonatal database of the case hospital as the subjects, adopting two different analysis methods of using support vector machine (SVM) for model predictions and using logistic regression to conduct factor screening prior to model predictions in SVM to examine the results. The results indicate that prediction accuracy is as high as 96.43% when the factors are screened and selected through logistic regression. Hence, the model constructed in this study will have real help in clinical diagnosis for the physicians and actually beneficial to the early interventions of newborn hearing impairment.
Keywords: Data mining, Hearing impairment, Logistic regression analysis, Support vector machines
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1793400 Double Flux Orientation Control for a Doubly Fed Induction Machine
Authors: A. Ourici
Abstract:
Doubly fed induction machines DFIM are used mainly for wind energy conversion in MW power plants. This paper presents a new strategy of field oriented control ,it is based on the principle of a double flux orientation of stator and rotor at the same time. Therefore, the orthogonality created between the two oriented fluxes, which must be strictly observed, leads to generate a linear and decoupled control with an optimal torque. The obtained simulation results show the feasibility and the effectiveness of the suggested method.Keywords: Doubly fed induction machine, double fluxorientation control , vector control , PWM inverter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2255