Search results for: RAPD technique

Authors: Qianhong Zhang, Lihui Yang, Daixi Liao

Abstract:

In this paper, by employing a new Lyapunov functional and an elementary inequality analysis technique, some sufficient conditions are derived to ensure the existence and uniqueness of periodic oscillatory solution for fuzzy bi-directional memory (BAM) neural networks with time-varying delays, and all other solutions of the fuzzy BAM neural networks converge the uniqueness periodic solution. These criteria are presented in terms of system parameters and have important leading significance in the design and applications of neural networks. Moreover an example is given to illustrate the effectiveness and feasible of results obtained.

Keywords: Fuzzy BAM neural networks, Periodic solution, Global exponential stability, Time-varying delays

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Authors: Deependra Singh, Devender Singh, K. S. Verma

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This paper addresses a novel technique for placement of distributed generation (DG) in electric power systems. A GA based approach for sizing and placement of DG keeping in view of system power loss minimization in different loading conditions is explained. Minimal system power loss is obtained under voltage and line loading constraints. Proposed strategy is applied to power distribution systems and its effectiveness is verified through simulation results on 16, 37-bus and 75-bus test systems.

Keywords: Distributed generation (DG), Genetic algorithms (GA), optimal sizing and placement, Power loss.

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Authors: H. B. Kekre, Tanuja K. Sarode

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Mostly transforms are used for speech data compressions which are lossy algorithms. Such algorithms are tolerable for speech data compression since the loss in quality is not perceived by the human ear. However the vector quantization (VQ) has a potential to give more data compression maintaining the same quality. In this paper we propose speech data compression algorithm using vector quantization technique. We have used VQ algorithms LBG, KPE and FCG. The results table shows computational complexity of these three algorithms. Here we have introduced a new performance parameter Average Fractional Change in Speech Sample (AFCSS). Our FCG algorithm gives far better performance considering mean absolute error, AFCSS and complexity as compared to others.

Keywords: Vector Quantization, Data Compression, Encoding, , Speech coding.

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Authors: Sarra Senhadji, Amar Kateb, Hafida Belbachir

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Data replication in data grid systems is one of the important solutions that improve availability, scalability, and fault tolerance. However, this technique can also bring some involved issues such as maintaining replica consistency. Moreover, as grid environment are very dynamic some nodes can be more uploaded than the others to become eventually a bottleneck. The main idea of our work is to propose a complementary solution between replica consistency maintenance and dynamic load balancing strategy to improve access performances under a simulated grid environment.

Keywords: Consistency, replication, data grid, load balancing.

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Authors: Ahmed Jedidi, Mesfer Mohammed Alshamrani, Alwi Mohammad A. Bamhdi

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Optical performance monitoring and optical network management are essential in building a reliable, high-capacity, and service-differentiation enabled all-optical network. One of the serious problems in this network is the fact that optical crosstalk is additive, and thus the aggregate effect of crosstalk over a whole AON may be more nefarious than a single point of crosstalk. As results, we note a huge degradation of the Quality of Service (QoS) in our network. For that, it is necessary to identify and monitor the impairments in whole network. In this way, this paper presents new system to identify and monitor crosstalk in AONs in real-time fashion. particular, it proposes a new technique to manage intra-crosstalk in objective to relax QoS of the network.

Keywords: All-optical networks, optical crosstalk, optical cross-connect, crosstalk, monitoring crosstalk.

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Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

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In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.

Keywords: Brain balancing, kNN, power spectral density, 3D EEG model.

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Authors: Norshamsuri Ali, Hafizulfika, Salim Ali Al-Kathiri, Abdulla Al-Attas, Suhairi Saharudin, Mohamed Ridza Wahiddin

Abstract:

We demonstrate single-photon interference over 10 km using a plug and play system for quantum key distribution. The quality of the interferometer is measured by using the interferometer visibility. The coding of the signal is based on the phase coding and the value of visibility is based on the interference effect, which result a number of count. The setup gives full control of polarization inside the interferometer. The quality measurement of the interferometer is based on number of count per second and the system produces 94 % visibility in one of the detectors.

Keywords: single photon, interferometer, quantum key distribution.

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Authors: Taiwo. M. Akinmuyisitan, John Cosmas

Abstract:

This paper practically demonstrates the theories and concepts of an Advanced Convolutional Neural Network in the design and development of a scalable artificial intelligence model for the detection of criminal masterminds. The technique uses machine vision algorithms to compute the facial characteristics of suspects and classify actors as criminal or non-criminal faces. The paper proceeds further to compare the results of the error accuracy of two popular custom convolutional pre-trained networks, VGG16 and Resnet50. The result shows that VGG16 is probably more efficient than ResNet50 for the dataset we used.

Keywords: Artificial intelligence, convolutional neural networks, Resnet50, VGG16.

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Authors: Jennifer Leach, Umashanger Thayasivam

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The use of technology has benefited society in more ways than one ever thought possible. Unfortunately, as society’s knowledge of technology has advanced, so has its knowledge of ways to use technology to manipulate others. This has led to a simultaneous advancement in the world of fraud. Machine learning techniques can offer a possible solution to help decrease these advancements. This research explores how the use of various machine learning techniques can aid in detecting fraudulent activity across two different types of fraudulent datasets, and the accuracy, precision, recall, and F1 were recorded for each method. Each machine learning model was also tested across five different training and testing splits in order to discover which split and technique would lead to the most optimal results.

Keywords: Data science, fraud detection, machine learning, supervised learning.

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Authors: Cheng-Fang Huang, Meei-Ling Hung, Teh-Lu Liao, Her-Terng Yau, Jun-Juh Yan

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The design of chaos-based secure communication via synchronized modified Chua-s systems is investigated in this paper. A continuous control law is proposed to ensure synchronization of the master and slave modified Chua-s systems by using the variable structure control technique. Particularly, the concept of extended systems is introduced such that a continuous control input is obtained to avoid chattering phenomenon. Then, it becomes possible to ensure that the message signal embedded in the transmitter can be recovered in the receiver.

Keywords: Chaos, Secure communication, Synchronization, Variable structure control (VSC)

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Authors: Raid R. O. Al-Nima, S. S. Dlay, W. L. Woo

Abstract:

A relationship between face and signature biometrics is established in this paper. A new approach is developed to predict faces from signatures by using artificial intelligence. A multilayer perceptron (MLP) neural network is used to generate face details from features extracted from signatures, here face is the physical biometric and signatures is the behavioural biometric. The new method establishes a relationship between the two biometrics and regenerates a visible face image from the signature features. Furthermore, the performance efficiencies of our new technique are demonstrated in terms of minimum error rates compared to published work.

Keywords: Behavioural biometric, Face biometric, Neural network, Physical biometric, Signature biometric.

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Authors: M. Benbrahim, K. Benjelloun, A. Ibenbrahim, M. Kasmi, E. Ardil

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The automatic discrimination of seismic signals is an important practical goal for the earth-science observatories due to the large amount of information that they receive continuously. An essential discrimination task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, we present new techniques for seismic signals classification: local, regional and global discrimination. These techniques were tested on seismic signals from the data base of the National Geophysical Institute of the Centre National pour la Recherche Scientifique et Technique (Morocco) by using the Moroccan software for seismic signals analysis.

Keywords: Seismic signals, local discrimination, regionaldiscrimination, global discrimination, Moroccan software for seismicsignals analysis.

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Authors: A.T.Z. Mahamat, A.M. A Rani, Patthi Husain

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Copper based composites reinforced with WC and Ti particles were prepared using planetary ball-mill. The experiment was designed by using Taguchi technique and milling was carried out in an air for several hours. The powder was characterized before and after milling using the SEM, TEM and X-ray for microstructure and for possible new phases. Microstructures show that milled particles size and reduction in particle size depend on many parameters. The distance d between planes of atoms estimated from X-ray powder diffraction data and TEM image. X-ray diffraction patterns of the milled powder did not show clearly any new peak or energy shift, but the TEM images show a significant change in crystalline structure of corporate on titanium in the composites.

Keywords: ball milling, microstructures, titanium, tungstencarbides, X-ray

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Authors: Farouq Twaiq, Ishaq Al-Anbari, Mustafa Nasser

Abstract:

The kinetics of palm oil catalytic cracking over aluminum containing mesoporous silica Al-MCM-41 (5% Al) was investigated in a batch autoclave reactor at the temperatures range of 573 – 673 K. The catalyst was prepared by using sol-gel technique and has been characterized by nitrogen adsorption and x-ray diffraction methods. Surface area of 1276 m2/g with average pore diameter of 2.54 nm and pore volume of 0.811 cm3/g was obtained. The experimental catalytic cracking runs were conducted using 50 g of oil and 1 g of catalyst. The reaction pressure was recorded at different time intervals and the data were analyzed using Levenberg- Marquardt (LM) algorithm using polymath software. The results show that the reaction order was found to be -1.5 and activation energy of 3200 J/gmol.

Keywords: Batch Reactor, Catalytic Cracking, Kinetics, Palm Oil.

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Authors: Ahmed Helal, Sherif Zain Elabideen, Ahmed Lotfy

Abstract:

In this paper the modeling and analysis of Space Vector Pulse Width Modulation (SVPWM) based Dynamic Voltage Restorer (DVR) using PSCAD/EMTDC software will be presented in details. The simulation includes full modeling of the SVPWM technique used to control the DVR inverter. A test power system composed of three phase voltage source, sag generator, DVR and three phase resistive load is used to demonstrate restoration capability of the DVR. The simulation results of the presented DVR proved excellent voltage sag mitigation to protect sensitive loads.

Keywords: Dynamic voltage restorer, power quality, simulationand modeling, voltage sag.

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Authors: Mohamed M. Mousa, Aidarkhan Kaltayev

Abstract:

Based on the homotopy perturbation method (HPM) and Padé approximants (PA), approximate and exact solutions are obtained for cubic Boussinesq and modified Boussinesq equations. The obtained solutions contain solitary waves, rational solutions. HPM is used for analytic treatment to those equations and PA for increasing the convergence region of the HPM analytical solution. The results reveal that the HPM with the enhancement of PA is a very effective, convenient and quite accurate to such types of partial differential equations.

Keywords: Homotopy perturbation method, Padé approximants, cubic Boussinesq equation, modified Boussinesq equation.

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Authors: Alshalaa A. Shleeg, Issmail M. Ellabib

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Breast cancer is a major health burden worldwide being a major cause of death amongst women. In this paper, Fuzzy Inference Systems (FIS) are developed for the evaluation of breast cancer risk using Mamdani-type and Sugeno-type models. The paper outlines the basic difference between Mamdani-type FIS and Sugeno-type FIS. The results demonstrated the performance comparison of the two systems and the advantages of using Sugeno- type over Mamdani-type.

Keywords: Breast cancer diagnosis, Fuzzy Inference System (FIS), Fuzzy Logic, fuzzy intelligent technique.

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Authors: S. Thongkeaw, M. Boonthienthong

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This paper presents the techniques for voltage control in distribution system. It is integrated in the distribution management system. Voltage is an important parameter for the control of electrical power systems. The distribution network operators have the responsibility to regulate the voltage supplied to consumer within statutory limits. Traditionally, the On-Load Tap Changer (OLTC) transformer equipped with automatic voltage control (AVC) relays is the most popular and effective voltage control device. A static synchronous compensator (STATCOM) may be equipped with several controllers to perform multiple control functions. Static Var Compensation (SVC) is regulation slopes and available margins for var dispatch. The voltage control in distribution networks is established as a centralized analytical function in this paper. 

Keywords: Voltage Control, Reactive Power, Distribution System.

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Authors: M. Zarebnia, R. Parvaz

Abstract:

In this paper the Kuramoto-Sivashinsky equation is solved numerically by collocation method. The solution is approximated as a linear combination of septic B-spline functions. Applying the Von-Neumann stability analysis technique, we show that the method is unconditionally stable. The method is applied on some test examples, and the numerical results have been compared with the exact solutions. The global relative error and L∞ in the solutions show the efficiency of the method computationally.

Keywords: Kuramoto-Sivashinsky equation, Septic B-spline, Collocation method, Finite difference.

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Authors: A. Jabbari, R. Jedermann, W. Lang

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The new idea of this research is application of a new fault detection and isolation (FDI) technique for supervision of sensor networks in transportation system. In measurement systems, it is necessary to detect all types of faults and failures, based on predefined algorithm. Last improvements in artificial neural network studies (ANN) led to using them for some FDI purposes. In this paper, application of new probabilistic neural network features for data approximation and data classification are considered for plausibility check in temperature measurement. For this purpose, two-phase FDI mechanism was considered for residual generation and evaluation.

Keywords: Fault detection and Isolation, Neural network, Temperature measurement, measurement approximation and classification.

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Authors: Khidir R. Sharaf, Didar A. Ali

Abstract:

The nullity η(G) of a graph is the occurrence of zero as an eigenvalue in its spectra. A zero-sum weighting of a graph G is real valued function, say f from vertices of G to the set of real numbers, provided that for each vertex of G the summation of the weights f(w) over all neighborhood w of v is zero for each v in G.A high zero-sum weighting of G is one that uses maximum number of non-zero independent variables. If G is graph with an end vertex, and if H is an induced subgraph of G obtained by deleting this vertex together with the vertex adjacent to it, then, η(G)= η(H). In this paper, a high zero-sum weighting technique and the endvertex procedure are applied to evaluate the nullity of t-tupple and generalized t-tupple graphs are derived  and determined for some special types of graphs,

 Also, we introduce and prove some important results about the t-tupple coalescence, Cartesian and Kronecker products of nut graphs.

Keywords: Graph theory, Graph spectra, Nullity of graphs.

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Authors: S. Maheswari, P. Arockia Jansi Rani

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Human action is recognized directly from the video sequences. The objective of this work is to recognize various human actions like run, jump, walk etc. Human action recognition requires some prior knowledge about actions namely, the motion estimation, foreground and background estimation. Region of interest (ROI) is extracted to identify the human in the frame. Then, optical flow technique is used to extract the motion vectors. Using the extracted features similarity measure based classification is done to recognize the action. From experimentations upon the Weizmann database, it is found that the proposed method offers a high accuracy.

Keywords: Background subtraction, human silhouette, optical flow, classification.

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Authors: Hwa-Jong Kim

Abstract:

In many countries, digital city or ubiquitous city (u-City) projects have been initiated to provide digitalized economic environments to cities. Recently in Korea, Kangwon Province has started the u-Kangwon project to boost local economy with digitalized tourism services. We analyze the limitations of the ubiquitous IT approach through the u-Kangwon case. We have found that travelers are more interested in quality over speed in access of information. For improved service quality, we are looking to develop an IT-convergence service design framework (ISDF). The ISDF is based on the service engineering technique and composed of three parts: Service Design, Service Simulation, and the Service Platform.

Keywords: Service design, service simulation, service platform, service design framework.

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Authors: Benhamouda Sara, Guezouli Larbi

Abstract:

Nowadays, the dissemination of information touches the distributed world, where selecting the relevant servers to a user request is an important problem in distributed information retrieval. During the last decade, several research studies on this issue have been launched to find optimal solutions and many approaches of collection selection have been proposed. In this paper, we propose a new collection selection approach that takes into consideration the number of documents in a collection that contains terms of the query and the weights of those terms in these documents. We tested our method and our studies show that this technique can compete with other state-of-the-art algorithms that we choose to test the performance of our approach.

Keywords: Distributed information retrieval, relevance, server selection, collection selection.

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Authors: Ram Kumar Soni, Alok Jain, Rajiv Saxena

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The tree structured approach of non-uniform filterbank (NUFB) is normally used in perfect reconstruction (PR). The PR is not always feasible due to certain limitations, i.e, constraints in selecting design parameters, design complexity and some times output is severely affected by aliasing error if necessary and sufficient conditions of PR is not satisfied perfectly. Therefore, there has been generalized interest of researchers to go for near perfect reconstruction (NPR). In this proposed work, an optimized tree structure technique is used for the design of NPR non-uniform filterbank. Window functions of Blackman family are used to design the prototype FIR filter. A single variable linear optimization is used to minimize the amplitude distortion. The main feature of the proposed design is its simplicity with linear phase property.

Keywords: Tree structure, NUFB, QMF, NPR.

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Authors: Joseph C. Chen

Abstract:

Machine vision system provides automatic inspection to reduce manufacturing costs considerably. However, only a few principles have been found to optimize machine vision system and help it function more accurately in industrial practice. Mostly, there were complicated and impractical design techniques to improve the accuracy of machine vision system. This paper discusses implementing the Six Sigma Define, Measure, Analyze, Improve, and Control (DMAIC) approach to optimize the setup parameters of machine vision system when it is used as a direct measurement technique. This research follows a case study showing how Six Sigma DMAIC methodology has been put into use.

Keywords: DMAIC, machine vision system, process capability, Taguchi parameter design.

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Authors: V.P.Subramanyam Rallabandi, S.K.Sett

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An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of independent non-Gaussian densities. The algorithm estimates the data density in each class by using parametric nonlinear functions that fit to the non-Gaussian structure of the data. This improves classification accuracy compared with standard Gaussian mixture models. When applied to textures, the algorithm can learn basis functions for images that capture the statistically significant structure intrinsic in the images. We apply this technique to the problem of unsupervised texture classification and segmentation.

Keywords: Gaussian Mixture Model, Independent Component Analysis, Segmentation, Unsupervised Classification.

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Authors: M. Ertas, A. C. Onel, G. Ekinci, B. Toydemir, S. Durdu, M. Usta, L. Colakerol Arslan

Abstract:

To develop AZ91D magnesium alloys with improved properties, we have applied TiN and VN/TiN multilayer coatings using DC magnetron sputter technique. Coating structure, surface morphology, chemical bonding and corrosion resistance of coatings were analyzed by x-ray diffraction (XRD), scanning electron microscope (SEM), x-ray photoelectron spectroscopy (XPS), and tafel extrapolation method, respectively. XPS analysis reveal that VN overlayer reacts with oxygen at the VN/TiN interface and forms more stable TiN layer. Morphological investigations and the corrosion results show that VN/TiN multilayer thin film coatings are quite effective to optimize the corrosion resistance of Mg alloys.

Keywords: AZ91D Mg alloys, High corrosion resistance, Transition metal nitride coatings, Magnetron sputter.

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Authors: M.R.Shabgard, R.M.Shotorbani

Abstract:

FW4 is a newly developed hot die material widely used in Forging Dies manufacturing. The right selection of the machining conditions is one of the most important aspects to take into consideration in the Electrical Discharge Machining (EDM) of FW4. In this paper an attempt has been made to develop mathematical models for relating the Material Removal Rate (MRR), Tool Wear Ratio (TWR) and surface roughness (Ra) to machining parameters (current, pulse-on time and voltage). Furthermore, a study was carried out to analyze the effects of machining parameters in respect of listed technological characteristics. The results of analysis of variance (ANOVA) indicate that the proposed mathematical models, can adequately describe the performance within the limits of the factors being studied.

Keywords: Electrical Discharge Machining (EDM), linearregression technique, Response Surface Methodology (RSM)

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Authors: Khaled M. EL-Naggar, Khaled A. AL-Rumaih

Abstract:

This paper presents performance comparison of three estimation techniques used for peak load forecasting in power systems. The three optimum estimation techniques are, genetic algorithms (GA), least error squares (LS) and, least absolute value filtering (LAVF). The problem is formulated as an estimation problem. Different forecasting models are considered. Actual recorded data is used to perform the study. The performance of the above three optimal estimation techniques is examined. Advantages of each algorithms are reported and discussed.

Keywords: Forecasting, Least error squares, Least absolute Value, Genetic algorithms

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