Search results for: Slant weighted Toeplitz operator
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 556

Search results for: Slant weighted Toeplitz operator

196 Rural Connectivity Technologies Cost Analysis

Authors: F. Simba, L. Trojer, N.H. Mvungi, B.M. Mwinyiwiwa, E.M. Mjema

Abstract:

Rural areas of Tanzania are still disadvantaged in terms of diffusion of IP-based services; this is due to lack of Information and Communication Technology (ICT) infrastructures, especially lack of connectivity. One of the limitations for connectivity problems in rural areas of Tanzania is the high cost to establish infrastructures for IP-based services [1-2]. However the cost of connectivity varies from one technology to the other and at the same time, the cost is also different from one operator (service provider) to another within the country. This paper presents development of software system to calculate cost of connectivity to rural areas of Tanzania. The system is developed to make an easy access of connectivity cost from different technologies and different operators. The development of the calculator follows the V-model software development lifecycle. The calculator is used to evaluate the economic viability of different technologies considered as being potential candidates to provide rural connectivity. In this paper, the evaluation is based on the techno-economic analysis approach.

Keywords: rural, connectivity, cost, V-model, techno economic analysis.

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195 Optimal Compensation of Reactive Power in the Restructured Distribution Network

Authors: Atefeh Pourshafie, Mohsen. Saniei, S. S. Mortazavi, A. Saeedian

Abstract:

In this paper optimal capacitor placement problem has been formulated in a restructured distribution network. In this scenario the distribution network operator can consider reactive energy also as a service that can be sold to transmission system. Thus search for optimal location, size and number of capacitor banks with the objective of loss reduction, maximum income from selling reactive energy to transmission system and return on investment for capacitors, has been performed. Results is influenced with economic value of reactive energy, therefore problem has been solved for various amounts of it. The implemented optimization technique is genetic algorithm. For any value of reactive power economic value, when reverse of investment index increase and change from zero or negative values to positive values, the threshold value of selling reactive power has been obtained. This increasing price of economic parameter is reasonable until the network losses is less than loss before compensation.

Keywords: capacitor placement, deregulated electric market, distribution network optimization.

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194 High-Resolution 12-Bit Segmented Capacitor DAC in Successive Approximation ADC

Authors: Wee Leong Son, Hasmayadi Abdul Majid, Rohana Musa

Abstract:

This paper study the segmented split capacitor Digital-to-Analog Converter (DAC) implemented in a differentialtype 12-bit Successive Approximation Analog-to-Digital Converter (SA-ADC). The series capacitance split array method employed as it reduced the total area of the capacitors required for high resolution DACs. A 12-bit regular binary array structure requires 2049 unit capacitors (Cs) while the split array needs 127 unit Cs. These results in the reduction of the total capacitance and power consumption of the series split array architectures as to regular binary-weighted structures. The paper will show the 12-bit DAC series split capacitor with 4-bit thermometer coded DAC architectures as well as the simulation and measured results.

Keywords: Successive Approximation Register Analog-to- Digital Converter, SAR ADC, Low voltage ADC.

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193 Remote Sensing, GIS, and AHP for Assessing Physical Vulnerability to Tsunami Hazard

Authors: Abu Bakar Sambah, Fusanori Miura

Abstract:

Remote sensing image processing, spatial data analysis through GIS approach, and analytical hierarchy process were introduced in this study for assessing the vulnerability area and inundation area due to tsunami hazard in the area of Rikuzentakata, Iwate Prefecture, Japan. Appropriate input parameters were derived from GSI DEM data, ALOS AVNIR-2, and field data. We used the parameters of elevation, slope, shoreline distance, and vegetation density. Five classes of vulnerability were defined and weighted via pairwise comparison matrix. The assessment results described that 14.35km2 of the study area was under tsunami vulnerability zone. Inundation areas are those of high and slightly high vulnerability. The farthest area reached by a tsunami was about 7.50km from the shoreline and shows that rivers act as flooding strips that transport tsunami waves into the hinterland. This study can be used for determining a priority for land-use planning in the scope of tsunami hazard risk management.

Keywords: AHP, GIS, remote sensing, tsunami vulnerability.

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192 Security in Resource Constraints Network Light Weight Encryption for Z-MAC

Authors: Mona Almansoori, Ahmed Mustafa, Ahmad Elshamy

Abstract:

Wireless sensor network was formed by a combination of nodes, systematically it transmitting the data to their base stations, this transmission data can be easily compromised if the limited processing power and the data consistency from these nodes are kept in mind; there is always a discussion to address the secure data transfer or transmission in actual time. This will present a mechanism to securely transmit the data over a chain of sensor nodes without compromising the throughput of the network by utilizing available battery resources available in the sensor node. Our methodology takes many different advantages of Z-MAC protocol for its efficiency, and it provides a unique key by sharing the mechanism using neighbor node MAC address. We present a light weighted data integrity layer which is embedded in the Z-MAC protocol to prove that our protocol performs well than Z-MAC when we introduce the different attack scenarios.

Keywords: Hybrid MAC protocol, data integrity, lightweight encryption, Neighbor based key sharing, Sensor node data processing, Z-MAC.

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191 Hybrid TOA/AOA Schemes for Mobile Location in Cellular Communication Systems

Authors: Chien-Sheng Chen, Szu-Lin Su, Chuan-Der Lu

Abstract:

Wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. When fewer base stations (BSs) may be available for location purposes or the measurements with large errors in non-line-of-sight (NLOS) environments, it is necessary to integrate all available heterogeneous measurements to achieve high location accuracy. This paper illustrates a hybrid proposed schemes that combine time of arrival (TOA) at three BSs and angle of arrival (AOA) information at the serving BS to give a location estimate of the MS. The proposed schemes mitigate the NLOS effect simply by the weighted sum of the intersections between three TOA circles and the AOA line without requiring a priori information about the NLOS error. Simulation results show that the proposed methods can achieve better accuracy when compare with Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP).

Keywords: Time of arrival (TOA), angle of arrival (AOA), non-line-of-sight (NLOS).

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190 A New Self-Adaptive EP Approach for ANN Weights Training

Authors: Kristina Davoian, Wolfram-M. Lippe

Abstract:

Evolutionary Programming (EP) represents a methodology of Evolutionary Algorithms (EA) in which mutation is considered as a main reproduction operator. This paper presents a novel EP approach for Artificial Neural Networks (ANN) learning. The proposed strategy consists of two components: the self-adaptive, which contains phenotype information and the dynamic, which is described by genotype. Self-adaptation is achieved by the addition of a value, called the network weight, which depends on a total number of hidden layers and an average number of neurons in hidden layers. The dynamic component changes its value depending on the fitness of a chromosome, exposed to mutation. Thus, the mutation step size is controlled by two components, encapsulated in the algorithm, which adjust it according to the characteristics of a predefined ANN architecture and the fitness of a particular chromosome. The comparative analysis of the proposed approach and the classical EP (Gaussian mutation) showed, that that the significant acceleration of the evolution process is achieved by using both phenotype and genotype information in the mutation strategy.

Keywords: Artificial Neural Networks (ANN), Learning Theory, Evolutionary Programming (EP), Mutation, Self-Adaptation.

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189 A Relationship Extraction Method from Literary Fiction Considering Korean Linguistic Features

Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim

Abstract:

The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.

Keywords: Data mining, Korean linguistic feature, literary fiction, relationship extraction.

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188 Optimal Placement and Sizing of SVC for Load Margin Improvement Using BF Algorithm

Authors: Santi Behera, M. Tripathy, J. K. Satapathy

Abstract:

Power systems are operating under stressed condition due to continuous increase in demand of load. This can lead to voltage instability problem when face additional load increase or contingency. In order to avoid voltage instability suitable size of reactive power compensation at optimal location in the system is required which improves the load margin. This work aims at obtaining optimal size as well as location of compensation in the 39- bus New England system with the help of Bacteria Foraging and Genetic algorithms. To reduce the computational time the work identifies weak candidate buses in the system, and then picks only two of them to take part in the optimization. The objective function is based on a recently proposed voltage stability index which takes into account the weighted average sensitivity index is a simpler and faster approach than the conventional CPF algorithm. BFOA has been found to give better results compared to GA.

Keywords: BFOA, GA, SSVSL, WASI.

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187 Application of Neuro-Fuzzy Dynamic Programming to Improve the Reactive Power and Voltage Profile of a Distribution Substation

Authors: M. Tarafdar Haque, S. Najafi

Abstract:

Improving the reactive power and voltage profile of a distribution substation is investigated in this paper. The purpose is to properly determination of the shunt capacitors on/off status and suitable tap changer (TC) position of a substation transformer. In addition, the limitation of secondary bus voltage, the maximum allowable number of switching operation in a day for on load tap changer and on/off status of capacitors are taken into account. To achieve these goals, an artificial neural network (ANN) is designed to provide preliminary scheduling. Input of ANN is active and reactive powers of transformer and its primary and secondary bus voltages. The output of ANN is capacitors on/off status and TC position. The preliminary schedule is further refined by fuzzy dynamic programming in order to reach the final schedule. The operation of proposed method in Q/V improving is compared with the results obtained by operator operation in a distribution substation.

Keywords: Neuro-fuzzy, Dynamic programming, Reactive power, Voltage profile.

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186 Driver Fatigue State Recognition with Pixel Based Caveat Scheme Using Eye-Tracking

Authors: K. Thulasimani, K. G. Srinivasagan

Abstract:

Driver fatigue is an important factor in the increasing number of road accidents. Dynamic template matching method was proposed to address the problem of real-time driver fatigue detection system based on eye-tracking. An effective vision based approach was used to analyze the driver’s eye state to detect fatigue. The driver fatigue system consists of Face detection, Eye detection, Eye tracking, and Fatigue detection. Initially frames are captured from a color video in a car dashboard and transformed from RGB into YCbCr color space to detect the driver’s face. Canny edge operator was used to estimating the eye region and the locations of eyes are extracted. The extracted eyes were considered as a template matching for eye tracking. Edge Map Overlapping (EMO) and Edge Pixel Count (EPC) matching function were used for eye tracking which is used to improve the matching accuracy. The pixel of eyeball was tracked from the eye regions which are used to determine the fatigue state of the driver.

Keywords: Driver fatigue detection, Driving safety, Eye tracking, Intelligent transportation system, Template matching.

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185 A Modified Decoupled Semi-Analytical Approach Based On SBFEM for Solving 2D Elastodynamic Problems

Authors: M. Fakharian, M. I. Khodakarami

Abstract:

In this paper, a new trend for improvement in semianalytical method based on scale boundaries in order to solve the 2D elastodynamic problems is provided. In this regard, only the boundaries of the problem domain discretization are by specific subparametric elements. Mapping functions are uses as a class of higherorder Lagrange polynomials, special shape functions, Gauss-Lobatto- Legendre numerical integration, and the integral form of the weighted residual method, the matrix is diagonal coefficients in the equations of elastodynamic issues. Differences between study conducted and prior research in this paper is in geometry production procedure of the interpolation function and integration of the different is selected. Validity and accuracy of the present method are fully demonstrated through two benchmark problems which are successfully modeled using a few numbers of DOFs. The numerical results agree very well with the analytical solutions and the results from other numerical methods.

Keywords: 2D Elastodynamic Problems, Lagrange Polynomials, G-L-Lquadrature, Decoupled SBFEM.

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184 Data Mining Determination of Sunlight Average Input for Solar Power Plant

Authors: Fl. Loury, P. Sablonière, C. Lamoureux, G. Magnier, Th. Gutierrez

Abstract:

A method is proposed to extract faithful representative patterns from data set of observations when they are suffering from non-negligible fluctuations. Supposing time interval between measurements to be extremely small compared to observation time, it consists in defining first a subset of intermediate time intervals characterizing coherent behavior. Data projection on these intervals gives a set of curves out of which an ideally “perfect” one is constructed by taking the sup limit of them. Then comparison with average real curve in corresponding interval gives an efficiency parameter expressing the degradation consecutive to fluctuation effect. The method is applied to sunlight data collected in a specific place, where ideal sunlight is the one resulting from direct exposure at location latitude over the year, and efficiency is resulting from action of meteorological parameters, mainly cloudiness, at different periods of the year. The extracted information already gives interesting element of decision, before being used for analysis of plant control.

Keywords: Base Input Reconstruction, Data Mining, Efficiency Factor, Information Pattern Operator.

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183 A Neuro-Fuzzy Approach Based Voting Scheme for Fault Tolerant Systems Using Artificial Bee Colony Training

Authors: D. Uma Devi, P. Seetha Ramaiah

Abstract:

Voting algorithms are extensively used to make decisions in fault tolerant systems where each redundant module gives inconsistent outputs. Popular voting algorithms include majority voting, weighted voting, and inexact majority voters. Each of these techniques suffers from scenarios where agreements do not exist for the given voter inputs. This has been successfully overcome in literature using fuzzy theory. Our previous work concentrated on a neuro-fuzzy algorithm where training using the neuro system substantially improved the prediction result of the voting system. Weight training of Neural Network is sub-optimal. This study proposes to optimize the weights of the Neural Network using Artificial Bee Colony algorithm. Experimental results show the proposed system improves the decision making of the voting algorithms.

Keywords: Voting algorithms, Fault tolerance, Fault masking, Neuro-Fuzzy System (NFS), Artificial Bee Colony (ABC)

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182 Determining Cluster Boundaries Using Particle Swarm Optimization

Authors: Anurag Sharma, Christian W. Omlin

Abstract:

Self-organizing map (SOM) is a well known data reduction technique used in data mining. Data visualization can reveal structure in data sets that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOMs, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of a generic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOMs. The application of our method to unlabeled call data for a mobile phone operator demonstrates its feasibility. PSO algorithm utilizes U-matrix of SOMs to determine cluster boundaries; the results of this novel automatic method correspond well to boundary detection through visual inspection of code vectors and k-means algorithm.

Keywords: Particle swarm optimization, self-organizing maps, clustering, data mining.

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181 Forthcoming Big Data on Smart Buildings and Cities: An Experimental Study on Correlations among Urban Data

Authors: Yu-Mi Song, Sung-Ah Kim, Dongyoun Shin

Abstract:

Cities are complex systems of diverse and inter-tangled activities. These activities and their complex interrelationships create diverse urban phenomena. And such urban phenomena have considerable influences on the lives of citizens. This research aimed to develop a method to reveal the causes and effects among diverse urban elements in order to enable better understanding of urban activities and, therefrom, to make better urban planning strategies. Specifically, this study was conducted to solve a data-recommendation problem found on a Korean public data homepage. First, a correlation analysis was conducted to find the correlations among random urban data. Then, based on the results of that correlation analysis, the weighted data network of each urban data was provided to people. It is expected that the weights of urban data thereby obtained will provide us with insights into cities and show us how diverse urban activities influence each other and induce feedback.

Keywords: Big data, correlation analysis, data recommendation system, urban data network.

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180 A Study of Numerical Reaction-Diffusion Systems on Closed Surfaces

Authors: Mei-Hsiu Chi, Jyh-Yang Wu, Sheng-Gwo Chen

Abstract:

The diffusion-reaction equations are important Partial Differential Equations in mathematical biology, material science, physics, and so on. However, finding efficient numerical methods for diffusion-reaction systems on curved surfaces is still an important and difficult problem. The purpose of this paper is to present a convergent geometric method for solving the reaction-diffusion equations on closed surfaces by an O(r)-LTL configuration method. The O(r)-LTL configuration method combining the local tangential lifting technique and configuration equations is an effective method to estimate differential quantities on curved surfaces. Since estimating the Laplace-Beltrami operator is an important task for solving the reaction-diffusion equations on surfaces, we use the local tangential lifting method and a generalized finite difference method to approximate the Laplace-Beltrami operators and we solve this reaction-diffusion system on closed surfaces. Our method is not only conceptually simple, but also easy to implement.

Keywords: Close surfaces, high-order approach, numerical solutions, reaction-diffusion systems.

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179 An Evaluation Model for Semantic Enablement of Virtual Research Environments

Authors: Tristan O'Neill, Trina Myers, Jarrod Trevathan

Abstract:

The Tropical Data Hub (TDH) is a virtual research environment that provides researchers with an e-research infrastructure to congregate significant tropical data sets for data reuse, integration, searching, and correlation. However, researchers often require data and metadata synthesis across disciplines for crossdomain analyses and knowledge discovery. A triplestore offers a semantic layer to achieve a more intelligent method of search to support the synthesis requirements by automating latent linkages in the data and metadata. Presently, the benchmarks to aid the decision of which triplestore is best suited for use in an application environment like the TDH are limited to performance. This paper describes a new evaluation tool developed to analyze both features and performance. The tool comprises a weighted decision matrix to evaluate the interoperability, functionality, performance, and support availability of a range of integrated and native triplestores to rank them according to requirements of the TDH.

Keywords: Virtual research environment, Semantic Web, performance analysis, tropical data hub.

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178 Application of Feed-Forward Neural Networks Autoregressive Models with Genetic Algorithm in Gross Domestic Product Prediction

Authors: E. Giovanis

Abstract:

In this paper we present a Feed-Foward Neural Networks Autoregressive (FFNN-AR) model with genetic algorithms training optimization in order to predict the gross domestic product growth of six countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer of the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model. Moreover this technique can be used in Autoregressive-Moving Average models, with and without exogenous inputs, as also the training process with genetics algorithms optimization can be replaced by the error back-propagation algorithm.

Keywords: Autoregressive model, Feed-Forward neuralnetworks, Genetic Algorithms, Gross Domestic Product

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177 A New Hybrid RMN Image Segmentation Algorithm

Authors: Abdelouahab Moussaoui, Nabila Ferahta, Victor Chen

Abstract:

The development of aid's systems for the medical diagnosis is not easy thing because of presence of inhomogeneities in the MRI, the variability of the data from a sequence to the other as well as of other different source distortions that accentuate this difficulty. A new automatic, contextual, adaptive and robust segmentation procedure by MRI brain tissue classification is described in this article. A first phase consists in estimating the density of probability of the data by the Parzen-Rozenblatt method. The classification procedure is completely automatic and doesn't make any assumptions nor on the clusters number nor on the prototypes of these clusters since these last are detected in an automatic manner by an operator of mathematical morphology called skeleton by influence zones detection (SKIZ). The problem of initialization of the prototypes as well as their number is transformed in an optimization problem; in more the procedure is adaptive since it takes in consideration the contextual information presents in every voxel by an adaptive and robust non parametric model by the Markov fields (MF). The number of bad classifications is reduced by the use of the criteria of MPM minimization (Maximum Posterior Marginal).

Keywords: Clustering, Automatic Classification, SKIZ, MarkovFields, Image segmentation, Maximum Posterior Marginal (MPM).

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176 Secure Secret Recovery by using Weighted Personal Entropy

Authors: Leau Y. B., Dinna Nina M. N., Habeeb S. A. H., Jetol B.

Abstract:

Authentication plays a vital role in many secure systems. Most of these systems require user to log in with his or her secret password or pass phrase before entering it. This is to ensure all the valuables information is kept confidential guaranteeing also its integrity and availability. However, to achieve this goal, users are required to memorize high entropy passwords or pass phrases. Unfortunately, this sometimes causes difficulty for user to remember meaningless strings of data. This paper presents a new scheme which assigns a weight to each personal question given to the user in revealing the encrypted secrets or password. Concentration of this scheme is to offer fault tolerance to users by allowing them to forget the specific password to a subset of questions and still recover the secret and achieve successful authentication. Comparison on level of security for weight-based and weightless secret recovery scheme is also discussed. The paper concludes with the few areas that requires more investigation in this research.

Keywords: Secret Recovery, Personal Entropy, Cryptography, Secret Sharing and Key Management.

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175 Comparative Analysis of Different Page Ranking Algorithms

Authors: S. Prabha, K. Duraiswamy, J. Indhumathi

Abstract:

Search engine plays an important role in internet, to retrieve the relevant documents among the huge number of web pages. However, it retrieves more number of documents, which are all relevant to your search topics. To retrieve the most meaningful documents related to search topics, ranking algorithm is used in information retrieval technique. One of the issues in data miming is ranking the retrieved document. In information retrieval the ranking is one of the practical problems. This paper includes various Page Ranking algorithms, page segmentation algorithms and compares those algorithms used for Information Retrieval. Diverse Page Rank based algorithms like Page Rank (PR), Weighted Page Rank (WPR), Weight Page Content Rank (WPCR), Hyperlink Induced Topic Selection (HITS), Distance Rank, Eigen Rumor, Distance Rank Time Rank, Tag Rank, Relational Based Page Rank and Query Dependent Ranking algorithms are discussed and compared.

Keywords: Information Retrieval, Web Page Ranking, search engine, web mining, page segmentations.

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174 Performance Analysis of Fuzzy Logic Based Unified Power Flow Controller

Authors: Lütfü Saribulut, Mehmet Tümay, İlyas Eker

Abstract:

FACTS devices are used to control the power flow, to increase the transmission capacity and to optimize the stability of the power system. One of the most widely used FACTS devices is Unified Power Flow Controller (UPFC). The controller used in the control mechanism has a significantly effects on controlling of the power flow and enhancing the system stability of UPFC. According to this, the capability of UPFC is observed by using different control mechanisms based on P, PI, PID and fuzzy logic controllers (FLC) in this study. FLC was developed by taking consideration of Takagi- Sugeno inference system in the decision process and Sugeno-s weighted average method in the defuzzification process. Case studies with different operating conditions are applied to prove the ability of UPFC on controlling the power flow and the effectiveness of controllers on the performance of UPFC. PSCAD/EMTDC program is used to create the FLC and to simulate UPFC model.

Keywords: FACTS, Fuzzy Logic Controller, UPFC.

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173 A Self Adaptive Genetic Based Algorithm for the Identification and Elimination of Bad Data

Authors: A. A. Hossam-Eldin, E. N. Abdallah, M. S. El-Nozahy

Abstract:

The identification and elimination of bad measurements is one of the basic functions of a robust state estimator as bad data have the effect of corrupting the results of state estimation according to the popular weighted least squares method. However this is a difficult problem to handle especially when dealing with multiple errors from the interactive conforming type. In this paper, a self adaptive genetic based algorithm is proposed. The algorithm utilizes the results of the classical linearized normal residuals approach to tune the genetic operators thus instead of making a randomized search throughout the whole search space it is more likely to be a directed search thus the optimum solution is obtained at very early stages(maximum of 5 generations). The algorithm utilizes the accumulating databases of already computed cases to reduce the computational burden to minimum. Tests are conducted with reference to the standard IEEE test systems. Test results are very promising.

Keywords: Bad Data, Genetic Algorithms, Linearized Normal residuals, Observability, Power System State Estimation.

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172 A Geospatial Consumer Marketing Campaign Optimization Strategy: Case of Fuzzy Approach in Nigeria Mobile Market

Authors: Adeolu O. Dairo

Abstract:

Getting the consumer marketing strategy right is a crucial and complex task for firms with a large customer base such as mobile operators in a competitive mobile market. While empirical studies have made efforts to identify key constructs, no geospatial model has been developed to comprehensively assess the viability and interdependency of ground realities regarding the customer, competition, channel and the network quality of mobile operators. With this research, a geo-analytic framework is proposed for strategy formulation and allocation for mobile operators. Firstly, a fuzzy analytic network using a self-organizing feature map clustering technique based on inputs from managers and literature, which depicts the interrelationships amongst ground realities is developed. The model is tested with a mobile operator in the Nigeria mobile market. As a result, a customer-centric geospatial and visualization solution is developed. This provides a consolidated and integrated insight that serves as a transparent, logical and practical guide for strategic, tactical and operational decision making.

Keywords: Geospatial, geo-analytics, self-organizing map, customer-centric.

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171 An Improved Face Recognition Algorithm Using Histogram-Based Features in Spatial and Frequency Domains

Authors: Qiu Chen, Koji Kotani, Feifei Lee, Tadahiro Ohmi

Abstract:

In this paper, we propose an improved face recognition algorithm using histogram-based features in spatial and frequency domains. For adding spatial information of the face to improve recognition performance, a region-division (RD) method is utilized. The facial area is firstly divided into several regions, then feature vectors of each facial part are generated by Binary Vector Quantization (BVQ) histogram using DCT coefficients in low frequency domains, as well as Local Binary Pattern (LBP) histogram in spatial domain. Recognition results with different regions are first obtained separately and then fused by weighted averaging. Publicly available ORL database is used for the evaluation of our proposed algorithm, which is consisted of 40 subjects with 10 images per subject containing variations in lighting, posing, and expressions. It is demonstrated that face recognition using RD method can achieve much higher recognition rate.

Keywords: Face recognition, Binary vector quantization (BVQ), Local Binary Patterns (LBP), DCT coefficients.

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170 A Decision Matrix for the Evaluation of Triplestores for Use in a Virtual Research Environment

Authors: Tristan O’Neill, Trina Myers, Jarrod Trevathan

Abstract:

The Tropical Data Hub (TDH) is a virtual research environment that provides researchers with an e-research infrastructure to congregate significant tropical data sets for data reuse, integration, searching, and correlation. However, researchers often require data and metadata synthesis across disciplines for cross-domain analyses and knowledge discovery. A triplestore offers a semantic layer to achieve a more intelligent method of search to support the synthesis requirements by automating latent linkages in the data and metadata. Presently, the benchmarks to aid the decision of which triplestore is best suited for use in an application environment like the TDH are limited to performance. This paper describes a new evaluation tool developed to analyze both features and performance. The tool comprises a weighted decision matrix to evaluate the interoperability, functionality, performance, and support availability of a range of integrated and native triplestores to rank them according to requirements of the TDH.

Keywords: Virtual research environment, Semantic Web, performance analysis, tropical data hub.

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169 Power System Voltage Control using LP and Artificial Neural Network

Authors: A. Sina, A. Aeenmehr, H. Mohamadian

Abstract:

Optimization and control of reactive power distribution in the power systems leads to the better operation of the reactive power resources. Reactive power control reduces considerably the power losses and effective loads and improves the power factor of the power systems. Another important reason of the reactive power control is improving the voltage profile of the power system. In this paper, voltage and reactive power control using Neural Network techniques have been applied to the 33 shines- Tehran Electric Company. In this suggested ANN, the voltages of PQ shines have been considered as the input of the ANN. Also, the generators voltages, tap transformers and shunt compensators have been considered as the output of ANN. Results of this techniques have been compared with the Linear Programming. Minimization of the transmission line power losses has been considered as the objective function of the linear programming technique. The comparison of the results of the ANN technique with the LP shows that the ANN technique improves the precision and reduces the computation time. ANN technique also has a simple structure and this causes to use the operator experience.

Keywords: voltage control, linear programming, artificial neural network, power systems

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168 IMM based Kalman Filter for Channel Estimation in MB OFDM Systems

Authors: C.Ramesh, V.Vaidehi

Abstract:

Ultra-wide band (UWB) communication is one of the most promising technologies for high data rate wireless networks for short range applications. This paper proposes a blind channel estimation method namely IMM (Interactive Multiple Model) Based Kalman algorithm for UWB OFDM systems. IMM based Kalman filter is proposed to estimate frequency selective time varying channel. In the proposed method, two Kalman filters are concurrently estimate the channel parameters. The first Kalman filter namely Static Model Filter (SMF) gives accurate result when the user is static while the second Kalman filter namely the Dynamic Model Filter (DMF) gives accurate result when the receiver is in moving state. The static transition matrix in SMF is assumed as an Identity matrix where as in DMF, it is computed using Yule-Walker equations. The resultant filter estimate is computed as a weighted sum of individual filter estimates. The proposed method is compared with other existing channel estimation methods.

Keywords: Channel estimation, Kalman filter, UWB, Channel model, AR model

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167 Experiments on Element and Document Statistics for XML Retrieval

Authors: Mohamed Ben Aouicha, Mohamed Tmar, Mohand Boughanem, Mohamed Abid

Abstract:

This paper presents an information retrieval model on XML documents based on tree matching. Queries and documents are represented by extended trees. An extended tree is built starting from the original tree, with additional weighted virtual links between each node and its indirect descendants allowing to directly reach each descendant. Therefore only one level separates between each node and its indirect descendants. This allows to compare the user query and the document with flexibility and with respect to the structural constraints of the query. The content of each node is very important to decide weither a document element is relevant or not, thus the content should be taken into account in the retrieval process. We separate between the structure-based and the content-based retrieval processes. The content-based score of each node is commonly based on the well-known Tf × Idf criteria. In this paper, we compare between this criteria and another one we call Tf × Ief. The comparison is based on some experiments into a dataset provided by INEX1 to show the effectiveness of our approach on one hand and those of both weighting functions on the other.

Keywords: XML retrieval, INEX, Tf × Idf, Tf × Ief

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