Search results for: traditional approach
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6038

Search results for: traditional approach

5678 Analysis of Heuristic Based Hybrid Simulated Annealing Algorithm for Multiprocessor Task Scheduling

Authors: Supriya Arya, Sunita Dhingra

Abstract:

Multiprocessor task scheduling problem for dependent and independent tasks is computationally complex problem. Many methods are proposed to achieve optimal running time. As the multiprocessor task scheduling is NP hard in nature, therefore, many heuristics are proposed which have improved the makespan of the problem. But due to problem specific nature, the heuristic method which provide best results for one problem, might not provide good results for another problem. So, Simulated Annealing which is meta heuristic approach is considered. It can be applied on all types of problems. However, due to many runs, meta heuristic approach takes large computation time. Hence, the hybrid approach is proposed by combining the Duplication Scheduling Heuristic and Simulated Annealing (SA) and the makespan results of Simple Simulated Annealing and Hybrid approach are analyzed.

Keywords: Multiprocessor task scheduling Problem, Makespan, Duplication Scheduling Heuristic, Simulated Annealing, Hybrid Approach.

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5677 Real-time Tracking in Image Sequences based-on Parameters Updating with Temporal and Spatial Neighborhoods Mixture Gaussian Model

Authors: Hu Haibo, Zhao Hong

Abstract:

Gaussian mixture background model is widely used in moving target detection of the image sequences. However, traditional Gaussian mixture background model usually considers the time continuity of the pixels, and establishes background through statistical distribution of pixels without taking into account the pixels- spatial similarity, which will cause noise, imperfection and other problems. This paper proposes a new Gaussian mixture modeling approach, which combines the color and gradient of the spatial information, and integrates the spatial information of the pixel sequences to establish Gaussian mixture background. The experimental results show that the movement background can be extracted accurately and efficiently, and the algorithm is more robust, and can work in real time in tracking applications.

Keywords: Gaussian mixture model, real-time tracking, sequence image, gradient.

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5676 Neuro-Fuzzy Based Model for Phrase Level Emotion Understanding

Authors: Vadivel Ayyasamy

Abstract:

The present approach deals with the identification of Emotions and classification of Emotional patterns at Phrase-level with respect to Positive and Negative Orientation. The proposed approach considers emotion triggered terms, its co-occurrence terms and also associated sentences for recognizing emotions. The proposed approach uses Part of Speech Tagging and Emotion Actifiers for classification. Here sentence patterns are broken into phrases and Neuro-Fuzzy model is used to classify which results in 16 patterns of emotional phrases. Suitable intensities are assigned for capturing the degree of emotion contents that exist in semantics of patterns. These emotional phrases are assigned weights which supports in deciding the Positive and Negative Orientation of emotions. The approach uses web documents for experimental purpose and the proposed classification approach performs well and achieves good F-Scores.

Keywords: Emotions, sentences, phrases, classification, patterns, fuzzy, positive orientation, negative orientation.

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5675 New Approach for Manipulation of Stratified Programs

Authors: Amel Grissa-Touzi, Chadlia Jerad, Habib Ounelli

Abstract:

Negation is useful in the majority of the real world applications. However, its introduction leads to semantic and canonical problems. We propose in this paper an approach based on stratification to deal with negation problems. This approach is based on an extension of predicates nets. It is characterized with two main contributions. The first concerns the management of the whole class of stratified programs. The second contribution is related to usual operations optimizations on stratified programs (maximal stratification, incremental updates ...).

Keywords: stratified programs, stratification, standard model, update operations, SEPN formalism.

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5674 A Calibration Approach towards Reducing ASM2d Parameter Subsets in Phosphorus Removal Processes

Authors: N.Boontian

Abstract:

A novel calibration approach that aims to reduce ASM2d parameter subsets and decrease the model complexity is presented. This approach does not require high computational demand and reduces the number of modeling parameters required to achieve the ASMs calibration by employing a sensitivity and iteration methodology. Parameter sensitivity is a crucial factor and the iteration methodology enables refinement of the simulation parameter values. When completing the iteration process, parameters values are determined in descending order of their sensitivities. The number of iterations required is equal to the number of model parameters of the parameter significance ranking. This approach was used for the ASM2d model to the evaluated EBPR phosphorus removal and it was successful. Results of the simulation provide calibration parameters. These included YPAO, YPO4, YPHA, qPHA, qPP, μPAO, bPAO, bPP, bPHA, KPS, YA, μAUT, bAUT, KO2 AUT, and KNH4 AUT. Those parameters were corresponding to the experimental data available.

Keywords: ASM2d, calibration approach, iteration methodology, sensitivity, phosphorus removal

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5673 A Video-based Algorithm for Moving Objects Detection at Signalized Intersection

Authors: Juan Li, Chunfu Shao, Chunjiao Dong, Dan Zhao, Yinhong Liu

Abstract:

Mixed-traffic (e.g., pedestrians, bicycles, and vehicles) data at an intersection is one of the essential factors for intersection design and traffic control. However, some data such as pedestrian volume cannot be directly collected by common detectors (e.g. inductive loop, sonar and microwave sensors). In this paper, a video based detection algorithm is proposed for mixed-traffic data collection at intersections using surveillance cameras. The algorithm is derived from Gaussian Mixture Model (GMM), and uses a mergence time adjustment scheme to improve the traditional algorithm. Real-world video data were selected to test the algorithm. The results show that the proposed algorithm has the faster processing speed and more accuracy than the traditional algorithm. This indicates that the improved algorithm can be applied to detect mixed-traffic at signalized intersection, even when conflicts occur.

Keywords: detection, intersection, mixed traffic, moving objects.

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5672 An Integrated Natural Language Processing Approach for Conversation System

Authors: Zhi Teng, Ye Liu, Fuji Ren

Abstract:

The main aim of this research is to investigate a novel technique for implementing a more natural and intelligent conversation system. Conversation systems are designed to converse like a human as much as their intelligent allows. Sometimes, we can think that they are the embodiment of Turing-s vision. It usually to return a predetermined answer in a predetermined order, but conversations abound with uncertainties of various kinds. This research will focus on an integrated natural language processing approach. This approach includes an integrated knowledge-base construction module, a conversation understanding and generator module, and a state manager module. We discuss effectiveness of this approach based on an experiment.

Keywords: Conversation System, integrated knowledge-base construction, conversation understanding and generator, state manager

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5671 Performance Management Guide for Research and Development Process

Authors: Heejung Lee

Abstract:

Performance management seems to be essential in business area and is also an exciting topic. Despite significant and myriads of research efforts, performance management guide today as a rigorous approach is still in an immature state and metrics are often selected based on intuitive and heuristic approach. In R&D side, the difficulty to guide the proper performance management is even more increasing due to the natural characteristics of R&D such as unique or domain-specific problems. In our approach, we present R&D performance management guide considering various characteristics of R&D side: performance evaluation objectives, dimensions, metrics, and uncertainties of R&D sector.

Keywords: Performance management, R&D, metrics.

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5670 Toward an Open Network Business Approach

Authors: Valentina Ndou, Laura Schina, Giuseppina Passiante, Pasquale Del Vecchio, Marco De Maggio

Abstract:

The aim of this paper is to propose a dynamic integrated approach, based on modularity concept and on the business ecosystem approach, that exploit different eBusiness services for SMEs under an open business network platform. The adoption of this approach enables firms to collaborate locally for delivering the best product/service to the customers as well as globally by accessing international markets, interrelate directly with the customers, create relationships and collaborate with worldwide actors. The paper will be structured as following: We will start by offering an overview of the state of the art of eBusiness platforms among SME of food and tourism firms and then we discuss the main drawbacks that characterize them. The digital business ecosystem approach and the modularity concept will be described as the theoretical ground in which our proposed integrated model is rooted. Finally, the proposed model along with a discussion of the main value creation potentialities it might create for SMEs will be presented.

Keywords: component, Complexity; Digital Business Ecosystem, e Business Platforms, Modularity, Networks.

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5669 Computational Intelligence Hybrid Learning Approach to Time Series Forecasting

Authors: Chunshien Li, Jhao-Wun Hu, Tai-Wei Chiang, Tsunghan Wu

Abstract:

Time series forecasting is an important and widely popular topic in the research of system modeling. This paper describes how to use the hybrid PSO-RLSE neuro-fuzzy learning approach to the problem of time series forecasting. The PSO algorithm is used to update the premise parameters of the proposed prediction system, and the RLSE is used to update the consequence parameters. Thanks to the hybrid learning (HL) approach for the neuro-fuzzy system, the prediction performance is excellent and the speed of learning convergence is much faster than other compared approaches. In the experiments, we use the well-known Mackey-Glass chaos time series. According to the experimental results, the prediction performance and accuracy in time series forecasting by the proposed approach is much better than other compared approaches, as shown in Table IV. Excellent prediction performance by the proposed approach has been observed.

Keywords: forecasting, hybrid learning (HL), Neuro-FuzzySystem (NFS), particle swarm optimization (PSO), recursiveleast-squares estimator (RLSE), time series

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5668 Self-Organization-Based Approach for Embedded Real-Time System Design

Authors: S. S. Bendib, L. W. Mouss, S. Kalla

Abstract:

This paper proposes a self-organization-based approach for real-time systems design. The addressed issue is the mapping of an application onto an architecture of heterogeneous processors while optimizing both makespan and reliability. Since this problem is NP-hard, a heuristic algorithm is used to obtain efficiently approximate solutions. The proposed approach takes into consideration the quality as well as the diversity of solutions. Indeed, an alternate treatment of the two objectives allows to produce solutions of good quality while a self-organization approach based on the neighborhood structure is used to reorganize solutions and consequently to enhance their diversity. Produced solutions make different compromises between the makespan and the reliability giving the user the possibility to select the solution suited to his (her) needs.

Keywords: Embedded real-time systems design, makespan, reliability, self-organization, compromises.

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5667 A Graph-Based Approach for Placement of No-Replicated Databases in Grid

Authors: Cherif Haddad, Faouzi Ben Charrada

Abstract:

On a such wide-area environment as a Grid, data placement is an important aspect of distributed database systems. In this paper, we address the problem of initial placement of database no-replicated fragments in Grid architecture. We propose a graph based approach that considers resource restrictions. The goal is to optimize the use of computing, storage and communication resources. The proposed approach is developed in two phases: in the first phase, we perform fragment grouping using knowledge about fragments dependency and, in the second phase, we determine an efficient placement of the fragment groups on the Grid. We also show, via experimental analysis that our approach gives solutions that are close to being optimal for different databases and Grid configurations.

Keywords: Grid computing, Distributed systems, Data resourcesmanagement, Database systems, Database placement.

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5666 Sustainability of Urban Cemeteries and the Transformation of Malay Burial Practices in Kuala Lumpur Metropolitan Region

Authors: Mohamed Afla, Mohamad Reza

Abstract:

Land shortage for burials is one of many issues that emerge out of accelerated urban growth in most developing Asian cities, including Kuala Lumpur. Despite actions taken by the federal government and local authorities in addressing this issue, there is no strategic solution being formulated. Apart from making provisions for land to be developed as new cemeteries, the future plan is merely to allocate reserve land to accommodate the increasing demands of burial grounds around the city. This paper examines problems that arise from the traditional practices of Malay funerary as well as an insight to current urban practices in managing Muslim burial spaces around Kuala Lumpur metropolitan region. This paper will also provide some solutions through design approach that can be applied to counter the existing issues.

Keywords: Kuala Lumpur metropolitan region, Malay burial practices, sustainable development, urban cemeteries.

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5665 Evaluation of Leagile Criteria Using DEMATEL Approach

Authors: Naveen Virmani, Rajeev Saha, Rajeshwar Sahai

Abstract:

There is drastic change in manufacturing era in last two decades. It has become mandatory for the industries to become aware of latest and advanced manufacturing technologies and strategies. Leagile manufacturing focuses on minimizing the wastes and meeting customers’ requirements in minimum time possible. However, it becomes difficult to implement all leagile tools simultaneously in industry. In this paper, 17 main criteria of leagile manufacturing have been found and DEMATEL (Decision Making Trial and Evaluation Laboratory) approach has been applied to analyze importance of criteria and casual relations among these criteria.

Keywords: Agile, DEMATEL approach, lean, leagile manufacturing.

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5664 Image Retrieval Based on Multi-Feature Fusion for Heterogeneous Image Databases

Authors: N. W. U. D. Chathurani, Shlomo Geva, Vinod Chandran, Proboda Rajapaksha

Abstract:

Selecting an appropriate image representation is the most important factor in implementing an effective Content-Based Image Retrieval (CBIR) system. This paper presents a multi-feature fusion approach for efficient CBIR, based on the distance distribution of features and relative feature weights at the time of query processing. It is a simple yet effective approach, which is free from the effect of features' dimensions, ranges, internal feature normalization and the distance measure. This approach can easily be adopted in any feature combination to improve retrieval quality. The proposed approach is empirically evaluated using two benchmark datasets for image classification (a subset of the Corel dataset and Oliva and Torralba) and compared with existing approaches. The performance of the proposed approach is confirmed with the significantly improved performance in comparison with the independently evaluated baseline of the previously proposed feature fusion approaches.

Keywords: Feature fusion, image retrieval, membership function, normalization.

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5663 Applying Clustering of Hierarchical K-means-like Algorithm on Arabic Language

Authors: Sameh H. Ghwanmeh

Abstract:

In this study a clustering technique has been implemented which is K-Means like with hierarchical initial set (HKM). The goal of this study is to prove that clustering document sets do enhancement precision on information retrieval systems, since it was proved by Bellot & El-Beze on French language. A comparison is made between the traditional information retrieval system and the clustered one. Also the effect of increasing number of clusters on precision is studied. The indexing technique is Term Frequency * Inverse Document Frequency (TF * IDF). It has been found that the effect of Hierarchical K-Means Like clustering (HKM) with 3 clusters over 242 Arabic abstract documents from the Saudi Arabian National Computer Conference has significant results compared with traditional information retrieval system without clustering. Additionally it has been found that it is not necessary to increase the number of clusters to improve precision more.

Keywords: Hierarchical K-mean like clustering (HKM), Kmeans, cluster centroids, initial partition, and document distances

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5662 Big Brain: A Single Database System for a Federated Data Warehouse Architecture

Authors: X. Gumara Rigol, I. Martínez de Apellaniz Anzuola, A. Garcia Serrano, A. Franzi Cros, O. Vidal Calbet, A. Al Maruf

Abstract:

Traditional federated architectures for data warehousing work well when corporations have existing regional data warehouses and there is a need to aggregate data at a global level. Schibsted Media Group has been maturing from a decentralised organisation into a more globalised one and needed to build both some of the regional data warehouses for some brands at the same time as the global one. In this paper, we present the architectural alternatives studied and why a custom federated approach was the notable recommendation to go further with the implementation. Although the data warehouses are logically federated, the implementation uses a single database system which presented many advantages like: cost reduction and improved data access to global users allowing consumers of the data to have a common data model for detailed analysis across different geographies and a flexible layer for local specific needs in the same place.

Keywords: Data integration, data warehousing, federated architecture, online analytical processing.

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5661 Use of Semantic Networks as Learning Material and Evaluation of the Approach by Students

Authors: Philippe A. Martin

Abstract:

This article first summarizes reasons why current approaches supporting Open Learning and Distance Education need to be complemented by tools permitting lecturers, researchers and students to cooperatively organize the semantic content of Learning related materials (courses, discussions, etc.) into a fine-grained shared semantic network. This first part of the article also quickly describes the approach adopted to permit such a collaborative work. Then, examples of such semantic networks are presented. Finally, an evaluation of the approach by students is provided and analyzed.

Keywords: knowledge sharing, knowledge evaluation, e-learning

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5660 Tuning of PV Array Layout Configurations for Maximum Power Delivery

Authors: Hadj Bourdoucen, Adel Gastli

Abstract:

In this paper, an approach for finding optimized layouts for connecting PV units delivering maximum array output power is suggested. The approach is based on considering the different varying parameters of PV units that might be extracted from a general two-diode model. These are mainly, solar irradiation, reverse saturation currents, ideality factors, series and shunt resistances in addition to operating temperature. The approach has been tested on 19 possible 2×3 configurations and allowed to determine the optimized configurations as well as examine the effects of the different units- parameters on the maximum output power. Thus, using this approach, standard arrays with n×m units can be configured for maximum generated power and allows designing PV based systems having reduced surfaces to fit specific required power, as it is the case for solar cars and other mobile systems.

Keywords: Photovoltaic, PV unit, optimum configuration, maximum power, Orcad.

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5659 Reliability-Based Topology Optimization Based on Evolutionary Structural Optimization

Authors: Sang-Rak Kim, Jea-Yong Park, Won-Goo Lee, Jin-Shik Yu, Seog-Young Han

Abstract:

This paper presents a Reliability-Based Topology Optimization (RBTO) based on Evolutionary Structural Optimization (ESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. Deterministic Topology Optimization (DTO) is obtained without considering of the uncertainties related to the uncertainty parameters. However, RBTO involves evaluation of probabilistic constraints, which can be done in two different ways, the reliability index approach (RIA) and the performance measure approach (PMA). Limit state function is approximated using Monte Carlo Simulation and Central Composite Design for reliability analysis. ESO, one of the topology optimization techniques, is adopted for topology optimization. Numerical examples are presented to compare the DTO with RBTO.

Keywords: Evolutionary Structural Optimization, PerformanceMeasure Approach, Reliability-Based Topology Optimization, Reliability Index Approach.

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5658 Evaluation of Urban Development Proposals An ANP Approach

Authors: T. Gómez-Navarro, M. García-Melón, D. Díaz-Martín, S. Acuna-Dutra,

Abstract:

In this paper a new approach to prioritize urban planning projects in an efficient and reliable way is presented. It is based on environmental pressure indices and multicriteria decision methods. The paper introduces a rigorous method with acceptable complexity of rank ordering urban development proposals according to their environmental pressure. The technique combines the use of Environmental Pressure Indicators, the aggregation of indicators in an Environmental Pressure Index by means of the Analytic Network Process method and interpreting the information obtained from the experts during the decision-making process. The ANP method allows the aggregation of the experts- judgments on each of the indicators into one Environmental Pressure Index. In addition, ANP is based on utility ratio functions which are the most appropriate for the analysis of uncertain data, like experts- estimations. Finally, unlike the other multicriteria techniques, ANP allows the decision problem to be modelled using the relationships among dependent criteria. The method has been applied to the proposal for urban development of La Carlota airport in Caracas (Venezuela). The Venezuelan Government would like to see a recreational project develop on the abandoned area and mean a significant improvement for the capital. There are currently three options on their table which are currently under evaluation. They include a Health Club, a Residential area and a Theme Park. The participating experts coincided in the appreciation that the method proposed in this paper is useful and an improvement from traditional techniques such as environmental impact studies, lifecycle analysis, etc. They find the results obtained coherent, the process seems sufficiently rigorous and precise, and the use of resources is significantly less than in other methods.

Keywords: Environmental pressure indicators, multicriteria decision analysis, analytic network process.

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5657 A Subtractive Clustering Based Approach for Early Prediction of Fault Proneness in Software Modules

Authors: Ramandeep S. Sidhu, Sunil Khullar, Parvinder S. Sandhu, R. P. S. Bedi, Kiranbir Kaur

Abstract:

In this paper, subtractive clustering based fuzzy inference system approach is used for early detection of faults in the function oriented software systems. This approach has been tested with real time defect datasets of NASA software projects named as PC1 and CM1. Both the code based model and joined model (combination of the requirement and code based metrics) of the datasets are used for training and testing of the proposed approach. The performance of the models is recorded in terms of Accuracy, MAE and RMSE values. The performance of the proposed approach is better in case of Joined Model. As evidenced from the results obtained it can be concluded that Clustering and fuzzy logic together provide a simple yet powerful means to model the earlier detection of faults in the function oriented software systems.

Keywords: Subtractive clustering, fuzzy inference system, fault proneness.

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5656 Compression Strength of Treated Fine-Grained Soils with Epoxy or Cement

Authors: M. Mlhem

Abstract:

Geotechnical engineers face many problematic soils upon construction and they have the choice for replacing these soils with more appropriate soils or attempting to improve the engineering properties of the soil through a suitable soil stabilization technique. Mostly, improving soils is environmental, easier and more economical than other solutions. Stabilization soils technique is applied by introducing a cementing agent or by injecting a substance to fill the pore volume. Chemical stabilizers are divided into two groups: traditional agents such as cement or lime and non-traditional agents such as polymers. This paper studies the effect of epoxy additives on the compression strength of four types of soil and then compares with the effect of cement on the compression strength for the same soils. Overall, the epoxy additives are more effective in increasing the strength for different types of soils regardless its classification. On the other hand, there was no clear relation between studied parameters liquid limit, passing No.200, unit weight and between the strength of samples for different types of soils.

Keywords: Additives, clay, compression strength, epoxy, stabilization.

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5655 Forecasting Enrollment Model Based on First-Order Fuzzy Time Series

Authors: Melike Şah, Konstantin Y.Degtiarev

Abstract:

This paper proposes a novel improvement of forecasting approach based on using time-invariant fuzzy time series. In contrast to traditional forecasting methods, fuzzy time series can be also applied to problems, in which historical data are linguistic values. It is shown that proposed time-invariant method improves the performance of forecasting process. Further, the effect of using different number of fuzzy sets is tested as well. As with the most of cited papers, historical enrollment of the University of Alabama is used in this study to illustrate the forecasting process. Subsequently, the performance of the proposed method is compared with existing fuzzy time series time-invariant models based on forecasting accuracy. It reveals a certain performance superiority of the proposed method over methods described in the literature.

Keywords: Forecasting, fuzzy time series, linguistic values, student enrollment, time-invariant model.

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5654 Techno-Economic Analysis Framework for Wave Energy Conversion Schemes under South African Conditions: Modeling and Simulations

Authors: Siyanda S. Biyela, Willie A. Cronje

Abstract:

This paper presents a desktop study of comparing two different wave energy to electricity technologies (WECs) using a techno-economic approach. This techno-economic approach forms basis of a framework for rapid comparison of current and future technologies. The approach also seeks to assist in investment and strategic decision making expediting future deployment of wave energy harvesting in South Africa.

Keywords: Cost of energy, tool, wave energy converter, WEC-Sim.

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5653 Multiple Mental Thought Parametric Classification: A New Approach for Individual Identification

Authors: Ramaswamy Palaniappan

Abstract:

This paper reports a new approach on identifying the individuality of persons by using parametric classification of multiple mental thoughts. In the approach, electroencephalogram (EEG) signals were recorded when the subjects were thinking of one or more (up to five) mental thoughts. Autoregressive features were computed from these EEG signals and classified by Linear Discriminant classifier. The results here indicate that near perfect identification of 400 test EEG patterns from four subjects was possible, thereby opening up a new avenue in biometrics.

Keywords: Autoregressive, Biometrics, Electroencephalogram, Linear discrimination, Mental thoughts.

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5652 A Method of Planar-Template- Based Camera Self-Calibration for Single-View

Authors: Yue Zhao, Chao Li

Abstract:

Camera calibration is an important step in 3D reconstruction. Camera calibration may be classified into two major types: traditional calibration and self-calibration. However, a calibration method in using a checkerboard is intermediate between traditional calibration and self-calibration. A self is proposed based on a square in this paper. Only a square in the planar template, the camera self-calibration can be completed through the single view. The proposed algorithm is that the virtual circle and straight line are established by a square on planar template, and circular points, vanishing points in straight lines and the relation between them are be used, in order to obtain the image of the absolute conic (IAC) and establish the camera intrinsic parameters. To make the calibration template is simpler, as compared with the Zhang Zhengyou-s method. Through real experiments and experiments, the experimental results show that this algorithm is feasible and available, and has a certain precision and robustness.

Keywords: Absolute conic, camera calibration, circle point, vanishing point.

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5651 On the EM Algorithm and Bootstrap Approach Combination for Improving Satellite Image Fusion

Authors: Tijani Delleji, Mourad Zribi, Ahmed Ben Hamida

Abstract:

This paper discusses EM algorithm and Bootstrap approach combination applied for the improvement of the satellite image fusion process. This novel satellite image fusion method based on estimation theory EM algorithm and reinforced by Bootstrap approach was successfully implemented and tested. The sensor images are firstly split by a Bayesian segmentation method to determine a joint region map for the fused image. Then, we use the EM algorithm in conjunction with the Bootstrap approach to develop the bootstrap EM fusion algorithm, hence producing the fused targeted image. We proposed in this research to estimate the statistical parameters from some iterative equations of the EM algorithm relying on a reference of representative Bootstrap samples of images. Sizes of those samples are determined from a new criterion called 'hybrid criterion'. Consequently, the obtained results of our work show that using the Bootstrap EM (BEM) in image fusion improve performances of estimated parameters which involve amelioration of the fused image quality; and reduce the computing time during the fusion process.

Keywords: Satellite image fusion, Bayesian segmentation, Bootstrap approach, EM algorithm.

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5650 Fast Forecasting of Stock Market Prices by using New High Speed Time Delay Neural Networks

Authors: Hazem M. El-Bakry, Nikos Mastorakis

Abstract:

Fast forecasting of stock market prices is very important for strategic planning. In this paper, a new approach for fast forecasting of stock market prices is presented. Such algorithm uses new high speed time delay neural networks (HSTDNNs). The operation of these networks relies on performing cross correlation in the frequency domain between the input data and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the presented HSTDNNs is less than that needed by traditional time delay neural networks (TTDNNs). Simulation results using MATLAB confirm the theoretical computations.

Keywords: Fast Forecasting, Stock Market Prices, Time Delay NeuralNetworks, Cross Correlation, Frequency Domain.

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5649 University Curriculum Policy Processes in Chile: A Case Study

Authors: Victoria C. Valdebenito

Abstract:

Located within the context of accelerating globalization in the 21st-century knowledge society, this paper focuses on one selected university in Chile at which radical curriculum policy changes have been taking place, diverging from the traditional curriculum in Chile at the undergraduate level as a section of a larger investigation. Using a ‘policy trajectory’ framework, and guided by the interpretivist approach to research, interview transcripts and institutional documents were analyzed in relation to the meso (university administration) and the micro (academics) level. Inside the case study, participants from the university administration and academic levels were selected both via snow-ball technique and purposive selection, thus they had different levels of seniority, with some participating actively in the curriculum reform processes. Guided by an interpretivist approach to research, documents and interview transcripts were analyzed to reveal major themes emerging from the data. A further ‘bigger picture’ analysis guided by critical theory was then undertaken, involving interrogation of underlying ideologies and how political and economic interests influence the cultural production of policy. The case-study university was selected because it represents a traditional and old case of university setting in the country, undergoing curriculum changes based on international trends such as the competency model and the liberal arts. Also, it is representative of a particular socioeconomic sector of the country. Access to the university was gained through email contact. Qualitative research methods were used, namely interviews and analysis of institutional documents. In all, 18 people were interviewed. The number was defined by when the saturation criterion was met. Semi-structured interview schedules were based on the four research questions about influences, policy texts, policy enactment and longer-term outcomes. Triangulation of information was used for the analysis. While there was no intention to generalize the specific findings of the case study, the results of the research were used as a focus for engagement with broader themes, often evident in global higher education policy developments. The research results were organized around major themes in three of the four contexts of the ‘policy trajectory’. Regarding the context of influences and the context of policy text production, themes relate to hegemony exercised by first world countries’ universities in the higher education field, its associated neoliberal ideology, with accountability and the discourse of continuous improvement, the local responses to those pressures, and the value of interdisciplinarity. Finally, regarding the context of policy practices and effects (enactment), themes emerged around the impacts of the curriculum changes on university staff, students, and resistance amongst academics. The research concluded with a few recommendations that potentially provide ‘food for thought’ beyond the localized settings of this study, as well as possibilities for further research.

Keywords: Curriculum, policy, higher education, global-local dynamics.

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