Search results for: fault location andfault classification.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2188

Search results for: fault location andfault classification.

628 Simultaneous Clustering and Feature Selection Method for Gene Expression Data

Authors: T. Chandrasekhar, K. Thangavel, E. N. Sathishkumar

Abstract:

Microarrays are made it possible to simultaneously monitor the expression profiles of thousands of genes under various experimental conditions. It is used to identify the co-expressed genes in specific cells or tissues that are actively used to make proteins. This method is used to analysis the gene expression, an important task in bioinformatics research. Cluster analysis of gene expression data has proved to be a useful tool for identifying co-expressed genes, biologically relevant groupings of genes and samples. In this work K-Means algorithms has been applied for clustering of Gene Expression Data. Further, rough set based Quick reduct algorithm has been applied for each cluster in order to select the most similar genes having high correlation. Then the ACV measure is used to evaluate the refined clusters and classification is used to evaluate the proposed method. They could identify compact clusters with feature selection method used to genes are selected.

Keywords: Clustering, Feature selection, Gene expression data, Quick reduct.

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627 Microscopic Analysis of Welded Dental Alloys

Authors: S. Porojan, L. Sandu, F. Topalâ

Abstract:

Microplasma welding is a less expensive alternative to laser welding in dental technology. The aim of the study was to highlight discontinuities present in the microplasma welded joints of dental base metal alloys by visual analysis. Five base metal alloys designated for fixed prostheses manufacture were selected for the experiments. Using these plates, preliminary tests were conducted by microplasma welding in butt joint configuration, without filler material, bilaterally and with filler material, proper for each base metal. Macroscopic visual inspection was performed to assess carefully the irregularities in the welds. Electron microscopy allowed detection of discontinuities that are not visible to the eye and revealing details regarding location, trajectory, morphology and size of discontinuities. Supplementing visual control with microscopic analysis allows to detect small discontinuities, which escapes the macroscopic control and to make a detailed study of the weld.

Keywords: base metal alloys, fixed prosthodontics, microplasmawelding, visual inspection

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626 Evaluation of Minimization of Moment Ratio Method by Physical Modeling

Authors: Amin Eslami, Jafar Bolouri Bazaz

Abstract:

Under active stress conditions, a rigid cantilever retaining wall tends to rotate about a pivot point located within the embedded depth of the wall. For purely granular and cohesive soils, a methodology was previously reported called minimization of moment ratio to determine the location of the pivot point of rotation. The usage of this new methodology is to estimate the rotational stability safety factor. Moreover, the degree of improvement required in a backfill to get a desired safety factor can be estimated by the concept of the shear strength demand. In this article, the accuracy of this method for another type of cantilever walls called Contiguous Bored Pile (CBP) retaining wall is evaluated by using physical modeling technique. Based on observations, the results of moment ratio minimization method are in good agreement with the results of the carried out physical modeling.

Keywords: Cantilever Retaining Wall, Physical Modeling, Minimization of Moment Ratio Method, Pivot Point.

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625 An Efficient Technique for Extracting Fuzzy Rulesfrom Neural Networks

Authors: Besa Muslimi, Miriam A. M. Capretz, Jagath Samarabandu

Abstract:

Artificial neural networks (ANN) have the ability to model input-output relationships from processing raw data. This characteristic makes them invaluable in industry domains where such knowledge is scarce at best. In the recent decades, in order to overcome the black-box characteristic of ANNs, researchers have attempted to extract the knowledge embedded within ANNs in the form of rules that can be used in inference systems. This paper presents a new technique that is able to extract a small set of rules from a two-layer ANN. The extracted rules yield high classification accuracy when implemented within a fuzzy inference system. The technique targets industry domains that possess less complex problems for which no expert knowledge exists and for which a simpler solution is preferred to a complex one. The proposed technique is more efficient, simple, and applicable than most of the previously proposed techniques.

Keywords: fuzzy rule extraction, fuzzy systems, knowledgeacquisition, pattern recognition, artificial neural networks.

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624 Between Policy Options and Technology Applications: Measuring the Sustainable Impacts on Distance Learning

Authors: Subramaniam Chandran

Abstract:

This paper examines the interplay of policy options and cost-effective technology in providing sustainable distance education. A case study has been conducted among the learners and teachers. The emergence of learning technologies through CD, internet, and mobile is increasingly adopted by distance institutes for quick delivery and cost-effective factors. Their sustainability is conditioned by the structure of learners and well as the teaching community. The structure of learners in terms of rural and urban background revealed similarity in adoption and utilization of mobile learning. In other words, the technology transcended the rural-urban dichotomy. The teaching community was divided into two groups on policy issues. This study revealed both cost-effective as well as sustainability impacts on different learners groups divided by rural and urban location.

Keywords: Distance Education, Mobile Learning, Policy, Technology

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623 A Study of Gaps in CBMIR Using Different Methods and Prospective

Authors: Pradeep Singh, Sukhwinder Singh, Gurjinder Kaur

Abstract:

In recent years, rapid advances in software and hardware in the field of information technology along with a digital imaging revolution in the medical domain facilitate the generation and storage of large collections of images by hospitals and clinics. To search these large image collections effectively and efficiently poses significant technical challenges, and it raises the necessity of constructing intelligent retrieval systems. Content-based Image Retrieval (CBIR) consists of retrieving the most visually similar images to a given query image from a database of images[5]. Medical CBIR (content-based image retrieval) applications pose unique challenges but at the same time offer many new opportunities. On one hand, while one can easily understand news or sports videos, a medical image is often completely incomprehensible to untrained eyes.

Keywords: Classification, clustering, content-based image retrieval (CBIR), relevance feedback (RF), statistical similarity matching, support vector machine (SVM).

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622 A New Fuzzy Mathematical Model in Recycling Collection Networks: A Possibilistic Approach

Authors: B. Vahdani, R. Tavakkoli-Moghaddam, A. Baboli, S. M. Mousavi

Abstract:

Focusing on the environmental issues, including the reduction of scrap and consumer residuals, along with the benefiting from the economic value during the life cycle of goods/products leads the companies to have an important competitive approach. The aim of this paper is to present a new mixed nonlinear facility locationallocation model in recycling collection networks by considering multi-echelon, multi-suppliers, multi-collection centers and multifacilities in the recycling network. To make an appropriate decision in reality, demands, returns, capacities, costs and distances, are regarded uncertain in our model. For this purpose, a fuzzy mathematical programming-based possibilistic approach is introduced as a solution methodology from the recent literature to solve the proposed mixed-nonlinear programming model (MNLP). The computational experiments are provided to illustrate the applicability of the designed model in a supply chain environment and to help the decision makers to facilitate their analysis.

Keywords: Location-allocation model, recycling collection networks, fuzzy mathematical programming.

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621 Digital Learning Environments for Joint Master in Science Programmes in Building and Construction in Europe: Experimenting with Tools and Technologies

Authors: E. Dado, R. Beheshti

Abstract:

Recent developments in information and communication technologies (ICT) have created excellent conditions for profoundly enhancing the traditional learning and teaching practices. New modes of teaching in higher education subjects can profoundly enhance ones ability to proactively constructing his or her personal learning universe. These developments have contributed to digital learning environments becoming widely available and accessible. In addition, there is a trend towards enlargement and specialization in higher education in Europe. With as a result that existing Master of Science (MSc) programmes are merged or new programmes have been established that are offered as joint MSc programmes to students. In these joint MSc programmes, the need for (common) digital learning environments capable of surmounting the barriers of time and location has become evident. This paper discusses the past and ongoing efforts to establish such common digital learning environments in two joint MSc programmes in Europe and discusses the way technology-based learning environments affect the traditional way of learning.

Keywords: education, engineering, learning environments, ICT.

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620 Off-Line Hand Written Thai Character Recognition using Ant-Miner Algorithm

Authors: P. Phokharatkul, K. Sankhuangaw, S. Somkuarnpanit, S. Phaiboon, C. Kimpan

Abstract:

Much research into handwritten Thai character recognition have been proposed, such as comparing heads of characters, Fuzzy logic and structure trees, etc. This paper presents a system of handwritten Thai character recognition, which is based on the Ant-minor algorithm (data mining based on Ant colony optimization). Zoning is initially used to determine each character. Then three distinct features (also called attributes) of each character in each zone are extracted. The attributes are Head zone, End point, and Feature code. All attributes are used for construct the classification rules by an Ant-miner algorithm in order to classify 112 Thai characters. For this experiment, the Ant-miner algorithm is adapted, with a small change to increase the recognition rate. The result of this experiment is a 97% recognition rate of the training set (11200 characters) and 82.7% recognition rate of unseen data test (22400 characters).

Keywords: Hand written, Thai character recognition, Ant-mineralgorithm, distinct feature.

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619 Classification of Buckling Behavior on Uniaxial Compression using A5052-O Sheets

Authors: S. Onoda, S. Yoshihara, B. J. MacDonald, Y. Okude

Abstract:

Aluminum alloy sheets have several advantages such as the lightweight, high-specific strength and recycling efficiency. Therefore, aluminum alloy sheets in sheet forming have been used in various areas as automotive components and so forth. During the process of sheet forming, wrinkling which is caused by compression stress might occur and the formability of sheets was affected by occurrence of wrinkling. A few studies of uniaxial compressive test by using square tubes, pipes and sheets were carried out to clarify the each wrinkling behavior. However, on uniaxial compressive test, deformation behavior of the sheets hasn-t be cleared. Then, it is necessary to clarify the relationship between the buckling behavior and the forming conditions. In this study, the effect of dimension of the sheet in the buckling behavior on compression test of aluminum alloy sheet was cleared by experiment and FEA. As the results, the buckling deformation was classified by three modes in terms of the distribution of equivalent plastic strain.

Keywords: Sheet forming, Compression test, Aluminum alloy sheet, Buckling behavior

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618 Application of Generalized Autoregressive Score Model to Stock Returns

Authors: Katleho Daniel Makatjane, Diteboho Lawrence Xaba, Ntebogang Dinah Moroke

Abstract:

The current study investigates the behaviour of time-varying parameters that are based on the score function of the predictive model density at time t. The mechanism to update the parameters over time is the scaled score of the likelihood function. The results revealed that there is high persistence of time-varying, as the location parameter is higher and the skewness parameter implied the departure of scale parameter from the normality with the unconditional parameter as 1.5. The results also revealed that there is a perseverance of the leptokurtic behaviour in stock returns which implies the returns are heavily tailed. Prior to model estimation, the White Neural Network test exposed that the stock price can be modelled by a GAS model. Finally, we proposed further researches specifically to model the existence of time-varying parameters with a more detailed model that encounters the heavy tail distribution of the series and computes the risk measure associated with the returns.

Keywords: Generalized autoregressive score model, stock returns, time-varying.

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617 Natural Disaster Tourism as a Type of Dark Tourism

Authors: Dorota Rucińska

Abstract:

This theoretical paper combines the academic discourse regarding a specific part of dark tourism. Based on the literature analysis, distinction of natural disasters in thanatourism was investigated, which is connected with dynamic geographical conditions. Natural disasters used to play an important role in social life by their appearance in myths and religions. Nowadays, tourists pursuing natural hazards can be divided into three groups: Those interested in natural hazards themselves; those interested in landscape deformation and experiencing emotions shortly after extreme events - natural disasters - occur; and finally those interested in historic places log after an extreme event takes place. An important element of the natural disaster tourism is quick access to information on the location of a disaster and the destination of a potential excursion. Natural disaster tourism suits alternative tourism, yet it is opposed culture tourism, and sustainable tourism. The paper compares types and groups of tourists. It also considers the contradictions that describe dualism, which exists in dark tourism.

Keywords: Dark tourism, dualism, natural disasters, natural hazards, thanatoursim.

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616 OPEN_EmoRec_II- A Multimodal Corpus of Human-Computer Interaction

Authors: Stefanie Rukavina, Sascha Gruss, Steffen Walter, Holger Hoffmann, Harald C. Traue

Abstract:

OPEN_EmoRec_II is an open multimodal corpus with experimentally induced emotions. In the first half of the experiment, emotions were induced with standardized picture material and in the second half during a human-computer interaction (HCI), realized with a wizard-of-oz design. The induced emotions are based on the dimensional theory of emotions (valence, arousal and dominance). These emotional sequences - recorded with multimodal data (facial reactions, speech, audio and physiological reactions) during a naturalistic-like HCI-environment one can improve classification methods on a multimodal level. This database is the result of an HCI-experiment, for which 30 subjects in total agreed to a publication of their data including the video material for research purposes*. The now available open corpus contains sensory signal of: video, audio, physiology (SCL, respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus Major) and facial reactions annotations.

Keywords: Open multimodal emotion corpus, annotated labels.

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615 OPEN_EmoRec_II- A Multimodal Corpus of Human-Computer Interaction

Authors: Stefanie Rukavina, Sascha Gruss, Steffen Walter, Holger Hoffmann, Harald C. Traue

Abstract:

OPEN_EmoRec_II is an open multimodal corpus with experimentally induced emotions. In the first half of the experiment, emotions were induced with standardized picture material and in the second half during a human-computer interaction (HCI), realized with a wizard-of-oz design. The induced emotions are based on the dimensional theory of emotions (valence, arousal and dominance). These emotional sequences - recorded with multimodal data (facial reactions, speech, audio and physiological reactions) during a naturalistic-like HCI-environment one can improve classification methods on a multimodal level. This database is the result of an HCI-experiment, for which 30 subjects in total agreed to a publication of their data including the video material for research purposes*. The now available open corpus contains sensory signal of: video, audio, physiology (SCL, respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus Major) and facial reactions annotations.

Keywords: Open multimodal emotion corpus, annotated labels.

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614 Human Facial Expression Recognition using MANFIS Model

Authors: V. Gomathi, Dr. K. Ramar, A. Santhiyaku Jeevakumar

Abstract:

Facial expression analysis plays a significant role for human computer interaction. Automatic analysis of human facial expression is still a challenging problem with many applications. In this paper, we propose neuro-fuzzy based automatic facial expression recognition system to recognize the human facial expressions like happy, fear, sad, angry, disgust and surprise. Initially facial image is segmented into three regions from which the uniform Local Binary Pattern (LBP) texture features distributions are extracted and represented as a histogram descriptor. The facial expressions are recognized using Multiple Adaptive Neuro Fuzzy Inference System (MANFIS). The proposed system designed and tested with JAFFE face database. The proposed model reports 94.29% of classification accuracy.

Keywords: Adaptive neuro-fuzzy inference system, Facialexpression, Local binary pattern, Uniform Histogram

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613 A New Vector Quantization Front-End Process for Discrete HMM Speech Recognition System

Authors: M. Debyeche, J.P Haton, A. Houacine

Abstract:

The paper presents a complete discrete statistical framework, based on a novel vector quantization (VQ) front-end process. This new VQ approach performs an optimal distribution of VQ codebook components on HMM states. This technique that we named the distributed vector quantization (DVQ) of hidden Markov models, succeeds in unifying acoustic micro-structure and phonetic macro-structure, when the estimation of HMM parameters is performed. The DVQ technique is implemented through two variants. The first variant uses the K-means algorithm (K-means- DVQ) to optimize the VQ, while the second variant exploits the benefits of the classification behavior of neural networks (NN-DVQ) for the same purpose. The proposed variants are compared with the HMM-based baseline system by experiments of specific Arabic consonants recognition. The results show that the distributed vector quantization technique increase the performance of the discrete HMM system.

Keywords: Hidden Markov Model, Vector Quantization, Neural Network, Speech Recognition, Arabic Language

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612 Performance Analysis of a Dynamic Channel Reservation-Like Technique for Low Earth Orbit Mobile Satellite Systems

Authors: W. Kiamouche, S. Lasmari, M. Benslama

Abstract:

In order to derive important parameters concerning mobile subscriber MS with ongoing calls in Low Earth Orbit Mobile Satellite Systems LEO MSSs, a positioning system had to be integrated into MSS in order to localize mobile subscribers MSs and track them during the connection. Such integration is regarded as a complex implementation. We propose in this paper a novel method based on advantages of mobility model of Low Earth Orbit Mobile Satellite System LEO MSS which allows the evaluation of instant of subsequent handover of a MS even if its location is unknown. This method is utilized to propose a Dynamic Channel Reservation DCRlike scheme based on the DCR scheme previously proposed in literature. Results presented show that DCR-like technique gives different QoS performance than DCR. Indeed, an improve in handover blocking probability and an increase in new call blocking probability are observed for the DCR-like technique.

Keywords: cellular layout, DCR, LEO mobile satellite system, mobility model, positioning system

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611 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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610 Topological Sensitivity Analysis for Reconstruction of the Inverse Source Problem from Boundary Measurement

Authors: Maatoug Hassine, Mourad Hrizi

Abstract:

In this paper, we consider a geometric inverse source problem for the heat equation with Dirichlet and Neumann boundary data. We will reconstruct the exact form of the unknown source term from additional boundary conditions. Our motivation is to detect the location, the size and the shape of source support. We present a one-shot algorithm based on the Kohn-Vogelius formulation and the topological gradient method. The geometric inverse source problem is formulated as a topology optimization one. A topological sensitivity analysis is derived from a source function. Then, we present a non-iterative numerical method for the geometric reconstruction of the source term with unknown support using a level curve of the topological gradient. Finally, we give several examples to show the viability of our presented method.

Keywords: Geometric inverse source problem, heat equation, topological sensitivity, topological optimization, Kohn-Vogelius formulation.

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609 Image Analysis of Fine Structures of Supercavitation in the Symmetric Wake of a Cylinder

Authors: Y. Obikane , M.Kaneko, K.Kakioka, K.Ogura

Abstract:

The fine structure of supercavitation in the wake of a symmetrical cylinder is studied with high-speed video cameras. The flow is observed in a cavitation tunnel at the speed of 8m/sec when the sidewall and the wake are partially filled with the massive cavitation bubbles. The present experiment observed that a two-dimensional ripple wave with a wave length of 0.3mm is propagated in a downstream direction, and then abruptly increases to a thicker three-dimensional layer. IR-photography recorded that the wakes originated from the horseshoe vortexes alongside the cylinder. The wake was developed to inside the dead water zone, which absorbed the bubbly wake propelled from the separated vortices at the center of the cylinder. A remote sensing classification technique (maximum most likelihood) determined that the surface porosity was 0.2, and the mean speed in the mixed wake was 7m/sec. To confirm the existence of two-dimensional wave motions in the interface, the experiments were conducted at a very low frequency, and showed similar gravity waves in both the upper and lower interfaces.

Keywords: Supercavitation, density gradient correlation

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608 A Prediction-Based Reversible Watermarking for MRI Images

Authors: Nuha Omran Abokhdair, Azizah Bt Abdul Manaf

Abstract:

Reversible watermarking is a special branch of image watermarking, that is able to recover the original image after extracting the watermark from the image. In this paper, an adaptive prediction-based reversible watermarking scheme is presented, in order to increase the payload capacity of MRI medical images. The scheme divides the image into two parts, Region of Interest (ROI) and Region of Non-Interest (RONI). Two bits are embedded in each embeddable pixel of RONI and one bit is embedded in each embeddable pixel of ROI. The experimental results demonstrate that the proposed scheme is able to achieve high embedding capacity. This is mainly caused by two reasons. First, the pixels that were excluded from data embedding due to overflow/underflow are used for data embedding. Second, large location map that need to be added to watermark data as overhead is eliminated and thus lower data embedding capacity is prevented. Moreover, the scheme provides good visual quality to the watermarked image.

Keywords: Medical image watermarking, reversible watermarking, Difference Expansion, Prediction-Error Expansion.

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607 A Combined Fuzzy Decision Making Approach to Supply Chain Risk Assessment

Authors: P. Moeinzadeh, A. Hajfathaliha

Abstract:

Many firms implemented various initiatives such as outsourced manufacturing which could make a supply chain (SC) more vulnerable to various types of disruptions. So managing risk has become a critical component of SC management. Different types of SC vulnerability management methodologies have been proposed for managing SC risk, most offer only point-based solutions that deal with a limited set of risks. This research aims to reinforce SC risk management by proposing an integrated approach. SC risks are identified and a risk index classification structure is created. Then we develop a SC risk assessment approach based on the analytic network process (ANP) and the VIKOR methods under the fuzzy environment where the vagueness and subjectivity are handled with linguistic terms parameterized by triangular fuzzy numbers. By using FANP, risks weights are calculated and then inserted to the FVIKOR to rank the SC members and find the most risky partner.

Keywords: Analytic network process (ANP), Fuzzy sets, Supply chain risk management (SCRM), VIšekriterijumsko KOmpromisno Rangiranje (VIKOR)

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606 Intelligent Multi-Agent Middleware for Ubiquitous Home Networking Environments

Authors: Minwoo Son, Seung-Hun Lee, Dongkyoo Shin, Dongil Shin

Abstract:

The next stage of the home networking environment is supposed to be ubiquitous, where each piece of material is equipped with an RFID (Radio Frequency Identification) tag. To fully support the ubiquitous environment, home networking middleware should be able to recommend home services based on a user-s interests and efficiently manage information on service usage profiles for the users. Therefore, USN (Ubiquitous Sensor Network) technology, which recognizes and manages a appliance-s state-information (location, capabilities, and so on) by connecting RFID tags is considered. The Intelligent Multi-Agent Middleware (IMAM) architecture was proposed to intelligently manage the mobile RFID-based home networking and to automatically supply information about home services that match a user-s interests. Evaluation results for personalization services for IMAM using Bayesian-Net and Decision Trees are presented.

Keywords: Intelligent Agents, Home Network, Mobile RFID, Intelligent Middleware.

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605 Seismic Fragility Assessment of Strongback Steel Braced Frames Subjected to Near-Field Earthquakes

Authors: Mohammadreza Salek Faramarzi, Touraj Taghikhany

Abstract:

In this paper, seismic fragility assessment of a recently developed hybrid structural system, known as the strongback system (SBS) is investigated. In this system, to mitigate the occurrence of the soft-story mechanism and improve the distribution of story drifts over the height of the structure, an elastic vertical truss is formed. The strengthened members of the braced span are designed to remain substantially elastic during levels of excitation where soft-story mechanisms are likely to occur and impose a nearly uniform story drift distribution. Due to the distinctive characteristics of near-field ground motions, it seems to be necessary to study the effect of these records on seismic performance of the SBS. To this end, a set of 56 near-field ground motion records suggested by FEMA P695 methodology is used. For fragility assessment, nonlinear dynamic analyses are carried out in OpenSEES based on the recommended procedure in HAZUS technical manual. Four damage states including slight, moderate, extensive, and complete damage (collapse) are considered. To evaluate each damage state, inter-story drift ratio and floor acceleration are implemented as engineering demand parameters. Further, to extend the evaluation of the collapse state of the system, a different collapse criterion suggested in FEMA P695 is applied. It is concluded that SBS can significantly increase the collapse capacity and consequently decrease the collapse risk of the structure during its life time. Comparing the observing mean annual frequency (MAF) of exceedance of each damage state against the allowable values presented in performance-based design methods, it is found that using the elastic vertical truss, improves the structural response effectively.

Keywords: Strongback System, Near-fault, Seismic fragility, Uncertainty, IDA, Probabilistic performance assessment.

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604 3D CAD Models and its Feature Similarity

Authors: Elmi Abu Bakar, Tetsuo Miyake, Zhong Zhang, Takashi Imamura

Abstract:

Knowing the geometrical object pose of products in manufacturing line before robot manipulation is required and less time consuming for overall shape measurement. In order to perform it, the information of shape representation and matching of objects is become required. Objects are compared with its descriptor that conceptually subtracted from each other to form scalar metric. When the metric value is smaller, the object is considered closed to each other. Rotating the object from static pose in some direction introduce the change of value in scalar metric value of boundary information after feature extraction of related object. In this paper, a proposal method for indexing technique for retrieval of 3D geometrical models based on similarity between boundaries shapes in order to measure 3D CAD object pose using object shape feature matching for Computer Aided Testing (CAT) system in production line is proposed. In experimental results shows the effectiveness of proposed method.

Keywords: CAD, rendering, feature extraction, feature classification.

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603 Improving University Operations with Data Mining: Predicting Student Performance

Authors: Mladen Dragičević, Mirjana Pejić Bach, Vanja Šimičević

Abstract:

The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.

Keywords: Data mining, knowledge discovery in databases, prediction models, student success.

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602 Range-Free Localization Schemes for Wireless Sensor Networks

Authors: R. Khadim, M. Erritali, A. Maaden

Abstract:

Localization of nodes is one of the key issues of Wireless Sensor Network (WSN) that gained a wide attention in recent years. The existing localization techniques can be generally categorized into two types: range-based and range-free. Compared with rang-based schemes, the range-free schemes are more costeffective, because no additional ranging devices are needed. As a result, we focus our research on the range-free schemes. In this paper we study three types of range-free location algorithms to compare the localization error and energy consumption of each one. Centroid algorithm requires a normal node has at least three neighbor anchors, while DV-hop algorithm doesn’t have this requirement. The third studied algorithm is the amorphous algorithm similar to DV-Hop algorithm, and the idea is to calculate the hop distance between two nodes instead of the linear distance between them. The simulation results show that the localization accuracy of the amorphous algorithm is higher than that of other algorithms and the energy consumption does not increase too much.

Keywords: Wireless Sensor Networks, Node Localization, Centroid Algorithm, DV–Hop Algorithm, Amorphous Algorithm.

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601 A Weighted Approach to Unconstrained Iris Recognition

Authors: Yao-Hong Tsai

Abstract:

This paper presents a weighted approach to unconstrained iris recognition. In nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.

Keywords: Authentication, iris recognition, Adaboost, local binary pattern.

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600 Holomorphic Prioritization of Sets within Decagram of Strategic Decision Making of POSM Using Operational Research (OR): Analytic Hierarchy Process (AHP) Analysis

Authors: Elias O. Tembe, Hussain A. Al-Salamin

Abstract:

There is decagram of strategic decisions of operations and production/service management (POSM) within operational research (OR) which must collate, namely: design, inventory, quality, location, process and capacity, layout, scheduling, maintain ace, and supply chain. This paper presents an architectural configuration conceptual framework of a decagram of sets decisions in a form of mathematical complete graph and abelian graph. Mathematically, a complete graph is undirected (UDG), and directed (DG) a relationship where every pair of vertices is connected, collated, confluent, and holomorphic. There has not been any study conducted which, however, prioritizes the holomorphic sets which of POMS within OR field of study. The study utilizes OR structured technique known as The Analytic Hierarchy Process (AHP) analysis for organizing, sorting and prioritizing(ranking) the sets within the decagram of POMS according to their attribution (propensity), and provides an analysis how the prioritization has real-world application within the 21st century.

Keywords: AHP analysis, Decagram, Decagon, Holomorphic.

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599 Domestic Tourist Behaviours of the Tourism Place in Bangkok and Greater Area

Authors: Tanit P ruktara

Abstract:

This research aims to study the preferable tourism and the elements of choosing tourist destination from domestic tourist in Bangkok and the nearby areas in Thailand.The data were collected by using 1249 set of questionnaires, in mid-August 2012. The result illustrates that religious destinations are the most preferable places for the tourist. The average expense per travel is approximately 47 USD a time. Travellers travel based on the advertisement in the television and internet and their decisions is based on the reputation of the destinations. The result on a place dimension demonstrates the neatness and well managed location play a crucial role on tourist destination. Gender, age, marriage status and their origins are affecting their spending and travelling behaviour. The researcher reckon that providing the area of arcade, selling the souvenir and promoting tourism among a young professional group would be an important key follow the income distribution policy, including managing the destination to welcome the family group, which the result is to identified as the highest spending.

Keywords: Domestic Tourist, Tourism, Tourist Behaviours, Tourism Place.

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