Search results for: hierarchical segmentation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 533

Search results for: hierarchical segmentation

173 NSBS: Design of a Network Storage Backup System

Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan

Abstract:

The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and the snapshot and hierarchical index are used in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.

Keywords: Agent, network backup system, three architecture model, NSBS.

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172 Teaching Approach and Self-Confidence Effect Model Consistency between Taiwan and Singapore Multi-Group HLM

Authors: PeiWen Liao, Tsung Hau Jen

Abstract:

This study was conducted to explore the effects of two countries model comparison program in Taiwan and Singapore in TIMSS database. The researchers used Multi-Group Hierarchical Linear Modeling techniques to compare the effects of two different country models and we tested our hypotheses on 4,046 Taiwan students and 4,599 Singapore students in 2007 at two levels: the class level and student (individual) level. Design quality is a class level variable. Student level variables are achievement and self-confidence. The results challenge the widely held view that retention has a positive impact on self-confidence. Suggestions for future research are discussed.

Keywords: Teaching approach, self-confidence, achievement, multi-group HLM.

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171 A Study of the Influence of College Students’ Exercise and Leisure Motivations on the Leisure Benefits – Using Leisure Involvement as a Moderator

Authors: Chiung-En Huang, Cheng-Yu Tsai, Shane-Chung Lee

Abstract:

This study aim at the influence of college students’ exercise and leisure motivations on the leisure benefits while using the leisure involvement as a moderator. Whereby, the research tools used in this study included the application of leisure motivation scale, leisure involvement scale and leisure benefits scale, and a hierarchical regression analysis was performed by using a questionnaire-based survey, in which, a total of 1,500 copies of questionnaires were administered and 917 valid questionnaires were obtained, achieving a response rate of 61.13%. Research findings explore that leisure involvement has a moderating effect on the relationship between the leisure motivation and leisure benefits.

Keywords: Leisure motivation, leisure involvement, leisure benefits, moderator.

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170 An HCI Template for Distributed Applications

Authors: Xizhi Li

Abstract:

Both software applications and their development environment are becoming more and more distributed. This trend impacts not only the way software computes, but also how it looks. This article proposes a Human Computer Interface (HCI) template from three representative applications we have developed. These applications include a Multi-Agent System based software, a 3D Internet computer game with distributed game world logic, and a programming language environment used in constructing distributed neural network and its visualizations. HCI concepts that are common to these applications are described in abstract terms in the template. These include off-line presentation of global entities, entities inside a hierarchical namespace, communication and languages, reconfiguration of entity references in a graph, impersonation and access right, etc. We believe the metaphor that underlies an HCI concept as well as the relationships between a bunch of HCI concepts are crucial to the design of software systems and vice versa.

Keywords: HCI, MAS, computer game, programming language

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169 RAPD Analysis of the Genetic Polymorphism in the Collection of Rye Cultivars

Authors: L. Petrovičová, Ž. Balážová, Z. Gálová, M. Wójcik-Jagła, M. Rapacz

Abstract:

In the present study, RAPD-PCR was used to assess genetic diversity of the rye including landrances and new rye cultivars coming from Central Europe and the Union of Soviet Socialist Republics (SUN). Five arbitrary random primers were used to determine RAPD polymorphism in the set of 38 rye genotypes. These primers amplified altogether 43 different DNA fragments with an average number of 8.6 fragments per genotypes. The number of fragments ranged from 7 (RLZ 8, RLZ 9 and RLZ 10) to 12 (RLZ 6). DI and PIC values of all RAPD markers were higher than 0.8 that generally means high level of polymorphism detected between rye genotypes. The dendrogram based on hierarchical cluster analysis using UPGMA algorithm was prepared. The cultivars were grouped into two main clusters. In this experiment, RAPD proved to be a rapid, reliable and practicable method for revealing of polymorphism in the rye cultivars.

Keywords: Genetic diversity, polymorphism, RAPD markers, Secalecereale L.

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168 Discovering the Dimension of Abstractness: Structure-Based Model that Learns New Categories and Categorizes on Different Levels of Abstraction

Authors: Georgi I. Petkov, Ivan I. Vankov, Yolina A. Petrova

Abstract:

A structure-based model of category learning and categorization at different levels of abstraction is presented. The model compares different structures and expresses their similarity implicitly in the forms of mappings. Based on this similarity, the model can categorize different targets either as members of categories that it already has or creates new categories. The model is novel using two threshold parameters to evaluate the structural correspondence. If the similarity between two structures exceeds the higher threshold, a new sub-ordinate category is created. Vice versa, if the similarity does not exceed the higher threshold but does the lower one, the model creates a new category on higher level of abstraction.

Keywords: Analogy-making, categorization, learning of categories, abstraction, hierarchical structure.

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167 Increasing Performance of Autopilot Guided Small Unmanned Helicopter

Authors: Tugrul Oktay, Mehmet Konar, Mustafa Soylak, Firat Sal, Murat Onay, Orhan Kizilkaya

Abstract:

In this paper, autonomous performance of a small manufactured unmanned helicopter is tried to be increased. For this purpose, a small unmanned helicopter is manufactured in Erciyes University, Faculty of Aeronautics and Astronautics. It is called as ZANKA-Heli-I. For performance maximization, autopilot parameters are determined via minimizing a cost function consisting of flight performance parameters such as settling time, rise time, overshoot during trajectory tracking. For this purpose, a stochastic optimization method named as simultaneous perturbation stochastic approximation is benefited. Using this approach, considerable autonomous performance increase (around %23) is obtained.

Keywords: Small helicopters, hierarchical control, stochastic optimization, autonomous performance maximization, autopilots.

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166 Energy Efficient Data Aggregation in Sensor Networks with Optimized Cluster Head Selection

Authors: D. Naga Ravi Kiran, C. G. Dethe

Abstract:

Wireless Sensor Network (WSN) routing is complex due to its dynamic nature, computational overhead, limited battery life, non-conventional addressing scheme, self-organization, and sensor nodes limited transmission range. An energy efficient routing protocol is a major concern in WSN. LEACH is a hierarchical WSN routing protocol to increase network life. It performs self-organizing and re-clustering functions for each round. This study proposes a better sensor networks cluster head selection for efficient data aggregation. The algorithm is based on Tabu search.

Keywords: Wireless Sensor Network (WSN), LEACH, Clustering, Tabu Search.

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165 Size-Reduction Strategies for Iris Codes

Authors: Jutta Hämmerle-Uhl, Georg Penn, Gerhard Pötzelsberger, Andreas Uhl

Abstract:

Iris codes contain bits with different entropy. This work investigates different strategies to reduce the size of iris code templates with the aim of reducing storage requirements and computational demand in the matching process. Besides simple subsampling schemes, also a binary multi-resolution representation as used in the JBIG hierarchical coding mode is assessed. We find that iris code template size can be reduced significantly while maintaining recognition accuracy. Besides, we propose a two-stage identification approach, using small-sized iris code templates in a pre-selection stage, and full resolution templates for final identification, which shows promising recognition behaviour.

Keywords: Iris recognition, compact iris code, fast matching, best bits, pre-selection identification, two-stage identification.

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164 A Survey of Access Control Schemes in Wireless Sensor Networks

Authors: Youssou Faye, Ibrahima Niang, Thomas Noel

Abstract:

Access control is a critical security service in Wire- less Sensor Networks (WSNs). To prevent malicious nodes from joining the sensor network, access control is required. On one hand, WSN must be able to authorize and grant users the right to access to the network. On the other hand, WSN must organize data collected by sensors in such a way that an unauthorized entity (the adversary) cannot make arbitrary queries. This restricts the network access only to eligible users and sensor nodes, while queries from outsiders will not be answered or forwarded by nodes. In this paper we presentee different access control schemes so as to ?nd out their objectives, provision, communication complexity, limits, etc. Using the node density parameter, we also provide a comparison of these proposed access control algorithms based on the network topology which can be flat or hierarchical.

Keywords: Access Control, Authentication, Key Management, Wireless Sensor Networks.

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163 A Hybrid P2P Storage Scheme Based on Erasure Coding and Replication

Authors: Usman Mahmood, Khawaja M. U. Suleman

Abstract:

A peer-to-peer storage system has challenges like; peer availability, data protection, churn rate. To address these challenges different redundancy, replacement and repair schemes are used. This paper presents a hybrid scheme of redundancy using replication and erasure coding. We calculate and compare the storage, access, and maintenance costs of our proposed scheme with existing redundancy schemes. For realistic behaviour of peers a trace of live peer-to-peer system is used. The effect of different replication, and repair schemes are also shown. The proposed hybrid scheme performs better than existing double coding hybrid scheme in all metrics and have an improved maintenance cost than hierarchical codes.

Keywords: Erasure Coding, P2P, Redundancy, Replication.

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162 Key Frames Extraction for Sign Language Video Analysis and Recognition

Authors: Jaroslav Polec, Petra Heribanová, Tomáš Hirner

Abstract:

In this paper we proposed a method for finding video frames representing one sign in the finger alphabet. The method is based on determining hands location, segmentation and the use of standard video quality evaluation metrics. Metric calculation is performed only in regions of interest. Sliding mechanism for finding local extrema and adaptive threshold based on local averaging is used for key frames selection. The success rate is evaluated by recall, precision and F1 measure. The method effectiveness is compared with metrics applied to all frames. Proposed method is fast, effective and relatively easy to realize by simple input video preprocessing and subsequent use of tools designed for video quality measuring.

Keywords: Key frame, video, quality, metric, MSE, MSAD, SSIM, VQM, sign language, finger alphabet.

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161 Experimental teaching, Perceived usefulness, Ease of use, Learning Interest and Science Achievement of Taiwan 8th Graders in TIMSS 2007 Database

Authors: Pei Wen Liao, Tsung Hau Jen

Abstract:

the data of Taiwanese 8th grader in the 4th cycle of Trends in International Mathematics and Science Study (TIMSS) are analyzed to examine the influence of the science teachers- preference in experimental teaching on the relationships between the affective variables ( the perceived usefulness of science, ease of using science and science learning interest) and the academic achievement in science. After dealing with the missing data, 3711 students and 145 science teacher-s data were analyzed through a Hierarchical Linear Modeling technique. The major objective of this study was to determine the role of the experimental teaching moderates the relationship between perceived usefulness and achievement.

Keywords: TIMSS database, Science achievement, Experimental teaching, Perceived Usefulness, Perceived Ease of Use

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160 Improved BEENISH Protocol for Wireless Sensor Networks Based Upon Fuzzy Inference System

Authors: Rishabh Sharma, Renu Vig, Neeraj Sharma

Abstract:

The main design parameter of WSN (wireless sensor network) is the energy consumption. To compensate this parameter, hierarchical clustering is a technique that assists in extending duration of the networks life by efficiently consuming the energy. This paper focuses on dealing with the WSNs and the FIS (fuzzy interface system) which are deployed to enhance the BEENISH protocol. The node energy, mobility, pause time and density are considered for the selection of CH (cluster head). The simulation outcomes exhibited that the projected system outperforms the traditional system with regard to the energy utilization and number of packets transmitted to sink.

Keywords: Wireless sensor network, sink, sensor node, routing protocol, fuzzy rule, fuzzy inference system.

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159 Hybrid Modeling Algorithm for Continuous Tamil Speech Recognition

Authors: M. Kalamani, S. Valarmathy, M. Krishnamoorthi

Abstract:

In this paper, Fuzzy C-Means clustering with Expectation Maximization-Gaussian Mixture Model based hybrid modeling algorithm is proposed for Continuous Tamil Speech Recognition. The speech sentences from various speakers are used for training and testing phase and objective measures are between the proposed and existing Continuous Speech Recognition algorithms. From the simulated results, it is observed that the proposed algorithm improves the recognition accuracy and F-measure up to 3% as compared to that of the existing algorithms for the speech signal from various speakers. In addition, it reduces the Word Error Rate, Error Rate and Error up to 4% as compared to that of the existing algorithms. In all aspects, the proposed hybrid modeling for Tamil speech recognition provides the significant improvements for speechto- text conversion in various applications.

Keywords: Speech Segmentation, Feature Extraction, Clustering, HMM, EM-GMM, CSR.

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158 Simulation Data Summarization Based on Spatial Histograms

Authors: Jing Zhao, Yoshiharu Ishikawa, Chuan Xiao, Kento Sugiura

Abstract:

In order to analyze large-scale scientific data, research on data exploration and visualization has gained popularity. In this paper, we focus on the exploration and visualization of scientific simulation data, and define a spatial V-Optimal histogram for data summarization. We propose histogram construction algorithms based on a general binary hierarchical partitioning as well as a more specific one, the l-grid partitioning. For effective data summarization and efficient data visualization in scientific data analysis, we propose an optimal algorithm as well as a heuristic algorithm for histogram construction. To verify the effectiveness and efficiency of the proposed methods, we conduct experiments on the massive evacuation simulation data.

Keywords: Simulation data, data summarization, spatial histograms, exploration and visualization.

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157 An Ontology Model for Systems Engineering Derived from ISO/IEC/IEEE 15288: 2015: Systems and Software Engineering - System Life Cycle Processes

Authors: Lan Yang, Kathryn Cormican, Ming Yu

Abstract:

ISO/IEC/IEEE 15288: 2015, Systems and Software Engineering - System Life Cycle Processes is an international standard that provides generic top-level process descriptions to support systems engineering (SE). However, the processes defined in the standard needs improvement to lift integrity and consistency. The goal of this research is to explore the way by building an ontology model for the SE standard to manage the knowledge of SE. The ontology model gives a whole picture of the SE knowledge domain by building connections between SE concepts. Moreover, it creates a hierarchical classification of the concepts to fulfil different requirements of displaying and analysing SE knowledge.

Keywords: Knowledge management, model-based systems engineering, ontology modelling, systems engineering ontology.

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156 Multi-threshold Approach for License Plate Recognition System

Authors: Siti Norul Huda Sheikh Abdullah, Farshid Pirahan Siah, Nor Hanisah Haji Zainal Abidin, Shahnorbanun Sahran

Abstract:

The objective of this paper is to propose an adaptive multi threshold for image segmentation precisely in object detection. Due to the different types of license plates being used, the requirement of an automatic LPR is rather different for each country. The proposed technique is applied on Malaysian LPR application. It is based on Multi Layer Perceptron trained by back propagation. The proposed adaptive threshold is introduced to find the optimum threshold values. The technique relies on the peak value from the graph of the number object versus specific range of threshold values. The proposed approach has improved the overall performance compared to current optimal threshold techniques. Further improvement on this method is in progress to accommodate real time system specification.

Keywords: Multi-threshold approach, license plate recognition system.

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155 An Improved Fast Search Method Using Histogram Features for DNA Sequence Database

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

Abstract:

In this paper, we propose an efficient hierarchical DNA sequence search method to improve the search speed while the accuracy is being kept constant. For a given query DNA sequence, firstly, a fast local search method using histogram features is used as a filtering mechanism before scanning the sequences in the database. An overlapping processing is newly added to improve the robustness of the algorithm. A large number of DNA sequences with low similarity will be excluded for latter searching. The Smith-Waterman algorithm is then applied to each remainder sequences. Experimental results using GenBank sequence data show the proposed method combining histogram information and Smith-Waterman algorithm is more efficient for DNA sequence search.

Keywords: Fast search, DNA sequence, Histogram feature, Smith-Waterman algorithm, Local search

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154 White Blood Cells Identification and Counting from Microscopic Blood Image

Authors: Lorenzo Putzu, Cecilia Di Ruberto

Abstract:

The counting and analysis of blood cells allows the evaluation and diagnosis of a vast number of diseases. In particular, the analysis of white blood cells (WBCs) is a topic of great interest to hematologists. Nowadays the morphological analysis of blood cells is performed manually by skilled operators. This involves numerous drawbacks, such as slowness of the analysis and a nonstandard accuracy, dependent on the operator skills. In literature there are only few examples of automated systems in order to analyze the white blood cells, most of which only partial. This paper presents a complete and fully automatic method for white blood cells identification from microscopic images. The proposed method firstly individuates white blood cells from which, subsequently, nucleus and cytoplasm are extracted. The whole work has been developed using MATLAB environment, in particular the Image Processing Toolbox.

Keywords: Automatic detection, Biomedical image processing, Segmentation, White blood cell analysis.

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153 Paranoid Thoughts and Thought Control Strategies in a Nonclinical Population

Authors: Takashi Yamauchi, Anju Sudo, Yoshihiko Tanno

Abstract:

Recently, it has been suggested that thought control strategies aimed at controlling unwanted thoughts may be used to cope with paranoid thoughts in both clinical and nonclinical samples. The current study aims to examine the type of thought control strategies that were associated with the frequency of paranoid thoughts in nonclinical samples. A total of 159 Japanese undergraduate students completed the two scales–the Paranoia Checklist and the Thought Control Questionnaire. A hierarchical multiple regression analysis demonstrated that worry-based control strategies were associated with paranoid thoughts, whereas distraction- and social-based control strategies were inversely associated with paranoid thoughts. Our findings suggest that in a nonclinical population, worry-based strategies may be especially maladaptive, whereas distraction- and social-based strategies may be adaptive to paranoid thoughts.

Keywords: Nonclinical population, paranoid thoughts, thoughtcontrol strategies.

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152 Using Spectral Vectors and M-Tree for Graph Clustering and Searching in Graph Databases of Protein Structures

Authors: Do Phuc, Nguyen Thi Kim Phung

Abstract:

In this paper, we represent protein structure by using graph. A protein structure database will become a graph database. Each graph is represented by a spectral vector. We use Jacobi rotation algorithm to calculate the eigenvalues of the normalized Laplacian representation of adjacency matrix of graph. To measure the similarity between two graphs, we calculate the Euclidean distance between two graph spectral vectors. To cluster the graphs, we use M-tree with the Euclidean distance to cluster spectral vectors. Besides, M-tree can be used for graph searching in graph database. Our proposal method was tested with graph database of 100 graphs representing 100 protein structures downloaded from Protein Data Bank (PDB) and we compare the result with the SCOP hierarchical structure.

Keywords: Eigenvalues, m-tree, graph database, protein structure, spectra graph theory.

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151 Probabilistic Center Voting Method for Subsequent Object Tracking and Segmentation

Authors: Suryanto, Hyo-Kak Kim, Sang-Hee Park, Dae-Hwan Kim, Sung-Jea Ko

Abstract:

In this paper, we introduce a novel algorithm for object tracking in video sequence. In order to represent the object to be tracked, we propose a spatial color histogram model which encodes both the color distribution and spatial information. The object tracking from frame to frame is accomplished via center voting and back projection method. The center voting method has every pixel in the new frame to cast a vote on whereabouts the object center is. The back projection method segments the object from the background. The segmented foreground provides information on object size and orientation, omitting the need to estimate them separately. We do not put any assumption on camera motion; the proposed algorithm works equally well for object tracking in both static and moving camera videos.

Keywords: center voting, back projection, object tracking, size adaptation, non-stationary camera tracking.

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150 A Hybrid GMM/SVM System for Text Independent Speaker Identification

Authors: Rafik Djemili, Mouldi Bedda, Hocine Bourouba

Abstract:

This paper proposes a novel approach that combines statistical models and support vector machines. A hybrid scheme which appropriately incorporates the advantages of both the generative and discriminant model paradigms is described and evaluated. Support vector machines (SVMs) are trained to divide the whole speakers' space into small subsets of speakers within a hierarchical tree structure. During testing a speech token is assigned to its corresponding group and evaluation using gaussian mixture models (GMMs) is then processed. Experimental results show that the proposed method can significantly improve the performance of text independent speaker identification task. We report improvements of up to 50% reduction in identification error rate compared to the baseline statistical model.

Keywords: Speaker identification, Gaussian mixture model (GMM), support vector machine (SVM), hybrid GMM/SVM.

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149 En-Face Optical Coherence Tomography and Fluorescence in Evaluation of Orthodontic Interfaces

Authors: R. O. Rominu, C. Sinescu, D.M. Pop, M. Hughes, A. Bradu, M. Rominu, A. Gh. Podoleanu

Abstract:

Bonding has become a routine procedure in several dental specialties – from prosthodontics to conservative dentistry and even orthodontics. In many of these fields it is important to be able to investigate the bonded interfaces to assess their quality. All currently employed investigative methods are invasive, meaning that samples are destroyed in the testing procedure and cannot be used again. We have investigated the interface between human enamel and bonded ceramic brackets non-invasively, introducing a combination of new investigative methods – optical coherence tomography (OCT), fluorescence OCT and confocal microscopy (CM). Brackets were conventionally bonded on conditioned buccal surfaces of teeth. The bonding was assessed using these methods. Three dimensional reconstructions of the detected material defects were developed using manual and semi-automatic segmentation. The results clearly prove that OCT, fluorescence OCT and CM are useful in orthodontic bonding investigations.

Keywords: Optical coherence tomography, Confocal Microscopy, Orthodontic Bonding.

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148 Comparison of Fricative Vocal Tract Transfer Functions Derived using Two Different Segmentation Techniques

Authors: K. S. Subari, C. H. Shadle, A. Barney, R. I. Damper

Abstract:

The acoustic and articulatory properties of fricative speech sounds are being studied using magnetic resonance imaging (MRI) and acoustic recordings from a single subject. Area functions were derived from a complete set of axial and coronal MR slices using two different methods: the Mermelstein technique and the Blum transform. Area functions derived from the two techniques were shown to differ significantly in some cases. Such differences will lead to different acoustic predictions and it is important to know which is the more accurate. The vocal tract acoustic transfer function (VTTF) was derived from these area functions for each fricative and compared with measured speech signals for the same fricative and same subject. The VTTFs for /f/ in two vowel contexts and the corresponding acoustic spectra are derived here; the Blum transform appears to show a better match between prediction and measurement than the Mermelstein technique.

Keywords: Area functions, fricatives, vocal tract transferfunction, MRI, speech.

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147 A Study on the Design Elements of Sidewalk in Urban Commercial District

Authors: Ji Hyun Kang, Hwan Su Seo, Hong-Kyu Kim, Hong Sok Kim

Abstract:

This study was to search for the desirable direction of the sidewalk planning in Korea by establishing the concepts of walking and pedestrian space, and analyzing the advanced precedents in and out of country. Also, based on the precedent studies and relevant laws, regulations, and systems, it aimed for the following sequential process: firstly, to derive design elements from the functions and characteristics of sidewalk and cluster the similar elements by each characteristics, sampling representative characteristics and making them hierarchical; then, to analyze their significances via the first questionnaire survey, and the relative weights and priorities of each elements via the Analytic Hierarchy Process(AHP); finally, based on the analysis result, to establish the frame of suggesting the direction of policy to improve the pedestrian environment of sidewalk in urban commercial district for the future planning and design of pedestrian space.

Keywords: Sidewalk, Pedestrian, AHP, Indicator.

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146 Parameter Estimation for Viewing Rank Distribution of Video-on-Demand

Authors: Hyoup-Sang Yoon

Abstract:

Video-on-demand (VOD) is designed by using content delivery networks (CDN) to minimize the overall operational cost and to maximize scalability. Estimation of the viewing pattern (i.e., the relationship between the number of viewings and the ranking of VOD contents) plays an important role in minimizing the total operational cost and maximizing the performance of the VOD systems. In this paper, we have analyzed a large body of commercial VOD viewing data and found that the viewing rank distribution fits well with the parabolic fractal distribution. The weighted linear model fitting function is used to estimate the parameters (coefficients) of the parabolic fractal distribution. This paper presents an analytical basis for designing an optimal hierarchical VOD contents distribution system in terms of its cost and performance.

Keywords: VOD, CDN, parabolic fractal distribution, viewing rank, weighted linear model fitting

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145 Adoption and Diffusion of E-Government Services in India: The Impact of User Demographics and Service Quality

Authors: Sayantan Khanra, Rojers P. Joseph

Abstract:

This study attempts to analyze the impact of demography and service quality on the adoption and diffusion of e-Government services in the context of India. The objective of this paper is to study the users' perception about e-Government services and investigate the key variables that are most salient to the Indian populace. At the completion of this study, a research model that would help to understand the relationship involving the demographic variables and service quality dimensions, and the willingness to adopt e-Government services is expected to be developed. Dedicated authorities, particularly those in developing economies, may use that model or its augmented versions to design and update e-Government services and promote their use among citizens. After all, enhanced public participation is required to improve efficiency, engagement and transparency in the implementation of the aforementioned services.

Keywords: Adoption and diffusion of e-Government services, demographic variables, hierarchical regression analysis, service quality dimensions.

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144 Anticipating Action Decisions of Automated Guided Vehicle in an Autonomous Decentralized Flexible Manufacturing System

Authors: Rizauddin Ramli, Jaber Abu Qudeiri, Hidehiko Yamamoto

Abstract:

Nowadays the market for industrial companies is becoming more and more globalized and highly competitive, forcing them to shorten the duration of the manufacturing system development time in order to reduce the time to market. In order to achieve this target, the hierarchical systems used in previous manufacturing systems are not enough because they cannot deal effectively with unexpected situations. To achieve flexibility in manufacturing systems, the concept of an Autonomous Decentralized Flexible Manufacturing System (AD-FMS) is useful. In this paper, we introduce a hypothetical reasoning based algorithm called the Algorithm for Future Anticipative Reasoning (AFAR) which is able to decide on a conceivable next action of an Automated Guided Vehicle (AGV) that works autonomously in the AD-FMS.

Keywords: Flexible Manufacturing System, Automated GuidedVehicle, Hypothetical Reasoning, Autonomous Decentralized.

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