Search results for: Cluster dimension
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 731

Search results for: Cluster dimension

251 An Energy-Efficient Protocol with Static Clustering for Wireless Sensor Networks

Authors: Amir Sepasi Zahmati, Bahman Abolhassani, Ali Asghar Beheshti Shirazi, Ali Shojaee Bakhtiari

Abstract:

A wireless sensor network with a large number of tiny sensor nodes can be used as an effective tool for gathering data in various situations. One of the major issues in wireless sensor networks is developing an energy-efficient routing protocol which has a significant impact on the overall lifetime of the sensor network. In this paper, we propose a novel hierarchical with static clustering routing protocol called Energy-Efficient Protocol with Static Clustering (EEPSC). EEPSC, partitions the network into static clusters, eliminates the overhead of dynamic clustering and utilizes temporary-cluster-heads to distribute the energy load among high-power sensor nodes; thus extends network lifetime. We have conducted simulation-based evaluations to compare the performance of EEPSC against Low-Energy Adaptive Clustering Hierarchy (LEACH). Our experiment results show that EEPSC outperforms LEACH in terms of network lifetime and power consumption minimization.

Keywords: Clustering methods, energy efficiency, routingprotocol, wireless sensor networks.

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250 Cross-Cultural Socio-Economic Status Attainment between Muslim and Santal Couple in Rural Bangladesh

Authors: Md. Emaj Uddin

Abstract:

This study compared socio-economic status attainment between the Muslim and Santal couples in rural Bangladesh. For this we hypothesized that socio-economic status attainment (occupation, education and income) of the Muslim couples was higher than the Santal ones in rural Bangladesh. In order to examine the hypothesis 288 couples (145 couples for Muslim and 143 couples for Santal) selected by cluster random sampling from Kalna village, Bangladesh were individually interviewed with semistructured questionnaire method. The results of Pearson Chi-Squire test suggest that there were significant differences in socio-economic status attainment between the two communities- couples. In addition, Pearson correlation coefficients also suggest that there were significant associations between the socio-economic statuses attained by the two communities- couples in rural Bangladesh. Further crosscultural study should conduct on how inter-community relations in rural social structure of Bangladesh influence the differences among the couples- socio-economic status attainment

Keywords: Bangladesh, Couple, Cross-Cultural Comparison, Muslim, Socio-Economic Status Attainment, Santal.

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249 Genetic Programming Approach for Multi-Category Pattern Classification Appliedto Network Intrusions Detection

Authors: K.M. Faraoun, A. Boukelif

Abstract:

This paper describes a new approach of classification using genetic programming. The proposed technique consists of genetically coevolving a population of non-linear transformations on the input data to be classified, and map them to a new space with a reduced dimension, in order to get a maximum inter-classes discrimination. The classification of new samples is then performed on the transformed data, and so become much easier. Contrary to the existing GP-classification techniques, the proposed one use a dynamic repartition of the transformed data in separated intervals, the efficacy of a given intervals repartition is handled by the fitness criterion, with a maximum classes discrimination. Experiments were first performed using the Fisher-s Iris dataset, and then, the KDD-99 Cup dataset was used to study the intrusion detection and classification problem. Obtained results demonstrate that the proposed genetic approach outperform the existing GP-classification methods [1],[2] and [3], and give a very accepted results compared to other existing techniques proposed in [4],[5],[6],[7] and [8].

Keywords: Genetic programming, patterns classification, intrusion detection

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248 Aging Effect on Mechanical Behavior of Duplex Satinless Steel

Authors: Jungho Moon, Tae Kwon Ha

Abstract:

Effect of alloying on the microstructure and mechanical properties of heat-resisting duplex stainless steel (DSS) for Mg production was investigated in this study. 25Cr-8Ni based DSS’s were cast into rectangular ingots of which the dimension was 350×350×100 mm3 . Nitrogen and Yttrium were added in the range within 0.3 in weight percent. Phase equilibrium was calculated using the FactSage®, thermodynamic software. Hot exposure, high temperature tensile and compression tests were conducted on the ingots at 1230oC, which is operation temperature employed for Mg production by Silico-thermic reduction. The steel with N and Y showed much higher strength than 310S alloy in both tensile and compression tests. By thermal exposition at 1230oC for 200 hrs, hardness of DSS containing N and Y was found to increase. Hot workability of the heat-resisting DSS was evaluated by employing hot rolling at 1230 oC. Hot shortness was observed in the ingot with N and found to disappear after addition of Y.

Keywords: Duplex Stainless Steel, alloying elements, eutectic carbides, microstructure, aging treatment.

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247 Clustering Based Formulation for Short Term Load Forecasting

Authors: Ajay Shekhar Pandey, D. Singh, S. K. Sinha

Abstract:

A clustering based technique has been developed and implemented for Short Term Load Forecasting, in this article. Formulation has been done using Mean Absolute Percentage Error (MAPE) as an objective function. Data Matrix and cluster size are optimization variables. Model designed, uses two temperature variables. This is compared with six input Radial Basis Function Neural Network (RBFNN) and Fuzzy Inference Neural Network (FINN) for the data of the same system, for same time period. The fuzzy inference system has the network structure and the training procedure of a neural network which initially creates a rule base from existing historical load data. It is observed that the proposed clustering based model is giving better forecasting accuracy as compared to the other two methods. Test results also indicate that the RBFNN can forecast future loads with accuracy comparable to that of proposed method, where as the training time required in the case of FINN is much less.

Keywords: Load forecasting, clustering, fuzzy inference.

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246 Modes of Collapse of Compress–Expand Member under Axial Loading

Authors: Shigeyuki Haruyama, Aidil Khaidir Bin Muhamad, Ken Kaminishi, Dai-Heng Chen

Abstract:

In this paper, a study on the modes of collapse of compress- expand members are presented. Compress- expand member is a compact, multiple-combined cylinders, to be proposed as energy absorbers. Previous studies on the compress- expand member have clarified its energy absorption efficiency, proposed an approximate equation to describe its deformation characteristics and also highlighted the improvement that it has brought. However, for the member to be practical, the actual range of geometrical dimension that it can maintain its applicability must be investigated. In this study, using a virtualized materials that comply the bilinear hardening law, Finite element Method (FEM) analysis on the collapse modes of compress- expand member have been conducted. Deformation maps that plotted the member's collapse modes with regards to the member's geometric and material parameters were then presented in order to determine the dimensional range of each collapse modes.

Keywords: Axial collapse, compress-expand member, tubular member, finite element method, modes of collapse, thin-walled cylindrical tube.

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245 Optimization Approaches for a Complex Dairy Farm Simulation Model

Authors: Jagannath Aryal, Don Kulasiri, Dishi Liu

Abstract:

This paper describes the optimization of a complex dairy farm simulation model using two quite different methods of optimization, the Genetic algorithm (GA) and the Lipschitz Branch-and-Bound (LBB) algorithm. These techniques have been used to improve an agricultural system model developed by Dexcel Limited, New Zealand, which describes a detailed representation of pastoral dairying scenarios and contains an 8-dimensional parameter space. The model incorporates the sub-models of pasture growth and animal metabolism, which are themselves complex in many cases. Each evaluation of the objective function, a composite 'Farm Performance Index (FPI)', requires simulation of at least a one-year period of farm operation with a daily time-step, and is therefore computationally expensive. The problem of visualization of the objective function (response surface) in high-dimensional spaces is also considered in the context of the farm optimization problem. Adaptations of the sammon mapping and parallel coordinates visualization are described which help visualize some important properties of the model-s output topography. From this study, it is found that GA requires fewer function evaluations in optimization than the LBB algorithm.

Keywords: Genetic Algorithm, Linux Cluster, LipschitzBranch-and-Bound, Optimization

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244 The Attitudes of Pre-Service Teachers towards Analytical Thinking Skill Development Based On Miller’s Model

Authors: Thassanant Unnanantn, Suttipong Boonphadung

Abstract:

This research study aimed to survey and analyze the attitudes of pre-service teachers’ the analytical thinking development based on Miller’s Model. The informants of this study were 22 third year teacher students majoring in Thai. The course where the instruction was conducted was English for Academic Purposes in Thai Language 2. The instrument of this research was an open-ended questionnaire with two dimensions of questions: academic and satisfaction dimensions. The investigation revealed the positive attitudes. In the academic dimension, the majority of 12 (54.54%), the highest percentage, reflected that the method of teaching analytical thinking and language simultaneously was their new knowledge and the similar percentage also belonged to text cohesion in writing. For the satisfaction, the highest frequency count was from 17 of them (77.27%) and this majority favored the openness or friendliness of the teacher.

Keywords: Analytical thinking development, Attitudes, Miller’s Model, Pre-service teachers.

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243 2D and 3D Unsteady Simulation of the Heat Transfer in the Sample during Heat Treatment by Moving Heat Source

Authors: Z. Veselý, M. Honner, J. Mach

Abstract:

The aim of the performed work is to establish the 2D and 3D model of direct unsteady task of sample heat treatment by moving source employing computer model on the basis of finite element method. Complex boundary condition on heat loaded sample surface is the essential feature of the task. Computer model describes heat treatment of the sample during heat source movement over the sample surface. It is started from 2D task of sample cross section as a basic model. Possibilities of extension from 2D to 3D task are discussed. The effect of the addition of third model dimension on temperature distribution in the sample is showed. Comparison of various model parameters on the sample temperatures is observed. Influence of heat source motion on the depth of material heat treatment is shown for several velocities of the movement. Presented computer model is prepared for the utilization in laser treatment of machine parts.

Keywords: Computer simulation, unsteady model, heat treatment, complex boundary condition, moving heat source.

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242 A Review on Applications of Nanotechnology in Automotive Industry

Authors: Akshata S. Malani, Anagha D. Chaudhari, Rajeshkumar U. Sambhe

Abstract:

Nanotechnology in pristine sense refers to building of structures at atomic and molecular scale. Meticulously nanotechnology encompasses the nanomaterials with at least one dimension size ranging from 1 to 100 nanometres. Unlike the literal meaning of its name, nanotechnology is a massive concept beyond imagination. This paper predominantly deals with relevance of nanotechnology in automotive industries. New generation of automotives looks at nanotechnology as an emerging trend of manufacturing revolution. Intricate shapes can be made out of fairly inexpensive raw materials instead of conventional fabrication process. Though the current era have enough technology to face competition, nanotechnology can give futuristic implications to pick up the modern pace. Nanotechnology intends to bridge the gap between automotives with superior technical performance and their cost fluctuation. Preliminarily, it is an area of great scientific interest and a major shaper of many new technologies. Nanotechnology can be an ideal building block for automotive industries, under constant evolution offering a very wide scope of activity. It possesses huge potential and is still in the embryonic form of research and development.

Keywords: Nanotechnology, nanomaterials, manufacturing, automotive industry.

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241 An Organizational Strategic Analysis for Dynamics of Generating Firms- Alliance Networks

Authors: Takao Sakakura, Kazunori Fujimoto

Abstract:

This paper proposes an analytical method for the dynamics of generating firms- alliance networks along with business phases. Dynamics in network developments have previously been discussed in the research areas of organizational strategy rather than in the areas of regional cluster, where the static properties of the networks are often discussed. The analytical method introduces the concept of business phases into innovation processes and uses relationships called prior experiences; this idea was developed in organizational strategy to investigate the state of networks from the viewpoints of tradeoffs between link stabilization and node exploration. This paper also discusses the results of the analytical method using five cases of the network developments of firms. The idea of Embeddedness helps interpret the backgrounds of the analytical results. The analytical method is useful for policymakers of regional clusters to establish concrete evaluation targets and a viewpoint for comparisons of policy programs.

Keywords: Regional Clusters, Alliance Networks, Innovation Processes, Prior Experiences, Embeddedness.

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240 Manufacturing Dispersions Based Simulation and Synthesis of Design Tolerances

Authors: Nassima Cheikh, Abdelmadjid Cheikh, Said Hamou

Abstract:

The objective of this work which is based on the approach of simultaneous engineering is to contribute to the development of a CIM tool for the synthesis of functional design dimensions expressed by average values and tolerance intervals. In this paper, the dispersions method known as the Δl method which proved reliable in the simulation of manufacturing dimensions is used to develop a methodology for the automation of the simulation. This methodology is constructed around three procedures. The first procedure executes the verification of the functional requirements by automatically extracting the functional dimension chains in the mechanical sub-assembly. Then a second procedure performs an optimization of the dispersions on the basis of unknown variables. The third procedure uses the optimized values of the dispersions to compute the optimized average values and tolerances of the functional dimensions in the chains. A statistical and cost based approach is integrated in the methodology in order to take account of the capabilities of the manufacturing processes and to distribute optimal values among the individual components of the chains.

Keywords: functional tolerances, manufacturing dispersions, simulation, CIM.

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239 Sequential Straightforward Clustering for Local Image Block Matching

Authors: Mohammad Akbarpour Sekeh, Mohd. Aizaini Maarof, Mohd. Foad Rohani, Malihe Motiei

Abstract:

Duplicated region detection is a technical method to expose copy-paste forgeries on digital images. Copy-paste is one of the common types of forgeries to clone portion of an image in order to conceal or duplicate special object. In this type of forgery detection, extracting robust block feature and also high time complexity of matching step are two main open problems. This paper concentrates on computational time and proposes a local block matching algorithm based on block clustering to enhance time complexity. Time complexity of the proposed algorithm is formulated and effects of two parameter, block size and number of cluster, on efficiency of this algorithm are considered. The experimental results and mathematical analysis demonstrate this algorithm is more costeffective than lexicographically algorithms in time complexity issue when the image is complex.

Keywords: Copy-paste forgery detection, Duplicated region, Timecomplexity, Local block matching, Sequential block clustering.

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238 Comparing Abused and Normal Male Students in Tehran Guidance Schools: Emphasizing the Co-Dependency of Their Mothers

Authors: Mohamad Saleh Sangin Ostadi, Esmail Safari, Somayeh Akbari, Kaveh Qaderi Bagajan

Abstract:

The aim of this study is to compare abused and normal male students in Tehran guidance schools with emphasis on the co-dependency of their mothers. The method of this study is based on survey method and comparison (Ex-Post Facto). The method of sampling is also multi-stage cluster. Accordingly, we did sampling from secondary schools of education and training in Tehran, including 12 schools with levels of first, second and third. Each of the schools represents the three – high, medium and low- economic and social conditions. In the following, three classes from every school and 20 students from each class were randomly selected. By (CTQ) abused and normal students were separated that 670 children were recognized as normal and 50 children as abused. Then, 50 children were randomly selected from normal group and compared with abused group. Using Spanned-Fischer Co-dependency Scale, we compared mothers of abused and normal students. The results showed that mothers of the abused children have higher co- dependency average comparing to the mothers of the normal children.

Keywords: Co-dependency, child abuse, abused children, parental psychological health.

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237 Degradation of EE2 by Different Consortium of Enriched Nitrifying Activated Sludge

Authors: Pantip Kayee

Abstract:

17α-ethinylestradiol (EE2) is a recalcitrant micropollutant which is found in small amounts in municipal wastewater. But these small amounts still adversely affect for the reproductive function of aquatic organisms. Evidence in the past suggested that full-scale WWTPs equipped with nitrification process enhanced the removal of EE2 in the municipal wastewater. EE2 has been proven to be able to be transformed by ammonia oxidizing bacteria (AOB) via co-metabolism. This research aims to clarify the EE2 degradation pattern by different consortium of ammonia oxidizing microorganism (AOM) including AOA (ammonia oxidizing archaea) and investigate contribution between the existing ammonia monooxygenase (AMO) and new synthesized AOM. The result showed that AOA or AOB of N. oligotropha cluster in enriched nitrifying activated sludge (NAS) from 2mM and 5mM, commonly found in municipal WWTPs, could degrade EE2 in wastewater via co-metabolism. Moreover, the investigation of the contribution between the existing ammonia monooxygenase (AMO) and new synthesized AOM demonstrated that the new synthesized AMO enzyme may perform ammonia oxidation rather than the existing AMO enzyme or the existing AMO enzyme may has a small amount to oxidize ammonia.

Keywords: 17α-ethinylestradiol, nitrification, ammonia oxidizing bacteria, ammonia oxidizing archaea.

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236 Improvement of Durability of Wood by Maleic Anhydride

Authors: Yong F. Li, Yi X. Liu, Xiang M. Wang, Feng H. Wang

Abstract:

Wood as a natural renewable material is vulnerable to degradation by microorganisms and susceptible to change in dimension by water. In order to effectively improve the durability of wood, an active reagent, maleic anhydride (Man) was selected for wood modification. Man was first dissolved into a solvent, and then penetrated into wood porous structure under a vacuum/pressure condition. After a final catalyst-thermal treatment, wood modification was finished. The test results indicate that acetone is a good solvent for transporting Man into wood matrix. SEM observation proved that wood samples treated by Man kept a good cellular structure, indicating a well penetration of Man into wood cell walls. FTIR analysis suggested that Man reacted with hydroxyl groups on wood cell walls by its ring-ether group, resulting in reduction of amount of hydroxyl groups and resultant good dimensional stability as well as fine decay resistance. Consequently, Man modifying wood to improve its durability is an effective method.

Keywords: Wood, porous structure, durability improvement, maleic anhydride

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235 Human Motion Regeneration in 2-Dimension as Stick Figure Animation with Accelerometers

Authors: Alpha Agape Gopalai, Darwin Gouwanda, S.M.N. Arosha Senanayake

Abstract:

This paper explores the opportunity of using tri-axial wireless accelerometers for supervised monitoring of sports movements. A motion analysis system for the upper extremities of lawn bowlers in particular is developed. Accelerometers are placed on parts of human body such as the chest to represent the shoulder movements, the back to capture the trunk motion, back of the hand, the wrist and one above the elbow, to capture arm movements. These sensors placement are carefully designed in order to avoid restricting bowler-s movements. Data is acquired from these sensors in soft-real time using virtual instrumentation; the acquired data is then conditioned and converted into required parameters for motion regeneration. A user interface was also created to facilitate in the acquisition of data, and broadcasting of commands to the wireless accelerometers. All motion regeneration in this paper deals with the motion of the human body segment in the X and Y direction, looking into the motion of the anterior/ posterior and lateral directions respectively.

Keywords: Motion Regeneration, Virtual Instrumentation, Wireless Accelerometers

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234 DCBOR: A Density Clustering Based on Outlier Removal

Authors: A. M. Fahim, G. Saake, A. M. Salem, F. A. Torkey, M. A. Ramadan

Abstract:

Data clustering is an important data exploration technique with many applications in data mining. We present an enhanced version of the well known single link clustering algorithm. We will refer to this algorithm as DCBOR. The proposed algorithm alleviates the chain effect by removing the outliers from the given dataset. So this algorithm provides outlier detection and data clustering simultaneously. This algorithm does not need to update the distance matrix, since the algorithm depends on merging the most k-nearest objects in one step and the cluster continues grow as long as possible under specified condition. So the algorithm consists of two phases; at the first phase, it removes the outliers from the input dataset. At the second phase, it performs the clustering process. This algorithm discovers clusters of different shapes, sizes, densities and requires only one input parameter; this parameter represents a threshold for outlier points. The value of the input parameter is ranging from 0 to 1. The algorithm supports the user in determining an appropriate value for it. We have tested this algorithm on different datasets contain outlier and connecting clusters by chain of density points, and the algorithm discovers the correct clusters. The results of our experiments demonstrate the effectiveness and the efficiency of DCBOR.

Keywords: Data Clustering, Clustering Algorithms, Handling Noise, Arbitrary Shape of Clusters.

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233 The Fabrication of Scintillator Column by Hydraulic Pressure Injection Method

Authors: C. C. Chen, C. M. Chu, C. J. Wang, C. Y. Chen, K. J. Huang

Abstract:

Cesiumiodide with Na doping (CsI(Na)) solution or melt is easily forming three- dimension dendrites on the free surface. The defects or bobbles form inside the CsI(Na) during the solution or melt solidification. The defects or bobbles can further effect the x-ray path in the CsI(Na) crystal and decrease the scintillation characteristics of CsI(Na). In order to enhance the CsI(Na) scintillated property we made single crystal of CsI(Na) column in the anodic aluminum oxide (AAO) template by hydraulic pressure injection method. It is interesting that when CsI(Na) melt is confined in the small AAO channels, the column grow as stable single column without any dendrites. The high aspect ratio (100~10000) of AAO and nano to sub-micron channel structure which is a suitable template for single of crystal CsI(Na) formation. In this work, a new low-cost approach to fabricate scintillator crystals using anodic aluminum oxide (AAO) rather than Si is reported, which can produce scintillator crystals with a wide range of controllable size to optimize their performance in X-ray detection.

Keywords: Cesiumiodide, AAO, scintillator, crystal, X-ray.

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232 Effectiveness and Usability Evaluation of 'Li2D' Courseware

Authors: Zuraini Hanim Zaini, Wan Fatimah Wan Ahmad

Abstract:

Multimedia courseware has been accepted as a tool that can support teaching and learning process. 'Li2D' courseware was developed to assist student-s visualization on the topic of Loci in Two Dimension. This paper describes an evaluation on the effectiveness and usability of a 'Li2D' courseware. The quasi experiment was used for the effectiveness evaluation. Usability evaluation was accomplished based on four constructs of usability, namely: efficiency, learnability, screen design and satisfaction. An evaluation on the multimedia elements was also conducted. A total of 63 students of Form Two are involved in the study. The students are divided into two groups: control and experimental. The experimental group had to interact with 'Li2D' courseware as part of the learning activities while the control group used the conventional learning methods. The results indicate that the experimental group performed better than the control group in understanding the Loci in Two Dimensions topic. In terms of usability, the results showed that the students agreed on the usability in multimedia elements in the 'Li2D' courseware.

Keywords: Effectiveness, usability and multimedia elements, Loci in Two Dimensions.

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231 Volatility Switching between Two Regimes

Authors: Josip Visković, Josip Arnerić, Ante Rozga

Abstract:

Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most successful and popular models in modeling time varying volatility are GARCH type models. When financial returns exhibit sudden jumps that are due to structural breaks, standard GARCH models show high volatility persistence, i.e. integrated behavior of the conditional variance. In such situations models in which the parameters are allowed to change over time are more appropriate. This paper compares different GARCH models in terms of their ability to describe structural changes in returns caused by financial crisis at stock markets of six selected central and east European countries. The empirical analysis demonstrates that Markov regime switching GARCH model resolves the problem of excessive persistence and outperforms uni-regime GARCH models in forecasting volatility when sudden switching occurs in response to financial crisis.

Keywords: Central and east European countries, financial crisis, Markov switching GARCH model, transition probabilities.

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230 A 15 Minute-Based Approach for Berth Allocation and Quay Crane Assignment

Authors: Hoi-Lam Ma, Sai-Ho Chung

Abstract:

In traditional integrated berth allocation with quay crane assignment models, time dimension is usually assumed in hourly based. However, nowadays, transshipment becomes the main business to many container terminals, especially in Southeast Asia (e.g. Hong Kong and Singapore). In these terminals, vessel arrivals are usually very frequent with small handling volume and very short staying time. Therefore, the traditional hourly-based modeling approach may cause significant berth and quay crane idling, and consequently cannot meet their practical needs. In this connection, a 15-minute-based modeling approach is requested by industrial practitioners. Accordingly, a Three-level Genetic Algorithm (3LGA) with Quay Crane (QC) shifting heuristics is designed to fulfill the research gap. The objective function here is to minimize the total service time. Preliminary numerical results show that the proposed 15-minute-based approach can reduce the berth and QC idling significantly.

Keywords: Transshipment, integrated berth allocation, variable-in-time quay crane assignment, quay crane assignment.

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229 Ontology-based Concept Weighting for Text Documents

Authors: Hmway Hmway Tar, Thi Thi Soe Nyaunt

Abstract:

Documents clustering become an essential technology with the popularity of the Internet. That also means that fast and high-quality document clustering technique play core topics. Text clustering or shortly clustering is about discovering semantically related groups in an unstructured collection of documents. Clustering has been very popular for a long time because it provides unique ways of digesting and generalizing large amounts of information. One of the issues of clustering is to extract proper feature (concept) of a problem domain. The existing clustering technology mainly focuses on term weight calculation. To achieve more accurate document clustering, more informative features including concept weight are important. Feature Selection is important for clustering process because some of the irrelevant or redundant feature may misguide the clustering results. To counteract this issue, the proposed system presents the concept weight for text clustering system developed based on a k-means algorithm in accordance with the principles of ontology so that the important of words of a cluster can be identified by the weight values. To a certain extent, it has resolved the semantic problem in specific areas.

Keywords: Clustering, Concept Weight, Document clustering, Feature Selection, Ontology

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228 On-Line Impulse Buying and Cognitive Dissonance: The Moderating Role of the Positive Affective State

Authors: G. Mattia, A. Di Leo, L. Principato

Abstract:

The purchase impulsiveness is preceded by a lack of self-control: consequently, it is legitimate to believe that a consumer with a low level of self-control can result in a higher probability of cognitive dissonance. Moreover, the process of purchase is influenced by the pre-existing affective state in a considerable way. With reference to on-line purchases, digital behavior cannot be merely ascribed to the rational sphere, given the speed and ease of transactions and the hedonistic dimension of purchases. To our knowledge, this research is among the first cases of verification of the effect of moderation exerted by the positive affective state in the on-line impulse purchase of products with a high expressive value such as a smartphone on the occurrence of cognitive dissonance. To this aim, a moderation analysis was conducted on a sample of 212 impulsive millennials buyers. Three scales were adopted to measure the constructs of interest: IBTS for impulsivity, PANAS for the affective state, Sweeney for cognitive dissonance. The analysis revealed that positive affective state does not affect the onset of cognitive dissonance.

Keywords: Cognitive dissonance, impulsive buying, online shopping, online consumer behavior.

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227 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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226 Estimation of Functional Response Model by Supervised Functional Principal Component Analysis

Authors: Hyon I. Paek, Sang Rim Kim, Hyon A. Ryu

Abstract:

In functional linear regression, one typical problem is to reduce dimension. Compared with multivariate linear regression, functional linear regression is regarded as an infinite-dimensional case, and the main task is to reduce dimensions of functional response and functional predictors. One common approach is to adapt functional principal component analysis (FPCA) on functional predictors and then use a few leading functional principal components (FPC) to predict the functional model. The leading FPCs estimated by the typical FPCA explain a major variation of the functional predictor, but these leading FPCs may not be mostly correlated with the functional response, so they may not be significant in the prediction for response. In this paper, we propose a supervised FPCA method for a functional response model with FPCs obtained by considering the correlation of the functional response. Our method would have a better prediction accuracy than the typical FPCA method.

Keywords: Supervised, functional principal component analysis, functional response, functional linear regression.

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225 A Fuzzy Approach to Liver Tumor Segmentation with Zernike Moments

Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire

Abstract:

In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy CMeans methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc.).

Keywords: Defuzzification, floating search, fuzzy clustering, Zernike moments.

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224 A Hybrid Scheme for on-Line Diagnostic Decision Making Using Optimal Data Representation and Filtering Technique

Authors: Hyun-Woo Cho

Abstract:

The early diagnostic decision making in industrial processes is absolutely necessary to produce high quality final products. It helps to provide early warning for a special event in a process, and finding its assignable cause can be obtained. This work presents a hybrid diagnostic schmes for batch processes. Nonlinear representation of raw process data is combined with classification tree techniques. The nonlinear kernel-based dimension reduction is executed for nonlinear classification decision boundaries for fault classes. In order to enhance diagnosis performance for batch processes, filtering of the data is performed to get rid of the irrelevant information of the process data. For the diagnosis performance of several representation, filtering, and future observation estimation methods, four diagnostic schemes are evaluated. In this work, the performance of the presented diagnosis schemes is demonstrated using batch process data.

Keywords: Diagnostics, batch process, nonlinear representation, data filtering, multivariate statistical approach

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223 k-Neighborhood Template A-Type Three-Dimensional Bounded Cellular Acceptor

Authors: Makoto Nagatomo, Yasuo Uchida, Makoto Sakamoto, Tuo Zhang, Tatsuma Kurogi, Takao Ito, Tsunehiro Yoshinaga, Satoshi Ikeda, Masahiro Yokomichi, Hiroshi Furutani

Abstract:

This paper presents a four-dimensional computational model, k-neighborhood template A-type three-dimensional bounded cellular acceptor (abbreviated as A-3BCA(k)), and discusses the hierarchical properties. An A-3BCA(k) is a four-dimensional automaton which consists of a pair of a converter and a configuration-reader. The former converts the given four-dimensional tape to the three- and two- dimensional configuration and the latter determines the acceptance or nonacceptance of given four-dimensional tape whether or not the derived two-dimensional configuration is accepted. We mainly investigate the difference of the accepting power based on the difference of the configuration-reader. It is shown that the difference of the accepting power of the configuration-reader tends to affect directly that of the A-3BCA(k) for the case when the converter is deterministic. On the other hand, results are not analogous for the nondeterministic case.

Keywords: Cellular acceptor, configuration-reader, converter, finite automaton, four-dimension, on-line tessellation acceptor, parallel/sequential array acceptor, turing machine.

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222 Cooperative Sensing for Wireless Sensor Networks

Authors: Julien Romieux, Fabio Verdicchio

Abstract:

Wireless Sensor Networks (WSNs), which sense environmental data with battery-powered nodes, require multi-hop communication. This power-demanding task adds an extra workload that is unfairly distributed across the network. As a result, nodes run out of battery at different times: this requires an impractical individual node maintenance scheme. Therefore we investigate a new Cooperative Sensing approach that extends the WSN operational life and allows a more practical network maintenance scheme (where all nodes deplete their batteries almost at the same time). We propose a novel cooperative algorithm that derives a piecewise representation of the sensed signal while controlling approximation accuracy. Simulations show that our algorithm increases WSN operational life and spreads communication workload evenly. Results convey a counterintuitive conclusion: distributing workload fairly amongst nodes may not decrease the network power consumption and yet extend the WSN operational life. This is achieved as our cooperative approach decreases the workload of the most burdened cluster in the network.

Keywords: Cooperative signal processing, power management, signal representation, signal approximation, wireless sensor networks.

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