Search results for: Information security management
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6576

Search results for: Information security management

516 Initiative Strategies on How to Increasing Value Add of the Recycling Business

Authors: Yananda Siraphatthada

Abstract:

The current study was the succession of a previous study on value added of recycling business management. Its aims are to 1) explore conditions on how to increasing value add of Thai recycling business, and 2) exam the implementation of the 3-staged plan (short, medium, and long term), suggested by the former study, to increase value added of the recycling business as immediate mechanisms to accelerate government operation. Quantitative and qualitative methods were utilized in this research. A qualitative research consisted of in-depth interviews and focus group discussions. Responses were obtained from owners of the waste separation plants, and recycle shops, as well as officers in relevant governmental agencies. They were randomly selected via Quota Sampling. Data was analyzed via content analysis. The sample used for quantitative method consisted of 1,274 licensed recycling operators in eight provinces. The operators were randomly stratified via sampling method. Data were analyzed via descriptive statistics frequency, percentage, average (Mean) and standard deviation.The study recommended three-staged plan: short, medium, and long terms. The plan included the development of logistics, the provision of quality market/plants, the amendment of recycling rules/regulation, the restructuring recycling business, the establishment of green-purchasing recycling center, support for the campaigns run by the International Green Purchasing Network (IGPN), conferences/workshops as a public forum to share insights among experts/concern people.

Keywords: Strategies, Value Added, Recycle Business.

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515 Improvement of Stator Slot Structure based on Electro-Thermal Analysis in HV Generator

Authors: Diako Azizi, Ahmad Gholami, Vahid Abbasi

Abstract:

High voltage generators are being subject to higher voltage rating and are being designed to operate in harsh conditions. Stator windings are the main component of generators in which Electrical, magnetically and thermal stresses remain major failures for insulation degradation accelerated aging. A large number of generators failed due to stator winding problems, mainly insulation deterioration. Insulation degradation assessment plays vital role in the asset life management. Mostly the stator failure is catastrophic causing significant damage to the plant. Other than generation loss, stator failure involves heavy repair or replacement cost. Electro thermal analysis is the main characteristic for improvement design of stator slot-s insulation. Dielectric parameters such as insulation thickness, spacing, material types, geometry of winding and slot are major design consideration. A very powerful method available to analyze electro thermal performance is Finite Element Method (FEM) which is used in this paper. The analysis of various stator coil and slot configurations are used to design the better dielectric system to reduce electrical and thermal stresses in order to increase the power of generator in the same volume of core. This paper describes the process used to perform classical design and improvement analysis of stator slot-s insulation.

Keywords: Electromagnetic field, field distribution, insulation, winding, finite element method

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514 Psychosocial Risks and Occupational Health in a Mexican Small and Medium-Sized Enterprises

Authors: Magdalena Escamilla Quintal, Thelma Cetina Canto, Cecilia Aguilar Ortega

Abstract:

Due to the importance that people represent for companies, the setting of a clear control of the risks that threaten the health and the material and financial resources of workers is essential. It is irrelevant if the company is a small and medium-sized enterprise (SME) or a large multinational, or if it is in the construction or service sector. The risk prevention importance is related to a constitutional and human right that all people have; working in a risk-free environment to prevent accidents or illnesses that may influence their quality of life and the tranquility of their family. Therefore, the objective of this study was to determine the level of psychosocial risks (physical and emotional) of the employees of an SME. The participants of this study were 186 employees of a productive sector SME; 151 men and 35 women, all with an average age of 31.77 years. Their seniority inside the SME was between one month and 19.91 years. Ninety-six workers were from the production area, 28 from the management area, as well as 25 from the sales area and 40 from the supplies area. Ninety-three workers were found in Uman, 78 in Playa del Carmen, 11 in Cancun and seven in Cd. del Carmen. We found a statistically significant relationship between the burnout variable and the engagement and psychosomatic complaints as well as between the variables of sex, burnout and psychosomatic complaints. We can conclude that, for benefit of the SME, that there are low levels of burnout and psychosomatic complaints, the women experience major levels of burnout and the men show major levels of psychosomatic complaints. The findings, contributions, limitations and future proposals will be analyzed.

Keywords: Psychosocial risks, SME, burnout, engagement, psychosomatic complaints.

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513 Supply Chain Model of Catfish Production and Trade in Yogyakarta, Indonesia

Authors: Kuncoro Harto Widodo, Joewono Soemardjito, Dwi Ardianta Kurniawan

Abstract:

Currently, the demand for marine and fisheries commodity in Yogyakarta, Indonesia continues to increase. The existing condition shows that the aquaculture supply cannot be supplied by Yogyakarta region itself, but still need to be supported by regions outside Yogyakarta. The effort to optimize the market is initiated by reviewing and designing the supply chain of production and trade of aquaculture commodity in order to create the implementation of aquaculture production and trade commodity optimally. This formulated supply chain model indicates 4 performance indicators of measurable success in terms of: (1) efficiency; (2) flexibility; (3) responsiveness; and (4) quality. These indicators had been exercised as the success benchmarks for priority marketing management in local level as well as national level. The result of this research indicates that if the catfish fishery system is managed as business as usual then the catfish demand in Yogyakarta region will experience to increase in the future. The increase of demand is inline with the increase of number of people in Yogyakarta and also the fluctuation of catfish consumption per capita. The highest production of catfish will experience in the third year approximately 30,118 tons. Other result of the research indicates that the catfish demand in Yogyakarta region cannot be supplied yet from the local region. Therefore, to fulfill the supply from outside Yogyakarta region, the local farmers should improve the supply through land extension. The fluctuation of commodity price will experience in the future annually and the catfish supply from outside Yogyakarta region will be lowering the price in the market.

Keywords: Supply chain model, catfish, efficiency, flexibility

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512 Use of GIS for the Performance Evaluation of Canal Irrigation System in Rice Wheat Cropping Zone

Authors: Umm-e- Kalsoom, M. Arshad, Sadia Iqbal, M. Usman, M. Adnan

Abstract:

The research study evaluated the performance of irrigation system by using special scientific tools like Remote Sensing and GIS technology, so that proper measurements could be taken for the sustainable agriculture and water management. Different performance evaluation parameters had been calculated for the purposed data was gathered from field investigation and different government and private organizations. According to the calculations, organic matter ranges from 0.19% (low value) to 0.76% (high value). In flat irrigation system for wheat yield ranges from 3347.16 to 5260.39 kg/ha, while the total water applied to wheat crop ranges from 252.94 to 279.19 mm and WUE ranges from 13.07 to 18.37 kg/ha/mm. For rice yield ranges from 3347.47 to 5433.07 kg/ha with total water supplied to rice crop ranges from 764.71 to 978.15 mm and WUE ranges from 3.49 to 5.71 kg/ha/mm. Similarly, in raised bed system wheat yield ranges from 4569.13 to 6008.60 kg/ha, total water supplied ranges from 158.87 to 185.09 mm and WUE ranges from 27.20 to 33.54 kg/ha/mm while in rice crop, yield ranges from 5285.04 to 6716.69 kg/ha, total water supplied ranges from 600.72 to 755.06 mm and WUE ranges from 6.41 to 10.05 kg/ha/mm. Almost 51.3% water saving is observed in bed irrigation system as compared to flat system. Less water supplied to beds is more affective as its WUE value is higher than flat system where more water is supplied in both the seasons. Similarly, RWS values show that maximum water deficit while minimum area is getting adequate water supply. Greater yield is recorded in bed system as plant per square meter is more in bed system in comparison of flat system Thus, the integration of GIS tools to regularly compute performance indices could provide irrigation managers with the means for managing efficiently the irrigation system.

Keywords: Field survey, Relative Water Supply (RWS), Remote sensing maps, Water Use Efficiency (WUE).

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511 Linear Prediction System in Measuring Glucose Level in Blood

Authors: Intan Maisarah Abd Rahim, Herlina Abdul Rahim, Rashidah Ghazali

Abstract:

Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.

Keywords: Diabetes, glucose level, linear, near-infrared (NIR), non-invasive, prediction system.

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510 Optimal Selling Prices for Small Sized Poultry Farmers

Authors: Hidefumi Kawakatsu, Dong Li, Kosuke Kato

Abstract:

In Japan, meat-type chickens are mainly classified into three categories: (1) Broilers, (2) Branded chickens, and (3) Jidori (Free-range local traditional pedigree chickens). The Jidori chickens are certified by the Japanese Ministry of Agriculture, whilst, for the Branded chickens, there is no regulation with respect to their breed (genotype) or methods for rearing them. It is, therefore, relatively easy for poultry farmers to introduce Branded than Jidori chickens. The Branded chickens are normally fed a low-calorie diet with ingredients such as herbs, which lengthens their breeding period (compared with that of the Broilers) and increases their market value. In the field of inventory management, fast-growing animals such as broilers are categorised as ameliorating items. To the best of our knowledge, there are no previous studies that have explicitly considered smaller sized poultry farmers with limited breeding areas. This study develops an inventory model for a small sized poultry farmer that produces both the Broilers (Product 1) and the Branded chickens (Product 2) with different amelioration rates. The poultry farmer’s total profit per unit of time is formulated as a function of selling prices by using a price-dependent demand function. The existence of a unique optimal selling price for each product, which maximises the total profit, established. It has also been confirmed through numerical examples that, when the breeding area is fixed, the total profit could increase if the poultry farmer reduced the product quantity of Product 1 to introduce Product 2.

Keywords: Amelioration, deterioration, small sized poultry farmers, optimal price.

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509 Identifying the Barriers behind the Lack of Six Sigma Use in Libyan Manufacturing Companies

Authors: Osama Elgadi, Martin Birkett, Wai Ming Cheung

Abstract:

This paper investigates the barriers behind the underutilisation of six sigma in Libyan manufacturing companies (LMCs). A mixed-method methodology is proposed, starting by conducting interviews to collect qualitative data followed by the development of a questionnaire to obtain quantitative data. The focus of this paper is on discussing the findings of the interview stage and how these can be used to further develop the questionnaire stage. The interview results showed that only four key barriers were highlighted as being encountered by LMCs. With a difference in terms of their significance, these factors were identified, and placed in descending order according to their importance, namely: “Lack of top management commitment”, “Lack of training”, “Lack of knowledge about six sigma”, and “Culture effect”. The findings also showed that some barriers which, were found in previous studies of six sigma implementation were not considered as barriers to LMCs but can, in fact, be considered as success factors or enablers for six sigma adoption. These factors were identified as: “sufficiency of time and financial resources”; “customers unsatisfied”; “good communication between all departments in the company”; “we are certain about its results and benefits to our company and unhappy with the current quality system”. These results suggest that LMCs face fewer barriers to adopting six sigma than many well-established global companies operating in other countries and could take advantage of these successful factors by developing and implementing a six sigma framework to improve their product quality and competitiveness.

Keywords: Six sigma, barriers, Libyan manufacturing companies, interview.

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508 A Machine Learning Based Framework for Education Levelling in Multicultural Countries: UAE as a Case Study

Authors: Shatha Ghareeb, Rawaa Al-Jumeily, Thar Baker

Abstract:

In Abu Dhabi, there are many different education curriculums where sector of private schools and quality assurance is supervising many private schools in Abu Dhabi for many nationalities. As there are many different education curriculums in Abu Dhabi to meet expats’ needs, there are different requirements for registration and success. In addition, there are different age groups for starting education in each curriculum. In fact, each curriculum has a different number of years, assessment techniques, reassessment rules, and exam boards. Currently, students that transfer curriculums are not being placed in the right year group due to different start and end dates of each academic year and their date of birth for each year group is different for each curriculum and as a result, we find students that are either younger or older for that year group which therefore creates gaps in their learning and performance. In addition, there is not a way of storing student data throughout their academic journey so that schools can track the student learning process. In this paper, we propose to develop a computational framework applicable in multicultural countries such as UAE in which multi-education systems are implemented. The ultimate goal is to use cloud and fog computing technology integrated with Artificial Intelligence techniques of Machine Learning to aid in a smooth transition when assigning students to their year groups, and provide leveling and differentiation information of students who relocate from a particular education curriculum to another, whilst also having the ability to store and access student data from anywhere throughout their academic journey.

Keywords: Admissions, algorithms, cloud computing, differentiation, fog computing, leveling, machine learning.

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507 Bacteriological Screening and Antibiotic – Heavy Metal Resistance Profile of the Bacteria Isolated from Some Amphibian and Reptile Species of the Biga Stream in Turkey

Authors: Nurcihan Hacioglu, Cigdem Gul, Murat Tosunoglu

Abstract:

In this article, the antibiogram and heavy metal resistance profile of the bacteria isolated from total 34 studied animals (Pelophylax ridibundus = 12; Mauremys rivulata = 14; Natrix natrix = 8) captured around the Biga Stream, are described. There was no database information on antibiogram and heavy metal resistance profile of bacteria from these area’s amphibians and reptiles. A total of 200 bacteria were successfully isolated from cloaca and oral samples of the aquatic amphibians and reptiles as well as from the water sample. According to Jaccard’s similarity index, the degree of similarity in the bacterial flora was quite high among the amphibian and reptile species under examination, whereas it was different from the bacterial diversity in the water sample. The most frequent isolates were A. hydrophila (31.5%), B. pseudomallei (8.5%), and C. freundii (7%). The total numbers of bacteria obtained were as follows: 45 in P. ridibundus, 45 in N. natrix 30 in M. rivulata, and 80 in the water sample. The result showed that cefmetazole was the most effective antibiotic to control the bacteria isolated in this study and that approximately 93.33% of the bacterial isolates were sensitive to this antibiotic. The multiple antibiotic resistances (MAR) index indicated that P. ridibundus (0.95) > N. natrix (0.89) > M. rivulata (0.39). Furthermore, all the tested heavy metals (Pb+2, Cu+2, Cr+3, and Mn+2) inhibit the growth of the bacterial isolates at different rates. Therefore, it indicated that the water source of the animals was contaminated with both antibiotic residues and heavy metals.

Keywords: Amphibian, Bacteriological Quality, Reptile, Antibiotic & Heavy Metal Resistance.

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506 Smart Power Scheduling to Reduce Peak Demand and Cost of Energy in Smart Grid

Authors: Hemant I. Joshi, Vivek J. Pandya

Abstract:

This paper discusses the simulation and experimental work of small Smart Grid containing ten consumers. Smart Grid is characterized by a two-way flow of real-time information and energy. RTP (Real Time Pricing) based tariff is implemented in this work to reduce peak demand, PAR (peak to average ratio) and cost of energy consumed. In the experimental work described here, working of Smart Plug, HEC (Home Energy Controller), HAN (Home Area Network) and communication link between consumers and utility server are explained. Algorithms for Smart Plug, HEC, and utility server are presented and explained in this work. After receiving the Real Time Price for different time slots of the day, HEC interacts automatically by running an algorithm which is based on Linear Programming Problem (LPP) method to find the optimal energy consumption schedule. Algorithm made for utility server can handle more than one off-peak time period during the day. Simulation and experimental work are carried out for different cases. At the end of this work, comparison between simulation results and experimental results are presented to show the effectiveness of the minimization method adopted.

Keywords: Smart Grid, Real Time Pricing, Peak to Average Ratio, Home Area Network, Home Energy Controller, Smart Plug, Utility Server, Linear Programming Problem.

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505 Conjunctive Surface Runoff and Groundwater Management in Salinity Soils

Authors: S. Chuenchooklin, T. Ichikawa, P. Mekpruksawong

Abstract:

This research was conducted in the Lower Namkam Irrigation Project situated in the Namkam River Basin in Thailand. Degradation of groundwater quality in some areas is caused by saline soil spots beneath ground surface. However, the tail regulated gate structure on the Namkam River, a lateral stream of the Mekong River. It is aimed for maintaining water level in the river at +137.5 to +138.5 m (MSL) and flow to the irrigation canals based on a gravity system since July 2009. It might leach some saline soil spots from underground to soil surface if lack of understanding of the conjunctive surface water and groundwater behaviors. This research has been conducted by continuously the observing of both shallow and deep groundwater level and quality from existing observation wells. The simulation of surface water was carried out using a hydrologic modeling system (HEC-HMS) to compute the ungauged side flow catchments as the lateral flows for the river system model (HEC-RAS). The constant water levels in the upstream of the operated gate caused a slight rising up of shallow groundwater level when compared to the water table. However, the groundwater levels in the confined aquifers remained less impacted than in the shallow aquifers but groundwater levels in late of wet season in some wells were higher than the phreatic surface. This causes salinization of the groundwater at the soil surface and might affect some crops. This research aims for the balance of water stage in the river and efficient groundwater utilization in this area.

Keywords: Surface water, groundwater observation, irrigation, water balance.

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504 Decision Support System for Flood Crisis Management using Artificial Neural Network

Authors: Muhammad Aqil, Ichiro Kita, Akira Yano, Nishiyama Soichi

Abstract:

This paper presents an alternate approach that uses artificial neural network to simulate the flood level dynamics in a river basin. The algorithm was developed in a decision support system environment in order to enable users to process the data. The decision support system is found to be useful due to its interactive nature, flexibility in approach and evolving graphical feature and can be adopted for any similar situation to predict the flood level. The main data processing includes the gauging station selection, input generation, lead-time selection/generation, and length of prediction. This program enables users to process the flood level data, to train/test the model using various inputs and to visualize results. The program code consists of a set of files, which can as well be modified to match other purposes. This program may also serve as a tool for real-time flood monitoring and process control. The running results indicate that the decision support system applied to the flood level seems to have reached encouraging results for the river basin under examination. The comparison of the model predictions with the observed data was satisfactory, where the model is able to forecast the flood level up to 5 hours in advance with reasonable prediction accuracy. Finally, this program may also serve as a tool for real-time flood monitoring and process control.

Keywords: Decision Support System, Neural Network, Flood Level

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503 Reduction of False Positives in Head-Shoulder Detection Based on Multi-Part Color Segmentation

Authors: Lae-Jeong Park

Abstract:

The paper presents a method that utilizes figure-ground color segmentation to extract effective global feature in terms of false positive reduction in the head-shoulder detection. Conventional detectors that rely on local features such as HOG due to real-time operation suffer from false positives. Color cue in an input image provides salient information on a global characteristic which is necessary to alleviate the false positives of the local feature based detectors. An effective approach that uses figure-ground color segmentation has been presented in an effort to reduce the false positives in object detection. In this paper, an extended version of the approach is presented that adopts separate multipart foregrounds instead of a single prior foreground and performs the figure-ground color segmentation with each of the foregrounds. The multipart foregrounds include the parts of the head-shoulder shape and additional auxiliary foregrounds being optimized by a search algorithm. A classifier is constructed with the feature that consists of a set of the multiple resulting segmentations. Experimental results show that the presented method can discriminate more false positive than the single prior shape-based classifier as well as detectors with the local features. The improvement is possible because the presented approach can reduce the false positives that have the same colors in the head and shoulder foregrounds.

Keywords: Pedestrian detection, color segmentation, false positives, feature extraction.

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502 Exploring Dimensionality, Systematic Mutations and Number of Contacts in Simple HP ab-initio Protein Folding Using a Blackboard-based Agent Platform

Authors: Hiram I. Beltrán, Arturo Rojo-Domínguez, Máximo Eduardo Sánchez Gutiérrez, Pedro Pablo González Pérez

Abstract:

A computational platform is presented in this contribution. It has been designed as a virtual laboratory to be used for exploring optimization algorithms in biological problems. This platform is built on a blackboard-based agent architecture. As a test case, the version of the platform presented here is devoted to the study of protein folding, initially with a bead-like description of the chain and with the widely used model of hydrophobic and polar residues (HP model). Some details of the platform design are presented along with its capabilities and also are revised some explorations of the protein folding problems with different types of discrete space. It is also shown the capability of the platform to incorporate specific tools for the structural analysis of the runs in order to understand and improve the optimization process. Accordingly, the results obtained demonstrate that the ensemble of computational tools into a single platform is worthwhile by itself, since experiments developed on it can be designed to fulfill different levels of information in a self-consistent fashion. By now, it is being explored how an experiment design can be useful to create a computational agent to be included within the platform. These inclusions of designed agents –or software pieces– are useful for the better accomplishment of the tasks to be developed by the platform. Clearly, while the number of agents increases the new version of the virtual laboratory thus enhances in robustness and functionality.

Keywords: genetic algorithms, multi-agent systems, bioinformatics, optimization, protein folding, structural biology.

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501 Assessment of the Number of Damaged Buildings from a Flood Event Using Remote Sensing Technique

Authors: Jaturong Som-ard

Abstract:

The heavy rainfall from 3rd to 22th January 2017 had swamped much area of Ranot district in southern Thailand. Due to heavy rainfall, the district was flooded which had a lot of effects on economy and social loss. The major objective of this study is to detect flooding extent using Sentinel-1A data and identify a number of damaged buildings over there. The data were collected in two stages as pre-flooding and during flood event. Calibration, speckle filtering, geometric correction, and histogram thresholding were performed with the data, based on intensity spectral values to classify thematic maps. The maps were used to identify flooding extent using change detection, along with the buildings digitized and collected on JOSM desktop. The numbers of damaged buildings were counted within the flooding extent with respect to building data. The total flooded areas were observed as 181.45 sq.km. These areas were mostly occurred at Ban khao, Ranot, Takhria, and Phang Yang sub-districts, respectively. The Ban khao sub-district had more occurrence than the others because this area is located at lower altitude and close to Thale Noi and Thale Luang lakes than others. The numbers of damaged buildings were high in Khlong Daen (726 features), Tha Bon (645 features), and Ranot sub-district (604 features), respectively. The final flood extent map might be very useful for the plan, prevention and management of flood occurrence area. The map of building damage can be used for the quick response, recovery and mitigation to the affected areas for different concern organization.

Keywords: Flooding extent, Sentinel-1A data, JOSM desktop, damaged buildings.

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500 Statistical Feature Extraction Method for Wood Species Recognition System

Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

Abstract:

Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: Classification, fuzzy, inspection system, image analysis.

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499 On the Parameter Optimization of Fuzzy Inference Systems

Authors: Erika Martinez Ramirez, Rene V. Mayorga

Abstract:

Nowadays, more engineering systems are using some kind of Artificial Intelligence (AI) for the development of their processes. Some well-known AI techniques include artificial neural nets, fuzzy inference systems, and neuro-fuzzy inference systems among others. Furthermore, many decision-making applications base their intelligent processes on Fuzzy Logic; due to the Fuzzy Inference Systems (FIS) capability to deal with problems that are based on user knowledge and experience. Also, knowing that users have a wide variety of distinctiveness, and generally, provide uncertain data, this information can be used and properly processed by a FIS. To properly consider uncertainty and inexact system input values, FIS normally use Membership Functions (MF) that represent a degree of user satisfaction on certain conditions and/or constraints. In order to define the parameters of the MFs, the knowledge from experts in the field is very important. This knowledge defines the MF shape to process the user inputs and through fuzzy reasoning and inference mechanisms, the FIS can provide an “appropriate" output. However an important issue immediately arises: How can it be assured that the obtained output is the optimum solution? How can it be guaranteed that each MF has an optimum shape? A viable solution to these questions is through the MFs parameter optimization. In this Paper a novel parameter optimization process is presented. The process for FIS parameter optimization consists of the five simple steps that can be easily realized off-line. Here the proposed process of FIS parameter optimization it is demonstrated by its implementation on an Intelligent Interface section dealing with the on-line customization / personalization of internet portals applied to E-commerce.

Keywords: Artificial Intelligence, Fuzzy Logic, Fuzzy InferenceSystems, Nonlinear Optimization.

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498 An Automatic Bayesian Classification System for File Format Selection

Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

Abstract:

This paper presents an approach for the classification of an unstructured format description for identification of file formats. The main contribution of this work is the employment of data mining techniques to support file format selection with just the unstructured text description that comprises the most important format features for a particular organisation. Subsequently, the file format indentification method employs file format classifier and associated configurations to support digital preservation experts with an estimation of required file format. Our goal is to make use of a format specification knowledge base aggregated from a different Web sources in order to select file format for a particular institution. Using the naive Bayes method, the decision support system recommends to an expert, the file format for his institution. The proposed methods facilitate the selection of file format and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and specifications of file formats. To facilitate decision-making, the aggregated information about the file formats is presented as a file format vocabulary that comprises most common terms that are characteristic for all researched formats. The goal is to suggest a particular file format based on this vocabulary for analysis by an expert. The sample file format calculation and the calculation results including probabilities are presented in the evaluation section.

Keywords: Data mining, digital libraries, digital preservation, file format.

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497 Optimization and GIS-Based Intelligent Decision Support System for Urban Transportation Systems Analysis

Authors: Mohamad K. Hasan, Hameed Al-Qaheri

Abstract:

Optimization plays an important role in most real world applications that support decision makers to take the right decision regarding the strategic directions and operations of the system they manage. Solutions for traffic management and traffic congestion problems are considered major problems that most decision making authorities for cities around the world are looking for. This review paper gives a full description of the traffic problem as part of the transportation planning process and present a view as a framework of urban transportation system analysis where the core of the system is a transportation network equilibrium model that is based on optimization techniques and that can also be used for evaluating an alternative solution or a combination of alternative solutions for the traffic congestion. Different transportation network equilibrium models are reviewed from the sequential approach to the multiclass combining trip generation, trip distribution, modal split, trip assignment and departure time model. A GIS-Based intelligent decision support system framework for urban transportation system analysis is suggested for implementation where the selection of optimized alternative solutions, single or packages, will be based on an intelligent agent rather than human being which would lead to reduction in time, cost and the elimination of the difficulty, by human being, for finding the best solution to the traffic congestion problem.

Keywords: Multiclass simultaneous transportation equilibrium models, transportation planning, urban transportation systems analysis, intelligent decision support system.

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496 Improvement of Stator Slot Structure based on Insulation Stresses Analysis in HV Generator

Authors: Diako Azizi, Ahmad Gholami, Vahid Abbasi

Abstract:

High voltage generators are being subject to higher voltage rating and are being designed to operate in harsh conditions. Stator windings are the main component of generators in which Electrical, magnetical and thermal stresses remain major failures for insulation degradation accelerated aging. A large number of generators failed due to stator winding problems, mainly insulation deterioration. Insulation degradation assessment plays vital role in the asset life management. Mostly the stator failure is catastrophic causing significant damage to the plant. Other than generation loss, stator failure involves heavy repair or replacement cost. Electro thermal analysis is the main characteristic for improvement design of stator slot-s insulation. Dielectric parameters such as insulation thickness, spacing, material types, geometry of winding and slot are major design consideration. A very powerful method available to analyze electro thermal performance is Finite Element Method (FEM) which is used in this paper. The analysis of various stator coil and slot configurations are used to design the better dielectric system to reduce electrical and thermal stresses in order to increase the power of generator in the same volume of core. This paper describes the process used to perform classical design and improvement analysis of stator slot-s insulation.

Keywords: Electrical field, field distribution, insulation, winding, finite element method, electro thermal

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495 Assessment and Uncertainty Analysis of ROSA/LSTF Test on Pressurized Water Reactor 1.9% Vessel Upper Head Small-Break Loss-of-Coolant Accident

Authors: Takeshi Takeda

Abstract:

An experiment utilizing the ROSA/LSTF (rig of safety assessment/large-scale test facility) simulated a 1.9% vessel upper head small-break loss-of-coolant accident with an accident management (AM) measure under the total failure of high-pressure injection system of emergency core cooling system in a pressurized water reactor. Steam generator (SG) secondary-side depressurization on the AM measure was started by fully opening relief valves in both SGs when the maximum core exit temperature rose to 623 K. A large increase took place in the cladding surface temperature of simulated fuel rods on account of a late and slow response of core exit thermocouples during core boil-off. The author analyzed the LSTF test by reference to the matrix of an integral effect test for the validation of a thermal-hydraulic system code. Problems remained in predicting the primary coolant distribution and the core exit temperature with the RELAP5/MOD3.3 code. The uncertainty analysis results of the RELAP5 code confirmed that the sample size with respect to the order statistics influences the value of peak cladding temperature with a 95% probability at a 95% confidence level, and the Spearman’s rank correlation coefficient.

Keywords: LSTF, LOCA, uncertainty analysis, RELAP5.

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494 User Pattern Learning Algorithm based MDSS(Medical Decision Support System) Framework under Ubiquitous

Authors: Insung Jung, Gi-Nam Wang

Abstract:

In this paper, we present user pattern learning algorithm based MDSS (Medical Decision support system) under ubiquitous. Most of researches are focus on hardware system, hospital management and whole concept of ubiquitous environment even though it is hard to implement. Our objective of this paper is to design a MDSS framework. It helps to patient for medical treatment and prevention of the high risk patient (COPD, heart disease, Diabetes). This framework consist database, CAD (Computer Aided diagnosis support system) and CAP (computer aided user vital sign prediction system). It can be applied to develop user pattern learning algorithm based MDSS for homecare and silver town service. Especially this CAD has wise decision making competency. It compares current vital sign with user-s normal condition pattern data. In addition, the CAP computes user vital sign prediction using past data of the patient. The novel approach is using neural network method, wireless vital sign acquisition devices and personal computer DB system. An intelligent agent based MDSS will help elder people and high risk patients to prevent sudden death and disease, the physician to get the online access to patients- data, the plan of medication service priority (e.g. emergency case).

Keywords: Neural network, U-healthcare, MDSS, CAP, DSS.

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493 Globalisation, ICTs and National Identity: The Consequences of ICT Policy in Malaysia

Authors: Abd Rasid Abd Rahman

Abstract:

For the past thirty years the Malaysian economy has been said to contribute well to the progress of the nations. However, the intensification of global economy activity and the extensive use of Information Communication Technologies (ICTs) in recent years are challenging government-s effort to further develop Malaysian society. The competition posed by the low wage economies such as China and Vietnam have made the government realise the importance of engaging in high-skill and high technology industries. It is hoped this will be the basis of attracting more foreign direct investment (FDI) in order to help the country to compete in globalised world. Using Vision 2020 as it targeted vision, the government has decided to engage in the use of ICTs and introduce many policies pertaining to it. Mainly based on the secondary analysis approach, the findings show that policy pertaining to ICTs in Malaysia contributes to economic growth, but the consequences of this have resulted in greater division within society. Although some of the divisions such as gender and ethnicity are narrowing down, the gap in important areas such as regions and class differences is becoming wider. The widespread use of ICTs might contribute to the further establishment of democracy in Malaysia, but the increasing number of foreign entities such as FDI and foreign workers, cultural hybridisation and to some extent cultural domination are contributing to neocolonialism in Malaysia. This has obvious consequences for the government-s effort to create a Malaysian national identity. An important finding of this work is that there are contradictions within ICT policy between the effort to develop the economy and society.

Keywords: Globalisation, ICTs, ICT Policy, Malaysia, National Identity, Vision 2020

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492 Vehicle Gearbox Fault Diagnosis Based On Cepstrum Analysis

Authors: Mohamed El Morsy, Gabriela Achtenová

Abstract:

Research on damage of gears and gear pairs using vibration signals remains very attractive, because vibration signals from a gear pair are complex in nature and not easy to interpret. Predicting gear pair defects by analyzing changes in vibration signal of gears pairs in operation is a very reliable method. Therefore, a suitable vibration signal processing technique is necessary to extract defect information generally obscured by the noise from dynamic factors of other gear pairs.This article presents the value of cepstrum analysis in vehicle gearbox fault diagnosis. Cepstrum represents the overall power content of a whole family of harmonics and sidebands when more than one family of sidebands is present at the same time. The concept for the measurement and analysis involved in using the technique are briefly outlined. Cepstrum analysis is used for detection of an artificial pitting defect in a vehicle gearbox loaded with different speeds and torques. The test stand is equipped with three dynamometers; the input dynamometer serves asthe internal combustion engine, the output dynamometers introduce the load on the flanges of the output joint shafts. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. Also, a method for fault diagnosis of gear faults is presented based on order Cepstrum. The procedure is illustrated with the experimental vibration data of the vehicle gearbox. The results show the effectiveness of Cepstrum analysis in detection and diagnosis of the gear condition.

Keywords: Cepstrum analysis, fault diagnosis, gearbox.

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491 Evaluating Efficiency of Nina Distribution Company Using Window Data Envelopment Analysis and Malmquist Index

Authors: Hossein Taherian Far, Ali Bazaee

Abstract:

Achieving continuous sustained economic growth and following economic development can be the target for all countries which are looking for it. In this regard, distribution industry plays an important role in growth and development of any nation. So, estimating the efficiency and productivity of the so called industry and identifying factors influencing it, is very necessary. The objective of the present study is to measure the efficiency and productivity of seven branches of Nina Distribution Company using window data envelopment analysis and Malmquist productivity index from spring 2013 to summer 2015. In this study, using criteria of fixed assets, payroll personnel, operating costs and duration of collection of receivables were selected as inputs and people and net sales, gross profit and percentage of coverage to customers were selected as outputs. Then, the process of performance window data envelopment analysis was driven and process efficiency has been measured using Malmquist index. The results indicate that the average technical efficiency of window Data Envelopment Analysis (DEA) model and fluctuating trend is sustainable. But the average management efficiency in window DEA model is related with negative growth (decline) of about 13%. The mean scale efficiency in all windows, except in the second one which is faced with 8%, shows growth of 18% compared to the first window. On the other hand, the mean change in total factor productivity in all branches of the industry shows average negative growth (decrease) of 12% which are the result of a negative change in technology.

Keywords: Nina Distribution Company branches, window data envelopment analysis, Malmquist productivity index.

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490 Fuel Economy and Stability Enhancement of the Hybrid Vehicles by Using Electrical Machines on Non-Driven Wheels

Authors: P. Naderi, S.M.T. Bathaee, R. Hoseinnezhad, R. Chini

Abstract:

Using electrical machine in conventional vehicles, also called hybrid vehicles, has become a promising control scheme that enables some manners for fuel economy and driver assist for better stability. In this paper, vehicle stability control, fuel economy and Driving/Regeneration braking for a 4WD hybrid vehicle is investigated by using an electrical machine on each non-driven wheels. In front wheels driven vehicles, fuel economy and regenerative braking can be obtained by summing torques applied on rear wheels. On the other hand, unequal torques applied to rear wheels provides enhanced safety and path correction in steering. In this paper, a model with fourteen degrees of freedom is considered for vehicle body, tires and, suspension systems. Thereafter, powertrain subsystems are modeled. Considering an electrical machine on each rear wheel, a fuzzy controller is designed for each driving, braking, and stability conditions. Another fuzzy controller recognizes the vehicle requirements between the driving/regeneration and stability modes. Intelligent vehicle control to multi objective operation and forward simulation are the paper advantages. For reaching to these aims, power management control and yaw moment control will be done by three fuzzy controllers. Also, the above mentioned goals are weighted by another fuzzy sub-controller base on vehicle dynamic. Finally, Simulations performed in MATLAB/SIMULINK environment show that the proposed structure can enhance the vehicle performance in different modes effectively.

Keywords: Hybrid, pitch, roll, regeneration, yaw.

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489 Hash Based Block Matching for Digital Evidence Image Files from Forensic Software Tools

Authors: M. Kaya, M. Eris

Abstract:

Internet use, intelligent communication tools, and social media have all become an integral part of our daily life as a result of rapid developments in information technology. However, this widespread use increases crimes committed in the digital environment. Therefore, digital forensics, dealing with various crimes committed in digital environment, has become an important research topic. It is in the research scope of digital forensics to investigate digital evidences such as computer, cell phone, hard disk, DVD, etc. and to report whether it contains any crime related elements. There are many software and hardware tools developed for use in the digital evidence acquisition process. Today, the most widely used digital evidence investigation tools are based on the principle of finding all the data taken place in digital evidence that is matched with specified criteria and presenting it to the investigator (e.g. text files, files starting with letter A, etc.). Then, digital forensics experts carry out data analysis to figure out whether these data are related to a potential crime. Examination of a 1 TB hard disk may take hours or even days, depending on the expertise and experience of the examiner. In addition, it depends on examiner’s experience, and may change overall result involving in different cases overlooked. In this study, a hash-based matching and digital evidence evaluation method is proposed, and it is aimed to automatically classify the evidence containing criminal elements, thereby shortening the time of the digital evidence examination process and preventing human errors.

Keywords: Block matching, digital evidence, hash list.

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488 Multilevel Classifiers in Recognition of Handwritten Kannada Numerals

Authors: Dinesh Acharya U., N. V. Subba Reddy, Krishnamoorthi Makkithaya

Abstract:

The recognition of handwritten numeral is an important area of research for its applications in post office, banks and other organizations. This paper presents automatic recognition of handwritten Kannada numerals based on structural features. Five different types of features, namely, profile based 10-segment string, water reservoir; vertical and horizontal strokes, end points and average boundary length from the minimal bounding box are used in the recognition of numeral. The effect of each feature and their combination in the numeral classification is analyzed using nearest neighbor classifiers. It is common to combine multiple categories of features into a single feature vector for the classification. Instead, separate classifiers can be used to classify based on each visual feature individually and the final classification can be obtained based on the combination of separate base classification results. One popular approach is to combine the classifier results into a feature vector and leaving the decision to next level classifier. This method is extended to extract a better information, possibility distribution, from the base classifiers in resolving the conflicts among the classification results. Here, we use fuzzy k Nearest Neighbor (fuzzy k-NN) as base classifier for individual feature sets, the results of which together forms the feature vector for the final k Nearest Neighbor (k-NN) classifier. Testing is done, using different features, individually and in combination, on a database containing 1600 samples of different numerals and the results are compared with the results of different existing methods.

Keywords: Fuzzy k Nearest Neighbor, Multiple Classifiers, Numeral Recognition, Structural features.

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487 Irrigation Scheduling for Maize and Indian-mustard based on Daily Crop Water Requirement in a Semi- Arid Region

Authors: Vijay Shankar, C.S.P. Ojha, K.S. Hari Prasad

Abstract:

Maize and Indian mustard are significant crops in semi-arid climate zones of India. Improved water management requires precise scheduling of irrigation, which in turn requires an accurate computation of daily crop evapotranspiration (ETc). Daily crop evapotranspiration comes as a product of reference evapotranspiration (ET0) and the growth stage specific crop coefficients modified for daily variation. The first objective of present study is to develop crop coefficients Kc for Maize and Indian mustard. The estimated values of Kc for maize at the four crop growth stages (initial, development, mid-season, and late season) are 0.55, 1.08, 1.25, and 0.75, respectively, and for Indian mustard the Kc values at the four growth stages are 0.3, 0.6, 1.12, and 0.35, respectively. The second objective of the study is to compute daily crop evapotranspiration from ET0 and crop coefficients. Average daily ETc of maize varied from about 2.5 mm/d in the early growing period to > 6.5 mm/d at mid season. The peak ETc of maize is 8.3 mm/d and it occurred 64 days after sowing at the reproductive growth stage when leaf area index was 4.54. In the case of Indian mustard, average ETc is 1 mm/d at the initial stage, >1.8 mm/d at mid season and achieves a peak value of 2.12 mm/d on 56 days after sowing. Improved schedules of irrigation have been simulated based on daily crop evapo-transpiration and field measured data. Simulation shows a close match between modeled and field moisture status prevalent during crop season.

Keywords: Crop coefficient, Crop evapotranspiration, Field moisture, Irrigation Scheduling

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