Search results for: Usage performance of information systems
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12014

Search results for: Usage performance of information systems

5684 Design of Synchronous Torque Couplers

Authors: M. H. Nagrial, J. Rizk, A. Hellany

Abstract:

This paper presents the design, analysis and development of permanent magnet (PM) torque couplers. These couplers employ rare-earth magnets. Based on finite element analysis and earlier analytical works both concentric and face-type synchronous type couplers have been designed and fabricated. The experimental performance has good correlation with finite element calculations.

Keywords: Finite Element Analysis, Synchronous TorqueCouplers, Permanent Magnet Torque Couplers

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5683 Interoperable CNC System for Turning Operations

Authors: Yusri Yusof, Stephen Newman, Aydin Nassehi, Keith Case

Abstract:

The changing economic climate has made global manufacturing a growing reality over the last decade, forcing companies from east and west and all over the world to collaborate beyond geographic boundaries in the design, manufacture and assemble of products. The ISO10303 and ISO14649 Standards (STEP and STEP-NC) have been developed to introduce interoperability into manufacturing enterprises so as to meet the challenge of responding to production on demand. This paper describes and illustrates a STEP compliant CAD/CAPP/CAM System for the manufacture of rotational parts on CNC turning centers. The information models to support the proposed system together with the data models defined in the ISO14649 standard used to create the NC programs are also described. A structured view of a STEP compliant CAD/CAPP/CAM system framework supporting the next generation of intelligent CNC controllers for turn/mill component manufacture is provided. Finally a proposed computational environment for a STEP-NC compliant system for turning operations (SCSTO) is described. SCSTO is the experimental part of the research supported by the specification of information models and constructed using a structured methodology and object-oriented methods. SCSTO was developed to generate a Part 21 file based on machining features to support the interactive generation of process plans utilizing feature extraction. A case study component has been developed to prove the concept for using the milling and turning parts of ISO14649 to provide a turn-mill CAD/CAPP/CAM environment.

Keywords:

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5682 Automatic Segmentation of Retina Vessels by Using Zhang Method

Authors: Ehsan Saghapour, Somayeh Zandian

Abstract:

Image segmentation is an important step in image processing. Major developments in medical imaging allow physicians to use potent and non-invasive methods in order to evaluate structures, performance and to diagnose human diseases. In this study, an active contour was used to extract vessel networks from color retina images. Automatic analysis of retina vessels facilitates calculation of arterial index which is required to diagnose some certain retinopathies.

Keywords: Active contour, retinal vessel segmentation, image processing.

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5681 Study of Syntactic Errors for Deep Parsing at Machine Translation

Authors: Yukiko Sasaki Alam, Shahid Alam

Abstract:

Syntactic parsing is vital for semantic treatment by many applications related to natural language processing (NLP), because form and content coincide in many cases. However, it has not yet reached the levels of reliable performance. By manually examining and analyzing individual machine translation output errors that involve syntax as well as semantics, this study attempts to discover what is required for improving syntactic and semantic parsing.

Keywords: Machine translation, error analysis, syntactic errors, knowledge required for parsing.

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5680 Effect of Halo Protection Device on the Aerodynamic Performance of Formula Racecar

Authors: Mark Lin, Periklis Papadopoulos

Abstract:

This paper explores the aerodynamics of the formula racecar when a ‘halo’ driver-protection device is added to the chassis. The halo protection device was introduced at the start of the 2018 racing season as a safety measure against foreign object impacts that a driver may encounter when driving an open-wheel racecar. In the one-year since its introduction, the device has received wide acclaim for protecting the driver on two separate occasions. The benefit of such a safety device certainly cannot be disputed. However, by adding the halo device to a car, it changes the airflow around the vehicle, and most notably, to the engine air-intake and the rear wing. These negative effects in the air supply to the engine, and equally to the downforce created by the rear wing are studied in this paper using numerical technique, and the resulting CFD outputs are presented and discussed. Comparing racecar design prior to and after the introduction of the halo device, it is shown that the design of the air intake and the rear wing has not followed suit since the addition of the halo device. The reduction of engine intake mass flow due to the halo device is computed and presented for various speeds the car may be going. Because of the location of the halo device in relation to the air intake, airflow is directed away from the engine, making the engine perform less than optimal. The reduction is quantified in this paper to show the correspondence to reduce the engine output when compared to a similar car without the halo device. This paper shows that through aerodynamic arguments, the engine in a halo car will not receive unobstructed, clean airflow that a non-halo car does. Another negative effect is on the downforce created by the rear wing. Because the amount of downforce created by the rear wing is influenced by every component that comes before it, when a halo device is added upstream to the rear wing, airflow is obstructed, and less is available for making downforce. This reduction in downforce is especially dramatic as the speed is increased. This paper presents a graph of downforce over a range of speeds for a car with and without the halo device. Acknowledging that although driver safety is paramount, the negative effect of this safety device on the performance of the car should still be well understood so that any possible redesign to mitigate these negative effects can be taken into account in next year’s rules regulation.

Keywords: Automotive aerodynamics, halo device, downforce. engine intake.

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5679 Normal and Peaberry Coffee Beans Classification from Green Coffee Bean Images Using Convolutional Neural Networks and Support Vector Machine

Authors: Hira Lal Gope, Hidekazu Fukai

Abstract:

The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Keywords: Convolutional neural networks, coffee bean, peaberry, sorting, support vector machine.

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5678 Extraction of Bran Protein Using Enzymes and Polysaccharide Precipitation

Authors: Sudarat Jiamyangyuen, Tipawan Thongsook, Riantong Singanusong, Chanida Saengtubtim

Abstract:

Rice bran is normally used as a raw material for rice bran oil production or sold as feed with a low price. Conventionally, the protein in defatted rice bran was extracted using alkaline extraction and acid precipitation, which involves in chemical usage and lowering some nutritious component. This study was conducted in order to extract of rice bran protein concentrate (RBPC) from defatted rice bran using enzymes and employing polysaccharides in a precipitating step. The properties of RBPC obtained will be compared to those of a control sample extracted using a conventional method. The results showed that extraction of protein from rice bran using enzymes exhibited the higher protein recovery compared to that extraction with alkaline. The extraction conditions using alcalase 2% (v/w) at 50 C, pH 9.5 gave the highest protein (2.44%) and yield (32.09%) in extracted solution compared to other enzymes. Rice bran protein concentrate powder prepared by a precipitation step using alginate (protein in solution: alginate 1:0.016) exhibited the highest protein (27.55%) and yield (6.84%). Precipitation using alginate was better than that of acid. RBPC extracted with alkaline (ALK) or enzyme alcalase (ALC), then precipitated with alginate (AL) (samples RBP-ALK-AL and RBP-ALC-AL) yielded the precipitation rate of 75% and 91.30%, respectively. Therefore, protein precipitation using alginate was then selected. Amino acid profile of control sample, and sample precipitated with alginate, as compared to casein and soy protein isolated, showed that control sample showed the highest content among all sample. Functional property study of RBP showed that the highest nitrogen solubility occurred in pH 8-10. There was no statically significant between emulsion capacity and emulsion stability of control and sample precipitated by alginate. However, control sample showed a higher of foaming capacity and foaming stability compared to those of sample precipitated with alginate. The finding was successful in terms of minimizing chemicals used in extraction and precipitation steps in preparation of rice bran protein concentrate. This research involves in a production of value-added product in which the double amount of protein (28%) compared to original amount (14%) contained in rice bran could be beneficial in terms of adding to food products e.g. healthy drink with high protein and fiber. In addition, the basic knowledge of functional property of rice bran protein concentrate was obtained, which can be used to appropriately select the application of this value-added product from rice bran.

Keywords: Alginate, carrageenan, rice bran, rice bran protein.

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5677 Assessment of Groundwater Chemistry and Quality Characteristics in an Alluvial Aquifer and a Single Plane Fractured-Rock Aquifer in Bloemfontein, South Africa

Authors: Modreck Gomo

Abstract:

The evolution of groundwater chemistry and its quality is largely controlled by hydrogeochemical processes and their understanding is therefore important for groundwater quality assessments and protection of the water resources. A study was conducted in Bloemfontein town of South Africa to assess and compare the groundwater chemistry and quality characteristics in an alluvial aquifer and single-plane fractured-rock aquifers. 9 groundwater samples were collected from monitoring boreholes drilled into the two aquifer systems during a once-off sampling exercise. Samples were collected through low-flow purging technique and analysed for major ions and trace elements. In order to describe the hydrochemical facies and identify dominant hydrogeochemical processes, the groundwater chemistry data are interpreted using stiff diagrams and principal component analysis (PCA), as complimentary tools. The fitness of the groundwater quality for domestic and irrigation uses is also assessed. Results show that the alluvial aquifer is characterised by a Na-HCO3 hydrochemical facie while fractured-rock aquifer has a Ca-HCO3 facie. The groundwater in both aquifers originally evolved from the dissolution of calcite rocks that are common on land surface environments. However the groundwater in the alluvial aquifer further goes through another evolution as driven by cation exchange process in which Na in the sediments exchanges with Ca2+ in the Ca-HCO3 hydrochemical type to result in the Na-HCO3 hydrochemical type. Despite the difference in the hydrogeochemical processes between the alluvial aquifer and single-plane fractured-rock aquifer, this did not influence the groundwater quality. The groundwater in the two aquifers is very hard as influenced by the elevated magnesium and calcium ions that evolve from dissolution of carbonate minerals which typically occurs in surface environments. Based on total dissolved levels (600-900 mg/L), groundwater quality of the two aquifer systems is classified to be of fair quality. The negative potential impacts of the groundwater quality for domestic uses are highlighted.

Keywords: Alluvial aquifer, fractured-rock aquifer, groundwater quality, hydrogeochemical processes.

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5676 T-Wave Detection Based on an Adjusted Wavelet Transform Modulus Maxima

Authors: Samar Krimi, Kaïs Ouni, Noureddine Ellouze

Abstract:

The method described in this paper deals with the problems of T-wave detection in an ECG. Determining the position of a T-wave is complicated due to the low amplitude, the ambiguous and changing form of the complex. A wavelet transform approach handles these complications therefore a method based on this concept was developed. In this way we developed a detection method that is able to detect T-waves with a sensitivity of 93% and a correct-detection ratio of 93% even with a serious amount of baseline drift and noise.

Keywords: ECG, Modulus Maxima Wavelet Transform, Performance, T-wave detection

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5675 Storing OWL Ontologies in SQL Relational Databases

Authors: Irina Astrova, Nahum Korda, Ahto Kalja

Abstract:

Relational databases are often used as a basis for persistent storage of ontologies to facilitate rapid operations such as search and retrieval, and to utilize the benefits of relational databases management systems such as transaction management, security and integrity control. On the other hand, there appear more and more OWL files that contain ontologies. Therefore, this paper proposes to extract ontologies from OWL files and then store them in relational databases. A prerequisite for this storing is transformation of ontologies to relational databases, which is the purpose of this paper.

Keywords: Ontologies, relational databases, SQL, and OWL.

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5674 Plant Layout Analysis by Computer Simulation for Electronic Manufacturing Service Plant

Authors: Visuwan D., Phruksaphanrat B

Abstract:

In this research, computer simulation is used for Electronic Manufacturing Service (EMS) plant layout analysis. The current layout of this manufacturing plant is a process layout, which is not suitable due to the nature of an EMS that has high-volume and high-variety environment. Moreover, quick response and high flexibility are also needed. Then, cellular manufacturing layout design was determined for the selected group of products. Systematic layout planning (SLP) was used to analyze and design the possible cellular layouts for the factory. The cellular layout was selected based on the main criteria of the plant. Computer simulation was used to analyze and compare the performance of the proposed cellular layout and the current layout. It found that the proposed cellular layout can generate better performances than the current layout. In this research, computer simulation is used for Electronic Manufacturing Service (EMS) plant layout analysis. The current layout of this manufacturing plant is a process layout, which is not suitable due to the nature of an EMS that has high-volume and high-variety environment. Moreover, quick response and high flexibility are also needed. Then, cellular manufacturing layout design was determined for the selected group of products. Systematic layout planning (SLP) was used to analyze and design the possible cellular layouts for the factory. The cellular layout was selected based on the main criteria of the plant. Computer simulation was used to analyze and compare the performance of the proposed cellular layout and the current layout. It found that the proposed cellular layout can generate better performances than the current layout. 

Keywords: Layout, Electronic Manufacturing Service Plant (EMS), Computer Simulation, Cellular Manufacturing System (CMS).

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5673 A Multigranular Linguistic Additive Ratio Assessment Model in Group Decision Making

Authors: Wiem Daoud Ben Amor, Luis Martínez López, Jr., Hela Moalla Frikha

Abstract:

Most of the multi-criteria group decision making (MCGDM) problems dealing with qualitative criteria require consideration of the large background of expert information. It is common that experts have different degrees of knowledge for giving their alternative assessments according to criteria. So, it seems logical that they use different evaluation scales to express their judgment, i.e., multi granular linguistic scales. In this context, we propose the extension of the classical additive ratio assessment (ARAS) method to the case of a hierarchical linguistics term for managing multi granular linguistic scales in uncertain context where uncertainty is modeled by means in linguistic information. The proposed approach is called the extended hierarchical linguistics-ARAS method (ELH-ARAS). Within the ELH-ARAS approach, the decision maker (DMs) can diagnose the results (the ranking of the alternatives) in a decomposed style i.e., not only at one level of the hierarchy but also at the intermediate ones. Also, the developed approach allows a feedback transformation i.e., the collective final results of all experts are able to be transformed at any level of the extended linguistic hierarchy that each expert has previously used. Therefore, the ELH-ARAS technique makes it easier for decision-makers to understand the results. Finally, an MCGDM case study is given to illustrate the proposed approach.

Keywords: Additive ratio assessment, extended hierarchical linguistic, multi-criteria group decision making problems, multi granular linguistic contexts.

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5672 A Developmental Survey of Local Stereo Matching Algorithms

Authors: André Smith, Amr Abdel-Dayem

Abstract:

This paper presents an overview of the history and development of stereo matching algorithms. Details from its inception, up to relatively recent techniques are described, noting challenges that have been surmounted across these past decades. Different components of these are explored, though focus is directed towards the local matching techniques. While global approaches have existed for some time, and demonstrated greater accuracy than their counterparts, they are generally quite slow. Many strides have been made more recently, allowing local methods to catch up in terms of accuracy, without sacrificing the overall performance.

Keywords: Developmental survey, local stereo matching, stereo correspondence.

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5671 Inference of Stress-Strength Model for a Lomax Distribution

Authors: H. Panahi, S. Asadi

Abstract:

In this paper, the estimation of the stress-strength parameter R = P(Y < X), when X and Y are independent and both are Lomax distributions with the common scale parameters but different shape parameters is studied. The maximum likelihood estimator of R is derived. Assuming that the common scale parameter is known, the bayes estimator and exact confidence interval of R are discussed. Simulation study to investigate performance of the different proposed methods has been carried out.

Keywords: Stress-Strength model; maximum likelihoodestimator; Bayes estimator; Lomax distribution

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5670 Study on the Heat Transfer Performance of the Annular Fin under Condensing Conditions

Authors: Abdenour Bourabaa, Malika Fekih, Mohamed Saighi

Abstract:

A numerical investigation of the fin efficiency and temperature distribution of an annular fin under dehumidification has been presented in this paper. The non-homogeneous second order differential equation that describes the temperature distribution from the fin base to the fin tip has been solved using the central finite difference method. The effects of variations in parameters including relative humidity, air temperature, air face velocity on temperature distribution and fin efficiency are investigated and compared with those under fully dry fin conditions. Also, the effect of fin pitch on the dimensionless temperature has been studied.

Keywords: Annular fin, Dehumidification, Fin efficiency, Heat and mass transfer, Wet fin.

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5669 Bayes Net Classifiers for Prediction of Renal Graft Status and Survival Period

Authors: Jiakai Li, Gursel Serpen, Steven Selman, Matt Franchetti, Mike Riesen, Cynthia Schneider

Abstract:

This paper presents the development of a Bayesian belief network classifier for prediction of graft status and survival period in renal transplantation using the patient profile information prior to the transplantation. The objective was to explore feasibility of developing a decision making tool for identifying the most suitable recipient among the candidate pool members. The dataset was compiled from the University of Toledo Medical Center Hospital patients as reported to the United Network Organ Sharing, and had 1228 patient records for the period covering 1987 through 2009. The Bayes net classifiers were developed using the Weka machine learning software workbench. Two separate classifiers were induced from the data set, one to predict the status of the graft as either failed or living, and a second classifier to predict the graft survival period. The classifier for graft status prediction performed very well with a prediction accuracy of 97.8% and true positive values of 0.967 and 0.988 for the living and failed classes, respectively. The second classifier to predict the graft survival period yielded a prediction accuracy of 68.2% and a true positive rate of 0.85 for the class representing those instances with kidneys failing during the first year following transplantation. Simulation results indicated that it is feasible to develop a successful Bayesian belief network classifier for prediction of graft status, but not the graft survival period, using the information in UNOS database.

Keywords: Bayesian network classifier, renal transplantation, graft survival period, United Network for Organ Sharing

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5668 Increasing Power Transfer Capacity of Distribution Networks Using Direct Current Feeders

Authors: Akim Borbuev, Francisco de León

Abstract:

Economic and population growth in densely-populated urban areas introduce major challenges to distribution system operators, planers, and designers. To supply added loads, utilities are frequently forced to invest in new distribution feeders. However, this is becoming increasingly more challenging due to space limitations and rising installation costs in urban settings. This paper proposes the conversion of critical alternating current (ac) distribution feeders into direct current (dc) feeders to increase the power transfer capacity by a factor as high as four. Current trends suggest that the return of dc transmission, distribution, and utilization are inevitable. Since a total system-level transformation to dc operation is not possible in a short period of time due to the needed huge investments and utility unreadiness, this paper recommends that feeders that are expected to exceed their limits in near future are converted to dc. The increase in power transfer capacity is achieved through several key differences between ac and dc power transmission systems. First, it is shown that underground cables can be operated at higher dc voltage than the ac voltage for the same dielectric stress in the insulation. Second, cable sheath losses, due to induced voltages yielding circulation currents, that can be as high as phase conductor losses under ac operation, are not present under dc. Finally, skin and proximity effects in conductors and sheaths do not exist in dc cables. The paper demonstrates that in addition to the increased power transfer capacity utilities substituting ac feeders by dc feeders could benefit from significant lower costs and reduced losses. Installing dc feeders is less expensive than installing new ac feeders even when new trenches are not needed. Case studies using the IEEE 342-Node Low Voltage Networked Test System quantify the technical and economic benefits of dc feeders.

Keywords: Dc power systems, distribution feeders, distribution networks, energy efficiency, power transfer capacity.

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5667 The Differential Transform Method for Advection-Diffusion Problems

Authors: M. F. Patricio, P. M. Rosa

Abstract:

In this paper a class of numerical methods to solve linear and nonlinear PDEs and also systems of PDEs is developed. The Differential Transform method associated with the Method of Lines (MoL) is used. The theory for linear problems is extended to the nonlinear case, and a recurrence relation is established. This method can achieve an arbitrary high-order accuracy in time. A variable stepsize algorithm and some numerical results are also presented.

Keywords: Method of Lines, Differential Transform Method.

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5666 Performance Evaluation of Packet Scheduling with Channel Conditioning Aware Based On WiMAX Networks

Authors: Elmabruk Laias, Abdalla M. Hanashi, Mohammed Alnas

Abstract:

Worldwide Interoperability for Microwave Access (WiMAX) became one of the most challenging issues, since it was responsible for distributing available resources of the network among all users this leaded to the demand of constructing and designing high efficient scheduling algorithms in order to improve the network utilization, to increase the network throughput, and to minimize the end-to-end delay. In this study, the proposed algorithm focuses on an efficient mechanism to serve non_real time traffic in congested networks by considering channel status.

Keywords: WiMAX, Quality of Services (QoS), OPNE, Diff-Serv (DS).

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5665 Comparison of Multivariate Adaptive Regression Splines and Random Forest Regression in Predicting Forced Expiratory Volume in One Second

Authors: P. V. Pramila, V. Mahesh

Abstract:

Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients resulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF25, PEF, FEF25-75, FEF50 and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects) with the aforementioned input features. It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, as well as yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV1, Multivariate Adaptive Regression Splines Pulmonary Function Test, Random Forest.

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5664 Block Sorting: A New Characterization and a New Heuristic

Authors: Swapnoneel Roy, Ashok Kumar Thakur, Minhazur Rahman

Abstract:

The Block Sorting problem is to sort a given permutation moving blocks. A block is defined as a substring of the given permutation, which is also a substring of the identity permutation. Block Sorting has been proved to be NP-Hard. Until now two different 2-Approximation algorithms have been presented for block sorting. These are the best known algorithms for Block Sorting till date. In this work we present a different characterization of Block Sorting in terms of a transposition cycle graph. Then we suggest a heuristic, which we show to exhibit a 2-approximation performance guarantee for most permutations.

Keywords: Block Sorting, Optical Character Recognition, Genome Rearrangements, Sorting Primitives, ApproximationAlgorithms

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5663 Hospital Waste Management Practices: A Case Study in Iran

Authors: M. Farzadkia, S. Jorfi

Abstract:

Hospital waste is a category of waste consisting of infectious and non-infectious waste, which pose environmental and health risks. Therefore, special planning and management is required, due to the potential hazards of them. The lack of valid and comprehensive information regarding the generation and management of hospital waste in Iran is one of the most important problems in this field. This research aimed to evaluate hospital waste management efficiency in Karaj city, Iran. The four greatest hospitals in Karaj city had been selected in this cross-sectional study. Site observations and interviews with employees were implemented. The data was gathered based on the hospital waste management questionnaire which was designed by World Health Organization for developing countries. Collected Data had been analyzed using SPSS software. The average of solid waste which was generated per bed was 2.78 kg, which included 90% of domestic waste and 10% of infectious waste. Based on the quantitative analysis of general and infectious waste in these hospitals, the highest contributors of general waste were consisting of food waste (37.39%), while textile (28.06%) were the highest contributors of the infectious waste. According to the information contained in the questionnaires, the main defects of waste management in these hospitals were; inadequate staff in waste management sector, poorly disinfection of solid waste containers and temporary storage locations, and a lack of proper infectious waste treatment. According to the results of this research, waste management in these hospitals were far from optimum conditions. In order to improve the existing conditions, mentioned problems must be solved quickly, and planning for continuous monitoring in the waste management field in these hospitals should be established.

Keywords: Waste management, hospital wastes, solid wastes, Iran.

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5662 A Study of Neuro-Fuzzy Inference System for Gross Domestic Product Growth Forecasting

Authors: Ε. Giovanis

Abstract:

In this paper we present a Adaptive Neuro-Fuzzy System (ANFIS) with inputs the lagged dependent variable for the prediction of Gross domestic Product growth rate in six countries. We compare the results with those of Autoregressive (AR) model. We conclude that the forecasting performance of neuro-fuzzy-system in the out-of-sample period is much more superior and can be a very useful alternative tool used by the national statistical services and the banking and finance industry.

Keywords: Autoregressive model, Forecasting, Gross DomesticProduct, Neuro-Fuzzy

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5661 Designing Intelligent Adaptive Controller for Nonlinear Pendulum Dynamical System

Authors: R. Ghasemi, M. R. Rahimi Khoygani

Abstract:

This paper proposes the designing direct adaptive neural controller to apply for a class of a nonlinear pendulum dynamic system. The radial basis function (RBF) neural adaptive controller is robust in presence of external and internal uncertainties. Both the effectiveness of the controller and robustness against disturbances are importance of this paper. The simulation results show the promising performance of the proposed controller.

Keywords: Adaptive Neural Controller, Nonlinear Dynamical, Neural Network, RBF, Driven Pendulum, Position Control.

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5660 An Agent-Based Approach to Vehicle Routing Problem

Authors: Dariusz Barbucha, Piotr Jedrzejowicz

Abstract:

The paper proposes and validates a new method of solving instances of the vehicle routing problem (VRP). The approach is based on a multiple agent system paradigm. The paper contains the VRP formulation, an overview of the multiple agent environment used and a description of the proposed implementation. The approach is validated experimentally. The experiment plan and the discussion of experiment results follow.

Keywords: multi-agent systems, population-based methods, vehiclerouting problem.

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5659 Choosing R-tree or Quadtree Spatial DataIndexing in One Oracle Spatial Database System to Make Faster Showing Geographical Map in Mobile Geographical Information System Technology

Authors: Maruto Masserie Sardadi, Mohd Shafry bin Mohd Rahim, Zahabidin Jupri, Daut bin Daman

Abstract:

The latest Geographic Information System (GIS) technology makes it possible to administer the spatial components of daily “business object," in the corporate database, and apply suitable geographic analysis efficiently in a desktop-focused application. We can use wireless internet technology for transfer process in spatial data from server to client or vice versa. However, the problem in wireless Internet is system bottlenecks that can make the process of transferring data not efficient. The reason is large amount of spatial data. Optimization in the process of transferring and retrieving data, however, is an essential issue that must be considered. Appropriate decision to choose between R-tree and Quadtree spatial data indexing method can optimize the process. With the rapid proliferation of these databases in the past decade, extensive research has been conducted on the design of efficient data structures to enable fast spatial searching. Commercial database vendors like Oracle have also started implementing these spatial indexing to cater to the large and diverse GIS. This paper focuses on the decisions to choose R-tree and quadtree spatial indexing using Oracle spatial database in mobile GIS application. From our research condition, the result of using Quadtree and R-tree spatial data indexing method in one single spatial database can save the time until 42.5%.

Keywords: Indexing, Mobile GIS, MapViewer, Oracle SpatialDatabase.

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5658 Computational Assistance of the Research, Using Dynamic Vector Logistics of Processes for Critical Infrastructure Subjects Continuity

Authors: J. Urbánek Jiří, Krahulec Josef, Johanidesová Jitka, F. Urbánek Jiří

Abstract:

This paper deals with using of prevailing operation system MS Office (SmartArt...) for mathematical models, using DYVELOP (Dynamic Vector Logistics of Processes) method. It serves for crisis situations investigation and modelling within the organizations of critical infrastructure. In first part of paper, it will be introduced entities, operators, and actors of DYVELOP method. It uses just three operators of Boolean algebra and four types of the entities: the Environments, the Process Systems, the Cases, and the Controlling. The Process Systems (PrS) have five “brothers”: Management PrS, Transformation PrS, Logistic PrS, Event PrS and Operation PrS. The Cases have three “sisters”: Process Cell Case, Use Case, and Activity Case. They all need for the controlling of their functions special Ctrl actors, except ENV – it can do without Ctrl. Model´s maps are named the Blazons and they are able mathematically - graphically express the relationships among entities, actors and processes. In second part of this paper, the rich blazons of DYVELOP method will be used for the discovering and modelling of the cycling cases and their phases. The blazons need live PowerPoint presentation for better comprehension of this paper mission. The crisis management of energetic crisis infrastructure organization is obliged to use the cycles for successful coping of crisis situations. Several times cycling of these cases is necessary condition for the encompassment for both emergency events and the mitigation of organization´s damages. Uninterrupted and continuous cycling process brings for crisis management fruitfulness and it is good indicator and controlling actor of organizational continuity and its sustainable development advanced possibilities. The research reliable rules are derived for the safety and reliable continuity of energetic critical infrastructure organization in the crisis situation.

Keywords: Blazons, computational assistance, DYVELOP method, critical infrastructure.

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5657 Biodiesel Production from Soybean Oil over TiO2 Supported nano-ZnO

Authors: Mbala Mukenga, Edison Muzenda, Kalala Jalama, Reinout Meijboom

Abstract:

TiO2 supported nano-ZnO catalyst was prepared by deposition-precipitation and tested for the trans-esterification reaction of soybean oil to biodiesel. The TiO2 support stabilized the nano-ZnO in a dispersed form with limited crystallite size compared to the unsupported ZnO. The final ZnO dispersion and crystallite size and the material transfer resistance in the catalyst significantly influenced the supported nano-ZnO catalyst performance.

Keywords: nano-ZnO, soybean oil, TiO2, trans-esterification

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5656 Sensorless PM Motor with Multi Degree of Freedom Fuzzy Control

Authors: Faeka M. H. Khater, Farouk I. Ahmed, Mohamed I. Abu El- Sebah

Abstract:

This paper introduces application of multi degree of freedom fuzzy(MDOFF) controller in permanent magnet (PM)drive system. The drive system model is developed for FO control. Simulation of the system is carried out to predict the performance at NL and under load,. The results indicate that application of MDOFF controller is effective for sensorless PM drive system.

Keywords: Sensorless FO controller, PM drives system, MDOFF controller.

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5655 Analysis of Poverty Reduction Strategies as Mechanism for Development in Nigeria from 1999-2014

Authors: Ahmed Usman Egye, Hamza Muhammad

Abstract:

Poverty alleviation is one of the most difficult challenges facing third world countries in their development efforts. Evidences in Nigeria showed that the number of those in poverty has continued to increase. This paper is aimed at analyzing the performance of poverty alleviation measures undertaken by successive administrations in Nigeria with a view to addressing the quagmire. The study identified the whole gamut of factors that served as stumbling blocks to the implementation of each of the strategies and recommended the involvement of local people in the identification and design of projects so that sufficient participation could be achieved.

Keywords: Poverty, development, strategies, Nigeria.

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