Search results for: multiplicative weighted model

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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Authors: Mangesh R. Phate, V. H. Tatwawadi

Abstract:

This paper is intended to develop an artificial neural network (ANN) based model of material removal rate (MRR) in the turning of ferrous and nonferrous material in a Indian small-scale industry. MRR of the formulated model was proved with the testing data and artificial neural network (ANN) model was developed for the analysis and prediction of the relationship between inputs and output parameters during the turning of ferrous and nonferrous materials. The input parameters of this model are operator, work-piece, cutting process, cutting tool, machine and the environment.

The ANN model consists of a three layered feedforward back propagation neural network. The network is trained with pairs of independent/dependent datasets generated when machining ferrous and nonferrous material. A very good performance of the neural network, in terms of contract with experimental data, was achieved. The model may be used for the testing and forecast of the complex relationship between dependent and the independent parameters in turning operations.

Keywords: Field data based model, Artificial neural network, Simulation, Convectional Turning, Material removal rate.

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Authors: Mazhar B. Tayel, Amr H. Yassin

Abstract:

A proposed small-signal model parameters for a pseudomorphic high electron mobility transistor (PHEMT) is presented. Both extrinsic and intrinsic circuit elements of a smallsignal model are determined using genetic algorithm (GA) as a stochastic global search and optimization tool. The parameters extraction of the small-signal model is performed on 200-μm gate width AlGaAs/InGaAs PHEMT. The equivalent circuit elements for a proposed 18 elements model are determined directly from the measured S- parameters. The GA is used to extract the parameters of the proposed small-signal model from 0.5 up to 18 GHz.

Keywords: PHEMT, Genetic Algorithms, small signal modeling, optimization.

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Authors: Omar Boutkhoum, Mohamed Hanine, Abdessadek Bendarag

Abstract:

Sustainable economic growth is nowadays driving firms to extend toward the adoption of many green supply chain management (GSCM) solutions. However, the evaluation and selection of these solutions is a matter of concern that needs very serious decisions, involving complexity owing to the presence of various associated factors. To resolve this problem, a comparative analysis approach based on multi-criteria decision-making methods is proposed for adequate evaluation of sustainable supply chain management solutions. In the present paper, we propose an integrated decision-making model based on FAHP (Fuzzy Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) to contribute to a better understanding and development of new sustainable strategies for industrial organizations. Due to the varied importance of the selected criteria, FAHP is used to identify the evaluation criteria and assign the importance weights for each criterion, while TOPSIS and PROMETHEE methods employ these weighted criteria as inputs to evaluate and rank the alternatives. The main objective is to provide a comparative analysis based on TOPSIS and PROMETHEE processes to help make sound and reasoned decisions related to the selection problem of GSCM solution.

Keywords: GSCM solutions, multi-criteria analysis, FAHP, TOPSIS, PROMETHEE, decision support system.

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Authors: Yung C. Ho, Hui C. Fang, Ming J. Hsieh

Abstract:

When consistently innovative business-models can give companies a competitive advantage, longitudinal empirical research, which can reflect dynamic business-model changes, has yet to prove a definitive connection. This study consequently employs a dynamic perspective in conjunction with innovation theory to examine the relationship between the types of business-model innovation and firm value. This study tries to examine various types of business-model innovation in high-end and low-end technology industries such as HTC and the 7-Eleven chain stores with research periods of 14 years and 32 years, respectively. The empirical results suggest that adopting radical business-model innovation in addition to expanding new target markets can successfully lead to a competitive advantage. Sustained advanced technological competences and service/product innovation are the key successful factors in high-end and low-end technology industry business-models respectively. In sum up, the business-model innovation can yield a higher market value and financial value in high-end technology industries than low-end ones.

Keywords: Business-model, Dynamic Perspective, Firm Value, Innovation

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Authors: Karel Frajtak, Miroslav Bures, Ivan Jelinek

Abstract:

Software testing is important stage of software development cycle. Current testing process involves tester and electronic documents with test case scenarios. In this paper we focus on new approach to testing process using automated test case generation and tester guidance through the system based on the model of the system. Test case generation and model-based testing is not possible without proper system model. We aim on providing better feedback from the testing process thus eliminating the unnecessary paper work.

Keywords: Model based testing, test automation, test generating, tester support.

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Authors: Jānis Zuters

Abstract:

There are a lot of extensions made to the classic model of multi-layer perceptron (MLP). A notable amount of them has been designed to hasten the learning process without considering the quality of generalization. The paper proposes a new MLP extension based on exploiting topology of the input layer of the network. Experimental results show the extended model to improve upon generalization capability in certain cases. The new model requires additional computational resources to compare to the classic model, nevertheless the loss in efficiency isn-t regarded to be significant.

Keywords: Learning algorithm, multi-layer perceptron, topology.

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Authors: Mohamed M. El-Gendy, Ibrahim A. El-Arabi, Rafik W. Abdel-Missih, Omar A. Kandil

Abstract:

In the present research, a finite element model is presented to study the geometrical and material nonlinear behavior of reinforced concrete plane frames considering soil-structure interaction. The nonlinear behaviors of concrete and reinforcing steel are considered both in compression and tension up to failure. The model takes account also for the number, diameter, and distribution of rebar along every cross section. Soil behavior is taken into consideration using four different models; namely: linear-, nonlinear Winkler's model, and linear-, nonlinear continuum model. A computer program (NARC) is specially developed in order to perform the analysis. The results achieved by the present model show good agreement with both theoretical and experimental published literature. The nonlinear behavior of a rectangular frame resting on soft soil up to failure using the proposed model is introduced for demonstration.

Keywords: Nonlinear analysis, Geometric nonlinearity, Material nonlinearity, Reinforced concrete, Finite element method, Soilstructure interaction, Winkler's soil model, Continuum soil model

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Authors: Muhammad T. Alam, Zheng Da Wu

Abstract:

In this research, we propose a weighted class based queuing (WCBQ) mechanism to provide class differentiation and to reduce the load for the IMS (IP Multimedia Subsystem) presence server (PS). The tasks of admission controller for the PS are demonstrated. Analysis and simulation models are developed to quantify the performance of WCBQ scheme. An optimized dropping time frame has been developed based on which some of the preexisting messages are dropped from the PS-buffer. Cost functions are developed and simulation comparison has been performed with FCFS (First Come First Served) scheme. The results show that the PS benefits significantly from the proposed queuing and dropping algorithm (WCBQ) during heavy traffic.

Keywords: Admission control, presence, queuing.

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Authors: F. Achouri, K. Chouicha

Abstract:

The main parameters affecting the workability are the water content, particle size, and the total surface of the grains, as long as the mixing water begins by wetting the surface of the grains and then fills the voids between the grains to form entrapped water, the quantity of water remaining is called free water. The aim of this study is to undertake a fractal approach through the relationship between the concrete formulation parameters and workability. To develop this approach a series of concrete taken from the literature was investigated by varying formulation parameters such as G/S, the quantity of cement C and the quantity of water W. We also call another model as the model of water layer thickness and model of paste layer thickness to judge their relevance, hence the following results: the relevance of the water layer thickness model is considered as a relevant when there is a variation in the water quantity. The model of the paste layer thickness is only applicable if we considered that the paste is made with the grain value Dmax = 2.85: value from which we see a stability of the model.

Keywords: Concrete, fractal method, paste layer thickness, water layer thickness, workability.

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Authors: Iqbal Hossain, Dr. Monzur Imteaz, Dr. Shirley Gato-Trinidad, Prof. Abdallah Shanableh

Abstract:

Estimation of runoff water quality parameters is required to determine appropriate water quality management options. Various models are used to estimate runoff water quality parameters. However, most models provide event-based estimates of water quality parameters for specific sites. The work presented in this paper describes the development of a model that continuously simulates the accumulation and wash-off of water quality pollutants in a catchment. The model allows estimation of pollutants build-up during dry periods and pollutants wash-off during storm events. The model was developed by integrating two individual models; rainfall-runoff model, and catchment water quality model. The rainfall-runoff model is based on the time-area runoff estimation method. The model allows users to estimate the time of concentration using a range of established methods. The model also allows estimation of the continuing runoff losses using any of the available estimation methods (i.e., constant, linearly varying or exponentially varying). Pollutants build-up in a catchment was represented by one of three pre-defined functions; power, exponential, or saturation. Similarly, pollutants wash-off was represented by one of three different functions; power, rating-curve, or exponential. The developed runoff water quality model was set-up to simulate the build-up and wash-off of total suspended solids (TSS), total phosphorus (TP) and total nitrogen (TN). The application of the model was demonstrated using available runoff and TSS field data from road and roof surfaces in the Gold Coast, Australia. The model provided excellent representation of the field data demonstrating the simplicity yet effectiveness of the proposed model.

Keywords: Catchment, continuous pollutants build-up, pollutants wash-off, runoff, runoff water quality model.

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Authors: Sarah Motiee, Azadeh Nematzadeh, Mehrnoush Shamsfard

Abstract:

Increasing growth of information volume in the internet causes an increasing need to develop new (semi)automatic methods for retrieval of documents and ranking them according to their relevance to the user query. In this paper, after a brief review on ranking models, a new ontology based approach for ranking HTML documents is proposed and evaluated in various circumstances. Our approach is a combination of conceptual, statistical and linguistic methods. This combination reserves the precision of ranking without loosing the speed. Our approach exploits natural language processing techniques to extract phrases from documents and the query and doing stemming on words. Then an ontology based conceptual method will be used to annotate documents and expand the query. To expand a query the spread activation algorithm is improved so that the expansion can be done flexible and in various aspects. The annotated documents and the expanded query will be processed to compute the relevance degree exploiting statistical methods. The outstanding features of our approach are (1) combining conceptual, statistical and linguistic features of documents, (2) expanding the query with its related concepts before comparing to documents, (3) extracting and using both words and phrases to compute relevance degree, (4) improving the spread activation algorithm to do the expansion based on weighted combination of different conceptual relationships and (5) allowing variable document vector dimensions. A ranking system called ORank is developed to implement and test the proposed model. The test results will be included at the end of the paper.

Keywords: Document ranking, Ontology, Spread activation algorithm, Annotation.

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Authors: Svetlana Saksonova

Abstract:

Every commercial bank optimises its asset portfolio depending on the profitability of assets and chosen or imposed constraints. This paper proposes and applies a stylized model for optimising banks' asset and liability structure, reflecting profitability of different asset categories and their risks as well as costs associated with different liability categories and reserve requirements. The level of detail for asset and liability categories is chosen to create a suitably parsimonious model and to include the most important categories in the model. It is shown that the most appropriate optimisation criterion for the model is the maximisation of the ratio of net interest income to assets. The maximisation of this ratio is subject to several constraints. Some are accounting identities or dictated by legislative requirements; others vary depending on the market objectives for a particular bank. The model predicts variable amount of assets allocated to loan provision.

Keywords: asset structure, commercial bank, model, optimisation

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Authors: Shih-Ching Lo

Abstract:

Discrete choice model is the most used methodology for studying traveler-s mode choice and demand. However, to calibrate the discrete choice model needs to have plenty of questionnaire survey. In this study, an aggregative model is proposed. The historical data of passenger volumes for high speed rail and domestic civil aviation are employed to calibrate and validate the model. In this study, different models are compared so as to propose the best one. From the results, systematic equations forecast better than single equation do. Models with the external variable, which is oil price, are better than models based on closed system assumption.

Keywords: forecasting, passenger volume, dynamic competition model, external variable, oil price

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Authors: I. Zohourkari, M. Zohoor

Abstract:

In this paper, an erosion-based model for abrasive waterjet (AWJ) turning process is presented. By using modified Hashish erosion model, the volume of material removed by impacting of abrasive particles to surface of the rotating cylindrical specimen is estimated and radius reduction at each rotation is calculated. Different to previous works, the proposed model considers the continuous change in local impact angle due to change in workpiece diameter, axial traverse rate of the jet, the abrasive particle roundness and density. The accuracy of the proposed model is examined by experimental tests under various traverse rates. The final diameters estimated by the proposed model are in good accordance with experiments.

Keywords: Abrasive, Erosion, impact, Particle, Waterjet, Turning.

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Authors: Yan Shuang Zhang, Taehan Lee, Byung Ho Jeong

Abstract:

A DEA model can generally evaluate the performance using multiple inputs and outputs for the same period. However, it is hard to avoid the production lead time phenomenon some times, such as long-term project or marketing activity. A couple of models have been suggested to capture this time lag issue in the context of DEA. This paper develops a dual-MPO model to deal with time lag effect in evaluating efficiency. A numerical example is also given to show that the proposed model can be used to get efficiency and reference set of inefficient DMUs and to obtain projected target value of input attributes for inefficient DMUs to be efficient.

Keywords: DEA, efficiency, time lag, dual problem.

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Authors: Jagadish H. Pujar, Pallavi S. Gurjal, Shambhavi D. S, Kiran S. Kunnur

Abstract:

Medical image segmentation based on image smoothing followed by edge detection assumes a great degree of importance in the field of Image Processing. In this regard, this paper proposes a novel algorithm for medical image segmentation based on vigorous smoothening by identifying the type of noise and edge diction ideology which seems to be a boom in medical image diagnosis. The main objective of this algorithm is to consider a particular medical image as input and make the preprocessing to remove the noise content by employing suitable filter after identifying the type of noise and finally carrying out edge detection for image segmentation. The algorithm consists of three parts. First, identifying the type of noise present in the medical image as additive, multiplicative or impulsive by analysis of local histograms and denoising it by employing Median, Gaussian or Frost filter. Second, edge detection of the filtered medical image is carried out using Canny edge detection technique. And third part is about the segmentation of edge detected medical image by the method of Normalized Cut Eigen Vectors. The method is validated through experiments on real images. The proposed algorithm has been simulated on MATLAB platform. The results obtained by the simulation shows that the proposed algorithm is very effective which can deal with low quality or marginal vague images which has high spatial redundancy, low contrast and biggish noise, and has a potential of certain practical use of medical image diagnosis.

Keywords: Image Segmentation, Image smoothing, Edge Detection, Impulsive noise, Gaussian noise, Median filter, Canny edge, Eigen values, Eigen vector.

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Authors: R. Sammoura

Abstract:

In Lebanon, public construction projects are awarded to the contractor submitting the lowest bid price based on a competitive bidding process. The contractor has to make a strategic decision in choosing the appropriate bid price that will offer a satisfactory profit with a greater probability to win. A simulation model for bid price decision making based on the lowest bid price evaluation is developed. The model, built using Crystal Ball decisionengineering software, considers two main factors affecting the bidding process: the number of qualified bidders and the size of the project. The validity of the model is tested on twelve separate projects. The study also shows how to use the model to conduct risk analysis and help any specific contractor to decide on his bid price with associated certainty level in a scientific method.

Keywords: Bid price, Competition, Decision making, Simulation.

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Authors: P. Pongsumpun

Abstract:

One of the important tropical diseases is Chikunkunya. This disease is transmitted between the human by the insect-borne virus, of the genus Alphavirus. It occurs in Africa, Asia and the Indian subcontinent. In Thailand, the incidences due to this disease are increasing every year. In this study, the transmission of this disease is studied through dynamical model analysis.

Keywords: Chikunkunya, dynamical model, Endemic region, Routh-Hurwitz criteria.

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Authors: Nam Lethanh, Bryan T. Adey

Abstract:

In this paper, the potential use of an exponential hidden Markov model to model a hidden pavement deterioration process, i.e. one that is not directly measurable, is investigated. It is assumed that the evolution of the physical condition, which is the hidden process, and the evolution of the values of pavement distress indicators, can be adequately described using discrete condition states and modeled as a Markov processes. It is also assumed that condition data can be collected by visual inspections over time and represented continuously using an exponential distribution. The advantage of using such a model in decision making process is illustrated through an empirical study using real world data.

Keywords: Deterioration modeling, Exponential distribution, Hidden Markov model, Pavement management

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Authors: Julio Kauss, Miguel Cadillo, David Mauricio

Abstract:

E-commerce is a business model that allows companies to optimize the processes of buying, selling, transferring goods and exchanging services through computer networks or the Internet. In Peru, the electronic commerce is used infrequently. This situation is due, in part to the fact that there is no model that allows companies to implement an e-commerce solution, which means that most SMEs do not have adequate knowledge to adapt to electronic commerce. In this work, a reference model is proposed for the implementation of an e-commerce solution in Peruvian SMEs in the retail sector. It consists of five phases: Business Analysis, Business Modeling, Implementation, Post Implementation and Results. The present model was validated in a SME of the Peruvian retail sector through the implementation of an electronic commerce platform, through which the company increased its sales through the delivery channel by 10% in the first month of deployment. This result showed that the model is easy to implement, is economical and agile. In addition, it allowed the company to increase its business offer, adapt to e-commerce and improve customer loyalty.

Keywords: E-commerce, retail, SMEs, reference model.

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Authors: Do-Jin Jang, Sung-Ah Kim

Abstract:

In designing a kinetic façade, it is hard for the designer to make digital models due to its complex geometry with motion. This paper aims to present a methodology of converting a point cloud of a physical model into a single digital model with a certain topology and motion. The method uses a Microsoft Kinect sensor, and color markers were defined and applied to three paper folding-inspired designs. Although the resulted digital model cannot represent the whole folding range of the physical model, the method supports the designer to conduct a performance-oriented design process with the rough physical model in the reduced folding range.

Keywords: Design media, kinetic façades, tangible user interface, 3D scanning.

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Authors: Mehrnoush Shamsfard, Azadeh Nematzadeh, Sarah Motiee

Abstract:

Increasing growth of information volume in the internet causes an increasing need to develop new (semi)automatic methods for retrieval of documents and ranking them according to their relevance to the user query. In this paper, after a brief review on ranking models, a new ontology based approach for ranking HTML documents is proposed and evaluated in various circumstances. Our approach is a combination of conceptual, statistical and linguistic methods. This combination reserves the precision of ranking without loosing the speed. Our approach exploits natural language processing techniques for extracting phrases and stemming words. Then an ontology based conceptual method will be used to annotate documents and expand the query. To expand a query the spread activation algorithm is improved so that the expansion can be done in various aspects. The annotated documents and the expanded query will be processed to compute the relevance degree exploiting statistical methods. The outstanding features of our approach are (1) combining conceptual, statistical and linguistic features of documents, (2) expanding the query with its related concepts before comparing to documents, (3) extracting and using both words and phrases to compute relevance degree, (4) improving the spread activation algorithm to do the expansion based on weighted combination of different conceptual relationships and (5) allowing variable document vector dimensions. A ranking system called ORank is developed to implement and test the proposed model. The test results will be included at the end of the paper.

Keywords: Document ranking, Ontology, Spread activation algorithm, Annotation.

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Authors: Faraj El Dabee, Romeo Marian, Yousef Amer

Abstract:

This paper implements the inventory model developed in the first part of this paper in a simplified problem to simultaneously reduce costs and risks in JIT systems. This model is developed to ascertain an optimal ordering strategy for procuring raw materials by using regular multi-external and local backup suppliers to reduce the total cost of the products, and at the same time to reduce the risks arising from this cost reduction within production systems. A comparison between the cost of using the JIT system and using the proposed inventory model shows the superiority of the use of the inventory model.

Keywords: Lean manufacturing, Just-in-Time (JIT), production system, cost-risk reduction, inventory model, eternal supplier, local backup supplier.

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Authors: Nastaran Hajiheydari, Mohammad Soltani Delgosha

Abstract:

Vendor (supplier) selection is a group decision-making (GDM) process, in which, based on some predetermined criteria, the experts’ preferences are provided in order to rank and choose the most desirable suppliers. In the real business environment, our attitudes or our choices would be made in an uncertain and indecisive situation could not be expressed in a crisp framework. Intuitionistic fuzzy sets (IFSs) could handle such situations in the best way. VIKOR method was developed to solve multi-criteria decision-making (MCDM) problems. This method, which is used to determine the compromised feasible solution with respect to the conflicting criteria, introduces a multi-criteria ranking index based on the particular measure of 'closeness' to the 'ideal solution'. Until now, there has been a little investigation of VIKOR with IFS, therefore we extended the intuitionistic fuzzy (IF) VIKOR to solve vendor selection problem under IF GDM environment. The present study intends to develop an IF VIKOR method in a GDM situation. Therefore, a model is presented to calculate the criterion weights based on entropy measure. Then, the interval-valued intuitionistic fuzzy weighted geometric (IFWG) operator utilized to obtain the total decision matrix. In the next stage, an approach based on the positive idle intuitionistic fuzzy number (PIIFN) and negative idle intuitionistic fuzzy number (NIIFN) was developed. Finally, the application of the proposed method to solve a vendor selection problem illustrated.

Keywords: Group decision making, intuitionistic fuzzy entropy measure, intuitionistic fuzzy set, vendor selection VIKOR.

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Authors: Jaroslav Krutil, František Pochylý, Simona Fialová

Abstract:

The article presents two mathematical models of the interaction between a rotating shaft and an incompressible fluid. The mathematical model includes both the journal bearings and the axially traversed hydrodynamic sealing gaps of hydraulic machines. A method is shown for the identification of additional effects of the fluid acting on the rotor of the machine, both for a linear and a nonlinear model. The interaction is expressed by matrices of mass, stiffness and damping.

Keywords: CFD modeling, hydrodynamic gap, matrices of mass, stiffness and damping, nonlinear mathematical model.

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Authors: Ersin Kaya, Bulent Oran, Ahmet Arslan

Abstract:

In this study, fuzzy rule-based classifier is used for the diagnosis of congenital heart disease. Congenital heart diseases are defined as structural or functional heart disease. Medical data sets were obtained from Pediatric Cardiology Department at Selcuk University, from years 2000 to 2003. Firstly, fuzzy rules were generated by using medical data. Then the weights of fuzzy rules were calculated. Two different reasoning methods as “weighted vote method" and “singles winner method" were used in this study. The results of fuzzy classifiers were compared.

Keywords: Congenital heart disease, Fuzzy rule-basedclassifiers, Classification

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Authors: R. Pääkkönen, L. Korpinen, F. Gobba

Abstract:

The objective of our study is to investigate UV exposure in Finland through sample measurements as a typical case study in summer and winter. We measured UV-BC weighted radiation and calculated a daily dose, which is about 100–150 times the Finnish exposure limit value in summer and 1–6 times in winter. The measured ultraviolet indices varied from 0 to 7 (scale 0–18), which is less than the values obtained in countries that are located farther south from Tampere latitude of 61 degrees. In wintertime, the UV exposure was modest compared to summertime, 50–150 mW/m² and about 1–5 mW/m² in summer and winter, respectively. However, technical means to manage UV exposure in Scandinavia are also needed in summer- and springtime.

Keywords: Ultraviolet radiation, measurement, winter, summer.

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

Abstract:

We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior distribution for various parameters and latent function by using the variational Bayesian approximations and important sampling method, and next we derived a predictive distribution of latent function needed to classify new samples. The proposed model is applied to classify the synthetic multivariate dataset in order to verify the performance of our model. Experiment result shows that our model is more accurate than the other approximation methods.

Keywords: Multinomial dirichlet classification model, Gaussian process priors, variational Bayesian approximation, Importance sampling, approximate posterior distribution, Marginal likelihood evidence.

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Authors: H.Hosseini, A.A. Azemati

Abstract:

The fundamental defect inherent to the thermoforming technology is wall-thickness variation of the products due to inadequate thermal processing during production of polymer. A nonlinear viscoelastic rheological model is implemented for developing the process model. This model describes deformation process of a sheet in thermoforming process. Because of relaxation pause after plug-assist stage and also implementation of two stage thermoforming process have minor wall-thickness variation and consequently better mechanical properties of polymeric articles. For model validation, a comparative analysis of the theoretical and experimental data is presented.

Keywords: High-quality polymeric article, Thermal Processing, Rheological model, Minor wall-thickness variation.

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