Search results for: Gaussian Mixture Model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7907

Search results for: Gaussian Mixture Model

7427 Validity Domains of Beams Behavioural Models: Efficiency and Reduction with Artificial Neural Networks

Authors: Keny Ordaz-Hernandez, Xavier Fischer, Fouad Bennis

Abstract:

In a particular case of behavioural model reduction by ANNs, a validity domain shortening has been found. In mechanics, as in other domains, the notion of validity domain allows the engineer to choose a valid model for a particular analysis or simulation. In the study of mechanical behaviour for a cantilever beam (using linear and non-linear models), Multi-Layer Perceptron (MLP) Backpropagation (BP) networks have been applied as model reduction technique. This reduced model is constructed to be more efficient than the non-reduced model. Within a less extended domain, the ANN reduced model estimates correctly the non-linear response, with a lower computational cost. It has been found that the neural network model is not able to approximate the linear behaviour while it does approximate the non-linear behaviour very well. The details of the case are provided with an example of the cantilever beam behaviour modelling.

Keywords: artificial neural network, validity domain, cantileverbeam, non-linear behaviour, model reduction.

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7426 MPC of Single Phase Inverter for PV System

Authors: Irtaza M. Syed, Kaamran Raahemifar

Abstract:

This paper presents a model predictive control (MPC) of a utility interactive (UI) single phase inverter (SPI) for a photovoltaic (PV) system at residential/distribution level. The proposed model uses single-phase phase locked loop (PLL) to synchronize SPI with the grid and performs MPC control in a dq reference frame. SPI model consists of boost converter (BC), maximum power point tracking (MPPT) control, and a full bridge (FB) voltage source inverter (VSI). No PI regulators to tune and carrier and modulating waves are required to produce switching sequence. Instead, the operational model of VSI is used to synthesize sinusoidal current and track the reference. Model is validated using a three kW PV system at the input of UI-SPI in Matlab/Simulink. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: Matlab/Simulink, Model Predictive Control, Phase Locked Loop, Single Phase Inverter, Voltage Source Inverter.

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7425 An Experimental Study on the Effect of EGR and Engine Speed on CO and HC Emissions of Dual Fuel HCCI Engine

Authors: M. Ghazikhani, M. R. Kalateh, Y. K. Toroghi, M. Dehnavi

Abstract:

In this study, effects of EGR on CO and HC emissions of a dual fuel HCCI-DI engine are investigated. Tests were conducted on a single-cylinder variable compression ratio (VCR) diesel engine with compression ratio of 17.5. Premixed gasoline is provided by a carburetor connected to intake manifold and equipped with a screw to adjust premixed air-fuel ratio, and diesel fuel is injected directly into the cylinder through an injector at pressure of 250 bars. A heater placed at inlet manifold is used to control the intake charge temperature. Optimal intake charge temperature was 110-115ºC due to better formation of a homogeneous mixture causing HCCI combustion. Timing of diesel fuel injection has a great effect on stratification of in-cylinder charge in HCCI combustion. Experiments indicated 35 BTDC as the optimum injection timing. Coolant temperature was maintained 50ºC during the tests. Results show that increasing engine speed at a constant EGR rate leads to increase in CO and UHC emissions due to the incomplete combustion caused by shorter combustion duration and less homogeneous mixture. Results also show that increasing EGR reduces the amount of oxygen and leads to incomplete combustion and therefore increases CO emission due to lower combustion temperature. HC emission also increases as a result of lower combustion temperatures.

Keywords: Dual fuel HCCI engine, EGR, engine speed, CO andUHC emissions.

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7424 Model of Appropriate Science Teaching for Mathayomsuksa 3 (Grade 9) in Ang-Thong Province

Authors: Lertlop, W

Abstract:

This research aims to study the appropriate model of Science teaching for students, academic achievement and to survey students- attitudes toward using appropriate for students in Mathayomsuksa 3 in Ang-Thong province. The research results were as follows: 1. The appropriate model of Science teaching for Mathayomsuksa 3 students in Ang-Thong province including these following five steps: Step 1. The introduction of the lessons. Step 2. Setting the hypothesis. Step 3. Doing the experiment /survey. Step 4. Making conclusion. Step 5. Applying to daily life or other subjects. 2. There is no significant difference between using appropriate model teaching and regular teaching at 0.05 level significant difference. 3. There is a significant difference between before and after teaching using appropriate model of Science teaching at 0.05 level. 4. The satisfaction of students- attitudes to using the appropriate model of Science teaching for students was in intermediate level.

Keywords: Pedagogy, science teaching model, Ang-Thong province.

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7423 Knowledge Management Model for Research Projects Masters Program

Authors: Víctor Hugo Medina García, Darío Alejandro Segura Torres

Abstract:

This paper presents the adaptation of the knowledge management model and intellectual capital measurement NOVA to the needs of work or research project must be developed when conducting a program of graduate-level master. Brackets are added in each of the blocks which is represented in the original model NOVA and which allows to represent those involved in each of these.

Keywords: Knowledge management, masters programs, Nova model, research projects

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7422 Toward a Risk Assessment Model Based On Multi-Agent System for Cloud Consumer

Authors: Saadia Drissi, Siham Benhadou, Hicham Medromi

Abstract:

The cloud computing is an innovative paradigm that introduces several changes in technology that have resulted a new ways for cloud providers to deliver their services to cloud consumers mainly in term of security risk assessment, thus, adapting a current risk assessment tools to cloud computing is a very difficult task due to its several characteristics that challenge the effectiveness of risk assessment approaches. As consequence, there is a need of risk assessment model adapted to cloud computing. This paper requires a new risk assessment model based on multi-agent system and AHP model as fundamental steps towards the development of flexible risk assessment approach regarding cloud consumers.

Keywords: Cloud computing, risk assessment model, multi-agent system, AHP model, cloud consumer.

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7421 Effects of Sole and Integrated Application of Cocoa Pod Ash and Poultry Manure on Soil Properties and Leaf Nutrient Composition and Performance of White Yam

Authors: T. M. Agbede, A. O. Adekiya

Abstract:

Field experiments were conducted during 2013, 2014 and 2015 cropping seasons at Rufus Giwa Polytechnic, Owo, Ondo State, southwest Nigeria. The objective of the investigation was to determine the effect of Cocoa Pod Ash (CPA) and Poultry Manure (PM) applied solely and their combined form, as sources of fertilizers on soil properties, leaf nutrient composition, growth and yield of yam. Three soil amendments: CPA, PM (sole forms), CPA and PM (mixture), were applied at 20 t ha-1 with an inorganic fertilizer (NPK 15-15-15) at 400 kg ha-1 as a reference and a natural soil fertility, NSF (control). The five treatments were arranged in a randomized complete block design with three replications. The test soil was slightly acidic, low in organic carbon (OC), N, P, K, Ca and Mg. Results showed that soil amendments significantly increased (p = 0.05) tuber weights and growth of yam, soil and leaf N, P, K, Ca and Mg, soil pH and OC concentrations compared with the NSF (control). The mixture of CPA+PM treatment increased tuber weights of yam by 36%, compared with inorganic fertilizer (NPK) and 19%, compared with PM alone. Sole PM increased tuber weight of yam by 15%, compared with NPK. Sole or mixed forms of soil amendments showed remarkable improvement in soil physical properties, nutrient availability, compared with NPK and the NSF (control). Integrated application of CPA at 10 t ha-1 + PM at 10 t ha-1 was the most effective treatment in improving soil physical properties, increasing nutrient availability and yam performance than sole application of any of the fertilizer materials.

Keywords: Cocoa pod ash, leaf nutrient composition, poultry manure, soil properties, yam.

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7420 2D and 3D Unsteady Simulation of the Heat Transfer in the Sample during Heat Treatment by Moving Heat Source

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

Abstract:

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

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

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7419 External Effects on Dynamic Competitive Model of Domestic Airline and High Speed Rail

Authors: Shih-Ching Lo, Yu-Ping Liao

Abstract:

Social-economic variables influence transportation demand largely. Analyses of discrete choice model consider social-economic variables to study traveler-s mode choice and demand. However, to calibrate the discrete choice model needs to have plenty of questionnaire survey. Also, 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, models with different social-economic variables, which are oil price, GDP per capita, CPI and economic growth rate, are compared. From the results, the model with the oil price is better than models with the other social-economic variables.

Keywords: forecasting, passenger volume, dynamic competitive model, social-economic variables, oil price.

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7418 Optimal Control of Volterra Integro-Differential Systems Based On Legendre Wavelets and Collocation Method

Authors: Khosrow Maleknejad, Asyieh Ebrahimzadeh

Abstract:

In this paper, the numerical solution of optimal control problem (OCP) for systems governed by Volterra integro-differential (VID) equation is considered. The method is developed by means of the Legendre wavelet approximation and collocation method. The properties of Legendre wavelet together with Gaussian integration method are utilized to reduce the problem to the solution of nonlinear programming one. Some numerical examples are given to confirm the accuracy and ease of implementation of the method.

Keywords: Collocation method, Legendre wavelet, optimal control, Volterra integro-differential equation.

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7417 Removal of Cationic Heavy Metal and HOC from Soil-Washed Water Using Activated Carbon

Authors: Chi Kyu Ahn, Young Mi Kim, Seung Han Woo, Jong Moon Park

Abstract:

Soil washing process with a surfactant solution is a potential technology for the rapid removal of hydrophobic organic compound (HOC) from soil. However, large amount of washed water would be produced during operation and this should be treated effectively by proper methods. The soil washed water for complex contaminated site with HOC and heavy metals might contain high amount of pollutants such as HOC and heavy metals as well as used surfactant. The heavy metals in the soil washed water have toxic effects on microbial activities thus these should be removed from the washed water before proceeding to a biological waste-water treatment system. Moreover, the used surfactant solutions are necessary to be recovered for reducing the soil washing operation cost. In order to simultaneously remove the heavy metals and HOC from soil-washed water, activated carbon (AC) was used in the present study. In an anionic-nonionic surfactant mixed solution, the Cd(II) and phenanthrene (PHE) were effectively removed by adsorption on activated carbon. The removal efficiency for Cd(II) was increased from 0.027 mmol-Cd/g-AC to 0.142 mmol-Cd/g-AC as the mole ratio of SDS increased in the presence of PHE. The adsorptive capacity of PHE was also increased according to the SDS mole ratio due to the decrement of molar solubilization ratios (MSR) for PHE in an anionic-nonionic surfactant mixture. The simultaneous adsorption of HOC and cationic heavy metals using activated carbon could be a useful method for surfactant recovery and the reduction of heavy metal toxicity in a surfactant-enhanced soil washing process.

Keywords: Activated carbon, Anionic-nonionic surfactant mixture, Cationic heavy metal, HOC, Soil washing

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7416 Javanese Character Recognition Using Hidden Markov Model

Authors: Anastasia Rita Widiarti, Phalita Nari Wastu

Abstract:

Hidden Markov Model (HMM) is a stochastic method which has been used in various signal processing and character recognition. This study proposes to use HMM to recognize Javanese characters from a number of different handwritings, whereby HMM is used to optimize the number of state and feature extraction. An 85.7 % accuracy is obtained as the best result in 16-stated vertical model using pure HMM. This initial result is satisfactory for prompting further research.

Keywords: Character recognition, off-line handwritingrecognition, Hidden Markov Model.

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7415 Self-tuned LMS Algorithm for Sinusoidal Time Delay Tracking

Authors: Jonah Gamba

Abstract:

In this paper the problem of estimating the time delay between two spatially separated noisy sinusoidal signals by system identification modeling is addressed. The system is assumed to be perturbed by both input and output additive white Gaussian noise. The presence of input noise introduces bias in the time delay estimates. Normally the solution requires a priori knowledge of the input-output noise variance ratio. We utilize the cascade of a self-tuned filter with the time delay estimator, thus making the delay estimates robust to input noise. Simulation results are presented to confirm the superiority of the proposed approach at low input signal-to-noise ratios.

Keywords: LMS algorithm, Self-tuned filter, Systemidentification, Time delay estimation, .

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7414 Analytical Model to Predict the Shear Capacity of Reinforced Concrete Beams Externally Strengthened with CFRP Composites Conditions

Authors: Rajai Al-Rousan

Abstract:

This paper presents a proposed analytical model for predicting the shear strength of reinforced concrete beams strengthened with CFRP composites as external reinforcement. The proposed analytical model can predict the shear contribution of CFRP composites of RC beams with an acceptable coefficient of correlation with the tested results. Based on the comparison of the proposed model with the published well-known models (ACI model, Triantafillou model, and Colotti model), the ACI model had a wider range of 0.16 to 10.08 for the ratio between tested and predicted ultimate shears at failure. Also, an acceptable range of 0.27 to 2.78 for the ratio between tested and predicted ultimate shears by the Triantafillou model. Finally, the best prediction (the ratio between the tested and predicted ones) of the ultimate shear capacity is observed by using Colotti model with a range of 0.20 to 1.78. Thus, the contribution of the CFRP composites as external reinforcement can be predicted with high accuracy by using the proposed analytical model.

Keywords: Predicting, shear capacity, reinforced concrete, beams, strengthened, externally, CFRP composites.

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7413 An Enhanced Artificial Neural Network for Air Temperature Prediction

Authors: Brian A. Smith, Ronald W. McClendon, Gerrit Hoogenboom

Abstract:

The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. An improved model for temperature prediction in Georgia was developed by including information on seasonality and modifying parameters of an existing artificial neural network model. Alternative models were compared by instantiating and training multiple networks for each model. The inclusion of up to 24 hours of prior weather information and inputs reflecting the day of year were among improvements that reduced average four-hour prediction error by 0.18°C compared to the prior model. Results strongly suggest model developers should instantiate and train multiple networks with different initial weights to establish appropriate model parameters.

Keywords: Time-series forecasting, weather modeling.

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7412 Discovering the Dimension of Abstractness: Structure-Based Model that Learns New Categories and Categorizes on Different Levels of Abstraction

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

Abstract:

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

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

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7411 A Mean–Variance–Skewness Portfolio Optimization Model

Authors: Kostas Metaxiotis

Abstract:

Portfolio optimization is one of the most important topics in finance. This paper proposes a mean–variance–skewness (MVS) portfolio optimization model. Traditionally, the portfolio optimization problem is solved by using the mean–variance (MV) framework. In this study, we formulate the proposed model as a three-objective optimization problem, where the portfolio's expected return and skewness are maximized whereas the portfolio risk is minimized. For solving the proposed three-objective portfolio optimization model we apply an adapted version of the non-dominated sorting genetic algorithm (NSGAII). Finally, we use a real dataset from FTSE-100 for validating the proposed model.

Keywords: Evolutionary algorithms, portfolio optimization, skewness, stock selection.

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7410 The Gasoil Hydrofining Kinetics Constants Identification

Authors: C. Patrascioiu, V. Matei, N. Nicolae

Abstract:

The paper describes the experiments and the kinetic parameters calculus of the gasoil hydrofining. They are presented experimental results of gasoil hidrofining using Mo and promoted with Ni on aluminum support catalyst. The authors have adapted a kinetic model gasoil hydrofining. Using this proposed kinetic model and the experimental data they have calculated the parameters of the model. The numerical calculus is based on minimizing the difference between the experimental sulf concentration and kinetic model estimation.

Keywords: Hydrofining, kinetic, modeling, optimization.

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7409 Blind Non-Minimum Phase Channel Identification Using 3rd and 4th Order Cumulants

Authors: S. Safi, A. Zeroual

Abstract:

In this paper we propose a family of algorithms based on 3rd and 4th order cumulants for blind single-input single-output (SISO) Non-Minimum Phase (NMP) Finite Impulse Response (FIR) channel estimation driven by non-Gaussian signal. The input signal represents the signal used in 10GBASE-T (or IEEE 802.3an-2006) as a Tomlinson-Harashima Precoded (THP) version of random Pulse-Amplitude Modulation with 16 discrete levels (PAM-16). The proposed algorithms are tested using three non-minimum phase channel for different Signal-to-Noise Ratios (SNR) and for different data input length. Numerical simulation results are presented to illustrate the performance of the proposed algorithms.

Keywords: Higher Order Cumulants, Channel identification, Ethernet communication.

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7408 Selective Transverse Modes in a Diode End- Pumped Nd:Yag Pulsed Laser

Authors: M. Mohamadi, M. Mostamand, M. Moosavi, M. Soltanolkotabi

Abstract:

The output beam quality of multi transverse modes of laser, are relatively poor. In order to obtain better beam quality, one may use an aperture inside the laser resonator. In this case, various transverse modes can be selected. We have selected various transverse modes both by simulation and doing experiment. By inserting a circular aperture inside the diode end-pumped Nd:YAG pulsed laser resonator, we have obtained 00 TEM , 01 TEM , 20 TEM and have studied which parameters, can change the mode shape. Then, we have determined the beam quality factor of TEM00 gaussian mode.

Keywords: Beam shape, Transverse mode , Beam quality factor

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7407 Variable Rough Set Model and Its Knowledge Reduction for Incomplete and Fuzzy Decision Information Systems

Authors: Da-kuan Wei, Xian-zhong Zhou, Dong-jun Xin, Zhi-wei Chen

Abstract:

The information systems with incomplete attribute values and fuzzy decisions commonly exist in practical problems. On the base of the notion of variable precision rough set model for incomplete information system and the rough set model for incomplete and fuzzy decision information system, the variable rough set model for incomplete and fuzzy decision information system is constructed, which is the generalization of the variable precision rough set model for incomplete information system and that of rough set model for incomplete and fuzzy decision information system. The knowledge reduction and heuristic algorithm, built on the method and theory of precision reduction, are proposed.

Keywords: Rough set, Incomplete and fuzzy decision information system, Limited valued tolerance relation, Knowledge reduction, Variable rough set model

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7406 Plasma Arc Burner for Pulverized Coal Combustion

Authors: Gela Gelashvili, David Gelenidze, Sulkhan Nanobashvili, Irakli Nanobashvili, George Tavkhelidze, Tsiuri Sitchinava

Abstract:

Development of new highly efficient plasma arc combustion system of pulverized coal is presented. As it is well-known, coal is one of the main energy carriers by means of which electric and heat energy is produced in thermal power stations. The quality of the extracted coal decreases very rapidly. Therefore, the difficulties associated with its firing and complete combustion arise and thermo-chemical preparation of pulverized coal becomes necessary. Usually, other organic fuels (mazut-fuel oil or natural gas) are added to low-quality coal for this purpose. The fraction of additional organic fuels varies within 35-40% range. This decreases dramatically the economic efficiency of such systems. At the same time, emission of noxious substances in the environment increases. Because of all these, intense development of plasma combustion systems of pulverized coal takes place in whole world. These systems are equipped with Non-Transferred Plasma Arc Torches. They allow practically complete combustion of pulverized coal (without organic additives) in boilers, increase of energetic and financial efficiency. At the same time, emission of noxious substances in the environment decreases dramatically. But, the non-transferred plasma torches have numerous drawbacks, e.g. complicated construction, low service life (especially in the case of high power), instability of plasma arc and most important – up to 30% of energy loss due to anode cooling. Due to these reasons, intense development of new plasma technologies that are free from these shortcomings takes place. In our proposed system, pulverized coal-air mixture passes through plasma arc area that burns between to carbon electrodes directly in pulverized coal muffler burner. Consumption of the carbon electrodes is low and does not need a cooling system, but the main advantage of this method is that radiation of plasma arc directly impacts on coal-air mixture that accelerates the process of thermo-chemical preparation of coal to burn. To ensure the stability of the plasma arc in such difficult conditions, we have developed a power source that provides fixed current during fluctuations in the arc resistance automatically compensated by the voltage change as well as regulation of plasma arc length over a wide range. Our combustion system where plasma arc acts directly on pulverized coal-air mixture is simple. This should allow a significant improvement of pulverized coal combustion (especially low-quality coal) and its economic efficiency. Preliminary experiments demonstrated the successful functioning of the system.

Keywords: Coal combustion, plasma arc, plasma torches, pulverized coal.

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7405 DMC with Adaptive Weighted Output

Authors: Ahmed Abbas, M.R. M Rizk, Mohamed El-Sayed

Abstract:

This paper presents a new adaptive DMC controller that improves the controller performance in case of plant-model mismatch. The new controller monitors the plant measured output, compares it with the model output and calculates weights applied to the controller move. Simulations show that the new controller can help improve control performance and avoid instability in case of severe model mismatches.

Keywords: Adaptive control, dynamic matrix control, DMC, model predictive control

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7404 Segmentation of Piecewise Polynomial Regression Model by Using Reversible Jump MCMC Algorithm

Authors: Suparman

Abstract:

Piecewise polynomial regression model is very flexible model for modeling the data. If the piecewise polynomial regression model is matched against the data, its parameters are not generally known. This paper studies the parameter estimation problem of piecewise polynomial regression model. The method which is used to estimate the parameters of the piecewise polynomial regression model is Bayesian method. Unfortunately, the Bayes estimator cannot be found analytically. Reversible jump MCMC algorithm is proposed to solve this problem. Reversible jump MCMC algorithm generates the Markov chain that converges to the limit distribution of the posterior distribution of piecewise polynomial regression model parameter. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of piecewise polynomial regression model.

Keywords: Piecewise, Bayesian, reversible jump MCMC, segmentation.

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7403 Modeling of Radiative Heat Transfer in 2D Complex Heat Recuperator of Biomass Pyrolysis Furnace: A Study of Baffles Shadow and Soot Volume Fraction Effects

Authors: Mohamed Ammar Abbassi, Kamel Guedri, Mohamed Naceur Borjini, Kamel Halouani, Belkacem Zeghmati

Abstract:

The radiative heat transfer problem is investigated numerically for 2D complex geometry biomass pyrolysis reactor composed of two pyrolysis chambers and a heat recuperator. The fumes are a mixture of carbon dioxide and water vapor charged with absorbing and scattering particles and soot. In order to increase gases residence time and heat transfer, the heat recuperator is provided with many inclined, vertical, horizontal, diffuse and grey baffles of finite thickness and has a complex geometry. The Finite Volume Method (FVM) is applied to study radiative heat transfer. The blocked-off region procedure is used to treat the geometrical irregularities. Eight cases are considered in order to demonstrate the effect of adding baffles on the walls of the heat recuperator and on the walls of the pyrolysis rooms then choose the best case giving the maximum heat flux transferred to the biomass in the pyrolysis chambers. Ray effect due to the presence of baffles is studied and demonstrated to have a crucial effect on radiative heat flux on the walls of the pyrolysis rooms. Shadow effect caused by the presence of the baffles is also studied. The non grey radiative heat transfer is studied for the real existent configuration. The Weighted Sum of The Grey Gases (WSGG) Model of Kim and Song is used as non grey model. The effect of soot volumetric fraction on the non grey radiative heat flux is investigated and discussed.

Keywords: Baffles, Blocked-off region procedure, FVM, Heat recuperation, Radiative heat transfer, Shadow effect.

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7402 Generating Normally Distributed Clusters by Means of a Self-organizing Growing Neural Network– An Application to Market Segmentation –

Authors: Reinhold Decker, Christian Holsing, Sascha Lerke

Abstract:

This paper presents a new growing neural network for cluster analysis and market segmentation, which optimizes the size and structure of clusters by iteratively checking them for multivariate normality. We combine the recently published SGNN approach [8] with the basic principle underlying the Gaussian-means algorithm [13] and the Mardia test for multivariate normality [18, 19]. The new approach distinguishes from existing ones by its holistic design and its great autonomy regarding the clustering process as a whole. Its performance is demonstrated by means of synthetic 2D data and by real lifestyle survey data usable for market segmentation.

Keywords: Artificial neural network, clustering, multivariatenormality, market segmentation, self-organization

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7401 Model-Based Software Regression Test Suite Reduction

Authors: Shiwei Deng, Yang Bao

Abstract:

In this paper, we present a model-based regression test suite reducing approach that uses EFSM model dependence analysis and probability-driven greedy algorithm to reduce software regression test suites. The approach automatically identifies the difference between the original model and the modified model as a set of elementary model modifications. The EFSM dependence analysis is performed for each elementary modification to reduce the regression test suite, and then the probability-driven greedy algorithm is adopted to select the minimum set of test cases from the reduced regression test suite that cover all interaction patterns. Our initial experience shows that the approach may significantly reduce the size of regression test suites.

Keywords: Dependence analysis, EFSM model, greedy algorithm, regression test.

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7400 Model of the Increasing the Capacity of the Train and Railway Track by Using the New Type of Wagon

Authors: Martin Kendra, Jaroslav Mašek, Juraj Čamaj, Martin Búda

Abstract:

The paper deals with possibilities of increase train capacity by using a new type of railway wagon. In the first part is created a mathematical model to calculate the capacity of the train. The model is based on the main limiting parameters of the train - maximum number of axles per train, maximum gross weight of train, maximum length of train and number of TEUs per one wagon. In the second part is the model applied to four different model trains with different composition of the train set and three different average weights of TEU and a train consisting of a new type of wagons. The result is to identify where the carrying capacity of the original trains is higher, respectively less than a capacity of train consisting of a new type of wagons.

Keywords: Loading units, theoretical capacity model, train capacity, wagon for intermodal transport.

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7399 Modeling and Simulation Methods Using MATLAB/Simulink

Authors: Jamuna Konda, Umamaheswara Reddy Karumuri, Sriramya Muthugi, Varun Pishati, Ravi Shakya,

Abstract:

This paper investigates the challenges involved in mathematical modeling of plant simulation models ensuring the performance of the plant models much closer to the real time physical model. The paper includes the analysis performed and investigation on different methods of modeling, design and development for plant model. Issues which impact the design time, model accuracy as real time model, tool dependence are analyzed. The real time hardware plant would be a combination of multiple physical models. It is more challenging to test the complete system with all possible test scenarios. There are possibilities of failure or damage of the system due to any unwanted test execution on real time.

Keywords: Model Based Design, MATLAB, Simulink, Stateflow, plant model, real time model, real-time workshop, target language compiler.

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7398 Development of a Model for the Comprehensive Analysis and Evaluation of Service Productivity

Authors: A. Petz, S. Duckwitz, C. Schmalz, S. Meyer, S. Mütze-Niewöhner, C.M. Schlick

Abstract:

Although services play a crucial role in economy, service did not gain as much importance as productivity management in manufacturing. This paper presents key findings from literature and practice. Based on an initial definition of complex services, seven productivity concepts are briefly presented and assessed by relevant, complex service specific criteria. Following the findings a complex service productivity model is proposed. The novel model comprises of all specific dimensions of service provision from both, the provider-s as well as costumer-s perspective. A clear assignment of identified value drivers and relationships between them is presented. In order to verify the conceptual service productivity model a case study from a project engineering department of a chemical plant development and construction company is presented.

Keywords: assessment model, complex services, service productivity model, value driver.

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