Search results for: Modified Softened Truss Model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8125

Search results for: Modified Softened Truss Model

7855 A Multi-Objective Optimization Model to the Integrating Flexible Process Planning And Scheduling Based on Modified Particle Swarm Optimization Algorithm (MPSO)

Authors: R. Sahraian, A. Karampour Haghighi, E. Ghasemi

Abstract:

Process planning and production scheduling play important roles in manufacturing systems. In this paper a multiobjective mixed integer linear programming model is presented for the integrated planning and scheduling of multi-product. The aim is to find a set of high-quality trade-off solutions. This is a combinatorial optimization problem with substantially large solution space, suggesting that it is highly difficult to find the best solutions with the exact search method. To account for it, a PSO-based algorithm is proposed by fully utilizing the capability of the exploration search and fast convergence. To fit the continuous PSO in the discrete modeled problem, a solution representation is used in the algorithm. The numerical experiments have been performed to demonstrate the effectiveness of the proposed algorithm.

Keywords: Integrated process planning and scheduling, multi objective, MILP, Particle swarm optimization

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7854 Text Retrieval Relevance Feedback Techniques for Bag of Words Model in CBIR

Authors: Nhu Van NGUYEN, Jean-Marc OGIER, Salvatore TABBONE, Alain BOUCHER

Abstract:

The state-of-the-art Bag of Words model in Content- Based Image Retrieval has been used for years but the relevance feedback strategies for this model are not fully investigated. Inspired from text retrieval, the Bag of Words model has the ability to use the wealth of knowledge and practices available in text retrieval. We study and experiment the relevance feedback model in text retrieval for adapting it to image retrieval. The experiments show that the techniques from text retrieval give good results for image retrieval and that further improvements is possible.

Keywords: Relevance feedback, bag of words model, probabilistic model, vector space model, image retrieval

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7853 A Simple Deterministic Model for the Spread of Leptospirosis in Thailand

Authors: W. Triampo, D. Baowan, I.M. Tang, N. Nuttavut, J. Wong-Ekkabut, G. Doungchawee

Abstract:

In this work, we consider a deterministic model for the transmission of leptospirosis which is currently spreading in the Thai population. The SIR model which incorporates the features of this disease is applied to the epidemiological data in Thailand. It is seen that the numerical solutions of the SIR equations are in good agreement with real empirical data. Further improvements are discussed.

Keywords: Leptospirosis, SIR Model, Deterministic model, Thailand.

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7852 Implicit Eulerian Fluid-Structure Interaction Method for the Modeling of Highly Deformable Elastic Membranes

Authors: Aymen Laadhari, Gábor Székely

Abstract:

This paper is concerned with the development of a fully implicit and purely Eulerian fluid-structure interaction method tailored for the modeling of the large deformations of elastic membranes in a surrounding Newtonian fluid. We consider a simplified model for the mechanical properties of the membrane, in which the surface strain energy depends on the membrane stretching. The fully Eulerian description is based on the advection of a modified surface tension tensor, and the deformations of the membrane are tracked using a level set strategy. The resulting nonlinear problem is solved by a Newton-Raphson method, featuring a quadratic convergence behavior. A monolithic solver is implemented, and we report several numerical experiments aimed at model validation and illustrating the accuracy of the presented method. We show that stability is maintained for significantly larger time steps.

Keywords: Fluid-membrane interaction, stretching, Eulerian, finite element method, Newton, implicit.

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7851 A Semi-Implicit Phase Field Model for Droplet Evolution

Authors: M. H. Kazemi, D. Salac

Abstract:

A semi-implicit phase field method for droplet evolution is proposed. Using the phase field Cahn-Hilliard equation, we are able to track the interface in multiphase flow. The idea of a semi-implicit finite difference scheme is reviewed and employed to solve two nonlinear equations, including the Navier-Stokes and the Cahn-Hilliard equations. The use of a semi-implicit method allows us to have larger time steps compared to explicit schemes. The governing equations are coupled and then solved by a GMRES solver (generalized minimal residual method) using modified Gram-Schmidt orthogonalization. To show the validity of the method, we apply the method to the simulation of a rising droplet, a leaky dielectric drop and the coalescence of drops. The numerical solutions to the phase field model match well with existing solutions over a defined range of variables.

Keywords: Coalescence, leaky dielectric, numerical method, phase field, rising droplet, semi-implicit method.

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7850 Simulation of Surge Protection for a Direct Current Circuit

Authors: Pedro Luis Ferrer Penalver, Edmundo da Silva Braga

Abstract:

In this paper, the performance of a simple surge protection for a direct current circuit was simulated. The protection circuit was developed from modified electric macro models of a gas discharge tube and a transient voltage suppressor diode. Moreover, a combination wave generator circuit was used as source of energy surges. The simulations showed that the circuit presented ensures immunity corresponding with test level IV of the IEC 61000-4-5:2014 international standard. The developed circuit can be modified to meet the requirements of any other equipment to be protected. Similarly, the parameters of the combination wave generator can be changed to provide different surge amplitudes.

Keywords: Combination wave generator, IEC 61000-4-5, Pspice simulation, surge protection.

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7849 Cloud Computing Initiative using Modified Ant Colony Framework

Authors: Soumya Banerjee, Indrajit Mukherjee, P.K. Mahanti

Abstract:

Scheduling of diversified service requests in distributed computing is a critical design issue. Cloud is a type of parallel and distributed system consisting of a collection of interconnected and virtual computers. It is not only the clusters and grid but also it comprises of next generation data centers. The paper proposes an initial heuristic algorithm to apply modified ant colony optimization approach for the diversified service allocation and scheduling mechanism in cloud paradigm. The proposed optimization method is aimed to minimize the scheduling throughput to service all the diversified requests according to the different resource allocator available under cloud computing environment.

Keywords: Ant Colony, Cloud Computing, Grid, Resource allocator, Service Request.

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7848 Investigation of Titanium Oxide Layer in Thermal-Electrochemical Anodizing of Ti6Al4V Alloy

Authors: Z. Abdolldhi, A. A. Ziaee M., A. Afshar

Abstract:

In this paper the combination of thermal oxidation and electrochemical anodizing processes is used to produce titanium oxide layers. The response of titanium alloy Ti6Al4V to oxidation processes at various temperatures and electrochemical anodizing in various voltages are investigated. Scanning electron microscopy (SEM); X-Ray Diffraction (XRD) and porosity determination have been used to characterize the oxide layer thickness, surface morphology, oxide layer-substrate adhesion and porosity. In the first experiment, samples modified by thermal oxidation process then followed by electrochemical anodizing. Second experiment consists of surfaces modified by electrochemical anodizing process and then followed by thermal oxidation. The first method shows better properties than other one. In second experiment, Surfaces modified were achieved by thicker and more adherent thick oxide layers on titanium surface. The existence of an electrochemical anodized oxide layer did not improve the adhesion of thermal oxide layer. The high temperature, thermal formation of an oxide layer leads to a coarse oxide grain morphology and a complete oxidative particle. In addition, in high temperature oxidation porosity content is increased. The oxide layer of thermal oxidation and electrochemical anodizing processes; on Ti–6Al–4V substrate was covered with different colored oxide layers.

Keywords: Electrochemically anodizing, Porosity, Thermaloxidation, Ti6Al4 alloy.

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7847 Electrochemical Response Transductions of Graphenated-Polyaniline Nanosensor for Environmental Anthracene

Authors: O. Tovide, N. Jahed, N. Mohammed, C. E. Sunday, H. R. Makelane, R. F. Ajayi, K. M. Molapo, A. Tsegaye, M. Masikini, S. Mailu, A. Baleg, T. Waryo, P. G. Baker, E. I. Iwuoha

Abstract:

A graphenated–polyaniline (GR-PANI) nanocomposite sensor was constructed and used for the determination of anthracene. The direct electro-oxidation behavior of anthracene on the GR-PANI modified glassy carbon electrode (GCE) was used as the sensing principle. The results indicate thatthe response profile of the oxidation of anthracene on GR-PANI-modified GCE provides for the construction of sensor systems based onamperometric and potentiometric signal transductions. A dynamic linear range of 0.12- 100 µM anthracene and a detection limit of 0.044 µM anthracene were established for the sensor system.

Keywords: Electrochemical sensors, environmental pollutants, graphenated-polymers, polyaromatic hydrocarbon.

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7846 Kalman-s Shrinkage for Wavelet-Based Despeckling of SAR Images

Authors: Mario Mastriani, Alberto E. Giraldez

Abstract:

In this paper, a new probability density function (pdf) is proposed to model the statistics of wavelet coefficients, and a simple Kalman-s filter is derived from the new pdf using Bayesian estimation theory. Specifically, we decompose the speckled image into wavelet subbands, we apply the Kalman-s filter to the high subbands, and reconstruct a despeckled image from the modified detail coefficients. Experimental results demonstrate that our method compares favorably to several other despeckling methods on test synthetic aperture radar (SAR) images.

Keywords: Kalman's filter, shrinkage, speckle, wavelets.

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7845 New Insight into Fluid Mechanics of Lorenz Equations

Authors: Yu-Kai Ting, Jia-Ying Tu, Chung-Chun Hsiao

Abstract:

New physical insights into the nonlinear Lorenz equations related to flow resistance is discussed in this work. The chaotic dynamics related to Lorenz equations has been studied in many papers, which is due to the sensitivity of Lorenz equations to initial conditions and parameter uncertainties. However, the physical implication arising from Lorenz equations about convectional motion attracts little attention in the relevant literature. Therefore, as a first step to understand the related fluid mechanics of convectional motion, this paper derives the Lorenz equations again with different forced conditions in the model. Simulation work of the modified Lorenz equations without the viscosity or buoyancy force is discussed. The time-domain simulation results may imply that the states of the Lorenz equations are related to certain flow speed and flow resistance. The flow speed of the underlying fluid system increases as the flow resistance reduces. This observation would be helpful to analyze the coupling effects of different fluid parameters in a convectional model in future work.

Keywords: Galerkin method, Lorenz equations, Navier-Stokes equations.

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7844 Trajectory-Based Modified Policy Iteration

Authors: R. Sharma, M. Gopal

Abstract:

This paper presents a new problem solving approach that is able to generate optimal policy solution for finite-state stochastic sequential decision-making problems with high data efficiency. The proposed algorithm iteratively builds and improves an approximate Markov Decision Process (MDP) model along with cost-to-go value approximates by generating finite length trajectories through the state-space. The approach creates a synergy between an approximate evolving model and approximate cost-to-go values to produce a sequence of improving policies finally converging to the optimal policy through an intelligent and structured search of the policy space. The approach modifies the policy update step of the policy iteration so as to result in a speedy and stable convergence to the optimal policy. We apply the algorithm to a non-holonomic mobile robot control problem and compare its performance with other Reinforcement Learning (RL) approaches, e.g., a) Q-learning, b) Watkins Q(λ), c) SARSA(λ).

Keywords: Markov Decision Process (MDP), Mobile robot, Policy iteration, Simulation.

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7843 Effect of Surface-Modification of Indium Tin Oxide Particles on Their Electrical Conductivity

Authors: Y. Kobayashi, T. Kurosaka, K. Yamamura, T. Yonezawa, K. Yamasaki

Abstract:

The present work reports an effect of surface- modification of indium tin oxide (ITO) particles with chemicals on their electronic conductivity properties. Examined chemicals were polyvinyl alcohol (nonionic polymer), poly(diallyl dimethyl ammonium chloride) (cationic polymer), poly(sodium 4-styrene-sulfonate) (anionic polymer), (2-aminopropyl) trimethoxy silane (APMS) (silane coupling agent with amino group), and (3-mercaptopropyl) trimethoxy silane (MPS) (silane coupling agent with thiol group). For all the examined chemicals, volume resistivities of surface-modified ITO particles did not increase much when they were aged in air at 80 oC, compared to a volume resistivity of un-surface-modified ITO particles. Increases in volume resistivities of ITO particles surface-modified with the silane coupling agents were smaller than those with the polymers, since hydrolysis of the silane coupling agents and condensation of generated silanol and OH groups on ITO particles took place to provide efficient immobilization of them on particles. The APMS gave an increase in volume resistivity smaller than the MPS, since a larger solubility in water of APMS providing a larger amount of APMS immobilized on particles.

Keywords: Indium tin oxide, particles, surface-modification, volume resistivity.

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7842 Dynamic Model of a Buck Converter with a Sliding Mode Control

Authors: S. Chonsatidjamroen , K-N. Areerak, K-L. Areerak

Abstract:

This paper presents the averaging model of a buck converter derived from the generalized state-space averaging method. The sliding mode control is used to regulate the output voltage of the converter and taken into account in the model. The proposed model requires the fast computational time compared with those of the full topology model. The intensive time-domain simulations via the exact topology model are used as the comparable model. The results show that a good agreement between the proposed model and the switching model is achieved in both transient and steady-state responses. The reported model is suitable for the optimal controller design by using the artificial intelligence techniques.

Keywords: Generalized state-space averaging method, buck converter, sliding mode control, modeling, simulation.

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7841 An Optimization of Machine Parameters for Modified Horizontal Boring Tool Using Taguchi Method

Authors: Thirasak Panyaphirawat, Pairoj Sapsmarnwong, Teeratas Pornyungyuen

Abstract:

This paper presents the findings of an experimental investigation of important machining parameters for the horizontal boring tool modified to mouth with a horizontal lathe machine to bore an overlength workpiece. In order to verify a usability of a modified tool, design of experiment based on Taguchi method is performed. The parameters investigated are spindle speed, feed rate, depth of cut and length of workpiece. Taguchi L9 orthogonal array is selected for four factors three level parameters in order to minimize surface roughness (Ra and Rz) of S45C steel tubes. Signal to noise ratio analysis and analysis of variance (ANOVA) is performed to study an effect of said parameters and to optimize the machine setting for best surface finish. The controlled factors with most effect are depth of cut, spindle speed, length of workpiece, and feed rate in order. The confirmation test is performed to test the optimal setting obtained from Taguchi method and the result is satisfactory.

Keywords: Design of Experiment, Taguchi Design, Optimization, Analysis of Variance, Machining Parameters, Horizontal Boring Tool.

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7840 A Dynamic Hybrid Option Pricing Model by Genetic Algorithm and Black- Scholes Model

Authors: Yi-Chang Chen, Shan-Lin Chang, Chia-Chun Wu

Abstract:

Unlike this study focused extensively on trading behavior of option market, those researches were just taken their attention to model-driven option pricing. For example, Black-Scholes (B-S) model is one of the most famous option pricing models. However, the arguments of B-S model are previously mentioned by some pricing models reviewing. This paper following suggests the importance of the dynamic character for option pricing, which is also the reason why using the genetic algorithm (GA). Because of its natural selection and species evolution, this study proposed a hybrid model, the Genetic-BS model which combining GA and B-S to estimate the price more accurate. As for the final experiments, the result shows that the output estimated price with lower MAE value than the calculated price by either B-S model or its enhanced one, Gram-Charlier garch (G-C garch) model. Finally, this work would conclude that the Genetic-BS pricing model is exactly practical.

Keywords: genetic algorithm, Genetic-BS, option pricing model.

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7839 Automatic Generation Control of Multi-Area Electric Energy Systems Using Modified GA

Authors: Gayadhar Panda, Sidhartha Panda, C. Ardil

Abstract:

A modified Genetic Algorithm (GA) based optimal selection of parameters for Automatic Generation Control (AGC) of multi-area electric energy systems is proposed in this paper. Simulations on multi-area reheat thermal system with and without consideration of nonlinearity like governor dead band followed by 1% step load perturbation is performed to exemplify the optimum parameter search. In this proposed method, a modified Genetic Algorithm is proposed where one point crossover with modification is employed. Positional dependency in respect of crossing site helps to maintain diversity of search point as well as exploitation of already known optimum value. This makes a trade-off between exploration and exploitation of search space to find global optimum in less number of generations. The proposed GA along with decomposition technique as developed has been used to obtain the optimum megawatt frequency control of multi-area electric energy systems. Time-domain simulations are conducted with trapezoidal integration along with decomposition technique. The superiority of the proposed method over existing one is verified from simulations and comparisons.

Keywords: Automatic Generation Control (AGC), Reheat, Proportional Integral (PI) controller, Dead Band, Genetic Algorithm(GA).

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7838 The Microstructural and Mechanical Characterization of Organo-Clay-Modified Bitumen, Calcareous Aggregate, and Organo-Clay Blends

Authors: A. Gürses, T. B. Barın, Ç. Doğar

Abstract:

Bitumen has been widely used as the binder of aggregate in road pavement due to its good viscoelastic properties, as a viscous organic mixture with various chemical compositions. Bitumen is a liquid at high temperature and it becomes brittle at low temperatures, and this temperature-sensitivity can cause the rutting and cracking of the pavement and limit its application. Therefore, the properties of existing asphalt materials need to be enhanced. The pavement with polymer modified bitumen exhibits greater resistance to rutting and thermal cracking, decreased fatigue damage, as well as stripping and temperature susceptibility; however, they are expensive and their applications have disadvantages. Bituminous mixtures are composed of very irregular aggregates bound together with hydrocarbon-based asphalt, with a low volume fraction of voids dispersed within the matrix. Montmorillonite (MMT) is a layered silicate with low cost and abundance, which consists of layers of tetrahedral silicate and octahedral hydroxide sheets. Recently, the layered silicates have been widely used for the modification of polymers, as well as in many different fields. However, there are not too much studies related with the preparation of the modified asphalt with MMT, currently. In this study, organo-clay-modified bitumen, and calcareous aggregate and organo-clay blends were prepared by hot blending method with OMMT, which has been synthesized using a cationic surfactant (Cetyltrymethylammonium bromide, CTAB) and long chain hydrocarbon, and MMT. When the exchangeable cations in the interlayer region of pristine MMT were exchanged with hydrocarbon attached surfactant ions, the MMT becomes organophilic and more compatible with bitumen. The effects of the super hydrophobic OMMT onto the micro structural and mechanic properties (Marshall Stability and volumetric parameters) of the prepared blends were investigated. Stability and volumetric parameters of the blends prepared were measured using Marshall Test. Also, in order to investigate the morphological and micro structural properties of the organo-clay-modified bitumen and calcareous aggregate and organo-clay blends, their SEM and HRTEM images were taken. It was observed that the stability and volumetric parameters of the prepared mixtures improved significantly compared to the conventional hot mixes and even the stone matrix mixture. A micro structural analysis based on SEM images indicates that the organo-clay platelets dispersed in the bitumen have a dominant role in the increase of effectiveness of bitumen - aggregate interactions.

Keywords: Hot mix asphalt, stone matrix asphalt, organo clay, Marshall Test, calcareous aggregate, modified bitumen.

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7837 Butene Catalytic Cracking to Propylene over Iron and Phosphorus Modified HZSM-5

Authors: Jianwen Li, Hongfang Ma, Haitao Zhang, Qiwen Sun, Weiyong Ying

Abstract:

HZSM-5 zeolites modified by iron and phosphorus were applied in catalytic cracking of butene. N2 adsorption and NH3-TPD were employed to measure the structure and acidity of catalysts. The results indicate that increasing phosphorus loading decreased surface area, pore volume and strong acidity of catalysts. The addition of phosphorus significantly decreased butene conversion and promoted propylene selectivity. The catalytic performance of catalyst was strongly dependent on the reaction conditions. Appropriate reaction conditions could suppress side reactions and enhance propylene selectivity.

Keywords: Butene catalytic cracking, HZSM-5, modification, reaction conditions.

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7836 A High-Speed Multiplication Algorithm Using Modified Partial Product Reduction Tree

Authors: P. Asadee

Abstract:

Multiplication algorithms have considerable effect on processors performance. A new high-speed, low-power multiplication algorithm has been presented using modified Dadda tree structure. Three important modifications have been implemented in inner product generation step, inner product reduction step and final addition step. Optimized algorithms have to be used into basic computation components, such as multiplication algorithms. In this paper, we proposed a new algorithm to reduce power, delay, and transistor count of a multiplication algorithm implemented using low power modified counter. This work presents a novel design for Dadda multiplication algorithms. The proposed multiplication algorithm includes structured parts, which have important effect on inner product reduction tree. In this paper, a 1.3V, 64-bit carry hybrid adder is presented for fast, low voltage applications. The new 64-bit adder uses a new circuit to implement the proposed carry hybrid adder. The new adder using 80 nm CMOS technology has been implemented on 700 MHz clock frequency. The proposed multiplication algorithm has achieved 14 percent improvement in transistor count, 13 percent reduction in delay and 12 percent modification in power consumption in compared with conventional designs.

Keywords: adder, CMOS, counter, Dadda tree, encoder.

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7835 Dynamics of Phytoplankton Blooms in the Baltic Sea – Numerical Simulations

Authors: L. Dzierzbicka-Głowacka, M. Janecki

Abstract:

Dynamic of phytoplankton blooms in the Baltic Sea has been analyzed applying the numerical ecosystem model 3D CEMBS. The model consists of the hydrodynamic model (POP, version 2.1) and the ice model (CICE, version 4.0), which are imposed by the atmospheric data model (DATM7). The 3D model has an ecosystem module, activated in 2012 in the operational mode. The ecosystem model consists of 11 main variables: biomass of small-size phytoplankton and large-size phytoplankton and cyanobacteria, zooplankton biomass, dissolved and molecular detritus, dissolved oxygen concentration, as well as concentrations of nutrients, including: nitrates, ammonia, phosphates and silicates. The 3D-CEMBS model is an effective tool for solving problems related to phytoplankton blooms dynamic in the Baltic Sea

Keywords: Ecosystem model, phytoplankton, Baltic Sea

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7834 Development of Admire Longitudinal Quasi-Linear Model by using State Transformation Approach

Authors: Jianqiao. Yu, Jianbo. Wang, Xinzhen. He

Abstract:

This paper presents a longitudinal quasi-linear model for the ADMIRE model. The ADMIRE model is a nonlinear model of aircraft flying in the condition of high angle of attack. So it can-t be considered to be a linear system approximately. In this paper, for getting the longitudinal quasi-linear model of the ADMIRE, a state transformation based on differentiable functions of the nonscheduling states and control inputs is performed, with the goal of removing any nonlinear terms not dependent on the scheduling parameter. Since it needn-t linear approximation and can obtain the exact transformations of the nonlinear states, the above-mentioned approach is thought to be appropriate to establish the mathematical model of ADMIRE. To verify this conclusion, simulation experiments are done. And the result shows that this quasi-linear model is accurate enough.

Keywords: quasi-linear model, simulation, state transformation approach, the ADMIRE model.

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7833 Combined Sewer Overflow forecasting with Feed-forward Back-propagation Artificial Neural Network

Authors: Achela K. Fernando, Xiujuan Zhang, Peter F. Kinley

Abstract:

A feed-forward, back-propagation Artificial Neural Network (ANN) model has been used to forecast the occurrences of wastewater overflows in a combined sewerage reticulation system. This approach was tested to evaluate its applicability as a method alternative to the common practice of developing a complete conceptual, mathematical hydrological-hydraulic model for the sewerage system to enable such forecasts. The ANN approach obviates the need for a-priori understanding and representation of the underlying hydrological hydraulic phenomena in mathematical terms but enables learning the characteristics of a sewer overflow from the historical data. The performance of the standard feed-forward, back-propagation of error algorithm was enhanced by a modified data normalizing technique that enabled the ANN model to extrapolate into the territory that was unseen by the training data. The algorithm and the data normalizing method are presented along with the ANN model output results that indicate a good accuracy in the forecasted sewer overflow rates. However, it was revealed that the accurate forecasting of the overflow rates are heavily dependent on the availability of a real-time flow monitoring at the overflow structure to provide antecedent flow rate data. The ability of the ANN to forecast the overflow rates without the antecedent flow rates (as is the case with traditional conceptual reticulation models) was found to be quite poor.

Keywords: Artificial Neural Networks, Back-propagationlearning, Combined sewer overflows, Forecasting.

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7832 A Modified Fuzzy C-Means Algorithm for Natural Data Exploration

Authors: Binu Thomas, Raju G., Sonam Wangmo

Abstract:

In Data mining, Fuzzy clustering algorithms have demonstrated advantage over crisp clustering algorithms in dealing with the challenges posed by large collections of vague and uncertain natural data. This paper reviews concept of fuzzy logic and fuzzy clustering. The classical fuzzy c-means algorithm is presented and its limitations are highlighted. Based on the study of the fuzzy c-means algorithm and its extensions, we propose a modification to the cmeans algorithm to overcome the limitations of it in calculating the new cluster centers and in finding the membership values with natural data. The efficiency of the new modified method is demonstrated on real data collected for Bhutan-s Gross National Happiness (GNH) program.

Keywords: Adaptive fuzzy clustering, clustering, fuzzy logic, fuzzy clustering, c-means.

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7831 Intermolecular Dynamics between Alcohols and Fatty Acid Ester Solvents

Authors: Jacques J. Scheepers, Edison Muzenda

Abstract:

This work focused on the interactions which occur between ester solvents and alcohol solutes. The alcohols selected ranged from the simplest alcohol (methanol) to C10-alcohols, and solubility predictions in the form of infinite dilution activity coefficients were made using the Modified UNIFAC Dortmund group contribution model. The model computation was set up on a Microsoft Excel spreadsheet specifically designed for this purpose. It was found that alcohol/ ester interactions yielded an increase in activity coefficients (i.e. became less soluble) with an increase in the size of the ester solvent molecule. Furthermore, activity coefficients decreased with an increase in the size of the alcohol solute. The activity coefficients also decreased with an increase in the degree of unsaturation of the ester hydrocarbon tail. Tertiary alcohols yielded lower activity coefficients than primary alcohols. Finally, cyclic alcohols yielded higher activity coefficients than straight-chain alcohols until a point is reached where the trend is reversed, referred to as the ‘crossover’ point.

Keywords: Activity coefficients, alcohols, esters, solubility, van der Waals, UNIFAC.

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7830 Analysis of Slip Flow Heat Transfer between Asymmetrically Heated Parallel Plates

Authors: Hari Mohan Kushwaha, Santosh K. Sahu

Abstract:

In the present study, analysis of heat transfer is carried out in the slip flow region for the fluid flowing between two parallel plates by employing the asymmetric heat fluxes at surface of the plates. The flow is assumed to be hydrodynamically and thermally fully developed for the analysis. The second order velocity slip and viscous dissipation effects are considered for the analysis. Closed form expressions are obtained for the Nusselt number as a function of Knudsen number and modified Brinkman number. The limiting condition of the present prediction for Kn = 0, Kn2 = 0, and Brq1 = 0 is considered and found to agree well with other analytical results.

Keywords: Knudsen Number, Modified Brinkman Number, Slip Flow, Velocity Slip.

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7829 A Numerical Study on the Effects of N2 Dilution on the Flame Structure and Temperature Distribution of Swirl Diffusion Flames

Authors: Yasaman Tohidi, Shidvash Vakilipour, Saeed Ebadi Tavallaee, Shahin Vakilipoor Takaloo, Hossein Amiri

Abstract:

The numerical modeling is performed to study the effects of N2 addition to the fuel stream on the flame structure and temperature distribution of methane-air swirl diffusion flames with different swirl intensities. The Open source Field Operation and Manipulation (OpenFOAM) has been utilized as the computational tool. Flamelet approach along with modified k-ε model is employed to model the flame characteristics.  The results indicate that the presence of N2 in the fuel stream leads to the flame temperature reduction. By increasing of swirl intensity, the flame structure changes significantly. The flame has a conical shape in low swirl intensity; however, it has an hour glass-shape with a shorter length in high swirl intensity. The effects of N2 dilution decrease the flame length in all swirl intensities; however, the rate of reduction is more noticeable in low swirl intensity.

Keywords: Swirl diffusion flame, N2 dilution, OpenFOAM, Swirl intensity.

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7828 Improved Weighted Matching for Speaker Recognition

Authors: Ozan Mut, Mehmet Göktürk

Abstract:

Matching algorithms have significant importance in speaker recognition. Feature vectors of the unknown utterance are compared to feature vectors of the modeled speakers as a last step in speaker recognition. A similarity score is found for every model in the speaker database. Depending on the type of speaker recognition, these scores are used to determine the author of unknown speech samples. For speaker verification, similarity score is tested against a predefined threshold and either acceptance or rejection result is obtained. In the case of speaker identification, the result depends on whether the identification is open set or closed set. In closed set identification, the model that yields the best similarity score is accepted. In open set identification, the best score is tested against a threshold, so there is one more possible output satisfying the condition that the speaker is not one of the registered speakers in existing database. This paper focuses on closed set speaker identification using a modified version of a well known matching algorithm. The results of new matching algorithm indicated better performance on YOHO international speaker recognition database.

Keywords: Automatic Speaker Recognition, Voice Recognition, Pattern Recognition, Digital Audio Signal Processing.

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7827 Generalized Chaplygin Gas and Varying Bulk Viscosity in Lyra Geometry

Authors: A. K. Sethi, R. N. Patra, B. Nayak

Abstract:

In this paper, we have considered Friedmann-Robertson-Walker (FRW) metric with generalized Chaplygin gas which has viscosity in the context of Lyra geometry. The viscosity is considered in two different ways (i.e. zero viscosity, non-constant r (rho)-dependent bulk viscosity) using constant deceleration parameter which concluded that, for a special case, the viscous generalized Chaplygin gas reduces to modified Chaplygin gas. The represented model indicates on the presence of Chaplygin gas in the Universe. Observational constraints are applied and discussed on the physical and geometrical nature of the Universe.

Keywords: Bulk viscosity, Lyra geometry, generalized Chaplygin gas, cosmology.

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7826 A Multi-layer Artificial Neural Network Architecture Design for Load Forecasting in Power Systems

Authors: Axay J Mehta, Hema A Mehta, T.C.Manjunath, C. Ardil

Abstract:

In this paper, the modelling and design of artificial neural network architecture for load forecasting purposes is investigated. The primary pre-requisite for power system planning is to arrive at realistic estimates of future demand of power, which is known as Load Forecasting. Short Term Load Forecasting (STLF) helps in determining the economic, reliable and secure operating strategies for power system. The dependence of load on several factors makes the load forecasting a very challenging job. An over estimation of the load may cause premature investment and unnecessary blocking of the capital where as under estimation of load may result in shortage of equipment and circuits. It is always better to plan the system for the load slightly higher than expected one so that no exigency may arise. In this paper, a load-forecasting model is proposed using a multilayer neural network with an appropriately modified back propagation learning algorithm. Once the neural network model is designed and trained, it can forecast the load of the power system 24 hours ahead on daily basis and can also forecast the cumulative load on daily basis. The real load data that is used for the Artificial Neural Network training was taken from LDC, Gujarat Electricity Board, Jambuva, Gujarat, India. The results show that the load forecasting of the ANN model follows the actual load pattern more accurately throughout the forecasted period.

Keywords: Power system, Load forecasting, Neural Network, Neuron, Stabilization, Network structure, Load.

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