Search results for: Mathematical Model

Authors: S. Panda, S. K. Tomar, R. Prasad, C. Ardil

Abstract:

Order reduction of linear-time invariant systems employing two methods; one using the advantages of Routh approximation and other by an evolutionary technique is presented in this paper. In Routh approximation method the denominator of the reduced order model is obtained using Routh approximation while the numerator of the reduced order model is determined using the indirect approach of retaining the time moments and/or Markov parameters of original system. By this method the reduced order model guarantees stability if the original high order model is stable. In the second method Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical examples.

Keywords: Model Order Reduction, Markov Parameters, Routh Approximation, Particle Swarm Optimization, Integral Squared Error, Steady State Stability.

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Authors: S. Cagin, X. Fischer, E. Delacourt, N. Bourabaa, C. Morin, D. Coutellier, B. Carré, S. Loumé

Abstract:

The complexity of scavenging by ports and its impact on engine efficiency create the need to understand and to model it as realistically as possible. However, there are few empirical scavenging models and these are highly specialized. In a design optimization process, they appear very restricted and their field of use is limited. This paper presents a comparison of two methods to establish and reduce a model of the scavenging process in 2-stroke diesel engines. To solve the lack of scavenging models, a CFD model has been developed and is used as the referent case. However, its large size requires a reduction. Two techniques have been tested depending on their fields of application: The NTF method and neural networks. They both appear highly appropriate drastically reducing the model’s size (over 90% reduction) with a low relative error rate (under 10%). Furthermore, each method produces a reduced model which can be used in distinct specialized fields of application: the distribution of a quantity (mass fraction for example) in the cylinder at each time step (pseudo-dynamic model) or the qualification of scavenging at the end of the process (pseudo-static model).

Keywords: Diesel engine, Design optimization, Model reduction, Neural network, NTF algorithm, Scavenging.

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Authors: A. Rangan, A. Tansu

Abstract:

This paper generalizes Yeh Lam-s shock model for renewal shock arrivals and random threshold. Several interesting statistical measures are explicitly obtained. A few special cases and an optimal replacement problem are also discussed.

Keywords: shock model, optimal replacement, random threshold, shocks.

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Authors: George N. Prodromidis, Frank A. Coutelieris

Abstract:

Biogas can be currently considered as an alternative option for electricity production, mainly due to its high energy content (hydrocarbon-rich source), its renewable status and its relatively low utilization cost. Solid Oxide Fuel Cell (SOFC) stacks convert fuel’s chemical energy to electricity with high efficiencies and reveal significant advantages on fuel flexibility combined with lower emissions rate, especially when utilize biogas. Electricity production by biogas constitutes a composite problem which incorporates an extensive parametric analysis on numerous dynamic variables. The main scope of the presented study is to propose a detailed thermodynamic model on the optimization of SOFC-based power plants’ operation based on fundamental thermodynamics, energy and exergy balances. This model named THERMAS (THERmodynamic MAthematical Simulation model) incorporates each individual process, during electricity production, mathematically simulated for different case studies that represent real life operational conditions. Also, THERMAS offers the opportunity to choose a great variety of different values for each operational parameter individually, thus allowing for studies within unexplored and experimentally impossible operational ranges. Finally, THERMAS innovatively incorporates a specific criterion concluded by the extensive energy analysis to identify the most optimal scenario per simulated system in exergy terms. Therefore, several dynamical parameters as well as several biogas mixture compositions have been taken into account, to cover all the possible incidents. Towards the optimization process in terms of an innovative OPF (OPtimization Factor), presented here, this research study reveals that systems supplied by low methane fuels can be comparable to these supplied by pure methane. To conclude, such an innovative simulation model indicates a perspective on the optimal design of a SOFC stack based system, in the direction of the commercialization of systems utilizing biogas.

Keywords: Biogas, Exergy, Optimization, SOFC.

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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: Weihua Ruan, Kuan-Chou Chen

Abstract:

This paper is concerned with a system of Hamilton-Jacobi-Bellman equations coupled with an autonomous dynamical system. The mathematical system arises in the differential game formulation of political economy models as an infinite-horizon continuous-time differential game with discounted instantaneous payoff rates and continuously and discretely varying state variables. The existence of a weak solution of the PDE system is proven and a computational scheme of approximate solution is developed for a class of such systems. A model of democratization is mathematically analyzed as an illustration of application.

Keywords: Differential games, Hamilton-Jacobi-Bellman equations, infinite horizon, political-economy models.

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Authors: Paola Lecca, Lorenzo Dematte

Abstract:

Reactiondiffusion systems are mathematical models that describe how the concentration of one or more substances distributed in space changes under the influence of local chemical reactions in which the substances are converted into each other, and diffusion which causes the substances to spread out in space. The classical representation of a reaction-diffusion system is given by semi-linear parabolic partial differential equations, whose general form is ÔêétX(x, t) = DΔX(x, t), where X(x, t) is the state vector, D is the matrix of the diffusion coefficients and Δ is the Laplace operator. If the solute move in an homogeneous system in thermal equilibrium, the diffusion coefficients are constants that do not depend on the local concentration of solvent and of solutes and on local temperature of the medium. In this paper a new stochastic reaction-diffusion model in which the diffusion coefficients are function of the local concentration, viscosity and frictional forces of solvent and solute is presented. Such a model provides a more realistic description of the molecular kinetics in non-homogenoeus and highly structured media as the intra- and inter-cellular spaces. The movement of a molecule A from a region i to a region j of the space is described as a first order reaction Ai k- → Aj , where the rate constant k depends on the diffusion coefficient. Representing the diffusional motion as a chemical reaction allows to assimilate a reaction-diffusion system to a pure reaction system and to simulate it with Gillespie-inspired stochastic simulation algorithms. The stochastic time evolution of the system is given by the occurrence of diffusion events and chemical reaction events. At each time step an event (reaction or diffusion) is selected from a probability distribution of waiting times determined by the specific speed of reaction and diffusion events. Redi is the software tool, developed to implement the model of reaction-diffusion kinetics and dynamics. It is a free software, that can be downloaded from http://www.cosbi.eu. To demonstrate the validity of the new reaction-diffusion model, the simulation results of the chaperone-assisted protein folding in cytoplasm obtained with Redi are reported. This case study is redrawing the attention of the scientific community due to current interests on protein aggregation as a potential cause for neurodegenerative diseases.

Keywords: Reaction-diffusion systems, Fick's law, stochastic simulation algorithm.

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Authors: Paola Lecca

Abstract:

Modeling and simulation of biochemical reactions is of great interest in the context of system biology. The central dogma of this re-emerging area states that it is system dynamics and organizing principles of complex biological phenomena that give rise to functioning and function of cells. Cell functions, such as growth, division, differentiation and apoptosis are temporal processes, that can be understood if they are treated as dynamic systems. System biology focuses on an understanding of functional activity from a system-wide perspective and, consequently, it is defined by two hey questions: (i) how do the components within a cell interact, so as to bring about its structure and functioning? (ii) How do cells interact, so as to develop and maintain higher levels of organization and functions? In recent years, wet-lab biologists embraced mathematical modeling and simulation as two essential means toward answering the above questions. The credo of dynamics system theory is that the behavior of a biological system is given by the temporal evolution of its state. Our understanding of the time behavior of a biological system can be measured by the extent to which a simulation mimics the real behavior of that system. Deviations of a simulation indicate either limitations or errors in our knowledge. The aim of this paper is to summarize and review the main conceptual frameworks in which models of biochemical networks can be developed. In particular, we review the stochastic molecular modelling approaches, by reporting the principal conceptualizations suggested by A. A. Markov, P. Langevin, A. Fokker, M. Planck, D. T. Gillespie, N. G. van Kampfen, and recently by D. Wilkinson, O. Wolkenhauer, P. S. Jöberg and by the author.

Keywords: Mathematical structure, algorithmic implementation, biochemical network models.

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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: Azam Marjani, Saeed Shirazian

Abstract:

In this study is presented a general methodology to predict the performance of a continuous near-critical fluid extraction process to remove compounds from aqueous solutions using hollow fiber membrane contactors. A comprehensive 2D mathematical model was developed to study Porocritical extraction process. The system studied in this work is a membrane based extractor of ethanol and acetone from aqueous solutions using near-critical CO2. Predictions of extraction percentages obtained by simulations have been compared to the experimental values reported by Bothun et al. [5]. Simulations of extraction percentage of ethanol and acetone show an average difference of 9.3% and 6.5% with the experimental data, respectively. More accurate predictions of the extraction of acetone could be explained by a better estimation of the transport properties in the aqueous phase that controls the extraction of this solute.

Keywords: Solvent extraction, Membrane, Mass transfer, Densegas, Modeling

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Authors: K. Djellabi, M. E. H. Latreche

Abstract:

Induction heating computer simulation is a powerful tool for process design and optimization, induction coil design, equipment selection, as well as education and business presentations. The authors share their vast experience in the practical use of computer simulation for different induction heating and heat treating processes. In this paper treated with mathematical modeling and numerical simulation of induction heating furnaces with axisymmetric geometries for the numerical solution, we propose finite element methods combined with boundary (FEM) for the electromagnetic model using COMSOL® Multiphysics Software. Some numerical results for an industrial furnace are shown with high frequency.

Keywords: Numerical methods, Induction furnaces, Induction Heating, Finite element method, Comsol Multiphysics software.

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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: 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: Tsun-Hui Huang, Shyue-Cheng Yang, Chiou-Fen Shieh

Abstract:

In this paper, a nonlinear constitutive law and a curve fitting, two relationships between the stress-strain and the shear stress-strain for sandstone material were used to obtain a second-order polynomial constitutive equation. Based on the established polynomial constitutive equations and Newton’s second law, a mathematical model of the non-homogeneous nonlinear wave equation under an external pressure was derived. The external pressure can be assumed as an impulse function to simulate a real earthquake source. A displacement response under nonlinear two-dimensional wave equation was determined by a numerical method and computer-aided software. The results show that a suit pressure in the sandstone generates the phenomenon of stress solitary waves.

Keywords: Polynomial constitutive equation, solitary.

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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: 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: Dini Endah Setyo Rahaju, Dian Retno Sari Dewi

Abstract:

This paper presents an application of the improved QFD method for determining the specifications of kitchen utensils rack. By using the improved method, the subjective nature in original QFD was reduced; particularly in defining the relationship between customer requirement and engineering characteristics. The regression analysis that was used for obtaining the relationship functions between customer requirement and engineering characteristics also accommodated the inaccurateness of the competitive assessment results. The improved method which is represented in the form of a mathematical model had become a formal guidance to allocate the resource for improving the specifications of kitchen utensils rack. The specifications obtained had led to the achievement of the highest feasible customer satisfaction.

Keywords: Customer satisfaction, kitchen utensils rack design, QFD, specifications.

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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: 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: Ana Pauna

Abstract:

The Expert Witness Testimony in the Battered Woman Syndrome Expert witness testimony (EWT) is a kind of information given by an expert specialized in the field (here in BWS) to the jury in order to help the court better understand the case. EWT does not always work in favor of the battered women. Two main decision-making models are discussed in the paper: the Mathematical model and the Explanation model. In the first model, the jurors calculate ″the importance and strength of each piece of evidence″ whereas in the second model they try to integrate the EWT with the evidence and create a coherent story that would describe the crime. The jury often misunderstands and misjudges battered women for their action (or in this case inaction). They assume that these women are masochists and accept being mistreated for if a man abuses a woman constantly, she should and could divorce him or simply leave at any time. The research in the domain found that indeed, expert witness testimony has a powerful influence on juror’s decisions thus its quality needs to be further explored. One of the important factors that need further studies is a bias called the dispositionist worldview (a belief that what happens to people is of their own doing). This kind of attributional bias represents a tendency to think that a person’s behavior is due to his or her disposition, even when the behavior is clearly attributed to the situation. Hypothesis The hypothesis of this paper is that if a juror has a dispositionist worldview then he or she will blame the rape victim for triggering the assault. The juror would therefore commit the fundamental attribution error and believe that the victim’s disposition caused the rape and not the situation she was in. Methods The subjects in the study were 500 randomly sampled undergraduate students from McGill, Concordia, Université de Montréal and UQAM. Dispositional Worldview was scored on the Dispositionist Worldview Questionnaire. After reading the Rape Scenarios, each student was asked to play the role of a juror and answer a questionnaire consisting of 7 questions about the responsibility, causality and fault of the victim. Results The results confirm the hypothesis which states that if a juror has a dispositionist worldview then he or she will blame the rape victim for triggering the assault. By doing so, the juror commits the fundamental attribution error because he will believe that the victim’s disposition, and not the constraints or opportunities of the situation, caused the rape scenario.

Keywords: bias, expert/witness testimony, attribution error, jury, rape myth

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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: Hassan Baghgar Bostan Abad, Ali Yazdian Varjani, Taheri Asghar

Abstract:

Variable speed drives are growing and varying. Drives expanse depend on progress in different part of science like power system, microelectronic, control methods, and so on. Artificial intelligent contains hard computation and soft computation. Artificial intelligent has found high application in most nonlinear systems same as motors drive. Because it has intelligence like human but there are no sentimental against human like angriness and.... Artificial intelligent is used for various points like approximation, control, and monitoring. Because artificial intelligent techniques can use as controller for any system without requirement to system mathematical model, it has been used in electrical drive control. With this manner, efficiency and reliability of drives increase and volume, weight and cost of them decrease.

Keywords: Artificial intelligent, electrical motor, intelligent drive and control,

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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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