Search results for: VX2 tumor model.

Authors: S. Chumkiew, W. Srisang, K. Jaroensutasinee, M. Jaroensutasinee

Abstract:

This work investigated the phenology of Parah tree (Elateriospermum tapos) using the General Purpose Atmosphere Plant Soil Simulator (GAPS model) to determine the amount of Plant Available Water (PAW) in the soil. We found the correlation between PAW and the timing of budburst and flower burst at Khao Nan National Park, Nakhon Si Thammarat, Thailand. PAW from the GAPS model can be used as an indicator of soil water stress. The low amount of PAW may lead to leaf shedding in Parah trees.

Keywords: Basic GAPS, Parah (Elateriospermum tapos), Phenology, Climate, Nakhon Si Thammarat, Thailand.

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Authors: Gracia V. Navarro, Maria V. Gonzalez, Carlos G. Reed

Abstract:

The eudaimonic perspective in philosophy and psychology suggests that a good life is closely related to developing oneself in order to contribute to the well-being and happiness of other people and of the world as a whole. Educational psychology can help to achieve this through the design and validation of educative models. Since 2004, the University of Concepcion and other Chilean universities apply an educative model to train socially responsible professionals, people that in the exercise of their profession contribute to generate equity for the development and assess the impacts of their decisions, opting for those that serve the common good. The main aim is to identify if a relationship exists between achieved learning, attitudes toward social responsibility, self-attribution of socially responsible behavior, value type, professional behavior observed and, participation in a specific model to train socially responsible (SR) professionals. The Achieved Learning and Attitudes Toward Social Responsibility Questionnaire, interview with employers and Values Questionnaire and Self-attribution of SR Behavior Questionnaire is applied to 394 students and graduates, divided into experimental and control groups (trained and not trained under the educative model), in order to identify the professional behavior of the graduates. The results show that students and graduates perceive cognitive, affective and behavioral learning, with significant differences in attitudes toward social responsibility and self-attribution of SR behavior, between experimental and control. There are also differences in employers' perceptions about the professional practice of those who were trained under the model and those who were not. It is concluded that the educative model has an impact on the learning of social responsibility and educates for a full life. It is also concluded that it is necessary to identify mediating variables of the model effect.

Keywords: Educative model, good life, professional social responsibility (SR), values.

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Authors: Ali Nadi, Ali Edrissi

Abstract:

Relief demand and transportation links availability is the essential information that is needed for every natural disaster operation. This information is not in hand once a disaster strikes. Relief demand and network condition has been evaluated based on prediction method in related works. Nevertheless, prediction seems to be over or under estimated due to uncertainties and may lead to a failure operation. Therefore, in this paper a stochastic programming model is proposed to evaluate real-time relief demand and network condition at the onset of a natural disaster. To address the time sensitivity of the emergency response, the proposed model uses reinforcement learning for optimization of the total relief assessment time. The proposed model is tested on a real size network problem. The simulation results indicate that the proposed model performs well in the case of collecting real-time information.

Keywords: Disaster management, real-time demand, reinforcement learning, relief demand.

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Authors: Ε. Giovanis

Abstract:

In this paper we present an autoregressive model with neural networks modeling and standard error backpropagation algorithm training optimization in order to predict the gross domestic product (GDP) growth rate of four countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer after the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model in the out-of-sample period. The idea behind this approach is to propose a parametric regression with weighted variables in order to test for the statistical significance and the magnitude of the estimated autoregressive coefficients and simultaneously to estimate the forecasts.

Keywords: Autoregressive model, Error back-propagation Feed-Forward neural networks, , Gross Domestic Product

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Authors: B. Kiyani, R. H. Amiri, S. H. Hosseini, A. Bourouni, A. Karimi

Abstract:

Nowadays, offshore's complicated facilities need their own communications requirements. Nevertheless, developing and real-world applications of new communications technology are faced with tremendous problems for new technology users, developers and implementers. Traditional systems engineering cannot be capable to develop a new technology effectively because it does not consider the dynamics of the process. This paper focuses on the design of a holistic model that represents the dynamics of new communication technology development within offshore industry. The model shows the behavior of technology development efforts. Furthermore, implementing this model, results in new and useful insights about the policy option analysis for developing a new communications technology in offshore industry.

Keywords: Technology development, Offshore industry, Systemdynamics, Voice Over IP.

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Authors: E. Giovanis

Abstract:

In this paper we present a Feed-Foward Neural Networks Autoregressive (FFNN-AR) model with genetic algorithms training optimization in order to predict the gross domestic product growth of six countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer of the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model. Moreover this technique can be used in Autoregressive-Moving Average models, with and without exogenous inputs, as also the training process with genetics algorithms optimization can be replaced by the error back-propagation algorithm.

Keywords: Autoregressive model, Feed-Forward neuralnetworks, Genetic Algorithms, Gross Domestic Product

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Authors: Mesbaholdin Salami, Farzad Movahedi Sobhani, Mohammad Sadegh Ghazizadeh

Abstract:

Evaluation of organizational performance is among the most important measures that help organizations and entities continuously improve their efficiency. Organizations can use the existing data and results from the comparison of units under investigation to obtain an estimation of their performance. The Malmquist Productivity Index (MPI) is an important index in the evaluation of overall productivity, which considers technological developments and technical efficiency at the same time. This article proposed a model based on the multistage MPI, considering limited data (Grey’s theory). This model can evaluate the performance of units using limited and uncertain data in a multistage process. It was applied by the electricity market manager to Iran’s electric power supply chain (EPSC), which contains uncertain data, to evaluate the performance of its actors. Results from solving the model showed an improvement in the accuracy of future performance of the units under investigation, using the Grey’s system theory. This model can be used in all case studies, in which MPI is used and there are limited or uncertain data.

Keywords: Malmquist Index, Grey's Theory, Charnes Cooper & Rhodes (CCR) Model, network data envelopment analysis, Iran electricity power chain.

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Authors: Siyuan Jing, Kun She

Abstract:

Neighborhood Rough Sets (NRS) has been proven to be an efficient tool for heterogeneous attribute reduction. However, most of researches are focused on dealing with complete and noiseless data. Factually, most of the information systems are noisy, namely, filled with incomplete data and inconsistent data. In this paper, we introduce a generalized neighborhood rough sets model, called VPTNRS, to deal with the problem of heterogeneous attribute reduction in noisy system. We generalize classical NRS model with tolerance neighborhood relation and the probabilistic theory. Furthermore, we use the neighborhood dependency to evaluate the significance of a subset of heterogeneous attributes and construct a forward greedy algorithm for attribute reduction based on it. Experimental results show that the model is efficient to deal with noisy data.

Keywords: attribute reduction, incomplete data, inconsistent data, tolerance neighborhood relation, rough sets

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Authors: Changhyuk Jang, Keechul Jung

Abstract:

Human pose estimation can be executed using Active Shape Models. The existing techniques for applying to human-body research using Active Shape Models, such as human detection, primarily take the form of silhouette of human body. This technique is not able to estimate accurately for human pose to concern two arms and legs, as the silhouette of human body represents the shape as out of round. To solve this problem, we applied the human body model as stick-figure, “skeleton". The skeleton model of human body can give consideration to various shapes of human pose. To obtain effective estimation result, we applied background subtraction and deformed matching algorithm of primary Active Shape Models in the fitting process. The images which were used to make the model were 600 human bodies, and the model has 17 landmark points which indicate body junction and key features of human pose. The maximum iteration for the fitting process was 30 times and the execution time was less than .03 sec.

Keywords: Active shape models, skeleton, pose estimation.

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Authors: Shoji Katagiri, Hugang Han

Abstract:

This paper clarifies the role of ICT capital in economic growth. Albeit ICT remarkably contributes to economic growth, there are few studies on ICT capital in ICT sector from theoretical point of view. In this paper, production function of ICT which is used as input of intermediate good in final good and ICT sectors is incorporated into our model. In this setting, we analyze the role of ICT on balance growth path and show the possibility of general equilibrium solutions for this model. Through the simulation of the equilibrium solutions, we find that when ICT impacts on economy and economic growth increases, it is necessary that increases of efficiency at ICT sector and of accumulation of non-ICT and ICT capitals occur simultaneously.

Keywords: Endogenous economic growth, ICT, intensity, capital accumulation.

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Authors: Ahmad Majdi Bin Abdul-Rani, Mesfin Gizaw, Yusri Yusof

Abstract:

Researches related to standard product model and development of neutral manufacturing interfaces for numerical control machines becomes a significant topic since the last 25 years. In this paper, a detail description of STEP implementation on turnmill manufacturing has been discussed. It shows requirements of information contents from ISO14649 data model. It covers to describe the design of STEP-NC framework applicable to turn-mill manufacturing. In the framework, EXPRESS-G and UML modeling tools are used to depict the information contents of the system and established the bases of information model requirement. A product and manufacturing data model applicable for STEP compliant manufacturing. The next generation turn-mill operations requirements have been represented by a UML diagram. An object oriented classes of ISO1449 has been developed on Visual Basic dot NET platform for binding the static information model represented by the UML diagram. An architect of the proposed system implementation has been given on the bases of the design and manufacturing module of STEP-NC interface established. Finally, a part 21 file process plan generated for an illustration of turn-mill components.

Keywords: CAPP, ISO14649, Product modeling, STEP-NC

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Authors: Samin Jirehbandei, Alireza Nemaney Pour

Abstract:

Bythe development of the Internet, e-commerce has got very popular between organizations. E-commerce means buying and selling products and services over the Internet. One of the challenging issues in e-commerce is how to attract the customers and how to satisfy them. Therefore, it is important to keep good relationship with the customers. This paper proposes a new model to increase the customer satisfaction by introducing live-operator. Live-operator is a system which is involved both with the customers and the organization.In this system the customers feelthatthey receive the service directly from the organization. This model decreases the response time and the customer loss. Moreover, it increases customer trust and the ability of organizations.

Keywords: Customer, Customer Satisfaction, e-Commerce, e-CRM, Live-Operator, Organization

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Authors: Myint Myint Yi, Khin Sandar Linn, Marlar Kyaw

Abstract:

This paper proposed a novel model for short term load forecast (STLF) in the electricity market. The prior electricity demand data are treated as time series. The model is composed of several neural networks whose data are processed using a wavelet technique. The model is created in the form of a simulation program written with MATLAB. The load data are treated as time series data. They are decomposed into several wavelet coefficient series using the wavelet transform technique known as Non-decimated Wavelet Transform (NWT). The reason for using this technique is the belief in the possibility of extracting hidden patterns from the time series data. The wavelet coefficient series are used to train the neural networks (NNs) and used as the inputs to the NNs for electricity load prediction. The Scale Conjugate Gradient (SCG) algorithm is used as the learning algorithm for the NNs. To get the final forecast data, the outputs from the NNs are recombined using the same wavelet technique. The model was evaluated with the electricity load data of Electronic Engineering Department in Mandalay Technological University in Myanmar. The simulation results showed that the model was capable of producing a reasonable forecasting accuracy in STLF.

Keywords: Neural network, Load forecast, Time series, wavelettransform.

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Authors: Ugur Akyol, Dinçer Akal, Ahmet Cihan, Kamil Kahveci

Abstract:

This study is concerned with the investigation of the suitability of several empirical and semi-empirical drying models available in the literature to define drying behavior of viscose yarn bobbins. For this purpose, firstly, experimental drying behaviour of viscose bobbins was determined on an experimental dryer setup which was designed and manufactured based on hot-air bobbin dryers used in textile industry. Afterwards, drying models considered were fitted to the experimentally obtained moisture ratios. Drying parameters were drying temperature and bobbin diameter. The fit was performed by selecting the values for constants in the models in such a way that these values make the sum of the squared differences between the experimental and the model results for moisture ratio minimum. Suitability of fitting was specified as comparing the correlation coefficient, standard error and mean square deviation. The results show that the most appropriate model in describing the drying curves of viscose bobbins is the Page model.

Keywords: Drying, moisture ratio, Page model, viscose

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Authors: Hycham Aboutaleb, Bruno Monsuez

Abstract:

Current systems complexity has reached a degree that requires addressing conception and design issues while taking into account environmental, operational, social, legal and financial aspects. Therefore, one of the main challenges is the way complex systems are specified and designed. The exponential growing effort, cost and time investment of complex systems in modeling phase emphasize the need for a paradigm, a framework and an environment to handle the system model complexity. For that, it is necessary to understand the expectations of the human user of the model and his limits. This paper presents a generic framework for designing complex systems, highlights the requirements a system model needs to fulfill to meet human user expectations, and suggests a graphbased formalism for modeling complex systems. Finally, a set of transformations are defined to handle the model complexity.

Keywords: Higraph-based, formalism, system engineering paradigm, modeling requirements, graph-based transformations.

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Authors: Manisha Chaudhary, Joydip Dhar, Govind Prasad Sahu

Abstract:

A mathematical model is proposed considering the forest biomass density B(t), density of wood based industries W(t) and density of synthetic industries S(t). It is assumed that the forest biomass grows logistically in the absence of wood based industries, but depletion of forestry biomass is due to presence of wood based industries. The growth of wood based industries depends on B(t), while S(t) grows at a constant rate, independent of B(t). Further there is a competition between W(t) and S(t) according to market demand. The proposed model has four ecologically feasible steady states, namely, E1: forest biomass free and wood industries free equilibrium; E2: wood industries free equilibrium and two coexisting equilibria E∗1 , E∗2 . Behavior of the system near all feasible equilibria is analyzed using the stability theory of differential equations. In the proposed model, the natural depletion rate h1 is a crucial parameter and system exhibits Hopf-bifurcation about the non-trivial equilibrium with respect to h1. The analytical results are verified using numerical simulation.

Keywords: A mathematical model, Competition between wood based and synthetic industries, Hopf-bifurcation, Stability analysis.

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Authors: Samy M. El-Behery, W. A. El-Askary, K. A. Ibrahim, Mofreh H. Hamed

Abstract:

A steady two-phase flow model has been developed to simulate the drying process of porous particle in a pneumatic conveying dryer. The model takes into account the momentum, heat and mass transfer between the continuous phase and the dispersed phase. A single particle model was employed to calculate the evaporation rate. In this model the pore structure is simplified to allow the dominant evaporation mechanism to be readily identified at all points within the duct. The predominant mechanism at any time depends upon the pressure, temperature and the diameter of pore from which evaporating is occurring. The model was validated against experimental studies of pneumatic transport at low and high speeds as well as pneumatic drying. The effects of operating conditions on the dryer parameters are studied numerically. The present results show that the drying rate is enhanced as the inlet gas temperature and the gas flow rate increase and as the solid mass flow rate deceases. The present results also demonstrate the necessity of measuring the inlet gas velocity or the solid concentration in any experimental analysis.

Keywords: Two-phase, gas-solid, pneumatic drying, pneumatic conveying, heat and mass transfer

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Authors: Fares Laouacheria, Said Kechida, Moncef Chabi

Abstract:

The objective of the study was based on the hydrological routing modelling for the continuous monitoring of the hydrological situation in the Moudjar river catchment, especially during floods with Hydrologic Engineering Center–Hydrologic Modelling Systems (HEC-HMS). The HEC-GeoHMS was used to transform data from geographic information system (GIS) to HEC-HMS for delineating and modelling the catchment river in order to estimate the runoff volume, which is used as inputs to the hydrological routing model. Two hydrological routing models were used, namely Muskingum and Muskingum routing models, for conducting this study. In this study, a comparison between the parameters of the Muskingum and Muskingum-Cunge routing models in HEC-HMS was used for modelling flood routing in the Moudjar river catchment and determining the relationship between these parameters and the physical characteristics of the river. The results indicate that the effects of input parameters such as the weighting factor "X" and travel time "K" on the output results are more significant, where the Muskingum routing model was more sensitive to input parameters than the Muskingum-Cunge routing model. This study can contribute to understand and improve the knowledge of the mechanisms of river floods, especially in ungauged river catchments.

Keywords: HEC-HMS, hydrological modelling, Muskingum routing model, Muskingum-Cunge routing model.

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Authors: Jui P. Hung, Yuan L. Lai, Tzuo L. Luo, Hsi H. Hsiao

Abstract:

The machining performance is determined by the frequency characteristics of the machine-tool structure and the dynamics of the cutting process. Therefore, the prediction of dynamic vibration behavior of spindle tool system is of great importance for the design of a machine tool capable of high-precision and high-speed machining. The aim of this study is to develop a finite element model to predict the dynamic characteristics of milling machine tool and hence evaluate the influence of the preload of the spindle bearings. To this purpose, a three dimensional spindle bearing model of a high speed engraving spindle tool was created. In this model, the rolling interfaces with contact stiffness defined by Harris model were used to simulate the spindle bearing components. Then a full finite element model of a vertical milling machine was established by coupling the spindle tool unit with the machine frame structure. Using this model, the vibration mode that had a dominant influence on the dynamic stiffness was determined. The results of the finite element simulations reveal that spindle bearing with different preloads greatly affect the dynamic behavior of the spindle tool unit and hence the dynamic responses of the vertical column milling system. These results were validated by performing vibration on the individual spindle tool unit and the milling machine prototype, respectively. We conclude that preload of the spindle bearings is an important component affecting the dynamic characteristics and machining performance of the entire vertical column structure of the milling machine.

Keywords: Dynamic compliance, Milling machine, Spindle unit, Bearing preload.

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Authors: K. Petcharaporn, S. Kumchoo

Abstract:

The acidity (citric acid) is the one of chemical content that can be refer to the internal quality and it’s a maturity index of tomato, The titratable acidity (%TA) can be predicted by a non-destructive method prediction by using the transmittance short wavelength (SW-NIR) spectroscopy in the wavelength range between 665-955 nm. The set of 167 tomato samples divided into groups of 117 tomatoes sample for training set and 50 tomatoes sample for test set were used to establish the calibration model to predict and measure %TA by partial least squares regression (PLSR) technique. The spectra were pretreated with MSC pretreatment and it gave the optimal result for calibration model as (R = 0.92, RMSEC = 0.03%) and this model obtained high accuracy result to use for %TA prediction in test set as (R = 0.81, RMSEP = 0.05%). From the result of prediction in test set shown that the transmittance SW-NIR spectroscopy technique can be used for a non-destructive method for %TA prediction of tomato.

Keywords: Tomato, quality, prediction, transmittance, titratable acidity, citric acid.

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Authors: Jiajia Pan, Hung Tao Shen

Abstract:

Freeze and thaw occurs seasonally in river banks in northern countries. Little is known on how the riverbank soil temperature responds to air temperature changes and how freeze and thaw develops in a river bank seasonally. This study presents a two-dimensional heat conduction model for numerical investigations of seasonal freeze and thaw processes in an idealized river bank. The model uses the finite difference method and it is convenient for applications. The model is validated with an analytical solution and a field case with soil temperature distributions. It is then applied to the idealized river bank in terms of partially and fully saturated conditions with or without ice cover influence. Simulated results illustrate the response processes of the river bank to seasonal air temperature variations. It promotes the understanding of freeze and thaw processes in river banks and prepares for further investigation of frost and thaw impacts on riverbank stability.

Keywords: Freeze and thaw, river banks, 2D model, heat conduction.

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Authors: A. Charlangsut, M. Boonthienthong, N. Rugthaicharoencheep

Abstract:

This paper proposes a mathematical model for transmission expansion employing optimization method with scenario analysis approach. Economic transmission planning, on the other hand, seeks investment opportunities so that network expansions can generate more economic benefits than the costs. This approach can be used as a decision model for building new transmission lines added to the existing transmission system minimizing costs of the entire system subject to various system’s constraints and consider of loss value of transmission system and N-1 checking. The results show that the proposed model is efficient to be applied for the larger scale of power system topology.

Keywords: Transmission Expansion Planning, Economic Dispatch, Scenario Analysis, Contingency.

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Authors: Enrico Rukzio, George N. Prezerakos, Giovanni Cortese, Eleftherios Koutsoloukas, Sofia Kapellaki

Abstract:

The paper focuses on the area of context modeling with respect to the specification of context-aware systems supporting ubiquitous applications. The proposed approach, followed within the SIMPLICITY IST project, uses a high-level system ontology to derive context models for system components which consequently are mapped to the system's physical entities. For the definition of user and device-related context models in particular, the paper suggests a standard-based process consisting of an analysis phase using the Common Information Model (CIM) methodology followed by an implementation phase that defines 3GPP based components. The benefits of this approach are further depicted by preliminary examples of XML grammars defining profiles and components, component instances, coupled with descriptions of respective ubiquitous applications.

Keywords: 3GPP, context, context-awareness, context model, information model, user model, XML

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Authors: Victoriano Valencia García, Luis Usero Aragonés, Eugenio J. Fernández Vicente

Abstract:

Nowadays, the successful implementation of ICTs is vital for almost any kind of organization. Good governance and ICT management are essential for delivering value, managing technological risks, managing resources and performance measurement. In addition, outsourcing is a strategic IT service solution which complements IT services provided internally in organizations. This paper proposes the measurement tools of a new holistic maturity model based on standards ISO/IEC 20000 and ISO/IEC 38500, and the frameworks and best practices of ITIL and COBIT, with a specific focus on IT outsourcing. These measurement tools allow independent validation and practical application in the field of higher education, using a questionnaire, metrics tables, and continuous improvement plan tables as part of the measurement process. Guidelines and standards are proposed in the model for facilitating adaptation to universities and achieving excellence in the outsourcing of IT services.

Keywords: IT Governance, IT Management, IT Services, Maturity Model, Measurement Tools, Outsourcing.

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Authors: M. Othman, N. Bhuiyan, G. J. Gouw

Abstract:

In today-s global and competitive market, manufacturing companies are working hard towards improving their production system performance. Most companies develop production systems that can help in cost reduction. Manufacturing systems consist of different elements including production methods, machines, processes, control and information systems. Human issues are an important part of manufacturing systems, yet most companies do not pay sufficient attention to them. In this paper, a workforce planning (WP) model is presented. A non-linear programming model is developed in order to minimize the hiring, firing, training and overtime costs. The purpose is to determine the number of workers for each worker type, the number of workers trained, and the number of overtime hours. Moreover, a decision support system (DSS) based on the proposed model is introduced using the Excel-Lingo software interfacing feature. This model will help to improve the interaction between the workers, managers and the technical systems in manufacturing.

Keywords: Decision Support System, Human Factors, Manufacturing System, Workforce Planning.

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Authors: Ashiquer Rahman, Hares Mohammad, Ummey Salma

Abstract:

A country’s hourly compensation and unemployment rates are two of its most crucial components. They are not merely statistics but they have profound effects on individual, families, country, and the economy. They are inversely related to one another. The increased hourly compensation in the manufacturing sector can have a favorable effect on job changing issues. Moreover, the relationship between hourly compensation and unemployment is complex and influenced by broader economic factors. In this paper, in order to determine the effect of hourly compensation on unemployment rate, we use the panel data regression models and evaluate the expected link between hourly compensation and unemployment rate. We estimate the fixed effects model (FEM), evaluate the error components model (ECM), and determine which model (the FEM or ECM) is better through pooling all 60 observations. We then analyze and review the data by comparing countries (United States, Canada and the United Kingdom) using panel data regression models. Finally, we provide result, analysis and a summary of this extensive research on how the hourly compensation affects unemployment rate. Additionally, this paper offers relevant and useful guideline for the government and academic community to use an econometrics and social approach for the hourly compensation on unemployment rate to eliminate the problem.

Keywords: Hourly compensation, unemployment rate, panel data regression models, dummy variables, random effects model, fixed effects model, the linear regression model.

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Authors: K.Ramesh, A.Nirmalkumar, G.Gurusamy

Abstract:

In this paper, a new model order reduction phenomenon is introduced at the design stage of linear phase digital IIR filter. The complexity of a system can be reduced by adopting the model order reduction method in their design. In this paper a mixed method of model order reduction is proposed for linear IIR filter. The proposed method employs the advantages of factor division technique to derive the reduced order denominator polynomial and the reduced order numerator is obtained based on the resultant denominator polynomial. The order reduction technique is used to reduce the delay units at the design stage of IIR filter. The validity of the proposed method is illustrated with design example in frequency domain and stability is also examined with help of nyquist plot.

Keywords: Error index (J), Factor division method, IIR filter, Nyquist plot, Order reduction.

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Authors: S. Gao, S. Srirattayawong

Abstract:

In this study, a computational fluid dynamics (CFD) model has been developed for studying the effect of surface roughness profile on the EHL problem. The cylinders contact geometry, meshing and calculation of the conservation of mass and momentum equations are carried out using the commercial software packages ICEMCFD and ANSYS Fluent. The user defined functions (UDFs) for density, viscosity and elastic deformation of the cylinders as the functions of pressure and temperature are defined for the CFD model. Three different surface roughness profiles are created and incorporated into the CFD model. It is found that the developed CFD model can predict the characteristics of fluid flow and heat transfer in the EHL problem, including the main parameters such as pressure distribution, minimal film thickness, viscosity, and density changes. The results obtained show that the pressure profile at the center of the contact area directly relates to the roughness amplitude. A rough surface with kurtosis value of more than 3 has greater influence over the fluctuated shape of pressure distribution than in other cases.

Keywords: CFD, EHL, Kurtosis, Surface roughness.

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Authors: M. Norouzi, M. H. Kayhani, M. R. H. Nobari, M. Karimi Demneh

Abstract:

In this paper, fully developed flow and heat transfer of viscoelastic materials in curved ducts with square cross section under constant heat flux have been investigated. Here, staggered mesh is used as computational grids and flow and heat transfer parameters have been allocated in this mesh with marker and cell method. Numerical solution of governing equations has being performed with FTCS finite difference method. Furthermore, Criminale-Eriksen- Filbey (CEF) constitutive equation has being used as viscoelastic model. CEF constitutive equation is a suitable model for studying steady shear flow of viscoelastic materials which is able to model both effects of the first and second normal stress differences. Here, it is shown that the first and second normal stresses differences have noticeable and inverse effect on secondary flows intensity and mean Nusselt number which is the main novelty of current research.

Keywords: Viscoelastic, fluid flow, heat convection, CEF model, curved duct, square cross section.

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Authors: N. Sopipan, A. Intarasit, K. Chuarkham

Abstract:

 In this paper, we forecast the volatility of Baht/USDs using Markov Regime Switching GARCH (MRS-GARCH) models. These models allow volatility to have different dynamics according to unobserved regime variables. The main purpose of this paper is to find out whether MRS-GARCH models are an improvement on the GARCH type models in terms of modeling and forecasting Baht/USD volatility. The MRS-GARCH is the best performance model for Baht/USD volatility in short term but the GARCH model is best perform for long term.

Keywords: Volatility, Markov Regime Switching, Forecasting.

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