Search results for: fuzzy model

Authors: Yi-Hsien Wang, Fu-Ju Yang, Hwa-Rong Shen, Rui-Lin Tseng

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The business is notably related to the market risk according to the increase of liberalization of financial markets. Hence, the company usually utilized high financial leverage of derivatives to hedge the risk. When the company choose different hedging instruments to face a variety of exchange rate risk, we employ the Multinomial Logistic-AHP to analyze the impact of various derivatives. Hence, the research summarized the literature on relevant factors affecting managers selected exchange rate hedging instruments, using Multinomial Logistic Model and and further integrate AHP. Using Experts’ Questionnaires can test multi-level selection and hedging effect of different hedging instruments in order to calculate the hedging instruments and the multi-level factors of weights to understand the gap between the empirical results and practical operation. Finally, the Multinomial Logistic-AHP Model will sort the weights to analyze. The research findings can be a basis reference for investors in decision-making.

Keywords: exchange rate risk, derivatives, hedge, multinomial logistic-AHP

Procedia PDF Downloads 428

Authors: Andres Nieto-Leal, Victor N. Kaliakin, Tania P. Molina

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The nature of most engineering materials is quite complex. It is, therefore, difficult to devise a general mathematical model that will cover all possible ranges and types of excitation and behavior of a given material. As a result, the development of mathematical models is based upon simplifying assumptions regarding material behavior. Such simplifications result in some material idealization; for example, one of the simplest material idealization is to assume that the material behavior obeys the elasticity. However, soils are nonhomogeneous, anisotropic, path-dependent materials that exhibit nonlinear stress-strain relationships, changes in volume under shear, dilatancy, as well as time-, rate- and temperature-dependent behavior. Over the years, many constitutive models, possessing different levels of sophistication, have been developed to simulate the behavior geomaterials, particularly cohesive soils. Early in the development of constitutive models, it became evident that elastic or standard elastoplastic formulations, employing purely isotropic hardening and predicated in the existence of a yield surface surrounding a purely elastic domain, were incapable of realistically simulating the behavior of geomaterials. Accordingly, more sophisticated constitutive models have been developed; for example, the bounding surface elastoplasticity. The essence of the bounding surface concept is the hypothesis that plastic deformations can occur for stress states either within or on the bounding surface. Thus, unlike classical yield surface elastoplasticity, the plastic states are not restricted only to those lying on a surface. Elastoplastic bounding surface models have been improved; however, there is still need to improve their capabilities in simulating the response of anisotropically consolidated cohesive soils, especially the response in extension tests. Thus, in this work an improved constitutive model that can more accurately predict diverse stress-strain phenomena exhibited by cohesive soils was developed. Particularly, an improved rotational hardening rule that better simulate the response of cohesive soils in extension. The generalized definition of the bounding surface model provides a convenient and elegant framework for unifying various previous versions of the model for anisotropically consolidated cohesive soils. The Generalized Bounding Surface Model for cohesive soils is a fully three-dimensional, time-dependent model that accounts for both inherent and stress induced anisotropy employing a non-associative flow rule. The model numerical implementation in a computer code followed an adaptive multistep integration scheme in conjunction with local iteration and radial return. The one-step trapezoidal rule was used to get the stiffness matrix that defines the relationship between the stress increment and the strain increment. After testing the model in simulating the response of cohesive soils through extensive comparisons of model simulations to experimental data, it has been shown to give quite good simulations. The new model successfully simulates the response of different cohesive soils; for example, Cardiff Kaolin, Spestone Kaolin, and Lower Cromer Till. The simulated undrained stress paths, stress-strain response, and excess pore pressures are in very good agreement with the experimental values, especially in extension.

Keywords: bounding surface elastoplasticity, cohesive soils, constitutive model, modeling of geomaterials

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Authors: Michal Biały, Konrad Pietrykowski, Rafal Sochaczewski

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The kinematics and dynamics analysis of crank-piston system of aircraft engine. The object of the study was the high power aircraft engine ASz 62-IR. This engine is produced by a Polish company WSK "PZL-KALISZ" S.A.". All analyzes were performed numerically using CAD and CAE environment. Three-dimensional model of the crank-piston system was developed based on real engine located in the Laboratory of Centre of Innovation and Advanced Technologies of Lublin University of Technology. During the development of the model, the technique of reverse engineering - 3D scanning was used. ASz 62-IR engine is characterized by a radial type of crank-piston system. In this system the cylinders are arranged radially around the circle. This crank-piston system consists of a main connecting rod and eight additional connecting rods. In addition, three-dimensional model consists of a piston pins, pistons and piston rings. As a result of the specific engine design, characteristics of the piston individual movement are slightly different from each other. But the model assumes that they are the same during the analysis. Three-dimensional model of the engine was implemented into the MSC Adams software. The environment of MSC Adams allows for multibody simulation of the dynamic phenomena. This determines the state parameters of the moving elements, among which the load or force distribution on each kinematic node can be distinguished. Materials and characteristic materials parameters were adopted on the basis of commonly used materials for engine parts. The mass values of individual elements were adopted on the basis of real engine parts. The piston gas forces were replaced by calculation of pressure variations recorded during engine tests on the engine test bench. The research the changes of forces acting in the individual kinematic pairs of crank-piston system. The model allows to determine the load on the crankshaft main bearings. This gives the possibility for the main supports forces analysis The model allows for testing and simulation of kinematics and dynamics of a radial aircraft engine. This is the first stage of the work, which aims to numerical simulation of vibration of multi-cylinder aircraft engine. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.

Keywords: aircraft engine, CAD, CAE, dynamics, kinematics, MSC Adams, numerical simulation

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Authors: Dongju Kim, Youngjoo Suh, Hyojin Kim, Gyeongyeong Kim

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Acoustic Emission Testing (AET) is widely used to test the structural integrity of an operational hydrogen storage container, and clustering algorithms are frequently used in pattern recognition methods to interpret AET results. However, the interpretation of AET results can vary from user to user as the tuning of the relevant parameters relies on the user's experience and knowledge of AET. Therefore, it is necessary to use a deep learning model to identify patterns in acoustic emission (AE) signal data that can be used to classify defects instead. In this paper, a deep learning-based model for classifying the types of defects in hydrogen storage tanks, using AE sensor waveforms, is proposed. As hydrogen storage tanks are commonly constructed using carbon fiber reinforced polymer composite (CFRP), a defect classification dataset is collected through a tensile test on a specimen of CFRP with an AE sensor attached. The performance of the classification model, using one-dimensional convolutional neural network (1-D CNN) and synthetic minority oversampling technique (SMOTE) data augmentation, achieved 91.09% accuracy for each defect. It is expected that the deep learning classification model in this paper, used with AET, will help in evaluating the operational safety of hydrogen storage containers.

Keywords: acoustic emission testing, carbon fiber reinforced polymer composite, one-dimensional convolutional neural network, smote data augmentation

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Authors: T. Yuri, M. Zagloel, Inaki M. Hakim, Tegu Bintang Nugraha

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In an era of customer centricity, automotive parts manufacturer in Indonesia must be able to keep up with the uncertainty and fluctuation of consumer demand. Flexible Manufacturing System (FMS) is a strategy to react to predicted and unpredicted changes of demand in automotive industry. This research is about flexible mixed model assembly line design through Value Stream Mapping (VSM) and Line Balancing in mixed model assembly line prior to simulation. It uses value stream mapping to identify and reduce waste while finding the best position to add or reduce manpower. Line balancing is conducted to minimize or maximize production rate while increasing assembly line productivity and efficiency. Results of this research is a recommendation of standard work combination for specifics demand scenario which can enhance assembly line efficiency and productivity.

Keywords: automotive industry, demand uncertainty, flexible assembly system, line balancing, value stream mapping

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Authors: Jutamas Wisansing, Thanakarn Vongvisitsin, Udom Hongchatikul

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Designated Areas for Sustainable Tourism Administration (DASTA) is a public organization, dedicating to sustainable tourism development in 6 designated areas in Thailand. This paper provides rich reflections from a decade of DASTA, formulating an advanced model to deepen our understanding of 2 key intertwining issues; 1) what are the new landscapes of actors for community based tourism and 2) who are the benefactors and beneficiaries of tourism development within the community? An action research approach was used, enabling the process and evidence-based cases to be better captured. The aim is to build theoretical foundation through 13 communities/cases, which have engaged in community based tourism pilot projects. Drawing from emic and qualitative research, specific and contextual phenomenon provides succinct patterns of ‘Community Benefitting through Tourism (CbtT)’ model. The re-definition of the 2 key issues helps shape the interlinking of actors; practicalities of inclusive tourism and inter-sectoral framework and its value chain will also be set forth. In tourism sector, community members could be active primarily on the supply side as employees, entrepreneurs and local heritage experts. CbtT when well defined stimulates the entire value chain of local economy while promoting social innovation through positive dialogue with wider actors. Collaboration with a new set of actors who are from the tourism-related businesses and non-tourism related businesses create better impacts on mutual benefits.

Keywords: community based tourism, community benefitting through tourism -CbtT DASTA model, sustainable tourism in thailand, value chain and inclusive business

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Authors: David Percy

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Landslides are a geologic phenomenon that affects a large number of inhabited places and are constantly being monitored and studied for the prediction of future occurrences. Reconstructability analysis (RA) is a methodology for extracting informative models from large volumes of data that work exclusively with discrete data. While RA has been used in medical applications and social science extensively, we are introducing it to the spatial sciences through applications like landslide prediction. Since RA works exclusively with discrete data, such as soil classification or bedrock type, working with continuous data, such as porosity, requires that these data are binned for inclusion in the model. RA constructs models of the data which pick out the most informative elements, independent variables (IVs), from each layer that predict the dependent variable (DV), landslide occurrence. Each layer included in the model retains its classification data as a primary encoding of the data. Unlike other machine learning algorithms that force the data into one-hot encoding type of schemes, RA works directly with the data as it is encoded, with the exception of continuous data, which must be binned. The usual physical and derived layers are included in the model, and testing our results against other published methodologies, such as neural networks, yields accuracy that is similar but with the advantage of a completely transparent model. The results of an RA session with a data set are a report on every combination of variables and their probability of landslide events occurring. In this way, every combination of informative state combinations can be examined.

Keywords: reconstructability analysis, machine learning, landslides, raster analysis

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Authors: Salman Obaidoon, Mohamed Hassan, Omer Bakather

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As environmental regulations increase, the need for a clean and inexpensive energy is becoming necessary these days using an available raw material with high efficiency and low emissions of toxic gases. This paper presents a study on modifying a gas turbine power plant fired by diesel, which is located in Saudi Arabia in order to increase the efficiency and capacity of the station as well as decrease the rate of emissions. The studied power plant consists of 30 units with different capacities and total net power is 1470 MW. The study was conducted on unit number 25 (GT-25) which produces 72.3 MW with 29.5% efficiency. In the beginning, the unit was modeled and simulated by using WinSim Design II software. In this step, actual unit data were used in order to test the validity of the model. The net power and efficiency obtained from software were 76.4 MW and 32.2% respectively. A difference of about 6% was found in the simulated power plant compared to the actual station which means that the model is valid. After the validation of the model, the simple gas turbine power plant was converted to a combined cycle power plant (CCPP). In this case, the exhausted gas released from the gas turbine was introduced to a heat recovery steam generator (HRSG), which consists of three heat exchangers: an economizer, an evaporator and a superheater. In this proposed model, many scenarios were conducted in order to get the optimal operating conditions. The net power of CCPP was increased to 116.4 MW while the overall efficiency of the unit was reached to 49.02%, consuming the same amount of fuel for the gas turbine power plant. For the purpose of comparing the rate of emissions of carbon dioxide on each model. It was found that the rate of CO₂ emissions was decreased from 15.94 kg/s to 9.22 kg/s by using the combined cycle power model as a result of reducing of the amount of diesel from 5.08 kg/s to 2.94 kg/s needed to produce 76.5 MW. The results indicate that the rate of emissions of carbon dioxide was decreased by 42.133% in CCPP compared to the simple gas turbine power plant.

Keywords: combined cycle power plant, efficiency, heat recovery steam generator, simulation, validation, WinSim design II software

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Authors: Schehrazad Selmane

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We present a deterministic model which describes the dynamics of tuberculosis in Algerian population where the vaccination program with BCG is in place since 1969 and where the WHO recommendations regarding the DOTS (directly observed treatment, short course) strategy are in application. The impact of an intervention program, targeting recently infected people among all close contacts of active cases and their treatment to prevent endogenous reactivation, on the incidence of tuberculosis, is investigated. We showed that a widespread treatment of latently infected individuals for some years is recommended to shift from higher to lower equilibrium state and thereafter relaxation is recommended.

Keywords: deterministic model, reproduction number, stability, tuberculosis

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Authors: Zunaira Asif, Zhi Chen

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The sustainable measures on air quality management are recognized as one of the most serious environmental concerns in the mining region. The mining operations emit various types of pollutants which have significant impacts on the environment. This study presents a stochastic control strategy by developing the air pollution control model to achieve a cost-effective solution. The optimization method is formulated to predict the cost of treatment using linear programming with an objective function and multi-constraints. The constraints mainly focus on two factors which are: production of metal should not exceed the available resources, and air quality should meet the standard criteria of the pollutant. The applicability of this model is explored through a case study of an open pit metal mine, Utah, USA. This method simultaneously uses meteorological data as a dispersion transfer function to support the practical local conditions. The probabilistic analysis and the uncertainties in the meteorological conditions are accomplished by Monte Carlo simulation. Reasonable results have been obtained to select the optimized treatment technology for PM_2.5, PM₁₀, NO_x, and SO₂. Additional comparison analysis shows that baghouse is the least cost option as compared to electrostatic precipitator and wet scrubbers for particulate matter, whereas non-selective catalytical reduction and dry-flue gas desulfurization are suitable for NO_x and SO₂ reduction respectively. Thus, this model can aid planners to reduce these pollutants at a marginal cost by suggesting control pollution devices, while accounting for dynamic meteorological conditions and mining activities.

Keywords: air pollution, linear programming, mining, optimization, treatment technologies

Procedia PDF Downloads 188

Authors: Thiago Victor Cordeiro Marcos, Joao Felipe de Araujo Martos, Ronaldo de Lima Cardoso, David Romanelli Pinto, Paulo Gilberto de Paula Toro, Israel da Silveira Rego, Antonio Carlos de Oliveira

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Currently, the use of 3D rapid prototyping, also known as 3D printing, has been investigated by some universities around the world as an innovative technique, fast, flexible and cheap for a direct plastic models manufacturing that are lighter and with complex geometries to be tested for hypersonic shock tunnel. Initially, the purpose is integrated prototyped parts with metal models that actually are manufactured through of the conventional machining and hereafter replace them with completely prototyped models. The mechanical design models to be tested in hypersonic shock tunnel are based on conventional manufacturing processes, therefore are limited forms and standard geometries. The use of 3D rapid prototyping offers a range of options that enables geometries innovation and ways to be used for the design new models. The conception and project of a prototyped model for hypersonic shock tunnel should be rethought and adapted when comparing the conventional manufacturing processes, in order to fully exploit the creativity and flexibility that are allowed by the 3D prototyping process. The objective of this paper is to compare the conception and project of a 3D rapid prototyping model and a conventional machining model, while showing the advantages and disadvantages of each process and the benefits that 3D prototyping can bring to the manufacture of models to be tested in hypersonic shock tunnel.

Keywords: 3D printing, 3D prototyping, experimental research, hypersonic shock tunnel

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Authors: Mehdi Mirzaei Alavijeh, Farzad Jalilian

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Background: Marijuana is the most widely used illicit drug worldwide, especially among adolescents and young adults, which can cause numerous complications. The aim of this study was to determine the pattern, motivation use, and factors related to marijuana use among Iranian youths based on the integrative model of behavioral prediction Methods: A cross-sectional study was conducted among 174 youths marijuana user in Kermanshah County and Isfahan County, during summer 2014 which was selected with the convenience sampling for participation in this study. A self-reporting questionnaire was applied for collecting data. Data were analyzed by SPSS version 21 using bivariate correlations and linear regression statistical tests. Results: The mean marijuana use of respondents was 4.60 times at during week [95% CI: 4.06, 5.15]. Linear regression statistical showed, the structures of integrative model of behavioral prediction accounted for 36% of the variation in the outcome measure of the marijuana use at during week (R2 = 36% & P < 0.001); and among them attitude, marijuana refuse, and subjective norms were a stronger predictors. Conclusion: Comprehensive health education and prevention programs need to emphasize on cognitive factors that predict youth’s health-related behaviors. Based on our findings it seems, designing educational and behavioral intervention for reducing positive belief about marijuana, marijuana self-efficacy refuse promotion and reduce subjective norms encourage marijuana use has an effective potential to protect youths marijuana use.

Keywords: marijuana, youth, integrative model of behavioral prediction, Iran

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Authors: Reza Lotfalian, Sudarshan Martins, Peter Radziszewski

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The effect of reliability on life-cycle cost, including initial and maintenance cost of a system is studied. The failure probability of a component is used to calculate the average maintenance cost during the operation cycle of the component. The standard deviation of the life-cycle cost is also calculated as an error measure for the average life-cycle cost. As a numerical example, the model is used to study the average life cycle cost of an electric motor.

Keywords: initial cost, life-cycle cost, maintenance cost, reliability

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Authors: Yan Lyu, Yiqun Pan, Zhizhong Huang

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In the design stage of a new building, the energy model of this building is often required for the analysis of the performance on energy efficiency. In practice, a certain degree of geometric simplification should be done in the establishment of building energy models, since the detailed geometric features of a real building are hard to be described perfectly in most energy simulation engine, such as ESP-r, eQuest or EnergyPlus. Actually, the detailed description is not necessary when the result with extremely high accuracy is not demanded. Therefore, this paper analyzed the relationship between the error of the simulation result from building energy models and the geometric simplification of the models. Finally, the following two parameters are selected as the indices to characterize the geometric feature of in building energy simulation: the southward projected area and total side surface area of the building, Based on the parameterization method, the simplification from an arbitrary column building to a typical shape (a cuboid) building can be made for energy modeling. The result in this study indicates that this simplification would only lead to the error that is less than 7% for those buildings with the ratio of southward projection length to total perimeter of the bottom of 0.25~0.35, which can cover most situations.

Keywords: building energy model, simulation, geometric simplification, design, regression

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Authors: Juan Portoviejo Brito, Daniel Icaza Alvarez, Christian Castro Samaniego

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In this article, we present the modeling, simulations, and energy conversion analysis of the solar-wind system for the Quingeo Heritage Center in Ecuador. A numerical model was constructed based on the 19 equations, it was coded in MATLAB R2017a, and the results were compared with the experimental data of the site. The model is built with the purpose of using it as a computer development for the optimization of resources and designs of hybrid systems in the Parish of Quingeo and its surroundings. The model obtained a fairly similar pattern compared to the data and curves obtained in the field experimentally and detailed in manuscript. It is important to indicate that this analysis has been carried out so that in the near future one or two of these power generation systems can be exploited in a massive way according to the budget assigned by the Parish GAD of Quingeo or other national or international organizations with the purpose of preserving this unique colonial helmet in Ecuador.

Keywords: hybrid system, wind turbine, modeling, simulation, Smart Grid, Quingeo Azuay Ecuador

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Authors: J. Bahrawi, M. Elhag

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Estimation of evapotranspiration is always a major component in water resources management. Traditional techniques of calculating daily evapotranspiration based on field measurements are valid only for local scales. Earth observation satellite sensors are thus used to overcome difficulties in obtaining daily evapotranspiration measurements on regional scale. The Surface Energy Balance System (SEBS) model was adopted to estimate daily evapotranspiration and relative evaporation along with other land surface energy fluxes. The model requires agro-climatic data that improve the model outputs. Advance Along Track Scanning Radiometer (AATSR) and Medium Spectral Resolution Imaging Spectrometer (MERIS) imageries were used to estimate the daily evapotranspiration and relative evaporation over the entire Nile Delta region in Egypt supported by meteorological data collected from six different weather stations located within the study area. Daily evapotranspiration maps derived from SEBS model show a strong agreement with actual ground-truth data taken from 92 points uniformly distributed all over the study area. Moreover, daily evapotranspiration and relative evaporation are strongly correlated. The reliable estimation of daily evapotranspiration supports the decision makers to review the current land use practices in terms of water management, while enabling them to propose proper land use changes.

Keywords: daily evapotranspiration, relative evaporation, SEBS, AATSR, MERIS, Nile Delta

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Authors: Le Ngoc Hung, Abriak Nor Edine, Binetruy Christophe, Benzerzour Mahfoud, Shahrour Isam, Patrice Rivard

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Bottom ash from Municipal Solid Waste Incineration (MSWI) can be viewed as a typical granular material because these industrial by-products result from the incineration of various domestic wastes. MSWI bottom ashes are mainly used in road engineering in substitution of the traditional natural aggregates. As the characterization of their mechanical behavior is essential in order to use them, specific studies have been led over the past few years. In the first part of this paper, the mechanical behavior of MSWI bottom ash is studied with triaxial tests. After analysis of the experiment results, the simulation of triaxial tests is carried out by using the software package CESAR-LCPC. As the first approach in modeling of this new class material, the Mohr-Coulomb model was chosen to describe the evolution of material under the influence of external mechanical actions.

Keywords: bottom ash, granular material, triaxial test, mechanical behavior, simulation, Mohr-Coulomb model, CESAR-LCPC

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Authors: Getachew Tilahun, Oluwole Makinde, David Malonza

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We propose and analyze a non-linear mathematical model for the transmission dynamics of pneumonia disease in a population of varying size. The deterministic compartmental model is studied using stability theory of differential equations. The effective reproduction number is obtained and also the local and global asymptotically stability conditions for the disease free and as well as for the endemic equilibria are established. The model exhibit a backward bifurcation and the sensitivity indices of the basic reproduction number to the key parameters are determined. Using Pontryagin’s maximum principle, the optimal control problem is formulated with three control strategies; namely disease prevention through education, treatment and screening. The cost effectiveness analysis of the adopted control strategies revealed that the combination of prevention and treatment is the most cost effective intervention strategies to combat the pneumonia pandemic. Numerical simulation is performed and pertinent results are displayed graphically.

Keywords: cost effectiveness analysis, optimal control, pneumonia dynamics, stability analysis, numerical simulation

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Authors: Juan M. Rodriguez-Diaz

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The precision of parameter estimators in the Gaussian linear model is traditionally accounted by the variance-covariance matrix of the asymptotic distribution. However, this measure can underestimate the true variance, specially for small samples. Traditionally, optimal design theory pays attention to this variance through its relationship with the model's information matrix. For this reason it seems convenient, at least in some cases, adapt the optimality criteria in order to get the best designs for the actual variance structure, otherwise the loss in efficiency of the designs obtained with the traditional approach may be very important.

Keywords: correlated observations, information matrix, optimality criteria, variance-covariance matrix

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Authors: Somdech Rungsrisawat

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The objective of this research was to investigate how to develop an appropriate management and administration model for the College of Film, Television, Multimedia and Performing Arts at Suan Sunandha Rajabhat University. A combination of qualitative and quantitative data collection and analysis methods was employed. The data collection was from the 8 experts who were the academic staff and entrepreneurs in films, television, multimedia and performing arts, and from 471 students studying in the communication arts field. The findings of this research paper presented the appropriate management and administration model for the College of Film, Television, Multimedia and Performing Arts, which depended on 3 factors: [i] the marketing management and the supporting facilities such as buildings, equipments and accessibility for students to the college; [ii] the competency of academic staff or lecturers and supporting staff; and [iii] career opportunities after graduation.

Keywords: educational institution management, educational management, learning resources, non-formal education, Thai qualifications framework for higher education

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Authors: Afshan Saad, Muhammad Saad, Shah Muhammad Emaduddin

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Nowadays the business condition is so quick paced that enhancing ourselves consistently has turned into a huge factor for the presence of an undertaking. We can check this for structural building and significantly more so in the quick-paced universe of data innovation and programming designing. The lithe philosophies, similar to Scrum, have a devoted advance in the process that objectives the enhancement of the improvement procedure and programming items. Pivotal to process enhancement is to pick up data that grants you to assess the condition of the procedure and its items. From the status data, you can design activities for the upgrade and furthermore assess the accomplishment of those activities. This investigation builds a model that measures the product nature of the improvement procedure. The product quality is dependent on the useful and auxiliary nature of the product items, besides the nature of the advancement procedure is likewise vital to enhance programming quality. Utilitarian quality covers the adherence to client prerequisites, while the auxiliary quality tends to the structure of the product item's source code with reference to its practicality. The procedure quality is identified with the consistency and expectedness of the improvement procedure. The product quality model is connected in a business setting by social occasion the information for the product measurements in the model. To assess the product quality model, we investigate the information and present it to the general population engaged with the light-footed programming improvement process. The outcomes from the application and the client input recommend that the model empowers a reasonable evaluation of the product quality and that it very well may be utilized to help the persistent enhancement of the advancement procedure and programming items.

Keywords: Agile SDLC Tools, Agile Software development, business value, enterprise applications, IBM, IBM Rational Team Concert, RTC, software quality, software metrics

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Authors: A. A. Okafor, C. H. Achebe, J. L. Chukwuneke, C. G. Ozoegwu

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The performance of an engine whose basic design parameters are known can be predicted with the assistance of simulation programs into the less time, cost and near value of actual. This paper presents a comprehensive mathematical model of the performance parameters of four stroke spark ignition engine. The essence of this research work is to develop a mathematical model for the analysis of engine performance parameters of four stroke spark ignition engine before embarking on full scale construction, this will ensure that only optimal parameters are in the design and development of an engine and also allow to check and develop the design of the engine and it’s operation alternatives in an inexpensive way and less time, instead of using experimental method which requires costly research test beds. To achieve this, equations were derived which describe the performance parameters (sfc, thermal efficiency, mep and A/F). The equations were used to simulate and optimize the engine performance of the model for various engine speeds. The optimal values obtained for the developed bivariate mathematical models are: sfc is 0.2833kg/kwh, efficiency is 28.77% and a/f is 20.75.

Keywords: bivariate models, engine performance, injector engine, optimization, performance parameters, simulation, spark ignition

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Authors: M. Alsharqawi, T. Zayed, S. Abu Dabous

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To ensure safety and serviceability of bridge infrastructure, accurate condition assessment and rating methods are needed to provide basis for bridge Maintenance, Repair and Replacement (MRR) decisions. In North America, the common practices to assess condition of bridges are through visual inspection. These practices are limited to detect surface defects and external flaws. Further, the thresholds that define the severity of bridge deterioration are selected arbitrarily. The current research discusses the main deteriorations and defects identified during visual inspection and Non-Destructive Evaluation (NDE). NDE techniques are becoming popular in augmenting the visual examination during inspection to detect subsurface defects. Quality inspection data and accurate condition assessment and rating are the basis for determining appropriate MRR decisions. Thus, in this paper, a novel method for bridge condition assessment using the Quality Function Deployment (QFD) theory is utilized. The QFD model is designed to provide an integrated condition by evaluating both the surface and subsurface defects for concrete bridges. Moreover, an integrated condition rating index with four thresholds is developed based on the QFD condition assessment model and using K-means clustering technique. Twenty case studies are analyzed by applying the QFD model and implementing the developed rating index. The results from the analyzed case studies show that the proposed threshold model produces robust MRR recommendations consistent with decisions and recommendations made by bridge managers on these projects. The proposed method is expected to advance the state of the art of bridges condition assessment and rating.

Keywords: concrete bridge decks, condition assessment and rating, quality function deployment, k-means clustering technique

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Authors: Mikhail Zarechnev, Bora I. Kumova

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A syllogism is a deductive inference scheme used to derive a conclusion from a set of premises. In a categorical syllogisms, there are only two premises and every premise and conclusion is given in form of a quantified relationship between two objects. The different order of objects in premises give classification known as figures. We have shown that the ordered combinations of 3 generalized quantifiers with certain figure provide in total of 108 syllogistic moods which can be considered as different inference rules. The classical syllogistic system allows to model human thought and reasoning with syllogistic structures always attracted the attention of cognitive scientists. Since automated reasoning is considered as part of learning subsystem of AI agents, syllogistic system can be applied for this approach. Another application of syllogistic system is related to inference mechanisms on the Semantic Web applications. In this paper we proposed the mathematical model and algorithm for syllogistic reasoning. Also the model of iterative syllogistic reasoning in case of continuous flows of incoming data based on case–based reasoning and possible applications of proposed system were discussed.

Keywords: categorical syllogism, case-based reasoning, cognitive architecture, inference on the semantic web, syllogistic reasoning

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Authors: Narimen Rdhaounia Mohamed Kouni

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Our aim in this paper is to identify the origins of inflation in Tunisia on the period from 1988 to 2018. In order to estimate the model, an ARDL methodology is used. We studied also the effect of informal economy on inflation. Indeed, we estimated the size of the informal economy in Tunisia based on Gutmann method. The results showed that there are three main origins of inflation. In fact, the first origin is the fiscal policy adopted by Tunisia, particularly after revolution. The second origin is the increase of monetary variables. Finally, informal economy played an important role in inflation.

Keywords: inflation, consumer price index, informal, gutmann method, ARDL model

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Authors: Sixing Chen, Shuai Yang

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Online celebrity business, also known as Internet celebrity business (or Wanghong business in Chinese), is an emerging relational C2C business model, and an alternative to traditional C2C transactional business models. There are already millions of these consumers, and this number is growing. In this model, consumer purchase decisions are driven by recommendations and endorsements in videos posted online by celebrities. The purpose of this paper is to determine the relational constructs within consumer relationships in the Internet celebrity business model and to investigate relationships between the constructs and consumer purchase intention. A questionnaire-based study was conducted with consumers who had an awareness of, or prior purchase experience with online celebrities. The results of exploratory factor analysis (EFA) and multiple regression analysis revealed three valid relational constructs: product experience sharing, lifestyle association, and real-time interaction. This study indicated that these constructs had the direct effect on consumer preference and purchase intention. The findings of this study provide insight into a business model in which online shopping is driven by celebrities. They suggest that online celebrities should pay more attention to product experience sharing, life style association and real-time interaction for managing their product promotions. These are the most salient factors with respect to the relational constructs identified in this study.

Keywords: customer relationship, customer to customer, Internet celebrity, online celebrity, online marketing, purchase intention

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Authors: Narupot Putwattana

Abstract:

Changes in global situation such as environmental and economic crisis brought the new perspective for science education called integrative biology. STEM has been increasingly mentioned for several educational researches as the approach which combines the concept in Science (S), Technology (T), Engineering (E) and Mathematics (M) to apply in teaching and learning process so as to strengthen the 21st-century skills such as creativity and critical thinking. Recent studies demonstrated STEM as the pedagogy which described the engineering process along with the science classroom activities. So far, pedagogical contents for STEM explaining the content in biology have been scarce. A qualitative literature review was conducted so as to gather the articles based on electronic databases (google scholar). STEM education, engineering design, teaching and learning of biology were used as main keywords to find out researches involving with the application of STEM in biology teaching and learning process. All articles were analyzed to obtain appropriate teaching and learning model that unify the core concept of biology. The synthesized model comprised of engineering design, inquiry-based learning, biological prototype and biologically-inspired design (BID). STEM content and context integration were used as the theoretical framework to create the integrative biology instructional model for STEM education. Several disciplines contents such as biology, engineering, and technology were regarded for inquiry-based learning to build biological prototype. Direct and indirect integrations were used to provide the knowledge into the biology related STEM strategy. Meanwhile, engineering design and BID showed the occupational context for engineer and biologist. Technological and mathematical aspects were required to be inspected in terms of co-teaching method. Lastly, other variables such as critical thinking and problem-solving skills should be more considered in the further researches.

Keywords: biomimicry, engineering approach, STEM education, teaching and learning model

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Authors: Amit Kumar

Abstract:

Accurate identification of deteriorated air quality regions is very helpful in devising better environmental practices and mitigation efforts. In the present study, an attempt has been made to identify the air pollutant dispersion patterns especially NOX due to vehicular and industrial sources over a rapidly developing urban city, Visakhapatnam (17°42’ N, 83°20’ E), India, during April 2009. Using the emission factors of different vehicles as well as the industry, a high resolution 1 km x 1 km gridded emission inventory has been developed for Visakhapatnam city. A dispersion model AERMOD with explicit representation of planetary boundary layer (PBL) dynamics and offline coupled through a developed coupler mechanism with a high resolution mesoscale model WRF-ARW resolution for simulating the dispersion patterns of NOX is used in the work. The meteorological as well as PBL parameters obtained by employing two PBL schemes viz., non-local Yonsei University (YSU) and local Mellor-Yamada-Janjic (MYJ) of WRF-ARW model, which are reasonably representing the boundary layer parameters are considered for integrating AERMOD. Significantly different dispersion patterns of NOX have been noticed between summer and winter months. The simulated NOX concentration is validated with available six monitoring stations of Central Pollution Control Board, India. Statistical analysis of model evaluated concentrations with the observations reveals that WRF-ARW of YSU scheme with AERMOD has shown better performance. The deteriorated air quality locations are identified over Visakhapatnam based on the validated model simulations of NOX concentrations. The present study advocates the utility of tNumerical Simulation of Air Pollutant Using Coupled AERMOD-WRF Modeling System over Visakhapatnam: A Case Studyhe developed gridded emission inventory of NOX with coupled WRF-AERMOD modeling system for air quality assessment over the study region.

Keywords: WRF-ARW, AERMOD, planetary boundary layer, air quality

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Authors: Jatinder Kumar, Ajay Bansal

Abstract:

Simulation of a photocatalytic reactor helps in understanding the complex behavior of the photocatalytic degradation. Simulation also aids the designing and optimization of the photocatalytic reactor. Lack of simulation strategies is a huge hindrance in the commercialization of the photocatalytic technology. With the increased performance of computational resources, and development of simulation software, computational fluid dynamics (CFD) is becoming an affordable engineering tool to simulate and optimize reactor designs. In the present paper, a CFD (Computational fluid dynamics) model for simulating the performance of an immobilized-titanium dioxide based annular photocatalytic reactor was developed. The computational model integrates hydrodynamics, species mass transport, and chemical reaction kinetics using a commercial CFD code Fluent 6.3.26. The CFD model was based on the intrinsic kinetic parameters determined experimentally in a perfectly mixed batch reactor. Rhodamine B, a complex organic compound, was selected as a test pollutant for photocatalytic degradation. It was observed that CFD could become a valuable tool to understand and improve the photocatalytic systems.

Keywords: simulation, computational fluid dynamics (CFD), annular photocatalytic reactor, titanium dioxide

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Authors: Surya R. Niraula, Devendra B Chhetry, Girish K. Singh, S. Nagesh, Frederick A. Connell

Abstract:

Background: Although random sampling is generally considered to be the gold standard for population-based research, the majority of drug abuse research is based on non-random sampling despite the well-known limitations of this kind of sampling. Method: We compared the statistical properties of two surveys of drug abuse in the same community: one using snowball sampling of drug users who then identified “friend controls” and the other using a random sample of non-drug users (controls) who then identified “friend cases.” Models to predict drug abuse based on risk factors were developed for each data set using conditional logistic regression. We compared the precision of each model using bootstrapping method and the predictive properties of each model using receiver operating characteristics (ROC) curves. Results: Analysis of 100 random bootstrap samples drawn from the snowball-sample data set showed a wide variation in the standard errors of the beta coefficients of the predictive model, none of which achieved statistical significance. One the other hand, bootstrap analysis of the random-sample data set showed less variation, and did not change the significance of the predictors at the 5% level when compared to the non-bootstrap analysis. Comparison of the area under the ROC curves using the model derived from the random-sample data set was similar when fitted to either data set (0.93, for random-sample data vs. 0.91 for snowball-sample data, p=0.35); however, when the model derived from the snowball-sample data set was fitted to each of the data sets, the areas under the curve were significantly different (0.98 vs. 0.83, p < .001). Conclusion: The proposed method of random sampling of controls appears to be superior from a statistical perspective to snowball sampling and may represent a viable alternative to snowball sampling.

Keywords: drug abuse, matched case-control study, non-probability sampling, probability sampling

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