Search results for: Academic environment model

Authors: P. G. Siddheshwar, B. N. Veena

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Rayleigh-B´enard convection of a nanoliquid in shallow, square and tall enclosures is studied using the Khanafer-Vafai-Lightstone single-phase model. The thermophysical properties of water, copper, copper-oxide, alumina, silver and titania at 3000 K under stagnant conditions that are collected from literature are used in calculating thermophysical properties of water-based nanoliquids. Phenomenological laws and mixture theory are used for calculating thermophysical properties. Free-free, rigid-rigid and rigid-free boundary conditions are considered in the study. Intractable Lorenz model for each boundary combination is derived and then reduced to the tractable Ginzburg-Landau model. The amplitude thus obtained is used to quantify the heat transport in terms of Nusselt number. Addition of nanoparticles is shown not to alter the influence of the nature of boundaries on the onset of convection as well as on heat transport. Amongst the three enclosures considered, it is found that tall and shallow enclosures transport maximum and minimum energy respectively. Enhancement of heat transport due to nanoparticles in the three enclosures is found to be in the range 3% - 11%. Comparison of results in the case of rigid-rigid boundaries is made with those of an earlier work and good agreement is found. The study has limitations in the sense that thermophysical properties are calculated by using various quantities modelled for static condition.

Keywords: Enclosures, free-free, rigid-rigid and rigid-free boundaries, Ginzburg-Landau model, Lorenz model.

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Authors: M. S. Alam, M. R. Alam, Nusrat Jahan Imu

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This paper presents a computer simulation model based on system dynamics methodology for analyzing the dynamic characteristics of input energy structure in agriculture and Bangladesh is used here as a case study for model validation. The model provides an input energy structure linking the major energy flows with human energy and draft energy from cattle as well as tractors and/or power tillers, irrigation, chemical fertilizer and pesticide. The evaluation is made in terms of different energy dependent indicators. During the simulation period, the energy input to agriculture increased from 6.1 to 19.15 GJ/ha i.e. 2.14 fold corresponding to energy output in terms of food, fodder and fuel increase from 71.55 to 163.58 GJ/ha i.e. 1.28 fold from the base year. This result indicates that the energy input in Bangladeshi agricultural production is increasing faster than the energy output. Problems such as global warming, nutrient loading and pesticide pollution can associate with this increasing input. For an assessment, a comparative statement of input energy use in agriculture of developed countries (DCs) and least developed countries (LDCs) including Bangladesh has been made. The performance of the model is found satisfactory to analyze the agricultural energy system for LDCs

Keywords: Agriculture, energy indicator, system dynamics, energy flows.

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Authors: Nikolay P. Brayanov, Anna V. Stoynova

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Model-based development approach is gaining more support and acceptance. Its higher abstraction level brings simplification of systems’ description that allows domain experts to do their best without particular knowledge in programming. The different levels of simulation support the rapid prototyping, verifying and validating the product even before it exists physically. Nowadays model-based approach is beneficial for modelling of complex embedded systems as well as a generation of code for many different hardware platforms. Moreover, it is possible to be applied in safety-relevant industries like automotive, which brings extra automation of the expensive device certification process and especially in the software qualification. Using it, some companies report about cost savings and quality improvements, but there are others claiming no major changes or even about cost increases. This publication demonstrates the level of maturity and autonomy of model-based approach for code generation. It is based on a real live automotive seat heater (ASH) module, developed using The Mathworks, Inc. tools. The model, created with Simulink, Stateflow and Matlab is used for automatic generation of C code with Embedded Coder. To prove the maturity of the process, Code generation advisor is used for automatic configuration. All additional configuration parameters are set to auto, when applicable, leaving the generation process to function autonomously. As a result of the investigation, the publication compares the quality of generated embedded code and a manually developed one. The measurements show that generally, the code generated by automatic approach is not worse than the manual one. A deeper analysis of the technical parameters enumerates the disadvantages, part of them identified as topics for our future work.

Keywords: Embedded code generation, embedded C code quality, embedded systems, model-based development.

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Authors: Mounira Rouaïnia, Mohamed Salah Medjram, Noureddine Doghmane

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In Multiple Sclerosis, pathological changes in the brain results in deviations in signal intensity on Magnetic Resonance Images (MRI). Quantitative analysis of these changes and their correlation with clinical finding provides important information for diagnosis. This constitutes the objective of our work. A new approach is developed. After the enhancement of images contrast and the brain extraction by mathematical morphology algorithm, we proceed to the brain segmentation. Our approach is based on building statistical model from data itself, for normal brain MRI and including clustering tissue type. Then we detect signal abnormalities (MS lesions) as a rejection class containing voxels that are not explained by the built model. We validate the method on MR images of Multiple Sclerosis patients by comparing its results with those of human expert segmentation.

Keywords: EM algorithm, Magnetic Resonance Imaging, Mathematical morphology, Markov random model.

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Authors: Nhon Do, Hien Nguyen

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Nowadays there are many methods for representing knowledge such as semantic network, neural network, and conceptual graphs. Nonetheless, these methods are not sufficiently efficient when applied to perform and deduce on knowledge domains about supporting in general education such as algebra, analysis or plane geometry. This leads to the introduction of computational network which is a useful tool for representation knowledge base, especially for computational knowledge, especially knowledge domain about general education. However, when dealing with a practical problem, we often do not immediately find a new solution, but we search related problems which have been solved before and then proposing an appropriate solution for the problem. Besides that, when finding related problems, we have to determine whether the result of them can be used to solve the practical problem or not. In this paper, the extension model of computational network has been presented. In this model, Sample Problems, which are related problems, will be used like the experience of human about practical problem, simulate the way of human thinking, and give the good solution for the practical problem faster and more effectively. This extension model is applied to construct an automatic system for solving algebraic problems in middle school.

Keywords: educational software, artificial intelligence, knowledge base system, knowledge representation.

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Authors: S. M. Ali, N. R. Dhar

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Tool wear and surface roughness prediction plays a significant role in machining industry for proper planning and control of machining parameters and optimization of cutting conditions. This paper deals with developing an artificial neural network (ANN) model as a function of cutting parameters in turning steel under minimum quantity lubrication (MQL). A feed-forward backpropagation network with twenty five hidden neurons has been selected as the optimum network. The co-efficient of determination (R2) between model predictions and experimental values are 0.9915, 0.9906, 0.9761 and 0.9627 in terms of VB, VM, VS and Ra respectively. The results imply that the model can be used easily to forecast tool wear and surface roughness in response to cutting parameters.

Keywords: ANN, MQL, Surface Roughness, Tool Wear.

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Authors: So Jeong Nam, Seung Woo Lee, Jai-Kyung Lee

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With the globalized production and logistics environment, the need for reducing the product development interval and lead time, having a faster response to orders, conforming to quality standards, fair tracking, and boosting information exchanging activities with customers and partners, and coping with changes in the management environment, manufacturers are in dire need of an information management system in their manufacturing environments. There are lots of information systems that have been designed to manage the condition or operation of equipment in the field but existing systems have a decentralized architecture, which is not unified. Also, these systems cannot effectively handle the status data extraction process upon encountering a problem related to protocols or changes in the equipment or the setting. In this regard, this paper will introduce a system for processing and saving the status info of production equipment, which uses standard representation formats, to enable flexible responses to and support for variables in the field equipment. This system can be used for a variety of manufacturing and equipment settings and is capable of interacting with higher-tier systems such as MES.

Keywords: DAS, Equipment Status, Regular Expression

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Authors: Toshitaka Higashino, Naoki Wakamiya

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Human beings perform a task by perceiving information from outside, recognizing them, and responding them. There have been various attempts to analyze and understand internal processes behind the reaction to a given stimulus by conducting psychological experiments and analysis from multiple perspectives. Among these, we focused on Model Human Processor (MHP). However, it was built based on psychological experiments and thus the relation with brain activity was unclear so far. To verify the validity of the MHP and propose our model from a viewpoint of neuroscience, EEG (Electroencephalography) measurements are performed during experiments in this study. More specifically, first, experiments were conducted where Latin alphabet characters were used as visual stimuli. In addition to response time, ERPs (event-related potentials) such as N100 and P300 were measured by using EEG. By comparing cycle time predicted by the MHP and latency of ERPs, it was found that N100, related to perception of stimuli, appeared at the end of the perceptual processor. Furthermore, by conducting an additional experiment, it was revealed that P300, related to decision making, appeared during the response decision process, not at the end. Second, by experiments using Japanese Hiragana characters, i.e. Japan's own phonetic symbols, those findings were confirmed. Finally, Japanese Kanji characters were used as more complicated visual stimuli. A Kanji character usually has several readings and several meanings. Despite the difference, a reading-related task and a meaning-related task exhibited similar results, meaning that they involved similar information processing processes of the brain. Based on those results, our model was proposed which reflects response time and ERP latency. It consists of three processors: the perception processor from an input of a stimulus to appearance of N100, the cognitive processor from N100 to P300, and the decision-action processor from P300 to response. Using our model, an application system which reflects brain activity can be established.

Keywords: Brain activity, EEG, information processing model, model human processor.

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Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: Classification algorithms; data mining; tourism; knowledge discovery.

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Authors: Jianlin Li, Jizhen Li

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Transnational corporations (TNCs) are playing a major role in global R&D, not only through activities in their home countries but also increasingly abroad. However, the process of R&D offshoring is not yet discussed thoroughly. Based on in-depth case study on Agilent China Communications Operation, this paper presents a stage model for theorizing the R&D offshoring process. This stage model outlines 5 maturity levels of organization and the offshoring process: Subsidiary team, Mirror team, Independent team, Mirror sector and the Independent sector (from software engineering point of view, it is similar to the local team's capability level of maturity model). Moreover, the paper gives a detailed discussion on the relevant characteristics, as well as the ability/responsibility of transfer, priorities and the corresponding organization structure. It also gives the characteristics and key points of different level-s R&D offshoring implementation using actual team practice.

Keywords: Internationalization of R&D, R&D offshoring process, Multinational Corporations, Organization Level.

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Authors: Tlou J. Ramabu

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Programming is one of the challenging subjects in the field of computing. In the higher education sphere, some programming novices’ performance, retention rate, and success rate are not improving. Most of the time, the problem is caused by the slow pace of learning, difficulty in grasping the syntax of the programming language and poor logical skills. More importantly, programming forms part of major subjects within the field of computing. As a result, specialized pedagogical methods and innovation are highly recommended. Little research has been done on the potential productivity of the WhatsApp platform as part of a blended learning model. In this article, the authors discuss the WhatsApp group as a part of blended learning model incorporated for a group of programming novices. We discuss possible administrative activities for productive utilisation of the WhatsApp group on the blended learning overview. The aim is to take advantage of the popularity of WhatsApp and the time students spend on it for their educational purpose. We believe that blended learning featuring a WhatsApp group may ease novices’ cognitive load and strengthen their foundational programming knowledge and skills. This is a work in progress as the proposed blended learning model with WhatsApp incorporated is yet to be implemented.

Keywords: Blended learning, higher education, WhatsApp, programming, novices, lecturers.

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Authors: Aumnad Phdungsilp, Teeradej Wuttipornpun

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Decision support based upon risk analysis into comparison of the electricity generation from different renewable energy technologies can provide information about their effects on the environment and society. The aim of this paper is to develop the assessment framework regarding risks to health and environment, and the society-s benefits of the electric power plant generation from different renewable sources. The multicriteria framework to multiattribute risk analysis technique and the decision analysis interview technique are applied in order to support the decisionmaking process for the implementing renewable energy projects to the Bangkok case study. Having analyses the local conditions and appropriate technologies, five renewable power plants are postulated as options. As this work demonstrates, the analysis can provide a tool to aid decision-makers for achieving targets related to promote sustainable energy system.

Keywords: Analytic Hierarchy Process, Bangkok, MultiattributeRisk Analysis, Renewable Energy Technology.

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Authors: F. Urem, K. Fertalj, I. Livaja

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Constant upgrading of Enterprise Resource Planning (ERP) systems is necessary, but can cause new defects. This paper attempts to model the likelihood of defects after completed upgrades with Weibull defect probability density function (PDF). A case study is presented analyzing data of recorded defects obtained for one ERP subsystem. The trends are observed for the value of the parameters relevant to the proposed statistical Weibull distribution for a given one year period. As a result, the ability to predict the appearance of defects after the next upgrade is described.

Keywords: ERP, upgrade, reliability, Weibull model

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Authors: Alireza Noorpoor, Akbar Abvabi, Mehdi Saeed Kiasat

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Development, calibration and validation of a threedimensional model of the Legform impactor for pedestrian crash with bumper are presented. Lower limb injury is becoming an increasingly important concern in vehicle safety for both occupants and pedestrians. In order to prevent lower extremity injuries to a pedestrian when struck by a car, it is important to elucidate the loadings from car front structures on the lower extremities and the injury mechanism caused by these loadings. An impact test procedure with a legform addressing lower limb injuries in car pedestrian accidents has been proposed by EEVC/WG17. In this study a modified legform impactor is introduced and validated against EEVC/WG17 criteria. The finite element model of this legform is developed using LS-DYNA software. Total mass of legform impactor is 13.4 kg.Technical specifications including the mass and location of the center of gravity and moment of inertia about a horizontal axis through the respective centre of gravity in femur and tibia are determined. The obtained results of legform impactor static and dynamic tests are as specified in the EEVC/WG17.

Keywords: Legform impactor, Pedestrian safety, Finite element model, Knee joint, EEVC/WG17.

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Authors: Fariba Azizi, Firoozeh Haghighi, Viliam Makis

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In this paper, we propose a method to model the relationship between failure time and degradation for a simple step stress test where underlying degradation path is linear and different causes of failure are possible. It is assumed that the intensity function depends only on the degradation value. No assumptions are made about the distribution of the failure times. A simple step-stress test is used to shorten failure time of products and a tampered failure rate (TFR) model is proposed to describe the effect of the changing stress on the intensities. We assume that some of the products that fail during the test have a cause of failure that is only known to belong to a certain subset of all possible failures. This case is known as masking. In the presence of masking, the maximum likelihood estimates (MLEs) of the model parameters are obtained through an expectation-maximization (EM) algorithm by treating the causes of failure as missing values. The effect of incomplete information on the estimation of parameters is studied through a Monte-Carlo simulation. Finally, a real example is analyzed to illustrate the application of the proposed methods.

Keywords: Expectation-maximization (EM) algorithm, cause of failure, intensity, linear degradation path, masked data, reliability function.

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Authors: Suwaree Yordchim, Toby J. Gibbs

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The objective is to study the satisfaction on English with an online learning. Online learning system mainly consists of English lessons, exercises, tests, web boards, and supplementary lessons for language practice. The sample groups are 80 Thai students studying English for Business Communication, majoring in Hotel and Lodging Management. The data are analyzed by mean, standard deviation (S.D.) value from the questionnaires. The results were found that the most average of satisfaction on academic aspects are technological searching tool through E-learning system that support the students’ learning (4.51), knowledge evaluation on pre-post learning and teaching (4.45), and change for project selections according to their interest, subject contents including practice in the real situations (4.45), respectively.

Keywords: English Learning, Online System, Satisfaction.

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Authors: J. X. Dong, C. J. An, Z. Chen, E. H. Owens, M. C. Boufadel, E. Taylor, K. Lee

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Shorelines are vulnerable to significant environmental impacts from oil spills. Stranded oil can cause potential short- to long-term detrimental effects along beaches that include injuries to ecosystem, socio-economic and cultural resources. In this study, a three-dimensional (3D) numerical modeling approach is developed to evaluate the fate and transport of spilled oil for hypothetical oiled shoreline cases under various combinations of beach geomorphology and environmental conditions. The developed model estimates the spatial and temporal distribution of spilled oil for the various test conditions, using the finite volume method and considering the physical transport (dispersion and advection), sinks, and sorption processes. The model includes a user-friendly interface for data input on variables such as beach properties, environmental conditions, and physical-chemical properties of spilled oil. An experimental meso-scale tank design was used to test the developed model for dissolved petroleum hydrocarbon within shorelines. The simulated results for effects of different sediment substrates, oil types, and shoreline features for the transport of spilled oil are comparable to that obtained with a commercially available model. Results show that the properties of substrates and the oil removal by shoreline effects have significant impacts on oil transport in the beach area. Sensitivity analysis, through the application of the one-step-at-a-time method (OAT), for the 3D model identified hydraulic conductivity as the most sensitive parameter. The 3D numerical model allows users to examine the behavior of oil on and within beaches, assess potential environmental impacts, and provide technical support for decisions related to shoreline clean-up operations.

Keywords: dissolved petroleum hydrocarbons, environmental multimedia model, finite volume method, FVM, sensitivity analysis, total petroleum hydrocarbons, TPH

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Authors: Khaled Elbehiery, Hussam Elbehiery

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Smart cities are a framework of technologies along with sustainable infrastructure to provide their citizens an improved quality of life, safer environment, affordability, and more, which in turn helps with the society's economic growth. The proposed research will focus on the primary building block of the smart city; the infrastructure of the house itself. The traditional method of building houses has been, for a long time, nothing but a costly manufacturing process, and consequently, buying a house becomes not an option for everyone anymore. The smart cities' Modular Houses are not using traditional building construction materials; the design reduces the common lengthy construction times and associated high costs. The Modular Houses are technological homes, low-cost and customizable based on a family's requirements. In addition, the Modular Houses are environmentally friendly and healthy enough to assist with the pandemic situation.

Keywords: Smart cities, modular houses, single-unit property, multi-unit property, mobility features, chain-supply, livable environment, carbon footprint.

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Authors: V. Churkin, M. Lopatin

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The purpose of the paper is to estimate the US small wind turbines market potential and forecast the small wind turbines sales in the US. The forecasting method is based on the application of the Bass model and the generalized Bass model of innovations diffusion under replacement purchases. In the work an exponential distribution is used for modeling of replacement purchases. Only one parameter of such distribution is determined by average lifetime of small wind turbines. The identification of the model parameters is based on nonlinear regression analysis on the basis of the annual sales statistics which has been published by the American Wind Energy Association (AWEA) since 2001 up to 2012. The estimation of the US average market potential of small wind turbines (for adoption purchases) without account of price changes is 57080 (confidence interval from 49294 to 64866 at P = 0.95) under average lifetime of wind turbines 15 years, and 62402 (confidence interval from 54154 to 70648 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 90,7%, while in the second - 91,8%. The effect of the wind turbines price changes on their sales was estimated using generalized Bass model. This required a price forecast. To do this, the polynomial regression function, which is based on the Berkeley Lab statistics, was used. The estimation of the US average market potential of small wind turbines (for adoption purchases) in that case is 42542 (confidence interval from 32863 to 52221 at P = 0.95) under average lifetime of wind turbines 15 years, and 47426 (confidence interval from 36092 to 58760 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 95,3%, while in the second – 95,3%.

Keywords: Bass model, generalized Bass model, replacement purchases, sales forecasting of innovations, statistics of sales of small wind turbines in the United States.

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Authors: D. O. Omondi, M. K. Walingo, G. M. Mbagaya

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Objective: This study explored the possibility of integrating Health Belief Concepts as additional predictors of intention to adopt a recommended diet-category within the Theory of Planned Behavior (TPB). Methods: The study adopted a Sequential Exploratory Mixed Methods approach. Qualitative data were generated on attitude, subjective norm, perceived behavioral control and perceptions on predetermined diet-categories including perceived susceptibility, perceived benefits, perceived severity and cues to action. Synthesis of qualitative data was done using constant comparative approach during phase 1. A survey tool developed from qualitative results was used to collect information on the same concepts across 237 legible Type 2 diabetics. Data analysis included use of Structural Equation Modeling in Analysis of Moment Structures to explore the possibility of including perceived susceptibility, perceived benefits, perceived severity and cues to action as additional intention predictors in a single nested model. Results: Two models-one nested based on the traditional TPB model {χ2=223.3, df = 77, p = .02, χ2/df = 2.9; TLI = .93; CFI =.91; RMSEA (90CI) = .090(.039, .146)} and the newly proposed Planned Behavior Health Belief Model (PBHB) {χ2 = 743.47, df = 301, p = .019; TLI = .90; CFI=.91; RMSEA (90CI) = .079(.031, .14)} passed the goodness of fit tests based on common fit indicators used. Conclusion: The newly developed PBHB Model ranked higher than the traditional TPB model with reference made to chi-square ratios (PBHB: χ2/df = 2.47; p=0.19 against TPB: χ2/df = 2.9, p=0.02). The integrated model can be used to motivate Type 2 diabetics towards healthy eating.

Keywords: Theory, intention, predictors, mixed methods design.

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Authors: Karen Armstrong

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Recent concerns about the value of teaching cursive handwriting in the classroom are based on the belief that cursive handwriting or penmanship is an outdated and unnecessary skill in today’s online world. The discussion of this issue begins with a description of current initiatives to eliminate handwriting instruction in schools. This is followed by a brief history of cursive writing through the ages. Next considered is a description of its benefits as a preliminary process for younger children as compared with immediate instruction in keyboarding, particularly in the areas of vision, cognition, motor skills and automatic fluency. Also considered, is cursive’s companion, paper itself, and the impact of a paperless, “screen and keyboard” environment. The discussion concludes with a consideration of the unique contributions of cursive and keyboarding as written forms of communication, along with their respective surfaces, paper and screen. Finally, an assessment of the practical utility of each skill is followed by an informal assessment of what is lost and what remains as we move from a predominantly paper and pen world of handwriting to texting and keyboarding in an environment of screens.

Keywords: Asemic writing, cursive, handwriting, keyboarding, paper.

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Authors: Kaveh PourAkbar Saffar, Nima JamilPour, Ahmad Raeisi Najafi, Gholamreza Rouhi, Ahmad Reza Arshi, Abdolhossein Fereidoon

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The presence of chemical bonding between functionalized carbon nanotubes and matrix in carbon nanotube reinforced composites is modeled by elastic beam elements representing covalent bonding characteristics. Neglecting other reinforcing mechanisms in the composite such as relatively weak interatomic Van der Waals forces, this model shows close results to the Rule of Mixtures model-s prediction for effective Young-s modulus of a Representative Volume Element of composite for small volume fractions (~1%) and high aspect ratios (L/D>200) of CNTs.

Keywords: Beam Element, Carbon Nanotube Reinforced Composite, Cross-link, Young's modulus.

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Authors: Juan C. Domínguez, Belén Del Saz-Orozco, María V. Alonso, Mercedes Oliet, Francisco Rodríguez

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In the present study, the kinetics of thermal degradation of a phenolic and lignin reinforced phenolic foams, and the lignin used as reinforcement were studied and the activation energies of their degradation processes were obtained by a DAEM model. The average values for five heating rates of the mean activation energies obtained were: 99.1, 128.2, and 144.0 kJ.mol-1 for the phenolic foam; 109.5, 113.3, and 153.0 kJ.mol-1 for the lignin reinforcement; and 82.1, 106.9, and 124.4 kJ.mol-1 for the lignin reinforced phenolic foam. The standard deviation ranges calculated for each sample were 1.27-8.85, 2.22-12.82, and 3.17-8.11 kJ.mol-1 for the phenolic foam, lignin and the reinforced foam, respectively. The DAEM model showed low mean square errors (<1x10-5), proving that is a suitable model to study the kinetics of thermal degradation of the foams and the reinforcement.

Keywords: Kinetics, lignin, phenolic foam, thermal degradation.

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Authors: S. Yaman, S. Rostami

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In this study, a black box modeling of the coupled-tank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutionary computation method, genetic algorithm. All tuned controllers are applied to the fuzzy model of the coupled-tank experimental setup and analyzed under the different reference input values. According to the results, it is seen that function tuner method demonstrates better robust control performance and guarantees the closed loop stability.

Keywords: Function tuner method, fuzzy modeling, fuzzy PID controller, genetic algorithm.

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Authors: Ebrahim Abbasi, Amir Abouec

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In this research, the researchers have managed to design a model to investigate the current trend of stock price of the "IRAN KHODRO corporation" at Tehran Stock Exchange by utilizing an Adaptive Neuro - Fuzzy Inference system. For the Longterm Period, a Neuro-Fuzzy with two Triangular membership functions and four independent Variables including trade volume, Dividend Per Share (DPS), Price to Earning Ratio (P/E), and also closing Price and Stock Price fluctuation as an dependent variable are selected as an optimal model. For the short-term Period, a neureo – fuzzy model with two triangular membership functions for the first quarter of a year, two trapezoidal membership functions for the Second quarter of a year, two Gaussian combination membership functions for the third quarter of a year and two trapezoidal membership functions for the fourth quarter of a year were selected as an optimal model for the stock price forecasting. In addition, three independent variables including trade volume, price to earning ratio, closing Stock Price and a dependent variable of stock price fluctuation were selected as an optimal model. The findings of the research demonstrate that the trend of stock price could be forecasted with the lower level of error.

Keywords: Stock Price forecast, membership functions, Adaptive Neuro-Fuzzy Inference System, trade volume, P/E, DPS.

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Authors: F. Titouna, S. Benferhat, K. Aksa, C. Titouna

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A traffic light gives security from traffic congestion,reducing the traffic jam, and organizing the traffic flow. Furthermore,increasing congestion level in public road networks is a growingproblem in many countries. Using Intelligent Transportation Systemsto provide emergency vehicles a green light at intersections canreduce driver confusion, reduce conflicts, and improve emergencyresponse times. Nowadays, the technology of wireless sensornetworks can solve many problems and can offer a good managementof the crossroad. In this paper, we develop a new approach based onthe technique of clustering and the graphical possibilistic fusionmodeling. So, the proposed model is elaborated in three phases. Thefirst one consists to decompose the environment into clusters,following by the fusion intra and inter clusters processes. Finally, wewill show some experimental results by simulation that proves theefficiency of our proposed approach.KeywordsTraffic light, Wireless sensor network, Controller,Possibilistic network/Bayesain network.

Keywords: Traffic light, Wireless sensor network, Controller, Possibilistic network/Bayesain network.

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Authors: Hadi Seyedarabi, Ali Aghagolzadeh, Sohrab Khanmohammadi

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Face and facial expressions play essential roles in interpersonal communication. Most of the current works on the facial expression recognition attempt to recognize a small set of the prototypic expressions such as happy, surprise, anger, sad, disgust and fear. However the most of the human emotions are communicated by changes in one or two of discrete features. In this paper, we develop a facial expressions synthesis system, based on the facial characteristic points (FCP's) tracking in the frontal image sequences. Selected FCP's are automatically tracked using a crosscorrelation based optical flow. The proposed synthesis system uses a simple deformable facial features model with a few set of control points that can be tracked in original facial image sequences.

Keywords: Deformable face model, facial animation, facialcharacteristic points, optical flow.

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Authors: Mohammadamin Zanganeh, Vahid Khalajzadeh

Abstract:

The problems associated with wind predictions of WAsP model in complex terrain are already the target of several studies in the last decade. In this paper, the influence of surrounding orography on accuracy of wind data analysis of a train is investigated. For the case study, a site with complex surrounding orography is considered. This site is located in Manjil, one of the windiest cities of Iran. For having precise evaluation of wind regime in the site, one-year wind data measurements from two metrological masts are used. To validate the obtained results from WAsP, the cross prediction between each mast is performed. The analysis reveals that WAsP model can estimate the wind speed behavior accurately. In addition, results show that this software can be used for predicting the wind regime in flat sites with complex surrounding orography.

Keywords: Complex terrain, Meteorological mast, WAsPmodel, Wind prediction

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Authors: A. Ben Abdallah, H. Essabbah, M. H. Bedoui

Abstract:

The myocardial sintigraphy is an imaging modality which provides functional informations. Whereas, coronarography modality gives useful informations about coronary arteries anatomy. In case of coronary artery disease (CAD), the coronarography can not determine precisely which moderate lesions (artery reduction between 50% and 70%), known as the “gray zone", are haemodynamicaly significant. In this paper, we aim to define the relationship between the location and the degree of the stenosis in coronary arteries and the observed perfusion on the myocardial scintigraphy. This allows us to model the impact evolution of these stenoses in order to justify a coronarography or to avoid it for patients suspected being in the gray zone. Our approach is decomposed in two steps. The first step consists in modelling a coronary artery bed and stenoses of different location and degree. The second step consists in modelling the left ventricle at stress and at rest using the sphercical harmonics model and myocardial scintigraphic data. We use the spherical harmonics descriptors to analyse left ventricle model deformation between stress and rest which permits us to conclude if ever an ischemia exists and to quantify it.

Keywords: Spherical harmonics model, vascular bed, 3D reconstruction, left ventricle, myocardial scintigraphy.

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Authors: Gye-rok Jeon, Jae-hee Jung, In-cheol Kim, Ah-young Jeon, Sang-hwa Yoon, Jung-man Son, Jae-hyung Kim, Soo-young Ye, Jung-hoon Ro, Dong-hyun Kim, Chul-han Kim

Abstract:

A analysis on the conventional the blood pressure estimation method using an oscillometric sphygmomanometer was performed through a computer simulation using an arterial pressure-volume (APV) model. Traditionally, the maximum amplitude algorithm (MAP) was applied on the oscillation waveforms of the APV model to obtain the mean arterial pressure and the characteristic ratio. The estimation of mean arterial pressure and characteristic ratio was significantly affected with the shape of the blood pressure waveforms and the cutoff frequency of high-pass filter (HPL) circuitry. Experimental errors are due to these effects when estimating blood pressure. To find out an algorithm independent from the influence of waveform shapes and parameters of HPL, the volume oscillation of the APV model and the phase shift of the oscillation with fast fourier transform (FFT) were testified while increasing the cuff pressure from 1 mmHg to 200 mmHg (1 mmHg per second). The phase shift between the ranges of volume oscillation was then only observed between the systolic and the diastolic blood pressures. The same results were also obtained from the simulations performed on two different the arterial blood pressure waveforms and one hyperthermia waveform.

Keywords: Arterial blood pressure, oscillometric method

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