Search results for: predicting model

Authors: Nop Sopipan

Abstract:

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

Keywords: volatility, Markov Regime Switching, forecasting, Baht/USD

Procedia PDF Downloads 294

Authors: M. Eskandarighadi, C. R. McGann

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It is observed from past experiences of earthquakes that local site conditions can significantly affect the strong ground motion characteristics experience at the site. One-dimensional seismic site response analysis is the most common approach for investigating site response. This approach assumes that soil is homogeneous and infinitely extended in the horizontal direction. Therefore, tying side boundaries together is one way to model this behavior, as the wave passage is assumed to be only vertical. However, 1D analysis cannot capture the 2D nature of wave propagation, soil heterogeneity, and 2D soil profile with features such as inclined layer boundaries. In contrast, 2D seismic site response modeling can consider all of the mentioned factors to better understand local site effects on strong ground motions. 2D wave propagation and considering that the soil profile on the two sides of the model may not be identical clarifies the importance of a boundary condition on each side that can minimize the unwanted reflections from the edges of the model and input appropriate loading conditions. Ideally, the model size should be sufficiently large to minimize the wave reflection, however, due to computational limitations, increasing the model size is impractical in some cases. Another approach is to employ free-field boundary conditions that take into account the free-field motion that would exist far from the model domain and apply this to the sides of the model. This research focuses on implementing free-field boundary conditions in OpenSees for 2D site response analysisComparisons are made between 1D models and 2D models with various boundary conditions, and details and limitations of the developed free-field boundary modeling approach are discussed.

Keywords: boundary condition, free-field, opensees, site response analysis, wave propagation

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Authors: Manas Shah

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Black Scholes option pricing model is one of the most important concepts in modern world of computational finance. However, its practical use can be challenging as one of the input parameters must be estimated; implied volatility of the underlying security. The more precisely these values are estimated, the more accurate their corresponding estimates of theoretical option prices would be. Here, we present a novel model based on Cuckoo Search Optimization (CS) which finds more precise estimates of implied volatility than Particle Swarm Optimization (PSO) and Genetic Algorithm (GA).

Keywords: black scholes model, cuckoo search optimization, particle swarm optimization, genetic algorithm

Procedia PDF Downloads 442

Authors: Maryam Ziaee

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This research proposes a new approach and provides an opportunity for manufacturing companies to produce large amounts of products that meet their prospective customers’ tastes, needs, and expectations and simultaneously enable manufacturers to increase their profit. Mass customization is the production of products or services to meet each individual customer’s desires to the greatest possible extent in high quantities and at reasonable prices. This process takes place at different levels such as the customization of goods’ design, assembly, sale, and delivery status, and classifies in several categories. The main focus of this study is on one class of mass customization, called optional customization, in which companies try to provide their customers with as many options as possible to customize their products. These options could range from the design phase to the manufacturing phase, or even methods of delivery. Mass customization values customers’ tastes, but it is only one side of clients’ satisfaction; on the other side is companies’ fast responsiveness delivery. It brings the concept of agility, which is the ability of a company to respond rapidly to changes in volatile markets in terms of volume and variety. Indeed, mass customization is not effectively feasible without integrating the concept of agility. To gain the customers’ satisfaction, the companies need to be quick in responding to their customers’ demands, thus highlighting the significance of agility. This research offers a different method that successfully integrates mass customization and fast production in manufacturing industries. This research is built upon the hypothesis that the success key to being agile in mass customization is to forecast demand, cooperate with suppliers, and control inventory. Therefore, the significance of the supply chain (SC) is more pertinent when it comes to this stage. Since SC behavior is dynamic and its behavior changes constantly, companies have to apply one of the predicting techniques to identify the changes associated with SC behavior to be able to respond properly to any unwelcome events. System dynamics utilized in this research is a simulation approach to provide a mathematical model among different variables to understand, control, and forecast SC behavior. The final stage is delayed differentiation, the production strategy considered in this research. In this approach, the main platform of products is produced and stocked and when the company receives an order from a customer, a specific customized feature is assigned to this platform and the customized products will be created. The main research question is to what extent applying system dynamics for the prediction of SC behavior improves the agility of mass customization. This research is built upon a qualitative approach to bring about richer, deeper, and more revealing results. The data is collected through interviews and is analyzed through NVivo software. This proposed model offers numerous benefits such as reduction in the number of product inventories and their storage costs, improvement in the resilience of companies’ responses to their clients’ needs and tastes, the increase of profits, and the optimization of productivity with the minimum level of lost sales.

Keywords: agility, manufacturing, resilience, supply chain

Procedia PDF Downloads 82

Authors: Yousef Abdulaziz Almolhem

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Geographically, the most Arabic countries locate in areas confined to arid or semiarid regions. For this reason, most of our countries have adopted the seawater desalination as a strategy to overcome this problem. For example, the water supply of AUE, Kuwait, and Saudi Arabia is almost 100% from the seawater desalination plants. Many areas in Saudia Arabia and other countries in the world suffer from lack of fresh water which hinders the development of these areas, despite the availability of saline water and high solar radiation intensity. Furthermore, most developing countries do not have sufficient meteorological data to evaluate if the solar radiation is enough to meet the solar desalination. A mathematical model was developed to simulate and predict the thermal behavior of the solar still which used direct solar energy for distillation of seawater. Measurement data were measured in the Environment and Natural Resources Department, Faculty of Agricultural and Food sciences, King Faisal University, Saudi Arabia, in order to evaluate the present model. The simulation results obtained from this model were compared with the measured data. The main results of this research showed that there are slight differences between the measured and predicted values of the elements studied, which is resultant from the change of some factors considered constants in the model such as the sky clearance, wind velocity and the salt concentration in the water in the basin of the solar still. It can be concluded that the present model can be used to estimate the average total solar radiation and the thermal behavior of the solar still in any area with consideration to the geographical location.

Keywords: mathematical model, sea water, distillation, solar radiation

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Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: recurrent neural network, players lineup, basketball data, decision making model

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Authors: A. C. Obosi, H. O. Osinowo, L. I. Okeke

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Benign prostatic hyperplasia (BPH) is one among other prostate diseases with an increasing public health concern. The prevalence and increased psychological distress of BPH among men negatively impact on their health-related quality of life (HRQoL). Although several biomedical factors have been implicated in poor HRQoL among people with BPH, there is a dearth of research on the psychosocial factors predicting HRQoL among them especially in developing climes. This study, therefore, examined the psychosocial (knowledge, perceived stigma, depression, anxiety, perceived social support and illness acceptance) predictors of health-related quality of life among persons living with BPH in Ibadan, Nigeria. Biopsychosocial model and Health-related Quality of life guided this study which utilized ex-post facto design. Eighty-seven males living with BPH were purposively selected and actively participated in the study. Participants’ mean age was 61.77 ± 15.80 years. A standardized questionnaire comprising Socio-demographics and measures of health-related quality of life (α = 0.47); knowledge (α = 0.72); psychological distress (α = 0.95); perceived social support (α = 0.96) and Illness acceptance (α = 0.89) scales was utilized in the study. Data were content analysed, while bivariate correlation, hierarchical multiple regression and t-test for independent samples were computed at p < 0.05. Results revealed that 42.5% of the respondents reported poor HRQoL. Furthermore, age, length of illness, perceived stigma, depression, anxiety, knowledge, perceived social support and illness acceptance jointly predicted HRQoL significantly (R2=0.33, F(9,75)=4.05) and accounted for 33% variance in the total observed variance on HRQoL, while Illness acceptance (β=0.43), anxiety (β=-0.54), and perceived social support (β=0.16) had significant independent contributions to the observed variance on HRQoL. Illness acceptance, knowledge, perceived social support and psychological distress such as anxiety, depression and perceived stigma are important predictors of HRQoL. Therefore, it was recommended that urgent psychological intervention targeted at improving the quality of life of these persons be undertaken.

Keywords: benign prostatic hyperplasia, Health-related quality of life, prostate disorders, psychosocial factors

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Authors: N. Reppas, Y. L. Gui, B. Wetenhall, C. T. Davie, J. Ma

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A theoretical constitutive model describing the stress-strain behavior of rock subjected to different confining pressures is presented. A bounding surface plastic model with hardening effects is proposed which includes the effect of temperature drop. The bounding surface is based on a mapping rule and the temperature effect on rock is controlled by Poisson’s ratio. Validation of the results against available experimental data is also presented. The relation of deviatoric stress and axial strain is illustrated at different temperatures to analyze the effect of temperature decrease in terms of stiffness of the material.

Keywords: bounding surface, cooling of rock, plasticity model, rock deformation, elasto-plastic behavior

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Authors: Mohamed Mokhtar, Mostafa F. Shaaban

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Among the challenges facing solar photovoltaic (PV) systems in the United Arab Emirates (UAE), dust accumulation on solar panels is considered the most severe problem that faces the growth of solar power plants. The accumulation of dust on the solar panels significantly degrades output from these panels. Hence, solar PV panels have to be cleaned manually or using costly automated cleaning methods. This paper focuses on initiating cleaning actions when required to reduce maintenance costs. The cleaning actions are triggered only when the dust level exceeds a threshold value. The amount of dust accumulated on the PV panels is estimated using an artificial neural network (ANN). Experiments are conducted to collect the required data, which are used in the training of the ANN model. Then, this ANN model will be fed by the output power from solar panels, ambient temperature, and solar irradiance, and thus, it will be able to estimate the amount of dust accumulated on solar panels at these conditions. The model was tested on different case studies to confirm the accuracy of the developed model.

Keywords: machine learning, dust, PV panels, renewable energy

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Authors: Jefferson Hernandez, Juan Padilla

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Estimation of price elasticity of demand is a valuable tool for the task of price settling. Given its relevance, it is an active field for microeconomic and statistical research. Price elasticity in the industry of oil and gas, in particular for fuels sold in gas stations, has shown to be a challenging topic given the market and state restrictions, and underlying correlations structures between the types of fuels sold by the same gas station. This paper explores the Lotka-Volterra model for the problem for price elasticity estimation in the context of fuels; in addition, it is introduced multivariate random effects with the purpose of dealing with errors, e.g., measurement or missing data errors. In order to model the underlying correlation structures, the Inverse-Wishart, Hierarchical Half-t and LKJ distributions are studied. Here, the Bayesian paradigm through Markov Chain Monte Carlo (MCMC) algorithms for model estimation is considered. Simulation studies covering a wide range of situations were performed in order to evaluate parameter recovery for the proposed models and algorithms. Results revealed that the proposed algorithms recovered quite well all model parameters. Also, a real data set analysis was performed in order to illustrate the proposed approach.

Keywords: price elasticity, volume, correlation structures, Bayesian models

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Authors: Stephane Laussac, Jacques Piazzola, Gilles Tedeschi

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Estimation of the impact of atmospheric aerosols on the climate evolution is an important scientific challenge. One of a major source of particles is constituted by the oceans through the generation of sea-spray aerosols. In coastal areas, marine aerosols can affect air quality through their ability to interact chemically and physically with other aerosol species and gases. The integration of accurate sea-spray emission terms in modeling studies is then required. However, it was found that sea-spray concentrations are not represented with the necessary accuracy in some situations, more particularly at short fetch. In this study, the WRF-Chem model was implemented on a North-Western Mediterranean coastal region. WRF-Chem is the Weather Research and Forecasting (WRF) model online-coupled with chemistry for investigation of regional-scale air quality which simulates the emission, transport, mixing, and chemical transformation of trace gases and aerosols simultaneously with the meteorology. One of the objectives was to test the ability of the WRF-Chem model to represent the fine details of the coastal geography to provide accurate predictions of sea spray evolution for different fetches and the anthropogenic aerosols. To assess the performance of the model, a comparison between the model predictions using a local emission inventory and the physicochemical analysis of aerosol concentrations measured for different wind direction on the island of Porquerolles located 10 km south of the French Riviera is proposed.

Keywords: sea-spray aerosols, coastal areas, sea-spray concentrations, short fetch, WRF-Chem model

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Authors: Abdullahi Mohammed Auwal

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Formation and change or decamping from one political party to another have now become a common trend in Nigeria. Many of the parties’ members who could not secure positions and or win elections in their parties or are not very much satisfied with the trends occurring in the party’s internal democratic principles and mechanisms, change their respective parties. This paper developed/presented and analyzed the used of non linear mathematical model for defections between two political parties using epidemiological approach. The whole population was assumed to be a constant and homogeneously mixed. Equilibria have been analytically obtained and their local and global stability discussed. Conditions for the co-existence of both the political parties have been determined, in the study of defections between People Democratic Party (PDP) and All Progressive Congress (APC) in Nigeria using numerical simulations to support the analytical results.

Keywords: model, political parties, deffection, stability, equilibrium, epidemiology

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Authors: Zahra Abdolkarimi, Naser Zourikalatehsamad,

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Up to 40 years ago, after recognition of epilepsy, it was generally believed that these attacks occurred randomly and suddenly. However, thanks to the advance of mathematics and engineering, such attacks can be predicted within a few minutes or hours. In this way, various algorithms for long-term prediction of the time and frequency of the first attack are presented. In this paper, by considering the nonlinear nature of brain signals and dynamic recorded brain signals, ANFIS model is presented to predict the brain signals, since according to physiologic structure of the onset of attacks, more complex neural structures can better model the signal during attacks. Contribution of this work is the co-evolution algorithm for optimization of ANFIS network parameters. Our objective is to predict brain signals based on time series obtained from brain signals of the people suffering from epilepsy using ANFIS. Results reveal that compared to other methods, this method has less sensitivity to uncertainties such as presence of noise and interruption in recorded signals of the brain as well as more accuracy. Long-term prediction capacity of the model illustrates the usage of planted systems for warning medication and preventing brain signals.

Keywords: co-evolution algorithms, brain signals, time series, neural networks, ANFIS model, physiologic structure, time prediction, epilepsy suffering, illustrates model

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Authors: Abhimanyu Kumar, Chirag Gupta

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This work presents a comprehensive study on the employment of Model Predictive Control (MPC) for a three-phase voltage-source inverter to regulate the output voltage efficiently. The inverter is modeled via the Clarke Transformation, considering a scenario where the load is unknown. An LC filter model is developed, demonstrating its efficacy in Total Harmonic Distortion (THD) reduction. The system, when implemented with fault-tolerant multilevel inverter topologies, ensures reliable operation even under fault conditions, a requirement that is paramount with the increasing dependence on renewable energy sources. The research also integrates a Fuzzy Logic based fault tolerance system which identifies and manages faults, ensuring consistent inverter performance. The efficacy of the proposed methodology is substantiated through rigorous simulations and comparative results, shedding light on the voltage prediction efficiency and the robustness of the model even under fault conditions.

Keywords: total harmonic distortion, fuzzy logic, renewable energy sources, MLI

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Authors: Omar Imhemed Alramli

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As Transmission Control Protocol (TCP), User Datagram Protocol (UDP) is transfer protocol in the transportation layer in Open Systems Interconnection model (OSI model) or in TCP/IP model of networks. The UDP aspects evaluation were not recognized by using the pcattcp tool on the windows operating system platform like TCP. The study has been carried out to find a tool which supports UDP aspects evolution. After the information collection about different tools, iperf tool was chosen and implemented on Cygwin tool which is installed on both Windows XP platform and also on Windows XP on virtual box machine on one computer only. Iperf is used to make experimental evaluation of UDP and to see what will happen during the sending the packets between the Host and Guest in wired and wireless networks. Many test scenarios have been done and the major UDP aspects such as jitter, packet losses, and throughput are evaluated.

Keywords: TCP, UDP, IPERF, wireless LAN

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Authors: Hamed Saremi, Shahla Saremi

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In this study, control and management of construction projects is evaluated through developing a dynamic model in which some means are used in order to evaluating planning assumptions and reviewing the effectiveness of some project control policies based on previous researches about time, cost, project schedule pressure management, source management, project control, adding elements and sub-systems from cost management such as estimating consumption budget from budget due to costs, budget shortage effects and etc. using sensitivity analysis, researcher has evaluated introduced model that during model simulation by VENSIM software and assuming optimistic times and adding information about doing job and changes rate and project is forecasted with 373 days (2 days sooner than forecasted) and final profit $ 1,960,670 (23% amount of contract) assuming 15% inflation rate in year and costs rate accordance with planned amounts and other input information and final profit.

Keywords: dynamic planning, cost, time, performance, project management

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Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

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Authors: Thanh-Phong Dao, Shyh-Chour Huang

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This study presents the optimal design and formulation of a kinematic model of a flexible slider crank mechanism. The objective of the proposed innovative design is to take extra advantage of the compliant mechanism and maximize the fatigue life by applying the Taguchi method. A formulated kinematic model is developed using a Pseudo-Rigid-Body Model (PRBM). By means of mathematic models, the kinematic behaviors of the flexible slider crank mechanism are captured using MATLAB software. Finite Element Analysis (FEA) is used to show the stress distribution. The results show that the optimal shape of the flexible hinge includes a force of 8.5N, a width of 9mm and a thickness of 1.1mm. Analysis of variance shows that the thickness of the proposed hinge is the most significant parameter, with an F test of 15.5. Finally, a prototype is manufactured to prepare for testing the kinematic and dynamic behaviors.

Keywords: kinematic behavior, fatigue life, pseudo-rigid-body model, flexible slider crank mechanism

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Authors: Wookyong Kwon, Sangmoon Lee

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In this paper, a sampled-data model predictive tracking control method is presented for mobile robots which is modeled as constrained continuous-time linear parameter varying (LPV) systems. The presented sampled-data predictive controller is designed by linear matrix inequality approach. Based on the input delay approach, a controller design condition is derived by constructing a new Lyapunov function. Finally, a numerical example is given to demonstrate the effectiveness of the presented method.

Keywords: model predictive control, sampled-data control, linear parameter varying systems, LPV

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Authors: Jia Zhang, Fengmei Yao, Yanjing Tan

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The accurate estimation of crop yield is of great importance for the food security. In this study, a process-based mechanism model was modified to estimate yield of C4 crop by modifying the carbon metabolic pathway in the photosynthesis sub-module of the RS-P-YEC (Remote-Sensing-Photosynthesis-Yield estimation for Crops) model. The yield was calculated by multiplying net primary productivity (NPP) and the harvest index (HI) derived from the ratio of grain to stalk yield. The modified RS-P-YEC model was used to simulate maize yield in the Northeast China Plain during the period 2002-2011. The statistical data of maize yield from study area was used to validate the simulated results at county-level. The results showed that the Pearson correlation coefficient (R) was 0.827 (P < 0.01) between the simulated yield and the statistical data, and the root mean square error (RMSE) was 712 kg/ha with a relative error (RE) of 9.3%. From 2002-2011, the yield of maize planting zone in the Northeast China Plain was increasing with smaller coefficient of variation (CV). The spatial pattern of simulated maize yield was consistent with the actual distribution in the Northeast China Plain, with an increasing trend from the northeast to the southwest. Hence the results demonstrated that the modified process-based model coupled with remote sensing data was suitable for yield prediction of maize in the Northeast China Plain at the spatial scale.

Keywords: process-based model, C4 crop, maize yield, remote sensing, Northeast China Plain

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Authors: Xu Jinsheng, Tong Xin, Zheng Jian, Zhou Changsheng

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The NEPE (nitrate ester plasticized polyether) propellant is a kind of particle filling material with relatively high filling fraction. The experimental results show that the microcracks, microvoids and dewetting can cause the stress softening of the material. In this paper, a series of mechanical testing in inclusion with CCD technique were conducted to analyze the evolution of internal defects of propellant. The volume expansion function of the particle filling material was established by measuring of longitudinal and transverse strain with optical deformation measurement system. By analyzing the defects and internal damages of the material, a visco-hyperelastic constitutive model based on free energy theory was proposed incorporating damage function. The proposed constitutive model could accurately predict the mechanical properties of uniaxial tensile tests and tensile-relaxation tests.

Keywords: dewetting, constitutive model， uniaxial tensile tests, visco-hyperelastic, nonlinear

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Authors: Yuan-Jye Tseng, Shin-Han Lin

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In this research, a mathematical model for integrated evaluation of green design and green manufacturing processes is presented. To design a product, there can be alternative options to design the detailed components to fulfill the same product requirement. In the design alternative cases, the components of the product can be designed with different materials and detailed specifications. If several design alternative cases are proposed, the different materials and specifications can affect the manufacturing processes. In this paper, a new concept for integrating green design and green manufacturing processes is presented. A green design can be determined based the manufacturing processes of the designed product by evaluating the green criteria including energy usage and environmental impact, in addition to the traditional criteria of manufacturing cost. With this concept, a mathematical model is developed to find the green design and the associated green manufacturing processes. In the mathematical model, the cost items include material cost, manufacturing cost, and green related cost. The green related cost items include energy cost and environmental cost. The objective is to find the decisions of green design and green manufacturing processes to achieve the minimized total cost. In practical applications, the decision-making can be made to select a good green design case and its green manufacturing processes. In this presentation, an example product is illustrated. It shows that the model is practical and useful for integrated evaluation of green design and green manufacturing processes.

Keywords: supply chain management, green supply chain, green design, green manufacturing, mathematical model

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Authors: Nikola Tomasevic, Marko Batic, Sanja Vranes

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Emerging Semantic Web technologies can be seen as the next step in evolution of the intelligent facility management systems. Particularly, this considers increased usage of open source and/or standardized concepts for data classification and semantic interpretation. To deliver such facility management systems, providing the comprehensive integration and interoperability platform in from of the facility data model is a prerequisite. In this paper, one of the possible modelling approaches to provide such integrative facility data model which was based on the ontology modelling concept was presented. Complete ontology development process, starting from the input data acquisition, ontology concepts definition and finally ontology concepts population, was described. At the beginning, the core facility ontology was developed representing the generic facility infrastructure comprised of the common facility concepts relevant from the facility management perspective. To develop the data model of a specific facility infrastructure, first extension and then population of the core facility ontology was performed. For the development of the full-blown facility data models, Malpensa and Fiumicino airports in Italy, two major European air-traffic hubs, were chosen as a test-bed platform. Furthermore, the way how these ontology models supported the integration and interoperability of the overall airport energy management system was analyzed as well.

Keywords: airport ontology, energy management, facility data model, ontology modeling

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Authors: Abdelhafid Zenati, Mohamed Tadjine

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The mathematical formulation of biomedical problems is an important phase to understand and predict the dynamic of the controlled population. In this paper we perform a stability analysis of a coupled model for healthy and cancerous cells dynamics in Acute Myeloid Leukemia, this represents our first aim. Second, we illustrate the effect of the interconnection between healthy and cancer cells. The PDE-based model is transformed to a nonlinear distributed state space model (delay system). For an equilibrium point of interest, necessary and sufficient conditions of global asymptotic stability are given. Thus, we came up to give necessary and sufficient conditions of global asymptotic stability of the origin and the healthy situation and control of the dynamics of normal hematopoietic stem cells and cancerous during myelode Acute leukemia. Simulation studies are given to illustrate the developed results.

Keywords: distributed delay, global stability, modelling, nonlinear models, PDE, state space

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Authors: Abdulrahman M. Qahtani, Gary. B. Wills, Andy. M. Gravell

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Communicating and managing customers’ requirements in software development projects play a vital role in the software development process. While it is difficult to do so locally, it is even more difficult to communicate these requirements over distributed boundaries and to convey them to multiple distribution customers. This paper discusses the communication of multiple distribution customers’ requirements in the context of customised software products. The main purpose is to understand the challenges of communicating and managing customisation requirements across distributed boundaries. We propose a model for Communicating Customisation Requirements of Multi-Clients in a Distributed Domain (CCRD). Thereafter, we evaluate that model by presenting the findings of a case study conducted with a company with customisation projects for 18 distributed customers. Then, we compare the outputs of the real case process and the outputs of the CCRD model using simulation methods. Our conjecture is that the CCRD model can reduce the challenge of communication requirements over distributed organisational boundaries, and the delay in decision making and in the entire customisation process time.

Keywords: customisation software products, global software engineering, local decision making, requirement engineering, simulation model

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Authors: Youb Said, Fourar Ali

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To describe the influence of bottom roughness on the free surface flows by numerical modeling, a two-dimensional model was developed. The equations of continuity and momentum (Naviers Stokes equations) are solved by the finite volume method. We considered a turbulent flow in an open channel with a bottom roughness. For our simulations, the K-ε model was used. After setting the initial and boundary conditions and solve the equations set, we were able to achieve the following results: vortex forming in the hollow causing substantial energy dissipation in the obstacle areas that form the bottom roughness. The comparison of our results with experimental ones shows a good agreement in terms of the results in the rough area. However, in other areas, differences were more or less important. These differences are in areas far from the bottom, especially the free surface area just after the bottom. These disagreements are probably due to experimental constants used by the k-ε model.

Keywords: modeling, free surface flow, turbulence, bottom roughness, finite volume, K-ε model, energy dissipation

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Authors: V. Rashtchi, H. Bizhani, F. R. Tatari

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This paper presents a new online loss minimization for an induction motor drive. Among the many loss minimization algorithms (LMAs) for an induction motor, a particle swarm optimization (PSO) has the advantages of fast response and high accuracy. However, the performance of the PSO and other optimization algorithms depend on the accuracy of the modeling of the motor drive and losses. In the development of the loss model, there is always a trade off between accuracy and complexity. This paper presents a new online optimization to determine an optimum flux level for the efficiency optimization of the vector-controlled induction motor drive. An induction motor (IM) model in d-q coordinates is referenced to the rotor magnetizing current. This transformation results in no leakage inductance on the rotor side, thus the decomposition into d-q components in the steady-state motor model can be utilized in deriving the motor loss model. The suggested algorithm is simple for implementation.

Keywords: induction machine, loss minimization, magnetizing current, particle swarm optimization

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Authors: Malihe Motiei, Nor Hidayati Zakaria, Davide Aloini

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This study aims to present a method to develop the failure measurement model for ERP post-implementation. To achieve this outcome, the study firstly evaluates the suitability of Technology-Organization-Environment framework for the proposed conceptual model. This study explains how to discover the constructs and subsequently to design and evaluate the constructs as formative or reflective. Constructs are used including reflective and purely formative. Then, the risk dimensions are investigated to determine the instruments to examine the impact of risk on ERP failure after implementation. Two construct as formative constructs consist inadequate implementation and poor organizational decision making. Subsequently six construct as reflective construct include technical risks, operational risks, managerial risks, top management risks, lack of external risks, and user’s inefficiency risks. A survey was conducted among Iranian industries to collect data. 69 data were collected from manufacturing sectors and the data were analyzed by Smart PLS software. The results indicated that all measurements included 39 critical risk factors were acceptable for the ERP post-implementation failure model.

Keywords: critical risk factors (CRFs), ERP projects, ERP post-implementation, measurement instruments, ERP system failure measurement model

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Authors: Lakhoua Najeh

Abstract:

Aims of the work: After a presentation of the functionality of an example of a mechatronic system which is a paint mixer system, we present the concepts of modeling and safe operation. This paper briefly discusses how to model and protect the functioning of a mechatronic system relying mainly on functional analysis and safe operation techniques. Methods: For the study of an example of a mechatronic system, we use methods for external functional analysis that illustrate the relationships between a mechatronic system and its external environment. Thus, we present the Safe-Structured Analysis Design Technique method (Safe-SADT) which allows the representation of a mechatronic system. A model of operating safety and automation is proposed. This model enables us to use a functional analysis technique of the mechatronic system based on the GRAFCET (Graphe Fonctionnel de Commande des Etapes et Transitions: Step Transition Function Chart) method; study of the safe operation of the mechatronic system based on the Safe-SADT method; automation of the mechatronic system based on a software tool. Results: The expected results are to propose a model and safe operation of a mechatronic system. This methodology enables us to analyze the relevance of the different models based on Safe-SADT and GRAFCET in relation to the control and monitoring functions and to study the means allowing exploiting their synergy. Conclusion: In order to propose a general model of a mechatronic system, a model of analysis, safety operation and automation of a mechatronic system has been developed. This is how we propose to validate this methodology through a case study of a paint mixer system.

Keywords: mechatronic systems, system modeling, safe operation, Safe-SADT

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Authors: Makram Ben Jeddou

Abstract:

The ABC classification is widely used by managers for inventory control. The classical ABC classification is based on the Pareto principle and according to the criterion of the annual use value only. Single criterion classification is often insufficient for a closely inventory control. Multi-criteria inventory classification models have been proposed by researchers in order to take into account other important criteria. From these models, we will consider the ZF model in order to make a sensitive analysis on the composite score calculated for each item. In fact, this score based on a normalized average between a good and a bad optimized index can affect the ABC items classification. We will then focus on the weights assigned to each index and propose a classification compromise.

Keywords: ABC classification, multi criteria inventory classification models, ZF-model

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