Search results for: Predictive Model
7228 Adaptive Gaussian Mixture Model for Skin Color Segmentation
Authors: Reza Hassanpour, Asadollah Shahbahrami, Stephan Wong
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Skin color based tracking techniques often assume a static skin color model obtained either from an offline set of library images or the first few frames of a video stream. These models can show a weak performance in presence of changing lighting or imaging conditions. We propose an adaptive skin color model based on the Gaussian mixture model to handle the changing conditions. Initial estimation of the number and weights of skin color clusters are obtained using a modified form of the general Expectation maximization algorithm, The model adapts to changes in imaging conditions and refines the model parameters dynamically using spatial and temporal constraints. Experimental results show that the method can be used in effectively tracking of hand and face regions.Keywords: Face detection, Segmentation, Tracking, Gaussian Mixture Model, Adaptation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24037227 External Effects on Dynamic Competitive Model of Domestic Airline and High Speed Rail
Authors: Shih-Ching Lo, Yu-Ping Liao
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Social-economic variables influence transportation demand largely. Analyses of discrete choice model consider social-economic variables to study traveler-s mode choice and demand. However, to calibrate the discrete choice model needs to have plenty of questionnaire survey. Also, an aggregative model is proposed. The historical data of passenger volumes for high speed rail and domestic civil aviation are employed to calibrate and validate the model. In this study, models with different social-economic variables, which are oil price, GDP per capita, CPI and economic growth rate, are compared. From the results, the model with the oil price is better than models with the other social-economic variables.Keywords: forecasting, passenger volume, dynamic competitive model, social-economic variables, oil price.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15757226 Javanese Character Recognition Using Hidden Markov Model
Authors: Anastasia Rita Widiarti, Phalita Nari Wastu
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Hidden Markov Model (HMM) is a stochastic method which has been used in various signal processing and character recognition. This study proposes to use HMM to recognize Javanese characters from a number of different handwritings, whereby HMM is used to optimize the number of state and feature extraction. An 85.7 % accuracy is obtained as the best result in 16-stated vertical model using pure HMM. This initial result is satisfactory for prompting further research.Keywords: Character recognition, off-line handwritingrecognition, Hidden Markov Model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19787225 Mathematical Modeling of the AMCs Cross-Contamination Removal in the FOUPs: Finite Element Formulation and Application in FOUP’s Decontamination
Authors: N. Santatriniaina, J. Deseure, T.Q. Nguyen, H. Fontaine, C. Beitia, L. Rakotomanana
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Nowadays, with the increasing of the wafer's size and the decreasing of critical size of integrated circuit manufacturing in modern high-tech, microelectronics industry needs a maximum attention to challenge the contamination control. The move to 300 [mm] is accompanied by the use of Front Opening Unified Pods for wafer and his storage. In these pods an airborne cross contamination may occur between wafers and the pods. A predictive approach using modeling and computational methods is very powerful method to understand and qualify the AMCs cross contamination processes. This work investigates the required numerical tools which are employed in order to study the AMCs cross-contamination transfer phenomena between wafers and FOUPs. Numerical optimization and finite element formulation in transient analysis were established. Analytical solution of one dimensional problem was developed and the calibration process of physical constants was performed. The least square distance between the model (analytical 1D solution) and the experimental data are minimized. The behavior of the AMCs intransient analysis was determined. The model framework preserves the classical forms of the diffusion and convection-diffusion equations and yields to consistent form of the Fick's law. The adsorption process and the surface roughness effect were also traduced as a boundary condition using the switch condition Dirichlet to Neumann and the interface condition. The methodology is applied, first using the optimization methods with analytical solution to define physical constants, and second using finite element method including adsorption kinetic and the switch of Dirichlet to Neumann condition.
Keywords: AMCs, FOUP, cross-contamination, adsorption, diffusion, numerical analysis, wafers, Dirichlet to Neumann, finite elements methods, Fick’s law, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31617224 Analytical Model to Predict the Shear Capacity of Reinforced Concrete Beams Externally Strengthened with CFRP Composites Conditions
Authors: Rajai Al-Rousan
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This paper presents a proposed analytical model for predicting the shear strength of reinforced concrete beams strengthened with CFRP composites as external reinforcement. The proposed analytical model can predict the shear contribution of CFRP composites of RC beams with an acceptable coefficient of correlation with the tested results. Based on the comparison of the proposed model with the published well-known models (ACI model, Triantafillou model, and Colotti model), the ACI model had a wider range of 0.16 to 10.08 for the ratio between tested and predicted ultimate shears at failure. Also, an acceptable range of 0.27 to 2.78 for the ratio between tested and predicted ultimate shears by the Triantafillou model. Finally, the best prediction (the ratio between the tested and predicted ones) of the ultimate shear capacity is observed by using Colotti model with a range of 0.20 to 1.78. Thus, the contribution of the CFRP composites as external reinforcement can be predicted with high accuracy by using the proposed analytical model.
Keywords: Predicting, shear capacity, reinforced concrete, beams, strengthened, externally, CFRP composites.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8587223 An Enhanced Artificial Neural Network for Air Temperature Prediction
Authors: Brian A. Smith, Ronald W. McClendon, Gerrit Hoogenboom
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The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. An improved model for temperature prediction in Georgia was developed by including information on seasonality and modifying parameters of an existing artificial neural network model. Alternative models were compared by instantiating and training multiple networks for each model. The inclusion of up to 24 hours of prior weather information and inputs reflecting the day of year were among improvements that reduced average four-hour prediction error by 0.18°C compared to the prior model. Results strongly suggest model developers should instantiate and train multiple networks with different initial weights to establish appropriate model parameters.
Keywords: Time-series forecasting, weather modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18537222 Phenomenological Ductile Fracture Criteria Applied to the Cutting Process
Authors: František Šebek, Petr Kubík, Jindřich Petruška, Jiří Hůlka
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Present study is aimed on the cutting process of circular cross-section rods where the fracture is used to separate one rod into two pieces. Incorporating the phenomenological ductile fracture model into the explicit formulation of finite element method, the process can be analyzed without the necessity of realizing too many real experiments which could be expensive in case of repetitive testing in different conditions. In the present paper, the steel AISI 1045 was examined and the tensile tests of smooth and notched cylindrical bars were conducted together with biaxial testing of the notched tube specimens to calibrate material constants of selected phenomenological ductile fracture models. These were implemented into the Abaqus/Explicit through user subroutine VUMAT and used for cutting process simulation. As the calibration process is based on variables which cannot be obtained directly from experiments, numerical simulations of fracture tests are inevitable part of the calibration. Finally, experiments regarding the cutting process were carried out and predictive capability of selected fracture models is discussed. Concluding remarks then make the summary of gained experience both with the calibration and application of particular ductile fracture criteria.
Keywords: Ductile fracture, phenomenological criteria, cutting process, explicit formulation, AISI 1045 steel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25787221 Discovering the Dimension of Abstractness: Structure-Based Model that Learns New Categories and Categorizes on Different Levels of Abstraction
Authors: Georgi I. Petkov, Ivan I. Vankov, Yolina A. Petrova
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A structure-based model of category learning and categorization at different levels of abstraction is presented. The model compares different structures and expresses their similarity implicitly in the forms of mappings. Based on this similarity, the model can categorize different targets either as members of categories that it already has or creates new categories. The model is novel using two threshold parameters to evaluate the structural correspondence. If the similarity between two structures exceeds the higher threshold, a new sub-ordinate category is created. Vice versa, if the similarity does not exceed the higher threshold but does the lower one, the model creates a new category on higher level of abstraction.
Keywords: Analogy-making, categorization, learning of categories, abstraction, hierarchical structure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7717220 A Mean–Variance–Skewness Portfolio Optimization Model
Authors: Kostas Metaxiotis
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Portfolio optimization is one of the most important topics in finance. This paper proposes a mean–variance–skewness (MVS) portfolio optimization model. Traditionally, the portfolio optimization problem is solved by using the mean–variance (MV) framework. In this study, we formulate the proposed model as a three-objective optimization problem, where the portfolio's expected return and skewness are maximized whereas the portfolio risk is minimized. For solving the proposed three-objective portfolio optimization model we apply an adapted version of the non-dominated sorting genetic algorithm (NSGAII). Finally, we use a real dataset from FTSE-100 for validating the proposed model.
Keywords: Evolutionary algorithms, portfolio optimization, skewness, stock selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13967219 The Gasoil Hydrofining Kinetics Constants Identification
Authors: C. Patrascioiu, V. Matei, N. Nicolae
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The paper describes the experiments and the kinetic parameters calculus of the gasoil hydrofining. They are presented experimental results of gasoil hidrofining using Mo and promoted with Ni on aluminum support catalyst. The authors have adapted a kinetic model gasoil hydrofining. Using this proposed kinetic model and the experimental data they have calculated the parameters of the model. The numerical calculus is based on minimizing the difference between the experimental sulf concentration and kinetic model estimation.
Keywords: Hydrofining, kinetic, modeling, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20077218 Variable Rough Set Model and Its Knowledge Reduction for Incomplete and Fuzzy Decision Information Systems
Authors: Da-kuan Wei, Xian-zhong Zhou, Dong-jun Xin, Zhi-wei Chen
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The information systems with incomplete attribute values and fuzzy decisions commonly exist in practical problems. On the base of the notion of variable precision rough set model for incomplete information system and the rough set model for incomplete and fuzzy decision information system, the variable rough set model for incomplete and fuzzy decision information system is constructed, which is the generalization of the variable precision rough set model for incomplete information system and that of rough set model for incomplete and fuzzy decision information system. The knowledge reduction and heuristic algorithm, built on the method and theory of precision reduction, are proposed.Keywords: Rough set, Incomplete and fuzzy decision information system, Limited valued tolerance relation, Knowledge reduction, Variable rough set model
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15797217 Segmentation of Piecewise Polynomial Regression Model by Using Reversible Jump MCMC Algorithm
Authors: Suparman
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Piecewise polynomial regression model is very flexible model for modeling the data. If the piecewise polynomial regression model is matched against the data, its parameters are not generally known. This paper studies the parameter estimation problem of piecewise polynomial regression model. The method which is used to estimate the parameters of the piecewise polynomial regression model is Bayesian method. Unfortunately, the Bayes estimator cannot be found analytically. Reversible jump MCMC algorithm is proposed to solve this problem. Reversible jump MCMC algorithm generates the Markov chain that converges to the limit distribution of the posterior distribution of piecewise polynomial regression model parameter. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of piecewise polynomial regression model.
Keywords: Piecewise, Bayesian, reversible jump MCMC, segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16627216 Model-Based Software Regression Test Suite Reduction
Authors: Shiwei Deng, Yang Bao
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In this paper, we present a model-based regression test suite reducing approach that uses EFSM model dependence analysis and probability-driven greedy algorithm to reduce software regression test suites. The approach automatically identifies the difference between the original model and the modified model as a set of elementary model modifications. The EFSM dependence analysis is performed for each elementary modification to reduce the regression test suite, and then the probability-driven greedy algorithm is adopted to select the minimum set of test cases from the reduced regression test suite that cover all interaction patterns. Our initial experience shows that the approach may significantly reduce the size of regression test suites.Keywords: Dependence analysis, EFSM model, greedy algorithm, regression test.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19127215 Model of the Increasing the Capacity of the Train and Railway Track by Using the New Type of Wagon
Authors: Martin Kendra, Jaroslav Mašek, Juraj Čamaj, Martin Búda
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The paper deals with possibilities of increase train capacity by using a new type of railway wagon. In the first part is created a mathematical model to calculate the capacity of the train. The model is based on the main limiting parameters of the train - maximum number of axles per train, maximum gross weight of train, maximum length of train and number of TEUs per one wagon. In the second part is the model applied to four different model trains with different composition of the train set and three different average weights of TEU and a train consisting of a new type of wagons. The result is to identify where the carrying capacity of the original trains is higher, respectively less than a capacity of train consisting of a new type of wagons.Keywords: Loading units, theoretical capacity model, train capacity, wagon for intermodal transport.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23967214 Modeling and Simulation Methods Using MATLAB/Simulink
Authors: Jamuna Konda, Umamaheswara Reddy Karumuri, Sriramya Muthugi, Varun Pishati, Ravi Shakya,
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This paper investigates the challenges involved in mathematical modeling of plant simulation models ensuring the performance of the plant models much closer to the real time physical model. The paper includes the analysis performed and investigation on different methods of modeling, design and development for plant model. Issues which impact the design time, model accuracy as real time model, tool dependence are analyzed. The real time hardware plant would be a combination of multiple physical models. It is more challenging to test the complete system with all possible test scenarios. There are possibilities of failure or damage of the system due to any unwanted test execution on real time.
Keywords: Model Based Design, MATLAB, Simulink, Stateflow, plant model, real time model, real-time workshop, target language compiler.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16827213 Development of a Model for the Comprehensive Analysis and Evaluation of Service Productivity
Authors: A. Petz, S. Duckwitz, C. Schmalz, S. Meyer, S. Mütze-Niewöhner, C.M. Schlick
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Although services play a crucial role in economy, service did not gain as much importance as productivity management in manufacturing. This paper presents key findings from literature and practice. Based on an initial definition of complex services, seven productivity concepts are briefly presented and assessed by relevant, complex service specific criteria. Following the findings a complex service productivity model is proposed. The novel model comprises of all specific dimensions of service provision from both, the provider-s as well as costumer-s perspective. A clear assignment of identified value drivers and relationships between them is presented. In order to verify the conceptual service productivity model a case study from a project engineering department of a chemical plant development and construction company is presented.Keywords: assessment model, complex services, service productivity model, value driver.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14687212 A Mixed Integer Linear Programming Model for Flexible Job Shop Scheduling Problem
Authors: Mohsen Ziaee
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In this paper, a mixed integer linear programming (MILP) model is presented to solve the flexible job shop scheduling problem (FJSP). This problem is one of the hardest combinatorial problems. The objective considered is the minimization of the makespan. The computational results of the proposed MILP model were compared with those of the best known mathematical model in the literature in terms of the computational time. The results show that our model has better performance with respect to all the considered performance measures including relative percentage deviation (RPD) value, number of constraints, and total number of variables. By this improved mathematical model, larger FJS problems can be optimally solved in reasonable time, and therefore, the model would be a better tool for the performance evaluation of the approximation algorithms developed for the problem.Keywords: Scheduling, flexible job shop, makespan, mixed integer linear programming.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16647211 A Multiclass BCMP Queueing Modeling and Simulation-Based Road Traffic Flow Analysis
Authors: Jouhra Dad, Mohammed Ouali, Yahia Lebbah
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Urban road network traffic has become one of the most studied research topics in the last decades. This is mainly due to the enlargement of the cities and the growing number of motor vehicles traveling in this road network. One of the most sensitive problems is to verify if the network is congestion-free. Another related problem is the automatic reconfiguration of the network without building new roads to alleviate congestions. These problems require an accurate model of the traffic to determine the steady state of the system. An alternative is to simulate the traffic to see if there are congestions and when and where they occur. One key issue is to find an adequate model for road intersections. Once the model established, either a large scale model is built or the intersection is represented by its performance measures and simulation for analysis. In both cases, it is important to seek the queueing model to represent the road intersection. In this paper, we propose to model the road intersection as a BCMP queueing network and we compare this analytical model against a simulation model for validation.Keywords: Queueing theory, transportation systems, BCMPqueueing network, performance measures, modeling, simulation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24307210 An Automatic Model Transformation Methodology Based on Semantic and Syntactic Comparisons and the Granularity Issue Involved
Authors: Tiexin Wang, Sebastien Truptil, Frederick Benaben
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Model transformation, as a pivotal aspect of Modeldriven engineering, attracts more and more attentions both from researchers and practitioners. Many domains (enterprise engineering, software engineering, knowledge engineering, etc.) use model transformation principles and practices to serve to their domain specific problems; furthermore, model transformation could also be used to fulfill the gap between different domains: by sharing and exchanging knowledge. Since model transformation has been widely used, there comes new requirement on it: effectively and efficiently define the transformation process and reduce manual effort that involved in. This paper presents an automatic model transformation methodology based on semantic and syntactic comparisons, and focuses particularly on granularity issue that existed in transformation process. Comparing to the traditional model transformation methodologies, this methodology serves to a general purpose: crossdomain methodology. Semantic and syntactic checking measurements are combined into a refined transformation process, which solves the granularity issue. Moreover, semantic and syntactic comparisons are supported by software tool; manual effort is replaced in this way.Keywords: Automatic model transformation, granularity issue, model-driven engineering, semantic and syntactic comparisons.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21847209 BTG-BIBA: A Flexibility-Enhanced Biba Model Using BTG Strategies for Operating System
Authors: Gang Liu, Can Wang, Runnan Zhang, Quan Wang, Huimin Song, Shaomin Ji
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Biba model can protect information integrity but might deny various non-malicious access requests of the subjects, thereby decreasing the availability in the system. Therefore, a mechanism that allows exceptional access control is needed. Break the Glass (BTG) strategies refer an efficient means for extending the access rights of users in exceptional cases. These strategies help to prevent a system from stagnation. An approach is presented in this work for integrating Break the Glass strategies into the Biba model. This research proposes a model, BTG-Biba, which provides both an original Biba model used in normal situations and a mechanism used in emergency situations. The proposed model is context aware, can implement a fine-grained type of access control and primarily solves cross-domain access problems. Finally, the flexibility and availability improvement with the use of the proposed model is illustrated.Keywords: Biba model, break the glass, context, cross-domain, fine-grained.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11387208 A Fuzzy Mixed Integer Multi-Scenario Portfolio Optimization Model
Authors: M. S. Osman, A. A. Tharwat, I. A. El-Khodary, A. G. Chalabi
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In this paper, we propose a multiple objective optimization model with respect to portfolio selection problem for investors looking forward to diversify their equity investments in a number of equity markets. Based on Markowitz-s M-V model we developed a Fuzzy Mixed Integer Multi-Objective Nonlinear Programming Problem (FMIMONLP) to maximize the investors- future gains on equity markets, reach the optimal proportion of the budget to be invested in different equities. A numerical example with a comprehensive analysis on artificial data from several equity markets is presented in order to illustrate the proposed model and its solution method. The model performed well compared with the deterministic version of the model.
Keywords: Equity Markets, Future Scenarios, PortfolioSelection, Multiple Criteria Fuzzy Optimization
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19647207 Human Factors as the Main Reason of the Accident in Scaffold Use Assessment
Authors: Krzysztof J. Czarnocki, E. Czarnocka, K. Szaniawska
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Main goal of the research project is Scaffold Use Risk Assessment Model (SURAM) formulation, developed for the assessment of risk levels as a various construction process stages with various work trades. Finally, in 2016, the project received financing by the National Center for Research and development according to PBS3/A2/19/2015–Research Grant. The presented data, calculations and analyzes discussed in this paper were created as a result of the completion on the first and second phase of the PBS3/A2/19/2015 project. Method: One of the arms of the research project is the assessment of worker visual concentration on the sight zones as well as risky visual point inadequate observation. In this part of research, the mobile eye-tracker was used to monitor the worker observation zones. SMI Eye Tracking Glasses is a tool, which allows us to analyze in real time and place where our eyesight is concentrated on and consequently build the map of worker's eyesight concentration during a shift. While the project is still running, currently 64 construction sites have been examined, and more than 600 workers took part in the experiment including monitoring of typical parameters of the work regimen, workload, microclimate, sound vibration, etc. Full equipment can also be useful in more advanced analyses. Because of that technology we have verified not only main focus of workers eyes during work on or next to scaffolding, but we have also examined which changes in the surrounding environment during their shift influenced their concentration. In the result of this study it has been proven that only up to 45.75% of the shift time, workers’ eye concentration was on one of three work-related areas. Workers seem to be distracted by noisy vehicles or people nearby. In opposite to our initial assumptions and other authors’ findings, we observed that the reflective parts of the scaffoldings were not more recognized by workers in their direct workplaces. We have noticed that the red curbs were the only well recognized part on a very few scaffoldings. Surprisingly on numbers of samples, we have not recognized any significant number of concentrations on those curbs. Conclusion: We have found the eye-tracking method useful for the construction of the SURAM model in the risk perception and worker’s behavior sub-modules. We also have found that the initial worker's stress and work visual conditions seem to be more predictive for assessment of the risky developing situation or an accident than other parameters relating to a work environment.
Keywords: Accident assessment model, eye tracking, occupational safety, scaffolding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11297206 Building the Reliability Prediction Model of Component-Based Software Architectures
Authors: Pham Thanh Trung, Huynh Quyet Thang
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Reliability is one of the most important quality attributes of software. Based on the approach of Reussner and the approach of Cheung, we proposed the reliability prediction model of component-based software architectures. Also, the value of the model is shown through the experimental evaluation on a web server system.
Keywords: component-based architecture, reliability prediction model, software reliability engineering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14117205 An E-Government Implementation Model for Peruvian State Companies Based on COBIT 5.0: Definition and Goals of the Model
Authors: M. Bruzza, M. Tupia, F. Rodríguez
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As part of the regulatory compliance process and the streamlining of public administration, the Peruvian government has implemented the National E-Government Plan in all state institutions with the aim of providing citizens with solid services based on the use of Information and Communications Technologies (ICT). As part of the regulations, the requisites to be met by public institutions have been submitted. However, the lack of an implementation model was detected, one that can serve as a guide to such institutions in order to materialize the organizational and technological structures needed, which allow them to provide the required digital services. This paper develops an implementation model of electronic government (e-government) for Peru’s state institutions, in compliance with current regulations based on a COBIT 5.0 framework. Furthermore, the paper introduces phase 1 of this model: business and IT goals, the goals cascade and the future model of processes.
Keywords: E-government, implementation, model, COBIT 5.0, digital services, u-government, m-government.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13837204 Stability Analysis of Mutualism Population Model with Time Delay
Authors: Rusliza Ahmad, Harun Budin
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This paper studies the effect of time delay on stability of mutualism population model with limited resources for both species. First, the stability of the model without time delay is analyzed. The model is then improved by considering a time delay in the mechanism of the growth rate of the population. We analyze the effect of time delay on the stability of the stable equilibrium point. Result showed that the time delay can induce instability of the stable equilibrium point, bifurcation and stability switches.Keywords: Bifurcation, Delay margin, Mutualism population model, Time delay
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19717203 Fuzzy PID Controller with Coupled Rules for a Nonlinear Quarter Car Model
Authors: Şaban Çetin, Özgür Demir
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In this study, Fuzzy PID Control scheme is designed for an active suspension system. The main goal of an active suspension system for using in a vehicle model is reducing body deflections and handling high comfort for a passenger car. The present system was modelled as a two-degree-of-freedom (2-DOF) nonlinear vehicle model.Keywords: Active suspension system, Fuzzy PID controller, a nonlinear quarter car model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23857202 Effect of Different Model Drugs on the Properties of Model Membranes from Fishes
Authors: M. Kumpugdee-Vollrath, T. G. D. Phu, M. Helmis
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A suitable model membrane to study the pharmacological effect of pharmaceutical products is human stratum corneum because this layer of human skin is the outermost layer and it is an important barrier to be passed through. Other model membranes which were also used are for example skins from pig, mouse, reptile or fish. We are interested in fish skins in this project. The advantages of the fish skins are, that they can be obtained from the supermarket or fish shop. However, the fish skins should be freshly prepared and used directly without storage. In order to understand the effect of different model drugs e.g. lidocaine HCl, resveratrol, paracetamol, ibuprofen, acetyl salicylic acid on the properties of the model membrane from various types of fishes e.g. trout, salmon, cod, plaice permeation tests were performed and differential scanning calorimetry was applied.
Keywords: Fish skin, model membrane, permeation, DSC, lidocaine HCl, resveratrol, paracetamol, ibuprofen, acetyl salicylic acid.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11297201 Predictive Analytics of Student Performance Determinants in Education
Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi
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Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine (SVM), Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis (LDA), and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.
Keywords: Student performance, supervised machine learning, prediction, classification, cross-validation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5297200 Mathematical Models of Flow Shop and Job Shop Scheduling Problems
Authors: Miloš Šeda
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In this paper, mathematical models for permutation flow shop scheduling and job shop scheduling problems are proposed. The first problem is based on a mixed integer programming model. As the problem is NP-complete, this model can only be used for smaller instances where an optimal solution can be computed. For large instances, another model is proposed which is suitable for solving the problem by stochastic heuristic methods. For the job shop scheduling problem, a mathematical model and its main representation schemes are presented.
Keywords: Flow shop, job shop, mixed integer model, representation scheme.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 46597199 Brainwave Classification for Brain Balancing Index (BBI) via 3D EEG Model Using k-NN Technique
Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan
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In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.
Keywords: Brain balancing, kNN, power spectral density, 3D EEG model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2610