Search results for: mathematical programming model
7281 Discovery of Quantified Hierarchical Production Rules from Large Set of Discovered Rules
Authors: Tamanna Siddiqui, M. Afshar Alam
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Automated discovery of Rule is, due to its applicability, one of the most fundamental and important method in KDD. It has been an active research area in the recent past. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form: Decision If < condition> Generality
Keywords: Knowledge discovery in database, quantification, dempster shafer theory, genetic programming, hierarchy, subsumption matrix.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15297280 Automatic Generation of Ontology from Data Source Directed by Meta Models
Authors: Widad Jakjoud, Mohamed Bahaj, Jamal Bakkas
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Through this paper we present a method for automatic generation of ontological model from any data source using Model Driven Architecture (MDA), this generation is dedicated to the cooperation of the knowledge engineering and software engineering. Indeed, reverse engineering of a data source generates a software model (schema of data) that will undergo transformations to generate the ontological model. This method uses the meta-models to validate software and ontological models.
Keywords: Meta model, model, ontology, data source.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19997279 Zero Inflated Strict Arcsine Regression Model
Authors: Y. N. Phang, E. F. Loh
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Zero inflated strict arcsine model is a newly developed model which is found to be appropriate in modeling overdispersed count data. In this study, we extend zero inflated strict arcsine model to zero inflated strict arcsine regression model by taking into consideration the extra variability caused by extra zeros and covariates in count data. Maximum likelihood estimation method is used in estimating the parameters for this zero inflated strict arcsine regression model.Keywords: Overdispersed count data, maximum likelihood estimation, simulated annealing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17587278 Fuzzy Processing of Uncertain Data
Authors: Petr Morávek, Miloš Šeda
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In practice, we often come across situations where it is necessary to make decisions based on incomplete or uncertain data. In control systems it may be due to the unknown exact mathematical model, or its excessive complexity (e.g. nonlinearity) when it is necessary to simplify it, respectively, to solve it using a rule base. In the case of databases, searching data we compare a similarity measure with of the requirements of the selection with stored data, where both the select query and the data itself may contain vague terms, for example in the form of linguistic qualifiers. In this paper, we focus on the processing of uncertain data in databases and demonstrate it on the example multi-criteria decision making in the selection of variants, specified by higher number of technical parameters.Keywords: fuzzy logic, linguistic variable, multicriteria decision
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14227277 Comparison of Two Interval Models for Interval-Valued Differential Evolution
Authors: Hidehiko Okada
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The author previously proposed an extension of differential evolution. The proposed method extends the processes of DE to handle interval numbers as genotype values so that DE can be applied to interval-valued optimization problems. The interval DE can employ either of two interval models, the lower and upper model or the center and width model, for specifying genotype values. Ability of the interval DE in searching for solutions may depend on the model. In this paper, the author compares the two models to investigate which model contributes better for the interval DE to find better solutions. Application of the interval DE is evolutionary training of interval-valued neural networks. A result of preliminary study indicates that the CW model is better than the LU model: the interval DE with the CW model could evolve better neural networks.
Keywords: Evolutionary algorithms, differential evolution, neural network, neuroevolution, interval arithmetic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16697276 Evolution of Performance Measurement Methods in Conditions of Uncertainty: The Implementation of Fuzzy Sets in Performance Measurement
Authors: E. A. Tkachenko, E. M. Rogova, V. V. Klimov
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One of the basic issues of development management is connected with performance measurement as a prerequisite for identifying the achievement of development objectives. The aim of our research is to develop an improved model of assessing a company’s development results. The model should take into account the cyclical nature of development and the high degree of uncertainty in dealing with numerous management tasks. Our hypotheses may be formulated as follows: Hypothesis 1. The cycle of a company’s development may be studied from the standpoint of a project cycle. To do that, methods and tools of project analysis are to be used. Hypothesis 2. The problem of the uncertainty when justifying managerial decisions within the framework of a company’s development cycle can be solved through the use of the mathematical apparatus of fuzzy logic. The reasoned justification of the validity of the hypotheses made is given in the suggested article. The fuzzy logic toolkit applies to the case of technology shift within an enterprise. It is proven that some restrictions in performance measurement that are incurred to conventional methods could be eliminated by implementation of the fuzzy logic apparatus in performance measurement models.
Keywords: Fuzzy logic, fuzzy sets, performance measurement, project analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10807275 Symmetrical Analysis of a Six-Phase Induction Machine Under Fault Conditions
Authors: E. K.Appiah, G. M'boungui, A. A. Jimoh, J. L. Munda, A.S.O. Ogunjuyigbe
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The operational behavior of a six-phase squirrel cage induction machine with faulted stator terminals is presented in this paper. The study is carried out using the derived mathematical model of the machine in the arbitrary reference frame. Tests are conducted on a 1 kW experimental machine. Steady-state and dynamic performance are analyzed for the machine unloaded and loaded conditions. The results shows that with one of the stator phases experiencing either an open- circuit or short circuit fault the machine still produces starting torque, albeit the running performance is significantly derated.Keywords: Performance, fault conditions, six-phase induction machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28347274 Traffic Flow on Road Junctions
Authors: Wah Wah Aung, Cho Cho San
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The paper deals with a mathematical model for fluid dynamic flows on road networks which is based on conservation laws. This nonlinear framework is based on the conservation of cars. We focus on traffic circle, which is a finite number of roads that meet at some junctions. The traffic circle with junctions having either one incoming and two outgoing or two incoming and one outgoing roads. We describe the numerical schemes with the particular boundary conditions used to produce approximated solutions of the problem.
Keywords: boundary conditions, conservation laws, finite difference Schemes, traffic flow.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22377273 A Nodal Transmission Pricing Model based on Newly Developed Expressions of Real and Reactive Power Marginal Prices in Competitive Electricity Markets
Authors: Ashish Saini, A.K. Saxena
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In competitive electricity markets all over the world, an adoption of suitable transmission pricing model is a problem as transmission segment still operates as a monopoly. Transmission pricing is an important tool to promote investment for various transmission services in order to provide economic, secure and reliable electricity to bulk and retail customers. The nodal pricing based on SRMC (Short Run Marginal Cost) is found extremely useful by researchers for sending correct economic signals. The marginal prices must be determined as a part of solution to optimization problem i.e. to maximize the social welfare. The need to maximize the social welfare subject to number of system operational constraints is a major challenge from computation and societal point of views. The purpose of this paper is to present a nodal transmission pricing model based on SRMC by developing new mathematical expressions of real and reactive power marginal prices using GA-Fuzzy based optimal power flow framework. The impacts of selecting different social welfare functions on power marginal prices are analyzed and verified with results reported in literature. Network revenues for two different power systems are determined using expressions derived for real and reactive power marginal prices in this paper.
Keywords: Deregulation, electricity markets, nodal pricing, social welfare function, short run marginal cost.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16497272 Modeling of Material Removal on Machining of Ti-6Al-4V through EDM using Copper Tungsten Electrode and Positive Polarity
Authors: M. M. Rahman, Md. Ashikur Rahman Khan, K. Kadirgama M. M. Noor, Rosli A. Bakar
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This paper deals optimized model to investigate the effects of peak current, pulse on time and pulse off time in EDM performance on material removal rate of titanium alloy utilizing copper tungsten as electrode and positive polarity of the electrode. The experiments are carried out on Ti6Al4V. Experiments were conducted by varying the peak current, pulse on time and pulse off time. A mathematical model is developed to correlate the influences of these variables and material removal rate of workpiece. Design of experiments (DOE) method and response surface methodology (RSM) techniques are implemented. The validity test of the fit and adequacy of the proposed models has been carried out through analysis of variance (ANOVA). The obtained results evidence that as the material removal rate increases as peak current and pulse on time increases. The effect of pulse off time on MRR changes with peak ampere. The optimum machining conditions in favor of material removal rate are verified and compared. The optimum machining conditions in favor of material removal rate are estimated and verified with proposed optimized results. It is observed that the developed model is within the limits of the agreeable error (about 4%) when compared to experimental results. This result leads to desirable material removal rate and economical industrial machining to optimize the input parameters.Keywords: Ti-6Al-4V, material removal rate, copper tungsten, positive polarity, RSM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25407271 Smith Predictor Design by CDM for Temperature Control System
Authors: Roengruen P., Tipsuwanporn V., Puawade P., Numsomran A.
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Smith Predictor control is theoretically a good solution to the problem of controlling the time delay systems. However, it seldom gets use because it is almost impossible to find out a precise mathematical model of the practical system and very sensitive to uncertain system with variable time-delay. In this paper is concerned with a design method of smith predictor for temperature control system by Coefficient Diagram Method (CDM). The simulation results show that the control system with smith predictor design by CDM is stable and robust whilst giving the desired time domain system performance.
Keywords: CDM, Smith Predictor, temperature process
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24387270 Adomian’s Decomposition Method to Generalized Magneto-Thermoelasticity
Authors: Hamdy M. Youssef, Eman A. Al-Lehaibi
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Due to many applications and problems in the fields of plasma physics, geophysics, and other many topics, the interaction between the strain field and the magnetic field has to be considered. Adomian introduced the decomposition method for solving linear and nonlinear functional equations. This method leads to accurate, computable, approximately convergent solutions of linear and nonlinear partial and ordinary differential equations even the equations with variable coefficients. This paper is dealing with a mathematical model of generalized thermoelasticity of a half-space conducting medium. A magnetic field with constant intensity acts normal to the bounding plane has been assumed. Adomian’s decomposition method has been used to solve the model when the bounding plane is taken to be traction free and thermally loaded by harmonic heating. The numerical results for the temperature increment, the stress, the strain, the displacement, the induced magnetic, and the electric fields have been represented in figures. The magnetic field, the relaxation time, and the angular thermal load have significant effects on all the studied fields.
Keywords: Adomian’s Decomposition Method, magneto-thermoelasticity, finite conductivity, iteration method, thermal load.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7987269 A Martingale Residual Diagnostic for Logistic Regression Model
Authors: Entisar A. Elgmati
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Martingale model diagnostic for assessing the fit of logistic regression model to recurrent events data are studied. One way of assessing the fit is by plotting the empirical standard deviation of the standardized martingale residual processes. Here we used another diagnostic plot based on martingale residual covariance. We investigated the plot performance under several types of model misspecification. Clearly the method has correctly picked up the wrong model. Also we present a test statistic that supplement the inspection of the two diagnostic. The test statistic power agrees with what we have seen in the plots of the estimated martingale covariance.
Keywords: Covariance, logistic model, misspecification, recurrent events.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18837268 A Intelligent Inference Model about Complex Systems- Stability: Inspiration from Nature
Authors: Naiqin Feng, Yuhui Qiu, Yingshan Zhang, Fang Wang
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A logic model for analyzing complex systems- stability is very useful to many areas of sciences. In the real world, we are enlightened from some natural phenomena such as “biosphere", “food chain", “ecological balance" etc. By research and practice, and taking advantage of the orthogonality and symmetry defined by the theory of multilateral matrices, we put forward a logic analysis model of stability of complex systems with three relations, and prove it by means of mathematics. This logic model is usually successful in analyzing stability of a complex system. The structure of the logic model is not only clear and simple, but also can be easily used to research and solve many stability problems of complex systems. As an application, some examples are given.Keywords: Complex system, logic model, relation, stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13317267 Performance Comparison of Two Assembly Line Concepts: Conveyor Line and Box Assembly Line
Authors: Kezia Amanda Kurniadi, Emre Islamoglu, Kwangyeol Ryu
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As there has been a recognizable transition in automotive industry from mass production to mass customization, automobile manufacturers and their suppliers have been seeking ways for more flexible and efficient processes. Eventually, modular production is currently being applied to manage the changing orders of the industry. In this paper, two different modular assembly line concepts were studied: conveyor line and box assembly line. Mathematical model for two assembly line concepts were developed and their production line efficiency were compared as a performance measure to improve their assembly line balancing.Keywords: Line Efficiency, Box assembly line, Conventional conveyor line
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29657266 Learning Human-Like Color Categorization through Interaction
Authors: Rinaldo Christian Tanumara, Ming Xie, Chi Kit Au
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Human perceives color in categories, which may be identified using color name such as red, blue, etc. The categorization is unique for each human being. However despite the individual differences, the categorization is shared among members in society. This allows communication among them, especially when using color name. Sociable robot, to live coexist with human and become part of human society, must also have the shared color categorization, which can be achieved through learning. Many works have been done to enable computer, as brain of robot, to learn color categorization. Most of them rely on modeling of human color perception and mathematical complexities. Differently, in this work, the computer learns color categorization through interaction with humans. This work aims at developing the innate ability of the computer to learn the human-like color categorization. It focuses on the representation of color categorization and how it is built and developed without much mathematical complexity.Keywords: Color categorization, color learning, machinelearning, color naming.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15327265 A Combined Neural Network Approach to Soccer Player Prediction
Authors: Wenbin Zhang, Hantian Wu, Jian Tang
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An artificial neural network is a mathematical model inspired by biological neural networks. There are several kinds of neural networks and they are widely used in many areas, such as: prediction, detection, and classification. Meanwhile, in day to day life, people always have to make many difficult decisions. For example, the coach of a soccer club has to decide which offensive player to be selected to play in a certain game. This work describes a novel Neural Network using a combination of the General Regression Neural Network and the Probabilistic Neural Networks to help a soccer coach make an informed decision.
Keywords: General Regression Neural Network, Probabilistic Neural Networks, Neural function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37707264 An Alternative Proof for the Topological Entropy of the Motzkin Shift
Authors: Fahad Alsharari, Mohd Salmi Md Noorani
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A Motzkin shift is a mathematical model for constraints on genetic sequences. In terms of the theory of symbolic dynamics, the Motzkin shift is nonsofic, and therefore, we cannot use the Perron- Frobenius theory to calculate its topological entropy. The Motzkin shift M(M,N) which comes from language theory, is defined to be the shift system over an alphabet A that consists of N negative symbols, N positive symbols and M neutral symbols. For an x in the full shift, x will be in the Motzkin subshift M(M,N) if and only if every finite block appearing in x has a non-zero reduced form. Therefore, the constraint for x cannot be bounded in length. K. Inoue has shown that the entropy of the Motzkin shift M(M,N) is log(M + N + 1). In this paper, a new direct method of calculating the topological entropy of the Motzkin shift is given without any measure theoretical discussion.
Keywords: Motzkin shift, topological entropy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20137263 An Adverse Model for Price Discrimination in the Case of Monopoly
Authors: Daniela Elena Marinescu, Ioana Manafi, Dumitru Marin
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We consider a Principal-Agent model with the Principal being a seller who does not know perfectly how much the buyer (the Agent) is willing to pay for the good. The buyer-s preferences are hence his private information. The model corresponds to the nonlinear pricing problem of Maskin and Riley. We assume there are three types of Agents. The model is solved using “informational rents" as variables. In the last section we present the main characteristics of the optimal contracts in asymmetric information and some possible extensions of the model.Keywords: Adverse selection, asymmetric information, informational rent, nonlinear pricing, optimal contract
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13527262 Experimental Technique for Vibration Reduction of a Motor Pumpin Medical Device
Authors: Young Kuen Cho, Dae Won Lee, Young-Jin Jung, Sung Kuk Kim, Dong-Hyun Seo, Chang-Yong Ko, Han Sung Kim
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Many medical devices are driven by motor pumps. Some researchers reported that the vibration mainly affected medical devices using a motor pump. The purpose of this study was to examine the effect of stiffness and damping coefficient in a 3-dimensional (3D) model of a motor pump and spring. In the present paper, experimental and mathematical tests for the moments of inertia of the 3D model and the material properties were investigated by an INSTRON machine. The response surfaces could be generated by using 3D multi-body analysis and the design of experiment method. It showed that differences in contours of the response surface were clearly found for the particular area. Displacement of the center of the motor pump was decreased at K≈2000 N/M, C≈12.5 N-sec/M. However, the frequency was increased at K≈2000 N/M, C≈15 N-sec/M. In this study, this study suggested experimental technique for vibration reduction for a motor pump in medical device. The combined method suggested in this study will greatly contribute to design of medical devices concerning vibration and noise intervention.
Keywords: Motor pump, Spring, Vibration reduction, Medicaldevices, Moment of Inertia
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19047261 Modeling of Sensitivity for SPR Biosensors- New Aspects
Authors: Volodymyr Chegel
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The computer modeling is carried out for parameter of sensitivity of optoelectronic chemical and biosensors, using phenomena of surface plasmon resonance (SPR). The physical model of SPR-sensor-s is described with (or without) of modifications of sensitive gold film surface by a dielectric layer. The variants of increasing of sensitivity for SPR-biosensors, constructed on the principle gold – dielectric – biomolecular layer are considered. Two methods of mathematical treatment of SPR-curve are compared – traditional, with estimation of sensor-s response as shift of the SPRcurve minimum and proposed, for system with dielectric layer, using calculating of the derivative in the point of SPR-curve half-width.Keywords: Surface Plasmon Resonance, modeling, sensitivity, biosensor
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20727260 Analytical Model for Predicting Whole Building Heat Transfer
Authors: Xiaoshu Lu, Martti Viljanen
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A new analytical model is developed which provides close-formed solutions for both transient indoor and envelope temperature changes in buildings. Time-dependent boundary temperature is presented as Fourier series which can approximate real weather conditions. The final close-formed solutions are simple, concise, and comprehensive. The model was compared with numerical results and good accuracy was obtained. The model can be used as design and control guidelines in engineering applications for analysing mechanical heat transfer properties for buildings.Keywords: Analytical model, heat transfer, whole building.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20467259 Design of Identification Based Adaptive Control for Fermentation Process in Bioreactor
Authors: J. Ritonja
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The biochemical technology has been developing extremely fast since the middle of the last century. The main reason for such development represents a requirement for large production of high-quality biologically manufactured products such as pharmaceuticals, foods, and beverages. The impact of the biochemical industry on the world economy is enormous. The great importance of this industry also results in intensive development in scientific disciplines relevant to the development of biochemical technology. In addition to developments in the fields of biology and chemistry, which enable to understand complex biochemical processes, development in the field of control theory and applications is also very important. In the paper, the control for the biochemical reactor for the milk fermentation was studied. During the fermentation process, the biophysical quantities must be precisely controlled to obtain the high-quality product. To control these quantities, the bioreactor’s stirring drive and/or heating system can be used. Available commercial biochemical reactors are equipped with open loop or conventional linear closed loop control system. Due to the outstanding parameters variations and the partial nonlinearity of the biochemical process, the results obtained with these control systems are not satisfactory. To improve the fermentation process, the self-tuning adaptive control system was proposed. The use of the self-tuning adaptive control is suggested because the parameters’ variations of the studied biochemical process are very slow in most cases. To determine the linearized mathematical model of the fermentation process, the recursive least square identification method was used. Based on the obtained mathematical model the linear quadratic regulator was tuned. The parameters’ identification and the controller’s synthesis are executed on-line and adapt the controller’s parameters to the fermentation process’ dynamics during the operation. The use of the proposed combination represents the original solution for the control of the milk fermentation process. The purpose of the paper is to contribute to the progress of the control systems for the biochemical reactors. The proposed adaptive control system was tested thoroughly. From the obtained results it is obvious that the proposed adaptive control system assures much better following of the reference signal as a conventional linear control system with fixed control parameters.
Keywords: Adaptive control, biochemical reactor, linear quadratic regulator, recursive least square identification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9007258 Supply Chain Modeling and Improving Manufacturing Industry in Developing Countries: A Research Agenda
Authors: F.B. Georgise, K. D. Thoben, M. Seifert
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This paper presents a research agenda on the SCOR model adaptation. SCOR model is designated to measure supply chain performance and logistics impact across the boundaries of individual organizations. It is at its growing stage of its life cycle and is enjoying the leverage of becoming the industry standard. The SCOR model has been developed and used widely in developed countries context. This research focuses on the SCOR model adaptation for the manufacturing industry in developing countries. With a necessary understanding of the characteristics, difficulties and problems of the manufacturing industry in developing countries- supply chain; consequently, we will try to designs an adapted model with its building blocks: business process model, performance measures and best practices.Keywords: developing countries, manufacturing industry, SCOR model adaptation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22207257 Ride Control of Passenger Cars with Semi-active Suspension System Using a Linear Quadratic Regulator and Hybrid Optimization Algorithm
Authors: Ali Fellah Jahromi, Wen Fang Xie, Rama B. Bhat
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A semi-active control strategy for suspension systems of passenger cars is presented employing Magnetorheological (MR) dampers. The vehicle is modeled with seven DOFs including the, roll pitch and bounce of car body, and the vertical motion of the four tires. In order to design an optimal controller based on the actuator constraints, a Linear-Quadratic Regulator (LQR) is designed. The design procedure of the LQR consists of selecting two weighting matrices to minimize the energy of the control system. This paper presents a hybrid optimization procedure which is a combination of gradient-based and evolutionary algorithms to choose the weighting matrices with regards to the actuator constraint. The optimization algorithm is defined based on maximum comfort and actuator constraints. It is noted that utilizing the present control algorithm may significantly reduce the vibration response of the passenger car, thus, providing a comfortable ride.Keywords: Full car model, Linear Quadratic Regulator, Sequential Quadratic Programming, Genetic Algorithm
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29467256 Development of Logic Model for R&D Program Plan Analysis in Preliminary Feasibility Study
Authors: Hyun-Kyu Kang
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The Korean Government has applied the preliminary feasibility study to new government R&D program plans as a part of an evaluation system for R&D programs. The preliminary feasibility study for the R&D program is composed of 3 major criteria such as technological, policy and economic analysis. The program logic model approach is used as a part of the technological analysis in the preliminary feasibility study. We has developed and improved the R&D program logic model. The logic model is a very useful tool for evaluating R&D program plans. Using a logic model, we can generally identify important factors of the R&D program plan, analyze its logic flow and find the disconnection or jump in the logic flow among components of the logic model.
Keywords: Preliminary feasibility study, R&D program logic model, technological analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21577255 An Improved Model for Prediction of the Effective Thermal Conductivity of Nanofluids
Authors: K. Abbaspoursani, M. Allahyari, M. Rahmani
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Thermal conductivity is an important characteristic of a nanofluid in laminar flow heat transfer. This paper presents an improved model for the prediction of the effective thermal conductivity of nanofluids based on dimensionless groups. The model expresses the thermal conductivity of a nanofluid as a function of the thermal conductivity of the solid and liquid, their volume fractions and particle size. The proposed model includes a parameter which accounts for the interfacial shell, brownian motion, and aggregation of particle. The validation of the model is verified by applying the results obtained by the experiments of Tio2-water and Al2o3-water nanofluids.Keywords: Critical particle size, nanofluid, model, and thermal conductivity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20517254 Authentication Analysis of the 802.11i Protocol
Authors: Zeeshan Furqan, Shahabuddin Muhammad, Ratan Guha
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IEEE has designed 802.11i protocol to address the security issues in wireless local area networks. Formal analysis is important to ensure that the protocols work properly without having to resort to tedious testing and debugging which can only show the presence of errors, never their absence. In this paper, we present the formal verification of an abstract protocol model of 802.11i. We translate the 802.11i protocol into the Strand Space Model and then prove the authentication property of the resulting model using the Strand Space formalism. The intruder in our model is imbued with powerful capabilities and repercussions to possible attacks are evaluated. Our analysis proves that the authentication of 802.11i is not compromised in the presented model. We further demonstrate how changes in our model will yield a successful man-in-the-middle attack.Keywords: authentication, formal analysis, formal verification, security.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15197253 Integral Methods in the Determination of Temperature Fields of Cooled Blades of Gas Turbines
Authors: C. Ardil
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A mathematical model and an effective numerical method for calculating the temperature field of the profile part of convection cooled blades have been developed. The theoretical substantiation of the method is proved by corresponding theorems. To this end, convergent quadrature processes were developed and error estimates were obtained in terms of the Zygmund continuity moduli.The boundary conditions for heat exchange are determined from the solution of the corresponding integral equations and empirical relations.The reliability of the developed methods is confirmed by the calculation-experimental studies of the thermohydraulic characteristics of the nozzle apparatus of the first stage of a gas turbine.Keywords: Integral methods, determination of temperature fields, cooled blades, gas turbines.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7627252 Learning the Dynamics of Articulated Tracked Vehicles
Authors: Mario Gianni, Manuel A. Ruiz Garcia, Fiora Pirri
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In this work, we present a Bayesian non-parametric approach to model the motion control of ATVs. The motion control model is based on a Dirichlet Process-Gaussian Process (DP-GP) mixture model. The DP-GP mixture model provides a flexible representation of patterns of control manoeuvres along trajectories of different lengths and discretizations. The model also estimates the number of patterns, sufficient for modeling the dynamics of the ATV.Keywords: Dirichlet processes, Gaussian processes, robot control learning, tracked vehicles.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1784