Search results for: Fuzzy Goal Programming.
1341 Fuzzy Inference System for Determining Collision Risk of Ship in Madura Strait Using Automatic Identification System
Authors: Emmy Pratiwi, Ketut B. Artana, A. A. B. Dinariyana
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Madura Strait is considered as one of the busiest shipping channels in Indonesia. High vessel traffic density in Madura Strait gives serious threat due to navigational safety in this area, i.e. ship collision. This study is necessary as an attempt to enhance the safety of marine traffic. Fuzzy inference system (FIS) is proposed to calculate risk collision of ships. Collision risk is evaluated based on ship domain, Distance to Closest Point of Approach (DCPA), and Time to Closest Point of Approach (TCPA). Data were collected by utilizing Automatic Identification System (AIS). This study considers several ships’ domain models to give the characteristic of marine traffic in the waterways. Each encounter in the ship domain is analyzed to obtain the level of collision risk. Risk level of ships, as the result in this study, can be used as guidance to avoid the accident, providing brief description about safety traffic in Madura Strait and improving the navigational safety in the area.
Keywords: Automatic identification system, collision risk, DCPA, fuzzy inference system, TCPA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15391340 Design and Control Strategy of Diffused Air Aeration System
Authors: Doaa M. Atia, Faten H. Fahmy, Ninet M. Ahmed, Hassen T. Dorrah
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During the past decade, pond aeration systems have been developed which will sustain large quantities of fish and invertebrate biomass. Dissolved Oxygen (DO) is considered to be among the most important water quality parameters in fish culture. Fishponds in aquaculture farms are usually located in remote areas where grid lines are at far distance. Aeration of ponds is required to prevent mortality and to intensify production, especially when feeding is practical, and in warm regions. To increase pond production it is necessary to control dissolved oxygen. Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. This paper presents a new design of diffused aeration system using fuel cell as a power source. Also fuzzy logic control Technique (FLC) is used for controlling the speed of air flow rate from the blower to air piping connected to the pond by adjusting blower speed. MATLAB SIMULINK results show high performance of fuzzy logic control (FLC).Keywords: aeration system, Fuel cell, Artificial intelligence (AI) techniques, fuzzy logic control
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34941339 Soft Real-Time Fuzzy Task Scheduling for Multiprocessor Systems
Authors: Mahdi Hamzeh, Sied Mehdi Fakhraie, Caro Lucas
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All practical real-time scheduling algorithms in multiprocessor systems present a trade-off between their computational complexity and performance. In real-time systems, tasks have to be performed correctly and timely. Finding minimal schedule in multiprocessor systems with real-time constraints is shown to be NP-hard. Although some optimal algorithms have been employed in uni-processor systems, they fail when they are applied in multiprocessor systems. The practical scheduling algorithms in real-time systems have not deterministic response time. Deterministic timing behavior is an important parameter for system robustness analysis. The intrinsic uncertainty in dynamic real-time systems increases the difficulties of scheduling problem. To alleviate these difficulties, we have proposed a fuzzy scheduling approach to arrange real-time periodic and non-periodic tasks in multiprocessor systems. Static and dynamic optimal scheduling algorithms fail with non-critical overload. In contrast, our approach balances task loads of the processors successfully while consider starvation prevention and fairness which cause higher priority tasks have higher running probability. A simulation is conducted to evaluate the performance of the proposed approach. Experimental results have shown that the proposed fuzzy scheduler creates feasible schedules for homogeneous and heterogeneous tasks. It also and considers tasks priorities which cause higher system utilization and lowers deadline miss time. According to the results, it performs very close to optimal schedule of uni-processor systems.Keywords: Computational complexity, Deadline, Feasible scheduling, Fuzzy scheduling, Priority, Real-time multiprocessor systems, Robustness, System utilization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21051338 A Fuzzy Approach for Delay Proportion Differentiated Service
Authors: Mehran Garmehi, Yasser Mansouri
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There are two paradigms proposed to provide QoS for Internet applications: Integrated service (IntServ) and Differentiated service (DiffServ).Intserv is not appropriate for large network like Internet. Because is very complex. Therefore, to reduce the complexity of QoS management, DiffServ was introduced to provide QoS within a domain using aggregation of flow and per- class service. In theses networks QoS between classes is constant and it allows low priority traffic to be effected from high priority traffic, which is not suitable. In this paper, we proposed a fuzzy controller, which reduced the effect of low priority class on higher priority ones. Our simulations shows that, our approach reduces the latency dependency of low priority class on higher priority ones, in an effective manner.
Keywords: QoS, Differentiated Service (DiffServ), FuzzyController, Delay.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12651337 Scour Depth Prediction around Bridge Piers Using Neuro-Fuzzy and Neural Network Approaches
Authors: H. Bonakdari, I. Ebtehaj
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The prediction of scour depth around bridge piers is frequently considered in river engineering. One of the key aspects in efficient and optimum bridge structure design is considered to be scour depth estimation around bridge piers. In this study, scour depth around bridge piers is estimated using two methods, namely the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). Therefore, the effective parameters in scour depth prediction are determined using the ANN and ANFIS methods via dimensional analysis, and subsequently, the parameters are predicted. In the current study, the methods’ performances are compared with the nonlinear regression (NLR) method. The results show that both methods presented in this study outperform existing methods. Moreover, using the ratio of pier length to flow depth, ratio of median diameter of particles to flow depth, ratio of pier width to flow depth, the Froude number and standard deviation of bed grain size parameters leads to optimal performance in scour depth estimation.
Keywords: Adaptive neuro-fuzzy inference system, ANFIS, artificial neural network, ANN, bridge pier, scour depth, nonlinear regression, NLR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8981336 Predicting Residence Time of Pollutants in Transient Storage Zones of Rivers by Genetic Programming
Authors: Rajeev R. Sahay
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Rivers have transient storage or dead zones where injected pollutants or solutes are entrapped for considerable period of time, known as residence time, before being released into the main flowing zones of rivers. In this study, a new empirical expression for residence time, implementing genetic programming on published dispersion data, has been derived. The proposed expression uses few hydraulic and geometric characteristics of rivers which are normally known to the authorities. When compared with some reported expressions, based on various statistical indices, it can be concluded that the proposed expression predicts the residence time of pollutants in natural rivers more accurately.Keywords: Parameter estimation, pollutant transport, residence time, rivers, transient storage.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12421335 Using the Combined Model of PROMETHEE and Fuzzy Analytic Network Process for Determining Question Weights in Scientific Exams through Data Mining Approach
Authors: Hassan Haleh, Amin Ghaffari, Parisa Farahpour
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Need for an appropriate system of evaluating students- educational developments is a key problem to achieve the predefined educational goals. Intensity of the related papers in the last years; that tries to proof or disproof the necessity and adequacy of the students assessment; is the corroborator of this matter. Some of these studies tried to increase the precision of determining question weights in scientific examinations. But in all of them there has been an attempt to adjust the initial question weights while the accuracy and precision of those initial question weights are still under question. Thus In order to increase the precision of the assessment process of students- educational development, the present study tries to propose a new method for determining the initial question weights by considering the factors of questions like: difficulty, importance and complexity; and implementing a combined method of PROMETHEE and fuzzy analytic network process using a data mining approach to improve the model-s inputs. The result of the implemented case study proves the development of performance and precision of the proposed model.Keywords: Assessing students, Analytic network process, Clustering, Data mining, Fuzzy sets, Multi-criteria decision making, and Preference function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15581334 A Multi-Agent Intelligent System for Monitoring Health Conditions of Elderly People
Authors: Ayman M. Mansour
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In this paper, we propose a multi-agent intelligent system that is used for monitoring the health conditions of elderly people. Monitoring the health condition of elderly people is a complex problem that involves different medical units and requires continuous monitoring. Such expert system is highly needed in rural areas because of inadequate number of available specialized physicians or nurses. Such monitoring must have autonomous interactions between these medical units in order to be effective. A multi-agent system is formed by a community of agents that exchange information and proactively help one another to achieve the goal of elderly monitoring. The agents in the developed system are equipped with intelligent decision maker that arms them with the rule-based reasoning capability that can assist the physicians in making decisions regarding the medical condition of elderly people.
Keywords: Fuzzy Logic, Inference system, Monitoring system, Multi-agent system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22591333 QoS Improvement Using Intelligent Algorithm under Dynamic Tropical Weather for Earth-Space Satellite Applications
Authors: Joseph S. Ojo, Vincent A. Akpan, Oladayo G. Ajileye, Olalekan L, Ojo
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In this paper, the intelligent algorithm (IA) that is capable of adapting to dynamical tropical weather conditions is proposed based on fuzzy logic techniques. The IA effectively interacts with the quality of service (QoS) criteria irrespective of the dynamic tropical weather to achieve improvement in the satellite links. To achieve this, an adaptive network-based fuzzy inference system (ANFIS) has been adopted. The algorithm is capable of interacting with the weather fluctuation to generate appropriate improvement to the satellite QoS for efficient services to the customers. 5-year (2012-2016) rainfall rate of one-minute integration time series data has been used to derive fading based on ITU-R P. 618-12 propagation models. The data are obtained from the measurement undertaken by the Communication Research Group (CRG), Physics Department, Federal University of Technology, Akure, Nigeria. The rain attenuation and signal-to-noise ratio (SNR) were derived for frequency between Ku and V-band and propagation angle with respect to different transmitting power. The simulated results show a substantial reduction in SNR especially for application in the area of digital video broadcast-second generation coding modulation satellite networks.
Keywords: Fuzzy logic, intelligent algorithm, Nigeria, QoS, satellite applications, tropical weather.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7851332 The Estimation of Semi Elliptical Surface Cracks Advancement via Fuzzy Logic
Authors: Gürol Önal, Ahmet Avcı
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This paper presented the results of an experimental investigation into the axial fatigue behavior of a 5086 aluminum alloy which have several notch-aspect ratios a0/c0 and notch thickness ratio a/t with semi-elliptical surface cracks. Tests were conducted in la b air for stress levels of 50 % of their yield strength. Experiments were carried out for various notch to thickness ratios. Crack growth rates of test specimens both in surface and depth directions were determined by using die penetration method. Fuzzy Logic method was used to predict the deep direction crack growth because the dept of the crack is considerably difficult to measure.Keywords: Axial fatigue, Crack growth rate, surface crack, Al-Mg alloy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16531331 Design of a Fuzzy Feed-forward Controller for Monitor HAGC System of Cold Rolling Mill
Authors: S. Khosravi, A. Afshar, F. Barazandeh
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In this study we propose a novel monitor hydraulic automatic gauge control (HAGC) system based on fuzzy feedforward controller. This is used in the development of cold rolling mill automation system to improve the quality of cold strip. According to features/ properties of entry steel strip like its average yield stress, width of strip, and desired exit thickness, this controller realizes the compensation for the exit thickness error. The traditional methods of adjusting the roller position, can-t tolerate the variance in the entry steel strip. The proposed method uses a mathematical model of the system together with the expert knowledge to perform this adjustment while minimizing the effect of the stated problem. In order to improve the speed of the controller in rejecting disturbances introduced by entry strip thickness variations, expert knowledge is added as a feed-forward term to the HAGC system. Simulation results for the application of the proposed controller to a real cold mill show that the exit strip quality is highly improved.Keywords: Fuzzy feed-forward controller, monitor HAGC system, dynamic mathematical model, entry strip thickness deviation compensation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21871330 Nonlinear Model Predictive Swing-Up and Stabilizing Sliding Mode Controllers
Authors: S. Kahvecioglu, A. Karamancioglu, A. Yazici
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In this paper, a nonlinear model predictive swing-up and stabilizing sliding controller is proposed for an inverted pendulum-cart system. In the swing up phase, the nonlinear model predictive control is formulated as a nonlinear programming problem with energy based objective function. By solving this problem at each sampling instant, a sequence of control inputs that optimize the nonlinear objective function subject to various constraints over a finite horizon are obtained. Then, this control drives the pendulum to a predefined neighborhood of the upper equilibrium point, at where sliding mode based model predictive control is used to stabilize the systems with the specified constraints. It is shown by the simulations that, due to the way of formulating the problem, short horizon lengths are sufficient for attaining the swing up goal.Keywords: Inverted pendulum, model predictive control, swingup, stabilization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21681329 Differences in Goal Scoring and Passing Sequences between Winning and Losing Team in UEFA-EURO Championship 2012
Authors: Muhamad S., Norasrudin S, Rahmat A.
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The objective of current study is to investigate the differences of winning and losing teams in terms of goal scoring and passing sequences. Total of 31 matches from UEFA-EURO 2012 were analyzed and 5 matches were excluded from analysis due to matches end up drawn. There are two groups of variable used in the study which is; i. the goal scoring variable and: ii. passing sequences variable. Data were analyzed using Wilcoxon matched pair rank test with significant value set at p < 0.05. Current study found the timing of goal scored was significantly higher for winning team at 1st half (Z=-3.416, p=.001) and 2nd half (Z=-3.252, p=.001). The scoring frequency was also found to be increase as time progressed and the last 15 minutes of the game was the time interval the most goals scored. The indicators that were significantly differences between winning and losing team were the goal scored (Z=-4.578, p=.000), the head (Z=-2.500, p=.012), the right foot (Z=-3.788,p=.000), corner (Z=-.2.126,p=.033), open play (Z=-3.744,p=.000), inside the penalty box (Z=-4.174, p=.000) , attackers (Z=-2.976, p=.003) and also the midfielders (Z=-3.400, p=.001). Regarding the passing sequences, there are significance difference between both teams in short passing sequences (Z=-.4.141, p=.000). While for the long passing, there were no significance difference (Z=-.1.795, p=.073). The data gathered in present study can be used by the coaches to construct detailed training program based on their objectives.Keywords: Football, goals scored, passing, timing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28131328 User-Friendly Task Creation Using a CAD Integrated Robotic System on a Real Workcell
Authors: Alireza Changizi, Arash Rezaei, Jamal Muhammad, Jyrki Latokartano, Minna Lanz
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Offline programming (OLP) is a new method in robot programming which is used widely in the industry nowadays which is a simulation base method that can produce the robot codes for motion according to virtual world in the simulation software. In this project Delmia v5 is used as simulation software. First the work cell component was modelled by Catia v5 and all of them was imported to a process file in Delmia and placed roughly to form the virtual work cell. Then robot was added to the work cell from the Delmia library. Work cell was calibrated corresponding to real world work cell to have accurate code. Tool calibration is the first step of calibration scheme and then work cell equipment can be calibrated using 6 point calibration method. Finally generated code needs to be reformed to match related controller code instruction. At the last stage IO were set to accomplish robots cooperation and make their motion synchronized. The pros and cons also will be discussed to clarify the presented results show the feasibility of the method and its effect on production line efficiency. Finally the positive and negative points of the implementation will be discussed.
Keywords: Component, robotic, automated, production, offline programming, CAD.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10951327 A Self Supervised Bi-directional Neural Network (BDSONN) Architecture for Object Extraction Guided by Beta Activation Function and Adaptive Fuzzy Context Sensitive Thresholding
Authors: Siddhartha Bhattacharyya, Paramartha Dutta, Ujjwal Maulik, Prashanta Kumar Nandi
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A multilayer self organizing neural neural network (MLSONN) architecture for binary object extraction, guided by a beta activation function and characterized by backpropagation of errors estimated from the linear indices of fuzziness of the network output states, is discussed. Since the MLSONN architecture is designed to operate in a single point fixed/uniform thresholding scenario, it does not take into cognizance the heterogeneity of image information in the extraction process. The performance of the MLSONN architecture with representative values of the threshold parameters of the beta activation function employed is also studied. A three layer bidirectional self organizing neural network (BDSONN) architecture comprising fully connected neurons, for the extraction of objects from a noisy background and capable of incorporating the underlying image context heterogeneity through variable and adaptive thresholding, is proposed in this article. The input layer of the network architecture represents the fuzzy membership information of the image scene to be extracted. The second layer (the intermediate layer) and the final layer (the output layer) of the network architecture deal with the self supervised object extraction task by bi-directional propagation of the network states. Each layer except the output layer is connected to the next layer following a neighborhood based topology. The output layer neurons are in turn, connected to the intermediate layer following similar topology, thus forming a counter-propagating architecture with the intermediate layer. The novelty of the proposed architecture is that the assignment/updating of the inter-layer connection weights are done using the relative fuzzy membership values at the constituent neurons in the different network layers. Another interesting feature of the network lies in the fact that the processing capabilities of the intermediate and the output layer neurons are guided by a beta activation function, which uses image context sensitive adaptive thresholding arising out of the fuzzy cardinality estimates of the different network neighborhood fuzzy subsets, rather than resorting to fixed and single point thresholding. An application of the proposed architecture for object extraction is demonstrated using a synthetic and a real life image. The extraction efficiency of the proposed network architecture is evaluated by a proposed system transfer index characteristic of the network.Keywords: Beta activation function, fuzzy cardinality, multilayer self organizing neural network, object extraction,
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15391326 Artificial Intelligence Techniques for Controlling Spacecraft Power System
Authors: Hanaa T. El-Madany, Faten H. Fahmy, Ninet M. A. El-Rahman, Hassen T. Dorrah
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Advancements in the field of artificial intelligence (AI) made during this decade have forever changed the way we look at automating spacecraft subsystems including the electrical power system. AI have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. In this paper, a mathematical modeling and MATLAB–SIMULINK model for the different components of the spacecraft power system is presented. Also, a control system, which includes either the Neural Network Controller (NNC) or the Fuzzy Logic Controller (FLC) is developed for achieving the coordination between the components of spacecraft power system as well as control the energy flows. The performance of the spacecraft power system is evaluated by comparing two control systems using the NNC and the FLC.Keywords: Spacecraft, Neural network, Fuzzy logic control, Photovoltaic array.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19281325 An Implementation of Fuzzy Logic Technique for Prediction of the Power Transformer Faults
Authors: Omar M. Elmabrouk., Roaa Y. Taha., Najat M. Ebrahim, Sabbreen A. Mohammed
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Power transformers are the most crucial part of power electrical system, distribution and transmission grid. This part is maintained using predictive or condition-based maintenance approach. The diagnosis of power transformer condition is performed based on Dissolved Gas Analysis (DGA). There are five main methods utilized for analyzing these gases. These methods are International Electrotechnical Commission (IEC) gas ratio, Key Gas, Roger gas ratio, Doernenburg, and Duval Triangle. Moreover, due to the importance of the transformers, there is a need for an accurate technique to diagnose and hence predict the transformer condition. The main objective of this technique is to avoid the transformer faults and hence to maintain the power electrical system, distribution and transmission grid. In this paper, the DGA was utilized based on the data collected from the transformer records available in the General Electricity Company of Libya (GECOL) which is located in Benghazi-Libya. The Fuzzy Logic (FL) technique was implemented as a diagnostic approach based on IEC gas ratio method. The FL technique gave better results and approved to be used as an accurate prediction technique for power transformer faults. Also, this technique is approved to be a quite interesting for the readers and the concern researchers in the area of FL mathematics and power transformer.
Keywords: Fuzzy logic, dissolved gas-in-oil analysis, DGA, prediction, power transformer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13351324 A Framework for Early Differential Diagnosis of Tropical Confusable Diseases Using the Fuzzy Cognitive Map Engine
Authors: Faith-Michael E. Uzoka, Boluwaji A. Akinnuwesi, Taiwo Amoo, Flora Aladi, Stephen Fashoto, Moses Olaniyan, Joseph Osuji
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The overarching aim of this study is to develop a soft-computing system for the differential diagnosis of tropical diseases. These conditions are of concern to health bodies, physicians, and the community at large because of their mortality rates, and difficulties in early diagnosis due to the fact that they present with symptoms that overlap, and thus become ‘confusable’. We report on the first phase of our study, which focuses on the development of a fuzzy cognitive map model for early differential diagnosis of tropical diseases. We used malaria as a case disease to show the effectiveness of the FCM technology as an aid to the medical practitioner in the diagnosis of tropical diseases. Our model takes cognizance of manifested symptoms and other non-clinical factors that could contribute to symptoms manifestations. Our model showed 85% accuracy in diagnosis, as against the physicians’ initial hypothesis, which stood at 55% accuracy. It is expected that the next stage of our study will provide a multi-disease, multi-symptom model that also improves efficiency by utilizing a decision support filter that works on an algorithm, which mimics the physician’s diagnosis process.
Keywords: Medical diagnosis, tropical diseases, fuzzy cognitive map, decision support filters, malaria differential diagnosis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20701323 Control Strategy for Two-Mode Hybrid Electric Vehicle by Using Fuzzy Controller
Authors: Jia-Shiun Chen, Hsiu-Ying Hwang
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Hybrid electric vehicles can reduce pollution and improve fuel economy. Power-split hybrid electric vehicles (HEVs) provide two power paths between the internal combustion engine (ICE) and energy storage system (ESS) through the gears of an electrically variable transmission (EVT). EVT allows ICE to operate independently from vehicle speed all the time. Therefore, the ICE can operate in the efficient region of its characteristic brake specific fuel consumption (BSFC) map. The two-mode powertrain can operate in input-split or compound-split EVT modes and in four different fixed gear configurations. Power-split architecture is advantageous because it combines conventional series and parallel power paths. This research focuses on input-split and compound-split modes in the two-mode power-split powertrain. Fuzzy Logic Control (FLC) for an internal combustion engine (ICE) and PI control for electric machines (EMs) are derived for the urban driving cycle simulation. These control algorithms reduce vehicle fuel consumption and improve ICE efficiency while maintaining the state of charge (SOC) of the energy storage system in an efficient range.
Keywords: Hybrid electric vehicle, fuel economy, two-mode hybrid, fuzzy control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25781322 Representing Shared Join Points with State Charts: A High Level Design Approach
Authors: Muhammad Naveed, Muhammad Khalid Abdullah, Khalid Rashid, Hafiz Farooq Ahmad
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Aspect Oriented Programming promises many advantages at programming level by incorporating the cross cutting concerns into separate units, called aspects. Join Points are distinguishing features of Aspect Oriented Programming as they define the points where core requirements and crosscutting concerns are (inter)connected. Currently, there is a problem of multiple aspects- composition at the same join point, which introduces the issues like ordering and controlling of these superimposed aspects. Dynamic strategies are required to handle these issues as early as possible. State chart is an effective modeling tool to capture dynamic behavior at high level design. This paper provides methodology to formulate the strategies for multiple aspect composition at high level, which helps to better implement these strategies at coding level. It also highlights the need of designing shared join point at high level, by providing the solutions of these issues using state chart diagrams in UML 2.0. High level design representation of shared join points also helps to implement the designed strategy in systematic way.Keywords: Aspect Oriented Software Development, Shared Join Points.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16891321 A Fuzzy Classifier with Evolutionary Design of Ellipsoidal Decision Regions
Authors: Leehter Yao, Kuei-Song Weng, Cherng-Dir Huang
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A fuzzy classifier using multiple ellipsoids approximating decision regions for classification is to be designed in this paper. An algorithm called Gustafson-Kessel algorithm (GKA) with an adaptive distance norm based on covariance matrices of prototype data points is adopted to learn the ellipsoids. GKA is able toadapt the distance norm to the underlying distribution of the prototypedata points except that the sizes of ellipsoids need to be determined a priori. To overcome GKA's inability to determine appropriate size ofellipsoid, the genetic algorithm (GA) is applied to learn the size ofellipsoid. With GA combined with GKA, it will be shown in this paper that the proposed method outperforms the benchmark algorithms as well as algorithms in the field.
Keywords: Ellipsoids, genetic algorithm, classification, fuzzyc-means (FCM)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16761320 Supplier Selection by Considering Cost and Reliability
Authors: K. -H. Yang
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Supplier selection problem is one of the important issues of supply chain problems. Two categories of methodologies include qualitative and quantitative approaches which can be applied to supplier selection problems. However, due to the complexities of the problem and lacking of reliable and quantitative data, qualitative approaches are more than quantitative approaches. This study considers operational cost and supplier’s reliability factor and solves the problem by using a quantitative approach. A mixed integer programming model is the primary analytic tool. Analyses of different scenarios with variable cost and reliability structures show that the effectiveness of this approach to the supplier selection problem.Keywords: Mixed integer programming, quantitative approach, supplier’s reliability, supplier selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25241319 Aspect based Reusable Synchronization Schemes
Authors: Nathar Shah
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Concurrency and synchronization are becoming big issues as every new PC comes with multi-core processors. A major reason for Object-Oriented Programming originally was to enable easier reuse: encode your algorithm into a class and thoroughly debug it, then you can reuse the class again and again. However, when we get to concurrency and synchronization, this is often not possible. Thread-safety issues means that synchronization constructs need to be entangled into every class involved. We contributed a detailed literature review of issues and challenges in concurrent programming and present a methodology that uses the Aspect- Oriented paradigm to address this problem. Aspects will allow us to extract the synchronization concerns as schemes to be “weaved in" later into the main code. This allows the aspects to be separately tested and verified. Hence, the functional components can be weaved with reusable synchronization schemes that are robust and scalable.Keywords: Aspect-orientation, development methodologysoftware concurrency, synchronization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12241318 A Broadcasting Strategy for Interactive Video-on-Demand Services
Authors: Yu-Wei Chen, Li-Ren Han
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In this paper, we employ the approach of linear programming to propose a new interactive broadcast method. In our method, a film S is divided into n equal parts and broadcast via k channels. The user simultaneously downloads these segments from k channels into the user-s set-top-box (STB) and plays them in order. Our method assumes that the initial p segments will not have fast-forwarding capabilities. Every time the user wants to initiate d times fast-forwarding, according to our broadcasting strategy, the necessary segments already saved in the user-s STB or are just download on time for playing. The proposed broadcasting strategy not only allows the user to pause and rewind, but also to fast-forward.Keywords: Broadcasting, Near Video-on-Demand (VOD), Linear Programming, Video-Cassette-Recorder (VCR) Functions, Waiting Time.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17241317 Qualitative Modelling for Ferromagnetic Hysteresis Cycle
Authors: M. Mordjaoui, B. Boudjema, M. Chabane, R. Daira
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In determining the electromagnetic properties of magnetic materials, hysteresis modeling is of high importance. Many models are available to investigate those characteristics but they tend to be complex and difficult to implement. In this paper a new qualitative hysteresis model for ferromagnetic core is presented, based on the function approximation capabilities of adaptive neuro fuzzy inference system (ANFIS). The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach can restored the hysteresis curve with a little RMS error. The model accuracy is good and can be easily adapted to the requirements of the application by extending or reducing the network training set and thus the required amount of measurement data.Keywords: ANFIS modeling technique, magnetic hysteresis, Jiles-Atherton model, ferromagnetic core.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15661316 Stability Enhancement of a Large-Scale Power System Using Power System Stabilizer Based on Adaptive Neuro Fuzzy Inference System
Authors: Agung Budi Muljono, I Made Ginarsa, I Made Ari Nrartha
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A large-scale power system (LSPS) consists of two or more sub-systems connected by inter-connecting transmission. Loading pattern on an LSPS always changes from time to time and varies depend on consumer need. The serious instability problem is appeared in an LSPS due to load fluctuation in all of the bus. Adaptive neuro-fuzzy inference system (ANFIS)-based power system stabilizer (PSS) is presented to cover the stability problem and to enhance the stability of an LSPS. The ANFIS control is presented because the ANFIS control is more effective than Mamdani fuzzy control in the computation aspect. Simulation results show that the presented PSS is able to maintain the stability by decreasing peak overshoot to the value of −2.56 × 10−5 pu for rotor speed deviation Δω2−3. The presented PSS also makes the settling time to achieve at 3.78 s on local mode oscillation. Furthermore, the presented PSS is able to improve the peak overshoot and settling time of Δω3−9 to the value of −0.868 × 10−5 pu and at the time of 3.50 s for inter-area oscillation.Keywords: ANFIS, large-scale, power system, PSS, stability enhancement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11731315 A Simulator for Robot Navigation Algorithms
Authors: Michael A. Folcik, Bijan Karimi
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A robot simulator was developed to measure and investigate the performance of a robot navigation system based on the relative position of the robot with respect to random obstacles in any two dimensional environment. The presented simulator focuses on investigating the ability of a fuzzy-neural system for object avoidance. A navigation algorithm is proposed and used to allow random navigation of a robot among obstacles when the robot faces an obstacle in the environment. The main features of this simulator can be used for evaluating the performance of any system that can provide the position of the robot with respect to obstacles in the environment. This allows a robot developer to investigate and analyze the performance of a robot without implementing the physical robot.Keywords: Applications of Fuzzy Logic and Neural Networksin Robotics, Artificial Intelligence, Embedded Systems, MobileRobots, Robot Navigation, Robotics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17301314 Pectoral Muscles Suppression in Digital Mammograms Using Hybridization of Soft Computing Methods
Authors: I. Laurence Aroquiaraj, K. Thangavel
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Breast region segmentation is an essential prerequisite in computerized analysis of mammograms. It aims at separating the breast tissue from the background of the mammogram and it includes two independent segmentations. The first segments the background region which usually contains annotations, labels and frames from the whole breast region, while the second removes the pectoral muscle portion (present in Medio Lateral Oblique (MLO) views) from the rest of the breast tissue. In this paper we propose hybridization of Connected Component Labeling (CCL), Fuzzy, and Straight line methods. Our proposed methods worked good for separating pectoral region. After removal pectoral muscle from the mammogram, further processing is confined to the breast region alone. To demonstrate the validity of our segmentation algorithm, it is extensively tested using over 322 mammographic images from the Mammographic Image Analysis Society (MIAS) database. The segmentation results were evaluated using a Mean Absolute Error (MAE), Hausdroff Distance (HD), Probabilistic Rand Index (PRI), Local Consistency Error (LCE) and Tanimoto Coefficient (TC). The hybridization of fuzzy with straight line method is given more than 96% of the curve segmentations to be adequate or better. In addition a comparison with similar approaches from the state of the art has been given, obtaining slightly improved results. Experimental results demonstrate the effectiveness of the proposed approach.
Keywords: X-ray Mammography, CCL, Fuzzy, Straight line.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17241313 An Efficient Gaussian Noise Removal Image Enhancement Technique for Gray Scale Images
Authors: V. Murugan, R. Balasubramanian
Abstract:
Image enhancement is a challenging issue in many applications. In the last two decades, there are various filters developed. This paper proposes a novel method which removes Gaussian noise from the gray scale images. The proposed technique is compared with Enhanced Fuzzy Peer Group Filter (EFPGF) for various noise levels. Experimental results proved that the proposed filter achieves better Peak-Signal-to-Noise-Ratio PSNR than the existing techniques. The proposed technique achieves 1.736dB gain in PSNR than the EFPGF technique.
Keywords: Gaussian noise, adaptive bilateral filter, fuzzy peer group filter, switching bilateral filter, PSNR
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24631312 Simulating Drilling Using a CAD System
Authors: Panagiotis Kyratsis, Konstantinos Kakoulis
Abstract:
Nowadays, the rapid development of CAD systems’ programming environments results in the creation of multiple downstream applications, which are developed and becoming increasingly available. CAD based manufacturing simulations is gradually following the same trend. Drilling is the most popular holemaking process used in a variety of industries. A specially built piece of software that deals with the drilling kinematics is presented. The cutting forces are calculated based on the tool geometry, the cutting conditions and the tool/work-piece materials. The results are verified by experimental work. Finally, the response surface methodology (RSM) is applied and mathematical models of the total thrust force and the thrust force developed because of the main cutting edges are proposed.Keywords: Application programming interface, CAD, drilling, response surface methodology, RSM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1781