Search results for: Simulated Annealing Algorithm.
3283 Effects of Hidden Unit Sizes and Autoregressive Features in Mental Task Classification
Authors: Ramaswamy Palaniappan, Nai-Jen Huan
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Classification of electroencephalogram (EEG) signals extracted during mental tasks is a technique that is actively pursued for Brain Computer Interfaces (BCI) designs. In this paper, we compared the classification performances of univariateautoregressive (AR) and multivariate autoregressive (MAR) models for representing EEG signals that were extracted during different mental tasks. Multilayer Perceptron (MLP) neural network (NN) trained by the backpropagation (BP) algorithm was used to classify these features into the different categories representing the mental tasks. Classification performances were also compared across different mental task combinations and 2 sets of hidden units (HU): 2 to 10 HU in steps of 2 and 20 to 100 HU in steps of 20. Five different mental tasks from 4 subjects were used in the experimental study and combinations of 2 different mental tasks were studied for each subject. Three different feature extraction methods with 6th order were used to extract features from these EEG signals: AR coefficients computed with Burg-s algorithm (ARBG), AR coefficients computed with stepwise least square algorithm (ARLS) and MAR coefficients computed with stepwise least square algorithm. The best results were obtained with 20 to 100 HU using ARBG. It is concluded that i) it is important to choose the suitable mental tasks for different individuals for a successful BCI design, ii) higher HU are more suitable and iii) ARBG is the most suitable feature extraction method.Keywords: Autoregressive, Brain-Computer Interface, Electroencephalogram, Neural Network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18063282 Solving Fully Fuzzy Linear Systems by use of a Certain Decomposition of the Coefficient Matrix
Authors: S. H. Nasseri, M. Sohrabi, E. Ardil
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In this paper, we give a certain decomposition of the coefficient matrix of the fully fuzzy linear system (FFLS) to obtain a simple algorithm for solving these systems. The new algorithm can solve FFLS in a smaller computing process. We will illustrate our method by solving some examples.Keywords: Fully fuzzy linear system, Fuzzy number, LUdecomposition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17173281 Emission Constrained Economic Dispatch for Hydrothermal Coordination
Authors: Md. Sayeed Salam
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This paper presents an efficient emission constrained economic dispatch algorithm that deals with nonlinear cost function and constraints. It is then incorporated into the dynamic programming based hydrothermal coordination program. The program has been tested on a practical utility system having 32 thermal and 12 hydro generating units. Test results show that a slight increase in production cost causes a substantial reduction in emission.Keywords: Emission constraint, Hydrothermal coordination, and Economic dispatch algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18213280 Soft-Sensor for Estimation of Gasoline Octane Number in Platforming Processes with Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
Authors: Hamed.Vezvaei, Sepideh.Ordibeheshti, Mehdi.Ardjmand
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Gasoline Octane Number is the standard measure of the anti-knock properties of a motor in platforming processes, that is one of the important unit operations for oil refineries and can be determined with online measurement or use CFR (Cooperative Fuel Research) engines. Online measurements of the Octane number can be done using direct octane number analyzers, that it is too expensive, so we have to find feasible analyzer, like ANFIS estimators. ANFIS is the systems that neural network incorporated in fuzzy systems, using data automatically by learning algorithms of NNs. ANFIS constructs an input-output mapping based both on human knowledge and on generated input-output data pairs. In this research, 31 industrial data sets are used (21 data for training and the rest of the data used for generalization). Results show that, according to this simulation, hybrid method training algorithm in ANFIS has good agreements between industrial data and simulated results.Keywords: Adaptive Neuro-Fuzzy Inference Systems, GasolineOctane Number, Soft-sensor, Catalytic Naphtha Reforming
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21973279 Production and Remanufacturing of Returned Products in Supply Chain using Modified Genetic Algorithm
Authors: Siva Prasad Darla, C. D. Naiju, K. Annamalai, Y. Upendra Sravan
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In recent years, environment regulation forcing manufactures to consider recovery activity of end-of- life products and/or return products for refurbishing, recycling, remanufacturing/repair and disposal in supply chain management. In this paper, a mathematical model is formulated for single product production-inventory system considering remanufacturing/reuse of return products and rate of return products follows a demand like function, dependent on purchasing price and acceptance quality level. It is useful in decision making to determine whether to go for remanufacturing or disposal of returned products along with newly produced products to satisfy a stationary demand. In addition, a modified genetic algorithm approach is proposed, inspired by particle swarm optimization method. Numerical analysis of the case study is carried out to validate the model.Keywords: Genetic Algorithm, Particle Swarm Optimization, Production, Remanufacturing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17163278 Bit Model Based Key Management Scheme for Secure Group Communication
Authors: R. Varalakshmi
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For the last decade, researchers have started to focus their interest on Multicast Group Key Management Framework. The central research challenge is secure and efficient group key distribution. The present paper is based on the Bit model based Secure Multicast Group key distribution scheme using the most popular absolute encoder output type code named Gray Code. The focus is of two folds. The first fold deals with the reduction of computation complexity which is achieved in our scheme by performing fewer multiplication operations during the key updating process. To optimize the number of multiplication operations, an O(1) time algorithm to multiply two N-bit binary numbers which could be used in an N x N bit-model of reconfigurable mesh is used in this proposed work. The second fold aims at reducing the amount of information stored in the Group Center and group members while performing the update operation in the key content. Comparative analysis to illustrate the performance of various key distribution schemes is shown in this paper and it has been observed that this proposed algorithm reduces the computation and storage complexity significantly. Our proposed algorithm is suitable for high performance computing environment.
Keywords: Multicast Group key distribution, Bit model, Integer Multiplications, reconfigurable mesh, optimal algorithm, Gray Code, Computation Complexity, Storage Complexity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19753277 Design of Compact Dual-Band Planar Antenna for WLAN Systems
Authors: Anil Kumar Pandey
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A compact planar monopole antenna with dual-band operation suitable for wireless local area network (WLAN) application is presented in this paper. The antenna occupies an overall area of 18 ×12 mm2. The antenna is fed by a coplanar waveguide (CPW) transmission line and it combines two folded strips, which radiates at 2.4 and 5.2 GHz. In the proposed antenna, by optimally selecting the antenna dimensions, dual-band resonant modes with a much wider impedance matching at the higher band can be produced. Prototypes of the obtained optimized design have been simulated using EM solver. The simulated results explore good dual-band operation with -10 dB impedance bandwidths of 50 MHz and 2400 MHz at bands of 2.4 and 5.2 GHz, respectively, which cover the 2.4/5.2/5.8 GHz WLAN operating bands. Good antenna performances such as radiation patterns and antenna gains over the operating bands have also been observed. The antenna with a compact size of 18×12×1.6 mm3 is designed on an FR4 substrate with a dielectric constant of 4.4.
Keywords: CPW fed antenna, dual-band, electromagnetic simulation, wireless local area network, WLAN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8233276 Ultra Wideband Breast Cancer Detection by Using SAR for Indication the Tumor Location
Authors: Wittawat Wasusathien, Samran Santalunai, Thanaset Thosdeekoraphat, Chanchai Thongsopa
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This paper presents breast cancer detection by observing the specific absorption rate (SAR) intensity for identification tumor location, the tumor is identified in coordinates (x,y,z) system. We examined the frequency between 4-8 GHz to look for the most appropriate frequency. Results are simulated in frequency 4-8 GHz, the model overview include normal breast with 50 mm radian, 5 mm diameter of tumor, and ultra wideband (UWB) bowtie antenna. The models are created and simulated in CST Microwave Studio. For this simulation, we changed antenna to 5 location around the breast, the tumor can be detected when an antenna is close to the tumor location, which the coordinate of maximum SAR is approximated the tumor location. For reliable, we experiment by random tumor location to 3 position in the same size of tumor and simulation the result again by varying the antenna position in 5 position again, and it also detectable the tumor position from the antenna that nearby tumor position by maximum value of SAR, which it can be detected the tumor with precision in all frequency between 4-8 GHz.
Keywords: Specific absorption rate (SAR), ultra wideband (UWB), coordinates and cancer detection
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27513275 Mean Shift-based Preprocessing Methodology for Improved 3D Buildings Reconstruction
Authors: Nikolaos Vassilas, Theocharis Tsenoglou, Djamchid Ghazanfarpour
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In this work, we explore the capability of the mean shift algorithm as a powerful preprocessing tool for improving the quality of spatial data, acquired from airborne scanners, from densely built urban areas. On one hand, high resolution image data corrupted by noise caused by lossy compression techniques are appropriately smoothed while at the same time preserving the optical edges and, on the other, low resolution LiDAR data in the form of normalized Digital Surface Map (nDSM) is upsampled through the joint mean shift algorithm. Experiments on both the edge-preserving smoothing and upsampling capabilities using synthetic RGB-z data show that the mean shift algorithm is superior to bilateral filtering as well as to other classical smoothing and upsampling algorithms. Application of the proposed methodology for 3D reconstruction of buildings of a pilot region of Athens, Greece results in a significant visual improvement of the 3D building block model.Keywords: 3D buildings reconstruction, data fusion, data upsampling, mean shift.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20133274 Designing a Novel General Sorting Network Constructor Using Artificial Evolution
Authors: Michal Bidlo, Radek Bidlo, Lukas Sekanina
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A method is presented for the construction of arbitrary even-input sorting networks exhibiting better properties than the networks created using a conventional technique of the same type. The method was discovered by means of a genetic algorithm combined with an application-specific development. Similarly to human inventions in the area of theoretical computer science, the evolved invention was analyzed: its generality was proven and area and time complexities were determined.Keywords: Development, genetic algorithm, program, sorting network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12883273 Effect of Different Diesel Fuels on Formation of the Cavitation Phenomena
Authors: Mohammadreza Nezamirad, Sepideh Amirahmadian, Nasim Sabetpour, Azadeh Yazdi, Amirmasoud Hamedi
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Cavitation inside a diesel injector nozzle is investigated numerically in this study. The Reynolds Stress Navier Stokes set of equations (RANS) are utilized to investigate flow behavior inside the nozzle numerically. Moreover, K-ε turbulent model is found to be a better approach comparing to K-ω turbulent model. The Winklhofer rectangular shape nozzle is also simulated in order to verify the current numerical scheme, and with the mass flow rate approach, the current solution is verified. Afterward, a six-hole real size nozzle was simulated and it was found that among the different fuels used in this study with the same condition, diesel fuel provides the largest length of cavitation. Also, it was found that at the same boundary condition, rapeseed methyl ester (RME) fuel leads to the highest value of discharge coefficient and mass flow rate.
Keywords: cavitation, diesel fuel, CFD, real size nozzle, discharge coefficient
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4753272 Selective Sulfidation of Copper, Zinc and Nickelin Plating Wastewater using Calcium Sulfide
Authors: K. Soya, N. Mihara, D. Kuchar, M. Kubota, H. Matsuda, T. Fukuta
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The present work is concerned with sulfidation of Cu, Zn and Ni containing plating wastewater with CaS. The sulfidation experiments were carried out at a room temperature by adding solid CaS to simulated metal solution containing either single-metal of Ni, Zn and Cu, or Ni-Zn-Cu mixture. At first, the experiments were conducted without pH adjustment and it was found that the complete sulfidation of Zn and Ni was achieved at an equimolar ratio of CaS to a particular metal. However, in the case of Cu, a complete copper sulfidation was achieved at CaS to Cu molar ratio of about 2. In the case of the selective sulfidation, a simulated plating solution containing Cu, Zn and Ni at the concentration of 100 mg/dm3 was treated with CaS under various pH conditions. As a result, selective precipitation of metal sulfides was achieved by a sulfidation treatment at different pH values. Further, the precipitation agents of NaOH, Na2S and CaS were compared in terms of the average specific filtration resistance and compressibility coefficients of metal sulfide slurry. Consequently, based on the lowest filtration parameters of the produced metal sulfides, it was concluded that CaS was the most effective precipitation agent for separation and recovery of Cu, Zn and Ni.Keywords: Calcium sulfide, Plating Wastewater, Filtrationcharacteristics, Heavy metals, Sulfidation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32243271 Variable Regularization Parameter Normalized Least Mean Square Adaptive Filter
Authors: Young-Seok Choi
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We present a normalized LMS (NLMS) algorithm with robust regularization. Unlike conventional NLMS with the fixed regularization parameter, the proposed approach dynamically updates the regularization parameter. By exploiting a gradient descent direction, we derive a computationally efficient and robust update scheme for the regularization parameter. In simulation, we demonstrate the proposed algorithm outperforms conventional NLMS algorithms in terms of convergence rate and misadjustment error.Keywords: Regularization, normalized LMS, system identification, robustness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18833270 A New Method for Multiobjective Optimization Based on Learning Automata
Authors: M. R. Aghaebrahimi, S. H. Zahiri, M. Amiri
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The necessity of solving multi dimensional complicated scientific problems beside the necessity of several objective functions optimization are the most motive reason of born of artificial intelligence and heuristic methods. In this paper, we introduce a new method for multiobjective optimization based on learning automata. In the proposed method, search space divides into separate hyper-cubes and each cube is considered as an action. After gathering of all objective functions with separate weights, the cumulative function is considered as the fitness function. By the application of all the cubes to the cumulative function, we calculate the amount of amplification of each action and the algorithm continues its way to find the best solutions. In this Method, a lateral memory is used to gather the significant points of each iteration of the algorithm. Finally, by considering the domination factor, pareto front is estimated. Results of several experiments show the effectiveness of this method in comparison with genetic algorithm based method.Keywords: Function optimization, Multiobjective optimization, Learning automata.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16843269 Particle Swarm Optimization Based Genetic Algorithm for Two-Stage Transportation Supply Chain
Authors: Siva Prasad Darla, C. D. Naiju, K. Annamalai, S. S. Rajiv Sushanth
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Supply chain consists of all stages involved, directly or indirectly, includes all functions involved in fulfilling a customer demand. In two stage transportation supply chain problem, transportation costs are of a significant proportion of final product costs. It is often crucial for successful decisions making approaches in two stage supply chain to explicit account for non-linear transportation costs. In this paper, deterministic demand and finite supply of products was considered. The optimized distribution level and the routing structure from the manufacturing plants to the distribution centres and to the end customers is determined using developed mathematical model and solved by proposed particle swarm optimization based genetic algorithm. Numerical analysis of the case study is carried out to validate the model.Keywords: Genetic Algorithm, Particle Swarm Optimization, Production, Remanufacturing
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18463268 Investigating the Effects of Thermal and Surface Energy on the Two-Dimensional Flow Characteristics of Oil in Water Mixture between Two Parallel Plates: A Lattice Boltzmann Method Study
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A hybrid quasi-steady thermal lattice Boltzmann model was used to study the combined effects of temperature and contact angle on the movement of slugs and droplets of oil in water (O/W) system flowing between two parallel plates. The model static contact angle due to the deposition of the O/W droplet on a flat surface with simulated hydrophilic characteristic at different fluid temperatures, matched very well the proposed theoretical calculation. Furthermore, the model was used to simulate the dynamic behavior of droplets and slugs deposited on the domain’s upper and lower surfaces, while subjected to parabolic flow conditions. The model accurately simulated the contact angle hysteresis for the dynamic droplets cases. It was also shown that at elevated temperatures the required power to transport the mixture diminished remarkably.Keywords: Lattice Boltzmann method, Gunstensen model, thermal, contact angle, high viscosity ratio.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8883267 A New H.264-Based Rate Control Algorithm for Stereoscopic Video Coding
Authors: Yi Liao, Wencheng Yang, Gangyi Jiang
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According to investigating impact of complexity of stereoscopic frame pairs on stereoscopic video coding and transmission, a new rate control algorithm is presented. The proposed rate control algorithm is performed on three levels: stereoscopic group of pictures (SGOP) level, stereoscopic frame (SFrame) level and frame level. A temporal-spatial frame complexity model is firstly established, in the bits allocation stage, the frame complexity, position significance and reference property between the left and right frames are taken into account. Meanwhile, the target buffer is set according to the frame complexity. Experimental results show that the proposed method can efficiently control the bitrates, and it outperforms the fixed quantization parameter method from the rate distortion perspective, and average PSNR gain between rate-distortion curves (BDPSNR) is 0.21dB.
Keywords: Stereoscopic video coding, rate control, stereoscopic group of pictures, complexity of stereoscopic frame pairs.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17203266 An Improved Algorithm for Channel Estimations of OFDM System based Pilot Signal
Authors: Ahmed N. H. Alnuaimy, Mahamod Ismail, Mohd. A. M. Ali, Kasmiran Jumari, Ayman A. El-Saleh
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This paper presents a new algorithm for the channel estimation of the OFDM system based on a pilot signal for the new generation of high data rate communication systems. In orthogonal frequency division multiplexing (OFDM) systems over fast-varying fading channels, channel estimation and tracking is generally carried out by transmitting known pilot symbols in given positions of the frequency-time grid. In this paper, we propose to derive an improved algorithm based on the calculation of the mean and the variance of the adjacent pilot signals for a specific distribution of the pilot signals in the OFDM frequency-time grid then calculating of the entire unknown channel coefficients from the equation of the mean and the variance. Simulation results shows that the performance of the OFDM system increase as the length of the channel increase where the accuracy of the estimated channel will be increased using this low complexity algorithm, also the number of the pilot signal needed to be inserted in the OFDM signal will be reduced which lead to increase in the throughput of the signal over the OFDM system in compared with other type of the distribution such as Comb type and Block type channel estimation.
Keywords: Channel estimation, orthogonal frequency divisionmultiplexing (OFDM), comb type channel estimation, block typechannel estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14213265 Space Vector PWM Simulation for Three Phase DC/AC Inverter
Authors: M. Kubeitari, A. Alhusayn, M. Alnahar
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Space Vector Pulse Width Modulation SVPWM is one of the most used techniques to generate sinusoidal voltage and current due to its facility and efficiency with low harmonics distortion. This algorithm is specially used in power electronic applications. This paper describes simulation algorithm of SVPWM & SPWM using MatLab/simulink environment. It also implements a closed loop three phases DC-AC converter controlling its outputs voltages amplitude and frequency using MatLab. Also comparison between SVPWM & SPWM results is given.Keywords: DC-AC Converter, MatLab, SPWM, SVPWM, Vref - rotating frame.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 95073264 iCCS: Development of a Mobile Web-Based Student Integrated Information System Using Hill Climbing Algorithm
Authors: Maria Cecilia G. Cantos, Lorena W. Rabago, Bartolome T. Tanguilig III
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This paper describes a conducive and structured information exchange environment for the students of the College of Computer Studies in Manuel S. Enverga University Foundation in. The system was developed to help the students to check their academic result, manage profile, make self-enlistment and assist the students to manage their academic status that can be viewed also in mobile phones. Developing class schedules in a traditional way is a long process that involves making many numbers of choices. With Hill Climbing Algorithm, however, the process of class scheduling, particularly with regards to courses to be taken by the student aligned with the curriculum, can perform these processes and end up with an optimum solution. The proponent used Rapid Application Development (RAD) for the system development method. The proponent also used the PHP as the programming language and MySQL as the database.
Keywords: Hill climbing algorithm, integrated system, mobile web-based, student information system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37253263 Optimizing Boiler Combustion System in a Petrochemical Plant Using Neuro-Fuzzy Inference System and Genetic Algorithm
Authors: Yul Y. Nazaruddin, Anas Y. Widiaribowo, Satriyo Nugroho
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Boiler is one of the critical unit in a petrochemical plant. Steam produced by the boiler is used for various processes in the plant such as urea and ammonia plant. An alternative method to optimize the boiler combustion system is presented in this paper. Adaptive Neuro-Fuzzy Inference System (ANFIS) approach is applied to model the boiler using real-time operational data collected from a boiler unit of the petrochemical plant. Nonlinear equation obtained is then used to optimize the air to fuel ratio using Genetic Algorithm, resulting an optimal ratio of 15.85. This optimal ratio is then maintained constant by ratio controller designed using inverse dynamics based on ANFIS. As a result, constant value of oxygen content in the flue gas is obtained which indicates more efficient combustion process.
Keywords: ANFIS, boiler, combustion process, genetic algorithm, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9933262 Hot-Spot Blob Merging for Real-Time Image Segmentation
Authors: K. Kraus, M. Uiberacker, O. Martikainen, R. Reda
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One of the major, difficult tasks in automated video surveillance is the segmentation of relevant objects in the scene. Current implementations often yield inconsistent results on average from frame to frame when trying to differentiate partly occluding objects. This paper presents an efficient block-based segmentation algorithm which is capable of separating partly occluding objects and detecting shadows. It has been proven to perform in real time with a maximum duration of 47.48 ms per frame (for 8x8 blocks on a 720x576 image) with a true positive rate of 89.2%. The flexible structure of the algorithm enables adaptations and improvements with little effort. Most of the parameters correspond to relative differences between quantities extracted from the image and should therefore not depend on scene and lighting conditions. Thus presenting a performance oriented segmentation algorithm which is applicable in all critical real time scenarios.Keywords: Image segmentation, Model-based, Region growing, Blob Analysis, Occlusion, Shadow detection, Intelligent videosurveillance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15083261 A GA-Based Role Assignment Approach for Web-based Cooperative Learning Environments
Authors: Yi-Chun Chang, Jian-Wei Li
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Web-based cooperative learning focuses on (1) the interaction and the collaboration of community members, and (2) the sharing and the distribution of knowledge and expertise by network technology to enhance learning performance. Numerous research literatures related to web-based cooperative learning have demonstrated that cooperative scripts have a positive impact to specify, sequence, and assign cooperative learning activities. Besides, literatures have indicated that role-play in web-based cooperative learning environments enhances two or more students to work together toward the completion of a common goal. Since students generally do not know each other and they lack the face-to-face contact that is necessary for the negotiation of assigning group roles in web-based cooperative learning environments, this paper intends to further extend the application of genetic algorithm (GA) and propose a GA-based algorithm to tackle the problem of role assignment in web-based cooperative learning environments, which not only saves communication costs but also reduces conflict between group members in negotiating role assignments.
Keywords: genetic algorithm (GA), role assignment, role-play; web-based cooperative learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14633260 On the Numerical Approach for Simulating Thermal Hydraulics under Seismic Condition
Authors: Tadashi Watanabe
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The two-phase flow field and the motion of the free surface in an oscillating channel are simulated numerically to assess the methodology for simulating nuclear reacotr thermal hydraulics under seismic conditions. Two numerical methods are compared: one is to model the oscillating channel directly using the moving grid of the Arbitrary Lagrangian-Eulerian method, and the other is to simulate the effect of channel motion using the oscillating acceleration acting on the fluid in the stationary channel. The two-phase flow field in the oscillating channel is simulated using the level set method in both cases. The calculated results using the oscillating acceleration are found to coinside with those using the moving grid, and the theoretical back ground and the limitation of oscillating acceleration are discussed. It is shown that the change in the interfacial area between liquid and gas phases under seismic conditions is important for nuclear reactor thermal hydraulics.Keywords: Two-phase flow, simulation, seismic condition, moving grid, oscillating acceleration, interfacial area
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13793259 Reduced Inventories, High Reliability and Short Throughput Times by Using CONWIP Production Planning System
Authors: Tomas Duranik, Juraj Ruzbarsky, Markus Stopper
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CONWIP (constant work-in-process) as a pull production system have been widely studied by researchers to date. The CONWIP pull production system is an alternative to pure push and pure pull production systems. It lowers and controls inventory levels which make the throughput better, reduces production lead time, delivery reliability and utilization of work. In this article a CONWIP pull production system was simulated. It was simulated push and pull planning system. To compare these systems via a production planning system (PPS) game were adjusted parameters of each production planning system. The main target was to reduce the total WIP and achieve throughput and delivery reliability to minimum values. Data was recorded and evaluated. A future state was made for real production of plastic components and the setup of the two indicators with CONWIP pull production system which can greatly help the company to be more competitive on the market.Keywords: CONWIP, constant work in process, delivery reliability, hybrid production planning, PPS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22783258 Analysis of Cooperative Learning Behavior Based on the Data of Students' Movement
Authors: Wang Lin, Li Zhiqiang
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The purpose of this paper is to analyze the cooperative learning behavior pattern based on the data of students' movement. The study firstly reviewed the cooperative learning theory and its research status, and briefly introduced the k-means clustering algorithm. Then, it used clustering algorithm and mathematical statistics theory to analyze the activity rhythm of individual student and groups in different functional areas, according to the movement data provided by 10 first-year graduate students. It also focused on the analysis of students' behavior in the learning area and explored the law of cooperative learning behavior. The research result showed that the cooperative learning behavior analysis method based on movement data proposed in this paper is feasible. From the results of data analysis, the characteristics of behavior of students and their cooperative learning behavior patterns could be found.Keywords: Behavior pattern, cooperative learning, data analyze, K-means clustering algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8193257 GA Based Optimal Feature Extraction Method for Functional Data Classification
Authors: Jun Wan, Zehua Chen, Yingwu Chen, Zhidong Bai
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Classification is an interesting problem in functional data analysis (FDA), because many science and application problems end up with classification problems, such as recognition, prediction, control, decision making, management, etc. As the high dimension and high correlation in functional data (FD), it is a key problem to extract features from FD whereas keeping its global characters, which relates to the classification efficiency and precision to heavens. In this paper, a novel automatic method which combined Genetic Algorithm (GA) and classification algorithm to extract classification features is proposed. In this method, the optimal features and classification model are approached via evolutional study step by step. It is proved by theory analysis and experiment test that this method has advantages in improving classification efficiency, precision and robustness whereas using less features and the dimension of extracted classification features can be controlled.Keywords: Classification, functional data, feature extraction, genetic algorithm, wavelet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15623256 Mining Network Data for Intrusion Detection through Naïve Bayesian with Clustering
Authors: Dewan Md. Farid, Nouria Harbi, Suman Ahmmed, Md. Zahidur Rahman, Chowdhury Mofizur Rahman
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Network security attacks are the violation of information security policy that received much attention to the computational intelligence society in the last decades. Data mining has become a very useful technique for detecting network intrusions by extracting useful knowledge from large number of network data or logs. Naïve Bayesian classifier is one of the most popular data mining algorithm for classification, which provides an optimal way to predict the class of an unknown example. It has been tested that one set of probability derived from data is not good enough to have good classification rate. In this paper, we proposed a new learning algorithm for mining network logs to detect network intrusions through naïve Bayesian classifier, which first clusters the network logs into several groups based on similarity of logs, and then calculates the prior and conditional probabilities for each group of logs. For classifying a new log, the algorithm checks in which cluster the log belongs and then use that cluster-s probability set to classify the new log. We tested the performance of our proposed algorithm by employing KDD99 benchmark network intrusion detection dataset, and the experimental results proved that it improves detection rates as well as reduces false positives for different types of network intrusions.Keywords: Clustering, detection rate, false positive, naïveBayesian classifier, network intrusion detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 55403255 Constraint Based Frequent Pattern Mining Technique for Solving GCS Problem
Authors: First G.M. Karthik, Second Ramachandra.V.Pujeri, Dr.
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Generalized Center String (GCS) problem are generalized from Common Approximate Substring problem and Common substring problems. GCS are known to be NP-hard allowing the problems lies in the explosion of potential candidates. Finding longest center string without concerning the sequence that may not contain any motifs is not known in advance in any particular biological gene process. GCS solved by frequent pattern-mining techniques and known to be fixed parameter tractable based on the fixed input sequence length and symbol set size. Efficient method known as Bpriori algorithms can solve GCS with reasonable time/space complexities. Bpriori 2 and Bpriori 3-2 algorithm are been proposed of any length and any positions of all their instances in input sequences. In this paper, we reduced the time/space complexity of Bpriori algorithm by Constrained Based Frequent Pattern mining (CBFP) technique which integrates the idea of Constraint Based Mining and FP-tree mining. CBFP mining technique solves the GCS problem works for all center string of any length, but also for the positions of all their mutated copies of input sequence. CBFP mining technique construct TRIE like with FP tree to represent the mutated copies of center string of any length, along with constraints to restraint growth of the consensus tree. The complexity analysis for Constrained Based FP mining technique and Bpriori algorithm is done based on the worst case and average case approach. Algorithm's correctness compared with the Bpriori algorithm using artificial data is shown.Keywords: Constraint Based Mining, FP tree, Data mining, GCS problem, CBFP mining technique.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17053254 Segmentation of Gray Scale Images of Dropwise Condensation on Textured Surfaces
Authors: Helene Martin, Solmaz Boroomandi Barati, Jean-Charles Pinoli, Stephane Valette, Yann Gavet
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In the present work we developed an image processing algorithm to measure water droplets characteristics during dropwise condensation on pillared surfaces. The main problem in this process is the similarity between shape and size of water droplets and the pillars. The developed method divides droplets into four main groups based on their size and applies the corresponding algorithm to segment each group. These algorithms generate binary images of droplets based on both their geometrical and intensity properties. The information related to droplets evolution during time including mean radius and drops number per unit area are then extracted from the binary images. The developed image processing algorithm is verified using manual detection and applied to two different sets of images corresponding to two kinds of pillared surfaces.Keywords: Dropwise condensation, textured surface, image processing, watershed.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 696