Search results for: serial algorithm.
3458 The Simulation and Realization of Input-Buffer Scheduling Algorithm in Satellite Switching System
Authors: Yi Zhang, Quan Zhou, Jun Li, Yanlang Hu
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Scheduling algorithm is a key technology in satellite switching system with input-buffer. In this paper, a new scheduling algorithm and its realization are proposed. Based on Crossbar switching fabric, the algorithm adopts serial scheduling strategy and adjusts the output port arbitrating strategy for the better equity of every port. Consequently, it increases the matching probability. The algorithm can greatly reduce the scheduling delay and cell loss rate. The analysis and simulation results by OPNET show that the proposed algorithm has the better performance than others in average delay and cell loss rate, and has the equivalent complexity. On the basis of these results, the hardware realization and simulation based on FPGA are completed, which validate the feasibility of the new scheduling algorithm.
Keywords: Scheduling algorithm, input-buffer, serial scheduling, hardware design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14673457 Simulation Modeling of Manufacturing Systems for the Serial Route and the Parallel One
Authors: Tadeusz Witkowski, Paweł Antczak, Arkadiusz Antczak
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In the paper we discuss the influence of the route flexibility degree, the open rate of operations and the production type coefficient on makespan. The flexible job-open shop scheduling problem FJOSP (an extension of the classical job shop scheduling) is analyzed. For the analysis of the production process we used a hybrid heuristic of the GRASP (greedy randomized adaptive search procedure) with simulated annealing algorithm. Experiments with different levels of factors have been considered and compared. The GRASP+SA algorithm has been tested and illustrated with results for the serial route and the parallel one.Keywords: Makespan, open shop, route flexibility, serial and parallel route, simulation modeling, type of production.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18083456 Massively-Parallel Bit-Serial Neural Networks for Fast Epilepsy Diagnosis: A Feasibility Study
Authors: Si Mon Kueh, Tom J. Kazmierski
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There are about 1% of the world population suffering from the hidden disability known as epilepsy and major developing countries are not fully equipped to counter this problem. In order to reduce the inconvenience and danger of epilepsy, different methods have been researched by using a artificial neural network (ANN) classification to distinguish epileptic waveforms from normal brain waveforms. This paper outlines the aim of achieving massive ANN parallelization through a dedicated hardware using bit-serial processing. The design of this bit-serial Neural Processing Element (NPE) is presented which implements the functionality of a complete neuron using variable accuracy. The proposed design has been tested taking into consideration non-idealities of a hardware ANN. The NPE consists of a bit-serial multiplier which uses only 16 logic elements on an Altera Cyclone IV FPGA and a bit-serial ALU as well as a look-up table. Arrays of NPEs can be driven by a single controller which executes the neural processing algorithm. In conclusion, the proposed compact NPE design allows the construction of complex hardware ANNs that can be implemented in a portable equipment that suits the needs of a single epileptic patient in his or her daily activities to predict the occurrences of impending tonic conic seizures.Keywords: Artificial Neural Networks, bit-serial neural processor, FPGA, Neural Processing Element.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15623455 On the Efficient Implementation of a Serial and Parallel Decomposition Algorithm for Fast Support Vector Machine Training Including a Multi-Parameter Kernel
Authors: Tatjana Eitrich, Bruno Lang
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This work deals with aspects of support vector machine learning for large-scale data mining tasks. Based on a decomposition algorithm for support vector machine training that can be run in serial as well as shared memory parallel mode we introduce a transformation of the training data that allows for the usage of an expensive generalized kernel without additional costs. We present experiments for the Gaussian kernel, but usage of other kernel functions is possible, too. In order to further speed up the decomposition algorithm we analyze the critical problem of working set selection for large training data sets. In addition, we analyze the influence of the working set sizes onto the scalability of the parallel decomposition scheme. Our tests and conclusions led to several modifications of the algorithm and the improvement of overall support vector machine learning performance. Our method allows for using extensive parameter search methods to optimize classification accuracy.
Keywords: Support Vector Machine Training, Multi-ParameterKernels, Shared Memory Parallel Computing, Large Data
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14303454 A Rapid Code Acquisition Scheme in OOC-Based CDMA Systems
Authors: Keunhong Chae, Seokho Yoon
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We propose a code acquisition scheme called improved multiple-shift (IMS) for optical code division multiple access systems, where the optical orthogonal code is used instead of the pseudo noise code. Although the IMS algorithm has a similar process to that of the conventional MS algorithm, it has a better code acquisition performance than the conventional MS algorithm. We analyze the code acquisition performance of the IMS algorithm and compare the code acquisition performances of the MS and the IMS algorithms in single-user and multi-user environments.
Keywords: Code acquisition, optical CDMA, optical orthogonal code, serial algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21443453 Efficient Implementation of Serial and Parallel Support Vector Machine Training with a Multi-Parameter Kernel for Large-Scale Data Mining
Authors: Tatjana Eitrich, Bruno Lang
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This work deals with aspects of support vector learning for large-scale data mining tasks. Based on a decomposition algorithm that can be run in serial and parallel mode we introduce a data transformation that allows for the usage of an expensive generalized kernel without additional costs. In order to speed up the decomposition algorithm we analyze the problem of working set selection for large data sets and analyze the influence of the working set sizes onto the scalability of the parallel decomposition scheme. Our modifications and settings lead to improvement of support vector learning performance and thus allow using extensive parameter search methods to optimize classification accuracy.
Keywords: Support Vector Machines, Shared Memory Parallel Computing, Large Data
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15713452 Geographic Profiling Based on Multi-point Centrography with K-means Clustering
Authors: Jiaji Zhou, Le Liang, Long Chen
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Geographic Profiling has successfully assisted investigations for serial crimes. Considering the multi-cluster feature of serial criminal spots, we propose a Multi-point Centrography model as a natural extension of Single-point Centrography for geographic profiling. K-means clustering is first performed on the data samples and then Single-point Centrography is adopted to derive a probability distribution on each cluster. Finally, a weighted combinations of each distribution is formed to make next-crime spot prediction. Experimental study on real cases demonstrates the effectiveness of our proposed model.
Keywords: Geographic profiling, Centrography model, K-means algorithm
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20673451 Reducing SAGE Data Using Genetic Algorithms
Authors: Cheng-Hong Yang, Tsung-Mu Shih, Li-Yeh Chuang
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Serial Analysis of Gene Expression is a powerful quantification technique for generating cell or tissue gene expression data. The profile of the gene expression of cell or tissue in several different states is difficult for biologists to analyze because of the large number of genes typically involved. However, feature selection in machine learning can successfully reduce this problem. The method allows reducing the features (genes) in specific SAGE data, and determines only relevant genes. In this study, we used a genetic algorithm to implement feature selection, and evaluate the classification accuracy of the selected features with the K-nearest neighbor method. In order to validate the proposed method, we used two SAGE data sets for testing. The results of this study conclusively prove that the number of features of the original SAGE data set can be significantly reduced and higher classification accuracy can be achieved.Keywords: Serial Analysis of Gene Expression, Feature selection, Genetic Algorithm, K-nearest neighbor method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15973450 Performance Comparison and Analysis of Serial Concatenated Convolutional Codes
Authors: Dongwon Lee, Eon Kyeong Joo
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In this paper, the performance of three types of serial concatenated convolutional codes (SCCC) is compared and analyzed in additive white Gaussian noise (AWGN) channel. In Type I, only the parity bits of outer encoder are passed to inner encoder. In Type II and Type III, both the information bits and the parity bits of outer encoder are transferred to inner encoder. As results of simulation, Type I shows the best bit error rate (BER) performance at low signal-to-noise ratio (SNR). On the other hand, Type III shows the best BER performance at high SNR in AWGN channel. The simulation results are analyzed using the distance spectrum.Keywords: Distance spectrum, MAP algorithm, SCCC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17473449 Transceiver for Differential Wave Pipe-Lined Serial Interconnect with Surfing
Authors: Bhaskar M., Venkataramani B.
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In the literature, surfing technique has been proposed for single ended wave-pipelined serial interconnects to increase the data transfer rate. In this paper a novel surfing technique is proposed for differential wave-pipelined serial interconnects, which uses a 'Controllable inverter pair' for surfing. To evaluate the efficiency of this technique, a transceiver with transmitter, receiver, delay locked loop (DLL) along with 40mm metal 4 interconnects using the proposed surfing technique is implemented in UMC 180nm technology and their performances are studied through post layout simulations. From the study, it is observed that the proposed scheme permits 1.875 times higher data transmission rate compared to the single ended scheme whose maximum data transfer rate is 1.33 GB/s. The proposed scheme has the ability to receive the correct data even with stuck-at-faults in the complementary line.
Keywords: Controllable inverter pair, differential interconnect, serial link, surfing, wave pipelining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16643448 A Parallel Implementation of k-Means in MATLAB
Authors: Dimitris Varsamis, Christos Talagkozis, Alkiviadis Tsimpiris, Paris Mastorocostas
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The aim of this work is the parallel implementation of k-means in MATLAB, in order to reduce the execution time. Specifically, a new function in MATLAB for serial k-means algorithm is developed, which meets all the requirements for the conversion to a function in MATLAB with parallel computations. Additionally, two different variants for the definition of initial values are presented. In the sequel, the parallel approach is presented. Finally, the performance tests for the computation times respect to the numbers of features and classes are illustrated.Keywords: K-means algorithm, clustering, parallel computations, MATLAB.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11403447 A Revisited View to the Paced Auditory Serial Addition Test (PASAT) in Female and Male Normal Subjects
Authors: Javad Razjouyan, Shahriar Gharibzadeh, Ali Fallah, Mehdi Moghaddasi, Mohsen Seyfi, Amir Kasaeian
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Paced Auditory Serial Addition Test (PASAT) has been used as a common research tool for different neurological disorders like Multiple Sclerosis. Recently, technology let researchers to introduce a new versions of the visual test, the paced visual serial addition test (PVSAT). In this paper, the computerized version of these two tests is introduced. Beside the number of true responses are interpreted, the reaction time of subjects are calculated by the software. We hypothesize that paying attention to the reaction time may be valuable. For this purpose, sixty eight female normal subjects and fifty eight male normal subjects are enrolled in the study. We investigate the similarity between the PASAT3 and PVSAT3 in number of true responses and the new criterion (the average reaction time of each subject). The similarity between two tests were rejected (p-value = 0.000) which means that these two test differ. The effect of sex in the tests were not approved since the pvalues of different between PASAT3 and PVSAT3 in both sex is the same (p-value = 0.000) which means that male and female subjects performed the tests at no different level of performance. The new criterion shows a negative correlation with the age which offers aged normal subjects may have the same number of true responses as the young subjects but they have latent responses. This will give prove for the importance of reaction time.Keywords: Paced Auditory Serial Addition Test, Pace Visual Serial Addition Test, reaction time.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19523446 Monte Carlo Estimation of Heteroscedasticity and Periodicity Effects in a Panel Data Regression Model
Authors: Nureni O. Adeboye, Dawud A. Agunbiade
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This research attempts to investigate the effects of heteroscedasticity and periodicity in a Panel Data Regression Model (PDRM) by extending previous works on balanced panel data estimation within the context of fitting PDRM for Banks audit fee. The estimation of such model was achieved through the derivation of Joint Lagrange Multiplier (LM) test for homoscedasticity and zero-serial correlation, a conditional LM test for zero serial correlation given heteroscedasticity of varying degrees as well as conditional LM test for homoscedasticity given first order positive serial correlation via a two-way error component model. Monte Carlo simulations were carried out for 81 different variations, of which its design assumed a uniform distribution under a linear heteroscedasticity function. Each of the variation was iterated 1000 times and the assessment of the three estimators considered are based on Variance, Absolute bias (ABIAS), Mean square error (MSE) and the Root Mean Square (RMSE) of parameters estimates. Eighteen different models at different specified conditions were fitted, and the best-fitted model is that of within estimator when heteroscedasticity is severe at either zero or positive serial correlation value. LM test results showed that the tests have good size and power as all the three tests are significant at 5% for the specified linear form of heteroscedasticity function which established the facts that Banks operations are severely heteroscedastic in nature with little or no periodicity effects.
Keywords: Audit fee, heteroscedasticity, Lagrange multiplier test, periodicity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7273445 Backplane Serial Signaling and Protocol for Telecom Systems
Authors: Ali Poureslami, Hossein Borhanifar, Seyed Ali Alavian
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In this paper, we implement a modern serial backplane platform for telecommunication inter-rack systems. For combination high reliability and low cost protocol property, we applied high level data link control (HDLC) protocol with low voltage differential signaling (LVDS) bus for card to card communicated over backplane. HDLC protocol is a high performance with several operation modes and is famous in telecommunication systems. LVDS bus is a high reliability with high immunity against electromagnetic interference (EMI) and noise.Keywords: Backplane, BLVDS, HDLC, EMI, I2C, LCT, OSC, SFP, SNMP.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22593444 Pallet Tracking and Cost Optimization of the Flow of Goods in Logistics Operations by Serial Shipping Container Code
Authors: Dominika Crnjac Milic, Martina Martinovic, Vladimir Simovic
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The case study method in this paper shows the implementation of Information Technology (IT) and the Serial Shipping Container Code (SSCC) in a Croatian company that deals with logistics operations and provides logistics services in the cold chain segment. This company is aware of the sensitivity of the goods entrusted to them by the user of the service, as well as of the importance of speed and accuracy in providing logistics services. To that end, it has implemented and used the latest IT to ensure the highest standard of high-quality logistics services to its customers. Looking for efficiency and optimization of supply chain management, while maintaining a high level of quality of the products that are sold, today's users of outsourced logistics services are open to the implementation of new IT products that ultimately deliver savings. By analysing the positive results and the difficulties that arise when using this technology, we aim to provide an insight into the potential of this approach of the logistics service provider.
Keywords: Logistics operations, serial shipping container code, SSCC, information technology, cost optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9303443 A Hybrid Multi-Objective Firefly-Sine Cosine Algorithm for Multi-Objective Optimization Problem
Authors: Gaohuizi Guo, Ning Zhang
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Firefly algorithm (FA) and Sine Cosine algorithm (SCA) are two very popular and advanced metaheuristic algorithms. However, these algorithms applied to multi-objective optimization problems have some shortcomings, respectively, such as premature convergence and limited exploration capability. Combining the privileges of FA and SCA while avoiding their deficiencies may improve the accuracy and efficiency of the algorithm. This paper proposes a hybridization of FA and SCA algorithms, named multi-objective firefly-sine cosine algorithm (MFA-SCA), to develop a more efficient meta-heuristic algorithm than FA and SCA.Keywords: Firefly algorithm, hybrid algorithm, multi-objective optimization, Sine Cosine algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4943442 Approximating Fixed Points by a Two-Step Iterative Algorithm
Authors: Safeer Hussain Khan
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In this paper, we introduce a two-step iterative algorithm to prove a strong convergence result for approximating common fixed points of three contractive-like operators. Our algorithm basically generalizes an existing algorithm..Our iterative algorithm also contains two famous iterative algorithms: Mann iterative algorithm and Ishikawa iterative algorithm. Thus our result generalizes the corresponding results proved for the above three iterative algorithms to a class of more general operators. At the end, we remark that nothing prevents us to extend our result to the case of the iterative algorithm with error terms.
Keywords: Contractive-like operator, iterative algorithm, fixed point, strong convergence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20103441 Some Improvements on Kumlander-s Maximum Weight Clique Extraction Algorithm
Authors: Satoshi Shimizu, Kazuaki Yamaguchi, Toshiki Saitoh, Sumio Masuda
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Some fast exact algorithms for the maximum weight clique problem have been proposed. Östergard’s algorithm is one of them. Kumlander says his algorithm is faster than it. But we confirmed that the straightforwardly implemented Kumlander’s algorithm is slower than O¨ sterga˚rd’s algorithm. We propose some improvements on Kumlander’s algorithm.
Keywords: Maximum weight clique, exact algorithm, branch-andbound, NP-hard.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18473440 Application of Adaptive Genetic Algorithm in Function Optimization
Authors: Panpan Xu, Shulin Sui
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The crossover probability and mutation probability are the two important factors in genetic algorithm. The adaptive genetic algorithm can improve the convergence performance of genetic algorithm, in which the crossover probability and mutation probability are adaptively designed with the changes of fitness value. We apply adaptive genetic algorithm into a function optimization problem. The numerical experiment represents that adaptive genetic algorithm improves the convergence speed and avoids local convergence.
Keywords: Genetic algorithm, Adaptive genetic algorithm, Function optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17093439 Optimal External Merge Sorting Algorithm with Smart Block Merging
Authors: Mir Hadi Seyedafsari, Iraj Hasanzadeh
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Like other external sorting algorithms, the presented algorithm is a two step algorithm including internal and external steps. The first part of the algorithm is like the other similar algorithms but second part of that is including a new easy implementing method which has reduced the vast number of inputoutput operations saliently. As decreasing processor operating time does not have any effect on main algorithm speed, any improvement in it should be done through decreasing the number of input-output operations. This paper propose an easy algorithm for choose the correct record location of the final list. This decreases the time complexity and makes the algorithm faster.Keywords: External sorting algorithm, internal sortingalgorithm, fast sorting, robust algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21703438 Analog Circuit Design using Genetic Algorithm: Modified
Authors: Amod P. Vaze
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Genetic Algorithm has been used to solve wide range of optimization problems. Some researches conduct on applying Genetic Algorithm to analog circuit design automation. These researches show a better performance due to the nature of Genetic Algorithm. In this paper a modified Genetic Algorithm is applied for analog circuit design automation. The modifications are made to the topology of the circuit. These modifications will lead to a more computationally efficient algorithm.
Keywords: Genetic algorithm, analog circuits, design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22823437 Application of Hybrid Genetic Algorithm Based on Simulated Annealing in Function Optimization
Authors: Panpan Xu, Shulin Sui, Zongjie Du
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Genetic algorithm is widely used in optimization problems for its excellent global search capabilities and highly parallel processing capabilities; but, it converges prematurely and has a poor local optimization capability in actual operation. Simulated annealing algorithm can avoid the search process falling into local optimum. A hybrid genetic algorithm based on simulated annealing is designed by combining the advantages of genetic algorithm and simulated annealing algorithm. The numerical experiment represents the hybrid genetic algorithm can be applied to solve the function optimization problems efficiently.Keywords: Genetic algorithm, Simulated annealing, Hybrid genetic algorithm, Function optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25403436 Convergence Analysis of an Alternative Gradient Algorithm for Non-Negative Matrix Factorization
Authors: Chenxue Yang, Mao Ye, Zijian Liu, Tao Li, Jiao Bao
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Non-negative matrix factorization (NMF) is a useful computational method to find basis information of multivariate nonnegative data. A popular approach to solve the NMF problem is the multiplicative update (MU) algorithm. But, it has some defects. So the columnwisely alternating gradient (cAG) algorithm was proposed. In this paper, we analyze convergence of the cAG algorithm and show advantages over the MU algorithm. The stability of the equilibrium point is used to prove the convergence of the cAG algorithm. A classic model is used to obtain the equilibrium point and the invariant sets are constructed to guarantee the integrity of the stability. Finally, the convergence conditions of the cAG algorithm are obtained, which help reducing the evaluation time and is confirmed in the experiments. By using the same method, the MU algorithm has zero divisor and is convergent at zero has been verified. In addition, the convergence conditions of the MU algorithm at zero are similar to that of the cAG algorithm at non-zero. However, it is meaningless to discuss the convergence at zero, which is not always the result that we want for NMF. Thus, we theoretically illustrate the advantages of the cAG algorithm.
Keywords: Non-negative matrix factorizations, convergence, cAG algorithm, equilibrium point, stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16883435 Genetic Mining: Using Genetic Algorithm for Topic based on Concept Distribution
Authors: S. M. Khalessizadeh, R. Zaefarian, S.H. Nasseri, E. Ardil
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Today, Genetic Algorithm has been used to solve wide range of optimization problems. Some researches conduct on applying Genetic Algorithm to text classification, summarization and information retrieval system in text mining process. This researches show a better performance due to the nature of Genetic Algorithm. In this paper a new algorithm for using Genetic Algorithm in concept weighting and topic identification, based on concept standard deviation will be explored.Keywords: Genetic Algorithm, Text Mining, Term Weighting, Concept Extraction, Concept Distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36933434 A Serial Hierarchical Support Vector Machine and 2D Feature Sets Act for Brain DTI Segmentation
Authors: Mohammad Javadi
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Serial hierarchical support vector machine (SHSVM) is proposed to discriminate three brain tissues which are white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). SHSVM has novel classification approach by repeating the hierarchical classification on data set iteratively. It used Radial Basis Function (rbf) Kernel with different tuning to obtain accurate results. Also as the second approach, segmentation performed with DAGSVM method. In this article eight univariate features from the raw DTI data are extracted and all the possible 2D feature sets are examined within the segmentation process. SHSVM succeed to obtain DSI values higher than 0.95 accuracy for all the three tissues, which are higher than DAGSVM results.
Keywords: Brain segmentation, DTI, hierarchical, SVM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18483433 Application of ESA in the CAVE Mode Authentication
Authors: Keonwoo Kim, Dowon Hong, Kyoil Chung
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This paper proposes the authentication method using ESA algorithm instead of using CAVE algorithm in the CDMA mobile communication systems including IS-95 and CDMA2000 1x. And, we analyze to apply ESA mechanism on behalf of CAVE mechanism without the change of message format and air interface in the existing CDMA systems. If ESA algorithm can be used as the substitution of CAVE algorithm, security strength of authentication algorithm is intensified without protocol change. An algorithm replacement proposed in this paper is not to change an authentication mechanism, but to configure input of ESA algorithm and to produce output. Therefore, our proposal can be the compatible to the existing systems.Keywords: ESA, CAVE, CDMA, authentication, mobilecommunication.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15773432 Hybrid Minimal Repair for a Serial System
Authors: Ellysa Nursanti, Anas Ma'ruf, Tota Simatupang, Bermawi P. Iskandar
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This study proposes a hybrid minimal repair policy which combines periodic maintenance policy with age-based maintenance policy for a serial production system. Parameters of such policy are defined as and which indicate as hybrid minimal repair time and planned preventive maintenance time respectively . Under this hybrid policy, the system is repaired minimally if it fails during ,. A perfect repair is conducted on the first failure after at any machines. At the same time, we take opportunity to advance the preventive maintenance of other machines simultaneously. If the system is still operating properly up to , then the preventive maintenance is carried out as its predetermined schedule. For a given , we obtain the optimal value which minimizes the expected cost per time unit. Numerical example is presented to illustrate the properties of the optimal solution.Keywords: Hybrid minimal repair, opportunistic maintenance, preventive maintenance, series system
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16463431 A New Algorithm to Stereo Correspondence Using Rank Transform and Morphology Based On Genetic Algorithm
Authors: Razagh Hafezi, Ahmad Keshavarz, Vida Moshfegh
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This paper presents a novel algorithm of stereo correspondence with rank transform. In this algorithm we used the genetic algorithm to achieve the accurate disparity map. Genetic algorithms are efficient search methods based on principles of population genetic, i.e. mating, chromosome crossover, gene mutation, and natural selection. Finally morphology is employed to remove the errors and discontinuities.Keywords: genetic algorithm, morphology, rank transform, stereo correspondence
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21583430 Tele-Operated Anthropomorphic Arm and Hand Design
Authors: Namal A. Senanayake, Khoo B. How, Quah W. Wai
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In this project, a tele-operated anthropomorphic robotic arm and hand is designed and built as a versatile robotic arm system. The robot has the ability to manipulate objects such as pick and place operations. It is also able to function by itself, in standalone mode. Firstly, the robotic arm is built in order to interface with a personal computer via a serial servo controller circuit board. The circuit board enables user to completely control the robotic arm and moreover, enables feedbacks from user. The control circuit board uses a powerful integrated microcontroller, a PIC (Programmable Interface Controller). The PIC is firstly programmed using BASIC (Beginner-s All-purpose Symbolic Instruction Code) and it is used as the 'brain' of the robot. In addition a user friendly Graphical User Interface (GUI) is developed as the serial servo interface software using Microsoft-s Visual Basic 6. The second part of the project is to use speech recognition control on the robotic arm. A speech recognition circuit board is constructed with onboard components such as PIC and other integrated circuits. It replaces the computers- Graphical User Interface. The robotic arm is able to receive instructions as spoken commands through a microphone and perform operations with respect to the commands such as picking and placing operations.Keywords: Tele-operated Anthropomorphic Robotic Arm and Hand, Robot Motion System, Serial Servo Controller, Speech Recognition Controller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17533429 A Genetic Based Algorithm to Generate Random Simple Polygons Using a New Polygon Merge Algorithm
Authors: Ali Nourollah, Mohsen Movahedinejad
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In this paper a new algorithm to generate random simple polygons from a given set of points in a two dimensional plane is designed. The proposed algorithm uses a genetic algorithm to generate polygons with few vertices. A new merge algorithm is presented which converts any two polygons into a simple polygon. This algorithm at first changes two polygons into a polygonal chain and then the polygonal chain is converted into a simple polygon. The process of converting a polygonal chain into a simple polygon is based on the removal of intersecting edges. The experiments results show that the proposed algorithm has the ability to generate a great number of different simple polygons and has better performance in comparison to celebrated algorithms such as space partitioning and steady growth.
Keywords: Divide and conquer, genetic algorithm, merge polygons, Random simple polygon generation.
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