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2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE)最新文献

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Adaptive Interval Type-2 Fuzzy PI Sliding Mode Control with optimization of membership functions using genetic algorithm 利用遗传算法优化隶属函数的自适应区间2型模糊PI滑模控制
2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2012-12-31 DOI: 10.1109/ICCKE.2012.6395364
M. Ghaemi, M. Akbarzadeh-T., M. Jalaeian-F.
{"title":"Adaptive Interval Type-2 Fuzzy PI Sliding Mode Control with optimization of membership functions using genetic algorithm","authors":"M. Ghaemi, M. Akbarzadeh-T., M. Jalaeian-F.","doi":"10.1109/ICCKE.2012.6395364","DOIUrl":"https://doi.org/10.1109/ICCKE.2012.6395364","url":null,"abstract":"A new stable Adaptive Interval Type-2 Fuzzy Proportional Integral Sliding Mode Controller (AI2FPISMC) is introduced here to control a class of nonlinear systems. The proposed method is based on interval type-2 fuzzy logic system (IT2FLS) whose antecedent and consequent membership functions are interval type-2 fuzzy sets. IT2FLS is utilized to approximate unknown nonlinear functions. To achieve high performance, optimizing membership functions (MFs) of interval type-2 fuzzy sets (IT2FS) is required. Genetic algorithm (GA) is a parallel search optimization method; that here contributes to optimize the MFs. In order to cope with the chattering of sliding mode controller, PI control law is proposed and Lyapunov analysis is utilized to prove asymptotic stability of the proposed approach. The adaptation laws are derived using Lyapunov approach. Two nonlinear system simulation examples are presented to verify the effectiveness of the proposed method, and their results confirm the optimization merits.","PeriodicalId":154379,"journal":{"name":"2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129134165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
Application of PSO for selective harmonic elimination in a PWM AC/AC voltage regulator PSO在PWM交/交稳压器中选择性谐波消除的应用
2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2012-12-31 DOI: 10.1109/ICCKE.2012.6395353
S. M. Sadr, M. Monfared, H. R. Mashhadi
{"title":"Application of PSO for selective harmonic elimination in a PWM AC/AC voltage regulator","authors":"S. M. Sadr, M. Monfared, H. R. Mashhadi","doi":"10.1109/ICCKE.2012.6395353","DOIUrl":"https://doi.org/10.1109/ICCKE.2012.6395353","url":null,"abstract":"In this paper the particle swarm optimization (PSO) technique is used to find an optimal solution for the selective harmonic elimination (SHE) problem in PWM AC/AC voltage regulators. For this kind of voltage controllers, SHE leads to nonlinear and transcendental equations; as a result, solving them by conventional numerical methods highly depends on proper selection of initial values. The proposed PSO based algorithm affectively computes the required switching instances to eliminate pre-specified harmonics from the output voltage. Problem formulation, objective function and obtained switching angels trajectories for eliminating different sets of harmonics are presented. Simulation results using Matlab/Simulink are presented to confirm the theoretical results.","PeriodicalId":154379,"journal":{"name":"2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128658702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
Heart vessel extraction using motion based heart area extraction 基于运动的心脏区域提取的心脏血管提取
2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2012-12-31 DOI: 10.1109/ICCKE.2012.6395376
Majid Ziashahabiand, A. Behrad
{"title":"Heart vessel extraction using motion based heart area extraction","authors":"Majid Ziashahabiand, A. Behrad","doi":"10.1109/ICCKE.2012.6395376","DOIUrl":"https://doi.org/10.1109/ICCKE.2012.6395376","url":null,"abstract":"In this paper, a new method for heart vessel extraction based on heart area segmentation in angiogram image sequences is presented. One of the difficulties in vessel extraction in angiogram images is the detection of ribs and spins as vessels. Therefore, to cope with this problem, we utilize motion information to segment heart area. Then a two-stage vessel extraction algorithm is utilized to extract heart vessels efficiently. The vessel extraction algorithm, firstly extracts thick vessel, then the vessel extraction is completed by utilizing a new morphology based algorithm. Experimental results show that the proposed algorithm extracts heart area precisely using motion based segmentation, and hence vessel extraction accuracy of 95.16% is obtained.","PeriodicalId":154379,"journal":{"name":"2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE)","volume":"173 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120859468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Question classification in Persian language based on conditional random fields 基于条件随机场的波斯语问题分类
2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2012-12-31 DOI: 10.1109/ICCKE.2012.6395395
A. Mollaei, S. Rahati-Quchani, A. Estaji
{"title":"Question classification in Persian language based on conditional random fields","authors":"A. Mollaei, S. Rahati-Quchani, A. Estaji","doi":"10.1109/ICCKE.2012.6395395","DOIUrl":"https://doi.org/10.1109/ICCKE.2012.6395395","url":null,"abstract":"The question classification system is one of the important subsystems in the Question Answering Systems (QAS). In such systems through retrieval methods and information extraction the texts are retrieved in order to get to a correct answer. The current study is designed to present the architecture of question classification (QC) in Persian based on the Conditional Random Fields (CRF) machine learning model and evaluate effects of various features on its accuracy. In this study, sentences were classified into two levels of coarse and fine classes based on the type of the answer to each question. After extracting features and setting sliding window on the CRF model, CRF question classifier (QC) is train. Then, the QC predicts labels for every token in question. Next, a majority voting on the question classification output, is used to extract a unique label for each question. Further, the effects of different features on the ultimate accuracy of the system were evaluated. Finally results of this question classifier, illustrate a satisfactory accuracy.","PeriodicalId":154379,"journal":{"name":"2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE)","volume":"56 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126258128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
An empirical study using combination of SVM with PSO based scattering ratio optimization and K-means 基于支持向量机与粒子群算法相结合的散射比优化与K-means的实证研究
2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2012-12-31 DOI: 10.1109/ICCKE.2012.6395352
H. Azami, B. Bozorgtabar
{"title":"An empirical study using combination of SVM with PSO based scattering ratio optimization and K-means","authors":"H. Azami, B. Bozorgtabar","doi":"10.1109/ICCKE.2012.6395352","DOIUrl":"https://doi.org/10.1109/ICCKE.2012.6395352","url":null,"abstract":"One of the most significant practical challenges for face recognition is a likeness of faces which leads to a big problem in classification of different classes. To tackle this problem, we present a novel method based on similarity of each face with other faces using the Pearson correlation coefficients. Besides, another problem is variability in lighting intensity which its physics are difficult for accurate model. In this paper, first, discrete wavelet transform (DWT) is used for feature extraction. Next, with respect to the correlation matrix, two algorithms are employed, namely, K-means clustering and particle swarm optimization (PSO) based scattering ratio matrix of correlation features. Then for each cluster, the process of classification is continued by normalization of the each subset firstly and then the decision making for each subset is performed by support vector machine (SVM). The experiments are performed on the ORL and Yale databases and the results show that there are a significant improvement in 45 features based weighted recognition rate.","PeriodicalId":154379,"journal":{"name":"2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127531043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Energy efficient data gathering algorithm in hierarchical wireless sensor networks with mobile sink 具有移动接收器的分层无线传感器网络的高能效数据采集算法
2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2012-12-31 DOI: 10.1109/ICCKE.2012.6395384
F. Tashtarian, M. Moghaddam, S. Effati
{"title":"Energy efficient data gathering algorithm in hierarchical wireless sensor networks with mobile sink","authors":"F. Tashtarian, M. Moghaddam, S. Effati","doi":"10.1109/ICCKE.2012.6395384","DOIUrl":"https://doi.org/10.1109/ICCKE.2012.6395384","url":null,"abstract":"One of the most critical issues in wireless sensor networks is the limited energy availability of the network nodes. This paper is investigating the advantages of using controlled sink mobility in clustered wireless sensor networks (WSNs) which increases network lifetime. In a clustered sensor network all Cluster Heads (CHs) have to transmit their buffered data to the sink during a specified interval, called data reporting time (tdr). In this paper, we propose a scheme that prescribes the sink path for collecting all CHs data in tdr time span while maximizing network life time using the mathematical model MILP (Mixed Integer Linear Programming). The proposed scheme is compared with other related schemes by means of various simulation scenarios. Simulation results show that the proposed scheme significantly outperforms other schemes.","PeriodicalId":154379,"journal":{"name":"2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127533395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
A novel bidirectional neural network for face recognition 一种新的用于人脸识别的双向神经网络
2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2012-10-01 DOI: 10.1109/ICCKE.2012.6395345
Jalil Mazloum, A. Jalali, J. Amiryan
{"title":"A novel bidirectional neural network for face recognition","authors":"Jalil Mazloum, A. Jalali, J. Amiryan","doi":"10.1109/ICCKE.2012.6395345","DOIUrl":"https://doi.org/10.1109/ICCKE.2012.6395345","url":null,"abstract":"The recognition of face images is a complicated problem. Face images are often sufferedfrom variations in brightness, head rotation, facial emotions and so on. Besides, amazing abilities of human brain in face recognition in the presence of these variations, contribute to design face recognition systems based on procedure of human brain. Surveying the recognition and perceptual system of human, shows that, this system has hierarchical and bidirectional structure. Furthermore, the performance of the system would strongly be improved by applying the information of upper layers of face recognition system in interpreting and processing the input data. In this paper, novel bidirectional architecturefor face recognition inspired by human face recognition system is presentedvia applying inversion in artificial neural networks (ANN's). In this approach, storeddata in the inverse networkis applied in the recognition system iterativelyandthen the correctness of face recognition model has been consequently improved by 8%. The proposed model is able to produce 12 various facial expressions on the output, from only one input expressionof each person, after training with AUT database images.","PeriodicalId":154379,"journal":{"name":"2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132891682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
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