2014 4th International Conference on Computer and Knowledge Engineering (ICCKE)最新文献_第3页

Price and QoS competition in cloud market by using cellular learning automata 基于元胞学习自动机的云市场价格与QoS竞争

2014 4th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2014-12-22 DOI: 10.1109/ICCKE.2014.6993349

Shakiba Kheradmand, M. Meybodi

引用次数: 5

An approach for classifying large dataset using ensemble classifiers 一种使用集成分类器对大型数据集进行分类的方法

2014 4th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2014-12-22 DOI: 10.1109/ICCKE.2014.6993440

Sajad Khodarahmi Jahan Abad, Mohammad-Reza Zare-Mirakabad, M. Rezaeian

{"title":"An approach for classifying large dataset using ensemble classifiers","authors":"Sajad Khodarahmi Jahan Abad, Mohammad-Reza Zare-Mirakabad, M. Rezaeian","doi":"10.1109/ICCKE.2014.6993440","DOIUrl":"https://doi.org/10.1109/ICCKE.2014.6993440","url":null,"abstract":"Efficiency of general classification models in various problems is different according to the characteristics and the space of the problem. Even in a particular issue, it may not be distinguished a special privilege for a classifier method than the others. Ensemble classifier methods aim to combine the results of several classifiers to cover the deficiency of each classifier by others. This combination faces high computational complexity if it includes a lazy base classifier, especially when handling large datasets. In this paper a method is proposed to combine the results of classifiers, which uses clustering as a part of the training, resulting in reducing the computational complexity, while it provides an acceptable accuracy. In this method the base classifiers are trained by a part of the input dataset, first. Then, according to the labels defined by the base classifiers, the clusters are created for another part of dataset. Finally, the samples contained in the clusters, the cluster that each sample belongs to it, and the distance of each sample to the center of all clusters are given to an artificial neural network and the final class label of test data is determined by the neural network. Experiments on several datasets show advantages of proposed model.","PeriodicalId":152540,"journal":{"name":"2014 4th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128702181","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: 2

A new model predictive current controller with common mode voltage alleviation in three-phase inverters 一种新型三相逆变器共模减压模型预测电流控制器

2014 4th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2014-12-22 DOI: 10.1109/ICCKE.2014.6993335

N. Safari, A. Khoshooei, J. Moghani

引用次数: 1

Facial emotion recognition method based on Pyramid Histogram of Oriented Gradient over three direction of head 基于头部三个方向梯度金字塔直方图的面部情感识别方法

2014 4th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2014-12-22 DOI: 10.1109/ICCKE.2014.6993346

Sh. Shokrani, P. Moallem, M. Habibi

{"title":"Facial emotion recognition method based on Pyramid Histogram of Oriented Gradient over three direction of head","authors":"Sh. Shokrani, P. Moallem, M. Habibi","doi":"10.1109/ICCKE.2014.6993346","DOIUrl":"https://doi.org/10.1109/ICCKE.2014.6993346","url":null,"abstract":"Today Human Computer Interaction (HCI) is one of the most important topics in machine vision and image processing fields. Through features can get beneficial information about the variety of emotions and gestures which are produced by the movements of facial major parts. In this paper we presented the technique of Pyramid Histogram of Oriented Gradient for feature extraction and compare it with gabor filters. Six basic facial expressions plus the neutral pose are considered in the evaluations. The KNN and SVM techniques are used in the classification phase. Unlike most emotion detection approaches that focus on frontal face view this method concentrates on three views of the face and can easily be generalized to other poses and feelings. We have tested our algorithm on the Radboud faces database (RaFD) over three directions of head (frontal, 45 degree to the right and 45 degree to the left). Cohn-Kanade (CK+) and JAFFE are two other databases used in this work. The experiments using the proposed method demonstrate favorable results. In the best condition by using Pyramid Histogram Of Oriented Gradient plus KNN classification, the success rates were 100, 96.7, 98.1, 98.3 and 98.9 % for RaFD (frontal pose), RaFD (45 degree to the right), RaFD (45 degree to the left), JAFFE and CK+ databases respectively.","PeriodicalId":152540,"journal":{"name":"2014 4th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127473874","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: 9

Loss-tolerant confidential efficient authenticated broadcast scheme 容错保密高效认证广播方案

2014 4th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2014-12-22 DOI: 10.1109/ICCKE.2014.6993363

H. Nasiraee, J. B. Mohasefi

引用次数: 0

HPCMalHunter: Behavioral malware detection using hardware performance counters and singular value decomposition HPCMalHunter:使用硬件性能计数器和奇异值分解的行为恶意软件检测

2014 4th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2014-12-22 DOI: 10.1109/ICCKE.2014.6993402

Mohammad Bagher Bahador, M. Abadi, Asghar Tajoddin

{"title":"HPCMalHunter: Behavioral malware detection using hardware performance counters and singular value decomposition","authors":"Mohammad Bagher Bahador, M. Abadi, Asghar Tajoddin","doi":"10.1109/ICCKE.2014.6993402","DOIUrl":"https://doi.org/10.1109/ICCKE.2014.6993402","url":null,"abstract":"Malicious programs, also known as malware, often use code obfuscation techniques to make static analysis more difficult and to evade signature-based detection. To resolve this problem, various behavioral detection techniques have been proposed that focus on the run-time behaviors of programs in order to dynamically detect malicious ones. Most of these techniques describe the run-time behavior of a program on the basis of its data flow and/or its system call traces. Recent work in behavioral malware detection has shown promise in using hardware performance counters (HPCs), which are a set of special-purpose registers built into modern processors providing detailed information about hardware and software events. In this paper, we pursue this line of research by presenting HPCMalHunter, a novel approach for real-time behavioral malware detection. HPCMalHunter uses HPCs to collect a set of event vectors from the beginning of a program's execution. It also uses the singular value decomposition (SVD) to reduce these event vectors and generate a behavioral vector for the program. By applying support vector machines (SVMs) to the feature vectors of different programs, it is able to identify malicious programs in real-time. Our results of experiments show that HPCMalHunter can detect malicious programs at the beginning of their execution with a high detection rate and a low false alarm rate.","PeriodicalId":152540,"journal":{"name":"2014 4th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123384561","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: 74

A double threshold energy detection cooperative spectrum sensing scheme over Nakagami and Rician fading channels 一种基于Nakagami和ricar衰落信道的双阈值能量检测协同频谱感知方案

2014 4th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2014-12-22 DOI: 10.1109/ICCKE.2014.6993437

I. Sharifi, S. Alirezaee, R. Heydari, M. Ahmadi, S. Erfani, M. Naserian

引用次数: 1

Data accuracy: What does it mean to LOD? 数据准确性:LOD意味着什么?

2014 4th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2014-12-22 DOI: 10.1109/ICCKE.2014.6993457

Behshid Behkamal, E. Bagheri, M. Kahani, Majid Sazvar

引用次数: 3

Learner knowledge level calculation by concept map and concept weight estimation using neural networks 基于概念图的学习者知识水平计算和基于神经网络的概念权重估计

2014 4th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2014-12-22 DOI: 10.1109/ICCKE.2014.6993394

A. Kardan, Negin Razavi

{"title":"Learner knowledge level calculation by concept map and concept weight estimation using neural networks","authors":"A. Kardan, Negin Razavi","doi":"10.1109/ICCKE.2014.6993394","DOIUrl":"https://doi.org/10.1109/ICCKE.2014.6993394","url":null,"abstract":"Nowadays we can observe fast expansion of the E-learning environment with an increase in the usage of internet and other technologies. In every educational environment, one of the most important challenges and issues is learner knowledge assessment. Because of this reason, it is necessary that an accurate method for learner assessment be implemented in every educational system. One of the newest tools that is used for teaching and assessment in schools and universities, is the concept map. The concept map is a graph that is used for representation and organization of knowledge in a special field. This graph contains concepts and meaningful relations between them. In this study, a new approach is proposed for the assessment of knowledge level by a concept map. In this approach, an expert person and student draw their concept map and then the score of the student is estimated in every concept in the map by comparing the student's map with the expert's map. Afterwards, a test of all of the concepts in the map is taken by the student and his/her total score is obtained. Finally, using the scores of each concept and total score, the weight or importance of each concept is calculated by neural networks.","PeriodicalId":152540,"journal":{"name":"2014 4th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122195392","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: 2

Automatic external Persian plagiarism detection using vector space model 使用向量空间模型的自动外部波斯语抄袭检测

2014 4th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2014-12-22 DOI: 10.1109/ICCKE.2014.6993398

P. Mahdavi, Zahra Siadati, F. Yaghmaee

引用次数: 20