2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE)最新文献_第8页

Advance Strong Authentication Strong Integrity (ASASI) Protocol for Low Cost Radio Frequency Identification 低成本射频识别的高级强认证强完整性(ASASI)协议

2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE) Pub Date : 2018-07-01 DOI: 10.1109/ICSCEE.2018.8538436

Madiha Khalid, U. Khokhar, M. Najam-ul-Islam

引用次数: 1

A new Algorithm based on the Gbest of Particle Swarm Optimization algorithm to improve Estimation of Distribution Algorithm 基于粒子群优化算法的Gbest改进了分布估计算法

2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE) Pub Date : 2018-07-01 DOI: 10.1109/ICSCEE.2018.8538372

Qiuyue Zhao, Ying Gao

{"title":"A new Algorithm based on the Gbest of Particle Swarm Optimization algorithm to improve Estimation of Distribution Algorithm","authors":"Qiuyue Zhao, Ying Gao","doi":"10.1109/ICSCEE.2018.8538372","DOIUrl":"https://doi.org/10.1109/ICSCEE.2018.8538372","url":null,"abstract":"In recent years, with the rise of artificial intelligence and deep learning, as an evolutionary algorithm based on probability model, estimation of distribution algorithm has been widely research and development. The estimation of distribution algorithm without the traditional genetic operation such as crossover and mutation, is a new kind of evolution model. As an algorithm based on probabilistic mode, the estimation of distribution algorithm establishes a probabilistic model describing the solution space of optimization problems. With the emergence for big data, the convergence of the algorithm and the requirements for solving precision are also increasing. This paper attempts to improve the distribution estimation algorithm. The optimal population of each iteration is found through the location update of each iteration of the Particle Swarm Optimization (PSO) algorithm. The simulation test was carried out with ten benchmark test function. The proposed algorithm was compared with the GA_EDA9improved genetic algorithm) and the basic distribution estimation (EDA) algorithm. Experimental results show that the new algorithm is superior to GA_EDA and basic EDA in terms of convergence and accuracy.","PeriodicalId":265737,"journal":{"name":"2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134603949","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 Review of Evidence Extraction Techniques in Big Data Environment 大数据环境下证据提取技术综述

2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE) Pub Date : 2018-07-01 DOI: 10.1109/ICSCEE.2018.8538437

S. H. Mokhtar, Gopinath Muruti, Z. Ibrahim, Fiza Abdul Rahim, Hairoladenan Kasim

引用次数: 0

Investigation on the Effect of Different Window Size in Segmentation for Common Sport Activity 不同窗口大小对常见体育活动分割效果的研究

2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE) Pub Date : 2018-07-01 DOI: 10.1109/ICSCEE.2018.8538429

N. F. Ghazali, M. A. As’ari, N. Shahar, Hadafi Fitri Mohd Latip

{"title":"Investigation on the Effect of Different Window Size in Segmentation for Common Sport Activity","authors":"N. F. Ghazali, M. A. As’ari, N. Shahar, Hadafi Fitri Mohd Latip","doi":"10.1109/ICSCEE.2018.8538429","DOIUrl":"https://doi.org/10.1109/ICSCEE.2018.8538429","url":null,"abstract":"Signal segmentation is one of the most important processes in the activity recognition process. So far, windowing approaches is one of the commonly used segmentation technique to segment the data. The window size used to segment the data usually chosen based on the previous study and the effect of the activity recognition performance with the changes of window size is still vague and uncertain. Thus, in this study, we investigate the effect of different window size in segmentation process for common sports activity recognition. The study was conducted on ten subjects who wore a sensor from Gait Up called as Physilogic OR 4 Silver inertial sensor on their chest while performing several common sports activities such as stationary, walking, jogging, sprinting, and jumping. Three common used classifiers which are Decision Trees, k-Neighbor Nearest and Support Vector Machine were evaluated. Among the different ranges of window sizes tested, it was found that 2.5 seconds window size represents the best trade-off in recognition of common sports activity, with an obtained accuracy above 90%. From the result, it indicates that the selection of window size in segmentation process can affect the accuracy in detecting the common sports activity. The preferably employed window size in detecting the common sports activity is determined.","PeriodicalId":265737,"journal":{"name":"2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123967265","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: 4

Evaluation of Feature Detectors on Repeatability Quality of Facial Keypoints In Triangulation Method 三角剖分方法中特征检测器对人脸关键点重复性质量的评价

2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE) Pub Date : 2018-07-01 DOI: 10.1109/ICSCEE.2018.8538385

A. Kusnadi, Wella, R. Winantyo, I. Z. Pane

引用次数: 4

Multi-Class Sentiment Analysis Comparison Using Support Vector Machine (SVM) and BAGGING Technique-An Ensemble Method 基于支持向量机和BAGGING技术的多类情感分析比较——一种集成方法

2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE) Pub Date : 2018-07-01 DOI: 10.1109/ICSCEE.2018.8538397

Shashank Sharma, S. Srivastava, Ashish Kumar, Abhilasha Dangi

引用次数: 9

Educational Data Mining: Classifier Comparison for the Course Selection Process 教育数据挖掘:选课过程中的分类器比较

2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE) Pub Date : 2018-07-01 DOI: 10.1109/ICSCEE.2018.8538434

S. Srivastava, Saif Karigar, R. Khanna, R. Agarwal

引用次数: 7

Automated Essay Scoring with Ontology based on Text Mining and NLTK tools 基于文本挖掘和NLTK工具的本体自动作文评分

2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE) Pub Date : 2018-07-01 DOI: 10.1109/ICSCEE.2018.8538399

Jennifer O. Contreras, Shadi M. S. Hilles, Zainab Binti Abubakar

引用次数: 18

Copy-move Image Forgery Detection Based on Gabor Descriptors and K-Means Clustering 基于Gabor描述符和K-Means聚类的复制-移动图像伪造检测

2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE) Pub Date : 2018-07-01 DOI: 10.1109/ICSCEE.2018.8538432

H. Parvez, S. Sadeghi, H. Jalab, Ala'a R. Al-Shamasneh, Diaa M. Uliyan

{"title":"Copy-move Image Forgery Detection Based on Gabor Descriptors and K-Means Clustering","authors":"H. Parvez, S. Sadeghi, H. Jalab, Ala'a R. Al-Shamasneh, Diaa M. Uliyan","doi":"10.1109/ICSCEE.2018.8538432","DOIUrl":"https://doi.org/10.1109/ICSCEE.2018.8538432","url":null,"abstract":"At present, popularity of using image as the fundamental media of information is growing. Rapid development of technology brings effective image processing tools available and makes image forgery very easy. As an outcome, it turns into a complicated issue in late time. In that case, validating the legitimacy and integrity of digital images is ending up progressively vital issue. The most challenging region-duplication forgery is made by copying some portion of an image and pasting on different region of the same image. This study proposes an efficient region-duplication forgery detection technique. This research is categorized into segment-based region duplication forgery detection method. The design of the algorithm based on image segmentation and using Gabor descriptors and K-Means clustering. Initially, the image is segmented using normalized cut (NCut) segmentation technique. Then, applied Gabor Filters to extract image features and cluster similar features using KMeans clustering algorithm. Finally, comparing the clustering regions with the given threshold value will decide image authenticity. Experiment results proves the strength of the proposed method against various post-processing attacks such as rotation, scale, blurring and JPEG compression. A comparison with existing image forgery detection algorithms demonstrates that the proposed algorithm gives better performance.","PeriodicalId":265737,"journal":{"name":"2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127222374","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: 3