World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering最新文献_第5页

Deep Tweets Analyzer Model for Twitter Mood Visualization and Prediction Based Deep Learning Approach 基于深度学习方法的推特情绪可视化和预测的深度推特分析器模型

World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering Pub Date : 2019-01-01 DOI: 10.17706/IJCCE.2019.8.1.1-17

Maha Al-Ghalibi, Adil Al-Azzawi, K. Lawonn

{"title":"Deep Tweets Analyzer Model for Twitter Mood Visualization and Prediction Based Deep Learning Approach","authors":"Maha Al-Ghalibi, Adil Al-Azzawi, K. Lawonn","doi":"10.17706/IJCCE.2019.8.1.1-17","DOIUrl":"https://doi.org/10.17706/IJCCE.2019.8.1.1-17","url":null,"abstract":"In many of today’s big data analytics applications, it might need to analyze social media feeds as well as to visualize users’ opinions. This will provide a viable alternative source to establish new metrics in our digital life. Social interaction with people in Twitter is open-ended, making media analysis in Twitter easier in comparison with other social media. That is because the interaction in those media is often different since most of them are private. This work is therefore devoted to focus merely on design and implementation a Deep model for Twitter opinion (Mood) visualization based Deep Learning network. It is concerned with Natural Language Processing (NLP)-based sentiment analysis and Deep Learning framework for Twitter’s opinion mining visualization and classification. The utilized methodology is based on applying sentiment analysis NLP on a large number of tweets in order to visualize the predicted mood scoring of the tweet and thus to exploit public tweeting for knowledge discovery. This will moreover serve for fake news detection. The pertinent mechanism involves several consecutive steps, namely: dataset collection stage, the pre-processing stage, NLP stage, sentiment analysis stage, and prediction and classification stage using Deep Learning Model. The U.S. Airlines Sentiment Analysis Twitter dataset has been utilized which is already provided with Data for Everyone. The presented system is monitoring Twitter streams from both the media and the public. It is capable to visualize and extract meaningful data from tweets in real-time and store them into a Deep model for analysis. It is convenient for a wide application spectrum involving: big data analytics solutions, predicting e-commerce customer’s behavior, improving marketing strategy, getting market competitive advantages, besides visualization in various data mining applications.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"72 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85838969","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

Research on an Adaptive Maneuvering Target Tracking Algorithm 一种自适应机动目标跟踪算法研究

World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering Pub Date : 2019-01-01 DOI: 10.17706/ijcce.2019.8.2.50-59

X. Zhu, J. Yang, Y. Li

{"title":"Research on an Adaptive Maneuvering Target Tracking Algorithm","authors":"X. Zhu, J. Yang, Y. Li","doi":"10.17706/ijcce.2019.8.2.50-59","DOIUrl":"https://doi.org/10.17706/ijcce.2019.8.2.50-59","url":null,"abstract":"The maneuverability of modern targets becomes more and more complex and variable, which raises higher requirements on the tracking performance of detection systems. Especially the stable and accurate tracking of maneuvering targets is more critical. For the problem that statistical properties of detection system noise are unknown and the state of motion of targets is complex and variable, a new adaptive maneuvering target tracking algorithm is proposed. The algorithm adopts the combination of adaptive Kalman filtering under the spherical coordinate system and its counterpart under the Cartesian coordinate system. The adaptive Kalman filtering algorithm under the spherical coordinate system is based on Sage-Husa noise statistics estimator to estimate the statistical property of measurement noise. In the Cartesian coordinate system, the Singer model is used to describe the target motion. Relevant results of the adaptive Kalman filtering algorithm under the spherical coordinate system are used to achieve high-precision estimation of target motion information. Simulation results show that the proposed algorithm has satisfactory tracking accuracy.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87431919","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: 1

Review and Prospect of the Development of Multi-beam Reflector Antennas 多波束反射天线的发展回顾与展望

World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering Pub Date : 2019-01-01 DOI: 10.17706/ijcce.2019.8.4.184-194

Hongge Wei, Zhengjun Li

引用次数: 0

Sliding Mode Control of an Internet Teleoperated PUMA 600 Robot 互联网遥控PUMA 600机器人的滑模控制

World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering Pub Date : 2018-03-01 DOI: 10.5281/zenodo.1316313

A. Ghoul, B. Ouamri, I. K. Bousserhane

引用次数: 0

Intelligent Anomaly Detection Techniques for Denial of Service Attacks 拒绝服务攻击的智能异常检测技术

World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering Pub Date : 2018-01-01 DOI: 10.17706/IJCCE.2018.7.2.20-31

V. C. Gungor, Z. Aydın, Ramazan Karademir

{"title":"Intelligent Anomaly Detection Techniques for Denial of Service Attacks","authors":"V. C. Gungor, Z. Aydın, Ramazan Karademir","doi":"10.17706/IJCCE.2018.7.2.20-31","DOIUrl":"https://doi.org/10.17706/IJCCE.2018.7.2.20-31","url":null,"abstract":"To construct and evaluate intrusion detection, system researchers are limited to only a few available public datasets unless they prepare their own. Although the most prevalent KDDCUP’99 dataset provides a comparative analysis among researchers, the community needs a new dataset which reflects new attack types in current high-speed networks. The aim of this study is to prepare a new alternative dataset for the community for detection of denial of service attacks and to conduct performance analysis of different data mining methods on this dataset. To develop the dataset, distributed DoS attacks have been generated that target a commercial website in a real network environment, which has a million of users from all over the world. In addition to this, a richer attack dataset has been produced in a laboratory environment with the help of Labris Networks. After capturing data, significant network features have been identified and processed and labeled with related attack types. Furthermore, the performances of different data mining techniques have been evaluated, including binary classification, multi-class classification, outlier detection, feature selection methods and hybrid approaches with our dataset by using the following algorithms: K-Means clustering, Naïve Bayes, Decision Tree, Multilayer Perceptron, LibSVM, Random Forest and Random Tree.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"1 1","pages":"20-31"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87001243","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: 1

Improved Fuzzy Connectedness Segmentation Method for Medical Images with Multiple Seeds in MRI 磁共振多种子医学图像的改进模糊连通性分割方法

World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering Pub Date : 2018-01-01 DOI: 10.17706/ijcce.2018.7.3.32-44

Yunping Zheng, Tong Chang, M. Sarem

{"title":"Improved Fuzzy Connectedness Segmentation Method for Medical Images with Multiple Seeds in MRI","authors":"Yunping Zheng, Tong Chang, M. Sarem","doi":"10.17706/ijcce.2018.7.3.32-44","DOIUrl":"https://doi.org/10.17706/ijcce.2018.7.3.32-44","url":null,"abstract":"Image segmentation is a key step in medical image processing, since it affects the quality of the medical image in the follow-up steps. However, in the practice of processing MRI images, we find out that the segmentation process involves much difficulty due to the poorly defined boundaries of medical images, meanwhile, there are usually more than one target area. In this study, an improved algorithm based on the fuzzy connectedness framework for medical image is developed. The improved algorithm has involved an adaptive fuzzy connectedness segmentation combined with multiple seeds selection. Also, the algorithm can effectively overcome many problems when manual selection is used, such as the un-precise result of each target region segmented of the medical image and the difficulty of completion the segmentation when the areas are not connected. For testing the proposed method, some original real images, taken from a large hospital, were analyzed. The results have been evaluated with some rules, such as Dice’s coefficient, over segmentation rate, and under segmentation rate. The results show that the proposed method has an ideal segmentation boundary on medical images, meanwhile, it has a low time cost. In conclusion, the proposed method is superior to the traditional fuzzy connectedness segmentation methods for medical images.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"107 1","pages":"32-44"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85508261","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

A Collaborative Platform Featuring Visibility, Tracking, Monitoring and Awareness for Building Security In. 一个具有可见性、跟踪、监控和意识的建筑安全协作平台。

World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering Pub Date : 2018-01-01 DOI: 10.17706/IJCCE.2018.7.4.145-166

H. Herath, G. Wimalaratne

{"title":"A Collaborative Platform Featuring Visibility, Tracking, Monitoring and Awareness for Building Security In.","authors":"H. Herath, G. Wimalaratne","doi":"10.17706/IJCCE.2018.7.4.145-166","DOIUrl":"https://doi.org/10.17706/IJCCE.2018.7.4.145-166","url":null,"abstract":"Software developed referring to a poor design often causes the introduction of security issues which could spread into other phases of the Software Development Life Cycle if not address in the initial stages. This could lead to major security breaches and loss of valuable assets to the consumers. Identifying and fixing security issues as early as possible in a software product is the most cost-effective way of implementing software security. This research proposes a proactive approach to build security into the product itself with the aid of a new tool developed as a proof of concept. The proposed semi-automatic tool will address limitations in current approaches to secure software engineering when developing a software product by providing visibility, tracking, awareness, and progress monitoring. Additionally Developers, Architects, QA, BA, and Management, as well as the Users, can participate in the Threat Modeling and architectural security analysis contributing their input for Security Engineering with the support provided by the tool as an interactive platform, a knowledge base and as an integration platform. The Microsoft Threat Modeling Tool is being used to generate the threat models. The tool extracts threat model information and produces detailed mitigations using known vulnerability databases and classification techniques. Developers can better understand the potential threats, vulnerabilities when coding and integration functionality with a Project Management Tool can provide visibility and tracking of Building Security In throughout SDLC.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"29 1","pages":"145-166"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82287360","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

Time of Arrival (TOA) Based Radiolocation Architecture in CDMA Systems and Its Performance Analysis 基于到达时间(TOA)的CDMA系统无线定位体系结构及其性能分析

World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering Pub Date : 2018-01-01 DOI: 10.17706/IJCCE.2018.7.3.85-97

Abir Ahmed, Tamim Hossain, Kefayet Ullah, M. Kabir

引用次数: 2

TIP EXPRESS: An Android School Navigation Application 提示EXPRESS: Android学校导航应用程序

World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering Pub Date : 2018-01-01 DOI: 10.17706/IJCCE.2018.7.3.98-106

Reynaldo E. Castillo, Cubao Quezon City Metro Manila Philippines Aurora Boulevard, Paula Jean M. Castro, M. C. Aragon, Henry C. Macugay

{"title":"TIP EXPRESS: An Android School Navigation Application","authors":"Reynaldo E. Castillo, Cubao Quezon City Metro Manila Philippines Aurora Boulevard, Paula Jean M. Castro, M. C. Aragon, Henry C. Macugay","doi":"10.17706/IJCCE.2018.7.3.98-106","DOIUrl":"https://doi.org/10.17706/IJCCE.2018.7.3.98-106","url":null,"abstract":"Unfamiliarity about the school campus grounds results common problems for new students or visitors. They tend to get lost inside the campus, arrive late in classes or meetings. They navigate by themselves and ask security personnel, still they tend to take time to reach their destination or most often they get lost. This study is for new students and visitors. It helps them to explore and navigate the campus grounds thru a mobile application. The mobile application provides a user-friendly interface which considers user experience. The mobile application serves as a guiding tool in navigating around the school campus grounds. In the study, the mobile application used Google Map to track the current location of the user and plot the route from the origin to the destination inside the Technological Institute of the Philippines Quezon City campus using fuzzy logic algorithm to get the shortest route and channel selection algorithm to get the nearby user within a perimeter. The study used the Rapid Application Development model in order to deliver expected outputs. Surveys using a questioner drafted from ISO 25010 were conducted to determine the effectiveness of the developed mobile application in terms of its functionality, reliability and efficiency. It was concluded that the mobile application is an effective tool in giving navigation and campus information for its users. For the result, the average mean of all the criteria yields 4.12 interpreted as very effective using the 5 point Likert’s Scale. Thus, the mobile application is useful reliable, functional, and efficient to serve its purpose.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"7 1","pages":"98-106"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78473555","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

Contextual Feature Weighting Using Knowledge beyond the Repository Knowledge 使用知识库知识以外的知识进行上下文特征加权

World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering Pub Date : 2018-01-01 DOI: 10.17706/IJCCE.2018.7.3.45-57

Kazem Qazanfari, Abdou Youssef

{"title":"Contextual Feature Weighting Using Knowledge beyond the Repository Knowledge","authors":"Kazem Qazanfari, Abdou Youssef","doi":"10.17706/IJCCE.2018.7.3.45-57","DOIUrl":"https://doi.org/10.17706/IJCCE.2018.7.3.45-57","url":null,"abstract":"Bag of words, bigram, or more complex combinations of words are the most among general and widely used features in text classification. However, in almost all real-world text classification problems, the distribution of the available training dataset for each class often does not match the real distribution of the class concept, which reduces the accuracy of the classifiers. Let W(f) and R(f) be the discriminating power of feature f based on the world knowledge and the repository knowledge, respectively. In an ideal situation, W(f) = R(f) is desirable; however, in most situations, W(f) and R(f) are not equal and sometimes they are quite different, because the repository knowledge and the world knowledge do not have the same statistics about the discriminating power of feature f. In this paper, this phenomenon is called inadequacy of knowledge and we show how this phenomenon could reduce the performance of the text classifiers. To solve this issue, a novel feature weighting method is proposed which combines two bodies of knowledge, world knowledge and repository knowledge, using a particular transformation T. In this method, if both the world knowledge and the repository knowledge indicate a significantly high (resp., low) discriminating power of feature f, the weight of this feature is increased (resp., decreased); otherwise, the weight of the feature will be determined by a linear combination of the two weights. Experimental results show that the performance of classifiers like SVM, KNN and Bayes improves significantly if the proposed feature weighting method is applied on the contextual features such as bigram and unigram. It is shown also that pruning some words from the dataset using the proposed feature weighting method could improve the performance of the text classifier when the feature sets are created using Doc2vec.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"32 1","pages":"47-57"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90455634","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: 1