World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering最新文献
Pub Date : 2018-01-01DOI: 10.17706/IJCCE.2018.7.4.136-144
J. P. Lousado, A. Cruz, Sandra Antunes
{"title":"SPOTur—Tourists Protection and Orientation System in Inhospitable Environments","authors":"J. P. Lousado, A. Cruz, Sandra Antunes","doi":"10.17706/IJCCE.2018.7.4.136-144","DOIUrl":"https://doi.org/10.17706/IJCCE.2018.7.4.136-144","url":null,"abstract":"","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":"136-144"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74866093","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}
Pub Date : 2018-01-01DOI: 10.17706/IJCCE.2018.7.4.119-127
Guoping Chen, C. Telecommunications, Gonghai Yang
Power line communication (PLC) systems are contaminated with complicated noise. Five types of noise in power line communication systems are introduced in this paper. According to their properties, these noises are mainly divided into two types that are background noise and impulsive noise. Noise modelling approaches for background noise and impulsive noise are reviewed in this paper. A frequency-domain based model is applied to describe the properties of background noise and a frequency decreasing power spectral density (PSD) is revealed based on this model. The values of PSD are between -140dBm/Hz and -80dBm/Hz. A time-domain approach which is based on partitioned Markov chain is applied to describe the time behaviour of impulsive noise. Simulation results showed this model is suitable for the description and modelling of impulsive noise. This model revealed that impulsive noise rarely exceeds a few milliseconds.
{"title":"Empirical Noise Modelling in Power Line Communication Systems","authors":"Guoping Chen, C. Telecommunications, Gonghai Yang","doi":"10.17706/IJCCE.2018.7.4.119-127","DOIUrl":"https://doi.org/10.17706/IJCCE.2018.7.4.119-127","url":null,"abstract":"Power line communication (PLC) systems are contaminated with complicated noise. Five types of noise in power line communication systems are introduced in this paper. According to their properties, these noises are mainly divided into two types that are background noise and impulsive noise. Noise modelling approaches for background noise and impulsive noise are reviewed in this paper. A frequency-domain based model is applied to describe the properties of background noise and a frequency decreasing power spectral density (PSD) is revealed based on this model. The values of PSD are between -140dBm/Hz and -80dBm/Hz. A time-domain approach which is based on partitioned Markov chain is applied to describe the time behaviour of impulsive noise. Simulation results showed this model is suitable for the description and modelling of impulsive noise. This model revealed that impulsive noise rarely exceeds a few milliseconds.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"97 1","pages":"119-127"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74984389","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}
Pub Date : 2018-01-01DOI: 10.17706/IJCCE.2018.7.4.189-194
S. Elhamayed, Cairo Egypt Eri
Nowadays, people and companies use emails for information exchange, email messages, and etc., because they are the fastest and the cheapest way. The main problem that faces email messages is the undesirable emails which known as spams. Spams may cause overflow the internet with considerable copies of the same message or carry malicious content that harms user system and reduce the performance. The purpose of this work is to make a comparative study of several classification techniques on the basis of their performance parameters using spam dataset. The performance of the different classifiers is measured with different ratio of the testing and training dataset. Also, the performance of the classifiers is calculated with and without low variance filter. By applying the low variance filter the accuracy of the KNN classifier is enhanced with about 9% while the accuracy of the other classifier is decreased.
{"title":"Comparative Study on Different Classification Techniques for Spam Dataset","authors":"S. Elhamayed, Cairo Egypt Eri","doi":"10.17706/IJCCE.2018.7.4.189-194","DOIUrl":"https://doi.org/10.17706/IJCCE.2018.7.4.189-194","url":null,"abstract":"Nowadays, people and companies use emails for information exchange, email messages, and etc., because they are the fastest and the cheapest way. The main problem that faces email messages is the undesirable emails which known as spams. Spams may cause overflow the internet with considerable copies of the same message or carry malicious content that harms user system and reduce the performance. The purpose of this work is to make a comparative study of several classification techniques on the basis of their performance parameters using spam dataset. The performance of the different classifiers is measured with different ratio of the testing and training dataset. Also, the performance of the classifiers is calculated with and without low variance filter. By applying the low variance filter the accuracy of the KNN classifier is enhanced with about 9% while the accuracy of the other classifier is decreased.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"27 1","pages":"189-194"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87651375","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}
Pub Date : 2018-01-01DOI: 10.17706/IJCCE.2018.7.3.68-84
Hamed Hamzeh, Sofia Meacham, B. Virginas, Keith Phalp
Cloud computing is a paradigm that has become popular in recent decade. The flexibility, scalability, elasticity, inexpensive and unlimited use of resources have made the cloud an efficient and valuable infrastructure for many organizations to perform their computational operations. Specifically, the elasticity feature of cloud computing leads to the increase of complexity of this technology . Considering the emergence of new technologies and user demands, the existing solutions are not suitable to satisfy the huge volume of data and user requirements. Moreover, certain quality requirements that have to be met for efficient resource provisioning such as Quality of Service (QoS) is an obstacle to scalability. Hence, autonomic computing has emerged as a highly dynamic solution for complex administration issues that goes beyond simple automation to self-learning and highly-adaptable systems. Therefore, the combination of cloud computing and autonomics known as Autonomic Cloud Computing (ACC) seems a natural progression for both areas. This paper is an overview of the latest conducted research in ACC and the corresponding software engineering techniques. Additionally, existing autonomic applications, methods and their use cases in cloud computing environment are also investigated.
{"title":"Taxonomy of Autonomic Cloud Computing","authors":"Hamed Hamzeh, Sofia Meacham, B. Virginas, Keith Phalp","doi":"10.17706/IJCCE.2018.7.3.68-84","DOIUrl":"https://doi.org/10.17706/IJCCE.2018.7.3.68-84","url":null,"abstract":"Cloud computing is a paradigm that has become popular in recent decade. The flexibility, scalability, elasticity, inexpensive and unlimited use of resources have made the cloud an efficient and valuable infrastructure for many organizations to perform their computational operations. Specifically, the elasticity feature of cloud computing leads to the increase of complexity of this technology . Considering the emergence of new technologies and user demands, the existing solutions are not suitable to satisfy the huge volume of data and user requirements. Moreover, certain quality requirements that have to be met for efficient resource provisioning such as Quality of Service (QoS) is an obstacle to scalability. Hence, autonomic computing has emerged as a highly dynamic solution for complex administration issues that goes beyond simple automation to self-learning and highly-adaptable systems. Therefore, the combination of cloud computing and autonomics known as Autonomic Cloud Computing (ACC) seems a natural progression for both areas. This paper is an overview of the latest conducted research in ACC and the corresponding software engineering techniques. Additionally, existing autonomic applications, methods and their use cases in cloud computing environment are also investigated.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"27 1","pages":"68-84"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74787118","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}
Pub Date : 2018-01-01DOI: 10.17706/IJCCE.2018.7.4.167-177
Thirachit Saenphon
{"title":"Enhancing Particle Swarm Optimization Using Opposite Gradient Search for Travelling Salesman Problem","authors":"Thirachit Saenphon","doi":"10.17706/IJCCE.2018.7.4.167-177","DOIUrl":"https://doi.org/10.17706/IJCCE.2018.7.4.167-177","url":null,"abstract":"","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"60 1","pages":"167-177"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74107226","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}
Pub Date : 2018-01-01DOI: 10.17706/IJCCE.2018.7.2.8-19
Xin Jin, B. Economics, Hu Yang
To study the forms and causes of the evolution of network public opinion for emergency events, this paper uses the public opinion of 8.12 accident of Tianjin Port explosion in 2015 as the sample to evaluation the correlations between chacteristics of weibos about 8.12 accident and analyze sentiments of all periods of public opinion using SVM during the life cycle of public opinion. This paper discusses influence factors which influence the evolution of the public opinion and how to interact with each other from four dimensions (government, media, opinion leaders, Internet users). At last this paper proposes corresponding advices.
{"title":"Research on Evolution Mechanism and Sentiment Analysis of Emergency Network Public Opinion","authors":"Xin Jin, B. Economics, Hu Yang","doi":"10.17706/IJCCE.2018.7.2.8-19","DOIUrl":"https://doi.org/10.17706/IJCCE.2018.7.2.8-19","url":null,"abstract":"To study the forms and causes of the evolution of network public opinion for emergency events, this paper uses the public opinion of 8.12 accident of Tianjin Port explosion in 2015 as the sample to evaluation the correlations between chacteristics of weibos about 8.12 accident and analyze sentiments of all periods of public opinion using SVM during the life cycle of public opinion. This paper discusses influence factors which influence the evolution of the public opinion and how to interact with each other from four dimensions (government, media, opinion leaders, Internet users). At last this paper proposes corresponding advices.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"77 1","pages":"8-19"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74274411","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}
Pub Date : 2018-01-01DOI: 10.17706/ijcce.2018.7.4.107-118
Chengdong Wang, Xin Yang, Yong Feng, M. Tang
Sink relocation has been proven as an effective solution to relieve the network hot point problem, and to balance nodes’ energy consumption and thus prolong the network lifetime for wireless sensor networks. In this paper, we propose a Virtual Force based Sink Relocation strategy, called VFSR, which utilizes the resultant force derived from two kinds of virtual force, gravitational one and border repulsive one, to impel the sink node to relocate to the desired position. In VFSR, the gravitational force exists between each sensor and the sink, and is proportional to the node’s residual energy and inversely proportional to the distance from the node to the sink. The border repulsive force is adapted to avoid the sink node wandering nearby the network border. Under the action of the gravitational and the border repulsive force, the sink node approaches the nodes with high residual energy and makes them relay data from other nodes, which reduces data transmission overload of the nodes with low energy. Through simulation, we validate the effectiveness of VFSR.
{"title":"Virtual Force Based Sink Relocation Strategy in Wireless Sensor Networks","authors":"Chengdong Wang, Xin Yang, Yong Feng, M. Tang","doi":"10.17706/ijcce.2018.7.4.107-118","DOIUrl":"https://doi.org/10.17706/ijcce.2018.7.4.107-118","url":null,"abstract":"Sink relocation has been proven as an effective solution to relieve the network hot point problem, and to balance nodes’ energy consumption and thus prolong the network lifetime for wireless sensor networks. In this paper, we propose a Virtual Force based Sink Relocation strategy, called VFSR, which utilizes the resultant force derived from two kinds of virtual force, gravitational one and border repulsive one, to impel the sink node to relocate to the desired position. In VFSR, the gravitational force exists between each sensor and the sink, and is proportional to the node’s residual energy and inversely proportional to the distance from the node to the sink. The border repulsive force is adapted to avoid the sink node wandering nearby the network border. Under the action of the gravitational and the border repulsive force, the sink node approaches the nodes with high residual energy and makes them relay data from other nodes, which reduces data transmission overload of the nodes with low energy. Through simulation, we validate the effectiveness of VFSR.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"47 1","pages":"107-118"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85474499","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}
Pub Date : 2018-01-01DOI: 10.17706/ijcce.2018.7.1.1-7
Jen-Ho Yang, I. Lin, Po-Ching Chien
As the population of cloud service, more and more people concerns the privacy and security of cloud service. Therefore, an ID-based group key agreement scheme is proposed. In this paper, the group key agreement scheme is applied to the access control of cloud service. For achieving the access control and the privacy of data, the data owner can determine who can decrypt the encrypted data. In the aspect of computation cost, the bilinear pairing is used to compute the session key and the symmetric encryption is used to encrypt data in the scheme because of the bilinear pairing and symmetric encryption have lower computation cost than others. In the aspect of security, the scheme proposed in this paper not only can assist two attacks: impersonation attack and man-in-the-middle attack, but also can satisfy four security attributes: known-key security, key control, unknown key-share and key compromise impersonation.
{"title":"An ID-Based Group Key Agreement Scheme for Controlling Access and Privacy in Cloud","authors":"Jen-Ho Yang, I. Lin, Po-Ching Chien","doi":"10.17706/ijcce.2018.7.1.1-7","DOIUrl":"https://doi.org/10.17706/ijcce.2018.7.1.1-7","url":null,"abstract":"As the population of cloud service, more and more people concerns the privacy and security of cloud service. Therefore, an ID-based group key agreement scheme is proposed. In this paper, the group key agreement scheme is applied to the access control of cloud service. For achieving the access control and the privacy of data, the data owner can determine who can decrypt the encrypted data. In the aspect of computation cost, the bilinear pairing is used to compute the session key and the symmetric encryption is used to encrypt data in the scheme because of the bilinear pairing and symmetric encryption have lower computation cost than others. In the aspect of security, the scheme proposed in this paper not only can assist two attacks: impersonation attack and man-in-the-middle attack, but also can satisfy four security attributes: known-key security, key control, unknown key-share and key compromise impersonation.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"24 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89439634","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}
This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.
提出了一种基于深度学习算法的心音正常与异常自动分类模型。本研究使用MITHSDB心音数据集，数据集来自2016年PhysioNet/Computing in Cardiology Challenge数据库，假设心电图(ECG)与心音(PCG)同时记录。将PCG时间序列按每次心跳进行分割，并将每个子片段转换成一个平方强度矩阵，使用卷积神经网络(CNN)模型进行分类。这种方法消除了为监督机器学习算法提供分类特征的需要。相反，这些特征是通过训练从提供的时间序列中自动确定的。结果表明，该预测模型实现简单，分类精度合理，具有可比性。该方法可用于医疗物联网(IoMT)中心音的实时分类，如PCG信号的远程监测应用。
{"title":"Automatic Classification of Periodic Heart Sounds Using Convolutional Neural Network","authors":"Jia Xin Low, K. W. Choo","doi":"10.5281/ZENODO.1315910","DOIUrl":"https://doi.org/10.5281/ZENODO.1315910","url":null,"abstract":"This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"53 1","pages":"96-101"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89341348","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}
Pub Date : 2017-12-12DOI: 10.17706/IJCCE.2017.6.3.151-160
Hamed Hamzeh, Mahdi Hemmati, S. Shirmohammadi
{"title":"Bandwidth allocation with fairness in multimedia networks","authors":"Hamed Hamzeh, Mahdi Hemmati, S. Shirmohammadi","doi":"10.17706/IJCCE.2017.6.3.151-160","DOIUrl":"https://doi.org/10.17706/IJCCE.2017.6.3.151-160","url":null,"abstract":"","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"44 1","pages":"151-160"},"PeriodicalIF":0.0,"publicationDate":"2017-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81042041","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}
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