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Int. J. Distributed Syst. Technol.最新文献

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MQTT-Based QoS Model for IoT-M2M Critical Applications 基于mqtt的IoT-M2M关键应用的QoS模型
Int. J. Distributed Syst. Technol. Pub Date : 2021-10-01 DOI: 10.4018/ijdst.287862
S. Barkat, A. Bilami, A. Benayache
{"title":"MQTT-Based QoS Model for IoT-M2M Critical Applications","authors":"S. Barkat, A. Bilami, A. Benayache","doi":"10.4018/ijdst.287862","DOIUrl":"https://doi.org/10.4018/ijdst.287862","url":null,"abstract":"The expeditious development of information technology provides opportunities for new remote and monitoring critical systems to be performed based on IoT technologies and M2M communications. This paper discusses important QoS issues in IoT systems and suggests a new QoS model for critical IoT applications, where each information must be delivered only once and in real-time. The proposal is based on the MQTT protocol with dynamic QoS handling, accordingly to the information importance. A prioritization scheme is adopted using different traffic classes, considering specific requirements for real-time communications and reliable operations while reducing end-to-end delay, packet loss, bandwidth, and energy consumption.","PeriodicalId":118536,"journal":{"name":"Int. J. Distributed Syst. Technol.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134552556","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
Prediction of Breast Cancer Using Extremely Randomized Clustering Forests (ERCF) Technique: Prediction of Breast Cancer 使用极端随机聚类森林(ERCF)技术预测乳腺癌:预测乳腺癌
Int. J. Distributed Syst. Technol. Pub Date : 2021-10-01 DOI: 10.4018/ijdst.287859
Akhil Gupta, Rohit Anand, D. Pandey, Nidhi Sindhwani, Subodh Wairya, B. Pandey, Manvinder Sharma
{"title":"Prediction of Breast Cancer Using Extremely Randomized Clustering Forests (ERCF) Technique: Prediction of Breast Cancer","authors":"Akhil Gupta, Rohit Anand, D. Pandey, Nidhi Sindhwani, Subodh Wairya, B. Pandey, Manvinder Sharma","doi":"10.4018/ijdst.287859","DOIUrl":"https://doi.org/10.4018/ijdst.287859","url":null,"abstract":"cancer in breast indeed a significant public health concern in both developed and developing countries female population. It is almost one in three cancers diagnosed in all women. Data mining and pattern recognition applications in conjunction have been proven to be quite useful and relevant to extract the information useful for the medical purpose. This research work reflects the work based on Extremely Randomized Clustering Forests (ERCF) technique which is nothing but a type of pattern recognition technique that may be implemented as the prediction model for Breast Cancer (BC). The accuracy achieved through ERCF has also been compared with that of k-NN(Correlation) and k-NN(Euclidean) in this research work (where k-NN refers to k-Nearest Neighbours technique) and thereafter, final conclusions have been drawn depending upon the testing attributes. The results show that the accuracy of ERCF in the forecasting of breast cancer is so much larger than that of the exactness of k-NN(Correlation) and k-NN(Euclidean). Hence, ERCF, a randomized technique for pattern classification, is best","PeriodicalId":118536,"journal":{"name":"Int. J. Distributed Syst. Technol.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115911470","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
A Survey: Plant Disease Detection Using Deep Learning 基于深度学习的植物病害检测研究综述
Int. J. Distributed Syst. Technol. Pub Date : 2021-07-01 DOI: 10.4018/IJDST.2021070101
Anshul Tripathi, Uday Chourasia, P. Dixit, Victor I. Chang
{"title":"A Survey: Plant Disease Detection Using Deep Learning","authors":"Anshul Tripathi, Uday Chourasia, P. Dixit, Victor I. Chang","doi":"10.4018/IJDST.2021070101","DOIUrl":"https://doi.org/10.4018/IJDST.2021070101","url":null,"abstract":"Agriculture occupation has been the prime occupation in India since the primeval era. Nowadays, the country is ranked second in the prime occupations threatening global warming. Apart from this, diseases in plants are challenging to this prime source of livelihood. The present research can help in recognition of different diseases among plants and help to find out the solution or remedy that can be a defense mechanism in counter to the diseases. Finding diseases among plant DL is considered to the most perfect and exact paradigms. Four labels are classified as “bacterial spot,” “yellow leaf curl virus,” “late blight,” and “healthy leaf.” An exemplar model of the drone is also designed for the purpose. The said model will be utilized for a live report for extended large crop fields. In this exemplar drone model, a high-resolution camera is attached. The captured images of plants will act as software input. On this basis, the software will immediately tell which plants are healthy and which are diseased.","PeriodicalId":118536,"journal":{"name":"Int. J. Distributed Syst. Technol.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123396886","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
Teaching Management and Monitoring Abnormal Network Behaviors Under COVID-19 新冠肺炎疫情下的教学管理与网络异常行为监测
Int. J. Distributed Syst. Technol. Pub Date : 2021-04-01 DOI: 10.4018/IJDST.2021040106
Yao Li, Ping Luo
{"title":"Teaching Management and Monitoring Abnormal Network Behaviors Under COVID-19","authors":"Yao Li, Ping Luo","doi":"10.4018/IJDST.2021040106","DOIUrl":"https://doi.org/10.4018/IJDST.2021040106","url":null,"abstract":"Due to the epidemic of COVID-19, more social activities have been moved to the internet, such as online education and online learning. The education management to avoid burst events is a basic requirement of online education, especially when a huge number of persons are visiting at the same time. In order to monitor the abnormal and burst access in online education systems, this paper proposes an anomaly detection method by using data flow to mining high frequency events among massive network traffic data during online education. First, the data flow in traffic network is described as a special structure which is used to establish an efficient high frequent event detection algorithm. Second, the network traffic flow is reduced to make it possible to monitor large-scale concurrent network visiting. The effectiveness of the abnormal network behavior detection method is verified through the experiment on a real network environment for online education.","PeriodicalId":118536,"journal":{"name":"Int. J. Distributed Syst. Technol.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114956923","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
Fatigue and Abnormal State Detection by Using EMG Signal During Football Training 基于肌电信号的足球训练疲劳与异常状态检测
Int. J. Distributed Syst. Technol. Pub Date : 2021-04-01 DOI: 10.4018/IJDST.2021040102
Chunhai Cui, Enqian Xin, Meili Qu, Shuai Jiang
{"title":"Fatigue and Abnormal State Detection by Using EMG Signal During Football Training","authors":"Chunhai Cui, Enqian Xin, Meili Qu, Shuai Jiang","doi":"10.4018/IJDST.2021040102","DOIUrl":"https://doi.org/10.4018/IJDST.2021040102","url":null,"abstract":"This paper proposes to monitor and recognize the fatigue state during football training by analyzing the surface electromyography (EMG) signals. The surface electromyography (EMG) signal is closely connected with the state during sports and training. First, power frequency interference, motion artifacts, and baseline drift in the surface electromyography (EMG) signal are removed; second, the authors extract 6 features: rectified average value (ARV), integrated electromyography myoelectric value (IEMG), root mean square of electromyography value (RMS), median frequency (MF), average power frequency (MPF), and electromyography power (TP) to represent the surface electromyography (EMG) signal; lastly, the extracted features are input into a one-class support vector machine to determine whether the player has been fatigued and are input into a weighted support vector machine to determine the degree of fatigue if the player has been fatigued. The experimental results show that more than 95% of the fatigue state can be recognized by surface electromyography (EMG) signal.","PeriodicalId":118536,"journal":{"name":"Int. J. Distributed Syst. Technol.","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132741648","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
On Detecting Abnormal Access for Online Ideological and Political Education 论网络思想政治教育异常接入的检测
Int. J. Distributed Syst. Technol. Pub Date : 2021-04-01 DOI: 10.4018/IJDST.2021040104
Yuzhu Yang
{"title":"On Detecting Abnormal Access for Online Ideological and Political Education","authors":"Yuzhu Yang","doi":"10.4018/IJDST.2021040104","DOIUrl":"https://doi.org/10.4018/IJDST.2021040104","url":null,"abstract":"With the development and spread of networks, online education has become a new way in education. The online education platform encounters a large number of concurrent visiting, while the system must guarantee network security in the process of online education. The network visiting requests are real-time and dynamic in online education. In order to detect network intrusion and abnormal access in real time and adapt to the dynamic changes of network visiting requests, this paper adopts a data stream-based network intrusion detection method to monitor and manage online education visiting. First, a knowledge library is constructed by normal visiting mode and abnormal visiting mode. Second, the dissimilarity between data point and data cluster is used to measure the similarity between normal mode and abnormal mode. Lastly, the knowledge library is updated to reflect the changes of network in online education system by re-clustering. The proposed method is evaluated on a real dataset.","PeriodicalId":118536,"journal":{"name":"Int. J. Distributed Syst. Technol.","volume":"1978 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130210286","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: 7
Edge Computing-Induced Caching Strategy for National Traditional Sports Video Resources by Considering Unusual Items 考虑异常项的民族传统体育视频资源边缘计算缓存策略
Int. J. Distributed Syst. Technol. Pub Date : 2021-04-01 DOI: 10.4018/IJDST.2021040101
Wenwen Pan, Bei Liu, Zhiliang Song
{"title":"Edge Computing-Induced Caching Strategy for National Traditional Sports Video Resources by Considering Unusual Items","authors":"Wenwen Pan, Bei Liu, Zhiliang Song","doi":"10.4018/IJDST.2021040101","DOIUrl":"https://doi.org/10.4018/IJDST.2021040101","url":null,"abstract":"In order to promote the development of national traditional sports to carry forward the spirit and culture of a country or nation, this paper designs a system for national traditional sports video distribution with the help of software-defined network and mobile edge computing technologies. Thus, the popular national traditional sports resources can be cached in mobile edge computing servers, which can reduce the delay time from cloud center directly. In order to improve the hit rate of the cached videos, the ant colony-stimulated annealing is used as the caching strategy. The experimental results show that the ant colony-stimulated annealing caching strategy can increase the hit rate of the contents in mobile edge computing servers as well as decrease the delay time of the request videos. The ant colony-stimulated annealing caching strategy performs better than previous caching strategies for updating contents in mobile edge computing servers.","PeriodicalId":118536,"journal":{"name":"Int. J. Distributed Syst. Technol.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122719819","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: 5
Abnormal Financial Transaction Detection via AI Technology 基于AI技术的异常金融交易检测
Int. J. Distributed Syst. Technol. Pub Date : 2021-04-01 DOI: 10.4018/IJDST.2021040103
Zhuo Wang
{"title":"Abnormal Financial Transaction Detection via AI Technology","authors":"Zhuo Wang","doi":"10.4018/IJDST.2021040103","DOIUrl":"https://doi.org/10.4018/IJDST.2021040103","url":null,"abstract":"Financial supervision plays an important role in the construction of anti-corruption and honesty, but financial data has the characteristics of non-stationary, non-linearity, and low signal-to-noise ratio, and there is no special training set that is used to identify abnormal financial data. This paper generates time series of financial transaction data with a weekly time span, and selects the total transaction amount, transaction dispersion coefficient, and the number of transfers as the characteristics of financial account data. The features are then input in a weighted one-class support vector machine (WOC-SVM) model to determine whether the transaction is abnormal. The weighted one-class support vector machine (WOC-SVM) is learnt on a training set which consists of massive normal transaction due to the difficulty to collect abnormal transactions. The parameters in WOC-SVM are tuned by cross-validation. The experiments on simulation data demonstrate the effectiveness of the WOC-SVM model learnt on selected features to detect suspicious values.","PeriodicalId":118536,"journal":{"name":"Int. J. Distributed Syst. Technol.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134481213","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
Recognizing the Style of Artistic Painting via Information Entropy for Smart City Construction 基于信息熵的智慧城市建设艺术绘画风格识别
Int. J. Distributed Syst. Technol. Pub Date : 2021-04-01 DOI: 10.4018/IJDST.2021040105
Xiaojie Du, Wenhao Wang
{"title":"Recognizing the Style of Artistic Painting via Information Entropy for Smart City Construction","authors":"Xiaojie Du, Wenhao Wang","doi":"10.4018/IJDST.2021040105","DOIUrl":"https://doi.org/10.4018/IJDST.2021040105","url":null,"abstract":"Digitalization is conducive to the protection and inheritance of culture and civilization. The artistic painting recognition is an essential part in digitalization and plays an important role in smart city construction. This paper proposes a novel framework to recognize Chinese painting style by using information entropy. First, the authors choose the ink painting, pyrography, mural, and splash ink painting as the known artistic styles. Then, this article uses the information entropy to represent the paintings. The information entropy includes color entropy, block entropy, and contour entropy. The color entropy is obtained by a weighted function of Channel A and B in the lab color space. The block entropy is the average information entropy of blocks which are a small part of the image. The contour entropy is obtained from the contour information which is obtained by contourlet transform. The information entropy is input into an oracle to determine the style. The oracle includes a one-class classifier and a classical classifier. The effectiveness is verified on the real painting set.","PeriodicalId":118536,"journal":{"name":"Int. J. Distributed Syst. Technol.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117083363","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
A Levy Flight Sine Cosine Algorithm for Global Optimization Problems 一种求解全局优化问题的Levy飞行正弦余弦算法
Int. J. Distributed Syst. Technol. Pub Date : 2021-01-01 DOI: 10.4018/ijdst.2021010104
Yu Li, Yiran Zhao, Jingsen Liu
{"title":"A Levy Flight Sine Cosine Algorithm for Global Optimization Problems","authors":"Yu Li, Yiran Zhao, Jingsen Liu","doi":"10.4018/ijdst.2021010104","DOIUrl":"https://doi.org/10.4018/ijdst.2021010104","url":null,"abstract":"The sine cosine algorithm (SCA) is a recently proposed global swarm intelligence algorithm based on mathematical functions. This paper proposes a Levy flight sine cosine algorithm (LSCA) to solve optimization problems. In the update equation, the levy flight is introduced to improve optimization ability of SCA. By generating a random walk to update the position, this strategy can effectively search for particles to maintain better population diversity. LSCA has been tested 15 benchmark functions and real-world engineering design optimization problems. The result of simulation experiments with LSCA, SCA, PSO, FPA, and other improvement SCA show that the LSCA has stronger robustness and better convergence accuracy. The engineering problems are also shown that the effectiveness of the levy flight sine cosine algorithm to ensure the efficient results in real-world optimization problem.","PeriodicalId":118536,"journal":{"name":"Int. J. Distributed Syst. Technol.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127313625","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
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