Pub Date : 2023-01-01DOI: 10.1504/ijguc.2023.131004
Zhi Li, Yuemeng Ge, Min Jia, Yanrui Xu
The purpose is to deal with the network security problems in the background of the high information age, ensure the popularisation of Internet of things (IoT) technology based on Internet technology, and protect the information, life and property security of countries and individuals. First, the principle and advantages of edge computing and deep learning technology are described. Then, the current laws of IoT data protection are introduced, and the moral and ethical issues involved in IoT data are discussed. Finally, the research results of cyberspace governance in China and Europe are studied. The results show that the respondents who do not know anything about the data protection regulations and do not focus on the regulations are 27% and 18%, respectively.
{"title":"Data protection of internet of things for edge computing and deep learning and governance of cyberspace","authors":"Zhi Li, Yuemeng Ge, Min Jia, Yanrui Xu","doi":"10.1504/ijguc.2023.131004","DOIUrl":"https://doi.org/10.1504/ijguc.2023.131004","url":null,"abstract":"The purpose is to deal with the network security problems in the background of the high information age, ensure the popularisation of Internet of things (IoT) technology based on Internet technology, and protect the information, life and property security of countries and individuals. First, the principle and advantages of edge computing and deep learning technology are described. Then, the current laws of IoT data protection are introduced, and the moral and ethical issues involved in IoT data are discussed. Finally, the research results of cyberspace governance in China and Europe are studied. The results show that the respondents who do not know anything about the data protection regulations and do not focus on the regulations are 27% and 18%, respectively.","PeriodicalId":44878,"journal":{"name":"International Journal of Grid and Utility Computing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135783854","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}
{"title":"An enhanced human learning optimisation algorithm for effective data clustering","authors":"Jigyasa Goyal, Yugal Kumar, Pardeep Kumar, Arvinder Kaur","doi":"10.1504/ijguc.2023.10060384","DOIUrl":"https://doi.org/10.1504/ijguc.2023.10060384","url":null,"abstract":"","PeriodicalId":44878,"journal":{"name":"International Journal of Grid and Utility Computing","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135613878","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 : 2023-01-01DOI: 10.1504/ijguc.2023.133436
Yingjun He, Wenhui Ouyang, Shaolong Li, Lin Wang, Jing Zhou, Wenwei Su, Shenzhang Li, Donghui Mei, Yan Shi, Yanxu Jin, Chenglin Li, Yonghui Ren
{"title":"Cloud computing data privacy protection method based on blockchain","authors":"Yingjun He, Wenhui Ouyang, Shaolong Li, Lin Wang, Jing Zhou, Wenwei Su, Shenzhang Li, Donghui Mei, Yan Shi, Yanxu Jin, Chenglin Li, Yonghui Ren","doi":"10.1504/ijguc.2023.133436","DOIUrl":"https://doi.org/10.1504/ijguc.2023.133436","url":null,"abstract":"","PeriodicalId":44878,"journal":{"name":"International Journal of Grid and Utility Computing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135497214","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 : 2023-01-01DOI: 10.1504/ijguc.2023.133404
Munir Naveed, Yasir Javed, Muhammed Adnan, Israr Ahmed
Inventory control problem is faced by companies on a daily basis to optimise the supply chain process and for predicting the optimal pricing for the item sales or for providing services. The problem is heavily dependent on a key factor, i.e., demand variations. Inventories must be aligned according to demand variations to avoid overheads or shortages. This work focuses on exploring various machine learning algorithms to solve demand variation problem in real-time. Prediction of demand variations is a complex and non-trivial problem, particularly in the presence of open order. In this work, prediction of demand variation is addressed with the use-cases which are characterised with open orders. This work also presents a novel prediction model which is a hybrid of learning domains as well as domain specific parameters. It exploits the use of Internet of Things (IoT) to extract domain specific knowledge while a reinforcement learning technique is used for predicting the variations in these domain specific parameters which depend on demand variations. The new model is explored and compared with state-of-the-art machine learning algorithms using Grupo Bimbo case study. The results show that new model predicts the demand variations with significantly higher accuracy as compared to other models.
{"title":"Collaborative ambient intelligence-based demand variation prediction model","authors":"Munir Naveed, Yasir Javed, Muhammed Adnan, Israr Ahmed","doi":"10.1504/ijguc.2023.133404","DOIUrl":"https://doi.org/10.1504/ijguc.2023.133404","url":null,"abstract":"Inventory control problem is faced by companies on a daily basis to optimise the supply chain process and for predicting the optimal pricing for the item sales or for providing services. The problem is heavily dependent on a key factor, i.e., demand variations. Inventories must be aligned according to demand variations to avoid overheads or shortages. This work focuses on exploring various machine learning algorithms to solve demand variation problem in real-time. Prediction of demand variations is a complex and non-trivial problem, particularly in the presence of open order. In this work, prediction of demand variation is addressed with the use-cases which are characterised with open orders. This work also presents a novel prediction model which is a hybrid of learning domains as well as domain specific parameters. It exploits the use of Internet of Things (IoT) to extract domain specific knowledge while a reinforcement learning technique is used for predicting the variations in these domain specific parameters which depend on demand variations. The new model is explored and compared with state-of-the-art machine learning algorithms using Grupo Bimbo case study. The results show that new model predicts the demand variations with significantly higher accuracy as compared to other models.","PeriodicalId":44878,"journal":{"name":"International Journal of Grid and Utility Computing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135497727","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 : 2023-01-01DOI: 10.1504/ijguc.2023.10059539
Vishal Sharma, Niranjan Lal, Anand Sharma
{"title":"Performance evaluation using throughput and latency of a blockchain-enabled patient centric secure and privacy preserve EHR-based on IPFS","authors":"Vishal Sharma, Niranjan Lal, Anand Sharma","doi":"10.1504/ijguc.2023.10059539","DOIUrl":"https://doi.org/10.1504/ijguc.2023.10059539","url":null,"abstract":"","PeriodicalId":44878,"journal":{"name":"International Journal of Grid and Utility Computing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135953592","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 : 2022-01-01DOI: 10.1504/ijguc.2022.10049080
Yueyun Shao, Xiaohua Huang
{"title":"The use of interactive data visualisation technology in cultural digital heritage display using edge computing","authors":"Yueyun Shao, Xiaohua Huang","doi":"10.1504/ijguc.2022.10049080","DOIUrl":"https://doi.org/10.1504/ijguc.2022.10049080","url":null,"abstract":"","PeriodicalId":44878,"journal":{"name":"International Journal of Grid and Utility Computing","volume":"1 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66888295","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 : 2022-01-01DOI: 10.1504/ijguc.2022.10058205
M. Prasad, B. Madhavi
{"title":"Design and fabrication of dual band AMC-backed monopole antenna for WLAN and WiFi applications","authors":"M. Prasad, B. Madhavi","doi":"10.1504/ijguc.2022.10058205","DOIUrl":"https://doi.org/10.1504/ijguc.2022.10058205","url":null,"abstract":"","PeriodicalId":44878,"journal":{"name":"International Journal of Grid and Utility Computing","volume":"22 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66888432","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 : 2022-01-01DOI: 10.1504/ijguc.2022.10047657
Ricardo Rodriguez Jorge
{"title":"Rotating machinery fault diagnosis using a quadratic neural unit","authors":"Ricardo Rodriguez Jorge","doi":"10.1504/ijguc.2022.10047657","DOIUrl":"https://doi.org/10.1504/ijguc.2022.10047657","url":null,"abstract":"","PeriodicalId":44878,"journal":{"name":"International Journal of Grid and Utility Computing","volume":"12 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66888207","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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