Pub Date : 2023-04-06DOI: 10.1080/17517575.2023.2197406
Brij B. Gupta, Akshat Gaurav, P. Panigrahi, Varsha Arya
ABSTRACT In the digital age, businesses collect vast amounts of data, but often lack the knowledge and tools to fully utilize it. This paper analyzes current information management practices across different domains and highlights the need for global standards and cutting-edge technologies such as AI, ML, DL, and cloud/edge computing. By examining trends in published research, the study proposes new research lines and provides a comprehensive overview of the field’s development, definitions, and trends. The research contributes significantly to the subject of information management and offers a synthesized description of the field’s state.
{"title":"Analysis of cutting-edge technologies for enterprise information system and management","authors":"Brij B. Gupta, Akshat Gaurav, P. Panigrahi, Varsha Arya","doi":"10.1080/17517575.2023.2197406","DOIUrl":"https://doi.org/10.1080/17517575.2023.2197406","url":null,"abstract":"ABSTRACT In the digital age, businesses collect vast amounts of data, but often lack the knowledge and tools to fully utilize it. This paper analyzes current information management practices across different domains and highlights the need for global standards and cutting-edge technologies such as AI, ML, DL, and cloud/edge computing. By examining trends in published research, the study proposes new research lines and provides a comprehensive overview of the field’s development, definitions, and trends. The research contributes significantly to the subject of information management and offers a synthesized description of the field’s state.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2023-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49108095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ABSTRACT Hyperautomation can automate complex business processes, reduce human intervention and improve business operational efficiency. Recommendation systems (RS) facilitate hyperautomation greatly. However, these systems require a large amount of user data to train their machine learning (ML) models and hence user data privacy has received great attention. In this paper, we propose a decentralized federated learning framework with privacy-preserving for RS. In our framework, users train the private and public parameters locally but share the public parameters only. Extensive experiments verify that our approach is accurate and can well preserve privacy. This study is helpful for providing privacy preserving in hyperautomation.
{"title":"Decentralized federated learning with privacy-preserving for recommendation systems","authors":"Jianlan Guo, Qinglin Zhao, Guangcheng Li, Yuqiang Chen, Chengxue Lao, Li Feng","doi":"10.1080/17517575.2023.2193163","DOIUrl":"https://doi.org/10.1080/17517575.2023.2193163","url":null,"abstract":"ABSTRACT Hyperautomation can automate complex business processes, reduce human intervention and improve business operational efficiency. Recommendation systems (RS) facilitate hyperautomation greatly. However, these systems require a large amount of user data to train their machine learning (ML) models and hence user data privacy has received great attention. In this paper, we propose a decentralized federated learning framework with privacy-preserving for RS. In our framework, users train the private and public parameters locally but share the public parameters only. Extensive experiments verify that our approach is accurate and can well preserve privacy. This study is helpful for providing privacy preserving in hyperautomation.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48568459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-28DOI: 10.1080/17517575.2023.2193153
H. Gul
ABSTRACT Due to the importance of business process automation in industry, hyperautomation and Robotic Process Automation (RPA) attract increasing attention in the scientific field as well. Hyperautomation allows automation to do important tasks performed by business people by merging Artificial Intelligence (AI) technologies with RPA. Lomax distribution has been widely used in engineering science, service times, use and supply times of products in enterprise information systems, income and wealth data, business failure data, medical and biological science, life test and other fields. In this paper, the maximum likelihood estimation of unknown parameters of the Lomax distribution is considered using simple random sample, ranked set sample, median ranked set sample and extreme ranked set sample. Model parameters are estimated by the maximum likelihood estimation method based on Genetic Algorithm. An extensive Monte Carlo simulation study, considering perfect and imperfect ranking, is carried out in order to compare the performance of the genetic algorithm and classical optimisation method from ranked set sample-based designs with corresponding simple random sample estimators. Real-life data has been used to illustrate the application of the results obtained.
{"title":"Parameter estimation of the Lomax distribution using genetic algorithm based on the ranked set samples","authors":"H. Gul","doi":"10.1080/17517575.2023.2193153","DOIUrl":"https://doi.org/10.1080/17517575.2023.2193153","url":null,"abstract":"ABSTRACT Due to the importance of business process automation in industry, hyperautomation and Robotic Process Automation (RPA) attract increasing attention in the scientific field as well. Hyperautomation allows automation to do important tasks performed by business people by merging Artificial Intelligence (AI) technologies with RPA. Lomax distribution has been widely used in engineering science, service times, use and supply times of products in enterprise information systems, income and wealth data, business failure data, medical and biological science, life test and other fields. In this paper, the maximum likelihood estimation of unknown parameters of the Lomax distribution is considered using simple random sample, ranked set sample, median ranked set sample and extreme ranked set sample. Model parameters are estimated by the maximum likelihood estimation method based on Genetic Algorithm. An extensive Monte Carlo simulation study, considering perfect and imperfect ranking, is carried out in order to compare the performance of the genetic algorithm and classical optimisation method from ranked set sample-based designs with corresponding simple random sample estimators. Real-life data has been used to illustrate the application of the results obtained.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41586249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-27DOI: 10.1080/17517575.2023.2193557
Victor Chang, Danhne Lawrence, Le Minh Thao Doan, Ariel Qianwen Xu, B. Liu
{"title":"New product design and implementation of aboleth: a mobile D&D character creator for enterprise mobile applications and metaverse","authors":"Victor Chang, Danhne Lawrence, Le Minh Thao Doan, Ariel Qianwen Xu, B. Liu","doi":"10.1080/17517575.2023.2193557","DOIUrl":"https://doi.org/10.1080/17517575.2023.2193557","url":null,"abstract":"","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42774107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-15DOI: 10.1080/17517575.2023.2188122
Victor Chang, Lewis Golightly, Qi Xu, Thanaporn Boonmee, B. Liu
ABSTRACT The paper discusses cybersecurity for children (particularly teenagers) and focuses on Social Media’s impact using a theoretical approach. Many social media users are unaware of their Cybersecurity in Social Media and all-round digital privacy and do not understand the importance of developing privacythrough taking both digital and physical measures. We identify seven categories of hacking motivations through multimedia platforms: Emotions, Financial gains, Entertainment, Proficiency for jobs, Hacktivism, Espionage, and Cyber-warfare, particularly for children. As vulnerable people, they can be the principal victims. We explore various methods used for hacking, such as Sexting, Facebook depression, and Influence on buying advertisements. In our findings, we demonstrate that the most critical protection method is to fully understand the digital footprint left behind and its possible consequences. The users should know this as a self-protection mechanism to mitigate security issues before problems occur. It means adopting the same mindset and attitude of protecting oneself in the online world as in the real world.
{"title":"Cybersecurity for children: an investigation into the application of social media","authors":"Victor Chang, Lewis Golightly, Qi Xu, Thanaporn Boonmee, B. Liu","doi":"10.1080/17517575.2023.2188122","DOIUrl":"https://doi.org/10.1080/17517575.2023.2188122","url":null,"abstract":"ABSTRACT The paper discusses cybersecurity for children (particularly teenagers) and focuses on Social Media’s impact using a theoretical approach. Many social media users are unaware of their Cybersecurity in Social Media and all-round digital privacy and do not understand the importance of developing privacythrough taking both digital and physical measures. We identify seven categories of hacking motivations through multimedia platforms: Emotions, Financial gains, Entertainment, Proficiency for jobs, Hacktivism, Espionage, and Cyber-warfare, particularly for children. As vulnerable people, they can be the principal victims. We explore various methods used for hacking, such as Sexting, Facebook depression, and Influence on buying advertisements. In our findings, we demonstrate that the most critical protection method is to fully understand the digital footprint left behind and its possible consequences. The users should know this as a self-protection mechanism to mitigate security issues before problems occur. It means adopting the same mindset and attitude of protecting oneself in the online world as in the real world.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43207219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-14DOI: 10.1080/17517575.2023.2180777
Jianxin Li, Jie Liu, C. Li, Fei Jiang, Jinyu Huang, Shanshan Ji, Yang Liu
ABSTRACT When dealing with the mutual storage relationship of behavioral features in long time sequence video, the convolutional neural network is easy to miss important feature information. To solve the above problems, this paper proposes a super automatic algorithm combining nonlocal convolution and three-dimensional convolution neural network. The algorithm uses sparse sampling to segment the long time sequence video to reduce the amount of redundant information, and integrates non-local convolution into the residual neural network, thus forming a super automatic full variational - L1 algorithm. Experimental results show that the proposed method can significantly improve the efficiency of behavior recognition.
{"title":"A hyperautomative human behaviour recognition algorithm based on improved residual network","authors":"Jianxin Li, Jie Liu, C. Li, Fei Jiang, Jinyu Huang, Shanshan Ji, Yang Liu","doi":"10.1080/17517575.2023.2180777","DOIUrl":"https://doi.org/10.1080/17517575.2023.2180777","url":null,"abstract":"ABSTRACT When dealing with the mutual storage relationship of behavioral features in long time sequence video, the convolutional neural network is easy to miss important feature information. To solve the above problems, this paper proposes a super automatic algorithm combining nonlocal convolution and three-dimensional convolution neural network. The algorithm uses sparse sampling to segment the long time sequence video to reduce the amount of redundant information, and integrates non-local convolution into the residual neural network, thus forming a super automatic full variational - L1 algorithm. Experimental results show that the proposed method can significantly improve the efficiency of behavior recognition.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48003388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-10DOI: 10.1080/17517575.2023.2188123
Prakash Mohan, S. Neelakandan, A. Mardani, Dr Sudhanshu Maurya, N. Arulkumar, K. Thangaraj
ABSTRACT Hyper automation is the group of approaches and software companies utilised to automate manual procedures. Financial Technology (FinTech) was processed as a distinctive classification that highly inspects the financial technology sector from a broader group of functions for enterprises with utilise of Information Technology (IT) application. Financial crisis prediction (FCP) is the most essential FinTech technique, defining institutions’ financial status. This study proposes an Eagle Strategy Arithmetic Optimisation Algorithm with Optimal Deep Convolutional Forest (ESAOA-ODCF) based FinTech Application for Hyperautomation. The ESAOA-ODCF technique has achieved exceptional performance with maximum accu y of 98.61%, and F score of 98.59%. Extensive experimental research revealed that the ESAOA-ODCF model beat more modern, cutting-edge approaches in terms of overall performance.
{"title":"Eagle Strategy Arithmetic Optimisation Algorithm with Optimal Deep Convolutional Forest Based FinTech Application for Hyper-automation","authors":"Prakash Mohan, S. Neelakandan, A. Mardani, Dr Sudhanshu Maurya, N. Arulkumar, K. Thangaraj","doi":"10.1080/17517575.2023.2188123","DOIUrl":"https://doi.org/10.1080/17517575.2023.2188123","url":null,"abstract":"ABSTRACT Hyper automation is the group of approaches and software companies utilised to automate manual procedures. Financial Technology (FinTech) was processed as a distinctive classification that highly inspects the financial technology sector from a broader group of functions for enterprises with utilise of Information Technology (IT) application. Financial crisis prediction (FCP) is the most essential FinTech technique, defining institutions’ financial status. This study proposes an Eagle Strategy Arithmetic Optimisation Algorithm with Optimal Deep Convolutional Forest (ESAOA-ODCF) based FinTech Application for Hyperautomation. The ESAOA-ODCF technique has achieved exceptional performance with maximum accu y of 98.61%, and F score of 98.59%. Extensive experimental research revealed that the ESAOA-ODCF model beat more modern, cutting-edge approaches in terms of overall performance.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48874285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-06DOI: 10.1080/17517575.2023.2188124
Wenjun Lin, P. Babyn, Yan yan, Wenjun Zhang
ABSTRACT This paper proposes a new scheduling problem for patient visits with two objectives: minimizing patient waiting time and travel time. It also presents a novel encoding method for Genetic Algorithms (GA) that is well-suited for this problem. Experiments demonstrate that the proposed encoding method reduces optimization iterations by 17% compared to conventional methods, and the GA can decrease waiting time by up to 58.2% and travel time by up to 89.3% for specific examples. The novel scheduling problem and the encoding method are two main contributions of this work.
{"title":"A novel scheduling method for reduction of both waiting time and travel time of patients to visit health care units in the case of mobile communication","authors":"Wenjun Lin, P. Babyn, Yan yan, Wenjun Zhang","doi":"10.1080/17517575.2023.2188124","DOIUrl":"https://doi.org/10.1080/17517575.2023.2188124","url":null,"abstract":"ABSTRACT This paper proposes a new scheduling problem for patient visits with two objectives: minimizing patient waiting time and travel time. It also presents a novel encoding method for Genetic Algorithms (GA) that is well-suited for this problem. Experiments demonstrate that the proposed encoding method reduces optimization iterations by 17% compared to conventional methods, and the GA can decrease waiting time by up to 58.2% and travel time by up to 89.3% for specific examples. The novel scheduling problem and the encoding method are two main contributions of this work.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42507243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-28DOI: 10.1080/17517575.2023.2180328
Chun-Hao Chen, Cheng-Yu Lu, Rui-Dong Chiang, Gautam Srivastava, Chun-Wei Lin
ABSTRACT When a stock portfolio is suggested to inventors, they may need a mechanism to replace stocks when their future prospects are pessimistic. However, existing approaches only consider all assets to find a diverse group stock portfolio (DGSP), which may suffer massive losses as a result. In this paper, an intelligent optimisation algorithm is proposed to obtain a more profitable DGSP with active and inactive stocks. In the coding scheme, not only grouping, stocks, and weighting but also active stock parts are used to represent a DGSP. Two evaluation functions are developed according to five factors, including group balance, modified portfolio satisfaction, price balance, unit balance, and extended diversity factor. These functions are used to assess the fitness of a chromosome. Finally, empirical studies were conducted on two financial datasets to show the merits of the proposed algorithm.
{"title":"An evolutionary-based approach for optimising diverse group stock portfolio with active and inactive stocks","authors":"Chun-Hao Chen, Cheng-Yu Lu, Rui-Dong Chiang, Gautam Srivastava, Chun-Wei Lin","doi":"10.1080/17517575.2023.2180328","DOIUrl":"https://doi.org/10.1080/17517575.2023.2180328","url":null,"abstract":"ABSTRACT When a stock portfolio is suggested to inventors, they may need a mechanism to replace stocks when their future prospects are pessimistic. However, existing approaches only consider all assets to find a diverse group stock portfolio (DGSP), which may suffer massive losses as a result. In this paper, an intelligent optimisation algorithm is proposed to obtain a more profitable DGSP with active and inactive stocks. In the coding scheme, not only grouping, stocks, and weighting but also active stock parts are used to represent a DGSP. Two evaluation functions are developed according to five factors, including group balance, modified portfolio satisfaction, price balance, unit balance, and extended diversity factor. These functions are used to assess the fitness of a chromosome. Finally, empirical studies were conducted on two financial datasets to show the merits of the proposed algorithm.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47065099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-27DOI: 10.1080/17517575.2023.2172362
Feng Xiao, Shiwei He, R. Song, S. Chaudhry
ABSTRACT Transportation enterprises have started to pay more attention to the vast amount of historical operational data. In this paper, real route information is extracted from the freight car trajectory data and a satisfied route is proposed based on this information. The satisfied route not only can reduce the travel cost but also conform to the actual transportation situation. A solution framework driven by trajectory data is developed to obtain the satisfied route. A case study associated with the Chinese railway is used to verify the model and the solution framework proposed in this paper.
{"title":"Satisfied railway flow route problem integrated with ideal route and real trajectory information","authors":"Feng Xiao, Shiwei He, R. Song, S. Chaudhry","doi":"10.1080/17517575.2023.2172362","DOIUrl":"https://doi.org/10.1080/17517575.2023.2172362","url":null,"abstract":"ABSTRACT Transportation enterprises have started to pay more attention to the vast amount of historical operational data. In this paper, real route information is extracted from the freight car trajectory data and a satisfied route is proposed based on this information. The satisfied route not only can reduce the travel cost but also conform to the actual transportation situation. A solution framework driven by trajectory data is developed to obtain the satisfied route. A case study associated with the Chinese railway is used to verify the model and the solution framework proposed in this paper.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47814745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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