The advent of the metaverse has revolutionized virtual interactions and navigation, introducing intricate access control challenges. This paper addresses the need for effective access control models in the cloud-based metaverse. It explores its distinct characteristics, including its dynamic nature, diverse user base, and shared spaces, highlighting privacy concerns and legal implications. The paper analyzes access control principles specific to the cloud-based metaverse, emphasizing least privilege, separation of duties, RBAC, defense-in-depth, and auditability/accountability. It delves into identity verification and authorization methods, such as biometrics, multi-factor authentication, and role-based/attribute-based authorization. Advanced access control technologies for the cloud-based metaverse are examined, including SSO solutions, blockchain-based access control, ABAC, adaptive access control, and VMI for isolation. Risk mitigation strategies encompass IDS/IPS, SIEM, and user education programs.
{"title":"Mitigating Risks in the Cloud-Based Metaverse Access Control Strategies and Techniques","authors":"Utsav Upadhyay, Alok Kumar, Gajanand Sharma, Ashok Kumar Saini, Varsha Arya, Akshat Gaurav, Kwok Tai Chui","doi":"10.4018/ijcac.334364","DOIUrl":"https://doi.org/10.4018/ijcac.334364","url":null,"abstract":"The advent of the metaverse has revolutionized virtual interactions and navigation, introducing intricate access control challenges. This paper addresses the need for effective access control models in the cloud-based metaverse. It explores its distinct characteristics, including its dynamic nature, diverse user base, and shared spaces, highlighting privacy concerns and legal implications. The paper analyzes access control principles specific to the cloud-based metaverse, emphasizing least privilege, separation of duties, RBAC, defense-in-depth, and auditability/accountability. It delves into identity verification and authorization methods, such as biometrics, multi-factor authentication, and role-based/attribute-based authorization. Advanced access control technologies for the cloud-based metaverse are examined, including SSO solutions, blockchain-based access control, ABAC, adaptive access control, and VMI for isolation. Risk mitigation strategies encompass IDS/IPS, SIEM, and user education programs.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"358 15","pages":"1-30"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138625903","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}
M. AlShaikh, Waleed Alsemaih, Sultan Alamri, Qusai Ramadan
The rapid proliferation of internet of things (IoT) devices has ushered in a new era of technological development. However, this growth has also exposed these devices to various cybersecurity risks, including command and control (C&C) attacks. C&C attacks involve unauthorized entities taking control of IoT devices to carry out malicious activities. Traditional cybersecurity measures often fall short in addressing these evolving threats. To enhance IoT security and counter C&C threats, this study explores the potential of supervised learning, a subfield of machine learning. Supervised learning, a method that utilizes past data to train machine learning models capable of independently identifying patterns indicative of C&C threats in real time, offers additional protection to IoT networks. This article delves into the advantages and drawbacks of this approach, considering factors such as the need for well-defined labeled datasets, resource constraints of IoT devices, and ethical considerations surrounding data security.
{"title":"Using Supervised Learning to Detect Command and Control Attacks in IoT","authors":"M. AlShaikh, Waleed Alsemaih, Sultan Alamri, Qusai Ramadan","doi":"10.4018/ijcac.334214","DOIUrl":"https://doi.org/10.4018/ijcac.334214","url":null,"abstract":"The rapid proliferation of internet of things (IoT) devices has ushered in a new era of technological development. However, this growth has also exposed these devices to various cybersecurity risks, including command and control (C&C) attacks. C&C attacks involve unauthorized entities taking control of IoT devices to carry out malicious activities. Traditional cybersecurity measures often fall short in addressing these evolving threats. To enhance IoT security and counter C&C threats, this study explores the potential of supervised learning, a subfield of machine learning. Supervised learning, a method that utilizes past data to train machine learning models capable of independently identifying patterns indicative of C&C threats in real time, offers additional protection to IoT networks. This article delves into the advantages and drawbacks of this approach, considering factors such as the need for well-defined labeled datasets, resource constraints of IoT devices, and ethical considerations surrounding data security.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"23 1","pages":"1-19"},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139220922","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}
It is important for cloud users to be able to evaluate and compare different cloud services to achieve high performance and maximize cost savings. To that end, this research benchmarked Amazon web services elastic compute cloud and Rackspace cloud infrastructure and compared the results for the two public cloud providers. The intent of the study was to determine how these selected providers perform with regards to system parameter usage and hence three system-level benchmarks: STREAM, IOR, and NPB-EP were run on different configurations to provide an insight to the cloud users in selection of provider on VM clusters of 1,2,4,6, and 8 nodes. The clusters were created with similar virtual machines from both providers. The benchmarks examined bandwidth, I/O and CPU performance. A comparison of results for the two providers is presented graphically and T-test applied to determine if differences are significant. Observations were taken at multiple times at different time periods on weekdays and weekends to examine variance of cloud performance.
对于云用户来说，能够评估和比较不同的云服务以实现高性能和最大限度地节省成本是非常重要的。为此，本研究对Amazon web services弹性计算云和Rackspace云基础设施进行了基准测试，并比较了这两个公共云提供商的结果。该研究的目的是确定这些选定的提供商在系统参数使用方面的表现，因此三个系统级基准:STREAM、IOR和NPB-EP在不同的配置上运行，以便为云用户在1、2、4、6和8个节点的VM集群上选择提供商提供洞察。集群是用来自两个提供商的类似虚拟机创建的。基准测试测试了带宽、I/O和CPU性能。两个提供者的比较结果以图形形式呈现，并应用t检验来确定差异是否显著。在工作日和周末的不同时间段进行多次观测，以检验云性能的差异。
{"title":"System Level Benchmarking of Public Clouds","authors":"S. Ahuja","doi":"10.4018/ijcac.309933","DOIUrl":"https://doi.org/10.4018/ijcac.309933","url":null,"abstract":"It is important for cloud users to be able to evaluate and compare different cloud services to achieve high performance and maximize cost savings. To that end, this research benchmarked Amazon web services elastic compute cloud and Rackspace cloud infrastructure and compared the results for the two public cloud providers. The intent of the study was to determine how these selected providers perform with regards to system parameter usage and hence three system-level benchmarks: STREAM, IOR, and NPB-EP were run on different configurations to provide an insight to the cloud users in selection of provider on VM clusters of 1,2,4,6, and 8 nodes. The clusters were created with similar virtual machines from both providers. The benchmarks examined bandwidth, I/O and CPU performance. A comparison of results for the two providers is presented graphically and T-test applied to determine if differences are significant. Observations were taken at multiple times at different time periods on weekdays and weekends to examine variance of cloud performance.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133333957","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}
B. Rao, Vivek Sharma, N. Rathore, D. Prasad, Harishchander Anandaram, Gaurav Soni
The concept of cloud computing makes it possible to have a shared pool of reconfigurable computing resources that can be deployed and released with little involvement from administration work or service providers. Cloud computing makes this possible. The communication among the nodes is possible with the help of internet. All users are able to use the services of cloud. The small-scale industries are really happy to use the cloud services. The attackers are degrading the performance of services, and also the users are not receiving the response. This paper presents the imprint of cloud computing. Flooding attacks or the DoS attack is one attack that reserves the communication resources in network, and the rest of the attacks, like Sybil attack, misguide the users, and also it is not easy to identify the exact identification of the sender. The security schemes are able to remove attacker infection, and on the basis of that, it is possible to design better schemes against attackers in the cloud.
{"title":"A Secure Framework to Prevent Three-Tier Cloud Architecture From Malicious Malware Injection Attacks","authors":"B. Rao, Vivek Sharma, N. Rathore, D. Prasad, Harishchander Anandaram, Gaurav Soni","doi":"10.4018/ijcac.317220","DOIUrl":"https://doi.org/10.4018/ijcac.317220","url":null,"abstract":"The concept of cloud computing makes it possible to have a shared pool of reconfigurable computing resources that can be deployed and released with little involvement from administration work or service providers. Cloud computing makes this possible. The communication among the nodes is possible with the help of internet. All users are able to use the services of cloud. The small-scale industries are really happy to use the cloud services. The attackers are degrading the performance of services, and also the users are not receiving the response. This paper presents the imprint of cloud computing. Flooding attacks or the DoS attack is one attack that reserves the communication resources in network, and the rest of the attacks, like Sybil attack, misguide the users, and also it is not easy to identify the exact identification of the sender. The security schemes are able to remove attacker infection, and on the basis of that, it is possible to design better schemes against attackers in the cloud.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132345456","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}
The purpose of the research is to describe the sociocultural factors that emerge in times of global crisis. The study is qualitative. Netnography is used as a research method and Twitter as a data collection instrument. In order to analyze the flow of messages published on Twitter, the model that describes the sociocultural factors proposed by Perez-Cepeda and Arias-Bolzmann is used. Tweets published in times of global crisis around crowdfunding are categorized and classified based on structure and content, which makes it possible to determine sociocultural factors. The findings make it possible to determine that, through the analysis of the semantics used by the users in the tweets, it is possible to determine sociocultural factors, even establish sociocultural factors associated with various social groups. The limitations are that only the social network Twitter and tweets of users who interact with @gofundme official GoFundMe account are used.
{"title":"Sociocultural Factors in Times of Global Crisis","authors":"Maximiliano Perez, D. Coello","doi":"10.4018/ijcac.316868","DOIUrl":"https://doi.org/10.4018/ijcac.316868","url":null,"abstract":"The purpose of the research is to describe the sociocultural factors that emerge in times of global crisis. The study is qualitative. Netnography is used as a research method and Twitter as a data collection instrument. In order to analyze the flow of messages published on Twitter, the model that describes the sociocultural factors proposed by Perez-Cepeda and Arias-Bolzmann is used. Tweets published in times of global crisis around crowdfunding are categorized and classified based on structure and content, which makes it possible to determine sociocultural factors. The findings make it possible to determine that, through the analysis of the semantics used by the users in the tweets, it is possible to determine sociocultural factors, even establish sociocultural factors associated with various social groups. The limitations are that only the social network Twitter and tweets of users who interact with @gofundme official GoFundMe account are used.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114136656","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}
B. MadhumalaR., Harshvardhan Tiwari, C. DevarajVerma
To meet the ever-growing demand for computational resources, it is mandatory to have the best resource allocation algorithm. In this paper, Particle Swarm Optimization (PSO) algorithm is used to address the resource optimization problem. Particle Swarm Optimization is suitable for continuous data optimization, to use in discrete data as in the case of Virtual Machine placement we need to fine-tune some of the parameters in Particle Swarm Optimization. The Virtual Machine placement problem is addressed by our proposed model called Improved Particle Swarm Optimization (IM-PSO), where the main aim is to maximize the utilization of resources in the cloud datacenter. The obtained results show that the proposed algorithm provides an optimized solution when compared to the existing algorithms.
{"title":"Resource Optimization in Cloud Data Centers Using Particle Swarm Optimization","authors":"B. MadhumalaR., Harshvardhan Tiwari, C. DevarajVerma","doi":"10.4018/ijcac.305856","DOIUrl":"https://doi.org/10.4018/ijcac.305856","url":null,"abstract":"To meet the ever-growing demand for computational resources, it is mandatory to have the best resource allocation algorithm. In this paper, Particle Swarm Optimization (PSO) algorithm is used to address the resource optimization problem. Particle Swarm Optimization is suitable for continuous data optimization, to use in discrete data as in the case of Virtual Machine placement we need to fine-tune some of the parameters in Particle Swarm Optimization. The Virtual Machine placement problem is addressed by our proposed model called Improved Particle Swarm Optimization (IM-PSO), where the main aim is to maximize the utilization of resources in the cloud datacenter. The obtained results show that the proposed algorithm provides an optimized solution when compared to the existing algorithms.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125176329","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}
Rapidly developing cloud technology with enormous number of clients creates need of reducing power consumption of data centers. VM live migration is the most promising tool to achieve resource consolidation but it creates overheads in terms of additional CPU, disk I/O and network bandwidth utilization. This paper proposes a power-aware VM live migration based dynamic VM consolidation mechanism that focuses on reduction in datacenter’s resource utilization. Proposed mechanism is Pareto Optimal because during live migration it not only optimize the migration overheads but also select the VM and destination server by considering all the performance overheads to be generated during and after live migration. The proposed algorithm reduces nearly 60% of the VMs migration overheads. In terms of energy saving the proposed mechanism is 43% more efficient than the greedy scheduling approach and about 47% more energy efficient than the round-robin approach and thus achieves green computing goal.
{"title":"Resource-Efficient Pareto-Optimal Green Scheduler Architecture","authors":"Urmila Shrawankar, C. Dhule","doi":"10.4018/ijcac.305855","DOIUrl":"https://doi.org/10.4018/ijcac.305855","url":null,"abstract":"Rapidly developing cloud technology with enormous number of clients creates need of reducing power consumption of data centers. VM live migration is the most promising tool to achieve resource consolidation but it creates overheads in terms of additional CPU, disk I/O and network bandwidth utilization. This paper proposes a power-aware VM live migration based dynamic VM consolidation mechanism that focuses on reduction in datacenter’s resource utilization. Proposed mechanism is Pareto Optimal because during live migration it not only optimize the migration overheads but also select the VM and destination server by considering all the performance overheads to be generated during and after live migration. The proposed algorithm reduces nearly 60% of the VMs migration overheads. In terms of energy saving the proposed mechanism is 43% more efficient than the greedy scheduling approach and about 47% more energy efficient than the round-robin approach and thus achieves green computing goal.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114695920","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}
Stock market has received widespread attention from investors. How to grasp the changing regularity of the stock market and predict the trend of stock prices has always been a hot spot for investors and researchers. The rise and fall of stock prices are influenced by many factors such as politics, economy, society and market. For stock investors, the trend forecast of the stock market is directly related to the acquisition of profits. The more accurate the forecast, the more effectively it can avoid risks. For listed companies, the stock price not only reflects the company’s operating conditions and future development expectations, but also an important technical index for the analysis and research of the company. Stock forecasting research also plays an important role in the research of a country’s economic development. Therefore, the research on the intrinsic value and prediction of the stock market has great theoretical significance and wide application prospects.
{"title":"Stock Market E-Assistance on Platform-as-a-Service (PaaS)","authors":"Shahul Chettali Hameed","doi":"10.4018/ijcac.305858","DOIUrl":"https://doi.org/10.4018/ijcac.305858","url":null,"abstract":"Stock market has received widespread attention from investors. How to grasp the changing regularity of the stock market and predict the trend of stock prices has always been a hot spot for investors and researchers. The rise and fall of stock prices are influenced by many factors such as politics, economy, society and market. For stock investors, the trend forecast of the stock market is directly related to the acquisition of profits. The more accurate the forecast, the more effectively it can avoid risks. For listed companies, the stock price not only reflects the company’s operating conditions and future development expectations, but also an important technical index for the analysis and research of the company. Stock forecasting research also plays an important role in the research of a country’s economic development. Therefore, the research on the intrinsic value and prediction of the stock market has great theoretical significance and wide application prospects.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122874783","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}
A large scale distributed systems have advantages of high processing speeds and large communication bandwidths over the network. The processing of huge real-world data through distributed computing system becomes obscure, because the major concern in large-scale distrib-uted systems is, how to guarantee the completion of data processing task to be done within a budget and time constraints. This paper proposes a cost optimized data parallel task scheduling in multi-core resources to address the above issue. By running concurrent executions on a multi-core resource, the number of parallel executions could be increased correspondingly, thereby able to finish the task within the deadline. A model is developed here to optimize the operational cost of data parallel task by feasibly assigning load fractions to each multi-core resource. This work is ex-perimented with data parallel task, the outcome of work gives better solutions in terms of processing task by deadline at optimised computational cost.
{"title":"A Cost-Optimized Data Parallel Task Scheduling in Multi-Core Resources Under Deadline and Budget Constraints","authors":"K. Saravanan, R. RajalakshmiN.","doi":"10.4018/ijcac.305857","DOIUrl":"https://doi.org/10.4018/ijcac.305857","url":null,"abstract":"A large scale distributed systems have advantages of high processing speeds and large communication bandwidths over the network. The processing of huge real-world data through distributed computing system becomes obscure, because the major concern in large-scale distrib-uted systems is, how to guarantee the completion of data processing task to be done within a budget and time constraints. This paper proposes a cost optimized data parallel task scheduling in multi-core resources to address the above issue. By running concurrent executions on a multi-core resource, the number of parallel executions could be increased correspondingly, thereby able to finish the task within the deadline. A model is developed here to optimize the operational cost of data parallel task by feasibly assigning load fractions to each multi-core resource. This work is ex-perimented with data parallel task, the outcome of work gives better solutions in terms of processing task by deadline at optimised computational cost.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122231551","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}
The cloud platform has established itself as the de-facto standard in IT outsourcing. This is resulting in large-scale migration of infrastructure and development platforms from in-house to cloud service providers. Many recent proposals on cloud platforms have addressed several issues that appeared on the cloud horizon. VM placement (VMP) has been a serious concern when it comes to placement of VMs after migration or VM reallocation. Most of the recent works have lacked multiple VM placement (MVMP) problem instances. A recently researched idea of MVMP through depth first opportunistic exploration (DFOE) is proposed in this paper. The performance of MVMP is compared with existing single VM placement benchmark algorithm. Improvement in terms of number of VM migrations, energy consumption, and VM reallocation is reported through simulation of real-time load scenario. Cloud environments can benefit from MVMP and improve operating margins in terms of power saving and load balancing.
{"title":"Improving Virtual Machine Migration Effects in Cloud Computing Environments Using Depth First Inspired Opportunity Exploration","authors":"K.Akhil Kumar, Jyoti Thaman","doi":"10.4018/ijcac.314209","DOIUrl":"https://doi.org/10.4018/ijcac.314209","url":null,"abstract":"The cloud platform has established itself as the de-facto standard in IT outsourcing. This is resulting in large-scale migration of infrastructure and development platforms from in-house to cloud service providers. Many recent proposals on cloud platforms have addressed several issues that appeared on the cloud horizon. VM placement (VMP) has been a serious concern when it comes to placement of VMs after migration or VM reallocation. Most of the recent works have lacked multiple VM placement (MVMP) problem instances. A recently researched idea of MVMP through depth first opportunistic exploration (DFOE) is proposed in this paper. The performance of MVMP is compared with existing single VM placement benchmark algorithm. Improvement in terms of number of VM migrations, energy consumption, and VM reallocation is reported through simulation of real-time load scenario. Cloud environments can benefit from MVMP and improve operating margins in terms of power saving and load balancing.","PeriodicalId":442336,"journal":{"name":"Int. J. Cloud Appl. Comput.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125099283","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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