• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.105-118
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• 2024

The decision to integrate mobile cloud computing (MCC) in higher education without first defining suitable usage scenarios is a global issue as the usage of such services becomes extensive. Consequently, this study investigates the security determinants of the educational use of mobile cloud computing among universities students. This study proposes and develops a theoretical model by adopting and modifying the Protection Motivation Theory (PMT). The studys findings show that a significant amount of variance in MCC adoption was explained by the proposed model. MCC adoption intention was shown to be highly influenced by threat appraisal and coping appraisal factors. Perceived severity alone explains 37.8% of students "Intention" to adopt MCC applications, which indicates the student's perception of the degree of harm that would happen can hinder them from using MCC. It encompasses concerns about data security, privacy breaches, and academic integrity issues. Response cost, perceived vulnerability and response efficacy also have significant influence on students "intention" by 18.8%, 17.7%, and 6.7%, respectively.

• International Area Studies Review
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• v.21 no.1
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• pp.97-117
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• 2017

This research highlights the process of adopting cloud computing technology from users' perspective. Concentrating on perceived mechanism from employees side that lead to job performance at work. Cloud computing, the new player in our modern business environment, authors employ diffusion of innovation theory to capture how this new technology affect employees in workplace in terms of job performance. Education for this new system and managerial support by firm were used as moderating variable to test dependent variable, job performance. Research was done through survey from total 284 people working in metropolitan area at South Korea. The result shows that cloud computing system affect positively on work efficiency, and the extent of diffusion factors that influence from the most to least are as follow: 1. Users' Skill, 2. System Quality, 3. Information Quality, 4. Group Awareness, 5. Attitude towards New System. To test diffusion factors of cloud computing and job performance, South Korean people actually felt that cloud computing help their job performance and the extent of diffusion factors that influence from the most to least are as follow: 1. Users' Skill, 2. System Quality, 3. Information Quality, 4. Attitude towards New System, 5. Group Awareness. As for diffusion factors of cloud computing and productivity, result proved that cloud computing really helps firms, and the extent of diffusion factors that influence from the most to least are as follow: 1. Information Quality, 2. Attitude towards New System, 3. Group Awareness, 4. System Quality, 5. Users' Skill. Two moderating variables, employee education and managerial support were tested to prove whether these two variables affect the job performance and the result displays positive affect for both two factors. To conclude, adopting cloud computing helps firms by increase employees' work efficiency and job performance. In order to accelerate the process employees education really matters because users' skill is the most crucial among diffusion factors.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.30-39
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• 2012

In these day, some of IT venders already were going to cloud computing market, as well they are going to expand their territory for the cloud computing market through that based on their hardware and software technology, making collaboration between hardware and software vender. Distributed file system is very mainly technology for the cloud computing that must be protect performance and safety for high levels service requests as well data store. This paper introduced distributed file system for cloud computing and how to use this theory such as memory database, Hadoop file system, high availability database system. now In the market, this paper define a very large distributed processing architect as a reference by kind of distributed file systems through using technology in cloud computing market.

• Journal of Information Technology Services
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• v.23 no.3
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• pp.17-37
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• 2024

This study explores the tendency of corporations and organizations to continue with their current processes despite having incentives for better Information Technology (IT) innovation or transition. In this context, the study argues that organizations may struggle with 'outsourcing inertia,' a well-known concept referring to an organization's deficient adaptability to environmental changes, particularly defined here as the organization's slow adaptation to changes in outsourcing levels. To verify this, the study analyzes how key variables identified from existing IT Outsourcing (ITO) decision-making research and recent studies on cloud computing transitions actually affect a firm's transition intentions. In the process, this study investigates the moderating effect of a firm's outsourcing inertia, utilizing the Technology-Organization-Environment (TOE) framework and the Push-Pull-Mooring (PPM) model based on migration theory to propose a research model. The study aims to contribute to finding strategic approaches necessary for facilitating IT innovation and transition by understanding the impact of outsourcing inertia on the decision-making process related to IT outsourcing. It is important to note that the majority of domestic conglomerates own IT subsidiaries, which significantly influence the process of transitioning to cloud computing. Nevertheless, research on the impact of IT subsidiaries on cloud computing transition is relatively scarce. Based on this background, this study proposes that IT subsidiaries within domestic conglomerates can act as a significant mooring factor of organizational inertia in the decision-making process for adopting cloud computing. Through this, the study seeks to provide strategic insights for overcoming organizational inertia faced by IT subsidiaries during the cloud computing transition process.

• Proceedings of the KSRS Conference
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• v.2
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• pp.1007-1010
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• 2006

This study investigates the spatial structure of the total cloud liquid water content Q fields over the Northwest Pacific Ocean during winter monsoon. The distributions of Q have been estimated from the brightness temperatures of the ocean - atmosphere system $T_B(f)$, where f is frequency, measured by AQUA AMSR-E in January -March 2003. Marine strati (St) and stratocumuli (Sc) are typical for winter monsoon season. They were analysed using mainly high-frequency channel at f = 36.5 GHz, vertical polarisation. $T_B$ data were accompanied by the data on near surface wind speed, air temperature and humidity from the nearest meteorological stations. Tow one-dimensional spectra were computed for downwind and crosswind sections of Q fields. The AMSR-E antenna field of view (14-8 km) and the cloud field sizes (100-1000 km) restricted the spatial scales. The results of case study Jan 31 2003 are presented. Scale-invariant spectrum is typical. In the cases of extended St levels a spectral slope equals about -1.7, conforming to classical -5/3 of turbulence theory. For Sc cases the absolute magnitude of spectral slope is rather higher, as a rule. The value is about -2. In the case when cloud streets are presented, a strait line form of spectrum is less reliable with a slope being rather lower (about -1.4).

• Geomechanics and Engineering
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• v.30 no.5
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• pp.413-422
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• 2022

TBM is widely used in the construction of various underground projects in the current world, and has the unique advantages that cannot be compared with traditional excavation methods. However, due to the high cost of TBM, the damage is even greater when geological disasters such as collapse occur during excavation. At present, there is still a shortage of research on various types of risk prediction of TBM tunnel, and accurate and reliable risk prediction model is an important theoretical basis for timely risk avoidance during construction. In this paper, a prediction model is proposed to evaluate the risk level of tunnel collapse by establishing a reasonable risk index system, using analytic hierarchy process to determine the index weight, and using the normal cloud model theory. At the same time, the traditional analytic hierarchy process is improved and optimized to ensure the objectivity of the weight values of the indicators in the prediction process, and the qualitative indicators are quantified so that they can directly participate in the process of risk prediction calculation. Through the practical engineering application, the feasibility and accuracy of the method are verified, and further optimization can be analyzed and discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1258-1275
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• 2023

Cloud computing is a new technology that has adapted to the traditional way of service providing. Service providers are responsible for managing the allocation of resources. Selecting suitable containers and bandwidth for job scheduling has been a challenging task for the service providers. There are several existing systems that have introduced many algorithms for resource allocation. To overcome these challenges, the proposed system introduces an Optimized Task Scheduling Algorithm with Deep Learning (OTS-DL). When a job is assigned to a Cloud Service Provider (CSP), the containers are allocated automatically. The article segregates the containers as' Long-Term Container (LTC)' and 'Short-Term Container (STC)' for resource allocation. The system leverages an 'Optimized Task Scheduling Algorithm' to maximize the resource utilisation that initially inquires for micro-task and macro-task dependencies. The bottleneck task is chosen and acted upon accordingly. Further, the system initializes a 'Deep Learning' (DL) for implementing all the progressive steps of job scheduling in the cloud. Further, to overcome container attacks and errors, the system formulates a Container Convergence (Fault Tolerance) theory with high-level security. The results demonstrate that the used optimization algorithm is more effective for implementing a complete resource allocation and solving the large-scale optimization problem of resource allocation and security issues.

• Journal of Information Science Theory and Practice
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• v.2 no.1
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• pp.22-34
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• 2014

This paper analyzes India's contribution to world tribology research during the period 2001-2012 based on SCOPUS records. India's global publication share, annual output, and its citation impact of Indian contribution, partner countries, leading contributors, leading institutes, and highly cited papers were analyzed. Additionally, a cloud technique is used to map frequently used single words in titles. It is observed that India ranks in the $7^{th}$ position with a global publication share of 3.83% and an annual average growth rate of 25.58% during the period 2001-2012. The citation impact of India's contribution is 6.05 which decreased from 12.74 during 2001-2006 to 4.62 during 2007-2012. 17.4% of India's total research output was published with international collaboration.

• Electronics and Telecommunications Trends
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• v.34 no.2
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• pp.60-72
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• 2019

Commercial services providing quantum cryptographic communication are available in China and the United States of America (USA), and a commercial cloud service for quantum computing is available in the USA. This has been possible since the early stage prototypes of quantum technologies have transitioned from theory to practical applications. This has led to the development of a new industrial ecosystem so that governments are announcing plans to support further research and development, new ventures are being launched, and a market is emerging. We will discuss the technological possibilities of future developments from the early-stage achievements.

• Journal of Internet Computing and Services
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• v.11 no.5
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• pp.105-117
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• 2010

In recent years, dynamic collaboration (DC) among cloud providers (CPs) is becoming an inevitable approach for the widely use of cloud computing and to realize the greatest value of it. In our previous paper, we proposed a combinatorial auction (CA) based cloud market model called CACM that enables a DC platform among different CPs. The CACM model allows any CP to dynamically collaborate with suitable partner CPs to form a group before joining an auction and thus addresses the issue of conflicts minimization that may occur when negotiating among providers. But how to determine optimal group bidding prices, how to obtain the stability condition of the group and how to distribute the winning prices/profits among the group members in the CACM model have not been studied thoroughly. In this paper, we propose to formulate the above problems of cooperative negotiation in the CACM model as a bankruptcy game which is a special type of N-person cooperative game. The stability of the group is analyzed by using the concept of the core and the amount of allocationsto each member of the group is obtained by using Shapley value. Numerical results are presented to demonstrate the behaviors of the proposed approaches.