cloud computing environment
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2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Yanqing Chen

At present, many companies have many problems such as high financial costs, low financial management capabilities, and redundant frameworks; at the same time, the SASAC requires that the enterprise’s financial strategy transfer from “profit-driven” to “value-driven”, finance separate from accounting to improve the operational efficiency of the company. Under this background, more and more enterprise respond to the call of the SASAC; in order to achieve the goals of corporate financial cost savings and financial management efficiency improved, we began to provide services through financial sharing. The research of information fusion theory involves many basic theories, which can be roughly divided into two large categories from the algorithmic point of view: probabilistic statistical method and artificial intelligence method. The main task of artificial intelligence is to realize the computer for some learning, thinking process, and wisdom formation of simulation, and an important goal of information integration is the human brain comprehensive processing ability simulation, so artificial intelligence method will have broad application prospects in the field of information fusion; the common methods have D-S evidence reasoning, fuzzy theory, neural network, genetic algorithm, rough set, and other information fusion methods. The purpose of this paper is to proceed from the internal financial situation of the enterprise, analyze data security issues in the operation of financial shared services, and find a breakthrough in solving problems. But, with constantly expanding of enterprise group financial sharing service scale, the urgent problem to be solved is how to ensure the financial sharing services provided by enterprises in the cloud computing environment. This paper combines financial sharing service theory and information security theory and provides reference for building financial sharing information security for similar enterprises. For some enterprise that have not established a financial shared service center yet, they can learn from the establishment of the financial sharing information security system in this paper and provide a reference for enterprise to avoid the same types of risks and problems. For enterprise that has established and has begun to practice a financial shared information security system, appropriate risk aversion measures combined with actual situation of the enterprise with four dimensions related to information security system optimization was formulated and described in this paper. In summary, in the background of cloud computing, financial sharing services have highly simplified operational applications, and data storage capabilities and computational analysis capabilities have been improved greatly. Not only can it improve the quality of accounting information but also provide technical support for the financial sharing service center of the enterprise group, perform financial functions better, and enhance decision support and strategic driving force, with dual practical significance and theoretical significance.


2022 ◽  
pp. 1990-2021
Author(s):  
Robert-Christian Ziebell ◽  
Jose Albors-Garrigos ◽  
Klaus-Peter Schoeneberg ◽  
Maria Rosario Perello Marin

This qualitative study examines the digitisation of HRM in a cloud-based environment. The influencing factors for the transformation from conventional HRM to eHRM are examined with a special focus on the success factors from a strategic to the operational level. Additionally, an in-depth analysis of the currently existing and new HR metrics which emerge during the transformation takes place. The study is based on interviews with HR experts with extensive experience in transforming and working with the new technology. Active participation of the HR department is relevant for the success of the digital transformation HRM project. HR metrics have not been applied extensively so far and are used less for controlling and optimizing HR processes. New metrics would increase the acceptance of the new technology and thus the success of the overall HR transformation. The main contribution is related to the field of HR software adoption of cloud-based solutions.


2022 ◽  
Vol 59 (1) ◽  
pp. 102786
Author(s):  
Chunlin Li ◽  
SongYu Liang ◽  
Jing Zhang ◽  
Qiao-e Wang ◽  
Youlong Luo

2021 ◽  
Vol 17 (3) ◽  
pp. 197-218
Author(s):  
Karima Saidi ◽  
Ouassila Hioual ◽  
Abderrahim Siam

In this paper, we address the issue of resource allocation in a Cloud Computing environment. Since the need for cloud resources has led to the rapid growth of data centers and the waste of idle resources, high-power consumption has emerged. Therefore, we develop an approach that reduces energy consumption. Decision-making for adequate tasks and virtual machines (VMs) with their consolidation minimizes this latter. The aim of the proposed approach is energy efficiency. It consists of two processes; the first one allows the mapping of user tasks to VMs. Whereas, the second process consists of mapping virtual machines to the best location (physical machines). This paper focuses on this latter to develop a model by using a deep neural network and the ELECTRE methods supported by the K-nearest neighbor classifier. The experiments show that our model can produce promising results compared to other works of literature. This model also presents good scalability to improve the learning, allowing, thus, to achieve our objectives.


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