Current Issue : January-March Volume : 2024 Issue Number : 1 Articles : 5 Articles
In recent years, deep distributed neural networks (DDNNs) and neural networks (NN) have excelled in an extensive list of applications. For example, deep convolutional neural networks (DCNNs) are constantly gaining new features in various tasks in computer vision. At the same time, the number of end devices, including Internet of Things (IoT) devices has increased prominently. These devices are attractive targets for machine learning applications because they are often directly connected to sensors. For example (cameras, microphones, and gyroscopes) that record large amounts of input data in a stream mode. This study presents the design of a DDNN with end devices, edges, and clouds that spans computer hierarchies. The idea presented is considered one of the new ideas because it depends on two layers to distinguish, namely the convolutional layer and the pooling layer. The main objective behind using these two layers in one proposal is to provide and obtain the best results. Finally, we discovered that the proposed technique produced the best results in terms of accuracy and cost, with the precision of the definition reaching 99 % and the cost being quite affordable at 25. As a result, we conclude that these results are far superior to those achieved by the researchers in their ideas provided in previous recent literature....
In this paper, the inertia weighting strategy of the particle swarm is improved by using the properties of periodicity and fixed upper and lower bounds of sinusoidal function to model the task scheduling problem in cloud computing as a mathematical problem, and the improved particle swarm algorithm is discretized, and the improved discrete particle swarm algorithm is applied to task scheduling by corresponding encoding method. The task scheduling algorithm (PSOACO) that fuses the fast convergence and small computational power of the particle swarm algorithm with the global exploration capability of the ant colony algorithm for scheduling tasks is proposed. Two test cases, PageRank and wordcount, are selected to measure the performance of the PSO-ACO algorithm. In the performance comparison running the PageRank test case, the PSO-ACO algorithm obtains a performance speedup ratio of 3.8 times that of the native Domino when 50,000 pages are added. In the execution time comparison for the wordcount test case with an additional data set, the PSO-ACO algorithm is nearly 2.8 times faster than the native Domino when adding 1GB of data. Thus, the fusion algorithm reduces the task completion time and achieves a balance between the algorithm’s computational effort and the scheduling’s convergence performance....
This study aims to design an accounting information system for business entities—Village-owned (BUMDesa) Ketapang Banyuwangi with cloud computing. BUMDesa Ketapang has experienced good development in the last five years but has not been matched by an effective accounting system. The research methodology used is qualitative exploratory research with PIECES analysis. The results of this study refer to the cash receipt cycle, cash disbursement, and reporting cycle starting from recording transactions from the business unit and reporting to the treasurer then recorded in a journal, posted to a ledger, and producing financial reports in the form of a Financial Position Report, Profit Loss Report, and cash flow statements. The processes shown are data flow diagrams (DFD), flow charts, entity-relationship diagrams (ERD)....
The purpose of this research is to examine the impact of green electronic auditing on accounting information reliability and the mediating role of cloud computing in the Jordanian Social Security Corporation. A survey of 500 employees in the Jordanian Social Security Corporation was used to gather data, with a response rate of 31.4% (157 employees). The researcher used structural equation modeling to investigate the connections between cloud computing, auditing on data processing processes, auditing the inputs, auditing the outputs, prior auditing on inputs, and accounting information reliability. The findings revealed that auditing data processing activities, auditing outputs, cloud computing, and earlier auditing on inputs all have a substantial impact on accounting information reliability. However, auditing the inputs and the link between cloud computing and accounting information reliability were not significant. This study’s conclusions have ramifications for policymakers and auditing and accounting practitioners. The Jordanian Social Security Corporation must consider the significance of adequate auditing methods to assure correct accounting information, particularly in the context of cloud computing. This report also highlights the need for more research on the influence of cloud computing on accounting and auditing processes in underdeveloped countries....
Frequent data breaches in the cloud environment have seriously affected cloud subscribers and providers. Privacy-preserving image retrieval methods can improve the security of cloud image retrieval; however, existing methods have limited accuracy on dynamically updated image databases and mobile lightweight devices. In this study, we propose a privacy-preserving image retrieval method based on disordered local histograms and vision transformer in cloud computing, by designing a multiple encryption method and transformer-based feature model to better mine the local feature value of encrypted images. Specifically, the user performs different value substitution, position substitution, and color substitution on the subblocks of the image to protect the image information. The cloud server extracts the unordered local histogram from the encrypted image and generates retrievable features using transformer. Experiments show that compared with similar CNN schemes, the retrieval accuracy of this method is improved by 8.5%, and the retrieval efficiency is improved by 54.8%....
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