درخت حوزه‌های تخصصی

Cloud Computing has drastically simplified the management of IT resources by introducing the concept of resource pooling. It has led to a tremendous improvement in infrastructure planning. The major goals of cloud computing include maximization of computing resources with minimization of cost. But the truth is that everything has a price and cloud computing is no different. With Cloud computing there comes a number of security concerns which need to be addressed. Cloud forensics plays a vital role to address the security issues related to cloud computing by identifying, collecting and studying digital evidence in cloud environment. The aim of the research paper is to explore the concept of cloud forensic by applying optimization for feature selection before classification of data on cloud side. The data is classified as malicious and non-malicious using convolutional neural network. The proposed system makes a comparison of models with and without feature selection algorithms before applying the data to CNN. A comparison of different metaheuristics algorithms- Particle Swarm Optimization, Shuffled Frog Leap Optimization and Fire fly algorithm for feature optimization is done based on convergence rate and efficiency.

The backing of the fuzzy ideal is normal ideal in some ring and in same time there fuzzy set whose is not fuzzy ideal and it backing set is ideal, i.e., it crisp is normal ideal. Consequently, in this paper we constructing a fuzziness function which defined on fuzzy sets and assigns membership grade for every fuzzy set whose it backing set are crisp ideal. Now, Let  be collection of all fuzzy subsets of ring  and , and the function  defines from  to, such that the value of the function is greater than zero if the crisp set of fuzzy set is ideal, and the value of the function is equal to one when the crisp set is maximal ideal or is the ring  itself. But if the support of the fuzzy set did not ideal then the value may be equal to or large than 0. Therefore, we add another condition to the fuzziness function to be more determined with respect to the fuzzy set. From above we try to find relation between the fuzzy ideal and its crisp set. This concept is derives from the open grade for all fuzzy set in fuzzy topological space which called smooth topology.

The aim of this study is to analyze the factors affecting the acceptance of electronic health on the basis of the theory of planned behavior. E-health is a growing field of health communication that entails using medical informatics, public health, and trades. As a result, E-health facilitates the provision of health information and services through the internet and related technologies. In this regard, this study aims to explain the acceptance of e-health by its beneficiaries such as physicians, patients, and healthcare managers. The results have shown that the most important factors affecting the acceptance of e-health are:  1. Organizational related factors of e-health services; 2. Human-related factors of acceptors; 3. Environment-related factors; 4. Factors associated with financial sources and expenditures; 5. Technical and infrastructural factors. Taking advantage of interpretive structural modeling, we demonstrated these factors and determined the level of their reciprocal relations.

The great development witnessed by our current age has led to the emergence of many diverse modern technologies, one of these advanced technologies is Hologram technology and Augmented reality technology, These two technologies are somewhat similar to somewhat, as it can be said that they perform almost the same purpose, and at the same time, Hologram technology differs from augmented reality in several aspects, as the way in which the three-dimensional images are created and the properties of that images itself. This paper aims to compare and study the similarities and differences between Hologram technology and Augmented reality technology. It is a standard comparison as the comparison takes place according to a number of different aspects of both technologies. Comparing the characteristics of the two technologies showed that there is no one of them excels over the other, but according to different systems and situations, it is maybe better and more appropriate to use one of them than using the other one.

This paper aimed to explore IT innovations used in sustainable business models in the European single energy market. For this purpose, the academic literature and content analyses of organized marketplaces were performed. The results showed that end users are not always interested in changing the service and try to choose services/resources well known to them. At the same time, market operators see the need for radical change by introducing strategic innovations and digitizing energy markets. Sustainable e-government management models are typically sustained by IoT, blockchain, and smart grid management technologies.

This study aimed to analyze the factors that influenced millennial use of E-recruitment (online recruitment), through the Technology Acceptance Model (TAM). In this regard, TAM was extended by incorporating trust and privacy in the context of millennial technology adoption. A cross-sectional quantitative survey was carried out, utilizing purposive sampling of millennials who used the E-recruitment platform. The data were obtained from 270 respondents and analyzed with Partial-Least Squares Structural Equation Modeling (PLS-SEM) to explore the relationships between the factors. The results showed that perceived ease of use and trust had a significant influence on millennials’ intention to use E-recruitment services. Meanwhile, perceived usefulness and privacy did not have a significant influence. Intention to use E-recruitment services was a strong predictor of actual use. This study provided a practical understanding for human resource professionals and organizations that aim to improve E-recruitment strategies. It was emphasized that ease of use and building trust were important criteria used for promoting adoption among millennials. Future studies are recommended to use diverse samples and investigate the impact of technostress and cultural factors on E-recruitment adoption. In addition, it is necessary to evaluate employers’ perspectives, which can provide a more in-depth understanding of technology adoption in E-recruitment.

Scientific sources demonstrate different attitudes of researchers to cryptocurrencies because they treat them as a category of currency, virtual money, commodity, etc. Accordingly, the relation to the valuation and risk of cryptocurrency as an investment object is different. The purpose of the article is to identify cryptocurrency value formation factors and determine the risks of investing in cryptocurrency. Cryptocurrency is simultaneously considered a currency, an asset with uncertain income, and a specific product, the price of which is determined by the energy costs for mining new cryptocurrency blocks. Thus, the paper examines the risks of investing in cryptocurrency from several positions. First, the study identifies the factors of formation of the value and risk of cryptocurrency as ordinary money based on comparing cryptocurrency with traditional money. Unlike traditional money, cryptocurrency is not tied to the economic performance of a particular country; also, central banks do not control or regulate their mining. Instead, the cryptocurrency emissions depend on the computational capacity of the equipment used for their mining. As a financial asset, cryptocurrency can be a “financial bubble” because their value increasing often exceeds the cost of mining. On the other hand, given the emergence of cryptocurrency as a phenomenon of the information economy, the paper analyses the impact of specific technical features (cryptographic hashing algorithm, the complexity of creating new blocks, the technology of verification of mining operations, etc.) on the risk of investing in cryptocurrency assets.