نشریه اکتشاف و پردازش هوشمند دانش
پیاپی 6 (پاییز 1401)

One of the most important challenges in cloud data centers is the issue of scheduling tasks or allocating resources to user requests. There are several reasons why this can be seen as an NP-Complete issue. In a cloud computing environment, any user may encounter hundreds of virtual resources to perform any task. However, it is impossible for the user to assign tasks to virtual resources. Exploratory cloud methods in the form of exploratory search are a good option for these issues. One of these methods is genetic algorithm. Genetic algorithm is one of the best possible ways to solve the problem of scheduling tasks in the cloud, which has good performance for solving the problem of scheduling and dynamic load balance in parallel systems. In this research, we examine the concepts and methods presented in this field The location of virtual machines is of particular importance due to the increasing complexity of cloud systems. Due to the great importance of the scheduling process in cloud computing, various methods and algorithms have been proposed in order to achieve an acceptable scheduling in cloud computing. In all these algorithms, an attempt has been made to find an optimal solution to obtain a suitable schedule, in which each of the implemented methods has advantages and disadvantages, and a general solution. It is not recommended to improve all the parameters in the cloud

Detection of fraud is a very important field of study for online banking, as cyber criminals design new complex fraud attacks on a daily basis, so this requires researchers to constantly develop new fraud detection techniques. Bank fraud is one of the most threatening problems that any human society is facing due to its destructive effects. This refers to the intentional use of false information to defraud another person or organization of money or assets. The banking industry has used law-based systems for decades to detect fraud and humanly investigate transactions. Law-based systems include algorithms that perform various types of detection operations that are manually written by fraud experts. These systems require manual adjustment of scenarios, which challenge the implicit recognition of trading correlations that point to fraud.Given the inherent weaknesses of the law-based fraud detection approach in banks and the limited data used on commonly supervised machine learning algorithms, there is an urgent need for new fraud detection techniques or systems that can counteract the rapid rise of fraud and money laundering. This research uses a review approach and with the aim of examining the methods of detecting bank fraud, examines the research literature and describes the relevant results.

Centrality and spread of influence are two basic components in social network analysis. In recent years, the measurement of centrality has attracted the attention of many researchers, and this has led to many new studies on social network analysis and its applications. Older conventional models do not use diffusion of influence extensively to measure centrality. Many studies have been based on the independent cascade model. In this article, the assessment and measurement of centrality based on the linear threshold model in tagged and weighted social networks has been investigated. A method to measure the centrality in order to rank the members of the network is considered, which is named linear threshold rank. To evaluate the proposed method, four social networks have been compared with two measures of centrality and an independent cascade method. The result shows that the proposed method is more suitable for ranking network members and networks. A new centrality measure based on the linear threshold model was presented, which for each member, was considered as the number of members that could spread influence. Compare this metric with three other centrality metrics (Katz centrality, page rank, and independent cascade ranking) based on influence and influence in four real networks, two large networks (one directed, the other undirected) and two small networks (one directed, the other undirected) has been.

the acceptance of brands in the online environment is one of the most important topics in the field of information systems and brands, which has received less attention. In this research, the researcher has examined the relationship between the factors affecting consumer innovation and the performance of online brands with regard to the mediating role of customer interaction with the online brand (the case study of Ocala store in Mashhad). The statistical population includes all the citizens of Mashhad who buy online from Ocala, which is very large and uncertain. According to the characteristics of the statistical population and systematic random sampling and the use of Morgan's method, 384 sample units were considered. The researcher used a questionnaire made by the researcher based on documentary techniques to collect information and using face validity and using Cronbach's alpha reliability coefficient calculated a high reliability coefficient of 0.8 for it, the structural equation test was used to answer the research hypotheses. The results showed that customer interaction with the brand, the relationship between the factors affecting consumer innovation and brand performance. mediates in the online space (p = 0.0001 and 2.81 = t). Sub-hypothesis 1, there is a positive and significant relationship between factors affecting consumer innovation and brand performance in the online space (p = 0.0001 and t = 3.79). Sub-hypothesis 2, there is a positive and significant relationship between the factors affecting consumer innovation and the level of customer interaction with the brand (p = 0.0001 and t = 6.61). Sub-hypothesis 3, there is a positive and significant relationship between the amount of customer interaction with the brand and the performance of the brand in the online space (p = 0.0001 and t = 3.24). Therefore, in order to create effective and long-term relationships, it is necessary to know the effective bottom layers in consumer relations, and an insufficient understanding of emotional links destroys all the company's spent marketing costs.

Edges are one of the most important parts of an image. The border between two areas of the image that has a significant difference in brightness, color or texture is called an edge. Edge detection is a basic step in image segmentation and one of the most important steps to detect the characteristics of objects in an image. Recently, many researches have been carried out in the field of edge detection, each of which has tried to better detect the edges of the image. In this research, fuzzy theory and the concept of fuzzy clustering are used to detect the edge of digital images. At first, the pixels of the image are based on the amount of gray level. They are divided into clusters and then by determining the appropriate filters, the edge of the image is detected. The proposed method has recognized the edges of the image well, and has also shown remarkable performance in identifying the edges of the image that cannot be correctly recognized due to the inappropriate light level or noise. The results of this research showed that the proposed method has provided better results than usual methods in most cases and this is due to its good performance in detecting image details such as thickness and strong and weak edges, especially in images with lower resolution or lower contrast. It has performed very well.

Until recently, many researches have investigated the relationship between strategic orientation and company performance . Strategic orientation is an important and extensive field in business management literature. The strategic activities of the company can describe the general meaning of the strategic orientation that directly affects the performance of the company's superior performance. The present study is an analysis of the impact of strategic orientations on the implementation of green supply chain management practices and sustainable performance in Yazd Industrial Estate companies. In this research, the statistical population is 300 employees of Yazd Industrial City companies, using the Cochran formula, the final sample number is 168 people, after distributing the questionnaires, 150 questionnaires were collected. In this research, structural equation modeling using PLS and SPSS software was used. The results show that green entrepreneurship orientation has a significant impact on market orientation, green supply chain management practices, and knowledge management orientation. Also, knowledge management orientation has a significant impact on green supply chain management practices, and green entrepreneurship orientation has an impact on green supply chain management practices through knowledge management orientation. The strategic activities of the company can describe the general meaning of the strategic orientation that directly affects the performance of the company's superior performance.