درخت حوزه‌های تخصصی

Taxes serve as a vital source of funding for governments and significantly influence economic growth and income distribution, which varies based on a country's level of development and economic framework. Recently, researchers have introduced methods to identify effective factors in preventing tax evasion. Most of these methods rely on basic techniques such as regression, structural equations, and non-intelligent methods that cannot effectively analyze the relationship between the values of the variables involved in this field. Therefore, in this study, we introduce a method that leverages artificial intelligence techniques, specifically a meta-heuristic optimization approach and a perceptron neural network. This method effectively analyzes the nonlinear relationships within the data while addressing both the intrinsic and extrinsic aspects of the data dimensions simultaneously. The research sample consists of 25 experts from the Tax Affairs Organization, and the study was conducted in the year 2022. The results indicate a high prediction accuracy of approximately 98%. Additionally, it highlights the significant role of various factors contributing to tax evasion, including income concealment, money laundering, economic crises, political trust, the weaknesses, and complexities of tax laws and regulations, inadequate clarification of tax laws, contradictions in legal tax articles, administrative bureaucracy, and an inefficient tax structure.

Image classification is a significant process in the field of computer science. It has applications in every field, such as spam detection in emails, medical diagnosis, image recognition, sentiment analysis, object detection, weather forecasting, pattern recognition, and security. Image classification deals with the grouping of images based on labels or characteristics. Feature extraction, feature selection, feature reduction, and classification are the main steps used to classify images. A medicinal and non-medicinal flowers data set is prepared by clicking images for the study. Methodology is used to achieve satisfactory classification results on the seeds, Wisconsin Diagnostic Breast Cancer, Heart Failure Clinical Records, and Wisconsin Prognostic Breast Cancer data sets, which are taken from the University of California, Irvine (UCI) repository. The proposed methodology suggests an efficient feature extraction and selection approach for data sets under consideration. An information gain-based genetic algorithm is used for feature reduction. It is performed on the extracted features to retrieve an optimized feature set. Fitness of the features is evaluated to choose the most relevant features. A neural network is used to classify the obtained feature subset. Better classification results are attained with the help of feature extraction and feature reduction.

Purpose: The purpose of this research is to evaluate the feasibility of using digital scientific resources and virtual education using augmented reality technology in the educational program of professors and doctoral students of Shahid Bahonar University of Kerman. Method: This research is descriptive-survey but is applied in terms of type and purpose. The statistical population of this research is all professors who teach in the doctoral program and doctoral students in Shahid Bahonar University of Kerman. Sampling method in this research is stratified random sampling. The sample size was 333 using Cochran's formula. Data collection tool, researcher-made questionnaire and the validity of the questionnaire were calculated by experienced professors and experts. The validity and reliability of the questionnaire were calculated using Cronbach's alpha test of 0.86. The collected data were first stored in the database and then by transferring this data to SPSS and EXCEL 23 software, the field of analysis of this data and their results was provided. Findings: The findings showed the possibility of using virtual educational resources and digital scientific resources, as well as the possibility of using augmented reality technology in educational and scientific research programs at Shahid Bahonar University of Kerman. There is a significant difference between the views of professors and doctoral students in the use of virtual educational resources and digital scientific resources in the educational and research programs of professors and doctoral students, while there is no significant difference between their views on the use of augmented reality technology. Conclusion: One of the most important reasons for the need to organize e-learning centers and institutions is the growing demand for education, especially higher education in the country, which has become a special social issue due to limited resources and educational capacity in the current education system. Ease of access and use of digital scientific resources and better understanding and mental creativity with the use of new technologies, including augmented reality, has necessitated the use and application of this technology in the educational programs of scientific and academic centers. Have a long-term and codified plan with instructions and rules related to augmented reality technology. Provide adequate funding, create hardware and software infrastructure, motivate, desire, sufficient expertise and empower the ability of faculty and students to use augmented reality technology.

Purpose : The customers’ behavior is influenced by their mental image of the Banks. Information resources are one of the factors that shape this mental image. Electronic word of mouth (eWOM) is considered a powerful advertising tool and an important and influential resource of information on the attitudes and behavior of customers. The aim of the present research is to investigate the position of eWOM among the advertising strategies that shape the mental image of customers at Bank Day branches in the western part of the country. Method : This research is applied in terms of purpose and descriptive and analytical in terms of nature. It is also a field survey in terms of data collection. The background of the research was compiled through library resources and web browsing. Then, 8 options and 9 criteria were identified, and a decision matrix questionnaire was designed. Therefore, the researcher’s decision matrix was used to collect data, and its content validity was confirmed by professors. The statistical population of this research consisted of all experts working at Bank Day Gharb branches in the country. In this study, 23 experts were selected using purposive and snowball sampling. Findings : Data analysis was performed using Taxonomy software. The results showed that the eWOM advertising strategy ranked third among the advertising strategies, following television advertising and internet advertising, in shaping the customer's mental image. Conclusion : Based on the research findings, the electronic recommendation advertising strategy is considered an important advertising strategy in shaping the mental image of Bank Day customers. There is a need for skilled managers to design appropriate websites and social networks and provide the necessary preparations for its development.