درخت حوزه‌های تخصصی

The widespread use of E-commerce websites has drastically increased the need for automatic recommendation systems with machine learning. In recent years, many ML-based recommenders and analysers have been built; however, their scope is limited to using a single filtering technique and processing with clustering-based predictions. This paper aims to provide a systematic year-wise survey and evolution of these existing recommenders and analysers in specific deep learning-based hybrid filtering categories using movie datasets. They are compared to others based on their problem analysis, learning factors, data sets, performance, and limitations. Most contributions are found with collaborative filtering using user or item similarity and deep learning for the IMDB datasets. In this direction, this paper introduces a new and efficient Hybrid Filtering based Recommendation System using Deep Learning (HFRS-DL), which includes multiple layers and stages to provide a better solution for generating recommendations.

The cybersecurity in the modern world has become global, and cyber attacks are becoming more complex and large-scale. In the system of civil and criminal justice, computer forensics helps to ensure the integrity of digital evidence presented in court cases. The purpose of this study is to develop scientifically sound proposals and recommendations for the implementation of tools for forensic research of computer tools and systems in the fight against cybercrime. The relevance of this study is due to the need to implement active ways to protect and combat cybercrime. To achieve the goal of the study, methodological principles and approaches of legal science were used. It is proposed to use computer forensic methods more widely research in the fight against cybercrime.This study identifies the types of computer forensics: forensics database; electronic forensics; malware forensics; criminology of memory; mobile forensics; network forensics. The authors foundlack of a regulatory mechanism to regulate cybersecurity, capture and use of digital evidence and the regulatory framework for international cooperation. To brought need in strengthening international cooperation and in developing appropriate policies and legislative initiatives of security and network and information systems, improvement legislation in the field countering cybercrime.

The purpose of this study is to perform a meta-analysis of the relationship between auditor characteristics and profit quality. In order to integrate the results of different researches and identify the factors that modulate the relationships between auditor characteristics and profit quality, in this research we will use meta-analysis methodology which is one of the quantitative statistical methods. In order to implement the meta-analysis method, they were identified and collected from the websites of foreign journals (articles published in the period 2005 to 2020) and the Internet site of domestic scientific research journals (articles published during the years 2006 to 2021) as a statistical population of the research. Systematic removal has finally analyzed 50 studies; The results of studies conducted in the period and around this relationship indicate that most of these studies are heterogeneous. In order to identify the cause of this heterogeneity, by dividing the research based on different criteria for measuring profit quality and auditor characteristics and calculating intra-group chi-square statistics, we found that these different measurement criteria used in research are one of the factors of contradiction in the results. There have been researches. In the following study, it was observed that there is no significant relationship between auditor characteristics with profit smoothing and timely profit and also between non-audit services provided by the auditor and profit quality, while in contrast, there is no significant relationship between auditor characteristics and quality of accruals; Profit stability; There is the ability to predict profit and conservatism.

This paper sought to address the feasibility of dissecting stock price momentum in the firms listed in Tehran Stock Exchange using financial statement analysis (FSA). Different variables including those related to profitability, financial leverage and liquidity, and operating efficiency were used in this analysis. The study sample consisted of 130 firms listed in Tehran Stock Exchange over the period 2008-2019. The results showed that fundamental factors affected stock price momentum for one year in the winning portfolio and for two years in the losing one; after this period, financial information did not have a significant effect on stock price momentum. Therefore, stock price momentum performance is a function of the conformance of the past price performance to fundamentals. The results from investment strategies based on the past price performance-fundamentals conformance indicated that fundamentals cause a significant difference in stock excess returns in winning and losing portfolios.

Traditional approaches applied in supply chain management consider only the physical logistic operations and ignore the financial aspects of the chain. In this study, a mathematical model has been developed to address the supply chain network design problem with a value-based management approach. This model integrates both operations and financial aspects to maximize the value created and measured by shareholder value analysis (SVA) as an objective function. The results attributed to the developed model and the basic model are compared. The results indicate that creating more value for the company and its shareholders is achievable with appropriate financial decisions. To validate and show the applicability of the proposed model, it was solved by GAMS software with data provided by literature. Finally, sensitivity analyses on financial parameters were performed to evaluate the results. The results clearly reveal the improvement of using the new approach and convince managers to take advantage of the proposed approach.

This study investigates the effects of stock anomalies on excess stock and unexplained returns of multifactorial models in the companies listed at the Tehran Stock Exchange. We selected a sample of 120 companies listed at the Tehran Stock Exchange from 2008 to 2019 using the Fama-Macbeth [18] regression approach. The results revealed that stock anomalies led to considerable differences in excess stock returns of different portfolios, implying that stock returns at different anomaly levels significantly differ. In addition, it was found that the anomalies related to stock characteristics greatly impacted explaining excess stock returns in the three-factor and five-factor models suggested by Fama and French. Besides, in different portfolios of the anomalies, the unexplained return rates were significantly different from each other. Moreover, in Fama and French's three-factor and five-factor models, different anomaly portfolios show significant differences in explaining excess stock returns.

INTRODUCTION: Lack of a comprehensive classification of crisis and emergency management in Helal houses has caused many losses in the Red Crescent Society of Iran. Therefore, the root of these problems can be identified and investigated with a thorough investigation. METHODS: This applied research was conducted using a hybrid design. In this research, field and library methods were used. The data were collected by using questionnaire and conducting in-depth interviews with managers, specialists, and experts of the country's crisis management organization and professionals until theoretical saturation. In the first stage, 24 interviews were conducted and we reached theoretical saturation in the 20th interview. In the second stage, relying on inferential statistics methods, 422 questionnaires were distributed. The statistical population of the research is the Red Crescent Society of Iran and its time domain is the second half of 2022. FINDINGS: After performing the three stages of open, central, and selective coding, the final research model was obtained in which, 6 general categories, 15 subcategories, and 49 main concepts are mentioned. CONCLUSION: The results demonstrated that the categories of human resources, organizational communication, and government policies are among the effective factors on crisis management in Helal houses in the Iranian Red Crescent Society in the critical condition of Covid-19 and the consequences of these categories have a significant impact. There are other problems and crises in the formation.

INTRODUCTION: Identifying and classifying hospital suppliers and choosing the right hospital supplier are based on some criteria, such as price, quality, timely product delivery, and after-sales service. METHODS: The research method was to select a suitable supplier through multi-criteria decision-making methods, including fuzzy TOPSIS and fuzzy Delphi. This research analyzed the selection criteria of hospital suppliers using fuzzy TOPSIS and fuzzy Delphi methods. The weight of the selected criteria and their importance were determined by holding interviews with hospital experts. In the next stage, the suppliers were evaluated, and finally, they were ranked using the TOPSIS fuzzy method. FINDINGS: In this research, the criteria for selecting suppliers were based on the criteria determined by Dickson. According to the fuzzy Delphi method, 7 criteria of product quality, timely delivery, final product price, after-sales service, technical ability, product position among competitors, and easy-to-use product were selected for supplier evaluation. CONCLUSION: The selection of a reliable supplier is becoming increasingly crucial given the critical role played by the healthcare sector, which includes hospitals and the Red Crescent as its constituents, the expanding development of technology, and the growing variety of medical equipment. According to the results obtained by the fuzzy Delphi method, the criterion of product quality with a score of 0.88 was chosen as the most important criterion, while the ease-to-use product index with a score of 0.7 was chosen as the least important criterion. The selection and evaluation of suppliers were accomplished through several different quantitative and qualitative indicators, such as cost, quality, timely delivery, and after-sales service. As a result, companies must choose key indicators and suitable suppliers because the right supplier leads to a reduction in purchase costs, as well as an increase in the quality of the products and ultimately the success of the organization in reaching its goals.