درخت حوزه‌های تخصصی

The current research mainly aims to investigate the effective factors in creating a food tourism brand in Shiraz. The statistical population includes all experts in the field of tourism and hotel management, food, cooking, and restaurant industry, and tourists, who were selected using the purposeful sampling method. First, 13 factors were identified according to research literature. The identified factors were given to 10 selected experts who were aware of the desired criteria. Then, the relationships between these factors were determined using the fuzzy Dematel method, and the answer to the second question was also determined. The results showed that the factor of investment in the field of food tourism, and using new advertising tools in this field are the most important thing in creating a food tourism brand in Shiraz. The parameters of food quality and food authenticity are the most effective in this area. In addition, creating a good feeling towards the brand and advertising, in this field are among the most effective parameters, respectively. Food tourism branding issue is the most important issues that should be considered in Shiraz. In this regard, it is possible to identify the foods of Shiraz as intangible cultural heritage, bring them to the national register, prepare their files for global registration in UNESCO, and conduct cultural and political consultations so that the files should be presented at the international level.

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.

Cancer is an abnormal cell growth that occurs uncontrollably within the human body and has the potential to spread to other organs. One of the primary causes of mortality and morbidity for people is cancer, particularly lung cancer. Lung cancer is one of the non-communicable diseases (NCDs), causing 71% of all deaths globally, and is the second most common cancer diagnosed worldwide. The effectiveness of treatment and the survival rate of cancer patients can be significantly increased by early and exact cancer detection. An important factor in specifying the type of cancer is the histopathological diagnosis. In this study, we present a Simple Convolutional Neural Network (CNN) and EfficientNetB3 architecture that is both straightforward and efficient for accurately classifying lung cancer from medical images. EfficientnetB3 emerged as the best-performing classifier, acquiring a trustworthy level of precision, recall, and F1 score, with a remarkable accuracy of 100%, and superior performance demonstrates EfficientnetB3’s better capacity for an accurate lung cancer detection system. Nonetheless, the accuracy ratings of 85% obtained by Simple CNN also demonstrated useful categorization. CNN models had significantly lower accuracy scores than the EfficientnetB3 model, but these determinations indicate how acceptable the classifiers are for lung cancer detection. The novelty of our research is that less work is done on histopathological images. However, the accuracy of the previous work is not very high. In this research, our model outperformed the previous result. The results are advantageous for developing systems that effectively detect lung cancer and provide crucial information about the classifier’s efficiency.