درخت حوزه‌های تخصصی

Numerous face recognition systems employ deep learning techniques to identify individuals in public areas such as shopping malls, airports, and other high-security zones. However, adversarial attacks are susceptible to deep learning-based systems. The adversarial attacks are intentionally generated by the attacker to mislead the systems. These attacks are imperceptible to the human eye. In this paper, we proposed a feature-based masking iterative method (F-MIM) to generate the adversarial images. In this method, we utilize the features of the face to misclassify the models. The proposed approach is based on a black-box attack technique where the attacker does not have the information related to target models. In this black box attack strategy, the face landmark points are modified using the binary masking technique. In the proposed method, we have used the momentum iterative method to increase the transferability of existing attacks. The proposed method is generated using the ArcFace face recognition model that is trained on the Labeled Face in the Wild (LFW) dataset and evaluated the performance of different face recognition models namely ArcFace, MobileFace, MobileNet, CosFace and SphereFace under the dodging and impersonate attack. The F-MIM attack is outperformed in comparison to the existing attacks based on Attack Success Rate evaluation metrics and further improves the transferability.

This article aims to provide a model to explain the role of green human resource management in the resilience economy of small and medium-sized companies. The method of this research is a developmental-applied type of mixed research (qualitative-quantitative), which was used in the qualitative part of the Foundation (emerging) data method to identify components and indicators, and in the quantitative part, the descriptive-survey method was used. The statistical population in the qualitative part included experts (university faculty members) in the fields of human resource management, environment, and economics, after 28 interviews, the research reached theoretical saturation, and in a small part of the Cochran formula, there were 229 employees of the company. Industrial companies of Eshtehard town were selected. In the qualitative section, 13 codes were identified in process factors, 14 codes in prefixes, and 10 codes in suffixes. For the resistance economy, a researcher-made questionnaire with 31 indicators was used. The validity of the questionnaire was confirmed by the CVR method. Cronbach's alpha of the green human resources management questionnaire was equal to 0.761 and the resistance economy questionnaire was equal to 0.870. Two types of internal and external validity were used to validate the model. The results of the analysis of factor loadings of research components showed that there is a positive and significant linear relationship between each dimension of green human resource management. The results of the research model, it showed that among the identified factors, the antecedent dimension with a coefficient of 0.819, process factors with a coefficient of 0.797 and suffixes with a coefficient of 0.713, and finally, the coefficient of the impact of green human resources management on the resistance economy was obtained as 0.914, which shows the impact of 91 A percentage of aspects of green human resource management had resistance on the economy.

Purpose: One of the debates that has received much attention by many researchers in recent years and provided a platform to examine its various fields is customer experience management. Companies can differentiate themselves from competitors, create greater customer loyalty, and provide stronger brand relations via the experiences provided to their customers. The present study is aimed to identify the changes and progress made in customer experience management. Methodology: For this purpose, the papers available in the Web of Science database were analyzed over a period of 24 years (1998 to 2022) using scientometric methods. Findings: The results of the study present a comprehensive review of the field of customer experience management by identifying its basics, provide influential works and intellectual link between the works. It is noteworthy that the present analysis reveals more cited articles, key authors, keywords, intellectual turning points, and emerging research trends in this field. Conclusion: These results help researchers to perceive the boundaries of the researches conducted in customer experience management and gain valuable scientific information through which they can determine the development process of their future studies.

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.