درخت حوزه‌های تخصصی

This paper provides a comprehensive overview of the evolving Artificial Intelligence (AI) threat to cybersecurity, emphasizing the urgent need for finance leaders and cybersecurity professionals to adapt their strategies and controls to effectively combat AI-powered scams and cyber-attacks. The study delves into the specific ways in which AI is being used maliciously in cybercrime, such as enhanced phishing and Business Email Compromise (BEC) attacks, the creation of synthetic media including deepfakes, targeted attacks, automated attack strategies, and the availability of black-market AI tools on the dark web. Furthermore, it highlights the critical need for enhanced cybersecurity strategies and international cooperation to combat cyber threats effectively. The findings of this study provide valuable insights for finance leaders, cybersecurity professionals, policymakers, and researchers in understanding and addressing the challenges posed by generative AI in the cyber threat landscape.

Purpose: The key to startup success is a brand-centric approach that combines brand leadership strategy with creative, targeted, and cost-effective business methods. In the brand-centered approach, all company processes revolve around the development of brand identity in continuous interaction with customers, to create long-term competitive advantages for the brand. The purpose of this research is to investigate the impact of entrepreneurship-based branding in cyberspace on the performance of startups.Method: The current research is of an applied type and with a mixed method and a sequential qualitative-quantitative approach, first qualitative and then quantitative data was collected and analyzed. Due to the small size of the population, sampling was not done and all 52 people were examined. Smart PLS software was used to analyze quantitative data and test research hypotheses and implement structural equation modeling. Confirmatory factor analysis was also used to test the significance of the relationships and the fit of the obtained measurement models. To analyze the data and test the research hypotheses, the structural equation modeling method was applied.Findings: Qualitative findings showed that the branding model based on entrepreneurship in cyberspace includes six main themes and 18 sub-themes. Causal factors include risk-taking categories, business situation analysis, and brand content capabilities; Background factors include the categories of brand organizational structure, market orientation, and brand orientation; intervening conditions include the categories of legal infrastructure, customer characteristics, and economic uncertainty; the central category includes the three categories of brand vision depiction, brand integrity and entrepreneurial capabilities; strategies including three categories of brand positioning, strategic planning for branding and value creation; And the consequences include three categories of competitive advantage, strategic brand development and brand identity development. Quantitative findings showed that the causal conditions of branding with a score of 26.719 has a positive and significant effect on entrepreneurial branding; Entrepreneurial branding with a score of 4.873 on value-based brand positioning; And value-based positioning with a score of 29.960 has a positive and significant effect on the performance of startups.Conclusion: The results indicate that the branding model based on entrepreneurship in cyberspace and its impact on the performance of startups includes six main themes and 18 sub-themes, and branding based on entrepreneurship in cyberspace has a positive and significant effect on the performance of startups.

The application of machine learning technologies for cancer detection purposes are rising due to their ever-increasing accuracy. Melanoma is one of the most common types of skin cancer. Detection of melanoma in the early stages can significantly prevent illness and fetal death. The application of innovative machine learning technology is highly relevant and valuable due to medical practitioners' difficulty in early-stage diagnoses. This paper provides an open-source tutorial on the performance of an algorithm that helps to diagnose melanoma by extracting features from dermatoscopic images and their classification. First, we used a Dull-Razor preprocessing method to remove extra details such as hair. Next, histogram adjustments and lighting thresholds were used to increase the contrast and select lesion boundaries. After using a threshold, a binary-classified version of image was obtained, and the boundary of the lesion was determined. As a result, the features from skin tissue were extracted. Finally, a comparative study was conducted between three methods which are Artificial Neural Network (ANN), Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). The results show that ANN could achieve better accuracy (83.5%). In order to mitigate the biases in existing studies, the source code of this research is available at hadi-naghavipour.com/ml to serve aspiring researchers for improvement, correction and learning and provide a guideline for technology manager practitioners.

Purpose: This research aims to identify the factors affecting social network marketing based on gaining a competitive advantage and designing a model related to the communication between them.Method: This research is applied in its purpose, and conducted using a mixed approach (qualitative and quantitative). In the qualitative phase, first by reviewing the literature in the field of social network marketing and using the meta-combination method, the factors affecting it were identified and divided into three categories. subsequently, the relationships between these factors were determined and analytically analyzed using the interpretative structural modeling approach. In the modeling section, a questionnaire was distributed among experts selected through snowball sampling.Findings: The results of this research led to the classification of factors affecting social network marketing based on gaining competitive advantage and designing a model of these factors. In this model, the categories of organizational and structural resources (responsiveness to customers, service quality), marketing (attracting more customers, efficiency), and competitive advantage based on social media (branding, profitability), indicate the factors and the way of communication and interaction of these factors.Conclusion: Finally, the interpretation of the model, analysis of its levels, and the relationships among dimensions were discussed and solutions were provided in this regard.

Purpose: The main purpose of this research is to assess the feasibility of using VSAT satellites in the information services of university libraries.Method: The research method is a survey using the TOPSIS model, which indicates that the optimal method of providing the Internet is the method that has the greatest distance from negative factors and the least distance from positive factors. The opinions of user organizations, i.e. academic libraries and information centers, have been examined to clarify the necessity of using this method as well as its characteristics and advantages compared to other ways of providing the Internet.Findings: The findings show that VSAT satellite internet can have better conditions for providing services compared to other services such as ADSL, optical fiber, Wi-Fi and Wi-MAX. Also, their assessment determined that VSAT satellite internet is currently the best way to provide internet based on the criteria of service, support, cost, trust and quality, and ranks second in criteria such as security, confidentiality and service. In conclusion, the priority of solutions to provide library internet using TOPSIS analysis is: VSAT service; Optical fiber; ADSL service; Wi-Max services and wireless services.Conclusion: The results indicate that the VSAT satellite network, with advantages in the use of Internet services by libraries, plays an important role in improving the quality of these services.

The article proposes a methodical approach to assessing the competitiveness of enterprises in the logistics infrastructure of the Black Sea region in the context of the strategy of the development of the Black Sea. The article is presented is the author's interpretation of the steel development of the territory and injected into the logistic infrastructure. It was proposed of the methodical approach to assessing the competitiveness of enterprises-moving enterprises in the development of the territory, as one of the stages of the methodology for assessing the development of the territory in the region. It have been identified Indicators for assessing sustainable development in assessing the competitiveness of key enterprises in the region and in terms of using the TOPSIS model. The application of the TOPSIS model allows to assess the value of the aggregate indicator of sustainable development of a region or territory, taking into account the impact of the level of competitiveness of its key enterprises. In the context of this approach, it is studied and evaluated the level of competitiveness of powerful enterprises of the Black Sea region, which form the logistics infrastructure of the region. It was  determined their influence on the strategy of sustainable development of the territory. This approach allowed to expand the methodology for assessing the assessment of sustainable development of the territory through the methodology of assessing the competitiveness of enterprises-engines of development of the territory, as one of the stages of the overall methodology.

The paper considers the possibilities of optimizing the search for agricultural information based on Shannon information entropy criterion. A comparison of the degree of uncertainty of information search through the Internet – search systems with similar indicators of Ukrainian agricultural websites. According to the number of hit count in Ukraine in July 2020 to the search engine, which consists of 10 sources, and to agricultural websites (43 sources) by estimating entropy, a conclusion was made about the significant degree of dispersion of agricultural information sources. It should be emphasized that the artificial division into 4 categories (AgroMedia, Agrotrade web resources, Information and advisory resources, Specialized web resources) did not improve the situation according to the degree of uncertainty compared to the search engine system. As for the entropy index, for almost all 4 categories of entropy indices (heterogeneity or diversity) is close to the case of uniform distribution, i.e., the same hit count of all possible resources (their number for all categories is approximately the same 10-11). As a result of the analysis of the potential client base of electronic consulting, it can be quantified as 4,700,000 of agricultural households and about 50,000 small and medium-sized farms. The transition to the land market is likely to lead to a substantial increase in the number of the latter. It was demonstrated that the current educational level of household owners indicates both the need to increase this indicator and the presence of a close relationship with the existing system of professional advisory in Ukraine, which operates in recent years through self-sufficiency and uncertain financial support from central and regional authorities. The existing official database of advisors should be restructured in line with the call of the times to reduce the degree of uncertainty in finding a specialist of the desired profile.

After the Coronavirus diseases (COVID-19) outbreak, the Whole world witnessed the strangest buying behavior within the customers. Suddenly masks, hand sanitizers, and toilet papers became the priority list of the customers. High demand and lesser availability of essentials products like masks, toilet papers, and hand sanitizers create a chaotic situation inside the retail outlet's stores.  The buyer’s behavior and the chaotic scenario inside a retail outlet drew the attention of several consumer psychologists, academicians, and researchers. A panic buying situation is the most common behavior that exists in a time of crisis. This paper discusses the panic buying situation briefly during COVID-19. However, a few types of research and studies were captured in the panic buying behavior. The current study examined the factors that influenced the customers buying decisions during the COVID-19 outbreak and secondly, it examined to what extent the buying decision of a customer creates a panic situation. Furthermore, the study looked at the emotional and cognitive responses of the individuals which play a pivotal role in influencing customer decision making the journey. Qualitative content analysis and thematic methodology were considered for data analysis. The results indicated that fear and uncertainties were the key emotional responses; whereas rumors, fallacious thinking, and survivalist psychological were the key cognitive responses that influenced the customer decision journey.