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Conference Object Factors Affecting Entrepreneurial Activity in an Emerging Economy in the Case of Turkey: the Role of the Covid-19 Pandemic(Academic Conferences and Publishing International Limited, 2024) Usul, N.; Karadeniz, E.; Özdemir, Ö.This paper seeks to study factors influencing the early stages of entrepreneurship within the context of coronavirus pandemic, specifically within an emerging country. We utilize from a unique dataset collected by Global Entrepreneurship Monitor which is the sole global research repository compiling data on entrepreneurial activities and individual entrepreneurial attributes across 50 countries worldwide. In particular, this study focuses on the GEM survey data pertaining to Turkey during the period coinciding with the COVID-19 pandemic in the year 2021. The analysis is done by binary logistic regression with dependent variable being total entrepreneurship activity. Findings indicate that opportunity-driven respondents, with high-status aspirations, possessing necessary skills and acknowledging the challenges of their entrepreneurial environment, are the ones who show a higher probability of engaging in entrepreneurial activities. While these variables have been scrutinized in existing literature, our contribution lies in examining their effects within an emerging market, a relatively understudied context, particularly in the aftermath of a global pandemic. Results suggest that the individuals reporting a substantial increase in income during the pandemic, and perceiving a harder business environment to start a new venture show elevated probabilities of becoming an entrepreneur. These two are the pandemic-related variables demonstrating statistical significance, which highlights the fact that this period created its entrepreneurs, who exploit high resilience and dynamic capacity to adapt to crisis times. They experienced a significant increase in their income, capitalized on their comparative advantage in entrepreneurial skills within an environment where starting a business is not easy and took advantage of the opportunities seeking for high status using their adaptive capacity. These findings are consistent with Theories of Resilience and Dynamic Capabilities. Finally, younger respondents are more inclined to engage in entrepreneurial activity, which is consistent with the existing literature. In light of these findings, policymakers are encouraged to invest in educational programs for potential entrepreneurs to enhance their self-efficacy, given that the necessary skills for business initiation emerge as a pivotal factor for engaging in entrepreneurial activities. Moreover, creating platforms for successful entrepreneurs to share their experiences could amplify the perceived prestige associated with entrepreneurship, which may attract potential entrepreneurs. © 2024 Academic Conferences and Publishing International Limited. All rights reserved.Article Deep Learning Based Covid-19 Detection Using Computed Tomography Images(Prof.Dr. İskender AKKURT, 2024) Yılmaz, A.A.; Sevinç, Ö.The infectious coronavirus disease (COVID-19), seen in Wuhan city of China in December 2019, led to a global pandemic, resulting in countless deaths. The healthcare sector has become extensively use of deep learning (DL), a method that is currently quite popular. The aim of this study is to identify the best and most successful deep learning model and optimizer approach combination for COVID-19 diagnosis. For this reason, several DL methods and optimizer techniques are tested on two comprehensive public data set to select the best DL model with optimizer technique. A variety of performance evaluation metrics, including f-score, precision, specificity, and accuracy, were used to assess the models' effectiveness. The experimental results show that the most suitable and effective architecture is DenseNet-201 in the network comparison, which achieved a 98% accuracy rate using the AdaGrad optimizer and 200 iterations. © IJCESEN.
