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It is important for banks, which are of great importance for the national economy, to use their resources effectively and efficiently due to competition in the sector. For this reason, performance evaluations of banks should be made, and necessary measures should be taken as a result of the evaluation. The purpose of this study is to analyze the financial performance of participation banks in Turkey, which are increasing their share in the sector with an increasing momentum. In the study, the financial performances of 6 participation banks operating in the Turkish Banking Sector between 2019 and 2023 were compared using Multi-Criteria Decision-Making Methods. While the SD method was used for weighting the 8 criteria selected as a result of the literature research, the GIA method was used for the success rankings of the banks. The evaluation criterion with the highest impact on the financial performance of participation banks in the periods included in the analysis was “Net Income / Total Assets (ROA)” in 2019, while this criterion was “Total Funds Collected / Total Assets” in 2020 and 2021, when the pandemic was experienced. The evaluation criterion with the highest impact on financial performance in 2022 and 2023, the recovery period after the pandemic, was “Net Income/ Total Equity (ROE)”. On the other hand, it has been determined that the evaluation criterion with the least impact on the performance of participation banks varies over the years. In 2019 and 2020, Ziraat Katılım was the most financially successful participation bank, Kuveyt Türk in 2021 and 2022, and Vakıf Katılım in 2023. In all years except 2021, Albaraka Türk has been the lowest performing bank in terms of financial success. In the last four years except 2019, Vakıf Katılım and Emlak Katılım were in the top three except for 2023.

Early diagnosis and effective monitoring of diabetic retinopathy and glaucoma are essential for preventing vision loss and improving patient outcomes. These conditions, if detected early, can be managed effectively, reducing the burden on healthcare systems and improving quality of life for patients. This study presents the development of a user-friendly software interface designed to assist healthcare professionals in diagnosing these conditions more efficiently. We developed a custom 11-layer Convolutional Neural Network (CNN) architecture, beginning with a rescaling layer and incorporating data augmentation techniques. The primary architecture consists of three convolutional layers containing 16, 32, and 64 filters, respectively, each followed by max pooling layers. A dropout layer with a 0.7 rate was incorporated to reduce the risk of overfitting. The network also features a flattening layer, a dense layer with 128 neurons for feature extraction, and an output layer tailored to the number of classes. For glaucoma detection, a specialized preprocessing step focusing on the optic disc reduced validation loss by approximately 20%. Additionally, a manual zooming feature was developed to enhance diagnostic accuracy in complex glaucoma cases. The algorithms for diabetic retinopathy were meticulously designed to identify and highlight pathological areas, such as edema and hemorrhage. This approach facilitates precise visualization of vascular structures and significantly enhances the model's capability to provide accurate and timely diagnoses. The architecture that emerged upon conclusion of the study demonstrated an accuracy of 98% for diabetic retinopathy and 85% for glaucoma. This study highlights the potential of advanced deep learning combined with practical tools to improve diagnostics, offering clinicians a reliable system to enhance patient outcomes.

Digitalization has profoundly transformed the production, distribution, and consumption processes of the film industry, giving rise to new economic and cultural dynamics. Traditional analog technologies have been replaced by digital encoding, artificial intelligence-based content recommendation systems, and online platforms, thus lowering production costs and facilitating global reach. Platforms such as Netflix, Amazon Prime, and Disney+ analyze user data to generate content in a data-driven manner, establishing what has come to be known as “platform capitalism” within the film sector. While this development offers global visibility for independent cinema, it has also introduced risks of monopolization and content standardization due to the growing economic power of major media corporations. The economic sustainability of movie theaters, especially during the pandemic, has been severely challenged by direct online distribution strategies and the shortening of theatrical release windows. Digitalization has brought both aesthetic and technical innovations to the forefront. Although artificial intelligence reduces costs and accelerates processes in screenplay development and post-production, it raises the concern that creative originality may be overshadowed by formulaic approaches. On the other hand, VR, AR, and metaverse-based technologies have the potential to redefine conventional cinematic practice by providing audiences with interactive and individualized experiences. When viewed within the broader framework of cultural industries, these advancements prompt inquiries into how artistic production will be shaped by escalating market pressures and the extent to which viewers’ perceptions of reality may be altered. In conclusion, the impacts of digitalization on the film industry are multifaceted, encompassing the future dynamics that will reconfigure production, distribution, and audience engagement.

This study aims to investigate the potential impact of Industry 4.0 technology and its associated technological advances on Supply Chain management performance from a sustainability perspective. Many companies are adopting Industry 4.0 technologies to ensure operational sustainability against the increasing effects of climate change, reduce natural resources and increase consumer awareness on environmental issues. Although the concepts of smartness and sustainability are intertwined in ready maturity assessment, no studies focus on these concepts simultaneously. The study attempts to conceptualize and develop an operational framework supported by investigating the impact of Industry 4.0 technology on the functions of supply chain management from a sustainability perspective by conducting a literature review. It is verified by preparing a survey with production engineers at the Tümosan factory operating in Konya, which produces tractors in the automotive sector, and analyzing the results. The maturity level of sustainable supply chain management was examined by taking the basic information from the literature review presented in the previous chapters of the study. The model evaluates to what extent Industry 4.0 technologies are integrated with supply chain management in the social, environmental and economic dimensions, which are the three basic dimensions of the concept of sustainability, how much they contribute, how much they are included in organizational goals and what level of performance and maturity they have reached. Thus, by supporting sustainability and innovation activities by carrying out continuous R&D studies in the adaptation of industry 4.0 technologies to supply chain management, positive results such as evaluating existing situations with a performance and maturity approach, measuring performance and maturity and setting targets can be achieved. The functions of the Industry 4.0 technologies and sustainable supply chain maturity approach model are designed as 12 Industry 4.0 technologies and 10 sustainability functions in three main dimensions social, environmental and economic.