Kapadokya Üniversitesi Kurumsal Akademik Arşivi
DSpace@KÜNASİS, Kapadokya Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.
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Green AI: Sustainability-Focused Artificial Intelligence Approaches and Future Strategies
(Platanus Publishing, 2025) Taş, Özge; Deniz İsmail Emre; Deniz İsmail Emre
Green artificial intelligence (AI), in conjunction with sustainability, is an emerging interdisciplinary field. Its primary focus is the enhancement of the environmental sustainability of AI technologies, in addition to the leveraging of AI to address ecological challenges. Since its inception around 2019, Green AI has garnered attention due to the escalating concerns about the energy consumption and carbon footprint associated with advanced AI systems, particularly large language models (LLMs). This movement advocates for responsible technological development that aligns with global sustainability goals and addresses the pressing ecological impacts of AI advancements.Green AI encompasses two primary variants: The concept of "Green-in-AI" aims to minimise the environmental impact of AI technologies themselves by optimising algorithms and energy use. In contrast, "Green-by-AI" employs AI to address environmental issues, such as enhancing agricultural practices and biodiversity monitoring. As organisations increasingly rely on AI for various applications, the potential for significant reductions in greenhouse gas emissions through efficient energy management and resource allocation has become a focal point of research and application (Yang J., E.i. 2019; Brevini, B. 2020). Notwithstanding the promise of Green AI, notable controversies persist regarding its dual role as both a tool for sustainability and a contributor to environmental degradation. To illustrate, the energy-intensive processes necessary to train voluminous AI models can engender considerable carbon emissions, thus giving rise to questions surrounding the overall ecological merits of such technologies. Projections indicate that data centres, which are pivotal for AI operations, may consume up to 21% of global energy demand by 2030. This necessitates an urgent reevaluation of energy practices within the tech sector. As the field evolves, it faces challenges such as algorithmic bias, regulatory inadequacies, and the need for enhanced energy efficiency. The term "stakeholders" is employed to denote the individuals or groups with a vested interest in the subject under discussion. Ultimately, the future of Green AI will depend on balancing technological innovation with sustainable practices to foster a greener and more equitable world.
KUANTUM HATA DÜZELTME ENTEGRASYONU İLE GROVER SALDIRILARINA DİRENEN HİBRİT SİMETRİK ŞİFRELEME YAKLAŞIMI
(Serüven Yayınevi, 2025) Taş, Özge
Kuantum Hata Düzeltme Entegrasyonu ile Grover Saldırılarına Direnen Hibrit Simetrik Şifreleme Yaklaşımı
Hibrit şifreleme yaklaşımı kuantum hata düzeltme entegrasyonu ve grover saldırılarına karşı direnç göstermektedir. Gelişen kuantum hesaplama yöntemleriyle kriptografik sistemlerin güvenliğini arttırmak için yenilikçi hesaplama yöntemleri geliştirilmiştir.Kuantum algoritması olan grover algoritması geleneksel simetrik şifreleme yöntemlerini tehdit ettikçe kuantum hata düzeltmeyi içeren hibrit şifreleme yöntemleri geliştirilmesi giderek önemli hale gelmiştir. Bu yaklaşımla hassas verilerin korunması kuantum tehtidlerinin oluşturduğu diğer güvenlik açıklarını ele almak için simetrik ve asimetrik şifreleme yöntemlerinin birleşim yöntemleri kullanılmaktadır. Hibrit simetrik şifreleme çalışma prensibi simetrik bir anahtarın verilerin büyük bir kısmını şifrelediği ve asimetrik sistemin bu simetrik anahtarı ilettiği çift katmanlı bir mekanizma kullanır. Kuantum hata düzeltme tekniklerine entegre ederek bu yöntem şifrelenmiş verilerin iletim sırasında hatalara ve saldırılara karşı bütünlüğünü korumayı amaçlar ve bu durum modern iletişim altyapılarının güvenliğini sağlamada kritik önem taşır.Bu tür gelişmeler yalnızca gizliliği ve verimliliği sağlamakla kalmaz aynı zamanda kriptografik sistemlerin kuantum teknolojilerine hakim olduğu bir sistem sağlar.Bu hibrit yaklaşım önemli düzeydeki etkileri gelişmiş güvenlik önemlerinin alınmasına olanak sağlayarak , siber güvenlik alanında kuantum hesaplama zorluklarına uyum sağlama konusunda artan ihtiyaçlara yanıt sunar.Dünya çapındaki kurumlar Grover algoritmasının etkilerini ve yerleşik şifreleme standartlarına yönelik potansiyel risklerini araştırırken kuantum hata düzeltmenin hibrit şifreleme çözümlerine entegrasyonu veri güvenliğini korumak için proaktif bir önlem olarak görülmektedir. Bu değişimler özellikle geleneksel ve kuantum dirençli metodojiler arasındaki kriptografik uygulamaların geleceği hakkında önemli tartışmalara yol açmaktadır. Alanda yapılan önemli çalışmalar bu hibrit sistemlerin uygulanmasına, anahtar boyutlarında gerekli ayarlamalara ve kuantum sonrası kriptografik çözümlere geçişe odaklanmaktadır. Kuruluşların bu teknolojileri entegre etmesi için klasik ve kuantum teknolojilerinin getirdiği tehditlere dayanabilen güvenli ve ölçeklenebilir kriptografik çerçevelerin geliştirilmesinin araştırmalar için kritik öneme sahiptir.
An Innovative Multiparametric Sensor Design for Detecting Microplastics and Heavy Metals
(Kaunas University of Technology, 2025) Dal, Ekrem Kürşad; Güneş, Adem; Kılıç, Recai
Microplastics and heavy metals are materials that harm the environment and living organisms. Rapid detection enables their control or the identification of their sources. Conventional detection methods are expensive and require expert interpretation. The proposed sensor system detects these materials and evaluates their concentrations using a trainable multilayer perceptron algorithm. The system consists of twenty-two different light spectrum LEDs and eighteen narrow bandwidth photodiodes. The absorbance of incoming light and the shifted bandwidths in the spectrum can be evaluated by assessing multiparametric optical events. The study examines water samples containing eight different heavy metals, namely arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), and zinc (Zn), along with three types of microplastics: melamine particles with a diameter of 8 μm, polystyrene particles with a diameter of 8 μm, and polystyrene particles with a diameter of 10 μm. Classification was performed in a concentration-dependent and concentration-independent manner. The system performance was improved by selecting features using the Ranker method of the InfoGain algorithm. Measurements were performed without applying any indicator chemicals. The system demonstrated high success in concentration-independent evaluation and acceptable concentration accuracy for heavy metals.
Self‐Efficacy of General Practitioner Family Physicians in Mental Health Services: A Cross‐Sectional Study inTurkey
(Wiley, 2025) Güden, Emel; Borlu, Arda; Olguner Eker, Özlem; Özsoy, Saliha; Baykan, Zeynep
Rationale
The role of primary care physicians in mental health services is increasingly significant. However, there is a lack of research on general practitioners' interest and self-efficacy in providing mental health services.
Aims and Objectives
This study aims to assess the interest and self-efficacy of general practitioners in mental health services and to identify their educational needs in this area.
Methods
This study employs a cross-sectional design. A total of 461 family physicians are working in primary care health services in Kayseri, Turkey. The study sample included 415 general practitioners who had not received specialist training in family medicine after graduating from medical school. Face-to-face surveys were conducted with 270 general practitioners who agreed to participate in the study. The survey included questions about demographic characteristics, postgraduate training, experiences related to mental health, knowledge of mental health and medication treatment, self-evaluations of self-efficacy in mental health services, and requests for education on the subject.
Results
General practitioners reported low self-efficacy in the use and dosage of psychiatric medications (11.9%), but felt more competent in relation to drugs with addictive potential (34.4%). However, they generally perceived their competence in the use and monitoring of psychiatric medications to be low. The area where they felt least competent in managing mental illnesses in primary care was “intervention in suicide.” Their awareness and coordination regarding community mental health centers, as mental health service providers, were found to be low. Overall, general practitioners perceived themselves as inadequately competent in tracking and managing mental illnesses.
Conclusions
General practitioners acknowledge that mental health services are a primary care responsibility. However, there is a need to increase their self-efficacy in providing mental health services at the primary care level. Since all participants in this study were public employees, continuing mandatory postgraduate mental health training is crucial. Additionally, strengthening collaboration and coordination mechanisms, as well as providing more effective referrals to community mental health centers, is essential. These efforts will significantly contribute to improving the community's mental health.
Keywords: community health care, competence, general practice, mental health, physicians, primary care, self assessment
Investigation of the effect of colorless distributed combustion method on the flame of methane/hydrogen fuel mixture using image processing method
(Hydrogen Energy Publications LLC. Published by Elsevier Ltd., 2025) Alabas, Bugrahan; Kumuk, Osman
In a period when zero-emission combustion studies are gaining importance, researchers continue their research on alternative fuels. Although different alternative fuels are tested in combustion studies, the production and storage capabilities of these fuels also affect industrial practices. For this purpose, in this study, the combustion characteristics and emission behaviors of methane gas enriched with H2 at a volumetric ratio (20%), which can be transported in existing natural gas lines without any major changes, were examined. To solve the high flame speed problem caused by the hydrogen content of the fuel mixture, colorless distributed combustion conditions were proposed, and experiments were carried out. In the experiments, thermal power (5 kW), equivalence ratio (0.7), and number of vortices (0.4) were kept constant. The flame was exposed to external acoustic forcing frequencies in experiments under different conditions, and dynamic pressure oscillations were recorded. Addi tionally, in this study, flame image processing was performed with open-source software. The results showed that increasing the N2 ratio in the oxidizing air increased the resistance to acoustic disturbances. While flame stability increased in the mixture containing 19% O2 compared to standard air combustion conditions, when the O2 rate was reduced to 18%, the flame experienced blowoff instability under strain. The change in stability varied in direct proportion to the flame thickness and length. On the other hand, while CDC combustion conditions reduced NOX emissions in flue gas to almost zero, they caused an increase in CO emissions.
