Aksaray Üniversitesi Kurumsal Akademik Arşivi
DSpace@Aksaray, Aksaray 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 telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
Scheduling in the industry 5.0 environment: a bibliometric analysis
(Springer International Publishing AG, 2025) Başar, Ramazan; Engin, Orhan
The results of the bibliographic analysis evaluate the development of a field by examining publications, citations, and other metrics in the scientific literature. By bringing together the results of the analysis, trends in the literature, important figures, and the general development of the field can be understood. In this research, all scheduling studies in the Industry 5.0 environment that contained the words “Industry 5.0” and “scheduling” in the study title, abstract, and keywords were scanned using the Web of Science database. This database has a large corpus of data. As a result of the screening, a total of 62 studies were subjected to bibliometric analysis. The bibliometric package in the RStudio program was used for data analysis. As a result of the bibliometric analysis, various analyzes were performed according to year, author, keyword, source of publication, number of citations, institutions, and countries of publication, and the current situation related to academic writing was examined. According to the results obtained, industry 5.0-based scheduling studies are a very new topic that started to be studied in 2019 and has an annual growth rate of 25.99%.
Solar energy performance prediction with regression algorithm in machine learning based on weather condition: a case study
(Springer Science + Business Media, 2025) Coşgun, Atıl Emre
The escalating global demand for electrical energy, propelled by population growth, modern lifestyles, and technological advancements, underscores the necessity for transitioning toward renewable energy sources to mitigate the adverse impacts of fossil fuel dependency, notably global warming. Among renewables, solar photovoltaic (PV) energy systems have emerged as a prominent choice due to their eco-friendliness, sustainability, and minimal maintenance costs. However, the inherent unpredictability of renewable energy sources poses a significant challenge, particularly evident in the fluctuations of solar PV power generation caused by varying solar radiation and meteorological factors. This variability necessitates precise forecasting of solar PV power generation to optimize grid integration, ensure stability, and maximize benefits. Machine learning techniques offer a flexible and data-driven approach, capable of capturing complex nonlinear relationships between variables for enhanced forecasting accuracy. This paper is focused on regression algorithm forecasting approaches in machine learning for predicting solar PV power output under diverse weather conditions. For this, the regression learner tool from MATLAB’s machine learning has been used. By addressing key research questions, it aims to identify optimal forecasting approaches, assess their impact on solar energy production, and provide insights for policy formulation and regulation establishment, applicable to regions with limited research or data availability.
Using artificial ıntelligence in teaching health and physical education
(Taylor and Francis Ltd., 2025) Konukman, Ferman; Sortwell, Andrew; Filiz, Bijen; Tüfekçioğlu, Ertan; Yılmaz, Emine Büşra; Ünlü, Hüseyin
This article provides insight into the origin of AI, explores current research into the application of AI in HPE, and presents interdisciplinary research to provide practical and effective strategies for teachers.
Focusing on eco-friendly biosorption method: removal of reactive yellow-145 by natural ureolytic mixed culture
(Global NEST, 2025) Koçyiğit, Hasan; Manav, Esra
In this study, removal of reactive yellow 145 (RY 145) dyestuff by dry biomass of Ureolytic mixed microorganism culture (UMC), existing in domestic wastewater and various industrial wastewater, was studied. Optimum conditions of adsorption efficiency were tested. For this purpose, studies were conducted on the effect of initial dye concentration (30-50-75-100-150 mg/L), UMC amount (0.2-0.5-1.0-2.0 g), temperature (20-35-50 °C), pH (2-3-57-9) and contact time (1-5-10-20-30-60-120 min) on the efficiency of color removal. As a result of these studies, optimum conditions were revealed with 150 mg/L initial RY 145 concentration, 0.2 g dry UMC amount, 150 rpm agitation speed, 200C temperature, pH 2 and 30. minute contact time. After spectrophotometric calculations, according to Langmuir isotherm, it was found that 610.9 mg/g and the removal efficiency of tests was calculated as 84.5% under optimum conditions. It is seen that the process in which physisorption is at the forefront and single-layer adsorption occurs fits the Langmuir and pseudo-second order models. Thermodynamic data showed that the process occurred spontaneously and endothermically. The results support that UMC is both a promising and alternative environmentally friendly biosorbent for RY 145 removal.
Social work perspective on women’s empowerment women’s entrepreneurship
(CRC Press, 2025) Öztürk, Hatice
Women’s welfare is a priority issue in both national and international policies, and its importance has increased even more today. The emphasis on this issue in the Sustainable Development Goals is also noteworthy. In this regard, ensuring gender equality and empowering women is vital to ensuring that no one is left behind and to living a sustainable life. However, in most countries today, many women are exposed to inequalities due to factors such as poverty, injustice, and changing social and cultural norms. The social work profession focuses on the empowerment of women and benefits from its knowledge, skills, and value base in combating these inequalities. With an empowerment approach, social workers help unlock women’s potential and therefore encourage increased participation. Thus, women can realize their capabilities and have a say in politics, the health sector, education, and other fields. It is critical to recognize that female entrepreneurship is a powerful tool for women’s empowerment. Women’s entrepreneurship has important potential in terms of increasing women’s participation in working life and sustainability, as well as its impact on development. However, today’s deepening inequalities and inadequacies in implementation to ensure women’s welfare bring to the agenda the discussion of development approaches and policies. In view of this, the aim of this study is to discuss women’s entrepreneurship as a tool for empowering women from a social work viewpoint, benefiting from the existing literature.
