Kırşehir Ahi Evran Üniversitesi Kurumsal Akademik Arşivi
DSpace@Kırşehir, Kırşehir Ahi Evran 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 etkisimi artırmak için telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
The Scottish İnflammatory Prognostic Score: A Novel Biomarker for Predicting İn-Hospital Mortality in Acute Heart Failure with Reduced Ejection Fraction
(Elsevier Inc., 2025) Taş, Alperen; Tunca, Çağatay; Tanık, Veysel Ozan; Özlek, Bülent
Background: Acute heart failure with reduced ejection fraction (AHF) remains a leading cause of ED visits, hospitalizations, and in-hospital mortality. Objectives: To evaluate the prognostic utility of the Scottish Inflammatory Prognostic Score (SIPS) in patients with AHF. Methods: This retrospective study analyzed 508 patients admitted with AHF between November 2022 and November 2024. The SIPS was calculated based on albumin and neutrophil levels. Clinical and laboratory parameters were compared between survivors and non-survivors to identify predictors of all-cause in-hospital mortality. Results: At a median follow-up of 10 days (range 4–28), 63 patients (12.4 %) died. The mean age of the study population was 63 years, with non-survivors being older on average. Multivariable Cox proportional regression analysis revealed high SIPS values (HR: 2.335, 95 % CI: 1.044 - 5.221, p = 0.039), advanced age, elevated NT-pro-BNP levels, chronic renal failure, and low serum sodium as independent predictors of in-hospital mortality. When patients were categorized by SIPS scores of 0, 1, and 2, the associated mortality rates were 5.1 %, 14.0 %, and 46.0 %, respectively (p < 0.001). Additionally, ROC curve analysis indicated that a SIPS threshold of 0.5 effectively predicted in-hospital mortality, demonstrating a sensitivity of 77 % and a specificity of 58 % (95 % CI: 0.661–0.803, p < 0.001). Conclusions: This study is the first to analyze the association between SIPS and in-hospital mortality in patients with AHF. Integrating SIPS with other established risk factors may help improve the identification of high-risk AHF patients who could benefit from closer monitoring and intensified therapy, though further validation is warranted.
Some Novel Optical Pulses in Hydrodynamical Nonlinear Complex Equation using M-Truncated Fractional Derivative
(Nature Research, 2025) İlhan, Esin; Rehman, Shafqat Ur; Bilal, Muhammad; Baskonuş, Hacı Mehmet; Alawaideh, Yazen M.
This study investigates soliton solutions and dynamic wave structures in the complex Ginzburg-Landau (CGL) equation, which is crucial for understanding wave propagation in various physical systems. We employ three analytical methods: the Kumar-Malik method, the generalized Arnous method, and the energy balance method to derive novel closed-form solutions. These solutions exhibit diverse solitonic phenomena, including multi-wave solitons, complex solitons, singular solitons, periodic oscillating waves, dark-wave, and bright-wave profiles. Our results reveal new families of exact solitary waves via the generalized Arnous method and diverse soliton solutions through the Kumar-Malik method, including hyperbolic, trigonometric, and Jacobi elliptic functions. Verification is ensured through back-substitution to the considered model using Mathematica software. Additionally, we plot the various graphs with the appropriate parametric values under the influence of the M-truncated fractional derivative to visualize the solution behaviors with varying parameter values. This research contributes significantly to understanding wave dynamics in physical oceanography, and the unique outcomes explored in this research will play a vital role for the forthcoming investigation of nonlinear equations.
Determination of Quality Levels of Fish Oils Recovered from Trout Waste using Machine Learning and Odor Sensors
(Springer, 2025) Yavuzer, Emre; Yaprak Uslu, Dilek; Köse, Memduh; Yetişen, Mehmet; Alaşalvar, Hamza
[Not Abstract Available]
Is There A Place for Sdgs in Citizenship Education That Focuses on National İdentity? Perspectives of Social Studies Teacher Candidates in Turkey
(SAGE Publications Inc., 2026) Kuş, Zafer
This research investigates the incorporation of Sustainable Development Goals (SDGs) into civic education (CE) from the viewpoints of Turkish social studies teacher candidates. The relationship between national identity and global citizenship, in light of concerns like as globalization, migration, and environmental catastrophes, requires a redefining of CE. This research employs Q technique to investigate teacher candidates’ objectives and attitudes about the alignment of CE with SDGs, uncovering three diverse perspectives: National Identity, Kemalism, and Ecological-Critical Citizenship. Results underscore the necessity for educational reforms that harmonize national and international frameworks, promote environmental consciousness, and improve teaching methodologies to tackle global issues. Integrating CE with SDGs is crucial for cultivating critical, inclusive, and globally competent educators, which is vital for enhancing Turkey's sustainable development efforts and encouraging global citizenship.
Artificial Intelligence Image Processing with YOLO Algorithm for a Quadruped Robot
(Institute of Electrical and Electronics Engineers Inc., 2025) Köse, Memduh; Mert, Bünyamin; Kaygusuz, Melikhan; Ilgın, Hakkı Alparslan
This study focuses on a quadruped robot project where object detection and identification are carried out using a Raspberry Pi 4 Model B and the Raspberry Pi V4 camera module. To achieve this, the YOLO (You Only Look Once) family's YOLOv3 version was chosen, and it was integrated with the Darknet framework, developed by Joseph Redmon, which operates on the CUDA platform, under a single artificial intelligence network. Quadruped robots encounter various natural and artificial obstacles while moving, such as height differences, terrain conditions, distance variations, solid and liquid objects, as well as living beings. In this research, YOLO model and developed AI algorithms were used to recognize and locate these types of obstacles the robot may face during its walking process. The ultimate goal of the study is to develop a system that can detect and position objects and humans and analyze environmental factors. To this end, research on image processing for quadruped robots was conducted, and object detection was successfully achieved using YOLOv3.
