Welcome to the Koç University Institutional Academic Repository
The Koç University Institutional Academic Repository (KUHub Research) is a state-of-the-art academic repository that consolidates all academic outputs—such as articles, conference proceedings, theses, research data, and more—produced by the university since its establishment in 1993.
KUHub Research adheres to the principles of Open Access and FAIR (Findable, Accessible, Interoperable, Reusable), providing access to the bibliographic records, research data, and full texts of research outputs. Equipped with innovative features such as Author Profile pages and enhanced tools, KUHub Research aims to enhance the visibility of researchers both nationally and internationally. KUHub Research aims to preserve and maintain Koç University's valuable academic legacy for future generations while also serving the needs of today’s researchers.
For more information or inquiries please contact openaccess@ku.edu.tr
Recent Submissions
Simple and green process for silk fibroin production by water degumming
(American Chemical Society, 2025-01-05) N/A; KUYTAM (Koç University Surface Science and Technology Center); Department of Chemistry; Department of Chemical and Biological Engineering; Department of Molecular Biology and Genetics; Atay, İpek; Yağcı, Mustafa Barış; Sürme, Saliha; Kavaklı, İbrahim Halil; Yılgör, Emel; Yılgör, İskender; College of Sciences; College of Engineering
Silk fibroin (SF), a natural polymer with very desirable physicochemical and biological properties, is an ideal material for crafting biocompatible scaffolds in tissue engineering. However, conventional methods for removing the sericin layer and dissolving SF often involve environmentally harmful reagents and processes, requiring extensive dialysis procedures to purify the fibers produced. Such processes may also damage the surface and bulk properties of the SF produced. Here, we report a simple, green water degumming method, in which almost complete sericin removal of 30% by weight is achieved in 6 h in boiling water. The SF produced is easily dissolved in formic acid/orthophosphoric acid (90/10, 85/15, and 70/30) mixtures, eliminating the need for salts like LiBr and CaCl2 followed by dialysis and freeze-drying, thus simplifying the process significantly. Additionally, our findings demonstrate significantly enhanced cell viability in electrospun poly(lactic acid)/SF blends. Overall, SF production via water degumming offers an eco-friendly pathway for generating bioactive scaffolds in tissue engineering applications.
A centralized frost detection and estimation scheme for Internet-connected domestic refrigerators
(Elsevier Science Ltd, 2025) Department of Mechanical Engineering; MARC (Manufacturing and Automation Research Center); Graduate School of Sciences and Engineering; College of Engineering; GRADUATE SCHOOL OF SCIENCES AND ENGINEERING; Research Center
Frost accumulation on heat exchange units is a significant problem in refrigeration systems, adversely affecting their operating performance and thereby leading to increased power consumption. Therefore, timely detection and accurate quantification of frost are crucial for effective defrosting strategies. This study presents a novel centralized cloud-based IoT scheme for frost detection and thickness estimation. The image processing is performed on the cloud server to process evaporator coil images for frost thickness quantification. Experiments were conducted on a domestic refrigerator to assess the effectiveness of the proposed image-processing approach and determine latency and processing time. The presented scheme effectively quantifies frost thickness on the evaporator in the 1-5 mm range with a 10.8% error margin. The total inference time, which includes image acquisition, pre-processing, transmission latency, and frost thickness estimation, is approximately 5.15 seconds. The results demonstrate that the proposed image processing method performs comparably to conventional sensors and similar image processing techniques. Moreover, the centralized cloud-based IoT architecture presented effectively meets the scalability demands of consumer refrigerators.
Water and thermal management in PEM fuel cells using feasible humidity plots and model predictive controllers
(Pergamon-Elsevier Science Ltd, 2025) Yildiz, Deniz Sanli; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; College of Engineering; GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
Water and thermal management are critical for the performance, efficiency and longevity of PEM fuel cells (PEMFCs). Effective water and thermal management require the design of control systems that can maintain the water balance and temperature at stable and optimal levels. In this paper, we consider a stack of PEM fuel cells integrated with a water recovery and cooling system. A mechanistic dynamic model is developed to be able to predict the water content and temperature in response to the fuel cell inputs. Water management uses a cascade arrangement of a supervisory Model Predictive Controller (MPC) and local anode and cathode PID humidity controllers to balance the membrane water content. Thermal management consists of a separate MPC controller to regulate the fuel stack temperature. One novelty of this work lies in identifying and utilizing the feasible region for the relative humidities of the anode and cathode when controlling the membrane water content. We introduce the feasible humidity plots (FHP) which define the feasible values for the anode and cathode relative humidities for a given fuel cell design and its operating conditions. This useful information helps to assign the setpoint values to the local PID humidity controllers of the water management system. It is shown by simulations that the water and thermal management MPC controllers work in tandem and successfully track the desired setpoint changes in humidity and temperature while rejecting external disturbances such as load changes. In addition, the control system is robust against modeling errors and possible model-plant mismatch introduced by fuel cell aging.
Clinical outcomes and significance of postoperative ultrasound biomicroscopy in patients with Boston type 1 keratoprosthesis
(Consel Brasil Oftalmologia, 2025) Abay, Berk; School of Medicine; Taş, Ayşe Yıldız; Müftüoğlu, Orkun; SCHOOL OF MEDICINE
| Purpose: To determine the clinical outcomes in patients after type 1 Boston keratoprosthesis surgery and the significance of ultrasound biomicroscopy imaging for postoperative follow-up. Methods: This retrospective analysis included 20 eyes of 19 patients who underwent corneal transplantation with type 1 Boston keratoprosthesis between April 2014 and December 2021. Data on patient demographics, preoperative diagnosis, visual acuity, and postoperative clinical findings were analyzed. Results: Type 1 Boston keratoprosthesis implantation resulted in intermediate- and long-term positive outcomes. However, blindness and other serious complications such as glaucoma, retroprosthetic membrane formation, endophthalmitis, or retinal detachment also occurred. The use of ultrasound biomicroscopy imaging allowed for better evaluation of the back of the titanium plate, anterior segment structures, and the relationship of the prosthesis with surrounding tissues, which provided valuable postoperative information. Conclusion: Regular lifetime monitoring and treatment are necessary in patients who undergo Boston type 1 keratoprosthesis implantation for high-risk corneal transplantation. ultrasound biomicroscopy imaging can be a valuable imaging technique for the evaluation of patients with Boston type 1 keratoprosthesis, providing important information on anterior segment anatomy and potential complications. Further studies and consensus on postoperative follow-up protocols are required to optimize the management of patients with Boston type 1 keratoprosthesis. Keywords: Boston Keratoprosthesis; Corneal transplantation; Ultrasound biomicroscopy; Anterior segment; Prostheses and implants
A hybrid autoencoder and index modulation framework for OTFS modulation
(Springer, 2025) Department of Electrical and Electronics Engineering; CoreLab (Communications Research and Innovation Laboratory); College of Engineering; Laboratory
This paper presents an innovative approach to orthogonal time frequency space (OTFS) modulation by integrating autoencoder-based enhanced (AEE) joint delay-Doppler index modulation (JDDIM) techniques. The proposed AEE-JDDIM-OTFS framework leverages deep learning to optimize the mapping and demapping processes, significantly improving spectral and energy efficiency in high-mobility communication scenarios. The system's performance is further enhanced by the introduction of a low-complexity greedy detector that maintains robust detection accuracy, even under imperfect channel state information (CSI) conditions. Extensive simulation results demonstrate that the proposed scheme achieves superior bit error rate (BER) performance compared to conventional OTFS and other OTFS-based modulation schemes, even in imperfect channel state information situations. The findings suggest that the AEE-JDDIM-OTFS framework offers a practical, low-complexity solution with promising potential for next-generation wireless communication systems.