Welcome to IKU Academic Digital Archive System


OpenAccess@IKU is Istanbul Kultur University's Academic Digital Archive System, established in June 2014 to digitally store and provide open access to academic and artistic outputs in line with international standards and intellectual property rights. The system includes various outputs such as articles, presentations, theses, books, book chapters, reports, encyclopedias, and works of art produced by the university's faculty members and students.

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7152

Publications

1462

Thesis

929

Researchers

2175

Indexed Publications

 

Recent Submissions

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ASL UNDERPRESSURE: Gamification of American Sign Language Learning Through Human-Computer Interaction
(IEEE, 2025) ATIA, OSAMA; ASSKAR, HUSSAM; EL KHARCHY, OUSSAME; ELMASRY, WİSAM
ASL Underpressure is an innovative web-based game that utilizes video processing and deep learning models to improve the practice of American Sign Language (ASL) and bridge the communication gap between hearing and deaf communities. The game focuses on education and improving communication skills by challenging players to quickly and accurately form words using the ASL alphabet. The system incorporates a timer to maintain player engagement and allows for multiple attempts per word to encourage learning and mastery. This paper demonstrates the potential of technology to improve communication and foster understanding between diverse communities.
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Statistical Quasi Cauchyness on Asymmetric Spaces
(University of Nis, 2025) DAĞCI, FİKRİYE İNCE
We call a sequence (xm) of points in an asymmetric metric space (X, d) statistically forward quasi 1 Cauchy if lim (Formula present) for each positive ε, where |A| indicates the cardinality of the set A. We prove that a subset E of X is forward totally bounded if and only if any sequence of points in E has a statistically forward quasi Cauchy subsequence. We also introduce and investigate statistically upward continuity in the sense that a function defined on X into Y is called statistically upward continuous if it preserves statistically forward quasi Cauchy sequences, i.e. (f (xm)) is statistically forward quasi Cauchy whenever (xm) is.
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Revisiting the Naturalistic Form Contemporary Adaptations by Zinnie Harris and Alexandra Wood
(Bloomsbury Publishing Plc., 2025) ERDURUCAN, BÜŞRA
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BUSE, ÖZDEN
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PublicationOpen Access
Evaluation of Enzyme Activity Predictions for Variants of Unknown Significance in Arylsulfatase a
(Springer Science and Business Media Deutschland GmbH, 2025) BUSE, ÖZDEN
Continued advances in variant effect prediction are necessary to demonstrate the ability of machine learning methods to accurately determine the clinical impact of variants of unknown significance (VUS). Towards this goal, the ARSA Critical Assessment of Genome Interpretation (CAGI) challenge was designed to characterize progress by utilizing 219 experimentally assayed missense VUS in the Arylsulfatase A (ARSA) gene to assess the performance of community-submitted predictions of variant functional effects. The challenge involved 15 teams, and evaluated additional predictions from established and recently released models. Notably, a model developed by participants of a genetics and coding bootcamp, trained with standard machine-learning tools in Python, demonstrated superior performance among submissions. Furthermore, the study observed that state-of-the-art deep learning methods provided small but statistically significant improvement in predictive performance compared to less elaborate techniques. These findings underscore the utility of variant effect prediction, and the potential for models trained with modest resources to accurately classify VUS in genetic and clinical research.