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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Recent Submissions
Data-Driven Machine Learning Approaches to Demand Forecasting in Supply Chain Management
(IEEE, 2025) ALREFAAI, SAFA; ERMİŞ, MURAT
This study explores pharmaceutical demand forecasting by integrating statistical analysis and machine learning within the context of supply chain management. The dataset, from a pharmaceutical manufacturer, includes six drug categories and around 240 products. Initial data exploration was conducted using Power BI to understand the structure and trends. Statistical models, namely Moving Averages, Single Exponential Smoothing, Trend Analysis, and ARIMA, were applied, focusing specifically on Acantaine (Antibiotics class) for detailed analysis. Machine learning models were trained on the full dataset to improve generalization, but testing was focused on Acantaine, with accuracy metrics computed. A comparative analysis showed that machine learning models, especially Random Forest, significantly outperformed traditional statistical methods in forecasting accuracy. The study underscores the value of machine learning in enhancing prediction and supporting strategic decisions in pharmaceutical supply chains.
Determining Debris Collection Areas for the European Side of İstanbul
(Springer Science and Business Media Deutschland GmbH, 2025) DEMİREL, DUYGUN FATİH; Gönül Sezer, Eylül Damla
It is crucial to rapidly remove the debris generated after an earthquake, dispose of it in designated areas, and manage it using various methods. Especially in cities like Istanbul, which face a constant earthquake threat, it is essential to develop disaster management plans in advance. One key aspect of these plans is identifying suitable locations for debris collection after an earthquake. Studies in the literature show that different methods are used to consider multiple economic and environmental criteria for debris site selection. However, the lack of a similar scientific study for Istanbul is a significant gap. This project proposes a hybrid method that incorporates sustainable approaches to identify debris collection areas on the European Side of İstanbul. The study aims to identify potential debris sites. The selection model will be based on the multi-attribute utility theory (MAUT), considering factors like cost, environmental impact, proximity to debris areas and recycling centres, and effects on water resources and natural habitats.
Crank-Nicolson Method for the Chiral nonlinear Schrödinger Equation
(Institute of Physics, 2025) Wahyuningsih, Ester T.; Magdalena I.; AKKOYUNLU, CANAN
In this paper, we develop a finite difference scheme based on the Crank-Nicolson method for solving the chiral nonlinear Schrödinger (CNLS) equation, which describes the dynamics of nonlinear wave propagation with chirality effects. The CNLS equation supports two types of progressive wave solutions: bright solitons and dark solitons. The proposed Crank-Nicolson scheme is implicit, unconditionally stable, and achieves second-order accuracy in both space and time. To evaluate the accuracy of the method, numerical results are compared with exact analytical soliton solutions. Numerical simulations are presented for the propagation of single bright and dark solitons. The results demonstrate that the Crank-Nicolson method accurately preserves soliton structures, making it an effective tool for studying the dynamics governed by the chiral nonlinear Schrödinger equation. The study demonstrates the effectiveness of the Crank-Nicolson method in capturing the dynamics of chiral nonlinear wave propagation and lays the foundation for further exploration of chiral effects in quantum and optical systems.
An Investigation on the Vibrational Analysis, Molecular Structure and Interaction With the Cellulase Enzymes of the Cellulose I Alpha and Cellulose I Beta: Dft Calculations, Docking Simulations
(Chemical Society of Ethiopia, 2025) Demirag, Aliye Demet; Çelik, Sefa; Özel, Ayşen E.; AKYÜZ, SEVİM
Molecular docking is one of the most widely used techniques for simulating molecular interactions between molecules and forecasting the mode of binding and affinities between them. Due to the presence of structure-function relationship, in this study firstly, the molecular structures of the cellulose I(alpha) and I(beta) molecules were optimized and their most stable structures were determined by density functional theory (DFT) using B3LYP method with 6-31G(d,p) basis set. The vibrational wavenumbers of 1-ring, 2-ring, 3-ring, and 4-ring structures of cellulose I(alpha) and I(beta) were calculated using the same level of theory. Reliable vibrational assignments were made based on potential energy distribution (PED %) of the vibrational modes. The energy gap (Eg = ELUMO - EHOMO) of the cellulose Iα and cellulose Iβ was found to be 8.286 eV and 7.965 eV, respectively. To identify the molecular interactions between cellulose Iα and Iβ ligands and the cellulase enzymes, molecular docking studies were performed. The molecular docking results revealed the strong interaction of the cellulose Iα and Iβ with Endoglucanase enzyme (-6.4 and -6.3 kcal/mol, respectively), enzyme β-glucosidase (-5.3 and -5.2 kcal/mol, respectively), and Exoglucanase enzyme (-6.1 and -6.2 kcal/mol, respectively).
MOL, GÖKÇE
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