Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Article Improved Arithmetic Efficiency in TFHE Through Gate-Level Optimizations(Springer, 2025) Tasel, Faris Serdar; Saran, Ayse NurdanFully homomorphic encryption (FHE) enables computations to be performed directly on encrypted data without decryption, offering a promising solution for privacy-preserving applications, such as secure cloud computing, confidential machine learning, and encrypted analytics. However, one major drawback of FHE is the high computational cost of homomorphic operations, which slows down real-world implementations, making them impractical. This paper explores the implementation of arithmetic operations within the framework of Torus FHE (TFHE) and demonstrates the construction of gate-level optimization for fundamental operations such as addition, subtraction, negation, comparison, and multiplication on fixed-point numbers. Our work emphasizes optimizing arithmetic logic to reduce the number of bootstrapping operations, a critical factor in improving computational efficiency. Furthermore, we investigate the error rates associated with the proposed operations, providing valuable insight into their accuracy and practical applicability. This study contributes to developing more efficient and reliable arithmetic logic for privacy-preserving computations in FHE systems. The experimental results indicate that the proposed optimizations yield speedups of up to 2.27x for addition/subtraction, 3.55x for comparison, and 1.80x for multiplication operations.Article Comparative Analysis of Impedance Matching Techniques in Wireless Power Transfer Efficiency: A Focus on Resonant, Adaptive, and Hybrid Approaches(Springer, 2025) Hatem, Sude; Kurt, ErolWireless power transfer (WPT) efficiency is highly dependent on impedance matching; however, comparative analyses of matching techniques under dy namic operating conditions remain limited. This study presents a systematic evaluation of three impedance matching approaches, namely resonant, adaptive, and hybrid, via theoretical modeling and numerical simulations. The results prove that adaptive impedance matching maintains stable efficiency (90.0% +/- 0.9%) in load variations (20-100 Omega ), coil misalignment (0<bold>degrees</bold>-30<bold>degrees</bold>), and transmission distances (0.1-1 cm), with minimal fluctuations. In contrast, resonant matching shows the best efficiency (i.e., 95%) under ideal conditions (10 MHz, 0<bold>degrees</bold> misalignment, 50 Omega load) but degrades rapidly to <50% under deviation conditions (e.g., 30 misalignment or 1 cm distance). The hybrid solution yields a balanced compromise that maintaining 85-92% efficiency in larger operating ranges. Quantitative metrics-the fluctuation rate (adaptive: 0.07 vs. resonant: 0.15) and stability index (adaptive: 102 vs. resonant: 20)-exhibit adaptive matching's superior dynamic performance. These find ings present practical advice on selecting impedance matching techniques in real WPTapplications, such as electric vehicle charging and medical implants, where stability under variability is paramount.Article Citation - WoS: 1Citation - Scopus: 1Pure Bending of Fiber Reinforced Curved Beam at the Failure Limit(Springer, 2023) Farukoglu, Omer Can; Korkut, Ihsan; Motameni, AliThe purpose of this research is to study the limit failure stresses occurring on the rectangular cross section fiber reinforced curved beam subjected to couple moment at the ends of the geometry. Utilizing analytical methods, closed form solutions are obtained for plane stress conditions. Considering different parameters such as the radial thickness and fiber volume of the beam, stress and displacement fields are investigated in detail. Employing different failure criteria, Tsai-Wu and Norris, calculated failure limit moment and failure location differences in the beam are analyzed. Moreover, various transverse Young's modulus estimation methods available in the literature, Halpin-Tsai, Rule of Mixture, and Chamis, are considered. Effects of these estimations on the aforementioned fields are carefully handled as well. Using the material properties of glass fiber/epoxy constituents, numerical examples are generated by incorporating semi-analytical effective material property calculation models. Achieved numerical results have revealed that the radial thickness of the beam has more influence than fiber volume in terms of failure moment and stresses. Application of different criteria may cause different failure location acquisitions while mildly changing the limit failure moment. Young's modulus estimation influences the radial displacement prominently. In addition to the acquired results, from a general perspective, this study can be used as a benchmark model for failure stress analysis of related structures and may be expanded with appropriate numerical techniques.Article Citation - WoS: 8Citation - Scopus: 9Bitcoin Price Prediction Using Sentiment Analysis and Empirical Mode Decomposition(Springer, 2025) Arslan, SerdarCryptocurrencies have garnered significant attention recently due to widespread investments. Additionally, researchers have increasingly turned to social media, particularly in the context of financial markets, to harness its predictive capabilities. Investors rely on platforms like Twitter to analyze investments and detect trends, which can directly impact the future price movements of Bitcoin. Understanding and analyzing Twitter sentiments can potentially provide insights into future Bitcoin price movements and can shed light on how investor sentiment affects cryptocurrency markets. In this study, we explore the correlation between Twitter activity and Bitcoin prices by examining tweets related to Bitcoin price sentiments. Our proposed model consists of two distinct networks. The first network exclusively utilizes historical price data, which is further decomposed into various components using the Empirical Mode Decomposition method. This decomposition helps mitigate the impact of irregular fluctuations on Bitcoin price predictions. Each of these components is then separately processed by Long Short-Term Memory (LSTM) networks. The second network focuses on modeling user sentiments and emotions in conjunction with Bitcoin market data. User opinions are categorized into positive and negative classes and are integrated with historical data to predict the next-day price using LSTM networks. Finally, the outputs of each network are combined to form the ultimate prediction values. Experimental results demonstrate that Twitter sentiment can effectively helps us predict Bitcoin price trends. Furthermore, to validate our proposed model, we compared it with several state-of-the-art methods. The results indicate that our approach outperforms these existing models in terms of accuracy. © 2025 Elsevier B.V., All rights reserved.Article Enhancing Session-Based Trip Recommendations Using Matrix Factorization: a Study on Algorithm Efficiency and Resource Utilization(Springer, 2025) Mat, Abdullah Ugur; Saran, Ayse NurdanAs the impact and usefulness of recommendation systems continue to grow, their importance becomes more and more pronounced. Therefore, it is crucial to design and implement recommendation systems that are both efficient and highly accurate to meet the increasing demands and expectations. This study focuses on a model awarded first place in a travel forecasting recommendation system competition. This study aims to enhance matrix factorization-based recommender systems by conducting a comprehensive analysis of various factors. This includes examining the effects of resource utilization and recurrent neural network (RNN) algorithms on session-based factorization, as well as evaluating the influence of embeddings and optimization techniques concerning their efficiency and accuracy. The gated recurrent unit (GRU) algorithm has produced more accurate results for reduced datasets than long short-term memory (LSTM). Some modifications have been made on the embedding layers, and the results have been observed. In addition, the model's optimizer is changed, and the performance of different optimizers is evaluated. While random reduction of the dataset has led to a decrease in the success rate, methodical reduction has significantly increased the success rate. The highest and most reliable success rate (0.6654) was achieved by applying the selection method, which reduced the dataset to 1 M records from 1.5 M records. Optimizers have shown a wide range of effects on hardware.Article Citation - WoS: 2Citation - Scopus: 2Gender Gap in Digital Financial Inclusion Across Generations(Springer, 2025) Özşuca, Ekin AyşeThis paper analyzes and measures the contributing factors that explain variation in access to digital finance between men and women across different age groups for developing countries. The findings indicate that the gap is the largest for the working age population. The largest part of the gap is attributable to employment, while secondary education and income level are also found as significant contributors to the disparity. Notably, tertiary education acts towards closing the gap for young adults. © 2025 Elsevier B.V., All rights reserved.Article Citation - WoS: 4Citation - Scopus: 12Prioritizing Critical Success Factors for Wind Turbine Suppliers: a Neutrosophic Hybrid Dematel and Anp Approach(Springer, 2025) Edalatpanah, S. A.; Sicakyuz, C.; Nourkhah, S. A.; Pamucar, D.The global energy landscape is experiencing a transformative shift toward sustainability, with wind energy becoming an indispensable clean energy source crucial for combating climate change. As the number of wind turbine suppliers increases, stakeholders face significant challenges in selecting the most suitable partners, which can directly impact project outcomes and overall efficiency. This study aims to systematically identify and prioritize the critical success factors for wind turbine suppliers, facilitating effective decision-making in supplier selection. To achieve this, we present an innovative hybrid Decision Making Experiment and Evaluation Laboratory Method and Analytic Network Process framework, enhanced by a neutrosophic fuzzy environment. Our findings reveal that key factors such as component price (C1) with a weight of 0.055, operation and maintenance cost (C3) with 0.049, and annual energy production (C5) with 0.042 play significant roles in the decision-making process. Among these, component price (C1) is the most critical factor, indicating that cost considerations are paramount in the decision-making process. Notably, the findings emphasize the importance of optimizing supplier relationships, particularly in terms of service quality and technical competence, to ensure successful project implementation and long-term sustainability in the rapidly evolving renewable energy market. This study provides essential insights for both academic research and industry practice. Academically, it fills a critical gap in the literature on wind energy supplier selection by presenting a novel methodology that can guide future research. Practically, it equips industry stakeholders with actionable data to optimize supplier relationships, ultimately enhancing project outcomes and long-term sustainability. These findings are particularly relevant for stakeholders in emerging markets, where cost management and supplier selection are critical to project viability. By optimizing supplier selection, this study contributes to the broader goal of achieving sustainability in renewable energy projects.Article Citation - WoS: 1Citation - Scopus: 2Spectroscopic Ellipsometry Study of Linear and Nonlinear Optical Properties of Nabi(Mo0.5w0.5o4)2 Crystal(Springer, 2024) Isik, M.; Guler, I.; Gasanly, N. M.; Darvishov, N. H.In this study, linear and nonlinear optical characteristics of NaBi(Mo0.5W0.5O4)(2) crystal, a new material that may have potential for optoelectronic applications, were investigated. NaBi(Mo0.5W0.5O4)(2) single crystals were grown via the Czochralski method. Two sharp and well-defined peaks were observed in the x-ray diffraction pattern. These peaks were associated with tetragonal crystal structure. The data obtained from ellipsometer measurements was matched with a suitable optical model. This allowed for the presentation of the spectral dependence of various optical parameters like refractive index, dielectric constant, optical conductivity, extinction, and absorption coefficients in the range of 1.2-5.0 eV. As a result of studying the spectral dependence of the absorption coefficient under Tauc relationship, bandgap energy of the compound was found to be 3.20 eV. Using the spectral dependence of the dielectric function, the existence of two critical points with energy values of 3.72 and 4.44 eV was revealed. The change of the refractive index in the region under the bandgap was studied using the single oscillator model. Single oscillator and dispersion energies were determined from the analysis results. Nonlinear optical parameters of NaBi(Mo0.5W0.5O4)(2) crystal were also determined. With this study, the optical properties of the NaBi(Mo0.5W0.5O4)(2) are presented in more detail and valuable information is presented for the potential use of the material in optoelectronic devices.Article An Q-Uniformly Convergent Technique for Singularly Perturbed Problems, With an Interior Turning Point Occurring in Chemical Processes(Springer, 2025) Kumari, Parvin; Kumar, Devendra; Baleanu, DumitruA parameter-uniform solution is presented for singularly perturbed turning point problems with twin boundary layers. A fitted mesh is created in order to resolve the layers, and the provided equation is discretized using the cubic B-spline basis functions on this mesh. For the analytic solution and its derivatives, asymptotic bounds are provided. A brief analysis shows that the method is first-order precise in time and second-order accurate (up to a logarithm factor) in space, and that it is uniformly convergent regardless of the minuscule parameter. Two test problems are offered in order to verify the theoretical results.Correction The Anomalous Nucleation in Al-Tb Metallic Glasses (Vol 52a, Pg 700, 2021)(Springer, 2021) Ulucan, T. H.; Kalay, I.; Kalay, Y. E.