Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Book Part Comparison of Damage Predictions for Concrete Dams, Finite Elements with Smeared Crack vs. Discrete Element Models(International Association for Earthquake Engineering, 2024) Soysal, B.F.; Arici, Y.The seismic assessment of gravity dam monoliths has been treated within the framework of performance based earthquake engineering (PBEE) in the last decade. The necessary inclusion of the soil-structure-reservoir interaction in combination with predicting the damage on these structures for use in PBEE is a significant challenge. Within this context, smeared crack models with general purpose finite element codes became to be used generally as the assessment tool for these systems. Perhaps the most practical limitation in this approach is the difficulty with providing discrete cracks and the corresponding impediment to the rating of the damage on these systems leading to possibly subjective conclusions. On the other hand, discrete element techniques offer a proficient simulation alternative to the FE, enabling the interpretation of results from the main aspect of the damage on these system, i.e. cracking. A novel discrete element framework, incorporating dam-reservoir interaction, has been developed to this end as part of the doctoral studies of the first author. The model incorporates individual elements connected by multiple springs, successfully modelling initial continuum with the accurate prediction of discrete cracks at the latter stages of loading. The predicted damage and damage rating of a generic monolith is compared to the FE counterparts in this work. A comprehensive comparison with different ground motions at several levels focusing on crack widths is shown. The results showed the cracking on the system is very different in severe shaking compared to similar predictions in lower earthquake excitations. The FE simulations, commonly adopted for the investigation of these systems with smeared crack modelling, yielded less cracking as well as smaller propagation in severe shaking conditions. © 2024, International Association for Earthquake Engineering. All rights reserved.Conference Object Quantum Implementation of S-Boxes: A Memory Optimized Approach(Institute of Electrical and Electronics Engineers Inc., 2025) Tilki, Ozcan; Saran, A.N.; Cildiroglu, H.O.; Yayla, O.Substitution boxes (S-boxes) serve as fundamental non-linear components in symmetric cryptography, and their quantum circuit implementation is critical for quantum security. This work addresses the dual challenges of quantum circuit depth optimization and computational intractability in S-box synthesis. We introduce memory-optimized data structures, a pointer-efficient RandomAccessSet and a dynamic devector, that reduce memory overhead by 12 times per element, thereby mitigating the computational complexity associated with Pauli representation. Our enhanced Meet-in-the-Middle framework achieves exhaustive depth optimization for standardized S-boxes, demonstrating up to 8.5% depth reduction over DORCIS baselines at equivalent T-depth. The approach scales to 5-8-bit primitives, establishing memory efficiency as an independent resource dimension in quantum circuit synthesis. Comparative analysis under varied cost parameters provides new insights for resource-efficient cryptographic implementations on quantum hardware. © 2025 IEEE.Conference Object Sentiment Analysis for Arabic Using Deep Learning(Springer Science and Business Media Deutschland GmbH, 2026) al-Hamadani, S.A.S.; Sever, H.With the explosive growth of digital communication, understanding sentiment in online content has become increasingly critical for a wide range of applications, from customer feedback analysis to social media monitoring. However, sentiment analysis for Arabic presents unique challenges due to the language's rich morphology, diverse dialects, and complex syntactic structures. These challenges are further amplified in multimodal settings, where the fusion of textual, visual, and auditory cues is required to capture the full spectrum of human emotion. To address these issues, this paper introduces a new framework for Arabic Multimodal Sentiment Analysis (AMSA), combining multi-level deep learning approaches across text, audio, and visual modalities. Our approach utilizes state-of-the-art transformer-based architecturees, including Multimodal Transformer (MulT) and Early Fusion models, to tackle both linguistic complexity and multimodal alignment. Specifically, we leverage DeBERTa for extracting rich textual features, ViT (Vision Transformer) for visual cues, and Whisper for capturing nuanced audio signals, creating robust and contextualized representations. Experimental results on a curated Arabic multimodal dataset demonstrate the effectiveness of this approach, with our proposed MulT model achieving an F1 score of 72.73%, reflecting a substantial improvement of 13.98% in F1 score and 14.6% in accuracy over existing baselines. These findings highlight the power of cross-modal attention mechanisms and early fusion strategies in accurately capturing subtle sentiments across multiple modalities. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.Book Part The Art of Being: Haruki Murakami’s Killing Commendatore and Kierkegaardian Existentialism(Springer Science+Business Media, 2025) Rundholz, A.; Kirca, M.The protagonist of Killing Commendatore retreats to deal with the trauma of divorce. Pivotal to the protagonist’s journey is his discovery of a painting. Depicting a scene from Mozart’s opera, Don Giovanni, the painting marks the protagonist’s departure to finding meaning in a complex world. His self-discovery hinges on the arts, leading the protagonist to grasp his essence and place in an indifferent and absurd universe. Fantastic and surreal events in the novel can be seen as an adaptation of Kierkegaard’s existentialism, a reinterpretation of the philosopher’s tenets to fit the twenty-first century. © 2025 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.Editorial Introduction(Springer, 2008) Aydogan, N.Conference Object Citation - Scopus: 1Intelligent and Energy-Aware Task Scheduling in Cloud Systems(Springer Science and Business Media Deutschland GmbH, 2025) Böke, K.N.; Qadri, S.S.S.M.; Kabarcik, A.The rapid advancement of information technologies has significantly reshaped industrial operations and daily life, leading to a growing demand for responsive and scalable digital services. Among the technologies addressing this growing need, cloud computing has emerged as a foundational infrastructure for delivering on-demand computing resources over the internet. However, its increasing adoption presents complex challenges such as managing dynamic workloads and minimizing virtual machine (VM) usage costs. Therefore, cloud service providers aim to optimize performance and reduce the operational costs of VMs by integrating intelligent scheduling algorithms. In response to this need, the present study explores the use of algorithms, particularly focusing on machine learning driven approaches, to enhance the sustainability and efficiency of cloud systems. Specifically, the study investigates the effectiveness of reinforcement learning through Q-learning for optimizing task scheduling against the traditional Round Robin (RR) scheduling algorithm. The primary objective is to evaluate their performance in minimizing VM usage costs within dynamic and continuously evolving cloud environments. Experimental results indicate that in reducing costs, Q-learning outperforms RR with a 33.14% improvement, demonstrating its superior adaptability and cost efficiency under varying conditions. These insights highlight the potential of reinforcement learning to enable intelligent and cost-aware scheduling strategies in modern cloud computing systems. © 2025 Elsevier B.V., All rights reserved.Conference Object Design and Implementation of a Custom ERP Framework for a Drilling Equipment Manufacturer(Springer Science and Business Media Deutschland GmbH, 2025) Torunoğlu, D.; Erkoç, E.C.; Abay, Z.E.; Qadri, S.S.S.M.; Gök, E.C.; Karataş, D.; Güçlüer, G.This study presents the design and implementation of a web-based Enterprise Resource Planning (ERP) system tailored for a small-to-medium-sized enterprise (SME) operating in the manufacturing sector. With a focus on GEO Sondaj Makine İmalat LTD. ŞTİ, the system was developed to digitize and streamline core operational workflows, including sales order processing, production scheduling, inventory management, procurement, and coordination between customers and suppliers. Built using the Django web framework, the ERP platform provides modular functionality with real-time data integration across departments. Unlike generic ERP packages, this custom-built solution mirrors the company’s actual business processes and addresses typical challenges faced by SMEs, such as limited IT infrastructure, absence of digital records, and resistance to organizational change. The internally developed modules led to enhanced traceability, operational efficiency, and data-driven decision-making. The system also includes a simulation module to support production visualization and planning, although advanced features like bottleneck identification and dynamic queue tracking remain under development. The findings demonstrate that a cost-effective, scalable ERP system can be successfully deployed in resource-constrained environments when grounded in business-specific needs. The system was evaluated based on internal testing, interdepartmental workflow validation, and observed improvements in operational efficiency and traceability. This project offers a practical reference for other SMEs seeking to modernize their operations through digital integration. © 2025 Elsevier B.V., All rights reserved.Article The Impact of Technology on Economic Growth in Turkey(Inderscience Publishers, 2025) Ercan, M.; Temiz, D.; Gökmen, A.The Turkish economy has been suffering from trade imbalance for a long time. Exporting high value-added products will diminish Turkey’s dependence on foreign resources for capital and imported products. At the same time, it may be possible to divert more resources from gross domestic product (GDP) to R&D funds. Appropriate and efficient usage of technology will help companies innovate and find new areas of employment. As a result, the Turkish economy may have a better chance of obtaining a sustainable economic growth for the longer term. This study concludes that increased R&D expenditures leads to a rise in technology and this in turn contributes positively to economic growth. The results obtained from the study show that technology affects Turkey’s economic growth. Therefore, Turkey needs to work harder in the field of technology in order to achieve sustainable growth. Improving the situation and quality of research and development activities in Turkey, encouraging research and development investments by both the government and the business sector should be priority reform movements for Turkey. Policy makers should support science and technology, make institutional arrangements for intellectual property rights and raise the level of education, and make arrangements to increase R&D spending. © 2025 Elsevier B.V., All rights reserved.Article Cognitive and Social Antecedents of Brand Loyalty in Over-The Streaming Services(Science Publishing Corporation Inc., 2025) Ôzsaçmaci, B.This study examines cognitive (brand image, perceived quality, brand identity) and social (eWOM) antecedents of brand loyalty in Over-the-Top (OTT) streaming using a cross-sectional survey (N=418) and covariance-based SEM. All four antecedents significantly predict loyalty, with brand image exerting the strongest effect, followed by eWOM, then perceived quality and brand identity. Group comparisons show that evaluations of perceived quality, but not eWOM, identity, image, or loyalty, differ by usage frequency and subscription breadth. The findings substantiate a dual cognitive–social route to loyalty, and suggest that, in content-rich, multi-homing markets, quality functions as a hygiene factor while brand image carries the differentiating signal. We discuss managerial implications for sequencing investments (image, eWOM, quality thresholds) and outline finance-relevant links to CLV, LTV: CAC, and revenue stability. © 2025 Elsevier B.V., All rights reserved.Conference Object The Implementation of a Successive Cancellation Polar Decoder on Xilinx System Generator(Institute of Electrical and Electronics Engineers Inc., 2017) Arli, A.Ç.; Colak, A.; Gazi, O.Polar coding is the first kind of the capacity achieving codes which are defined for binary-input discrete memoryless channels initially. Parallel processing property of the FPGA allows to decode faster with a margin of complexity. Xilinx System Generator as a practical tool to construct decoding designs in shorter time is a fact. In this study, FPGA implementation of decoding polar codes through Xilinx System Generator is shown. © 2023 Elsevier B.V., All rights reserved.