Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
Browse
237 results
Search Results
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.Article Citation - WoS: 1Citation - Scopus: 1Optical Wireless Communication in Atmosphere and Underwater: Statistical Models, Improvement Techniques, and Recent Applications(Institute of Electrical and Electronics Engineers Inc., 2026) Ata, Y.; Al-Sallami, F.M.; Gökçe, M.C.; Vegni, A.M.; Rajbhandari, S.; Baykal, Y.Optical Wireless Communication Systems (OWCSs) are becoming more popular each day, especially after numerous mobile applications are being employed within the concept of Internet of Things (IoT). OWCSs are largely used in both terrestrial and non-terrestrial environments, like underwater, air, and space scenarios. Due to the large applicability of OWCS, it represents one of the main candidate technologies for the future 6G wireless communication systems. Naturally, this market trend forces the system designers to reach the best performance in their designs, as well as optimize the cost. In this survey paper, we intend to provide information to the researchers working in this field on the statistical models adopted in OWCS, the methods and techniques used to improve their performances, mainly in outdoor environment like air, space, and underwater. In this respect, the background on theoretical aspects of OWCS, together with their benefits, limitations and challenges are presented. Performance improvement techniques employed in OWCSs, such as power increase, partial coherence, beamforming, aperture averaging, spatial diversity, and intelligent reflecting surfaces, are also introduced. Finally, we discuss the open challenges that researchers are still facing, together with future directions on next steps for a large-scale adoption of OWCS. © 1998-2012 IEEE.Article Comprehensive Analysis of Data Augmentation Methods in Classification for an Imbalanced Epilepsy Dataset(Institute of Electrical and Electronics Engineers Inc., 2026) Calis, A.G.; Ergezer, H.Imbalanced class distribution reduces the generalizability of classifiers in EEG-based epilepsy detection. This study examines the impact of the synthetic minority oversampling technique (SMOTE) and its variants on imbalanced electroencephalography (EEG) data, utilizing an end-to-end data processing pipeline. Band-limited filtering is applied as pre-processing, and then the training data is gradually oversampled by 20% increments in four scenes. Experiments are conducted on coarse-k-nearest neighbor (Coarse-KNN), bagged trees, and artificial neural network (ANN) classifiers, and evaluation is performed using accuracy, precision, recall, F1 score, and Matthew’s correlation coefficient (MCC) metrics. In Scene #4, where the inter-class imbalance is eliminated, Borderline-SMOTE yielded the highest and most consistent results (F1 Score = 0.903–0.937, MCC = 0.830–0.894). Safe level-SMOTE (SL-SMOTE) and SMOTE/Geometric-SMOTE(G-SMOTE) produced second-ranked results. The findings demonstrate that appropriate variant selection provides consistent gains even across classifiers, making Borderline-SMOTE the recommended approach for imbalanced EEG classification. Furthermore, in the detailed analysis of ensemble sampling limits, SMOTE-based combined approaches (e.g., SL + G SMOTE) also produced consistent results. Basic descriptive statistics (mode, median, variance, and kurtosis) of the synthetic samples were found to be comparable to those of the real data, providing additional evidence of distributional consistency. © 2013 IEEE.Article NATO-EU Complementarity Through Strategic Concept and the Strategic Compass: The Impact of the Strategic Compass on European Integration(Faculty of European Studies, 2025) Akşemsettinoğlu, G.The Russia-Ukraine war and the changing geopolitical interests of the major powers have created several new threats for Europe. At the same time, new challenges such as cyber-attacks, hybrid wars and climate change have alarmed the European states. Therefore, these developments required NATO and the EU to take measures separately and proceed by common action. In line with this need, NATO issued the Strategic Concept and the EU issued the Strategic Compass. Examining the two strategies has revealed that they are not competing but completing documents to provide European defence and security. Therefore, the first purpose of this article is to present the idea of complementarity between NATO and the EU in European security. This understanding will also serve the second purpose of the article, which is the manifestation of the impact of the Strategic Compass on European integration. In other words, complementarity will create a structural framework for strengthening the Strategic Compass and the European integration process. In this context, since the Strategic Compass has reflected a consensus of the EU member states to cooperate on defence and security issues, it is essential to know whether it has contributed to the European integration process by deepening policies on defence and security. Thus, the article concludes that, strengthened by NATO’s strategic concept in the context of complementarity, the strategic compass has become an important step in the European integration process. © 2025 Faculty of European Studies. All rights reserved.Article Crack Detection on Asphalt Runway Using Unmanned Aerial Vehicle Data With Non-Crack Object Removal and Deep Learning Methods(Pontificia Universidad Catolica de Chile, Escuela de Construccion Civil, 2025) Tapkin, S.; Tercan, E.; Bostan, A.; Şengül, G.Unmanned aerial vehicles are extensively utilized for image acquisition in a cheap, fast, and effective way. In this study, an automatic crack detection method with non-crack object removal and deep learning-based approaches are developed and tested on images captured by unmanned aerial vehicle. The motivation of this study is to detect either a crack exists or not in the asphalt-runway. The novelty of this study lies in integrating a non-crack artifact removal process with six classical edge detectors and comparing the resulting performance with four lightweight CNN models on the same UAV-acquired runway image dataset, enabling a unified evaluation of classical and learning-based approaches. For deep learning-based approach, four lightweight CNN models, namely GoogleNet, SqueezeNet, MobileNetv2, and ShuffleNet, are trained and the best accuracy of 87.9 is obtained whenever GoogleNet model is used. For the non-crack object removal approach, exclusion of non-crack objects from the images is the first step, where crack-detection which makes use of edge-detection techniques is the latter. In the study, Sobel, Prewitt, Canny, Laplacian of Gaussian, Roberts and Zero Cross edge detection algorithms are examined and their success rates in detecting cracks are comparatively presented. With sensitivity=0.981, specificity=0.744, accuracy=0.917, precision=0.912 and F-score=0.945 values Canny algorithm performs significantly better than others in detecting the cracks. This study provides enough evidence for the practicability of automated crack detection on unprocessed digital photographs by the results of the study conducted on asphalt runway. © (c) 2025 Tapkın, S., Tercan, E., Bostan, A. and Şengül, G. This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivatives 4.0 International License. https://creativecommons.org/licenses/by-nc-nd/4.0/Article A Discrete Element Method for Evaluating the Seismic Performance of Concrete Gravity Dam-Reservoir Systems Under Main Shock-Aftershock Events(Tulpar Academic Publishing, 2025) Soysal, B.F.Dams are crucial for water supply, flood prevention, and hydroelectric power generation. Often located in seismically active regions, they are vulnerable to main shock-aftershock (MS-AS) sequences, which can compromise structural integrity and hydraulic safety. Critical aspects of dam response to MS–AS events remain unclear, particularly the required rest time between successive events and threshold AS-to-MS intensity measure ratios that could serve as predictors of additional damage. This study addresses these gaps by analyzing concrete gravity dam–reservoir systems of three heights (50 m, 100 m, and 150 m) using the developed discrete element–based approach coupled with displacement/pressure-based mixed finite elements for the reservoir. Empirical rest time equations were derived from 124 as-recorded ground motions, while seismic performance under varying intensity levels was evaluated using 14 as-recorded MS–AS sequences. Damage was quantified using discrete indices of base crack length, maximum base crack width, and maximum total upstream crack width. Results indicate that AS primarily propagate existing cracks at lower intensities, whereas higher intensities generate new cracks along the upstream face, increasing crack widths by 25–30% on average. The 50 m high dam remained within the mild damage category, while taller dams occasionally reached moderate levels, posing potential seepage risks. Threshold AS-to-MS ratios for four different intensity measures were identified. These findings provide mechanistic insight into crack propagation under MS-AS events, providing practical guidance for post-earthquake dam safety assessment, inspection prioritization, and incorporating sequential seismic effects into design and emergency planning. © 2025 by the Author.Article New Insights Into the Correlation Between Secondary Traumatic Stress and Cognitive Flexibility in Mental Health Therapists and Counselors(Florida Gulf Coast University, 2025) Durak, H.; Çelik, E.G.; Çelik, B.Mental health professionals regularly witness their clients' challenging life events, which they must cope with throughout their careers. This study examines the association between secondary traumatic stress (STS) and cognitive flexibility among counselors and therapists and explores their variations by demographic and professional factors. The participants included 536 professionals (psychiatrists, psychologists, social workers, and child development specialists). Secondary traumatic stress and cognitive flexibility were assessed using the Secondary Traumatic Stress Scale and the Cognitive Control and Flexibility Scale, respectively. Demographic data were collected using the Personal Data Form. SPSS 21.0 software was used for data analysis. Pearson correlation analysis revealed a moderate negative association between the participants' STS and cognitive flexibility levels. The findings indicated a higher STS risk among child development specialists, younger professionals, those who are single or do not have children, those who have lower income or fewer years of experience, and those without trauma-related training or supervision. Conversely, older age, marriage, children, higher income, higher level of education, longer experience, and trauma-related training were identified as protective factors for cognitive flexibility. Several recommendations were provided to strengthen mental health professionals’ flexibility and reduce the impact of STS on them. First, supportive measures in protection, prevention, and treatment for mental health professionals who work in the field of trauma should be taken. Second, priority should be given to extending certified training programs that will improve the professional skills of mental health workers. Third, counselors should be supported by peer, individual, and group supervision. Finally, examining gender-specific risks is essential to increase women's cognitive flexibility and improve their physical and emotional well-being. © 2025, Florida Gulf Coast University. 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.Article Perspectives on Audit Opinions and Key Audit Matters in the Global Airline Industry and the COVID-19 Pandemic(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Dansık, Umutcan; Öztürk, C.The present study investigates whether the COVID-19 pandemic had a negative effect on audit opinion and led to differences in the composition of key audit matters (KAMs) observed in the airline industry. This study uses a sample of 55 airlines whose financial statements are based on International Financial Reporting Standards (IFRSs) and whose financial statement audit follows National or International Standards on Auditing (ISAs) for audit opinion, as well as a sample of 42 airlines whose financial statements are based on IFRSs and whose financial statement audit follows ISAs for the composition of KAMs. A textual analysis, a content analysis, a frequency distribution, and a chi-square test were conducted for the periods before, during, and after the COVID-19 pandemic. The findings reveal that the COVID-19 pandemic had no significant effect on audit opinion, except for one airline whose audit report declared a disclaimer of opinion. In contrast, the impairment of goodwill and intangible assets (as an industry-specific KAM) and going concern (as a KAM specific to the COVID-19 pandemic) were the two KAMs that were typically observed during the COVID-19 pandemic due to increased uncertainty. This was found to be the case, even though the main KAMs in the airline industry are usually revenue recognition; lease accounting; property, plant, and equipment (PPE); and hedge accounting. This study contributes to the debate on the effect of the COVID-19 pandemic on audit opinions and KAMs by offering evidence from the underexplored airline industry. © 2025 by the authors.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.