Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Article Optimization of Fleet Search on Network of Regions(Elsevier Ltd, 2026) Yakıcı, E.; Erişkin, L.; Karatas, M.; Karasakal, O.Unmanned Aerial Vehicles (UAVs) are widely used in modern military missions, primarily for surveillance, reconnaissance, search and detection, and air-to-ground strikes. The widespread use of UAVs in recent conflicts, such as the Russia–Ukraine war, once again highlighted their growing strategic importance. The complexity of military missions carried out by UAVs, coupled with the need for autonomous and coordinated fleet operations, requires analytical approaches to optimize deployment planning and improve operational efficiency. In this study, we address a UAV deployment planning problem for search and detection missions, in which a homogeneous fleet of UAVs is tasked with searching for hostile assets across a network of disjoint regions. Each region is characterized by an a priori probability of target presence, a search difficulty factor which affects the probability of detection, and known inter-region distances. For this purpose, we first develop a mixed-integer nonlinear programming formulation which determines the base locations of UAVs, allocates the limited search time across regions, and sequences the visits to maximize the total time-weighted detection probability mass to achieve the highest probability as much and as early as possible during the operation. Next, we apply a tangent line approximation technique to reformulate the model as a mixed-integer linear programming problem, which we solve using commercial off-the-shelf solvers. We then propose a hybrid heuristic approach based on the ant colony optimization method to generate high-quality solutions. Our computational experiments reveal that the proposed heuristic significantly reduces solution time while maintaining superior performance compared to the linear approximation model. © 2026 The AuthorsArticle 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 Citation - Scopus: 1Randomised Comparison Between Navigation and Non-Navigation Camera Control Performance in a Surgical Simulation Task Using a Haptic Device Interface(Wolters Kluwer Medknow Publications, 2026) Cagiltay, Nergiz Ercil; Topalli, Damla; Tuner, Emre; Berker, MustafaIntroduction:Navigation skills for controlling the camera in the surgical field are critical for many minimally invasive surgery (MIS) procedures. Currently, endoscopes lack integrated navigation aids, making camera control a challenging task. This experimental study aims to investigate the effect of navigation guidance on the performance of beginners.Patients and Methods:A custom computer-based simulation environment was developed for this study, featuring two conditions - one with navigation guidance and one without - focussed on a camera-cleaning task. Participants (64 beginners) were randomly assigned to one of these groups and used two haptic devices to simulate the endoscope and surgical tools.Results:Participants in the guided condition performed significantly better than those in the unguided condition. Notably, female participants completed the task in significantly less time under the guided condition compared to the unguided one.Conclusion:These findings suggest that incorporating navigation aids into endoscope interfaces could improve user performance, especially for beginners. Medical device manufacturers should consider adding navigation features to enhance usability. In addition, simulation-based instructional systems should integrate navigation aids to better support surgical training.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.Article Forecasting the Methane Yield of a Commercial-Scale Anaerobic Digestor Based on the Biomethane Potential of Feedstocks(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Türker Bayrak, Ö.T.; Uludaǧ-Demirer, S.; Xu, M.; Liao, W.; Bayrak, Ozlem TurkerWith rising energy demand and the need for sustainable waste treatment, anaerobic digestion (AD) has emerged as a key technology for converting organic residues into renewable energy. However, predicting methane yield in full-scale facilities remains challenging due to the complexity of AD processes, the variability of feedstocks, and the impracticality of frequent biochemical methane potential (BMP) testing. In this study, we developed a simple, data-driven approach to forecast methane production in a commercial-scale digester co-digesting manure and food waste. The model employs weekly cumulative BMP of feedstock mixtures, calculated from literature values, as the explanatory variable. The model achieved an R2 of 0.70 and a forecast mean absolute percentage error (MAPE) of 7.4, indicating its potential for full-scale AD prediction. Importantly, the analysis revealed a long-run equilibrium between BMP and methane yield, with deviations corrected within roughly one month—closely matching the system’s hydraulic retention time. These findings demonstrate that literature-based BMP values can be used to reliably predict methane yield in operating AD systems, offering a low-cost and scalable tool to support decision-making in waste management and biogas plant operations. © 2025 by the authors.Conference Object AviBERT: Transformer Tabanlı Hava Aracı Metni Sınıflandırma(Institute of Electrical and Electronics Engineers Inc., 2025) Unal, Muhammed Cihat; Yurtalan, Gokhan; Karatas, Yahya Bahadir; Karamanlioglu, Alper; Demirel, BerkanIn recent years, transformer-based models pre-trained on extensive corpora have played a critical role in the advancement of Natural Language Processing methodologies. Particularly, methods based on BERT have demonstrated remarkable performance across various tasks by offering robust capabilities in deeply understanding texts semantically. However, despite these advancements, there is a notable scarcity of studies applying these technologies in the aviation sector. This paper develops a multi-class classification model for aviation-specific texts using variants of BERT. The study encompasses the processes of collecting web content related to aircraft, labeling and model training. The details of the dataset are explained and the outcomes of the study are assessed based on the macro F1-score and accuracy of different models. © 2025 Elsevier B.V., All rights reserved.
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