WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8653
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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 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 Visual Comfort and Indoor Environmental Quality in a Workplace Setting: A Case Study in Ankara, Türkiye(Univ Zagreb Fac Architecture, 2025) Avci, Ayse NihanWorkplaces are occasionally specified in locations where learning environments are placed together, and they are also found in common areas with various functions. Individuals need light, as it is a vital component of modern life that fosters a sense of comfort, health, and well-being. Lighting systems in interior architecture need to be designed according to the function of the space and individual needs. In cases where natural lighting is insufficient, comfortable, healthy, and prosperous places are designed with mixed-use lighting. Factors affecting indoor environmental quality, such as sound, color, and thermal comfort, should be designed together with lighting. This study aims to investigate the indoor environmental quality parameters of the specified workplace regarding visual comfort. Students voluntarily participated in the study. An experimental space on the first floor of the building, known as the "Common Building" of & Ccedil;ankaya University and serving as a connection point for the faculties, was chosen for the study. This type of research is crucial for ensuring that indoor environmental quality parameters are effectively utilized indoors to enhance human-centric interior design.Book Part A Study of the Thorp Green Poems of Anne Bronte: Poetic Artistry as a Cure for Her Nostalgia(Vernon Press, 2025) Sonmez-Demir, YagmurAmong the Bronte Sisters, Anne Bronte is the least studied, and the bulk of literary scholarship is on her novels. Most of the critics agree on the fact that her literary production is autobiographical. Taking my cue from the existing scholarship on Anne Bronte, I will study the poems Anne wrote when she was employed as a governess in Thorp Green by the Robinsons between 1840 and 1845. Highly influenced by the romantic poets preceding her, she shared her emotions in her poems. As her biographers (Gerin, Chitham, Langland) also noted, she felt excluded and lonely, especially at the start of her employment in Thorp Green, and she was able to visit her family only on Christmas and two weeks in June each year, which led her to develop a longing for her home and her family. An exhaustive study of her Thorp Green poems displays that she dislikes being there, experiences homesickness, and longs for the past days. With the exception of Gondal and religious poems written at that time span, she expresses her loneliness, solitude, and feelings of melancholy in the poems. When her homesickness heightened, she found solace in her memories and turned her feelings of longing into poetic creation. She either draws on her memories about her home in Haworth or uses objects in nature, such as a flower or a scenery as memorative signs to trigger her memories. According to sociologist Svetlana Boym, nostalgia can be "a poetic creation, an individual mechanism of survival, a countercultural practice, a poison, or a cure" (Boym 18). In this study, I will read Anne Bronte's Thorp Green Poems through the prism of theories of nostalgia, and argue that she wrote poems in order to deal with her nostalgia, for which her poetic creation becomes a cure.Conference Object Software Standards in Action: A Complaint-Driven Game Inspired by Real Project Failures(Fac Organization and Informatics, University Zagreb, 2025) Tunc, Sevgi KoyuncuComplaint to Compliance is a classroom-based game teaching ISO/IEC/IEEE 12207 standards through real-world complaint-driven scenarios. Grounded in experiential learning, its low-tech, card-based design fosters active learning via guided discussion. A qualitative case study (n=21) analyzed student perceptions, revealing: (1) conceptual bridging of theory and practice, (2) professional identity development, and (3) enhanced engagement through gamification. The accessible design offers a scalable model for standards education. Preliminary findings suggest pedagogical value for information systems education, with further cross-cultural validation needed.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 Covariance Features for Trajectory Analysis(IEEE, 2016) Karadeniz, Talha; Maras, Hadi HakanIn this work, we aimed to demonstrate that covariance estimation methods can be used for trajectory classification. We have shown that, features obtained via shrunk covariance estimation are suitable for describing trajectories. We have arrived to the conclusion that, when compared to Dynamic Time Warping, the explained technique is faster and may yield more accurate results.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.Conference Object Citation - WoS: 1Citation - Scopus: 1Dengesiz Epilepsi Veri Seti İçin Sınıflandırmada Farklı SMOTE Yöntemlerinin Etkileri(Institute of Electrical and Electronics Engineers Inc., 2025) Calis, Ahmet Gokay; Ergezer, HalitIn this study, the effects of different SMOTE methods on machine learning algorithms for the imbalanced epilepsy dataset were investigated. After filtering, the imbalanced dataset was balanced with 5 different SMOTE methods and classified with various machine learning algorithms. Coarse-K-Nearest Neighbor, Bagged Trees, and Artificial Neural Networks models were evaluated in epilepsy detection. The performance of these different models was compared with Matthews Correlation Coefficient (MCC) and F1 Score metrics. The results showed that the Borderline-SMOTE algorithm had the highest F1 Score and MCC values among all machine learning algorithms. © 2025 Elsevier B.V., All rights reserved.