WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article GenShare: A Blockchain-Based Genomic Data Sharing Platform(Association for Computing Machinery, 2026-01-27) Dedeturk, B.A.; Soran, A.; Bakir-Güngör, B.Every day, hundreds of gigabytes of data are produced due to the exponential growth of next-generation sequencing and omics technologies. By combining omics data with other data types, such as electronic health record data, panomics research is actively attempting to uncover novel and potentially useful biomarkers. For the effective analysis of high-throughput-derived omics data, it is imperative to establish robust and reliable platforms that prioritize ethical considerations while effectively managing privacy, ownership concerns, and the responsible sharing of data. The GenShare model was proposed to provide an efficient platform that fits these needs. GenShare is a hybrid platform that utilizes blockchain technology. Paillier’s homomorphic encryption scheme in tandem with Intel Software Guard Extension (SGX) serves to enable the sharing of genomic data, execution of count queries, and statistical analysis of genomic data while preserving privacy and avoiding compromise of sensitive information. The objective of this paradigm is to confront security and privacy concerns through the integration of homomorphic encryption and SGX, addressing additional challenges associated with Hyperledger Fabric and Ethereum. In pursuit of this objective, the implementation of the system involved establishing the Hyperledger Fabric network, with various workloads employed to assess the network’s efficiency. Consequently, it was hypothesized that the new GenShare model would enhance the data collection and dissemination cycle and serve as a proficient platform catering to the needs of its users. © 2026 Copyright held by the owner/author(s).Erratum Correction to “Multifaceted Effects of the Dielectric Component within Plasmon-Assisted Light-Emitting Structures”(American Chemical Society, 2025-12-17) Kulakovich, O.; Muravitskaya, A.; Ramanenka, A.; Efimova, T.; Krukov, V.; Mutlugün, E.; Gaponenko, S.In the original version of the article, the affiliation of Hilmi Volkan Demir needs following correction. The first affiliation of the author “Department of Electrical-Electronics Engineering, Abdullah Gul University, Kayseri 38080, Turkey” should be replaced by the affiliation “UNAM – Institute of Materials Science and Nanotechnology and The National Nanotechnology Research Center and Department of Electrical and Electronics Engineering, Department of Physics, Bilkent University, Ankara 06800, Turkey”. Therefore, the correct affiliations for H.V.D. are “UNAM – Institute of Materials Science and Nanotechnology and The National Nanotechnology Research Center and Department of Electrical and Electronics Engineering, Department of Physics, Bilkent University, Ankara 06800, Turkey; LUMINOUS! Center of Excellence for Semiconductor Lighting and Displays, School of Electrical and Electronic Engineering, School of Physical and Mathematical Sciences, School of Materials Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore”. © 2025 American Chemical SocietyConference Object Shooting a Water Slug Into an Air Column with and without Vent(Amer Soc Mechanical Engineers, 2025-07-20) Bozkus, Zafer; Dincer, Ali Ersin; Tijsseling, Arris S.; van de Ven, FonsCompressed air is used to shoot a single water slug into an upward sloping pipe with elbow and orifice at its upper end. The experiment concerns a 12 m long pipe of 0.1 m diameter connected to a 0.5 m3 air vessel. The 10 to 50 kg heavy slugs are initially at rest in the lower part of the system. Because the upper end is closed by a flange with orifice, the water slug is expected not to hit the upstream elbow. It causes - like a piston - a fast compression of the air column ahead of it. Sometimes the slug bounces back and forth, which results in a pressure oscillation of serious amplitude. Numerical simulations based on an elementary mathematical model are normally used to interpret the pressure measurements, not all of which are fully understood. Lessons learned are summarised, and suggestions for improved experiments and enhanced simulations are given. The research is of importance, for example, for steam lines where liquid condensates may collect in lower parts after power failure. Start-up of the system will then lead to rapid slug acceleration and potentially damaging impact on elbows, orifices, and machinery.Conference Object Security Through Digital Twin-Based Intrusion Detection: A Swat Dataset Analysis(IEEE, 2023-10-18) Bozdal, MehmetDigital twin, as a virtual replica of physical entity, offer valuable insights into Industrial Control System (ICS) behavior and characteristics. Leveraging the convergence of digital twins and cybersecurity, this research explores its role in securing critical infrastructure, using the Secure Water Treatment (SWaT) system as a case study. Existing intrusion detection systems (IDS) for SWaT encounter challenges related to requiring huge amounts of a dataset for training, being unable to adopt high data dimensionality, and adaptability to emerging threats. To address these issues, a hybrid digital twin model is proposed, combining physics-based models and data-driven approaches. This model facilitates precise attack localization and explainable IDS outcomes. The method exhibits promising capabilities for enhancing critical infrastructure security and adapting to evolving cyber threats. Experimental results demonstrate the ability to detect eight out of nine attack types.Article High-Accuracy Identification of Durian Leaf Diseases: A Convolutional Neural Network Approach Validated with K-Fold Cross-Validation and Bayesian Optimization(Springer, 2025-11-18) Soylemez, Ismet; Nalici, Mehmet Eren; Unlu, RamazanTo address the economic losses caused by plant diseases in durian farming, this study presents an optimized deep learning model that diagnoses diseases from leaf images with high accuracy. The model's performance is maximized through Bayesian optimization and hyperparameter tuning, while its reliability is maximized through layered five-fold cross-validation. Training the convolutional neural network model on 2595 leaf images displaying six different states (five diseased and one healthy) resulted in an average test accuracy of 91.98%. This high, consistent success rate demonstrates the model's generalizability to different datasets without overfitting. While the 'Healthy' and 'Algal' classes were successfully detected with high F1-scores, there are difficulties distinguishing between the 'Blight' and 'Colletotrichum' classes due to visual similarities. This study establishes a new reference point for durian disease classification and makes a significant contribution to the development of reliable artificial intelligence-based diagnostic tools for precision agriculture.Article Citation - WoS: 1Citation - Scopus: 1A Comparative Study of Existing and Current On-Site Documentation of Anatolian Seljuk Kümbets(Elsevier Ltd, 2025-12) Güzelci, O.Z.; Türel, A.During the Anatolian Seljuk period (1077–1307), monumental tombs known as kümbets emerged as a distinct architectural typology in present-day Türkiye. 2D drawings of these structures, produced since the early 20th century, contain inconsistencies that necessitate verification and accurate documentation. This study digitally documents Anatolian Seljuk kümbets in 3D to generate updated 2D sections reflecting their current condition and compares these with previously published drawings. The methodology includes collecting available 2D sections, digitally documenting kümbets through field studies, generating new 2D sections from 3D models, and systematically comparing these datasets. Two image-based metrics are employed in the comparison: the Exact Pixel Match Ratio (EPMR), which evaluates pixel-level alignment, and the Structural Similarity Index Measure (SSIM), a standard indicator for visual similarity. The results provide a comparative framework for assessing previous drawings and present a verified, up-to-date dataset of kümbet sections for future research. © 2025 Elsevier B.V., All rights reserved.Article Citation - WoS: 4Citation - Scopus: 3Multifaceted Effects of the Dielectric Component Within Plasmon-Assisted Light-Emitting Structures(American Chemical Society, 2025-10-23) Kulakovich, O.; Muravitskaya, A.; Ramanenka, A.; Efimova, T.; Krukov, V.; Mutlugün, E.; Gaponenko, S.Plasmon-enhanced photoluminescence of molecular probes and semiconductor nanocrystals is a rapidly developing field that promises enhanced sensitivity in chemical and biomedical analyses, as well as higher efficiency of light-emitting devices and single-photon sources. The dielectric component, or spacer, is typically used to control the distance between the emitter and the plasmonic nanoparticle in order to decrease undesirable nonradiative energy transfer to the metal and achieve high enhancement efficiency. While most research focuses on the shape and organization of the plasmonic nanoparticles, less attention is given to the role of the dielectric component in plasmon-enhancing structures. Meanwhile, the dielectric shell or environment critically modulates near-field enhancement, far-field scattering, charge and energy exchange between the emitter and the plasmonic structure, and the general environmental stability of the structure. In this review, we discuss all mentioned topics and therefore consider both the optical and chemical influence of the widely used spacers and dielectric layers on plasmon-enhanced photoluminescence efficiency. Investigating the role of individual components in plasmon-assisted light-emitting structures is critical for optimizing device performance and for advancing the integration of plasmonic architectures in optoelectronic and sensing applications. This review challenges the passive interpretation of dielectrics, revealing them as one of the key players in plasmonic structures, mediating field enhancement, emission dynamics, and chemical stability simultaneously. © 2025 American Chemical SocietyArticle Citation - WoS: 2Citation - Scopus: 2Measuring Eudaimonic and Hedonic Wellbeing: Development and Validation of the Holistic Wellbeing Measure(Routledge, 2025-10-09) Arslan, G.; Coşkun, M.The primary goal of this study was to develop a concise, theoretically grounded tool –the Holistic Wellbeing Measure (HWM)– that captures both hedonic and eudaimonic facets of wellbeing. Items for the HWM were generated through a careful review of existing wellbeing scales and literature, followed by expert consultation, pilot testing, and iterative refinement to ensure conceptual coverage, clarity, and face validity. Data were collected from three distinct samples: adolescents (n = 453), young adults (n = 361), and adults (n = 358). Exploratory and confirmatory factor analyses supported a two-factor structure, with 12 items reflecting independent but related hedonic and eudaimonic wellbeing dimensions. The measure demonstrated strong internal reliability and evidence of convergent, discriminant, and concurrent validity across all age groups. Regression analyses further indicated that the HWM contributed unique variance to the prediction of general health indicators (physical, social, and mental health) and psychological problems (depression, anxiety, and somatization), above the effects of gender, age, and psychological wellbeing. These results suggest that the HWM is a valid and reliable measure for assessing both aspects of wellbeing across age groups and can support strategies aimed at promoting overall mental health. © 2025 Taylor & Francis Group, LLC.Conference Object Citation - WoS: 1Citation - Scopus: 1Oscillator Phase Noise Impact on Monostatic/Bistatic Space-Borne Sub-THz ISAR(IEEE, 2025-05-21) Bekari, Ali; Gashinova, Marina; Bekar, Muge; Martorellai, Marco; Antonioni, Michail; Bekar, Ali; Martorella, Marco; Antoniou, MichailThis study develops an oscillator phase noise model and analyzes its effects on the performance of spaceborne monostatic and bistatic Inverse Synthetic Aperture Radar (B-ISAR) systems operating at the sub-THz band. The B-ISAR study is of current importance as it can provide a basis for distributed space-based ISAR to enable persistent co-operative space domain awareness (Co-SDA).Conference Object Enhancing Complex Disease Group Scoring with Mirgedinet: A Multi-Algorithm Machine Learning Framework Based on the GSM Approach(IEEE, 2025-06-25) Qumsiyeh, Emma; Bakir-Gungor, Burcu; Yousef, MalikIntegrating biological prior knowledge for disease gene associations has shown significant promise in discovering new biomarkers with potential translational applications. This work investigates the application of a multi-algorithm machine learning framework based on the Grouping-Scoring-Modeling (G-S-M) approach for improving the prediction of complex diseases. The study identifies the primary gene and miRNA interactions in various complex diseases with the help of miRGediNET, which is a machine-learning based tool that integrates data from three biological databases. Traditional methods have only focused on independence between features; the G-S-M method focuses on aggregating genes based on biological interactions, pinpointing the scoring of gene groups for a disease, and modeling its predictive capability using advanced machine learning algorithms. In this research paper, seven algorithms, including Support Vector Machine, Decision Tree, and CatBoost, were applied to eight datasets extracted from the GEO database. This framework proved very robust in ranking gene clusters, thus predicting critical biomarkers while doing 100-fold randomized cross-validation within the evaluation. The results indicate this approach's high potential for refining disease and supporting research for choosing the best algorithm that can provide biological insights and computational advances.