WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Analysis of Power-Law Fin-Type Problems Using Physics Informed Neural Networks(Sciendo, 2025-12-01) Gocer, M.; Coskun, S. B.; Atay, M. T.This study aims to model the temperature distribution in a single fin subjected to steady one-dimensional heat conduction with nonlinear thermal behavior. For the modeling and solution of the problem, the Physics-Informed Neural Networks (PINNs) architecture was used. The temperature-dependent heat conduction problem and the nonlinear boundary conditions of this problem were formulated with a differential equation. With the help of the PINN architecture, the loss function was minimized in order to reduce the difference between the true value and the predicted value. During this minimization process, the PINN architecture was forced to be consistent with the physical laws. The results obtained after training the PINN architecture exhibit successful performance in terms of accuracy and reliability when compared with the results in the literature. These findings highlight the potential of PINNs as a powerful alternative to conventional methods for solving complex nonlinear heat conduction problems.Conference 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 Citation - WoS: 1Citation - Scopus: 1Numerical Analysis and Experimental Comparison of Stress and Stiffness Parameters of Steel Reinforced Geopolymer Concrete Columns(Elsevier Sci Ltd, 2026-01) Ozbayrak, Ahmet; Kucukgoncu, Hurmet; Aslanbay, Huseyin Hilmi; Aslanbay, Yuksel Gul; Altun, FatihDespite extensive research, Geopolymer concrete (GPC) lacks reinforced concrete construction and design specifications. Developing such specifications requires comprehensive studies to promote the use of GPC, which is known for its superior performance and environmental benefits compared to ordinary Portland cement concrete (OPC). This study numerically investigated and compared the behavior and strength of fly ash-based geopolymer-reinforced concrete columns with the experimental results. Comparisons with OPC were made based on existing specifications. Herein, FEM analyses were conducted on 16 GPC and 4 OPC columns under eccentric axial compressive loads. Parameters such as eccentricity, reinforcement ratio, curing method, and activation solution ratios were varied. According to average numerical results, the GPC columns have 7% more moment capacity and 30% more curvature values than OPC. Moreover, GPC columns absorbed more energy than OPC columns. Also, GPC columns have higher axial load and bending moment carrying capacities than OPC for numerical results. Error analysis between FEM and experimental data revealed a strong correlation, with MAPE values of 8.88% (axial load) and 7.20% (moment) for GPC columns, confirming the reliability of the numerical model. ACI 318 and Eurocode 2 specifications were deemed applicable for GPC columns, provided axial loads are limited per TEC 2018.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: 1Citation - Scopus: 1An Ultra-Low Fabric Capacitive Glove for Real-Time Motion Tracking and Human–computer Interaction(Institute of Physics, 2025-11-04) Başıbüyük, Y.; Mutluç, M.N.; Şavur, Ö.; İçöz, K.This study presents the development of a wearable glove system that integrates ultra-low-cost, fabric-based capacitive sensors for motion detection and human–computer interaction. The system combines touch and bend sensors fabricated from commercially available silver-coated fabric and silicone acrylic tape, enabling real-time tracking of finger movements via measurable capacitance changes. The glove translates physical gestures into digital commands, facilitating intuitive control in virtual environments. Experimental evaluation demonstrated stable operation across a wide pressure range (10–200 g, equivalent to 1.25–25 kPa), with an unnormalized sensitivity of ∼0.00504 pF g−1 (∼0.0040 pF kPa−1), corresponding to a normalized sensitivity of ∼0.0067 kPa−1 when referenced to the baseline capacitance (C<inf>0</inf> ≈ 6 pF). The device exhibited high repeatability over 4000 loading cycles, and minimal signal variation (coefficient of variation, CV < 0.005). Integration with a Unity-based interface enabled low-latency gesture tracking in real time. Each sensor was fabricated for less than $0.05 using simple, scalable methods, without nanomaterials or cleanroom processing. Owing to its affordability, fabrication simplicity, and mechanical robustness, the proposed glove system provides a practical and scalable platform for wearable motion tracking, with strong potential in rehabilitation, assistive technologies, and interactive systems. © 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.Article 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 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.Conference Object High Performance and Resource Efficient Low Density Parity Check Decoder Design(IEEE, 2025-06-25) Unal, BurakLow Density Parity Check (LDPC) codes have gained popularity in communication systems due to their capacity-approaching error correction performance. In this study, a highperformance LDPC decoding algorithm with extremely low resource usage is proposed. Among the hard decision class of LDPC decoders, Gallager B (GaB) provides high-performance hardware due to its computational simplicity. However, GaB suffers from poor error-correction performance. In this study, a new intrinsic computation technique for GaB called Intrinsic Gallager B (IGaB) is introduced to improve error correction performance. Our simulation results show that the IGaB algorithm provides better error correction performance compared with GaB. GaB and IGaB algorithms are implemented on Field Programmable Gate Array (FPGA) to compare hardware performance.Conference Object Exploring Microbiome Signatures in Autism Spectrum Disorder via Grouping-Scoring Based Machine Learning(IEEE, 2025-06-25) Temiz, Mustafa; Ersoz, Nur Sebnem; Yousef, Malik; Bakir-Gungor, BurcuThe rapid increase in omic data production increased the importance of machine learning (ML) methods to analze these data. In particular, the use of metagenomic data in the diagnosis, prognosis and treatment of diseases is becoming widespread. Autism Spectrum Disorder (ASD) is a neurodevelopmental disease that occurs in early childhood and continues lifelong. The aim of this study is to increase ML performance, reduce computational costs and achieve successful classification performance using a small number of metagenomic features. In addition, disease prediction is performed; ASD associated biomarkers are determined using the microBiomeGSM on metagenomic data. Classification is performed at three different taxonomic levels (genus, family and order) using the relative abundance values of species. The best performance metric (0.95 AUC) was obtained at the order taxonomic level using an average of 416 features with microBiomeGSM. The identified ASD-related taxonomic species are presented.