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).Article Enhancing Mode Transition Dynamics in Non-Inverting Buck-Boost Inverters for PV Systems(Institute of Electrical and Electronics Engineers Inc., 2026) Keskinkilic, E.; Tekgun, B.Quasi-single-stage inverters (QSSIs) are notable for their simple structure and bidirectional operation capability in applications such as photovoltaic (PV) systems. Among these QSSI, the non-inverting buck-boost inverter (NIBBI) or four-switch buck-boost inverter (FSBBI) is often preferred due to its ability to perform both step-down and step-up operations. However, when traditional control is used, achieving a smooth transition and efficient conversion becomes challenging as the output voltage approaches the input voltage. The pulse width ratio limitations and non-idealities of active and passive components are the cause of this. In this paper, a comparative analysis of the mode transition techniques in FSBBI is presented using methods available for DC/DC converters. System efficiency and output voltage signal quality are selected as performance metrics. A 2-kW FSBBI is installed and controlled using single, two, modified two, three, and four-mode techniques. Simulation and experimental studies were conducted to validate the results. Based on these studies, the four-mode control technique was observed to be the most effective in eliminating dead zone effects, reducing total harmonic distortion (THD), and achieving the highest system efficiency in a PV system where a battery powers the AC load. Experimental results indicate that the four-mode modulation attained an efficiency of 95.49% with a THD of 2.97%. © 1986-2012 IEEE.Article Citation - WoS: 2Citation - Scopus: 1Resilience and Market Diversification in Sustainable Tourism: Evidence from International Arrivals to Türkiye (2012-2025)(Emerald Group Publishing Ltd, 2026-02-02) Atay, Mehmet Tarik; Ciuffreda, Raffaela; Coskun, Safa BozkurtPurposeThis study analyzes the possible connections between resilience and market diversification of inbound tourism to T & uuml;rkiye from 2012 to 2025. The aim is to assess the reaction of international arrivals to global fluctuations, such as the COVID-19 pandemic era, and to examine the structural linkage to primary source markets within the concept of sustainable tourism management.Design/methodology/approachThe research uses annual country-specific data related to international arrivals. We used time-series analysis to uncover long-term behaviors and the consequences of crises. The research also used Shannon entropy and the Herfindahl-Hirschman Index to look at market concentration and diversity. A comparative analysis of the primary source countries indicates variations in recovery trajectories and resilience in the concept of sustainable tourism management.FindingsThe results show that T & uuml;rkiye's inbound tourism grew steadily until 2019, decreased severely during the pandemic and then bounced back strongly from 2022 to 2024. Market diversity has improved over time, but dependence on Germany and the Russian Federation tourists' activities is still high. Although the UK was more stable, and regional markets like Bulgaria and Iran were more unstable, their positive effect on achieving the sustainable tourism goal is still weak.Research limitations/implicationsThe study is constrained by the partial coverage of 2025 data and the lack of direct indicators for environmental or social sustainability. Future research may combine these dimensions and their data to construct a more thorough and detailed evaluation for better understanding of the sustainable tourism context.Practical implicationsThe results show that for tourism in T & uuml;rkiye to be sustainable, it needs to have more diverse source markets, be better prepared for global or local crises and have plans for managing capacity, especially tourism management and seasonality. These insights can help government policymakers and local destination management bodies make long-term sustainability stronger.Social implicationsHighly concentrated tourism markets may cause revenue and employment volatility when principal source countries experience a downturn. Advocating for diversity in terms of various source markets for inbound tourism activities enhances tourism-related economic and social resilience and community welfare in terms of stable income flow and fosters inclusive growth throughout the local and national community in accordance with sustainable tourism objectives.Originality/valueThis study directly connects resilience and diversity to the management of sustainable tourism in a new destination. By integrating long-term real case data with related, respected and detailed market structure metrics, it offers novel insights into how destinations might improve their competitiveness, decreased vulnerabilities in crisis time periods and improve the sustainability of the tourism sector.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: 2Citation - Scopus: 2Numerical 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 Microstrip Stub Filter Design with Enhanced Performance Inspired by SIW Structures Operating at 1.93 GHz GSMBand(Gazi Univ, 2026-03-29) Tosun, Huseyin; Yentur, Abdulkadir; Kilic, Veli TayfunThis paper reports a microstrip stub filter design operating at 1.93 GHz GSM band with enhanced performance inspired by SIW structures. In the designed filter additional vias are placed around the microstrip lines to enhance the encasing of the electromagnetic fields while propagating through the filter to develop the filter performance. The filter was examined with electromagnetic simulations for various numbers of vias and different via to microstrip line distances. Results show that the maximum transmission coefficient (S21 parameter) magnitude value reached in the pass band of the filter increases with the number of the vias and as the vias get closer to the lines. On the other hand, when the via number increases and the space between them and the lines narrows, the frequency at which the maximum S21 value is attained shifts to lower frequencies. The designed filters were manufactured, too. Results obtained in the measurements agree well with the simulation results. Additionally, a receiver system operating at 1.93 GHz band was constructed. System experiments were carried out with the constructed prototype for the manufactured filters. Results show that a greater signal level in the filter pass band is achieved and unwanted signals outside the filter pass band are suppressed more in the system where the filter with vias is used instead of the filter without any additional via. The findings indicate that the designed filters inspired by SIW structures are promising for applications requiring high signal quality.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.