Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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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.Book Part Nanomaterials Incorporated Intelligent Food Packing for the Detection and Prevention of Microbial Contamination and Spoilage(CRC Press, 2025-10-23) Dadi, S.; Temu, N.; Ozdemir, E.; Nisari, M.; Azizoglu, U.; Öçsoy, I.Food packaging plays a critical role in the quality and safety of food and the health of consumers. Environmental factors such as food storage conditions (temperature and light) and microbial contamination are highly effective in food spoilage. Environmental factors on traditional food packaging can negatively affect the shelf life of food products, which poses significant risks to human health. To track the quality and safety of food, the development of intelligent food packaging technologies has received great attention from researchers. The advances in food packaging technology emphasize the importance of developing real-time-traceable, long shelf life, microbial contamination–inhibiting, and biocompatible packaging solutions. In recent years, various nanomaterials (NMs) in the development of intelligent food packaging have been used. NM-based food packaging exhibits many properties, such as antimicrobial and antioxidant effects, electrical conductivity, thermal stability, and catalytic activity. In this chapter, we present a broad overview of NM-based intelligent packaging systems for sensing and preventing microbial contamination and food spoilage. © 2026 selection and editorial matter, Priya Sutaoney, Priyambada Singh, Durgesh Nandini Chauhan, Nagendra Singh Chauhan, and Kamal Shah; individual chapters, the contributors.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.Conference Object Citation - Scopus: 2miRcorrNetPro: Unraveling Algorithmic Insights Through Cross-Validation in Multi-Omics Integration for Comprehensive Data Analysis(Institute of Electrical and Electronics Engineers Inc., 2023-12-05) Ünlü Yazici, Miray; Yousef, Malik; Marron, J. S.; Bakir-Güngör, Burcu; Yazici, Miray UnluHigh throughput -omics technologies facilitate the investigation of regulatory mechanisms of complex diseases. Along this line, scientists develop promising tools and methods to extend our understanding at the molecular and functional levels. To this end, miRcorrNet tool performs integrative analysis of MicroRNA (miRNA) and gene expression profiles via machine learning (ML) approach to identify significant miRNA groups and their associated target genes. In this study, we propose miRcorrNetPro tool, which extends miRcorrNet by tracking group scoring, ranking and other information through the cross-validation iterations. Heatmap visualizations enable deep novel insights into the collective behavior of clusters of groups in cellular signaling and hence facilitate detection of potential biomarkers for the disease under investigation. Although miRcorrNetPro is designed as a generic tool, here we present our findings and potential miRNA biomarkers for Breast Cancer (BRCA). The miRcorrNetPro tool and all other supplementary files are available at https://github.com/Miray-Unlu/miRcorrNetPro. © 2024 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 1Words Speak Louder Than Actions: Decoding Emotions Through NLP(Institute of Electrical and Electronics Engineers Inc., 2024-10-26) Paksoy, Melda; Bakal, GokhanEmotion detection in text remains a significant challenge in Natural Language Processing due to human emotions' complexity and subtle nuances. This paper presents multiple experimental models for emotion classification using an up-to-date dataset curated to address 13 emotions implied in Twitter posts. We evaluated various machine learning (ML) models, including Logistic Regression, Random Forest, SVM, and XGBoost, alongside deep learning (DL) architectures such as LSTM and CNN. Our results demonstrate the efficacy of deep learning models, particularly the CNN model by achieving an impressive F1 score of 0.99. This study contributes to emotion detection capabilities, paving the way for more nuanced and accurate sentiment analysis (SA) in various text analysis applications. © 2025 Elsevier B.V., All rights reserved.Book Part Citation - Scopus: 4Within Our Walls: White-Collar Crime in Greek Academia(Taylor and Francis, 2015) Georgoulas, Stratos; Voulvouli, AimiliaBook Part Citation - WoS: 5Citation - Scopus: 5Wireless MEMS for Smart Grids(Woodhead Publ Ltd, 2017) Tuna, G.; Gungor, V. C.; Dursun, B.Book Part Citation - Scopus: 3Using Night-Time Lights and Statistical Data to Measure Regional Inequality in Turkey(IGI Global, 2024-04-12) Ustaoglu, EdaPoverty and inequality are the outstanding challenges in both developing and developed countries in the globe. Using Suomi National Polar-orbiting Partnership (NPP)-Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light (NTL) images and socio-economic data from administrative sources, this chapter focuses on the association between nighttime lights and economic activities with an aim of computing regional income inequality indices for the year 2015 in Turkey. Gini, the Atkinson and Theil statistics were used to establish regional inequality indices using both NTL and statistics data. The findings indicated that urban NTLs are strongly correlated with economic activity while the correlation is much weaker regarding rural nightlights and agricultural output. It can be noted that there was increasing regional inequality in north-west, south, and south-east regions whereas regional equality was more homogeneously distributed. The results indicated that NPP-VIIRS nightlight data can help to perform regional inequality assessments for the urban areas in Turkey. © 2024 Elsevier B.V., All rights reserved.Conference Object Urban Pornography: Anti-Places of Modern Architectural Heritage in Turkey(Docomomo, 2021) Kesim, Berk; Baturayoğlu Yöney, Nilüfer; Yöney, Nilüfer BaturayoğluPlaces are distinctive yet sometimes architecture may degrade them by design: Rebuilding the same architectural entity may not always reproduce the authentic place and its attributes but instead create anti-places in the urban environment, which may absorb and deprive the surrounding settings by creating sameness. The term pornography here has no erotic connotations but describes an image-oriented anti-design attitude, the way architects may create anti-places by copying, pasting, overemphasizing, and thus, objectifying certain place attributes. The urban-scape exposed by architectural design and deprived of its dignity is urban pornography. The paper focuses on two examples from Turkey: The Turkish Monopoly Liquor and Cognac Factory (Mecidiyeköy, Istanbul; Rob Mallet-Stevens, 1930), now rebuilt as Mecidiyeköy Towers (EAA, Istanbul, 2010-2017) and the Sait Bey and Semih Rüstem villas (Atatürk Street, Adana; Semih Rüstem Temel, 1932), now rebuilt as Semih Rüstem Commercial Center (MArS Architects, Istanbul, 2006-2012), both with a more than 10-fold increase in built area. The reconstruction in both cases was based on a declaration of being unfit in terms of function and technology beyond the obvious urban pressure of increasing the built-up area. Although both listed, the reconstructions did not preserve any characteristics or original architectural elements except for the general form and parts of the authentic names. Ultimately, the paper identifies this eradication of character and the creation of anti-places upon the case studies, perhaps the greatest threat against modern architectural heritage in urban areas. © 2021 Elsevier B.V., All rights reserved.