WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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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: 20Citation - Scopus: 24miRdisNET: Discovering MicroRNA Biomarkers That Are Associated With Diseases Utilizing Biological Knowledge-Based Machine Learning(Frontiers Media S.A., 2023-01-12) Jabeer, Amhar; Temiz, Mustafa; Bakir-Gungor, Burcu; Yousef, MalikDuring recent years, biological experiments and increasing evidence have shown that MicroRNAs play an important role in the diagnosis and treatment of human complex diseases. Therefore, to diagnose and treat human complex diseases, it is necessary to reveal the associations between a specific disease and related miRNAs. Although current computational models based on machine learning attempt to determine miRNA-disease associations, the accuracy of these models need to be improved, and candidate miRNA-disease relations need to be evaluated from a biological perspective. In this paper, we propose a computational model named miRdisNET to predict potential miRNA-disease associations. Specifically, miRdisNET requires two types of data, i.e., miRNA expression profiles and known disease-miRNA associations as input files. First, we generate subsets of specific diseases by applying the grouping component. These subsets contain miRNA expressions with class labels associated with each specific disease. Then, we assign an importance score to each group by using a machine learning method for classification. Finally, we apply a modeling component and obtain outputs. One of the most important outputs of miRdisNET is the performance of miRNA-disease prediction. Compared with the existing methods, miRdisNET obtained the highest AUC value of .9998. Another output of miRdisNET is a list of significant miRNAs for disease under study. The miRNAs identified by miRdisNET are validated via referring to the gold-standard databases which hold information on experimentally verified MicroRNA-disease associations. miRdisNET has been developed to predict candidate miRNAs for new diseases, where miRNA-disease relation is not yet known. In addition, miRdisNET presents candidate disease-disease associations based on shared miRNA knowledge. The miRdisNET tool and other supplementary files are publicly available at: .Article Citation - Scopus: 1eTNT: Enhanced Textnettopics With Filtered LDA Topics and Sequential Forward / Backward Topic Scoring Approaches(Science and Information Organization, 2024) Voskergian, Daniel; Jayousi, Rashid; Bakir-Güngör, BurcuTextNetTopics is a novel text classification-based topic modelling approach that focuses on topic selection rather than individual word selection to train a machine learning algorithm. However, one key limitation of TextNetTopics is its scoring component, which evaluates each topic in isolation and ranks them accordingly, ignoring the potential relationships between topics. In addition, the chosen topics may contain redundant or irrelevant features, potentially increasing the feature set size and introducing noise that can degrade the overall model performance. To address these limitations and improve the classification performance, this study introduces an enhancement to TextNetTopics. eTNT integrates two novel scoring approaches: Sequential Forward Topic Scoring (SFTS) and Sequential Backward Topic Scoring (SBTS), which consider topic interactions by assessing sets of topics simultaneously. Moreover, it incorporates a filtering component that aims to enhance topics' quality and discriminative power by removing non-informative features from each topic using Random Forest feature importance values. These integrations aim to streamline the topic selection process and enhance classifier efficiency for text classification. The results obtained from the WOS-5736, LitCovid, and MultiLabel datasets provide valuable insights into the superior effectiveness of eTNT compared to its counterpart, TextNetTopics. © 2024 Elsevier B.V., All rights reserved.Article Citation - WoS: 29Citation - Scopus: 32Wind Farm Site Selection Using GIS-Based Multicriteria Analysis With Life Cycle Assessment Integration(Springer Heidelberg, 2024-01-19) Demir, Abdullah; Dincer, Ali Ersin; Ciftci, Cihan; Gulcimen, Sedat; Uzal, Nigmet; Yilmaz, KutayThe sustainability of wind power plants depends on the selection of suitable installation locations, which should consider not only economic and technical factors including manufacturing and raw materials, but also issues pertaining to the environment. In the present study, a novel methodology is proposed to determine the suitable locations for wind turbine farms by analyzing from the environmental perspective. In the methodology, the life cycle assessment (LCA) of wind turbines is incorporated into the decision process. The criteria are ranked using analytical hierarchy process (AHP). The study area is chosen as the western region of Turkiye. The obtained suitability map reveals that wind speed is not the sole criterion for selecting a site for wind turbine farms; other factors, such as bird migration paths, distance from urban areas and land use, are also crucial. The results also reveal that constructing wind power plants in the vicinity of Izmir, canakkale, Istanbul, and Balikesir in Turkiye can lead to a reduction in emissions. Izmir and its surrounding area show the best environmental performance with the lowest CO2 per kilowatt-hour (7.14 g CO2 eq/kWh), to install a wind turbine due to its proximity to the harbor and steel factory across the study area. canakkale and the northwest region of Turkiye, despite having high wind speeds, are less environmentally favorable than Izmir, Balikesir, and Istanbul. The findings of LCA reveal that the nacelle and rotor components of the wind turbine contribute significantly (43-97%) to the environmental impact categories studied, while the tower component (0-36%) also has an impact.Article Citation - WoS: 6Citation - Scopus: 7Whether and When Did Bitcoin Sentiment Matter for Investors? Before and During the COVID-19 Pandemic(Springer, 2023-12-21) Aysan, Ahmet Faruk; Mugaloglu, Erhan; Polat, Ali Yavuz; Tekin, HasanUsing a wavelet coherence approach, this study investigates the relationship between Bitcoin return and Bitcoin-specific sentiment from January 1, 2016 to June 30, 2021, covering the COVID-19 pandemic period. The results reveal that before the pandemic, sentiment positively drove prices, especially for relatively higher frequencies (2-18 weeks). During the pandemic, the relationship was still positive, but interestingly, the lead-lag relationship disappeared. Employing partial wavelet tools, we factor out the number of COVID-19 cases and deaths and the Equity Market Volatility Infectious Disease Tracker index to observe the direct relationship between a change in sentiment and return. Our results robustly reveal that, before the pandemic, sentiment had a positive effect on return. Although positive coherence still existed during the pandemic, the lead-lag relationship disappeared again. Thus, the causal relationship that states that sentiment leads to return can only be integrated into short-term trading strategies (up to six weeks frequency).Article Citation - WoS: 6Citation - Scopus: 6WDR31 Displays Functional Redundancy With GTpase-Activating Proteins (GAPs) ELMOD and RP2 in Regulating Ift Complex and Recruiting the BBsome to Cilium(Life Science Alliance Llc, 2023-05-19) Cevik, Sebiha; Peng, Xiaoyu; Beyer, Tina; Pir, Mustafa S.; Yenisert, Ferhan; Woerz, Franziska; Kaplan, Oktay, IThe correct intraflagellar transport (IFT) assembly at the ciliary base and the IFT turnaround at the ciliary tip are key for the IFT to perform its function, but we still have poor understanding about how these processes are regulated. Here, we identify WDR31 as a new ciliary protein, and analysis from zebrafish and Caeno-rhabditis elegans reveals the role of WDR31 in regulating the cilia morphology. We find that loss of WDR-31 together with RP-2 and ELMD-1 (the sole ortholog ELMOD1-3) results in ciliary accumu-lations of IFT Complex B components and KIF17 kinesin, with fewer IFT/BBSome particles traveling along cilia in both anterograde and retrograde directions, suggesting that the IFT/BBSome entry into the cilia and exit from the cilia are impacted. Furthermore, anterograde IFT in the middle segment travels at increased speed in wdr-31;rpi-2;elmd-1. Remarkably, a non-ciliary protein leaks into the cilia of wdr-31;rpi-2;elmd-1, possibly because of IFT de-fects. This work reveals WDR31-RP-2-ELMD-1 as IFT and BBSome trafficking regulators.Article Citation - WoS: 7Citation - Scopus: 7Very High Early Strength Calcium Aluminate Based Binary and Ternary Cementitious Systems: Properties, Hydration and Microstructure(Taylor & Francis Ltd, 2023-06-16) Saydan, Murat; Keskin, Ulku Sultan; Uzal, BurakCalcium aluminate cement (CAC) is a cement type that has superior properties such as rapid strength gain, high resistance to high temperatures and harmful chemicals. However, the result of the using of CACs in the production of structural elements occur strength decreases at later ages as a result of a series of chemical reactions called 'conversion reactions' seen in these cements. In this study, the hydration kinetics and the crystalline and amorphous structures formed as a result of hydration were investigated in CAC containing different amounts and types of main oxides-based binary and ternary systems. Considering the results obtained, the main hydration product seen in these specimens was ettringite. Unlike many studies in the literature, metastable structures which cause conversion reactions, such as CAH(10), C(2)AH(8), have not been observed. Instead of conversion of the phases, ettringite needles were became thin and elongate which causes the paste structure porous and thus causing expansion and strength reduction at the later stages of hydration in some mixtures produce high amounts of ettringite. On the other hand, it is understood that the formation of stratlingite was limited strength decreases in systems where high silica fume is used.Article Citation - WoS: 7Citation - Scopus: 7Villages in the City - Urban Planning for Neighbourhood Love(Wiley, 2024-03-17) Kourtit, Karima; Nijkamp, Peter; Turk, Umut; Wahlstrom, MiaThe city comprises of a wide variety of heterogeneous territorial units (e.g. districts or neighbourhoods). In many - especially larger - cities, social capital assets (like community bonds) are mirrored at the level of neighbourhoods which form the home for many sociocultural communities or distinct socio-economic classes. We postulate in this study that the big city is essentially an 'archipelago' made up of 'urban villages'. We analyse the residents' perceived attractiveness regarding their daily local neighbourhood by introducing the concept of 'village love' (or 'neighbourhood love'), inspired by the recent literature on 'city love' (comprising 'body', 'soul' and 'community' constituents of urban life). Based on an extensive and detailed multi-annual database for all neighbourhoods in Rotterdam, the present paper seeks to identify the background factors shaping 'village love' in the city, with particular attention to the citizens' subjective appreciation for and access to a great variety of (physical and immaterial) urban amenities shaping the place-based satisfaction of residents. The theoretical framing of our research resembles the basics of traditional central place theory here transmitted to the urban space in which local proximity to amenities plays a key role. A wide array of relevant amenities impacting on the place-specific well-being feelings ('village love') of residents in various neighbourhoods in the city of Rotterdam is distinguished using inter alia-rich multi-annual survey data. This approach is empirically tested and verified by means of LISA statistics and advanced spatial econometric dependence models ('urbanometrics'). The findings confirm the usefulness of a central place interpretation of 'urban village love' in the city. 'Villages in the City - Urban Planning for Neighbourhood Love': This study advocates that cities are composed of interconnected 'urban villages', each with its own social capital and community bonds. Using extensive data from Rotterdam, we investigate the factors influencing residents' perceived attractiveness and satisfaction with their local neighbourhoods. Our analysis highlights the importance of access to diverse amenities in shaping residents' sense of 'village love'. Through spatial econometric models, the study confirms the central place interpretation of 'urban village love' in the city, shaping future urban planning strategies for fostering vibrant and cohesive communities.imageArticle Use of Confocal Microscopy to Monitor Structural Transformations in Nanopillars Based on DNA and CdSe/CdZnSe Quantum Dots(Springer, 2023-06-24) Motevich, I. G.; Erdem, T.; Akrema, A.; Maskevich, S. A.; Strekal, N. D.Chip system prototypes in the form of nanopillars were created from DNA complexes with CdSe/CdZnSe/ZnS quantum dots immobilized on a plasmonic gold fi lm by the use of vacuum deposition technology and inorganic synthesis. The design and presence of terminal DNA labeled with Cy3 cyanine dyes makes it possible to carry out the hybridization reaction of this terminal strand with complementary DNA and to control the process by variation of the giant Raman scattering (GRS) and the fluorescence signal. The effect of molecular recognition of complementary DNA is accompanied by a change in the GRS spectrum, a 20-fold increase in the fluorescence intensity, and a decrease in the duration of fluorescence decay.Article Citation - WoS: 7Citation - Scopus: 7Unveiling the Multifaceted Properties of a 3D Covalent-Organic Framework: Pressure-Induced Phase Transition, Negative Linear Compressibility and Auxeticity(Elsevier, 2023-08) Erkartal, MustafaHigh-pressure behavior and mechanical properties of a three-dimensional covalent-organic framework (NPN-1) were investigated by using different types of first principles molecular simulations. An irreversible pressureinduced first-order isosymmetric phase transition was predicted at 0.14 GPa. The subunit of NPN-1 retains its rigidity under pressure thanks to the strong covalent bonds. However, compression leads to significant tilting of the nitrophenyl groups. The mechanical properties of frameworks are highly anisotropic. Remarkably, both phases exhibit not only negative linear compressibility along the c-axis but also negative Poisson's ratio in certain directions. Detailed structural analysis revealed that the origin of the phase transition and anomalous mechanical properties of both phases are the wine-rack motif and strut-hinge mechanism. To the best of our knowledge, this study is the first report of such behavior in COFs, opening up new avenues for the exploration of COFs as materials for many promising applications.