Computer Engineering / Bilgisayar Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/10
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Conference Object Enhancing genomic data sharing with blockchain-enabled dynamic consent in beacon V2(Springernature, 2024) Binokay, Leman; Celik, Hamit Mervan; Gurdal, Gultekin; Ayav, Tolga; Tuglular, Tugkan; Oktay, Yavuz; Karakulah, GokhanArticle Citation - WoS: 41Citation - Scopus: 50Bim-Carem: Assessing the Bim Capabilities of Design, Construction and Facilities Management Processes in the Construction Industry(Elsevier, 2023) Gökçen, Yılmaz; Akçamete, Aslı; Demirörs, OnurBIM adoption has accelerated worldwide since it is an important enabling technology for digitalisation in the construction industry. Adopting BIM requires transforming the traditional building life cycle stages (planning, design, construction and facilities management) into BIM-integrated project deliveries. Assessing the BIM ca- pabilities of these stages helps organisations to identify gaps in their BIM uses and improve them. There is a lack of a comprehensive model in the literature for assessing the BIM capabilities of individual building life cycle stages and their processes. Existing assessment models focus on assessing the BIM maturity of construction projects and organisations which do not inform the required BIM improvements for individual stages and their processes. Hence, we iteratively developed the Building Information Modelling (BIM) Capability Assessment REference Model (BIM-CAREM) and demonstrated its usability through multiple explanatory case studies per- formed with two international design and engineering companies and two general contractors in Turkey. We assessed the BIM capabilities of design, construction and facility management processes of various buildings i.e. residential, stadiums, hospitals and airports. The results showed that the BIM capability levels of design, con- struction and facility management processes vary within and across the companies.Article Citation - WoS: 4Citation - Scopus: 4Integrative Biological Network Analysis To Identify Shared Genes in Metabolic Disorders(Institute of Electrical and Electronics Engineers, 2022) Tenekeci, Samet; Işık, ZerrinIdentification of common molecular mechanisms in interrelated diseases is essential for better prognoses and targeted therapies. However, complexity of metabolic pathways makes it difficult to discover common disease genes underlying metabolic disorders; and it requires more sophisticated bioinformatics models that combine different types of biological data and computational methods. Accordingly, we built an integrative network analysis model to identify shared disease genes in metabolic syndrome (MS), type 2 diabetes (T2D), and coronary artery disease (CAD). We constructed weighted gene co-expression networks by combining gene expression, protein-protein interaction, and gene ontology data from multiple sources. For 90 different configurations of disease networks, we detected the significant modules by using MCL, SPICi, and Linkcomm graph clustering algorithms. We also performed a comparative evaluation on disease modules to determine the best method providing the highest biological validity. By overlapping the disease modules, we identified 22 shared genes for MS-CAD and T2D-CAD. Moreover, 19 out of these genes were directly or indirectly associated with relevant diseases in the previous medical studies. This study does not only demonstrate the performance of different biological data sources and computational methods in disease-gene discovery, but also offers potential insights into common genetic mechanisms of the metabolic disorders.Article Citation - WoS: 6Citation - Scopus: 6Cauchy-Rician Model for Backscattering in Urban Sar Images(Institute of Electrical and Electronics Engineers, 2022) Karakuş, Oktay; Kuruoğlu, Ercan Engin; Achim, Alin; Altınkaya, Mustafa AzizThis letter presents a new statistical model for urban scene synthetic aperture radar (SAR) images by combining the Cauchy distribution, which is heavy tailed, with the Rician backscattering. The literature spans various well-known models most of which are derived under the assumption that the scene consists of multitudes of random reflectors. This idea specifically fails for urban scenes since they accommodate a heterogeneous collection of strong scatterers such as buildings, cars, and wall corners. Moreover, when it comes to analyzing their statistical behavior, due to these strong reflectors, urban scenes include a high number of high amplitude samples, which implies that urban scenes are mostly heavy-tailed. The proposed Cauchy-Rician model contributes to the literature by leveraging nonzero location (Rician) heavy-tailed (Cauchy) signal components. In the experimental analysis, the Cauchy-Rician model is investigated in comparison to state-of-the-art statistical models that include $\mathcal {G}_{0}$ , generalized gamma, and the lognormal distribution. The numerical analysis demonstrates the superior performance and flexibility of the proposed distribution for modeling urban scenes.Article Citation - WoS: 6Citation - Scopus: 10Efficient Privacy-Preserving Whole-Genome Variant Queries(Oxford University Press, 2022) Akgün, Mete; Pfeifer, Nico; Kohlbacher, OliverMotivation: Diagnosis and treatment decisions on genomic data have become widespread as the cost of genome sequencing decreases gradually. In this context, disease-gene association studies are of great importance. However, genomic data are very sensitive when compared to other data types and contains information about individuals and their relatives. Many studies have shown that this information can be obtained from the query-response pairs on genomic databases. In this work, we propose a method that uses secure multi-party computation to query genomic databases in a privacy-protected manner. The proposed solution privately outsources genomic data from arbitrarily many sources to the two non-colluding proxies and allows genomic databases to be safely stored in semi-honest cloud environments. It provides data privacy, query privacy and output privacy by using XOR-based sharing and unlike previous solutions, it allows queries to run efficiently on hundreds of thousands of genomic data. Results: We measure the performance of our solution with parameters similar to real-world applications. It is possible to query a genomic database with 3 000 000 variants with five genomic query predicates under 400 ms. Querying 1 048 576 genomes, each containing 1 000 000 variants, for the presence of five different query variants can be achieved approximately in 6 min with a small amount of dedicated hardware and connectivity. These execution times are in the right range to enable real-world applications in medical research and healthcare. Unlike previous studies, it is possible to query multiple databases with response times fast enough for practical application. To the best of our knowledge, this is the first solution that provides this performance for querying large-scale genomic data.Article Citation - WoS: 7Citation - Scopus: 8Tracking Code Bug Fix Ripple Effects Based on Change Patterns Using Markov Chain Models(Institute of Electrical and Electronics Engineers Inc., 2022) Ufuktepe, Ekincan; Tuğlular, Tuğkan; Palaniappan, KanappanChange impact analysis evaluates the changes that are made in the software and finds the ripple effects, in other words, finds the affected software components. Code changes and bug fixes can have a high impact on code quality by introducing new vulnerabilities or increasing their severity. A recent high-visibility example of this is the code changes in the log4j web software CVE-2021-45105 to fix known vulnerabilities by removing and adding method called change types. This bug fix process exposed further code security concerns. In this article, we analyze the most common set of bug fix change patterns to have a better understanding of the distribution of software changes and their impact on code quality. To achieve this, we implemented a tool that compares two versions of the code and extracts the changes that have been made. Then, we investigated how these changes are related to change impact analysis. In our case study, we identified the change types for bug-inducing and bug fix changes using the Quixbugs dataset. Furthermore, we used 13 of the projects and 621 bugs from Defects4J to identify the common change types in bug fixes. Then, to find the change types that cause an impact on the software, we performed an impact analysis on a subset of projects and bugs of Defects4J. The results have shown that, on average, 90% of the bug fix change types are adding a new method declaration and changing the method body. Then, we investigated if these changes cause an impact or a ripple effect in the software by performing a Markov chain-based change impact analysis. The results show that the bug fix changes had only impact rates within a range of 0.4-5%. Furthermore, we performed a statistical correlation analysis to find if any of the bug fixes have a significant correlation with the impact of change. The results have shown that there is a negative correlation between caused impact with the change types adding new method declaration and changing method body. On the other hand, we found that there is a positive correlation between caused impact and changing the field type.Article Citation - WoS: 7Citation - Scopus: 8Long-Term Image-Based Vehicle Localization Improved With Learnt Semantic Descriptors(Elsevier, 2022) Çınaroğlu, İbrahim; Baştanlar, YalınVision based solutions for the localization of vehicles have become popular recently. In this study, we employ an image retrieval based visual localization approach, in which database images are kept with GPS coordinates and the location of the retrieved database image serves as the position estimate of the query image in a city scale driving scenario. Regarding this approach, most existing studies only use descriptors extracted from RGB images and do not exploit semantic content. We show that localization can be improved via descriptors extracted from semantically segmented images, especially when the environment is subjected to severe illumination, seasonal or other long-term changes. We worked on two separate visual localization datasets, one of which (Malaga Streetview Challenge) has been generated by us and made publicly available. Following the extraction of semantic labels in images, we trained a CNN model for localization in a weakly-supervised fashion with triplet ranking loss. The optimized semantic descriptor can be used on its own for localization or preferably it can be used together with a state-of-the-art RGB image based descriptor in hybrid fashion to improve accuracy. Our experiments reveal that the proposed hybrid method is able to increase the localization performance of the standard (RGB image based) approach up to 7.7% regarding Top-1 Recall values.Conference Object Citation - WoS: 37Graph Theoretic Clustering Algorithms in Mobile Ad Hoc Networks and Wireless Sensor Networks (survey)(Azerbaijan National Academy of Sciences, 2007) Erciyeş, Kayhan; Dağdeviren, Orhan; Çokuslu, Deniz; Özsoyeller, DenizClustering in mobile ad hoc networks (MANETs) and wireless sensor networks (WSNs) is an important method to ease topology management and routing in such networks. Once the clusters are formed, the leaders (coordinators) of the clusters may be used to form a backbone for efficient routing and communication purposes. A set of clusters may also provide the underlying physical structure for multicast communication for a higher level group communication module which may effectively be used for fault tolerance and key management for security purposes. We survey graph theoretic approaches for clustering in MANETs and WSNS and show that although there is a wide range of such algorithms, each may be suitable for a different cross-layer design objective.Article Citation - WoS: 2Citation - Scopus: 2Density-Aware Cellular Coverage Control: Interference-Based Density Estimation(Elsevier, 2019) Eroğlu, Alperen; Yaman, Okan; Onur, ErtanAs demand for mobile communications increases, cells have to become smaller to efficiently use the scarce spectrum and to increase capacity, and small-cell networks will hereby emerge. They may be large in scale and highly dynamic resembling ad hoc networks due to the moving base stations. The variations in the density of the small cell networks impact the quality of service and introduce many novel challenges such as coverage control. We propose two novel base station density estimators, the interference-based density estimator (IDE) and the multi-access edge cloud-based density estimator (CDE) in a three-dimensional field. The estimators employ received signal strength measurements. We validate these two density estimators by using Monte-Carlo simulations. Furthermore, we analyze the impact of density on network outage in cellular networks and propose a density-aware cell zooming technique. According to the observations, base station (BS) density affects network coverage significantly. Received signal strength (RSS)-based density estimators can easily be implemented and applied in the network communication stack although they are more prone to shadowing and fading. Under favour of the density-aware cell zooming method, the network outage can be managed dynamically by adapting the transmit power, which provides a self-configurable and -organized network. (C) 2019 Elsevier B.V. All rights reserved.Article Citation - WoS: 17Citation - Scopus: 19Pixelated Colorimetric Nucleic Acid Assay(Elsevier, 2020) Aydın, Hakan Berk; Cheema, Jamal Ahmed; Arnmanath, Gopal; Toklucu, Cihan; Yücel, Müge; Özenler, Sezer; Yıldız, Ümit HakanConjugated polyelectrolytes (CPEs) have been widely used as reporters in colorimetric assays targeting nucleic acids. CPEs provide naked eye detection possibility by their superior optical properties however, as concentration of target analytes decrease, trace amounts of nucleic acid typically yield colorimetric responses that are not readily perceivable by naked eye. Herein, we report a pixelated analysis approach for correlating colorimetric responses of CPE with nucleic acid concentrations down to 1 nM, in plasma samples, utilizing a smart phone with an algorithm that can perform analytical testing and data processing. The detection strategy employed relies on conformational transitions between single stranded nucleic acid-cationic CPE duplexes and double stranded nucleic acid-CPE triplexes that yield distinct colorimetric responses for enabling naked eye detection of nucleic acids. Cationic poly[N,N,N-triethyl-3-((4-methylthiophen-3-yl)oxy)propan-1-aminium bromide] is utilized as the CPE reporter deposited on a polyvinylidene fluoride (PVDF) membrane for nucleic acid assay. A smart phone application is developed to capture and digitize the colorimetric response of the individual pixels of the digital images of CPE on the PVDF membrane, followed by an analysis using the algorithm. The proposed pixelated approach enables precise quantification of nucleic acid assay concentrations, thereby eliminating the margin of error involved in conventional methodologies adopted for interpretation of colorimetric responses, for instance, RGB analysis. The obtained results illustrate that a ubiquitous smart phone could be utilized for point of care colorimetric nucleic acids assays in complex matrices without requiring sophisticated software or instrumentation.
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