Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Conference Object Outage and Intercept Performance in THz LEO-Ground Communication With Satellite Selection(IEEE, 2025) Bakirci, Emre Berker; Ahrazoglu, Evla Safahan; Altunbas, Ibrahim; Erdogan, EylemSatellite communication and THz communication systems are some of the methods that aim to meet the demand of increasing data rates. With an importance growing alongside increasing data amounts, data security is on its way to a position that cannot be neglected when building systems. In this study, it has been shown that secure data transmission can be made possible through the use of THz frequencies in a link between LEO satellites and a ground station. Proposed scenarios data transmission performance have been analyzed. It has been shown that selection transmission have improved both data transmission and security performances.Conference Object Teaching Accelerated Computing with Hands-On Experience(IEEE Computer Soc, 2025) Oz, Isil; Iheme, Leonardo O.Heterogeneous computing systems maintain high-performance executions with parallel hardware resources. Graphics Processing Units (GPUs) with many parallel efficient cores and high-bandwidth memory structures enable accelerated computing for high-performance, deep learning, and embedded programs from diverse domains. The expertise in GPU programming requires a significant effort to utilize parallel computational units efficiently. Teaching programming for heterogeneous systems also becomes difficult due to dedicated hardware requirements and up-to-date course materials. In this paper, we present our teaching experience in an undergraduate parallel programming course, where we adopt NVIDIA Deep Learning Institute workshop and teaching kit contents and GPU devices at different scales to expose students to a set of hardware platforms with hands-on coding experience.Conference Object Performance Evaluation of Filter-Based Gene Selection Methods in Cancer Classification(IEEE, 2025) Gokalp, OsmanWith the advances in microarray technology, gene expression levels can be measured efficiently, and this data can be used to solve important problems such as cancer classification. However, microarray data suffers from the high-dimensionality problem and requires dimensionality reduction techniques such as feature selection. This study addresses the cancer classification problem using microarray datasets and comparatively evaluates the performance of different filter-based gene (feature) selection methods. To this end, 11 microarray datasets have been evaluated using 6 different filter methods, and experimental results are presented. According to the findings, the gene selection methods used can improve classification performance by 5% to 30%. Using 5-fold cross-validation, the highest accuracy rates were achieved with 32 genes selected by the gain ratio filter for the Breast and Colon datasets, and with 8 genes selected by the information gain filter for the CNS dataset.Article Citation - WoS: 1Citation - Scopus: 1Reconfigurable Polyhedral Mechanisms Using Scissor-Like Elements with Cantellation Transformation Between Dual Geometries(Pergamon-Elsevier Science Ltd, 2025) Liao, Yuan; Kiper, Gokhan; Krishnan, SudarshanDeployable polyhedron mechanisms (DPMs) have garnered significant interest in architecture, aerospace, and robotics, where reconfigurable and space-efficient structures are crucial. This paper presents a tangential design method for DPMs using scissor-like elements (SLEs). Scissor units are placed along the edges of an equilateral polyhedron, tangential to its midsphere. This method enables the mechanisms to transform between a polyhedron and its dual, following the cantellation operation. Using screw theory, the kinematic properties of these mechanisms are analyzed. Results show that the DPMs exhibit 1-degree of freedom (DOF) under normal conditions and gain additional DOFs at multifurcation points, allowing for reconfigurable motion modes. Physical models based on various geometries, including Platonic, Archimedean, Johnson, and Catalan solids, help to validate the method's feasibility. Observations indicate that this method is only applicable to equilateral supporting polyhedra. The transformability and reconfigurability observed in these mechanisms demonstrate the potential of this approach for applications in architecture, aerospace, and robotics.Conference Object Machine Learning-Based Antenna Selection and Secrecy Capacity Analysis(Institute of Electrical and Electronics Engineers Inc., 2025) Erdurak, Burak; Erdoǧan, Eylem; Gürkan, FilizThe performance of machine learning methods was analyzed to optimize antenna selection in wireless communication systems, and system's secrecy performance was observed. To enhance the antenna selection process, Deep Neural Networks (DNNs), Convolutional Neural Networks (CNNs), and the KNearest Neighbors (KNN) algorithm were utilized. Channel vectors were used as model inputs, aiming to select the most optimal transmission path among N possible candidates. During the training phase, the antenna with the highest Signal-to-Noise Ratio (SNR) was selected for data labeling. The performance of Single-Input Multiple-Output (SIMO), Multiple-Input SingleOutput (MISO), and Multiple-Input Multiple-Output (MIMO) system architectures was evaluated using model accuracy and the F1-score. Additionally, the secrecy capacity corresponding to the selected antennas was computed, demonstrating the feasibility of secure communication. The results indicate that deep learningbased methods achieved higher accuracy, with the CNN model emerging as the most successful approach, reaching an accuracy of over 95% across all system configurations. © 2025 Elsevier B.V., All rights reserved.Book Part Citation - Scopus: 1Online Urban Information Systems(IGI Global, 2008) Yigitcanlar, Tan; Saygin, ÖmürCountless factors affect the inner workings of a city, so in an attempt to gain an understanding of place and making sound decisions, planners need to utilize decision support systems (DSS) or planning support systems (PSS). PSS were originally developed as DSS in academia for experimental purposes, but like many other technologies, they became one of the most innovative technologies in parallel to rapid developments in software engineering as well as developments and advances in networks and hardware. Particularly, in the last decade, the awareness of PSS have been dramatically heightened with the increasing demand for a better, more reliable and furthermore a transparent decision-making process (Klosterman, Siebert, Hoque, Kim, & Parveen, 2003). Urban planning as an act has quite different perspective from the PSS point of view. The unique nature of planning requires that spatial dimension must be considered within the context of PSS. Additionally, the rapid changes in socio-economic structure cannot be easily monitored or controlled without an effective PSS. © 2025 Elsevier B.V., All rights reserved.Book Part Information and Communication Technology for E-Regions(IGI Global, 2008) Velibeyoǧlu, Koray; Yigitcanlar, TanInformation and communication technologies (ICTs) are essential components of the knowledge economy, and have an immense complementary role in innovation, education, knowledge creation, and relations with government, civil society, and business within city regions. The ability to create, distribute, and exploit knowledge has become a major source of competitive advantage, wealth creation, and improvements in the new regional policies. Growing impact of ICTs on the economy and society, rapid application of recent scientific advances in new products and processes, shifting to more knowledge-intensive industry and services, and rising skill requirements have become crucial concepts for urban and regional competitiveness. Therefore, harnessing ICTs for knowledge-based urban development (KBUD) has a significant impact on urban and regional growth (Yigitcanlar, 2005). In this sense, e-region is a novel concept utilizing ICTs for regional development. Since the Helsinki European Council announced Turkey as a candidate for European Union (EU) membership in 1999, the candidacy has accelerated the speed of regional policy enhancements and adoption of the European regional policy standards. These enhancements and adoption include the generation of a new regional spatial division, NUTS-II statistical regions; a new legislation on the establishment of regional development agencies (RDAs); and new orientations in the field of high education, science, and technology within the framework of the EU’s Lisbon Strategy and the Bologna Process. The European standards posed an ambitious new agenda in the development and application of contemporary regional policy in Turkey (Bilen, 2005). In this sense, novel regional policies in Turkey necessarily endeavor to include information society objectives through efficient use of new technologies such as ICTs. Such a development seeks to be based on tangible assets of the region (Friedmann, 2006) as well as the best practices deriving from grounding initiatives on urban and local levels. These assets provide the foundation of an e-region that harnesses regional development in an information society context. With successful implementations, the Marmara region’s local governments in Turkey are setting the benchmark for the country in the implementation of spatial information systems and e-governance, and moving toward an e-region. Therefore, this article aims to shed light on organizational and regional realities of recent practices of ICT applications and their supply instruments based on evidence from selected local government organizations in the Marmara region. This article also exemplifies challenges and opportunities of the region in moving toward an e-region and provides a concise review of different ICT applications and strategies in a broader urban and regional context. The article is organized in three parts. The following section scrutinizes the e-region framework and the role of ICTs in regional development. Then, Marmara’s opportunities and challenges in moving toward an e-region are discussed in the context of ICT applications and their supply instruments based on public-sector projects, policies, and initiatives. Subsequently, the last section discusses conclusions and prospective research. © 2025 Elsevier B.V., All rights reserved.Book Part Citation - Scopus: 1Strengthening the Knowledge-Base of Cities Through ICT Strategies(IGI Global, 2008) Yigitcanlar, Tan; Velibeyoǧlu, KorayThe chapter sets out to explain the KBD processes and challenges and opportunities in information acceptance and use in urban policy making. This chapter draws on providing a clear understanding on policy frameworks and relevant ICT applications of the Queensland Smart State experience. © 2025 Elsevier B.V., All rights reserved.Article Deposition of (La,Sr)CoO₃-δ and (La,Sr)₂CoO₄-δ Cathode Layers on Gadolinia-Doped Ceria by Electrospray Deposition(Springer, 2025) Ergen, Emre; Akkurt, SedatLa-, Sr-, and Co-based oxides have proven their performances in the cathode layers of intermediate temperature levels of solid oxide fuel cells (SOFC), and hence have been frequently studied. They are deposited on the electrolyte layer by chemical vapor deposition (CVD), screen printing, pulsed laser deposition (PLD), etc. The electrospray deposition (ESD) proved itself as an effective and facile method for cathode deposition. Cathode layers deposited on gadolinia-doped ceria (GDC) with the compositions of (La0.5Sr0.5)CoO3, (La0.8Sr0.2)CoO3, (La0.5Sr0.5)2CoO4, and (La0.8Sr0.2)2CoO4 are known to provide low resistance values which are critical in cell performance. In this study, ESD is used for the first time as the coating method of these compositions. Area-specific resistance (ASR) measurements made by electrochemical impedance spectroscopy (EIS) showed promising results. Particularly, the sample coated in (La0.5Sr0.5)CoO3 composition showed an ASR value of 0.11 Omega.cm2 at 700 degrees C. ESD showed the ability to control the cathode coating microstructure by controlling the spraying parameters.Article Making Hierarchically Aware Decisions on Short Findings for Automatic Summarisation(Elsevier, 2025) Inan, EmrahAn impression in a typical radiology report emphasises critical information by providing a conclusion and reasoning based on the findings. However, the findings and impression sections of these reports generally contain brief texts, as they highlight crucial observations derived from the clinical radiograph. In this scenario, abstractive summarisation models often experience a degradation in performance when generating short impressions. To address this challenge in the summarisation task, our work proposes a method that combines well-known fine-tuned text classification and abstractive summarisation language models. Since fine-tuning a language model requires an extensive, well-defined training dataset and is a time-consuming task dependent on high GPU resources, we employ prompt engineering, which uses prompt templates to programme language models and improve their performance. Our method first predicts whether the given findings text is normal or abnormal by leveraging a fine-tuned language model. Then, we apply a radiology-specific BART model to generate the summary for abnormal findings. In the zero-shot setting, our method achieves remarkable results compared to existing approaches on a real-world dataset. In particular, our method achieves scores of 37.43 for ROUGE-1, 21.72 for ROUGE-2, and 35.52 for ROUGE-L.