Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Now showing 1 - 10 of 6529
  • Conference Object
    A Comparative Study of Attention-Augmented YOLO Architectures for Defect Detection in Fused Deposition Modelling
    (Institute of Electrical and Electronics Engineers Inc., 2025) Cezayirli, H.; Tetik, H.; Dede, M.I.C.; Phone, W.L.; Alkan, B.
    Additive manufacturing (AM), particularly fused deposition modelling (FDM), facilitates the fabrication of complex geometries with increasing flexibility and efficiency. Ensuring consistent print quality in FDM processes necessitates the development of accurate defect detection mechanisms. Attention-augmented YOLO (You Only Look Once) models have emerged as a promising solution for addressing this challenge. In this study, we systematically benchmark and evaluate the performance of YOLO architectures enhanced with attention mechanisms within the context of FDM 3D printing applications. The models were trained and evaluated using representative defect datasets. The attention-augmented models demonstrate improved detection performance. © 2025 IEEE.
  • Article
    Citation - WoS: 2
    Citation - Scopus: 1
    Çelik Fiber Katkısının Farklı Boyuna Donatı Oranına Sahip Betonarme Döşemelerin Zımbalama Davranışı Üzerinde Etkileri
    (2019) Saatci, Selcuk; Yasayanlar, Suleyman; Yasayanlar, Yonca; Batarlar, Baturay
    Sunulan çalışmada her iki yönde birbirine dik 0,004 (D1 serisi) ve 0,002 (D2 serisi) oranında boyuna donatıiçeren 2150x2150x150 mm boyutlarında iki grup betonarme döşeme, hacimce %0, %0,5, %1 ve %1,5oranında çelik fiber katkısı içeren beton karışımlarıyla dökülmüştür. Üretilen toplam sekiz döşeme ortanoktalarından statik yük altında test edilmişlerdir. Çelik fiber katkısı olmayan numunelerde yüksek boyunadonatı oranına sahip döşeme boyuna donatısında akma gerçekleşmeden gevrek bir şekilde zımbalamagöçmesi oluşurken düşük boyuna donatı oranına sahip döşeme zımbalama gerçekleşmeden önce çok dahasünek bir davranış göstermiştir. Çelik fiber katkısı her iki boyuna donatı oranında da iki kata varan oranlardazımbalama dayanımı artışlarına sebep olmuştur. Ancak D1 serisi döşemelerde çelik fiber katkısı maksimumyer değiştirmeleri önemli ölçüde arttırırken D2 serisinde maksimum yer değiştirmelerde önemli bir farkoluşmamış, bu döşemelerin yer değiştirmesi boyuna donatının akması tarafından kontrol edilmiştir. Çelikfiber katkısı oranının arttırılması D1 serisi döşemelerde dayanımın ve maksimum yer değiştirmelerinartmasına sebep olurken, D2 serisi döşemelerde %1'in üstü çelik fiber katkı oranları davranışta önemli birfark oluşturmamıştır. Yapılan deneyler Kritik Kesme Çatlağı Teorisi kullanılarak analitik olarakmodellenmiş ve bu tip modelleme ile ilgili bazı iyileştirmeler önerilmiştir.
  • 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, Eylem
    Satellite 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, Osman
    With 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
    A Capsular Polysaccharide from a Healthy Human Microbiota Member Activates a Lag-3-NK Cell Axis to Restrain Colon Cancer and Augment Immunotherapy
    (Cell Press, 2025) Weis, Allison M.; Tang, William W.; Stephen-Victor, Emmanuel; Bell, Rickesha; Brown, D. Garrett; Round, June L.
    Colorectal cancer (CRC) is increasing globally, making identification of preventative measures necessary. Transplantation of the microbiota from CRC and non-CRC patients into mice demonstrates that non-diseased individuals possess organisms that reduce tumor formation and highlights Bacteriodes uniformis as protective. B. uniformis is reduced in humans with CRC, and proactive treatment with B. uniformis slows tumor growth in mice. Natural killer (NK) cells, but not T cells, are required for B. uniformis-mediated protection. CRC is recalcitrant to immunotherapies; however, addition of B. uniformis restores response to alpha-CTLA-4 treatment in an NK cell-dependent manner. We report that high Lag-3 expression is associated with greater survival in CRC patients and that B. uniformis-mediated protection is reliant on Lag-3 in innate cells. Induction of NK cell activity and reduced tumor growth is dependent on a specific B. uniformis capsular polysaccharide. Thus, healthy individuals possess tumor suppressor microbes that prevent cancer development and can be harnessed therapeutically.
  • Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Reconfigurable Polyhedral Mechanisms Using Scissor-Like Elements with Cantellation Transformation Between Dual Geometries
    (Pergamon-Elsevier Science Ltd, 2025) Liao, Yuan; Kiper, Gokhan; Krishnan, Sudarshan
    Deployable 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, Filiz
    The 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.
  • Article
    Dysfunctional K+ Homeostasis as a Driver for Brain Inflammation
    (Multidisciplinary Digital Publishing Institute (MDPI), 2024) Ozsoy, Nagihan; Dallas, Mark L.
    The central nervous system (CNS) relies on precise regulation of potassium ion (K+) concentrations to maintain physiology. This regulation involves complex cellular and molecular mechanisms that work in concert to regulate both intracellular and extracellular K+ levels. Inflammation, a key physiological response, encompasses a series of cell-specific events leading to inflammasome activation. Perturbations in K+-sensitive processes can result in either chronic or uncontrolled inflammation, highlighting the intricate relationship between K+ homeostasis and inflammatory signalling. This review explores molecular targets that influence K+ homeostasis and have been implicated in inflammatory cascades, offering potential therapeutic avenues for managing inflammation. We examine both cell-specific and common molecular targets across different cell types, providing a comprehensive overview of the interplay between K+ regulation and inflammation in the CNS. By elucidating these mechanisms, we identify leads for drug discovery programmes aimed at modulating inflammatory responses. Additionally, we highlight potential consequences of targeting individual molecular entities for therapeutic purposes, emphasizing the need for a nuanced approach in developing anti-inflammatory strategies. This review considers current knowledge on K+-sensitive inflammatory processes within the CNS, offering critical insights into the molecular underpinnings of inflammation and potential therapeutic interventions. Our findings underscore the importance of considering K+ homeostasis in the development of targeted therapies for inflammatory conditions within the CNS. © 2025 Elsevier B.V., All rights reserved.
  • Book Part
    Citation - Scopus: 1
    Online Urban Information Systems
    (IGI Global, 2008) Yigitcanlar, Tan; Saygin, Ömür
    Countless 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.