https://hdl.handle.net/20.500.12573/30 Faculty of Engineering Sat, 04 Apr 2026 06:51:26 GMT 2026-04-04T06:51:26Z https://hdl.handle.net/20.500.12573/2542 An effective colorectal polyp classification for histopathological images based on supervised contrastive learning Yengec-Tasdemir,Sena Busra; Aydin,Zafer; Akay,Ebru; Doğan,Serkan; Yilmaz,Bulent Early detection of colon adenomatous polyps is pivotal in reducing colon cancer risk. In this context, accurately distinguishing between adenomatous polyp subtypes, especially tubular and tubulovillous, from hyperplastic variants is crucial. This study introduces a cutting-edge computer-aided diagnosis system optimized for this task. Our system employs advanced Supervised Contrastive learning to ensure precise classification of colon histopathology images. Significantly, we have integrated the Big Transfer model, which has gained prominence for its exemplary adaptability to visual tasks in medical imaging. Our novel approach discerns between in-class and out-of-class images, thereby elevating its discriminatory power for polyp subtypes. We validated our system using two datasets: a specially curated one and the publicly accessible UniToPatho dataset. The results reveal that our model markedly surpasses traditional deep convolutional neural networks, registering classification accuracies of 87.1% and 70.3% for the custom and UniToPatho datasets, respectively. Such results emphasize the transformative potential of our model in polyp classification endeavors Mon, 01 Jan 2024 00:00:00 GMT https://hdl.handle.net/20.500.12573/2542 2024-01-01T00:00:00Z https://hdl.handle.net/20.500.12573/2540 Integrating Biological Domain Knowledge with Machine Learning for Identifying Colorectal-Cancer-Associated Microbial Enzymes in Metagenomic Data Bakir-Gungor, Burcu; Ersoz, Nur Sebnem; Yousef, Malik Advances in metagenomics have revolutionized our ability to elucidate links between the microbiome and human diseases. Colorectal cancer (CRC), a leading cause of cancer-related mortality worldwide, has been associated with dysbiosis of the gut microbiome. This study aims to develop a method for identifying CRC-associated microbial enzymes by incorporating biological domain knowledge into the feature selection process. Conventional feature selection techniques often evaluate features individually and fail to leverage biological knowledge during metagenomic data analysis. To address this gap, we propose the enzyme commission (EC)-nomenclature-based Grouping-Scoring-Modeling (G-S-M) method, which integrates biological domain knowledge into feature grouping and selection. The proposed method was tested on a CRC-associated metagenomic dataset collected from eight different countries. Community-level relative abundance values of enzymes were considered as features and grouped based on their EC categories to provide biologically informed groupings. Our findings in randomized 10-fold cross-validation experiments imply that glycosidases, CoA-transferases, hydro-lyases, oligo-1,6-glucosidase, crotonobetainyl-CoA hydratase, and citrate CoA-transferase enzymes can be associated with CRC development as part of different molecular pathways. These enzymes are mostly synthesized by Eschericia coli, Salmonella enterica, Klebsiella pneumoniae, Staphylococcus aureus, Streptococcus pneumoniae, and Clostridioides dificile. Comparative evaluation experiments showed that the proposed model consistently outperforms traditional feature selection methods paired with various classifiers. Wed, 01 Jan 2025 00:00:00 GMT https://hdl.handle.net/20.500.12573/2540 2025-01-01T00:00:00Z https://hdl.handle.net/20.500.12573/2539 Axial free vibration analysis of a tapered nanorod using Adomian decomposition method Coskun, Safa B.; Kara, Ozge; Atay, Mehmet T. This study aimed to conduct an analysis of the axial free vibration of tapered nanorods based on nonlocal elasticity theory. The small-scale effect on the free axial vibration of a tapered nanorod was studied employing the Adomian decomposition method (ADM) and the finite difference method (FDM) as a checking tool where a contradiction existed between the results of this study and available results in one highly cited work in the literature, which was used for comparison purposes in this work. Different boundary conditions for the nanorod were considered: fixed-fixed nanorod, fixed-free nanorod, and fixed-linear spring nanorod. The governing equation of the problem is a variable coefficient differential equation for which analytical solutions are strictly limited. For this type of problem, analytical approximate methods are effective, and there are many studies available in the literature on the application of these methods to solve linear/nonlinear ordinary/partial differential equations. ADM is one of the methods and was successfully used in this study to analyze the free vibration of nanorods. The results obtained in this study have shown that the presented technique is so powerful and has potential for applications in nanomechanics based on nonlocal elasticity theory. Wed, 01 Jan 2025 00:00:00 GMT https://hdl.handle.net/20.500.12573/2539 2025-01-01T00:00:00Z https://hdl.handle.net/20.500.12573/2538 Horseradish peroxidase (HRP) nanoflowers-mediated polymerization of vinyl monomers Ozaydin, Gulbahar; Mirioglu, Muge; Kaplan, Naime; Dadi, Seyma; Ocsoy, Ismail; Gokturk, Ersen The effects of flower-shaped hybrid nano biocatalyst (hFe-NFs) from coordination between horseradish peroxidase (HRP) enzyme and Fe2+ ions on the free-radical polymerization reactions of three different vinyl monomers (styrene, methylmethacrylate and acrylamide) were investigated. Polymerizations of styrene and methylmethacrylate (MMA) were performed under emulsion conditions using three different surfactants in the presence of acetylacetone (AcAc) and hydrogen peroxide (H2O2) initiator. Polymerization of water soluble acrylamide was accomplished under surfactant-free media. According to the obtained outcomes, hFe-NFs exhibited higher catalytic activity towards polymerization of vinyl monomers compared to the free-HRP enzyme in terms of yields and the number average molecular weights (Mn) of the synthesized polymers. hFe-NFs also demonstrated very high thermal stability. While optimum polymerization of styrene was achieved at room temperature (RT), the highest polymerization yields for acrylamide and MMA were respectively accomplished at 70 and 60 degrees C in which free-HRP enzyme loses its catalytic activity. Preparation of the flower-shaped hFe-NFs, therefore, enables inexpensive and stable catalyst system for free-radical polymerization of vinyl monomers compared to free-HRP enzyme. Increasing catalytic activity and stability of hFe-NFs at higher reaction temperatures are very crucial for utilization of these types of catalysts in both scientific and industrial purposes. Mon, 01 Jan 2024 00:00:00 GMT https://hdl.handle.net/20.500.12573/2538 2024-01-01T00:00:00Z