Muhammet Burhan Navdar
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Muhammet Burhan Navdar has a total of 24 co-authors. Here are the top co-authors by number of shared publications:
Erkan Çelebi
3 shared publications- Bekir Aktaş
Erciyes Universitesi
2 shared publications - Ferhat Çeçen
Süleyman Demirel Üniversitesi
2 shared publications - Hakan Öztürk
Department of Civil Engineering, Engineering Faculty, Sakarya University, Sakarya 54050, Turkey
2 shared publications - Muaz Kemerli
Department of Mechanical, Industrial, and Manufacturing Engineering, University of Toledo, Toledo, USA
2 shared publications - Sefer Arda Serbes2 shared publications
Latest Publications
- 4 October 2026
- Published by Elsevier in Engineering Structures
- Vol. 369
Time-delay effects on the sensitivity and robustness of semi-active TLCD control under far and near field earthquakes
- 4 October 2026
- Published by Elsevier in Engineering Structures
- Vol. 369
Time-delay effects on the sensitivity and robustness of semi-active TLCD control under far and near field earthquakes
- Open Access
- 18 December 2025
- Published by MDPI AG in Diagnostics
- Vol. 15 (24) , 3236
SPX-GNN: An Explainable Graph Neural Network for Harnessing Long-Range Dependencies in Tuberculosis Classifications in Chest X-Ray Images
Background/Objectives: Traditional medical image analysis methods often suffer from locality bias, limiting their ability to model long-range contextual relationships between spatially distributed anatomical structures. To overcome this challenge, this study proposes SPX-GNN (Superpixel Explainable Graph Neural Network). This novel method reformulates image analysis as a structural graph learning problem, capturing both local anomalies and global topological patterns in a holistic manner. Methods: The proposed framework decomposes images into semantically coherent superpixel regions, converting them into graph nodes that preserve topological relationships. Each node is enriched with a comprehensive feature vector encoding complementary diagnostic clues, including colour (CIELAB), texture (LBP and Haralick), shape (Hu moments), and spatial location. A Graph Neural Network is then employed to learn the relational dependencies between these enriched nodes. The method was rigorously evaluated using 5-fold stratified cross-validation on a public dataset comprising 4200 chest X-ray images. Results: SPX-GNN demonstrated exceptional performance in tuberculosis classification, achieving a mean accuracy of 99.82%, an F1-score of 99.45%, and a ROC-AUC of 100.00%. Furthermore, an integrated Explainable Artificial Intelligence module addresses the black box problem by generating semantic importance maps, which illuminate the decision mechanism and enhance clinical reliability. Conclusions: SPX-GNN offers a novel approach that successfully combines high diagnostic accuracy with methodological transparency. By providing a robust and interpretable workflow, this study presents a promising solution for medical imaging tasks where structural information is critical, paving the way for more reliable clinical decision support systems.
- 18 December 2025
- Published by MDPI AG in Diagnostics
- Vol. 15 (24) , 3236
Open AccessSPX-GNN: An Explainable Graph Neural Network for Harnessing Long-Range Dependencies in Tuberculosis Classifications in Chest X-Ray Images
Background/Objectives: Traditional medical image analysis methods often suffer from locality bias, limiting their ability to model long-range contextual relationships between spatially distributed anatomical structures. To overcome this challenge, this study proposes SPX-GNN (Superpixel Explainable Graph Neural Network). This novel method reformulates image analysis as a structural graph learning problem, capturing both local anomalies and global topological patterns in a holistic manner. Methods: The proposed framework decomposes images into semantically coherent superpixel regions, converting them into graph nodes that preserve topological relationships. Each node is enriched with a comprehensive feature vector encoding complementary diagnostic clues, including colour (CIELAB), texture (LBP and Haralick), shape (Hu moments), and spatial location. A Graph Neural Network is then employed to learn the relational dependencies between these enriched nodes. The method was rigorously evaluated using 5-fold stratified cross-validation on a public dataset comprising 4200 chest X-ray images. Results: SPX-GNN demonstrated exceptional performance in tuberculosis classification, achieving a mean accuracy of 99.82%, an F1-score of 99.45%, and a ROC-AUC of 100.00%. Furthermore, an integrated Explainable Artificial Intelligence module addresses the black box problem by generating semantic importance maps, which illuminate the decision mechanism and enhance clinical reliability. Conclusions: SPX-GNN offers a novel approach that successfully combines high diagnostic accuracy with methodological transparency. By providing a robust and interpretable workflow, this study presents a promising solution for medical imaging tasks where structural information is critical, paving the way for more reliable clinical decision support systems.
- 13 October 2025
- Published by Elsevier in Soil Dynamics and Earthquake Engineering
- Vol. 200
A novel semi-active piston-TLCD for structural vibration control: Design, modeling, and performance assessment
- 13 October 2025
- Published by Elsevier in Soil Dynamics and Earthquake Engineering
- Vol. 200
A novel semi-active piston-TLCD for structural vibration control: Design, modeling, and performance assessment
- 28 December 2024
- Published by Elsevier in Journal of Building Engineering
- Vol. 102
Experimental and numerical study on vibration mitigation of slender structures with TLCD under second-order effects
- 28 December 2024
- Published by Elsevier in Journal of Building Engineering
- Vol. 102
Experimental and numerical study on vibration mitigation of slender structures with TLCD under second-order effects
- Open Access
- 15 November 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (22) , 10544
An Effective Alternative to the Open Trench Method for Mitigating Ground-Borne Environmental Body Waves: Corrugated Cardboard Boxes Reinforced with Balsa Wood
This research develops and evaluates a recyclable corrugated cardboard vibration isolation box reinforced with balsa wood as an alternative to traditional open trench methods for mitigating ground-borne environmental body waves. This study includes designing and testing scaled prototypes, laboratory analyses, prototype fabrication, and full-scale field experiments. In soft ground conditions, ensuring slope stability during deep excavations is a key engineering challenge for open trenches. For this purpose, scaled prototypes were subjected to laboratory tests to assess the resistance of the wave barrier’s wall surface. Numerical analyses were also conducted to evaluate the strength of the internal lattice structure under various loads. A prototype was fabricated for on-site experiments simulating real-world conditions. Field experiments evaluated the vibration isolation performance of the proposed barrier. Accelerometer sensors were strategically placed to gather data, analyzing ground surface vibrations for free field motions to assess the vibration shielding efficiency of both the open trench method and the corrugated vibration isolation box, with and without Styrofoam infill. This study concludes that the recyclable corrugated vibration isolation box is a viable alternative, offering comparable or improved vibration isolation efficiency in soft soil conditions while promoting environmental sustainability using recyclable materials.
- 15 November 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (22) , 10544
Open AccessAn Effective Alternative to the Open Trench Method for Mitigating Ground-Borne Environmental Body Waves: Corrugated Cardboard Boxes Reinforced with Balsa Wood
This research develops and evaluates a recyclable corrugated cardboard vibration isolation box reinforced with balsa wood as an alternative to traditional open trench methods for mitigating ground-borne environmental body waves. This study includes designing and testing scaled prototypes, laboratory analyses, prototype fabrication, and full-scale field experiments. In soft ground conditions, ensuring slope stability during deep excavations is a key engineering challenge for open trenches. For this purpose, scaled prototypes were subjected to laboratory tests to assess the resistance of the wave barrier’s wall surface. Numerical analyses were also conducted to evaluate the strength of the internal lattice structure under various loads. A prototype was fabricated for on-site experiments simulating real-world conditions. Field experiments evaluated the vibration isolation performance of the proposed barrier. Accelerometer sensors were strategically placed to gather data, analyzing ground surface vibrations for free field motions to assess the vibration shielding efficiency of both the open trench method and the corrugated vibration isolation box, with and without Styrofoam infill. This study concludes that the recyclable corrugated vibration isolation box is a viable alternative, offering comparable or improved vibration isolation efficiency in soft soil conditions while promoting environmental sustainability using recyclable materials.
- 13 March 2024
- Published by Springer Nature
- p. 35-38
Non-linear Dynamic Analysis of Structures Including Site Response Effects with Soil–Structure Interaction Problem
- 13 March 2024
- Published by Springer Nature
- p. 35-38
Non-linear Dynamic Analysis of Structures Including Site Response Effects with Soil–Structure Interaction Problem
- 31 January 2022
- Published by Demiryolu Muhendisligi Dergisi, Demiryolu Muhendisleri Dernegi in Demiryolu Mühendisliği
- No. 15,p. 97-110
Karbon-Fiber Plaka Donatılı Traverslerin, B70-Tipi Öngerilmeli Beton Traverslerle Karşılaştırmalı İncelenmesi
Bu çalışma kapsamında, yerli karbon fiber takviyeli poliüretan plakalar ile donatılandırılmış beton traverslerin merkez negatif eğilme performansı, öngerilmeli B70 tipi traverslerle karşılaştırmalı yürütülen deneyler ile araştırılmıştır. Yapılan testler sonucunda, yeni tip traverslerin yorulma esaslı dizayn yükünün, B70 tipi öngerilmeli traverslerin 2 katına ulaşan oranda daha yüksek sonuçlandığı görülmüştür. Ayrıca yeni tip traverslerde herhangi bir öngerilme kuvveti veya etriye kullanılmamasına rağmen, B70 tipi öngerilmeli traverslerin kırılma yükünün üzerindeki yük değerlerinde dahi, meydana gelen çatlak genişliklerinin halen 0,05 mm’nin altında kaldığı görülmüştür. Bu avantajlar, raylı sistemlerde ekartman açıklıklarının korunarak deray ve kazaların önlenmesi ve travers servis ömrünün artırılması adına oldukça önemlidir.
- 31 January 2022
- Published by Demiryolu Muhendisligi Dergisi, Demiryolu Muhendisleri Dernegi in Demiryolu Mühendisliği
- No. 15,p. 97-110
Karbon-Fiber Plaka Donatılı Traverslerin, B70-Tipi Öngerilmeli Beton Traverslerle Karşılaştırmalı İncelenmesi
Bu çalışma kapsamında, yerli karbon fiber takviyeli poliüretan plakalar ile donatılandırılmış beton traverslerin merkez negatif eğilme performansı, öngerilmeli B70 tipi traverslerle karşılaştırmalı yürütülen deneyler ile araştırılmıştır. Yapılan testler sonucunda, yeni tip traverslerin yorulma esaslı dizayn yükünün, B70 tipi öngerilmeli traverslerin 2 katına ulaşan oranda daha yüksek sonuçlandığı görülmüştür. Ayrıca yeni tip traverslerde herhangi bir öngerilme kuvveti veya etriye kullanılmamasına rağmen, B70 tipi öngerilmeli traverslerin kırılma yükünün üzerindeki yük değerlerinde dahi, meydana gelen çatlak genişliklerinin halen 0,05 mm’nin altında kaldığı görülmüştür. Bu avantajlar, raylı sistemlerde ekartman açıklıklarının korunarak deray ve kazaların önlenmesi ve travers servis ömrünün artırılması adına oldukça önemlidir.
- 1 January 2022
- Published by Elsevier in Engineering Failure Analysis
- Vol. 131
Comparison of prestressed concrete railway sleepers and new LCR concrete sleepers with experimental modal analysis
- 1 January 2022
- Published by Elsevier in Engineering Failure Analysis
- Vol. 131
Comparison of prestressed concrete railway sleepers and new LCR concrete sleepers with experimental modal analysis