TY - JOUR AU - Mehrabi Hashjin, Nastaran AU - Amiri, Mohammad Hussein AU - Mohammadzadeh, Ardashir AU - Mirjalili, Seyedali AU - Khodadadi, Nima TI - Novel hybrid classifier based on fuzzy type-III decision maker and ensemble deep learning model and improved chaos game optimization JF - CLUSTER COMPUTING J2 - CLUSTER COMPUT VL - & PY - 2024 SP - & SN - 1386-7857 DO - 10.1007/s10586-024-04475-7 UR - https://m2.mtmt.hu/api/publication/34857410 ID - 34857410 AB - This paper presents a unique hybrid classifier that combines deep neural networks with a type-III fuzzy system for decision-making. The ensemble incorporates ResNet-18, Efficient Capsule neural network, ResNet-50, the Histogram of Oriented Gradients (HOG) for feature extraction, neighborhood component analysis (NCA) for feature selection, and Support Vector Machine (SVM) for classification. The innovative inputs fed into the type-III fuzzy system come from the outputs of the mentioned neural networks. The system’s rule parameters are fine-tuned using the Improved Chaos Game Optimization algorithm (ICGO). The conventional CGO’s simple random mutation is substituted with wavelet mutation to enhance the CGO algorithm while preserving non-parametricity and computational complexity. The ICGO was evaluated using 126 benchmark functions and 5 engineering problems, comparing its performance with well-known algorithms. It achieved the best results across all functions except for 2 benchmark functions. The introduced classifier is applied to seven malware datasets and consistently outperforms notable networks like AlexNet, ResNet-18, GoogleNet, and Efficient Capsule neural network in 35 separate runs, achieving over 96% accuracy. Additionally, the classifier’s performance is tested on the MNIST and Fashion-MNIST in 10 separate runs. The results show that the new classifier excels in accuracy, precision, sensitivity, specificity, and F1-score compared to other recent classifiers. Based on the statistical analysis, it has been concluded that the ICGO and propose method exhibit significant superiority compared to the examined algorithms and methods. The source code for ICGO is available publicly at https://nimakhodadadi.com/algorithms-%2B-codes . LA - English DB - MTMT ER - TY - JOUR AU - Haidegger, Tamás AU - Galambos, Péter AU - Tar, József AU - Kovács, Levente AU - Kozlovszky, Miklós AU - Zrubka, Zsombor AU - Eigner, György AU - Drexler, Dániel András AU - Szakál, Anikó AU - Reicher, Viktória AU - Árendás, Csaba AU - Tarsoly, Sándor AU - Garamvölgyi, Tivadar AU - Rudas, Imre TI - Strategies and Outcomes of Building a Successful University Research and Innovation Ecosystem JF - ACTA POLYTECHNICA HUNGARICA J2 - ACTA POLYTECH HUNG VL - 21 PY - 2024 IS - 10 SP - 13 EP - 35 PG - 23 SN - 1785-8860 DO - 10.12700/APH.21.10.2024.10.2 UR - https://m2.mtmt.hu/api/publication/34849856 ID - 34849856 LA - English DB - MTMT ER - TY - JOUR AU - Jafari-Asl, Jafar AU - Lara Montaño, Oscar D. AU - Mirjalili, Seyedali AU - Faes, Matthias G.R. TI - A meta-heuristic approach for reliability-based design optimization of shell-and-tube heat exchangers JF - APPLIED THERMAL ENGINEERING J2 - APPL THERM ENG VL - 248 PY - 2024 SP - 123161 PG - 15 SN - 1359-4311 DO - 10.1016/j.applthermaleng.2024.123161 UR - https://m2.mtmt.hu/api/publication/34842684 ID - 34842684 LA - English DB - MTMT ER - TY - JOUR AU - Li, Xiaohang AU - Shi, Peng AU - Zhang, Weidong AU - Saif, Mehrdad TI - Resilient Synchronization for Insecure Markovian Jump Neural Networks to Mitigate Dual Cyber Attacks JF - IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS J2 - IEEE T CIRCUITS-I PY - 2024 PG - 13 SN - 1549-8328 DO - 10.1109/TCSI.2024.3383839 UR - https://m2.mtmt.hu/api/publication/34836711 ID - 34836711 LA - English DB - MTMT ER - TY - JOUR AU - Károlyi, Mihály AU - Polacin, Malgorzata AU - Kolossváry, Márton József AU - Sokolska, Justyna M. AU - Matziris, Ioannis AU - Weber, Lucas AU - Alkadhi, Hatem AU - Manka, Robert TI - Comparative analysis of late gadolinium enhancement assessment techniques for monitoring fibrotic changes in myocarditis follow-up JF - EUROPEAN RADIOLOGY J2 - EUR RADIOL PY - 2024 SP - 1 EP - 11 PG - 11 SN - 0938-7994 DO - 10.1007/s00330-024-10756-x UR - https://m2.mtmt.hu/api/publication/34836311 ID - 34836311 LA - English DB - MTMT ER - TY - JOUR AU - Singh, Alka AU - Kumar, Rakesh AU - Gandomi , Amirhossein TI - Adaptive isomap feature extractive gradient deep belief network classifier for diabetic retinopathy identification JF - MULTIMEDIA TOOLS AND APPLICATIONS: AN INTERNATIONAL JOURNAL J2 - MULTIMED TOOLS APPL PY - 2024 SN - 1380-7501 DO - 10.1007/s11042-024-19216-6 UR - https://m2.mtmt.hu/api/publication/34833556 ID - 34833556 LA - English DB - MTMT ER - TY - JOUR AU - Zhang, Daotong AU - Shi, Peng AU - Agarwal, Ramesh K. AU - Kovács, Levente TI - Reference Tracking MPC for Cyber-Physical Systems Under Denial-of-Service Attacks: An Omnidirectional Robot Application JF - IEEE SYSTEMS JOURNAL J2 - IEEE SYST J PY - 2024 PG - 9 SN - 1932-8184 DO - 10.1109/JSYST.2024.3384372 UR - https://m2.mtmt.hu/api/publication/34833548 ID - 34833548 LA - English DB - MTMT ER - TY - JOUR AU - Radnia, Aram AU - Alikhani, Amirhossein AU - Teimourian, Behnoosh AU - Nejad, Mahyar Yousef AU - Farahani, Mohammad Hossein AU - Pashaei, Fakhereh AU - Rahmim, Arman AU - Zaidi, Habib AU - Ay, Mohammad Reza TI - Development of novel low-cost readout electronics for large field-of-view gamma camera detectors JF - PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS J2 - PHYS MEDICA VL - 121 PY - 2024 SP - 103357 SN - 1120-1797 DO - 10.1016/j.ejmp.2024.103357 UR - https://m2.mtmt.hu/api/publication/34833013 ID - 34833013 LA - English DB - MTMT ER - TY - JOUR AU - Takács, Kristóf AU - Lukács, Eszter AU - Levendovics, Renáta AU - Pekli, Damján AU - Szijártó, Attila AU - Haidegger, Tamás TI - Assessment of Surgeons’ Stress Levels with Digital Sensors during Robot-Assisted Surgery: An Experimental Study JF - SENSORS J2 - SENSORS-BASEL VL - 24 PY - 2024 IS - 9 PG - 12 SN - 1424-8220 DO - 10.3390/s24092915 UR - https://m2.mtmt.hu/api/publication/34833010 ID - 34833010 AB - Robot-Assisted Minimally Invasive Surgery (RAMIS) marks a paradigm shift in surgical procedures, enhancing precision and ergonomics. Concurrently it introduces complex stress dynamics and ergonomic challenges regarding the human–robot interface and interaction. This study explores the stress-related aspects of RAMIS, using the da Vinci XI Surgical System and the Sea Spikes model as a standard skill training phantom to establish a link between technological advancement and human factors in RAMIS environments. By employing different physiological and kinematic sensors for heart rate variability, hand movement tracking, and posture analysis, this research aims to develop a framework for quantifying the stress and ergonomic loads applied to surgeons. Preliminary findings reveal significant correlations between stress levels and several of the skill-related metrics measured by external sensors or the SURG-TLX questionnaire. Furthermore, early analysis of this preliminary dataset suggests the potential benefits of applying machine learning for surgeon skill classification and stress analysis. This paper presents the initial findings, identified correlations, and the lessons learned from the clinical setup, aiming to lay down the cornerstones for wider studies in the fields of clinical situation awareness and attention computing. LA - English DB - MTMT ER - TY - JOUR AU - Agarwal, Monika AU - Rani, Geeta AU - Kumar, Ambeshwar AU - K, Pradeep Kumar AU - Manikandan, R. AU - Gandomi , Amirhossein TI - Deep learning for enhanced brain Tumor Detection and classification JF - RESULTS IN ENGINEERING J2 - RESULT ENGIN VL - 22 PY - 2024 PG - 12 SN - 2590-1230 DO - 10.1016/j.rineng.2024.102117 UR - https://m2.mtmt.hu/api/publication/34831712 ID - 34831712 LA - English DB - MTMT ER -