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DieT Transformer model with PCA-ADE integration for advanced multi-class brain tumor classification

Intelligence-Based Medicine 2025年 11卷 100192-100192页

作者： Amin, Mohammad Nahar, Khalid M.O. Gharaibeh, Hasan Nasayreh, Ahmad Alsalmanc, Neda'a Alomar, Alaa Malkawi, Majd Alqasem, Noor Smerat, Aseel Zitar, Raed Abu Nusier, Shawd Ezugwu, Absalom E. Abualigah, Laith Department of Information Technology and Computer Sciences Yarmouk University Irbid 211633 Jordan Faculty of Computer Studies Arab Open University P.O.Box 84901 Riyadh 11681 Saudi Arabia Department of Computer Science Faculty of Information Technology Jordan University of Science and Technology Irbid 22110 Jordan Department of Medicine Faculty of Medicine Jordan University of Science and Technology Irbid 22110 Jordan Department of Biomedical Systems and Informatics Engineering Hijjawi Faculty for Engineering Technology Yarmouk University Irbid 21163 Jordan Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura 140401 India Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai 602105 India Artificial Intelligence and Sensing Technologies (AIST) Research Center University of Tabuk Tabuk 71491 Saudi Arabia Faculty of Engineering and Computing Liwa College Abu Dhabi United Arab Emirates Department of Health and Clinical Outcomes Research Saint Louis University St. Louis MO United States Unit for Data Science and Computing North-West University 11 Hofman Street Potchefstroom 2520 South Africa Computer Science Department Al al-Bayt University Mafraq 25113 Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan

Early and accurate diagnosis of brain tumors is crucial to improving patient outcomes and optimizing treatment strategies. Long-term brain injury results from aberrant proliferation of either malignant or nonmalignant tissues in the brain. MRIs, or magnetic resonance imaging, are one of the most used approaches for detecting brain tumors. Professionals physically evaluate people after they have had MRI filtering, the process of enhancing MRI scans for radiologist interpretation, to establish if they have a brain tumor. Because different specialists use different frames to make judgments on the same MRI image, their analyses may yield contradictory results. Furthermore, simply detecting a tumor is insufficient. Inconsistent diagnoses can lead to delays in treatment, impacting survival rates and quality of care. It is also crucial to diagnose the patient's tumor so that treatment can begin as soon as possible. In this research, we investigate the multi-class classification of brain tumors utilizing a cutting-edge methodology that includes feature extraction from pictures using the DieT Transformer model, dimensionality reduction with PCA, and feature selection using the ADE algorithm. The proposed model, known in the publication as ADE_DieT, obtained an accuracy of 96.09 %. In addition, this article analyzes the performance of various pre-trained models, including MobileNetV3, NasNet, ResNet50, VGG16, VGG19, and DeiT. The proposed approach shortens the time required for manual diagnosis by clinicians by assisting in the rapid and accurate identification of brain tumors using MRI data. In oncology, this is important since it allows for early treatment. Integrating ADE_DieT into clinical workflows can support radiologists by reducing diagnosis time and enhancing diagnostic consistency. © 2024 The Authors

关键词： Brain tumor Medical image analysis MRI Vision Transformer

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Reliable Multihop Routing and Congestion Aware Chicken Swarm Optimization in Vehicular Ad-Hoc Network

Reliable Multihop Routing and Congestion Aware Chicken Swarm...

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Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Cuddapah Anitha Dalia Al-Tarazi GD. Vignesh A. Vinotha Vasuki Jayant Giri M. Dinesh Department of Computer Science and Engineering School of Computing Mohan Babu University Erstwhile Sree Vidyanikethan Engineering College Tirupati India Department of Architecture Engineering Faculty of Engineering Zarqa university Zarqa Jordan College of Engineering University of Business and Technology Jeddah Saudi Arabia Department of Electronics and Communication Engineering St. Joseph's College of Engineering Chennai India Department of Computer Science and Engineering J.P. College of Engineering Tenkasi India Department of Mechanical Engineering Yeshwantrao Chavan College of Engineering Nagpur India Division of Research and Development Lovely Professional University Phagwara India Department of VLSI Microelectronics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Background: Vehicular Ad Hoc Networks (VANETs) play a crucial role in intelligent transportation by facilitating communication between vehicles and vehicles with infrastructure-based models. They encounter problems such as significant movement, overcrowding, and loss of data. This research presents a novel deep reinforcement learning-based resource allocation and congestion optimization (DRLRCO) framework aimed at improving communication efficiency and high reliability using an effective learning process. Method Used: The DRLRCO framework employs agent-based learning to ensure precise data transmission, AdMAC Protocol for dynamic packet delivery, and Congestion-Aware Chicken Swarm Optimization (CSO) to enhance network performance. Result: The DRLRCO framework surpasses reinforcement learning models for comprehensive testing. Significant enhancements involve improved accuracy, reduced data loss, minimized overhead, increased throughput, and shorter average delays for real-time communication. Conclusion: The DRLRCO framework successfully tackles congestion and data loss in vehicular communication. Future studies might involve Artificial Intelligence (AI) for traffic forecasting, experimentation among high-speed vehicles and investigating blockchain for enhanced security.

关键词： Vehicular ad hoc networks Routing Throughput Synchronization Resource management Dedicated short range communication Particle swarm optimization Artificial intelligence Vehicle dynamics Testing

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Small-Scale Testbeds for Connected and Automated Vehicles and Robot Swarms: Challenges and a Roadmap

arXiv

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arXiv 2025年

作者： Xu, Jianye Alrifaee, Bassam Betz, Johannes Mokhtarian, Armin Mittal, Archak Cai, Mengchi Mangharam, Rahul Shehata, Omar M. Elias, Catherine M. Zaech, Jan-Nico Scheffe, Patrick Jahncke, Felix Ulhas, Sangeet Sankaramangalam Arfvidsson, Kaj Munhoz Department of Computer Science RWTH Aachen University Germany Department of Aerospace Engineering University of the Bundeswehr Munich Germany Professorship of Autonomous Vehicle Systems Technical University of Munich Germany Department of Civil Engineering Indian Institute of Technology Bombay India School of Vehicle and Mobility Tsinghua University China Department of Electrical and Systems Engineering University of Pennsylvania United States Mechatronics Engineering Department Faculty of Engineering and Materials Science The German University in Cairo Egypt Department of Computer Science Engineering The German University in Cairo Egypt INSAIT Sofia University "St. Kliment Ohridski" Bulgaria School for Engineering of Matter Transport and Energy Arizona State University United States Division of Decision and Control Systems KTH Royal Institute of Technology Sweden

This article proposes a roadmap to address the current challenges in small-scale testbeds for Connected and Automated Vehicles (CAVs) and robot swarms. The roadmap is a joint effort of participants in the workshop "1st Workshop on Small-Scale Testbeds for Connected and Automated Vehicles and Robot Swarms," held on June 2 at the IEEE Intelligent Vehicles Symposium (IV) 2024 in Jeju, South Korea. The roadmap contains three parts: 1) enhancing accessibility and diversity, especially for underrepresented communities, 2) sharing best practices for the development and maintenance of testbeds, and 3) connecting testbeds through an abstraction layer to support collaboration. The workshop features eight invited speakers, four contributed papers [1]–[4], and a presentation of a survey paper on testbeds [5]. The survey paper provides an online comparative table of more than 25 testbeds, available at https://***/testbeds-survey. The workshop’s own website is available at https://***/iv24-workshop. Copyright © 2025, The Authors. All rights reserved.

关键词： Testbeds

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Motor imagery enhances performance beyond the imagined action

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Proceedings of the National Academy of sciences of the United States of America 2025年第20期122卷 e2423642122页

作者： Gippert, Magdalena Shih, Pei-Cheng Heed, Tobias Howard, Ian S. Jamshidi Idaji, Mina Villringer, Arno Sehm, Bernhard Nikulin, Vadim V. Department of Neurology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig 04103 Germany Sony Computer Science Laboratories 141-0022 Tokyo Japan Department of Psychology and Centre for Cognitive Neuroscience University of Salzburg 5020 Salzburg Austria School of Engineering Computing and Mathematics Faculty of Science and Engineering University of Plymouth Plymouth PL4 8AA United Kingdom Machine Learning Group Berlin Institute for the Foundations of Learning and Data 10587 Berlin Germany Machine Learning Group Institute of Software Engineering and Theoretical Computer Science Electrical Engineering and Computer Science Faculty Technical University Berlin 10587 Berlin Germany Department of Neurology Martin Luther University of Halle-Wittenberg Halle (Saale) 06120 Germany

Motor imagery is frequently utilized to improve the performance of specific target movements in sports and rehabilitation. In this study, we show that motor imagery can facilitate learning of not only the imagined target movements but also sequentially linked overt movements. Hybrid sequences comprising imagined and physically executed segments allowed participants to learn specific movement characteristics of the executed segments when they were consistently associated with specific imagined segments. Electrophysiological recordings revealed that the degree of event-related synchronization in the alpha and beta bands during a basic motor imagery task was correlated with imagery-evoked motor learning. Thus, both behavioral and neural evidence indicate that motor imagery's benefits extend beyond the imagined movements, improving performance in linked overt movements. This provides decisive evidence for the functional equivalence of imagined and overt movements and suggests applications for imagery in sports and rehabilitation.

关键词： adaptation force field motor imagery motor learning motor sequence

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Evaluation of Ethernet Subsystem for Domain controller in Autonomous Vehicles

Evaluation of Ethernet Subsystem for Domain Controller in Au...

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2021 Zooming Innovation in Consumer Technologies Conference, ZINC 2021

作者： Kenjic, Dusan Antic, Marija Bjelica, Milan University of Novi Sad Faculty of Technical Sciences Department of Computing and Control Engineering Serbia

ISBN: (纸本)9781665404174

The expansion of the automotive industry is reflected in the expansion of functionalities and services offered by a modern vehicle. In order for all of them to be executed, it is also necessary to increase the number of physical components within the vehicle. As the entire system grows, so does the problem of connecting the entities within it. The efficient simplification of the system is achieved by introducing domain controllers, and separating the physical components based on the functionality they perform, while creating the backbone communication network between domain controllers. Time-critical and other performance requirements, which are driven by the development of autonomous driving, demand the utilization of new standards and solutions for this communication network backbone. One of those solutions is Automotive Ethernet. In this paper, an implementation of the Ethernet subsystem of the domain controller for autonomous vehicles will be presented and evaluated. © 2021 IEEE.

关键词： Automotive industry

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Irreversibility analysis of the radiative flow of cross fluid comprising three distinct nanoparticles across a stretching cylinder with chemical reactions

Results in Engineering

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Results in Engineering 2025年 26卷

作者： Pasha, Amjad Ali Anjum, Asra Peerusab, Samdani Faizan, M. Ameen, Hawzhen Fateh M. Ali, Farhan Khan, Umair Zaib, A. Hussain, Syed Modassir Aerospace Engineering Department King Abdulaziz University Jeddah21589 Saudi Arabia Mathematics and Computing Skills Unit Preparatory Studies Centre University of Technology and Applied Sciences Salalah P O Box 608 PC:211 Salalah Oman Department of Engineering College of Engineering and Technology University of Technology and Applied Sciences Salalah P O Box 608 PC:211 Salalah Oman Department of Mathematical Sciences Federal Urdu University of Arts Sciences & Technology Gulshan-e-Iqbal Karachi75300 Pakistan Department of Petroleum Engineering Knowledge University Erbil Iraq Department of Petroleum Technology Erbil Technology College Erbil Polytechnic University Kurdistan Region Erbil Iraq Department of Mathematics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai602105 India Department of Mathematics Faculty of Science Sakarya University Sakarya Serdivan54050 Turkey Department of Mathematics Faculty of Science Islamic University of Madinah Madinah42351 Saudi Arabia

This study investigates entropy development in a magnetohydrodynamic (MHD) flow of trihybrid nanofluid in a cross fluid, including convective, thermal radiation, and heat source-sink through a stretching cylinder. The liquid that is contained within the enclosure is carboxymethyl cellulose (CMC) water with tri-hybrid nanoparticles MoS2,SiO2 and Ag. Suitable self-similarity variables are utilized to convert the nonlinear differential systems into ordinary ones. This transformation is accomplished through the bvp4c in MATLAB software. The influence of various variables on the velocity, temperature, concentration, entropy production, Bejan number, skin friction, Nusselt number, and the Sherwood number are sketched and elaborated. It is observed that an enhancement in the magnetic field (M) and Weissenberg number (We) reduce the velocity profile, whilst the temperature uplifts due to (We) and (M). Moreover, an increase in the curvature parameter increases the thermal profile. In addition, uplifting the We number ultimately increases the skin friction by approximately 37.4% and heat transmission by 45.21%, whereas the Sherwood number up to 1.98%. Comparison with previously published material confirms the accuracy of the presented numerical computations and supports our current proposed model. In biomedical applications, magnetic and electromagnetic fields play a significant role in radiofrequency ablation (RFA), magnetic resonance imaging (MRI), cancer therapy, tumor therapy, and malaria infection. This theoretical investigation may be productive in biomedical engineering, particularly in cardiology, skin problems treatment, and removing malignancies from the uterus. © 2025 The Author(s)

关键词： Heat radiation

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Landscape and climatic drivers of dengue fever in Lao People’s Democratic Republic and Thailand: a retrospective analysis during 2002–2019

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Landscape Ecology 2025年第5期40卷 1-18页

作者： Zafar, Sumaira Rocklöv, Joacim Paul, Richard E. Shipin, Oleg Rahman, Md. Siddikur Pientong, Chamsai Aromseree, Sirinart Poolphol, Petchaboon Mayxay, Mayfong Pongvongsa, Tiengkham Vannavong, Nanthasane Overgaard, Hans J. Haque, Ubydul Institute of Nutrition Mahidol University Nakhon Pathom Thailand Heidelberg Institute of Global Health & the Interdisciplinary Centre for Scientific Computing Heidelberg University Heidelberg Germany Department of Public Health and Clinical Medicine Umeå University Umeå 90187 Sweden Ecology and Emergence of Arthropod-Borne Pathogens Unit Institut Pasteur CNRS UMR2000 Université Paris Cité Paris 75015 France Department of Environmental Engineering and Management Asian Institute of Technology Khlong Luang Thailand Department of Statistics Begum Rokeya University Rangpur Bangladesh Department of Microbiology Faculty of Medicine Khon Kaen University Khon Kaen Thailand The Office of Disease Prevention and Control Region 10(th) Ubon Ratchathani 34000 Thailand Institute of Research and Education Development (IRED) University of Health Sciences Ministry of Health Vientiane Laos Microbiology Laboratory Lao-Oxford-Mahosot Hospital-Welcome Trust Research Unit (LOMWRU) Mahosot Hospital Vientiane Laos Centre for Tropical Medicine and Global Health University of Oxford Oxford United Kingdom Saw Swee Hock School of Public Health National University of Singapore Singapore Singapore Savannakhet Provincial Health Department Savannakhet Province Savannakhet Laos Champasak Provincial Health Office Pakse Laos Faculty of Science and Technology Norwegian University of Life Sciences P.O. Box 5003 Ås Norway Rutgers Global Health Institute Piscataway NJ United States Department of Biostatistics and Epidemiology School of Public Health Rutgers University Newark United States

Context: Dengue is a major public health threat in the Lao People’s Democratic Republic (Laos) and Thailand. Dengue transmission is ecologically complex. Concurrently identifying both climate and landscape-based risk factors for dengue virus transmission is necessary to improve dengue prevention and control efforts in Laos and Thailand. Objectives: The objective of this study was to determine how changes in climate (temperature and rainfall), and land use (e.g. built-up areas, agricultural crops, fruit orchards, rubber plantations) and land cover (e.g. evergreen and deciduous forests, permanent and temporary wetlands) affect dengue risk in four provinces in southern Laos and north-eastern Thailand during 2002 to 2019. Methods: A conditional autoregressive Bayesian spatiotemporal modeling framework was used to analyze the risk of dengue by spatiotemporal variations in land use and land cover (LULC) and climatic parameters. Results: The average annual temperatures in the study area increased by 0.44–0.94 °C during the study period. The model indicated that an increase of 1 °C in weekly average temperatures (up to a 29 °C threshold level) increased the average dengue risk by up to 24% in the two Lao provinces and 18.9% in the two Thai provinces. The model suggested that a rainfall increase of 1 mm up to 60 mm increased dengue risk by 1.8–3.2%. A 0.6–1.6% increase in built-up land use increased dengue risk by 1.8–6.9%. Built-up areas and rubber plantations were positively associated with dengue in the Ubon Ratchathani province of Thailand, while wetlands were negatively associated with dengue cases in the Savannakhet province of Laos. Conclusions: Changes in dengue risk were clearly related to increases in rainfall and temperature as well as changes in LULC in both Laos and Thailand. These insights may inform community-based dengue control activities by targeting geographically localized areas (microgeographic scale) to deploy dengue control activities more effectively

关键词： Bayesian Climate change Dengue Land use and landcover Vectors

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Accidental Centralization: Pitfalls of Blockchain-Based Project Architectures 11

Accidental Centralization: Pitfalls of Blockchain-Based Proj...

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11th International Conference on Electrical, Electronic and computing Engineering, IcETRAN 2024

作者： Petrović, Veljko B. Dragan, Dinu Gajlć, Dušan B. University of Novi Sad Faculty of Technical Sciences Control and Computing Department Novi Sad Serbia

ISBN: (纸本)9798350386998

Making use of blockchain in complex projects in ways which scale and keep costs down can lead to very complex architectural patterns. The problem with such patterns is that it is very easy to set up a system that only seems decentralized but, in fact, operates under a degraded trust model or is even centralized in practice. Using a blockchain to implement a centralized system represents a grotesque waste of computational resources for no benefit at all. This paper analyzes several cases of such architectural malfunction and shows how degraded trust can occur, how to detect it, and how to respond to this issue. © 2024 IEEE.

关键词： Blockchain

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Analysing student spatial deployment in a computer laboratory

Analysing student spatial deployment in a computer laborator...

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4th International Conference on Educational Data Mining, EDM 2011

作者： Ivancevic, Vladimir Celikovic, Milan Lukovic, Ivan Department of Computing and Control Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia

ISBN: (纸本)9789038625379

Although data mining techniques are constantly improved and made more easy to use, there is still little application of related methods in the investigation of student seating choices and respective implications. Therefore, in this paper we analyse characteristics and effects of student spatial deployment in a computer laboratory by using data mostly gathered through electronic student testing system. For a first semester programming course, we examine relations between student assessment results and student choices of seating locations in a laboratory, as well as search for regularities in the spatial deployment, such as students' test location changes throughout the semester and the connection they share with the success on tests. Obtained results demonstrate the existence of patterns, whose meaning is also discussed, and emphasise the importance of considering student spatial choices in the study of understanding and improving student behaviour and learning.

关键词： Students

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Electric power distribution system visualization with graph partitioning

Electric power distribution system visualization with graph ...

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IEEE AFRICON 2013

作者： Kovačev, Nemanja Lendák, Imre Čapko, Darko Erdeljan, Aleksandar Computing and control department Faculty of technical sciences University of Novi Sad Novi Sad Serbia

ISBN: (纸本)9781467359405

This paper presents an electric power distribution system (EPDS) visualization algorithm which performs graph partitioning before generating the visual representations, i.e. one line diagrams. The proposed algorithm is different from similar algorithms as it performs graph partitioning to reduce the solution space. The partitioning step is necessary because modern EPDS can consist of thousands of distribution transformers, pole switches and line segments. After the partitioning step, in its second phase, the algorithm lays out the subgraphs and then combines the drawings into complete one-line diagrams. During the experiments, the partitioning and layout phases were performed with various combinations of the genetic and branch and bound algorithm. The algorithm was tested on partial, real life electric power distribution systems of up to 150 objects and it generated visually pleasing one-line diagrams. © 2013 IEEE.

关键词： Visualization

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