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23rd RoEduNet Conference: Networking in Education and Research, RoEduNet 2024

作者： Vizitiu, Cristian Turcin, Ioan Dominey, Kevin Alexander Softic, Selver Dinculescu, Adrian-Catalin Bocanet, Vlad I. Dugan, Cosmin Moraru, Sorin-Aurel The Space Applications and Technologies Laboratory Institute of Space Science-Subsidiary of INFLPR Magurele Romania Transilvania University of Brasov Faculty of Electrical Engineering and Computer Science Department of Automatics and Information Technology Brasov Romania CAMPUS 02 University of Applied Sciences Department Automation Technology Graz Austria CAMPUS 02 University of Applied Sciences Department IT and Business Informatics Graz Austria Robotics and Production Management Technical University of Cluj-Napoca Cluj-Napoca Faculty of Industrial Engineering Department of Manufacturing Engineering Romania Bucharest University Emergency Hospital Bucharest Romania

ISBN: (纸本)9798331540388

Perspiration is a physiological response in high-stress situations, that also plays a key role in thermoregulation and stress management. Understanding perspiration patterns is used for assessing physiological responses and optimizing human performance especially in professions such as emergency medical services and military operations, as well as for individuals exposed to Isolated Confined Extreme (ICE) environments such as astronauts and space analog mission participants. This paper defines a Digital Twin (DT) model, that will be integrated with an existing physical sweat simulator module (SSM) prototype. Its goal is to simulate human perspiration under high-stress conditions by integrating environmental, physiological, and psychological data. The system architecture is developed via Model-Based Systems engineering (MBSE). The scope of the designed virtual model is to accurately reflect physical perspiration, detect abnormal perspiration patterns, and generate recommendations regarding stress countermeasures. The goal is to influence the behavioral and/or physiological state of the physical twin, thereby creating a dynamic, responsive system. Machine learning (ML) models will be used to identify patterns in the environmental, physiological, and psychological inputs and predict sweat volume, chemical composition, and regional sweat distributions across the body. ML will also be used to detect abnormal perspiration patterns based on input data. The application of generative AI for creating test data from simulation templates is anticipated to facilitate the comparative analysis of two to three distinct profiles, such as astronauts, soldiers, and paramedics or firefighters, using simulated values. The SSM, with its integrated sensors, will serve the dual purpose of validating the model and providing realistic physical simulation. © 2024 IEEE.

关键词： Physiological models

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Inventory Model for Imperfect Deteriorating Items Under Fuzzy Environment 11

Inventory Model for Imperfect Deteriorating Items Under Fuzz...

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11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Mittal, Mandeep Pandey, Jayanti Tripathi Jain, Muskan School of Computer Science Engineering and Technology Bennett University Uttar Pradesh Greater Noida India Amity Institute of Applied Sciences Amity University Uttar Pradesh Department of Mathematics Uttar Pradesh Noida India

ISBN: (纸本)9798350350357

The aim of this study is to introduce the application of fuzzy numbers in an Economic Order Quantity (EOQ) model for defective items under deterioration. In practice, the fuzziness of parameters tends to reduce over time compared to the theoretical assumptions, which justifies the use of fuzzy numbers. The proposed model starts with crisp approach which later involves the fuzzification of inventory parameters, such as demand rate, holding cost, deterioration rate, purchase cost, screening cost, and ordering cost, to account for uncertainty and imprecision. The triangular fuzzy numbers are utilized to represent these parameters, and a fuzzy model is developed accordingly. To defuzzify the model, Yager's ranking index is adopted, and a detailed comparison is made between crisp and general fuzzy solutions. The model is validated through numerical examples and graphical illustrations, followed by a thorough sensitivity analysis to gain a deeper comprehension of how modifications in parameters affect the optimal solution. © 2024 IEEE.

关键词： Deterioration

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An Efficient Identity Based Multi- Proxy Multi-Signcryption Scheme for Electronic Commerce using Bilinear Pairing

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Procedia computer science 2025年 259卷 1592-1601页

作者： Tej Singh Rashid Ali Vikas Tyagi Department of Applied Sciences ABES Engineering College Ghaziabad UP India Department of Applied Sciences KIET Group of Institutions Ghaziabad UP India School of Computer Science Engineering & Technology Bennett University Greater Noida UP India

With the rapid growth of electronic commerce and the increasing need for secure communication in online transactions, there is a pressing demand for efficient and secure cryptographic schemes. The researcher is using various approaches to secure communication in online transactions. However, ensuring secure communication and protecting sensitive information in electronic commerce (E-commerce) systems remains a significant concern. Traditional cryptographic schemes often suffer from limitations in terms of efficiency, scalability, and flexibility. Thus, the proposed work presents an innovative Identity Based Multi-Proxy Multi-Signcryption (IB-MPMS) scheme for electronic commerce applications. It involves the collaboration of two distinct groups of signcrypters namely original signcryption and group of proxy signcrypters. To facilitate this process in the domain of secure and efficient communication in electronic commerce, we design a multi-proxy multi-signcryption scheme with the help of the bilinear pairings. This authorization enables the generation of a multi-proxy multi-signcryption in the proposed IB-MPMS scheme. Moreover, the collaborative effort of all signcrypters in the proxy group is considered towards the implementation of these multi-proxy multi-signcryption approaches. Due to the utilization of identity-based cryptography, the proposed scheme IB-MPMS effectively addresses the key management problem, resulting in simplified processes. However, in the proposed IB-MPMS scheme both the original and proxy signcrypter ensures fair protection during E-commerce transactions. Moreover, in comparison to previous schemes, our proposed scheme exhibits more efficiency. From a computational perspective, our scheme only necessitates 4 pairing computations, whereas the state of art requires 8 pairing computations.

关键词： Identity-based cryptography bilinear pairings multi-signature ID-based signcryption proxy-signature

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Astrometric Observations of NEA 1998 HH49 Using the Daocheng 50 cm Telescope

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Research in Astronomy and Astrophysics 2024年第7期24卷 71-78页

作者： Huan Xu Xiang-Ming Cheng Yi-Gong Zhang Teng-Fei Song Zhen-Jun Zhang Qing-Yu Peng Yunnan Observatories Chinese Academy of SciencesKunming 650216China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of the Structure and Evolution of Celestial Objects Chinese Academy of SciencesKunming 650216China Engineering Laboratory on Applied Astronomical Technology of Yunnan Kunming 650216China School of Information Engineering Kunming UniversityKunming 650214China School of Computer Science and Information Engineering Anyang Institute of TechnologyAnyang 455000China Department of Computer Science Jinan UniversityGuangzhou 510632China Sino-French Joint Laboratory for Astrometry Dynamics and Space ScienceJinan UniversityGuangzhou 510632China

This study details an astrometric observation campaign of the Near-Earth Asteroid 1998 HH49,conducted with the aim of refining our understanding of its physical *** the 50 cm telescope located at the Wumingshan Mountain in Daocheng,Sichuan,images were obtained over four nights,from 2023 October 19 to October *** observations were processed using Astrometrica software,facilitating the precise determination of the asteroid's *** observational results were compared with the ephemerides from three distinct sources to verify accuracy:the Jet Propulsion Laboratory(JPL)Horizons System,the Institut de Mécanique Céleste et de Calcul deséphémérides(IMCCE)Miriade,and the Near-Earth Objects Dynamic Site(NEODyS-2).When compared with the JPL ephemeris,a mean observed-minus-calculated(O-C)result of 0.″07 in the *** and-0.″35 in the *** was ***,the comparison with the IMCCE ephemeris yielded mean O-C results of 0.″08 in the *** and-0.″06 in the *** comparison with the NEODyS-2 ephemeris yielded the mean O-C results of 0.″06 in ***-0.″49 in *** study's findings demonstrate a general consistency between the observed data and the ephemeris predictions,with minor discrepancies observed across the data ***,both the JPL and NEODyS-2 ephemerides show that the residuals in the *** exceed those in the *** disparities may result from atmospheric differential color refraction,ephemeris discrepancies,observational errors,and other ***,it is worth noting that further investigation is required due to the potential influence of additional ***,the Daocheng 50 cm Telescope exhibits the ability to conduct high-precision positional measurements.

关键词： astrometry ephemerides time

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Generative AI for Radiological Image Data: Current Trends and Outlook 14

Generative AI for Radiological Image Data: Current Trends an...

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14th International Conference on Information and Communication Technology Convergence, ICTC 2023

作者： Han, Ji-Won Lee, Yeon-Joon Hanyang University Major in Bio Artificial Intelligence Department of Applied Artificial Intelligence Seoul Korea Republic of Hanyang University Major in Bio Artificial Intelligence Department of Computer Science and Engineering Seoul Korea Republic of

ISBN: (纸本)9798350313277

Generative artificial intelligence (AI) has gained prominence, particularly in the field of radiological image data. This study investigates current trends and prospects of generative AI in X-ray, CT, MRI, and PET imaging. Emphasizing the importance of data quantity and quality, we ensure reliable and useful outputs. Given the significance of ethical dimensions in generative AI for radiological imaging, ethical considerations are also addressed. By analyzing recent advancements, this study offers insights into the evolution of generative AI in radiological image data and future directions. © 2023 IEEE.

关键词： CT GAN Generative AI MRI PET X-ray

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BLOCK-SECURE: AI-Based Blockchain Enabled Secure Framework for IoMT Applications

BLOCK-SECURE: AI-Based Blockchain Enabled Secure Framework f...

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2024 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2024

作者： Panchal, Barkha Bhatia, Jitendra Kumhar, Malaram Tanwar, Sudeep Dutta, Ashit Kumar Rodrigues, Joel J.P.C. Department of Computer Science and Engineering Institute of Technology Nirma University Ahmedabad India Dept. of Comp. Science and Information Systems College of Applied Sciences AlMaarefa University Saudi Arabia Amazonas State University AM Manaus Brazil

ISBN: (纸本)9798350350548

The Internet of Medical Things (IoMT) revolutionizes healthcare by integrating medical devices and systems with the internet. However, the vast amounts of sensitive medical data in IoMT networks pose significant security and privacy concerns. Traditional security measures often fall short in identifying the malicious data attacks within the IoMT ecosystems. This paper introduces an AI-based non-malicious data classification scheme based on blockchain. We applied and evaluated the machine learning (ML) classifiers, such as support vector machine (SVM), random forest (RF), and K-Nearest neighbor (KNN). We evaluated the proposed framework based on various performance metrics that includes accuracy, precision, recall, and F1 score. The accuracy using SVM obtained 75.3%, RF is 75.9%, and KNN is 84.3%. The results shows that KNN performs better than other models by the factor of 9%. © 2024 IEEE.

关键词： Adversarial machine learning

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Real-time simulation of ship movements for a robot-assisted e-fueling process: A pathway to decarbonization through sector coupling

Real-time simulation of ship movements for a robot-assisted ...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Max Anton Senkbeil Dominik Raup Christoph Wree Bernd Finkemeyer Department of Computer Science and Electrical Engineering University of Applied Sciences Kiel Kiel Germany

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

As part of the energy transition, the UN shipping organization has decided that by 2050 the oceans should be sailed in a climate-neutral way. As most ships are still based on fossil fuels, alternative propulsion systems such as hydrogen or electrically powered units must now be investigated. In the development of new ships, autonomous steering systems are also increasingly being researched. Therefore, the development of an autonomous fueling process for ships, based on sustainable e-fuels, is crucial for implementing sector coupling and thus decarbonizing the transportation industry. To execute the autonomous fueling process in a test environment, robots can be used to emulate the movement of the ship and accomplish the autonomous plugging and fueling process. When simulating ship movements multiple approaches are known, ranging from simple algebraic equations up to complex numerical simulations based on differential equations. We present an approach for a real-time-capable simulation of ship movements that can be performed by a collaborative robot kinematics. The wave simulation is based on the oceanographic spectra and the Inverse Fast Fourier Transform. With this approach, simulation times of less than ten milliseconds are demonstrated.

关键词： Couplings Robot kinematics Transportation industry Kinematics Collaborative robots Propulsion Robot sensing systems

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Transformative effects of ChatGPT on modern education: Emerging Era of AI Chatbots

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Internet of Things and Cyber-Physical Systems 2024年第1期4卷 19-23页

作者： Gill, Sukhpal Singh Xu, Minxian Patros, Panos Wu, Huaming Kaur, Rupinder Kaur, Kamalpreet Fuller, Stephanie Singh, Manmeet Arora, Priyansh Parlikad, Ajith Kumar Stankovski, Vlado Abraham, Ajith Ghosh, Soumya K. Lutfiyya, Hanan Kanhere, Salil S. Bahsoon, Rami Rana, Omer Dustdar, Schahram Sakellariou, Rizos Uhlig, Steve Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Raygun Performance Monitoring Wellington New Zealand Center for Applied Mathematics Tianjin University Tianjin China Department of Science Kings Education London United Kingdom Cymax Group Technologies BC Canada QM Academy Queen Mary University of London London United Kingdom Jackson School of Geosciences University of Texas at Austin AustinTX United States Centre for Climate Change Research Indian Institute of Tropical Meteorology Pune India Microsoft Hyderabad India Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Machine Intelligence Research Labs AuburnWA United States Faculty of Computing and Data Science FLAME University Maharashtra Pune India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Department of Computer Science University of Western Ontario London Canada Sydney Australia School of Computer Science University of Birmingham United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom Laboratory School of Computing and Information Systems The University of Melbourne Australia

ChatGPT, an AI-based chatbot, offers coherent and useful replies based on analysis of large volumes of data. In this article, leading academics, scientists, distinguish researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research discusses ChatGPT capabilities and its use in the education sector, identifies potential concerns and challenges. Our preliminary evaluation shows that ChatGPT perform differently in different subject areas including finance, coding, maths, and general public queries. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions, transforming education through smartphones and IoT gadgets, and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported "hallucinations" within GenerativeAI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial. © 2023 The Authors

关键词： Machine learning

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A Comparative Analysis of IoT Data Using Machine Learning Algorithms 15th

A Comparative Analysis of IoT Data Using Machine Learning Al...

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15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Nagashree, B.A. Satheesh Kumar, S. Muthukumaran, V. Munrathnam, Meram Angeline Kavitha, M. Department of Computer Science and Applications School of CSA REVA University Bangalore India Department of Computer Science School of Applied Sciences REVA University Bangalore India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Chennai India Department of Mathematics Rajiv Gandhi University of Knowledge Technologies R.K. Valley Kadapa District Andhra Pradesh Idupulapaya516330 India Department of Mathematics Voorhees College Vellore632001 India

ISBN: (纸本)9783031889912

IoT (Internet of Things) is revolutionizing the commercial environment by acquiring vast amounts of data from various sources. However, processing and analyzing this data is challenging due to the large volume of IoT devices. AI-powered IoT creates intelligent machines that mimic human intelligence, aiding decision-making with minimal human input. Both individuals and professionals’ benefit from this combination, as IoT is concerned with communicating online, but AI allows machines to learn from data and experience. This study demonstrates the analysis of IoT data using machine learning algorithms and compares the accuracy of various machine learning algorithms used. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Contrastive Learning

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A Novel Hybrid Machine Learning Approach for Classification of Brain Tumor Images

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computers, Materials & Continua 2022年第10期73卷 641-655页

作者： Abdullah A.Asiri Amna Iqbal Javed Ferzund Tariq Ali Muhammad Aamir Khalaf A.Alshamrani Hassan A.Alshamrani Fawaz F.Alqahtani Muhammad Irfan Ali H.D.Alshehri Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Department of Computer Science COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan College of Engineering Najran UniversityNajran61441Saudi Arabia

Abnormal growth of brain tissues is the real cause of brain *** for the diagnosis of brain tumor at initial stages is one of the key step for saving the life of a *** manual segmentation of brain tumor magnetic resonance images(MRIs)takes time and results vary significantly in low-level *** address this issue,we have proposed a ResNet-50 feature extractor depended on multilevel deep convolutional neural network(CNN)for reliable images segmentation by considering the low-level features of *** this model,we have extracted features through ResNet-50 architecture and fed these feature maps to multi-level CNN *** handle the classification process,we have collected a total number of 2043 MRI patients of normal,benign,and malignant *** model CNN,multi-level CNN,and ResNet-50 based multi-level CNN have been used for detection and classification of brain *** the model results are calculated in terms of various numerical values identified as precision(P),recall(R),accuracy(Acc)and f1-score(F1-S).The obtained average results are much better as compared to already existing *** modified transfer learning architecture might help the radiologists and doctors as a better significant system for tumor diagnosis.

关键词： Brain tumor magnetic resonance images convolutional neural network classification

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