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UPB Scientific Bulletin, Series C: Electrical Engineering and computer Science 2025年第1期87卷 21-34页

作者： Contașel, Cristian Rughiniș, Răzvan Trancă, Dumitru Cristian Țurcanu, Dinu Dept. of Computer Science and Engineering National University of Science and Technology POLITEHNICA Bucharest Romania Dep. of Software Engineering and Automatics Technical University of Moldova Chișinău Moldova

This study provides an innovative architectural model for e-Health systems that aims to improve cyber resilience while maintaining high availability under fluctuating traffic loads. We examined typical cybersecurity incidents in the field of e-Health, their correlations with architectural defects, and frequent design patterns in currently operational systems. A testing approach based on our research finds those weaknesses and proposes viable fixes. In this paper, a comprehensive support strategy for transitioning from conventional monolithic architectures to microservices is presented. This change makes use of cloud computing's vertical and horizontal scalability to maximize resource utilization while ensuring system reliability. We also discuss dep.oyment ideas for the new microservices, focusing on operational resilience and cybersecurity in e-Health environments. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Electronic health record

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Comparison of Milk Quality Grades Using the Logistic Model Tree Algorithm

Comparison of Milk Quality Grades Using the Logistic Model T...

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Cybernetics and Innovations (ICCI), International Conference on

作者： Phanintorn Suaprae Thanakrit Janchidfah Brijesh Bhatt Dep. Of Business Information Technology Management Phibulsongkram Rajabhat University Phitsanulok Thailand Dep. Of Digital Media Technology Muban Chombueng Rajabhat University Ratchaburi Thailand Dep. Of Computer Engineering Faculty of Technology Dharmsinh Desai University India

ISBN: (数字)9798331533267

ISBN: (纸本)9798331533274

This study aims to track and categorize milk quality grades using the Logistic Model Tree (LMT) algorithm, based on the analysis of 1,059 milk samples. The focus of the research is to evaluate key factors such as pH value, taste, smell, fat content, concentration, and color, which play a crucial role in determining the overall quality of milk. The goal is to create an efficient and standardized process for sorting cow's milk, which can save significant time and resources in the dairy industry. To identify the most suitable algorithm for this task, the research team initially tested 12 different algorithms, assessing their performance in predicting milk quality. Among these, the Logistic Model Tree (LMT) emerged as the most effective model, achieving an impressive accuracy rate of 99.76%. The LMT algorithm, known for combining the advantages of decision trees and logistic regression, demonstrated its ability to classify milk quality grades with high precision. The results of this study indicate that the LMT algorithm can be a valuable tool for automating the milk quality grading process. By leveraging key attributes such as pH, fat content, and color, it is possible to efficiently sort and grade milk, reducing the need for manual inspection and improving overall productivity in the dairy industry. This method offers a significant improvement over traditional quality assessment techniques and has the potential to be widely adopted for milk sorting and quality control applications.

关键词： Analytical models Dairy products Accuracy Standardization Prediction algorithms Data models Classification algorithms Quality assessment Logistics Sorting

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Introduction to the HICSS-58 Software technology and Software Development Minitrack

Proceedings of the Annual Hawaii International Conference on...

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Proceedings of the Annual Hawaii International Conference on System Sciences 2025年 7379-7380页

作者： Majchrzak, Tim A. Grønli, Tor-Morten Kaindl, Hermann University of Agder Kristiansand Norway Kristiania University College Dep. Technology Oslo Norway TU Wien Inst. of Computer Tech. Vienna Austria

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Brain Tumor Classification System Using Decision Tree Algorithm

Brain Tumor Classification System Using Decision Tree Algori...

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Cybernetics and Innovations (ICCI), International Conference on

作者： Sattarpoom Thaiparnit Thanakrit Janchidfah Adil Farooq Dep. Of Information System and Computer Business Faculty of Business Administration Rajamangala University of Technology Suvarnabhumi Suphan Buri Thailand dep. Of Digital Media Technology Muban Chombueng Rajabhat University Ratchaburi Thailand Department of Electronic Engineering Maynooth University Ireland

ISBN: (数字)9798331533267

ISBN: (纸本)9798331533274

This research aims to study, design, and develop a brain tumor classification system using artificial intelligence, specifically decision tree algorithms. The system's primary objective is to assist medical personnel in making decisions, as distinguishing between two types of brain tumors-benign and malignant (cancerous)-can be challenging, especially for less experienced medical staff. Due to the similarities between these two types of tumors, it may be difficult for medical practitioners with limited expertise to differentiate between them in a timely manner. The proposed brain tumor classification system is designed to address this challenge. The research team conducted the study over approximately seven months, starting from the second semester of the 2023 academic year through the first semester of the 2024 academic year. Experimental results revealed that among the tree-based algorithms, Random Forest achieved the highest accuracy, followed by M5P. The best average accuracy from the experiments was obtained using a 70% training and 30% testing split, yielding an accuracy of 96.83%. Therefore, the research team selected the 70% training and 30% testing split for model development, as it provided the highest accuracy compared to the 60% training and 40% testing split, and the 80% training and 20% testing split, which showed lower accuracy. The results demonstrate that the 70% training and 30% testing approach is optimal for the brain tumor classification system, ensuring high accuracy in classifying brain tumors.

关键词： Training Technological innovation Accuracy Machine learning algorithms Brain tumors Brain modeling Classification algorithms Decision trees Testing Cancer

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A Multivariate Functional Analysis of Inter-Hands Spatiotemporal Coordination in Human Bimanual Tasks and its Implications for Robotics

A Multivariate Functional Analysis of Inter-Hands Spatiotemp...

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International Conference on Autonomous Robots and Agents, ICARA

作者： Marco Baracca Andre Meixner Giuseppe Averta Paolo Salaris Tamim Asfour Matteo Bianchi Dept. of Information Engineering Research Center “E. Piaggio” University of Pisa Pisa Italy Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany Dep. of Control and Computer Engineering Politecnico di Torino Turin Italy

ISBN: (数字)9798331509231

ISBN: (纸本)9798331509248

Dual-arm manipulation is a key enabler for significantly enhancing the interaction between humans and robots, and their capabilities to purposefully shape the surrounding environment. However, the spatiotemporal coordination between the motion of the hands required for this type of actions makes their planning not trivial. A proper definition of these coordination patterns moving from the human example could simplify their translation on the robot side, fostering the generation of effective bimanual tasks. In this work, we propose Multivariate functional Principal Component Analysis (MfPCA) as a mathematical tool to encode inter-hands temporal kinematic covariations in terms of principal spatiotemporal coordination patterns in the Cartesian domain. We compared these patterns extracted from a dataset of human bimanual tasks with those resulting from the usage of classical fPCA, applied indep.ndently to each hand (univariate fPCA). We found that MfPCA allows for a better classification of the tasks, with respect to a state of the art taxonomy. For what concerns motion planning, MfPCA and fPCA yield similar accuracy in the reconstruction of the motion, but with a smaller number of principal components needed in the MfPCA case. These results, although preliminary, can open interesting perspectives for the usage of MfPCA for human-like bimanual motion planning and control of robotic manipulators, as well as for action recognition, to enable a more effective human-robot interaction.

关键词： Hands Translation Shape Robot kinematics Taxonomy Human-robot interaction Functional analysis Planning Spatiotemporal phenomena Principal component analysis

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Using A novel noisy deep reinforcement learning approach for detecting the cyberattacks in stored hydrogen fuel based AC-DC networks

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International Journal of Hydrogen Energy 2025年 135卷 457-476页

作者： Oveysikian, Ali Abed, Azher M. Davatgar, Shiva Mosallaei, Behrooz Basem, Ali Habib Ali, Sadek Ahmed, Mohsen Faculty of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran Mechanical Power Technical Engineering Department College of Engineering and Technology Al-Mustaqbal University Hilla Babylon51001 Iraq Department of Electrical Engineering Islamic Azad University Ahvaz Branch Ahvaz Iran The Klipsch School of Electrical and Computer Engineering New Mexico State University Las CrucesNM88003 United States Faculty of Engineering Warith Al-Anbiyaa University Karbala56001 Iraq Dep. of Electrical Engineering Techniques Al-Amarah University College Maysan Iraq Imam Abdulrahman Bin Faisal University P.O. Box 1982 Eastern Province Dammam31441 Saudi Arabia

Rising hydrogenous renewable energy and distributed storage integration in hybrid AC-DC networks present new challenges to grid reliability and security. Existing detection methods struggle with the complex dynamics of these systems, particularly when faced with sophisticated cyber threats. Voltage attacks, capable of causing widespread outages and equipment damage, are a significant threat. This paper proposes a novel deep reinforcement learning (DRL) approach using Ornstein-Uhlenbeck noise for enhanced voltage attack detection. Our approach addresses the limitations of conventional detection methods that suffer from low accuracy and poor convergence in complex hybrid environments. The Noisy Deep Q-Network (NDQN) leverages this noise exploration technique to achieve efficient state space exploration and smoother convergence during training. An advanced attack model specifically designed to target vulnerabilities in stored hydrogen fuel-based AC-DC systems based on hydrogen fuel resources is also presented. The NDQN approach's effectiveness is evaluated in a realistic and complex hybrid AC-DC environment under the proposed attack model. The results demonstrate significant improvements in detection accuracy (62.44 % higher average return compared to traditional DQN) and robustness compared to existing methods. Additionally, the approach helped maintain system integrity while reducing generation from the electrical grid by 42.7 %, leading to substantial cost savings. This work showcases the combined efficacy of the novel attack model and the NDQN approach, offering a promising solution for bolstering power grid security and reliability. © 2025 Hydrogen Energy Publications LLC

关键词： Reinforcement learning

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VIs2sound on Reconfigurable hardware

VIs2sound on Reconfigurable hardware

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2008 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2008

作者： Manilas, C. Cobos, J.P. Pelayo, F.J. Prieto, A. Romero, S. Dep. of Computer Architecture and Techonoly University of Granada Spain Dep. of Computer Science University of Jaen Spain

ISBN: (纸本)9780769534749

This work describes the implementation of a bioinspired visual processing system on configurable logic, designed for the enhancement of relevant information on a real scene, for its use on a complete system to assist the visually-impaired. For this purpose, a sensorial transduction module has been developed, which transforms visual information into sound patterns with 3D spatial localization. The requirements for this application, as portability, constrained power consumption, real-time performance, and customization to fit the specific features of the patient's affection, lead us to consider programmable logic as the best option for the design and development of the whole system, specifically FPGAs. A prototype of the system, including two video inputs with three spatial filters, two weighed sums, a disparity computation module, and the 3D sound generator, has been implemented on a Virtex-II XC2V6000, and performs at a maximum rate of 60 frames per second. © 2008 IEEE.

关键词： Reconfigurable hardware

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Work in progress - Achieving the ABET professional skills using solidarity projects

Work in progress - Achieving the ABET professional skills us...

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38th ASEE/IEEE Frontiers in Education Conference, FIE 2008

作者： Alonso, Javier López, David Cruz, Josep-Llorenç Álvarez, Carlos Jimenez-González, Darnel Fernández, Agustín Sánchez, Fermín Technical University of Catalonia Computer Architecture Dep. Spain

Traditionally, engineering studies have focused on preparing students technically and given little importance to social or ethical aspects, nor the ability to work in multi-disciplinary teams. Currently though, these skills are an added value and have been included in most prestigious centre's curricula. As a result, they have become a subject of study for the education community and the focus of numerous papers. Correspondingly, the Barcelona School of Informatics has developed a hardly explored initiative in order to inculcate these values and help students acquire these skills. This initiative gets them involved in what we call solidarity projects, where both students and professors get administrative and subsidized support to create cooperative work that will provide a solution to specific problems on developing countries and poor local areas. These projects may be introduced in some courses and during Bachelor and Master Thesis and have contributed towards the professional skills development of both students and professors involved. © 2008 IEEE.

关键词： Students

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Crossing-Preserving Geodesic Tracking on Spherical Images

arXiv

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arXiv 2025年

作者： van den Berg, Nicky J. Sherry, Finn M. Berendschot, Tos T.J.M. Duits, Remco CASA Dep. of Mathematics & Computer Science Eindhoven University of Technology Netherlands EAISI Eindhoven University of Technology Netherlands Ophthalmology Department Maastricht University Netherlands

In image analysis one often encounters spherical images, for instance in retinal imaging. The behavior of the vessels in the retina is an indicator of several diseases. To automate disease diagnosis using retinal images, it is necessary to develop an algorithm that automatically identifies and tracks vessels. To deal with crossings due to projected blood vessels in the image it is common to lift retinal images to the space of planar positions and orientations M2:= R2×S1. This implicitly assumes that the flat image accurately represents the geometry of the retina. As the eyeball is a sphere (and not a plane), we propose to compute the cusp-free, crossing-preserving geodesics in the space of spherical positions and orientations W2 on wide-field images. We clarify how to relate both manifolds and compare the calculated geodesics. The results show clear advantages of crossing-preserving tracking in W2 over non-crossing-preserving tracking in W2 and are comparable to tracking results in M2. Copyright © 2025, The Authors. All rights reserved.

关键词： Geometry

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A method for showing progress

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Formal Aspects of Computing 1995年第5期7卷 576-580页

作者： Rustan, K. Leino, M. Denvir, T. California inst. technology dep. computer sci. Pasadena CA

Charmed by the ease with which [vdS95] shows that its program makes progress, I state a theorem that allows for showing progress of a UNITY-like program in an easy way. I also give a proof of that theorem.

关键词： Software engineering

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