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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 deployment 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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Preliminary Identification of the Dynamics of a Floating Offshore Wind Turbine Barge

Renewable Energy and Power Quality Journal

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Renewable Energy and Power Quality Journal 2023年 21卷 539-544页

作者： Galeote, I. Esteban, S. Santos, M. Dept. of Computer Architecture and Automatics Complutense University of Madrid Faculty of Physics Plaza de Ciencias 1 Madrid28040 Spain Institute of Knowledge Engineering Complutense University of Madrid Spain

Offshore wind turbines have become an increasingly attractive source of renewable energy because of their potential to access and utilize energy from deeper waters with more stable, stronger winds. The goal of this paper is to propose a mathematical model based on transfer functions to identify and study the behavior of the six degrees of freedom of floating turbines. For this purpose, the system has been simulated with OpenFAST for specific environmental conditions. A subset of data has been used to identify transfer functions to obtain a control-oriented model. The model has been progressively validated, extending the preliminary proposed model. The scope and limitations of this methodology have been assessed, as well as the possibilities of extending the present work to include a more functional methodology oriented to system co-design. © 2023, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Transfer functions

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Analysis and Detection of Melanoma through Collective Intelligence with AI

Analysis and Detection of Melanoma through Collective Intell...

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Annual IEEE Symposium on computer-Based Medical Systems

作者： Enrique Fernández-Morales Carlos L. Sanchez-Bocanegra Rafael Pastor-Vargas José-Juan Pereyra-Rodriguez Juan M. Haut José Alberto Benítez-Andrades Communications and Control Systems Dpt. Computer Science Faculty UNED Madrid Spain Communications and Control Systems Dpt. Computer Science Faculty UNED Malaga Spain Virgen Del Rocio Hospital Universitario Seville Spain School of Tecnology University of Extremadura Cáceres Spain Dept. of Electric Systems and Automatics Engineering Universidad de León León Spain

ISBN: (数字)9798350384727

ISBN: (纸本)9798350384734

Cancer is a widespread global health problem, claiming millions of lives each year, and skin cancer represents a significant threat as it is one of the most common types. Early tumor detection via medical imaging is critical for effective treatment. Leveraging artificial intelligence, particularly novel models like Transformers, presents promising avenues for improved diagnosis. This paper explores the efficacy of a Collective Intelligence approach using AI in classifying cancerous and non-cancerous tumors, aiming to reduce classification errors and support clinical decision-making. We created five different configurations using various datasets to compare the results. The results show solid performance for the CI in the evaluated tasks, reaching up to 75.89% accuracy. The lack of images in certain classes significantly contributes to overfitting. It is suggested to explore data expansion strategies and improve consistency in image capture for future work.

关键词： Accuracy Melanoma Collective intelligence Image capture Transformers Solids Artificial intelligence

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A Novel Multi-Criteria Decision-Making Method for Wind Power Plant Repowering

A Novel Multi-Criteria Decision-Making Method for Wind Power...

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International Conference on Environment and Electrical engineering (EEEIC)

作者： Isabel C. Gil-Garcí a Ana Ferná ndez-Guillamó n Á ngel Molina-Garcí a M. Socorro Garcí a-Cascales Faculty of Engineering Distance University of Madrid Madrid Spain Dept. of Electrical Eng. Electronics Automatics and Applied Physic Universidad Polit&#x00E9 cnica de Madrid Madrid Spain Dept. of Automatics Electrical Eng. and Electronic Technology Universidad Polit&#x00E9 cnica de Cartagena 30 Cartagena Spain Dept. of Electronics Computer Technology and Projects Universidad Polit&#x00E9 cnica de Cartagena Cartagena Spain

ISBN: (数字)9781665485371

ISBN: (纸本)9781665485388

In recent decades, there have been alterations in the rhythm of nature mainly due to the climate change. In parallel, there has been an increasing social awareness regarding decarbonization and renewable promotion. Most of governments have then included new policies and financing for renewable integration into different sector. In fact, the deployment of technologies based on renewable energies for the generation of electricity is a key factor in the current energy transformation. It is estimated to add approximately 305 GW per year between 2021 and 2026 to the global capacity of renewable generation electricity. Among the different resources, the wind sector par-ticipation, both onshore and offshore, plays a crucial role in the generation of electricity from renewables; expecting that, by the year 2050, there will be more than 6,000 GW of installed global capacity. However, the useful life of many wind power plants is coming to the end. Subsequently, many national power systems will be faced in the coming years with the decision to repower or partially or totally dismantle their wind turbines. This work proposes an updated methodology to determine the feasibility of repowering wind installations. A complex network of factors usually considered in decision-making processes are selected: cli-matic, technological, environmental, social and economic. These factors are then analyzed and optimized under different multi-criteria evaluation method approaches.

关键词： Renewable energy sources Wind speed Decision making Complex networks Low-carbon economy Wind power generation Rhythm

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Detection of cerebral ischaemia using transfer learning techniques

Detection of cerebral ischaemia using transfer learning tech...

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Annual IEEE Symposium on computer-Based Medical Systems

作者： Cristina Antón-Munárriz Rafael Pastor-Vargas Juan M. Haut Antonio Robles-Gómez Mercedes E. Paoletti José Alberto Benítez-Andrades Radiology area Hospital Universitario de Navarra Pamplona Spain Computer Science Faculty UNED Madrid Spain School of Tecnology University of Extremadura Caceres Spain University Centre of Merida University of Extremadura Merida Spain Dept. of Electric Systems and Automatics Engineering Universidad de Leon Leon Spain

Cerebrovascular accident (CVA) or stroke is one of the main causes of mortality and morbidity today, causing permanent disabilities. Its early detection helps reduce its effects and its mortality: time is brain. Currently, non-contrast computed tomography (NCCT) continues to be the first-line diagnostic method in stroke emergencies because it is a fast, available, and cost-effective technique that makes it possible to rule out haemorrhage and focus attention on the ischemic origin, that is, due to obstruction to arterial flow. NCCT are quantified using a scoring system called ASPECTS (Alberta Stroke Program Early Computed Tomography Score) according to the affected brain structures. This paper aims to detect in an initial phase those CTs of patients with stroke symptoms that present early alterations in CT density using a binary classifier of CTs without and with stroke, to alert the doctor of their existence. For this, several well-known neural network architectures are implemented in the ImageNet challenges (VGG, NasNet, ResNet and DenseNet), with 3D images, covering the entire brain volume. The training results of these networks are exposed, in which different parameters are tested to obtain maximum performance, which is achieved with a DenseNet3D network that achieves an accuracy of 98% in the training set and 95% in the test set.

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A Novel Method for Wind Power Plants’ Repowering Based on Multi-Criteria Decision-Making

SSRN

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SSRN 2023年

作者： Gil García, Isabel C. Fernández-Guillamón, Ana García-Cascales, M. Socorro Molina-García, Ángel c/ Coruña km 38500 Collado Villalba Madrid28400 Spain Dept. of Applied Mechanics and Projects Engineering - E.T.S. de Ingenieros Industriales & Renewable Energy Research Institute Universidad de Castilla-La Mancha C/ De la Investigación S/N Albacete02006 Spain Department of Electronics Computer Architecture and Project Engineering Department of Automatics Electrical Engineering and Electronic Technology Universidad Politécnica de Cartagena Campus Muralla del Mar Murcia Cartagena30202 Spain

Due to the climate change, over the last decades there have been changes in the rhythm of nature. However, there is an increasing social consciousness regarding decarbonization, and governments include new policies and economic support measures for renewables. The participation of the onshore and offshore wind sectors play a central role in this scenario, expecting that more than 6000 GW will be globally installed in 2050. However, the useful life of many wind power plants is coming to their end, and thus, some countries will face in the coming years the decision of repowering, decommissioning, installing new turbines, or a combination of them. In general, such areas with the greatest wind potential are already occupied by relatively old wind turbines. Subsequently, a complex group of factors influences on the best solution decision-making: climatic, technological, environmental, social or economic. This paper proposes an optimized methodology based on multi-criteria decision-making to estimate the most appropriate solution for extending the useful-life of wind power plants. The methodology is divided into three stages: (i) data, (ii) alternatives and (iii) optimization. It was assessed with a Spanish onshore wind power plant connected to the grid. From the initial data, 11 alternatives were designed based on 10 selection factors. The results provide an optimal solution, combining both repowering and installation of new wind turbines. It would allow us to reduce the LCOE of the new wind plants installed in the European Union by more than 50%. © 2023, The Authors. All rights reserved.

关键词： Wind turbines

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Thermal management in three dimensional networkonchip using bioinspired liquid channel placement 49

Thermal management in three dimensional networkonchip using ...

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49th Summer computer Simulation Conference, SCSC 2017, Part of the 2017 Summer Simulation Multi-Conference, SummerSim 2017

作者： Dash, Ranjita K. Majumdar, Amartya Turuk, Ashok K. Risco-Martín, José L. Ayala, José L. Pangracious, Vinod Dept. of Computer Science and Engineering National Institute of Technology Rourkela India Dept. of Computer Architecture and Automatics Complutense University of Madrid Madrid Spain Dept. of Electrical and Computer Engineering American University of Dubai Dubai United Arab Emirates

ISBN: (纸本)9781510838284

Three-dimensional Network-on-Chip systems are becoming popular because of reduced communication delay, heterogeneous integration of different technologies in a single chip, high yield, reduced latency, and less consumption of interconnect power. However, the addition of functional units in the Z-direction has resulted in higher on-chip temperature and appearance of hot spots on the die. Liquid channel cooling has emerged as an efficient and scalable solution for 3-D NoC. This paper proposed a placement strategy of liquid micro-channels in the chip using the genetic algorithm. The proposed liquid cooling approach is independent of any topology. By performing an extensive set of experiments, the result shows a substantial decrease in peak on-chip temperature. © 2017 Society for Modeling & Simulation International (SCS).

关键词： Network-on-chip

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Non-matrix tactile sensors: How can be exploited their local connectivity for predicting grasp stability?

arXiv

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arXiv 2018年

作者： Zapata-Impata, Brayan S. Gil, Pablo Torres, Fernando Automatics Robotics and Artificial Vision Research Group Dept. of Physics System Engineering and Signal Theory University of Alicante Alicante03690 Spain Computer Science Research Institute University of Alicante Alicante03690 Spain

Tactile sensors supply useful information during the interaction with an object that can be used for assessing the stability of a grasp. Most of the previous works on this topic processed tactile readings as signals by calculating handpicked features. Some of them have processed these readings as images calculating characteristics on matrix-like sensors. In this work, we explore how non-matrix sensors (sensors with taxels not arranged exactly in a matrix) can be processed as tactile images as well. In addition, we prove that they can be used for predicting grasp stability by training a Convolutional Neural Network (CNN) with them. We captured over 2500 real three-fingered grasps on 41 everyday objects to train a CNN that exploited the local connectivity inherent on the non-matrix tactile sensors, achieving 94.2% F1-score on predicting stability. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

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Considerations on using genetic algorithms for the 2D bin packing problem: A general model and detected difficulties 21

Considerations on using genetic algorithms for the 2D bin pa...

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21st International Conference on System Theory, Control and Computing, ICSTCC 2017

作者： Lam, Gia Thuan Ho, Viet Anh Logofatu, Doina Badica, Costin Vietnamese-German University Le Lai Street Hoa Phu Ward Dau Mot City Binh Duong Province Viet Nam Dept. of Computer Science and Engineering Frankfurt University of Applied Sciences Frankfurt am Main Germany Faculty of Automatics Computers and Electronics University of Craiova Craiova Romania

ISBN: (纸本)9781538638422

The 2-dimensional bin packing problem appears in various fields across many industries such as wood, glass, or paper industries. They may differ in terms of specific constraints with respects to each area but they all share a common objective that is to maximize the material utilization. Belonging to the class of NP-Hard problems, there exist no efficient method to solve it, but only approximate solution by combining a greedy placement strategy with some optimization techniques such as Genetic Algorithms. That combination approach is very popular in this topic, but few researchers have clearly presented their method and no one has explained the difficulty of applying Genetic Algorithms to this problem, making it difficult for new researchers to reimplement the known algorithms. In this paper, in addition to proposing a general framework for applying Genetic Algorithms to solving this problem, we also identify the main difficulties of using this approach and propose 2 genetic operators, path recombination and hill-climbing mutation, to support our genetic model. © 2017 IEEE.

关键词： Genetic algorithms

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Breast tissue characterization in X-Ray and ultrasound images using fuzzy local directional patterns and support vector machines 10

Breast tissue characterization in X-Ray and ultrasound image...

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10th International Conference on computer Vision Theory and Applications, VISAPP 2015

作者： Abdel-Nasser, Mohamed Puig, Domenec Moreno, Antonio Saleh, Adel Marti, Joan Martin, Luis Magarolas, Anna Department of Computer Engineering and Mathematics Rovira I Virgili University Tarragona Spain Dept. of Electronics Computer Engineering and Automatics University of Girona Girona Spain Hospital Universitari Joan XXIII de Tarragona Tarragona Spain

ISBN: (纸本)9789897580895

Accurate breast mass detection in mammographies is a difficult task, especially with dense tissues. Although ultrasound images can detect breast masses even in dense breasts, they are always corrupted by noise. In this paper, we propose fuzzy local directional patterns for breast mass detection in X-ray as well as ultrasound images. Fuzzy logic is applied on the edge responses of the given pixels to produce a meaningful descriptor. The proposed descriptor can properly discriminate between mass and normal tissues under different conditions such as noise and compression variation. In order to assess the effectiveness of the proposed descriptor, a support vector machine classifier is used to perform mass/normal classification in a set of regions of interest. The proposed method has been validated using the well-known mini-MIAS breast cancer database (X-ray images) as well as an ultrasound breast cancer database. Moreover, quantitative results are shown in terms of area under the curve of the receiver operating curve analysis. Copyright © 2015 SCITEPRESS - Science and Technology Publications All rights reserved.

关键词： Fuzzy logic

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