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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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A SENSITIVITY ANALYSIS ON THE EFFECT OF HYPERPARAMETERS IN DEEP NEURAL OPERATORS APPLIED TO SOUND PROPAGATION 10

A SENSITIVITY ANALYSIS ON THE EFFECT OF HYPERPARAMETERS IN D...

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10th Convention of the European Acoustics Association, EAA 2023

作者： Borrel-Jensen, Nikolas Engsig-Karup, Allan P. Jeong, Cheol-Ho Technical University of Denmark Dep. of Electrical and Photonics Engineering Denmark Technical University of Denmark Dep. of Applied Mathematics and Computer Science Denmark

ISBN: (纸本)9788888942674

Deep neural operators have seen much attention in the scientific machine learning community over the last couple of years due to their capability of efficiently learning the nonlinear operators mapping from input function spaces to output function spaces showing good generalization properties. This work will show how to set up a per-formant DeepONet architecture in acoustics for predicting 2-D sound fields with parameterized moving sources for real-time applications. A sensitivity analysis is carried out with a focus on the choice of network architectures, activation functions, Fourier feature expansions, and data fidelity to gain insight into how to tune these models. Specifically, a default feed-forward neural network (FNN), a modified FNN, and a convolutional neural network will be compared. This work will de-mystify the DeepONet and provide helpful knowledge from an acoustical point of view. © 2023 Nikolas Borrel-Jensen et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

关键词： Sensitivity analysis

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CCDF measurement with Multi Impairment of Wi-Fi 6 performance using MATLAB Simulink 3

CCDF measurement with Multi Impairment of Wi-Fi 6 performanc...

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3rd International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2023

作者： Al-Azzawi, Fatima Faydhe Abbas, Rasha Hassan Al-Azzawi, Zainab Faydhe Kamal, Kamal Y. Institute of Technology Electronics Technical Department Middle Technical University MTU Baghdad Iraq AL- Mansour University College Dep. Computer Technology Engineering Iraq

ISBN: (纸本)9781665494007

The current 802.11ac WiFi standard is built upon and improved by WiFi 6, commonly referred to as 'AX WiFi' or '802.11ax WiFiIn response to the increasing number of gadgets in the globe, WiFi 6 was first developed. If you have numerous smart home devices, VR equipment, or a lot of other gadgets, WiFi 6 employs a 160 MHz Channel to offer a channel that larger and providing by 1024-QAM to more data with one packed, increasing efficiency. In this paper 802.11 ax design and implemented in MATLAB Simulink where CCDF measurement (Complementary Cumulative Distribution Function measure the probability that a signal's instantaneous power may exceed its target level or average power) with multi-impairment performance illustrated using 1024-QAM to offer a packed signal with increasing data and a channel with160 MHz, 1024 QAM examined with AWGN and Rayliegh fading channel in term of bit error rate. © 2023 IEEE.

关键词： Fading channels

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Multi-RAT Fiber-Wireless Technologies towards 6G Networks 23

Multi-RAT Fiber-Wireless Technologies towards 6G Networks

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23rd International Conference on Transparent Optical Networks, ICTON 2023

作者： Vagionas, Chris Maximidis, Ronis Kanta, Konstantina Toumasis, Panagiotis Giannoulis, Giannis Apostolopoulos, Dimitris Kalfas, George Gatzianas, Marios Mesodiakaki, Agapi Avramopoulos, Hercules Miliou, Amalia Pleros, Nikos Aristotle University of Thessaloniki CIRI Dep. of Informatics 54636 Greece National Technical University of Athens School of Electrical and Computer Engineering Greece

ISBN: (纸本)9798350303032

At the dawning of the beyond 5G era, broadband last mile connectivity is stimulating rapid developments in optical and wireless technologies that will efficiently handle the traffic generated by mobile users and demanding network applications. To this end, multiple Radio Access (multi-RAT) technologies operating at various millimeter wave (mmWave) frequency bands, e.g., V-/E-/D-band are being actively pursued, in parallel with the investigation of efficient fiber wireless fronthaul schemes, e.g. Analog Radio over Fiber (aRoF) or Intermediate Frequency over Fiber (IFoF), to deliver low-complexity, broadband, last-mile connectivity. However, integration of such novel technologies in an actual mobile network infrastructure remains a challenge, as it needs to support compatibility with the network operators' equipment. The current talk aims to present a holistic Fiber Wireless (FiWi) connectivity, demonstrating the co-existence of Analog and Digital RoF traffic along with flexible, reconfigurable point-to-multipoint connectivity to multi-RAT antenna units. Experimental results on high capacity FiWi fronthaul links operating in the V- (60 GHz) and D- (145 GHz) will be presented. Moreover, end-to-end, integrated real-time traffic and network operation will also be discussed and experimentally presented, indicating a possible technology roadmap towards multi-RAT 6G networks. © 2023 IEEE.

关键词： Radio-over-fiber

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Pollutant correlation analysis in measurements at four classrooms in four Norwegian schools 17

Pollutant correlation analysis in measurements at four class...

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17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022

作者： Alonso, Maria Justo Jørgensen, Rikke Bramming Madsen, Henrik Mathisen, Hans Martin Dep. Energy and Process Engineering Trondheim Norway Dep. Industrial Economics and Technology Management Trondheim Norway Technical University of Denmark Applied Mathematics and Computer Science Kgs. Lyngby Denmark

Demand-controlled ventilation (DCV) is often used in school buildings to save energy by modulating the airflow rates based on the demand. However, other pollutants and indoor air parameters may affect health and are not necessarily correlated to CO2. In this study investigation of correlations between PM2.5, formaldehyde, absolute humidity, CO2 and temperature are performed. Measurements of these parameters were performed between two months and one year, positioned in the supply air in four CO2-based DCV classrooms at four different schools. The time series of measurements were de-trended to avoid overestimating cross-correlation functions. From the measurements we have concluded the need to measure: 1) pollutants related to human activities (CO2) 2) pollutants that infiltrate from processes like combustion or traffic outdoors (PM2.5), and 3) parameters related to other "non-combustion-related activities" indoors, heat sources and moisture loads (temperature). Formaldehyde from building materials seems to be mostly degassed in these older than one-year buildings, but this study should be repeated on newer buildings. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

关键词： Formaldehyde

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IoT based on Membrane Computing Models 11

IoT based on Membrane Computing Models

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11th International Conference on Electromechanical and Energy Systems, SIELMEN 2021

作者： Victor, Ababii Viorica, Sudacevschi Silvia, Munteanu Olesea, Borozan Ana, Nistiriuc Victor, Lasco Technical University of Moldova Computer Sciences and Systems Engineering Dep. Chisinau Moldova

ISBN: (纸本)9781665400787

In the given paper it is approached a method of the application of the Membrane Computing models in the design of IoT systems with Collective Intelligence properties. The topology of the IoT system is presented as a Mesh network that ensures a total interconnection of its devices. The Collective Intelligence definition model presents a Hopfield Neural Network based on the set of knowledge consisting of data and their processing models. The following were elaborated: cell structure, cell interaction diagram and the manner of formation of hierarchical structures and of Collective Intelligence. The synthesis process of an IoT system on the basis of Membrane Computing models with Collective Intelligence properties is presented by the sequence of operations that begins with the definition of the mathematical model and ends with the development of the structure of the IoT system on the basis of the programmable devices ESP8266. © 2021 IEEE.

关键词： Hopfield neural networks

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Bayesian Network Structure Discovery Using Antlion Optimization Algorithm.

International Journal of Systematic Innovation

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International Journal of Systematic Innovation 2022年第1期7卷 46-65页

作者： Awla, Hoshang Qasim Kareem, Shahab Wahhab Mohammed, Amin Salih Computer science department Faculty of Science Soran University Erbil Iraq Dep. of Technical Information Systems Engineering Erbil Technical Engineering College Erbil Poly-technic University Erbil Iraq Department of Information Technology College of Engineering and Computer Science Lebanese French University Kurdistan Region Erbil Iraq

Bayesian networks have recently been used for discovering an optimal learning structure in machine learning. Bayes networks can describe possible dep.ndencies of explanatory variables. As a novel approach to studying the structure of a Bayesian network, the authors present the Antlion Optimization Algorithm (ALO). In the algorithm;deletion, rewind, insertion, and change are utilized to produce ALO to reach the best hull solution. Essentially, the technique used in the ALO algorithm imitates the antlions’ behaviors while hunting. The suggested approach is contrasted with simulated Annealing, Simulated Annealing Hybrid Bee, Greedy Search Hybrid Bee, optimization inspired by Pigeon, and greedy search using the BDe Score function. The researchers also studied the representation of the confusion matrix of these techniques using different reference data sets. The findings of the assessments reveal that the proposed algorithm works better than the other algorithms and has better consistency and score values. As shown by the experimental evaluations, the proposed method has a more reliable performance than other algorithms (including the production of excellent scores and accuracy values). © 2022. All Rights Reserved.

关键词： Antlion Optimization Bayesian Network Hunting Search Local & Global Search Metaheuristics Search and Score Structure Learning

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Machine learning algorithms in Bigdata Analysis and its applications: A review 4

Machine learning algorithms in Bigdata Analysis and its appl...

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4th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2022

作者： Khoshaba, Farah Kareem, Shahab Awla, Hoshang Mohammed, Chnar Erbil Polytechnic University Technical Engineering College Information System Engineering Department Erbil Iraq Lebanese French University College of Engineering and Computer Science Dep. of Information Technology Kurdistan Erbil Iraq Soran University College of Science Department of Computer Science Erbil Iraq

ISBN: (纸本)9781665468350

A wide range of disparate variety of heterogeneous and even disparate data sources has been integrated into the computer science research principles through the assistance of Artificial Intelligence (AI) and Machine Learning (ML) delivering excellent results in accuracy and data quality. Even so, taking machine learning approaches to very broad and dynamic datasets is both logistically and computationally costly. Some people are generating so much data regularly, which means that advanced analytics platforms have greater importance than ever before. Spark Machine Learning has extensive capabilities for a variety of ML activities such as regression, grouping, dimension reduction, and extraction of rules. While it has numerous datasets of high quality and consistency of structure. The specification of the MapReduce programming model was intended for the massive density of large-volume computation. It accomplishes this by splitting the job into several well-defined sub-sized units. There are various sets of data mining frameworks that link to a distributed device. Hadoop serves as the infrastructure for the distributed system. Several resources claim that Mahout will scale to handle massive datasets. This article discusses and demonstrates the use of algorithms and their significant impact on Bigdata, as well as a comparison between their implementations among Apache Spark and Apache Mahout. © 2022 IEEE.

关键词： Big data

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Multi-RAT Fiber-Wireless Technologies towards 6G Networks

Multi-RAT Fiber-Wireless Technologies towards 6G Networks

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International Conference on Transparent Optical Networks

作者： Chris Vagionas Ronis Maximidis Konstantina Kanta Panagiotis Toumasis Giannis Giannoulis Dimitris Apostolopoulos George Kalfas Marios Gatzianas Agapi Mesodiakaki Hercules Avramopoulos Amalia Miliou Nikos Pleros Dep. of Informatics CIRI Aristotle University of Thessaloniki Greece School of Electrical and Computer Engineering National Technical University of Athens Greece

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Image Encryption using Chaotic Techniques: A Survey Study

Image Encryption using Chaotic Techniques: A Survey Study

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2021 International Conference in Advances in Power, Signal, and Information Technology, APSIT 2021

作者： Ayad, Jenan Hasan, Fadhil Sahib Ali, Alaa H. Hussein, Zaid Khudhur Abdulkareem, Hanan J. Jalil, Mustafa A. Ahmed, Ghaidaa Sadiq, Ahmed University of Technology Electrical Engineering Dep. Baghdad Iraq Electrical Engineering Dep. Mustansiriyah University Baghdad Iraq Technical Engineering Al-Esraa University College Medical Instrumentation Baghdad Iraq Al-Esraa University College Computer Technical Engineering Baghdad Iraq

ISBN: (纸本)9781665425063

The sharing of information through unsecured networks like the internet has increased fast recently. This information could be text, audio, image, or video. The security of data transmission is an essential issue. Encryption is one of the most effective techniques to assure safe data transmission. Videos and Images size are very large and have a high correlation between neighboring pixels, so the classical encryption techniques such as RSA, DES, AES, etc., cannot be utilized for image encryption while chaotic image encryption schemes, which use a high level of unpredictability in key generation, can solve this problem. The chaos encryption main properties are pseudorandom number, sensitivity to initial conditions, and large key size. The goal of this study was to find the best chaotic map for picture encryption, this research looks into the use of chaos maps for image encryption, such as the Tent map, Logistic map, Sine map, and others. Arnold's Cat map, and also presents a comparison for their performance. © 2021 IEEE.

关键词： Data transfer

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