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4th International Conference on Digital Age and Technological Advances for Sustainable Development, ICDATA 2023

作者： Meyma, Mint Mohamed Laaz, Naziha Mbarki, Samir Ibn Tofail University Information Modeling and Communication Systems Team Edpags Laboratory Faculty of Sciences Kenitra Morocco Hassania School of Public Works Ehtp Asyr Rt Lages Laboratory Department of Mathematics Computer Science and Geomatics Casablanca Morocco

ISBN: (纸本)9798350311112

The article presents an MDA approach for upgrading e-health applications, based on QVTo mapping which is defined by OMG as the language used to model the transformation. Its purpose is to transform abstract models into concrete ones so that the reader can understand how the complete transformation takes place. The work focuses on the modernization of eHealth applications by applying MDE principles, techniques and tools. To do so, a comparative study was conducted to see the difference between eHealth 2.0 and eHealth 3.0 applications. EHealth 2.0 applications are characterized by the use of social web, wikis, blogs. As for the 3.0 applications, they rely on artificial intelligence and semantic web in addition to web 2.0 properties. So, a development process is proposed that takes as input two PIM models, derived from both UML and IFML standards, and as output the two PSM models that respect ODM and HTML5 respectively. © 2023 IEEE.

关键词： eHealth

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CNN-RNN Hybrid Model For Dangerous Sound Detection in Urban Area

CNN-RNN Hybrid Model For Dangerous Sound Detection in Urban ...

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Smart information systems and Technologies (SIST), IEEE International Conference on

作者： Zeinel Momynkulov Nurzhan Omarov Aigerim Altayeva Department of Mathematical and Computer Modeling International Inforamtion Technology University Almaty Kazakhstan Department of Information Systems Al-Farabi Kazakh National University Almaty Kazakhstan

ISBN: (数字)9798350374865

ISBN: (纸本)9798350374872

In the realm of audio signal processing, detecting impulsive urban sounds within continuous audio streams remains a complex endeavor. This paper presents an innovative solution via a hybrid Convolutional Neural Network - Recurrent Neural Network (CNN-RNN) framework. The CNN segments of the model target the extraction of spatial hierarchies from the audio, while the RNN components leverage their temporal memory capabilities to recognize and sequence sporadic urban auditory events. Drawing data from a rich collection of urban audio signals sourced from multiple global metropolises, the hybrid model was rigorously trained and evaluated. Findings underscore its superior detection accuracy in comparison to conventional methods, with a marked decrease in false positives. Moreover, the adaptability of the CNN-RNN architecture was evidenced by its consistent performance across diverse acoustic environments. This advancement in impulsive urban sound detection not only accentuates the efficacy of combined CNN-RNN systems but also has broader implications for urban planning, environmental assessments, and public safety initiatives.

关键词： Training Adaptation models Recurrent neural networks Accuracy Target recognition Urban planning Public security

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Sensitivity of DC Network Representation for GIC Analysis

Sensitivity of DC Network Representation for GIC Analysis

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IEEE Texas Power and Energy Conference (TPEC)

作者： Aniruddh Mishra Arthur K. Barnes Jose E. Tabarez Adam Mate Department of Electrical and Computer Engineering University of Texas at Austin Austin TX Information Systems and Modeling Group Los Alamos National Laboratory Los Alamos NM

ISBN: (数字)9798331541125

ISBN: (纸本)9798331541132

Geomagnetic disturbances are a threat to the reliability and security of our national critical energy infrastructures. These events specifically result in geomagnetically induced currents, which can cause damage to transformers due to magnetic saturation. In order to mitigate these effects, blocker devices must be placed in optimal locations. Finding this placement requires a dc representation of the ac transmission lines, which this paper discusses. Different decisions in this process, including the method of representing the blocking devices, result in significant variations to the power loss calculations. To analyze these effects, we conclude the paper by comparing the losses on a sample network with different modeling implementations.

关键词： Analytical models Sensitivity Substations Power transmission lines Windings Circuit faults Security Reliability Electric fields Saturation magnetization

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Simulated annealing for resource and power allocation in 5G and B5G D2D communications 6

Simulated annealing for resource and power allocation in 5G ...

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6th International Conference on Pattern Analysis and Intelligent systems, PAIS 2024

作者： Benbraika, Mohamed Kamel Bourekkache, Samir Kraa, Okba Himeur, Yassine Telli, Khaled Ouamane, Abdelmalik University of El-Oued Computer Science Department El-Oued Algeria Mohamed Khider University Smart Computer Science Laboratory Biskra Algeria Mohamed Khider University Energy Systems Modeling Laboratory Biskra Algeria University of Dubai College of Engineering And Information Technology United Arab Emirates Mohamed Khider University Laboratory of LI3C Biskra Algeria

ISBN: (纸本)9798350350265

Device-to-device connection is a captivating new approach that holds great potential for the next generation of mobile networks, among others 5G and beyond. One of the reasons for this is that it has the capacity to boost system throughput, reduce the burden on the network core, and enhance spectral efficiency. Therefore, in order to make the most of these advantages, it is of the utmost importance to enhance the allocation of resources and power in order to reduce the amount of interference caused by co-channels. This paper proposes utilizing a based simulated annealing (SAA) technique to enhance combined radio spectrum and energy allocation. The SAA is made up of a phase that involves heating, which is then followed by slow and steady cooling. This is a method that is very often used in the field of metallurgy. Doing so results in an ordered and therefore stronger metal with more flexibility and less energy. The simulation outcomes show that the proposed approach surpasses both the random solution and Genetic approach (GA) in terms of time to stabilize to an optimal solution, throughput, and obtaining a feasible solution. © 2024 IEEE.

关键词： Genetic algorithms

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An Advanced Data Fabric Architecture Leveraging Homomorphic Encryption and Federated Learning

arXiv

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arXiv 2024年

作者： Rieyan, Sakib Anwar News, Raisul Kabir Muntasir Rahman, A.B.M. Khan, Sadia Afrin Jawad Zaarif, Sultan Tasneem Alam, Golam Rabiul Hassan, Mohammad Mehedi Ianni, Michele Fortino, Giancarlo Department of Computer Science and Engineering School of Data and Sciences BRAC University 66 Mohakhali Dhaka1212 Bangladesh Department of Information Systems College of Computer and Information Sciences King Saud University Riyadh11543 Saudi Arabia Department of Informatics Modeling Electronics and Systems University of Calabria CS Rende87036 Italy

Data fabric is an automated and AI-driven data fusion approach to accomplish data management unification without moving data to a centralized location for solving complex data problems. In a Federated learning architecture, the global model is trained based on the learned parameters of several local models that eliminate the necessity of moving data to a centralized repository for machine learning. This paper introduces a secure approach for medical image analysis using federated learning and partially homomorphic encryption within a distributed data fabric architecture. With this method, multiple parties can collaborate in training a machine-learning model without exchanging raw data but using the learned or fused features. The approach complies with laws and regulations such as HIPAA and GDPR, ensuring the privacy and security of the data. The study demonstrates the method’s effectiveness through a case study on pituitary tumor classification, achieving a significant level of accuracy. However, the primary focus of the study is on the development and evaluation of federated learning and partially homomorphic encryption as tools for secure medical image analysis. The results highlight the potential of these techniques to be applied to other privacy-sensitive domains and contribute to the growing body of research on secure and privacy-preserving machine learning. © 2024, CC BY.

关键词： Medical imaging

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Economic and Mathematical Models for Determining the Level of Maturity of an Enterprise in Knowledge Management and Project Management

Economic and Mathematical Models for Determining the Level o...

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International Conference on Advanced computer information Technologies (ACIT)

作者： Inna Chaikovska Maksym Chaikovskyi Department of Economics Analytics Modeling and Information Technologies in Business Khmelnytskyi National University Khmelnytskyi Ukraine Department of Computer Engineering and Information Systems Khmelnytskyi National University Khmelnytskyi Ukraine

The article offers an economical and mathematical modeling toolkit to determine the enterprise’s knowledge and project management maturity level. In particular, gray relational analysis and the hierarchy analysis method were used in forming a comprehensive assessment of the knowledge management system and determining the level of maturity of a knowledge management enterprise. Fuzzy logic was used in forming a comprehensive evaluation of a project management system and determining the maturity level of a project management enterprise. The following maturity levels are proposed: low, below average, average, above average, and high, and membership functions for these terms are formed. The obtained comprehensive indicators of the enterprise’s knowledge management and project management system can be used in modeling functional relationships in the knowledge management system in the operational and project activities of the enterprise to identify problem areas for achieving the target values of performance criteria.

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Models of Battle Dynamics in Strategic computer Games 16

Models of Battle Dynamics in Strategic Computer Games

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16th International Conference Management of Large-Scale System Development, MLSD 2023

作者： Laryushin, Ivan Dmitrievich Pashin, Dmitrii Sergeevich Koltochenko, Yaroslav Alekseevich Ereshko, Felix Ivanovich Gaponov-Grekhov Institute of Applied Physics Ras Plasma Physics Department Nizhny Novgorod Russia State University of Nizhny Novgorod Faculty of Physics National Research Lobachevsky Nizhny Novgorod Russia Moscow Institute of Physics and Technology Department of Mathematical Modeling of Complex Systems and Optimization Moscow Russia Federal Research Center 'Computer Science and Control' of the Ras Department of Information and Computing Systems Moscow Russia

ISBN: (纸本)9798350337907

A set of new models that describe the dynamics of battles in strategic computer games is presented. These models not only have descriptive functions, but also allow solving problems of optimizing army control under given conditions, as well as calculating the most efficient composition of the army for the planned operation within a computer game. © 2023 IEEE.

关键词： computer games

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Fuzzy System of IT-Project Works Priority

Fuzzy System of IT-Project Works Priority

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International Conference on Advanced computer information Technologies (ACIT)

作者： Nadia Vasylkiv Lesia Dubchak Mikolaj Karpinski Iryna Turchenko Liubomyr Flud Tetiana Nadvynychna Department of Information Computer Systems and Control West Ukrainian National University Ternopil Ukraine Department of Computer Engineering West Ukrainian National University Ternopil Ukraine Department of Cyber Security University of the National Education Commission Krakow Poland Department of Information Systems and Computer Modeling Ukrainian National Forestry University Lviv Ukraine Subdepartment of Psychology and Social Work West Ukrainian National University Ternopil Ukraine

ISBN: (数字)9798350350043

ISBN: (纸本)9798350350050

A fuzzy system for setting the priority of IT project work has been developed, in which a preliminary analysis of the metrics of readiness, permission and complexity of tasks is carried out, which makes it possible to determine the priority of the project work. Based on this, the business analyst can effectively make decisions about the workload of the project team. The results of the work can be successfully applied to the effective management of the implementation of IT projects and the proactive management of project teams.

关键词： Measurement Accuracy Employment Companies Software Hardware Complexity theory information technology Fuzzy systems Business

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Development of Software for modeling the Drying Process of Hygroscopic Materials Using Cellular Automata

Development of Software for Modeling the Drying Process of H...

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International computer Sciences and information Technologies (CSIT)

作者： Yaroslav Sokolovskyy Oleksiy Sinkevych Roman Voliansky Oleksandr Storozhuk Department of Computer-Aided Design Systems Lviv Polytechnic National University Lviv Ukraine Department of Computer Science Ukrainian National Forestry University Lviv Ukraine Department of Electromechanical Systems Automation and Electric Drives National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Kyiv Ukraine Department of Information Systems and Computer Modeling Ukrainian National Forestry University Lviv Ukraine

ISBN: (数字)9798331542634

ISBN: (纸本)9798331542641

In this work, software is developed for modeling the drying process of hygroscopic materials using cellular automata. The modeling process using cellular automata is described, and the developed transition rules that consider heat and mass transfer not only within the material but also between stacks are provided. The developed software uses a modern multi-tier client-server architecture, including a database for handling large volumes of computational data. Additionally, the results of the modeling, including their validation based on existing experimental data, are presented and analyzed.

关键词： computer science Accuracy Databases Computational modeling Automata computer architecture Software Data models information technology Heat transfer

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Human Behavior-based Personalized Meal Recommendation and Menu Planning Social System

arXiv

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arXiv 2023年

作者： Islam, Tanvir Joyita, Anika Rahman Alam, Md. Golam Rabiul Hassan, Mohammad Mehedi Hassan, Md. Rafiul Gravina, Raffaele The Department of Computer Science and Engineering BRAC University Dhaka1212 Bangladesh Department of Information Systems College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia The College of Arts & Sciences University of Maine at Presque IsleME04769 United States The Department of Informatics Modeling Electronics and Systems University of Calabria Italy

The traditional dietary recommendation systems are basically nutrition or health-aware where the human feelings on food are ignored. Human affects vary when it comes to food cravings, and not all foods are appealing in all moods. It takes a lot of effort to learn people’s food preferences and make recommendations based on their affects and nutrition. A questionnaire-based and preference-aware meal recommendation system can be a solution. However, automated recognition of social affects on different foods and planning the menu considering nutritional demand and social-affect has some significant benefits over the questionnaire-based and preference-aware meal recommendations. A patient with severe illness, a person in a coma, or patients with locked-in syndrome and amyotrophic lateral sclerosis (ALS) cannot express their meal preferences. Therefore, the proposed framework includes a social-affective computing module to recognize the affects of different meals where the person’s affect is detected using electroencephalography signals. EEG allows to capture the brain signals and analyze them to anticipate affective state toward a food. In this study, we have used a 14-channel wireless Emotiv Epoc+ to measure affectivity for different food items. A hierarchical ensemble method is applied to predict affectivity upon multiple feature extraction methods and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is used to generate a food list based on the predicted affectivity. In addition to the meal recommendation, an automated menu planning approach is also proposed considering a person’s energy intake requirement, affectivity, and nutritional values of the different menus. The bin-packing algorithm is used for the personalized menu planning of breakfast, lunch, dinner, and snacks. The experimental findings reveal that the suggested affective computing, meal recommendation, and menu planning algorithms perform well across a variety of assessment param

关键词： Electroencephalography

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