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Modeling and Optimal control for Resource Allocation in the Epidemic Monitoring of a Multi-group Population

SN computer science 2024年第1期5卷 121页

作者： Di Giamberardino, Paolo Iacoviello, Daniela Papa, Federico Department of Computer Control and Management Engineering “A. Ruberti” Sapienza University of Rome Via Ariosto 25 Rome 00185 Italy Institute for System Analysis and Computer Science “A. Ruberti” CNR Via dei Taurini 19 Rome 00185 Italy

In the last 3 years, the entire world has been facing the sanitary emergency due to the SARS-CoV2;it has been stressed the mutual interdependence of the human populations, as well as the strong impact of specific conditions, such as age, work, habits, on the disease spread among subgroups of a given population. Moreover, the high percentage of asymptomatic individuals, especially among young subjects, improves the infection spread among groups with higher probability of fatal consequences. The vaccination campaign has strongly contributed to reduce mortality, so bringing the epidemic scenario probably closer to the endemic state. Nevertheless, the loss of the vaccination protection, the appearance of new variants and the mixing of moving people require a surveillance action to reduce new virus waives. By suitable modeling and optimal control design, this paper addresses the planning of a swab test campaign for the surveillance of the disease spread within a given multi-group population, when resource limitation and distinctive epidemiological characteristics of the subgroups are present. The proposed approach, applied on a case study in which the population is split into four groups, stresses the importance of a suitable tuned swab test campaign, saving a significant number of infections (and therefore of human lives), by scheduling the surveillance effort on the different populations. The determination of this kind of control is useful not only in the endemic condition, but also as general surveillance strategy at the beginning of an epidemic spread, with limitations in material and logistic resources. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Epidemic monitoring Mathematical modeling of epidemics Optimal control Resource allocation

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A Strengthened Primal-Dual Decomposition Algorithm for Solving Electricity Market Pricing With Revenue-Adequacy and FFR Constraints

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2024年第3期2卷 379-391页

作者： Goudarzi, Hamed Hesamzadeh, Mohammad Reza Bunn, Derek Fotuhi-Firuzabad, Mahmud Shahidehpour, Mohammad Sharif University of Technology Center of Excellence in Power System Management and Control Tehran11365-11155 Iran Kth Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm10044 Sweden London Business School Department of Management Science and Operations LondonNW1 4SA United Kingdom Illinois Institute of Technology Electrical and Computer Engineering Department ChicagoIL60616 United States

This paper develops a new decomposition algorithm for solving Electricity Market Pricing (EMP) problem, taking into account both revenue-adequacy and Fast Frequency Reserve (FFR) constraints. Due to revenue-adequacy constraint, a bilevel model of the EMP problem is introduced (BL-EMP). The upper level of the BL-EMP model represents the non-convex unit commitment (UC) decisions as well as the revenue-adequacy constraints of the market participants (generators, loads, and battery-storage owner). The lower level is a convex economic dispatch model with FFR constraint. To tackle the computational complexity of the considered BL-EMP model, this paper develops, tests, and proposes a Strengthened Primal-Dual Decomposition (SPDD) algorithm, which takes benefits from both Benders-like and Lagrange Dual-like algorithms. The new SPDD algorithm has a series of interesting computational properties, which are theoretically discussed in the paper. The SPDD algorithm has better computational performance than standard Benders decomposition algorithm and it also does not need tuning of the Big-M (or disjunctive) parameters for solving the proposed BL-EMP problem. Results from the modified IEEE 24-bus, the IEEE 118-bus, and the IEEE 300-bus system show the superiority of proposed SPDD algorithm over the classic Benders algorithm. © 2023 IEEE.

关键词： Power markets

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Adversarial Neural Network Classifiers for COVID-19 Diagnosis in Ultrasound Images

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computers, Materials & Continua 2022年第1期70卷 1683-1697页

作者： Mohamed Esmail Karar Marwa Ahmed Shouman Claire Chalopin Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering(FEE)Menoufia UniversityMenouf32952Egypt Department of Computer Engineering and Networks College of Computing and Information TechnologyShaqra UniversityShaqra11961Saudi Arabia Department of Computer Science and Engineering Faculty of Electronic Engineering(FEE)Menoufia UniversityMenouf32952Egypt Innovation Center for Computer Assisted Surgery(ICCAS) Universit鋞LeipzigLeipzig04103Germany

The novel Coronavirus disease 2019(COVID-19)pandemic has begun in China and is still affecting thousands of patient livesworldwide *** X-ray and Computed Tomography are the gold standardmedical imaging modalities for diagnosing potentially infected COVID-19 cases,applying Ultrasound(US)imaging technique to accomplish this crucial diagnosing task has attracted many physicians *** this article,we propose two modified deep learning classifiers to identify COVID-19 and pneumonia diseases in US images,based on generative adversarial neural networks(GANs).The proposed image classifiers are a semi-supervised GAN and a modifiedGANwith auxiliary *** one includes a modified discriminator to identify the class of the US image using semi-supervised learning technique,keeping its main function of defining the“realness”of tested *** tests have been successfully conducted on public dataset of US images acquired with a convex US *** study demonstrated the feasibility of using chest US images with two GAN classifiers as a new radiological tool for clinical check of COVID-19 *** results of our proposed GAN models showed that high accuracy values above 91.0%were obtained under different sizes of limited training data,outperforming other deep learning-based methods,such as transfer learning models in the recent ***,the clinical implementation of our computer-aided diagnosis of US-COVID-19 is the future work of this study.

关键词： COVID-19 medical imaging machine learning applications adversarial neural networks ultrasound

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A Ray-based Asynchronous Distributed Parallel K-SVD Method 12

A Ray-based Asynchronous Distributed Parallel K-SVD Method

引用

12th International Conference on Advanced Cloud and Big Data, CBD 2024

作者： Li, Yongkang Chen, Xiaodong Wan, Xiaohui Sun, Jin Zheng, Peng Wang, Yunchang Wu, Zebin School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China Quzhou Transportation Bureau Department of Industry Development Quzhou China Chang shan Inspection and Testing institute Department of Quality Control and Testing Quzhou China

ISBN: (纸本)9798331511074

K-SVD (K-Singular Value Decomposition)is a com-monly used dictionary learning method that progressively opti-mizes dictionaries to better represent data by iterating sparse coding and dictionary update steps. However, with the increasing data size, the traditional K -SVD method faces significant challenges in terms of computational efficiency. Therefore, this paper proposes an asynchronous distributed parallel K-SVD method based on Ray framework to cope with the computational efficiency problem in large-scale data processing. This method achieves efficient parallel computation by decomposing the sparse coding and dictionary updating steps of the K-SVD method into multiple independent tasks and utilizing the distributed scheduling capability of the Ray framework. Since the zero elements of the coefficient matrix are unevenly distributed, we introduce a stride partitioning approach when performing the decomposition. In addition, in order to avoid the method falling into local optima and failing to find global optima due to parallelism, this paper synchronizes with the global at the same time as the atomic update of the dictionary. Meanwhile, for the purpose of avoiding the overhead caused by data synchronization, a parameter server is introduced to realize asynchronous updating of dictionary and coefficient matrix to reduce the overhead caused by communication. The experimental results show that, compared with the traditional K-SVD method, the method proposed in this paper has a significant advantage in computational efficiency and is able to efficiently process hyperspectral image datasets under the premise of guaranteeing the sparse representation accuracy. Compared with the synchronous parallel K-SVD method, the proposed method has faster error convergence and does not fall into local optima. © 2024 IEEE.

关键词： Network security

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Analysis of YouTube Video Comments with NLP Methods 16

Analysis of YouTube Video Comments with NLP Methods

引用

16th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2024

作者： Mironela, Pirnau Iustin, Priescu Mihaela, Priescu Catalina Claudiu, Pirnau Daniel, Ghiculescu Liviu 'Titu Maiorescu' University Faculty of Informatics Department of Informatics Bucharest Romania National University of Science and Technology Politehnica Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania National University of Science and Technology Politehnica Bucharest Faculty of Industrial Engineering and Robotics Manufacturing Engineering Department Bucharest Romania

ISBN: (纸本)9798350371154

This study proposes methods that can be used to examine and interpret comments that users have made after watching videos on YouTube on a particular topic. YouTube tutorials are very popular among young people. They have become an important pillar in informal education, thus contributing to the rapid acquisition of skills and knowledge. Under these circumstances, we were interested in analysing the YouTube videos comments, knowing that the platform has a continuous increase in popularity, which is also due to the opportunities of sharing them. Since ChatGPT-themed YouTube videos have seen a significant surge in popularity since 2022, we were interested to analyse some videos that approach the topics of 'ChatGPT, AI clone, AI robot and Deep Learning.' © 2024 IEEE.

关键词： Deep learning

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Bipolar Picture Fuzzy Graph Based Multiple Attribute Decision Making Approach–Part I 1

引用

4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Gong, Shu Hua, Gang Department of Computer Science Guangdong University of Science and Technology Dongguan523083 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China

ISBN: (数字)9783031200991

ISBN: (纸本)9783031200984

The multiple attribute decision making (MADM) is a one of most crucial topic in decision making and computer science. The key technology for MADM is to learn the correlation between different attributes, and the graph model is an appropriate tool to analyze it. In this work, the MADM problem is formulated in the bipolar picture fuzzy graph framework, and decision making algorithms are designed to characterize the relationships among attributes. The numerical example is introduced in this paper to show how to handle the MADM problem in terms of bipolar picture graph model. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fuzzy sets

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SS-DBSCAN: Epsilon Estimation with Stratified Sampling for Density-Based Spatial Clustering of Applications with Noise

SS-DBSCAN: Epsilon Estimation with Stratified Sampling for D...

引用

2023 International Conference on Automation, control and Electronics engineering, CACEE 2023

作者： Monko, Gloriana Joseph Kimura, Masaomi Shibaura Institute of Technology Graduate School Department of Functional Control Systems Tokyo Japan Shibaura Institute of Technology Department of Computer Science and Engineering Tokyo Japan

ISBN: (纸本)9798350309201

Clustering algorithms are crucial in uncovering hidden patterns and structures within datasets. Among the density-based clustering algorithms, DBSCAN (Density-Based Spatial Clustering of Applications with Noise) has gained considerable attention for its effectiveness in various applications. However, determining appropriate parameter values for this algorithm remains a challenging task. This paper presents a novel methodology for eps parameter estimation for an improved DBSCAN, namely SS-DBSCAN. The experimental results across nine datasets demonstrate the efficacy of our proposed method in accurately determining clusters with eps value from SS-DBSCAN algorithm. The clusters identified using estimated eps values by SS-DBSCAN align well with the inherent structure of the datasets, yielding better cluster results than the manually set parameters and other methods used for automatic estimations of the eps for DBSCAN. Our approach adapted well to the peculiarities of each dataset, whether dealing with different scales, dimensions, or densities;it proved the versatility and robustness across various datasets, thereby emphasizing its generalizability and potential for broader applications. © 2023 IEEE.

关键词： Parameter estimation

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Decision Making Analysis of Traffic Accidents on Mountain Roads in Yunnan Province 1

引用

4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Gong, Shu Hua, Gang Department of Computer Science Guangdong University Science and Technology Dongguan523083 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China

ISBN: (数字)9783031200991

ISBN: (纸本)9783031200984

Bipolar objects are widespread in nature, and they describe the opposition and unity of the things. Inspired by decision making characterizing in terms of fuzzy graph structures, we propose a bipolar fuzzy graph-based case study on mountain road traffic accident analysis in Yunnan province. The bipolar membership functions on corresponding bipolar graph are proposed and a novel algorithm for mountain road traffic accident in specific area is given. We analyze the result and give a reasonable explanation for this phenomenon. Some suggestions for reducing the number of mountain traffic accident are proposed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision making

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control and Stability of Large-scale Power System with Highly Distributed Renewable Energy Generation:Viewpoints from Six Aspects

引用

CSEE Journal of Power and Energy Systems 2023年第1期9卷 8-14页

作者： Qing-Hua Wu Anjan Bose Chanan Singh Joe H.Chow Gang Mu Yuanzhang Sun Zhaoxi Liu Zhigang Li Yang Liu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China School of Electrical Engineering&Computer Science Washington State UniversityPullmanWA 99164USA Department of Electrical and Computer Engineering Texas A&M UniversityCollege StationTX 77843USA Department of Electrical Computer and Systems EngineeringRensselaer Polytechnic Institute(RPI)TroyNYUSA Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin 132012China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China

Power systems are moving toward a low-carbon or carbon-neutral future where high penetration of renewables is *** conventional fossil-fueled synchronous generators in the transmission network being replaced by renewable energy generation which is highly distributed across the entire grid,new challenges are emerging to the control and stability of large-scale power *** analysis and control methods are needed for power systems to cope with the ongoing *** the CSEE JPES forum,six leading experts were invited to deliver keynote speeches,and the participating researchers and professionals had extensive exchanges and discussions on the control and stability of power ***,potential changes and challenges of power systems with high penetration of renewable energy generation were introduced and explained,and advanced control methods were proposed and analyzed for the transient stability enhancement of power grids.

关键词： Distributed energy resources high converter penetration power system control renewable energy generation stability control transient stability

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Renewable integration and energy reduction in multiple stage evaporator

引用

Materials Today: Proceedings 2023年 80卷 24-31页

作者： Pati, Smitarani Kumar Sharma, Tarun Kumar Goyal, Kapil Prakash Verma, Om Department of Instrumentation and Control Engineering Dr B R Ambedkar National Institute of Technology Jalandhar Punjab Jalandhar 144011 India Department of Computer Science and Engineering Shobhit University UP Saharanpur-247341 India Department of Industrial and Production Engineering Dr B R Ambedkar National Institute of Technology Jalandhar Punjab Jalandhar 144011 India

Multiple Effect Evaporator (MEE) is an imperative part of the paper industry. It is used to process the waste byproduct named Black Liquor to enhance its solid concentration that may be further utilized to produce biomass-based energy. This process accounts very high energy consumption which leads to the energy intensiveness of this unit. A substantial amount of energy-saving may be accumulated by integrating various Energy Reduction Schemes (ERSs) with the MEE. Steam splitting, feed splitting, feed liquor preheating, thermo-vapor compressor, etc. are the well-known ERSs that may be incorporated with the MEE to reduce energy utilization. Hence, this study investigates the hybrid ERSs incorporated with MEE to observe their energy efficiency in an optimal manner. The prime focus of this investigation is to achieve enhanced energy efficiency in teams of maximum steam efficiency which is computed by formulating the nonlinear mathematical models of the MEE. To achieve the maximized energy efficiency, an optimization function has been developed under a constraint environment and solved by using metaheuristic-based approach named Flow Direction Algorithm. Another ERSs named flash tanks can also be integrated with this system to encourage waste heat re-utilization and ensures an increase in energy efficiency with constant steam consumption. This work also deals with the incorporation of the Linear Fresnel Reflector with ERSs integrated MEE which is capable of reducing the conventional energy load. The overall integrated MEE model achieves an energy-efficient and renewably operated MEE unit that may enhance the self-sustainability of the industry. © 2022

关键词： Energy efficiency

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