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检索条件"机构=DOS in Computer Science"

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Integrating Dynamic Digital Twins: Enabling Real-Time Connectivity for IoT and Virtual Reality 24

Integrating Dynamic Digital Twins: Enabling Real-Time Connec...

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Proceedings of the Winter Simulation Conference

作者： Lejla Erdal Ammar Gubartalla Paulo Victor Lopes Huizhong Cao Guodong Shao Per Lonnehed Henri Putto Abbe Ahmed Sven Ekered Björn Johansson Dept. of Industrial and Materials Science Chalmers University Gothenburg Sweden Dept. of Industrial and Materials Science Chalmers University Gothenburg Sweden and Dept. Computer Science Aeronautics Institute of Technology São José dos Campos Brazil NIST Gaithersburg Maryland US PTC Gothenburg Sweden Rockwell Automation Gothenburg Sweden

ISBN: (纸本)9798331534202

When Industry 4.0 technology is applied, it can increase resilience in production systems with interconnected machines and workers. As it is still evolving, research and implementation gaps due to issues such as costs, security, and a lack of use cases and domain expertise for enabling Digital Twins, need to be bridged. This paper proposes a framework connecting an Internet of Things platform with Digital Twin-compliant software based on ISO 23247. The simulation software provides cognitive support for the user who is immersed in the Digital Twin through Virtual Reality, and provides applications such as remote control and exploration of what-if scenarios. Connectivity with an Internet of Things platform facilitates real-time bi-directional communication, collaboration, monitoring, and assistance. A proof-of-concept use case based on an assembly line for a lab-scale drone factory was used for validation of the deployed Digital Twin based on ISO 23347.

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Enhancing Digital Twins with Deep Reinforcement Learning: A Use Case in Maintenance Prioritization 24

Enhancing Digital Twins with Deep Reinforcement Learning: A ...

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Proceedings of the Winter Simulation Conference

作者： Siyuan Chen Paulo Victor Lopes Silvan Marti Mohan Rajashekarappa Sunith Bandaru Christina Windmark Jon Bokrantz Anders Skoogh Dept. of Industrial and Materials Science Chalmers University of Technology Gothenburg SWEDEN Dept. of Computer Science Aeronautics Institute of Technology (ITA) Sao Jose dos Campos BRAZIL School of Eng. Science University of Skövde Skövde SWEDEN Dept. of Mechanical Eng. Sciences Lund University Lund SWEDEN

ISBN: (纸本)9798331534202

This paper introduces an innovative framework that enhances digital twins with deep reinforcement learning (DRL) to support maintenance in manufacturing systems. Utilizing a sophisticated artificial intelligence (AI) layer, this framework integrates real-time and historical production data from a physical manufacturing system to a digital twin, enabling dynamic simulation and analysis. Maintenance decisions are informed by DRL algorithms that analyze this data, facilitating smart maintenance strategies that adaptively prioritize tasks based on predictive analytics. The effectiveness of this approach is demonstrated through a case study in a lab-scale drone factory, where maintenance tasks are prioritized using a proximal policy optimization. This integration not only refines maintenance decisions but also aligns with the broader goals of operational efficiency and sustainability in Industry 4.0. Our results highlight the potential of combining DRL with digital twins to significantly enhance decision-making in industrial maintenance, offering a novel approach to predictive and prescriptive maintenance practices.

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Weapon Engagement Zone Maximum Launch Range Estimation Using a Deep Neural Network 10th

Weapon Engagement Zone Maximum Launch Range Estimation Using...

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10th Brazilian Conference on Intelligent Systems, BRACIS 2021

作者： Dantas, Joao P. A. Costa, Andre N. Geraldo, Diego Maximo, Marcos R. O. A. Yoneyama, Takashi Decision Support Systems Subdivision Institute for Advanced Studies SP Sao Jose dos Campos12.288-001 Brazil Computer Science Division Aeronautics Institute of Technology SP Sao Jose dos Campos12228-900 Brazil Electronic Engineering Division Aeronautics Institute of Technology SP Sao Jose dos Campos12228-900 Brazil

ISBN: (纸本)9783030916985

This work investigates the use of a Deep Neural Network (DNN) to perform an estimation of the Weapon Engagement Zone (WEZ) maximum launch range. The WEZ allows the pilot to identify an airspace in which the available missile has a more significant probability of successfully engaging a particular target, i.e., a hypothetical area surrounding an aircraft in which an adversary is vulnerable to a shot. We propose an approach to determine the WEZ of a given missile using 50,000 simulated launches in variate conditions. These simulations are used to train a DNN that can predict the WEZ when the aircraft finds itself on different firing conditions, with a coefficient of determination of 0.99. It provides another procedure concerning preceding research since it employs a non-discretized model, i.e., it considers all directions of the WEZ at once, which has not been done previously. Additionally, the proposed method uses an experimental design that allows for fewer simulation runs, providing faster model training. © 2021, Springer Nature Switzerland AG.

关键词： Deep neural networks

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Nash Equilibrium-based Resource Allocation Mechanism in Internet of Vehicles

Nash Equilibrium-based Resource Allocation Mechanism in Inte...

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IEEE Latin-American Conference on Communications, LATINCOM

作者： Matheus P. Leal Lourenço A. P. Júnior Daniel L. Guidoni Vinícius P. Gonçalves Geraldo P. Rocha Filho Luis Nakamura Rodolfo I. Meneguette Department of Computer Science São Paulo State University (UNESP) São José do Rio Preto Brazil Department of Computer Science Instituto Tecnológico de Aeronáutica (ITA) São José dos Campos Brazil Department of Computer Science Federal University of Ouro Preto (UFOP) Ouro Preto Brazil Department of Computer Science University of Brasilia (UNB) Brasilia Brazil Department of Exact and Technological Sciences State University of Southwest Bahia (UESB) Vitória da Conquista BA Brazil Department of Computer System University of São Paulo (USP) São Carlos Brazil

ISBN: (数字)9798331521110

ISBN: (纸本)9798331521127

An increasing number of research topics, including the Internet of Vehicles, have emerged and developed as a result of 5G and 6G mobile networks. Nonetheless, a number of issues have to be addressed in this context, particularly with regard to applications of the Intelligence Transportation System, which have high mobility rates and are very susceptible to delays. Because of these issues, using traditional vehicular clouds is challenging because the minimal quality of service standards are not satisfied. In order to allocate resources to environments that use cloud and edge simultaneously, we therefore propose METRO, a Nash equilibrium-based resource allocation mechanism. The effectiveness of the approach was verified using a Vehicle-to-Everything simulation environment, which contrasted a straightforward random algorithm with a metaheuristic algorithm called GWO. METRO thus had superior load.

关键词： Cloud computing Metaheuristics Transportation Quality of service Resource management Game theory Vehicle-to-everything Standards Internet of Vehicles Edge computing

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Triple Pseudo-Siamese Network with Cross-Contextual Attention for Medical Image Retrieval

Triple Pseudo-Siamese Network with Cross-Contextual Attentio...

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Intelligent Cyber Physical Systems and Internet of Things (ICoICI), International Conference on

作者： G Kavitha Yogesh Lohumi Kamal Kant H K Bhargav Harshal Patil Ramya Maranan DOS in CS&E University BDT College of Engineering Davangere India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Computer Science and Engineering School of Engineering and Technology (formerly known as UIET) CSJM University Kanpur UP India Department of Computer Science and Engineering Industry Institute Interaction Cell (IIIC) Shridevi Institute of Engineering and Technology Tumakuru Karnataka India School of Computer Science & Engineering IILM University Greater Noida Uttar Pradesh India Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai Tamil Nadu India

ISBN: (数字)9798331540661

ISBN: (纸本)9798331540678

Hospitals are now increasingly using digital imaging data, therefore medical image archives become larger and larger. Sizable databases of these sorts are difficult to organize and query; hence there is a need for content-based medical image retrieval (CBMIR) solutions. The CBMIR systems have a main challenge which is the semantic gap among the high level semantic detail obtained by human beings and low level visual detail rendered by imaging equipments. This research presents a novel approach to medical image retrieval that uses ImageCLEFMed 2009 dataset in order to address them. By pre-processing phase, we mean an improved square root Sage-Husa adaptive Kalman filter technique used for increasing the quality of images while reducing noise. For feature extraction, it combines Short-Time Fourier Transform and Continuous Wavelet Transform (STFT-CWT) together. The Triple Pseudo-Siamese Network with Cross-Contextual Attention (TPS-CCA), which captures complex patterns and relationships within the field of medicine, forms the core of this methodology. Salp Swarm Optimization has been employed for fine-tuning parameters of TPS-CCA model in order to improve its performance further. Therefore, this method shows significantly better accuracy, precision, sensitivity, specificity and F1-score compared to existing ones. This system provides a robust and efficient solution for retrieving relevant medical images, potentially aiding in improved diagnostics and patient care. The proposed method attains higher accuracy as (99.4%), precision as (99.5%), sensitivity as (99.6%), specificity as (99.8%), F1-score as (99.6%) and lower error rate as 3.

关键词： Adaptation models Sensitivity Accuracy Image retrieval Semantics Noise Kalman filters Reliability Particle swarm optimization Medical diagnostic imaging

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Synthetic Simulated Environment for Discrete Manufacturing Systems: A Demonstrator Through a Computational Modeling Approach

Synthetic Simulated Environment for Discrete Manufacturing S...

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Simulation Winter Conference

作者： Silvan Marti Paulo Victor Lopes Siyuan Chen Mohan Rajashekarappa Elham Rekabi Bana Amon Göppert Mélanie Déspeisse Johan Stahre Björn Johansson Dept. of Industrial and Materials Science Chalmers University of Technology Gothenburg SWEDEN Dept. Computer Science Aeronautics Institute of Technology São José dos Campos BRAZIL Lab. for Machine Tools and Production Eng. (WZL) RWTH Aachen University Aachen GERMANY

ISBN: (数字)9798331534202

ISBN: (纸本)9798331534219

In light of the challenges posed by the often unavailability of coherent data in manufacturing for operational Artificial Intelligence (AI) decision support systems, the generation and utilization of synthetic datasets have become essential. This study introduces a simple numerical Synthetic Simulated Environment (SSE) using timed and parametrizable Petri Net (PN) modules, embedded in a Directed Acyclic Graph (DAG) structure described by an adjacency matrix to represent material flow. Implemented in PyTorch for seamless integration with AI components, our simulation framework simplifies manufacturing systems, yet remains expandable for diverse use cases. The simulation model was demonstrated displaying its capability of generating synthetic data. This approach explores the practicality and applicability of generated data. It could serve as an ideal environment to benchmark Artificial Intelligence (AI) algorithms in comparative experiments, investigating operational problems featured in the dynamic interactions of discrete manufacturing systems.

关键词： Decision support systems Directed acyclic graph Heuristic algorithms Computational modeling Petri nets Benchmark testing Data models Artificial intelligence Manufacturing systems Synthetic data

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Dielectric strength characterization in BSZT ceramic capacitors

Dielectric strength characterization in BSZT ceramic capacit...

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International Conference on Pulsed Power

作者： Lauro P. Silva Neto Rangel G. Aredes José O. Rossi Eduardo Antonelli Gustavo N. Lima Edl. Schamiloglu Joaquim J. Barroso Dept.Science and Technology Federal University of São Paulo São José dos Campos Brazil Associated Plasma Laboratory National Institute for Space Research São José dos Campos Brazil Electrical and Computer Engineering Department University of New Mexico Albuquerque USA

Ceramic capacitors are used in electronic devices that need a specific behavior or some project requirements such as temperature range, maximum voltage, dielectric strength, low loss, and others. In this work we synthesized ceramic capacitors using BSZT (Barium, Strontium, Zirconium, and Titanium) to be applied in Nonlinear Transmission Lines - NLTLs to produce high-power oscillations. In addition to sintering, we performed a dielectric strength characterization using ten samples and the Weibull distribution to determine the average dielectric strength and standard deviation. The results showed a ceramic material with dielectric strength of the order of 7.0 kV/mm and a standard deviation of +/- 1.2 kV/mm.

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Complexity-Driven Sampling for Bagging 24th

Complexity-Driven Sampling for Bagging

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24th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2023

作者： Lancho, Carmen C. P. de Souto, Marcilio Lorena, Ana C. Martín de Diego, Isaac Data Science Laboratory Rey Juan Carlos University C/ Tulipán s/n Móstoles28933 Spain Fundamental Computer Science Laboratory University of Orléans Léonard de Vinci B.P. 6759 Orleans Cedex 2F-45067 France Aeronautics Institute of Technology Praça Marechal Eduardo Gomes 50 São José dos Campos São Paulo12228-900 Brazil

ISBN: (纸本)9783031482311

Ensemble learning consists of combining the prediction of different learners to obtain a final output. One key step for their success is the diversity among the learners. In this paper, we propose to reach the diversity in terms of the classification complexity by guiding the sampling of instances in the Bagging algorithm with complexity measures. The proposed Complexity-driven Bagging algorithm complements the classic Bagging algorithm by considering training samples of different complexity to cover the complexity space. Besides, the algorithm admits any complexity measure to guide the sampling. The proposal is tested in 28 real datasets and for a total of 9 complexity measures, providing satisfactory and promising results and revealing that training with samples of different complexity, ranging from easy to hard samples, is the best strategy when sampling based on complexity. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Computational complexity

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Brazilian Engineering Research Center for the Aerial Mobility of the Future

Brazilian Engineering Research Center for the Aerial Mobilit...

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International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & International Transportation Electrification Conference (ESARS-ITEC)

作者： Domingos A. Rade Luciano J. Pedrote dos Santos Jose A. Pomilio Roberto G. Annes da Silva Carlos Henrique C. Ribeiro Alfredo Rocha de Faria Emilia Villani Mechanical Eng. Division Aeronautics Inst. of Technology Sao Jose dos Campos Brazil R&D Deptartment Embraer S.A. Sao Jose dos Campos Brazil Systems and Energy Dept. University of Campinas Campinas Brazil Aeronautics Division Aeronautics Inst. of Technology Sao Jose dos Campos Brazil Computer Science Division Aeronautics Inst. of Technology Sao Jose dos Campos Brazil

The paper describes the constitution of the Engineering Research Center for the Aerial Mobility of the Future (ERC-AMF) having ITA as the host institution, Embraer as the industrial partner, and researchers from the University of São Paulo and the University of Campinas. The objective of the ERC-AMF is the realization of R&D to contribute to overcoming challenges to the shaping of aerial mobility in the upcoming decades. These challenges arise from the necessity of reducing pollutant and noise emissions, and the need for increased efficiency of manufacturing processes, besides the trend of introducing in the market novel aircraft adapted for operation in urban environments and short-range travels. Five research areas are focused on the first operation phase of the Center: Machine Control for Electric Propulsion; Aeropropulsion Integration in Electric Aircraft; Methods for Decision Making in Autonomous Systems; Advanced Design for Metallic Additive Manufacturing; and Intelligent Aircraft Final Assembly. Each line will be developed by researchers from partner universities and engineers from Embraer. It is expected that the Center will contribute to the appropriation, by the Brazilian aeronautical industry, of scientific and technological knowledge generated, and, as a result, increase its preparedness to face challenges that shall be overcome in the process of shaping the aerial mobility of the upcoming decades.

关键词： Industries Urban areas Transportation Three-dimensional printing Manufacturing Aircraft manufacture Aircraft propulsion

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From trivium to smart education 11th

From trivium to smart education

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11th International Conference on EUropean Transnational Education, ICEUTE 2020

作者： Teira-Lafuente, Javier Gil-González, Ana Belén de Luis Reboredo, Ana Faculty of Philosophy University of Salamanca Salamanca Spain Computer Science and Automation Department University of Salamanca Plaza de los Caídos. s/n Salamanca37008 Spain

ISBN: (纸本)9783030577988

Rethinking the classics for thinking the future. This could be the compendium of the present article, in which we propose a revision of the immediate future of education based on the classic project of the Trivium. We will analyze, first, the transformation of education in the perspective of smart education, determined by the impact of technology and by the reflection on the competences of the 21st century;secondly, we will review the strategic and methodological proposals in accordance with this transformation, based on the theory of generative learning;thirdly, from the point of view of contents, we will analyse the importance of core digital skills as programming and computational thinking. On this basis, the paper offers a proposal from a dual perspective. Firstly, by rethinking the main issues of education in the light of the history of the Trivium and the epistemological principles that shaped it. Secondly, by proposing the recovery of the Trivium disciplines (Grammar, Rhetoric and Logic) having in mind the debate on the competences of the 21st century, as the best instrument to enrich the current educational systems, especially in view of the challenges of digitalization. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Computation theory

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