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International Workshop on Secure Internet of Things (SIoT)

作者： Alexandre Bellargus S. Costa Joaci Campos S. Neto Rafaella C. Santos Deodato V. Bastos Neto Cecilia A. C. Cesar Computer Science Division Technological Institute of Aeronautics São José dos Campos Brazil

ISBN: (数字)9798331507466

ISBN: (纸本)9798331507473

The pandemic has brought as a legacy a vast growth in online teaching that must use strategies different from in-person teaching. In both environments, it is crucial for learning to capture the student's attention and propose activities that maintain the necessary focus. However, it is difficult to capture attention in real life due to inexperienced teachers, classrooms with many students, students with too many other activities, their attention divided with other electronic devices, or simply a lack of interest in the topic. It is possible to support this complex scenario with technology. Some proposals for using technology to monitor attention require using headbands; others harm students' privacy. In this proposal, we have a camera measuring the room's attention that does not perform facial recognition but uses AI to calculate the position of the students' faces, indicating their engagement. An application for the teacher available during the class summarizes what the system captures and can suggest actions for improvement. The data is also processed in an application for managers. Initial tests indicated helpful support for the teacher to better interact with the students and for successful learning.

关键词： Privacy Refining Prototypes Position measurement Social Internet of Things Planning Proposals Synchronization Monitoring Testing

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INTEGRATING DYNAMIC DIGITAL TWINS: ENABLING REAL-TIME CONNECTIVITY FOR IOT AND VIRTUAL REALITY

INTEGRATING DYNAMIC DIGITAL TWINS: ENABLING REAL-TIME CONNEC...

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2024 Winter Simulation Conference, WSC 2024

作者： Erdal, Lejla Gubartalla, Ammar Lopes, Paulo Victor Cao, Huizhong Shao, Guodong Lonnehed, Per Putto, Henri Ahmed, Abbe Ekered, Sven Johansson, Björn Dept. of Industrial and Materials Science Chalmers University Gothenburg Sweden Dept. Computer Science Aeronautics Institute of Technology São José dos Campos Brazil NIST GaithersburgMD United States 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. © 2024 IEEE.

关键词： Application programs

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Motion Consistency Loss for Monocular Visual Odometry with Attention-Based Deep Learning

arXiv

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arXiv 2024年

作者： Françani, André O. Maximo, Marcos R.O.A. Computer Science Division Aeronautics Institute of Technology SP São José dos Campos Brazil

Deep learning algorithms have driven expressive progress in many complex tasks. The loss function is a core component of deep learning techniques, guiding the learning process of neural networks. This paper contributes by introducing a consistency loss for visual odometry with deep learning-based approaches. The motion consistency loss explores repeated motions that appear in consecutive overlapped video clips. Experimental results show that our approach increased the performance of a model on the KITTI odometry *** Codes 68T45 68T07 © 2024, CC BY.

关键词： Vision

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Improving Explainability of the Attention Branch Network with CAM Fostering Techniques in the Context of Histological Images 26

Improving Explainability of the Attention Branch Network wit...

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26th International Conference on Enterprise Information Systems, ICEIS 2024

作者： Miguel, Pedro Lucas Lumini, Alessandra Medalha, Giuliano Cardozo Roberto, Guilherme F. Rozendo, Guilherme Botazzo Cansian, Adriano Mauro Tosta, Thaína A.A. do Nascimento, Marcelo Z. Neves, Leandro A. Department of Computer Science and Statistics São Paulo State University SP São José do Rio Preto Brazil Department of Computer Science and Engineering University of Bologna Italy 325 SP São José do Rio Preto15084-010 Brazil Faculty of Engineering University of Porto Porto Portugal Institute of Science and Technology Federal University of São Paulo SP São José dos Campos Brazil Faculty of Computer Science Federal University of Uberlândia MG Uberlândia Brazil

ISBN: (纸本)9789897586927

Convolutional neural networks have presented significant results in histological image classification. Despite their high accuracy, their limited interpretability hinders widespread adoption. Therefore, this work proposes an improvement to the attention branch network (ABN) in order to improve its explanatory power through the gradient-weighted class activation map technique. The proposed model creates attention maps and applies the CAM fostering strategy to them, making the network focus on the most important areas of the image. Two experiments were performed to compare the proposed model with the ABN approach, considering five datasets of histological images. The evaluation process was defined via quantitative metrics such as coherency, complexity, confidence drop, and the harmonic average of those metrics (ADCC). Among the results, the proposed model through the ResNet-50 was able to provide an improvement of 4.16% in the average ADCC metric and 3.88% in the coherence metric when compared to the respective ABN model. Considering the DesneNet-201 network as the explored backbone, the proposed model achieved an improvement of 14.87% in the average ADCC metric and 9.77% in the coherence metric compared to the corresponding ABN model. The contributions of this work are important to make the results via computer-aided diagnosis more comprehensible for clinical practice. Copyright © 2024 by SCITEPRESS – science and Technology Publications, Lda.

关键词： Image enhancement

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Modeling Risk Prioritization of a Manufacturing Supply Chain using Discrete Event Simulation

Modeling Risk Prioritization of a Manufacturing Supply Chain...

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2023 Winter Simulation Conference, WSC 2023

作者： Chari, Arpita Marti, Silvan Johansson, Björn Despeisse, Mélanie Stahre, Johan Lopes, Paulo Victor Chalmers University of Technology Department of Industrial and Materials Science Hörsalsvägen 7a Gothenburg41296 Sweden Computer Science Division Praça Marechal Eduardo Gomes 50 São José dos Campos12228-900 Brazil

ISBN: (纸本)9798350369663

Supply chains face a myriad of adverse risks that impact their daily operations and make them vulnerable. In addition, supply chains continue to grow in size and complexity which further sophisticates the problem. Lack of a structured approach and limitations in existing risk management methods contribute towards effective mitigation strategies not being properly developed. In this paper, we develop a discrete event simulation modelling approach to quantify the performance and risk assessment of a manufacturing supply chain in Sweden which is under the impact of risks. This approach could support decision makers by prioritizing risks according to their performance impact and facilitating the development of mitigation strategies to enhance the resilience of the supply chain. The conceptual digital model can also be used to generate synthetic data to build an artificial intelligence-enhanced predictive demonstrator model to showcase capabilities for building data-driven resilience of the supply chain. © 2023 IEEE.

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Dielectric strength characterization in BSZT ceramic capacitors

Dielectric strength characterization in BSZT ceramic capacit...

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2023 IEEE Pulsed Power Conference, PPC 2023

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

ISBN: (纸本)9798350332339

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. © 2023 IEEE.

关键词： Weibull distribution

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A Minimalist Open Source Behavior Tree Framework in C++ 18

A Minimalist Open Source Behavior Tree Framework in C++

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18thLatin American Robotics Symposium, 13th Brazilian Symposium on Robotics, and 12th Workshop on Robotics in Education, LARS-SBR-WRE 2021

作者： Silva, Gustavo L. Maximo, Marcos R. O. A. Pereira, Lourenco A. Computer Science Division SP São José dos Campos Brazil

ISBN: (纸本)9781665407618

Decision making is one of the most important topics in agent related environments, like video games and robotics competitions. Among many agent behavior architectures, behavior trees became the standard in the scientific and industrial community, due to their modular and extensible properties. In this work, we developed an open source behavior tree framework in C++. This framework benefits from the large experience our robotics team, ITAndroids, has using behavior trees in robot soccer competitions. Its implementation is minimalist, but easily extensible since we needed to accommodate requirements from different projects in our team. We also show tests and application examples of this framework. Despite being developed with robotics competitions in mind, we believe it may be easily integrated into many applications where intelligent agents are needed. We were able to create a simple, intuitive, and efficient structure, which can be easily implemented and extended. © 2021 IEEE.

关键词： Decision making

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Exploring Differential Privacy in Practice 23

Exploring Differential Privacy in Practice

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23rd International Conference on Enterprise Information Systems, ICEIS 2021

作者： Hasuda, Davi Grossi de Melo Bezerra, Juliana Computer Science Department ITA São José dos Campos Brazil

ISBN: (纸本)9789897585098

Every day an unimaginable amount of data is collected from Internet users. All this data is essential for designing, improving and suggesting products and services. In this frenzy of capturing data, privacy is often put at risk. Therefore, there is a need for considering together capturing relevant data and preserving the privacy of each person. Differential Privacy is a method that adds noise in data in a way to keep privacy. Here we investigate Differential Privacy in practice, aiming to understand how to apply it and how it can affect data analysis. We conduct experiments with four classification techniques (including Decision Tree, Näive Bayes, MLP and SVM) by varying privacy degree in order to analyze their accuracy. Our initial results show that low noise guarantees high accuracy;larger data size is not always better in the presence of noise;and noise in the target does not necessary disrupt accuracy. Copyright © 2021 by SCITEPRESS – science and Technology Publications, Lda. All rights reserved.

关键词： Decision trees

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A Blockchain Approach to Support Vaccination Process in a Country 23

A Blockchain Approach to Support Vaccination Process in a Co...

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23rd International Conference on Enterprise Information Systems, ICEIS 2021

作者： Carniel, Andrei Leme, Gustavo de Melo Bezerra, Juliana Hirata, Celso Massaki Computer Science Department ITA São José dos Campos Brazil

ISBN: (纸本)9789897585098

Vaccines are important means to prevent diseases and save lives. Data related to vaccination process, such as vaccine identification and number of vaccinated people, is critical to the production and distribution of vaccines in a way to achieve the desired immunization in a country. We propose a reliable approach based on Blockchain to manage vaccination data. We describe the roles played in a vaccination process as well as their relations. Aiming to validate our approach with a prototype, we present the data required in two scenarios, including the registration of a vaccine administration and the visualization of the vaccination history of a citizen. We discuss the potential of our proposal, by indicating analysis that can be conducted with the vaccination data, as well as challenges to be addressed in further investigations. Copyright © 2021 by SCITEPRESS – science and Technology Publications, Lda. All rights reserved.

关键词： Vaccines

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Advanced Social Internet of Things for Real Time Monitoring of Diabetics Patient in Healthcare System

Advanced Social Internet of Things for Real Time Monitoring ...

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2021 International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2021

作者： Santhosh Kumar, K S Hanumantappa, J. Chikkoppa, Balachandra G. University of Mysore DoS in Computer Science Mysuru India KLE Institute of Technology Department of Computer Science and Engineering Hubballi India

ISBN: (纸本)9781665425032

Health monitoring has become a crucial aspect in this modern era of society. Various traditional approaches being used in this has their own limitations in terms of data collection and data transfer across public networks. With the advancements in IoT for cloud platforms, many of the research is being carried out in this area. In our proposed model, we accumulate the various parameters of the patients such as pulse rate, glucose level, temperature and blood pressure using Ardunio UNO. The collected data is preprocessed to compute the dominating features resulting for diabetics using Principal Component Analysis (PCA). These features are pushed to the public cloud in real time and machine learning models can be used to notify the patients and hospital authorities for the severity of the patient. In our experiment we have used Support Vector Machine as Training Model. The experiments resulted with an accuracy of upto 96.80%. © 2021 IEEE.

关键词： Blood pressure

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