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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Teixeira, Natalia S. Pastrana, M.A. Moura, Henrique G. Munoz, Daniel M. University of Brasilia Faculty of Gama Automotive Engineering Undergraduate Program Brasilia Brazil University of Brasilia Department of Mechanical Engineering Mechatronics Graduate Program Brasilia Brazil University of Brasilia Faculty of Gama Electronics Engineering Undergraduate Program Brasilia Brazil

ISBN: (纸本)9798350374575

Vibration analysis is crucial for predictive maintenance of bearing systems, aiming to reduce costs and prevent failures. This paper investigates signal processing techniques such as FFTs and Hilbert Transforms for fault diagnosis, alongside decision tree models, particularly the J48 algorithm within the WEKA environment, for fault classification. The study emphasizes the integration of signal processing and machine learning for effective fault diagnosis and maintenance. Notably, a classification model with low computational cost has been chosen, facilitating implementation in embedded systems. This model also offers interpretability of outputs, as it is based on decision trees of frequency components obtained through preprocessing. © 2024 IEEE.

关键词： Predictive maintenance

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Sub-optimal Perceptron Controller Using WOA Algorithm for Farming Watering Mobile Robot

Sub-optimal Perceptron Controller Using WOA Algorithm for Fa...

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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Pastrana, M.A. Oliveira, L.H. Bautista, J. Pinto-Lopera, Jesus Mendoza-Penaloza, Jose Munoz, Daniel M. University of the Amazonia Faculty of Engineering Systems Undergraduate Program Florencia Caquetá Colombia University of Brasilia Mechatronics Graduate Program Department of Mechanical Engineering Brasilia Brazil University of Brasilia Faculty of Gama Electronics Engineering Undergraduate Program Brasilia Brazil

ISBN: (纸本)9798350374575

Artificial neural networks (ANNs) are intricate mathematical models, drawing inspiration from the biological nervous system, and offering intelligence alongside nonparametric capabilities. The efficacy of ANNs heavily relies on their learning process. Heuristic search algorithms have been proposed in literature as reliable options for optimizing neural networks utilizing the Perceptron architecture. This paper presents an suboptimal neural network Perceptron training method employing the Whale Optimization Algorithm for the application of farming watering mobile robots. To achieve this, a fitness function based on system responses such as overshoot, settling Time, and steady-state Error was developed. The sub-optimal Perceptron controller was then implemented using MATLAB, CoppeliaSim software and the EVA robot, resulting in a 66.17% overshoot, a 4.7% steady-state error, and a settling time of 3.05 seconds. Moreover, the sub-optimal Perceptron controller was mapped onto a System on Chip FPGA AMD-Xilinx Zynq 7020, resulting in a hardware resources consumption of 1,870 (3.52%) Lookup table, 2 (0.9%) Digital Signal Processing blocks, 1,019 (0.96%) Flip-Flops and a power consumtion of 0.005 W. Finally, Hardware-in-The-Loop validation was performed using CoppeliaSim, Python, Universal Direct Memory Access, and the EVA robot. The results showed an overshoot of 94.83%, a settling time of 2 seconds, and a steady-state error of 4.5%. © 2024 IEEE.

关键词： MATLAB

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Design and Performance Comparison of Low Dropout Regulators for a 32-bit Microcontroller Using 22nm Technology 16

Design and Performance Comparison of Low Dropout Regulators ...

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16th IEEE Latin American Symposium on Circuits and Systems, LASCAS 2025

作者： Johnson, Emmanuel K. M. Lima, Luis Victor N. Campagnucci, Pamela. R. A. N. Haddad, Sandro A. P. Amaral, Wellington A. Munoz, Daniel M. University of Brasilia Mechatronics Graduate Program Department of Mechanical Engineering DF Brasilia Brazil University of Brasilia Faculty of Gama Electronics Engineering Undergraduate Program DF Brasilia Brazil

ISBN: (纸本)9798331522124

This paper presents a comparison between two LDOs (Low Dropout Regulators) developed for a PMIC (Power Management Integrated Circuit) responsible for powering a 32-bit microcontroller based on the RISC-V microarchitecture, designed in 22 nm technology. The microcontroller will be integrated with a radio frequency interface for IoT (Internet of Things) applications. Two LDOs were designed: one with external compensation and the other a capacitor-less LDO. Both operate with an input voltage of 2.5V, an output voltage of 0.8V, and a maximum current of 150mA. The externally compensated LDO exhibited greater stability in response to load variations and a higher PSRR (Power Supply Rejection Ratio), while the capacitor-less LDO demonstrated faster regulation speed and occupied a chip area similar to the externally compensated LDO. © 2025 IEEE.

关键词： Low power electronics

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Project Edubot: Exploring Pedagogical Approaches in High School Robotics Education 16

Project Edubot: Exploring Pedagogical Approaches in High Sch...

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16th Brazilian Symposium on Robotics and 15th Workshop on Robotics in Education, SBR-WRE 2024

作者： Nunes Daltro, Isabela Silva Santos, João Victor de Sousa, Guilherme Barbosa Martins, Rodrigo Pastrana, M.A. de Souza Baptista, Roberto Mechatronics Engineering Undergraduate Program University of Brasilia DF Brasilia Brazil Department of Mechanical Engineering Mechatronics Graduate Program University of Brasilia DF Brasilia Brazil Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia DF Brasilia Brazil

ISBN: (纸本)9798350391084

This study focus on passive and active learning within the context of robotics education on public high schools. By synthesizing research findings and practical insights, this paper offers valuable recommendations for educators aiming to optimize the delivery of robotics education in public high schools, addressing the significance of the utilization of appropriate resources and technologies to support effective instruction. We implemented two distinct teaching methodologies to compare and study students’ reactions and learning outcomes: Group A experienced a passive methodology, while Group B engaged with an active methodology. We conducted a survey and the results show that the majority of the students prefer the active approach used in classes. ©2024 IEEE.

关键词： Contrastive Learning

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Hybrelastic: a hybrid elasticity strategy with dynamic thresholds for microservice-based cloud applications

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International Journal of Cloud Computing 2024年第2期13卷 99-123页

作者： Accorsi, José Augusto da Rosa Righi, Rodrigo Rodrigues, Vinicius Facco da Costa, Cristiano André Singh, Dhananjay Applied Computing Graduate Program Universidade do Vale do Rio dos Sinos RS São Leopoldo Brazil Department of Electronics Engineering Hankuk University of Foreign Studies Yongin17035 Korea Republic of

Microservices-based architectures aim to divide the application’s functionality into small services so that each one of them can be scaled, managed, implemented, and updated individually. Currently, more and more microservices are used in application modelling, making them compatible with resource elasticity. In the literature, solutions employ elasticity to improve application performance;however, most of them are based on CPU utilisation metrics and only on reactive elasticity. In this context, this article proposes the hybrelastic model, which combines reactive and proactive elasticity with dynamically calculated thresholds for CPU and network metrics. The article presents three contributions in the context of microservices: 1) combination of two elasticity policies;2) use of more than one elasticity evaluation metric;3) use of dynamic thresholds to trigger elasticity. Experiments with hybrelastic demonstrate 10.31% higher performance and 20.28% lower cost compared to other executions without hybrelastic. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Elasticity

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Utilizing Mobile Robots to Teach Dengue and Chikungunya Prevention in Brazilian Schools 16

Utilizing Mobile Robots to Teach Dengue and Chikungunya Prev...

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16th Brazilian Symposium on Robotics and 15th Workshop on Robotics in Education, SBR-WRE 2024

作者： Costa, R.B. Gomes, Pedro H.L. Rodriguez Silva, Luiz F. Pastrana, M.A. Gontijo, Maria C.C. Luiz, M.S. Muñoz, Daniel M. Department of Mechanical Engineering Mechatronics Graduate Program University of Brasilia DF Brasilia Brazil Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia DF Brasilia Brazil Faculty of Gama Aerospace Engineering Undergraduate Program University of Brasilia DF Brasilia Brazil

ISBN: (纸本)9798350391084

This paper introduces a novel approach to combating the spread of Dengue and Chikungunya, two prevalent arboviruses in tropical regions, especially in Brazil. The research presents a low-cost differential topology robot designed as an educational tool to raise awareness about mosquito breeding grounds among students and teachers in public schools across the Federal District, Brazil. Developed at the University of Brasilia, the robot is deployed in collaboration with the Federal District Health Department to support prevention campaigns in schools. The paper evaluates the effectiveness of this innovative tool in enhancing community engagement and improving health outcomes. The findings suggest that integrating robotics into health education can significantly elevate awareness and strengthen prevention strategies against arboviral diseases. ©2024 IEEE.

关键词： Mobile robots

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Quantitative Analysis of Ankle Spasticity Through Electromyography Signal

Quantitative Analysis of Ankle Spasticity Through Electromyo...

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2024 Medical Technologies Congress, TIPTEKNO 2024

作者： Gurluk, Ayse Bilal, Hafiz Muhammad Hocaoglu, Elif Living Robotics Laboratory Graduate School of Health Sciences Physiotherapy and Rehabilitation Program Istanbul Medipol University Istanbul Turkey Living Robotics Laboratory Graduate School of Engineering and Natural Sciences Electrical-Electronics Engineering and Cyber-Systems Program Istanbul Medipol University Istanbul Turkey Living Robotics Laboratory Department of Electrical and Electronics Engineering Istanbul Medipol University Istanbul Turkey

ISBN: (纸本)9798331529819

This study presents a more accurate evaluation method for assessing ankle spasticity compared to conventional goniometric techniques by utilizing measurements obtained from Inertial Measurement Units (IMU) and surface electromyography (sEMG) devices. Integrating IMU and EMG sensors provides substantial benefits for accurately determining the range of motion (ROM) associated with spasticity during targeted movements. In this study, the proposed method provides precise measurement and an objective evaluation of onset time detection of antagonistic muscle co-contraction, and accordingly the ROM of the actuated joint. Moreover, the implementation of cost-effective wearable sensors enables the monitoring of muscle spasticity in clinical environments and can be particularly valuable in regions with limited access to experienced therapists, providing a more efficient approach to tracking spasticity levels. © 2024 IEEE.

关键词： Electromyography

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Improving Control Theory Education Through Face-to-Face Implementation of a Mobile Robotics Methodology 16

Improving Control Theory Education Through Face-to-Face Impl...

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16th Brazilian Symposium on Robotics and 15th Workshop on Robotics in Education, SBR-WRE 2024

作者： Pastrana, M.A. Cuéllar Sánchez, William Humberto Mendoza-Peñaloza, Jose Santana, M.S. Muñoz, Daniel M. Department of Mechanical Engineering Mechatronics Graduate Program University of Brasilia DF Brasilia Brazil Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia DF Brasilia Brazil University of Federal District UDF DF Brasilia Brazil

ISBN: (纸本)9798350391084

Advances in information and communication technologies have significantly transformed engineering education. Virtual laboratories are increasingly adopted to enhance student interaction with control system simulations. The improved visualization and interaction capabilities of modern computers offer a more organic way to teach theoretical foundations. This paper describes the implementation of a methodology for teaching control theory that until now was entirely online in a face-to-face environment at the University of the Federal District in Brasilia, Brazil. This methodology utilizes virtual laboratories with CoppeliaSim, MATLAB, and the EVA mobile robot to teach control theory focused on single-input, single-output (SISO) systems for mobile robot tracking and obstacle avoidance applications. The results of the face-to-face implementation are compared to those of the fully online methodology, revealing that in-person teaching significantly enhances the quality of instruction. ©2024 IEEE.

关键词： MATLAB

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Fuzzy Logic for Assessing the Health of a Corn Crop within Family Farming

Fuzzy Logic for Assessing the Health of a Corn Crop within F...

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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Mendonca, Vanessa Santos, Mikael Munoz, Daniel M. Humberto Llanos, Carlos Federal Institute of Brasilia Department of Computer Science Brazil Mechatronics Graduate Program Department of Mechanical Engineering Brazil Federal Institute of Brasilia Department of Agronomy Brazil University of Brasilia Faculty of Gama Electronics Engineering Undergraduate Program Brasilia Brazil

ISBN: (纸本)9798350374575

Technological advancements are increasingly evident across various sectors, including automobiles, industry, and healthcare. In precision agriculture, significant progress has been made, with AgroTICs and Smart Agriculture gaining substantial traction in the market. However, a gap remains between cutting-edge technology and family farming, presenting a challenge from both social and applied research perspectives. However, there is still a gap between cutting-edge technology and family farming, which creates a challenge from a social and applied research point of view. In this context, this paper proposes a monitoring model based on Fuzzy Logic and sensor automation applied to estimate the health of a corn crop. The proposed Fuzzy inference system involves calculating an indicator of nutrients as well as the average color and area of corn plants. The nutrient indicator is automatically computed by an ESP32 microcontroller using sensor readings, while the average color and area inputs are manually entered via a mobile application. Additionally, the Fuzzy inference is integrated into the ESP32. The model underwent experimental validation on the health of the plantation, and the results were evaluated in four areas: one was designated for testing, and three were for validation. The model achieved an accuracy of 97.5% in Scenario 3, categorized as 'Very Favorable', and an accuracy of 65% in Scenarios 2 and 4, categorized as 'Unfavorable'. The implications of this research contribute to the advancement of AgroTICs among small producers, with the potential to enhance and automate the monitoring of their harvest production. © 2024 IEEE.

关键词： Agribusiness

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Multiplexed Nanoscopy via Buffer Exchange

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ACS Nano 2024年第34期18卷 23445-23456页

作者： Chang, Ting-Jui Ben Yang, T. Tony Department of Electrical Engineering National Taiwan University Taipei10617 Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei10617 Taiwan Department of Physics National Taiwan University Taipei10617 Taiwan Nano Science and Technology Program Taiwan International Graduate Program Academia Sinica and National Taiwan University Taipei10617 Taiwan

Understanding cellular functions, particularly in their intricate complexity, can greatly benefit from the spatial mapping of diverse molecules through multitarget single-molecule localization microscopy (SMLM). Existing methodologies, primarily restricting the encoding dimensions to color and lifetime or requiring cyclic staining, often involve broad chromatic detection, specialized optical configurations, or sophisticated labeling techniques. Here, we propose a simple approach called buffer-exchange stochastic optical reconstruction microscopy (beSTORM), which introduces an additional dimension to differentiate between single molecules irrespective of their spectral properties. This method leverages the distinguishable photoblinking responses to distinct buffer conditions, offering a straightforward yet effective means of fluorophore discrimination. Through buffer exchanges, beSTORM achieves multitarget SMLM imaging with minimal crosstalk. Direct integration with expansion microscopy (ExM) demonstrates its capability to resolve up to six proteins at the molecular level within a single emission color without chromatic aberration. Overall, beSTORM presents a highly compatible imaging platform, promising significant advancements in highly multiplexed nanoscopy for exploring multiple targets in biological systems with nanoscale precision. © 2024 The Authors. Published by American Chemical Society.

关键词： Stochastic systems

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