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arXiv 2023年

作者： Fikri, Muhamad Rausyan Candra, Taufiq Saptaji, Kushendarsyah Noviarini, Ajeng Nindi Wardani, Dilla Ayu Automation Technology and Mechanical Engineering Faculty of Engineering and Science Tampere University Tampere33720 Finland Information Systems Faculty of Engineering and Technology Sampoerna University Jakarta12780 Indonesia Industrial Engineering Faculty of Engineering and Technology Sampoerna University Jakarta12780 Indonesia Mechanical Engineering Faculty of Engineering and Technology Sampoerna University Jakarta12780 Indonesia Computer Science Faculty of Engineering and Technology Sampoerna University Jakarta12780 Indonesia

The rapid development of technology has brought unmanned aerial vehicles (UAVs) to become widely known in the current era. The market of UAVs is also predicted to continue growing with related technologies in the future. UAVs have been used in various sectors, including livestock, forestry, and agriculture. In agricultural applications, UAVs are highly capable of increasing the productivity of the farm and reducing farmers' workload. This paper discusses the application of UAVs in agriculture, particularly in spraying and crop monitoring. This study examines the urgency of UAV implementation in the agriculture sector. A short history of UAVs is provided in this paper to portray the development of UAVs from time to time. The classification of UAVs is also discussed to differentiate various types of UAVs. The application of UAVs in spraying and crop monitoring is based on the previous studies that have been done by many scientific groups and researchers who are working closely to propose solutions for agriculture-related issues. Furthermore, the limitations of UAV applications are also identified. The challenges in implementing agricultural UAVs in Indonesia are also presented. Copyright © 2023, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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A kind of epistasis-tunable test functions for genetic algorithms

A kind of epistasis-tunable test functions for genetic algor...

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作者： Mo, Hongqiang Li, Zhong Zhu, Chunmei School of Automation Science and Engineering South China University of Technology Guangzhou510641 China Faculty of Mathematics and Computer Science FernUniversitaet in Hagen Hagen58084 Germany College of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Zhongshan Institute Zhongshan528400 China

Genetic algorithm (GA) is one of the most popular algorithms of evolutionary computation. To evaluate the performance of GAs, test functions with different levels of epistasis have been included in most of the commonly used benchmark platforms. Such test functions have been produced in general by assuming an underlying linear model for the fitness of a string, in which variable interaction should be known beforehand. This paper proposes to compose epistasis-tunable test functions via linear combinations of simple basis functions so as to avoid explicit dependence on the knowledge of variable interaction. It is remarked that, for a GA with a binary encoding, a linearly separable fitness function, ie, a zero-epistasis fitness function, can be decomposed into a superposition of periodical basis functions whose frequencies are exponential to 2. A kind of epistasis-tunable test functions is accordingly produced by summing up sinusoidal basis functions with such frequencies and proper phases. The merits of thus constructed test functions are: Both the locations and values of the global maxima are trivially known;their degrees of epistasis are smoothly tunable simply by changing the locations of the global maxima. Finally, illustration examples are studied, and the results confirm the claims about the merits. © 2018 John Wiley & Sons, Ltd.

关键词： Genetic algorithms

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Self-adaptive Teaching-learning-based Optimizer with Improved RBF and Sparse Autoencoder for Complex Optimization Problems

Self-adaptive Teaching-learning-based Optimizer with Improve...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Jing Bi Ziqi Wang Haitao Yuan Junfei Qiao Jia Zhang MengChu Zhou Faculty of Information Technology Beijing University of Technology Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China Department of Computer Science Lyle School of Engineering at Southern Methodist University Dallas TX USA Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

Evolutionary algorithms are commonly used to solve many complex optimization problems in such fields as robotics, industrial automation, and complex system design. Yet, their performance is limited when dealing with high-dimensional complex problems because they often require enormous computational resources to yield desired solutions, and they may easily trap into local optima. To solve this problem, this work proposes a Self-adaptive Teaching-learning-based Optimizer with an improved Radial basis function model and a sparse Autoencoder (STORA). In STORA, a Self-adaptive Teaching-learning-based Optimizer is designed to dynamically adjust parameters for balancing exploration and exploitation during its solution process. Then, a sparse autoencoder (SAE) is adopted as a dimension reduction method to compress search space into lower-dimensional one for more efficiently guiding population to converge towards global optima. Besides, an Improved Radial Basis Function model (IRBF) is designed as a surrogate model to balance training time and prediction accuracy. It is adopted to save computational resources for improving overall performance. In addition, a dynamic population allocation strategy is adopted to well integrate SAE and IRBF in STORA. We evaluate it by comparing it with several state-of-the-art algorithms through six benchmark functions. We further test it by applying it to solve a real-world computational offloading problem.

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Portable Baby Incubator Monitoring using Smartphone

Portable Baby Incubator Monitoring using Smartphone

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International Conference on Electrical, Telecommunication and computer Engineering (ELTICOM)

作者： Nur Sultan Salahuddin Sri Poernomo Sari Nora Trisna Tumewa Aqilla Rahman Musyaffa Arif Wijaya Ema Herawati Satrio Dwi Yudhanto Ambariani Pujiati Faculty of Computer Science and Information Technology Gunadarma University Jakarta Indonesia Faculty of Industrial Technology Gunadarma University Jakarta Indonesia Multimedia And Robotics Laboratory Gunadarma University Depok Indonesia Industrial Automation Laboratory Gunadarma University Depok Indonesia Faculty of Health Sciences and Pharmacy Gunadarma University Depok Indonesia

Most neonatal deaths occur at the age of 0-6 days (78.5%) and prematurity is one of the main causes of infant death in Indonesia, ranking fifth in the number of premature births. A baby incubator is very necessary to help premature babies adapt to their new environment. An incubator is a health care tool for critical/premature neonates that provides warmth and humidity according to the needs of newborns under controlled conditions. A portable baby incubator monitoring system using wifi as a communication medium to monitor babies, equipped with a DS18B20 sensor to measure the baby’s body temperature, an AD8232 sensor to measure the baby’s heartbeat and an ESP32 Cam to capture the baby’s face has been created. The test results showed that this incubator was able to detect the baby’s body temperature, the baby’s heartbeat and take the baby’s face remotely using an Android-based smartphone, weighs around 5.8 kg, has a simple design, can be carried around making it easier for medical personnel to carry out supervision premature baby.

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Multi-swarm Genetic Gray Wolf Optimizer with Embedded Autoencoders for High-dimensional Expensive Problems

Multi-swarm Genetic Gray Wolf Optimizer with Embedded Autoen...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Jing Bi Jiahui Zhai Haitao Yuan Ziqi Wang Junfei Qiao Jia Zhang MengChu Zhou Faculty of Information Technology Beijing University of Technology Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China Department of Computer Science Lyle School of Engineering at Southern Methodist University Dallas TX USA Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

High-dimensional expensive problems are often encountered in the design and optimization of complex robotic and automated systems and distributed computing systems, and they suffer from a time-consuming fitness evaluation process. It is extremely challenging and difficult to produce promising solutions in a high-dimensional search space. This work proposes an evolutionary optimization framework with embedded autoencoders that effectively solve optimization problems with high-dimensional search space. Autoencoders provide strong dimension reduction and feature extraction abilities that compress a high-dimensional space to an informative low-dimensional one. Search operations are performed in a low-dimensional space, thereby guiding whole population to converge to the optimal solution more efficiently. Multiple subpopulations coevolve iteratively in a distributed manner. One subpopulation is embedded by an autoencoder, and the other one is guided by a newly proposed Multi-swarm Gray-wolf-optimizer based on Genetic-learning (MGG). Thus, the proposed multi-swarm framework is named Autoencoder-based MGG (AMGG). AMGG consists of three proposed strategies that balance exploration and exploitation abilities, i.e., a dynamic subgroup number strategy for reducing the number of subpopulations, a subpopulation reorganization strategy for sharing useful information about each subpopulation, and a purposeful detection strategy for escaping from local optima and improving exploration ability. AMGG is compared with several widely used algorithms by solving benchmark problems and a real-life optimization one. The results well verify that AMGG outperforms its peers in terms of search accuracy and convergence efficiency.

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Time Delay Estimation with Fixed-time SMC Scheme for Nonlinear Dynamics

Time Delay Estimation with Fixed-time SMC Scheme for Nonline...

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2024 International Conference on Control, automation and Diagnosis, ICCAD 2024

作者： Ahmed, Saim Azar, Ahmad Taher Fekik, Arezki Wang, Haoping Njima, Chakib Ben Prince Sultan University College of Computer and Information Sciences Riyadh Saudi Arabia Riyadh11586 Saudi Arabia Benha University Faculty of Computers and Artificial Intelligence Benha Egypt University Akli Mohand Oulhadj-Bouria Department of Electrical Engineering Rue Drissi Yahia Bouira 10000 Algeria Nantes Université École Centrale Nantes Cnrs LS2N Umr 6004 NantesF-44000 France Nanjing University of Science and Technology School of Automation China University of Sousse Tunisia

ISBN: (纸本)9798350361025

Time delay estimation using fixed-time terminal sliding mode control (TDEFxSMC) for unknown nonlinear systems with uncertainty and external disturbances is presented in this study. Firstly, the notion of fixed-time terminal sliding mode control (FxSMC) is outlined and thoroughly examined. Using the FxSMC scheme, nonsingular fixed-time control, non-chatter control inputs, and high performance tracking positions have been achieved. To estimate the unknown dynamics, proposed method incorporates a TDE scheme. The Lyapunov theorem is applied to find whether the proposed system can achieve its stability in a fixed-time. The effectiveness of the suggested method is evaluated and demonstrated by presenting the results of the proposed method implemented to the nonlinear robot dynamics. © 2024 IEEE.

关键词： Dynamical systems

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Comprehensive electrical models for a wireless sensor network device

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Heliyon 2024年第23期10卷 e40415页

作者： León Ávila, Bernardo Yaser García Vázquez, Carlos Alberto Pérez Baluja, Osmel Cotfas, Daniel Tudor Cotfas, Petru Adrian Transilvania University of Brașov Department of Electronics and Computers Faculty of Electrical Engineering and Computer Science Brasov 500036 Romania University of Sancti Spiritus “José Martí Pérez” Department of Computer Engineering Faculty of Business and Technical Sciences Comandante Manuel Fajardo s/n Olivos 1 Sancti Spíritus 60100 Cuba Technological University of Havana Department of Automation and Computing Faculty of Automation and Biomedical Engineering Street 114 No. 11901 between Ciclovía and Rotonda Havana 19390 Cuba

This paper proposes a novel circuit model of a Wireless Sensor Network (WSN) device. The model is designed to accurately represent the behavior of a WSN device operating in a duty cycle, capturing the essential characteristics of its components, including the microcontroller, sensor, transceiver, and power supply. The proposed model incorporates static and dynamic power consumption aspects, reflecting the energy usage patterns during various operational states such as sensing, processing, and communication. The model's accuracy is validated through a comparative analysis with a LTspice® implementation and a real mote implemented for this study. Simulation results closely match the empirical data, demonstrating the model's effectiveness in predicting the mote's behavior. This approach provides a valuable tool for optimizing power consumption and extending the lifetime of WSN deployments within a simulation environment, offering significant insights for designers and researchers in this field. © 2024 The Authors

关键词： Electric model SPICE model Wireless sensor network node

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An asymptotic formula for Aldaz-Kounchev-Render operators on the hypercube

arXiv

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arXiv 2023年

作者： Acu, Ana-Maria Raşa, Ioan Lucian Blaga University of Sibiu Department of Mathematics and Informatics Romania Technical University of Cluj-Napoca Faculty of Automation and Computer Science Department of Mathematics Str. Memorandumului nr. 28 Cluj-Napoca400114 Romania

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Searching for better spatio-temporal alignment in few-shot action recognition 22

Searching for better spatio-temporal alignment in few-shot a...

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Proceedings of the 36th International Conference on Neural Information Processing Systems

作者： Yichao Cao Xiu Su Qingfei Tang Shan You Xiaobo Lu Chang Xu School of Automation Southeast University School of Computer Science Faculty of Engineering The University of Sydney Enbo Technology Co. Ltd. China SenseTime Research

ISBN: (纸本)9781713871088

Spatio-Temporal feature matching and alignment are essential for few-shot action recognition as they determine the coherence and effectiveness of the temporal patterns. Nevertheless, this process could be not reliable, especially when dealing with complex video scenarios. In this paper, we propose to improve the performance of matching and alignment from the end-to-end design of models. Our solution comes at two-folds. First, we encourage to enhance the extracted Spatio-Temporal representations from few-shot videos in the perspective of architectures. With this aim, we propose a specialized transformer search method for videos, thus the spatial and temporal attention can be well-organized and optimized for stronger feature representations. Second, we also design an efficient non-parametric spatio-temporal prototype alignment strategy to better handle the high variability of motion. In particular, a query-specific class prototype will be generated for each query sample and category, which can better match query sequences against all support sequences. By doing so, our method SST enjoys significant superiority over the benchmark UCF101 and HMDB51 datasets. For example, with no pretraining, our method achieves 17.1% Top-1 accuracy improvement than the baseline TRX on UCF101 5-way 1-shot setting but with only 3x fewer FLOPs.

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Modelling and automation of a process for obtaining coagulum in treatment of industrial 15

Modelling and automation of a process for obtaining coagulum...

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15th Global Congress on Manufacturing and Management, GCMM 2021

作者： Safonyk, A. Tarhonii, I. Burduk, A. Batako, A. National University of Water and Environmental Engineering Department of the Automation Electrotechnical and Computer-Integrated Technologies Soborna str. Rivne33028 Ukraine Wroclaw University of Science and Technology Faculty of Mechanical Engineering Wybrzeze Wyspianskiego 27 Wroclaw50-370 Poland Faculty of Engineering and Technology Liverpool John Moores University Byrom Street LiverpoolL3 3AF United Kingdom

This paper present the development a model for obtaining a coagulant for the process of cleaning and discoloration of industrial waste water and the development of a PID automated system for wastewater treatment. The description of the processes taking place in an electro-coagulator is given along with the solution obtained by model. The influence of current on the concentration of divalent iron water temperature is investigated. The algorithm of two-circuit regulation of concentration of pollution in sewage with the feedback current between the coagulator plates and the concentration pollutants in the water entering the automated purification system is developed. The automated control system for wastewater treatment process with the implementation of the coagulant forecasting algorithm in relation to the input pollution concentration is developed. The control of current magnitude in the electro-coagulator with minimal electricity consumption was realized. It is planned to manage the system with the ability to change the performance of the entire installation in real time using the SCADA - system. © Published under licence by IOP Publishing Ltd.

关键词： SCADA systems

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