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检索条件"任意字段=2nd International Conference on Automation, Robotics and Computer Engineering, ICARCE 2023"

共 908 条记录，以下是51-60 订阅

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Proton Exchange Membrane Fuel Cell Performance Decay Prediction Based on Relieff and Long Short-term Memory

Proton Exchange Membrane Fuel Cell Performance Decay Predict...

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automation, robotics and computer engineering (icarce), international conference on

作者： Guofeng Xie Wenyang Qin School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China School of Mechanical Automation Wuhan University of Science and Technology Wuhan China

The PEMFC performance decay are closely linked to fuel cell maintenance and energy management. Existing PEMFC performance decay prediction algorithms generally have the problem of single feature selection, which cannot adapt to multiple operating conditions. In order to better predict attenuation under multiple operating conditions, this paper proposes a degradation prediction method based on the combination of Relieff's feature selection algorithm and the LSTM network, where Relieff selects the parameters that have high correlation with the degradation of the performance according to the operating parameters of the different conditions as the inputs of the LSTM prediction model in order to make this model more effective. The method's prediction performance is validated using real PEMFC experimental data. The experimental results confirm that the model can effectively selects attenuation-related indicators as input for LSTM, thereby enhancing the accuracy of the PEMFC performance prediction method across various operating conditions.

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Dual-Path Neural Networks Enabled Fetal ECG Extractions From Abdominal Electrohysterograpgy

Dual-Path Neural Networks Enabled Fetal ECG Extractions From...

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automation, robotics and computer engineering (icarce), international conference on

作者： Yiwei Lin Zhenqin Chen Kaixiao Zheng Luyi Ruan Jinshan Xu College of Computer Science Zhejiang University of Technology Hangzhou China

Fetal heart monitoring is crucial for the early detection of potential risks to fetal health conditions. However, the non-invasive fetal heart monitoring technology using maternal abdominal electrocardiography (AECG) is susceptible to interference from maternal electrocardiography (MECG) and multi-source noise. To address the above challenge, we propose a novel Dual-path Encoder-Decoder Model to extract fetal electrocardiography (FECG) signals from maternal abdominal recordings. It can effectively separate and remove MECG interference to obtain FECG. Additionally, a Feature Augmentation Module based on attention-guided is introduced to optimize the quality of the remaining features after MECG removal. Finally, the optimized features are fed into a decoder with external skip connections to reconstruct the FECG signal. Experimental results show that the proposed method achieves outstanding performance on two public datasets, providing an effective solution for fetal health monitoring and assisting physicians in diagnosing fetal abnormalities.

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Role of robotics and automation in Food Industries: An Overview 2

Role of Robotics and Automation in Food Industries: An Overv...

引用

2nd international conference on Advancements in Electrical, Electronics, Communication, Computing and automation, ICAECA 2023

作者： Raffik, R. Roshan, R.P. Subash, C. Sanjeev, K.B. Mechatronics Engineering Kumaraguru College of Technology Coimbatore India

ISBN: (纸本)9798350306811

Food is grown, produced, prepared, packaged, stored, distributed, and consumed. The food industries have lagged behind other industrial sectors in integrating robots;the cost of labour can account for up to half of the overall cost of the product. Robots are reprogrammable, multifunctional manipulators designed to manipulate particles. Robots work with the consideration of hygiene and greater productivity, and food safety and hygiene are becoming an increasing concern and customer demand. In the food sector, AI and machine learning are employed for robots and automation. Robots utilize sensors to detect touch, smell, measure, and so on. A detailed analysis of automated systems and robotics in the food industry is given in this study. The advantages are that robots win out in effectiveness and accuracy over people and cannot be distracted from the task. Never get tired like humans, and never get bored by repetition. The drawbacks include job losses and the loss of people's key skills. The significance of automation systems in the food processing sector was briefly discussed in this study. © 2023 IEEE.

关键词： Manipulators

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Assessment of a Modular Upper-Limb Exoskeleton with Powered Assistance

Assessment of a Modular Upper-Limb Exoskeleton with Powered ...

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automation, robotics and computer engineering (icarce), international conference on

作者： Kaida Wu Peihao Xiang Rodrigo Ramon Aparna Aravelli Leonel Lagos Ou Bai Department of Electrical and Computer Engineering Florida International University Miami FL USA Applied Research Center Florida International University Miami FL USA

Upper extremity exoskeletons can provide support to workers for carrying tasks while reducing workers’ muscle fatigue and the prevalence of work-related musculoskeletal disorders in workers’ elbows. Nevertheless, current upper-limb exoskeletons suffer from issues like excessive weight, inconvenient wearability, high rigidity, poor human-machine interaction, and limited modularity. To address these issues, this study introduces a design for a lightweight, powered-assistive, and modular upper-limb exoskeleton. The research developed a prototype specifically tailored for the elbow joint. The experiment encompassed three control modes (Constant torque, Gravity compensation, and Impedance control) to assess the efficacy of the exoskeleton. Subjects engaged in “pick-hold-drop” tasks with varying loads (4kg, 3kg, 2kg), simulating real load-bearing scenarios, performed five times. The experimental results indicate that the proposed design provided effective assistance to the subjects. During the “hold” phase, the EMG Maximum Voluntary Contraction (MVC) values of the subjects’ biceps muscles notably decreased, averaging a reduction of 9.29%.

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Real Time Violence Detection Using Autonomous Intelligent Surveillance Robot 2

Real Time Violence Detection Using Autonomous Intelligent Su...

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2nd international conference on Advancements in Electrical, Electronics, Communication, Computing and automation, ICAECA 2023

作者： Aishwarya, Shree J. Hari, Ram Karthik M. Richie, Soshan E. Sudhakar, R. Sri Ramakrishna Engineering College Robotics and Automation Engg. Coimbatore India

ISBN: (纸本)9798350306811

Intelligent surveillance robots dominate the entire world with its efficiency and accuracy helping in performing dangerous *** surveillance robot helps to survey the area. The violence keeps on growing day by *** paper presents an intelligent surveillance robot capable of detecting and preventing violence in two modes - motion-controlled and autonomous. The motion-controlled mode allows the user to manually control the robot's movement and camera orientation, while the autonomous mode allows the robot to navigate and monitor the environment independently. In both modes, the robot employs a deep learning algorithm taken from CNN and LSTM for accurately detecting violence and sending a notification through email with the image of the violent *** a authenticated dataset, the proposed concept has been examined, the outcomes looks promising in regards to accuracy and *** integration of motion control and autonomous operation modes makes the surveillance robot versatile and effective in a range of surveillance scenarios. Overall, this project demonstrates the potential of machine learning and robotics for enhancing security and surveillance measures. © 2023 IEEE.

关键词： Long short-term memory

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An approach of using contexts for in-home activity recognition and forecast 2

An approach of using contexts for in-home activity recogniti...

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2nd international conference on Control, automation and robotics, ICCAR 2016

作者： Le, Tien Nguyen, Duy Nguyen, Son School of Computer Science and Engineering IU VNU Ho Chi Minh City Viet Nam Dept. of Information Technology Bolt Institute Binh Duong University Thu Dau Mot City Binh Duong Province Viet Nam Dept. of Computer Engineering UIT VNU Ho Chi Minh City Viet Nam

ISBN: (纸本)9781467398596

Smart home is one of the most important applications of ubiquitous computing. In this work, we propose an infrastructure of Vietnamese Smart homes as well as a training framework for activity recognition and forecast. In this framework, active learning technique is applied and a new mining algorithm is proposed. In addition to activity recognition, a forecast mechanism is also added into the smart home simulation system by using activity sequence as an extra type of in-home contexts. Experiment results show that the system efficiency is improved when compared to the previous work of Enamul Hoque et al. © 2016 IEEE.

关键词： Ubiquitous computing

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An enhanced Active Reinforcement Learning for Autonomous robotics in Industrial automation 2

An enhanced Active Reinforcement Learning for Autonomous Rob...

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2nd IEEE international conference on Industrial Electronics: Developments and Applications, ICIDeA 2023

作者： Rajan, V. Aravinda Marimuthu, T. Bhardwaj, Rajat Shukla, Rishi Prakash Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamil Nadu Krishnankoil Virudhunagar626 126 India Rv University School of Computer Science and Engineering Bengaluru560059 India Ait Management Chandigarh University Punjab Mohali India

ISBN: (纸本)9798350381979

An enhanced active reinforcement learning technique has been proposed to enable autonomous robots to operate and execute tasks in industrial automation. This approach combine hierarchical reinforcement learning and Bayesian optimization, to acquire knowledge from complex real-world environments and acquire optimal policies which can enable autonomous robots to perform collaborative tasks efficiently. The main advantage of this enhanced active reinforcement learning approach is the capability of the autonomous robot to autonomously adapt its movements and decision-making strategies when new tasks are required. It allows for the robot to explore its environment and learn how to complete tasks optimally while reducing the burden of manual intervention. Moreover, the proposed approach can generalize its knowledge to establish rewarding collaborative behaviors between robots and humans, thus allowing for collaborative human-robot interactions. This will be beneficial in performing industrial automation with robot cooperative tasks and optimize the efficiency of the industrial automation system.. © 2023 IEEE.

关键词： Decision making

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Application of Multidimensional Information in Predicting Blue Side Attack Actions: A Matching Degree Calculation Method

Application of Multidimensional Information in Predicting Bl...

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automation, robotics and computer engineering (icarce), international conference on

作者： Qia Chen Yanyan Huang Yuqi Xia School of Automation Nanjing University of Science and Technology Nanjing China

In response to the problem of difficulty in accurately predicting the intention of blue troops to attack targets on the land battlefield, this paper proposes a prediction method based on matching degree, aiming to predict the intention of blue troops to attack. This article adopts a comprehensive analysis method based on multidimensional information to analyze the matching degree between the blue attacking force and the possible targets of the red side. Firstly, integrate the features of the blue attacking force obtained from the battlefield with the feature information of the red potential target to form a panel of data. Next, the position matching degree, marching angle matching degree, and force target matching degree between the troops and the target are calculated separately, in order to establish the matching degree relationship between the blue attacking troops and the possible attacked targets of the red side, and then use it to speculate on the probability of the blue army implementing the attack, thereby achieving the prediction of the target of the blue attacking action. Finally, an example analysis shows that this matching degree-based prediction method can more comprehensively consider the fusion of multi-dimensional intelligence information, which helps to improve the reliability and effectiveness of target attack prediction.

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Enhancing Data engineering and Accelerating Learning through Intelligent automation 2

Enhancing Data Engineering and Accelerating Learning through...

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2nd international conference on Trends in Electrical, Electronics and computer engineering, TEECCON 2023

作者： Pradeep, Aneesh Rustamov, Azamat Shokirov, Xudoyshukur Ibragimovna, Guli Tirova Farkhadovna, Sabirova Umida Medetovna, Akhmedova Feruza New Uzbekistan University Software Engineering Tashkent Uzbekistan New Uzbekistan University Mechanical Engineering Tashkent Uzbekistan Bukhara State University Uzbek Linguistics and Journlism Uzbekistan University Named after Mirzo Ulugbek Department of Sociology Tashkent Uzbekistan Uzbekistan Named after Mirzo Ulugbek Department of Sociology Tashkent Uzbekistan

ISBN: (纸本)9798350339949

The rapid growth of data and the increasing complexity of analytical tasks have necessitated the development of efficient data engineering processes and accelerated learning techniques. Intelligent data engineering and automated learning are two important fields in the domain of artificial intelligence. The aim of intelligent data engineering is to develop efficient and effective algorithms for processing large volumes of data. Automated learning, on the other hand, focuses on creating algorithms that can learn from data without being explicitly programmed. Both fields are closely related and have significantly contributed to the development of various applications such as machine learning, natural language processing, computer vision, and robotics. Through a comprehensive review of data engineering concepts, challenges, and automated learning techniques, this paper highlights the benefits and advantages of incorporating intelligent automation into data engineering workflows. It presents case studies and real-world examples showcasing successful implementations of intelligent automation in data engineering projects. In addition, the paper discusses performance evaluation metrics, challenges, ethical considerations, and potential intelligent automation risks. In addition, it discusses future research and development opportunities in the disciplines of intelligent data engineering and automated learning. The findings of this study shed light on the potential of intelligent automation in augmenting data engineering processes and accelerating learning, thereby revealing new avenues for efficient data utilization and knowledge extraction across a variety of domains. © 2023 IEEE.

关键词： automation

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Automatic Area Measurement of Ring Cooler Corner Images Based on EU-Net 2

Automatic Area Measurement of Ring Cooler Corner Images Base...

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2nd international conference on Artificial Intelligence, Human-computer Interaction and robotics, AIHCIR 2023

作者： Wang, Wei Zhang, Dezheng Li, Qing Li, Jing Ma, Jinge Xi, Yaming School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China School of Mathematics and Physics University of Science and Technology Beijing Beijing China

ISBN: (纸本)9798350360363

Aimed to mitigate the challenges associated with manual detection, such as elevated risks and limited accuracy, a machine vision-based automatic measurement method is proposed for determining the area of a ring cooler corner. Specifically, an enhanced lightweight model known as EU-Net (Efficient U-Net), derived from the classic semantic segmentation U-Net model, is developed to accurately segment the ring cooler corners within the images. Subsequently, the OpenCV toolkit is employed to conduct area statistics on the segmented masks. The results show that EU-Net achieves comparable segmentation effectiveness and area statistics results to the classic U-Net, while utilizing only 0.097% of the parameters present in the latter model. Our improved algorithm obtains 99.74% and 94.5% in pixel-wise accuracy and intersection over union. Moreover, it can process 60 frames per second, effectively meeting real-time operational demands. © 2023 IEEE.

关键词： computer vision

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