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EC-WGAN: Enhanced Conditional and Wasserstein GAN for Fault Samples Augmentation 6

EC-WGAN: Enhanced Conditional and Wasserstein GAN for Fault ...

引用

6th international conference on robotics, Control and Automation engineering, RCAE 2023

作者： Li, Lingli Li, Zhongxin Wang, Xiuli Gong, Jianye College of Information Engineering Zhejiang University of Technology Hangzhou China College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9798350315301

Considering the issue of limited and imbalanced fault samples, an enhanced conditional and Wasserstein GAN (EC-GAN) is proposed for fault samples augmentation of bearing. At first, random noise along with fault category are inputted into the generator for synthetic samples. Then, the authenticity between real samples and synthetic samples are judged by the discriminator in a minmax cost function with Wasserstein distance. Moreover, the gradient penalty is applied for keeping continuous of the Lipschitz function and gradient vanishing in Wasserstein GAN training. As the collected samples are time series data, one-dimensional convolutional layers replace the fully connected layers of the generator and the discriminator. Finally, the effectiveness of the proposed EC-GAN is verified under the limited data of Case Western Reserve University bearings. © 2023 IEEE.

关键词： Generative adversarial networks

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Intelligent E-Commerce Chatbot for Personalized Product Recommendations Using Text Mining and Machine Learning 2

Intelligent E-Commerce Chatbot for Personalized Product Reco...

引用

2nd international conference on advances in Computation, Communication and Information technology, ICAICCIT 2024

作者： Minu, M.S. Adithya Kavya SreeRanjini Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai India Department of Computer Science and Engineering with Specialization in Big Data Analytics SRM Institute of Science and Technology Ramapuram Chennai India

ISBN: (纸本)9798331541217

Innovative technology solutions have been developed in response to the growing need for effective and customized client contact on e-commerce platforms. This work introduces an intelligent chatbot system that uses machine learning and text mining techniques to improve user satisfaction and answer customer concerns. Advanced Natural Language Processing (NLP) models have been trained on large datasets, allowing for precise user intent interpretation and pertinent product recommendations. A strong recommendation engine is included into the system architecture to aid in decision-making, ultimately enhancing the customer experience by providing individualized, real-time help. The study also highlights the significance of data privacy by using privacy-preserving techniques to safeguard user data. The system's scalability and performance benefits are highlighted through thorough comparisons with current models. By showcasing the useful uses of machine learning and text mining in enhancing customer contact and service delivery, this study makes a substantial contribution to the development of AI-driven solutions in e-commerce. © 2024 IEEE.

关键词： Big Data Chatbot Cost Data Mining e-Commerce Hadoop Machine Learning Product Purchasing Recommendation

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Garment Shape-Forming Actuator Unit with Variable Stiffness and Friction for Dressing and Undressing ∗

Garment Shape-Forming Actuator Unit with Variable Stiffness ...

引用

2024 IEEE international conference on robotics and Biomimetics, ROBIO 2024

作者： Hayashi, Ikumi Nishimura, Toshihiro Watanabe, Tetsuyou Graduated school of Natural science and Technology Kanazawa University Kakuma-machi Kanazawa9201192 Japan Institute of Science and Engineering Kanazawa University Faculty of Frontier Engineering Kakuma-machi Ishikawa Kanazawa city9201192 Japan

ISBN: (纸本)9781665481090

This study developed a new actuator unit that enhances clothing stiffness to maintain its shape and thereby facilitate dressing and undressing. The actuator unit consists of a Straighten Actuator that provides stiffness along the longitudinal axis of a shirt sleeve, a Bending Actuator that maintains the armhole shape, and an airflow system. SA and BA are based on the flat tube mechanisms driven by supplied air. The BA features notches and surfaces of varying thickness to enable simultaneous bending and expansion when air is supplied. The airflow system to reduce friction was also introduced to further ease the dressing and undressing processes. The efficacy of the proposed system was experimentally validated and subsequently evaluated by human subjects. Compared to when no air is supplied to the actuator unit, the results showed a significant increase in 'spaciousness' and a significant improvement in the ease of 'dressing' and 'undressing' when air is supplied. © 2024 IEEE.

关键词： Friction

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Cloud Based Automated Control System Workshops and Rooms for Controlling Parameters 1

Cloud Based Automated Control System Workshops and Rooms for...

引用

1st international conference on advances in Computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Kumar, Dinesh Kuntal, Ravinder Singh Deep, Pragya Chamoli, Anup Shekhar Singh, Pinki Mandal, Rishabh SRM Institute of Science & Technology Department of Computer Science and Engineering UP Ghaziabad India Nitte Meenakshi Institute of Technology Department of Mathematics Karnataka Bangalore India IIMT College of Engineering Department of AI & DS Greater Noida India Uttaranchal School of Computing Sciences Uttaranchal University Dehradun248001 India Accurate College of Engineering & Management Department of Computer Science and Engineering Greator Noida India Tula's Institute Department of Computer Science and Engineering UK Dehradun India

ISBN: (纸本)9798331518578

Across all industries, cloud-based automated control systems have completely changed how operational and environmental parameters are tracked and controlled. With cloud-integrated systems for real-time data collection, processing, and control, this concept presents intelligent, remote-controlled workshops and control rooms. To guarantee accurate control of crucial variables like temperature, humidity, pressure, and equipment efficiency, these systems make use of IoT devices, AI techniques, and big data analytics. Through sophisticated data perspectives, the cloud-based strategy enables predictive maintenance, improves flexibility, and lowers operating expenses. Stakeholders may make prompt, data-driven choices from anywhere with remote access to control rooms. These seminars provide practical experience with cloud-controlled settings and function as training and development centres. The system's flexibility to meet a range of industrial demands is further enhanced by its compatibility with external tools and equipment. The design, deployment, and possible uses of cloud-based control systems are covered in this paper, with an emphasis on how they might promote operational excellence, energy efficiency, and smart manufacturing. © 2025 IEEE.

关键词： Smart manufacturing

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Enhancing Time Series Prediction in Industrial Processes: A Self-Attention BiLSTM Approach 7

Enhancing Time Series Prediction in Industrial Processes: A ...

引用

7th international conference on robotics, Control and Automation engineering, RCAE 2024

作者： Wen, Sicheng Xu, Jiajun University of Engineering Science Department of Electronic and Electrical Engineering Shanghai Shanghai China University of Shanghai for Science and Technology Department of Optical-Electrical and Computer Engineering Shanghai China

ISBN: (纸本)9798350355642

The development of data-driven soft sensors for modeling complex data, particularly in scenarios characterized by strong nonlinearity, high dimensionality, cross-correlation and autocorrelation, remains a significant challenge in process data analysis. Bidirectional Long Short-Term Memory (BiLSTM) networks are highly effective in capturing both forward and backward dependencies within sequences, thereby enhancing the extraction of temporal features from time series data. However, BiLSTM networks may struggle to capture global dependencies, especially in long sequences. To address this limitation, the self-attention mechanism, which excels in modeling global relationships across all positions in the input sequence, can be integrated with BiLSTM by applying weighted attention to the two different directions of BiLSTM, thereby enhancing its performance. This study proposes a novel method called SA-BiLSTM, which combines the strengths of the BiLSTM network and the self- attention mechanism. The self-attention layer captures global dependencies, while the BiLSTM layer extracts comprehensive temporal features in both directions, which are then passed to a fully connected layer for final prediction. Extensive comparisons with traditional methods such as BiLSTM, LSTM with added self-attention mechanism, LSTM, RNN, and SVM validate the superior performance of the proposed SA-BiLSTM method in handling complex time series data. © 2024 IEEE.

关键词： Spatio-temporal data

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A SAR Denoising Network Based on Generative Adversarial Learning 6

A SAR Denoising Network Based on Generative Adversarial Lear...

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6th international conference on robotics, Control and Automation engineering, RCAE 2023

作者： Yi, Niannian Pei, Shengchang Ai, Nianxin Zhang, Shuiping Wuhan Institute of Technology Hubei Key Laboratory of Intelligent Robot Wuhan China

ISBN: (纸本)9798350315301

Synthetic Aperture Radar (SAR) images are critical in microwave remote sensing and are used for resource exploration and target location. However, due to the principle of coherent imaging, SAR images are often interfered by speckle noise, which reduces image quality. It is necessary to remove noise but retain details. We are committed to improving the network structure to increase the diversity and authenticity of generated images. Inspired by Se-Res-Unet, we fuse generative adversarial networks for SAR image denoising and named the model SAR-RsuGan. In it, the generator and the discriminator compete with each other to generate high-quality images. We use synthetic SAR images for training and compare with other methods to obtain the best performance. © 2023 IEEE.

关键词： Synthetic aperture radar

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VLSI Implementation of Power Efficient 4-bit Flash ADC

VLSI Implementation of Power Efficient 4-bit Flash ADC

引用

2024 IEEE international conference on Recent advances in science and engineering technology, ICRASET 2024

作者： Tharun Tejas, G. Shobha, B.N. Ramkumar, B.M. Naveen, K.B. Manoj Kumar, S.B. Shivakumaraswamy, K.N. Bgs Institute of Technology Adichunchanagiri University Department of Ece Karnataka BG Nagara571448 India Bangalore Institute of Technology Department of Ece Karnataka Bangalore India Bgs Institute of Technology Adichunchanagiri University Deputy Librarian Karnataka BG Nagara India

ISBN: (纸本)9798350388602

The project aims to design and implement a 4-bit Thermometer-coded Flash Analog-to-Digital Converter (ADC) using Very Large-Scale Integration (VLSI) technology. The proposed design employs a high-speed, fully parallel architecture that uses a resistor ladder network to generate the reference voltages for flash comparison. The ADC will be implemented using the 180 nm CMOS technology node, and simulation results will be obtained using Cadence Virtuoso tools. The performance of the design will be evaluated based on several metrics, including resolution, speed, power consumption, and accuracy. The project aims to achieve a high-resolution, high=speed ADC with low power consumption that is suitable for use in various applications, such as digital signal processing, data acquisition, and instrumentation. The results of this project can contribute to the development of advanced ADC designs and enhance the performance of various electronic systems. © 2024 IEEE.

关键词： CMOS integrated circuits

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Hip Hiking Gait Improvement with Electrohydraulic Robotic Knee: Preliminary Results 46

Hip Hiking Gait Improvement with Electrohydraulic Robotic Kn...

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46th Annual international conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Zhong, Heran Gao, Siyuan Wang, Qining Peking University College of Engineering Department of Advanced Manufacturing and Robotics Beijing100871 China Peking University College of Engineering The Institute for Artificial Intelligence Department of Advanced Manufacturing and Robotics Beijing100871 China Peking University Third Hospital Beijing100191 China University of Health and Rehabilitation Sciences Qingdao266071 China

ISBN: (纸本)9798350371499

Individuals with Transfemoral Amputation (TFA) usually exhibit hip hiking walking with passive prostheses due to insufficient knee flexion. Powered knee prostheses can provide net-positive energy in the knee joint with improved gait symmetry. However, their effects on improving hip hiking are not well understood. This study investigates residual hip hiking through walking experiments using a robotic transfemoral prosthesis that can provide swing assistance. Different levels of assistive flexion torque were provided during the pre-swing and the mid-swing (no assistance, low assistance, medium assistance, high assistance). The kinematic and electromyographic (EMG) results indicate that with the increasing assistive torque level applied, the residual hip hiking was improved. The results preliminarily demonstrate the positive effect of knee flexion assistance on hip hiking improvement. © 2024 IEEE.

关键词： Knee prostheses

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An Approach in Prediction of Medicine Side Effects Using RNN Networks 8

An Approach in Prediction of Medicine Side Effects Using RNN...

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8th IEEE international conference on Distributed Computing, VLSI, Electrical Circuits and robotics, DISCOVER 2024

作者： Nargis, Tanzila Nisar Shaha, Suhail Ahamed Hazareena, Asia Nitte Dept. of Information Science & Engineering Karkala India Yenepoya Institute of Technology Dept. of Information Science & Engineering Vidyanagar Moodabidri India P.A. College of Engineering Dept. of Electronics & Communication Mangalore India

ISBN: (纸本)9798350350593

Adverse Drug Reactions (ADRs) are a critical issue in the field of medicine that demands innovative solutions. Various research has been done using machine learning and deep learning approaches to predict the drug side effects. This study delves deep into the realm of Recurrent Neural Networks (RNNs) to revolutionize the prediction of ADRs associated with medications. The groundbreaking RNN-based model harnesses sequential data from both drug structures and patient characteristics to effectively anticipate potential side effects. Through extensive training on a vast dataset of drug-ADR connections and rigorous evaluation, the developed model has demonstrated remarkable accuracy of 98.95% in predicting previously unseen ADRs. When compared to traditional machine learning methods, The proposed RNN model has showcased its process in capturing the intricate relationships between drugs, patients, and side effects. This pioneering work holds immense promise in enhancing patient safety by proactively identifying potential ADRs prior to drug administration. © 2024 IEEE.

关键词： Recurrent neural networks

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Geometric-based Bimodal Control for Hybrid Aerial/Ground Vehicles

Geometric-based Bimodal Control for Hybrid Aerial/Ground Veh...

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2024 IEEE international conference on Real-Time Computing and robotics, RCAR 2024

作者： Tang, Haoming Miao, Zhiqiang Wang, Haoyu Chen, Yizong Zhang, Hui Wang, Yaonan Hunan University College of Electrical and Information Engineering Changsha410082 China National Engineering Research Center for Robot Visual Perception and Control Changsha China School of Robotics Hunan University Changsha410082 China

ISBN: (纸本)9798350372601

Hybrid ground/aerial vehicles, capable of adapting to both terrestrial and aerial environments simultaneously, can accomplish more complex tasks, holding promising applications across various domains. Furthermore, designing a highly real-time multi-modal controller to adapt to environmental and modal changes, is currently a critical issue to be addressed. Based on this requirement, a geometric-based bimodal control structure is proposed in this study. We initially design the aerial controller in the Lie algebra space, based on a geometric attitude controller. Moreover, inspired by the characteristics of ground locomotion, we modify the aerial controller to satisfy the constraints of this mode. Through this approach, we can simplify the design process of the ground controller. Both controllers feature a similar and simpler structure, meet real-time control requirements, and allow them to use the same parameters. Ultimately, the proposed method's efficacy and performance are validated through ROS-Gazebo simulation environment. © 2024 IEEE.

关键词： Antenna grounds

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