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检索条件"任意字段=International Conference on Advances in Science, Engineering and Robotics Technology"

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Concentric Tube Robot for Intrathecal Drug Administration 8

Concentric Tube Robot for Intrathecal Drug Administration

引用

8th IEEE international conference on Advanced robotics and Mechatronics, ICARM 2023

作者： Gunderman, Anthony L. Donsante, Anthony Boulis, Nicholas M. Chen, Yue Georgia Institute of Technology/Emory Biomedical Engineering Department AtlantaGA United States Emory University Department of Neurosurgery AtlantaGA United States

ISBN: (纸本)9798350300178

Amyotrophic Lateral Sclerosis (ALS) is a fatal neurological disorder characterized by motor neuron degeneration. Although there is no known cure, FDA approved treatment options exist. However, these medications are administered orally, which limits dosing due to hepatic toxicity and asthenia. In addition, the expression of multidrug transporters on the blood-brain barrier (BBB) is increased in ALS patients, significantly reducing the influx of drug into the central nervous system from the blood stream. Recent work has explored intrathecal administration to obtain higher spinal cord concentrations, bypassing the BBB and avoiding the risk for adverse events associated with systemic drug exposure. However, current intrathecal catheter designs distribute the drug heterogeneously. In this paper we present a fluidic model for the first ever concentric tube robot (CTR) for intrathecal drug delivery and its corresponding envisioned system implementation for homogeneous intrathecal delivery of riluzole throughout the cerebral spinal fluid for patients suffering from ALS. The fluidic model is derived using the energy equation, and orifice diameters along the CTR are optimized to minimize fluidic head loss while maintaining a desired flow rate at each orifice. Simulation results show that the proposed design is able to provide homogeneous drug delivery via optimal design of the orifices along the whole CTR body. © 2023 IEEE.

关键词： Orifices

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Fault Diagnostic Opportunities for Electromagnetic Coils of Active Magnetic Bearings using Physics-of-Failure Analysis 5

Fault Diagnostic Opportunities for Electromagnetic Coils of ...

引用

5th international conference on System Reliability and Safety engineering, SRSE 2023

作者： Li, Ruiqi Wang, Kai Zeng, Peng Cao, Jiwei Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang110016 China Harbin Institute of Technology Department of Electrical Engineering China

ISBN: (纸本)9798350305944

Active magnetic bearings (AMBs) have many advantages over traditional oil bearings due to their non-contact characteristics. They are environmentally friendly solution and have been proven to be highly reliable and available. Electromagnetic coils are vital components of AMB and they are failure prone. In this paper, the failure mode of magnetic bearing coil and its corresponding failure mechanism are reviewed by FMMEA method, and the existing coil fault diagnosis methods are introduced. Future directions for coil insulation health monitoring aiming at the application characteristics of AMBs are also discussed. © 2023 IEEE.

关键词： Failure analysis

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Relationship of Noise Level with Pavement Distresses 1st

Relationship of Noise Level with Pavement Distresses

引用

Proceedings of the 1st international conference on Sustainable Technologies and advances in Automation, Aerospace and robotics, STAAAR 2022

作者： Makendran, C. National Institute of Technology Tamil Nadu Tiruchirappalli620015 India

ISBN: (纸本)9789819923489

This paper predicted a noise level for Indian highways and developed a relationship between noise and pavement distress cracks (CR), potholes (PH), and the international Roughness Index (IRI). The government of India is investing huge amounts in road construction every year. Poor road construction quality and subsequent maintenance lead to faster road deterioration, which reduces vehicle speed and increases noise pollution. In this regard, scientific procedures must evolve to predict noise pollution levels. In this research, data was collected on the age of the pavement, the number of commercial vehicles, the noise level, and the condition of the pavement. This information was used to make a noise prediction model with the Multiple Linear Regression (MLR) technique and an R2 of 0.90. Environmental and highway engineers can use this study to predict noise pollution in pavement distress. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Noise pollution

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YOLOV7 Vehicle Environmental Target Detection Based on Feature Reorganization and Lightweight Fusion 24

YOLOV7 Vehicle Environmental Target Detection Based on Featu...

引用

4th international conference on Control and Intelligent robotics, ICCIR 2024

作者： Liu, Xincen Zhou, Bowen Ruan, Aoao College of Information and Electrical Engineering Hunan University of Science and Technology Xiangtan411201 China

ISBN: (纸本)9798400709937

In the target detection of the complex vehicle driving environment, due to the dense and complex small-sized targets, it is easy to have problems such as false detections and missed detections. To solve such problems, this paper makes two improvements to the YOLOV7 network. The multi-branch convolution module RFB is used to replace the SPPCSPC pyramid pooling layer of the original YOLOV7 network, which adaptively adjusts the size and position of the sensory field through convolution and dilated convolution of different sizes, and effectively extracts the feature information of targets of different sizes while minimizing the count of network parameters. Since the original network model of YOLOV7 is too large, this paper proposes a lightweight generalized up-sampling operator CARAFE to replace the original up-sampling operation of YOLOV7,which minimizes the amount of calculation and improves the target detection accuracy at the same time. According to the experimental results, training under the BDD100K dataset, the mAP is improved by 0.85% to 59.72%, and the precision and recall rates are increased by 0.24% and 0.93% respectively. It is an effective improvement in vehicle environmental target detection algorithms. © 2024 held by the owner/author(s).

关键词： Autonomous Driving

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Electrochemical Monitoring of Intracellular Reactive Oxygen Species Based on Automated Nanoprobe Platform

Electrochemical Monitoring of Intracellular Reactive Oxygen ...

引用

2023 Annual IEEE international conference on Manipulation, Manufacturing and Measurement on the Nanoscale, 3M-NANO 2023

作者： Ma, Yanmei Hu, Weikang Ruan, Muyang Zhan, Zhen Zhang, Yi Hu, Chengzhi Southern University of Science and Technology Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Shenzhen China City University of HongKong Department of Biomedical Engineering Hong Kong

ISBN: (纸本)9798350344486

The electrochemical detection of endogenous molecules from a single cell is a crucial technique for understanding fundamental cellular processes at the subcellular level and uncovering cellular heterogeneity. However, high throughput intracellular detection has posed significant challenges. This paper proposes a simple method for fabricating a nanoprobe for the electrochemical monitoring of intracellular reactive oxygen species (ROS), which are important signaling molecules that play a key role in a wide range of cellular processes, including apoptosis, proliferation, and differentiation. Combined with the automated nanoprobe platform, the study successfully achieved minimally invasive and efficient intracellular ROS detection in living cells. Moreover, the results reveal that the average ROS concentration in the cytoplasm and nucleus is uneven, which has important implications for the understanding of cellular redox signaling. © 2023 IEEE.

关键词： Nanoprobes

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Automobile Valuation Prediction Using Machine Learning based Algorithms

Automobile Valuation Prediction Using Machine Learning based...

引用

2023 international conference on the Confluence of Advancements in robotics, Vision and Interdisciplinary technology Management, IC-RVITM 2023

作者： Deepak, N.A. Kumar, Ravi Gupta, Tarun Gaurav, Shubham Yadav, Pulkit Singh Pranesh, B. Computer Science and Engineering Rvitm Bengaluru India

ISBN: (纸本)9798350306088

With remarkable technological advancements and the emergence of new technical expertise, combined with substantial economic growth within our nation, there has been a noticeable shift in consumer preferences towards the purchase of automobiles, particularly cars, over other modes of transportation. This research paper aims to conduct a comprehensive analysis of the prevailing trends in used car pricing. Additionally, it endeavors to predict the prices of used cars using supervised machine learning algorithms. Considerable number of distinct attributes are examined for the reliable and accurate prediction. Also, it seeks to identify the most effective machine learning algorithm among those selected for the purpose of predicting car prices. Previous studies have already explored machine learning algorithms such as linear regression, multiple regression, and random forest in this context. Our objective is to assess which algorithm offers the most reliable and accurate predictions for car prices. This research has practical implications, as it can benefit first-time used car buyers by providing them with valuable insights into pricing dynamics. Furthermore, the model was evaluated using test data and the accuracy of 91% was obtained. © 2023 IEEE.

关键词： Costs

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Optimization of Parameters of the OWC Wave Energy Converter Device Using a Machine Learning Approach 5

Optimization of Parameters of the OWC Wave Energy Converter ...

引用

5th IEEE international conference on advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2025

作者： Karnavat, Kush Vadodaria, Nilansh Trivedi, Kshma Patel, Prashant School of Computer Science and Engineering Vellore Institute of Technology Chennai Campus Chennai India School of Advanced Sciences VIT-AP University Department of Mathematics Amaravati India

ISBN: (纸本)9798350356236

In this study, the performance of an L-shaped front wall OWC (Oscillating Water Column) device is investigated in the presence of irregular incident waves. To efficiently explore the complex interactions between input features and the target variable, two supervised machine learning models: (i) a decision tree model and (ii) an XGBoost model are considered. The input parameters selected for this analysis are: OWC Front wall Draft, OWC Duct Length, Chamber Length, ripple Number, and ripple amplitude of the sinusoidal seabed. The output attribute is the maximum power extracted by the OWC device. The XG Boost model is used to identify critical input regions where power extraction peaks, while the decision tree model further aids in understanding the parameter influences on power extraction. A dataset of 3125 samples was generated for training, validation, and testing. By employing accumulated local effect plots with the XG Boost model, five specific regions in the input space were identified that maximize annual average power extraction. The results indicate that optimal power extraction is achieved for a specific value of each parameter, thereby validating the influence of each on OWC device performance. © 2025 IEEE.

关键词： Wave energy conversion

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A Survey of Automatic Driving Environment Perception 24

A Survey of Automatic Driving Environment Perception

引用

24th IEEE international conference on Software Quality, Reliability and Security Companion, QRS-C 2024

作者： Zhao, Hui Li, Xin Xu, Cheng Xu, Bingxin Liu, Hongzhe Beijing Key Laboratory of Information Service Engineering Beijing Union University Beijing China College of Robotics Beijing Union University Beijing China

ISBN: (纸本)9798350365658

Driven by new generation AI technologies such as big data, cloud computing and machine learning, autonomous driving has been significantly developed and progressed in recent years. Among the core technologies of autonomous driving, environment perception, as one of them, simulates the visual perception ability of the human eye to enable vehicles to recognize and understand the surrounding environment, thereby achieving safe and efficient driving. However, autonomous driving faces numerous challenges in practical applications, such as the impact of adverse weather on the quality of visual images, the accuracy problem of visual recognition and so on. To solve these problems, scholars have carried out a large amount of research work. This review will comprehensively sort out the research results in the above related fields, aiming to provide readers with a comprehensive view of machine vision technology and perception technology in autonomous vehicles, and explore its future development trend and possible challenges. We will introduce the basic concepts and key technologies of autonomous driving perception, and discuss various advanced perception methods and their applications in detail. Finally, we will look forward to the future development trend of autonomous driving perception technology, which can provide reference for further promoting the development of autonomous driving technology and is of practical significance for researchers and practitioners. © 2024 IEEE.

关键词： Adversarial machine learning

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Gait Phase Recognition for Soft Exoskeleton Assistance Based on Inertial Sensors

Gait Phase Recognition for Soft Exoskeleton Assistance Based...

引用

2023 IEEE international conference on robotics and Biomimetics, ROBIO 2023

作者： Liu, Yong Wang, Jiaxin Zhao, Zhendong Liu, Lei Deng, Huanyu Guo, Shijie School of Mechanical Engineering Hebei University of Technology Eng. Res. Ctr. of the Min. of Educ. for Intelligent Rehab. Equipment and Detection Technologies Tianjin300132 China Hebei University of Technology School of Artificial Intelligence Tianjin300132 China

ISBN: (纸本)9798350325706

To improve the control of exoskeleton robot for gait assistance, a gait phase recognition method for exoskeleton assistance based on three inertial sensors is proposed, which includes motion state recognition based on support vector machine (SVM), gait phase recognition relying on long short-term memory (LSTM), and a rule-based method for labeling lower limb gait event. Firstly, we used SVM to identify six motion states: standing, level walking, turning left, turning right, left steering, and right steering. Then, an LSTM model was employed to identify the six phases of the lower limb gait during level walking. The experiments demonstrate that this method achieves accuracy rates of 99.65% and 96.81% for the wearer's motion state recognition and gait phase recognition, respectively, with corresponding F1 scores of 0.9957 and 0.9683. © 2023 IEEE.

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Bionic Gastropod Robot Based on Continuous Actuation 24

Bionic Gastropod Robot Based on Continuous Actuation

引用

4th international conference on robotics and Control engineering, RobCE 2024

作者： Ji, Qinjie Song, Aiguo Miao, Tianyuan Wang, Shaohu Zhang, Yaohua Southeast University Southeast University Shenzhen Research Institute Nanjing Jiangsu China Nanjing University of Information Science and Technology Jiangsu Nanjing China

ISBN: (纸本)9798400716782

Gastropods crawl on complex surfaces using pedal waves, inspiring potential solutions for navigating rough, narrow, and steep terrains. The most common method for pedal wave actuation involves discrete traveling waves, which use finite states to mimic continuous movement. This work presents a bionic gastropod robot that employs continuous wave actuation, accompanied by a comprehensive theoretical analysis. An elastic model is proposed, integrating both strain potential and gravitational potential. This model is thoroughly explained and can be used for control purposes, offering an alternative to the black box approach. Additionally, a controller based on Central Pattern Generators (CPG) using the Hopf oscillator was designed. Experimental results demonstrated that the theoretical curves calculated from the elastic model accurately describe the shape of gastropod waves under both small and large bending deformations. The bidirectional driving of the gastropod waves was successfully achieved by the designed controller. Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Molluscs

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