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检索条件"任意字段=3rd International Conference on Informatics in Control, Automation and Robotics"

共 2673 条记录，以下是121-130 订阅

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Harnessing Medical Imaging Applications: Survey on 3D Deep Learning Models for Image Segmentation 3

Harnessing Medical Imaging Applications: Survey on 3D Deep L...

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3rd international conference on Communication, control, and Intelligent Systems, CCIS 2024

作者： Nambiar, Rajashree Nanjundegowda, Raghu Dept of Electronics and Communication Bengaluru India Dept of Robotics and Ai Engineering Nitte India Dept of Electrical and Electronics Engineering Bengaluru India

ISBN: (纸本)9798331528201

The domain of 3D medical image segmentation has progressed markedly with the incorporation of deep learning methodologies, offering critical instruments for accurate and quick examination of intricate medical pictures. Various research has created 3D convolutional neural networks (CNNs) designed to segment diverse anatomical and pathological features, tackling specific issues such as high dimensionality, class imbalance, and computing requirements. Innovative models such as DeepMedic, which implemented a multiresolution strategy for brain lesion identification, together with other U-Net adaptations, have attained remarkable outcomes in tumor and organ segmentation through the integration of contextual and spatial data. Recent advancements encompass models employing large-kernel (LK) attention modules, transformer-based architectures, and hybrid approaches such as UNETR++ with Efficient Paired Attention, all enhancing accuracy while optimizing computing efficiency. These developments highlight the potential of 3D deep learning for clinical applications;yet, challenges such as restricted data availability, substantial annotation expenses, and generalizability across varied datasets persist as avenues for additional investigation. © 2024 IEEE.

关键词： Convolutional neural networks

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An Empirical Review of Supervised and Reinforcement Learning Algorithms for Personalized Exoskeleton Robot Training Systems in Neurorehabilitation 3

An Empirical Review of Supervised and Reinforcement Learning...

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3rd international conference on automation, Computing and Renewable Systems, ICACRS 2024

作者： Narula, Sweety Pol, R.S. Patil, R.V. Dept of ENTC Engineering Vishwakarma Institute of Technology & Science Pune India PDEA COE Manjari Pune India

ISBN: (纸本)9798331532420

There is an increasing need for developing more personalized machine learning algorithms for the training system of exoskeleton robots that are in use for the purpose of human neurorehabilitation patients. With increased neurological disorders, demand for effective and individually tailored rehabilitation solutions parallels. Traditional methods of rehabilitation are inadequate to keep up with the adjustment of treatment based on the needs of a patient that may result in very poor recuperation results. Current reviews on the applicability of machine learning in neurorehabilitation rarely fully consider the needs and complexities involved in the design of personalized exoskeleton training systems. There are several major limitations in the literature reviews: very often, they do not consider the possibility of integrating machine learning personalization into the processes of exoskeleton training;besides, in most cases, they lack a methodical way to compare algorithm effectiveness in various patient profiles;lastly, they do not give an adequate meta-analysis of the strong and weak points for the existing methodologies. These gaps impede the construction of more effective and more individualized rehabilitation programs. In this respect, the systematic review that will be presented herein will involve a systematic literature review, meta-analysis, and critical appraisal following machine learning algorithms specific for exoskeleton robot training systems. The methods include a systematic literature review by searching, categorizing, and the relevant studies;then meta-analysis is carried out based on the data gathered to give a quantitative assessment of the performance and effectiveness of these algorithms. This review is guided by the PRISMA guidelines for rigorous and transparent reporting. Furthermore, a critical appraisal framework enhances the review so that strengths and weaknesses of the many different machine learning techniques—from supervised learning to rein

关键词： Exoskeleton (robotics)

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Utilizing Augmented Reality and Mobile Devices to Support robotics Lessons 20th

Utilizing Augmented Reality and Mobile Devices to Support Ro...

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20th international conference on Remote Engineering and Virtual Instrumentation: Open Science in Engineering, REV 2023 co-organized with the international Edunet World conference, IEWC 2023

作者： Pasalidou, Christina Fachantidis, Nikolaos Orfanidis, Christos University of Macedonia 156 Egnatia Street Thessaloniki54636 Greece Laboratory of Informatics and Robotic Applications in Education and Society University of Macedonia 156 Egnatia Street Thessaloniki54636 Greece

ISBN: (纸本)9783031424663

In the educational conditions of the twenty-first century, using technologies such as Mixed Reality (MR), Augmented Reality (AR), and robotics provides new possibilities in education. This study proposes a learning environment that utilizes augmented reality technology and mobile devices to support educational robotics lessons and enhance their learning context. The research aims to investigate the characteristics of the innovative learning system that integrates AR into educational robotics lessons. The implementation of the designed learning environment shows the positive aspects along with the limitations of using AR in educational robotics. The study participants were 20 Primary School students from the 3rd, 5th, and 6th grades who had already attended educational robotics lessons. Data was collected using observation and semi-structured interviews. The data was pseudonymized so that the participants’ identities were not revealed. Results indicate that students’ attitudes toward mobile AR in robotics education are positive and they would like to use it again. Their participation was active and they had authentic learning experiences. The results of the present study provide useful feedback and show that integrating Augmented Reality technology in educational robotics lessons is quite promising. Further, qualitative and quantitative studies are required to examine the effectiveness of AR learning environments in robotics. The optimization that the virtual objects provide in the real world for a deeper understanding of various topics should also be examined in future research. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Augmented reality Educational robotics Mobile devices

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Mitigating the Impact of Packet Corruption Loss in rdMA Networks with Switch Assistance 3

Mitigating the Impact of Packet Corruption Loss in RDMA Netw...

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3rd international conference on Cloud Computing, Big Data Application and Software Engineering, CBASE 2024

作者： Wan, Anbang School of Informatics Xiamen University Xiamen China

ISBN: (纸本)9798331506582

As cloud computing increases its demand for high-performance networks, rdMA networks have become a mainstream technology to support high-speed data transmission. Traditionally, rdMA networks are assumed lossless by enabling Priority Flow control (PFC). However, packet loss due to packet corruption is still inevitable and common, which has a serious impact on the performance of rdMA networks. Therefore, this paper proposes Protego, a solution to mitigate the impact of packet corruption loss in rdMA networks. Protego leverages the switch's in-network vision and packet processing capabilities to detect packet corruption loss, and helps recovery to alleviate performance degradation. Protego considers different timeout situations caused by packet loss and provides fine-grained processing, and intercepts redundant packets in advance to save bandwidth. Protego is well compatible with the rdMA protocol, and our experiments show the effectiveness of Protego. © 2024 IEEE.

关键词： Packet loss

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Microfluidic Lab-on-a-Chip Design and Analysis for GFAP Biomarker Detection Using Machine Learning Algorithms 3

Microfluidic Lab-on-a-Chip Design and Analysis for GFAP Biom...

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3rd international conference on Communication, control, and Intelligent Systems, CCIS 2024

作者： Balaji, P. Devasena, D. Rithick, P. Karthi, T. Rishmitha, K. Roopa, R. Sri Ramakrishna Engineering College Dept. Of. Electronics and Instrumentation Engineering Tamilnadu Coimbatore India Sri Ramakrishna Engineering College Dept. of Robotics and Automation Engineering Tamilnadu Coimbatore India Kongu Engineering College Dept. of Automobile Engineering Erode India Science Arjun College of Technology Dept. of Artificial Intelligence and Data Tamilnadu Coimbatore India

ISBN: (纸本)9798331528201

The detection of Glial Fibrillary Acidic Protein (GFAP) is a crucial biomarker for diagnosing neurological conditions such as traumatic brain injuries (TBI) and astrocytoma. This paper presents the design and analysis of a novel microfluidic Lab-on-a-Chip (LoC) platform for GFAP biomarker detection. The system integrates microfluidic channels with embedded gold nanoparticle-functionalized electrochemical sensors for high-sensitivity biomarker capture. The microfluidic chip is designed using soft lithography and PDMS (Polydimethylsiloxane), allowing for precise fluid handling and minimal sample consumption. The electrochemical sensors generate voltage signals corresponding to GFAP concentration levels, which are processed using digital filtering techniques to mitigate noise and improve signal quality. For accurate biomarker quantification, machine learning algorithms, including Random Forest ,KNN and Support Vector Machine (SVM), are employed to classify sensor output data into clinically significant concentration ranges. The model is trained on both simulated and experimentally collected sensor data, achieving an accuracy of over 93 percent in distinguishing low (below 50 ng/mL) and high (above 50 ng/mL) GFAP concentrations. The combination of microfluidic precision, sensitive electrochemical detection, and data analysis enables rapid and reliable detection of GFAP , providing a scalable and portable solution for early diagnosis of brain injuries and neurodegenerative diseases. This system highlights the potential of integrating microfluidics and machine learning in next-generation point-of-care diagnostic devices. © 2024 IEEE.

关键词： Polydimethylsiloxane

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Design and Implementation of IoT-Based Smart Energy Meter to Augment Residential Energy Consumption 3

Design and Implementation of IoT-Based Smart Energy Meter to...

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3rd international conference on robotics, Electrical and Signal Processing Techniques, ICREST 2023

作者： Midul, Md Abul Hayat Shahjee Pranta, Shahadat Hossain Biddut, Al Shaharea Islam Siam, Sifatul Islam Hazari, Md. Rifat Mannan, Mohammad Abdul American International University-Bangladesh Department of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350346435

There is a constant push for automation, portability, and remote control in the management systems of all organizations. A new IoT -based multifunctional smart energy meter is presented in this paper for automated metering and billing system. Arduino Nano with GSM Short Message Service (SMS) connection provides a meter reading system with predefined automatic functions followed by ESP-8266 WiFi Module to monitor energy parameters. Proteus 8.0 was used to model the project before the hardware implementation was built. With the GSM module and embedded controller, the proposed system can transmit data such as kWh consumption and generated bills over the GSM network, which can then be fed into existing energy management systems at power companies or organizations to provide services to customers without the need for human intervention. As a result, consumer energy analysis is made considerably simpler and more manageable. This device aids in the detection of power theft as well. As a result, this smart meter facilitates wireless connection and home automation utilizing IoT, which is a significant step towards a Digital Bangladesh. Moreover, a prepaid mode is incorporated as part of billing system. © 2023 IEEE.

关键词： Microcontrollers

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Neural Networks Application for the Classification Problem Solving with Domain Constraints 3

Neural Networks Application for the Classification Problem S...

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3rd international conference on Technology Enhanced Learning in Higher Education, TELE 2023

作者： Mikhaylov, Ilya Sergeevich Aung, Ye Thu Win, Myo Hlaing Aung, Zayar Applies Mathematics and Informatics Moscow Russia

ISBN: (纸本)9798350326567

The paper investigates an approach based on neural networks to solve the classification problem with domain constraints. The practical application of the developed methods in the subject area of oil production for solving the problem of optimizing the control of pumping equipment of oil wells is considered. The solution of the problem is carried out in real time based on the classification of the flow modes of the oil-water-gas flow according to the indications of a multiphase flow meter installed on an oil well. © 2023 IEEE.

关键词： Data mining

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Trajectory Adaptation with Impedance control for Human-Robot Collaboration Tasks 8

Trajectory Adaptation with Impedance Control for Human-Robot...

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

作者： Zhang, Chaoyi Luo, Jing Zeng, Chao Tang, Biwei Pang, Muye Yang, Chenguang School of Automation Wuhan University of Technology Wuhan430070 China University of Hamburg Department of Informatics Hamburg22527 Germany School of Automation Science and Engineering South China University of Technology Guangzhou510641 China

ISBN: (纸本)9798350300178

In human-robot collaboration tasks, an operator usually interacts with a robot physically and guides the robot to move by employing the interaction force in the model of impedance control. However, in physical human-robot interaction (pHRI), the trade-off between the position accuracy and interaction force is one of the main disadvantages of impedance control. In order to achieve compliant control with a high position control accuracy, a method of trajectory adaptation based on impedance control is proposed with minimized interaction force and small position error in pHRI and the effectiveness of the collaboration tasks is guaranteed. We use impedance control to generate the robot's movement for compliant control and use trajectory adaptation to regulate the robot's reference trajectory. By employing the proposed method, the interaction force can be reduced with small position error. The results of experiment verify the effectiveness of the proposed method. © 2023 IEEE.

关键词： Trajectories

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Design and Implement of a Super-Twisting ESO-Based Impedance control for Lower Limb Exoskeleton 3

Design and Implement of a Super-Twisting ESO-Based Impedance...

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3rd international conference on Mechatronics and automation Technology, ICMAT 2024

作者： Zhang, Wenhao Ji, Pingxin Song, Peng Liu, Hao Li, Qiang Mo, Xinmin Northwest Institute of Mechanical and Electrical Engineering Shaanxi Xianyang712099 China Department of Mechanical and Engineering Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781643685649

This brief proposes a super-twisting ESO-based impedance control for lower limb exoskeleton to promote the human-machine interaction-based coordination and stability with the unmodeled tire dynamics and external perturbations into consideration. The kinetics both in hip and knee joint is constructed and expected to match the authentic angle curve which depicts the moving organization in real-time. Then, by insetting a generalized super-twisting algorithm, the super-twisting ESO (STESO) is introduced to capture the immeasurable entire disturbances by utilizing the angle state merely. Subsequently, by quoting the impedance control theory, the global terminal angles can be calculated and adjusted basing the human-interaction force, even on the environment mapping. Finally, some theoretical analysis and simulations are collected and provided to demonstrate the correctness and effectiveness for proposed method. © 2024 The Authors.

关键词： Exoskeleton (robotics)

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Latent 3D Scene Graph with Aligned Visual-Language Perception for Object-Goal Navigation 3

Latent 3D Scene Graph with Aligned Visual-Language Perceptio...

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3rd international conference on Mechatronics, control and robotics, ICMCR 2025

作者： Zhang, Jianwei Zhou, Kang Yang, Junjie Li, Xiaojian College of Engineering Southern University of Science and Technology Shen Zhen China School of Computer Science City University of Hong Kong Hong Kong Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shen Zhen China

ISBN: (纸本)9798331544546

Object-goal navigation requires agents to accurately locate and navigate to specified target objects in complex indoor environments. Existing methods primarily rely on single visual observations or simple semantic matching, making it difficult to effectively understand 3D scene relationships between target objects, which leads to inefficient path planning during navigation. Furthermore, the feature discrepancy between visual and language modalities poses challenges for accurate target identification. To address these issues, we propose Latent 3D Scene Graph with Aligned Visual-Language Perception (LSGAP), a novel approach that explicitly models 3D scene relationships between objects through depth perception and latent 3D scene graph construction. Meanwhile, we leverage multimodal pretraining strategies to achieve effective visual-language feature alignment, enhancing the model's target recognition capabilities. This end-to-end architectural design improves spatial cognition ability and enables more efficient navigation decision-making. We conduct extensive experimental evaluations in the AI2THOR interactive environment to validate the effectiveness of our navigator. © 2025 IEEE.

关键词： Depth perception

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