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检索条件"任意字段=3rd International Conference on Robot Intelligence Technology and Applications"

共 6132 条记录，以下是461-470 订阅

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Sustainable Seas RoboScrub: An Arduino based Sludge Cleaning System 3

Sustainable Seas RoboScrub: An Arduino based Sludge Cleaning...

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3rd international conference on Innovative Mechanisms for Industry applications, ICIMIA 2023

作者： Kayalvizhi, S. Akash, M. Gayathri, R. Harini, P. Easwari Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350343632

The maritime industry heavily relies on various fluids stored in ship tanks, encompassing fuel, oils, sludge, sewage, and water. Over time, these fluids solidify, forming layers that necessitate regular cleaning. Traditional cleaning methods pose severe risks to human workers, despite safety measures, with the potential for accidents and explosions [F. The paper underscores the pressing need for a safer and more efficient sludge cleaning solution tailored for ships. To address this, the proposal introduces an innovative approach - an autonomous robot equipped with a specialized attachment explicitly designed for efficient sludge removal. Engineered to navigate and thoroughly clean all tank areas, this technology aims to significantly diminish risks, prevent accidents, curtail time delays, and optimize labor costs associated with sludge maintenance. The integration of this robotic solution not only enhances safety protocols but also revolutionizes the efficiency of sludge management practices in the maritime sector. © 2023 IEEE.

关键词： Maritime Safety Oil Transportation Ship Maintenance Sludge Removal Tank Cleaning robot

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Design and Comparison of Wideband Cascode Low Noise Amplifier using GAA-JLFET and GAA-NC-JLFET for RFIC applications 3

Design and Comparison of Wideband Cascode Low Noise Amplifie...

引用

3rd international conference on Artificial intelligence and Signal Processing, AISP 2023

作者： Raut, Pratikhya Nanda, Umakanta Panda, Deepak Kumar Hsu, Chih-Chieh VIT-AP University School of Electronics Engineering Near Vijayawada522237 India National Yunlin University of Science and Technology Department of Electronic Engineering Douliu Taiwan National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology Douliu Taiwan

ISBN: (纸本)9798350320749

This manuscript describes the design of a wideband Cascode Low Noise Amplifier (LNA) using Verilog-A models and several passive components. In this paper, look up table (LUT) based Verilog-A models for GAA-JLFET (Gate All Around Junctionless FET) and GAA-NC-JLFET (Gate All Around Negative capacitance Junctionless FET) are developed with reference to their TCAD device simulation results. The models are then integrated into the Cadence EDA tool so that the proposed devices may be utilized in circuit simulation. The noise performances of the GAA-NC-JLFET based LNA have been investigated and compared with GAA-JLFET based LNA. © 2023 IEEE.

关键词： Low noise amplifiers

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Artificial intelligence Revolutionizing The Restaurant Industry - Analyzing Customer Experience Through Data Mining and Thematic Content Analysis 3

Artificial Intelligence Revolutionizing The Restaurant Indus...

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3rd international conference on Innovative Practices in technology and Management, ICIPTM 2023

作者： Kaur, Navleen Mahajan, Navita Singh, Vibha Gupta, Astha Amity International Business School Amity University Uttar Pradesh Noida201301 India

ISBN: (纸本)9798350336238

Artificial intelligence is rapidly changing the way restaurants operate. AI can help restaurants increase productivity, streamline processes, and boost customer satisfaction. AI can assist restaurants in creating menus that are suited to their customer's interests and preferences by evaluating data on consumer preferences and purchase history. Moreover, chatbots and virtual assistants powered by AI can be used to collect purchases, respond to consumer inquiries, and make tailored recommendations. As a result, consumers can enjoy a more smooth and delightful dining experience while also saving time and money on labour. Predictive analytics, which may forecast demand for specific items, is another method AI is utilised in restaurants. The intent of this study is to examine the application of Artificial intelligence in restaurant industry and review the opinion of people on the introduction of Humanoid robots in restaurants. AI is a game-changer in the industry, fully transforming the way the industry operates, hence giving a futuristic spin to dining. This research is based on reviews of people about content related to humanoid robots through YouTube videos. Data mining techniques were applied, and Thematic Content Analysis was done to analyze the attitude of people towards human-robot interaction. © 2023 IEEE.

关键词： Anthropomorphic robots

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Advanced Lung Cancer Diagnosis and Treatment with Artificial intelligence: applications, Methods, and Future Directions 3

Advanced Lung Cancer Diagnosis and Treatment with Artificial...

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3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Chaudhari, Pawan Dilip Gudadhe, Amit Maharashtra Wardha442001 India Maharashtra Wardha442001 India

ISBN: (纸本)9798331509675

AI technology revolutionizes the treatment of lung cancer and other related lung cancer diagnoses, hence becoming the game-changing technology in the diagnosis and treatment of this serious disease. As one of the most prevalent and deadliest cancers globally, early identification, precise diagnosis, and efficient planning for the treatment of lung cancer have always been difficult. The therapy using AI-based methods is introducing another novel way of addressing the problems concerning lung cancer via advanced imaging analysis, predictive modeling, and tailored plans of treatment, the most important among which is of course, imaging analysis. What is certainly most exciting among the applications of AI in lung cancer treatment is in the realm of imaging analysis. AI has been seen to be extremely clever in the interpretation of images rather than using machine learning or deep learning but has been much faster and more accurate than a human being while doing it. Besides, these systems also increase the general accurateness of diagnosis through a reduction of the error in diagnosis and consistent results. Alluring promises are made for AI soon for the treatment of lung cancer. In this paper, we discuss how AI has been transformed into imaging, diagnosis, and treatment planning and how this will improve patient outcomes and completely transform the way healthcare is delivered. We also consider barriers still to be cleared for realizing fully the potential benefits of AI. These include problems such as the quality of available data used in model interpretation and generalizability across different healthcare settings. Therefore, we end and suggest some future research on collaboration by emphasizing the safe, effective, and ethical entry of AI into normal clinical practice. © 2025 IEEE.

关键词： Lung cancer

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Structure Design and Simulation of robot Arm for Confined Space Inner Roadway Repair 3

Structure Design and Simulation of Robot Arm for Confined Sp...

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3rd IEEE international conference on Power, Electronics and Computer applications, ICPECA 2023

作者： Chenglin, Hao Shanxi Tiandi Coal Machinery Co.Ltd Taiyuan Institute Taiyuan030006 China China Coal Technology and Engineering Group Co. Taiyuan030006 China National Engineering Laboratory for Coal Mining & Excavation Machinery Equipment Taiyuan030006 China

ISBN: (纸本)9781665472784

In order to solve the problems such as low efficiency, heavy task, low mechanization and potential safety hazards in the process of underground roadway repair in coal mines, a multifunctional mechanical arm with large folding expansion ratio is developed to improve the roadway adaptability of the roadway repair robot and ensure that it can successfully complete the designated roadway repair task in the confined space. This paper introduces the structure composition, working principle and structural characteristics of the multi-functional roadway repair manipulator, and then uses the computer virtual simulation technology to verify the rationality and safety of the manipulator structure. The finite element analysis is carried out in the ANSYS Workbench environment, including the static analysis, dynamic analysis and modal analysis of the manipulator under two extreme working conditions. The analysis results show that the strength of the manipulator meets the requirements;The amplitude of the first six modes of the boom is too large, so it is necessary to increase the rib plate or the thickness of the plate at the appropriate position to improve its stability. © 2023 IEEE.

关键词： Static analysis

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A Brief Survey of Text Classification Methods 3

A Brief Survey of Text Classification Methods

引用

3rd IEEE international conference on Information technology, Big Data and Artificial intelligence, ICIBA 2023

作者： Jiao, Qilu Xiamen Institute of Software Technology China

ISBN: (纸本)9781665490788

Text classification is a long-standing research spot in natural language processing (NLP), which greatly facilitates various NLP tasks. With the rapid development of Internet and social media, the need for effective data management also makes text classification become more and more important. Its research methodology has also developed from the early shallow classification based on handcrafted features to the deep language modeling with various neural networks. In this paper, we first give a brief introduction to its background and definition, and then describe its representative methods at different stages of development. Meanwhile, we also introduce the recently popular pre-trained language models on large-scale corpus, and discuss their applications to text classification. Overall, this paper gives a quick guide to understanding text classification research. © 2023 IEEE.

关键词： Information management

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Prediction of gender from structural MRI images using Multiscale ShuffleNet Extreme Learning Machine 3

Prediction of gender from structural MRI images using Multis...

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3rd international conference on Artificial intelligence For Internet of Things, AIIoT 2024

作者： Stanley, Berakhah.F. Jeen Retna Kumar, R. Gnanaprakash, V. Bini Palas, P. Patturose, J Gold Beaulah Joel Devadass Daniel, D.J. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India SRM Easwari Engineering College Department of Electronics and Communication Engineering Chennai India St. Joseph's Institute of Technology Department of Artificial Intelligence and Data Science Chennai India

ISBN: (纸本)9798350372120

In recent years, the application of machine learning techniques to medical imaging data has shown promising results in various clinical tasks. One such task is the prediction of gender from structural MRI (magnetic resonance imaging) images, which holds potential implications for personalized medicine and understanding neurobiological differences between genders. In this study, we propose a novel approach utilizing Multiscale ShuffleNet Extreme Learning Machine (MSEL), a fusion of Multiscale feature extraction and ShuffleNet architecture with Extreme Learning Machine classifier. We demonstrate the effectiveness of our method on a large dataset of structural MRI images, employing state-of-the-art preprocessing techniques and feature extraction methods. Our results indicate significant accuracy and robustness in gender prediction, outperforming existing methodologies. Furthermore, we conduct comprehensive analyses to investigate the contribution of different components in our proposed framework, shedding light on the underlying mechanisms of gender-related brain structural differences. Overall, our study presents a promising avenue for utilizing advanced machine learning techniques in neuroimaging research, with potential applications in clinical diagnostics and personalized healthcare. © 2024 IEEE.

关键词： Magnetic resonance imaging

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HandEEGnet: A Kolmogorov-Arnold Network for Hand Movements Classification from Motor Imagery EEG 3

HandEEGnet: A Kolmogorov-Arnold Network for Hand Movements C...

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3rd IEEE international conference on robotics, Automation, Artificial-intelligence and Internet-of-Things, RAAICON 2024

作者： Hasan, Tasnimul Hossain, A.B.M. Aowlad Biswas, Shuvagata Tazrin, Farhana Khulna University of Engineering & Technology Department of Biomedical Engineering Khulna9203 Bangladesh Khulna University of Engineering & Technology Department of Electronics and Communication Engineering Khulna9203 Bangladesh Khulna University of Engineering & Technology Department of Computer Science and Engineering Khulna9203 Bangladesh

ISBN: (纸本)9798331534400

Motor imagery-based BCI plays a vital role in controlling hand movements by processing and recognizing features from EEG signals associated with the imagination of those movements. In this paper, we present a Kolmogorov-Arnold Networks (KAN) based framework in order to classify the left and right-hand movements along with the absence of movement's intention from the electroencephalogram (EEG) signal. The emergence of KAN is expected to be a breakthrough concept in the artificial intelligence paradigm considering its learnable activation functions mechanism and interpretability opportunities. Preprocessing of the collected raw EEG data has been accomplished with band-pass filtering of EEG components of five well-matched channels and corresponding power spectral density feature extraction. We have used 15282 samples with annotated classes from a publicly available dataset to train, validate, and test the classifier. A comparative analysis of the performance of KAN and conventional Multi-Layer Perceptron (MLP) networks has been conducted in order to investigate the effectiveness of the KAN for this classification task. The proposed framework attains 96.14% classification accuracy for 3057 blind test samples, which is found to be better than the conventional MLP neural network approach (76.64% accuracy) and compatible with the existing techniques. The finding of this research might be useful in hand movement-related applications for robotics, prosthetics, and neuro-rehabilitation supports. © 2024 IEEE.

关键词： Multilayer neural networks

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A Flexible Hybrid Resource Allocation Model for Enhanced Efficiency using AI in Wireless Sensor Networks 3

A Flexible Hybrid Resource Allocation Model for Enhanced Eff...

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3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Endla, Purushotham Mohandas, R. Saikia, Achinta Lakshmi, C. Karthikeyan, G. Moharekar, Tejashree Tejpal Sr University School of Sciences and Humanities Department of Physics Telangana Warangal506371 India Chennai Institute of Technology Department of Ece Chennai India Mariani College Department of Statistics Mariani Assam Jorhat785634 India Saveetha Engineering College Chennai India Karpagam College of Engineering Department of Artificial Intelligence & Data Science Coimbatore India Shivaji University Yashwantrao Chavan School of Rural Development Maharashtra Kolhapur India

ISBN: (纸本)9798331509675

Wireless Sensor Networks (WSNs) have become a cornerstone technology in various fields, including environmental monitoring, industrial automation, and healthcare. This paper presents a novel hybrid resource allocation model designed to enhance efficiency in Wireless Sensor Networks (WSNs) using advanced Artificial intelligence (AI) techniques. The proposed model integrates static and dynamic resource allocation strategies with machine learning and reinforcement learning to optimize key network resources such as energy, bandwidth, and processing power. Comprehensive evaluations demonstrate that the proposed model outperforms nine existing models across multiple metrics, including energy efficiency, network lifetime, throughput, delay, latency, and accuracy of resource allocation. The proposed model achieved an energy efficiency of 0.98 J/bit, extended network lifetime to 620 days, and maintained a high throughput of 620 Kbps. Notably, the model demonstrated the lowest delay (90 ms) and latency (180 ms) while achieving the highest resource allocation accuracy of 97.8%. These results highlight the model's capability to dynamically adjust resource allocation in response to real-time network conditions, ensuring optimal performance and resource utilization. The proposed model's success in efficiently managing WSN resources marks a significant advancement in the field, offering a robust solution for various WSN applications requiring high efficiency and reliability. © 2025 IEEE.

关键词： Artificial intelligence Energy Efficiency Machine Learning Network Lifetime Reinforcement Learning Resource Allocation Wireless Sensor Networks

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Wheely: An Accessible Platform for Experimenting with Wheeled-Legged Quadrupedal robots 3

Wheely: An Accessible Platform for Experimenting with Wheele...

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3rd international conference on Computer, Control and robotics, ICCCR 2023

作者： Zhang, William Wang, Ke Weston High School Grade 10 Boston United States Imperial College London Robot Intelligence Lab London United Kingdom

ISBN: (纸本)9781665492126

Wheely is a small and inexpensive wheeled-legged quadruped robot made to be an accessible method of experimenting with wheeled-legged robots. The current robotics environment lacks economic wheeled-legged quadrupedal robots for low stakes experimentation and use. The robot uses low-cost and easy to acquire servo motors for a simple, but reliable build. With total costs within 600 dollars, Wheely is around 0.2 m tall and weighs roughly 3 kg. Wheely's simplistic and small-scale nature allows it to be deployed by a single operator and is modification friendly. Wheely is the combination of the best of two worlds, wheeled and legged locomotion, allowing efficient travel on both smooth and rugged terrain. Experiments on robot were conducted in a simulated environment using Pybullet. Wheely is capable of autonomously surmounting stairs 0.05 m tall, 25% of its normal body height, using open loop gaits generated using Bezier curves. On flat surfaces, Wheely can reach speeds of up to 0.09 m/s using wheeled and 0.04 m/s using legged locomotion. Wheely's relatively low-cost and accessible nature will allow for the proliferation of wheeled-legged quadruped technologies and freedom of experimentation. © 2023 IEEE.

关键词： Costs

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