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共 47828 条记录，以下是601-610 订阅

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A Review on DeepLungNet: CNN-Based Lung Cancer Detection Techniques Using CT Images

A Review on DeepLungNet: CNN-Based Lung Cancer Detection Tec...

引用

2024 international conference on advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Nair, Surabhi S. John, Asha Susan Raju, Juby Musaliar College Of Engineering And Technology Department Of Electronics And Communication Engineering Pathanamthitta India Kalasalingam Academy Of Research And Education Department Of Electronics And Communication Engineering Virudhanagar Tamil Nadu Krishnan kovil626 126 India Hindustan Institute Of Technology And Science Department Of Computer Science Engineering TamilNadu India

ISBN: (纸本)9798350364828

The disease known as lung cancer, which is common and frequently deadly, starts in the cells of the lungs and causes symptoms like exhaustion, chest pain, and persistent coughing. Since small cell lung cancer (SCLC) is less frequent but more dangerous than non-small cell lung cancer (NSCLC), knowledge of its causes, including smoking, pollution, and genetic factors, is essential. Survival rates are greatly increased by early identification by about 20%. This study comprehensively analyzes deep learning and machine learning models-based lung cancer prediction methods from 2016 to 2023. The review emphasizes how well these models work to achieve greater accuracy. Expanding on this, a new method is suggested that combines data augmentation and denoising preprocessing methods with a CNN in a ResNet architecture for classification. The goal of this hybrid model is to maintain and improve accuracy levels in the identification of benign and malignant lung pictures. This methodology offers promising promises for more accurate and reliable lung cancer prediction by utilizing advances in both preprocessing and classification techniques. © 2024 IEEE.

关键词： Diseases

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Personalized Gait Generation Using Convolutional Neural Network for Lower Limb Rehabilitation Robots

Personalized Gait Generation Using Convolutional Neural Netw...

引用

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

作者： Ren, Jiale Wang, Aihui Meng, Lin Li, Hengyi Wang, Yan Zhongyuan University of Technology School of Automation and Electrical Engineering Zhengzhou451191 China Ritsumeikan University Research Organization of Science and Technology Kusatsu525-8577 Japan Ritsumeikan University College of Science and Engineering Kusatsu525-8577 Japan

ISBN: (纸本)9798350372601

In walking training, tailoring the gait trajectories to accommodate individual patient conditions is pivotal for improving the effectiveness and comfort of rehabilitation. This paper proposes a novel gait generation model based on 1D convolution techniques, capitalizing on the correlation between gait patterns and physiological parameters to learn personalized gait patterns. Firstly, the method applies Fourier fitting to the gait trajectories, incorporating data from hip and knee joints, thereby transforming fitted parameters into a comprehensive representation of the gait trajectory. To improve the network's capability of feature extraction, a multi-branch architecture is utilized, incorporating the squeeze and excitation (SE) blocks to fine-tune the channel weights. Furthermore, the model undergoes structural re-parameterization, a process that converts the multi-branch structure into a single-path structure. This procedure significantly reduces memory usage and computational demand without sacrificing accuracy. Comparative analysis reveals that our model outperforms existing benchmarks, achieving the lowest average loss of 0.1124, thereby demonstrating exceptional generalization capabilities. The optimized model further achieves a 35.63% reduction in inference time, with a negligible average error discrepancy. The generated gait trajectories are intended to serve as reference paths for lower limb rehabilitation robots, thereby offering the groundwork for delivering personalized training to patients. © 2024 IEEE.

关键词： Exoskeleton (robotics)

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Evaluation of Global Sizes and Cylindricity Errors Based on fminimax Optimization Function 2

Evaluation of Global Sizes and Cylindricity Errors Based on ...

引用

2nd international conference on Automation, robotics and Computer engineering, ICARCE 2023

作者： Zhao, Xinyu Zhao, Zexiang Ren, Dongxu School of Computer Science Zhongyuan University of Technology Zhengzhou China School of Mechatronics Engineering Zhongyuan University of Technology Zhengzhou China Technology for Mechanical Industry Key Laboratory of Optical Sensing and Testing Zhengzhou China

ISBN: (纸本)9798350308341

Based on the evaluation definitions of minimum circumscribed, maximum inscribed and minimum zone methods for global sizes and cylindricity errors of cylinder, the optimization objective function of the axis parameters of the reference cylindrical surfaces and the evaluation models of global sizes and cylindricity errors were built. The subprograms for the optimization objective functions of the axis parameters of the reference cylindrical surfaces and the evaluation of global sizes and cylindricity errors were written by using Matlab language. The roundness profiles of four cylindrical samples were extracted, and their global sizes and cylindricity errors were evaluated based on least square, minimum circumscribed, maximum inscribed and minimum zone methods. The evaluation results of the optimization characteristic values of fminimax optimization function were compared with those evaluated by using other optimization methods, and it turned out that the accuracy of the optimization objective characteristic values of fminimax optimization function are higher or equal to those evaluated by other optimization methods, which is suitable to the application in the evaluation of global sizes and cylindricity errors. © 2023 IEEE.

关键词： Least squares approximations

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Angular Velocity Estimation in Asymmetric IMU Array 2

Angular Velocity Estimation in Asymmetric IMU Array

引用

2nd international conference on Automation, robotics and Computer engineering, ICARCE 2023

作者： Li, Yanzhi Zhou, Zebo School of Aeronautics and Astronautics University of Electronic Scicence and Technology of China Chengdu China

ISBN: (纸本)9798350308341

This paper is primarily dedicated to the methodology for angular velocity estimation. Initially, a specific force equation is formulated utilizing an accelerometer to establish the relationship between a single Inertial Measurement Unit (IMU) and the centroid of the asymmetric array frame. Within this framework, a Bias-Estimation Extended Kalman Filter (EKF) method is employed to enhance the precision of angular velocity estimation. Additionally, the estimation of acceleration and angular acceleration is integrated to refine orientation within the Kalman filtering process. Moreover, to simulate the presence of IMU noise, the accelerometers' biases are estimated and treated as time-varying variables rather than fixed constants. A simulation study is conducted to demonstrate the validity and efficacy of the proposed angular velocity estimation methodologies. © 2023 IEEE.

关键词： Accelerometers

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Advancing Personalized Recommendation Systems with a Groundbreaking Collaborative Filtering Algorithm Driven by Machine Learning 2

Advancing Personalized Recommendation Systems with a Groundb...

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2nd IEEE international conference on advances in Information technology, ICAIT 2024

作者： Anbalagan, E. Sasikumar, S. Kumar, M. Guru Vimal Paramesh, J. Sriram, K.P. Professor Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Professor Department of Computer Science and Engineering Saveetha Engineering College Chennai Associate Professor Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Professor Department of Computer Science and Engineering Mohamed Sathak A.J. College of Engineering Ekattu Siruseri Chennai India Assistant Professor Information Technology St.Joseph's Institute of Technology Chennai India

ISBN: (纸本)9798350383867

By introducing this collaborative filtering algorithm, which is dependent on machine learning that can be used in enhancing the user-based recommendation systems, this paper is trying to achieve more advanced personalized recommendation systems. Utilizing recent innovative designs of networks together with relevant contextual information, the algorithm provides high accuracy recommendation, scalability, and aids in improving user experience than traditional approaches. The model is shown to perform exceedingly well in all respects by its being subjected to a thorough assessment and compared with the baseline and enhanced models. It joins ranks with the best in all the indices of performance like precision, recall, F1-score, mean average precision and user satisfaction. In addition, hyperparameter tuning, and scalability metrics, so ending efficiency for model configuring and deployment recommendation models which could deal with large-scale datasets and offer users timely suggestions are of vital importance. To summarize, these results highlight the disruptive character of the latest machine learning algorithms that might create a new reality of recommendation systems with the trend of the time of individualization of relationships in the digital world. ©2024 IEEE.

关键词： Collaborative filtering

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Model Predictive Event-Triggered Non-Fragile Fault-Tolerant Control for IT2 T-S Fuzzy Systems with Static Output Feedback 6

Model Predictive Event-Triggered Non-Fragile Fault-Tolerant ...

引用

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

作者： Liu, Rui Li, Yueyang Zhao, Dong School of Electrical Engineering University of Jinan Jinan China School of Cyber Science and Technology Beihang University Beijing China

ISBN: (纸本)9798350315301

This paper presents an innovative event-triggered non-fragile fault-tolerant control approach towards the interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy systems subject to bounded disturbances and actuator faults based on model predictive control (MPC) strategy. The proposed fault-tolerant control method integrates both an event-triggered strategy to alleviate the transmission pressure and energy consumption of the network and a non-fragile controller design strategy to remain resilient to potential gain perturbations. Quadratic bounded (QB) technology is used to design static output feedback controllers. Moreover, the proposed method guarantees recursive feasibility and quadratical stability of closed-loop dynamics. The validity of method is verified through an example. © 2023 IEEE.

关键词： Model predictive control

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Green Vision: Plant Care Monitoring System 1

Green Vision: Plant Care Monitoring System

引用

1st IEEE international conference on Cognitive robotics and Intelligent Systems, ICC - ROBINS 2024

作者： Nithish, M. Denisha, M. Karunya Institute of Technology and Sciences Division of Computer Science and Engineering Coimbatore India

ISBN: (数字)9798350372748

ISBN: (纸本)9798350372748

The entire human development process is dependent on plants, however caring for them can be quite difficult. The occurrence of different type of diseases that are difficult to identify have blended into these plants. This research study has recognized the usage of technology such as mobile applications and Convolutional Neural Networks [CNN] to examine the afflicted plant and to lessen the human efforts whenever scientists or doctors are unable to travel to different locations to examine them. This study has developed an Android smartphone application, which allows users to remotely analyze their plants and determine which diseases they may have entrenched in them and provide cure for it. All it takes is taking a picture of the plant with a camera or importing it from the gallery to receive diagnosis reports and the cures and needs for it with a simple user-interface, which will help all users to use it easily. © 2024 IEEE.

关键词： Diagnosis

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Intelligent Recognition of Leaf Abnormalities Using Deep Learning Method

Intelligent Recognition of Leaf Abnormalities Using Deep Lea...

引用

2023 international conference on Recent advances in science and engineering technology, ICRASET 2023

作者： Anusha, M.N. Prafulla, P.S. Prabhavathi, K. Divyashree, R.H. Kiran Srividya, C.N. Bgs Institute of Technology Dept. of Electronics & Communication Mandya India Vidyavardhaka College of Engineering Dept. of Electronics & Communication Mysuru India

ISBN: (纸本)9798350306927

Deep Neural Networks (DNNs) have significantly improved the detection of different diseases affecting plants. The impact of unidentified and untreated plant diseases is to reduce crop yield significantly, as they negatively affect the quality and quantity of horticultural and agricultural products. Therefore, early recognition of plant diseases is essential for improving crop quality and reducing production losses. To this end, a modern framework has been developed that incorporates image acquisition and analysis, utilizing DNN models to calculate various evaluation metrics such as Recall, F1 scaling, accuracy, and precision. By diversifying the results, it becomes possible to differentiate between healthy and bacterial plant leaves. The proposed methodology has been tested on two types of plants - pepper, and potato - and can determine the percentage of infection on plant leaves. © 2023 IEEE.

关键词： Image acquisition

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Mechatronic Design of an Omnidirectional Octorotor UAV 10

Mechatronic Design of an Omnidirectional Octorotor UAV

引用

10th international conference on Automation, robotics, and Applications, ICARA 2024

作者： Hamandi, Mahmoud Ali, Abdullah Mohamed Evangeliou, Nikolaos Chaikalis, Dimitris Tzes, Anthony Kyriakopoulos, Konstantinos Khorrami, Farshad Center for Artificial Intelligence and Robotics Abu Dhabi129188 United Arab Emirates Electrical Engineering NYUAD Abu Dhabi129188 United Arab Emirates New York University Electrical and Computer Engineering BrooklynNY11201 United States

ISBN: (纸本)9798350394245

The design of an omnidirectional octorotor (OmniOcta) is the scope of this article. The pose of the UAV's thrusters is computed via an optimization algorithm that guarantees the omnidirectionality of the platform. The thrusters' positions are restricted in a semispherical volume with different polar coordinates while their pose is determined in order to avoid the interaction between their propellers' air-funnels. The octorotor is manufactured using 3D printed parts and its employed electronics were selected so as to have the smallest weight. The number of thrusters was then selected as the minimal number that could lift the platform's weight in all rotation directions with the chosen electronic and aerodynamic components. Simulations were conducted to show the capacity of the UAV to lift its weight, while experiments were conducted to identify the allocation matrix of the constructed UAV. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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An Efficient, Affordable and Reliable SMPS Battery Chargers for Automobile Industry 2

An Efficient, Affordable and Reliable SMPS Battery Chargers ...

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

作者： Niveditha, J. Venkatesh, T. Reethika, A. Ramya, U. Sreejaa, S. Vinothini, V. Department of Electronics and Communication Engineering KPR Institute of Engineering and Technology Coimbatore India Department of Electronics and Communication Engineering Sri Ramakrishna Engineering College Coimbatore India Department of Computer Science and Engineering Sri Ranganathar Institute of Engineering and Technology Coimbatore India

ISBN: (纸本)9798331541217

As we are utilizing Conventional vehicles, Electric Vehicles require charging the batteries, so the chargers for batteries are becoming more and more crucial within the automobile industry. While the current chargers mostly rely on bulky and inefficient transformer models, this proposed work aims to explore the integration of Switched-Mode Power Supply (SMPS) technology. The method employed in this work is that replaces the charging based on transformers with SMPS technology, with the goal of improving efficiency, reducing size, and reducing heat generation. The result of the project has a successfully developed battery charger that utilizes SMPS technology. It has achieved increased efficiency, reduced size, and lower heat generation in comparison to traditional models. Furthermore, the revised charger exhibits a simpler and more affordable circuit, catering to a wider consumer base. As a result, this product can be used in both workshops and automobile showrooms with more efficiency at an affordable cost. © 2024 IEEE.

关键词： Automotive industry

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