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共 15474 条记录，以下是171-180 订阅

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Robust Learning-Based Impedance control of Robotic Manipulators in Unknown Environments 16th

Robust Learning-Based Impedance Control of Robotic Manipula...

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16th APCA international conference on automatic control and Soft computing, controlO 2024

作者： Nazmara, G. Reza Neto, Pedro Aguiar, A. Pedro Faculty of Engineering SYSTEC-ARISE Research Center for Systems and Technologies University of Porto Porto4200-465 Portugal Department of Mechanical Engineering - POLO II University of Coimbra Coimbra3030-788 Portugal

ISBN: (纸本)9783031817236

This research focuses on implementing Machine Learning Impedance control for robot arms to ensure both effective and safe interaction within unknown environments. The designed Machine Learning system comprises two key steps. Firstly, a Neural Network Classifier framework categorizes attributes by assigning labels to various impedance behaviors. Secondly, employing a regularization technique, the system determines the appropriate impedance behavior as a command signal for the internal control loop. Utilizing a backstepping-based algorithm alongside Taylor’s parameter adaptation within the control loop facilitates achieving effective interaction. To validate the efficacy of this control approach, the proposed method undergoes testing and simulation on a two-link robot manipulator across varying environmental stiffness levels. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Robotic arms

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Radius-Based Authentication: UFrames’ Novel Approach to Prevent Account Sharing 5th

Radius-Based Authentication: UFrames’ Novel Approach to Pre...

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5th international conference on computing and Network Communications, CoCoNet 2023

作者： Vardhan, D. Sai Tanmayi, Doddapaneni Rakesh, Kakaraparthi Sreevidya, B. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9789819745395

OTT platforms such as Netflix and Amazon Prime have been in the market for more than a decade. They have come to full-fledged usage especially during the lockdown. The main reason for their magnanimous success is ease of use and feasibility to access unlimited content anywhere and anytime with basic Internet connection. The features in OTT have made accessing the content and viewing the content easy and delightful for the users. However, the "sharing account" option enabled for a single user to access the content from multiple devices is instead being used to share one account among multiple users, negatively affecting the business of OTT creators. In this paper, the focus is to build an OTT platform that proves advantageous to both users and providers. Besides the prevailing features that are found across platforms, including sign-in and sign-up functionalities, categorized content selection, and payment options, the proposed system enables automatic sign-out when the non-primary device strays beyond range from the primary device, content uploading, and more. Furthermore, there is a proposal to implement a GPS technology-based mechanism aimed at preventing users from sharing their accounts with others. The proposed approach conceptually and experimentally proves to be beneficial to the OTT platforms from a business perspective. The scheme is able to prevent users from sharing the account beyond a geographical limit, thus improving the profit. At the same time, these stringent requirements are developed in such a way that a balance is made between user experience, ease of use experience along with improved security measures. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Global positioning system

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Zonotope-based fault estimation for Lipschitz nonlinear systems 3

Zonotope-based fault estimation for Lipschitz nonlinear syst...

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2024 3rd international conference on Aerospace and control engineering, ICoACE 2024

作者： Ma, Siyuan Zhang, Wei Jiang, Qiang Gao, Sheng School of Automatic and Electrical Engineering Shenyang Ligong University Shenyang110158 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China China-Portugal Belt and Road Joint Laboratory on Space & Sea Technology Advanced Research Shanghai200120 China

An estimation of fault intervals using a T-N-L structured observer is suggested for Lipschitz nonlinear systems. By augmenting state vectors, the augmentation system and its observer are established, enabling the observer to concurrently estimate fault and system states. The L∞ performance is applied to enhance the resilience of the fault interval estimation to external disturbances and unanticipated inputs. An adequate requirement for the observer design is also presented. The interval estimation of states and faults is ultimately created by using a zonotope. The proposed method exhibits advantages and feasibility when compared to existing simulation techniques. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Nonlinear systems

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Enhancing IoT-Driven Smart Home Security and Automation with a GCN Model 3

Enhancing IoT-Driven Smart Home Security and Automation with...

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3rd international conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Ganti, Sreelakshmi Vankayalapati, Ravi Kumar Krishnamoorthy, P. Thakare, Pallavi S. Nayak, Ullal Akshatha Vignesh, P. Geethanjali College of Engineering and Technology Department of Electronics and Communication Engineering Medchal India Equinix TX United States Sasi Institute of Technology & Engineering Department of Computer Science and Engineering West Godavari India Dr D. Y. Patil Institute of Technology Department of Information Technology Pimpri India Nitte Meenakshi Institute of Technology Department of Information Science and Engineering Bangalore India Kcg College of Technology Department of Mathematics Chennai India

ISBN: (纸本)9798331508456

A network of computing devices and sensors, the Internet of Things (IoT) rapidly exchanges data to assess circumstances and propose new services. Intelligent home technologies rely on IoT. Contemporary smart home systems offer automatic lighting control, smoke detectors, temperature sensors, and smart lock installations. But these technologies raise serious privacy and security concerns. Security flaws let hackers access sensitive data, sendoff false alarms, and take control monitoring systems. Smart home technology is vulnerable to many threats because consumers are wary of it. Recommended steps are preprocessing, sensing, and model training. Preparing raw, unstructured data for analysis. DHT11 humidity and temperature sensors and HC-SR501 PIR motion detectors collect data. It trained the model using Multiscale DGCN data. Better than GCN and BiLSTM, Multiscale DGCN performs. It uses Internet of Things-based smart home security data well, with an average accuracy rate of 93.87%. Identifying outliers in sensor data solves major smart home security challenges. Increasing smart home system accuracy reduces security concerns and boosts user trust, which may drive adoption. © 2025 IEEE.

关键词： Smart homes

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Enhancing Emotion Recognition from Speech Signals Using Deep Learning and Open-Source Datasets

Enhancing Emotion Recognition from Speech Signals Using Deep...

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2025 international conference on Intelligent control, computing and Communications, IC3 2025

作者： Anandhi, R.J. Kansal, Lavish Singh, Jay Subhashini, P. Jabbar, Fatimah Dhari Priya, R. Sathiya Prasanna, J. Lakshmi New Horizon College of Engineering Department of Information Science Engineering Bangalore India Lovely Professional University Phagwara India Gl Bajaj Institute of Technology and Management Dept. of Eee U.P. Gr. Noida India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India College of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India Griet Department of Cse Bachupally Telangana Hyderabad India

ISBN: (纸本)9798331527495

In this work, we focus on emotions from speech signals using deep learning methods on the RAVDESS database. The audio signals are preprocessed by means of sampling, normalization and the subsequent feature extraction in the form of Mel Frequency Cepstral Coefficients (MFCCs). Classification of emotions is then performed using a Convolutional Neural Network often abbreviated as CNN. The model's performance is therefore measured with performance metrics including accuracy, precision, recall, and F1 score, to give a measure of the model's capabilities in detecting emotions from voices. The results of the confusion matrix analysis help to understand better the ability of the model to predict different emotions. The analysis proves the significance of deep learning approaches, for example, CNNs that significantly outperform classical approaches in terms of emotion recognition rates. The study also finds out the audio features, which have very high impact in the classification of emotions and contains finding that will be useful for further improvements of affective computing. © 2025 IEEE.

关键词： Convolutional neural networks

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Identification of control Law and Trajectory for Mobile Disturbance Rejection in a 2D Thermal Context 16th

Identification of Control Law and Trajectory for Mobile D...

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16th APCA international conference on automatic control and Soft computing, controlO 2024

作者： Fakih, Sara Perez, Laetitia Autrique, Laurent LARIS Polytech University of Angers 62 avenue notre dame du lac Angers49000 France

ISBN: (纸本)9783031817236

In the realm of thermal systems governed by parabolic partial differential equations, achieving precise control and trajectory of mobile heating sources creates a formidable challenge, particularly in the presence of moving disturbances. This study delves into the thermal dynamics of a 3D steel plate, typically analyzed in 2D due to its negligible thickness. Initially, the plate maintained equilibrium through natural convection and heat fluxes subjected to its surface. However, mobile disturbances existence has disrupted this balance, significantly across a fixed array of sensors. To track and reject these perturbations, the identification of control and trajectory of a mobile disk is studied. This process is treated as an inverse heat conduction problem, known as ill-posed. Consequently, the conjugate gradient regularization method is applied. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Thermal engineering

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Artificial Neural Network-Based Fast Power Reserve control for Active Power Balancing

Artificial Neural Network-Based Fast Power Reserve Control f...

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international conference of the TC Electrimacs Committee, ELECTRIMACS 2024

作者： Tannous, Antonella Razi, Reza Binot, Ferréol Francois, Bruno Univ. Lille Arts et Metiers Institute of Technology Centrale Lille JUNIA Lille France

ISBN: (纸本)9783031739200

Microgrids play a crucial role in modernizing the power grid by facilitating the integration of renewable energy sources. However, these sources exhibit high intermittency and stochastic behaviour, leading to challenges in effectively managing a microgrid amidst varying load demand and unexpected grid events. To address these uncertainties, local advanced control methods that leverage real-time data and enhanced computing capabilities are required. Frequency droop controllers generate additional power faster than the allocated power reserve to achieve an instantaneous balance of the electrical system. The automatic frequency restoration consists in making other generators participate gradually after 30 seconds. This paper proposes an intelligent control technique designed to enhance the static frequency droop controller, aiming to achieve active power balancing while minimizing CO2 emissions and operating costs. Consequently, an artificial neural network-based adaptive module is developed to anticipate and substitute the diesel-based reserve with a low carbon footprint reserve. This module considers new influencing input factors to anticipate and adjust the power setpoints of a stationary storage unit. The effectiveness of the proposed method is demonstrated on an islanded AC microgrid. The real-time simulation is conducted and validated on Opal-RT simulator, showing improved active power balancing while reducing both costs and CO2 emissions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Microgrids

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Peer-to-Peer Integrated Smart Gardening Automation Using Cloud Technology with Real-Time Environmental Monitoring and Logging via Blynk Cloud Dashboard

Peer-to-Peer Integrated Smart Gardening Automation Using Clo...

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2025 international conference on Intelligent control, computing and Communications, IC3 2025

作者： Malik, Praveen Kumar Bharti, Veena Misra, Neeti Yamsani, Nagendar Mahajan, Anshul Singh, Parulpreet School of Electronics and Electrical Engineering Lovely Professional University Punjab Phagwara India Raj Kumar Goel Institute of Technology Ghaziabad India Uttaranchal Institute of Management Uttaranchal University Department of Management Uttarakhand Dehradun India School of Computer Science and Artificial Intelligence Sr University Warangal India

ISBN: (纸本)9798331527495

The authors of this article discuss the holistic method of automation of gardening operations based on IoT technology that allows real time environmental factors to be monitored, decisions to be made based on data, and those decisions to be executed at a distance. The objective of the system is to minimize the amount of water used, to improve the state of the plants, and ultimately to allow the users of the system to control their gardens from anywhere in the world with as little effort as possible. The concept makes use of the continuously monitored network of sensors to observe important parameters like soil moisture, temperature, humidity, light intensity and rainfall among others. After being received, this information is up to date and the system will use this data to manage irrigation and lighting systems for the plants efficiently. Also, the support of this cloudbased platform is essential today as it allows the users to look up the parameters in their garden remotely and go for manual intervention when required. All the advantages of cloud technology provide remote control of the system but also all the historical data sets which are important trends in future decision making. © 2025 IEEE.

关键词： Green computing

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Improving the Multi-scale Object Detection Method of YOLOv5s for Autonomous Driving

Improving the Multi-scale Object Detection Method of YOLOv5s...

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international conference of electrical, Electronic and Networked Energy Systems, EENES 2024

作者： Li, Ying Wang, Guifang Wang, Jialu Zhang, Jianing Zhu, Changfei School of Electrical and Control Engineering Liaoning Technical University Liaoning Huludao125105 China School of Mathematics and Systems Science Shenyang Normal University Liaoning Shenyang110034 China

ISBN: (纸本)9789819618675

In response to the challenges posed by high-speed vehicle movement and the complex and dynamic surrounding environment, accurately identifying and locating objects of different scales such as cars, pedestrians, and traffic signal lights is not an easy task. This paper proposes an automatic driving multi-scale object detection method called GSM-YOLO. Firstly, by introducing a small object detection layer, the detection performance for small objects is enhanced. Subsequently, a GSE-SPPF module is designed to increase the feature extraction capability of the main network. Furthermore, in the neck network, the SC-ELAN structure is proposed to efficiently utilize spatial and channel information among features, capturing target information of different scales and reducing information loss. Finally, the MPDIOU function is utilized to optimize loss, improving the convergence speed and accuracy of the network. Experimental results show that on the autonomous driving BDD100K dataset, the GSM-YOLO algorithm outperforms the YOLOv5s algorithm, achieving an average precision increase of 6.1% to reach 55.7%. Additionally, the detection speed reaches 111.1 frames per second. The proposed improvement method effectively realizes object detection in road environments and can be widely applied in research related to autonomous driving object detection. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Traffic signals

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Auto Labeling for Liver CT Image Based on Edge Detection and Region of Interest Segmentation 16th

Auto Labeling for Liver CT Image Based on Edge Detection and...

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16th international conference on Genetic and Evolutionary computing, ICGEC 2024

作者： Horng, Jun-Yan Ho, Jiun-Huei Lo, Chun-Chih Shieh, Chin-Shiuh Horng, Mong-Fong Department of Electronic Engineering National Kaohsiung University of Science Kaohsiung Taiwan Cheng Shiu University Kaohsiung Taiwan

ISBN: (纸本)9789819615346

This study proposes an automatic labeling method for liver regions in Computed Tomography (CT) images, addressing the time-consuming nature of manual medical image labeling. The approach utilizes edge detection to identify overall edge distributions in CT images, constrains the region of interest to locate characteristic liver areas, and performs object segmentation to generate liver masks for labeling. The method tackles key challenges in liver CT image analysis, including image noise, blurred edge features, and minimal pixel differences in suspected tumor areas. It employs Gaussian blur for noise reduction, followed by brightness and contrast adjustments to enhance edge characteristics. The watershed algorithm is then applied to segment the complete liver contour. Performance evaluation using approximately 17,000 images from the LiTS datasets demonstrated an average accuracy of 75% for liver labeling, with a maximum of 80% and a minimum of 62%. The process achieves a labeling speed of about 1 s per 100 images, highlighting its efficiency. The proposed method shows promise in automating liver labeling in CT images, potentially streamlining the image analysis process in medical research and diagnosis. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Noise abatement

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