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检索条件"任意字段=10th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2020"

共 309 条记录，以下是21-30 订阅

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Convolutional Neural Network based Digital Twin of Rolling Bearings for CNC Machine Tools in Cloud computing 10

Convolutional Neural Network based Digital Twin of Rolling B...

引用

10th international conference on Dependable systems and their Applications, DSA 2023

作者： Wang, Zhaoming Gong, Siqian Liu, Yang Beijing Jiaotong University School of Mechanical Electronic and Control Engineering Beijing China Nanjing University State Key Laboratory for Novel Software Technology Nanjing China

ISBN: (纸本)9798350304770

CNC machine tool is the mother of industry, and the realization of Intelligent CNC machine tool is an important link to promote the development of intelligent manufacturing. the fault diagnosis of key components of CNC machine tools is very important for the machining process. the traditional fault diagnosis methods have problems such as poor real-time performance and inaccurate prediction. therefore, with the help of digital twin technology and cloud computing, this paper proposes a five-dimensional digital twin system architecture of CNC machine tool rolling bearing based on cloud computing to solve the above problems. And a deep learning technology for data processing is established, which is a hybrid network structure based on CNN-LSTM. Taking the fault diagnosis and prediction of rolling bearing as an example, it is verified that the prediction effect of the algorithm is good, and it can be used for system data processing. © 2023 ieee.

关键词： Cloud computing

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Cybersecurity Issues in Motion control - An Overview of Challenges 10

Cybersecurity Issues in Motion Control - An Overview of Chal...

引用

10th international conference on Electrical, Electronic and computing engineering, IcETRAN 2023

作者： Jakovljević, Živana Nedeljković, Dušan University of Belgrade Faculty of Mechanical Engineering 16 Kraljice Marije Belgrade11000 Serbia

ISBN: (纸本)9798350307115

the fourth industrial revolution known as Industry 4.0 brings digitalization of manufacturing processes to a new level through ubiquitous interconnection and real-time information flow between information technologies (IT) and operational technologies (OT) as parts of Industrial control systems (ICS). this information flow is not limited to but expands beyond factory walls enabling manufacturing systems to adapt quickly and efficiently to changing customer demands and diversified products. the adaptation is carried out through physical and/or functional reconfiguration of manufacturing systems where Industrial Internet of things (IIoT) based on Cyber-Physical systems (CPS) represents the key technical enabler. these changes result in a transition from centralized to distributed control systems architecture where the whole control task is achieved through intensive cooperation between smart devices (e.g., sensors and actuators) with integrated communication and computation capabilities. However, introducing IIoT in ICS brings about new cybersecurity issues due to increased communication between system elements and connection to the global network, making ICS vulnerable to different cyber-attacks with potentially catastrophic consequences. Recently, the research in ICS cybersecurity has intensified leading to significant results for continuous time and discrete events-controlled systems. However, cybersecurity issues in motion control systems that are frequently employed in different manufacturing resources such as machine tools and industrial robots were not sufficiently explored. this work provides an overview of the cybersecurity related challenges in motion control tasks. © 2023 ieee.

关键词： Cyber Physical system

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Automotive CAN-Based Intelligent Collision Avoidance system using Machine Learning and Cloud computing 10

Automotive CAN-Based Intelligent Collision Avoidance System ...

引用

10th international conference on Communication and Signal Processing, ICCSP 2024

作者： Santhuja, P. Selvi, C. Jehan, C. Aghalya, S. Meenakshi, B. Mathivanan, K. Cmr Technical Campus Department of Computer Science and Engineering Telangana Hyderabad India Department of Electronics and Communication Engineering Tamil Nadu Namakkal India Vel Tech Multitech Dr.Rangarajan Dr.Sagunthala Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India St. Joseph's College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Chennai India Sri Sairam Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Adhiparasakthi Engineering College Department of Electronics and Communication Engineering Tamil Nadu Melmaruvathur India

ISBN: (纸本)9798350353068

New automobiles must use controller Area Network (CAN) architecture to meet automation needs and simplify point-to-point wire harnesses. this study offers a complete system that uses a CAN bus-based network to promote effective data transmission inside the automotive environment. Essential data, including speed, distance from other cars, in-car alcohol concentration, and unintentional lane changes, are all monitored by the system's integrated sensors. the technology may successfully avoid accidents by constantly monitoring these factors and immediately alerting the driver if any move beyond the safe range. the system's use goes much beyond simple warnings to drivers. the device uses a bump sensor to detect crashes and immediately sends an SMS message using GSM technology to seek fast help in distant places where accidents may occur. Changing lanes when another car is in the blind area is a prime example of a situation where this technology might be useful. the technology identifies the other vehicle's presence using built-in sensors and alerts the driver before the lane change is initiated, reducing the likelihood of a collision. the suggested system's reliance on CAN bus-based communication increases its adaptability and scalability, making it better able to accommodate the inevitable technological advances of the future. the combination of sensors and immediate warning mechanisms shows the potential of cutting-edge in-vehicle technology to improve road safety and accident avoidance. © 2024 ieee.

关键词： control system synthesis

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RSD-Diff: Boundary-Frequency Feature-Enhanced Rail Surface Defect Inspection with Diffusion-Based Transformer Decoder 10

RSD-Diff: Boundary-Frequency Feature-Enhanced Rail Surface D...

引用

10th international conference on systems and Informatics, ICSAI 2024

作者： Wang, Dezhou Su, Shixiang Lu, Xiaobo School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9798331510138

Rail surface defect inspection is an essential task for the railway system. However, due to the similarity of the background and defect foreground pixels, uneven textures, irregular shapes and multiple scales of the existing defects, the inspection accuracy is still required to be further improved. In this paper, we first expand our dataset by GAN-based method for the scarcity of the defect samples. then, we propose a diffusion-based model to perform the classification and segmentation task. the diffusion model predicts the mask from the Gaussian noise broken ground truth by successive designed transformer decoder. Meanwhile, to better distinguish the pixels in the boundary or other illegible regions, a boundary-frequency feature enhancement module (BFM) is proposed to make the model pay more attention to the defect-related features. Experiments on the rail surface defect dataset revealed that the proposed diffusion-based transformer decoder and BFM can work well together and efficiently improve the rail surface defect segmentation accuracy. © 2024 ieee.

关键词： Decoding

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Traffic control in 6G-Mobile Internet of things Using Recurrent Neural Networks and Fuzzy Logic 10

Traffic Control in 6G-Mobile Internet of Things Using Recurr...

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10th international conference on Smart computing and Communication, ICSCC 2024

作者： Sefati, Seyed Salar Nor, Ahmed M. Fratu, Octavian Halunga, Simona National University for Science and Technology POLITEHNICA Bucharest Telecommunications Department Bucharest Romania

ISBN: (纸本)9798350363104

the Mobile Internet of things (MIoT) refers to a network of interconnected, internet-enabled devices that can communicate and share data together through mobile and wireless networks. this paper presents a novel framework for congestion management in MIoT networks by integrating Long Short-Term Memory (LSTM) networks with fuzzy logic to enhance predictive and adaptive decision-making capabilities for 6G networks. With the proliferation of MIoT devices, network congestion is becoming increasingly problematic, necessitating advanced solutions to maintain efficient data flow and network stability. the approach begins with systematic data collection, capturing essential traffic metrics. this data undergoes to a preprocessing step to facilitate Long Short-Term Memory (LSTM) analysis, focusing on normalization and time-series structuring. the LSTM models are trained to accurately predict traffic patterns, employing strategies such as regularization and dropout to prevent overfitting and enhance model reliability. Subsequently, a fuzzy logic system interprets these predictions, applying a set of linguistic rules to refine the forecasts further. this methodology enables dynamic, proactive management of network congestion, and improves data transmission efficiency and network resource optimization. © 2024 ieee.

关键词： Long short-term memory

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Mathematical Modeling of the Impact of a 5 Day Interim Relaxation at 21 Days in 42 days Lockdown Strategy on COVID-19 Transmission in India 10

Mathematical Modeling of the Impact of a 5 Day Interim Relax...

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10th international conference on Biosignals, Images and Instrumentation, ICBSII 2024

作者： Immaculyne, Flavia Bakiyaambikapathy Krishnamurthy, Kamalanand De Britto, Lourduraj Benoi Cresent Schlumberger- Reda Production System Singapore Vel Tech Rangarajan Dr Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India Anna University Department of Instrumentation Engineering MIT Campus Chennai India Vector Control Research Centre Indian Council of Medical Research Puducherry India

ISBN: (纸本)9798350350951

As of the first week of May 2020, the COVID-19 pandemic is present in 212 nations globally. Many countries have enforced lockdown measures strategically to slow down the epidemic's spread, with the objective of relieving pressure on healthcare systems. Mathematical modelling serves as a useful tool for the prediction of the future numbers of the infected population and for analyzing the effects of various intervention strategies. In this work, a mathematical model based on ordinary differential equations has been developed for analyzing the impact of an interim relaxation of 5 days at 21 days in a 42 days lockdown period. Results of the simulation demonstrate that the relaxation of 5 days during the 42 days lockdown does not result in any adverse effects if the transmission rate remains the same. However, the model-based analysis suggests that an increase in the transmission rate by a factor of 1.2 times during the relaxation period due to the possible aggregation of the susceptible with the infected, it could shift the growth pattern of infected cases from sub-exponential to exponential. © 2024 ieee.

关键词： COVID-19

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Enhancing Fan Base Engagement through Explainable Self-Learning Sentiment Analysis 10

Enhancing Fan Base Engagement through Explainable Self-Learn...

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10th international Multidisciplinary engineering Research conference on Moratuwa engineering Research, MERCon 2024

作者： Lye, Mikael Wijesinghe, Nethmi Informatics Institute of Technology School of Computing Colombo Sri Lanka

ISBN: (纸本)9798331529048

Individuals and brands with large fan bases face difficulty in understanding fan sentiment and its potential impact on fan engagement and performance. this is particularly pertinent within fast-paced sports such as Formula 1, where fan opinions can significantly influence driver and team morale. To address the above-mentioned problem, this study proposes the use of deep learning-based sentiment analysis techniques to enhance fan base engagement. the system would act as a tool to automate the process of marketing and public relations teams by analysing textual data provided by the fan base and providing meaningful insight/reports of the fan base's emotion of the posted content. this is achieved by a novel multi-class sentiment analysis system that utilizes a fine-tuned Distil-BERT model for classification, self-supervised techniques for self-improvement, and an explainable AI (XAI) approach for interpretability. the proposed system demonstrated strong performance during testing and evaluation, achieving an overall accuracy of 82% and an F1-score of 80%. Overall, the systems components and structure focuses on utilizing the least amount of resources while also maintaining a high prediction accuracy and speed. this ultimately results in a budget friendly and robust tool that can be integrated into bigger analytics systems. © 2024 ieee.

关键词： Budget control

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Gender Based Access control system 10

Gender Based Access Control System

引用

10th international conference on Emerging Trends in engineering and Technology - Signal and Information Processing, ICETET-SIP-22 2022

作者： Dube, R.R. Walchand Institute of Technology Electronics and Telecommunication Engineering MH Solapur India

ISBN: (纸本)9781665467414

Gender classification finds out whether the given facial image belongs to male or female. Face detection is feature based approach, the apparent property of the face such as skin color and face geometry are used. Feature based face detection method depends on feature derivation and analysis to gain the required knowledge about face. this recognized gender through classification can be used to give the authorized access at some public spaces or some specific places where particular gender people are expected to come and have access. the system is developed using simple edge computing device Raspberry pi interfaced with camera and solenoid latch. the openCV and python based Artificial Neural Network model is used to classify the gender. this paper discuss the need and implementation of such system with its parametric case study for future implementation. © 2022 ieee.

关键词： Geometry Latches Image color analysis Face recognition Information processing Feature extraction Market research

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Frontal Face Tracking in the thermal Infrared Imaging for Autism Spectrum Disorder Children

Frontal Face Tracking in the Thermal Infrared Imaging for Au...

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ieee international conference on control system, computing and engineering (iccsce)

作者： M.A Rashidan S.N Sidek H.M Yusof A.S Ghazali N Rusli Department of Mechatronics Kulliyyah of Engineering International Islamic University Malaysia 53100 Jalan Gombak Kuala Lumpur Malaysia ProStrain Technologies 1-10 HIVE 12 Taman Teknologi MRANTI Bukit Jalil Kuala Lumpur Malaysia

the research and application of therapeutic robotics for children have gained significant attention. this study introduces a system for emotion recognition in Autism Spectrum Disorder (ASD) children that utilizes infrared thermal imaging cameras to capture the frontal facial images. the paper focuses on the development to automate, recognize and track the subjects frontal face using the Shape-Adapted Mean Shift algorithm (SAMShift) applied to thermal images. this system targets the identification of affective states in ASD children and employs non-invasive thermal imaging instead of invasive sensor patches. By integrating tracking and affective state analysis within a single modality, the system addresses the limitations of traditional visual-based systems, which often suffer from invasiveness due to the use of sensor patches, difficulty in automating and tracking facial features, and challenges in accurately identifying affective states. the SAMShift algorithm, implemented in the LabVIEW® vision module environment, is utilized for tracking the frontal face image. Experimental results demonstrate the effectiveness of the proposed method, achieving an average accuracy of 89.20% and an average precision of 95.40%. this research contributes to advancing the field of therapeutic robotics for children with ASD by providing an automated, non-invasive, and accurate approach to emotion recognition.

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Modeling and Verification of Inter-Station Section Direction control Function Applicable to TBTC and CBTC 10

Modeling and Verification of Inter-Station Section Direction...

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10th international conference on Information systems and computing Technology, ISCTech 2022

作者： Pan, Liang Zhang, Lei CASCO SIGNAL LTD. System Integration Department Shanghai China Engineering Tongji University Tongji University Department of Traffic Information and Control Shanghai China

ISBN: (纸本)9798350332933

In the process of requirement analysis of Interstation Section Direction control function applicable to TBTC and CBTC, to prevent the introduction of inherent safety defects due to misunderstanding of requirements. the formal method is used to improve the accuracy of describing the functional requirements of Inter-station Section Direction control, enhance the rationality of design, and reduce the risk of introducing safety defects. First, the EVENT-B language model of each layer is established by using state transition diagram and refinement strategy, and the safety characteristics of the system are verified by proving the invariant proof obligation. through the accuracy and hierarchy of the formal modeling process and the corresponding verification activities, it is proved that the method is feasible and efficient. © 2022 ieee.

关键词： Defects

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