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检索条件"任意字段=International Conference on Process Automation, Control and Computing"

共 28217 条记录，以下是151-160 订阅

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EEG Based Emotion Recognition using Variational Mode Decomposition and Convolutional Neural Network for Affective computing Interfaces 11

EEG Based Emotion Recognition using Variational Mode Decompo...

引用

11th international conference on control, Mechatronics and automation (ICCMA)

作者： Dondup, Thacchan Manikandan, M. Sabarimalai Cenkeramaddi, Linga Reddy Indian Inst Technol Palakkad Dept Elect Engn Palakkad Kerala India Univ Agder Informat & Commun Technol Grimstad Norway

ISBN: (纸本)9798350315684

Human emotion recognition plays a vital role in brain-to-brain communication, human-machine interactions and affective computing interfaces. This paper presents electroencephalogram (EEG) based emotion recognition using variational mode decomposition (VMD) and convolutional neural network (CNN) by finding optimal hyperparameters for recognizing three emotional classes: positive, neutral and negative. The two-stage VMD based EEG processing is proposed for effectively removing artifacts and noises from the EEG signal and also for decomposing EEG signal into five brain waves such as delta, theta, alpha,beta and gamma. The CNN based emotion recognition is presented based on the differential entropy feature extracted from 1 second brain waves instead of using brain waves directly in order to reduce size of CNN model. In this study, we created twelve CNN models using three number of layers (2, 5, and 7) and four activation functions with major objective of finding best CNN model(s). The standard SEED database is used to obtain trained CNN models and test their performance. Evaluation results show that the CNN architecture with rectified linear unit (ReLU) yielded higher accuracy of 90.33% among four activation functions. For predicting emotions of positive, negative and neutral, the CNN model with 2-layer and ReLU achieves an accuracy of 100%, 94.44% and 78.2%, respectively whereas the CNN model with 7-layer results in accuracy of 100%, 94.40% and 89.13%, respectively. This study also demonstrates significance of selecting optimal hyperparameters and best activation function.

关键词： Electroencephalogram Emotion classification Variational mode decomposition Convolutional neural network brain-to-brain communication and affective computing

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Data Integration in Smart Energy Meter Using Cloud computing 8

Data Integration in Smart Energy Meter Using Cloud Computing

引用

8th IEEE international conference on computing, Communication, control and automation, ICCUBEA 2024

作者： Ghodake, Asha Sale, Hanamant More, Ayush A. Nalawade, Pankaj .S Patil, Chaitrali V Patil, Dimple B. Bharati Vidyapeeth College of Engineering Department of Electronics & Telecommunication Engineering Navi Mumbai India Bharati Vidyapeeth College of Engineering Department of Information Technology Navi Mumbai India

ISBN: (纸本)9798350391770

Smart energy management systems, or SEMS, are intended to increase the efficacy and efficiency of energy use in a range of contexts, including residences, workplaces, and entire communities. These systems monitor and manage energy use in real time using cutting-edge IoT and communication protocols including GSM, Zigbee, and the Internet of Things. The use of cloud computing, which enables the central storage and analysis of enormous amounts of data, is one way to implement SEMS. Anywhere with an internet connection can access this data, which can be used to track energy consumption, pinpoint areas for development, and adjust and cut down on energy waste. In addition to improving energy efficiency, SEMS can also help reduce energy costs and contribute to a more sustainable energy future. By using advanced technologies and communication protocols, these systems can help individuals, businesses, and communities make informed decisions about their energy usage and take steps to reduce their carbon footprint. © 2024 IEEE.

关键词： cloud computing efficiency Energy IoT management Zigbee

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Neuro-Adaptive Dynamic control with Edge-computing for Collaborative Digital Twin of an Industrial Robotic Manipulator

Neuro-Adaptive Dynamic Control with Edge-Computing for Colla...

引用

IEEE international conference on Robotics and automation (ICRA)

作者： Das, Sumit Kumar Uddin, Mohammad Helal Popa, Dan O. Baidya, Sabur Univ Louisville LARRI Louisville KY 40292 USA

ISBN: (纸本)9798350323658

With the advancement of industrial manufacturing and an increase in introduction of robots in the workspace, the need of safe operation, communication and information sharing is paramount. The work presented here focuses on cyber-physical system integration through Digital Twin (DT) technology. Our novel DT architecture is based on a modelfree Neuro-Adaptive controller (NAC), and an edge-computing scheme for scene monitoring. The NAC can account for varying robot dynamics in both real and virtual environments, and allows for the DT system to expand the realm of cyberphysical integration without expensive model tuning. The edge-computing device introduced in our architecture, observes the robot's workspace from a distance with a wider field of view. This wide viewpoint, enhances the detection and mitigation of any obstacles entering the robot's workspace during operation. We experimentally evaluated the performance of our proposed architecture by introducing dynamic obstacles during a pick-and-place task that both the physical robot and its digital twin had to avoid. Results show that the proposed DT architecture successfully integrates the novel controller and edge-computing elements and successfully performs the given navigation task. The results also show that NAC outperforms a PD controller with more than 70% improvement in joint tracking error between the physical and virtual robots. It was observed that the latency experienced while using NAC is about 48% lower than when Proportional-Derivative (PD) controller was operational.

关键词： Industry 5.0 Digital Twin Edge-computing Neuro-Adaptive controller (NAC) Smart Manufacturing Simulation Robot Operating System (ROS)

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Model-based Optimization for Laboratory-Scale Upstream processing in Monoclonal Antibody Production 11

Model-based Optimization for Laboratory-Scale Upstream Proce...

引用

11th Vienna international conference on Mathematical Modelling (MATHMOD)

作者： Pimentel, Guilherme A. Garcia-Tenorio, Camilo Fekih-Salem, Radhouane Toussaint, Cedric Kanfoud, Ahmed Cornet, Thomas Helleputte, Thibault Boes, Adrien Marega, Riccardo Wouwer, Alain Vande Dewasme, Laurent Univ Mons Syst Estimat Control & Optimizat Grp Mons Belgium DNAlytics Ottignies Belgium CER Grp Immunobiol Lab Marche En Famenne Belgium Univ Tunis El Manor Natl Engn Sch Tunis LAMSIN Tunis Tunisia

The production of monoclonal antibodies (mAbs) is a complex pharmacological process involving upstream and downstream chains, focusing on mAbs production and purification, respectively. This paper presents a process optimization based on an end-to-end mechanistic model for the upstream process chain to enhance the production of mAbs. Upstream processing considers cell expansion, cell production, and primary harvesting steps by filtration. The optimization results offer users the optimal initial concentrations of the medium in the bioreactors, the duration of the cultures, the feed flow rate profiles, and the permeate flow profile in the filtration operation. Simulations incorporating interconnected reactors and process constraints led to optimized initial media concentrations and feed flow profiles, resulting in a 25% increase in mAb production compared to baseline conditions.

关键词： process optimization monoclonal antibodies upstream processing mechanistic modeling

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Arduino Based automation in Coagulation process and Sludge Reduction in Dyeing 5

Arduino Based Automation in Coagulation Process and Sludge R...

引用

5th international conference on Inventive Research in computing Applications, ICIRCA 2023

作者： Revathi, P. Mrunalini, T. Kanchhi Verma, V. Madhavan, R. Dhivya Shree, A. Kongu Engineering College Department of Eie Tamil Nadu Erode India

ISBN: (纸本)9798350321425

With upgrades, automation has recently had an impact on a wide range of businesses in addition to production and manufacturing. In wastewater treatment, increasingly complex and varied techniques are being used more frequently. As a result, a reliable operation is also necessary, and automation is playing an increasingly important role in this regard. Automated controls are used to save the proper amount of water, which is what they are primarily focused on doing. Water filtration is important for a number of industrial activities. A practical solution that may maximize process efficiency and resource availability is required to manage productivity, quality of product/service improvement, downtime reduction, and operating costs in the current sustainable concern. The main focus of the critical analysis in this study is the technological problems of automation control systems that can advance the automation industry in terms of management level and process effectiveness. Long-term cost constraints can be reduced in this situation by automation. Beyond effective solid handling, automation offers numerous advantages and efficiently saves energy. For an effective and safe process of wastewater treatment automationis incorporated in the process of coagulation, where the method of adding chemicals for filtration, which is the first step of any wastewater treatment is being done manually by labors leading to variationand disturbance in the production of sludge and causing an decreasein the efficiency of treated water. However, because it has concentrations of heavy metals, sulphates, and chlorides in high concentration, the sludge produced as a result of treating textile industry effluent is causing storage and disposal issues. When sludgeis stored in open yards and disposed in landfills, which may be challenging to manage and expensive, these chemicals and heavy metals once more constitute a major threat to the environment. Due to its high-water content, low dewaterabilit

关键词： Wastewater treatment

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Performance Measurement in Optimizing Customer Relationship Management Systems through Robotic process automation with FlaUI 7

Performance Measurement in Optimizing Customer Relationship ...

引用

7th international conference on Information and Computer Technologies, ICICT 2024

作者： Tan, Wei En Chunyuyau, Peter Keoh, SyeLoong Tso, Ejoe Wong, Dennis Tang, Lai Meng University Of Glasgow School Of Computing Science United Kingdom Macao Polytechnic University Faculty Of Applied Sciences China Hong Kong Institute Of Vocational Education Hong Kong Hong Kong

ISBN: (纸本)9798350385625

The rapid advancement of digitalization in the Asia-Pacific region, accelerated by the recent global pandemic, has compelled organizations to adopt new technology solutions to bridge the skills gap and keep up with Industry 4.0. This project aims to enhance existing system by incorporating Robotic process automation to streamline processes and optimize resource utilization. The effectiveness of utilizing FlaUI in addressing the challenge will be explored and evaluated. © 2024 IEEE.

关键词： Robotics

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Minimizing End-to-End Latency in Edge computing-Enabled IoT Networks Through Edge-to-Edge Resource Allocation 2

Minimizing End-to-End Latency in Edge Computing-Enabled IoT ...

引用

2nd IEEE international conference on IoT, Communication and automation Technology, ICICAT 2024

作者： Saxena, Mohit Srivastava, Swapnil Dwivedi, Vijay Kumar Chitranshi, Roshan Mishra, Pradeep Kumar United College of Engineering & Research Department of CSE Prayagraj211006 India United College of Engineering & Research Department of EE Prayagraj211006 India United College of Engineering & Research Department of Mathematics Prayagraj211006 India

ISBN: (纸本)9798350368109

The emerging Internet of Things (IoT) applications in healthcare and smart homes need ultra-low latency in task processing. The IoT devices have limited computing power hence, they leverage the cloud servers to process their computational tasks. However, the far-located cloud server restricts the real-time response. Edge computing enables computing resources to be located near IoT devices. Hence, edge computing can minimize the dependency of IoT devices on cloud servers. However, the computing capacity of edge devices is less than that of cloud servers. Thus, edge computing-enabled IoT networks demand an efficient resource allocation strategy. This paper addresses the challenges in edge-to-edge resource distribution that minimizes the total latency in edge-enabled IoT networks. The proposed method enables the optimal resource provisioning of available edge devices. The numerical results indicate that the proposed method reduces the total latency significantly than the cloud-based solutions © 2024 IEEE.

关键词： Mobile edge computing

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Cutting Tool Surface Defect Detection based on Chaos Difference Method in Manufacturing process 20

Cutting Tool Surface Defect Detection based on Chaos Differe...

引用

IEEE 20th international conference on automation Science and Engineering (CASE)

作者： Wu, Ziqin Niu, Weilong Sun, Xiaoguang Chen, Li Jinan Univ Sch Intelligent Syst Sci & Engn Zhuhai 519070 Peoples R China Soochow Univ Sch Rail Transportat Suzhou 215137 Jiangsu Peoples R China Suzhou Ahno Precis Tangent Technol Co Suzhou Peoples R China

ISBN: (纸本)9798350358513;9798350358520

CPMS(Cyber-Physical Manufacturing Systems) plays a pivotal role in Industry 4.0, driving the automation and intelligence of modern manufacturing. In industrial quality control, however, manual visual inspection persists for detecting surface defects in small products, incurring high labor and time costs detrimental to automation. The cutting tools commonly utilized in machine tools typically have diameters ranging from 8mm to 15mm, making their surface defects even more minute. This paper introduces an MDC (Modeling Differences in Chaos) method enhancing deep learning models for detecting tiny surface defects in CPMS, which improving contrast in regions with defects by leveraging the similarity relationships among cutting tools that share the same type, achieving 86.08% Precision, 76.95% mIoU and 84.04% Recall in experiments, outperforming classical semantic segmentation algorithms.

关键词： Smart manufacturing

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EEG-Driven Approach to Improve Academic Performance via Auditory Brainwave Entrainment Techniques 8

EEG-Driven Approach to Improve Academic Performance via Audi...

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8th IEEE international conference on computing, Communication, control and automation, ICCUBEA 2024

作者： Banait, Shweta Kanhere Ranjan, Prabhat Chavan, Sanjana Chavan, Devang D Y Patil International University School of Interdisciplinary Research and Studies Maharashtra Pune India D Y Patil International University School of Bio-Sciences and Bio-Engineering Maharashtra Pune India D Y Patil International University School of Computer Science Engineering and Applications Maharashtra Pune India

ISBN: (纸本)9798350391770

As the most intelligent species, humans possess highly developed cognitive abilities facilitated by complex neural mechanisms. Our brains generate electrical signals in response to sensory inputs and experiences. Audiovisual Entrainment (AVE) techniques leverage this neuroplasticity, allowing external stimuli to modulate brain wave patterns. This approach has shown potential in addressing various neurological conditions, alleviating stress and anxiety, and enhancing cognitive performance and overall well-being. Brain-Computer Interface (BCI) technologies enable direct monitoring and analysis of neural activity through non-invasive methods like Electroencephalography (EEG). EEG provides a cost-effective and practical solution for recording brain wave patterns during cognitive tasks, facilitating insights into neurophysiological processes and informing the development of targeted interventions, such as AVE. © 2024 IEEE.

关键词： Electroencephalography

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OPC UA PubSub and Industrial controller Redundancy 29

OPC UA PubSub and Industrial Controller Redundancy

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29th IEEE international conference on Emerging Technologies and Factory automation, ETFA 2024

作者： Johansson, Bjarne Holmgren, Olof Dahl, Martin Forsberg, Håkan Nolte, Thomas Papadopoulos, Alessandro V. Abb Process Automation Process Control Platform Västerås Sweden Mälardalen University Västerås Sweden Abb Process Automation Process Control Platform Minden Germany

ISBN: (纸本)9798350361230

Industrial controllers constitute the core of numerous automation solutions. Continuous control system operation is crucial in certain sectors, where hardware duplication serves as a strategy to mitigate the risk of unexpected operational halts due to hardware failures. Standby controller redundancy is a commonly adopted strategy for process automation. This approach involves an active primary controller managing the process while a passive backup is on standby, ready to resume control should the primary fail. Typically, redundant controllers are paired with redundant networks and devices to eliminate any single points of failure. The process automation domain is on the brink of a paradigm shift towards greater interconnectivity and interoperability. OPC UA is emerging as the standard that will facilitate this shift, with OPC UA PubSub as the communication standard for cyclic real-time data exchange. Our work investigates standby redundancy using OPC UA PubSub, analyzing a system with redundant controllers and devices in publisher-subscriber roles. The analysis reveals that failovers are not subscriber-transparent without synchronized publisher states. We discuss solutions and experimentally validate an internal stack state synchronization alternative. © 2024 IEEE.

关键词： Redundancy

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