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Evaluation of control over the Edge of a Configurable Mid-band 5G Base Station 6

Evaluation of Control over the Edge of a Configurable Mid-ba...

引用

6th IEEE international conference on Fog and Edge computing (ICFEC)

作者： Peng, Haorui Tarneberg, William Fitzgerald, Emma Tufvesson, Fredrik Kihl, Maria Lund Univ Dept Elect & Informat Technol Lund Sweden Warsaw Univ Technol Inst Telecommun Warsaw Poland

ISBN: (纸本)9781665495240

Mission-critical applications such as industrial control processes are evolving towards a new development paradigm by offloading their heavy computations to the edge of the emerging Fifth Generation Wireless Specifications (5G) network. In this manner, the applications can gain the economical and efficiency benefits of cloud computing, as well as reliable communication from the 5G network. However, the limited access to a configurable infrastructure of the 5G network and its edge computing infrastructure has restrained academic researchers from experimenting and validating their mission-critical application design under reasonable communication and computation scenarios. In this paper, we present a configurable mid-band 5G Stand-Alone (SA) deployment and demonstrate a control process that is running over the edge of the 5G network. We show in this paper a complete system setup for control over the Edge (CoE) of the 5G network, and validate the feasibility of deploying similar mission-critical applications over the edge of 5G network.

关键词： control over edge 5G Mission-critical application Mobile edge computing

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Identify the objective parameters of direct communication between PLC and MS SQL server 24

Identify the objective parameters of direct communication be...

引用

24th international Carpathian control conference, ICCC 2023

作者： Flaga, Stanislaw Majcher, Maciej AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics Department of Process Control Krakow Poland

ISBN: (纸本)9798350310221

When building digital twins of existing technical solutions, we need a large amount of data on the parameters of their operation under various conditions. The source of data on the values of process variables at the lowest level is control devices - most often PLCs. There are many ways to acquire the qualities of process variables available from the PLC level. Increasingly, OPC UA is replacing the OPC model, and the OPC UA server is increasingly a functionality of the PLC CPU. The Industrial Internet of Things IIoT is used in companies moving toward Factory 4.0. Data from controllers can be acquired using high-level languages such as C++, C# or Python. Libraries often made available under an open-source license are used for this. For example, you can find commercial libraries for communication between PLCs of selected manufacturers and MySQL servers. Siemens provides a library for communication between S7-1200/1500 controllers and MS SQL server. The author has yet to find an exhaustive analysis of such a solution. In the literature, there need to be more studies of experiments describing the performance of query generation and execution and the impact of the library on PLC performance. The article presents the results of an experimental study of this issue. © 2023 IEEE.

关键词： Libraries

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User Plane Management Function: A Solution for Automatic Deployment of UPF on cloud-native 5G Core Network Architecture 14

User Plane Management Function: A Solution for Automatic Dep...

引用

14th international conference on Information and communication Technology Convergence, ICTC 2023

作者： Phung, Kieu-Ha Dung, Luong Vu Tung Thai, Quang Ko, Namseok Hanoi University of Science and Technology Ha Noi Viet Nam Etri Network Research Division Daejeon Korea Republic of

ISBN: (纸本)9798350313277

5G and beyond mobile networks have emerged to provide QoS stringent services for the huge number of user devices with several technological enablers including edge computing, network slicing, SDF, NFV. The Service Based Architecture 5G facilitates the separation of control plane from data plane. The service establishments are directed by network functions in the control plane, while data session establishment are served by User Plane Functions located at the edge. Various UPFs combining to working network slices, serving as the anchor points for user data traffic plays a pivotal role in ensuring seamless data delivery, quality of service (QoS), edge computing, and security. This article proposes a solution to effectively manage UPF, a new network function called User Plane Management Function integrates between SMF and UPF. The point-to-point packet forwarding control protocol is replaced by the Service Based Interface. By implementing our solution, UPF deployment on each network slice can be automatically configured, easily scalable, and efficiently managed;opening the way to deploy UPFs in the cloud-native infrastructure. © 2023 IEEE.

关键词： 5G and beyond Cloud computing Service Based Architecture

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Enhancing Heavy Vehicle Safety with Intelligent Driver Behaviour Monitoring via Multi-Sensor Fusion and Embedded Systems

Enhancing Heavy Vehicle Safety with Intelligent Driver Behav...

引用

2024 international conference on System, Computation, automation and Networking, ICSCAN 2024

作者： Kanagamalliga, S. Nath, Srigitha S Nivetha, T. Baby Shalini, M. Saveetha Engineering College Dept. of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331510022

This research presents the development of a sensor fusion-based driver assistance system (DAS) aimed at enhancing the safety of heavy vehicle operators. The system integrates an alcohol sensor, an ADXL 335 accelerometer sensor, and an eye blink detection sensor with an Arduino platform for real-time monitoring of driver behaviour. LabVIEW software was employed for data processing and visualization, providing a user-friendly interface to track driver alertness, speed, and alcohol consumption. A classification algorithm was implemented to categorize the driver's condition into various risk levels based on sensor inputs. Alerts were generated in real-time to notify the driver of potential hazards, such as drowsiness, intoxication, or speeding. Experimental trials demonstrated the system's effectiveness in accurately detecting dangerous driving behaviours and issuing timely warnings. The use of sensor fusion enhanced data reliability by cross-verifying multiple inputs, reducing false positives. The system proved to be robust and practical for implementation in heavy vehicle operations, contributing to road safety. Future enhancements may include additional physiological sensors, integration with vehicle control systems, and the practise of machine learning (ML) algorithms to improve classification accuracy. This research highlights the potential of sensor fusion technology in the development of advanced DAS, particularly in the transportation sector. © 2024 IEEE.

关键词： Advanced driver assistance systems

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Design of Intelligent Decision Support System With Ensembled Machine Learning to Predict Students' Performance

Design of Intelligent Decision Support System With Ensembled...

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2024 international conference on communication, Computer Sciences and Engineering, IC3SE 2024

作者： Deepan, S. Rajendran, Dineshkumar Dhaliwal, Navdeep Praveena, K. Lourens, Melanie Anandhi, R.J. School Of Cs & Ai Sr University Telangana Warangal India School Of Computing And Innovative Technologies British University Computer Games Design And Programming Viet Nam Lovely Professional University Phagwara India Institute Of Aeronautical Engineering Dundigal Hyderabad India Durban University Of Technology Faculty Of Management Sciences South Africa New Horizon College Of Engineering Department Of Information Science Engineering Bangalore India

ISBN: (纸本)9798350366846

Evaluating student performance is important for universities and institutions in the current student education landscape because it helps them create models that work better for students. The automation of various features related to fundamental student traits and behaviours that manage massive amounts of data efficiently processes these. To handle student records that included information about students' behaviour and how it related to their academic performance, the companies employed models of classification with mining concepts. Additionally, the quality of result classification can be substantially improved by using learning analytics and Educational Data Mining (EDM). The educational establishments are making an effort to lower the low student performance. To address this issue, numerous methods for assessing student performance have been devised, allowing the relevant faculties to intervene and enhance the final product. Three classes - Low Performance Student, Average Student, and Smart Student - were created using the K-Mean Clustering methodology for classifying student records. Features including grade point, number of deficits, student attendance, medium of education, and board of education are taken into account when classifying the data. In this case, the WEKA tool is also utilized for implementing the model and outcome assessments. © 2024 IEEE.

关键词： Decision support systems

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Automatic Temperature control of Blast Furnace Based on Data Analysis Model 2

Automatic Temperature Control of Blast Furnace Based on Data...

引用

2nd international conference on Artificial Intelligence, automation, and High-Performance computing, AIAHPC 2022

作者： Wang, Xijuan Feng, Jingxiao School of Physics and Electronic Information Luoyang Normal University Luoyang471000 China

ISBN: (纸本)9781510657717

The heating process of the blast furnace is a complex and huge controlled object, which has the characteristics of nonlinear, multivariable, distributed parameters, fast and slow processes intertwined. It is impossible to achieve satisfactory control results only by traditional control. With the development of artificial intelligence in recent years, neural networks, expert technology, fuzzy and predictive control provide new ideas for the heating control of the blast furnace. In this paper, based on the deep learning framework of artificial intelligence, the LSTM algorithm is proposed. Based on the massive production data, through the model simulation comparison, the results show that the LSTM network modeling has stronger generalization ability, smaller error, and higher accuracy. The LSTM neural network algorithm can effectively deal with the characteristics of time series data, provide guidance for the production practice, and lay a good foundation for the predictive control of blast furnaces. © 2022 SPIE. All rights reserved.

关键词： Blast furnaces

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Integrated Data-Driven Framework for Automatic controller Tuning with Setpoint Stabilization Through Reinforcement Learning 19

Integrated Data-Driven Framework for Automatic Controller Tu...

引用

19th international conference on Software Technologies, ICSOFT 2024

作者： Mohajer, Babak Singh, Neelaksh Liebeskind, Joram BELIMO Automation AG Brunnenbachstrasse 1 Hinwil8340 Switzerland

ISBN: (纸本)9789897587061

We introduce a three-stage framework for designing an optimal controller. First, we apply offline black-box optimization algorithms to find optimal controller parameters based on a heuristically chosen setpoint profile and a novel cost function for penalizing control signal oscillations and direction changes. Then, we leverage cloud data to generate device-specific setpoint profiles and tune the controller parameters to perform well on the device with respect to the same cost function. Finally, we train a control policy on top of the offline tuned controller after deployment on device through an online learning algorithm to handle unseen setpoint variations. A novel reward function encouraging setpoint stabilization is added for preventing destabilization from coupling effects. Bayesian Optimization and Nelder-Mead methods are used for offline optimization, and a state-of-the-art model free Reinforcement Learning algorithm namely Soft Actor-Critic is used for online optimization. We validate our framework using a realistic HVAC hydraulic circuit simulation. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Reinforcement learning

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Insider Threat Detection Using Bidirectional Encoder Representations from Transformers and Optimized AdaBoost Classifier

Insider Threat Detection Using Bidirectional Encoder Represe...

引用

2024 international conference on Circuit, Systems and communication, ICCSC 2024

作者： Kumpf, Katarina Protic, Mihajlo Jovanovic, Luka Cajic, Miroslav Zivkovic, Miodrag Bacanin, Nebojsa Singidunum University Faculty of Informatics and Computing Belgrade Serbia University 'Union Nikola Tesla' Faculty of Information Technology and Engineering Belgrade Serbia

ISBN: (纸本)9798350365306

Cybersecurity plays an increasingly vital role in contemporary times, particularly as large companies face escalating threats and substantial losses, with ransomware attacks standing out as one of the more sophisticated forms of intrusion. In such attacks, hackers infiltrate systems, encrypt crucial company data, and then demand a ransom for data decryption or the restoration of control over the system. The application of natural language processing (NLP) emerges as a promising avenue, offering the potential to analyze attack patterns and recognize malicious intentions before actual attempts occur. Given the inherent specificity of each system, fine-tuning AI algorithms with special settings becomes imperative for optimal efficiency. This research delves into the synergy of NLP and robust classification algorithms to detect cyber attacks through website content analysis. Recognizing that classifier performance hinges on the judicious selection of hyperparameters, we explore a modified version of the recently introduced red fox algorithm (RFO). This adaptation is combined with bidirectional encoder representations from transformers to identify malicious intent in email content. The proposed approach undergoes testing on a real-world dataset, with the best models demonstrating an accuracy of 0.975822 suggesting viability. © 2024 IEEE.

关键词： Natural language processing systems

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IoT Based Intruder Detection System Integrated with Chatbot for Authentication 5

IoT Based Intruder Detection System Integrated with Chatbot ...

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

作者： Edward Kennady, L. Bethanny Janney, J. Bernatin, T. Sathyabama Institute of Science and Technology Department of Electronics and Communication Chennai India Sathyabama Institute of Science and Technology Department of Biomedical Engineering Chennai India

ISBN: (纸本)9798350321425

Internet of Things (IoT) enables connectivity and interoperability between users' devices, systems, services, networks, and especially control systems. Smart video surveillance is an IOT application as it uses the internet for a variety of functions. IOT-based Intruder Detection System (IDS) is the latest technology used in a wide range of places. It serves as a remote eye for the security force. In the existing technique, the AdaBoost algorithm needs a quality data set. And also, noisy data and outliershave to be avoided before adopting this algorithm. So, in this study, machine learning techniques such as the Haar-Cascade and local binary pattern histogram algorithms are used to overcome the above disadvantage to clearly detect the face. The camera module captures an image of a person as soon as the smart home switch is pressed, sends the still image to the Android device through the Telegram app, and alerts the owner about the person who is trying to enter through the door. The entire systems programming has been established in Python and Embedded C for a controller. © 2023 IEEE.

关键词： Machine learning

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Experimental research on Assisted control of Lower limb exoskeleton Robot 2

Experimental research on Assisted Control of Lower limb exos...

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2nd international conference on Artificial Intelligence, automation, and High-Performance computing, AIAHPC 2022

作者： Zhou, Xiong Yu, Zhipeng Wang, Meiling Ye, Xiaodong Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei230031 China University of Science and Technology of China Hefei230026 China

ISBN: (纸本)9781510657717

With the rapid increase of aging population in China, more and more power-assisted devices need to be used. In this paper, aiming at the walking problem of the elderly or the disabled, a lower limb exoskeleton assisted robot based on motor drive is designed. This article first briefly introduces the mechanical structure, hardware system and software control system of the lower limb exoskeleton, and then proposes the assist control algorithm based on the dynamic model of the lower limb exoskeleton robot. Plantar pressure is used as the metrics to evaluate the effectiveness of the power control algorithm. Experimental results verify the effectiveness of our proposed assisted control algorithm. Experimental results show that the proposed algorithm can significantly reduce the plantar pressure of the wearer, which verified the effectiveness of the assisted control algorithm. © 2022 SPIE. All rights reserved.

关键词： Robots

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