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Machine Learning for Intricate Detection in 6G Networks 2

Machine Learning for Intricate Detection in 6G Networks

引用

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

作者： Tiwari, Annapurna Nand Revathi, N. Almusawi, Muntather Prabha, Sakthi Karpagam, J. Hafeena, Md. IES College of Technology Department of Electronics & Communication Engineering M. P Bhopal India Nehru Institute of Technology T.M Department of Electronics and Communication Engineering Tamil Nadu Palayam India The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering TN India Academy of Higher Education Department of Electrical and Electronics Engineering Karpagam TN India CMR Technical Campus Medchal Hyderabad India

ISBN: (纸本)9798350368109

In the world of 6G networks, the merging of micro-services-oriented designing and intelligent network management demonstrates the central role of neural networks (AI), machine learning (ML), and supervised learning (DL). This study looks into strengthening the security of 6G communications networks through the development of a new anomaly recognition System for 6G Connections (AD6GNs) utilizing ensemble learning (EL). The EL-ADCN workflow comprises prior processing, feature selection utilizing the hybrid methodology CFS-RF, and intruder detection applying hybrid EL methods. The system shows impressive performance on datasets with names like NSL-KDD, UNSW-NB2015, CIC-IDS2017, when CICDDOS2019, getting accuracy of 99.5%, 99.9%, 99.8%, while 99.95426%, respectively, with low false alarm rates. The combination of assistance vector machines (SVM) particularly random forest computing (RF) as EL techniques further improves the efficiency of packing and adaboosting in guaranteeing network that self-sustainability and preventive threat prevention in the envisioned 6G model. © 2024 IEEE.

关键词： Network intrusion

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Reference Model for Building automation 28

Reference Model for Building Automation

引用

28th IEEE international conference on Emerging Technologies and Factory automation, ETFA 2023

作者： Pannosch, Jurgen Kastner, Wolfgang Institute of Computer Engineering TU Wien Vienna Austria

ISBN: (纸本)9798350339918

During the last decades, the complexity of building automation systems increased, starting with a growing number of sensors and actuators to several communication protocols that need to be interoperable with each other. Different techniques are introduced to handle this complexity and to support engineers during development, like abstraction, layered design, and reference architecture models. Reference architecture models are used in various domains, like in the Smart Grid domain with Smart Grid Architecture Model (SGAM) or in the Industry 4.0 domain with Reference Architecture Model Industrie 4.0 (RAMI 4.0) to reduce the complexity during design and support the modeling process. No such reference architecture model exists for the area of building automation. This paper proposes a reference architecture model for the building automation domain to support engineers in the development and modeling process of a building automation system. © 2023 IEEE.

关键词： Interoperability

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Analysis of Posture Influence on Memory Using fNIRS-BCI 6

Analysis of Posture Influence on Memory Using fNIRS-BCI

引用

6th international conference on Robotics and automation in Industry, ICRAI 2024

作者： Mustafa, Ali Nazeer, Hammad Naseer, Noman Air University Department of Mechatronics and Biomedical Engineering Islamabad Pakistan

ISBN: (纸本)9798350355703

This study explores the impact of three varied body postures-sitting, standing, and upper-body movement on human memory using functional near-infrared spectroscopy (fNIRS) based brain- computer interface (BCI). The study involves two distinct cognitive activities i.e., the mental arithmetic and picture recall activity. The fNIRS brain signals from 10 healthy subjects (5 male and 5 female) were recorded, and pre-processed. After extracting features, supervised learning was used for classification to analyze how altering body postures affects the memory The Gaussian Naïve Bayes (NB), Decision Tree (DT), and Random Forest (RF) classifiers were applied. For the Mental Arithmetic Activity, sitting posture emerged as the optimal posture, demonstrating the maximum achieved accuracy of 84.2%. Conversely, for the Picture Recall Activity, the upper-body movement emerged as the optimal posture, achieving the maximum accuracy of 87.4%. Through comprehensive analysis, this research contributes insights into the intricate relationship between body postures and cognitive functions. © 2024 IEEE.

关键词： Near infrared spectroscopy

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Detecting and Preventing Brute Force Attacks on Mobile Devices Using Advanced Encryption Techniques 3

Detecting and Preventing Brute Force Attacks on Mobile Devic...

引用

3rd IEEE international conference on automation and Computation, AUTOCOM 2025

作者： Franklin, Ramya G. Kaur, Savinder Kumari, Binita Gupta, Mohit Gopalakrishna, K. Maharishi, Trapty Agarwal Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Department of Computer Applications Odisha Bhubaneswar India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh Baddi174103 India Karnataka Bangalore India School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798331542375

Brute pressure attacks are a not unusual approach utilized by malicious actors to gain unauthorized rights of entry to touchy records on mobile devices. Those assaults involve trying out multiple combinations of usernames and passwords until the precise one is located. This poses a huge risk to mobile security, as those devices often incorporate a tremendous quantity of personal and private information. The proposed solution is to detect and save brute force attacks on cellular gadgets by enforcing superior encryption techniques. Those techniques contain complex algorithms and methods to protect touchy records from being accessed by way of unauthorized events. This may make it easier for attackers to decipher the encrypted documents, even though they're capable of getting entry to them. The device will constantly display the get entry to attempts and locate any unusual styles or suspicious pastimes. If a brute pressure assault is detected, the device will robotically block further entry attempts and cause an alert to the consumer. It'll additionally encrypt the information in the tool to save it from being compromised. This answer will appreciably increase the security of cell gadgets because it will make it almost impossible for hackers to benefit from unauthorized admission to sensitive data. It's going to supply user's peace of thoughts, understanding that their statistics are covered, and offer an extra layer of security to cell gadgets. © 2025 IEEE.

关键词： Sensitive data

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automation of Traffic Signal for Better Commutation of Vehicles 3

Automation of Traffic Signal for Better Commutation of Vehic...

引用

3rd international conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Vaghela, Aarzoo Maruf, Padaya Meitei, Naorem Yaipharenba Singh, Laiphrakpam Dolendro National Institute of Technology Department of Computer Science and Engineering Assam Silchar India Indian Institute of Technology NineLabs Electronics & Electrical Engineering Assam Guwahati India

ISBN: (纸本)9798331523893

Traffic congestion poses a significant challenge in urban areas globally, resulting in wasted time, increased fuel consumption, and heightened pollution levels. Traditional traffic light systems often rely on fixed timers, failing to adjust to fluctuating traffic patterns and causing unnecessary delays. To tackle this issue, an adaptive traffic signal timer is designed to dynamically respond to real-time traffic conditions. The proposed system harnesses live camera feeds from traffic junctions and employs object detection techniques to analyze traffic density accurately. The proposed method represents a proactive approach to addressing urban congestion challenges, promising more efficient traffic management and improved commuting experiences for residents and commuters. A comprehensive simulation platform is developed to validate our system's efficacy and facilitate comparative analysis with existing static systems. © 2025 IEEE.

关键词： Vehicle detection

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Development of a Software System Based on Microservice Architecture for Flaw Detection of Industrial Products 3

Development of a Software System Based on Microservice Archi...

引用

3rd IEEE international conference on Problems of Informatics, Electronics and Radio engineering, PIERE 2024

作者： Peshkov, Alexander V. Novosibirsk State Technical University Faculty of Automation and Computer Engineering Novosibirsk Russia

ISBN: (纸本)9798331516321

This paper presents the results of developing a prototype software system for detecting fine defects in industrial products. The core of the computing unit contains a previously developed computational-heuristic algorithm that allows detecting thin defects in the product under study based on a priori information about the reference sample of this product. The developed software system is designed on the basis of a microservice architecture, which allows dividing a monolithic application into independently operating modules. The paper also presents an algorithm for generating cracks in the object model, which allows creating the necessary set of test data close to real ones. The presented results demonstrate a significant increase in system performance compared to the previous implementation due to the use of a multi-threaded approach. The developed prototype of the system can be further developed and used to solve real problems in the field of industrial flaw detection. © 2024 IEEE.

关键词： Application programs

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Analysis of Serial Peripheral Interface 2

Analysis of Serial Peripheral Interface

引用

2nd IEEE international conference on Measurement, Instrumentation, Control and automation, ICMICA 2023

作者： Patra, Aritra Saini, Lalit Mohan National Institute of Technology School of Vlsi and Embedded System Design Haryana Kurukshetra India National Institute of Technology Department of Electrical Engineering Haryana Kurukshetra India

ISBN: (纸本)9798350355048

Serial peripheral interface, a term originally coined by Motorola in the 1980s, serves as a protocol facilitating the communication of serial synchronous data between a master device, often a microcontroller, and various peripherals. These peripherals encompass a broad range, including EEPROMs (Electrically Erasable Programmable Read-Only Memory), sensors, cards and more. Functioning as a full-duplex serial protocol, SPI (Serial peripheral interface) involves transmission and reception of synchronous serial data. This document elucidates the operational intricacies and distinctive features of the SPI Interface Protocol, focusing on a configuration with one master and one slave. In this setup, master device orchestrates communication, dictating the timing and flow of data, while slave device responds to master's commands. Understanding working principles and characteristics of SPI is paramount for its effective implementation in diverse applications. © 2024 IEEE.

关键词： Mice (computer peripherals)

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Research on Dual Channel Medical Short Text Intention Recognition Algorithm 6

Research on Dual Channel Medical Short Text Intention Recogn...

引用

6th international conference on computer Network, Electronic and automation, ICCNEA 2023

作者： Wang, Chao Sun, Yongyong Xu, Fei Xi'an Technological University School of Computer Science and Engineering Xi'an China

ISBN: (纸本)9798350305388

Common medical short text intention recognition When extracting local information, Convolutional neural network is better than other neural networks, but Convolutional neural network can't consider the whole situation of short text. To utilize whole sentence information, we propose a dual channel short text intention recognition model combining TextCNN and BiGRU-Att, which uses local features and global features to recognize short text intention, Optimized the use of intent recognition models for global text features. The AB-CNN-BGRU-Att algorithm first utilizes the ALBERT multi-layer bidirectional Transformer structure to vectorize the input text, and then sends the vectors into the TextCNN and BiGRU network models to obtain local and global features. Fuse these two features and obtain the intention through softmax. The experimental data shows that in THUCNewsTitle dataset, the AB-CNN-BGRU-Att algorithm proposed in this article achieved an Acc of 96.68%, an F1 value of 96.67%, and an accuracy of 86.02% on the KUAKE-QIC dataset. Compared to other intention recognition models, the performance has been improved. © 2023 IEEE.

关键词： Convolution

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GILV: An integrated GNSS/IMU positioning method enhanced by lane line and template matching VO 2

GILV: An integrated GNSS/IMU positioning method enhanced by ...

引用

2nd international conference on Frontiers of Applied Optics and computer engineering, AOCE 2025

作者： Wang, Rongchen Zeng, Qingxi Huang, Yuhua Ji, Xufang Shi, Yanwei Yuan, Liying College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China Xuzhou Power Supply Branch of State Grid Jiangsu Electric Power Co. Ltd. Xuzhou221000 China

ISBN: (纸本)9781510689404

Ensuring precise and flexible positioning is a fundamental prerequisite for autonomous mobility of unmanned ground vehicles. In the context of Global Navigation Satellite System (GNSS) signals facing suppression, the traditional joint GNSS and IMU positioning is subject to positioning drift due to the cumulative error of the IMU. In this paper, we propose a low-cost integrated localization system called GILV that fuses inertial and visual data through an error state Kalman filter (ESKF) framework to achieve continuous localization under GNSS rejection. GILV utilizes a downward-facing camera to provide vehicle position constraints through a template matching algorithm that is used to smooth out IMU predictions and mitigate dispersion of localization errors. At the same time, the forward-facing camera detects lane lines and combines this information with high-precision maps to provide lateral position constraints without cumulative errors, ensuring that the Integrated Positioning System (IPS) accuracy is stabilized at the decimeter level without degradation due to cumulative IMU errors. The Integrated Positioning System (IPS) is realized on the ROS platform and has been verified through outdoor experiments. The results show that GILV consistently limits the position error to within 0.5 meters and maintains an average position error within 10 centimeters during a 100-second GNSS signal outage. This resilience greatly reduces the dependence of the positioning system on the quality of GNSS signals. © The Authors.

关键词： Global positioning system

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Robust Model-Free Control of a Floating Offshore Wind Turbine under High Wind & Wave Conditions

Robust Model-Free Control of a Floating Offshore Wind Turbin...

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2024 international conference on Control, automation and Diagnosis, ICCAD 2024

作者： Owayjan, Michel Houari, Azeddine Achkar, Roger Ait-Ahmed, Mourad Tahliati, Mahfoud Ferahtia, Seydali Saint-Nazaire France American University of Science & Technology Faculty of Engineering and Computer Science Beirut Lebanon Icam Nantes France

ISBN: (纸本)9798350361025

Offshore wind energy can provide a substantial amount of the world's current electricity demand. Yet, harvesting this energy poses additional technical and economic challenges to the design and control of Floating Offshore Wind Turbines (FOWT). Different control strategies have been used to mitigate these challenges to increase the efficiency of the FOWTs and stabilize their power output. This paper presents a model-free adaptive control using Generalized Proportional Integral Control (GPIC) based on integral reconstruction in the form of robust Classical Compensation Networks (CCN) to control the collective pitch angle of a FOWT operating above rated wind speed (Region 3). The control is validated on a nonlinear model of a 5 MW FOWT with a semi-submersible platform and compared to the basic Gain Scheduling PI (GSPI) controller with Anti-Windup. Results show a more robust performance of the proposed controller under various wind and wave conditions. © 2024 IEEE.

关键词： Controllers

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