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检索条件"任意字段=3rd IEEE Intelligent Data Acquisition and Advanced Computing Systems"

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Intrusion Detection System for 5G with a Focus on DOS/DDOS Attacks 11

Intrusion Detection System for 5G with a Focus on DOS/DDOS A...

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11th ieee International Conference on intelligent data acquisition and advanced computing systems - Technology and Applications (IDAACS)

作者： Iashvili, Giorgi Iavich, Maksim Bocu, Razvan Odarchenko, Roman Gnatyuk, Sergiy Caucasus Univ Paata Saakadze St 1 GE-0102 Tbilisi Georgia Transilvania Univ Brasov Brasov 500036 Romania Natl Aviat Univ Liubomyra Huzara Ave 1 UA-03058 Kiev Ukraine

ISBN: (纸本)9781665426053

The industry of telecommunications is being transformed towards 5G technology, because it has to deal with the emerging and existing use cases. Because, 5G wireless networks need rather large data rates and much higher coverage of the dense base station deployment with the bigger capacity, much better Quality of Service - QoS, and the need very low latency [1-3]. The provision of the needed services which are envisioned by 5G technologies need the new service models of deployment, networking architectures, processing technologies and storage to be defined. These technologies will cause the new problems for the cybersecurity of 5G systems and the security of their functionality. The developers and researchers working in this field make their best to secure 5G systems. The researchers showed that 5G systems have the security challenges. The researchers found the vulnerabilities in 5G systems which allow attackers to integrate malicious code into the system and make the different types of the illegitimate actions. MNmap, Battery drain attacks and MiTM can be successfully implemented on 5G. The paper makes the analysis of the existing cyber security problems in 5G technology. Based on the analysis, we suggest the novel Intrusion Detection System - IDS by means of the machine-learning algorithms. In the related papers the scientists offer to use NSL-KDD in order to train IDS. In our paper we offer to train IDS using the big datasets of DOS/DDOS attacks, besides of training using NSL-KDD. The research also offers the methodology of integration of the offered intrusion detection systems into an standard architecture of 5G. The paper also offers the pseudo code of the designed system.

关键词： 5G security intrusion detection systems ids

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Availability Assessment of a Cloud Server System: Comparing Markov and Semi-Markov Models 11

Availability Assessment of a Cloud Server System: Comparing ...

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11th ieee International Conference on intelligent data acquisition and advanced computing systems - Technology and Applications (IDAACS)

作者： Ivanchenko, Oleg Kharchenko, Vyacheslav Moroz, Boris Ponochovnyi, Yuriy Degtyareva, Larysa Dnipro Univ Technol Dept Comp Syst & Software 19 Dmytra Yavornytskogo Ave Dnipro Ukraine Natl Aerosp Univ Kharkiv Aviat Inst Dept Comp Syst Networks & Cybersecur 17 Chkalova St Kharkiv Ukraine Poltava State Agr Acad Dept Informat Syst & Technol 1-3 Skovorody St Poltava Ukraine

ISBN: (纸本)9781665426053

Nowadays Markov Modelling Processes (MMP) found widely use into realm pertaining to availability assessments of diverse complex technical systems and devices. In this regard, Cloud Server systems (CSSs) are no exception. However, in order to leverage MMPs for the availability evaluation of CSSs the researchers should take into account that this assessment procedure based on the utilization of just one distribution, that is exponential distribution of times to failure, times to repair etc. It is a serious constraint, which would be need preliminary substantiate considering different negative events and impacts. In that regard, to note that some groups of researchers into realm pertaining to CSSs availability are increasingly trying to le. erage approaches based on SemiMarkov Modelling Processes (SMMPs). Using SMMPs the researchers can consider more number of parametric characteristics and have a realistic picture as regards change of availability level for the server system. In addition, seeking to improve overall availability of CSSs, the researchers can determine accuracy of numerical modeling results for SMMPs in the so-called borders' states, when Non-Markovian Process transforms at Markovian Process. By considering significance of these aspects, authors of this paper propose to perform mathematical modeling of behavior of a cloud server system based on joint usage of MMPs and SMMPs and get availability assessments considering diverse influence factors on states of the concrete CSS. This information is to be studded and can be used by developers in order to as well as design of the CSSs considering different influence factors.

关键词： Cloud Server System Markov and Semi-Markov Modelling Processes availabilty assessments

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An intelligent Quadcopter Unbalance Classification Method Based on Stochastic Gradient Descent Logistic Regression 3

An Intelligent Quadcopter Unbalance Classification Method Ba...

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3rd Information Technology to Enhance e-Learning and Other Application, IT-ELA 2022

作者： Al-Haddad, Luttfi Ahmed Jaber, Alaa Abdulhady University of Technology Mechanical Engineering Department Baghdad Iraq

ISBN: (纸本)9798350334968

As the global use of Unmanned Aerial Vehicles (UAVs) expands rapidly across a vast array of applications, it becomes imperative to identify their flaws and imbalances. This study presents and demonstrates the efficacy of an Optimized Stochastic Gradient Descent Logistic Regression (OSGD-LR) machine learning algorithm for classifying unbalances in quadrotor UAVs. Utilizing vibration-based signal processing characteristics in the time domain necessitated the use of a 3-axis accelerometer sensor and a data acquisition device. As the proposed model is tested with the quadcopter in hover mode at a fixed motor speed, minor and major imbalance conditions are detected. The proposed model tests, trains, and accurately predicts the flight's status as either balanced or unbalanced. In addition, diverse unbalanced blade scenarios were used to demonstrate the model's reliability in identifying the locations of imbalanced blades. In terms of classifying unbalanced UAV blades, the OSGD-LR is significantly more precise than a standard logistic regression method, as demonstrated by experimental results. © 2022 ieee.

关键词： Stochastic systems

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Implementing an intelligent Irrigation System in Oman Using Machine Learning Technique 3

Implementing an Intelligent Irrigation System in Oman Using ...

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3rd ieee International Conference on Device Intelligence, computing and Communication Technologies, DICCT 2025

作者： Stephen, Vimal Kumar Sharma, Sanjiv Al-Jufaili, Zaina Rashid Salim Jayapal, Senthil University of Technology And Applied Sciences College of Computing and Information Sciences Ibra Oman

ISBN: (纸本)9798331543358

In this study, machine-learning technique is used to collect environmental data in real time and measures other aspects like soil moisture, temperature, water level, humidity. Water use efficiency has recently increased because to new agricultural techniques, sophisticated sensors as Micro Controller, and Wireless Sensor Network (WSN). Irrigation Fault Detection method based on XGBoost (IFD-XGBoost) Algorithm used as proposed method as robust to missing values imputing them naturally during tree splitting. The Suggested method is optimized for speed, using parallel and distributed computing to make predictions faster compare to other Regression Algorithm and avoid over fitting. Using Min-Max Normalization, features with different sizes and units can affect the efficacy of several machine learning algorithms. By warping the statistical relationship between features, removal of noisy data and error detection can reduce the machine learning models' efficiency. Lasso Regression is a linear model that combines regularization and feature selection. Additionally, less data will be kept in the centralized cloud as a result. Using the IFD-XGBoost Algorithm's ability to handle missing data, learn from past errors, and adjust parameters, our proposed approach would be the best model to implement. It outperform from other algorithm in Predictive accuracy, making it reliable for calculating water needs and forecasting weather. Investigating the implementation of several machine learning models that can offer the best real-world irrigation decision management is the main goal of this article. The comparative analysis to evaluate the IFD-XGBoost method yielded a minimum RMSE of 0.3524, MAE of 0.1832, MAPE of 4.24 with the highest accuracy of 99.2%, precision of 96.2% and AUC-ROC of 95%, indicates when combined, these metrics provide insightful data about each model's ability to anticipate future developments in irrigation systems. © 2025 ieee.

关键词： Distributed cloud

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Energy Management, Design Constraints and Solution for data Dissemination in Wireless Sensor Networks 3

Energy Management, Design Constraints and Solution for Data ...

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3rd International Conference on intelligent computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Agbulu, G. Pius Kumar, G. Joselin Retna Gunasekar, S. Srm Institute of Science and Technology Department of Electronics and Instrumentation Engineering Tamil Nadu Chennai603203 India Srm Institute of Science and Technology Tamil Nadu Chennai603203 India Sree Vidyanikethan Engineering College AndhraPradesh Sree Sainath Nagar Tirupathi 517102 India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

Wireless sensor network (WSN) technology has become an essential constituent of our lives in health care, homes, food, and vehicles. Nonetheless, the sensors in WSNs naturally have limited device lifecycle due to serious energy-constraints, and so cannot guarantee to satisfy the QoS (Quality of Service) demands of different monitoring applications. This presents a significant setback to the effective application of WSNs in real-word. Therefore, to enhance the lifecycles of WSNs, it is fundamental to improve the energy management at the nodes as they are mostly set-out in geographically isolated zones. To achieve this, several communications mechanisms for energy-management and reliable routing operations is required. In this paper, we examine energy-management and the reliable routing mechanisms of WSNs with specific emphases on mobile and static deployments. We also consider fundamental design challenges and mechanisms to deal with routing challenges posed by innate constraints of the node. We assess various recent routing schemes for energy management in WSNs and propose an application-specific time-driven distributed routing scheme named Wi-Fi-based multi-hop routing algorithm (WMHR). We show the performance of the proposed WMHR in terms of energy -saving in comparison with other classical time-driven routing models. © 2022 ieee.

关键词： Energy management

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Research on the Application of Cloud computing-based Dual-Machine Hot Standby System in Railway Signal Safety Management 3

Research on the Application of Cloud Computing-based Dual-Ma...

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3rd International Conference on Integrated Circuits and Communication systems, ICICACS 2025

作者： Ji, Zhe Wang, Ding Liu, Bing Liu, Yiming Research and Design Institute Co. Ltd Shenzhen China China Academy of Railway Sciences Co. Ltd Beijing China

ISBN: (纸本)9798331508456

This paper investigates the application of cloud computing-based dual-computer hot standby computer security platform in railway signalling security management, aiming to enhance the reliability and security of railway signalling system. With the increasing importance of railway transport to modern society, the safety of railway signal system has become a key factor for public safety and social stability. This paper first analyses the security challenges faced by railway signalling systems and explores the potential of dual-machine hot-standby systems in improving system availability and security. Then, this paper details the design and implementation of a cloud-based dual-machine hot standby architecture, including system architecture, signal monitoring module, data encryption module, security audit module, and event response module. Through experimental validation, this paper compares the performance of the cloud-based dual-machine hot-standby architecture with that of the traditional single-machine system in terms of failure recovery time, resource utilisation and system response time, and the results show that the dual-machine hot-standby architecture has significant advantages in these key performance indicators. Finally, the paper discusses the limitations of the research and proposes directions for future research, including cost-benefit analysis, resource optimisation, technology adaptation research and intelligent development, with a view to providing a more efficient and intelligent solution for railway signal safety management. © 2025 ieee.

关键词： Subway signal systems

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The Application of Digital Empowerment Combined with intelligent Algorithms of Computer Technology in Decision Support systems

The Application of Digital Empowerment Combined with Intelli...

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Integrated Circuits and Communication systems (ICICACS), ieee International Conference on

作者： Wan Lu Li Chen Fei Gao Chang Wang Wuhan Windoor Information &Technology Co. Ltd Wuhan Hubei China

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Traditional decision support systems (DSS) show obvious limitations in dealing with increasingly complex and dynamic decision-making scenarios. By integrating graph neural networks (GNNs) and expert systems (ESs), this paper constructs a new IDSS framework aimed at improving decision-making efficiency and accuracy. In terms of research methods, large-scale distributed computing is performed in the cloud based on parallel computing technology; the logical reasoning of expert systems and the self-learning ability of graph neural networks are combined to achieve dynamic updates and efficient processing of data by unstructured knowledge bases. Compared with traditional DSS, the accuracy of IDSS based on the fusion of GNNs and ES in financial forecasting and risk assessment scenarios is improved to more than 90%, and resource utilization is significantly optimized. This study shows that the integrated application of intelligent algorithms has broad prospects in improving the dynamic adaptability of decision support systems and coping with complex decision-making environments.

关键词： Decision support systems Accuracy Heuristic algorithms systems architecture Graph neural networks Real-time systems Risk management Resource management Expert systems Optimization

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A BP Neural Network-based Approach to intelligent Computer Image Recognition

A BP Neural Network-based Approach to Intelligent Computer I...

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Power Electronics, Computer Applications (ICPECA), ieee International Conference on

作者： Jingwen Ze Tianjin University of Technology Tianjin China

The computer image recognition model based on BP neural network can effectively identify the convergence recognition error. To solve the problems of low convergence speed and inability to quickly reduce recognition errors in the practical application of traditional image recognition methods, an optimized model for computer image recognition based on GA & BP deep neural network algorithm is proposed through computer image data acquisition and processing, image recognition model construction based on BP neural network and computer image recognition model training.

关键词： Training Image recognition Computational modeling Neural networks data models Real-time systems Power electronics

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An Efficient Defect Detection System for Printed Circuit Boards with Edge-Cloud Fusion computing 3

An Efficient Defect Detection System for Printed Circuit Boa...

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3rd International Conference on Industrial Artificial Intelligence, IAI 2021

作者： Wu, Yi Wang, Jing Chen, Yang-Quan Beijing University of Chemical Technology College of Information Science and Technology Beijing China University of Technology School of Electrical and Control Engineering Beijing China University of California Mechatronics Embedded Systems and Automation Lab MercedCA95343 United States

ISBN: (纸本)9781665435178

Many intelligent methods have been proposed and applied in the field of autonomous manufacturing inspection. These advanced algorithms with high requirements on computing power and network may lead to time delay, high cost and energy consumption in practical applications with massive data to be processed. We carry out an efficient defect detection system in an end-edge-cloud architecture with the concept of edge computing to process the big data quickly and effectively. A branchy deep learning model with early exit capability of inference is proposed to detect the category and location of the defect in printed circuit boards. We offload part of the computing tasks to the edge nodes by segmenting and deploying the DL model. Therefore, our system has high detection efficiency and makes real-time defect detection possible. © 2021 ieee.

关键词： Printed circuit boards

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Design and Implementation of a High-temperature and High-speed Monitoring and Analysis System based on Labview

Design and Implementation of a High-temperature and High-spe...

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intelligent Manufacturing, advanced Sensing and Big data (IMASBD), International Conference on

作者： Haoqi Xu Lijun Meng State Key Laboratory of Precision Blasting Jianghan University Wuhan China

ISBN: (数字)9798331524456

ISBN: (纸本)9798331524463

Aiming at the traditional high-temperature monitoring scenarios in the temperature measurement range is limited, the detection rate is low, the data analysis and processing ability is not strong and other shortcomings. Take Labview as the software development platform and NI's CRIO acquisition controller as the hardware basis. Designed a set of virtual instrument technology based thermocouple dual-channel temperature real-time monitoring system. The system to state machine (State Machine, SM) and user interface event processor (Event Handler Loop, EHL) combined design mode for the development background. It realizes a series of functions such as real-time temperature display and alarm for different kinds of thermocouples with dual channels, data storage and data playback for different acquisition frequencies, partial interception of the playback data, filtering and analyzing them, etc. In addition, a down-sampling function is defined to prevent high-speed storage data overflow. Finally verified by high-temperature experiments, under the sampling rate of 10KS/s, the temperature curve of dual-channel 0-500℃ range can be displayed in real time, and the display error is ±5℃.

关键词： Temperature measurement Temperature distribution data analysis Thermocouples Memory User interfaces Real-time systems Software Hardware Monitoring

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