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检索条件"主题词=software algorithms"

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Research on Fault Mode Analysis Method of Nuclear I&C software Based on Time Automata

Research on Fault Mode Analysis Method of Nuclear I&C Softwa...

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Prognostics and System Health Management Conference (PHM-Qingdao)

作者： Genhua Liang Yong Li Yanqun Wu Fei Yang Zhichuan Zeng Xuanlin Zhu HongXin Deng National key Laboratory of Nuclear Reactor Technology Nuclear Power Institute of China Chengdu China School of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai China

ISBN: (数字)9798350354010

ISBN: (纸本)9798350354027

This paper presents a novel fault mode analysis method for nuclear instrumentation and control (I&C) software based on timed automata. The proposed approach addresses the limitations of traditional fault analysis techniques in handling complex, real-time systems by accurately capturing the dynamic characteristics and intricate interaction patterns of nuclear I&C software. Key contributions include: (1) development of a timed automata-based modeling framework tailored for nuclear I&C software; (2) design of a comprehensive fault mode library compatible with timed automata models; and (3) implementation of an automated fault mode analysis algorithm leveraging model checking techniques. The method's efficacy is demonstrated through a case study on a digital reactor protection system, specifically the Reactor Coolant Pump speed protection subsystem. Results show significant improvements in fault mode identification rates, particularly for time-related faults, and enhanced capabilities in quantitative analysis and dynamic behavior capture compared to traditional methods. This approach provides a more rigorous and systematic tool for improving the reliability and safety of digital I&C systems in nuclear power plants, with potential applications in other safety-critical domains.

关键词： Analytical models Systematics Statistical analysis Instruments software algorithms Automata software software reliability Protection Inductors

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Detection of Link Fabrication Attacks in software-Defined Networks using DBSCAN

Detection of Link Fabrication Attacks in Software-Defined Ne...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Abirami Ganesh Lakshana Ravishankar Nithiyashri Sankar Meignanamoorthi D V. Vetriselvi Department of Computer Science and Engineering College of Engineering Guindy Anna University Chennai India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Topology poisoning attacks pose a significant security threat to software-Defined Networking (SDN) environments. Centralized control in SDN brings about vulnerabilities, such as the susceptibility to topology poisoning attacks. The relay attack disrupts network traffic routing, leading to potential data breaches and degraded network performance. To maintain the integrity and security of SDN operations, it is crucial to ensure accurate network topology information. Topology poisoning attacks often mimic legitimate network behavior which makes it complex to detect them. The increasing deployment of SDNs in 5G networks, IoT, and cloud services increases the necessity of addressing these attacks. We propose the detection of fake links using link latency-based anomaly detection system using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. The true positive percentage for detecting fake links obtained was 95.0% and true negative percentage was 99.60%.

关键词： Fabrication Network topology Noise software algorithms Telecommunication traffic Routing Topology Security software defined networking Relays

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USASAT-NGSO-3X Filing Analysis Using ITU-BR GIBC software For Various Orbital Shells

USASAT-NGSO-3X Filing Analysis Using ITU-BR GIBC Software Fo...

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IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)

作者： Fika Triana Meiditomo Sutyarjoko Heroe Wijanto Graduate Program of Regulation and Management of Telecommunication School of Eletrical Engineering Telkom University Bandung Indonesia Regulation and Management of Telecommunication School of Electrical Engineering Telkom University Bandung Indonesia The University Center of Excellence for Intelligent Sensing-IoT School of Electrical Engineering Telkom University Bandung Indonesia

ISBN: (数字)9798331543105

ISBN: (纸本)9798331543112

Interference is a significant problem in satellite communication operations, one of which is between Non-Geostationary Orbit (non-GSO) satellites and Geostationary Orbit (GSO) ground stations. To calculate the impact of this interference, an evaluation of the EPFD (Equivalent Power Flux Density) is carried out, which describes the average power density of the signal received at the receiving station location. This study conducted an in-depth study of the level of interference by signals from the USASAT NGSO-3X satellite in various orbital shells that affect the GSO system. By using the worst-case geometry method, the EPFD calculation can provide valuable insight into the level of interference that occurs. Based on the results of the study, it was concluded that a more in-depth study of the ITU-BR GIBC software algorithm was needed regarding the analysis of EPFD values using the worst-case geometry method. GIBC simulations show inconsistencies in the EPFD values correlated with the values set in Article 22 ITU-R and S.1503-2 ITU-R, both through aggregate and separate orbit examinations, so that a review of the ITU-R S.1503-2 algorithm is needed to ensure that interference between non-GSO satellites and GSO earth stations remains under control within the specified limits.

关键词： Space vehicles Geometry Earth Satellites Aggregates Space technology software algorithms Interference Orbits software

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Cost-sensitive Approach for improving AUC-ROC Curve of software Defect Prediction

Cost-sensitive Approach for improving AUC-ROC Curve of Softw...

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International Seminar on Intelligent Technology and Its Applications (ISITIA)

作者： Rizal Broer Bahaweres Islah Khofifah Nuraini Department of Informatics UIN Jakarta Indonesia

ISBN: (数字)9798350378573

ISBN: (纸本)9798350378580

Defects in software can cause various problems that are detrimental to many parties, from owners and developers to users. Predicting defects in software is one of the crucial factors that must be done before an application is launched. However, often when the prediction process is carried out, misclassification occurs, which causes losses at a later date. Misclassification usually occurs in datasets that are not balanced between majority and minority data. We suggest a combination of neural network (NN) and cost-sensitive method to minimize losses affected by misclassification. The author then compares the results of the evaluation of the proposed model with models without cost sensitivity to find out whether the model's performance has increased. Other classification algorithms such as decision tree (DT), logistic regression (LR), random forest (RF), and SVM will also be evaluated as part of a performance comparison of the proposed model based on AUC and ROC values in five different NASA datasets. The findings show that the cost-sensitive method can increase the AUC value in all datasets with an average increase of 13.6%. Cost-sensitive can overcome classification errors by increasing the AUC value in all models, and the optimal algorithm based on the average score in the proposed of neural network model.

关键词： Support vector machines Seminars Radio frequency Sensitivity software algorithms NASA Prediction algorithms

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Design and Implementation of a Cross-Platform Real-Time Power System Simulation software for the New power system

Design and Implementation of a Cross-Platform Real-Time Powe...

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Intelligent Power and Systems (ICIPS), International Conference on

作者： Ying Huang Yuanhong Lu Jingyue Zhang Jie Zhan Yanjun Zhao Yufeng Hu State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou 510663 China Southern Power Grid Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou 510663 China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou 510663 China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou 510663 China Southern Power Grid Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou Guangzhou China

ISBN: (数字)9798331532765

ISBN: (纸本)9798331532772

With the rapid increase in renewable energy installation nodes and the substantial enhancement of switching frequencies in the new power system, this paper proposes a design scheme for a cloud simulation software that employs the Latency Insertion Method (LIM) to decompose large-scale new power system models into several subsystems, enabling multi-platform integrated parallel computing. The self-developed platform meets the demands of ultra-large simulation scales, ultra-small simulation time steps, and massive simulation computations in power systems. Experimental results demonstrate that the accelerated simulation technology, which integrates model segmentation using LIM with multi-core parallel execution, can enhance the simulation speed by up to 858 times while maintaining simulation accuracy. This significantly improves simulation efficiency and is suitable for large-scale simulations of new power systems.

关键词： Renewable energy sources Accuracy Computational modeling Switching frequency software algorithms Random access memory Parallel processing software Real-time systems Power systems

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Enhanced Accuracy and Prediction of Novel Random Forest Algorithm Compared over K-Nearest Neighbor in software Bug Prediction System

Enhanced Accuracy and Prediction of Novel Random Forest Algo...

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Advances in Data Engineering and Intelligent Computing Systems (ADICS), International Conference on

作者： KS Bharath T. J. Nagalakshmi N. Meenakshisundaram Dept of CSE Saveetha School of Engineering SIMATS Chennai India Department of ECE Saveetha School of Engineering SIMATS Chennai India

ISBN: (数字)9798350364828

ISBN: (纸本)9798350364835

The purpose of this research is to compare and contrast the effectiveness of the traditional K-Nearest Neighbor (KNN) method with a new approach based on random forests (RF) for detecting software bugs (SB). The main goal is to evaluate how well the proposed technique finds and predicts software problems while keeping security risks to a minimum. The KNN technique and a new RF based methodology are compared in this research to see which one is better at predicting SB. In order to gather information on software projects and the bug reports that are associated with them, we make use of the Eclipse Bug Data dataset. This dataset is accessible to the general public and contains information about the number of lines of code, the complexity of the code, and the number of developers that participated in the project. In order to evaluate the effectiveness of different approaches, the dataset is randomly split into two groups, every consisting of 10 samples. We train and test the KNN technique with one set of data, and then we train and test the innovative RF - based approach with the other set of data. Both approaches are executed using Python and the scikit-learn package for machine learning (ML). Statistical power (G-power) = 0.85, alpha = 0.5, beta = 0.2, and confidence interval = 95% were used to perform the research and guarantee the findings' validity and reliability. Results from the experiments showed that compared to the KNN method's 75.59% accuracy, the proposed RF - based technique reached an impressive 78.59%. According to these results, the innovative strategy reduced security risks better than the KNN technique for SB prediction. The values obtained were 0.000 (p<0.05), indicating statistical significance. Research shows that when dealing with missing data and high-dimensional data both of which are common in software issue prediction the RF based approach performs better.

关键词： Radio frequency Codes Computer bugs software algorithms Prediction algorithms software Complexity theory

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The use of software Testing Techniques in software Development: Literature Review

The use of Software Testing Techniques in Software Developme...

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International Conference on Cyber and IT Service Management (CITSM)

作者： Yuni Sugiarti Mohammad Caesar Maulana Marshelia Az-zahra E Oos M Anwas Anggraeni Dian Permatasari Khofifa Najma Iftitah Information System UIN Syarif Hidayatullah Jakarta Jakarta Indonesia National Research and Innovation Agency Jakarta Indonesia

ISBN: (数字)9798331528799

ISBN: (纸本)9798331528805

In the modern digital era, software has become the backbone of various aspects of life, which makes software testing an essential step in development to detect and correct defects, thereby producing quality products according to user needs. The purpose of writing this Systematic Literature Review (SLR) is to see various types of utilization of testing software in development software. The method used in this study is literature review with utilizing typeset tools, Mendeley and Google Translate to support the research process. The results of this research provide an overview of various software testing techniques that can be used in various software development contexts, as well as the importance of conducting appropriate testing to ensure the quality and reliability of the final product.

关键词： software testing Automation Bibliographies software algorithms Closed box Manuals software quality software reliability Complexity theory software development management

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A Comprehensive Study on Weather Predicting Automation Bot Using Automation software and Machine Learning

A Comprehensive Study on Weather Predicting Automation Bot U...

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Innovation in Technology (APCIT), Asia Pacific Conference on

作者： Vedant Joshi Priya Jadhav Robotics and Automation Department Symbiosis Institute of Technology Pune India

ISBN: (数字)9798350361537

ISBN: (纸本)9798350361544

Weather forecasting is crucial in our daily lives, influencing everything from when to walk outside to what to dress. In this era of automation and data-driven decision-making, a new and reliable way of weather prediction is now possible thanks to the collaboration of automation software and machine learning. This study closely investigates the development and implementation of an automation bot for weather forecasting that employs machine learning and automation software techniques. This study investigates the complexity of this automation system, the underlying algorithms, its ease of use, and the accuracy of the forecasts it generates. The study shows how this unique concept not only increases weather forecast accuracy but also mentions the procedure, making it more accessible to users in daily life. This study shows the significant advancement in weather forecasting by combining the use of automation software with data-driven insights from machine learning. This will help in a more accurate and precise real-time understanding of climate change.

关键词： Technological innovation Automation Accuracy Machine learning algorithms software algorithms Weather forecasting Machine learning

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software Reliability Prediction Model Based on Improved Resampling Algorithm

Software Reliability Prediction Model Based on Improved Resa...

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Prognostics and System Health Management Conference (PHM-Qingdao)

作者： Qingkang Wen Zhaojun Steven Li Green Energy Business Unit Zhuzhou CRRC Times Electric Co. Ltd. Zhuzhou China Department of Industrial Engineering and Engineering Management Western New England University Springfield United States

ISBN: (数字)9798350354010

ISBN: (纸本)9798350354027

Reliable software can provide security in finance, aerospace and other fields, and it can help find and repair potential software defects and problems, reducing the cost of software maintenance and support. The difficulty of software reliability is that modern software systems are becoming more and more complex, which makes it more difficult to predict and analyze software errors. In this paper, a software reliability evaluation model based on an improved particle filter algorithm is proposed. In the resamping stage, the selection probability of unique position particles is improved through the adaptive distance comparison step. In addition, the method further proposes the strategy of generating new particles, re-selecting low-weight particles and adding random noise, and finally obtaining small batches of new particles. The software reliability model and improved particle filter algorithm are combined to predict the number of software faults, and more accurate prediction results are obtained.

关键词： software maintenance software algorithms Noise Predictive models Prediction algorithms software systems Particle filters software reliability Security Prognostics and health management

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Research on Low Energy software Defined Industrial Network Time Synchronization Method

Research on Low Energy Software Defined Industrial Network T...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Jianmou Li Yongxin Miao Yunxu Zhang Shibo Wang Yongbao Guan Shuai Shao State Grid YingKou Electric Power Supply Company China Yingkou Liaoning Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Shenyang Liaoning

ISBN: (数字)9798350360868

ISBN: (纸本)9798350360875

Industrial control networks are becoming increasingly complex, with various types of networks and devices interconnected, forming a heterogeneous industrial control network environment. In this environment, network time synchronization becomes the key to ensuring the reliable and stable operation of industrial networks and production manufacturing. However, traditional time synchronization algorithms suffer from the problem of frequent broadcasting with fixed cycles, resulting in high communication overhead and hindering the achievement of green and low-carbon production goals. Therefore, studying a low-energy industrial network time synchronization method has important practical significance. This article proposes a low-energy software defined industrial network time synchronization method to solve the communication overhead problem caused by traditional time synchronization algorithms with fixed cycle frequent broadcasts. This method is based on the software defined network concept, constructs a layered network topology, and is compatible with various time synchronization protocols according to application requirements. Considering the impact of dynamic link delay on time synchronization accuracy, low-power synchronous broadcasting was achieved by dynamically adjusting the time synchronization period of each layer of the network, and the time synchronization period was further optimized.

关键词： Energy consumption Accuracy Industrial control software algorithms Production Broadcasting software

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