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International Conference on. Cryptology and Network Security with Machine Learning, ICCNSML 2023

作者： Pandey, Rashmikiran Pandey, Mrinal Nazarov, Alexey Department of Radio Engineering and Cybernetics Moscow Institute of Physics and Technology Moscow Russia Federal Research Center Computer Science and Control Russian Academy of Science Moscow Russia

ISBN: (纸本)9789819706402

In the rapidly evolving realm of cyber-security, the detection of network anomalies serves as a pivotal line of defense against a myriad of malicious activities and cyberthreats. This research undertakes the task of enhancing the accuracy and efficacy of network anomaly detection by employing a comparative analysis of various individual machine learning models. The study delves into the performance of distinct models, including Random Forest, Gradient Boosting, AdaBoost, neural networks, and SVM, meticulously scrutinizing their capabilities in detecting network anomalies. The crux of this study lies in its meticulous evaluation of each individual model on the revered NSL-KDD dataset—an established benchmark within the field of network intrusion detection. Through a systematic blend of rigorous mathematical frameworks, precise model implementations, and comprehensive experimental assessments, this research offers a deep understanding of the inner workings of each algorithm. The pivotal aspect of this study revolves around the comprehensive comparative analysis of these standalone models. Going beyond the mere quantifica-tion of accuracy, the exploration delves into aspects of precision, recall, F1-score, and more, shedding light on their diverse facets of performance. With achieved accuracies of 99.2419% for Random Forest, 99.5197% for Gradient Boosting, 86.6044% for AdaBoost, 84.00% for neural networks, and 87.00% for SVM, this research underlines the distinctive attributes and potential of each model in the context of network anomaly detection. As the study unravels the distinct strengths and limitations of each model, it contributes to the broader landscape of cyber-security by providing insights into the efficacy of individual machine learning approaches. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Support vector machines

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Method for Evaluating the Performance of Aircraft Collaborative Decision-Making Based on Dynamic Bayesian Network

Method for Evaluating the Performance of Aircraft Collaborat...

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2024 International Conference on Electronics and Devices, Computational Science, ICEDCS 2024

作者： Zhang, Wenbo Yu, Boxiao Tong, Jiahui Li, Jing Beijing Electro-Mechanical Engineering Institute National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Beijing Institute of Technology School of Computer Science and Technology Beijing China

ISBN: (纸本)9798331527624

This research addresses the challenge of assessing equipment decision-making effectiveness in environments characterized by uncertainty and multiple influencing factors. We propose a novel approach involving the creation and optimization of a dynamic Bayesian network-based model tailored for equipment decision-making processes. The model facilitates a systematic evaluation of decision-making effectiveness by incorporating various factors, including equipment performance, environmental conditions, and enemy defensive capabilities. A comprehensive assessment system has been developed to simulate the penetration capabilities of different equipment through enemy defenses. Moreover, this study identifies potential errors in the effectiveness evaluation model by analyzing its performance in typical scenarios, pinpointing areas for enhancement. © 2024 IEEE.

关键词： Decision-making Dynamic Bayesian networks Equipment Simulation Uncertainty Management

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SS-DBSCAN: Epsilon Estimation with Stratified Sampling for Density-Based Spatial Clustering of Applications with Noise

SS-DBSCAN: Epsilon Estimation with Stratified Sampling for D...

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2023 International Conference on Automation, control and Electronics engineering, CACEE 2023

作者： Monko, Gloriana Joseph Kimura, Masaomi Shibaura Institute of Technology Graduate School Department of Functional Control Systems Tokyo Japan Shibaura Institute of Technology Department of Computer Science and Engineering Tokyo Japan

ISBN: (纸本)9798350309201

Clustering algorithms are crucial in uncovering hidden patterns and structures within datasets. Among the density-based clustering algorithms, DBSCAN (Density-Based Spatial Clustering of Applications with Noise) has gained considerable attention for its effectiveness in various applications. However, determining appropriate parameter values for this algorithm remains a challenging task. This paper presents a novel methodology for eps parameter estimation for an improved DBSCAN, namely SS-DBSCAN. The experimental results across nine datasets demonstrate the efficacy of our proposed method in accurately determining clusters with eps value from SS-DBSCAN algorithm. The clusters identified using estimated eps values by SS-DBSCAN align well with the inherent structure of the datasets, yielding better cluster results than the manually set parameters and other methods used for automatic estimations of the eps for DBSCAN. Our approach adapted well to the peculiarities of each dataset, whether dealing with different scales, dimensions, or densities;it proved the versatility and robustness across various datasets, thereby emphasizing its generalizability and potential for broader applications. © 2023 IEEE.

关键词： Parameter estimation

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Research on the Mechanism and Suppression Methods of Commutation Failure in High-Voltage Direct Current Transmission Systems 7

Research on the Mechanism and Suppression Methods of Commuta...

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7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： Li, Ming Shen, Xiaolin Li, Xuanlang Liu, Yiqi State Grid Economic and Technology Research Institute Co. Ltd. Beijing China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (纸本)9798350359558

High-voltage Direct Current (HVDC) transmission technology has obvious advantages in power transmission, so it has been developed rapidly. Commutation failure is one of the most common faults in HV AC-DC hybrid transmission systems, which can cause DC lock and power oscillation. This paper takes commutation failure as the research object analyzes its causes and main influencing factors and puts forward corresponding suppression strategies, which are significant for the safe and stable operation of HVDC transmission systems. © 2024 IEEE.

关键词： HVDC power transmission

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Modeling and Optimal control for Resource Allocation in the Epidemic Monitoring of a Multi-group Population

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SN computer Science 2024年第1期5卷 121页

作者： Di Giamberardino, Paolo Iacoviello, Daniela Papa, Federico Department of Computer Control and Management Engineering “A. Ruberti” Sapienza University of Rome Via Ariosto 25 Rome 00185 Italy Institute for System Analysis and Computer Science “A. Ruberti” CNR Via dei Taurini 19 Rome 00185 Italy

In the last 3 years, the entire world has been facing the sanitary emergency due to the SARS-CoV2;it has been stressed the mutual interdependence of the human populations, as well as the strong impact of specific conditions, such as age, work, habits, on the disease spread among subgroups of a given population. Moreover, the high percentage of asymptomatic individuals, especially among young subjects, improves the infection spread among groups with higher probability of fatal consequences. The vaccination campaign has strongly contributed to reduce mortality, so bringing the epidemic scenario probably closer to the endemic state. Nevertheless, the loss of the vaccination protection, the appearance of new variants and the mixing of moving people require a surveillance action to reduce new virus waives. By suitable modeling and optimal control design, this paper addresses the planning of a swab test campaign for the surveillance of the disease spread within a given multi-group population, when resource limitation and distinctive epidemiological characteristics of the subgroups are present. The proposed approach, applied on a case study in which the population is split into four groups, stresses the importance of a suitable tuned swab test campaign, saving a significant number of infections (and therefore of human lives), by scheduling the surveillance effort on the different populations. The determination of this kind of control is useful not only in the endemic condition, but also as general surveillance strategy at the beginning of an epidemic spread, with limitations in material and logistic resources. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Epidemic monitoring Mathematical modeling of epidemics Optimal control Resource allocation

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Optimizing Electrocardiogram Signal Augmentation for Realistic Synthetic Data in Deep Learning Model 27

Optimizing Electrocardiogram Signal Augmentation for Realist...

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27th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2024

作者： Safdar, Muhammad Farhan Palka, Piotr Faresi, Ahmed Al Nowak, Robert Marek Institute of Computer Science Warsaw University of Technology Poland Institute of Control and Computation Engineering Warsaw University of Technology Poland United Arab Emirates University College of Information Technology United Arab Emirates

ISBN: (纸本)9788362065486

Electrocardiograms (ECG) are non-invasive signals and have proven useful in assessing the heart condition. Given the necessity for extensive datasets in ECG classification using deep learning (DL) models, there is a critical imperative to devise data augmentation methods capable of generating synthetic but realistic dataset suitable for training DL model. In this study, we propose a novel approach for augmenting ECG signals, aiming to produce realistic signals while optimizing memory usage and resource requirements. Building upon our previous work in ECG signal augmentation, we revisit the methodology to address limitations observed in the generation of synthetic signals. The existing method segmented ECG signals into fixed-length segments and combined them, occasionally resulting in unrealistic heart cycles within the signals in extreme condition. To address this issue, our proposed technique incorporates R peak detection, signal segmentation, and reordering based on the R-peaks information. We evaluated the proposed method using three benchmark datasets, including PTB-XL, Chapman-Shaoxin from PhysioNet, and the dataset from China Physiological Signal Challenge 2018 (CPSC-2018), for classifying atrial fibrillation from normal samples. Our approach achieved an accuracy of 0.83, sensitivity of 0.86, specificity of 0.80, F1-score of 0.83, and precision of 0.80. These results underscore the effectiveness and efficiency of our method in augmenting ECG signals for various applications in healthcare and biomedical research. © 2024 Division of Signal Processing and Electronic Systems, Poznan University of Technology (DSPES PUT).

关键词： Convolutional neural networks

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Beyond the network-based multi-omics data integration in COPD: A pathway-centric analysis

Beyond the network-based multi-omics data integration in COP...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Sibilio, Pasquale Conte, Federica Paci, Paola Sapienza University of Rome Department of Computer Control and Management Engineering Rome Italy National Research Council Institute for Systems Analysis and Computer Science 'Antonio Ruberti' Rome Italy Karolinska Institutet Stockholm17177 Sweden

ISBN: (纸本)9798350386226

Chronic obstructive pulmonary disease (COPD) is a lung disease causing hundred thousand of death each year worldwide and defined as a respiratory and airflow impairment majorly due to large and small airways dysfunctions. COPD could be considered as a syndrome that includes disease axes of variable pathological and clinical conditions. Despite recent advances, the comprehension of the molecular mechanisms responsible for COPD disease spectrum is far to be reached. Moreover, we should also consider continuous smoking exposure, which could lead to variability in the disease mechanisms and progression. Network-based multi-omics data integration can help to study the association between molecular determinants on diverse biomolecular layers in a disease context. In a previous study, we leveraged lung RNA-seq and DNA-methylation data of a COPD-control cohort to build a correlation-based integrated network (called coupled network), that helped to unveil genes involved in immune and inflammatory modulation of COPD. Therefore, in our previous study we highlighted the most important genes of the coupled network and inspected their single contribution to disease-related pathways. In this study we aim to overcome this limitation by performing a pathway activity analysis by considering the expression and DNA methylation profiles of coupled network genes. Moreover, we exploit this analysis to study the possible contribution of coupled network genes to the differential disease progression between current and former smokers patients. © 2024 IEEE.

关键词： Lung cancer

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Research on the Flux-weakening Capability of the Reverse-salient Permanent Magnet Synchronous Motor 26

Research on the Flux-weakening Capability of the Reverse-sal...

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26th International Conference on Electrical Machines and Systems, ICEMS 2023

作者： Zhao, Xiaokun Zhang, Cheng Wang, Weinan Kou, Baoquan Zhu, Liangkuan Northeast Forestry University College of Computer and Control Engineering Harbin China Harbin Institute of Technology Department of Electrical and Automation Harbin China

ISBN: (纸本)9798350317589

Permanent magnet synchronous motors (PMSMs) offer the benefits of high torque density and a superior power factor. Nevertheless, the challenge lies in the inherent difficulty of adjusting the permanent magnet flux. To address this issue, this paper analyzes the influence of electromagnetic parameters on the constant-power speed range (CPSR). First, the analysis focuses on the influence of d-axis inductance and saliency ratio, aiming to establish a design method for achieving a wide CPSP in PMSMs. Second, based on the electromagnetic parameter requirements, a reverse-salient PMSM is proposed and its working principle is explained. Finally, the electromagnetic characteristics, including torque and the CPSP, are determined through the application of the finite element method (FEM). The obtained results confirm that the reverse-salient PMSM achieves a CPSP of 7:1, thus validating the accuracy of the theoretical analysis. © 2023 IEEE.

关键词： Finite element method

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A WSN Node Fault Diagnosis Model Based on BRB with Self-Adaptive Quality Factor

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computers, Materials & Continua 2023年第4期75卷 1157-1177页

作者： Guo-Wen Sun Gang Xiang Wei He Kai Tang Zi-Yi Wang Hai-Long Zhu School of Computer Science and Information Engineering Harbin Normal UniversitySongbei DistrictHarbin150025China Beihang University School of Automation Science and Electrical Engineering Beijing100191China Beijing Aerospace Automatic Control Institute Beijing100074China Rocket Force University of Engineering Xi’anShaanxi Province710025China

Wireless sensor networks (WSNs) operate in complex and harshenvironments;thus, node faults are inevitable. Therefore, fault diagnosis ofthe WSNs node is essential. Affected by the harsh working environment ofWSNs and wireless data transmission, the data collected by WSNs containnoisy data, leading to unreliable data among the data features extracted duringfault diagnosis. To reduce the influence of unreliable data features on faultdiagnosis accuracy, this paper proposes a belief rule base (BRB) with a selfadaptivequality factor (BRB-SAQF) fault diagnosis model. First, the datafeatures required for WSN node fault diagnosis are extracted. Second, thequality factors of input attributes are introduced and calculated. Third, themodel inference process with an attribute quality factor is designed. Fourth,the projection covariance matrix adaptation evolution strategy (P-CMA-ES)algorithm is used to optimize the model’s initial parameters. Finally, the effectivenessof the proposed model is verified by comparing the commonly usedfault diagnosis methods for WSN nodes with the BRB method consideringstatic attribute reliability (BRB-Sr). The experimental results show that BRBSAQFcan reduce the influence of unreliable data features. The self-adaptivequality factor calculation method is more reasonable and accurate than thestatic attribute reliability method.

关键词： Self-adaptive quality factor belief rule base wireless sensor networks fault diagnosis

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A Method Based on Phase-shifting Carrier for Reducing DC-link Current Harmonics in Dual Three-phase PMSM Drive under Open-phase Conditions 6

A Method Based on Phase-shifting Carrier for Reducing DC-lin...

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2022 6th International Conference on Electrical, Mechanical and computer engineering, ICEMCE 2022

作者： Wang, Qingzhe Du, Yanwei Yang, Guang Liu, Hongyang Computer & Electronic System Engineering Dept AVIC xi'An Flight Automatic Control Research Institute Shanxi Province Xi'an710076 China

The All-Electric of modern military equipment has become an important trend, in the field of aircraft the traditional servo control focus on the exact control of the motor. With the development of power electronics technology, a high-power motor has expanded into a multiphase kind which cast off the limitation of traditional three-phase motors. The multiphase motor has more control resources and fault-tolerant control ability under the fault condition, which has practical meaning for high safety and high-reliability applications in an airborne environment. The multiphase motor can be controlled by a series of phase-shift carriers, which can reduce DC current ripple more effectively than the traditional carrier-based pulse width modulation, but it needs to find the optimal phase shift angle. In this paper, the optimal carrier phase shift angle is analyzed mathematically which can be used for both under health and single open-phase fault of a dual three-phase motor, and the simulation result illustrates that the carrier phase shift method used in this paper has the DC current ripple optimization effect. © Published under licence by IOP Publishing Ltd.

关键词： Synchronous motors

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