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Asymmetrical Fault Current Calculation Method and Influencing Factors Analysis of Droop-Controlled Inverters

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 562-573页

作者： Huimin Zhao Zhikang Shuai Jun Ge An Luo Weimin Wu Z.John Shen College of Electrical and information Engineering Hunan UniversityChangsha 410006China Electrical Engineering department Shanghai Maritime UniversityShanghai 201306China department of Electrical and Computer Engineering Ilinois Institute of TechnologyChicagoIL 60616 USA

Since the fault dynamic of droop-controlled inverter is different from synchronous generators (SGs), protection devices may become invalid, and the fault overcurrent may damage power electronic devices and threaten the safety of the microgrid. Therefore, it is imperative to conduct a comprehensive fault analysis of the inverter to guide the design of protection schemes. However, due to the complexity of droop control strategy, existing literatures have simplified asymmetric fault analysis of droop-controlled inverters to varying degrees. Therefore, accurate fault analysis of a droop-controlled inverter is needed. In this paper, by analyzing the control system, an accurate fault model is established. Based on this, a calculation method for instantaneous asymmetrical fault current is proposed. In addition, the current components and current characteristics are analyzed. It was determined that fault currents are affected by control loops, fault types, fault distance and nonlinear limiters. In particular, the influences of limiters on the fault model, fault current calculation and fault current characteristics were analyzed. Through detailed analysis, it was found that dynamics of the control loop cannot be ignored, the fault type and fault distance determine fault current level, and part of the limiters will totally change the fault current trend. Finally, calculation and experimental results verify the correctness of the proposed method.

关键词： Asymmetrical fault analysis droop control fault current calculation method limiter transient fault characteristics

Enhancing Cybersecurity Competency in the Kingdom of Saudi Arabia:A Fuzzy Decision-Making Approach

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Computers, Materials & Continua 2024年第5期79卷 3211-3237页

作者： Wajdi Alhakami department of information technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

The Kingdom of Saudi Arabia(KSA)has achieved significant milestones in *** has maintained solid regulatorymechanisms to prevent,trace,and punish offenders to protect the interests of both individual users and organizations from the online threats of data poaching and *** widespread usage of information technology(IT)and IT Enable Services(ITES)reinforces *** constantly evolving cyber threats are a topic that is generating a lot of *** this league,the present article enlists a broad perspective on how cybercrime is developing in KSA at present and also takes a look at some of the most significant attacks that have taken place in the *** existing legislative framework and measures in the KSA are geared toward deterring criminal activity *** competency models have been devised to address the necessary cybercrime competencies in this *** research specialists in this domain can benefit more by developing a master competency level for achieving optimum *** address this research query,the present assessment uses the Fuzzy Decision-Making Trial and Evaluation Laboratory(Fuzzy-DMTAEL),Fuzzy Analytic Hierarchy Process(***),and Fuzzy TOPSIS methodology to achieve segment-wise competency development in cyber security *** similarities and differences between the three methods are also *** cybersecurity analysis determined that the National Cyber Security Centre got the highest *** study concludes by perusing the challenges that still need to be examined and resolved in effectuating more credible and efficacious online security mechanisms to offer amoreempowered ITES-driven economy for ***,cybersecurity specialists and policymakers need to collate their efforts to protect the country’s digital assets in the era of overt and covert cyber warfare.

关键词： Cyber security fuzzy DMTAEL security policy cyber crime MCDM

A Non-Parametric Scheme for Identifying Data Characteristic Based on Curve Similarity Matching

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1424-1437页

作者： Quanbo Ge Yang Cheng Hong Li Ziyi Ye Yi Zhu Gang Yao School of Automation Nanjing University of Information Science&TechnologyJiangsu Provincial University Key Laboratory of Big Data Analysis and Intelligent SystemsNanjing University of Information Science&Technologyand the Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)Nanjing University of Information Science&TechnologyNanjing 210044China School of department of Logistics Engineering Shanghai Maritime UniversityShanghai 201306China China Classification Society Nantong Office Nantong 226006China Chinese Flight Test Establishment Xi’an 710089China School of Mathematics Tsinghua UniversityBeijing 100084China School of Automation Nanjing University of Information Science&TechnologyNanjing 210044China department of Logistics Engineering Shanghai Maritime UniversityShanghai 201306China IEEE

For accurately identifying the distribution charac-teristic of Gaussian-like noises in unmanned aerial vehicle(UAV)state estimation,this paper proposes a non-parametric scheme based on curve similarity *** the framework of the pro-posed scheme,a Parzen window(kernel density estimation,KDE)method on sliding window technology is applied for roughly esti-mating the sample probability density,a precise data probability density function(PDF)model is constructed with the least square method on K-fold cross validation,and the testing result based on evaluation method is obtained based on some data characteristic analyses of curve shape,abruptness and *** com-parison simulations with classical methods and UAV flight exper-iment shows that the proposed scheme has higher recognition accuracy than classical methods for some kinds of Gaussian-like data,which provides better reference for the design of Kalman filter(KF)in complex water environment.

关键词： Curve similarity matching Gaussian-like noise non-parametric scheme parzen window.

Graph-decomposed k-NN searching algorithm on road network

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Frontiers of Computer Science 2024年第3期18卷 243-245页

作者： Wei JIANG Bo NING Guanyu LI Mei BAI Xiao JIA Fangliang WEI Faculty of information Science and technology Dalian Maritime UniversityDalian 116026China Jiangxing Intelligence Inc. Shenzhen 518100China

1 Introduction The k-NN(k Nearest Neighbors)searching problem on road network constitutes a crucial aspect of location-oriented services,which has boasted the practical implications.

关键词： services searching network

Influence of railway wheel tread damage on wheel-rail impact loads and the durability of wheelsets

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Railway Engineering Science 2024年第1期32卷 20-35页

作者： Michele Maglio Tore Vernersson Jens C.O.Nielsen Anders Ekberg Elena Kabo CHARMEC Department of Mechanical and Maritime SciencesChalmers University of TechnologySE‑41296 GothenburgSweden

Dynamic wheel-rail contact forces induced by a severe form of wheel tread damage have been measured by a wheel impact load detector during full-scale field tests at different vehicle *** on laser scanning,the measured three-dimensional damage geometry is employed in simulations of dynamic vehicle-track interaction to calibrate and verify a simulation *** relation between the magnitude of the impact load and various operational parameters,such as vehicle speed,lateral position of wheel-rail contact,track stiffness and position of impact within a sleeper bay,is *** calibrated model is later employed in simulations featuring other forms of tread damage;their effects on impact load and subsequent fatigue impact on bearings,wheel webs and subsurface initiated rolling contact fatigue of the wheel tread are *** results quantify the effects of wheel tread defects and are valuable in a shift towards condition-based maintenance of running gear,and for general assessment of the severity of different types of railway wheel tread damage.

关键词： Wheel tread damage Rolling contact fatigue cluster Field measurements Dynamic vehicle-track interaction Wheel-rail impact load Wheelset durability

A Review of Image Steganography Based on Multiple Hashing Algorithm

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Computers, Materials & Continua 2024年第8期80卷 2463-2494页

作者： Abdullah Alenizi Mohammad Sajid Mohammadi Ahmad A.Al-Hajji Arshiya Sajid Ansari department of information technology College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia department of Computer Science College of Engineering and Information TechnologyOnaizah CollegesQassim56312Saudi Arabia

Steganography is a technique for hiding secret messages while sending and receiving communications through a cover *** ancient times to the present,the security of secret or vital information has always been a significant *** development of secure communication methods that keep recipient-only data transmissions secret has always been an area of ***,several approaches,including steganography,have been developed by researchers over time to enable safe data *** this review,we have discussed image steganography based on Discrete Cosine Transform(DCT)algorithm,*** have also discussed image steganography based on multiple hashing algorithms like the Rivest–Shamir–Adleman(RSA)method,the Blowfish technique,and the hash-least significant bit(LSB)*** this review,a novel method of hiding information in images has been developed with minimal variance in image bits,making our method secure and effective.A cryptography mechanism was also used in this *** encoding the data and embedding it into a carry image,this review verifies that it has been ***,embedded text in photos conveys crucial signals about the *** review employs hash table encryption on the message before hiding it within the picture to provide a more secure method of data *** the message is ever intercepted by a third party,there are several ways to stop this operation.A second level of security process implementation involves encrypting and decrypting steganography images using different hashing algorithms.

关键词： Image steganography multiple hashing algorithms Hash-LSB approach RSA algorithm discrete cosine transform(DCT)algorithm blowfish algorithm

A Review on the Recent Trends of Image Steganography for VANET Applications

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Computers, Materials & Continua 2024年第3期78卷 2865-2892页

作者： Arshiya S.Ansari department of information technology College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

Image steganography is a technique of concealing confidential information within an image without dramatically changing its outside *** vehicular ad hoc networks(VANETs),which enable vehicles to communicate with one another and with roadside infrastructure to enhance safety and traffic flow provide a range of value-added services,as they are an essential component of modern smart transportation *** steganography has been suggested by many authors for secure,reliable message transfer between terminal/hope to terminal/hope and also to secure it from attack for privacy *** paper aims to determine whether using steganography is possible to improve data security and secrecy in VANET applications and to analyze effective steganography techniques for incorporating data into images while minimizing visual quality *** to simulations in literature and real-world studies,Image steganography proved to be an effectivemethod for secure communication on VANETs,even in difficult network *** this research,we also explore a variety of steganography approaches for vehicular ad-hoc network transportation systems like vector embedding,statistics,spatial domain(SD),transform domain(TD),distortion,masking,and *** study possibly shall help researchers to improve vehicle networks’ability to communicate securely and lay the door for innovative steganography methods.

关键词： Steganography image steganography image steganography techniques information exchange data embedding and extracting vehicular ad hoc network(VANET) transportation system

Pervasive Attentive Neural Network for Intelligent Image Classification Based on N-CDE’s

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Computers, Materials & Continua 2024年第4期79卷 1137-1156页

作者： Anas W.Abulfaraj department of information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityRabigh21911Saudi Arabia

The utilization of visual attention enhances the performance of image classification *** attentionbased models have demonstrated notable performance,but many of these models exhibit reduced accuracy when confronted with inter-class and intra-class similarities and ***-Controlled Differential Equations(N-CDE’s)and Neural Ordinary Differential Equations(NODE’s)are extensively utilized within this ***’s possesses the capacity to effectively illustrate both inter-class and intra-class similarities and differences with enhanced *** this end,an attentive neural network has been proposed to generate attention maps,which uses two different types of N-CDE’s,one for adopting hidden layers and the other to generate attention *** distinct attention techniques are implemented including time-wise attention,also referred to as bottom N-CDE’s;and element-wise attention,called topN-CDE’***,a trainingmethodology is proposed to guarantee that the training problem is sufficiently *** classification tasks including fine-grained visual classification andmulti-label classification,are utilized to evaluate the *** proposedmethodology is employed on five publicly available datasets,including CUB-200-2011,ImageNet-1K,PASCAL VOC 2007,PASCAL VOC 2012,and MS *** obtained visualizations have demonstrated that N-CDE’s are better appropriate for attention-based activities in comparison to conventional NODE’s.

关键词： Differential equations neural-controlled DE image classification attention maps N-CDE’s

Intelligent Machine Learning Based Brain Tumor Segmentation through Multi-Layer Hybrid U-Net with CNN Feature Integration

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Computers, Materials & Continua 2024年第4期79卷 1301-1317页

作者： Sharaf J.Malebary department of information technology Faculty of Computing and Information TechnologyKing Abdulaziz UniversityP.O.Box 344Rabigh21911Saudia Arabia

Brain tumors are a pressing public health concern, characterized by their high mortality and morbidity ***, the manual segmentation of brain tumors remains a laborious and error-prone task, necessitatingthe development of more precise and efficient methodologies. To address this formidable challenge, we proposean advanced approach for segmenting brain tumorMagnetic Resonance Imaging (MRI) images that harnesses theformidable capabilities of deep learning and convolutional neural networks (CNNs). While CNN-based methodshave displayed promise in the realm of brain tumor segmentation, the intricate nature of these tumors, markedby irregular shapes, varying sizes, uneven distribution, and limited available data, poses substantial obstacles toachieving accurate semantic segmentation. In our study, we introduce a pioneering Hybrid U-Net framework thatseamlessly integrates the U-Net and CNN architectures to surmount these challenges. Our proposed approachencompasses preprocessing steps that enhance image visualization, a customized layered U-Net model tailoredfor precise segmentation, and the inclusion of dropout layers to mitigate overfitting during the training ***, we leverage the CNN mechanism to exploit contextual information within brain tumorMRI images,resulting in a substantial enhancement in segmentation *** experimental results attest to the exceptionalperformance of our framework, with accuracy rates surpassing 97% across diverse datasets, showcasing therobustness and effectiveness of our approach. Furthermore, we conduct a comprehensive assessment of ourmethod’s capabilities by evaluating various performance measures, including the sensitivity, Jaccard-index, andspecificity. Our proposed model achieved 99% accuracy. The implications of our findings are profound. Theproposed Hybrid U-Net model emerges as a highly promising diagnostic tool, poised to revolutionize brain tumorimage segmentation for radiologists and clinician

关键词： Brain tumor Hybrid U-Net CLAHE transfer learning MRI images