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Chinese Physics C 2024年第10期48卷 176-184页

作者： Anshul Dadwal Xiao-Tao He department of Nuclear Science and technology College of Materials Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjing 210016China

A variable moment of inertia(VMI)inspired interacting boson model(IBM),which includes many-body interactions and a perturbation possessing(5)(or(5))symmetry,is used to investigate the rotational bands of the mass region.A novel modification is introduced,extending the Arima coefficient to the third *** study is dedicated to the quantitative analysis of evolving trends in intrabandγ-transition energy as well as the kinematic and dynamic moments of inertia(MoIs)within the rotational bands of^(244)Pu and^(248)*** computed outcomes exhibit an exceptional degree of agreement with experimental observations across various *** significance of including a higher-order Arima coefficient is further examined by contrasting it with the previously proposed *** calculated results demonstrate the significance of both the anti-pairing and pairing effects in the evolution of the dynamic ***,these insights reveal the importance of a newly introduced parameter in accurately depicting complex nuclear behaviors,such as back-bending,up-bending,and downturn in the MoI.

关键词： rotational bands nuclear structure back-bending up-bending 250 mass region

Resilence Control of DC Microgrid Integrated with Multi-Nanogrids Considering Connected-Islanded States

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 786-796页

作者： Hossien Faraji Reza Hemmati Pierluigi Siano department of Electrical Engineering Amirkabir University of TechnologyTehranIran department of Electrical Engineering Kermanshah University of TechnologyKermanshahIran department of Management&Innovation Systems University of Salernoand also with the Department of Electrical and Electronic Engineering ScienceUniversity of JohannesburgJohannesburg 2006South Africa

In this paper, a DC microgrid (DCMG) integrated with a set of nano-grids (NG) is studied. DCMG exchanges predetermined active and reactive power with the upstream network. DCMG and NGs are coordinately controlled and managed in such a way the exchanged P-Q power with external grid are kept on scheduled level following all events and operating conditions. The proposed control system, in addition to the ability of mutual support between DCMG and NGs, makes NGs support each other in critical situations. On the other hand, in all operating conditions, DCMG not only feeds three-phase loads with time-varying active and reactive power on the grid side but also injects constant active power into the grid. During events, NGs support each other, NGs support DCMG, and DCMG supports NGs. Such control strategies are realized by the proposed control method to increase resilience of the system. For these purposes, all resources and loads in DCMG and NGs are equipped with individual controllers. Then, a central control unit analyzes, monitors, and regularizes performance of individual controllers in DCMG and NGs. Nonlinear simulations show the proposed model can effectively control DCMG and NGs under normal and critical conditions.

关键词： Control system DC microgrid nanogrid resilience

Optimal investment based on relative performance and weighted utility

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Applied Mathematics(A Journal of Chinese Universities) 2024年第2期39卷 328-342页

作者： WANG Lei DONG Ying-hui HUA Chun-rong department of Mathematics Suzhou University of Science and TechnologySuzhou 215009China Changshu Institute of technology Changshu 215500China

This paper studies the optimal portfolio allocation of a fund manager when he bases decisions on both the absolute level of terminal relative performance and the change value of terminal relative performance comparison to a predefined reference point. We find the optimal investment strategy by maximizing a weighted average utility of a concave utility and an Sshaped utility via a concavification technique and the martingale method. Numerical results are carried out to show the impact of the extent to which the manager pays attention to the change of relative performance related to the reference point on the optimal terminal relative performance.

关键词： relative performance weighted utility S-shaped utility concavification

Elasto-inertial focusing and particle migration in high aspect ratio microchannels for highthroughput separation

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Microsystems & Nanoengineering 2024年第3期10卷 381-394页

作者： Selim Tanriverdi Javier Cruz Shahriar Habibi Kasra Amini Martim Costa Fredrik Lundell Gustaf Mårtensson Luca Brandt Outi Tammisola Aman Russom Division of Nanobiotechnology Department of Protein ScienceScience for Life LaboratoryKTH Royal Institute of TechnologySolna 17165Sweden Division of Microsystems technology Department of Materials Science and EngineeringUppsala UniversityUppsala 75237Sweden FLOW and SeRC(Swedish e-Science Research Centre) Department of Engineering MechanicsRoyal Institute of TechnologyStockholm SE 10044Sweden FLOW and Fluid Physics Laboratory Department of Engineering MechanicsRoyal Institute of TechnologyStockholmSweden Wallenberg Wood Science Center Royal Institute of TechnologyStockholm SE 10044Sweden department of Energy and Process Engineering Norwegian University of Science and Technology(NTNU)TrondheimNorway AIMES Center for the Advancement of Integrated Medical and Engineering Sciences at Karolinska Institutet and KTH Royal Institute of technology StockholmSweden

The combination of flow elasticity and inertia has emerged as a viable tool for focusing and manipulating particles using *** there is considerable interest in the field of elasto-inertial microfluidics owing to its potential applications,research on particle focusing has been mostly limited to low Reynolds numbers(Re<1),and particle migration toward equilibrium positions has not been extensively *** this work,we thoroughly studied particle focusing on the dynamic range of flow rates and particle migration using straight microchannels with a single inlet high aspect *** initially explored several parameters that had an impact on particle focusing,such as the particle size,channel dimensions,concentration of viscoelastic fluid,and flow *** experimental work covered a wide range of dimensionless numbers(0.05

关键词： particle separation straight

Detection and defending the XSS attack using novel hybrid stacking ensemble learning-based DNN approach

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Digital Communications and Networks 2024年第3期10卷 716-727页

作者： Muralitharan Krishnan Yongdo Lim Seethalakshmi Perumal Gayathri Palanisamy IMS Sungkyunkwan UniversitySuwon16419South Korea department of Mathematics Sungkyunkwan UniversitySuwon16419South Korea department of Information technology Madras Institute of TechnologyChennaiIndia department of Mathematics PSG College of Arts and ScienceTamilnaduIndia

Existing web-based security applications have failed in many situations due to the great intelligence of *** web applications,Cross-Site Scripting(XSS)is one of the dangerous assaults experienced while modifying an organization's or user's *** avoid these security challenges,this article proposes a novel,all-encompassing combination of machine learning(NB,SVM,k-NN)and deep learning(RNN,CNN,LSTM)frameworks for detecting and defending against XSS attacks with high accuracy and *** on the representation,a novel idea for merging stacking ensemble with web applications,termed“hybrid stacking”,is *** order to implement the aforementioned methods,four distinct datasets,each of which contains both safe and unsafe content,are *** hybrid detection method can adaptively identify the attacks from the URL,and the defense mechanism inherits the advantages of URL encoding with dictionary-based mapping to improve prediction accuracy,accelerate the training process,and effectively remove the unsafe JScript/JavaScript keywords from the *** simulation results show that the proposed hybrid model is more efficient than the existing detection *** produces more than 99.5%accurate XSS attack classification results(accuracy,precision,recall,f1_score,and Receiver Operating Characteristic(ROC))and is highly resistant to XSS *** order to ensure the security of the server's information,the proposed hybrid approach is demonstrated in a real-time environment.

关键词： Machine learning Deep neural networks Classification Stacking ensemble XSS attack URL encoding JScript/JavaScript Web security

Novel Fractal-Based Features for Low-Power Appliances in Non-Intrusive Load Monitoring

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Computers, Materials & Continua 2024年第7期80卷 507-526页

作者： Anam Mughees Muhammad Kamran department of Electrical Engineering University of Engineering and Technology(UET)Lahore54890Pakistan department of Electrical Engineering Government College UniversityFaisalabad38000Pakistan department of Electrical Engineering and technology Muhammad Nawaz Sharif University of Engineering&Technology(MNS UET)Multan60000Pakistan

Non-intrusive load monitoring is a method that disaggregates the overall energy consumption of a building to estimate the electric power usage and operating status of each appliance *** studies have mostly concentrated on the identification of high-power appliances like HVAC systems while overlooking the existence of low-power ***-power consumer appliances have comparable power consumption patterns,which can complicate the detection task and can be mistaken as *** research tackles the problem of classification of low-power appliances and uses turn-on current transients to extract novel features and develop unique appliance signatures.A hybrid feature extraction method based on mono-fractal and multi-fractal analysis is proposed for identifying low-power *** dimension,Hurst exponent,multifractal spectrum and the Hölder exponents of switching current transient signals are extracted to develop various‘turn-on’appliance signatures for *** classifiers,i.e.,deep neural network,support vector machine,decision trees,and K-nearest neighbours have been optimized using Bayesian optimization and trained using the extracted *** simulated results showed that the proposed method consistently outperforms state-of-the-art feature extraction methods across all optimized classifiers,achieving an accuracy of up to 96%in classifying low-power appliances.

关键词： Nonintrusive load monitoring multi-fractal analysis appliance classification switching transients

Restoration of the JPEG Maximum Lossy Compressed Face Images with Hourglass Block-GAN

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Computers, Materials & Continua 2024年第3期78卷 2893-2908页

作者： Jongwook Si Sungyoung Kim department of Computer AI Convergence Engineering Kumoh National Institute of TechnologyGumi39177Korea department of Computer Engineering Kumoh National Institute of TechnologyGumi39177Korea

In the context of high compression rates applied to Joint Photographic Experts Group(JPEG)images through lossy compression techniques,image-blocking artifacts may *** necessitates the restoration of the image to its original *** challenge lies in regenerating significantly compressed images into a state in which these become ***,this study focuses on the restoration of JPEG images subjected to substantial degradation caused by maximum lossy compression using Generative Adversarial Networks(GAN).The generator in this network is based on theU-Net *** features a newhourglass structure that preserves the characteristics of the deep *** addition,the network incorporates two loss functions to generate natural and high-quality images:Low Frequency(LF)loss and High Frequency(HF)*** loss uses a pretrained VGG-16 network and is configured using a specific layer that best represents *** can enhance the performance in the high-frequency *** contrast,LF loss is used to handle the low-frequency *** two loss functions facilitate the generation of images by the generator,which can mislead the discriminator while accurately generating high-and low-frequency ***,by removing the blocking effects frommaximum lossy compressed images,images inwhich identities could be recognized are *** study represents a significant improvement over previous research in terms of the image resolution performance.

关键词： JPEG lossy compression restoration image generation GAN

Workout Action Recognition in Video Streams Using an Attention Driven Residual DC-GRU Network

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Computers, Materials & Continua 2024年第5期79卷 3067-3087页

作者： Arnab Dey Samit Biswas Dac-Nhuong Le department of Computer Science and technology Indian Institute of Engineering Science and TechnologyShibpurHowrah711103India Faculty of Information technology Haiphong UniversityHaiphong180000Vietnam

Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions in videostreams holds significant importance in computer vision research, as it aims to enhance exercise adherence, enableinstant recognition, advance fitness tracking technologies, and optimize fitness routines. However, existing actiondatasets often lack diversity and specificity for workout actions, hindering the development of accurate recognitionmodels. To address this gap, the Workout Action Video dataset (WAVd) has been introduced as a significantcontribution. WAVd comprises a diverse collection of labeled workout action videos, meticulously curated toencompass various exercises performed by numerous individuals in different settings. This research proposes aninnovative framework based on the Attention driven Residual Deep Convolutional-Gated Recurrent Unit (ResDCGRU)network for workout action recognition in video streams. Unlike image-based action recognition, videoscontain spatio-temporal information, making the task more complex and challenging. While substantial progresshas been made in this area, challenges persist in detecting subtle and complex actions, handling occlusions,and managing the computational demands of deep learning approaches. The proposed ResDC-GRU Attentionmodel demonstrated exceptional classification performance with 95.81% accuracy in classifying workout actionvideos and also outperformed various state-of-the-art models. The method also yielded 81.6%, 97.2%, 95.6%, and93.2% accuracy on established benchmark datasets, namely HMDB51, Youtube Actions, UCF50, and UCF101,respectively, showcasing its superiority and robustness in action recognition. The findings suggest practicalimplications in real-world scenarios where precise video action recognition is paramount, addressing the persistingchallenges in the field. TheWAVd datas

关键词： Workout action recognition video stream action recognition residual network GRU attention

Automatic Requirement Dependency Extraction Based on Integrated Active Learning Strategies

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Machine Intelligence Research 2024年第5期21卷 993-1010页

作者： Hui Guan Guorong Cai Hang Xu department of Computer Science and technology Shenyang University of Chemical TechnologyShenyang110142China Key Laboratory of Industrial Intelligence technology on Chemical Process Shenyang110142China

Since requirement dependency extraction is a cognitively challenging and error-prone task,this paper proposes an automatic requirement dependency extraction method based on integrated active learning *** this paper,the coefficient of variation method was used to determine the corresponding weight of the impact factors from three different angles:uncertainty probability,text similarity difference degree and active learning variant prediction divergence *** combining the three factors with the proposed calculation formula to measure the information value of dependency pairs,the top K dependency pairs with the highest comprehensive evaluation value are selected as the optimal *** the optimal samples are continuously added into the initial training set,the performance of the active learning model using different dependency features for requirement dependency extraction is rapidly ***,compared with other active learning strategies,a higher evaluation measure of requirement dependency extraction can be achieved by using the same number of ***,the proposed method using the PV-DM dependency feature improves the weight-F1 by 2.71%,the weight-recall by 2.45%,and the weight-precision by 2.64%in comparison with other strategies,saving approximately 46%of the labelled data compared with the machine learning approach.

关键词： Requirement dependency dependency extraction dependency features integrated active learning strategies coefficient of variation

Determination of Material Parameters of EVA Foam under Uniaxial Compressive Testing Using Hyperelastic Models

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Journal of Wuhan University of technology(Materials Science) 2024年第3期39卷 800-804页

作者： Nattapong Sangkapong Fasai Wiwatwongwana Nattawit Promma department of Mechanical Engineering Faculty of EngineeringChiang Mai UniversityChiang Mai 50300Thailand department of Advanced Manufacturing technology Faculty of EngineeringPathumwan Institute of TechnologyBangkok 10330Thailand

The objective of this research was to determine the mechanical parameter from EVA foam and also investigate its behavior by using Blatz-Ko,Neo-Hookean,Mooney model and experimental *** physical characteristic of EVA foam was also evaluated by scanning electron microscopy(SEM).The results show that Blatz-Ko and Neo-Hookean model can fit the curve at 5%and 8%strain,*** Mooney model can fit the curve at 50%*** modulus of rigidity evaluated from Mooney model is 0.0814±0.0027 *** structure of EVA foam from SEM image shows that EVA structure is a closed cell with homogeneous porous *** the result,it is found that Mooney model can adjust the data better than other *** model can be applied for mechanical response prediction of EVA foam and also for reference value in engineering application.

关键词： hyperelastic models modulus of rigidity EVA foam curve fitting method strain energy function uniaxial compressive testing