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Machine learning based models for predicting compressive strength of geopolymer concrete

Frontiers of Structural and Civil Engineering 2024年第7期18卷 1028-1049页

作者： Quang-Huy le Duy-Hung NGUYEN Thanh SANG-TO Samir KHATIR Hoang le-MINH Amir H.GANDOMI Thanh CUONG-le Center for Engineering Application and Technology Solutions Ho Chi Minh City Open UniversityHo Chi Minh 700000Vietnam Institute of Civil Engineering Ho Chi Minh City University of TransportHo Chi Minh 700000Vietnam Faculty of Engineering&Information Technology University of Technology SydneyUltimoNSW 2007Australia

Recently,great attention has been paid to geopolymer concrete due to its advantageous mechanical and environmentally friendly *** effort has been made in experimental studies to advance the understanding of geopolymer concrete,in which compressive strength is one of the most important *** facilitate engineering work on the material,an efficient predicting model is *** this study,three machine learning(ML)-based models,namely deep neural network(DNN),K-nearest neighbors(KNN),and support vector machines(SVM),are developed for forecasting the compressive strength of the geopolymer concrete.A total of 375 experimental samples are collected from the literature to build a database for the development of the predicting models.A careful procedure for data preprocessing is implemented,by which outliers are examined and removed from the database and input variables are standardized before feeding to the fitting *** standard K-fold cross-validation approach is applied for evaluating the performance of the models so that overfitting status is well managed,thus the generalizability of the models is *** effectiveness of the models is assessed via statistical metrics including root mean squared error(RMSE),mean absolute error(MAE),correlation coefficient(R),and the recently proposed performance index(PI).The basic mean square error(MSE)is used as the loss function to be minimized during the model fitting *** three ML-based models are successfully developed for estimating the compressive strength,for which good correlations between the predicted and the true values are obtained for DNN,KNN,and *** numerical results suggest that the DNN model generally outperforms the other two models.

关键词： geopolymer concrete compressive strength prediction machine-learning based model deep neural network K-nearest neighbor support vector machines

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Boundless love:a German Professor Uli Schwarz in China

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Protein & Cell 2024年第8期15卷 553-558页

作者： le Kang State Key Laboratory of Integrated Management of Pest Insects and Rodents Institute of ZoologyChinese Academy of SciencesBeijing 100101China

More than 20 years ago,an old German man embarked on a quest to explore the suburbs of Shanghai and the villages of jiangsu Province in search of antique Chinese *** was not a mere antique collector or aficionado of ancient furmiture,but a German scientist motivated by his profound love of Chinese *** name was Uli Schwarz(Fig.1),a distinguished German scientist who had dedicated the majority of his life to promoting cross-cultural scientific exchanges,an effort that left an indelible mark on the landscape of research collaborations between China and Germany.

关键词： Schwarz German landscape

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A Graded Speed Control Method for Cyborg Rats Based on Electrical Stimulation of the Cuneiform Nucleus

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Journal of Bionic Engineering 2024年第3期21卷 1334-1346页

作者： Hanyi Ling le Han Nenggan Zheng Qiushi Academy for Advanced Studies(QAAS) Zhejiang UniversityHangzhou310007China The State Key Lab of Brain-Machine Intelligence Zhejiang UniversityHangzhou310007China College of Biomedical Engineering&Instrument Science Zhejiang UniversityHangzhou310007China College of Computer Science and Technology Zhejiang UniversityHangzhou310007China CCAI by MOE and Zhejiang Provincial Government(ZJU) Hangzhou310007China

The precise movement speed regulation is a key factor to improve the control effect and efficiency of the cyborg ***,the current stimulation techniques cannot realize the graded control of the *** this study,we achieved the multi-level speed regulation of cyborg rats in the large open field and treadmill by specifically targeting the Cuneiform Nucleus(CnF)of the Mesencephalic Locomotor Region(MLR).Detailed,we measured the influence of each stimulation parameter on the speed control process which included the real-time speed,accelerated speed,response time,and acceleration *** concluded that the pulse period and the pulse width were the main determinants influencing the accelerated speed of cyborg *** the amplitude of stimulation was found to affect the response time exhibited by the cyborg *** study provides valuable insights into the regulation of rat locomotion speed and highlights the potential for utilizing this approach in various experimental settings.

关键词： Cyborg rats Cuneiform nucleus Graded control Speed regulation

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Adaptive fault-tolerant control for non-minimum phase hypersonic vehicles based on adaptive dynamic programming

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Chinese Journal of Aeronautics 2024年第3期37卷 290-311页

作者： le WANG Ruiyun QI Bin JIANG State Key Laboratory of Mechanics and Control for Aerospace Structures Nanjing University of Aeronautics and AstronauticsNanjing 210016China College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China

In this paper,a novel adaptive Fault-Tolerant Control(FTC)strategy is proposed for non-minimum phase Hypersonic Vehicles(HSVs)that are affected by actuator faults and parameter *** strategy is based on the output redefinition method and Adaptive Dynamic Programming(ADP).The intelligent FTC scheme consists of two main parts:a basic fault-tolerant and stable controller and an ADP-based supplementary *** the basic FTC part,an output redefinition approach is designed to make zero-dynamics stable with respect to the new ***,Ideal Internal Dynamic(IID)is obtained using an optimal bounded inversion approach,and a tracking controller is designed for the new output to realize output tracking of the nonminimum phase HSV *** the ADP-based compensation control part,an ActionDependent Heuristic Dynamic Programming(ADHDP)adopting an actor-critic learning structure is utilized to further optimize the tracking performance of the HSV control ***,simulation results are provided to verify the effectiveness and efficiency of the proposed FTC algorithm.

关键词： Hypersonic vehicle Fault-tolerant control Non-minimum phase system Adaptive control Nonlinear control Adaptive dynamic programming

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Silent battles:immune responses in asymptomatic SARS-CoV-2 infection

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Cellular & Molecular Immunology 2024年第2期21卷 159-170页

作者： Nina le Bert Taraz Samandari Program in Emerging Infectious Diseases Duke-NUS Medical SchoolSingaporeSingapore

SARS-CoV-2 infections manifest with a broad spectrum of presentations,ranging from asymptomatic infections to severe pneumonia and fatal *** review centers on asymptomatic infections,a widely reported phenomenon that has substantially contributed to the rapid spread of the *** such asymptomatic infections,we focus on the role of innate,humoral,and cellular ***,asymptomatic infections are characterized by an early and robust innate immune response,particularly a swift type 1 IFN reaction,alongside a rapid and broad induction of SARS-CoV-2-specific T ***,antibody levels tend to be lower or undetectable after asymptomatic infections,suggesting that the rapid control of viral replication by innate and cellular responses might impede the full triggering of humoral *** if antibody levels are present in the early convalescent phase,they wane rapidly below serological detection limits,particularly following asymptomatic ***,prevalence studies reliant solely on serological assays likely underestimate the extent of community exposure to the virus.

关键词： COVID-19 asymptomatic cellular immunity antibody

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Heat Transfer and Flow Structure of a Turbine Blade's Air-cooled leading Edge Considering Different Hole Shapes and Additional Flow Angles

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Journal of Thermal Science 2024年第4期33卷 1421-1442页

作者： QIN Runxuan ZHOU Xun WANG Songtao CAI le School of Energy Science and Engineering Harbin Institute of TechnologyHarbin150001China

A numerical study is conducted to elucidate the impact of hole shapes and additional flow angles on the flow structure of the coolant and temperature field in the leading edge area of the gas turbine *** typical hole shapes are considered for the GE-E3 *** impact of the additional flow angle(E)within each hole shape on the temperature field is *** results indicate that for the leading edge area and suction surface,the fan-shaped hole case performs best in decreasing temperatures,with a decrease of about 43 *** is mainly due to the fact that the fan-shaped hole has the maximum expansion in hole spanwise *** the pressure surface,the console hole case performs best in decreasing temperatures,with a maximum reduction of about 47.2 *** influence of E on the surface temperature at leading edge area varied between the different hole *** the cylinder hole and console hole,the E=-20°case has the lowest area-averaged *** both the fan-shaped hole and the 7-7-7 shaped hole are expansion holes,the pattern of variation of the leading edge area temperature with increasing E is similar for the fan-shaped hole case and 7-7-7 shaped hole *** E=20°case shows the lowest spanwise-averaged temperature near the hole outlet,and the E=-20°case shows the lowest spanwise-averaged temperature further downstream.

关键词： film cooling GE-E3 turbine rotor blade conjugate heat transfer leading edge

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Path signature-based XAI-enabled network time series classification

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Science China(Information Sciences) 2024年第7期67卷 91-106页

作者： le SUN Yueyuan WANG Yongjun REN Feng XIA Department of Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science and Technology School of Computing Technologies Royal Melbourne Institute of Technology

Classifying network time series(NTS) is crucial for automating network administration and ensuring cyberspace security. It enables the detection of anomalies, the identification of network attacks,and the monitoring of performance issues, thereby providing valuable support for network protection and optimization. However, modern communication networks pose challenges for NTS classification *** include handling large-scale and complex NTS data, extracting features from intricate datasets, and addressing explainability requirements. These challenges are particularly pronounced for complex 5G networks. Notably, explainability has become crucial for the widespread deployment of network automation for 5G networks and beyond. To tackle these challenges, we propose a path-signature-based NTS classification model called recurrent signature(Recur Sig). This innovative model is designed to overcome the time-consuming feature selection problem by utilizing deep-learning(DL) techniques. Additionally, it provides a solution for addressing the black-box issue associated with DL models in network automation systems(NAS) by incorporating an explainable classification approach. Extensive experimentation on various public datasets demonstrates that Recur Sig outperforms existing models in accuracy and explainability. The results indicate its potential for application in cyberspace security and automated network management, offering an explainable solution for network protection and optimization.

关键词： network time series classification explainable artificial intelligence path signature automated network management recurrent neural network

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Energy harvesting technology for AC overhead insulated transmission line based on electric field induction

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High Voltage 2024年第4期9卷 816-825页

作者： le Zhou Hongwei Liu Kun Zuo Kuo Shang School of Electrical and Electronic Engineering North China Electric Power UniversityBeijingChina Electric Power Company of Sichuan Province Tianfu Power Supply Company ChengduSichuanChina Changde Power Supply Branch State Grid Hunan Electric Power Company LimitedChangdeHunanChina

To solve the problem of the energy harvesting(EEH)effect of the condition monitoring devices power supply on the transmission line is not *** authors designed three kinds of EEH schemes based on AC electric field induction,which can effectively improve the output power of load power *** EEH principle of each scheme was analysed in detail,and the influence factors such as the shape of outer energy harvester,capacitance compensation and impedance matching characteristics were ***,the experiment showed that 140.9 mW of power was obtained in direct-mode field EEH when the line voltage level was 10 *** high-potential field EEH mode obtained 4.1 mW of *** harvesting effect of the inner energy harvester with the same potential as the aluminium wire was obviously better,and 30.7 mW of power was ***,based on the third mode,when the load resistance was 2200Ω,the rectifier received 23.7 mW DC *** experimental results are in agreement with the theoretical analysis,which verifies the effectiveness of the electric field induction power supply technology.

关键词： field harvesting mode

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Proposing a machine learning approach to analyze and predict basic high-temperature properties of iron ore fines and its factors

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Journal of Iron and Steel Research International 2024年第5期31卷 1082-1094页

作者： Qing-ke Sun Yao-zu Wang Jian-liang Zhang Zheng-jian Liu le-le Niu Chang-dong Shan Yun-fei Ma Institute of Artificial Intelligence University of Science and Technology BeijingBeijing100083China School of Intelligence Science and Technology University of Science and Technology BeijingBeijing100083China School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing100083China

The basic high-temperature properties of iron ore play a crucial role in optimizing sintering and ore blending,but the testing process for these properties is complex and has significant lag time,which cannot meet the actual needs of ore blending.A prediction model for the basic high-temperature properties of iron ore fines was thus proposed based on a combination of machine learning algorithms and genetic ***,the prediction accuracy of different machine learning models for the basic high-temperature properties of iron ore fines was ***,a random forest model optimized by genetic algorithms was built,further improving the prediction accuracy of the *** test results show that the random forest model optimized by genetic algorithms has the highest prediction accuracy for the lowest assimilation temperature and liquid phase fluidity of iron ore,with a determination coefficient of 0.903 for the lowest assimilation temperature and 0.927 for the liquid phase fluidity after *** trained model meets the fluctuation requirements of on-site testing and has been successfully applied to actual production on site.

关键词： Iron ore Basic high-temperature property Machine learning Random forest Genetic algorithm

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leader-follower Optimal Selection Method for Distributed Control System in Active Distribution Networks

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 314-323页

作者： Jian le Liangang Zhao Cao Wang Qian Zhou Yang Wang School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China

Aiming at the shortcomings of a traditional centralized control in an active distribution network(AND),this paper proposes a leader-follower distributed group cooperative control strategy to realize multiple operation and control tasks for an *** distributed information exchange protocols of the distributed generation(DG)group devoted to node voltage regulation or exchange power control are developed using a DG power utilization ratio as the consensus *** these bases,this study further investigates the leader optimal selection method for a DG group to improve the response speed of the distributed control ***,a single or multiple leader selection model is established to minimize the constraints of the one-step convergence factor and the number of leaders to improve the response speed of the distributed control *** simulation results of the IEEE 33 bus standard test system show the effectiveness of the proposed distributed control *** addition,the response speed of a DG control group can be improved effectively when the single or multiple leaders are selected optimally.

关键词： Active distribution1network consensus algorithm leader-follower system mixed-integer semidefinite programming optimal distributed control

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