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A New Industrial Intrusion Detection Method Based on CNN-BiLSTM

Computers, Materials & Continua 2024年第6期79卷 4297-4318页

作者： jun wang Changfu Si Zhen wang Qiang Fu College of Computer Science and Technology Shenyang University of Chemical TechnologyShenyang110142China

Nowadays,with the rapid development of industrial Internet technology,on the one hand,advanced industrial control systems(ICS)have improved industrial production ***,there are more and more cyber-attacks targeting industrial control *** ensure the security of industrial networks,intrusion detection systems have been widely used in industrial control systems,and deep neural networks have always been an effective method for identifying cyber *** intrusion detection methods still suffer from low accuracy and a high false alarm ***,it is important to build a more efficient intrusion detection *** paper proposes a hybrid deep learning intrusion detection method based on convolutional neural networks and bidirectional long short-term memory neural networks(CNN-BiLSTM).To address the issue of imbalanced data within the dataset and improve the model’s detection capabilities,the Synthetic Minority Over-sampling Technique-Edited Nearest Neighbors(SMOTE-ENN)algorithm is applied in the preprocessing *** algorithm is employed to generate synthetic instances for the minority class,simultaneously mitigating the impact of noise in the majority *** approach aims to create a more equitable distribution of classes,thereby enhancing the model’s ability to effectively identify patterns in both minority and majority *** the experimental phase,the detection performance of the method is verified using two data *** results show that the accuracy rate on the CICIDS-2017 data set reaches 97.7%.On the natural gas pipeline dataset collected by Lan Turnipseed from Mississippi State University in the United States,the accuracy rate also reaches 85.5%.

关键词： Intrusion detection convolutional neural network bidirectional long short-term memory neural network multi-head self-attention mechanism

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Nanostructured AlFeO_(3) thin films as a novel photoanode for photoelectrochemical water splitting

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Nano Research 2024年第3期17卷 1075-1085页

作者： Xin Sun Min wang Qi geng Shuailin Chen Xiaojun Lv Xunlei Ding Meicheng Li State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of New EnergyNorth China Electric Power UniversityBeijing 102206China School of Mathematics and Physics North China Electric Power UniversityBeijing 102206China

The earth-abundant and robust aluminum ferrite,AlFeO_(3)(AFO),is mainly studied in the context of ***,we demonstrate that AFO can be used as a stable solar absorber in photoelectrochemical cells for solar water splitting,exhibiting attractive *** is the first report on the photoelectrochemical activity of *** thin-film photoelectrodes prepared by solution-processing methods are composed of vertically oriented thin nanosheets,featuring the rhombohedral symmetry(R3c)and n-type *** as-prepared AFO photoanodes generate a photocurrent density of+0.78 mA·cm^(-2) at 1.23 V *** hydrogen electrode(RHE)with the photocurrent _(onset) potential(U_(onset))close to the flat band potential of 0.5 V *** in the presence of hole ***,the U_(onset) of AFO for solar water splitting coincides with the flat band potential as well,which is rare in n-type inorganic *** also report other properties of AFO associated with photoelectrochemical *** films exhibit a band gap energy of 2.31 eV and positive band edges with low ***,the carrier lifetimes in AFO films are up to millisecond timescales under the mediation of defect *** on the photoelectrochemical behavior and optoelectronic properties,we believe that AFO has great potential for application in photoelectrochemical cells.

关键词： AlFeO_(3) photoanode nanosheets photoelectrochemistry onset potential

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Intelligent overheating fault diagnosis for overhead transmission line using semantic segmentation

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High Voltage 2024年第2期9卷 309-318页

作者： Xiangyu Yang Youping Tu Zhikang Yuan Zhong Zheng geng Chen Cong wang Yan Xu Beijing Key Laboratory of High Voltage and EMC North China Electric Power UniversityBeijingChina College of Electronic and Information Engineering Tongji UniversityShanghaiChina

The strain clamps and leading wires are important components that connect conductors on overhead transmission lines and conduct *** operation,poor contact between these components can cause abnormal overheating,leading to electric failures and threatening power system ***,the use of unmanned aerial vehicles equipped with infrared thermal imagers for strain clamp and leading wire maintenance has become increasingly *** learning-based image recognition shows promising prospects for intelligent fault diagnosis of overheating faults.A pre-treatment method is proposed based on dynamic histogram equalisation to enhance the contrast of infrared *** DeepLab v3+network,loss function,and existing networks with different backbones are *** DeepLab v3+network with ResNet101 and convolutional block attention module added,and the Focal Loss function achieved the highest performance with an average pixel accuracy of 0.614,an average intersection over union(AIoU)of 0.567,an F1 score of 0.644,and a frequency weighted intersection over union of 0.594 on the test *** optimised Atrous rates has increased the AIoU by 12.91%.Moreover,an intelligent diagnosis scheme for evaluating the defect state of the strain clamps and leading wires is proposed and which achieves a diagnostic accuracy of 91.0%.

关键词： union fault diagnosis

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Reaction Mechanism of Actin ATP Hydrolysis Studied by QM/MM Calculations

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Chemical Research in Chinese Universities 2024年第5期40卷 849-855页

作者： wang Yiwen LIN Lirui XU Li-Yan LI En-Min DONG geng Department of Biochemistry and Molecular Biology Shantou University Medical CollegeShantou515041P.R.China Department of Bioinformatics Shantou University Medical CollegeShantou515041P.R.China Medical Informatics Research Center Shantou University Medical CollegeShantou515041P.R.China Key Laboratory of Molecular Biology in High Cancer Incidence Coastal Area of Guangdong Higher Education Institutes Shantou University Medical CollegeShantou515041P.R.China Cancer Research Center Shantou University Medical CollegeShantou515041P.R.China Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology Shantou University Medical CollegeShantou515041P.R.China

Actin fibers are an important part of the cytoskeleton,providing vital support for the plasma *** function is driven by its ATPase(ATP:adenosine triphosphate)activity,i.e.,ATP+H_(2)O→ADP+*** seemingly simple reaction has attracted much attention because the hydrolysis of ATP provides energy to support life ***,the reaction mechanism of ATP hydrolysis in actin is not *** order to gain deep insights into the functions of actin,it is essential to elucidate the reaction mechanism of the actin ATP *** this paper,we have studied the reaction mechanism of the ATP hydrolysis in actin by the combined quantum mechanical and molecular mechanics(QM/MM)*** results show that 1)bond cleavage of the Pγ—OS of ATP and bond formation between oxygen of the lytic water and Pγatoms take place simultaneously,and this is the rate-limiting step of the hydrolysis;2)the proton on the lytic water transfers to the phosphate to form H_(2)P_(γ)O_(4)−via one bridge *** energy barrier of the complete reaction is 17.6 kcal/mol(1 kcal=4.184 kJ),which is in high agreement with the experimental value.

关键词： Actin Adenosine triphosphate(ATP)hydrolysis Quantum mechanical and molecular mechanics(QM/MM) Reaction mechanism

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Progress on the glassy-crystal laminates:From design,microstructure to deformation and future solutions

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Journal of Materials Science & Technology 2024年第5期172卷 113-144页

作者： Yu Chen Ronggao Cui jun Shen Gang wang College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China College of Physics and Optoelectronic Engineering Shenzhen UniversityShenzhen 518060China Department of Motor Design Business Weichai New Energy Technology Co.Ltd.Weifang 261061China Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robots Shenzhen UniversityShenzhen 518060China Laboratory for Microstructures Institute of MaterialsShanghai UniversityShanghai 200444China

The development of new design strategies to create innovative structural materials,refine existing ones,and achieves compatible combinations of strength and plasticity remains a worldwide *** alloys,such as shape memory alloys(SMAs),bulk metallic glasses(BMGs),high entropy alloys(HEAs),and heterogeneous pure metals such as Cu,have excellent mechanical responses,but they still fall short of meeting all the requirements of structural materials due to specific flaws,such as lack of tensile de-formation for BMGs and low yielding strength for *** address these shortcomings,proposals such as integrating glassy matrices and crystallized alloys,such as HEAs/SMAs,have been ***,these solutions have unresolved issues,such as the challenging control of B2 phase formation in BMG ***,glass-crystal(A/C)laminated alloys with alternating layers have been reported to exhibit improved mechanical properties and activated work-hardening behaviors,but they still face press-ing issues such as bonding interfaces and unknown deformation *** review focuses on design routes such as the selection of alloy components and processing techniques,exploration of micro-structural evolution and deformation modes with an increase in strain,and future solutions to address pressing and unsolved *** prominent advantages include diversified deformation mechanisms,such as deformation twinning,martensitic phase transformation,and precipitation hardening,as well as tuned interactive reactions of shear bands(SBs)near the A/C ***,this review provides a promising pathway to design and develop structural materials in the materials field community.

关键词： Glassy-crystal laminates Bulk metallic glasses High entropy alloys Shape memory alloys Microstructure Deformation mechanisms Future solutions

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An artificial intelligence approach for particle transport velocity prediction in horizontal flows

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Particuology 2024年第9期92卷 234-250页

作者： Haoyu Chen Zhiguo wang Hai Huang jun Zhang College of Petroleum Engineering Xi'an Shiyou UniversityXi'an710065China Shaanxi Key Laboratory of Carbon Dioxide Sequestration and Enhanced Oil Recovery Xi'an710065China College of New Energy Xi'an Shiyou UniversityXi'an710065China Engineering Research Center of Smart Energy and Carbon Neutral in Oil&Gas Field Universities of Shaanxi ProvinceChina The Erosion/Corrosion Research Center The University of TulsaOK74104United States

Particle entrainment is an inevitable phenomenon in pipeline systems,especially during the development and extraction phases of oil and gas *** predicting the critical velocity for particle transport is a key focus for implementing effective sand control *** work presents a semi-supervised learning–deep hybrid kernel extreme learning machine(SSL-DHKELM)model for predicting the critical velocity,which integrates multiple machine learning theories including the deep learning approach,which is adept at advanced feature ***,the SSL framework enhances the model's capabilities when data availability is *** improved slime mould algorithm is also employed to optimize the model's *** proposed model has high accuracy on both the sample dataset and out-of-sample *** trained with only 10%of the data,the model's error still did not increase ***,this model achieves superior predictive accuracy compared to existing mechanistic models,demonstrating its impressive performance and robustness.

关键词： Particle transport Critical velocity Deep learning Semi-supervised learning Extreme learning machine

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Optimal Model Average Prediction in Orthogonal Kriging Models

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Journal of Systems Science & Complexity 2024年第3期37卷 1080-1099页

作者： wang jun HE Jiabei LIANG Hua LI Xinmin School of Mathematics and Statistics Qingdao UniversityQingdao 266071China Department of Statistics George Washington UniversityWashington DC 20052USA

The main objective of this paper is to consider model averaging methods for kriging *** paper proposes a Mallows model averaging procedure for the orthogonal kriging model and demonstrate the asymptotic optimality of the model averaging estimators in terms of mean square *** studies are conducted to evaluate the performance of the proposed method and compare it with the competitors to demonstrate its *** authors also analyse a real dataset for an illustration.

关键词： Asymptotic optimality Mallows criterion optimal model averaging orthogonal kriging model

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Exhaust hood performance and its improvement technologies in industrial buildings:A literatu rereview

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Building Simulation 2024年第1期17卷 23-40页

作者： Jing Zhang Jian wang jun Gao Weimin Zhang Architectural Engineering Institute Jinhua PolytechnicJinhua 321017China Institute of HVAC Engineering Schoolof Mechanical EngineeringTongji UniversityShanghai 200092China Tongji Architectural Design(Group)Co .LtdShanghai 200092China

The pollutant control performance of exhaust hoods plays a crucial role in the indoor air quality and energy consumption of ventilation systems in industrial *** better understand the impact of local ventilation on the industrial indoor environment,this paper presents a literature review of exhaust hood performance and its improvement *** create an index for evaluating the performance of exhaust hoods,the capture velocity,capture efficiency,flow ratio of pollutant emissions and exhaust airflow and energy consumption are first introduced.A number of factors affecting exhaust hood performance are assessed such as hood type,hood opening size,exhaust rate,installation distance,pollution source emission and environmental *** to structural improvement methods,the use of active airflow is a more effective way to improve the exhaust hood *** most commonly used methods for determining the exhaust rate are the controlled speed method and the flow ratio *** use of an exhaust hood with an appropriate exhaust rate and jet parameters(for an active air-assisted hood)can effectively improve the pollutant control performance and reduce the energy consumption that would be wasted on the redundant exhaust *** more information focused on exhaust hood performance,this work suggests more effective strategies for improving indoor air quality and reducing energy consumption in industrial buildings.

关键词： industrial ventilation exhaust hood capture efficiency exhaust rate performance improvement

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Experimental Study of Temperature Control Based on Composite Phase Change Materials during Charging and Discharging of Battery

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Journal of Thermal Science 2024年第2期33卷 578-590页

作者： LI Xiaolin wang jun CAO Wenxiang ZHANG Xuesong School of Automotive and Traffic Engineering Jiangsu UniversityZhenjiang212013China

This study is to utilize the heat-absorbing and releasing capabilities of phase change materials(PCM)to regulate the surface temperature fluctuations of batteries during charging and *** goal is to keep the battery within the optimal operating temperature *** impact of PCM thickness and phase change temperature on battery temperature is investigated by encircling a cylindrical battery with a PCM *** improve the thermal conductivity of PCM,expanded graphite(EG) is added to make a composite phase change material(CPCM),and the effects of various EG mass ratios on battery surface temperature and CPCM utilization level are *** findings indicate that increasing PCM thickness effectively extends temperature control time,but its impact is *** difference in phase change temperature of PCM controls the battery temperature in different temperature *** phase change temperatures are unsuitable for controlling battery temperature in high temperature *** addition of EG enhances the thermal conductivity of PCM,leading to further control of battery *** results show that the addition of 6%(mass ratio) EG to CPCM extends the effective temperature control time by 11 min and improves by 28% compared to a single *** CPCM utilization is also more satisfactory and achieved a balance between heat storage and thermal conductivity in a battery thermal management system(BTMS) based on PCM.

关键词： phase change material expanded graphite thermal management system effective control time

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Time-history performance optimization of flapping wing motion using a deep learning based prediction model

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Chinese Journal of Aeronautics 2024年第5期37卷 317-331页

作者： Tianqi wang Liu LIU jun LI Lifang ZENG School of Aeronautics and Astronautics Zhejiang UniversityHangzhou 310027China Huanjiang Laboratory Zhuji 311800China

Flapping Wing Micro Aerial Vehicles(FWMAVs)have caused great concern in various fields because of their high efficiency and *** wing motion is a very important factor that affects the performance of the aircraft,and previous works have always focused on the time-averaged performance ***,the time-history performance is equally important in the design of motion mechanism and flight control *** this paper,a time-history performance optimization framework based on deep learning and multi-island genetic algorithm is presented,which is designed in order to obtain the optimal two-dimensional flapping wing ***,the training dataset for deep learning neural network is constructed based on a validated computational fluid dynamics *** aerodynamic surrogate model for flapping wing is obtained after the convergence of *** surrogate model is tested and proved to be able to accurately and quickly predict the time-history curves of lift,thrust and ***,the optimization framework is used to optimize the flapping wing motion in two specific cases,in which the optimized propulsive efficiencies have been improved by over 40%compared with the ***,a dimensionless parameter C_(variation)is proposed to describe the variation of the time-history characteristics,and it is found that C_(variation)of lift varies significantly even under close time-averaged *** the importance of time-history performance in practical applications,the optimization that integrates the propulsion efficiency as well as C_(variation)is carried *** final optimal flapping wing motion balances good time-averaged and time-history performance.

关键词： FWMAV Flapping wing motion Deep learning Unsteady aerodynamic performance Optimization Time-history curve

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