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Towards understanding and prediction of corrosion degradation of organic coatings under tropical marine atmospheric environment via a data-driven approach

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International Journal of Minerals,Metallurgy and Materials 2025年第5期32卷 1151-1161页

作者： Shaopeng Liu Lingwei Ma Jinke Wang Yiran Li Haiyan Gong Haitao Ren Xiaogang Li Dawei Zhang Beijing Advanced Innovation Center for Materials Genome Engineering Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China National Materials Corrosion and Protection Data Center University of Science and Technology BeijingBeijing 100083China Institute of Materials Intelligent Technology Liaoning Academy of MaterialsShenyang 110004China Luoyang Ship Material Research Institute Sanya 572032China

The corrosion degradation of organic coatings in tropical marine atmospheric environments results in substantial economic losses across various *** complexity of a dynamic environment,combined with high costs,extended experimental periods,and limited data,places a limit on the comprehension of this *** study addresses this challenge by investigating the corrosion de-gradation of damaged organic coatings in a tropical marine environment using an atmospheric corrosion monitoring sensor and a random forest(RF)*** damage simulation,a polyurethane coating applied to a Fe/graphite corrosion sensor was intentionally scratched and exposed to the marine atmosphere for over one *** correlation analysis was performed for the collection and filtering of en-vironmental and corrosion current *** to the RF model,the following specific conditions contributed to accelerated degrada-tion:relative humidity(RH)above 80%and temperatures below 22.5℃,with the risk increasing significantly when RH exceeded 90%.High RH and temperature exhibited a cumulative effect on coating degradation.A high risk of corrosion occurred in the *** RF model was also used to predict the coating degradation process using environmental data as input parameters,with the accuracy show-ing improvement when the duration of influential environmental ranges was considered.

关键词： organic coating degradation atmospheric corrosion machine learning exposure test random forest coating sensor

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Assessing the sustainability of small hydropower sites in the Citarum Watershed, Indonesia employing CA-Markov and SWAT models

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Water Supply 2024年第9期24卷 3253-3268页

作者： Pranoto, Bono Hartulistiyoso, Edy Aidi, Muhammad Nur Sutrisno, Dewayany Nahib, Irmadi Purwono, Nugroho Hudayat, Nurul Rais, Achmad Fahruddin Rahmila, Yulizar Ihrami IPB University Bogor16144 Indonesia Research Center for Limnology and Water Resources National Research and Innovation Agency Bogor16911 Indonesia Department of Mechanical and Biosystems Engineering IPB University Bogor16680 Indonesia Department of Statistics and Data Science IPB University Bogor16680 Indonesia Research Center for Conservation of Marine and Inland Water Resources National Research and Innovation Agency Bogor16911 Indonesia Research Center for Population National Research and Innovation Agency Jakarta12710 Indonesia Research Center for Ecology and Ethnobiology National Research and Innovation Agency Bogor16911 Indonesia

This study investigates the sustainability of potential small hydropower sites within the Citarum Watershed in West Java, Indonesia. The Citarum River, with a catchment area of 6,090 km2, plays a crucial role in regional water supply and hydroelectric power generation. However, environmental challenges such as deforestation, land use changes, and sedimentation pose significant risks. We employed the CA-Markov model integrated with IDRISI TerrSet software and the Soil and Water Assessment Tool to predict future land use changes and assess water supply, soil erosion, and sedimentation impacts for 2030 and 2040. The analysis revealed diverse trends in water yield across different catchment areas, with some regions showing increased water availability and others facing declines. High erosion and sedimentation rates were identified as critical issues affecting hydropower efficiency. The study highlights the need for comprehensive watershed management strategies, including reforestation, sustainable land management practices, and sediment management, to enhance the sustainability of small hydropower projects. Our findings underscore the importance of integrating environmental considerations into hydropower development to ensure the ecological integrity of the Citarum Watershed. © 2024 The Authors.

关键词： Runoff

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Two efficient beamforming methods for hybrid IRS-aided AF relay wireless networks

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science China(Information sciences) 2025年第4期68卷 363-379页

作者： Xuehui WANG Qingbo LI Wen ZHU Feng SHU Mengxing HUANG Fuhui ZHOU Riqing CHEN Cunhua PAN Yongpeng WU Jiangzhou WANG School of Mathematics and Statistics Hainan Normal University Key Laboratory of Data Science and Smart Education Ministry of Education Hainan Normal University School of Information and Communication Engineering Hainan University Collaborative Innovation Center of Information Technology Hainan University School of Electronic and Optical Engineering Nanjing University of Science and Technology College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Digital Fujian Institute of Big Data for Agriculture Fujian Agriculture and Forestry University National Mobile Communications Research Laboratory Southeast University Shanghai Key Laboratory of Navigation and Location Based Services Shanghai Jiao Tong University School of Engineering University of Kent

Owing to its ability to mitigate the double-fading effect by amplifying the reflected signal, the active intelligent reflecting surface(IRS) has garnered significant attention. In this paper, an amplify-and-forward(AF) relay network assisted by a hybrid IRS consisting of both passive and active units is developed. A signal-to-noise ratio(SNR) maximization problem is formulated, where the AF relay beamforming matrix and the hybrid IRS reflecting coefficient matrices for two-time slots need to be optimized. To address the SNR maximization problem, this paper proposes both a high-performance(HP) method and a low-complexity(LC) method. The HP method is based on the semidefinite relaxation and fractional programming(SDR-FP)algorithm, with rank-1 solutions obtained through Gaussian randomization. For the LC method, the amplification coefficient of each active IRS element is assumed to be equal. The SNR maximization problem is then addressed using the whitening filter,generalized power iteration, and generalized Rayleigh-Ritz(WF-GPI-GRR) approach. Simulation results show that compared with the benchmarks, such as the passive IRS-aided AF relay network, the proposed HP-SDR-FP and WF-GPI-GRR methods achieve significant rate improvements. In particular, the HP-SDR-FP and WF-GPI-GRR methods yield more than a 135.0%rate gain when the transmit power Ps of the source is 10 dBm. Furthermore, the proposed HP-SDR-FP method outperforms the WF-GPI-GRR method in terms of rate performance.

关键词： double-fading intelligent reflecting surface active elements passive elements hybrid IRS AF relay

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Atomic Spin Polarization Controllability Analysis:A Novel Controllability Determination Method for Spin-Exchange Relaxation-Free Co-Magnetometers

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 699-708页

作者： Zhuo Wang Sixun Liu Ruigang Wang Linlin Yuan Jiong Huang Yueyang Zhai Sheng Zou IEEE the Research Institute for Frontier Science the Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beihang University the School of Instrumentation and Optoelectronic Engineering Beihang University the Research Institute of Frontier Science Beihang University

This paper investigates the atomic spin polarization controllability of spin-exchange relaxation-free co-magnetometers(SERFCMs).This is the first work in the field of controllability analysis for the atomic spin ensembles systems,whose dynamic behaviors of spin polarization are described by the Bloch *** on the Bloch equations,a state-space model of the atomic spin polarization for SERFCM is first established,which belongs to a particular class of nonlinear *** this class of nonlinear systems,a novel determination method for the global state controllability is proposed and ***,this method is implemented in the process of controllability analysis on the atomic spin polarization of an actual ***,a theoretically feasible and reasonable solution of the control input is proposed under some physical constraints,with whose limitation of realistic conditions,the controller design can be accomplished more practically and more ***,the simulation results demonstrate the feasibility and validation of the proposed controllability determination method.

关键词： Atomic spin polarization Bloch equations controllability determination nonlinear state-space model spin-exchange relaxation-free co-magnetometer(SERFCM)

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Small Object Detection Algorithm for Unmanned Aerial Vehicle Based on Multifaceted Feature Information Extraction and Fusion 8

Small Object Detection Algorithm for Unmanned Aerial Vehicle...

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8th International Symposium on Computer science and Intelligent Control, ISCSIC 2024

作者： Yin, Shasha Ge, Yueran Tian, Lingling Hebei University of Technology School of Artificial Intelligence and Data Science Tianjin China Hebei University of Technology Control Engineering Technology Innovation Center of Hebei Province Tianjin China

ISBN: (纸本)9798350380286

Unmanned Aerial Vehicle (UAV) image object detection has been widely applied in security and disaster relief and other aspects. For the sake of solving the problem of many small objects, this paper proposes a Multifaceted feature information extraction and fusion algorithm (MFIEF). Firstly, the multi-information feature extraction convolution module (MFECM) is adopted, which retains more small object feature information and surrounding spatial information. Secondly, the optimized FPN structure (OFPN) is used, the fusion of horizontal and vertical information avoids the loss of information, and the addition of lightweight attention convolution module (LACM) reduces the number of parameters while improving attention to key object information. The experimental results on the VisDrone datasets demonstrate that the MFIEF algorithm achieves a obvious improvement in performance compared to the benchmark algorithm. Specifically, the mAP@0.5 value of MFIEF is 9.7 percentage points higher, while the mAP@0.5:0.95 value of MFIEF is 6.7 percentage points higher than the benchmark algorithm. These findings highlight the superior performance of MFIEF in object detection tasks on the VisDrone datasets. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Solar-tracking methodology based on refraction-polarization in Snell's window for underwater navigation

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Chinese Journal of Aeronautics 2022年第3期35卷 380-389页

作者： Pengwei HU Jian YANG Lei GUO Xiang YU Wenshuo LI School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beihang UniversityBeijing 100191China Hangzhou Innovation Institute Beihang UniversityHangzhou 310051China

Underwater navigation system is an indispensable part for autonomous underwater *** to the indiscernibility of satellite signal,however,the underwater navigation problem is quite challenging,and a satellite-free navigation scheme should be looked *** navigation,inspired by insects’capability of autonomous homing and foraging,is an alternative solution to satellite navigation with great application *** polarization provides an indirect sun compass to animals for orientation ***,it is difficult to apply terrestrial solar-tracking methodologies in underwater situations due to the refraction of polarized skylight at the air–water *** resolve this issue,an underwater solar-tracking algorithm is developed based on the underwater refraction-polarization pattern inside the Snell’s *** employing Snell’s law and Fresnel refraction formula to decouple the refractive ray bending and polarization deflection,the celestial polarization pattern is obtained based on underwater *** further improve the accuracy,the degree of polarization is employed as a weight factor for E-vector.A long-lasting underwater experiment was conducted to validate the effectiveness of the proposed approach,and the results showed the root-mean-square errors of solar zenith and azimuth employing this algorithm were 0.3°and 1.3°,*** experimental results show that the refraction-polarization pattern inside the Snell’s window exhibits immense potential to improve the solar-tracking accuracy for underwater navigation.

关键词： Polarization Refraction Snell’s window Solar position Underwater navigation

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Hybrid feature-based neural network regression method for load profiles forecasting

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Energy Informatics 2025年第1期8卷 1-20页

作者： Satan, Aidos Zhakiyev, Nurkhat Nugumanova, Aliya Friedrich, Daniel Department of Science and Innovation Astana IT University Astana010000 Kazakhstan Big Data and Blockchain technologies Research Center Astana IT University Astana Kazakhstan School of Engineering Institute for Energy Systems University of Edinburgh EdinburghEH93DW United Kingdom Department of Energy Engineering University of Genova Savona17100 Italy

This study addresses the critical need for improved demand forecasting models that can accurately predict energy consumption, particularly in the context of varying geographical and climatic conditions. The work introduces a novel demand forecasting model that integrates clustering techniques and feature engineering into neural network regression, with a specific focus on incorporating correlations with air temperature. Evaluation of the model’s efficacy utilized a benchmark dataset from Tetouan, Morocco, where existing forecasting methods yielded RMSE values ranging from 6429 to 10,220 [MWh]. In contrast, the proposed approach achieved a significantly lower RMSE of 5168, indicating its superiority. Subsequent application of the model to forecast demand in Astana, Kazakhstan, as a case study, showcased its efficacy further. Comparative analysis against a baseline neural network method revealed a notable improvement, with the proposed model exhibiting a MAPE of 5.19% compared to the baseline’s 17.36%. These findings highlight the potential of the proposed approach to enhance demand forecasting accuracy, particularly across diverse geographical contexts, by leveraging climate-related inputs, the methodology also demonstrates potential for broader applications, such as flood forecasting, agricultural yield prediction, or water resource management. © The Author(s) 2025.

关键词： Demand response

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Piezoelectric-Based Smart Bone Plate for Fracture Healing Progress Monitoring

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Journal of Shanghai Jiaotong university(science) 2022年第4期27卷 561-569页

作者： GAO Zihang WANG Xin ZHAO Yifana JIN Zhehuia WANG Gang GAO Shuo School of Instrumentation Science and Optoelectronic Engineering Beihang UniversityBeijing100083China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Interdisciplinary Innovation Institute of Medicine and EngineeringBeihang UniversityBeijing100083China

Fracture healing progress monitoring techniques attract global research attention due to the importance of selecting the timing of removing the fixation *** this end,in this research,we present a piezoelectric-based smart internal fixation device,in which a piezoelectric sandwich structure is laminated to the surface of a bone *** the content,we explain the reasons for utilizing piezoelectric films,elaborate the mechanism of fracture monitoring,and introduce the mechanical parameters of the *** simulation and experimental results show that the electrical output of the device is associated with the elastic modulus of the filler between the tested broken bones when the working load is maintained,indicating that the bone recovery progress could be successfully detected by the developed technique.

关键词： piezoelectric device bone plate fracture healing monitoring Internet of Health Things

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Facile synthesis of W-Mo bimetallic oxides with high adsorption properties from secondary resources

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Tungsten 2024年第4期6卷 806-820页

作者： Jia-Li Cheng Yang-Si Liu Xiao-Li Xi Zuo-Ren Nie Collaborative Innovation Center of Capital Resource-Recycling Material Technology College of Materials Science and EngineeringBeijing University of TechnologyBeijing100124China National Engineering Laboratory for Industrial Big-Data Application Technology Beijing University of TechnologyBeijing100124China Key Laboratory of Advanced Functional Materials Ministry of EducationBeijing University of TechnologyBeijing100124China

A simple solvothermal method was used to obtain W-Mo bimetallic oxides from W-Mo alloy scrap,and pure metal powders were also used as the raw materials to simulate *** products had a sea urchin-like structure with abundant oxygen vacancies and the products prepared at low temperatures forms a sosoloid resembling orthorhombic W_(0.4)Mo_(0.6)O_(3).The WMo bimetallic oxide prepared at the reaction temperature of 120℃exhibited excellent selective adsorption performance for methylene blue(MB),which the adsorption rate of MB reached 99%in 12 min and the adsorption rate reached 90%after6 adsorption *** the W-Mo molar ratio is 1:3,the maximum adsorption capacity of sample for MB can reach1148 mg·g^(-1).The adsorption process followed the Langmuir and pseudo-second-order models,which is surface-controlled monolayer *** experimental results show the feasibility of preparing W-Mo bimetal oxide products from pure materials and *** process is simple and effective,which offered a potential approach for secondary resource recycling and reusing.

关键词： W-Mo bimetallic oxide Oxygen vacancy Selective adsorption W-Mo alloy scrap Solvothermal

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MAML^(2):meta reinforcement learning via meta-learning for task categories

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Frontiers of Computer science 2023年第4期17卷 57-67页

作者： Qiming FU Zhechao WANG Nengwei FANG Bin XING Xiao ZHANG Jianping CHEN School of Electronics and Information Engineering Suzhou University of Science and TechnologySuzhou 215009China Chongqing Industrial Big Data Innovation Center Co.Ltd. Chongqing 404100China School of Medical Informatics Xuzhou Medical UniversityXuzhou 221004China School of Architecture and Urban Planning Suzhou University of Science and TechnologySuzhou 215009China

Meta-learning has been widely applied to solving few-shot reinforcement learning problems,where we hope to obtain an agent that can learn quickly in a new ***,these algorithms often ignore some isolated tasks in pursuit of the average performance,which may result in negative adaptation in these isolated tasks,and they usually need sufficient learning in a stationary task *** this paper,our algorithm presents a hierarchical framework of double meta-learning,and the whole framework includes classification,meta-learning,and ***,in the classification process,we classify tasks into several task subsets,considered as some categories of tasks,by learned parameters of each task,which can separate out some isolated tasks ***,in the meta-learning process,we learn category parameters in all subsets via ***,based on the gradient of each category parameter in each subset,we use meta-learning again to learn a new metaparameter related to the whole task set,which can be used as an initial parameter for the new ***,in the re-adaption process,we adapt the parameter of the new task with two steps,by the meta-parameter and the appropriate category parameter ***,we demonstrate our algorithm prevents the agent from negative adaptation without losing the average performance for the whole task ***,our algorithm presents a more rapid adaptation process within ***,we show the good performance of our algorithm with fewer samples as the agent is exposed to an online meta-learning setting.

关键词： meta-learning reinforcement learning few-shot learning negative adaptation

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