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IEEE Symposium on Nuclear science (NSS/MIC)

作者： Peng Fan Siliang Feng Chenglin Zhu Chunqing Zhao Yigang Ding Zicai Shen Yaqiang Liu Tianyu Ma Yan Xia Beijing Institute of Spacecraft Environment Engineering and National key Laboratory of Science and Technology on Reliability and Environmental Engineering Beijing China Beijing Institute of Spacecraft Environment Engineering Beijing China Tsinghua University Beijing China

Artificial neural networks (ANN) based on learning the features of the entire measured gamma energy spectrum has been used for radioisotope identification and proved promising especially for gamma-ray spectroscopy with low energy resolution. The implementation of ANN method, however, requires tedious experimental measurement process in generation of training data for various radioisotopes. In this work, we propose an ANN-based radioisotope identification method with simulated training data. Gamma energy spectra of 27 different radioisotopes were generated with Monte Carlo simulation. A detector energy response model was proposed to match the energy spectra generated from simulation and measured from experiment, thus “pseudo” measured energy spectra of various radioisotopes transformed from simulation can be used for ANN training, which eliminates the tedious experimental measurement process for training data generation. To reduce the complexity of the training process, the principal component analysis (PCA) method was used for dimension reduction of the input energy spectra in ANN and the channel number of the energy spectra was reduced from 2000 to 50. The trained ANN was further used to identify experimentally measured gamma energy spectra of various radioisotopes including 60 Co., 137 CS., 18 F, 131 I, 226 Ra and 232 Th at 10 3 , 10 4 and 10 5 count levels. In single isotope identification test, with increased count level, higher correct identification rate is achieved and at 10 5 count level, all the isotopes are correctly identified for all the samples. In mixed isotope identification test, at 10 5 count level, all the radioisotope combinations can be identified with a correct identification rate larger than 98%, which demonstrates the feasibility and accuracy of the ANN method. To conclude, the proposed ANN method with simulated training data features good radioisotope identification capability with greatly simplified training data generation process

关键词： Training Radioactive materials Spectroscopy Energy resolution Training data Energy measurement Artificial neural networks

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A node-centric network congestion estimation method considering average spatiooral scale 2

A node-centric network congestion estimation method consider...

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2nd International Conference on Computer Information science and Application technology, CISAT 2019

作者： Wen, Guoyi Huang, Ning Zhu, Juxing School of Air Technical Sergeant Air Force Engineering University Xinyang Henan464000 China School of Reliability and Systems Engineering Beihang University Beijing100191 China Key Laboratory of Science and Technology on Reliability and Environmental Engineering Beihang University Beijing100191 China

Congestion estimation is a significant issue to analyse and mitigate network congestion. Many researchers have used various estimation methods based on the load data of roads in a single moment. However, congestion is always node-centric and formed around intersections gradually. An estimation method to describe the average congestion around intersections or nodes is also valuable and needed to discover the most congested parts but is absent according to our literature researches. In this paper, we propose a node-centric network congestion method, which can evaluate the average spatiooral congestion scale around nodes. Based on the widely used simulation platform NetLogo, the simulation results have proved the reasonability of the proposed estimation method by the stable values of the fixed traffic network intersections, which becomes increasingly stable as time goes on, and it is found that the node-centric values calculated by our estimation method is more stable than the values by the edge-centric because of its superiority. This node-centric network congestion estimation method considering average spatiooral scale will be widely used because of its simplicity and universality. © Published under licence by IOP Publishing Ltd.

关键词： Simulation platform

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Regional pollution source apportionment and emission thresholds determination in Zunyi's major watersheds: Implications for environmental management

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environmental Pollution 2025年 381卷 126640页

作者： Zhao, Keke Gan, Yujin Li, Chen Guan, Xiao Wang, Zhenbei Li, Fan Liu, Yatao Qi, Fei Zhu, Xingcheng Beijing Key Lab for Source Control Technology of Water Pollution College of Environmental Science and Engineering Beijing Forestry University Beijing100083 China Hebei Province Key Laboratory for Emerging Contaminant Remediation and Risk Prevention and Elimination Beijing Forestry University Hebei Xiong'an New Area072350 China State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental Sciences Beijing100012 China Zunyi Environmental Protection Monitoring Center Station Zunyi563000 China

Zunyi City, in the Yangtze River Economic Belt, faces significant pollution challenges in the Wujiang and Chishui watersheds. This study analyzed water quality changes from 2021 to 2023. To support current and future water environment management, pollutant emissions in 2022 were estimated, and major pollutants were traced during flood and non-flood seasons. Emission thresholds were established for districts and counties firstly, identifying key areas for pollution control. This research innovatively integrates urban non-point sources and forest soil erosion into emissions calculations and introduces pollution emissions threshold. Results indicate that agricultural non-point sources, particularly livestock farming and crop cultivation, are the dominant contributors to watershed pollution, while urban non-point sources play a comparatively minor role, for both two studied watersheds. Natural factors including drought and forest soil erosion also significantly influence pollution degree, particularly during flood seasons when increased erosion intensifies pollutant transport, which was especially pronounced for Chishui watershed. Methodologically, the Positive Matrix Factorization (PMF) model demonstrated greater accuracy and reliability than the Absolute Principal Component Scores-Multiple Linear Regression (APCS-MLR) model in apportioning complex pollution sources, for both two studied watersheds. Based on pollution emissions and source apportionment, regional emission thresholds for COD, NH3-N, TN, and TP were proposed. The results reveal that COD emissions in Xishui, Huichuan, Bozhou, and Chishui exceeded their respective thresholds, with TN and TP also surpassing limits in some areas. In summary, this study provides a scientific basis for targeted water quality management in Zunyi City and validates the PMF model as a reliable tool for source apportionment in complex watershed environments. © 2025 Elsevier Ltd

关键词： River pollution

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Distinguishing the main climatic drivers of terrestrial vegetation carbon dynamics in pan-Arctic ecosystems

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Ecological Informatics 2025年

作者： Chengfeng Meng Hao Zhou Xichuan Liu Jiao Zheng Jun Wang Qingwei Zeng Shuai Hu College of Meteorology and Oceanography National University of Defense Technology Changsha 410073 China Key Laboratory of High Impact Weather (Special) China Meteorological Administration (CMA) Changsha 410073 China Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science & Technology (NUIST) Nanjing 210044 China Frontiers Science Center for Critical Earth Material Cycling International Institute for Earth System Science Nanjing University Nanjing 210023 China

Pan-Arctic terrestrial ecosystems have experienced widespread greening over the past few decades due to climate warming. However, the dynamic variations and climatic causes of such greening in the pan-Arctic are still unclear due to limitations in high-latitude ground-based measurements. The study first evaluated the applicability of three satellite-based vegetation indices (VIs) for pan-Arctic carbon dynamics in previous decades compared with multisource observations. Three VIs presented significant increasing trends up to 0.0005–0.0017 yr −1 for pan-Arctic ecosystems in the past 23 years, and near-infrared reflectance of vegetation (NIRv) could better capture pan-Arctic terrestrial carbon dynamic variations (e.g., increasing trends) than other VIs among most vegetation types, such as grasslands. The separate contributions of climatic factors to satellite-based NIRv variability were further quantified using partial correlation and ridge regression analysis over pan-Arctic ecosystems from 2001 to 2023. Carbon dioxide (CO 2 ) and air temperature (AT) presented positive partial correlations with the satellite-based NIRv over entire pan-Arctic ecosystems, due to fertilization and warming effects. However, the vapor pressure deficit (VPD) showed positive (negative) partial correlations with NIRv variations in high (low) pan-Arctic ecosystems because of diverse stomatal responses to air dryness. Therefore, increases in VPD contributed 11.2 % of the pan-Arctic NIRv variability, although positive (negative) effects were detected for high (low) pan-Arctic ecosystems. These findings highlight the advantages of the NIRv for representing terrestrial carbon dynamics in fragile ecosystems (e.g., the pan-Arctic) and reveal the diverse effects of the regional climate (e.g., air dryness) on pan-Arctic ecosystems under climate warming.

关键词： Pan-Arctic Vegetation index Climate change CO 2 VPD

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Transient Fault Diagnosis Algorithm based on Feature Classification and Its Application in High-Power Laser facility

Transient Fault Diagnosis Algorithm based on Feature Classif...

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第32届中国控制与决策会议

作者： Qiang Ren Hang Gao Hailei Ren Baoran An Tianyou Yun Xiaoli Wang Institute of Computer Application China Academy of Engineering Physics State Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System College of Electronic Science and TechnologyNational University of Defense Technology Institute of Fluid Physics China Academy of Engineering Physis

High-power laser facility plays an import role both in scientific research and military application,and the occurred faults are usually *** this paper,a transient fault diagnosis algorithm based on feature classification is proposed,and the algorithm has been applied in the high-power laser *** method extracts the features of input data with an autoencoder *** based on the extracted features,a multi-layer full connection neural network is adopted for fault *** comparing the results with those obtained by traditional fault diagnosis methods,the performance of the algorithm has been verified.

关键词： High-power laser facility transient fault diagnosis feature-extraction

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Combining heat exchangers and metal foam and phase change materials for increased energy storage and heat generation using an exhaust heater: An experimental investigation

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Case Studies in Thermal engineering 2025年 72卷

作者： Qixian Zhang Xin Li Ali B.M. Ali Narinderjit Singh Sawaran Singh Arian Yazdekhasti M. Pirmoradian Riadh Marzouki Xi'an Institue of Applied Optics Xi'an Shaanxi 710065 PR China State Key Laboratory of Pulsed Power Laser Technology College of Electronic Engineering NationalUniversity of Defense Technology Hefei Anhui 230037 PR China Anhui Province Laboratory of Advanced Laser Technology College of Electronic Engineering NationalUniversity of Defense Technology Hefei Anhui 230037 PR China Nanhu Laser Laboratory National University of Defense Technology Changsha 410073 PR China Air Conditioning Engineering Department College of Engineering University of Warith Al-Anbiyaa Karbala Iraq Faculty of Data Science and Information Technology INTI International University Persiaran Perdana BBN Putra Nilai Nilai 71800 Malaysia Department of Mechanical Engineering Isfahan University of Technology Isfahan 84156-83111 Iran Department of Mechanical Engineering Khomeinishahr Branch Islamic Azad University Khomeinishahr Iran Department of Chemistry College of Science King Khalid University P.O. Box 9004 61413 Abha Saudi Arabia

The increase in performance of home heaters, accompanied by energy and environmental crises, becomes noticeable in the construction industry. Hence, this paper has investigated a solution to enhance the system's efficiency. For this purpose, a novel experimental set-up is provided to simulate the heater, exhaust heater, and indoor environment. This setup includes two boxes, a heat source controlled by a Proportional Integral Derivative (PID) controller and an aluminum box with copper tubes. The heat is transferred from the first box as a heater to the aluminum box as a heat exhaust by the air force of the fan to warm the second box. Also, Lauric acid as a phase change material (PCM) and metal foam are used to increase heat absorption and heat transfer inside the heater exhaust regarding the thermal and physical properties of these two materials. Seven temperature sensors are located in different places to evaluate and control the system. Moreover, 6 modes are designed to find the best arrangement of materials for improving the system. The results show that a new arrangement of materials defined as filling the aluminum box with PCM and covering this box with metal foam, acquires remarkable efficiency. According to the achieved data, the mentioned design can decrease the outlet temperature of exhaust up to 2.3 ± 0.1 °C as well as increase the second box temperature in a home environment to 1.6 ± 0.1 °C. Finally, this mode can improve the efficiencies of the system both in outlet temperature and indoor temperature of the second box as much as 4.73 ± 0.1 % in the former and 3.72 ± 0.1 % in the latter.

关键词： Phase change materials (PCMs) Metal foam Thermal management Heat exchanger Exhaust heater

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Advanced Analysis of Arabidopsis thaliana Leaf Traits Using RGB Imaging and Machine Learning

Advanced Analysis of Arabidopsis thaliana Leaf Traits Using ...

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International Symposium on Industrial Electronics (INDEL)

作者： Rijad Sarić Edhem Čustović Martin Trtílek Amila Akagić Mathew G. Lewsey James Whelan La Trobe Institute for Sustainable Agriculture & Food (LISAF) La Trobe University Melbourne VIC Australia Australian Research Council Research Hub for Medicinal Agriculture La Trobe University Melbourne VIC Australia School of Computing Engineering and Mathematical Sciences La Trobe University (LTU) Melbourne VIC Australia Scientific Instruments Australia (SIA) Melbourne VIC Australia Photon Systems Instruments (PSI) Plant Phenotyping Research Centre Drasov Brno Czech Republic Faculty of Electrical Engineering University of Sarajevo (UNSA) Sarajevo Bosnia and Herzegovina State Key Laboratory of Plant Environmental Resilience College of Life Science Zhejiang University (ZJU) P.R. China Provincial International Science and Technology Cooperation Base on Engineering Biology Zhejiang University P.R China

ISBN: (数字)9798350352320

ISBN: (纸本)9798350352337

Image-based high-throughput plant phenotyping utilises various imaging techniques to automatically and non-invasively understand the growth of different plant species. These innovative imaging infrastructures are implemented to monitor plant development over time in indoor or outdoor environments. However, understanding the relationship between genotype and phenotype interactions under different environments remains challenging. This research study demonstrates superior extraction of leaf morphological features of different Arabidopsis thaliana ecotypes by analysing leaf geometry using a sequence of RGB images. Upon successful extraction of anatomical features, leaf length and area are converted into physical coordinates. Furthermore, considering these leaf features as 1D signals, the Fourier Spectrum is analysed, and most descriptive features are selected using PCA. Finally, leaf shape classification is established by training and testing five distinct ML models. A thorough evaluation of selected models demonstrates superiority in classifying two common leaf shapes of Arabidopsis plants.

关键词： Training Shape Biological system modeling Imaging Machine learning Feature extraction Real-time systems reliability Testing Principal component analysis

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Advancements in understanding emission characteristics, data-driven olfactory-chemical measurements, and health impacts of the emerging odor pollution

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Environment International 2025年 201卷 109596页

作者： Xinyuan Xu Haixin Gu Zihao Zhang Yantong Liu Lingling Zhang Junfeng Wang Mindong Chen Yu Huang Junji Cao Shun-cheng Lee Haiwei Li Xinlei Ge Joint International Research Laboratory of Climate and Environment Change Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science and Technology Nanjing 210044 PR China Department of Environmental Engineering of Oulu School Nanjing Institute of Technology Nanjing 211167 PR China Jiangsu Academy of Environmental Industry and Technology Corp. Nanjing 210019 PR China State Key Laboratory of Loess and Quaternary Geology (SKLLQG) and Key Laboratory of Aerosol Chemistry and Physics Institute of Earth Environment Chinese Academy of Sciences Xi’an 710061 PR China Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 PR China Sustainable Energy and Environment Thrust The Hong Kong University of Science and Technology (Guangzhou) Guangzhou 511453 PR China School of Environment and Energy Engineering Anhui Jianzhu University Hefei 230601 PR China

Odor pollution presents a multi-scale challenge to global environmental governance, with significant gaps in measurement reliability, temporal mismatches between emission patterns and regulatory standards, and acknowledgment of the undervaluation of its associated health risks. Analytical data reveal that odor concentrations vary over three to four orders of magnitude across different emission sources. These discrepancies are exacerbated by inconsistencies in measurement protocols, which hinder the establishment of standardized regulatory benchmarks. At present, there are inherent uncertainties in human olfactory thresholds and variability in sensor responses. To address this, recent field studies in hybrid monitoring methodologies, integrating human sensory evaluation with instrumental analysis, have improved predictive accuracy by 30–50 %. Notably, municipal waste disposal facilities are identified as primary contributors to odor emissions, often exhibiting pronounced diurnal peaks. Monitoring data show that 65–80 % of landfills exceed permissible odor thresholds, correlating with odor complaints representing ‌∼30 % of urban environmental grievances‌. Health risk assessments further indicate that 15–25 % of industrial odor sources‌ emit carcinogenic compounds exceeding the acceptable risk threshold (e.g., a lifetime cancer risk of 1 × 10 −6 ), equating to at least one case per million exposed individuals. Despite this, fewer than 10 % of regulatory frameworks explicitly prioritize odor-related carcinogens, underscoring a critical disconnect between risk quantification and policy implementation. To address these gaps, this work advocates for the development of high-sensitivity sensor networks for real-time detection of trace-level odorants, establishment of health-based exposure limits for prioritized carcinogenic odorants, and implementation of predictive models to quantify the synergistic effects of odorant mixtures.

关键词： Odor pollution Emission profiles Chemical complexity Measurements Health risk assessment

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Application Prospect of Fission-Powered Spacecraft in Solar System Exploration Missions

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空间科学与技术（英文） 2022年第5期2022卷 89-103页

作者： Yan Xia Jian Li Ruiqiong Zhai Jing Wang Boying Lin Qin Zhou Beijing Institute of Spacecraft Environment Engineering BeijingChina Science and Technology on Reliability and Environmental Engineering Laboratory BeijingChina Beijing Institute of Spacecraft Environment Engineering BeijingChina Institute of Nuclear and New Energy Technology of Tsinghua University The Key Laboratory of Advanced Reactor Engineering and SafetyMinistry of EducationBeijingChina

Fission power is a promising technology,and it has been proposed for several future space *** is being considered for highpower missions whose goal is to explore the solar system and even *** fission power has made great progress when NASA's 1 kWe Kilowatt Reactor Using Stirling technology(KRUSTY)prototype completed a full power scale nuclear test in *** success stimulated a new round of research competition among the major space *** article reviews the development of the Kilopower reactor and the KRUSTY system *** summarizes the current missions that fission reactors are being considered as a power and/or propulsion *** projects include visiting Jupiter and Saturn systems,Chiron,and Kuiper belt object;Neptune exploration missions;and lunar and Mars surface base *** studies suggest that the Fission Electric Propulsion(FEP)/Fission Power System(FPS)is better than the Radioisotope Electric Propulsion(REP)/Radioisotope Power System(RPS)in the aspect of cost for missions with a power level that reaches～1 kWe,and when the power levels reaches～8 kWe,it has the advantage of lower *** a mission that travels further than～Saturn,REP with plutonium may not be cost acceptable,leaving FEP the only *** missions prefer the use of FPS because it satisfies the power level of 10's kWe,and FPS vastly widens the choice of possible landing *** to the current situation,we are expecting a flagship-level fission-powered space exploration mission in the next 1-2 decades.

关键词： application prospect system exploration fission-powered missions solar spacecraft

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Mitigation of cross-eye jamming using a dual-polarization array

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Journal of Systems engineering and Electronics 2018年第3期29卷 491-498页

作者： MA Jiazhi SHI Longfei XIAO Shunping WANG Xuesong State Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System National University of Defense Technology Changsha 410073China School of Science National University of Defense TechnologyChangsha 410073China

This paper presents an approach for mitigating the cross-eye jamming using a dual-polarization array. By transmitting a sum beam and a difference beam in two orthogonal polarimetric channels, a synthesized transmitted beam with spatially varying polarization is produced, such that the polarization of the transmitted radar wave varies in azimuth or elevation. Thus, the phases of the signals received on the two antennas of a cross-eye jammer become unequal, and an additional phase difference is introduced to disrupt the 180？ phase shifting in the retrodirective loop of the jammer. By means of beam scanning in a small angular range,the optimal beam steering configuration can be found to maximize the phase error for the mitigation of cross-eye jamming. As a result, the jamming performance of the cross-eye jammer degrades largely. Theoretical analysis and simulation results indicate that the proposed method is valid and feasible.

关键词： cross-eye jamming monopulse radar spatially varying polarization insertion phase beam scanning

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