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algorithm for improving the sizing accuracy in real-time bioaerosol single particle mass spectrometer

JOURNAL OF AEROSOL SCIENCE 2025年 184卷

作者： Li, Shaoyong Tang, Lingjun Li, Jingzhen Su, Zhanming Huang, Zhengxu Li, Mei Gao, Wei Li, Xue Zhang, Guohua Li, Lei Jinan Univ Inst Mass Spectrometry & Atmospher Environm Coll Environm & Climate Guangzhou 510632 Peoples R China Jinan Univ Inst Mass Spectrometry & Atmospher Environm Coll Environm & Climate Guangdong Prov Engn Res Ctr Online Source Apportio Guangzhou 510632 Peoples R China Guangdong MS Inst Sci Instrument Innovat Guangzhou 510530 Peoples R China Chinese Acad Sci Guangzhou Inst Geochem State Key Lab Organ Geochem Guangzhou 510640 Peoples R China Chinese Acad Sci Guangzhou Inst Geochem Guangdong Key Lab Environm Protect & Resources Uti Guangzhou 510640 Peoples R China

The newly developed bioaerosol single particle mass spectrometer (Bio-SPAMS) has been innovatively designed for its optical sizing system. The first laser beam in the previous single particle mass spectrometer was split into near distance double beams, similar to the design of APS (Aerodynamic Particle Sizer) and SBS-LIBS (Single Beam Splitting-Laser Induced Breakdown Spectroscopy). All the particles focused by the aerodynamic lens can be sized and got number concentration statistic. However, due to the imperfect beam quality and the large scattering intensity of the large-sized particles, there may be some noise in the scattered signals, particle diameter measured by this sizing system was often larger than actual value if the same trigger threshold was set. In this study, when measuring PSL microspheres with diameters of 1.9, 3.1, and 4.9 mu m, the identification rates of the fixed threshold algorithm were only 75.25%, 55.26%, and 0.27%, respectively. To address such issue, we developed a dynamic threshold waveform recognition algorithm based on field programmable gate array (FPGA), which could process the photoelectric signals collected by a photomultiplier tube (PMT) in real time. The algorithm can dynamically adjust the trigger threshold of the collected scattered signals and accurately calculate the interval time between the near distance double beam. For PSL microspheres with diameters of 1.9, 3.1, and 4.9 mu m, the accuracy of the dynamic threshold algorithm increased by 19.09%, 25.72%, and 88.20%, respectively. This algorithm effectively solves the problem of particle sizing deviation, and improves the particle size measurement accuracy of the bioaerosol mass spectrometer in a wide particle size range from 0.3-6 mu m.

关键词： Bioaerosol single particle mass spectrometer (bio-SPAMS) Particle size measurement algorithm Field programmable gate array (FPGA)

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algorithm for the chemical ingredient being known to identify their class of archaic glassworks

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JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2025年

作者： Liu, Wenbin Liu, Dongbing Wuhan Technol & Business Univ Wuhan Peoples R China Wuchang Inst Technol Wuhan Peoples R China Panzhihua Univ Coll Math & Comp Panzhihua 617000 Peoples R China

In the paper, the chemical ingredient of potash glasswork and baryta glasswork is known from the archaic Chinese glassworks. The class, ornamentation and pigment of glasswork are known both without and with rotting. The chemical ingredient percentage before rotting is predicted. Thus, the chemical ingredient is subclassified. The relativity of the chemical ingredient between the different classes of glasswork is found.

关键词： archaic glasswork the chemical ingredient analysis the chemical ingredient identification algorithm

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algorithm development for the automation of death certificate analysis and coding

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ANNALS OF EPIDEMIOLOGY 2025年 104卷 15-20页

作者： Mccord, Kaylee Gause, Emma L. Mclone, Suzanne Bard, Hannah Gilson, Thomas Jay, Jonathan Boston Univ Chobanian & Avedisian Sch Med 72 E Concord St Boston MA 02118 USA Boston Univ Sch Publ Hlth 715 Albany St Boston MA 02118 USA Univ Washington Sch Med Dept Pediat Firearm Injury & Policy Res Program 1959 NE Pacific St Seattle WA 98195 USA Off Cuyahoga Cty Med Examiner 11001 Cedar Ave Cleveland OH 44106 USA

Purpose: We developed an open-source, rule-based algorithm to automate cause of death coding for analyzing mortality in understudied populations, such as people experiencing homelessness, and dynamic public health crises including overdoses and climate-related deaths. Methods: Death categories of immediate public health concern were selected and keyword lists representing each category were developed in consultation with a domain expert. A rule-based keyword matching algorithm was built to assign death records into the selected death categories. The algorithm was trained on death certificate data from five counties across the United States. A case study applying the algorithm to deaths among people experiencing homelessness in Clark County, NV from 2015 to 2018 (N = 646) tested the accuracy of the program against a manual coder. Results: There was strong agreement between the algorithm and the manual coder in the all-cause identification (kappa 0.905) and mutually exclusive sorting (kappa 0.853) methods. Our findings illustrate the algorithm's ability to accurately classify death certificates into useful categories. Conclusion: This open-source, customizable algorithm may be utilized by researchers, journalists, and others to conduct mortality analyses with publicly available death certificate data, bridging gaps in existing mortality tracking efforts.

关键词： Mortality Death Certificate Cause of Death algorithm Overdose

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Insulator defect detection under extreme weather based on synthetic weather algorithm and improved YOLOv7

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High Voltage 2025年第1期10卷 69-77页

作者： Yong Yang Shuai Yang Chuan Li Yunxuan Wang Xiaoqian Pi Yuxin Lu Ruohan Wu State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical Engineering and ElectronicsHuazhong University of Science and TechnologyWuhanChina State Grid Hunan Electric Power Company ChangshaChina

Efficient and accurate insulator defect detection is essential for maintaining the safe and stable operation of transmission ***,the detection effectiveness is adversely impacted by complex and changeable environmental backgrounds,particularly under extreme weather that elevates accident ***,this research proposes a high-precision intelligent strategy based on the synthetic weather algorithm and improved YOLOv7 for detecting insulator defects under extreme *** proposed meth-odology involves augmenting the dataset with synthetic rain,snow,and fog algorithm ***,the original dataset undergoes augmentation through affine and colour transformations to improve model's generalisation performance under complex power inspection *** achieve higher recognition accuracy in severe weather,an improved YOLOv7 algorithm for insulator defect detection is proposed,integrating focal loss with SIoU loss function and incorporating an optimised decoupled head *** results indicate that the synthetic weather algorithm processing significantly improves the insulator defect detection accuracy under extreme weather,increasing the mean average precision by 2.4%.Furthermore,the authors’improved YOLOv7 model achieves 91.8%for the mean average precision,outperforming the benchmark model by 2.3%.With a detection speed of 46.5 frames per second,the model meets the requirement of real-time detection of insulators and their defects during power inspection.

关键词： weather extreme algorithm

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Wave effect of gravitational waves intersected with a microlens field II:An adaptive hierarchical tree algorithm and population study

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Science China(Physics,Mechanics & Astronomy) 2025年第1期68卷 237-250页

作者： Xikai Shan Guoliang Li Xuechun Chen Wen Zhao Bin Hu Shude Mao Purple Mountain Observatory Chinese Academy of SciencesNanjing 210023China Department of Astronomy Tsinghua UniversityBeijing 100084China Institute for Frontier in Astronomy and Astrophysics Beijing Normal UniversityBeijing 102206China School of Physics and Astronomy Beijing Normal UniversityBeijing 100875China School of Astronomy and Space Science University of Science and Technology of ChinaHefei 230026China CAS Key Laboratory for Researches in Galaxies and Cosmology Department of AstronomyUniversity of Science and Technology of ChinaChinese Academy of SciencesHefei 230026China

The gravitational lensing wave effect generated by a microlensing field embedded in a lens galaxy is an inevitable phenomenon in strong lensed gravitational waves(SLGWs).This effect presents both challenges and opportunities for the detection and appli-cation of ***,investigating this wave effect requires computing a complete diffraction integral over each microlens in the *** is extremely time-consuming due to the large number of microlenses(10^(3)-10^(6)).Therefore,simply adding all the microlenses is ***,the complexity of the time delay surface makes the lens plane resolution a crucial factor in controlling numerical *** this paper,we propose a trapezoid approximation-based adaptive hierarchical tree algo-rithm to meet the challenges of calculation speed and *** find that this algorithm accelerates the calculation by four orders of magnitude compared to the simple adding method and is one order of magnitude faster than the fixed hierarchical tree algorithm proposed for electromagnetic *** importantly,our algorithm ensures controllable numerical errors,increasing confidence in the *** with our previous work(***.66,239511,2023),this paper addresses all numerical issues,including integral convergence,precision,and computational time1).Finally,we conducted a population study on the microlensing wave effect of SLGWs using this algorithm and found that the microlensing wave effect cannot be ignored,especially for Type II SLGWs(from saddle position of the time delay surface)due to their intrinsic geometric structures and their typical intersection with a denser microlensing ***,more than 33%(11%)of SLGWs have a mismatch larger than 1%(3%)compared to the unlensed ***,we found that the mismatch between signal pairs in a doubly imaged GW is generally larger than 10^(−3),and 61%(25%)of signal pairs have a mismatch larger than 1%(3%).Theref

关键词： gravitational lensing diffractional integral algorithm gravitational wave

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An improved meta-heuristic algorithm for energy optimization in smart grids considering photovoltaic, storage battery, and demand response

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JOURNAL OF ENERGY STORAGE 2025年 119卷

作者： Hafeez, Ghulam Ullah, Safeer Islam, Mazhar Khan, Farrukh Aslam Alsafran, Ahmed S. Alghamdi, Baheej Kraiem, Habib Univ Engn & Technol Dept Elect Engn Mardan 23200 Pakistan Quaid E Azam Coll Engn & Technol Dept Elect Engn Sahiwal 57000 Pakistan Shenzhen Univ China Coll Elect & Informat Engn Shenzhen 518060 Guangdong Peoples R China King Saud Univ Ctr Excellence Informat Assurance Riyadh 11653 Saudi Arabia Univ Tenaga Nas Coll Comp & Informat Kajang 43000 Selangor Malaysia King Faisal Univ Coll Engn Dept Elect Engn Al Hasa Saudi Arabia King Abdulaziz Univ Ctr Res Excellence Renewable Energy & Power Syst Smart Grids Res Grp Jeddah 21589 Saudi Arabia King Abdulaziz Univ Fac Engn Dept Elect & Comp Engn Jeddah 21589 Saudi Arabia Northern Border Univ Ctr Sci Res & Entrepreneurship Ar Ar 73213 Saudi Arabia

Residential load scheduling in smart power grids (SPGs), especially those incorporating renewable energy sources (RESs), storage battery, and demand response (DR) faces significant challenges due to the limitations of traditional optimization algorithms. These challenges include premature convergence, high computational costs, imbalanced exploration and exploitation, lack of adaptability, and sensitivity to parameters. Such issues make it difficult to effectively manage energy consumption, alleviate peak loads, and reduce energy costs while maintaining user comfort. To address these challenges, we propose an improved particle swarm optimization (IPSO) algorithm that enhances exploration and exploitation balance through inertia weight adjustment, velocity damping, and the inclusion of crossover and mutation strategies. These enhancements prevent premature convergence and allow for faster, more accurate convergence to optimal solutions. The proposed IPSO is integrated into a power usage scheduler (PUS) for optimal residential load scheduling under an adaptive pricing scheme considering photovoltaic (PV) and storage battery, focusing on reducing peak energy usage, rebound peaks, energy costs, and user discomfort. The effectiveness of the IPSO-based PUS is demonstrated through a comparison with other optimization algorithms such as genetic optimization algorithm (GOA), particle swarm optimization (PSO), and wind-driven optimization (WDO). Results show that the IPSO algorithm consistently outperforms these alternatives in terms of energy consumption, peak energy alleviation, cost reduction, and grid stability, while also achieving faster execution times and superior convergence rates. This work provides a robust solution for residential load scheduling, offering significant insights and practical benefits for energy optimization in SPGs.

关键词： Demand response Distributed generation Energy storage Power usage scheduling Improved particle swarm optimization algorithm Storage battery Smart power grid

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A discrete water source cycle algorithm design for solving production scheduling problem in flexible manufacturing systems

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SWARM AND EVOLUTIONARY COMPUTATION 2025年 94卷

作者： Xu, Wenxiang Xu, Shimin Liang, Junyong Qin, Tao Liu, Dezheng Wang, Lei Hubei Univ Arts & Sci Hubei Longzhong Lab Xiangyang 441000 Peoples R China Sichuan Univ Sci & Engn Sch Civil Engn Zigong 643000 Peoples R China Wuhan Univ Technol Sch Mech & Elect Engn Wuhan 430070 Peoples R China

Aiming at solving the production scheduling problems in flexible manufacturing systems including the flexible job shop scheduling (FJSP) and distributed flexible job shop scheduling (DFJSP) with operation outsourcing, which are two kinds of typical NP-hard problems, the general mathematical model with two optimization objectives including minimizing the total costs as well as makespan are developed. Then, an innovative discrete water source cycle algorithm (IDWCA) inspired by the water cycle process is proposed to address the model. In the IDWCA, the operators including evaporation mixing, precipitation, local mixing, modification of water source composition and water source loss are designed to search for optimization solutions. Finally, 15 FJSP comparison experiments and 45 DFJSP comparison experiments with different scales are provided to verify the comprehensive performance of the IDWCA, in which the IDWCA, the original water cycle algorithm (OWCA), and the two general meta-heuristic algorithms genetic algorithm (GA) and particle swarm optimization (PSO) are involved. Compared with OWCA, GA and PSO, IDWCA performs significantly better in all FJSP experiments, while it performs better in 43 out of 45 DFJSP experiments, and its advantages are more significant in solving the medium-scale and large-scale problems. In addition, the evolutionary curves of the above algorithms indicate that the IDWCA has the better convergence speed and results than that of OWCA, GA and PSO. Therefore, the developed mathematical model and IDWCA are effective in solving the studied FJSP and DFJSP, the proposed algorithm enriches the theoretical researches on meta-heuristic algorithms and production scheduling.

关键词： Flexible job shop scheduling Distributed flexible job shop scheduling Operation outsourcing Innovative discrete water source cycle algorithm Multi-objective optimization

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Emergency evacuation risk assessment for toxic gas attacks in airport terminals: Model, algorithm, and application

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2025年 253卷

作者： Luan, Tianyi Gai, Wenmei Sun, Diange Dong, Hao China Univ Geosci Beijing Sch Engn & Technol Beijing 100083 Peoples R China China Univ Ind Relat Inst Safety Engn Beijing 100048 Peoples R China

Transportation infrastructure has often been the target of terrorist attacks, and mitigation of the risk of toxic gas attacks is a challenging task in the design of indoor emergency evacuation systems. Considering multiple emergency response modes, we propose an agent-based risk assessment model and its algorithm to integrate gas diffusion and pedestrian movement data for emergency response, quickly assessing average individual exposure risk. We assessed the exposure status of individuals with respect to their emergency response actions following a toxic gas attack in an airport terminal. The results indicate that in the event of a general gas attack on an airport terminal, ventilation must be immediately ceased along with early evacuation. In areas with a shelter-in-place environment, the ventilation mode and shelter-in-place time should be determined based on the concentration of indoor and outdoor gases. In areas with nerve gas exposure and high population density, a new exit must be established at evacuation bottlenecks, and pedestrians must be guided to evacuate while promptly closing ventilation. These results offer suggestions and strategies for emergency response and decision-making in airport terminals during such incidents.

关键词： Emergency management Individual response Airport terminal Toxic gas attack Risk assessment algorithm

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A new intelligent prediction model using machine learning linked to grey wolf optimizer algorithm for O2/N2 adsorption

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CANADIAN JOURNAL OF CHEMICAL ENGINEERING 2025年第3期103卷 1229-1245页

作者： Mashhadimoslem, Hossein Kermani, Vahid Zanganeh, Kourosh Shafeen, Ahmed Elkamel, Ali Univ Waterloo Chem Engn Dept Waterloo ON N2L 3G1 Canada Nat Resources Canada NRCan CanmetENERGY Ottawa CE O Ottawa ON Canada Khalifa Univ Dept Chem Engn Abu Dhabi U Arab Emirates

To address the deficiency and predict the adsorption performance in different adsorbents, this study proposes a new optimizer linked to the machine learning (ML) model considering the performance of the adsorption process. The main goal is to predict adsorption under different process conditions with different adsorbents and provide a unified framework, leading to the prediction of adsorption phenomena instead of traditional isotherm models. This research focuses on predicting the adsorbed amount of O2 and N2 on several carbon-based adsorbents using the ML approach linked to the grey wolf optimizer algorithm (GWO). Experimental isotherm data (dataset 1344) on adsorbent type, temperature, pressure, gas type, and adsorption capacity of the process adsorption were used as input and output datasets. The best algorithm was Broyden-Fletcher-Goldfarb-Shanno (BFGS), a two-layer network from a multi-layer perceptron (MLP) method applying 28 neurons. The new MLP-GWO network would have the best mean square error (MSE) efficiencies of 0.00037, while the R2 (r-squared) was 0.9934. The new ML-generated model can accurately predict the adsorption process behaviour of different carbon-based adsorbents under various process conditions. The results of this research have the potential to assist a wide range of gas separation industries.

关键词： adsorption algorithm gas separation grey wolf optimizer MLP

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The Application of the Convective-Stratiform Classification algorithm for Feature Detection in Polarimetric Radar Variables and QPE Retrieval During Warm-Season Convection

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REMOTE SENSING 2025年第7期17卷 1176-1176页

作者： Mikidadi, Ndabagenga Daudi Huang, Xingyou Bu, Lingbing Nanjing Univ Informat Sci & Technol Sch Atmospher Phys Nanjing 210044 Peoples R China Tanzania Meteorol Author Forecasting Off Kilimanjaro Int Airport Hai POB 03 Kilimanjaro Tanzania

Feature detection is one of the hot topics in the weather radar research community. This study employed a convective-stratiform classification algorithm to detect features in polarimetric radar variables and Quantitative Precipitation Estimation (QPE) retrieval during a heavy precipitation event in Crossville, Tennessee, during warm-season convection. Analysis of polarimetric radar variables revealed that strong updrafts, mixed-phase precipitation, and large hailstones in the radar resolution volume during the event were driven by the existence of supercell thunderstorms. The results of feature detection highlight that the regions with convective-stratiform cores and strong-faint features in the reflectivity field are similar to those in the rainfall field, demonstrating how the algorithm more effectively detects features in both fields. The results of the estimates, accounting for uncertainty during feature detection, indicate that an offset of +2 dB overestimated convective features in the northeast in both the reflectivity and rainfall fields, while an offset of -2 dB underestimated convective features in the northwest part of both fields. The results highlight that convective cores cover a small area with high rainfall exceeding 50 mmh-1, while stratiform cores cover a larger area with greater horizontal homogeneity and lower rainfall intensity. These findings are significant for nowcasting weather, numerical models, hydrological applications, and enhancing climatological computations.

关键词： weather radar feature detection polarimetric variables QPE algorithm

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