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Spatial and Temporal Variations in the Atmospheric Age Distribution of Primary and Secondary Inorganic Aerosols in China

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engineering 2023年第9期28卷 117-129页

作者： Xiaodong Xie Qi Ying Hongliang Zhang Jianlin Hu Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologyNanjing University of Information Science&TechnologyNanjing 210044China Zachry Department of Civil Engineering Texas A&M UniversityCollege StationTX 77843USA Department of Environmental Science and Engineering Fudan UniversityShanghai 200438China

The aging timescale of particles is a key parameter in determining their impacts on air quality,human health,and *** this study,a one-year simulation of the age distributions of the primary and secondary inorganic fine particulate matter(PM_(2.5))components was conducted over China using an age-resolved Community Multiscale Air Quality(CMAQ)*** results indicate that primary PM_(2.5)(PPM)and ammonium mainly originate from fresh local emissions,with approximately 60%-80%concentrated in 0-24 h age bins in most of China throughout the *** average age is about15-25 h in most regions in summer,but increases to 40-50 h in southern region of China and the Sichuan Basin(SCB)in *** is more aged than PPM,indicating an enhanced contribution from regional *** sulfate with atmospheric age>48 h account for 30%-50%of total sulfate in most regions and seasons,and the concentrations in the>96 h age bin can reach up to 15μg·m-3 in SCB during *** seasonal variations occur in the Yangtze River Delta,Pearl River Delta,and SCB,with highest average age of 60-70 h in winter and lowest of 40-45 h in *** average age of nitrate is 20-30 h in summer and increases to 40-50 h in *** enhanced deposition rate of nitric acid vapor combined with the faster chemical reaction rate of nitrogen oxides leads to a lower atmospheric age in ***,on pollution days,the contributions of old age bins(>24 h)increase notably for both PPM and secondary inorganic aerosols in most cities and seasons,suggesting that regional transport plays a vital role during haze *** age information of PM_(2.5),provided by the age-resolved CMAQ model,can help policymakers design effective emergent emission control measures to eliminate severe haze episodes.

关键词： Atmospheric age PM_(2.5) CMAQ model control strategy

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A Method for Filtering Data-Driven Predictive control Aimed at Vehicle Lateral Stabilization in Compacted-Snow Rutted Road Conditions 8

A Method for Filtering Data-Driven Predictive Control Aimed ...

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8th CAA International Conference on Vehicular control and Intelligence, CVCI 2024

作者： Zhao, Xu Guo, Hongyan Shi, Wanqing College of Communication Engineering Jilin University Changchun China Jilin Institute of Chemical Technology Department of Aircraft Control and Information Engineering Changchun China College of Communication Engineering Jilin University State Key Laboratory of Automotive Simulation and Control Changchun China

ISBN: (纸本)9798331504892

Designing a data-driven predictive controller for lateral stability of vehicles on compacted-snow rutted roads, especially when the data is subjected to non-stationary noise disturbances, is a significant challenge. This paper introduces a novel subspace predictive equation construction method that incorporates filtering using the inverse of a first-order disturbance model. Based on this, a filtering data-driven predictive controller is designed. The proposed method is tested through numerical simulations and MATLAB/CarSim co-simulation. Simulation results show that the proposed subspace predictive equation with filtering effectively mitigates the variance and bias introduced by non-stationary noise. The co-simulation results demonstrate that the controller ensures the stability and robustness of the vehicle system. © 2024 IEEE.

关键词： Predictive control systems

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Large language models for human–robot interaction:A review

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Biomimetic Intelligence & Robotics 2023年第4期3卷 1-15页

作者： Ceng Zhang Junxin Chen Jiatong Li Yanhong Peng Zebing Mao Department of Mechanical Engineering National University of SingaporeSingapore 119077Singapore School of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China Department of Information and Communication Engineering Graduate School of EngineeringNagoya UniversityNagoya 464-8603Japan Department of Mechanical Engineering Tokyo Institute of TechnologyTokyo 152-8550Japan

The fusion of large language models and robotic systems has introduced a transformative paradigm in human–robot interaction,offering unparalleled capabilities in natural language understanding and task *** review paper offers a comprehensive analysis of this nascent but rapidly evolving domain,spotlighting the recent advances of Large Language Models(LLMs)in enhancing their structures and performances,particularly in terms of multimodal input handling,high-level reasoning,and plan ***,it probes the current methodologies that integrate LLMs into robotic systems for complex task completion,from traditional probabilistic models to the utilization of value functions and metrics for optimal *** these advancements,the paper also reveals the formidable challenges that confront the field,such as contextual understanding,data privacy and ethical *** our best knowledge,this is the first study to comprehensively analyze the advances and considerations of LLMs in Human–Robot Interaction(HRI)based on recent progress,which provides potential avenues for further research.

关键词： Large language models Human-robot interaction Task completion Considerations and challenges

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Multi-functional metasurface:ultra-wideband/multi-band absorption switching by adjusting guided-mode resonance and local surface plasmon resonance effects

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Communications in Theoretical Physics 2024年第6期76卷 174-184页

作者： Wenxin Li Shubo Cheng Huafeng Zhang Zao Yi Bin Tang Can Ma Pinghui Wu Qingdong Zeng Rizwan Raza School of Physics and Optoelectronic Engineering Yangtze UniversityJingzhouHubei 434023China Joint Laboratory for Extreme Conditions Matter Properties Southwest University of Science and TechnologyMianyang 621010China School of Chemistry and Chemical Engineering Jishou UniversityJishou 416000China School of Microelectronics and Control Engineering Changzhou UniversityChangzhou 213164China Department of Oncology Sichuan Science City HospitalMianyangSichuan Province 621000China Office of Science and Technology Quanzhou Normal UniversityQuanzhou 362000China School of Physics and Electronic-information Engineering Hubei Engineering UniversityXiaogan 432000China Department of Physics COMSATS Institute of Information Technology 54000 LahorePakistan

This study introduces an innovative dual-tunable absorption film with the capability to switch between ultra-wideband and narrowband *** manipulating the temperature,the film can achieve multi-band absorption within the 30-45 THz range or ultra-wideband absorption spanning 30-130 THz,with an absorption rate exceeding ***,the structural parameters of the absorption film are optimized using the particle swarm optimization(PSO)algorithm to ensure the optimal absorption *** absorption response of the film is primarily attributed to the coupling of guided-mode resonance and local surface plasmon resonance *** film's symmetric structure enables polarization incoherence and allows for tuning through various means such as doping/voltage,temperature and structural *** the case of a multi-band absorption response,the film exhibits good sensitivity to refractive index changes in multiple absorption ***,the absorption spectrum of the film remains effective even at large incidence angles,making it highly promising for applications in fields such as biosensing and infrared stealth.

关键词： PSO optimization ultra-wideband/narrowband absorption switching intelligent absorption film vanadium dioxide

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Design of High Sensitivity Split Ring Resonator Sensor for Invasive Blood Glucose Monitoring

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IFAC-PapersOnLine 2024年第24期58卷 303-308页

作者： Ameer B. Alsultani Omer S. Alkhafaf Ákos Szlávecz J. Geoffrey Chase Balázs Benyó Budapest University of Technology and Economics Faculty of Electrical Engineering and Information Technology Department of Control Engineering and Information Technology Budapest Hungary Department of Mechanical Engineering University of Canterbury Christchurch New Zealand Department of Communications Engineering University of Technology Iraq

Blood glucose level is one of the most frequently measured physiological parameters in clinical and home-care settings. This study aimed to develop a novel biosensor using a Split Ring Resonator (SRR) for measuring the glucose concentration of solutions like blood. In the simulation, changes in the solution's dielectric properties yielded a significant shift of the original, 6.8 GHz, resonance frequency when the SRR, constructed on a Rogers RO4003 substrate, was exposed to solutions with varying glucose concentrations. The frequency shift can indicate the solution's glucose levels, enabling the sensor to detect concentrations ranging from 20 mg/dL up to 200 mg/dL. The proposed method shows promise for invasive blood glucose monitoring with a sensitivity of 4.4 MHz per mg/dL and a straightforward structure design.

关键词： Biomedical sensors Blood Glucose Monitoring Microwave technology Split Ring Resonator

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Judgment of blast furnace iron-tapping status based on data differential processing and dynamic window analysis algorithm

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Progress in Natural Science:Materials International 2023年第4期33卷 450-457页

作者： Youcheng Zong Zixian Wang Xiang Liu Yi Nian Jianian Pan Chaojie Zhang Yingxue Wang Jianhua Chu Liqiang Zhang The Intelligent Metallurgy Research Institute School of Metallurgical Engineering Anhui University of Technology Department of Technical Quality Manufacturing Management Division(Technical Center) Anhui Changjiang Steel Co. Ltd. National Engineering Research Center for Public Safety Risk Perception and Control by Big Data(RPP) China Academic of Electronics and Information Technology

Ironmaking plants hold a core position in steel production. Efficient level detection and iron-tapping status judgment can accurately measure the liquid level and predict the amount of molten iron in the ladle, thereby ensuring production safety and improving production efficiency. At present, the judgment of the start and end statuses of blast furnace iron-tapping mainly relies on manual visual inspection. However, due to the high-temperature environment on-site and interference from iron powder, gunning mud, and other dust, operators find it challenging to make accurate judgments. To address these issues, this study proposes a robust and accurate method for judging the iron-tapping status of blast furnaces. This study collected four million on-site liquid level data, underwent interpolation, noise reduction, normalization, and other preprocessing steps, and then used differential processing to calculate the iron-tapping rate. Combined with dynamic window feature analysis, it effectively captured the change characteristics of the liquid level in the ladle under different iron-tapping *** simulated on-site experiments, the method achieved a 96.6 % accuracy rate for iron-tapping status *** real-time iron-tapping status judgment method based on differential processing of liquid level data and dynamic window feature analysis proposed in this study demonstrates high precision and robustness in the complex environment of ironmaking plants. This technology not only improves the production efficiency of the iron and steel link but also frees on-site operators from the harsh working environment, eliminating human errors in judgments and omissions, further promoting the intelligent process of ironmaking plants.

关键词： Blast furnace iron-tapping Molten iron level Radar level gauge Iron-tapping status judgment Data differential processing Sliding window

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Personalized Federated Learning with Kolmogorov-Arnold Enhanced CNN for Rotating Equipment Fault Diagnosis 21

Personalized Federated Learning with Kolmogorov-Arnold Enhan...

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21st International Computer Conference on Wavelet Active Media technology and information Processing, ICCWAMTIP 2024

作者： Kulevome, Delanyo Kwame Bensah Man, Qiu Mawuli, Ernest Smith Opoku-Mensah, Edward Qilu Institute of Technology Department of Computer and Information Engineering Shandong Jinan250200 China Qilu Institute of Technology Department of Intelligent Manufacturing and Control Engineering Shandong Jinan250200 China Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development Department of Electrical/Electronic Technology Education Kumasi Ghana HEC Department of Information Technologies Montréal Canada

ISBN: (纸本)9798331519254

Fault diagnosis of rotating equipment plays a crucial role in ensuring operational reliability and minimizing downtime in industrial systems. This study proposes a novel approach that integrates personalized federated learning (PFL) with a Kolmogorov-Arnold network (KAN)-enhanced convolutional neural network (CNN) to improve diagnostic accuracy across heterogeneous operational environments. The framework is designed to address variations in equipment conditions and data distributions, providing personalized models tailored to specific clients. A comprehensive evaluation is conducted using benchmark datasets, demonstrating significant improvements in fault classification accuracy, model interpretability, and training efficiency under non-IID data settings using the KAN-enhanced CNN model. This study contributes to advancing predictive maintenance practices, paving the way for resilient and intelligent industrial systems. © 2024 IEEE.

关键词： Federated learning

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A Novel Cutting Fluids Performance Assurance System for CNC Machine Tools

A Novel Cutting Fluids Performance Assurance System for CNC ...

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2024 International Automatic control Conference, CACS 2024

作者： Chou, You-Syuan Chen, Yi-Shiang Chiang, Fu-Yu Yang, Chen-Yen Shi, Zhe-Xun Lin, Yu-Sheng Lin, Shang-Chih Su, Shun-Feng Huang, Yennun Feng Chia University Institute of Automatic Control Engineering Taichung407 Taiwan Feng Chia University Department of Automatic Control Engineering Taichung407 Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei106 Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei115 Taiwan

ISBN: (纸本)9798350354904

In the CNC machine tool industry, cutting fluid is a crucial component of the machining process. Nevertheless, as the duration of cutting fluid use increases, its performance progressively deteriorates, presenting a significant challenge that necessitates resolution. This study introduces an innovative intelligent monitoring system designed to optimize the preparation of cutting fluid in CNC machine tools. The aim is to extend the fluid's service life, mitigate tool wear, and address issues arising from fluid degradation. The system integrates a heating plate, sensors, pumping motors, and embedded systems to monitor and manage the cutting fluid effectively. Testing was conducted using a customdesigned container, and data analysis identified the optimal supply strategy, thereby extending the usable lifespan of the cutting fluid. This system enhances production longevity and allows for the configuration of containers with appropriate capacities based on specific requirements, ensuring consistent and high-quality production. © 2024 IEEE.

关键词： Cutting fluids

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Developing modified k–εturbulence models for neutral atmospheric boundary layer flow simulation using OpenFOAM

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Building Simulation 2024年第12期17卷 2281-2295页

作者： Yuanbo Wang Jiqin Li Wei Liu Jiankai Dong Jing Liu School of Architecture Harbin Institute of TechnologyKey Laboratory of Cold Region Urban and Rural Human Settlement Environment Science and TechnologyMinistry of Industry and Information TechnologyHarbin 150090China Tianjin Key Laboratory of Indoor Air Environmental Quality Control School of Environmental Science and EngineeringTianjin University92 Weijin RoadTianjin 300072China Division of Sustainable Buildings Department of Civil and Architectural EngineeringKTH Royal Institute of TechnologyBrinellvägen 2310044 StockholmSweden

Accurate turbulence modeling is essential for simulation studies of urban *** this study,the comprehensive atmospheric boundary layer(ABL)model involving a variable model coefficient and an additional turbulent dissipation source term was implemented using the open-source software *** with consistent inlet wind profiles and rough wall functions of different turbulence variables based on the aerodynamic roughness,the model maintained the horizontal homogeneity ***,a hybrid approach was introduced to consider buildings immersed in ABL flows,enabling automatic transformation of the turbulence model between the region around the buildings and the free flow region away from any ***,the effects of applying different model forms to the airflow field around buildings were evaluated in detail through three-dimensional building cases representing six urban prototypes based on three wind tunnel *** findings indicated that all modified k–εmodels perform well in reproducing the flow data of the CEDVAL and Architectural Institute of Japan(AIJ)experiments consisting of a single building,an array of buildings,and an isolated high-rise ***,the modified k–εmodel with an additional correction term performed poorly in the database of Niigata Institute of technology and the case of complex terrain and urban building configurations,because the correction term inhibited the generation of turbulent kinetic *** addition,from the comparison between the experimental data of all cases,the model with the original formulation of the coefficient performed the best in terms of prediction *** root mean square errors of the normalized velocity were 0.1250,0.0879,0.1145,0.1350,and 0.1492 in different cases,which proved the reliability of this turbulence model.

关键词： urban airflow computational fluid dynamics(CFD) atmospheric boundary layer OpenFOAM turbulence model

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Feature Enhancement Method for Multimodal Nighttime Pedestrian Detection 7

Feature Enhancement Method for Multimodal Nighttime Pedestri...

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7th International Conference on Electrical, Mechanical and Computer engineering, ICEMCE 2023

作者： Wang, Yonggui Zhu, Zhongpan Li, Jian Wang, Zhipeng Chang, Qi He, Bin School of Electronic Information and Artificial Intelligence Shanxi University of Science & Technology Xi'an China College of Electronics and Information Engineering Tongji University Department of Control Science and Engineering Shanghai China

ISBN: (纸本)9798350382877

Nighttime Pedestrian Detection in Low-Light Conditions poses a challenging task, as previous processing methods often introduced noise and limited model generalization due to the low image quality in low-light conditions. This study presents a feature enhancement algorithm tailored for multimodal nighttime pedestrian detection, harnessing the advantages of infrared and visible light data. Our approach utilizes an adaptive weight fusion algorithm and a spatial detail module for multimodal fusion and spatial detail feature extraction, respectively, to accomplish the nighttime pedestrian detection task. Experimental results demonstrate that our method, compared to the baseline algorithm, achieves performance improvements of 3.3%, 11.9%, and 4.5% on the LLVIP dataset. © 2023 IEEE.

关键词： Feature extraction

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