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Quantifying the contribution of activity patterns to PM_(2.5)exposure inequity between urban and rural residents by a novel method

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Building Simulation 2024年第8期17卷 1323-1333页

作者： Wei Du Zhanpeng Cui Jinze Wang Yuqiong Wang Yungui Li Xiaoan Li Yan Zhou Tao Jiang Kang Mao Xianbiao Lin Jianwu Shi Dengzhou Gao Yiming Qin Yunnan Provincial Key Laboratory of Soil Carbon Sequestration and Pollution Control Faculty of Environmental Science&EngineeringKunming University of Science&TechnologyKunming 650500China Laboratory of Earth Surface Processes College of Urban and Environmental SciencesPeking UniversityBeijing 100871China Department of Environmental Engineering Southwest University of Science and TechnologyMianyang 621010China NHC Key Laboratory of Nuclear Technology Medical Transformation Mianyang Central HospitalSchool of MedicineUniversity of Electronic Science and Technology of ChinaMianyang 621000China State Key Laboratory of Environmental Geochemistry Institute of GeochemistryChinese Academy of SciencesGuiyang 550081China Key Laboratory of Marine Chemistry Theory and Technology Ministry of EducationOcean University of ChinaQingdao266100China Key Laboratory for Humid Subtropical Eco-Geographical Processes of the Ministry of Education School of Geographical SciencesFujian NormalUniversityFuzhou350117China School of Energy and Environment City University of Hong KongHong KongChina

PM_(2.5)pollution variations in different microenvironments would result in PM_(2.5)exposure inequity between rural and urban *** this study,the real-time PM_(2.5)exposure of urban and rural residents in china was examined based on portable PM_(2.5)sensors together with activity patterns derived from questionnaire surveys,with a focus on students and senior citizens who are sensitive to air *** results showed that PM_(2.5)exposure varied significantly among different resident groups,with higher PM_(2.5)exposure of rural residents than those of urban ***_(2.5)exposure peaks mostly occurred during(Accompanied)cooking activities owing to strong *** and resting were the main activities that affected PM_(2.5)exposures of different resident groups,accounting for 60.7%-94.5%of total daily ***,the long duration of sleeping makes it the predominant activity contributing to PM 25 exposure *** is necessary to obtain point-to-point respiratory volume(respiratory rate)data when measuring real-time PM_(2.5)exposure data and incorporate respiratory volume(respiratory rate)into the analysis of PM_(2.5)*** the first time,this study quantified the PM_(2.5)exposure inequality based on a novel method and can provide useful information for further studies on the exposure inequity.

关键词： PM_(2.5)exposure environmental inequity activity pattern urban and rural difference

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Algorithm for Solving Traveling Salesman Problem Based on Self-Organizing Mapping Network

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Journal of Shanghai Jiaotong university(Science) 2024年第3期29卷 463-470页

作者：朱江辉叶航航姚莉秀蔡云泽 Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China Key Laboratory of Marine Intelligent Equipment and System Ministry of EducationShanghai 200240China Huawei Technologies Co. Ltd.Shanghai 201206China

Traveling salesman problem(TSP)is a classic non-deterministic polynomial-hard optimization *** on the characteristics of self-organizing mapping(SOM)network,this paper proposes an improved SOM network from the perspectives of network update strategy,initialization method,and parameter *** paper compares the performance of the proposed algorithms with the performance of existing SOM network algorithms on the TSP and compares them with several heuristic *** show that compared with existing SOM networks,the improved SOM network proposed in this paper improves the convergence rate and algorithm *** with iterated local search and heuristic algorithms,the improved SOM net-work algorithms proposed in this paper have the advantage of fast calculation speed on medium-scale TSP.

关键词： traveling salesman problem(TSP) self-organizing mapping(SOM) combinatorial optimization neu-ral network

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Expression and characterization of a novel GH128 laminarinase OUC-Bs Lam26 harboring both hydrolyzing and transferring activities

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Food Science and Human Wellness 2025年第1期14卷 134-143页

作者： Yueyang Dong Yongyi Quan Hong Jiang Hamed I.Hamouda Zewei Lu Yimiao Chen Chengqiang Li Xiangzhao Mao State Key Laboratory of Marine Food Processing and Safety Control College of Food Science and EngineeringOcean University of ChinaQingdao 266404China Qingdao Key Laboratory of Food Biotechnology Qingdao 266404China Key Laboratory of Biological Processing of Aquatic Products China National Light IndustryQingdao 266404China Sanya Ocean Research Institute Ocean University of ChinaSanya 572025China Processes Design and Development Department Egyptian Petroleum Research InstituteCairo 11727Egypt Laboratory for Marine Drugs and Bioproducts of Qingdao National Laboratory for Marine Science and Technology Qingdao 266237China

Laminarin oligosaccharides(LOSs)with a specific degree of polymerization prepared through the laminarin degradation via laminarinase present more significant nutritional functions and application *** intestinal bacteria are promising potential producers of novel carbohydrate-active enzymes with unique ***,a novel glycoside hydrolase family 128(GH128)laminarinase OUC-BsLam26 from the intestinal bacterium Bacteroides ***7301 was heterologously expressed and *** recombinant OUC-BsLam26 with a molecular mass of 49.86 kDa exhibits highest activity(6.60 U/mg)at 45℃ and pH 6.0,which shows noticeable temperature and pH *** purified OUC-BsLam26 could degrade laminarin via an endo-type mode with the generation of laminaripentaose,laminaritetraose,laminaritriose,and laminaribiose,among them,laminaritetraose is the principal product,which accounts for 45.25% of the total products,which is significantly different from the reported GH128 *** minimum recognition substrate of OUC-BsLam26 is ***,OUC-BsLam26 also could catalyze the transglycosylation process with the production of some novel ***,the intestinal bacterium Bacteroides ***7301 contains laminarinase with unique product composition and OUC-BsLam26 is a hopeful bio-catalyst with the potential to produce laminaritetraose and some novel glycosides.

关键词： Laminarinase Expression Laminarin oligosaccharides Hydrolytic pattern Novel glycosides

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Multi-Band Hyperspectral Object Tracking: Leveraging Spectral Information Prompts and Spectral Scale-Aware Representation 13

Multi-Band Hyperspectral Object Tracking: Leveraging Spectra...

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13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2023

作者： Liu, Hongjiao He, Jiayue Wang, Jinpeng Su, Nan Zhao, Chunhui Yan, Yiming Feng, Shou Liu, Ze Liu, Jianfei Zhao, Zilong Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Harbin Engineering University Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology Harbin China

ISBN: (纸本)9798350395570

Under the constraint of limited training samples, achieving robust tracking of hyperspectral data with various target characteristics using a single network is challenging. To address this issue, firstly, we propose a Multi-Band hyperspectral object tracking algorithm based on Spectral Scale-Aware representation (SSAMB). This algorithm can adaptively perceive and capture object characteristics in hyperspectral data across different spectral scales. Secondly, inspired by the 'prompt learning' paradigm, we propose a Hyperspectral Object Tracking network based on Spectral Information Prompts (SIPHOT). It aims to fully leverage the powerful tracking capability of the RGB-based model to alleviate the issue of limited training samples affecting the model's generalization performance. Meanwhile, it can effectively utilize the 'spectral dimension advantage' of hyperspectral data to enhance object tracking accuracy. The experimental results on the HOT2023 dataset demonstrate that the proposed SSAMB and SIPHOT trackers perform excellently on different spectral data, validating the effectiveness of our methods. © 2023 IEEE.

关键词： Deep learning

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Channel Allocation for Wireless Mesh Networks based on Topology control and Potential Game 15

Channel Allocation for Wireless Mesh Networks based on Topol...

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15th International Conference on Microwave and Millimeter Wave technology, ICMMT 2023

作者： Ye, Fang Sun, Xue Zhang, Wei Tian, Yuan Ministry of Industry and Information Key Laboratory of Advanced Marine Communication and Information Technology China Harbin Engineering University College of Information and Communication Engineer Harbin150001 China

ISBN: (纸本)9798350338874

Wireless Mesh Network (WMN) is widely studied for its adaptability in real-world network scenarios, and channel allocation is gradually gaining attention as one of the key technologies affecting WMN's network performance. In this paper, we propose a topology control and potential game based partial overlapping channel assignment method to solve the problem of network congestion and network performance degradation caused by uneven load distribution in traffic aggregation scenarios. The proposed method applies the topology control method to make the load balanced. Furthermore, it designs the benefit function of the game model and proves the existence of the Nash equilibrium solution of the potential game. A better response Nash equilibrium solution method based on incentive mechanism is proposed to improve the convergence speed. Simulation results show that the scheme achieves fair channel allocation at different network sizes while effectively reducing network interference. © 2023 IEEE.

关键词： Network performance

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Resource Allocation for V2V-Enabled Vehicular communications Based on Hypergraph Partition 15

Resource Allocation for V2V-Enabled Vehicular Communications...

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15th International Conference on Microwave and Millimeter Wave technology, ICMMT 2023

作者： Li, Yibing Wang, Ningxin Bai, Neng Tian, Yuan Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Ministry of Industry and Information Key Laboratory of Advanced Marine Communication and Information Technology Harbin150001 China

ISBN: (纸本)9798350338874

In cellular networks that support Vehicle-to-Vehicle (V2V) direct communication, a new resource allocation algorithm based on hypergraph partitioning is proposed to solve the resource allocation problem of Vehicle-to-Infrastructure (V2I) uplink multiplexing, in order to obtain the best resource allocation and robust channel change. Under the interference of V2V, the large scale fading information of wireless channels that changes slowly is used to combine communication reliability and power control, and the optimization model of maximizing the channel capacity of V2I is established to meet the heterogeneous requirements of vehicle network services, and then the minimum capacity maximization is considered to provide more uniform capacity performance. Simulation results show that the proposed algorithm improves the channel capacity of V2V and the channel is more robust on the premise of ensuring the reliability of V2V communication. © 2023 IEEE.

关键词： Resource allocation

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Adaptive Channel Assignment for Wireless Mesh Networks Based on Multi-Intelligent Body Reinforcement Learning 7

Adaptive Channel Assignment for Wireless Mesh Networks Based...

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7th IEEE International Conference on Electronic Information and communication technology, ICEICT 2024

作者： Su, Hang Ye, Fang Su, Chunxia Sun, Xue Harbin Engineering University Key Laboratory of Advanced Marine Communication and Information Technology College of Information and Communication Engineering Harbin China Harbin Engineering University National Key Laboratory of Underwater Acoustic Technology College of Information and Communication Engineering Harbin China Suzhou University of Science and Technology School of Electronic and Information Engineering Suzhou China

ISBN: (纸本)9798350384437

With the popularity of emerging applications and the diversification of IoT device needs, wireless mesh networks (WMN) have been recognized as an effective way to solve "last mile"coverage. In the scenario where the network environment status is unknown, an adaptive channel allocation algorithm based on multi-agent reinforcement learning is proposed to solve the problem that static channel allocation in wireless mesh network cannot adapt well to traffic changes in the network environment, resulting in the degradation of link communication quality. Map the channel allocation problem as a multi-agent reinforcement learning process. The state space based on multiple factors such as interference and load is established, and the relationship between exploration and utilization in the algorithm is balanced by using the improved greedy action selection mechanism, and the return function based on link satisfaction is designed to guide the channel selection to improve the quality of link communication. The simulation results show that the proposed algorithm can effectively adapt to the dynamic changes of traffic and source nodes in the network to ensure the quality of user service. © 2024 IEEE.

关键词： MESH networking

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A Direction-Aware Inshore Ship Detection Method for SAR Images 1

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2nd International Conference on Internet of Things, communication and Intelligent technology, IoTCIT 2023

作者： Liu, Haodong Wang, Lu Zhao, Chunhui Shang, Zhigang Li, Kaiyu Sun, Bailiang College of Information and Communication Engineering Harbin Engineering University Harbin China Key Laboratory of Advanced Marine Communication and Information Technology Ministry of Industry and Information Technology Harbin China College of Underwater Acoustic Engineering Harbin Engineering University Harbin China National Key Laboratory of Underwater Acoustic Technology Harbin Engineering University Harbin China Key Laboratory of Marine Information Acquisition and Security Harbin Engineering University Ministry of Industry and Information Technology Harbin150001 China College of Underwater Acoustic Engineering Harbin Engineering University Harbin150001 China Sanya Nanhai Innovation and Development Base of Harbin Engineering University Sanya57202 China

ISBN: (数字)9789819727575

ISBN: (纸本)9789819727568

In areas such as maritime rescue, fisheries management, traffic surveillance, and national defense, ship detection and recognition based on synthetic aperture radar pictures is crucial. Deep learning offers a fresh approach to high-performance detection and recognition for SAR ships in the past few years with the growth of artificial intelligence. This work examines the ship target recognition approach in SAR images and suggests a direction-aware inshore ship detection method in order to meet the challenges of multi-scale ship target detection in SAR images as well as the complicated background of ships stationed in ports. Multiscale features are observed by using the pyramid feature extraction module with attention method. Aiming at the phase ambiguity problem in OBB regression, the direction-aware classification regression head was designed to accurately determines the position and direction of ship targets. Finally, the experimental part verifies that the proposed method reduces the computational complexity of our method and ensuring the detection performance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Synthetic aperture radar

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Lighting control with Myo armband based on customized classifier

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The Journal of china Universities of Posts and Telecommunications 2022年第4期29卷 106-116页

作者： Jiang Yujian Yang Xue Zhang Junming Song Yang Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of ChinaBeijing 100024China Beijing Key Laboratory of Modern Entertainment Technology Communication University of ChinaBeijing 100024China School of Information and Communication Engineering Communication University of ChinaBeijing 100024China

This paper focuses on gesture recognition and interactive lighting *** collection of gesture data adopts the Myo armband to obtain surface electromyography(sEMG).Considering that many factors affect sEMG,a customized classifier based on user calibration data is used for gesture *** this paper,machine learning classifiers k-nearest neighbor(KNN),support vector machines(SVM),and naive Bayesian(NB)classifier,which can be used in small sample sets,are selected to classify four gesture *** performance of the three classifiers under different training parameters,different input features,including root mean square(RMS),mean absolute value(MAV),waveform length(WL),slope sign change(SSC)number,zero crossing(ZC)number,and variance(VAR)are tested,and different input channels are also *** results show that:The NB classifier,which assumes that the prior probability of features is polynomial distribution,has the best performance,reaching more than 95%***,an interactive stage lighting control system based on Myo armband gesture recognition is implemented.

关键词： Myo armband gesture recognition surface electromyography customized classifier lighting control

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A Comparative Study of IMM Kalman Filters and Neural Computing for Underwater Bearing Only Target Motion Analysis 21

A Comparative Study of IMM Kalman Filters and Neural Computi...

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21st International Bhurban Conference on Applied Sciences and technology, IBCAST 2024

作者： Ali, Wasiq Gang, Qiao Shah, Syed Asim College of Underwater Acoustic Engineering Harbin Engineering University National Key Laboratory of Underwater Acoustic Technology Key Laboratory of Marine Information Acquisition and Security Ministry of Industry and Information Technology Harbin150001 China College of Information and Communication Engineering Harbin Engineering University Harbin150001 China

ISBN: (纸本)9798331516680

Bearing only target motion analysis (BOTMA) is essential for tracking and locating underwater targets, particularly in situations when conventional approaches such as range-based observations are not feasible or accessible. This paper offers a comparative investigation of interacting multiple model (IMM) Kalman filters and neural computing modelling for analyzing the motion of a target in underwater environment using only bearing data. The study aims to assess the effectiveness of above methods in efficiently analyzing motion features of an underwater target using just bearing observations obtained from two passive observers. The proposed methodologies address the challenges given by noisy and limited bearings, providing a substantial improvement in the analysis of the target's motion. To determine the performance of these two adaptive approaches, a supervised large turning track is developed for an underwater maneuvering target. Real time position, velocity, and turning features of a passive object are estimated in a cluttered marine atmosphere. The objective is to minimize the mean square error (MSE) among true and estimated motion of the target. The performance of each technique is evaluated on the basis of accuracy and resilience through detailed analysis. The results clearly demonstrate superiority of neural computing modelling compared to typical nonlinear filtering tools, like interacting multiple model extended Kalman filter (IMMEKF) and interacting multiple model unscented Kalman filter (IMMUKF). Therefore, this comparative study offers useful insights into the merits and drawbacks of each method, providing recommendations for future advancements in underwater target motion analysis and tracking models. © 2024 IEEE.

关键词： Extended Kalman filters

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