检索结果-内蒙古大学图书馆

Mercury transformation processes in nature: Critical knowledge gaps and perspectives for moving forward

Journal of Environmental Sciences 2022年第9期34卷 152-165页

作者： Zhiyuan Gao Wang Zheng Yanbin Li Yurong Liu Mengjie Wu Shouying Li Ping Li Guangliang Liu Xuewu Fu Shuxiao Wang Feiyue Wang Yong Cai Xinbin Feng Baohua Gu Huan Zhong Yongguang Yin Centre for Earth Observation Science and Department of Environment and GeographyUniversity of ManitobaWinnipegMB R3T 2N2Canada Institute of Surface-Earth System Science Tianjin UniversityTianjin 300192China Key Laboratory of Marine Chemistry Theory and Technology Ministry of Education and College of Chemistry and Chemical EngineeringOcean University of ChinaQingdao 266100China State Key Laboratory of Agricultural Microbiology Huazhong Agricultural UniversityWuhan 430070China School of the Environment Nanjing UniversityState Key Laboratory of Pollution Control and Resource ReuseNanjing 210023China State Key Laboratory of Environmental Geochemistry Institute of GeochemistryChinese Academy of SciencesGuiyang 550081China Department of Chemistry and Biochemistry Florida International UniversityMiamiFL 33199USA School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua UniversityBeijing 100084China Environmental Sciences Division Oak Ridge National LaboratoryOak RidgeTennessee 37831USA Environmental and Life Sciences Program(EnLS) Trent UniversityPeterboroughOntario K9L 0G2Canada Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China

The transformation of mercury(Hg) in the environment plays a vital role in the cycling of Hg and its risk to the ecosystem and human health. Of particular importance are Hg oxidation/reduction and methylation/demethylation processes driven or mediated by the dynamics of light, microorganisms, and organic carbon, among others. Advances in understanding those Hg transformation processes determine our capacity of projecting and mitigating Hg risk. Here, we provide a critical analysis of major knowledge gaps in our understanding of Hg transformation in nature, with perspectives on approaches moving forward. Our analysis focuses on Hg transformation processes in the environment, as well as emerging methodology in exploring these processes. Future avenues for improving the understanding of Hg transformation processes to protect ecosystem and human health are also explored.

关键词： Mercury oxidation reduction methylation demethylation isotope fractionation

来源：评论

学校读者我要写书评

暂无评论

An Attention Detection system Based on Gaze Estimation Using Self-supervised Learning 8th

An Attention Detection System Based on Gaze Estimation Usin...

引用

8th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2023

作者： Zeng, Xiang-Yu Zhang, Bo-Yang Liu, Zhen-Tao School of Future Technology China University of Geosciences Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789819975891

With the rapid development of online education around world, it becomes difficult for teachers to evaluate the effect of learning during the online class. To solve this problem, an attention detection system based on gaze estimation using self-supervised learning is proposed. Self-supervised learning is used to train the gaze estimation network and it achieved an average gaze angle error of 6. 5∘ on the MPIIFaceGaze dataset. Cross dataset testing was performed by 5 test subjects in the RT-GENE dataset and all samples in the Columbia dataset, in which achieved average gaze angle error 13. 8∘ and 5. 5∘. It is found that the network has good cross dataset generalization performance, but it is susceptible to factors such as feature occlusion and low image clarity. Then, we developed an attention detection system which has functions of unmanned detection, eye state detection, and gaze detection. Online classroom experiments were conducted to verify the effectiveness of the proposed method, in which the average accuracy of the detection of distraction is around 60%. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Supervised learning

来源：评论

学校读者我要写书评

暂无评论

Evaluating Image Quality of DIBR-synthesized Views in Texture and Depth Domains

Evaluating Image Quality of DIBR-synthesized Views in Textur...

引用

2021 China Automation Congress, CAC 2021

作者： Wang, Guangcheng Guo, Nan Liu, Hongyan Zhang, Yonghui Zhou, Yazhen Gu, Ke Faculty of Information Technology Beijing University of Technology Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Artificial Intelligence Institute Beijing100124 China

ISBN: (纸本)9781665426473

Accurately predicting the quality of depth-image-based-rendering (DIBR) synthesized images is of great significance in promoting DIBR techniques. Recently, Many DIBR-synthesized image quality assessment (IQA) algorithms based on quantifying the distortion existed in texture images have been proposed. However, these methods ignore the damage of DIBR algorithms on the depth structure of DIBR-synthesized images and thus fail to evaluate the visual quality of DIBR-synthesized images accurately. To this end, we present a DIBR-synthesized image quality assessment metric with multi-modal information (i.e. integrating texture and depth information), dubbed as MMI. MMI predicts the quality of DIBR-synthesized images by jointly measuring the texture structure and depth structure of the synthesized image. The design principle of our MMI is that the local geometric distortion, introduced by DIBR techniques in the hole-filling process, destroys the texture structure and the depth structure of DIBR-synthesized images. Thus, we can accurately evaluate DIBR-synthesized image quality by a joint representation of texture structure and depth structure. Experiments show that our MMI is better than the competing state-of-the-art IQA algorithms in predicting DIBR-synthesized image quality. © 2021 IEEE

关键词： Textures

来源：评论

学校读者我要写书评

暂无评论

Remote Sensing Inversion for River Turbidity Estimation Based on Noise Injection and Ensemble Learning

Remote Sensing Inversion for River Turbidity Estimation Base...

引用

2021 China Automation Congress, CAC 2021

作者： Zhou, Yazhen Shi, Shuang Liu, Hongyan Zhang, Yonghui Gu, Ke Qiao, Junfei Faculty of Information Technology Beijing University of Technology Beijing 100124 China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Artificial Intelligence Institute

ISBN: (纸本)9781665426473

Turbidity is one main indicator of quality typically used for monitoring water pollution and water eutrophication. The monitoring technology of river water quality can be divided into contact monitoring technology based on physical sensors and non-contact monitoring technology based on remote sensing satellites. The traditional contact monitoring technology has limited monitoring spatial resolution. As a new technology, the remote sensing monitoring technology of the river can conveniently solve the above-mentioned shortcomings and realize the coverage of the whole river basin. However, due to the scarcity of remote sensing data and the measurement errors of remote sensing satellites themselves, learning-based turbidity measurement methods have weak generalization ability and thus are easily prone to produce large deviations. To effectively address such difficulty, a noise injection method is introduced into a river turbidity measurement model based on ensemble learning. To be specific, we randomly generate many noise sets and add them to the remote sensing data to make it closer to the real application scene, and then adopt the ensemble learning model to estimate river turbidity. Experiments validate that the random noise injection strategy can effectively improve the generalization performance of river turbidity measurement. © 2021 IEEE

关键词： Rivers

来源：评论

学校读者我要写书评

暂无评论

Wind Power Forecasting Methods Based on Deep Learning:A Survey

引用

Computer Modeling in engineering & Sciences 2020年第1期122卷 273-301页

作者： Xing Deng Haijian Shao Chunlong Hu Dengbiao Jiang Yingtao Jiang School of Computer Science Jiangsu University of Science and TechnologyZhenjiangChina School of Automation Key Laboratory of Measurement and Control for CSEMinistry of EducationSoutheast UniversityNanjingChina Department of Electrical and Computer Engineering University of NevadaLas VegasUSA

Accurate wind power forecasting in wind farm can effectively reduce the enormous impact on grid operation safety when high permeability intermittent power supply is connected to the power *** to provide reference strategies for relevant researchers as well as practical applications,this paper attempts to provide the literature investigation and methods analysis of deep learning,enforcement learning and transfer learning in wind speed and wind power forecasting ***,wind speed and wind power forecasting around a wind farm requires the calculation of the next moment of the definite state,which is usually achieved based on the state of the atmosphere that encompasses nearby atmospheric pressure,temperature,roughness,and *** an effective method of high-dimensional feature extraction,deep neural network can theoretically deal with arbitrary nonlinear transformation through proper structural design,such as adding noise to outputs,evolutionary learning used to optimize hidden layer weights,optimize the objective function so as to save information that can improve the output accuracy while filter out the irrelevant or less affected information for *** establishment of high-precision wind speed and wind power forecasting models is always a challenge due to the randomness,instantaneity and seasonal characteristics.

关键词： Deep learning reinforcement learning transfer learning wind power forecasting

来源：评论

学校读者我要写书评

暂无评论

Disturbance Observer-Based control of Weight on Bit in Drilling Process with Formation Variation

Disturbance Observer-Based Control of Weight on Bit in Drill...

引用

Asian control Conference

作者： Shipeng Chen Wangnian Li Chengda Lu Yang Zhou Weihua Cao Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China CCTEG Xi'an Research Institute (Group) Co. Ltd. Xi'an China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

In deep geological drilling, encountering various formations is inevitable. Formation changes can lead to fluc-tuations in the weight on bit due to the bit-rock interaction. This paper proposes a disturbance observer-based weight on bit control system to mitigate the adverse effects of formation changes on system performance. First, an axis-torsion coupled dynamic model is established, and the relationship between the two dimensions is analyzed. The validity of the model is confirmed through comparison with field data collected from a geothermal well drilling operation. Then, a disturbance observer is designed to estimate and compensate for the disturbance at the control input, thereby reducing weight on bit fluctuations caused by formation variations. Simulation results considering formation variation during drilling verify the effectiveness of the proposed method.

关键词： Drilling Simulation system performance Geology Process control control systems Disturbance observers

来源：评论

学校读者我要写书评

暂无评论

Creation and control of high-dimensional multi-partite classically entangled light

引用

Light(Science & Applications) 2021年第5期10卷 796-805页

作者： Yjie Shen Iaac Nape Xilin Yang Xing Fu Mali Gong Darryl Naidoo Andrew Forbes School of Physics University of the WitwatersrandPrivate Bag 3Wits 2050South Africa State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision InstrumentTsinghua University100084 BeijingChina Electrical and Computer Engineering Department University of CaliforniaLos AngelesCA 90095USA Key Laboratory of Photonic Control Technology(Tsinghua University) Ministry of Education100084 BeijingChina CSIR National Laser Centre PO Box 395Pretoria 0001South Africa Optoelectronics Research Centre University of SouthamptonSouthampton S0171BJUK

Vector beams,non-separable in spatial mode and polarisation,have emerged as enabling tools in many diverse applications,from communication to *** applicability has been achieved by sophisticated laser designs controlling the spin and orbital angular momentum,but so far is restricted to only two-dimensional *** we demonstrate the first vectorially structured light created and fully controlled in eight dimensions,a new *** externally modulate our beam to control,for the frst time,the complete set of classical Greenberger-Horne-Zeilinger(GHZ)states in paraxial structured light beams,in analogy with high-dimensional multi-partite quantum entangled states,and introduce a new tomography method to verify their *** complete theoretical framework reveals a rich parameter space for further extending the dimensionality and degrees of freedom,opening new pathways for vetorilly structured light in the classical and quantum regimes.

关键词： quantum analogy dimensions

来源：评论

学校读者我要写书评

暂无评论

Stability and Bifurcation control of Fractional BAM Neural Networks with Diffusion and Time Delays

Stability and Bifurcation control of Fractional BAM Neural N...

引用

Chinese control Conference (CCC)

作者： Feng Liu Wei Wang Gang Cai Feifan Zhou Hua O Wang Xiuqin Yang School of Automation China University of Geosciences Wuhan China Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Department of Mechanical Engineering Boston University Boston MA USA School of Education Minzu University of China Beijing China

Based on fractional calculus theory and reaction-diffusion equation theory, a fractional-order time-delay reaction-diffusion neural network with Neumann boundary conditions is investigated. By constructing the phase space basis based on the Laplace operator eigenvector, the system equation is linearized to obtain the characteristic equation. Then, the characteristic equation is analyzed, and the local stability of the system at the equilibrium point is discussed. And taking the time delay as the bifurcation parameter, the stability changes of the system at the equilibrium point and the generation conditions of the Hopf bifurcation are studied when the time delay changes. Moreover, a state feedback controller is designed to control the bifurcation of the system. Finally, the theoretical derivation is verified by numerical simulation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Anthropogenic monoterpenes aggravating ozone pollution

引用

National Science Review 2022年第9期9卷 178-185页

作者： Haichao Wang Xuefei Ma Zhaofeng Tan Hongli Wang Xiaorui Chen Shiyi Chen Yaqin Gao Ying Liu Yuhan Liu Xinping Yang Bin Yuan Limin Zeng Cheng Huang Keding Lu Yuanhang Zhang State Key Joint Laboratory of Environmental Simulation and Pollution Control State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution ControlCollege of Environmental Sciences and Engineering Peking University School of Atmospheric Sciences Sun Yat-sen University Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary Key Laboratory of Tropical Atmosphere–Ocean System Ministry of Education Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Institute of Energy and Climate Research IEK-8:TroposphereForschungszentrum Jülich Gmb H State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Complex Shanghai Academy of Environmental Sciences Institute for Environmental and Climate Research Jinan University

Monoterpenes have been known to have a critical influence on air quality and climate change through their impact on the formation of fine *** we present field evidence that monoterpene oxidations largely enhanced local ozone production in a regional site in eastern *** observed monoterpene was most likely from biomass burning rather than biogenic emissions,as indicated by the high correlation with CO at night-time,and the observed ratio of these two species was consistent with previously determined values from biomass burning *** monoterpene oxidations were determined experimentally based on direct radical measurements,leading to a daily ozone enhancement of 4-18 parts per billion by volume（ppb）,which was 6%-16% of the total ozone production,depending on the speciation of *** demonstrates that the previously overlo oked anthropogenic monoterpenes make an important contribution to 03 production in eastern *** role could possibly be important at similar locations across China and other parts of the world that are characterized by massive emissions,especially where there are high *** results highlight that anthropogenic monoterpenes should be taken into account when proceeding with the coordinated mitigation of O3and particulate matter pollution.

关键词： monoterpenes ozone pollution biomass burning anthropogenic emissions radical chemistry

来源：评论

学校读者我要写书评

暂无评论

Dynamic Analysis and control of Fractional Order Memristor Hopfield Neural Network

Dynamic Analysis and Control of Fractional Order Memristor H...

引用

Chinese control Conference (CCC)

作者： Feng Liu Gang Cai Feifan Zhou Wei Wang Hua Wang Xiuqin Yang School of Automation China University of Geosciences Wuhan China Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Department of Mechanical Engineering Boston University Boston MA USA School of Education Minzu University of China Beijing China

In this paper, a novel smooth magnetron is introduced to construct a fractional memristor Hopfield neural network (fractional order M-HNN). The local stability of equilibrium point are analyzed theoretically. Taking the memristor coupling strength coefficient and the fractional order as bifurcation parameters, the phase trajectory diagram, the bifurcation diagram of the system are drawn to analyze the influence on the dynamic behavior of the neural network. When the system parameters are fixed, the hyperchaos phenomenon of the fractional order M-HNN model is revealed. Finally, the PD controller is applied to the model to enhance the stability of the system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：