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arXiv 2022年

作者： Su, Lan Niu, Yong Han, Zhu Ai, Bo He, Ruisi Wang, Yibing Wang, Ning Su, Xiang The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-Speed Railway System Beijing Jiaotong University Beijing100044 China The National Mobile Communications Research Laboratory Southeast University Nanjing211189 China The Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The School of Information Engineering Zhengzhou University Zhengzhou450001 China The Norwegian University of Science and Technology Norway and University of Oulu Finland

With the explosive growth of vehicle applications, vehicular networks based on millimeter wave (mmWave) bands have attracted interests from both academia and industry. mmWave communications are able to utilize the huge available bandwidth to provide multiple Gbps transmission rates among vehicles. In this paper, we address the content distribution scheduling problem in mmWave vehicular networks. It has been challenging for all vehicles in the same network to complete content downloading due to the limited communication resources of roadside units (RSUs) and the high mobility of vehicles. We propose a joint vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) scheduling scheme to minimize the total number of content distribution time slots from a global optimization perspective. In the V2I phase, the RSU serially transmits integrity content to vehicles, which are selected according to the vehicular network topology and transmission scheduling scheme. In the V2V phase, full-duplex communications and concurrent transmissions are exploited to achieve content sharing between vehicles and improve transmission efficiency. Performance evaluations demonstrate that our proposed scheme reduces the number of time slots and significantly improves system throughput when compared with other schemes, especially under large-size file transfers and a large number of vehicles. Copyright © 2022, The Authors. All rights reserved.

关键词： Millimeter waves

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Photo-Based Monitoring of Particulate Matter in the Campus: A New Strategy for Student Health

Photo-Based Monitoring of Particulate Matter in the Campus: ...

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作者： Yonghui Zhang Ke Gu Zhifang Xia Junfei Qiao Faculty of Information Technology Beijing University of Technology Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing Key Laboratory of Computational Intelligence and Intelligent System State Information Center

It is imperative for the students' future health to ensure the students in good physical levels. Recent years have witnessed the increasingly serious harm to student health caused by the continually growing concentration of Particulate Matters(PMs). Consequently, the task of preventing and controlling PM concentrations in the campus is eagerly required. A welldesigned model for the monitoring of PM(as the basis for PM prevention and control) has posed a big challenge. Prior works have revealed that photo-based methods are available for the monitoring of PM. Towards validating the effectiveness of existing methods for PM monitoring in the campus, we construct a novel dataset that involves 1,500 photos collected in the Beijing University of Technology. Results confirm that stated-of-the-art methods are far from ideal for the monitoring of PM in the campus. To solve the aforesaid issue, this paper further proposes a novel photo-based PM monitoring model by using the weighted average method solved by LASSO regression to fuse the above methods' outputs tested to infer the PM values. Results demonstrate the superiority of our proposed model as compared to state-of-theart methods on the large-scale AQPDBJUT dataset.

关键词： LASSO Photo-Based Monitoring of Particulate Matter in the Campus A New Strategy for Student Health

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Air Quality controlling-Oriented Highly Efficient Method for Monitoring Particulate Matters

Air Quality Controlling-Oriented Highly Efficient Method for...

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第三十九届中国控制会议

Since Particulate Matters（PMs） are closely related to people’s living and health, it has become one of the most important indicator of air quality monitoring around the world. But the existing sensor-based methods for PMs monitoring have remarkable disadvantages, such as low-density monitoring stations and high-requirement monitoring conditions. It is highly desired to devise a method that can obtain the PMs concentration at any location for the following air quality control in *** prior works indicate that the PMs concentration can be monitored by using ubiquitous photos. To further investigate such issue, we gathered 1,500 photos in big cities to establish a new AQPDCITY dataset. Experiments conducted to check nine stateof-the-art methods on this dataset show that the performance of those above methods perform poorly in the AQPDCITY *** address the above issue, we propose a new photo-based model for PMs monitoring. To be specific, we use the Support Vector Regression（SVR） to incorporate four types of 18 features to obtain a high-density PMs monitoring map. Experiments show that the newly proposed model has achieved superior performance than recently developed methods in the AQPDCITY dataset.

关键词： Particulate Matters（PMs） Monitoring AQPDCITY Dataset Feature Extrastion and Fusion

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Sustainability Nexus AID: groundwater

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Sustainability Nexus Forum 2024年第1期32卷 1-12页

作者： Soltanian, Mohamad Reza Moeini, Farzad Dai, Zhenxue Sawyer, Audrey H. Fleckenstein, Jan H. Doherty, John Curtis, Zachary Chaudhuri, Abhijit Chiogna, Gabriele Fahs, Marwan Han, Weon Shik Mseli, Zaina Hussein Lotti, Francesca Moon, Hee Sun Zhu, Lin Al-Masri, Dema Zhan, Chuanjun Hoteit, Hussein Matin, Mir A. Zarei, Azin Carroll, Kenneth C. Evans, Sarah G. Madani, Kaveh Department of Geosciences University of Cincinnati Cincinnati USA Department of Environmental Engineering University of Cincinnati Cincinnati USA College of Construction Engineering Jilin University Changchun China School of Environmental and Municipal Engineering Qingdao University of Technology Qingdao China School of Earth Sciences The Ohio State University Columbus USA Department of Hydrogeology Helmholtz Centre for Environmental Research UFZ-Leipzig Leipzig Germany Watermark Numerical Computing Brisbane Australia Hydrosimulatics Inc Lansing USA Department of Applied Mechanics Indian Institute of Technology Madras Chennai India GeoZentrum Nordbayern Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Institute Terre Et Environment de Strasbourg University of Strasbourg CNRS ENGEES Strasbourg France Department of Earth System Sciences Yonsei University Seoul Republic of Korea Department of Environmental Engineering and Management University of Dodoma Dodoma Tanzania Kataclima S.R.L. / SYMPLE S.R.L Vetralla Viterbo Italy Groundwater Environment Research Center Climate Change Response Division Korea Institute of Geoscience and Mineral Resources Daejeon Republic of Korea Beijing Laboratory of Water Resources Security Capital Normal University Beijing China Qatar Environment and Energy Research Institute (QEERI) Hamad Bin Khalifa University Qatar Foundation Doha Qatar Physical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia United Nations University Institute for Water Environment and Health (UNU-INWEH) Richmond Hill Canada United Nations University Institute for Integrated Management of Material Fluxes and of Resources (UNU-FLORES) Dresden Germany Plant and Environmental Sciences Department New Mexico State University Las Cruces USA Department of Geological and Environmental Sciences Appalachian State University Boone USA

The Groundwater Module within the Sustainability Nexus Analytics, Informatics, and Data (AID) Programme of the United Nations University (UNU) addresses critical challenges in sustainable groundwater management. Groundwater resources around the world are under increasing stress from overextraction and pollution, threatening water and food security for billions. Groundwater governance is not one-dimensional but multi-faceted, and central to the management of environmental, social, and economic systems worldwide. In line with the Nexus Approach, the goal of the UNU Sustainability Nexus AID Programme's Groundwater Module is improving access to data and information tools that help scientists and decision-makers address interdisciplinary groundwater problems that affect humans and nature. Here, we describe the critical need for a Nexus Approach to groundwater-related issues and highlight current challenges involving data and information gaps and data-model operability. The Groundwater Module can help address these challenges by offering a central hub for data, analytics, and informatics for addressing groundwater-related issues. By integrating dispersed datasets and modeling tools, this module aims to enable analysis and new insights. We showcase some of the tools in the Groundwater Module and discuss future opportunities in the global pursuit to fulfill the UN Sustainable Development Goals (SDGs).

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Online Analysis of Volatile and Semivolatile Organic Compounds in Water Matrices Using a Dual-Channel Comprehensive Two-Dimensional Gas Chromatography Coupled with Time-of-Flight Mass Spectrometry system

SSRN

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SSRN 2024年

作者： Chen, Guangxu Wu, Manman Ma, Qin Li, Mei Zhou, Zhen Xu, Jingwei Waterhouse, Geoffrey I.N. Song, Ninghui Zhao, Wei-Wei School of Environment and Energy State Key Laboratory of Luminescent Materials and Devices Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control South China University of Technology Guangzhou510006 China Hangzhou Lin'an Ecological Environment Monitoring Station Hangzhou311300 China Institute of Mass Spectrometry and Atmospheric Environment Guangdong Provincial Engineering Research Center for Online Source Apportionment System of Air Pollution Jinan University Guangzhou510632 China Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality Guangzhou510632 China Guangdong MS Institute of Scientific Instrument Innovation Guangzhou510530 China School of Chemical Sciences The University of Auckland Auckland1142 New Zealand Nanjing Institute of Environmental Sciences Ministry of Ecology and Environment Nanjing210042 China State Key Laboratory of Analytical Chemistry for Life Science School of Chemistry and Chemical Engineering Nanjing University Nanjing210023 China

Monitoring organic compounds in aquatic matrices can be a complex and time-consuming process. To address this issue, we present a novel approach that uses a dual-channel comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry (GC × GC–TOFMS) system equipped with an automatic pretreatment platform for online monitoring of volatile organic compounds (VOCs) and semivolatile organic compounds (SVOCs) in water matrices. Our automatic pretreatment platform incorporates headspace sampling (HS) and liquid–liquid extraction (LLE) to extract VOCs and SVOCs from water matrices. The GC × GC–TOFMS system features a dual-channel analytical structure column configuration, allowing for the sequential analysis of VOCs in the GC–TOFMS mode and SVOCs in the GC × GC–TOFMS mode. We quantitatively detected 55 and 104 target VOCs and SVOCs, respectively, in a water sample using the instrument system. Our method demonstrated excellent correlation coefficients ranging from 0.990 to 1.000, method detection limit ranging from 0.08 to 4.78 μg·L−1, relative standard deviation below 19.3%, and recovery rates ranging from 50.0% to 124.0%. To validate the online monitoring capabilities of our system, we tested the target SVOCs at three different concentration levels over a 3-day period. Most compounds exhibited recovery rates ranging from 70.0% to 130.0%. Furthermore, we applied our method to analyze a real water sample and successfully detected more than 100 target and nontarget VOCs/SVOCs, including alcohols, aldehydes, ketones, acids, esters, and phenols. Our results indicated the potential of our novel instrument system for effective screening and analysis of organic contaminants in aquatic matrices. This innovation provides a promising solution for improving the efficiency and accuracy of organic compound monitoring in water matrices. © 2024, The Authors. All rights reserved.

关键词： Volatile organic compounds

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Estimation of Reduced Greenhouse Gas Emission from Municipal Solid Waste Incineration with Electricity Recovery in Prefecture- and County-Level Cities of China

SSRN

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SSRN 2022年

作者： Zhao, Qing Tang, Weihao Han, Mengjie Cui, Wenjing Zhu, Lei Xie, Huaijun Li, Wei Wu, Fengchang National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management Institute of Eco-environmental and Soil Sciences Guangdong Academy of Sciences Guangzhou510650 China Key Laboratory of Pollution Ecology and Environmental Engineering Institute of Applied Ecology Chinese Academy of Sciences Shenyang110016 China Department of Earth System Science Ministry of Education Key Laboratory for Earth System Modeling Institute for Global Change Studies Tsinghua University Beijing100084 China Institute for Carbon Neutrality Tsinghua University Beijing100084 China Dalian Key Laboratory on Chemicals Risk Control and Pollution Prevention Technology School of Environmental Science and Technology Dalian University of Technology Linggong Road 2 Dalian116024 China State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental Sciences Beijing100012 China

Municipal solid waste (MSW) without proper managements could be a significant source of greenhouse gas (GHG) emissions. MSW incineration with electricity recovery (MSW-IER) is recognized as a sustainable way to utilize waste, but its effectiveness on reducing GHG emissions at the city scale in China remain unclear due to limited data of MSW compositions. In this study, MSW compositions in 297 cities of China from 2002 to 2017 were predicted using a random forest model trained by a combination of socio-economic, climate and spatiotemporal factors. Spatiotemporal and climatic factors (such as economic development level, precipitation) accounted for 6.5%-20.7% and 20.1%-37.6% to total contributions on MSW composition, respectively. The GHG emissions from MSW-IER in each Chinese city were further calculated based on the predicted MSW compositions. The plastic is the main GHG emission source, accounting for over 91% of the total emission during 2002-2017. Compared to baseline (landfill) emission, the GHG emission reduction from MSW-IER was 12.5 × 107 kg CO2-eq in 2002 and 415 × 107 kg CO2-eq in 2017, with an average annual growth rate of 26.3%. The results provide basic data for estimating GHG emission in MSW management in China. © 2022, The Authors. All rights reserved.

关键词： Municipal solid waste

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Robust symbol-level precoding and passive beamforming for IRS-aided communications

arXiv

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arXiv 2021年

作者： Zhang, Guangyang Shen, Chao Ai, Bo Zhong, Zhangdui Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing100044 China Frontiers Science Center for Smart High-speed Railway System Beijing100044 China Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications 100044 China Key Laboratory of Railway Industry of Broadband Mobile Information Communications Beijing100044 China

This paper investigates a joint beamforming design in a multiuser multiple-input single-output (MISO) communication network aided with an intelligent reflecting surface (IRS) panel. The symbol-level precoding (SLP) is adopted to enhance the system performance by exploiting the multiuser interference (MUI) with consideration of bounded channel uncertainty. The joint beamforming design is formulated into a nonconvex worst-case robust programming to minimize the transmit power subject to single-to-noise ratio (SNR) requirements. To address the challenges due to the constant modulus and the coupling of the beamformers, we first study the single-user case. Specifically, we propose and compare two algorithms based on the semidefinite relaxation (SDR) and alternating optimization (AO) methods, respectively. It turns out that the AO-based algorithm has much lower computational complexity but with almost the same power to the SDR-based algorithm. Then, we apply the AO technique to the multiuser case and thereby develop an algorithm based on the proximal gradient descent (PGD) method. The algorithm can be generalized to the case of finite-resolution IRS and the scenario with direct links from the transmitter to the users. numerical results show that the SLP can significantly improve the system performance. Meanwhile, 3-bit phase shifters can achieve near-optimal power performance. © 2021, CC BY.

关键词： Gradient methods

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Dual-Net for Joint Channel Estimation and Data Recovery in Grant-free Massive Access

Dual-Net for Joint Channel Estimation and Data Recovery in G...

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2021 IEEE Global Communications Conference (GLOBECOM)

作者： Yanna Bai Wei Chen Yuan Ma Ning Wang Bo Ai State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University China Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications Beijing China Frontiers Science Center for Smart High-speed Railway System Beijing China College of Electronics and Information Engineering Shenzhen University Shenzhen China School of Information Engineering Zhengzhou University Zhengzhou China Key Laboratory of Railway Industry of Broadband Mobile Information Communications Beijing China

ISBN: (纸本)9781728181059

In massive machine-type communications (mMTC), the conflict between millions of potential access devices and limited channel freedom leads to a sharp decrease in spectral efficiency. The sparse nature of mMTC provides a solution by using compressive sensing (CS) to perform multiuser detection (MUD) but suffers conflict between the high computation complexity and low latency requirements. In this paper, we propose a novel Dual-network for joint channel estimation and data recovery. The proposed Dual-Net utilizes the sparse consistency between the channel vector and data matrix of all users. Experimental results show that the proposed Dual-Net outperforms existing CS algorithms and general neural networks in computation complexity and accuracy, which means reduced access delay and more supported devices.

关键词： Multiuser detection Performance evaluation Spectral efficiency Channel estimation Sensors Delays Sparse matrices

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Design of a high speed drawing frame monitoring system based on IoT using MQTT protocol

Design of a high speed drawing frame monitoring system based...

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International Conference on Mechanical, Electric and Industrial engineering, MEIE 2018

作者： Cui, Zishang Wu, Jing Shen, Chen Chen, Bing National Engineering Research Center of Numerical Control System Huazhong University of Science and Technology Wuhan430074 China

Online monitoring for sliver quality is an important part of the drawing process. This paper presents a high-speed drawing frame monitoring system based on Internet of Things (IoT) using Message Queuing Telemetry Transport (MQTT) protocol, which consists of drawing frame IoT terminal equipment, the cloud server and PC or mobile terminal equipments. Drawing frame IoT terminal equipment takes Cortex-A7 and Cortex-M4 of series of ***7 as its control cores. The A7 processor publishes IoT data as a communication gateway while the M4 processor collects sensor data and executes local on-line detection program. Two processors run Linux and FreeRTOS as operating system respectively, and the data exchange between them adopt rpmsg pattern. The communication gateway using MQTT publishes data of the IoT terminal to the cloud server for remoting monitoring and intelligent diagnosis, when the local on-line detection system aims at acquiring real-time status of the sliver on drawing frame. Users can check the real-time status of the drawing frame at the subscription end of IoT and on the computer or mobile phone end by subscribing message by theme. Experiments show that the system operates with reliability, and is good compatible with other devices because of the modular design. The adoption of this system can promote the digitization and the intelligentialize of the drawing frame. © Published under licence by IOP Publishing Ltd.

关键词： Internet of things

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Parallel Building Process Management system

Parallel Building Process Management System

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Chinese Automation Congress (CAC)

作者： Sheng Liu Xisong Dong Gang Xiong Zhen Shen Bin Hu Xiaoyu Chen State Key Laboratory for Management and Control of Complex System Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Institution of Intelligent Manufacturing Qingdao Academy of Intelligent Industries Qingdao China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665426480

With the development of industrialized building and intelligence technology, it becomes necessary and possible to realize building process intelligence management. In recent years, digital twins and parallel management get more and more attentions in academic research and industrial applications. This paper addresses how parallel building system performs intelligence management on industrialized building process. Firstly, actual building model and artificial building model are created according to actual building system. Then business driving engine and simulation engine drive actual building model and artificial building model, respectively. Participants receive and send messages by software interfaces. Business driving engine changes the status of actual building model and sends the changes to simulation engine. Simulation engine updates the status of artificial building model and runs artificial building model with various parameters. Then it sends the parameter with the best effect to business driving engine. Business driving engine sends recommendations to participants according to the best parameter. Thus, building process intelligence management is achieved.

关键词： Automation Digital twin Buildings User interfaces Software Engines Business

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