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Influence of surface albedo and vegetation fractional coverage on thermal environment of mining area

Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of technology 2022年第12期54卷 117-126页

作者： Hou, Chunhua Li, Fuping He, Baojie Ma, Pengkun Song, Wen Zhao, Jingjing College of Mining Engineering North China University of Science and Technology Hebei Tangshan063210 China Department of Computer Science Tangshan Normal University Hebei Tangshan063000 China Faculty of Architecture and Urban Planning Chongqing University Chongqing400405 China Faculty of Built Environment University of New South Wales Sydney2052 Australia Institute of Urban Boundary Layer and Atmospheric Environment Institute of Urban Meteorology CMA Beijing100089 China Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China

The influence of the changes in surface albedo on the thermal environment of the mining area due to the destruction of the original vegetation caused by the high-intensity mining of mineral resources was analyzed. Taking Malanzhuang Iron Mine in Qian'an city of Hebei province as an example, the statistical model method was adopted to retrieve the surface albedo based on the visible light band of Landsat remote sensing image, and the pixel trisection model was used to retrieve the vegetation fractional coverage based on NDVI-DFI. By means of radiative transfer equation method, the land surface temperature (LST) was retrieved based on the thermal infrared band of Landsat remote sensing image. With the aid of superposition analysis method, correlation analysis method, and regression analysis method, the response of spatiotemporal heterogeneity of surface thermal environment to the changes in photosynthetic vegetation coverage (fPV) and surface albedo was quantitatively and visually explored. Results showed that the spatial distribution of surface thermal environment in the study area showed obvious heterogeneity and regularity. The high temperature zone was mainly distributed in the northern Shaheshan stope, central Liuheyu dump, and the unreclaimed Baimashan dump in the south. The moderate temperature zone was mainly located at the edge of the high temperature zone and other bare surfaces. The low temperature zone was mainly located in the northern reclaimed tailings pond and reclaimed waste dump, as well as the green land and water bodies in the area. The spatiotemporal variation of photosynthetic vegetation coverage and surface albedo resulted in a large heterogeneity of the surface thermal environment during the summer midday in the study area. The mean surface temperature of underlying surface in the third phase of the image was ranked as follows: mining area bare rock > dump slag > reclamation vegetation > water body. The regression analysis results showed that f

关键词： Vegetation

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Species-Shared and -Specific Structural Connections Revealed by Dirty Multi-task Regression 23rd

Species-Shared and -Specific Structural Connections Revealed...

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23rd International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2020

作者： Zhang, Tuo He, Zhibin Jiang, Xi Guo, Lei Hu, Xiaoping Liu, Tianming Du, Lei School of Automation Northwestern Polytechnical University Xian China School of Life Science and Technology MOE Key Lab for Neuroinformation University of Electronic Science and Technology of China Chengdu China Department of Bioengineering UC Riverside RiversideCA United States Cortical Architecture Imaging and Discovery Lab Department of Computer Science and Bioimaging Research Center The University of Georgia AthensGA United States

ISBN: (纸本)9783030597276

Comparative studies across species, such as primates in this work, reveal the shared structural or functional patterns that might be inherited from the common ancestors and the specific ones that might be related to individualized evolution strategies. Both the shared or specific patterns could help promote the understanding of mechanisms of brain structural and functional architectures and brain dynamics. Many previous studies can be found to report the comparative results on species pairs. However, very few studies were found to perform a comparison of large-scale connectomes across multiple species via a data-driven method. To this end, we construct brain connectomes for three primates, macaque, chimpanzee and human, by using Brodmann areas as graphic nodes and diffusion MRI derived white matter fibers to define edges and edge weights. On these connectomes, a novel dirty multi-task regression method is developed in the attempt to automatically identified the species-shared and -specific connections. The concordance of the findings via our method and previous reports demonstrate the effectiveness and the promise of this framework. © 2020, Springer Nature Switzerland AG.

关键词： Magnetic resonance imaging

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Tackling the muon identification in water Cherenkov detectors problem for the future Southern Wide-field Gamma-ray Observatory by means of Machine Learning

arXiv

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arXiv 2021年

作者： González, B.S. Conceição, R. Pimenta, M. Tomé, B. Guillén, A. - Lisbon Av. Prof. Gama Pinto 2 Lisbon1649-003 Portugal Universidade de Lisboa Av. Rovisco Pais 1 Lisbon1049-001 Portugal Computer Architecture and Technology Department University of Granada Granada Spain

This paper presents several approaches to deal with the problem of identifying muons in a water Cherenkov detector with a reduced water volume and 4 PMTs. Different perspectives of information representation are used and new features are engineered using the specific domain knowledge. As results show, these new features, in combination with the convolutional layers, are able to achieve a good performance avoiding overfitting and being able to generalise properly for the test set. The results also prove that the combination of state-of-the-art Machine Learning analysis techniques and water Cherenkov detectors with low water depth can be used to efficiently identify muons, which may lead to huge investment savings due to the reduction of the amount of water needed at high altitudes. This achievement can be used in further research to be able to discriminate between gamma and hadron induced showers using muons as discriminant. © 2021, CC BY-NC-SA.

关键词： Cosmic rays

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Pricing Strategy for Household Energy-Saving Option (Heso): A Novel Option-Based Intervention for Promoting Household Energy Efficiency

SSRN

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SSRN 2022年

作者： Xu, Qian Li, Shengping Shen, Liyin Chang, Ruidong Wang, Qian-Cheng Liu, Xuan Department of the Built Environment College of Design and Engineering National University of Singapore 4 Architecture Drive Singapore117566 Singapore Department of Infrastructure Engineering Faulty of Engineering and Information Technology The University of Melbourne VIC3010 Australia School of Spatial Planning and Design Zhejiang University City College Hangzhou China School of Management Science and Real Estate Chongqing University Chongqing China School of Architecture and Built Environment Faculty of Engineering Computer and Mathematical Sciences The University of Adelaide SA5005 Australia Department of Land Economy University of Cambridge CambridgeCB3 9EP United Kingdom Department of the Built Environment Eindhoven University of Technology Eindhoven5600MB Netherlands

Household energy-saving interventions are essential in reducing energy consumption in residential buildings. One of the effective interventions is Household Energy-Saving Option (HESO). However, the pricing strategy of this innovative intervention has not been explored. This study aims to establish a feasible valuation strategy for HESO to facilitate the application of market-based energy-saving interventions among households. This study first provides a pricing strategy of HESO from a market zero-profit perspective. It continues by developing a price cap and floor for HESO's market price. The theoretical pricing model was validated by a field experiment consisting of two-tiered HESO trading among 67 households in Singapore. The results revealed decisive implications for both environmental policymakers and HESO suppliers. Policymakers are suggested to launch HESO in countries or regions with stable and relatively high electricity prices and low discount rates. HESO suppliers may choose to adjust rewards and duration accordingly when the market price deviates from the zero-profit equilibrium price of HESO. The valuation strategy of HESO also helps quantitative estimation of households’ perceived value of HESO. © 2022, The Authors. All rights reserved.

关键词： Costs

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Deep learning based Identification of Solid Waste Management in Smart Cities through Garbage Separation and Monitoring

Deep learning based Identification of Solid Waste Management...

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International Conference on Inventive Research in Computing Applications (ICIRCA)

作者： Abin George Sham H. Mankar N V S Suryanarayana Manish Gupta R Sathish A Priya Knowledge and technology management Division Council of Scientific & Industrial Research National Aerospace Laboratories Bangaluru Karnataka India Department of Mechanical Engineering Pimpri Chinchwad College of Engineering and Research Pune Maharashtra India Administrative Officer Central Tribal University of Andhra Pradesh Vizianagaram Andhra Pradesh India Division of Research and Development Lovely Professional University Phagwara Punjab India Department of Computer Science Shri Nehru Maha Vidayala College of Arts and Science Coimbatore Tamil Nadu India School of Architecture Koneru Lakshmaiah Educational Foundation Gundur Andhra Pradesh India

The solid waste management is the process of proper decomposition of waste materials within a period of time. This includes the collection of garbage's and then proceeded through certain measures for decomposition. There are various methods adopted in the garbage separation process. This includes the artificial intelligence techniques for the estimation and determination of the solid waste through automatic detection and separation of the garbage waste using control and sensing units. They are integrated with the internet of things to enable the two way communication system. This helps to visualize the functioning of the system adopting the digital platform. The proposed system is implemented through the smart dust bin held in every household that automatically senses the non-biodegradable and biodegradable waste materials. The classification of the waste materials are identified through the image processing techniques.

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The Mercedes water Cherenkov detector

arXiv

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arXiv 2022年

作者： Assis, P. Bakalová, A. Barres De Almeida, U. Brogueira, P. Conceição, R. De Angelis, A. Gibilisco, L. González, B.S. Guillén, A. La Mura, G. Mendes, L.M.D. Mendes, L.F. Pimenta, M. Shellard, R.C. Tomé, B. Vícha, J. Laboratório de Instrumentac ão e Física Experimental de Partículas Lisbon Portugal Universidade de Lisboa Lisbon Portugal Institute of Physics The Czech Academy of Sciences Prague Czech Republic Rio de Janeiro Brazil Università di Padova INFN INAF PadovaI-35131 Italy Computer Architecture and Technology Department University of Granada Granada Spain

The concept of a small, single-layer water Cherenkov detector, with three photomultiplier tubes (PMTs), placed at its bottom in a 120° star configuration (Mercedes Water Cherenkov Detector) is presen-ted. The PMTs are placed near the lateral walls of the stations with an adjustable inclination and may be in-stalled inside or outside the water volume. To illustrate the technical viability of this concept and obtain a first-order estimation of its cost, an engineering design was elaborated. The sensitivity of these stations to low energy Extensive Air Shower (EAS) electrons, photons and muons is discussed, both in compact and sparse array configurations. It is shown that the analysis of the intensity and time patterns of the PMT signals, using machine learning techniques, enables the tagging of muons, achieving an excellent gamma/hadron discrimination for TeV showers. This concept minimises the station production and maintenance costs, allowing for a highly exible and fast installation. Mercedes Water Cherenkov Detectors (WCDs) are thus well-suited for use in high-altitude large gamma-ray observatories covering an extended energy range from the low energies, closing the gap between satellite and ground-based measurements, to very high energy regions, beyond the PeV scale. Copyright © 2022, The Authors. All rights reserved.

关键词： Tellurium compounds

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A Biometric Entrance Guard Control System for Improving the Entrance Security of Intelligent Rental Housing 23rd

A Biometric Entrance Guard Control System for Improving the ...

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23rd International computer Symposium, ICS 2018

作者： Lin, Jerry Chao-Lee Lin, Jim-Min Chen, Vivien Yi-Chun Department of Information Engineering and Computer Science Feng Chia University Taichung Taiwan Department of Architecture Wuchang University of Technology Wuhan China Department of Architecture Fujian University of Technology No. 33 Xueyuan Road Minhou County FuzhouFujian China

ISBN: (纸本)9789811391897

With the rapid development of the information and communication technology, the security requirement of the entrance guard control systems has significantly increased. In recent years, the rise and popularity of various portable smart devices, including traditional keys, inductive buckles, inductive magnetic disks, biometrics, and so on. It has been already ripe that the biometrics, especially the finger-print identification technology from intelligence mobile phones, intelligence watches, etc., has matured and become an important member of an entrance guard control system. This research is to enhance the entrance guard control management in the traditional rental housing industry with a new generation of intelligent ultrasonic bio-metric entrance guard control system. In addition to preventing loss of cards and copy of keys, the research can also have the feature of achieving remotely monitor of the rental situation of a rented house. Even if it is not in the local area, the security of the rental house can be immediately controlled by the system to achieve the optimization result of the unattended intelligent lease access control system. Finally, the of goal of this study is to provide a convenient and safe living environment for rental houses. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Biometrics

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Multi-Objective Squirrel Search Algorithm for EEG Feature Selection

SSRN

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SSRN 2022年

作者： Wang, Chao Li, Songjie Shi, Miao Zhao, Jie Acharya, U. Rajendra Xie, Neng-Gang Cheong, Kang Hao College of Civil Engineering and Architecture Anhui Polytechnic University Anhui Wuhu241000 China Anhui Province Key Laboratory of Multidisciplinary Management and Control of Complex Systems Anhui Ma’anshan 243002 China Department of Management science and Engineering Anhui University of Technology Anhui Maanshan243002 China 8 Somapah Road Singapore487372 Singapore Department of Mechanical Engineering Anhui University of Technology Maanshan243002 China Department of Electronics and Computer Engineering Ngee Ann Polytechnic S599489 Singapore Department of Biomedical Engineering School of Science and Technology SUSS University Singapore Department of Biomedical Informatics and Medical Engineering Asia University Taichung Taiwan

Feature selection plays a critical role in the application of Brain computer Interface (BCI) systems. Many methods have been used to solve the feature selection problem, but they model it as a single-objective problem, considering only classification accuracy or number of features. To close this critical gap, we improve the squirrel search algorithm by combining it with the grid method, and propose a Multi-Objective Squirrel Search Algorithm (MOSSA) to solve the feature selection problem in BCI. We conduct experiments on three publicly available motion imagery datasets, and the experimental results reveal the best classification results of the method on dataset 1. The average classification accuracy of dataset 2 is 96.71%, with the number of selected features reduced to 18 on average. The highest classification accuracy of dataset 3 is 83.57% on the training set and 82.86% on the test set. In addition, we compare MOSSA with other algorithms and the results show the superiority of our proposed method in solving the feature selection problem. Finally, we combine MOSSA with an online application of BCI, where subjects visualise controlling the robot to perform the corresponding actions by the left and right hand movements. The average recognition rate of the three subjects is approximately 70%. In summary, the MOSSA is an effective method for solving the feature selection problem and is useful for the development of online © 2022, The Authors. All rights reserved.

关键词： Brain computer interface

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Corrigendum to “An analysis of urban sprawl growth and prediction using remote sensing and machine learning techniques” [J. S. Am. Earth Sci. Volume 142 , 15 August 2024, 104988]

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Journal of South American Earth Sciences 2025年 152卷

作者： Alanoud Al Mazroa Mashael Maashi Fadoua Kouki Kamal M. Othman Nahla Salih Mohamed Ahmed Elfaki Sabarunisha Begum S Department of Information Systems College of Computer and Information Sciences Princess Nourah bint Abdulrahman University (PNU) P.O. Box 84428 Riyadh 11671 Saudi Arabia Department of Software Engineering College of Computer and Information Sciences King Saud University Po box 103786 Riyadh 11543 Saudi Arabia Department of Financial and Banking Sciences Applied College at Muhail Aseer King Khalid University Saudi Arabia Department of Electrical Engineering College of Engineering and Islamic Architecture Umm Al-Qura University Makkah Saudi Arabia Department of Computer Science Applied College Imam Abdulrahman Bin Faisal University Saudi Arabia Department of Computer Science College of Computing and Information Technology Shaqra University Shaqra Saudi Arabia Department of Biotechnology P.S.R. Engineering College Sivakasi 626140 India

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OpenAPMax: Abnormal Patterns-based Model for Real-World Alzheimer’s Disease Diagnosis

arXiv

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arXiv 2023年

作者： Huang, Yunyou Guan, Xianglong Lu, Xiangjiang Liang, Xiaoshuang Miao, Xiuxia Xie, Jiyue Liu, Wenjing Ma, Li Tang, Suqin Zhang, Zhifei Zhan, Jianfeng The Key Lab of Education Blockchain and Intelligent Technology Ministry of Education The Guangxi Key Laboratory of Multi-Source Information Mining and Security Guangxi Normal University China The School of Electronic and Information Engineering School of Integrated Circuits Guangxi Normal University Guilin530015 China The Key Lab of Education Blockchain and Intelligent Technology Ministry of Education Guangxi Normal University China The State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing100086 China The Department of Physiology and Pathophysiology Capital Medical University Beijing100069 China The Guilin Medical University Guilin541001 China The Guangxi Key Lab of Multi-Source Information Mining & Security China

Alzheimer’s disease (AD) cannot be reversed, but early diagnosis will significantly benefit patients’ medical treatment and care. In recent works, AD diagnosis has the primary assumption that all categories are known a prior—a closed-set classification problem, which contrasts with the open-set recognition problem. This assumption hinders the application of the model in natural clinical settings. Although many open-set recognition technologies have been proposed in other fields, they are challenging to use for AD diagnosis directly since 1) AD is a degenerative disease of the nervous system with similar symptoms at each stage, and it is difficult to distinguish from its pre-state, and 2) diversified strategies for AD diagnosis are challenging to model uniformly. In this work, inspired by the concerns of clinicians during diagnosis, we propose an open-set recognition model, OpenAPMax, based on the anomaly pattern to address AD diagnosis in real-world settings. OpenAPMax first obtains the abnormal pattern of each patient relative to each known category through statistics or a literature search, clusters the patients’ abnormal pattern, and finally, uses extreme value theory (EVT) to model the distance between each patient’s abnormal pattern and the center of their category and modify the classification probability. We evaluate the performance of the proposed method with recent open-set recognition, where we obtain state-of-the-art results. Copyright © 2023, The Authors. All rights reserved.

关键词： Patient treatment

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