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Improved Hungarian algorithm-based task scheduling optimization strategy for remote sensing big data processing

地球空间信息科学学报（英文版） 2024年第4期27卷 1141-1154页

作者： Sheng Zhang Yong Xue Heng Zhang Xiran Zhou Kaiyuan Li Runze Liu School of Environment and Spatial Informatics China University of Mining and TechnologyXuzhouChina School of Environment and Spatial Informatics China University of Mining and TechnologyXuzhouChina School of Computing and Engineering University of DerbyDerbyUK Artificial Intelligence Research Institute China University of Mining and TechnologXuzhouChina Shandong Province Institute of Land Surveying and Mapping JinanChina School of Environment and Spatial Informatics China University of Mining and TechnologyXuzhouChina Artificial Intelligence Research Institute China University of Mining and TechnologXuzhouChina

With the development of remote sensing technology and computing science,remote sensing data present typical big data *** rapid development of remote sensing big data has brought a large number of data processing tasks,which bring huge challenges to *** computing is the primary means to process remote sensing big data,and task scheduling plays a key role in this *** study analyzes the characteristics of batch processing of remote sensing big *** paper uses the Hungarian algorithm as a basis for proposing a novel strategy for task assignment optimization of remote sensing big data batch workflow,called optimal sequence dynamic assignment algorithm,which is applicable to hetero-geneously distributed computing *** strategy has two core contents:the improved Hungarian algorithm model and the multi-level optimal assignment task queue ***,the strategy solves the dependency,mismatch,and computational resource idleness problems in the optimal scheduling of remote sensing batch processing *** proposed strategy likewise effectively improves data processing efficiency without increasing computer hardware resources and without optimizing the computational *** experimented with the aerosol optical depth retrieval algorithm workflow using this *** with the processing before optimization,the makespan of the proposed method was shortened by at least 20％.Compared with popular scheduling algorithm,the proposed method has evident competitiveness in acceleration effect and large-scale task scheduling.

关键词： Workflow Hungarian algorithm optimal assignment remote sensing big data large-scale task

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Performance of single PN/A reactor under wide fluctuation of nitrogen load

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environmental science and Pollution Research 2024年第47期31卷 58083-58092页

作者： Yang, Daxin Zhang, Chuanyi Ge, Sijie Xie, Yaqi Yuan, Limei School of Environment and Spatial Informatics China University of Mining and Technology Jiangsu Xuzhou221116 China

Partial nitritation-anammox (PN/A) is a cost-effective technology in high ammonia–nitrogen wastewater treatment. However, PN/A is prone to instability as the ammonia–nitrogen sharply fluctuates. In this study, a packed bed reactor is employed to construct a single-stage PN/A system to investigate the operational characteristics and explore the denitrification mechanism. The effluent NH4+-N concentration, ammonia nitrogen removal rate (ARE), and total nitrogen removal rate (TNR) could be sustained at about 60 mg/L, 80%, and over 70%, respectively, when the influent nitrogen load rate (NLR) is changed from 0.733 to 0.879 kg-N/m3/day. Both ARE and TNR are decreased when NLR continues increasing to 1.026 kg-N/m3/day. The influent NLR decreases from 0.879 to 0.147 kg-N/m3/day, and ARE and TNR reached 98% and 85.4%, respectively. Therefore, the denitrification effect of the reactor could be recovered, and the excellent nitrogen removal capacity could be obtained within a wide range of influent NLR. Moreover, the high-throughput sequencing and metagenomic testing indicate that the Proteobacteria and Planctomycetes that the PN/A functional strains (i.e., ammonia-oxidizing bacteria (AOB) and anammox bacteria (AnAOB)) account for 38.8% in the sludge. The relative abundance of Nitrospira containing the nitrite-oxidizing bacteria (NOB) has dropped to 0.01%, and the functional gene nxr of the nitrite oxidation process is also inhibited. The relative expression of the functional gene is dominated by the short-range nitritation and anammox oxidation, which demonstrates that the nitrogen removal is mainly dominated by nitritation-anammox. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Ammonia

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Photocatalytic degradation of organophosphorus flame retardants in aqueous solutions: a review and future prospects

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environmental science and Pollution Research 2024年第40期31卷 52707-52723页

作者： Xu, Zihui Zhang, Lucheng Wang, Tingting Zhang, Mingqing Kang, Gang Wu, Shilong Liu, Bingfeng School of Environment and Spatial Informatics China University of Mining & ampTechnology Xuzhou221116 China

The widespread use of organophosphorus flame retardants (OPFRs) in industrial and household products increases the risk of their environmental exposure, posing a serious threat to ecosystems and human health. Photocatalytic technology has been widely used in wastewater treatment due to its high efficiency, mild reaction conditions, and robustness. This review summarizes the current status of research on photocatalytic degradation of OPFRs, focusing on the effect of different types of catalysts on the degradation efficiency, the effects of pH, and co-existing inorganic and organic ions. And pH and co-existing inorganic mainly affect the active oxygen and the active surface sites of the catalyst. In addition, toxicological calculations of the intermediates of the degradation pathway using T.E.S.T. and ECOSAR showed that photocatalysis could effectively reduce the toxicity of OPFRs. Development of new photocatalytic materials, in-depth study of the degradation mechanism of different catalysts and flame retardants, and attention to practical applications and toxicity issues can be the development direction of future research. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Wastewater treatment

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Merging TROPOMI and eddy covariance observations to quantify 5-years of daily CH_(4) emissions over coal-mine dominated region

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International Journal of Coal science & technology 2024年第4期11卷 225-237页

作者： Wei Hu Kai Qin Fan Lu Ding Li Jason B.Cohen Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization School of Environment and Spatial InformaticsChina University of Mining and TechnologyXuzhou 221116China

A simple and flexible mass balance approach was applied to observations of XCH_(4)from TROPOMI to estimate CH_(4)emissions over Shanxi Province,including the impacts of advective transport,pressure transport,and atmospheric ***-frequency eddy-covariance flux observations were used to constrain the driving terms of the mass balance *** equation was then used to calculate day-to-day and 5 km×5 km grided CH_(4)emissions from May 2018 to July 2022 based on TROPOMI RPRO column CH_(4)*** Shanxi-wide emissions of CH_(4),126±58.8 ug/m^(2)/s,shows a fat tail distribution and high variability on a daily time scale(the 90th percentile is 2.14 times the mean and 2.74 times the median).As the number of days in the rolling average increases,the change in the variation decreases to 128±35.7 ug/m^(2)/s at 10-day,128±19.8 ug/m^(2)/s at 30-day and 127±13.9 ug/m^(2)/s at *** range of values of the annual mean emissions on coal mine grids within Shanxi for the years 2018 to 2022 was 122±58.2,131±71.2,111±63.6,129±87.1,and 138±63.4 ug/m^(2)/s,*** 5-year average emissions from TROPOMI are 131±68.0 ug/m^(2)/s versus 125±94.6 ug/m^(2)/s on the grids where the EDGAR bottom-up database also has data,indicating that those pixels with mines dominate the overall emissions in terms of both magnitude and *** results show that high-frequency observation-based campaigns can produce a less biased result in terms of both the spatial and temporal distribution of CH_(4)emissions as compared with approaches using either low-frequency data or bottom-up databases,that coal mines dominate the sources of CH_(4)in Shanxi,and that the observed fat tail distribution can be accounted for using this approach.

关键词： Methane TROPOMI Coal mine Mass balance equation

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Remediation of phenanthrene contaminated soil by persulphate coupled with Pseudomonas aeruginosa GZ7 based on oxidation prediction model

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environmental science and Pollution Research 2024年第31期31卷 44415-44430页

作者： Yao, Zhenxian Zhou, Xiangyuan Jin, Tao Wang, Liping Liu, Na Wu, Lin Institute Name: School of Environment Science and Spatial Informatics China University of Mining and Technology No.1 Daxue Road Xuzhou Jiangsu221116 China

Chemical oxidation coupled with microbial remediation has attracted widespread attention for the removal of polycyclic aromatic hydrocarbons (PAHs). Among them, the precise evaluation of the feasible oxidant concentration of PAH-contaminated soil is the key to achieving the goal of soil functional ecological remediation. In this study, phenanthrene (PHE) was used as the target pollutant, and Fe2+-activated persulphate (PS) was used to remediate four types of soils. Linear regression analysis identified the following important factors influencing remediation: PS dosage and soil PHE content for PHE degradation, Fe2+ dosage, hydrolysable nitrogen (HN), and available phosphorus for PS decomposition. A comprehensive model of "soil characteristics-oxidation conditions-remediation effect" with a high predictive accuracy was constructed. Based on model identification, Pseudomonas aeruginosa GZ7, which had high PAHs degrading ability after domestication, was further applied to coupling repair remediation. The results showed that the optimal PS dose was 0.75% (w/w). The response relationship between soil physical, chemical, and biological indicators at the intermediate interface and oxidation conditions was analysed. Coupled remediation effects were clarified using microbial diversity sequencing. The introduction of Pseudomonas aeruginosa GZ7 stimulated the relative abundance of Cohnella, Enterobacter, Paenibacillus, and Bacillus, which can promote material metabolism and energy transformation during remediation. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Soils

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Machine Learning-Based Soil Moisture Retrieval Using CYGNSS and Interpolated SMAP Data

Machine Learning-Based Soil Moisture Retrieval Using CYGNSS ...

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2024 Mid-term Symposium on spatial Information to Empower the Metaverse

作者： Zhang, Kun Yu, Kegen Xu, Nianfu Wang, Changyang Lin, Yiruo School of Environment Science and Spatial Informatics China University of Mining and Technology Xuzhou China

Soil moisture is a crucial component of the global terrestrial ecosystem water vapor cycle, and higher spatial-temporal soil moisture product has significant impacts on research in agriculture, hydrology, and ecology. Spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) is a new remote sensing technology which can be used to retrieve soil moisture. Cyclone Global Navigation Satellite System (CYGNSS), launched by NASA in 2016 to observe ocean surface hurricanes, has also collected a substantial amount of data of GNSS signals reflected over the land. This paper focuses on soil moisture retrieval using CYGNSS and SMAP dataset. In this study, three machine learning methods (GSVM, BP and RF) are used for spatial interpolation of SMAP soil moisture data. Result shows RF interpolation is the best with the RMSE of 0.044 cm3/cm3 and the CC of 0.959 compared with SMAP truly SM. Then soil moisture data after RF interpolation and conventional linear interpolation are respectively used as response variables to train the retrieval model by ELM, BP and RF machine learning methods respectively. Results show that, among the six regression models, the RF-RF regression model performs the best with the RMSE of 0.012 cm3/cm3 and the CC of 0.986. Using this model, we get a global soil moisture product and have higher temporal and spatial resolution. © Author(s) 2024.

关键词： NASA

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Synergistic degradation of Tris (2-Chloroethyl) Phosphate (TCEP) by US/Fenton system: Experimental, DFT calculation and toxicity evaluation

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environmental science and Pollution Research 2024年第27期31卷 39120-39137页

作者： Zhang, Lucheng Wang, Tingting Zhang, Mingqing Liu, Qi She, Yi Wu, Shilong Liu, BingFeng School of Environment and Spatial Informatics China University of Mining & ampTechnology Xuzhou221116 China School of Low-Carbon Energy and Power Engineering China University of Mining & ampTechnology Xuzhou221116 China

Organophosphorus esters (OPEs), exemplified by tris (2-chloroethyl) phosphate (TCEP), find extensive application in diverse industries such as construction materials, textiles, chemical manufacturing, and electronics, consequently resulting in an increased concentration of these compounds in industrial wastewater. The fundamental objective of this investigation was to examine the degradation of TCEP through the implementation of US/Fenton oxidation techniques in a solution. The findings revealed that the US/Fenton system effectively facilitated the degradation of TCEP, with the Chan kinetic model precisely elucidating the degradation process. Under optimized reaction conditions, the degradation efficiency of TCEP reached an impressive 93.18%. However, the presence of common co-existing aqueous substrates such as Cl−, HCO3−, H2PO4−, and HA hindered the degradation process. Bursting tests and electron paramagnetic resonance (EPR) studies affirmed ∙OH oxidation as the principal mechanism underlying TCEP degradation. Detailed degradation pathways for TCEP were established through the utilization of density-functional theory (DFT) calculations and GC/MS tests. Moreover, the ecotoxicological evaluation of TCEP and its intermediates was conducted using the Toxicity Estimation Software Tool (T.E.S.T.). © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Toxicity

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Evaluation of nonwoven geotextile drainage performance and experimental simulation of key processes in Yellow River sediment-backfilled reclaimed coal-mined subsided lands

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International Journal of Agricultural and Biological Engineering 2024年第6期17卷 193-201页

作者： Huang Sun Zhenqi Hu Deyun Song Shuai Wang Yi Yu Institute of Land Reclamation and Ecological Restoration China University of Mining and Technology-BeijingBeijing 100083China School of Environment and Spatial Informatics China University of Mining and TechnologyXuzhou 221116JiangsuChina

The innovative utilization of Yellow River sediment to reclaim coal-mined subsided lands addresses dual environmental challenges by offering a sustainable remediation ***,efficient water drainage constitutes a significant hurdle in this *** strategic placement of nonwoven geotextile at the tail end of the fill sections has ameliorated fine sediment loss and drainage efficacy *** study assesses various nonwoven geotextile grades for their effectiveness in moisture expulsion,integrating comprehensive evaluations and simulation tests of pivotal *** findings reveal that selected nonwoven geotextiles(N1,N2,T1,T2,T3,T4)demonstrate appropriate apparent opening size(AOS)and permeability,coupled with clogging resistance,aligning with theoretical criteria for soil conservation,water permeation,and blockage *** to the nonwoven geotextile’s clogging are factors such as apparent opening size(AOS),thickness,permeability,load capacity,gradient ratio(GR),and sediment retention-all requiring meticulous selection for real-world *** choice of nonwoven geotextile in the drainage of Yellow River sediment reclaimed lands must hinge on a holistic assessment framework,encompassing retention,permeability,anti-clogging attributes,and additional performance metrics,to ensure that the materials fulfill the specific technical standards while remaining *** study provides valuable insights into the selection and application of geotextiles in Yellow River sediment-backfilled reclamation drainage projects,contributing to the advancement of mine ecological restoration practices,particularly in the context of Yellow River sediment-backfilled reclamation projects.

关键词： nonwoven geotextile drainage performance Yellow River sediment coal-mined subsided land filling reclamation engineering construction

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Enhanced Genetic Algorithm-Based Wi-Fi Access Points Deployment for RTT Positioning: Fitness Function Design and Analysis 14

Enhanced Genetic Algorithm-Based Wi-Fi Access Points Deploym...

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14th International Conference on Indoor Positioning and Indoor Navigation - Work-in Progress Papers, IPIN-WiP 2024

作者： Sun, Meng Wang, Yunjia Zheng, Nanshan Wang, Qianxin Chen, Guoliang Li, Zengke School of Environment and Spatial Informatics China University of Mining and Technology Xuzhou221116 China

Wi-Fi ranging positioning based on round-trip time (RTT) measurement is influenced by complex environments and the deployment of access points (AP). This work proposes an enhanced genetic algorithm (EGA)-based strategy for Wi-Fi AP deployment and analyzes the performance of the EGA-based framework by designing fitness functions using Cramer-Rao lower bound (CRLB), simulated localization error and measurement errors of Wi-Fi RTT and received signal strength (RSS). Simulation experiments are conducted to compare RTT ranging positioning using different Wi-Fi AP layouts generated by the EGA algorithm configured with various fitness functions. The results show that designing a fitness function based on simulated localization error provides the optimal Wi-Fi AP deployment strategy, leading to the best positioning accuracy with considerable time complexity compared to fitness functions based on CRLB and RTT/RSS measurement errors. © 2024 Copyright for this paper by its authors.

关键词： Genetic algorithms

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Weakly supervised segmentation for plant disease using class activation maps and weak annotation labels

Weakly supervised segmentation for plant disease using class...

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2022 International Conference on Geographic Information and Remote Sensing technology, GIRST 2022

作者： Chen, Shuo Zhang, Kefei Wu, Suqin Tang, Ziqian Zhao, Yindi Sun, Yaqin School of Environment and Spatial Informatics China University of Mining and Technology Xuzhou China

ISBN: (纸本)9781510662186

The segmentation of crop disease is an important task for plant image processing. Fully supervised segmentation methods are commonly used to segment disease on plant leaves, and a large amount of manually annotated information is needed. In contrast, weakly supervised segmentation methods have the advantages of reducing the workload of manual annotation. In this study, a weakly supervised segmentation method for plant disease was proposed for the segmentation of rust in apple rust images using the procedure below. A classification model was trained using images of both diseased and healthy leaves, and class activation maps (CAMs) of disease were obtained as pseudo labels for a further segmentation of the disease. The segmentation method using CAMs only achieved an Intersection over Union (IoU) score of 0.45. Then point-auxiliary labels and line-auxiliary labels of disease were also constructed to improve the accuracy of the disease segmentation. The IoU values resulting from the two schemes - the point-auxiliary labels + CAMs and line-auxiliary labels + CAMs methods reached 0.64 and 0.74, respectively. Moreover, the proposed method was also applied to the segmentation of disease on whole leaves. Furthermore, the proportion of disease in whole leaves can be also obtained, and the coefficient of the correlation between the obtained disease proportion and true disease proportion was 0.89. The results suggest the feasibility of the proposed method to segment plant disease and evaluate the severity degree of the plant disease. © 2023 SPIE.

关键词： Semantic Segmentation

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