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multiple linear regression model for the prediction of Changma onset date in Korea

INTERNATIONAL JOURNAL OF CLIMATOLOGY 2014年第4期34卷 1000-1010页

作者： Choi, Ki-Seon Kang, Sung-Dae Kim, Hae-Dong Korea Meteorol Adm Natl Typhoon Ctr Cheju South Korea Keimyung Univ Dept Environm Conservat Taegu South Korea

In this research, the multiple linear regression models for the prediction of the Changma onset in Korea have been developed. The predictors are based on correlation analysis between Changma onset dates over 30years (1973-2002), and the winds and geopotential heights at high, middle, and low levels of the troposphere during the preceding 6months (December to May). The clearest correlation was observed at 850 hPa geopotential height field in the preceding April among 6months. The fundamental meaning of this model indicates that Changma in Korea comes earlier when the Mascarene high becomes languished and the tropical storms around India and western North Pacific subtropical high (WNPSH) become strengthened. The reliability of this model has been tested and proved by statistical cross-validation analysis, and additionally, has been analysed for differences in the 850 hPa stream flows for those years that Changma comes earlier and later. From the preceding April onwards, the Mascarene high tends to become weakened so that the cross-equatorial flow is strengthened along the African east coast. The cross-equatorial flow fortifies the tropical storms around Indian as it moves to the east. In the long run, the flow is influenced so that the WNPSH is more developed to the north, influencing Changma rain band to move north faster. To determine why Changma comes later in Korea, the water equivalent of accumulated snow depth (WEASD) difference between the late and early onset phases in the preceding April has been analysed. The result indicated that WEASD had a positive value for most East Asian regions. Since the snow reflects solar radiation by the Albedo effect, it decreases the difference in temperature between continents and oceans by decreasing the surface air temperature. The result has been confirmed by analysing the sensible heat net flux (SHTFL) difference between the two phases. In this way, small temperature gaps between continents and oceans weaken the WNPSH allow

关键词： Changma multiple linear regression model Mascarene high

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Candidate of low carbon economy concrete: Reinforcing recycled concrete via hybrid fibers

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ENVIRONMENTAL RESEARCH 2025年 276卷 121478页

作者： Tan, Chunlei Cai, Se Ding, Jianxiang Zhang, Xiaohui Han, Shangsong Su, Liuyue Li, Yahao Cui, Lisan Guangxi Univ Sci & Technol Sch Civil Engn & Architecture Energy Efficient & Storage Mat Lab Intelligent Environm Protect Bldg Mat Lab Liuzhou 545006 Peoples R China Hezhou Univ Coll Mat & Chem Engn Guangxi Key Lab Calcium Carbonate Resources Compre Hezhou 542899 Peoples R China China Three Gorges Univ Coll Elect Engn & New Energy Hubei Prov Collaborat Innovat Ctr New Energy Micro Yichang 443002 Hubei Peoples R China

Doping fibers are a highly effective method to rescue the weak mechanical properties of recycled concrete (RC). In this study, a complex three-dimensional network structure was constructed by using the unique arrangement and interweaving of three mixed fibers steel fiber (SF), glass fiber (GF), and coir fiber (CF). At the same time, along with the micro-aggregate reaction and pozzolanic reaction of fly ash (FA), the dual advantages of mixed fibers and FA were combined to enhance the mechanical properties of RC, reduce carbon emissions. The effects of FA, SF, GF, and CF on the mechanical properties of RC were discussed using a single-factor test and SEM analysis. An orthogonal test determined the optimal mix ratio, and the synergistic effect of FA, SF, GF, and CF on RC was discussed. Through multiple regression analysis, it was proved the correlation between the compressive strength and flexural strength of hybrid fiber reinforced recycled concrete (HFRC) and FA, SF, GF, and CF. A multiple regression model was proposed to predict the compressive strength and flexural strength of HFRC. Then, HFRCfilled steel tube members were used to measure the bi-directional deviatoric tensile properties to indicate material effectiveness. Finally, the carbon emissions of HFRC are calculated and analyzed. The results show that compared with the control group, the compressive and flexural strengths are increased by 61.68 % and 15.55 % when the mixing ratio is 1 % FA, 2 % SF, 1 % GF, and 1 % CF. The bearing capacity of HFRC-filled steel tube members under bidirectional bias load is 48.2 % higher than that of ordinary concrete-filled steel tube members. Finally, compared to the same dosage of manufactured sand, the use of construction waste groups reduced carbon emissions.

关键词： Recycled concrete Hybrid fibers Bi-directional bias pull multiple linear regression model Carbon emission calculation

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A Study of the Influencing Mechanism of Travel Mode Choice for Primary School Students: A Case Study in Wuhan

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BUILDINGS 2025年第5期15卷

作者： Chen, Shuting Hong, Mengyao Wei, Wei Wuhan Univ Sch Urban Design Wuhan 430072 Peoples R China

The motorization of school commutes reduces the physical activity of children and causes a series of urban traffic and social problems, such as traffic congestion in school districts and parents becoming necessary for transportation. To alleviate traffic jams and related social problems, as well as to encourage physical activity amongst students, we advocate non-motorized travel modes for students, such as walking and cycling. Based on a case study of the Wuhan East Lake High-Tech Development Zone, we use a multiple linear regression model to analyze the relationship between influence factors and student travel mode choices. The results show that built environment factors (the built environment factors are divided into density, diversity, accessibility, and destination) have a significant impact on school travel mode choices, especially accessibility and diversity. Furthermore, the study highlights the pivotal role of travel perceptions, particularly perceptions of safety, comfort, and convenience. Through a questionnaire survey, we collect students' travel perceptions and their actual school travel modes, which offer valuable insights for urban planners and policymakers. The findings indicate the complex interplay between student commuting and the built environment. Additionally, these findings can be valuable, both in academia and for policymakers. We provide strategies that could be beneficial for reducing motor vehicle activities (especially driving).

关键词： built environment "homo urbanicus" theory travel mode choice multiple linear regression model Wuhan

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Monitoring Dissolved Oxygen Concentrations in the Coastal Waters of Zhejiang Using Landsat-8/9 Imagery

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REMOTE SENSING 2024年第11期16卷 1951页

作者： Dong, Lehua Wang, Difeng Song, Lili Gong, Fang Chen, Siyang Huang, Jingjing He, Xianqiang Minist Nat Resources Inst Oceanog 2 State Key Lab Satellite Ocean Environm Dynam Hangzhou 310012 Peoples R China Southern Marine Sci & Engn Guangdong Lab Guangzhou Guangzhou 511400 Peoples R China Minist Nat Resources Daya Bay Observat & Res Stn Marine Risks & Hazards Hangzhou 310012 Peoples R China Marine Monitoring & Forecasting Ctr Zhejiang Prov Hangzhou 310012 Peoples R China Zhejiang Univ Ocean Coll Hangzhou 310027 Peoples R China

The Zhejiang coastal waters (ZCW), which exhibit various turbidity levels, including low, medium, and high turbidity levels, are vital for regional ecological balance and sustainable marine resource utilization. Dissolved oxygen (DO) significantly affects marine organism survival and ecosystem health, yet there is limited research on remote sensing monitoring of DO in the ZCW, and the underlying mechanisms are unclear. This study addresses this gap by utilizing high-resolution Landsat 8/9 imagery and sea surface temperature (SST) data to develop a multiple linear regression (MLR) model for DO estimation. Compared to previous studies that utilize remote sensing band reflectance data as inputs, the results show that the red and blue bands are more suitable for establishing DO inversion models for such water bodies. The model was applied to analyze variations in the DO concentrations in the ZCW from 2013 to 2023, with a focus on Hangzhou Bay (HZB), Xiangshan Bay (XSB), Sanmen Bay (SMB), and Yueqing Bay (YQB). The temporal and spatial distributions of DO concentrations and their relationships with environmental factors, such as chlorophyll-a (Chl-a) concentrations, total suspended matter (TSM) concentrations, and thermal effluents, are analyzed. The results reveal significant seasonal fluctuations in DO concentrations, which peak in winter (e.g., 9.02 mg/L in HZB) and decrease in summer (e.g., 6.83 mg/L in HZB). Changes in the aquatic environment, particularly in the thermal effluents from the Sanmen Nuclear Power Plant (SNPP), significantly decrease coastal dissolved oxygen (DO) concentrations near drainage outlets. Chl-a and TSM directly or indirectly affect DO concentrations, with notable correlations observed in XSB. This study offers a novel approach for monitoring and managing water quality in the ZCW, facilitating the early detection of potential hypoxia issues in critical zones, such as nuclear power plant heat discharge outlets.

关键词： dissolved oxygen multiple linear regression model Zhejiang coastal waters Landsat 8/9

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An assessment of how street view imagery and remote-sensing data of green and blue spaces can explain variations in housing prices: a case study in Suzhou, China

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REMOTE SENSING LETTERS 2024年第12期15卷 1209-1217页

作者： Zhu, Jin Liu, Changchang Yu, Cheng Du, Jinglong Suzhou Univ Sci & Technol Sch Geog Sci & Geomatics Engn Suzhou Peoples R China Suzhou Univ Sci & Technol Sch Environm Sci & Engn Suzhou Peoples R China

Urban blue and green spaces have significant influences on housing prices. In this study, we employed three data sources of blue and green space data sources (street view images, remote-sensing indicators, and land use data) and compared the variations of the three data sources of data in housing prices in Suzhou, China. The Spearman correlation showed street view data and remote sensing data reflect different perspectives of blue and green spaces. In terms of green spaces, street view greenery demonstrated the highest explanatory power for housing prices. This finding suggests that residents favour street greenery than Normalized Difference Vegetation Index (NDVI) and green space land use data. Regarding blue spaces, Normalized Difference Water Index (NDWI) exhibited the highest explanatory power for housing prices. This can be attributed to the fact that NDWI effectively captures water bodies around residential areas. The findings of this study have significant implications for urban planning and real estate development.

关键词： Blue and green spaces housing prices multiple linear regression model street view imagery NDVI

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Optical Properties Prediction for Red and Near-Infrared Emitting Carbon Dots Using Machine Learning

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SMALL 2024年第29期20卷 2310402-2310402页

作者： Tuchin, Vladislav S. Stepanidenko, Evgeniia A. Vedernikova, Anna A. Cherevkov, Sergei A. Li, Di Li, Lei Doering, Aaron Otyepka, Michal Ushakova, Elena V. Rogach, Andrey L. ITMO Univ Int Res & Educ Ctr Phys Nanostruct St Petersburg 197101 Russia Jilin Univ Coll Mat Sci & Engn Changchun 130012 Peoples R China City Univ Hong Kong Dept Mat Sci & Engn Hong Kong 999077 Peoples R China City Univ Hong Kong Ctr Funct Photon CFP Hong Kong 999077 Peoples R China VSB Tech Univ Ostrava IT4Innovat 17 Listopadu 2172-15 Ostrava 70800 Czech Republic Palacky Univ Olomouc Czech Adv Technol & Res Inst CATRIN Reg Ctr Adv Technol & Mat RCPTM Slechtitelu 27 Olomouc 78371 Czech Republic

Functional nanostructures build up a basis for the future materials and devices, providing a wide variety of functionalities, a possibility of designing bio-compatible nanoprobes, etc. However, development of new nanostructured materials via trial-and-error approach is obviously limited by laborious efforts on their syntheses, and the cost of materials and manpower. This is one of the reasons for an increasing interest in design and development of novel materials with required properties assisted by machine learning approaches. Here, the dataset on synthetic parameters and optical properties of one important class of light-emitting nanomaterials - carbon dots are collected, processed, and analyzed with optical transitions in the red and near-infrared spectral ranges. A model for prediction of spectral characteristics of these carbon dots based on multiple linear regression is established and verified by comparison of the predicted and experimentally observed optical properties of carbon dots synthesized in three different laboratories. Based on the analysis, the open-source code is provided to be used by researchers for the prediction of optical properties of carbon dots and their synthetic procedures. The dataset on synthetic parameters and optical properties of red and near-infrared emitting carbon dots are collected, processed, and analyzed. A model for prediction of spectral characteristics of these carbon dots is established as open-source code and experimentally validated in three different laboratories, and it can be accessed by researchers for the prediction of carbon dots properties. image

关键词： carbon dots luminescence machine learning multiple linear regression model quantum yield

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Numerical study on wave run-up and forces on a fixed cylinder under linear and nonlinear focused waves

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OCEAN ENGINEERING 2024年 300卷

作者： Zhang, Huidong Wang, Tong Chen, Lixian Shi, Hongda Soares, C. Guedes Ocean Univ China Coll Engn Dept Ocean Engn Qingdao 266100 Peoples R China Ocean Univ China Shandong Prov Key Lab Ocean Engn Qingdao 266100 Peoples R China Univ Lisbon Ctr Marine Technol & Engn CENTEC Inst Super Tecn Lisbon Portugal

To study the difference between wave run-up and wave forces on a fixed column under the action of focused waves formed with different physical mechanisms, a 3D two-phase numerical wave tank is developed based on the Navier-Stokes equation and the Finite Volume Method. The influences of wave nonlinearity, column radius and water depth on the run-up and force discrepancies are systematically investigated in four sets of numerical experiments. For focused waves with identical crest height and trough-to-trough period, the run-up height and dynamic pressure around the circumference of a cylinder are mostly larger in linear focused waves than in nonlinear focused waves, due to their different hydrodynamic characteristics. With the increased wave nonlinearity either by changing the period or crest height of the focused waves, the discrepancies become greater for run-up height while smaller for dynamic pressure. Moreover, both of them, less affected by water depth, are more sensitive to the variation of column radius in linear focused waves, showing a steeper gradient in space. Therefore, in practical engineering, the physical generation mechanism must be considered in evaluating the safety of columns of wind turbines hit by freak waves.

关键词： Wave run-up Wave force multiple linear regression model linear and nonlinear focused waves Wave generation mechanism

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A comprehensive evaluation of influencing factors of neonicotinoid insecticides (NEOs) in farmland soils across China: First focus on film mulching

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JOURNAL OF HAZARDOUS MATERIALS 2024年 470卷 134284页

作者： Hou, Jie Wang, Lixi Wang, Jinze Chen, Liyuan Han, Bingjun Li, Yujun Yu, Lu Liu, Wenxin Peking Univ Coll Urban & Environm Sci Key Lab Earth Surface Proc Beijing 100871 Peoples R China Nanjing Forestry Univ Coll Ecol & Environm Coinnovat Ctr Sustainable Forestry Southern China Nanjing 210037 Peoples R China

Neonicotinoid insecticide (NEO) residues in agricultural soils have concerning and adverse effects on agroecosystems. Previous studies on the effects of farmland type on NEOs are limited to comparing greenhouses with open fields. On the other hand, both NEOs and microplastics (MPs) are commonly found in agricultural fields, but their co-occurrence characteristics under realistic fields have not been reported. This study grouped farmlands into three types according to the covering degree of the film, collected 391 soil samples in mainland China, and found significant differences in NEO residues in the soils of the three different farmlands, with greenhouse having the highest NEO residue, followed by farmland with film mulching and farmland without film mulching (both open fields). Furthermore, this study found that MPs were significantly and positively correlated with NEOs. As far as we know this is the first report to disclose the association of film mulching and MPs with NEOs under realistic fields. Moreover, multiple linear regression and random forest models were used to comprehensively evaluate the factors influencing NEOs (including climatic, soil, and agricultural indicators). The results indicated that the random forest model was more reliable, with MPs, farmland type, and total nitrogen having higher relative contributions.

关键词： Neonicotinoid insecticides Microplastics Influencing factors multiple linear regression model Random Forest model

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Using Sensor Errors to Define Autonomous System Situational Awareness

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IEEE ACCESS 2024年 12卷 193763-193781页

作者： Costello III, Donald H. Cienfuegos, Paola Jaramillo Xu, Huan Univ Maryland A James Clark Sch Engn MATRIX Lab College Pk MD 20619 USA US Naval Acad Weap Robot & Control Engn Dept Annapolis MD 21402 USA Univ Maryland Inst Syst Res Aerosp Engn College Pk MD 20742 USA

Autonomous uncrewed aerial systems (UASs) are expected to operate without a human being in or on the loop. As there will not be a human to interpret the environment, the autonomous UAS is expected to make aeronautical decisions based on situational awareness (SA). This is a limiting factor in the field of truly autonomous systems. Before we can field systems that function without human oversight, we need methods to evaluate whether the SA of that system has been established. This study uses a hypothetical scenario and subject matter expert (SME) opinion to establish a quantifiable metric for SA within an established United States Department of Defense recognized modeling and simulation (M&S) environment. Within this environment, it is assumed that all errors within the UAS sensor suite are known. Through the M&S environment, we were able to vary six separate error variables, with three unique values to provide a total of 729 different data points to be analyzed in our attempt to develop predictive equations. Each data point was evaluated 2,000 times, which gave us a dataset consisting of over 1.4 million individual simulations. From the dataset, we developed linear and nonlinear statistical models to define a point where the SA formed by the UAS is no longer valid for making a sound aeronautical decision. We developed objective measures (inequalities) for the subjective end (SA) through both linear and nonlinear analyses. The M&S environment may not be a direct duplication of reality;however, the results of this study may influence how future autonomous UASs are fielded. This study demonstrates that if a point can be defined where an UAS possesses sufficient SA, decision-makers (Subject Matter Experts in this case) would permit the UAS to make decisions currently reserved for fully qualified human operators.

关键词： Aircraft Certification Military aircraft Robot sensing systems Monitoring linear regression Degradation Current measurement Atmospheric modeling US Department of Defense Autonomous systems autonomy certification military applications generalized additive model multiple linear regression model

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Decadal trends and predictive insights into aquatic ecosystem health in the Namhan River, South Korea: Longitudinal analysis of hydro-environmental factors and stream health indices (2008-2022)

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ENVIRONMENTAL POLLUTION 2024年第Pt 2期363卷 125184页

作者： Cho, Hemie Fabian, Pamela Sofia Lee, Sang-Hoon You, Kyung-A Kwon, Hyun-Han Sejong Univ Dept Civil & Environm Engn Seoul South Korea Natl Inst Environm Res Water Environm Res Dept Water Environm Engn Res Div Incheon South Korea

The main focus of this study is to explore the complex interactions between aquatic ecosystem health (AEH) and time-varying hydro-environmental factors. We measure AEH in the Namhan River of South Korea using stream health index (SHI) scores for the trophic diatom index (TDI), benthic macroinvertebrate index (BMI), and fish assessment index (FAI) for 2008 to 2022. Key hydro-environmental variables associated with AEH, including their time-lagged responses, are identified. Water quality parameters such as chemical oxygen demand (COD) are significantly and negatively correlated with TDI (r = - 0.68), BMI (r = - 0.87), and FAI (r = - 0.70), highlighting the critical role of water quality in the sensitivities of diatoms, macroinvertebrates, and fish health. The apparent response lag of aquatic ecosystems to hydrological parameters, such as a one-year-lagged correlation of BMI with mean flow (r = 0.74) and annual flow anomalies (r = 0.73), suggests their potential use as predictors in AEH models. A longitudinal analysis of SHIs over a decade showed consistent changes in AEH from upstream to downstream, with notable trends in the deterioration and improvement of SHIs in different areas. The upstream TDI and BMI deteriorated, while the upstream FAI improved. A multiple-linear-regression-based predictive model demonstrated efficacy in predicting AEH under various hydro-environmental conditions, achieving R2 values up to 0.85 for BMI and also has the potential to simulate the impacts of anticipated climatic and hydrological changes.

关键词： Hydro-environmental factors Longitudinal analysis Stream health indices Water quality multiple linear regression model

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