Article
Urban Studies
Zhenshan Yang, Di Wu, Dawei Wang
Summary: The notion of path dependence is utilized to understand the dynamics of industrial space, with a focus on spatial path dependence in this paper. Through the use of big data technology, the study quantifies spatial distribution and examines spatial path dependence in information service industries in Beijing during 2008 and 2013. The findings reveal the existence of spatial path dependence in these industries during the two periods, highlighting the importance of considering previous spatial distribution in future spatial planning.
Article
Computer Science, Information Systems
Abraham Noah Wu, Filip Biljecki
Summary: This research presents a new method for creating spatial data using a generative adversarial network. By utilizing coarse and widely available geospatial data, it is able to generate maps of less available features in the built environment. The method enables the translation of geospatial datasets with high fidelity and has the potential to fill in missing or incomplete data in various applications.
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
(2022)
Article
Geochemistry & Geophysics
Xin Lin, Shoufa Lin, Domenico Cicchella, Wensheng Yao, Hanjiang Pan, Zhizhong Cheng, Ganggang Meng
Summary: Terrane recognition and boundary identification are crucial for understanding continental tectonics. However, discrepant interpretations of terranes and boundaries are still common in South China. In this study, a large geochemical dataset was used to characterize proposed terranes and locate their boundaries. Data mining techniques were applied to extract valuable information, and the results showed distinct geochemical patterns at regional and terrane scales. The defined boundaries were supported by geophysical, Nd isotopic, and geological evidence, providing better insights into the origin and assembly of South China.
JOURNAL OF GEOCHEMICAL EXPLORATION
(2022)
Article
Geosciences, Multidisciplinary
Minu Treesa Abraham, Neelima Satyam, Prashita Jain, Biswajeet Pradhan, Abdullah Alamri
Summary: This study evaluated the impacts of spatial resolution and data splitting on the performance of different machine learning algorithms for landslide modeling, with results indicating that these factors affected the algorithms differently.
GEOMATICS NATURAL HAZARDS & RISK
(2021)
Article
Environmental Sciences
Sahar Amiri-Doumari, Ahmadreza Karimipour, Seyed Nader Nayebpour, Javad Hatamiafkoueieh
Summary: The study used a combination of optimization algorithms and data handling methods to delineate groundwater potential zones in Boroujen, Iran. Factors such as rainfall, land use/cover, and altitude were found to play a significant role in groundwater assessment.
ENVIRONMENTAL EARTH SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Hanrong Zheng
Summary: This article builds a map symbol library and formulates data processing rules based on ArcGIS software, and designs a high-resolution GIS image flowchart. Adding jump connections to the convolutional neural network can effectively improve the performance of the overall network model. By utilizing the advantages of jump connections in convolutional neural networks, a more dense connection network is proposed through multiple uses and improvements. It also designs a wetland park environmental data monitoring platform and analyzes and processes the data based on the wetland park environmental monitoring indicators. The research results indicate that the proposed algorithm retrieves most high-frequency information without adding too much noise, and the model outperforms other super-resolution reconstruction algorithms in terms of visual effects in remote sensing image reconstruction.
Article
Computer Science, Artificial Intelligence
Hongquan Gui, Jialan Liu, Chi Ma, Mengyuan Li
Summary: The thermal error can reduce the machining accuracy of machine tools and needs to be effectively controlled. Previous studies mainly focused on the temporal feature of the thermal error and ignored the spatial feature. To address these challenges, a new dynamic TS memory graph convolutional network (DTSMGCN) model is proposed in this study to learn the dynamic TS features of the thermal error.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Environmental Sciences
Guoqing Liu, Alireza Arabameri, M. Santosh, Omid Asadi Nalivan
Summary: A new modeling approach was used to map gully erosion susceptibility in the Golestan Dam basin of Iran. The study identified distance from the stream, elevation, distance from the road, and vertical distance of the channel network as the most important factors affecting gully erosion. The results can provide valuable guidelines for choosing machine learning methods in regions without a complete gully inventory.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Bin Zhu, Jie Zhou
Summary: This paper builds a virtual urban planning design model based on GIS big data technology and machine learning algorithms, proposing a solution that combines multiple features. The research results demonstrate that using multiple features can better express ground object information, while using the ELM method and extreme learning machine classification algorithm can improve classification accuracy and planning score.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
J. Armando Barron-Lugo, Jose Luis Gonzalez-Compean, Jesus Carretero, Ivan Lopez-Arevalo, Raffaele Montella
Summary: This paper presents a novel processing model for building environmental big data services in the cloud, with transversality, infrastructure-agnosticism, and generality. By deploying processing structures in edge, fog, and cloud environments, and embedding analytics and machine learning, it supports automatic conversion into big data services.
ENVIRONMENTAL MODELLING & SOFTWARE
(2021)
Review
Agriculture, Dairy & Animal Science
Giovanni Franzo, Matteo Legnardi, Giulia Faustini, Claudia Maria Tucciarone, Mattia Cecchinato
Summary: In the future, the demand for poultry meat and eggs is predicted to increase with population growth. This expansion brings both opportunities and challenges such as pollution, competition for resources, animal welfare concerns, and infectious diseases. Optimization and increased efficiency are needed in poultry production, and the use of big data offers the opportunity to develop tools to maximize farm profitability and reduce impacts. Sensor technologies and advanced statistical techniques are discussed, as well as the progress in pathogen genome sequencing and analysis.
Article
Environmental Sciences
Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Soo-Mi Choi
Summary: This study utilized three ensemble machine learning algorithms to model asthma-prone areas in Tehran, Iran. Factors influencing asthma occurrence, such as distance to the street, NDVI, and traffic volume, were identified using spatial databases and remote sensing imagery. The AdaBoost algorithm outperformed Bagging and Stacking algorithms in spatial modeling of asthma-prone areas.
Article
Information Science & Library Science
Arpan Kumar Kar, Spyros Angelopoulos, H. Raghav Rao
Summary: While data availability and access used to be challenging for information systems research, the growth and ease of access to large datasets and data analysis tools has increased interest in using such resources for publishing. However, these publications often lack strong theoretical contributions and focus only on descriptive analysis of big data. This article addresses the need for theory building with Big Data by providing guidelines for both inductive and deductive approaches, as well as highlighting common pitfalls to avoid.
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT
(2023)
Review
Clinical Neurology
Yuzhe Liu, Yuan Luo, Andrew M. Naidech
Summary: Significant advances in medical data accumulation, computational techniques, and management have been made in the last decade. Big data and computational methods can address gaps in patient selection, complications prediction, and outcome understanding. Automated neuroimaging analysis can help triage patients, and data-intensive techniques enable accurate risk calculations for timely prediction of adverse events.
Article
Geosciences, Multidisciplinary
Ratiranjan Jena, Biswajeet Pradhan, Shilpa Gite, Abdullah Alamri, Hyuck-Jin Park
Summary: This study applied SHAP to estimate earthquake probability using two different ML approaches (ANN and RF) and compared their performance. The results showed that SHAP could help interpret the models' outputs and identify the contributing factors for earthquake probability estimation. Testing on the Indian subcontinent demonstrated high overall accuracy of the ANN and RF models.
Article
Environmental Sciences
Haofan Xu, Chaosheng Zhang
Summary: The study reveals special spatially varying relationships between total organic carbon (TOC) and pH values in European agricultural soil, with both negative and positive correlations observed locally. Significantly positive correlations are found in central-eastern Europe, while negative correlations are mainly observed in northern Europe, and mixed relationships occur in southern Europe. The study highlights the importance of specific natural factors, such as quartz-rich soil, and potentially anthropogenic inputs in influencing the TOC and pH spatial distribution. Geographically weighted regression (GWR) proves to be a powerful technique for exploring these spatially varying relationships at the local level.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Environmental Sciences
Yizhong Huan, Tao Liang, Haitao Li, Chaosheng Zhang
Summary: In 2015, 193 countries committed to achieving 17 sustainable development goals (SDGs). A lack of methods for quantitative assessment of regional progress in achieving SDGs prompted the development of the Composite SDG Index, which categorized the goals into four dimensions and introduced a Coupling Coordinated SDG subindex for the first time to measure coordination between dimensions. The framework, used to assess 15 countries along the Belt and Road, aims to enhance mutual understanding among global stakeholders and support coordinated planning and decision-making at the national level.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Environmental Sciences
Daijin Chen, Ranran Liu, Qinhao Lin, Shengtao Ma, Guiying Li, Yingxin Yu, Chaosheng Zhang, Taicheng An
Summary: A study on the ambient volatile organic compounds (VOCs) emitted in an e-waste dismantling region found that the dismantling process releases BTEX pollutants, with pollution levels varying seasonally and some VOCs posing potential cancer risks.
Article
Environmental Sciences
Haofan Xu, Peter Croot, Chaosheng Zhang
Summary: The study utilized spatial clustering techniques to analyze the geochemical information of 15 potentially toxic elements in Northern Ireland, revealing clear associations with geological features, particularly peat and basalt. K-means clustering analysis identified three hidden patterns among the samples, which were consistent with the spatial clustering patterns of PTEs, emphasizing the dominant control of peat and basalt in the topsoil of Northern Ireland.
ENVIRONMENT INTERNATIONAL
(2021)
Article
Environmental Sciences
Xueqi Xia, Junfeng Ji, Chaosheng Zhang, Zhongfang Yang, Huading Shi
Summary: This study investigated the extent and controlling factors of high Cadmium (Cd) background in the southwest region of China using data from the Multi-Purpose Regional Geochemical Survey and the Regional Geochemistry-National Reconnaissance Program. The results showed that the high Cd area coincided well with carbonate distribution and that the composition of parent rock, climate conditions, and land use were controlling factors of Cd enrichment. The study also found that soil Cd concentration related to carbonate background could be predicted by major element concentrations, which is useful for differentiating Cd background from human pollution in future soil pollution monitoring.
Article
Soil Science
Haofan Xu, Peter Croot, Chaosheng Zhang
Summary: The investigation of spatially varying relationships is important in identifying influencing factors and sources of potentially toxic elements (PTEs). This study demonstrates the efficiency of Geographically Weighted Pearson Correlation Coefficient (GWPCC) in exploring the spatial relationships between Pb and Al in soils and identifying associations with related influencing factors, which traditional techniques cannot achieve.
Article
Environmental Sciences
Cheng Li, Chaosheng Zhang, Tao Yu, Xu Liu, Yeyu Yang, Qingye Hou, Zhongfang Yang, Xudong Ma, Lei Wang
Summary: This study investigated the factors influencing soil Cd bioavailability in karst areas and proposed a new land classification scheme based on an artificial neural network prediction model to ensure safe rice consumption. The higher CaO level in karst soil was found to lead to elevated soil pH value, inhibiting Cd mobility. The ANN prediction model was more accurate in predicting soil Cd concentration than the traditional linear regression model.
ENVIRONMENTAL POLLUTION
(2022)
Article
Environmental Sciences
Siyu Wang, Zhunan Xiong, Lingqing Wang, Xiao Yang, Xiulan Yan, You Li, Chaosheng Zhang, Tao Liang
Summary: Dismantling and recycling e-waste can be a potential emission source of rare earth elements. This study focused on Guiyu Town as an example and examined the characteristics, spatial distribution, and pollution level of REEs caused by e-waste dismantling. The results showed that the distribution of REEs in soil was affected by multiple factors, with some soil samples being lightly polluted and the hot spots of REE-polluted soil coinciding with known pollution sources.
ENVIRONMENTAL POLLUTION
(2022)
Article
Immunology
Hongqin Xu, Hongyan Li, Hailong You, Peng Zhang, Nan Li, Nan Jiang, Yang Cao, Ling Qin, Guixiang Qin, Hongbo Qu, Heyuan Wang, Bo Zou, Xia He, Dan Li, Huazhong Zhao, Gang Huang, Yang Li, Hefeng Zhang, Liping Zhu, Hongmei Qiao, Hongjun Li, Shurong Liu, Lina Gu, Guidong Yin, Ye Hu, Songbai Xu, Weiying Guo, Nanya Wang, Chaoying Liu, Pujun Gao, Jie Cao, Yang Zheng, Kaiyu Zhang, Yang Wang, Hui Chen, Jian Zhang, Dongmei Mu, Junqi Niu
Summary: In spring 2022, there was a rapid spread of the Omicron variant in Jilin Province, China. A study using real-world data showed that inactivated COVID-19 vaccines were effective in reducing the risk of pneumonia and severe disease. Booster vaccination further enhanced this protective effect.
EMERGING MICROBES & INFECTIONS
(2023)
Article
Environmental Sciences
Haofan Xu, Hailong Wang, Bhupinder Pal Singh, Peter Croot, Chaosheng Zhang
Summary: This study investigated the potential sources and spatial relationships between 9 PTEs and PAHs in the topsoil of Dublin. The results identified high-temperature combustion, natural lithologic factors, mineralisation and mining, as well as anthropogenic inputs as the main sources of these elements. The study also revealed different spatial interactions between selected elements and PAHs, indicating different controlling factors. This research provides valuable insights into the geochemical features of PTEs and PAHs in Dublin's topsoil.
ENVIRONMENTAL POLLUTION
(2023)
