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Extracting Named Entity Using Entity Labeling in Geological Text Using Deep Learning Approach

Journal of Earth Science 2023年第5期34卷 1406-1417页

作者： Qinjun Qiu Miao Tian Zhong Xie Yongjian Tan Kai Ma Qingfang Wang Shengyong Pan Liufeng Tao State Key Laboratory of Geo-Information Engineering and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR Chinese Academy of Surveying and MappingBeijing 100036China Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities MNRShanghai 20063China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang 443002China College of Computer and Information Technology China Three Gorges UniversityYichang 443002China Chengdu Geological Environment Monitoring Station Chengdu 610036China Wuhan Zondy Cyber Science&Technology Co. Ltd.Wuhan 430074China

Artificial intelligence(AI) is the key to mining and enhancing the value of big data, and knowledge graph is one of the important cornerstones of artificial intelligence, which is the core foundation for the integration of statistical and physical representations. Named entity recognition is a fundamental research task for building knowledge graphs, which needs to be supported by a high-quality corpus, and currently there is a lack of high-quality named entity recognition corpus in the field of geology, especially in Chinese. In this paper, based on the conceptual structure of geological ontology and the analysis of the characteristics of geological texts, a classification system of geological named entity types is designed with the guidance and participation of geological experts, a corresponding annotation specification is formulated, an annotation tool is developed, and the first named entity recognition corpus for the geological domain is annotated based on real geological reports. The total number of words annotated was 698 512 and the number of entities was 23 345. The paper also explores the feasibility of a model pre-annotation strategy and presents a statistical analysis of the distribution of technical and term categories across genres and the consistency of corpus annotation. Based on this corpus, a Lite Bidirectional Encoder Representations from Transformers(ALBERT)-Bi-directional Long Short-Term Memory(BiLSTM)-Conditional Random Fields(CRF) and ALBERT-BiLSTM models are selected for experiments, and the results show that the F1-scores of the recognition performance of the two models reach 0.75 and 0.65 respectively, providing a corpus basis and technical support for information extraction in the field of geology.

关键词： ontology geological reports named entity recognition geological corpus construction semi-automated annotation platforms deep learning

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Research on Ornamental Fish Recognition Base on Improved Shufflenet V2 Network 4

Research on Ornamental Fish Recognition Base on Improved Shu...

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4th International Conference on big data and Artificial Intelligence and Software Engineering, ICBASE 2023

作者： Zhang, Xingyun Chen, Hongming Zhang, Longqing Chen, Qian Zhejiang Ocean University Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province Zhoushan316022 China Guangdong University of Science and Technology School of Computer Science Dongguan523083 China Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China

ISBN: (纸本)9798350329490

With the advancement of computer vision technology, fish recognition plays a crucial role in various fields such as aquaculture processing and disseminating fish knowledge. In this study, we propose an enhanced and lightweight fish recognition algorithm to accomplish fish classification recognition with limited data samples. Based on the ShuffleNet V2 network, we incorporate Transfer Learning and the SE attention mechanism. Additionally, we replace the ReLu activation function with the AM-Softmax activation function. Comparative evaluations are conducted against Resnet50, MobileNet V2, MobileNet V3, and the original ShuffleNet V2 network model. Our experimental findings demonstrate that the proposed algorithm outperforms the aforementioned models, resulting in recognition accuracy improvements of 16.01%, 19.05%, 15.04%, and 14.44% respectively. The final recognition accuracy achieved is 97.20%, successfully attaining the desired outcome. © 2023 IEEE.

关键词： Computer vision

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MapColorAI: Designing Contextually Relevant Choropleth Map Color Schemes Using a Large Language Model

arXiv

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arXiv 2025年

作者： Yang, Nai Wang, Yijie Wu, Fan Wei, Zhiwei School of Geography and Information Engineering China University of Geosciences Hubei Wuhan China School of Geographic Sciences Hunan Normal University Hunan Changsha China Hunan Key Laboratory of geospatial big data mining and application Hunan Normal University Hunan Changsha China

Choropleth maps, which utilize color schemes to visualize spatial patterns and trends, are simple yet effective tools for geographic data analysis. As such, color scheme design is a critical aspect of choropleth map creation. The traditional coloring methods offered by GIS tools such as ArcGIS and QGIS are not user-friendly for nonprofessionals. On the one hand, these tools provide numerous color schemes, making it hard to decide which one best matches the theme. On the other hand, it is difficult to fulfill some ambiguous and personalized coloring needs of users, such as requests for ‘summer-like’ map colors. To address these shortcomings, we develop a novel system that leverages a large language model and map color design principles to generate contextually relevant and user-aligned choropleth map color schemes. The system follows a three-stage process: data processing, which provides an overview of the data and classifies the data into meaningful classes;Color Concept Design, where the color theme and color mode are conceptualized based on data characteristics and user intentions;and Color Scheme Design, where specific colors are assigned to classes based on generated color theme, color mode, and user requirements. Our system incorporates an interactive interface, providing necessary visualization for choropleth map color design and allowing users to customize and refine color choices flexibly. Through user studies and evaluations, the system demonstrates acceptable usability, accuracy, and flexibility, with users highlighting the tool’s efficiency and ease of use. Copyright © 2025, The Authors. All rights reserved.

关键词： Modeling languages

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Modeling the Soil Evaporation Loss in Typical Subtropical Secondary Forests-A Changsha Case Study

SSRN

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SSRN 2024年

作者： Zhang, Yong Zhang, Xinping Xiao, Xiong Dai, Junjie Jiang, Wanjing Du, Zhen Zhan, Xuhong Liu, Lu College of Geographic Science Hunan Normal University Changsha410081 China Key Laboratory of Geospatial Big Data Mining and Applications in Hunan Province Hunan Normal University Changsha410081 China

Under the more frequent and extreme global drought events, utilizing stable isotopes to quantify soil evaporation losses (SEL) is of great significance for understanding the water supply capacity from soil to plants. From March 2017 to September 2019, we continuously monitored meteorological factors, soil temperature and humidity, and collected precipitation and soil water stable isotope data. Used the Craig-Gordon (C-G) model and the line-conditioned excess (lc-excess) couple with Rayleigh fractionation (RL) model to quantify SEL in subtropical secondary forests. The results showed: (1) The theoretical Evaporation Line (EL) slope correlated negatively with air temperature (AT). Water source isotopic values were more positive in autumn and more negative in spring. The aridity index (AI) and soil evaporation loss ratio (f) from both models indicated drier conditions from March to September 2018 compared to 2017 and 2019;(2) Comparative analysis showed the C-G model agreed more closely with measured evapotranspiration (ET0) and water surface evaporation (E) than the RL model, indicating its better suitability for the study region;(3) Because the "inverse temperature effect" of the precipitation isotopes, the linear fitting method was not suitable for determining the water source in spring, summer, autumn, and on the annual scale, while the EL slope obtained by the fitted slope was consistent with the basic principle of soil evaporation in winter. Thus, the theoretical method was more suitable for determining the EL slope in such regions;(4) because the different fundamentals, the C-G model was positively correlated with air temperature (AT) and negatively with relative humidity (h), while the RL model showed the opposite, indicating different applicability. Meanwhile, SEL is influenced by soil thickness, atmospheric evaporation, and soil water supply capacities. These findings support using stable isotope techniques to quantify SEL and are important for analyzing soil

关键词： Water supply

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Detection of Pine Wood Nematode Infestation Based on Improved YOLOv5 5

Detection of Pine Wood Nematode Infestation Based on Improve...

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2023 5th International Conference on Artificial Intelligence Technologies and applications, ICAITA 2023

作者： Miao, Jiaming Zhang, Chunhui Yuan, Mengfei Gu, Shenming School of Information Engineering Zhejiang Ocean University Zhoushan316022 China Evaluation Department Binzhou Safety Evaluation Center Co. Ltd. Binzhou256600 China Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province Zhejiang Ocean University Zhoushan316022 China

Pine wilt disease is a destructive forest disease caused by the parasitism of pine wood nematodes inside pine trees. Once infected, pine trees quickly wither and die due to the inability to drain water, hence it is also known as pine tree withering disease. It is mainly spread by pine sawyer beetles, with the characteristics of fast dissemination, rapid onset, and high mortality rate, making it a significant global plant disease. Failure to effectively control the pine wilt disease in a timely manner will result in the massive death of pine trees in a short period of time in forest areas. With the continuous development and popularization of artificial intelligence and UAV (Unmanned Aerial Vehicle) technology, combining various methods can timely detect diseased trees, and performing timely treatment and protection can greatly save the time and personnel costs of biological pest control. While it is also conducive to promoting the work of multiple related disciplines, such as bioengineering and greening engineering. In this paper, we first conducted a large number of aerial surveys on the forest area through UAV, collected relevant data, and preprocessed the obtained data, including data augmentation, cleaning, filtering, deduplication, formatting, etc., to ensure data quality and accuracy. Then, we labeled the data, and made certain improvements to the original YOLOv5. We added a new RRAM (Recurrent Residual Attention Module) to the original network model, which enables the network to timely focus on important information in redundant data, thus improving the network's performance. Compared with the original YOLOv5, our network has a stronger performance. © Published under licence by IOP Publishing Ltd.

关键词： Antennas

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Soliton Molecule and Breather-Soliton Molecule Structures for a General Sixth-Order Nonlinear Equation

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Chinese Physics Letters 2021年第8期38卷 1-6页

作者： Kai-Hua Yin Xue-Ping Cheng Ji Lin School of Mathematics Physics and Information ScienceZhejiang Ocean UniversityZhoushan 316022China Key Laboratory of Oceanographic Big Data Mining&Application of Zhejiang Province Zhoushan 316022China Institute of Nonlinear Physics Zhejiang Normal UniversityJinhua 321004China

Starting from a general sixth-order nonlinear wave equation,we present its multiple kink solutions,which are related to the famous Hirota *** also investigate the restrictions on the coefficients of this wave equation for possessing multiple kink *** introducing the velocity resonance mechanism to the multiple kink solutions,we obtain the soliton molecule solution and the breather-soliton molecule solution of the sixth-order nonlinear wave equation with particular *** three-dimensional image and the density map of these soliton molecule solutions with certain choices of the involved free parameters are well *** matching the parametric restrictions of the sixth-order nonlinear wave equation for having three-kink solution with the coefficients of the integrable bidirectional Sawada-Kotera-Caudrey-Dodd-Gibbons(SKCDG)equation,the breather-soliton molecule solution for the bidirectional SKCDG equation is also illustrated.

关键词： soliton equation nonlinear

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Modeling the Soil Evaporation Loss in Typical Subtropical Secondary Forests-A Changsha Case Study

SSRN

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SSRN 2024年

Under the more frequent and extreme global drought events, quantifying soil evaporation losses (SEL) is crucial for understanding the water supply capacity from soil to plants. From March 2017 to September 2019, we monitored meteorological factors, soil conditions and collected precipitation and soil water stable isotope data. Used the Craig-Gordon (C-G) model and the line-conditioned excess (lc-excess) couple with Rayleigh fractionation (RL) model to quantify SEL in subtropical secondary forests. The results showed: (1) Water source isotopic values were more positive in autumn and more negative in spring. Both models indicated drier conditions from March to September 2018 compared to 2017 and 2019;(2) Comparative analysis showed the C-G model agreed more closely with measured evapotranspiration (ET0) and water surface evaporation (E) than the RL model, indicating its better suitability for the study region;(3) Because the "inverse temperature effect" of the precipitation isotopes, the linear fitting method only conforms to the basic principle of soil evaporation in winter. Thus, the theoretical method was more suitable for determining the Evaporation Line (EL) slope in such regions;(4) Because the different fundamentals, the C-G model was positively correlated with air temperature (AT) and negatively with relative humidity (h), while the RL model showed the opposite, indicating different applicability. These findings showed stable isotope techniques are effective for quantifying SEL and crucial for studying soil water resources. © 2024, The Authors. All rights reserved.

关键词： Water supply

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Underwater image enhancement based on improved adaptive MSRCR and Gamma function

Underwater image enhancement based on improved adaptive MSRC...

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Cloud Computing, big data applications and Software Engineering (CBASE), International Conference on

作者： Lin Zhang Tong Peng School of Information Engineering Zhejiang Ocean University Zhoushan China Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province Zhoushan China

In order to solve the problem that light is absorbed by different scales and scattered by particles in water, resulting in overall color deviation, low contrast and unclear details of the image, an underwater image enhancement algorithm based on improved adaptive MSRCR(Multi-Scale Retinex with Color Restoration) and two-dimensional gamma function based on details is proposed. Firstly, the weight of the convolution function in different scales is redistributed according to the image gradient information as the selection factor, and then the guided filter and gaussian filter are used as the adaptive MSRCR surround function and linear fusion to solve the problems of color decay and insufficient sharpness. Finally, the improved two-dimensional gamma function with CLAHE(Contrast Limited Adaptive Histogram Equalization) algorithm is used to correct the image contrast after fusion. The experimental results show that the enhanced image processed by this method has good enhancement effect in underwater image elimination of color distortion, image detail enhancement and obtaining real and natural restored image, and has obvious advantages over other contrast algorithms.

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Novelty detection technology for Alzheimer's disease based on autoencoder feature extractor and MCD classification 7

Novelty detection technology for Alzheimer's disease based o...

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Real-time Photonic Measurements, data Management, and Processing VII 2023

作者： Zhang, Shuheng Zhang, Yan Pan, Jie Lin, Xintian Ding, Xuemei Yang, Hongqin Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education Provincial Key Laboratory for Photonics Technology Fujian Normal University Fuzhou350117 China Fujian Provincial Engineering Research Center for Public Service Big Data Mining and Application Fujian Normal University Fuzhou350117 China Xiamen Jingyi zhikang Technology Co. Ltd. Xiamen361000 China

ISBN: (纸本)9781510667938

Alzheimer's disease (AD) is a neurodegenerative disorder that affects the life quality of millions of people worldwide. To diagnose new cases in a timely manner, we propose a new novelty detection technique that combines Autoencoder and Minimum Covariance Determinant (MCD). The technique consists of two steps: first, we use an Autoencoder to extract low-dimensional and discriminative features from the publicly available ADNI dataset, where we only train the Autoencoder with normal data, making the abnormal data more distinguishable in the feature space;second, based on the features of normal data, we use MCD to construct a decision boundary, and judge the degree of abnormality by the distance of the test point to the boundary. Compared with traditional methods without using Autoencoder, our technique has significant advantages in terms of accuracy and sensitivity, and can effectively deal with data imbalance problem. Experimental results show that our method can efficiently detect novel AD cases, and has a wide range of application prospects. © 2023 SPIE.

关键词： Neurodegenerative diseases

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Attribute Reduction of Object Granules of Concept Lattice Based on Three-Way Decision

Attribute Reduction of Object Granules of Concept Lattice Ba...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Tong-Jun Li Run-Ze Zhang School of Information Engineering Zhejiang Ocean University Zhoushan Zhejiang China Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province China

Formal concept analysis is a key tool in data analysis and knowledge representation and a specific method for granular computing. Object granules constitute the basic granular knowledge in a concept lattice. Three-way decision is a reasonable approach to extracting decision rules. This study employs the principle of three-way decision to divide all the object granules of a formal context into three parts: positive, negative and boundary regions, then two groups of certainty decision rules are extracted from the positive region and the negative region, and one group of possibility decision rules is induced from the boundary region. The notion of attribute reduction keeping the performance of the decision rules unchanged are proposed. An approach for computing attribute reducts is put forward by utilizing the discernibility matrix and discernibility function. Some examples are taken to explain or show the relevant conclusions and prove the feasibility of the reduction method.

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