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Article ; Online: Improved Word Segmentation System for Chinese Criminal Judgment Documents

Chi Zhang

Applied Artificial Intelligence, Vol 38, Iss

2024 Volume 1

Abstract: ABSTRACTIn this paper, a system for automatic word segmentation of Chinese criminal judgment documents is proposed. The system uses a hybrid model composed of fine-tuned BERT (Bidirectional Encoder Representations from Transformers), BiLSTM ( ... ...

Abstract	ABSTRACTIn this paper, a system for automatic word segmentation of Chinese criminal judgment documents is proposed. The system uses a hybrid model composed of fine-tuned BERT (Bidirectional Encoder Representations from Transformers), BiLSTM (Bidirectional Long Short Term Memory) and CRF (Conditional Random Field) for named entity recognition, and introduces a custom dictionary that includes common professional terms in Chinese criminal trial documents, as well as a rule system based on judicial system and litigation procedure related regulations, to further improve the accuracy of word segmentation. BERT uses a deep bidirectional Transformer encoder to pre-train general language representations from large-scale unlabeled text corpora. BiLSTM uses two LSTM networks, one for the forward direction and one for the backward direction, to capture the context from both sides of the input sequence. CRF uses a set of features and weights to define a log-linear distribution over the output sequence. Experimental results show that the proposed system has significantly improved word segmentation accuracy compared to the current commonly used Chinese word segmentation models. In the results of the segmentation of the test data, the F1 scores for jieba, THULAC and the segmentation system proposed in this paper are 85.59%, 87.94% and 94.82%, respectively.
Keywords	Electronic computers. Computer science ; QA75.5-76.95 ; Cybernetics ; Q300-390
Subject code	006
Language	English
Publishing date	2024-12-01T00:00:00Z
Publisher	Taylor & Francis Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Smartphones and telemedicine for older people in China

Chi Zhang

Digital Health, Vol

Opportunities and challenges

2022 Volume 8

Abstract: The development of 5G technology has brought major advances and diverse challenges in healthcare services for older people, and access to equitable telemedicine is a high priority. Smartphones are most commonly used device to access the internet and ... ...

Abstract	The development of 5G technology has brought major advances and diverse challenges in healthcare services for older people, and access to equitable telemedicine is a high priority. Smartphones are most commonly used device to access the internet and bring the convenience of telemedicine to the user's fingertips. In the period where aging and informatization coexist in China, the role of smartphones in their daily lives, long-term care, and future opportunities and challenges needs serious reconsideration. We provide the latest evidence of smartphone use among the older adults of China and expound on issues about fairness in accessing mobile health, the substantial digital divide, and potential drawbacks of problematic smartphone use.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7
Language	English
Publishing date	2022-11-01T00:00:00Z
Publisher	SAGE Publishing
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Quantifying architectural color Quality

Chi Zhang / Guanzheng Tan

Ecological Indicators, Vol 157, Iss , Pp 111237- (2023)

A Machine learning integrated framework driven by quantitative color metrics

2023

Abstract: The assessment and prediction of architectural color quality play a pivotal role in urban spatial environments, influencing the aesthetic and psychological dimensions of urban space. Despite the criticality, there exists a lacuna in efficient ... ...

Abstract	The assessment and prediction of architectural color quality play a pivotal role in urban spatial environments, influencing the aesthetic and psychological dimensions of urban space. Despite the criticality, there exists a lacuna in efficient methodologies capable of quantitatively evaluating architectural color quality. This study endeavors to bridge this gap by introducing a novel framework employing a machine learning approach in conjunction with operationalizable color feature templates for predicting architectural color quality. Four machine learning models - XGBoost, ANN, SVM, and LGBM - are utilized to assess the color quality based on selected color feature indices. Moreover, this research employs SHAP values to elucidate the contribution of various color features towards model prediction. The findings reveal that among the tested models, XGBoost outshines in terms of prediction accuracy. Significant color features including building height, lightness and saturation of primary colors, and red values in both primary and secondary colors were found to exert substantial influence on the model's predictive capacity. This pioneering approach provides a scalable and quantifiable means to evaluate and predict architectural color quality, which has the potential to significantly contribute to urban color planning and evaluation, thereby propelling forward the domain of architectural color research.
Keywords	Machine Learning ; Color Quality Assessment ; Urban Color Planning ; North Bund ; Shanghai ; Ecology ; QH540-549.5
Subject code	720
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Exploring explicit and implicit attitudes towards wildlife food

Qiang Wei / Chi Zhang / Dong Lv / Xinyu Du

Global Ecology and Conservation, Vol 49, Iss , Pp e02799- (2024)

2024

Abstract: Illegitimate wildlife consumption poses threats to public health, biodiversity and natural ecosystems. Understanding of public attitudes towards wildlife as food can help promote wildlife conservation. However, almost wildlife consumption researches ... ...

Abstract	Illegitimate wildlife consumption poses threats to public health, biodiversity and natural ecosystems. Understanding of public attitudes towards wildlife as food can help promote wildlife conservation. However, almost wildlife consumption researches limit insights to subjective attitudes. To address this gap, the present employs a comprehensive approach, combining questionnaires, the Implicit Association Test (IAT) paradigm, and Event-Related Potential (ERP) method. This multi-method strategy enables better exploration of both explicit and implicit attitudes toward wildlife food. Participants who had been exposed to wildlife food consumption were randomly recruited. Compared to non-wildlife foods, people had a lower acceptability of wildlife foods, a longer reaction time when paired with positive words and a smaller N400 component when paired with negative words. These results revealed that public showed negative attitudes towards wildlife food compared to non-wildlife food, and this result was consistent between explicit and implicit attitudes. This outcome also provides a positive signal for wildlife conservation. Leveraging the public's negative perceptions of wildlife food in conjunction with the adverse consequences of eating wildlife food can be employed to further the cause of wildlife conservation.
Keywords	Illegal wildlife consumption ; Wildlife food ; Explicit attitude ; Implicit attitude ; Event related potentials ; Ecology ; QH540-549.5
Subject code	333
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Floating clavicle with medial clavicular fracture causing diagnostic dilemma - A case report and literature review.

Yu, Pengkun / Chi, Zhang

International journal of surgery case reports

2023 Volume 112, Page(s) 108925

Abstract: Introduction and importance: A rare case of a fracture of the medial third of the clavicle on the basis of the "floating clavicle" was hereby reported. To the best of our knowledge, this complex clavicle fracture has not yet been published. This article ...

Abstract	Introduction and importance: A rare case of a fracture of the medial third of the clavicle on the basis of the "floating clavicle" was hereby reported. To the best of our knowledge, this complex clavicle fracture has not yet been published. This article aims to describe, for the first time, a case of the diagnosis and treatment of this special clavicle fracture. Case presentation: The 26-year-old male patient suffered from a right sternoclavicular dislocation, a fracture of the right medial third of the clavicle, and a dislocation of the right acromioclavicular joint due to a car accident. In the course of treatment, he was missed diagnosis, and after active adjustment of treatment plan, good therapeutic effect was achieved. Clinical discussion: A special case of a floating clavicle was hereby reported. The missed diagnosis of sternoclavicular dislocation will cause great difficulties in the management of the disease. Based on the condition and clear diagnosis of the patient, surgical treatment was actively recommended for the patient. The selection of the implant for surgical treatment varied due to its specificity. A comprehensive literature review is also provided. Conclusion: Clavicular bone fracture is common in clinical practice. At the same time, the injury of sternoclavicular joint and acromioclavicular joint should be vigilant. For the complex clavicle fracture reported in this paper, the computed tomography scan with 3D reconstruction can assist in diagnosis. In the case of definite diagnosis, the use of a contralateral distal clavicular plate in combination with the conventional clavicular hook plate is an appropriate choice.
Language	English
Publishing date	2023-10-11
Publishing country	Netherlands
Document type	Case Reports
ISSN	2210-2612
ISSN	2210-2612
DOI	10.1016/j.ijscr.2023.108925
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: An Improved Model of Product Classification Feature Extraction and Recognition Based on Intelligent Image Recognition

Baiqiang Gan / Chi Zhang

Computational Intelligence and Neuroscience, Vol

2022 Volume 2022

Abstract: With the development of the new generation of technological revolution, the manufacturing industry has entered the era of intelligent manufacturing, and people have higher and higher requirements for the technology, industry, and application of product ... ...

Abstract	With the development of the new generation of technological revolution, the manufacturing industry has entered the era of intelligent manufacturing, and people have higher and higher requirements for the technology, industry, and application of product manufacturing. At present, some factories have introduced intelligent image recognition technology into the production process in order to meet the needs of customers' personalized customization. However, the current image recognition technology has limited capabilities. When faced with many special customized products or complex types of small batch products in the market, it is still impossible to perfectly analyze the product requirements and put them into production. Therefore, this paper conducts in-depth research on the improved model of product classification feature extraction and recognition based on intelligent image recognition: 3D modeling of the target product is carried out, and various data of the model are analyzed and recorded to facilitate subsequent work. Use the tools and the established 3D model tosimulate the parameters of the product in the real scene, and record them. Atthe same time, various methods such as image detection and edge analysis areused to maximize the accuracy of the obtained parameters, and variousalgorithms are used for cross-validation to obtain the correct rate of the obtaineddata, and the standard is 90% and above. Build a data platform, compare simulated data with display data by software and algorithm, and check by cloud computing force, so that the model data can be as close to the parameters of the real product as possible. Experimental results show that the algorithm has high accuracy and can meet the requirements of different classification prospects in actual production.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7 ; Neurosciences. Biological psychiatry. Neuropsychiatry ; RC321-571
Subject code	670
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Hindawi Limited
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Progress, Challenge, and Prospect of LiMnO2

Jin Ma / Tingting Liu / Jie Ma / Chi Zhang / Jinhu Yang

Advanced Science, Vol 11, Iss 2, Pp n/a-n/a (2024)

An Adventure toward High‐Energy and Low‐Cost Li‐Ion Batteries

2024

Abstract: Abstract Lithium manganese oxides are considered as promising cathodes for lithium‐ion batteries due to their low cost and available resources. Layered LiMnO2 with orthorhombic or monoclinic structure has attracted tremendous interest thanks to its ... ...

Abstract	Abstract Lithium manganese oxides are considered as promising cathodes for lithium‐ion batteries due to their low cost and available resources. Layered LiMnO2 with orthorhombic or monoclinic structure has attracted tremendous interest thanks to its ultrahigh theoretical capacity (285 mAh g−1) that almost doubles that of commercialized spinel LiMn2O4 (148 mAh g−1). However, LiMnO2 undergoes phase transition to spinel upon cycling cause by the Jahn‐Teller effect of the high‐spin Mn3+. In addition, soluble Mn2+ generates from the disproportionation of Mn3+ and oxygen release during electrochemical processes may cause poor cycle performance. To address the critical issues, tremendous efforts have been made. This paper provides a general review of layered LiMnO2 materials including their crystal structures, synthesis methods, structural/elemental modifications, and electrochemical performance. In brief, first the crystal structures of LiMnO2 and synthetic methods have been summarized. Subsequently, modification strategies for improving electrochemical performance are comprehensively reviewed, including element doping to suppress its phase transition, surface coating to resist manganese dissolution into the electrolyte and impede surface reactions, designing LiMnO2 composites to improve electronic conductivity and Li+ diffusion, and finding compatible electrolytes to enhance safety. At last, future efforts on the research frontier and practical application of LiMnO2 have been discussed.
Keywords	element doping ; Li‐ion batteries ; LiMnO2 cathode ; surface coating ; synthesis methods ; Science ; Q
Subject code	540
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	Wiley
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Pluvial flood susceptibility mapping for data-scarce urban areas using graph attention network and basic flood conditioning factors

Ze Wang / Heng Lyu / Chi Zhang

Geocarto International, Vol 0, Iss 0, Pp 1-

2023 Volume 25

Abstract: Pluvial floods are destructive natural disasters in cities. With high computational efficiency, machine learning models are increasingly used for flood susceptibility mapping. However, limited flooded or nonflooded samples constrain models’ predictive ... ...

Abstract	Pluvial floods are destructive natural disasters in cities. With high computational efficiency, machine learning models are increasingly used for flood susceptibility mapping. However, limited flooded or nonflooded samples constrain models’ predictive capability and introduce uncertainty in feature engineering. This study introduces a semi-supervised graph-structured model, Graph Attention Network (GAT), to address data scarcity and enable the use of only basic flood conditioning factors as inputs. GAT uses nodes and edges to represent spatial units and their relative spatial relationships. Based on its graph structure and attention mechanism, GAT automatically extracts high-order features from inputs of labeled and unlabeled units for modeling. In the metropolitan area of Dalian, China, GAT outperformed other models in flooded-nonflooded sample classification and exhibited a rational flood susceptibility distribution pattern, with only four basic flood conditioning factors and less than 1.2% of units for training. GAT can be an effective tool for practical urban flood management.
Keywords	urban pluvial flood ; flood susceptibility ; machine learning ; graph attention network ; gis ; Physical geography ; GB3-5030
Subject code	910
Language	English
Publishing date	2023-10-01T00:00:00Z
Publisher	Taylor & Francis Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Generative adversarial networks for detecting contamination events in water distribution systems using multi-parameter, multi-site water quality monitoring

Zilin Li / Haixing Liu / Chi Zhang / Guangtao Fu

Environmental Science and Ecotechnology, Vol 14, Iss , Pp 100231- (2023)

2023

Abstract: Contamination events in water distribution networks (WDNs) can have a huge impact on water supply and public health; increasingly, online water quality sensors are deployed for real-time detection of contamination events. Machine learning has been used ... ...

Abstract	Contamination events in water distribution networks (WDNs) can have a huge impact on water supply and public health; increasingly, online water quality sensors are deployed for real-time detection of contamination events. Machine learning has been used to integrate multivariate time series water quality data at multiple stations for contamination detection; however, accurate extraction of spatial features in water quality signals remains challenging. This study proposed a contamination detection method based on generative adversarial networks (GANs). The GAN model was constructed to simultaneously consider the spatial correlation between sensor locations and temporal information of water quality indicators. The model consists of two networks—a generator and a discriminator—the outputs of which are used to measure the degree of abnormality of water quality data at each time step, referred to as the anomaly score. Bayesian sequential analysis is used to update the likelihood of event occurrence based on the anomaly scores. Alarms are then generated from the fusion of single-site and multi-site models. The proposed method was tested on a WDN for various contamination events with different characteristics. Results showed high detection performance by the proposed GAN method compared with the minimum volume ellipsoid benchmark method for various contamination amplitudes. Additionally, the GAN method achieved high accuracy for various contamination events with different amplitudes and numbers of anomalous water quality parameters, and water quality data from different sensor stations, highlighting its robustness and potential for practical application to real-time contamination events.
Keywords	Contamination detection ; Generative adversarial network ; Multi-site time series data ; Water distribution system ; Water quality ; Environmental sciences ; GE1-350 ; Environmental technology. Sanitary engineering ; TD1-1066
Subject code	550
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Impacts of Land-Use Change on Ecosystem Services Value in the South-to-North Water Diversion Project, China

Jing Zhuge / Jie Zeng / Wanxu Chen / Chi Zhang

International Journal of Environmental Research and Public Health, Vol 20, Iss 5069, p

2023 Volume 5069

Abstract: The South-to-North Water Diversion Project (SNWD) in China is a trans-basin water transfer project for water resource optimization that affects ecosystem services functions along its main transfer line. Exploring the effects of land-use change on ... ...

Abstract	The South-to-North Water Diversion Project (SNWD) in China is a trans-basin water transfer project for water resource optimization that affects ecosystem services functions along its main transfer line. Exploring the effects of land-use change on ecosystem services in the headwater and receiving areas along the SNWD is conducive to improving the protection of the surrounding ecological environment. However, previous research lacks a comparative analysis of ecosystem services values (ESVs) in these areas. In this study, the land-use dynamic degree index, land-use transfer matrix, and spatial analysis method were used to comparatively analyze the impact of land-use changes on ESVs in the headwater and receiving areas of the SNWD. The results show that cultivated land was the main land use type in the receiving areas and HAER. From 2000 to 2020, CLUDD in the headwater areas was faster than that in the receiving areas. Spatially, in general, the land-use change areas of the receiving areas were larger. During the study period, cultivated land in the headwater areas of the middle route mainly transferred to water areas and forestry areas, while built-up areas mainly occupied cultivated land in the headwater areas of the east route, receiving areas of the middle route, and receiving areas of the east route. From 2000 to 2020, the ESV increased only in the headwater areas of the middle route, while the ESV in the other three sections decreased. The variation extent of ESV in the receiving areas was greater than that in the headwater areas. The results of this study have important policy significance for land use and ecological protection in the headwater and receiving areas of the SNWD in the future.
Keywords	land-use ; ecosystem services value ; South-to-North Water Diversion Project ; China ; Medicine ; R
Subject code	710
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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