Long-term Preservation of Electronic Record Based on Digital Continuity in Smart Cities

Ren, Yongjun; Zhu, Kui; Gao, Yuqiu; Xia, Jinyue; Zhou, Shi; Hu, Ruiguo; Feng, Xiujuan

doi:10.32604/cmc.2021.011153

Cited by 23 publications

(18 citation statements)

References 25 publications

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“…So, it is necessary to construct a lung rehabilitation program in line with the physiological characteristics of children. Lang et al [34][35][36] put forward comprehensive rehabilitation strategies for children with mechanical ventilation from the aspects of posture management, motor function recovery, respiratory muscle training, sleep management, and psychological support. But they lacked specific evaluation and intervention time.…”

Section: Early Lung Rehabilitationmentioning

confidence: 99%

Structured Graded Lung Rehabilitation for Children with Mechanical Ventilation

Ren¹,

Hu²,

Li³

et al. 2022

Computer Systems Science and Engineering

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Lung rehabilitation is safe and feasible, and it has positive benefits in weaning the machine as soon as possible, shortening the time of hospitalization and improving the prognosis of children with mechanical ventilation. However, at present, the traditional medical concept is deep-rooted, and doctors' understanding of early rehabilitation is inadequate. It is necessary to make in-depth exploration in the relevant guidelines and expert consensus to formulate standardized early rehabilitation diagnosis and treatment procedures and standards for mechanically ventilated children. In the paper, a structured graded lung rehabilitation program is constructed for children with mechanical ventilation to improve their respiratory function, shorten the time of mechanical ventilation and pediatric intensive care unit (PICU) hospitalization, and reduce their anxiety, based on the principal component analysis of functional pneumonia data. Scientific evaluation and dynamic monitoring ensure the safety of the implementation of the program and promote the prognosis and prognosis of the disease. The proposed lung rehabilitation program provides a reference basis for the formulation of lung rehabilitation guidelines for children with mechanical ventilation. And It has important reference significance for clinical pulmonary rehabilitation to alleviate the concerns of clinicians and lay the foundation for the large-scale promotion of early lung rehabilitation.

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Section: Early Lung Rehabilitationmentioning

confidence: 99%

Structured Graded Lung Rehabilitation for Children with Mechanical Ventilation

Ren¹,

Hu²,

Li³

et al. 2022

Computer Systems Science and Engineering

Self Cite

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“…In recent years, scholars in China have expanded the application of BP neural networks to the economic field. Zhang Jingxin researched on prediction of stock price fluctuation by the financial index [38,39]. Xiao [40] investigated the performance evaluation of suppliers for telecommunication operating enterprises.…”

Section: Related Workmentioning

confidence: 99%

Correlation Analysis between Economic Growth and Environmental Quality

Zhou¹,

Li²,

Lu³

et al. 2022

Computer Systems Science and Engineering

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With the rapid development of the economy, China's environment has been damaged severely, which has attracted much attention from scholars and the local government. The concept of green development has been an underlying trend since 2012, and it is of great significance to explore the relationship between economic growth and environmental quality. Huzhou is a prefecture-level city under the jurisdiction of Zhejiang Province, and it is one of the 27 cities in the central area of the Yangtze River Delta. In recent years, this city develops well not only in economic development but also in maintaining a green environment. In the paper, the back propagation neural network is used to evaluate the local environmental quality. Meanwhile, the panel model is exploited to analyze the relationship between economic growth and environmental quality. All the data presented in the paper range from the year 2008 to 2018. Theoretical analysis indicates that the evaluation value of environmental quality, the emissions of industrial SO 2 , and waste water exhibit an inverted U-shaped relationship with economic growth. As for the regression results, the inflection point of income in the environmental Kuznets curve of the model which takes the evaluation value of the environmental quality as a dependent variable is higher than that of the model which takes the SO 2 emission as an independent variable. The research result would help the local government to take appropriate countermeasures to improve the environment and economy.

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“…Yu et al [28] proposed a new token embedding method, position-aware character embedding (PACE). It splits a token into characters, then the token's embedding is the weighted sum of one-hot encoding of all characters [29]. This embedding technique requires no training and can apply to arbitrary tokens.…”

Section: Vector Representation Approachesmentioning

confidence: 99%

Improve Representation for Cross-Language Clone Detection by Pretrain Using Tree Autoencoder

Ling¹,

Zhang²,

Yin³

et al. 2022

Intelligent Automation &Amp; Soft Computing

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With the rise of deep learning in recent years, many code clone detection (CCD) methods use deep learning techniques and achieve promising results, so is cross-language CCD. However, deep learning techniques require a dataset to train the models. The dataset is typically small and has a gap between real-world clones due to the difficulty of collecting datasets for cross-language CCD. This creates a data bottleneck problem: data scale and quality issues will cause that model with a better design can still not reach its full potential. To mitigate this, we propose a tree autoencoder (TAE) architecture. It uses unsupervised learning to pretrain with abstract syntax trees (ASTs) of a large-scale dataset, then finetunes the trained encoder in the downstream CCD task. Our proposed TAE contains a tree Long Short-Term Memory (LSTM) encoder and a tree LSTM decoder. We design a novel embedding method for AST nodes, including type embedding and value embedding. In the training of TAE, we present an "encode and decode by layers" strategy and a node-level batch size design. For the CCD dataset, we propose a negative sampling method based on probability distribution. The experimental results on two datasets verify the effeteness of our embedding method, as well as that TAE and its pretrain enhance the performance of the CCD model. The node context information is well captured, and the reconstruction accuracy of the node-value reaches 95.45%. TAE pretrain improves the performance of CCD with a 4% increase in F1 score, which alleviates the data bottleneck problem.

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Long-term Preservation of Electronic Record Based on Digital Continuity in Smart Cities

Cited by 23 publications

References 25 publications

Structured Graded Lung Rehabilitation for Children with Mechanical Ventilation

Structured Graded Lung Rehabilitation for Children with Mechanical Ventilation

Correlation Analysis between Economic Growth and Environmental Quality

Improve Representation for Cross-Language Clone Detection by Pretrain Using Tree Autoencoder

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