Xiaoning Li, Xinbo Liao, Qingwen Zhong, Kai Zheng, Shaoxing Chen, Xiao-Jun Chen, Jin-Xiu Zhu and Hongyuan Yang
The purpose of this paper is to analyze the influencing factors of patients’ financial burden through a case study of hospital on public‒private partnerships (PPP) model (Chaonan…
Abstract
Purpose
The purpose of this paper is to analyze the influencing factors of patients’ financial burden through a case study of hospital on public‒private partnerships (PPP) model (Chaonan Minsheng Hospital of Guangdong Province) and provide some useful information to policymakers for better development of hospitals on PPP model.
Design/methodology/approach
There are total six indicators that are defined as patients’ financial burden, basing on the policy of “indicators of medical quality management and control on the third level large general hospital (2011 edition),” issued by Chinese Government. In total, 23 potentially influencing factors of patients’ financial burden for hospital on PPP model were chosen from the above policy. The five-year (2007‒2011) data for the above 29 indicators come from statistic department of hospital on PPP model. Grey relational analysis (GRA) was applied to analyze the influencing factors of patients’ financial burden for hospital on PPP model.
Findings
A clear rank of influencing factors of patients’ financial burden is obtained and suggestions are provided from results of GRA, which provide reference for policymakers of hospital on PPP model. The five main influencing factors of patients’ financial burden for hospital on PPP model, in sequence, are rescuing critical ill patients on emergency, rescuing critical ill inpatients, inpatient bed occupancy rate, working days per bed and medical building area.
Originality/value
The study on the influencing factors of patients’ financial burden for hospital on PPP model not only provides decision-making for policymaker of hospital and controlling of medical expenditure but also contributes to release patients’ financial burden for hospitals on PPP model.
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Xiaoning Li, Xinbo Liao, Xuerui Tan and Haijing Wang
The purpose of this paper is to evaluate resource configuration and service ability in hospital on public private partnership (PPP) model (Chaonan Minsheng Hospital of Guangdong…
Abstract
Purpose
The purpose of this paper is to evaluate resource configuration and service ability in hospital on public private partnership (PPP) model (Chaonan Minsheng Hospital of Guangdong Province), supplying decision-making reference for participants of hospital on PPP model.
Design/methodology/approach
Four model of grey relational analysis (GRA) (Deng's correlation degree, grey absolute correlation degree, grey relative correlation degree and grey comprehensive correlation degree) are applied to evaluate resource configuration and service ability, a total of 11 indicators of hospital on PPP model public hospital and private hospital from 2007 to 2011.
Findings
The paper finds that different GRA models have different results when the paper applied them to evaluate resource configuration and service ability in hospital on PPP model. More than 60 per cent indicators of resource configuration (total six indicators) and service ability (total six indicators) are assessed as “hospital on PPP model ≻ public hospital” or “hospital on PPP model≻ private hospital” from three models of Deng's correlation degree, grey absolute correlation degree and grey comprehensive correlation degree.
Practical implications
Evaluation of resource configuration and service ability for hospital on PPP model with GRA makes results quantified objective and provides reference for decision making and management. GRA makes the comparison of resource configuration and service ability between hospital on PPP model and other model hospitals becoming possible.
Originality/value
The shortcoming for data analysis method of “large sample” is overcome and data analysis method of “small sample” is realized by using GRA, which broaden the method of evaluating hospital on PPP model.
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Luya Yang, Xinbo Huang, Yucheng Ren, Qi Han and Yanchen Huang
In the process of continuous casting and rolling of steel plate, due to the influence of rolling equipment and process, there are scratches, inclusions, patches, scabs and pitted…
Abstract
Purpose
In the process of continuous casting and rolling of steel plate, due to the influence of rolling equipment and process, there are scratches, inclusions, patches, scabs and pitted surfaces on the surface of steel plate, which will not only affect the corrosion resistance, wear resistance and fatigue strength of steel plate but also may cause production accidents. Therefore, the detection of steel plate surface defect must be strengthened to ensure the production quality of steel plate and the smooth development of industrial construction.
Design/methodology/approach
(1) A steel plate surface defect detection technology based on small datasets is proposed, which can detect multiple surface defects and fill in the blank of scab defect detection. (2) A detection system based on intelligent recognition technology is built. The steel plate images are collected by the front-end monitoring device, then transmitted to the back-end monitoring center and processed by the embedded intelligent algorithms. (3) In order to reduce the impact of external light on the image, an improved Multi-Scale Retinex (MSR) enhancement algorithm based on adaptive weight calculation is proposed, which lays the foundation for subsequent object segmentation and feature extraction. (4) According to the different factors such as the cause and shape, the texture and shape features are combined to classify different defects on the steel plate surface. The defect classification model is constructed and the classification results are recorded and stored, which has certain application value in the field of steel plate surface defect detection. (5) The practicability and effectiveness of the proposed method are verified by comparison with other methods, and the field running tests are conducted based on the equipment commissioning field of China Heavy Machinery Institute.
Findings
When applied to small dataset, the precision of the proposed method is 94.5% and the time is 23.7 ms. In order to compare with deep learning technology, after expanding the image dataset, the precision and detection time of this paper are 0.948 and 24.2 ms, respectively. The proposed method is superior to other traditional image processing and deep learning methods. And the field recognition precision is 91.7%.
Originality/value
In brief, the steel plate surface defect detection technology based on computer vision is effective, but the previous attempts and methods are not comprehensive and the accuracy and detection speed need to be improved. Therefore, a more practical and comprehensive technology is developed in this paper. The main contributions are as follows: (1) A steel plate surface defect detection technology based on small datasets is proposed, which can detect multiple surface defects and fill in the blank of scab defect detection. (2) A detection system based on intelligent recognition technology is built. The steel plate images are collected by the front-end monitoring device, then transmitted to the back-end monitoring center and processed by the embedded intelligent algorithms. (3) In order to reduce the impact of external light on the image, an improved MSR enhancement algorithm based on adaptive weight calculation is proposed, which lays the foundation for subsequent object segmentation and feature extraction. (4) According to the different factors such as the cause and shape, the texture and shape features are combined to classify different defects on the steel plate surface. The defect classification model is constructed and the classification results are recorded and stored, which has certain application value in the field of steel plate surface defect detection. (5) The practicability and effectiveness of the proposed method are verified by comparison with other methods, and the field running tests are conducted based on the equipment commissioning field of China Heavy Machinery Institute.
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Xueli Song, Fengdan Wang, Rongpeng Li, Yuzhu Xiao, Xinbo Li and Qingtian Deng
In structural health monitoring, localization of multiple slight damage without baseline data is significant and difficult. The purpose of this paper is to discuss these issues.
Abstract
Purpose
In structural health monitoring, localization of multiple slight damage without baseline data is significant and difficult. The purpose of this paper is to discuss these issues.
Design/methodology/approach
Damage in the structure causes singularities of displacement modes, which in turn reveals damage. Methods based on the displacement modes may fail to accurately locate the slight damage because the slight damage in engineering structure results in a relatively small variation of the displacement modes. In comparison with the displacement modes, the strain modes are more sensitive to the slight damage because the strain is the derivative of the displacement. As a result, the slight variation in displacement data will be magnified by the derivative, leading to a significant variation of the strain modes. A novel method based on strain modes is proposed for the purpose of accurately locating the multiple slight damage.
Findings
In the two bay beam and steel fixed-fixed beams, the numerical simulations and the experimental cases, respectively, illustrate that the proposed method can achieve more accurate localization in comparison with the one based on the displacement modes.
Originality/value
The paper offers a practical approach for more accurate localization of multiple slight damage without baseline data. And the robustness to measurement noise of the proposed method is evaluated for increasing levels of artificially added white Gaussian noise until its limit is reached, defining its range of practical applicability.
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Xinbo Wang, Zhongwei Yin, Hulin Li, Gengyuan Gao and Jun Cao
The purpose of this paper is to study the frictional behaviors of CuAl10Fe3 journal bearings sliding against chromium electroplated 42CrMo shafts and diamond-like carbon-coated…
Abstract
Purpose
The purpose of this paper is to study the frictional behaviors of CuAl10Fe3 journal bearings sliding against chromium electroplated 42CrMo shafts and diamond-like carbon-coated 42CrMo shafts, respectively, under two different conditions and to compare the two kinds of friction pairs.
Design/methodology/approach
All journal bearing samples underwent 24 h running-in and repeatability verification. Then, the journal bearing friction experiments were carried out under two different conditions. After testing, the torques, friction coefficients, power consumptions and other parameters were obtained.
Findings
The pair of CuAl10Fe3 journal bearing and diamond-like carbon–coated shaft could drive greater load to start up than the pair of CuAl10Fe3 journal bearing and chromium electroplated 42CrMo shaft, but it had greater power consumption during the steady running period under the identical condition. With the changing of specific pressure or rotational speed, the friction coefficients had different variations. The frictional oscillations appeared at 32 rotations per minute under heavy loads for both kinds of pairs, the oscillation frequencies were equal to rotational frequency of the test shaft and the oscillation amplitude for diamond-like carbon coating was much greater.
Originality/value
These results have guiding significance for practical industrial applications.