Comprehensive multivariate grey incidence degree based on principal component analysis

To overcome the too fine-grained granularity problem of multivariate grey incidence analysis and to explore the comprehensive incidence analysis model, three multivariate grey incidences degree models based on principal component analysis （PCA） are proposed. Firstly, the PCA method is introduced to extract the feature sequences of a behavioral matrix. Then, the grey incidence analysis between two behavioral matrices is transformed into the similarity and nearness measure between their feature sequences. Based on the classic grey incidence analysis theory, absolute and relative incidence degree models for feature sequences are constructed, and a comprehensive grey incidence model is proposed. Furthermore, the properties of models are researched. It proves that the proposed models satisfy the properties of translation invariance, multiple transformation invariance, and axioms of the grey incidence analysis, respectively. Finally, a case is studied. The results illustrate that the model is effective than other multivariate grey incidence analysis models.

Grey incidence clustering method based on multidimensional dynamic time warping distance

The traditional grey incidence degree is mainly based on the distance analysis methods, which is measured by the displacement difference between corresponding points between sequences. When some data of sequences are missing (inconsistency in the length of the sequences), the only way is to delete the longer sequences or to fill the shorter sequences. Therefore, some uncertainty is introduced. To solve this problem, by introducing three-dimensional grey incidence degree (3D-GID), a novel GID based on the multidimensional dynamic time warping distance (MDDTW distance-GID) is proposed. On the basis of it, the corresponding grey incidence clustering (MDDTW distance-GIC) method is constructed. It not only has the simpler computation process, but also can be applied to the incidence comparison between uncertain multidimensional sequences directly. The experiment shows that MDDTW distance-GIC is more accurate when dealing with the uncertain sequences. Compared with the traditional GIC method, the precision of the MDDTW distance-GIC method has increased nearly 30%.

Using an Interprofessional Lens to Analyze Serious Adverse Events in a Teaching Hospital: An Analysis with the TeamSTEPPS® Framework

This paper explores the contribution of teamwork skills in serious adverse events, using the TeamSTEPPS® framework. Adverse events are the undesirable events that are not due to the natural course of a disease;they are considered serious when they prolong a hospital stay, lead to a physical disability or to death. Failures in teamwork, particularly with interprofessional teams, can lead to potential risks to patient safety. Using a dataset of de-identified reports of serious adverse events in 2016 in a tertiary teaching hospital, we explored the contribution of teamwork skills according to the TeamSTEPPS® framework to these adverse events. We found that 61% of the 41 analyzed events involved failures in teamwork skills, with 80% of these involving communication, 52% in situation monitoring and team structure, 44% in mutual support and 40% in leadership. Sixty-four percent of the events involved more than one teamwork component. Our findings emphasize the need to improve teamwork training in healthcare, focusing not only on communication, but also on other teamwork skills as they often contribute together in adverse events. Future analyses of serious adverse events should include a focus on teamwork competencies, to guide the development of future quality and safety training programs.

The Time Series Weight－changing Grey Incidence Analysis of the Development of Agricultural Mechanization in China

This paper studies quantitatively the intensity of influence and internal incident mechanism of the different influential factors on field crop cultivation mechanization by the method of Grey Incidence Analysis.Because of the need of the identification of the time series effect and the changing trend of each influential factor,the time series weight changing Grey incident model is put forward.On this basis,the paper discusses the situation and problems of the development of agricutural me chanization in China.

Trend analysis of cancer incidence and mortality in China

The National Central Cancer Registry of China(NCCRC)updated their nationwide statistics of cancer incidence and mortality in China according to 2013 population-based cancer registration data(due to the time required for data collection,quality control and analysis,the latest cancer statistics available in China have a 3-year lag behind the current year).In this report,the NCCRC provides a comprehensive review of cancer incidence and mortality rates,as well as the statistics overall and by geographical area,cancer sites or age groups(Chen et al.,2017a).It shows that the burden of cancer

Incident analyses of frost heaving failure of municipal underground gas pipelines in cold regions of northern China

In the cold regions of northern China, incidents of municipal underground gas pipeline rupture and leakage occur quite fi-equently, aaost often in winter. To prevent harm to citizen safety and property, analysis of the causes of such cracking and leakage is therefore valuable. Two incident analyses are discussed here and the reasons why most of these types of cases occur dttring winter are clarified. Fhe effects of vehicle loadings above buried pipelines are calculated and compared with the effects and calculations of frost heaving forces. We demonstrate thtit when the soil layer above a pipeline freezes rapidly, the soil generates repeated frost heaving, which exerts heaving forces on the pipeline that can result in fatigue crack propagation and ultimate pipeline failure. Therefore, the incident induced 9y frost heaving is one of the primary reasons of gas pipeline failure. Based on these analyses, we present some recommendations pertaining to the proper design, construction, and management of gas pipelines.