Association rules are used in different data mining applications, including Web mining, intrusion detection, and bioinformatics. This study mainly discusses the COVID‐19 patient diagnosis and treatment data mining algorithm based on association rules. General data The key time interval during the main diagnosis and treatment process (including onset to dyspnea, first diagnosis, admission, mechanical ventilation, death, and the time from first diagnosis to admission, etc.), the cause of death by laboratory examination, and so forth. The frequency of drug use was counted and association rule algorithm was used to analyse and study the effect of drug treatment. The results could provide reference for rational drug use in COVID‐19 patients. In this study, in order to improve the efficiency of data mining in data processing, it is necessary to pre‐process these data. Secondly, in the application of this data mining, the main objective is to extract association rules of COVID‐19 complications. So its properties for mining should be various diseases. Therefore, it is necessary to classify individual disease types. During the construction of association rules database, the data in the data warehouse is analysed online and the association rules data mining is analysed. The results are stored in the knowledge base for decision support. For example, the prediction results of the decision tree can be displayed at this level. After the construction of the mining model, the display interface can be mined, and the decision‐maker can input the corresponding attribute value and then predict it. 0.76% of people had both COVID‐19, CHD and hypertension, while 46.5% of people with COVID‐19 and CHD were likely to have hypertension. This study is helpful to analyse the imaging factors of COVID‐19 disease.

Aiming at the limitation by the high cost of test and length cycle process of the CNC grinding machine reliability evaluation, this article adopted small sample technology which needs less data while getting higher evaluation accuracy, by using the theory of Bayes theorem and failure rate as of the random variables, the experiment data of tracking CNC grinding machine for a year is analyzed. Results indicate that results acquired by this mean are consistent with the actual; meanwhile, it shortens test cycle and reduces cost, which is a very effective way to analysis CNC grinding machine. Therefore, it’s very essential that the small sample technology research is applied in the CNC grinding machine evaluation.

Fatigue crack growth rates (FCGRs) of X70 pipeline steel base metal (BM) and heat affected zone (HAZ) were studied in the hydrogen sulphide environment. X-ray diffraction method was used to measure the residual stress of BM and HAZ. Modified wedge open loaded specimen was selected for the test in the simulated actual working conditions. In the saturated H 2 S environment, the crack growth experiments were carried out under low frequency (f50?01 Hz) and three stress ratios (R50?7, 0?8 and 0?9). Results showed that there was obvious residual tensile stress in HAZ. The presence of H 2 S greatly accelerated the FCGR. With rising stress ratio, crack closure effect weakened, and then the increasing degree of hydrogen embrittlement of the crack tip leads to FCGR acceleration. Microstructure defects, inclusions and high residual tensile stress of HAZ made the FCGR of this area higher than the FCGR of BM. Scanning electron microscopy scans of the fracture suggested that the fracture mode of the corrosion fatigue of the X70 material belonged to brittle fracture. Cleavage fracture was the dominant form. The differences between corrosion fatigue fracture morphologies of BM and HAZ were not very large, and the relief of the fracture of HAZ was larger and the cracks longer.

In the era of rapid development of information technology, the application of smart sensors is becoming more and more extensive. All measurement and control equipment need to obtain raw data through sensors, and machines can also obtain various information through sensors. And this information, especially from the perspective of reliability, accuracy, and intelligent interaction, requires higher interactivity in people’s lives. In order to solve the problem that the existing interactive design is difficult and not intelligent enough, and the information fusion is not uniform enough, the results of the design have various deviations. This article intends to design through the use of smart sensors and information fusion technology to make an improvement to its interactive art design.

Fatigue crack growth rates of 4130X steel used for compressed natural gas vessels were investigated in this paper. Considering the operating conditions, corrosion fatigue tests at a low frequency of 0?0067 Hz, in H 2 S saturated, H 2 S unsaturated and air environments were conducted on modified wedge opening load specimens by using a home made low cycle fatigue test system. Curve fitting was applied to the fatigue test data of da/dN-DK according to Paris formula. A correlation study between fracture surface and stress intensity factor range was conducted and K values for three stages in different environments were characterised quantitatively. The results show that da/dN in H 2 S environment is more than 20 times faster than in an air environment. When the H 2 S concentration reaches a certain range, the increase of da/dN becomes slower than that of the H 2 S concentration. da/dN differs by 2?4 times while the concentration differs by 11 times. The corrosive environment accelerates the fatigue failure.