Stroke is one of the major causes of death worldwide, and in Korea, it has the second highest mortality rate after cancer. Stroke patients require continuous observation and rehabilitation treatment after onset, and in particular, paralysis symptoms are likely to worsen during rehabilitation, emphasizing the need for a real-time monitoring system. Meanwhile, the importance of medical data quality control (QC) algorithms is increasing. In this study, various causes such as failure of sensors such as voltage, current, and temperature of the patient's imaging device diagnostic device, or power loss, may cause malfunctions and transmit inaccurate data. Therefore, in order to secure the reliability of the patient's imaging device diagnostic device data, we plan to design data analysis and algorithms based on QC data of the imaging device diagnostic device. In order to design data analysis and algorithms based on QC data, a system capable of measuring and analyzing sensor data of imaging device diagnostic equipment was built. The reference values of the algorithms to be developed, such as physical limit tests, continuity tests, step tests, median filter tests, and frequency distribution tests, were derived. Voltage, current, and temperature sensor data were statistically analyzed, and in the case of analysis that changes in real time, algorithm S/W was inserted to calculate in real time. It is judged that by monitoring in real time, efficient management and maintenance of the device, and rapid response to device failures will be possible. In the case of device failure, various accidents and high costs can occur. Therefore, if real-time failures are confirmed and rapid maintenance is possible, maintenance costs can be reduced and reliability can be improved, so it is judged that efficient management of the device will be possible.

This study conducted frequency analysis, reliability analysis, descriptive statistics, and correlation analysis to determine the impact of quality control managers' perception and implementation of KS certification factory inspection evaluation items on follow-up management. Through a multiple linear regression model, the influence of KS certification officer's awareness and implementation of KS certification factory inspection on post management was found to have a positive (+) influence on post management, with implementation having a greater influence on post management than awareness. It was having an impact. The independent variable (perception) has a statistically significant impact on the mediating variable (execution), and in the stage of verifying the mediating effect, the influence of the independent variable (perception) on the dependent variable (follow-up management) has a statistically significant impact. , In the stage where the independent variable (perception) and the mediator (implementation) are input simultaneously, both the independent variable and the mediator have a statistically significant effect on the dependent variable, indicating that there is a mediation effect.

In this study, the QA/QC test for the combined application of DNPH cartridge – HPLC/UV method was investigated in the collection and analysis of formaldehyde in air using three types of DNPH cartridge samplers made by three independent manufacturers. For these experiments, gaseous standards of formaldehyde (FA) were prepared at 7 concentration levels that fell in the range of 44.1~3400 nmol/mol. According to our analysis, the levels of cartridge blank (0.13 ~ 0.26 ng) are found to be fairly high to require routine check up for each experiment. The recovery patterns of FA were highly comparable between different cartridge products, when standard gases are supplied in the concentration range up to 177 nmol/mol. All 3 types of DNPH cartridge exhibited highly similar recovery rates at concentrations below 1.7 ㎛ol/mol, while the maximum recovery was attained from the product B. The overall results of our study suggest that one should calibrate the samples in the optimal range of recovery with routine check up of blank values.