Calibration of Portable Particulate Matter-Monitoring Device using Web Query and Machine Learning.

BACKGROUND: Monitoring and control of PM2.5 are being recognized as key to address health issues attributed to PM2.5. Availability of low-cost PM2.5 sensors made it possible to introduce a number of portable PM2.5 monitors based on light scattering to the consumer market at an affordable price. Accuracy of light scattering-based PM2.5 monitors significantly depends on the method of calibration. Static calibration curve is used as the most popular calibration method for low-cost PM2.5 sensors particularly because of ease of application. Drawback in this approach is, however, the lack of accuracy. METHODS: This study discussed the calibration of a low-cost PM2.5-monitoring device (PMD) to improve the accuracy and reliability for practical use. The proposed method is based on construction of the PM2.5 sensor network using Message Queuing Telemetry Transport (MQTT) protocol and web query of reference measurement data available at government-authorized PM monitoring station (GAMS) in the republic of Korea. Four machine learning (ML) algorithms such as support vector machine, k-nearest neighbors, random forest, and extreme gradient boosting were used as regression models to calibrate the PMD measurements of PM2.5. Performance of each ML algorithm was evaluated using stratified K-fold cross-validation, and a linear regression model was used as a reference. RESULTS: Based on the performance of ML algorithms used, regression of the output of the PMD to PM2.5 concentrations data available from the GAMS through web query was effective. The extreme gradient boosting algorithm showed the best performance with a mean coefficient of determination (R2) of 0.78 and standard error of 5.0 µg/m3, corresponding to 8% increase in R2 and 12% decrease in root mean square error in comparison with the linear regression model. Minimum 100 hours of calibration period was found required to calibrate the PMD to its full capacity. Calibration method proposed poses a limitation on the location of the PMD being in the vicinity of the GAMS. As the number of the PMD participating in the sensor network increases, however, calibrated PMDs can be used as reference devices to nearby PMDs that require calibration, forming a calibration chain through MQTT protocol. CONCLUSIONS: Calibration of a low-cost PMD, which is based on construction of PM2.5 sensor network using MQTT protocol and web query of reference measurement data available at a GAMS, significantly improves the accuracy and reliability of a PMD, thereby making practical use of the low-cost PMD possible.

Control of Industrial Safety Based on Dynamic Characteristics of a Safety Budget-Industrial Accident Rate Model in Republic of Korea.

BACKGROUND: Despite the recent efforts to prevent industrial accidents in the Republic of Korea, the industrial accident rate has not improved much. Industrial safety policies and safety management are also known to be inefficient. This study focused on dynamic characteristics of industrial safety systems and their effects on safety performance in the Republic of Korea. Such dynamic characteristics are particularly important for restructuring of the industrial safety system. METHODS: The effects of damping and elastic characteristics of the industrial safety system model on safety performance were examined and feedback control performance was explained in view of cost and benefit. The implications on safety policies of restructuring the industrial safety system were also explored. RESULTS: A strong correlation between the safety budget and the industrial accident rate enabled modeling of an industrial safety system with these variables as the input and the output, respectively. A more effective and efficient industrial safety system could be realized by having weaker elastic characteristics and stronger damping characteristics in it. A substantial decrease in total social cost is expected as the industrial safety system is restructured accordingly. CONCLUSION: A simple feedback control with proportional-integral action is effective in prevention of industrial accidents. Securing a lower level of elastic industrial accident-driving energy appears to have dominant effects on the control performance compared with the damping effort to dissipate such energy. More attention needs to be directed towards physical and social feedbacks that have prolonged cumulative effects. Suggestions for further improvement of the safety system including physical and social feedbacks are also made.

A wearable intravenous infusion device facilitating ambulation: a pre-clinical report.

A wearable ambulatory intravenous infusion device (AIVD) has been developed to facilitate the ambulation of patients. To enhance ambulation, a wearable AIVD was designed and a prototype was developed that consists of an air bag, a reciprocating air pump, a drip rate sensor, and a microprocessor-based controller. Using air pressure as a source for actuation greatly contributes to decreasing the weight of the proposed device and the power consumption. Experimental results show that the proposed infusion device can provide a variety of flow rates ranging from 36-90 mL h(-1) with less than a 10% error. A series of experiments were performed with the prototype of the proposed device at a wide range of flow rates and the results verify that the accuracy and controllability of the prototype is comparable with those of the current intravenous infusion devices available. It is expected that the AIVD significantly contributes to the early recovery of patients by offering a convenient and cost-effective means of ambulation.

Acoustic streaming induced by ultrasonic flexural vibrations and associated enhancement of convective heat transfer.

Acoustic streaming induced by ultrasonic flexural vibrations and the associated convection enhancement are investigated. Acoustic streaming pattern, streaming velocity, and associated heat transfer characteristics are experimentally observed. Moreover, analytical analysis based on Nyborg's formulation is performed along with computational fluid dynamics (CFD) simulation using a numerical solver CFX 4.3. Two distinctive acoustic streaming patterns in half-wavelength of the flexural vibrations are observed, which agree well with the theory. However, acoustic streaming velocities obtained from CFD simulation, based on the incompressible flow assumption, exceed the theoretically estimated velocity by a factor ranging from 10 to 100, depending upon the location along the beam. Both CFD simulation and analytical analysis reveal that the acoustic streaming velocity is proportional to the square of the vibration amplitude and the wavelength of the vibrating beam that decreases with the excitation frequency. It is observed that the streaming velocity decreases with the excitation frequency. Also, with an open-ended channel, a substantial increase in streaming velocity is observed from CFD simulations. Using acoustic streaming, a temperature drop of 40 degrees C with a vibration amplitude of 25 microm at 28.4 kHz is experimentally achieved.