• Applied Chemistry for Engineering
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• v.32 no.1
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• pp.75-82
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• 2021

This study investigated the fire risk assessment of woods and plastics for construction materials, focusing on the fire performance index-III (FPI-III), fire growth index-III (FGI-III), and fire risk index-IV (FRI-IV) by a newly designed method. Japanese cedar, red pine, polymethylmethacrylate (PMMA), and polyvinyl chloride (PVC) were used as test pieces. Fire characteristics of the materials were investigated using a cone calorimeter (ISO 5660-1) equipment. The fire performance index-III measured after the combustion reaction was found to be 1.0 to 15.0 with respect to PMMA. Fire risk by fire performance index-III increased in the order of PVC, red pine, Japanese cedar, and PMMA. The fire growth index-III was found to be 0.5 to 3.3 based on PMMA. Fire risk by fire growth index-III increased in the order of PVC, PMMA, red pine, and Japanese cedar. COpeak concentrations of all specimens were measured between 106 and 570 ppm. In conclusion, it is understood that Japanese cedar with a low bulk density and PMMA containing a large amount of volatile organic substances have a low fire performance index-III and high fire growth index-III, and thus have high fire risk due to fire. This was consistent with the fire risk index-IV.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.620-626
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• 2020

This research propose and simulate a solar power generation system monitoring system based on Modbus TCP communication using RaspberryPi, an IOT equipment, as a master and an inverter as a slave. In this model, various sensors are added to the RaspberryPi to add necessary information for monitoring solar power plants, and power generation prediction and monitoring information are transmitted to the smart phone through real-time power generation prediction. In addition, information that is continuously generated by the solar power plant is built on the server as big data, and a deep learning model for predicting power generation is trained and updated. As a result of the study, stable communication was possible based on Modbus TCP with the Raspberry Pi in the inverter, and real-time prediction was possible with the deep learning model learned in the Raspberry Pi. The server was able to train various deep learning models with big data, and it was confirmed that LSTM showed the best error with a learning error of 0.0069, a test error of 0.0075, and an RMSE of 0.0866. This model suggested that it is possible to implement a real-time monitoring system that is simpler, more convenient, and can predict the amount of power generation for inverters of various manufacturers.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.555-564
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• 2021

Thalamus is known to play an important role in the regulation of nerve function. Thalamus, located in the center of the brain, is involved in sleep, arousal, and emotional regulation, and has been reported to be associated with multiple sclerosis, essential tremors, and neurodegenerative diseases such as Parkinson's disease. In addition, it has been reported that iron deposits in the thalamus can cause depressive symptoms with age. Although there are discrepancies between studies, it can be deduced that the thalamus region has a clear effect on neurological disorders due to a strong relationship between the thalamus and neurological functions such as emotional control and processing. Through tractography analysis, the connectivity between the detailed areas of each subcortical region was investigated in the form of a matrix, showing strong connectivity and weak interhemispheric connectivity. In the 59> group, the WM connectivity of thalamus was found to be weaker than those of the two groups. Comparisons between the two groups showed that the young groups (10-39 and 40-59) had higher connection intensity than the 59> group and that statistically significant differences in 3 connection pathways were found in each hemisphere. A decrease in thalamus-related connection strength in aging has shown that it can affect emotional and neurological disorders such as anxiety and depression, and network measurements can help assess cognitive impairment across clinical conditions.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.38-50
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• 2022

Purpose: The goal of this research is to create a numerical analytic database that may assist fire prevention managers and building officials in prioritizing items that need to be addressed in order to improve evacuation safety performance while working within a constrained budget and time frame. Method: It was carried out utilizing the CFD Tool, a quantitative evaluation approach, to assess evacuation safety. One direct staircase-type apartment houses and one corridor-type apartment were chosen to make it. Result: In the fire compartment category, Apartment A's evacuation time was around 130 percent longer than that of sprinkler facilities. Conclusion: Fire prevention managers and building officials feel that starting with a single level and implementing "dwelling unit separations" will increase evacuation safety, and that maintaining fire compartments and sprinkler systems at all times will be effective. Because of the limited characteristics of smoke propagation in corridor-type apartments compared to direct staircase-type flats, it is thought that fire extinguishing equipment should be addressed.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.299-306
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• 2022

In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.

• Tunnel and Underground Space
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• v.32 no.3
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• pp.194-202
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• 2022

An increased number of cases have occurred in applying ICT technology in the resource development field due to factors such as safety, eco-friendliness, and low cost since the 2000s. In Korea, the 2nd mining master plan specified the significance of converging the full cycle of mining and ICT, while the 3rd mining master plan highlighted ICT and smart mining such as supporting the supply of an ICT mining device and introducing demonstrational smart mining. This study introduces the application of an ICT device and safety system operation in the Jangseong underground mine of Korea Cement Co., Ltd. Currently, Jangseong mine combines two different kinds of 3D equipment including the handheld 3D scanner and multi-station that provides both the measurement and 3D scanning to perform a 3D measurement of the mine. Taken from the 3D measurement of the mine, it is now possible to identify any hazardous areas and abnormalities in different directions and analyze the safety of the crown pillar between two stopes in different level. Besides, the real-time location tracking and communications system have established highly efficient rescue and evacuation plans to effectively deal with any accidents in the mine.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.863-872
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• 2022

Rare earth elements (REEs) have been used as one of power tracers for understanding geological and environmental changes due to their similar physico-chemical properties. In this study, we investigated the characteristics of rare earth elements in atmospheric particulates(PM_2.5) collected in Beijing and Gwangju during January 2018. The total concentrations of REEs in the Beijing samples were about 16X higher than those in Gwangju samples, and both samples are enriched in light REE than heavy REE, up to 8-10 times. The Post Archean Australian Shale (PAAS)-normalized pattern showed that both samples are enriched in Eu, Tb, and Er, and displayed positive Eu but negative Ce anomalies. The elemental correlations indicate that both samples originated from China desert and Loess plateau as well as cities surrounding Beijing. This study suggests that REEs in PM_2.5 can be used as a powerful proxy of revealing the difference between China and Korea, and provide basic information on the source and transport of PM_2.5.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.421-428
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• 2022

The earthwork is a core process of all constructions, and compaction measurement of earthwork play an important role in improving productivity. The analog tests such as Plate Bearing Test and Sand-cone occupy current compaction measurement techniques. Due to advanced 4th Industrial Revolution, research on analog tests combined smart construction technology are actively conducted. DCPT (Dynamic Cone penetration Test), simpler and faster than conventional tests, has recently on rise. However, it is also an analog that measures data manually and has several disadvantages such as history management and data verification. The IoT-based DCPT system developed in this study combines digital wire sensors, mobile phones, and Bluetooth with conventional DCPT. Compare to conventional test methods, IoT-based DCPT has advantages such as performance time, single-person measurement, low cost, mobile-based management, and real-time data verification. In addition, a test bed was built to verify IoT-based DCPT. The test bed was built under similar conditions to the actual earthworks site through roller equipment. DCPT data obtained from 322 stations. As a result, IoT-based DCPT showed good performance, and the test bed was also showed stable results as the compaction was carried out.

• Journal of Appropriate Technology
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• v.7 no.1
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• pp.41-50
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• 2021

Gongali model Co. Ltd located in Arusha, Tanzania is operating a Nanofilter water station using locally produced bone char to remove fluoride in groundwater. Bone char produced locally had a high turbidity and high concentration of organic matter, which cause color. In addition, since the fluorine adsorption efficiency is low, there is a problem in high maintenance cost due to a short replacement cycle of bone char. In order to overcome this challenge, our research team was that a local furnace was manufactured and applied for produce high adsorption bone char in Gongali model Co. Ltd. By producing high-adsorption bone char locally, the operating efficiency of the Nanofilter water station increased, and it was possible to stably and continuously provide drinking water to local residents. In addition, by presenting a sustainable business model to Gongali model Co Ltd, the persistence of high adsorption bone char and a plan to spread the Nanofilter water station were suggested. Therefore, it was possible to propose a plan to continuously supply low-cost drinking water to the low-income and the neglected class through this local project.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.403-410
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• 2021

There are positive effects, such as pain reduction, when rheumatism patients exercise in water, but the cause of the pain reduction is unclear, and research on this is inadequate. This study examined the flow of the surface of the foot and the principles of pain relief. Unsteady simulations were conducted to analyze the flow, which was performed by repeatedly setting the movement of the foot raising and descending three times. Pressure fluctuations and frequencies were analyzed by designating pressure points at the painful location. The results showed that a positive and negative pressure of approximately ±500Pa was applied overall. A pressure of approximately ±2000Pa was applied when the direction of movement was changed. A frequency of approximately 35 to 80Hz was generated in the area where rheumatoid arthritis pain frequently occurs. The effects of reducing pain could be predicted when continuous pressure fluctuations and frequencies are applied repeatedly to the painful location, blood circulation promotion. The results could be used as basic data to understand the principles of aquatic exercise and support the development of underwater exercise programs and developing related medical equipment.