• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.27 no.1
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• pp.38-45
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• 2017

Objectives: Radon may be second only to smoking as a cause of lung cancer. Radon is a colorless, tasteless radioactive gas that is formed via the radioactive decay of radium. Therefore, radon levels can build up based on the amount of radium contained in construction materials such as phospho-gypsum board or when ventilation rates are low. This study provides our findings from evaluation of radon gas at facilities and offices in an industrial complex. Methods: We evaluated the office rooms and processes of 12 manufacturing factories from May 14, 2014 to September 23, 2014. Short-term data were measured by using real-time monitoring detectors(Model 1030, Sun Nuclear Co., USA) indoors in the office buildings. The radon measurements were recorded at 30-minute intervals over approximately 48 hours. The limit of detection of this instrument is $3.7Bq/m^3$. Also, long-term data were measured by using ${\alpha}-track$ radon detectors(${\alpha}-track$, Rn-tech Co., Korea) in the office and factory buildings. Our detectors were exposed for over 90 days, resulting in a minimum detectable concentration of $7.4Bq/m^3$. Detectors were placed 150-220 cm above the floor. Results: Radon concentrations averaged $20.6{\pm}17.0Bq/m^3$($3.7-115.8Bq/m^3$) in the overall area. The monthly mean concentration of radon by building materials were in the order of gypsum>concrete>cement. Radon concentrations were measured using ${\alpha}-track$ in parallel with direct-reading radon detectors and the two metric methods for radon monitoring were compared. A t-test for the two sampling methods showed that there is no difference between the average radon concentrations(p<0.05). Most of the office buildings did not have central air-conditioning, but several rooms had window- or ceiling-mounted units. Employees could also open windows. The first, second and third floors were used mainly for office work. Conclusions: Radon levels measured during this assessment in the office rooms of buildings and processes in factories were well below the ICRP reference level of $1,000Bq/m^3$ for workplaces and also below the lower USEPA residential guideline of $148Bq/m^3$. The range of indoor annual effective dose due to radon exposure for workers working in the office and factory buildings was 0.01 to 1.45 mSv/yr. Construction materials such as phospho-gypsum board, concrete and cement were the main emission sources for workers' exposure.

• Journal of the Korean Institute of Gas
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• v.25 no.3
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• pp.27-38
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• 2021

We devised the system to automatically shutdown the boiler and to fundamentally block the harmful gases, including carbon monoxide, into the indoor when the exhaust system swerves: (1) The discharge pressure of the exhaust gas decreases when the exhaust pipe is disconnected. The monitoring system of the exhaust pipe is implemented by measuring the output voltage of APS(Air Pressure Sensor) installed to control the amount of combustion air. (2) The operating software was modified so that when the system recognizes the fault condition of a flue pipe, the boiler control unit displays the fault status on the indoor regulator while shutting down the boiler. In accordance with the ventilation facility standards in the "Rules for Building Equipment Standards" by the Ministry of Land, Infrastructure and Transport, experiments were conducted to ventilate indoor air. When carbon monoxide leaked in worst-case scenario, it was possible to prevent poisoning accidents. However, since 2013, the number of indoor air exchange times has been mitigated from 0.7 to 0.5 times per hour. We observed the concentration exceeding TWA 30 ppm occasionally and thus recommend to reinforce this criterion. In conclusion, if the flue pipe fault detection and the indoor air ventilation system are introduced, carbon monoxide poisoning accidents are expected to decrease significantly. Also when the manufacturing and inspection steps, the correct installation and repair are supplemented with the user's attention in missing flue, it will be served to prevent human casualties from carbon monoxide poisoning.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.103-113
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• 2019

License plate recognition camera is dedicated device designed for acquiring images of the target vehicle for recognizing letters and numbers in a license plate. Mostly, it is used as a part of the system combined with server and image analysis module rather than as a single use. However, building a system for vehicle license plate recognition is costly because it is required to construct a facility with a server providing the management and analysis of the captured images and an image analysis module providing the extraction of numbers and characters and recognition of the vehicle's plate. In this study, we would like to develop an embedded type convergent camera (Edge Base) which can expand the function of the camera to not only the license plate recognition but also the security CCTV function together and to perform two functions within the camera. This embedded type convergence camera equipped with a high resolution 4K IP camera for clear image acquisition and fast data transmission extracted license plate area by applying YOLO, a deep learning software for multi object recognition based on open source neural network algorithm and detected number and characters of the plate and verified the detection accuracy and recognition accuracy and confirmed that this camera can perform CCTV security function and vehicle number plate recognition function successfully.

• Journal of architectural history
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• v.28 no.5
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• pp.43-58
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• 2019

After the study of Fujishima Gaijiro(1930), although it is common to see that the Tang-ruler(唐尺) was used in the construction of the Silla Sacheonwangsa temple(679), the basis of the discrimination of the construction measure and the detection of the unit length is not actually sufficient since conventional research was done before the excavation. The study was based on archaeological results, which was secured through the excavation research(2006~2012) of the temple site in recent years, to determine the construction measure and try to detect the unit length. In the analysis of the measured value of the ruins, the numerical data were obtained through measurements on drawings of the ruins, the tendency of conversion measure's number appearing by dividing each unit length of the Goguryeo-ruler(高句麗尺) and Tang-ruler within a certain range was compared from the Wansu-je(完數制) viewpoint. The research results are summarized as follows : 1)As a result of the analysis of the distance between the site's center, the case that conversion Cheok's(尺) number is converged to the unit of Jang(丈) within the range of unit length expresses three times more in Tang-ruler, and it is confirmed that a simple multiple relationship based on the unit of Jang is established between conversion Cheok's number. 2)As a result of analysis of Bokan(梁間) of the each Corridor site and the measured value of the stonework ruins, it could be confirmed that appears overwhelmingly in the Tang-ruler when conversion Cheok's number becomes an integer within the range of unit length. The results of the analysis are judged to be a clear basis for viewing the Tang-ruler as the construction measure of the Sacheonwangsa temple. 3)The estimated unit lengths of the construction measure that were obtained from the analysis of the distance between the site'scenter, the foundation stone center distance of the building site and the measured value of the stonework ruins are slightly different. There is a limit to the verification of the construction error about this, however it is difficult to specify, it is mentioned 294.37mm which is obtained from the analysis of the distance between the site's center.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.603-611
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• 2020

Potholes on the road directly affect drivers' safety, satisfaction, and vehicle damage. Thus, real-time detection and response are required. Increasing frequency of patrols allows for potholes to be detected and responded to quickly, but this takes much manpower, money, and time. In addition, potholes have different occurrence characteristics depending on the rain conditions, so it is necessary to consider the optimal frequency from an economic and road-service perspective. Therefore, a quantitative analysis was done on the effects of rainfall on the occurrence characteristics of potholes. Information on the persistence, impact of rainfall intensity, and weather information was collected over a long period. Based on the results, a risk-based, optimized, and changeable road-patrol strategy is presented. The analysis results show that the probability of pothole occurrence increases by 2.4 times in rainy weather. Furthermore, the impact continues for 3 days even after the rain stops. The probability of pothole occurrence increases by 0.46% per 1 mm of rainfall, and the occurrence characteristics react sensitively to even a small amount of rain of around 1 mm. It was concluded that road patrol is required at least once every three days for an effect-free period, while twice a day is needed for the "sphere of influence" period to achieve a 95% reliability level.ys for effect-free period, while twice a day for sphere of influence period to satisfy 95% reliability level.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.175-181
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• 2022

The condition of infrastructure deteriorates as the service life increases. Since most infrastructure in South Korea were intensively built during the period of economic growth, the proportion of outdated infrastructure is rapidly increasing now. Aging of such infrastructure can lead to safety accidents and even human casualties. To prevent these issues in advance, periodic and accurate inspection is essential. For this reason, the need for research to detect various types of damage using computer vision and deep learning is increasingly required in the field of remotely controlled or autonomous inspection. To this end, this study proposed a neural network structure that can detect concrete damage by classifying it into three types. In particular, the proposed neural network can detect them more accurately through a hierarchical learning technique. This neural network was trained with 2,026 damage images and tested with 508 damage images. As a result, we completed an algorithm with average mean intersection over union of 67.04% and F1 score of 52.65%. It is expected that the proposed damage detection algorithm could apply to accurate facility condition diagnosis in the near future.

• Journal of Service Research and Studies
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• v.12 no.2
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• pp.23-37
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• 2022

Based on the service scenario proposed by the existing Kim Tae-wan (2018) who can safely evacuate inmates with the help of a mobile application linked to a fire detection system in the event of a fire, the final purpose of this study is to develop the scenario by incorporating more realistic scenarios with mobile stimuli that can help them escape or act through the Delph In addition, to make the scenarios produced more realistic considering the structure and copper lines of a typical building, expert scenario verification and Delphi technique were applied to exclude unnecessary or impractical aspects of the existing scenarios. The results of the second Delphi survey showed that the primary psychology that could be seen at the time of the fire alarm were doubts, safety concerns and alarm, and the results of the second Delphi survey were analyzed, and the satisfaction of the content adequacy (CVR), convergence, and consensus was derived. Finally, this was applied to create a scenario in which a mobile application was assisted to evacuate the fire response phase. This study will allow the use of methods to increase the evacuation rate of those who are in the event of a fire.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.127-143
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• 2023

Currently, the domestic traditional market has not escaped the swamp of stagnation that began in the early 2000s despite various projects promoted by many related players such as the central government and local governments. In order to overcome the crisis faced by the traditional market, various R&Ds have recently been conducted on how to build a smart traditional market that combines information and communication technologies such as big data analysis, artificial intelligence, and the Internet of Things. This study analyzes various previous studies, users of traditional markets, and application cases of ICT technology in foreign traditional markets since 2012 and proposes a model to build a smart traditional market using ICT technology based on the analysis. The model proposed in this study includes building a traditional market metaverse that can interact with visitors, certifying visits to traditional markets through digital signage with NFC technology, improving accuracy of fire detection functions using IoT and AI technology, developing smartphone apps for market launch information and event notification, and an e-commerce system. If a smart traditional market platform is implemented and operated based on the smart traditional market platform model presented in this study, it will not only draw interest in the traditional market to MZ generation and foreigners, but also contribute to revitalizing the traditional market in the future.