• Korean Journal of Heritage: History & Science
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• v.54 no.1
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• pp.206-219
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• 2021

The warming of the climate is increasing the damage caused by termites to wooden buildings, cultural properties and houses. A group removal system can be installed around the building to detect and remove termite damage; however, if the site is not visited regularly, every one to two months, you cannot observe whether termites have spread within, and it is difficult to take prompt effective action. In addition, since the system is installed and operated in an exposed state for a long period of time, it may be ineffective or damaged, resulting in a loss of function. Furthermore if the system is installed near a cultural site, it may affect the aesthetic environment of the site. In this study, we created a detection system that uses wood, cellulose, magnets, and magnetic sensors to determine whether termites have entered the area. The data was then transferred to a low power LoRa Network which displayed the results without the necessity of visiting the site. The wood was made in the shape of a pile, and holes were made from the top to the bottom to make it easier for termites to enter and produce a cellulose sample. The cellulose sample was made in a cylindrical shape with a magnet wrapped in cellulose and inserted into the top of a hole in the wood. Then, the upper part of the wood pile was covered with a stopper to prevent foreign matter from entering. It also served to block external factors such as light and rainfall, and to create an environment where termites could add cellulose samples. When the cellulose was added by the termites, a space was created around the magnet, causing the magnet to either fall or tilt. The magnetic sensor inside the stopper was fixed on the top of the cellulose sample and measured the change in the distance between the magnet and the sensor according to the movement of the magnet. In outdoor experiments, 11 cellulose samples were inserted into the wood detection system and the termite inflow was confirmed through the movement of the magnet without visiting the site within 5 to 17 days. When making further improvements to the function and operation of the system it in the future, it is possible to confirm that termites have invaded without visiting the site. Then it is also possible to reduce damage and fruiting due to product exposure, and which would improve the condition and appearance of cultural properties.

• Journal of Yeungnam Medical Science
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• v.15 no.2
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• pp.325-340
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• 1998

A cross-sectional study was conducted to evaluate the relationship between sick building syndrome(SBS) and the environmental factors affecting SBS on 130 underground workers and 60 controls. The study consisted of 1) a review of environmental condition 2) measurement of temperature, $O_2$, $CO_2$, CO, and formaldehyde and 3) a questionnaire survey of symptom prevalence and perception of environmental conditions using indoor Air Quality questionnaire recommended by National Institute for Occupational Safety and Health. Bronchitis and dust allergy were more prevalent in underground workers significantly(p < 0.05). Among the 18 symptoms related to the indoor air pollution, the experience rate of dry, itching or irritated eyes, sore or dry throat, chest tightness, tired or strained eyes and dry or itchy skin symptom was significantly different between the underground workers and controls. The diagnostic criteria of SBS was defined as at least 1 symptom is experienced 1-3 times a week during the last 1 month among 18 indoor air pollution related symptoms which can be relieved by moving out of the underground. Applying the criteria, the mean symptom score was significant higher in underground workers than controls significantly (p < 0.05). These resalts indicated that underground workers are under inappropriate ergonomic and physical condition and inadequate ventilation. Their experience rate of symptoms related to indoor air pollution and prevalence of SBS was significantly higher than controls. To reduce the prevalence of SBS of underground workers, the surveillance system of indoor air quality, restriction of using fuel in underground and legislative regulations for the environment are needed to establish a better indoor air quality. Early detection, treatment and prevention of SBS through medical attention is also needed.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.379-399
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• 2020

The detection of illegal ship is one of the key factors in building a marine surveillance system. Effective marine surveillance requires the means for continuous monitoring over a wide area. In this study, the possibility of ship detection monitoring based on satellite SAR, HF radar, UAV and AIS integration was investigated. Considering the characteristics of time and spatial resolution for each platform, the ship monitoring scenario consisted of a regular surveillance system using HFR data and AIS data, and an event monitoring system using satellites and UAVs. The regular surveillance system still has limitations in detecting a small ship and accuracy due to the low spatial resolution of HF radar data. However, the event monitoring system using satellite SAR data effectively detects illegal ships using AIS data, and the ship speed and heading direction estimated from SAR images or ship tracking information using HF radar data can be used as the main information for the transition to UAV monitoring. For the validation of monitoring scenario, a comprehensive field experiment was conducted from June 25 to June 26, 2019, at the west side of Hongwon Port in Seocheon. KOMPSAT-5 SAR images, UAV data, HF radar data and AIS data were successfully collected and analyzed by applying each developed algorithm. The developed system will be the basis for the regular and event ship monitoring scenarios as well as the visualization of data and analysis results collected from multiple platforms.

• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.1-7
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• 2010

With the widespread use of vision-based surveillance systems, the capability for person identification is now an essential component. However, the CCTV cameras used in surveillance systems tend to produce relatively low-resolution images, making it difficult to use face recognition techniques for person identification. Therefore, an algorithm is proposed for person identification in CCTV camera images based on the clothing. Whenever a person is authenticated at the main entrance of a building, the clothing feature of that person is extracted and added to the database. Using a given image, the clothing area is detected using background subtraction and skin color detection techniques. The clothing feature vector is then composed of textural and color features of the clothing region, where the textural feature is extracted based on a local edge histogram, while the color feature is extracted using octree-based quantization of a color map. When given a query image, the person can then be identified by finding the most similar clothing feature from the database, where the Euclidean distance is used as the similarity measure. Experimental results show an 80% success rate for person identification with the proposed algorithm, and only a 43% success rate when using face recognition.

• Geophysics and Geophysical Exploration
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• v.13 no.1
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• pp.40-50
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• 2010

The building process of any geological map involves linking sparse lithological outcrop information with equally sparse geometrical measurements, all in a single entity which is the preferred interpretation of the field geologist. The actual veracity of this interpretative map is partially dependent upon the frequency and distribution of geological outcrops compounded by the complexity of the local geology. Geophysics is commonly used as a tool to augment the distribution of data points, however it normally does not have sufficient geometrical constraints due to: a) all geophysical inversion models being inherently non-unique; and b) the lack of knowledge of the physical property contrasts associated with specific lithologies. This contribution proposes the combined use of geophysical edge detection routines and 'three point' solutions from topographic data as a possible approach to obtaining geological contact geometry information (strike and dip), which can be used in the construction of a preliminary geological model. This derived geological information should first be assessed for its compatibility with the scale of the problem, and any directly observed geological data. Once verified it can be used to help constrain the preferred geological map interpretation being developed by the field geologist. The method models the contacts as planar surfaces. Therefore, it must be ensured that this assumption fits the scale and geometry of the problem. Two examples are shown from folded sequences at the Bathurst Mining Camp, New Brunswick, Canada.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.21 no.3
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• pp.139-145
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• 2011

Objectives: This investigation is purposed to evaluate the airborne asbestos concentrations in the public buildings having asbestos containing materials(ACMs) in Seoul. Methods: The Seoul Metropolitan Government carried out an asbestos survey to the city-owned public buildings to identify the level of risk exposure, classified into low, moderate and high risk. To evaluate the airborne concentration of asbestos, 11 sampling sites in ten buildings based on the survey were selected. The air samples from the eleven sites were analyzed by Phase Contrast Microscopy(PCM) and Transmission Electron Microscopy (TEM), and compared the analytical results from the both. Results: 1. The airborne fiber concentrations by PCM were less than the detection limit($7f/mm^2$) in 9(82%) out of 11 sampling sites. The highest concentration was 0.0043 f/cc, but it was below the guideline value for indoor air quality(0.01 f/cc), proposed by the Ministry of Environment, Korea. 2. In two sampling sites, having moderate risk level, the chrysotile was identified and showed it's concentrations of 0.0102 s/cc and 0.0058 s/cc, less than $5{\mu}m$ lengths. 3. The ACMs identified in the two sampling sites were a packing material(65% of chrysotile) in mechanical area and a thermal system insulation(5% of chrysotile) in a boiler room. Having more possibility of asbestos emission in the mechanical area, it would be required to set up and carry out the asbestos management plan. Conclusions: Based on the result of this study, the airborne asbestos concentrations in the public buildings with ACMs were generally lower than the guideline value for indoor air quality. There are widespread concerns about the possible health risk resulting from the presence of airborne asbestos fibers in the public buildings. Most of the previous studies about airborne asbestos analysis in Korea were performed based on PCM method that asbestos and non-asbestos fibers are counted together. In the public and commercial buildings, having ACMs, it is suggested that the asbestos be analyzed by TEM method to identify asbestos due to concerns about asbestos exposure to workers and unspecified people.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.787-799
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• 2018

Accurate and effective mapping is critical step to monitor the spatial distribution and change of flood inundated area in large scale flood event. In this study, we try to suggest methods to use low spatial resolution satellite optical imagery for flood mapping, which has high temporal resolution to cover wide geographical area several times per a day. We selected the Sebou watershed flood in Morocco that was occurred in early 2010, in which several hundred $km^2$ area of the Gharb lowland plain was inundated. MODIS daily surface reflectance product was used to detect the flooded area. The study area showed several distinct spectral patterns within the flooded area, which included pure turbid water and turbid water with vegetation. The flooded area was extracted by thresholding on selected band reflectance and water-related spectral indices. Accuracy of these flooding detection methods were assessed by the reference map obtained from Landsat-5 TM image and qualitative interpretation of the flood map derived. Over 90% of accuracies were obtained for three methods except for the NDWI threshold. Two spectral bands of SWIR and red were essential to detect the flooded area and the simple thresholding on these bands was effective to detect the flooded area. NIR band did not play important role to detect the flooded area while it was useful to separate the water-vegetation mixed flooded classes from the purely water surface.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.1
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• pp.41-49
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• 2014

This study spatially assesses the impact of trees on residential rooftop solar energy potential using urban three-dimensional models derived from Light Detection and Ranging(LiDAR) data in San Francisco, California. In recent years on-site solar energy generation in cities has become an essential agenda in municipal climate action plans. However, it can be limited by neighboring environments such as shade from topography, buildings and trees. Of all these effects, the impact of trees on rooftop photovoltaics(PVs) requires careful attention because improper situation of solar panels without considering trees can result in inefficient solar energy generation, tree removal, and/or increasing building energy demand and urban heat island effect. Using ArcMap 9.3.1, we calculated the incoming annual solar radiation on individual rooftops in San Francisco and the reduced insolation affected by trees. Furthermore, we performed a multiple regression analysis to see what attributes of trees in a neighborhood(tree density, tree heights, and the variance of tree heights) affect rooftop insolation. The result shows that annual total residential rooftops insolation in San Francisco is 18,326,671 MWh and annual total light-loss reduction caused by trees is 326,406 MWh, which is about 1.78%. The annual insolation shows a wide range of values from $34.4kWh/m^2/year$ to $1,348.4kWh/m^2/year$. The result spatially maps the locations that show the various levels of impact from trees. The result from multiple regression shows that tree density, average tree heights and the variation of tree heights in a neighborhood have statistically significant effects on the rooftop solar potential. The results can be linked to municipal energy planning in order to manage potential conflicts as cities with low to medium population density begin implementing on-site solar energy generation. Rooftop solar energy generation makes the best contribution towards achieving sustainability when PVs are optimally located while pursuing the preservation of urban trees.

• The KIPS Transactions:PartC
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• v.13C no.6 s.109
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• pp.709-716
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• 2006

According to the increase of various AV media devices and contents in the digital home, the DLNA becomes to play an important role as the interoperability standard between then Since this guideline only focuses on the interoperability among home networked devices, media players, and media contents existing inside of the homenetwork, there is no retrieval and transmission method for sharing multimedia contents located over several homes via Internet. Additionally, this guideline lets device-detection and notification messages to be transmitted using W multicast methods, and current Internet environment cannot guarantee consistent IP multicast services, it has the limitation that it cannot retrieve and control DLNA devices in other digital homes remotely via the Internet. Therefore, in this paper, we propose the IHM(Inter-Home Media) proxy system and its operating mechanism to provide a way of sharing media contents distributed over multiple DLNA-based homes, through analyzing these limitations and building up a sharing method for A/V media contents distributed over the DLNA homes based on the dynamic or private IP networks. Our method removes the limitation on the user locations through sharing distributed media contents, and also makes cost-downs for storing media contents, from the view point of individual residents.

• Tunnel and Underground Space
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• v.30 no.5
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• pp.462-472
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• 2020

Rock classification is fundamental discipline of exploring geological and geotechnical features in a site, which, however, may not be easy works because of high diversity of rock shape and color according to its origin, geological history and so on. With the great success of convolutional neural networks (CNN) in many different image-based classification tasks, there has been increasing interest in taking advantage of CNN to classify geological material. In this study, a feasibility of the deep CNN is investigated for automatically and accurately identifying rock types, focusing on the condition of various shapes and colors even in the same rock type. It can be further developed to a mobile application for assisting geologist in classifying rocks in fieldwork. The structure of CNN model used in this study is based on a deep residual neural network (ResNet), which is an ultra-deep CNN using in object detection and classification. The proposed CNN was trained on 10 typical rock types with an overall accuracy of 84% on the test set. The result demonstrates that the proposed approach is not only able to classify rock type using images, but also represents an improvement as taking highly diverse rock image dataset as input.