• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.9
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• pp.967-972
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• 2014

The good light permeability and hardness of glass allow it to be used in various fields. Non-conventional machining methods have been used for glass machining because of its brittle properties. As one non-contact machining method, a laser has advantages that include a high machining speed and the fact that no tool making is required. However, glass has light permeability. Thus, the use of a laser to machine glass has limitations. A nanosecond pulse laser can be used at low power for laser-induced backside wet etching, which is an indirect method. In previous studies, a short-wave laser that had good light absorption but a high price was used. In this study, a near-infrared laser was used to test the possibility of glass micro-machining. In particular, when deeper machining was conducted on a glass structure, more problems could result. To solve these problems, microstructure manufacturing was conducted using ultrasonic vibration.

• The Journal of the Korean dental association
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• v.48 no.12
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• pp.893-918
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• 2010

This article is purposed of reviewing the development history of Japanese dental devices and instrument, and their related advertisement activities during the Japanese colonized period in Korea in early 20th century. Japanese dental devices and instrument were redesigned to accommodate their ergonomic shape above the simple imitation, and it implies the excessive desires brought them frustrations. The tragic earthquake on Sep. l, 1923, medical insurance law enforcement on Jan. 1, 1927, celebration of "Cavity prevention Day" started on Jun. 4, 1928, and the attack of Manchuria and China by Japan after 1931, all of these historical incidents become the preliminary requirement for the development of dental devices. On Nov. 1, 1937, Japanese government started to control dental materials, driving the campaigns for excluding foreign products and encourging the use of local products. In 1939, Nakajima dental manufacturers used this political and social atmosphere on their advertisement as saying "Our Nakajima's products have no compromise with the short raw materials, but only commitment to our quality". Since after 1940, the price and supply have been strongly under control, and the control group was appeared to manage all of supply and distribution of raw materials, regular price system, and specifications. At last, the Japanese national power were devastated in its production and distribution capacities, and get to the frustrated period. The main advertised dental devices and instruments in Korea during the Japanese colonized period were 1) dental chair, unit and cabinet, 2) dental x-ray, 3) compressors, 4) dental needles, 5) small instrument and carryon medical(emergency) kit, 6) oral hygiene and pyorrhea alveolaris, infrared rays, sunlight lamp, ultrashort wave treatment devices, 7)crown former, electric furnace, casting machine, articulator, electric lathe, and laboratory equipments, etc.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.397-400
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• 2007

For mapping the distribution of heavy metals in the mining area, field spectroscopy and hyperspectral remote sensing were used in this study. Although heavy metals are spectrally featureless from the visible to the short wave infrared range, possible variations in spectral signal due to heavy metals bound onto minerals can be explained with the metal binding reaction onto the mineral surface. Variations in the spectral absorption shapes of lattice OH and oxygen on the mineral surface due to the combination of heavy metals were surveyed over the range from 420 to 2400 nm. Spectral parameters such as peak ratio and peak area were derived and statistically linked to metal concentration levels in the streambed samples collected from the dry stream channels. The spatial relationships between spectral parameters and concentrations of heavy metals were yielded as well. Based on the observation at a ground level for the relationship between spectral signal and metal concentration levels, the spectral parameters were classified in a hyperspectral image and the spatial distribution patterns of classified pixels were compared with the product of analysis at the ground level. The degree of similarity between ground dataset and image dataset was statistically validated. These techniques are expected to support assessment of dispersion of heavy metal contamination and decision on optimal sampling point.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_3
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• pp.1147-1154
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• 2022

Now that the development of autonomous driving is progressing, LiDAR has become an indispensable element. However, LiDAR is a device that uses lasers, and laser side effects may occur. One of them is the much-talked-about eye-safety, and developers have been satisfying this through laser characteristics and operation methods. But eye-safety is just one of the problems lasers pose. For example, irradiating a laser with a specific energy level or higher in a dusty environment can cause deterioration of the dust particles, leading to a sudden explosion. For this reason, the dust ignition proof regulations clearly state that "a source with a pulse period of less than 5 seconds is considered a continuous light source, and the average energy does not exceed 5 mJ/mm 2 or 35 mW" [2]. Energy of output optical power is limited by the law. In this way, the manufacturer cannot define the usage environment of the LiDAR, and the development of a LiDAR that can be used in such an environment can increase the ripple effect in terms of use in application fields using the LiDAR. In this paper, we develop a LiDAR with low optical power that can be used in environments where high power lasers can cause problems, evaluate its performance. Also, we discuss and present one of the directions for the development of LiDAR with laser power limited by dust ignition proof regulations.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.283-295
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• 2023

With the development of sensor and satellite technology, numerous high-resolution and multi-spectral satellite images have been available. Due to their wavelength-dependent reflection, transmission, and scattering characteristics, multi-spectral satellite images can provide complementary information for earth observation. In particular, the short-wave infrared (SWIR) band can penetrate certain types of atmospheric aerosols from the benefit of the reduced Rayleigh scattering effect, which allows for a clearer view and more detailed information to be captured from hazed surfaces compared to the visible band. In this study, we proposed a multi-resolution transform-based image fusion method to combine visible and SWIR satellite images. The purpose of the fusion method is to generate a single integrated image that incorporates complementary information such as detailed background information from the visible band and land cover information in the haze region from the SWIR band. For this purpose, this study applied the Laplacian pyramid-based multi-resolution transform method, which is a representative image decomposition approach for image fusion. Additionally, we modified the multiresolution fusion method by combining a haze-guided weight map based on the prior knowledge that SWIR bands contain more information in pixels from the haze region. The proposed method was validated using very high-resolution satellite images from Worldview-3, containing multi-spectral visible and SWIR bands. The experimental data including hazed areas with limited visibility caused by smoke from wildfires was utilized to validate the penetration properties of the proposed fusion method. Both quantitative and visual evaluations were conducted using image quality assessment indices. The results showed that the bright features from the SWIR bands in the hazed areas were successfully fused into the integrated feature maps without any loss of detailed information from the visible bands.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.4
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• pp.94-100
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• 2008

Recently, global warming for climate system is a crucial issue over the world and it brings about severe climate change, abnormal temperature, a downpour, a drought, and so on. Especially, a drought over the earth surface accelerates desertification which has been advanced over the several years mainly originated from a climatic change. The objective of this study is to detect variation of vegetation water condition around China and Mongolia desert by using satellite data having advantage in observing surface biological system. In this study, we use SPOT/VEGETATION satellite image to calculate NDWI (Normalized Difference Water Index) around study area desert for monitoring of status of vegetation characteristics. The vegetation water status index from remotely sensing data is related to desertification since dry vegetation is apt to desertify. We can infer vegetation water status using NDWI acquired by NIR (Near infrared) and SWIR (Short wave infrared) bands from SPOT/VGT. The consequence is that NDWI decreased around desert from 1999 to 2006. The areas that NDWI was decreased are located in the northeast of Mongolian Gobi desert and the southeast of China Taklamakan desert.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.695-706
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• 2022

Medium and high-resolution optical satellites have proven their effectiveness in detecting wildfire areas. However, smoke plumes generated by wildfire scatter visible light incidents on the surface, thereby interrupting accurate monitoring of the area where wildfire occurs. Therefore, a technology to extract smoke in advance is required. Deep learning technology is expected to improve the accuracy of smoke extraction, but the lack of training datasets limits the application. However, for clouds, which have a similar property of scattering visible light, a large amount of training datasets has been accumulated. The purpose of this study is to develop a smoke extraction technique using deep learning, and the limits due to the lack of datasets were overcome by using a cloud dataset on transfer learning. To check the effectiveness of transfer learning, a small-scale smoke extraction training set was made, and the smoke extraction performance was compared before and after applying transfer learning using a public cloud dataset. As a result, not only the performance in the visible light wavelength band was enhanced but also in the near infrared (NIR) and short-wave infrared (SWIR). Through the results of this study, it is expected that the lack of datasets, which is a critical limit for using deep learning on smoke extraction, can be solved, and therefore, through the advancement of smoke extraction technology, it will be possible to present an advantage in monitoring wildfires.

• The Journal of the Petrological Society of Korea
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• v.22 no.1
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• pp.1-8
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• 2013

Physical properties, XRF, UV-Vis, FTIR studies were carried out in order to characterize gemological features of ruby from Tajikistan. Fluorescence reaction of the Tajikistan ruby to short wave ultraviolet was moderate to very strong in red and long wave ultraviolet rays was weakly detected. UV-visible analysis strong absorption bands at 468.5, 475, 476.5 nm and broaden bands at 550 nm were observed for ruby due to $Cr^{3+}$. According to FT-IR analysis, all rubies from Tajikistan showed the similar patterns and kaolinite peaks at 3500, 3617, 3630, $3677cm^{-1}$ and boehmite broaden absorption bands at 3085 and $3320cm^{-1}$. Inclusions in Tajikistan ruby are observed solid inclusions, negative crystals, needle and silk inclusions. These distinctive characteristics mentioned above can be used to identify the locality and source of ruby stones from Tajikistan.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.4
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• pp.32-40
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• 2008

In this study, we monitor ice cap using calculated NDSI from September to December in 2001, 2003, 2006, 2007 and snow cover area in 2007 decrease by compare with 2001. Global warming is one of the most important issue in this world. Because global-warming is the reason of various meteorological disasters and extreme weather events in these days and snow and glaciers showed that global warming effect most easily. Snow and glaciers play an important role in Earth cooling system because of their high reflectance. The present study has been carried out monitoring ice cap in Himalayas, using MODIS(Moderate Resolution Imaging Spectroradiometer)data. Indicator to monitoring ice cap, NDSI(Normalized Differenced Snow Index) was used in this study. The NDSI is a spectral band ratio that takes advantage of the spectral differences of snow in visible and short-wave infrared domain to detect snow cover area versus non-snow cover area in a scene. This study is quantitative evaluation about effect of global warming for icecap.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.52-67
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• 2020

Recently, the Arctic has been exposed to snow-covered land due to melting permafrost every year, and the Korea Geographic Information Institute(NGII) provides polar spatial information service by establishing spatial information of the polar region. However, there is a lack of spatial information on vegetation sensitive to climate change. This research used a multi-temporal Sentinel-2 image to perform land cover classification of the Ny-Ålesund in Arctic Svalbard. In the pre-processing step, 10 bands and 6 vegetation spectral index were generated from multi-temporal Sentinel-2 images. In image-classification step is consisted of extracting the vegetation area through 8-class land cover classification and performing the vegetation species classification. The image classification algorithm used Random Forest to evaluate the accuracy and calculate feature importance through Out-Of-Bag(OOB). To identify the advantages of multi- temporary Sentinel-2 for vegetation classification, the overall accuracy was compared according to the number of images stacked and vegetation spectral index. Overall accuracy was 77% when using single-time Sentinel-2 images, but improved to 81% when using multi-time Sentinel-2 images. In addition, the overall accuracy improved to about 83% in learning when the vegetation index was used additionally. The most important spectral variables to distinguish between vegetation classes are located in the Red, Green, and short wave infrared-1(SWIR1). This research can be used as a basic study that optimizes input characteristics in performing the classification of vegetation in the polar regions.