• Geophysics and Geophysical Exploration
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• v.12 no.3
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• pp.246-254
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• 2009

We developed a novel polarization filter to separate linearly polarized waves from elliptically polarized waves in an infinite homogeneous medium and at the free surface using methods of multicomponent complex trace analysis. Sensitivity to filter parameters were examined using synthetic data simulating particle motions in a homogeneous medium. For known amplitude ratios of horizontal-to-vertical components of P and Rayleigh waves $C_L$ and $C_R$, respectively, the polarization filter precisely removes Rayleigh waves. Errors in the vertical and horizontal components of the filtered results increase with the ratio $C_R$/$C_L$ and the product $C_R$.$C_L$, respectively. The vertical component errors also increase rapidly as the ratios of applied-to-modeled values of $C_L$ and $C_R$ ($C_L'$/$C_L$ and $C_R'$/$C_R$) decrease, and are sensitive to $C_R'$/$C_R$ and $C_L'$/$C_L$ for small and large incidence angles, respectively. Errors of the filter are exactly the same for shear waves when the incidence angle is the supplementary of P-wave incidence angle.

• Applied Chemistry for Engineering
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• v.33 no.6
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• pp.563-573
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• 2022

This work aimed to develop a new equation for turbidity (Turb) simulation and prediction using statistical methods based on principal component analysis (PCA) and multiple linear regression (MLR). For this purpose, water samples were collected monthly over a five year period from Cheurfa dam, an important reservoir in Northwestern Algeria, and analyzed for 12 parameters, including temperature (T°), pH, electrical conductivity (EC), turbidity (Turb), dissolved oxygen (DO), ammonium (NH₄⁺), nitrate (NO₃^-), nitrite (NO₂^-), phosphate (PO₄^3-), total suspended solids (TSS), biochemical oxygen demand (BOD₅) and chemical oxygen demand (COD). The results revealed a strong mineralization of the water and low dissolved oxygen (DO) content during the summer period. High levels of TSS and Turb were recorded during rainy periods. In addition, water was charged with phosphate (PO₄^3-) in the whole period of study. The PCA results revealed ten factors, three of which were significant (eigenvalues >1) and explained 75.5% of the total variance. The F1 and F2 factors explained 36.5% and 26.7% of the total variance, respectively and indicated anthropogenic pollution of domestic agricultural and industrial origin. The MLR turbidity simulation model exhibited a high coefficient of determination (R² = 92.20%), indicating that 92.20% of the data variability can be explained by the model. TSS, DO, EC, NO₃^-, NO₂^-, and COD were the most significant contributing parameters (p values << 0.05) in turbidity prediction. The present study can help with decision-making on the management and monitoring of the water quality of the dam, which is the primary source of drinking water in this region.

• Journal of Distribution Science
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• v.13 no.5
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• pp.45-52
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• 2015

Purpose - Augmented reality (AR) content used in mobile media today can accommodate a wide variety of contextual information. This indicates that making people experience a sense of presence and flow is a very significant factor in augmented reality content. Flow represents a rich immersion potential as representing the progress of emotion and the means to facilitate the operation of the smart phone. Therefore, users will have friendly relational continuance behavior with products and brands that supply this experience. Based on that, the purpose of this study is to investigate the relationships among smart phone AR application traits, presence, flow experience, and relational continuance behavior. First, AR application traits are defined as three categories sensory immersion, navigation, and manipulation, based on preceding studies. This study then examines the influence of AR application traits on the presence and flow experience and looks into the relation among presence, flow experience, and relational continuance behavior. This analysis suggests more detailed and concentrated strategic implications. Research design, data, and methodology - A research model is designed to examine the relation among AR application traits, presence, flow experience, and relational continued behavior. For data collection, questionnaire surveys were composed of multi-items for each component and the direct interview method was used for the interviews. To collect the data, after running the smart phone AR applications, the consumer behaviors of the respondents were generally determined. The questionnaire surveys were conducted for one month, October 2014. A total of 300 questionnaires were distributed with 278 questionnaires used for analysis, excluding the unanswered and insincere questionnaires. The data were analyzed using SPSS ver. 20.0 and LISREL ver. 8.51. Results - The following results are found: First, AR application traits have a significantly positive effect on presence with sensory immersion, navigation, and manipulation all having a significantly positive effect. Second, sensory immersion and manipulation among the AR application traits have a significantly positive effect on flow. However, navigation did not have a significantly positive effect on flow. Third, presence has a significantly positive effect on flow and has a significantly positive effect on relational continuance behavior. Moreover, flow also has a significantly positive effect on relational continuance behavior. This behavior tends to be formed since brands want to encourage relational continuance behavior and positive emotions with the brands being used. Relational continuance behavior accompanies repeat purchasing, positive word-of-mouth and recommendation activities, and forms of trust with the brand. Conclusions - The research results showed that smart phone AR traits had significantly positive effect on presence, flow, and relational continuance behavior. Based on this, smart phone AR application providers should establish an aggressive marketing strategy to accommodate more realistic problems in order to positively influence user behavior. Additionally, the marketers should make efforts to provide fun or convenience in the AR application operation process of the user.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.925-939
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• 2018

Absorbed shortwave radiation at the surface is an important component of energy analysis among the atmosphere, land, and ocean. In this study, the absorbed shortwave radiation was calculated using a radiation model and surface broadband albedo data for application to Geostationary Earth Orbit Korea Multi-Purpose SATellite (GEO-KOMPSAT-2A; GK-2A). And the results (GWNU algorithm) were compared with CERES data and calculation results using pyranometer and MODIS (Moderate Resolution Imaging Spectroradiometer) data to be selected as the reference absorbed shortwave radiation. This GWNU algorithm was also compared with the physical and statistical algorithms of GOSE-R ABI and two algorithms (Li et al., 1993; Kim and Jeong, 2016) using regression equation. As a result, the absorbed shortwave radiation calculated by GWNU algorithm was more accurate than the values calculated by the other algorithms. However, if the problem about computing time and accuracy of albedo data arise when absorbed shortwave radiation is calculated by GWNU algorithm, then the empirical algorithms explained above should be used with GWNU algorithm.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1605-1613
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• 2020

The tidal channel is a coastal sedimentary terrain that plays the most important role in the formation and development of tidal flats, and is considered a very important index for understanding and distribution of tidal flat sedimentation/erosion terrain. The purpose of this study is to understand the changes in tidal channels by a period after the opening of the floodgate of the seawall in the reclaimed land of Sihwa Lake using KOMPSAT high-resolution multispectral satellite image data and to evaluate the applicability and efficiency of high-resolution satellite images. KOMPSAT 2 and 3 images were used for extraction of the tidal channels' lineaments in 2009, 2014, and 2019 and were applied to supervised classification method based on Principal Component Analysis (PCA), Artificial Neural Net (ANN), Matched Filtering (MF), and Spectral Angle Mapper (SAM) and band ratio techniques using Normalized Difference Water Index (NDWI) and MF/SAM. For verification, a numerical map of the National Geographic Information Service and Landsat 7 ETM+ image data were utilized. As a result, KOMPSAT data showed great agreement with the verification data compared to the Landsat 7 images for detecting a direction and distribution pattern of the tidal channels. However, it has been confirmed that there will be limitations in identifying the distribution of tidal channels' density and providing meaningful information related to the development of the sedimentary process. This research is expected to present the possibility of utilizing KOMPSAT image-based high-resolution remote exploration as a way of responding to domestic intertidal environmental issues, and to be used as basic research for providing multi-platform-image-based convergent thematic maps and topics.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

• Journal of the Korean Institute of Landscape Architecture
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• v.31 no.5
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• pp.20-30
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• 2003

This study is aimed at establishing the categories and items for ecological assessment and evaluation of the environmental friendliness of golf courses in the capital region of Korea. The categories and items for the assessment have been derived based on the existing literature and interviews with golf experts. This study covers 32 golf courses in the capital region of Korea that are available in terms of data and on-site surveys. In order to conduct a comprehensive assessment of the environmental friendliness of the golf courses, the assessment area was divided into 4 categories that include a total of 14 sub-categories. The 4 categories encompass 1) location, 2) topography, 3) vegetation, and 4) construction. As its sub-categories, the location category includes current land use and zoning in the National Land Use Management Law. Topography has 2 sub-categories in the damage ratio of existing topography, gradient, cut area, and slope height. The assessment of vegetation is largely based on site surveys in the categories of preservation of the existing vegetation, the use of natural resources and existing trees, the component ratio of native tree species, the multi-layered structure of vegetation, and the utilization of water purification plants. In the aspect of construction, afforestation on tile slopes and the utilization of existing surface soil were evaluated. The examination of comparative analysis among the 10 items as a ratio measure showed that the scores were low in the sub-categories of current land we, the use of existing trees, and the multi-layered structure of vegetation. However, the rating results were satisfactory in the 2 sub-categories including cut area, and the utilization of native tree species. Those proved to be contributing factors in the ecological health of the golf courses. According to correlation analysis of the 10 items to the overall ecological rating of each golf course, the sizes of the 32 golf courses were mainly affected by the damage ratio of existing topography, gradient, preservation of vegetation and slope height. This study has the initiative to conduct an ecological assessment of golf courses in the country based on site surveys. The study results revealed that location factors such as current land use, damage ratio of topography and gradient and topographical factors were the main factors affecting the environmental friendliness of golf courses. This indicates indicating the significance of these factors in the future construction practices of golf courses. Furthermore, this study raises the need for follow-up studies to establish more detailed assessment criteria and to develop assessment techniques for areas such as slope afforestation and water purification plants that need a qualitative approach.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10C
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• pp.933-941
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• 2006

In this paper, we proposed an efficient coding method for digital hologram (fringe pattern) acquired by a CCD camera or by computer generation using multi-view prediction technique and MPEG video compression standard technique. It proceeds each R, G, or B color component separately. The basic processing unit is a partial image segmented into the size of $N{\times}N$. Each partial image retains the information of the whole object. This method generates an assembled image for a row of the segmented and frequency-transformed partial images, which is the basis of the coding process. That is, a motion estimation and compensation technique of MPEG is applif:d to the reconstructed images from the assembled images with the disparities found during generation of assembled image and the original partial images. Therefore the compressed results are the disparity of eachpartial image to form the assembled image for the corresponding row, assembled image, and the motion vectors and the compensated image for each partial image. The experimental results with the implemented algorithm showed that the proposed method has NC (Normal Correlation) values about 4% higher than the previous method, by which ours has better compression efficiency. Consequently, the Proposed method is expected to be used effectively in the application areas to transmit the digital hologram data. can be identified in comparison with the previous researches and commercial IPs.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.117-126
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• 2020

A maritime object detection system is an intelligent assistance system to maritime autonomous surface ship(MASS). It detects automatically floating debris, which has a clash risk with objects in the surrounding water and used to be checked by a captain with a naked eye, at a similar level of accuracy to the human check method. It is used to detect objects around a ship. In the past, they were detected with information gathered from radars or sonar devices. With the development of artificial intelligence technology, intelligent CCTV installed in a ship are used to detect various types of floating debris on the course of sailing. If the speed of processing video data slows down due to the various requirements and complexity of MASS, however, there is no guarantee for safety as well as smooth service support. Trying to solve this issue, this study conducted research on the minimization of computation volumes for video data and the increased speed of data processing to detect maritime objects. Unlike previous studies that used the Hough transform algorithm to find the horizon and secure the areas of interest for the concerned objects, the present study proposed a new method of optimizing a binarization algorithm and finding areas whose locations were similar to actual objects in order to improve the speed. A maritime object detection system was materialized based on deep learning CNN to demonstrate the usefulness of the proposed method and assess the performance of the algorithm. The proposed algorithm performed at a speed that was 4 times faster than the old method while keeping the detection accuracy of the old method.

• Journal of the Korean Society of Marine Environment & Safety
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• v.16 no.4
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• pp.345-352
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• 2010

The objective of this paper is to explore the short-term variability of water temperature and chlorophyll a (Chl-a) derived from in-situ and satellite data (NOAA, Sea WiFS and QuikScat) in the upwelling region of the southeastern part of Korean Peninsula in June and August, 2007. Particularly we focused on the spatial variability of sea surface temperature(SST) and Chl-a in the East Korean Warm Current region. In the results of the in-situ data, the peaks of Chl-a in june was shown at a depth of 50m The peaks of Chl-a in August was shown at a depth of 10m at the stations 4 and 5 near the land, and a depth of 30m at the other stations. The Chl-a concentrations in August were also lower than those in june except for station 5. As a result, the peaks of Chl-a in August occurred at a depth of 20~40 m shallower than those of Chl-a in june. This indicates that the nutrient-rich water within the mixed layer depth may be immediately supplied by the coastal upwelling, which is due to the southerly component of wind. The relationship between SST and Chl-a showed a negative correlation, and the high concentration of Chl-a occurred in the cold water area. The southerly wind and the East Korean Warm Current influenced a remarkable offshore movement of the cold water and Chl-a near the coastal area.