• The Korean Journal of Nuclear Medicine
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• v.32 no.3
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• pp.225-237
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• 1998

Purpose: We investigated the statistical methods to compose the functional brain map of human working memory and the principal factors that have an effect on the methods for localization. Materials and Methods: Repeated PET scans with successive four tasks, which consist of one control and three different activation tasks, were performed on six right-handed normal volunteers for 2 minutes after bolus injections of 925 MBq $H_2^{15}O$ at the intervals of 30 minutes. Image data were analyzed using SPM96 (Statistical Parametric Mapping) implemented with Matlab (Mathworks Inc., U.S.A.). Images from the same subject were spatially registered and were normalized using linear and nonlinear transformation methods. Significant difference between control and each activation state was estimated at every voxel based on the general linear model. Differences of global counts were removed using analysis of covariance (ANCOVA) with global activity as covariate. Using the mean and variance for each condition which was adjusted using ANCOVA, t-statistics was performed on every voxel To interpret the results more easily, t-values were transformed to the standard Gaussian distribution (Z-score). Results: All the subjects carried out the activation and control tests successfully. Average rate of correct answers was 95%. The numbers of activated blobs were 4 for verbal memory I, 9 for verbal memory II, 9 for visual memory, and 6 for conjunctive activation of these three tasks. The verbal working memory activates predominantly left-sided structures, and the visual memory activates the right hemisphere. Conclusion: We conclude that rCBF PET imaging and statistical parametric mapping method were useful in the localization of the brain regions for verbal and visual working memory.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.449-459
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• 2015

The conventional National Forest Inventory(NFI)-based forest carbon stock estimation method is suitable for national-scale estimation, but is not for regional-scale estimation due to the lack of NFI plots. In this study, for the purpose of regional-scale carbon stock estimation, we created grid-based forest carbon stock maps using spatial ancillary data and two types of up-scaling methods. Chungnam province was chosen to represent the study area and for which the $5^{th}$ NFI (2006~2009) data was collected. The first method (method 1) selects forest type map as ancillary data and uses regression model for forest carbon stock estimation, whereas the second method (method 2) uses satellite imagery and k-Nearest Neighbor(k-NN) algorithm. Additionally, in order to consider uncertainty effects, the final AGB carbon stock maps were generated by performing 200 iterative processes with Monte Carlo simulation. As a result, compared to the NFI-based estimation(21,136,911 tonC), the total carbon stock was over-estimated by method 1(22,948,151 tonC), but was under-estimated by method 2(19,750,315 tonC). In the paired T-test with 186 independent data, the average carbon stock estimation by the NFI-based method was statistically different from method2(p<0.01), but was not different from method1(p>0.01). In particular, by means of Monte Carlo simulation, it was found that the smoothing effect of k-NN algorithm and mis-registration error between NFI plots and satellite image can lead to large uncertainty in carbon stock estimation. Although method 1 was found suitable for carbon stock estimation of forest stands that feature heterogeneous trees in Korea, satellite-based method is still in demand to provide periodic estimates of un-investigated, large forest area. In these respects, future work will focus on spatial and temporal extent of study area and robust carbon stock estimation with various satellite images and estimation methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.363-373
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• 2020

During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.

• Economic and Environmental Geology
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• v.36 no.6
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• pp.511-525
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• 2003

The Okcheon Group in the southwestern part of the Okcheon Metamorphic Belt is subdivided into two distinct tectonostratigraphic units: the Boeun unit in the south and the Pibanryeong unit in the north. The Boeun unit consists of petites, psammites, carbonaceous petites, limestones and pebble-bearing quartzites. The Pibanryeong unit is composed of petites, well-sorted fine-grained psammites, carbonaceous psammites and quartzites. In order to outlining stratigraphy and depositional environments of the Okcheon Group, detailed stratigraphic sections were measured in three locations; one section(Gosan section) of the Boeun unit and two sections(Sorungjae and Hwangryeongzae sections) of the Pibanryeong unit. The Gosan section of the Boeun unit is interpreted to be deposited in the shallow marine environments, whereas the Sorungjae and Hwangryeonaiae sections of the Pibanryeong unit appear to be deposited in slope and deep basin environments. This result indicates rapid subsidence between deposition of the Boeun and Pibanryeong units in sedimentary environment. The trace of sedimentological environments in the Hwasan area was investigated by geochemical analysis of 109 metapelitic and psammitic rock samples. Distinct chemical variations of politic and psammitic rocks from the Boeun and Pibanryeong units in the study area are evident from plots of major elements and $A1_2O_3$/$SiO_2$ versus Basicity Index($Fe_2O_3{＋}MgO$)/($SiO_2{＋}K_2O{＋}Na_2O$). The rocks show a progressive chemical trend from the Boeun unit to the Pibanryeong unit on these diagrams. They in the southern sector of the Boeun unit display lower values and a comparatively wide range of $A1_2O_3$/$SiO_2$ and Basicity Index, as compared with those from the northern sector of the Boeun and Pibanryeong units. The southern sector of the Pibanryeong unit including narrow staurolite-bearing zone is characterized by values that are transitional between the Boeun and Pibanryeong units. These data, combined with depositional environment progressively deepened towards the northwest, support a half-graben model for the Okcheon basin, as proposed by Cluzel et al.(1990)

• Journal of the Korean Society of Environmental Restoration Technology
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• v.2 no.3
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• pp.10-17
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• 1999

In order to confirm the effectiveness of the natural river improvement technique, the analysis of vegetation was carried out in Yangjae stream between 1996 and 1998. The results of this study showed the numbers of riparian plants had increased from 41 species to 53 species, and the dominant species had changed from annual and biannual(Humulus japonicus, Persicaria thunbergii, Persicaria hydropiper, Panicum dichotomiflorum, Echinochloa crus-galli) to perennials (Phragmites communis). The variation in biomass and biodiversity index were measured and calculated according to the rehabilitation method. Biomass were varied 302 to $828g/m^2$ and biodiversity index was varied 1.53 to 1.52 at point bar plots(A treatment plots) from 1996 to 1998. In conclusion, the natural river improvement technique which has operated in Yanjaecheon for three years has contributed to restoration of riparian plants. Additionally, subsequent study using this technique should be followed in the near future.

• Korean Journal of Ecology and Environment
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• v.47 no.3
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• pp.160-166
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• 2014

This study was aimed at looking into the distribution status and age structure of Abies holophylla population in Sudo-Am temple forest. It was found that a total of 302 individuals of Abies holophylla existed which were more than 2m in height within the study area. Furthermore the population size is one of the largest in the southern region of Korea. The CBH of Abies holophylla ranged from 1.5 cm to 500.8 cm. Age structure of Abies holophylla looks like a gourd-shaped bottle. This means that they have an unstable structure status and do not survive very long. This status results from a variety of factors including, vegetation succession, anthropogenic activities, and global warming. The environmental characteristics of Abies holophylla population was $931{\pm}64.5m$ in mean altitude, $19.2{\pm}8.7^{\circ}$ in mean slope in the northeastern and southeastern area of the slope direction, and $1,324,323{\pm}174,459wh\;m^{-2}$ in average of direct normal irradiation. Among the site environmental factors, the significant ones which influence the potential habitat for Abies holophylla distribution were chosen using the MaxEnt model. According to the results of this study, altitude and slope were found as the important factors. The average value of environmental conditions by ROC analysis were altitude 903.2 m, slope $20.04^{\circ}$, irradiation $1,352.248wh\;m^{-2}$, and the southeastern aspect.

• Applied Microscopy
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• v.34 no.1
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• pp.31-42
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• 2004

Acute respiratory distress syndrome (ARDS) is a kind of acute lung injury characterized by inflammatory disruption of alveolar-capillary barrier and notorious for its high mortality. Neutrophils cause cell damage through the production of free radicals, inflammatory mediators, and proteases in ARDS. $PLA_2$ might serve a primary regulatory role in the activation of neutrophils. This present study was performed to elucidate the effect of rutin known as $PLA_2$ inhibitor on ARDS induced by endotoxin. Endotoxin had increased lung myeloperoxidase (MPO) activity, BAL (bronchoalveolar lavage) protein content, numbers of neutrophils in BALF (bronchoalveolar lavage fluid) compared with those of control rat (p<0.001). In addition, histological evidence of lung injury was correlated with neutrophil influx into alveolar space and cerrous perhydroxide granules were found in lining of endothelial cell, alveolar type I, II cells. In contrast, pretreated group of rutin had significantly decreased all of the parameters (p<0.001). These data suggest that inhibition of $PLA_2$ is one step approach that block the process of ARDS. Accordingly, we conclude that rutin can be used as the prophylactic agent for ARDS on the bases of these experimental results.

• Investigative Magnetic Resonance Imaging
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• v.14 no.2
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• pp.103-114
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• 2010

Purpose : To generate a Korean specific brain template, especially in patients with Alzheimer's disease (AD) by optimizing the voxel-based analysis. Materials and Methods : Three-dimensional T1-weighted images were obtained from 123 subjects who were 43 cognitively normal subjects and patients with 44 mild cognitive impairment (MCI) and 36 AD. The template and the corresponding aprior maps were created by using the matched pairs approach with considering differences of age, gender and differential diagnosis (DDX). We measured several characteristics in both our and the MNI templates, including in the ventricle size. Also, the fractions of gray matter and white matter voxels normalized by the total intracranial were evaluated. Results : The high resolution template and the corresponding aprior maps of gray matter, white matter (WM) and CSF were created with the voxel-size of $1{\times}1{\times}1\;mm$. Mean distance measures and the ventricle sizes differed between two templates. Our brain template had less gray matter and white matter areas than the MNI template. There were volume differences more in gray matter than in white matter. Conclusion : Gray matter and/or white matter integrity studies in populations of Korean elderly and patients with AD are needed to investigate with this template.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.107-123
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• 2020

With stabilization of the recent multi-GNSS infrastructure, and as multi-GNSS has been proven to be effective in improving the accuracy of the positioning performance in various industrial sectors. In this study, in view that SF(Single frequency) GNSS receivers are widely used due to the low costs, evaluate effectiveness of SF Real Time Point Positioning(SF-RT-PP) based on four multi-GNSS surveying methods with RTCM-SSR correction streams in static and kinematic modes, and also derive response challenges. Results of applying SSR correction streams, CNES presented good results compared to other SSR streams in 2D coordinate. Looking at the results of the SF-RT-PP surveying using SF signals from multi-GNSS, were able to identify the common cause of large deviations in the altitude components, as well as confirm the importance of signal bias correction according to combinations of different types of satellite signals and ionospheric delay compensation algorithm using undifferenced and uncombined observations. In addition, confirmed that the improvement of the infrastructure of Multi-GNSS allows SF-RT-SPP surveying with only one of the four GNSS satellites. In particular, in the case of code-based SF-RT-SPP measurements using SF signals from GPS satellites only, the difference in the application effect between broadcast ephemeris and SSR correction for satellite orbits/clocks was small, but in the case of ionospheric delay compensation, the use of SBAS correction information provided more than twice the accuracy compared to result of the Klobuchar model. With GPS and GLONASS, both the BDS and GALILEO constellations will be fully deployed in the end of 2020, and the greater benefits from the multi-GNSS integration can be expected. Specially, If RT-ionospheric correction services reflecting regional characteristics and SSR correction information reflecting atmospheric characteristics are carried out in real-time, expected that the utilization of SF-RT-PPP survey technology by multi-GNSS and various demands will be created in various industrial sectors.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.