• Journal of the Korean Society of Safety
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• v.36 no.4
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• pp.20-28
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• 2021

With an increase in the commercialization of electricity, and the development of advanced and large electric devices and various wireless radio wave services, concerns over the effects of electromagnetic fields on human health have increased. Accordingly, the World Health Organization encouraged the development of international standards by establishing the 'International Electromagnetic Fields Project' in 1996 based on studies on the harmful effects of electromagnetic fields on the human body. Moreover, the National Institute of Environmental Health Sciences (NIEHS) classified electromagnetic fields as possible carcinogens under Group 2B category, even though they have been found to have a weak correlation with those effects on human health. Mid-to-large-sized electric facilities used at industrial sites mostly adopt a commercial frequency of 60 Hz, and workers handling these facilities are exposed to such extremely low frequency (ELF) fields for a long time. A previous study suggested that exposure to ELF electromagnetic fields with frequency ranges from 0 to 300 Hz, even for a short time, at densities higher than 100 μT may have harmful effects on human body as it affects the activation of nerve cells in the central nervous system by inducing an electric field and current and stimulating muscles and the nervous system in the body. Such studies, however, focused on home appliances used by ordinary people, and research on facilities utilizing high-capacity current and operated by workers at industrial sites is lacking. Therefore, in this study, a 3000 kilowatt generator, which is a high-capacity electric facility employed at industrial sites, was investigated, and the size of the magnetic fields generated during its no-load and high-load operations per distance to produce a map was measured to reveal spots deemed hazardous according to domestic and international exposure standards. The findings of this study is expected to alleviate workers' anxiety about the harmful effects of magnetic fields on their body and to minimize the level of exposure during operations.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.4
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• pp.1-10
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• 2022

Attempts to interpret human perspectives using computer vision have been developed in various fields. In this paper, we propose a method for evaluating the walking environment through semantic segmentation results of images from road images. First, the Kakao Map API was used to collect road images, and four-way images were collected from about 50,000 points in JeonJu. 20% of the collected images build datasets through crowdsourcing-based paired comparisons, and train various regression models using paired comparison data. In order to derive the walkability score of the image data, the ranking score is calculated using the Trueskill algorithm, which is a ranking algorithm, and the walkability and analysis using various regression models are performed using the constructed data. Through this study, it is shown that the walkability of Jeonju can be evaluated and scores can be derived through the correlation between pixel distribution classification information rather than human vision.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.141-150
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• 2021

Fine dust is a substance that greatly affects human health, and various studies have been conducted in this regard. Due to the human influence of particulate matter, various studies are being conducted to predict particulate matter grade using past data measured in the monitoring network of Seoul city. In this paper, predictive model have focused on particulate matter concentration in May, 2019, Seoul. The air pollutant variables were used to training such as SO₂, CO, NO₂, O₃. The predictive model based on Adaboost, and training model was dividing PM₁₀ and PM_2.5. As a result of the prediction performance comparison through confusion matrix, the Adaboost model was more conformable for predicting the particulate matter concentration grade. Although air pollutant variables have a higher correlation with PM2.5, training model need to train a lot of data and to use additional variables such as traffic volume to predict more effective PM₁₀ and PM_2.5 distribution grade.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.70.1-70.1
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• 2021

We examine the HI gas kinematics and distributions of galaxy pairs in group or cluster environments from high-resolution Australian Square Kilometer Array Pathfinder (ASKAP) WALLABY pilot observations. We use 32 well-resolved close pair galaxies from the Hydra, Norma, and NGC 4636, two clusters and a group of which are identified by their spectroscopy information and additional visual inspection. We perform profile decomposition of HI velocity profiles of the galaxies using a new tool, BAYGAUD which allows us to separate a line-of-sight velocity profile into an optimal number of Gaussian components based on Bayesian MCMC techniques. Then, we construct super profiles via stacking of individual HI velocity profiles after aligning their central velocities. We fit a model which consists of double Gaussian components to the super profiles, and classify them as kinematically cold and warm HI gas components with respect to their velocity dispersions, narrower or wider 𝜎, respectively. The kinematically cold HI gas reservoir (M_cold/M_HI) of the paired galaxies is found to be relatively higher than that of unpaired control samples in the clusters and the group, showing a positive correlation with the HI mass in general. Additionally, we quantify the gravitational instability of the HI gas disk of the sample galaxies using their Toomre Q parameters and HI morphological disturbances. While no significant difference is found for the Q parameter values between the paired and unpaired galaxies, the paired galaxies tend to have larger HI asymmetry values which are derived using their moment0 map compared to those of the non-paired control sample galaxies in the distribution.

• Plant Breeding and Biotechnology
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• v.1 no.1
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• pp.1-8
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• 2013

Low-temperature stress is an important factor controlling the growth and development of rice (Oryza sativa L.) in temperate region. In this study, a molecular linkage map consisting of 136 SSR markers was employed to identify QTL associated with cold tolerance at the seedling stage. 80 recombinant inbred lines (RILs) from an intersubspecific cross between Milyang23 (O. sativa ssp. Indica) and Hapcheonaengmi3, a japonica weedy rice and the parents were evaluated for leaf discoloration and SAPD value of seedlings. Rice plants were grown for 15 days in the low-temperature condition (13/20℃ day/night) and the control condition (25/20℃ day/night) in the growth chamber. The degree of leaf discoloration showed a highly significant correlation with the SPAD value in the low-temperature plot (r = -0.708, P < 0.0001). A total of four QTLs for SPAD were identified and the phenotypic variance explained by each QTL ranged from 5.4 to 16.0%. Two QTLs detected in the control condition were located on chromosomes 2 and 5, respectively. Two QTL on chromosomes 1 and 4 were detected at the low-temperature condition and Hapcheonaengmi3 alleles increased the SPAD values at these loci. Substitution mapping was conducted to delimit the position of qSPA-4 using introgression lines derived from the same cross. Results indicated that qSPA-4 was located in a 810-Kb region flanked by RM16333 and RM16368. The results indicated that Hapcheonaengmi3 contains QTL alleles that are likely to improve cold tolerance of Indica rice.

• Journal of Gifted/Talented Education
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• v.20 no.3
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• pp.767-788
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• 2010

The purpose of this study was to examine emotional characteristics and to provide information about the special needs of counselling of science gifted in Korea. The subjects were 143 science gifted high school students in Busan that had been tested MBTI and MMPI-A. The distribution map of MBTI type was examined and Pearson's correlation, one-way ANOVA, multiple regression analysis were used to analyse the relation between MBTI and MMPI-A through SPSS 17.0 program. The results showed as follows: first, ENTP, INTP, ISTJ personality types and NT temperament type were the most frequently from the distribution map of MBTI type. Second, F1, F2, F, Hs, D, Pt, Sc and Si scales of MMPI-A were positively related to I preference of MBTI and K and Ma scales of MMPI-A were significantly related to E preference of MBTI from Pearson's correlation. Third, The score of IN group was significantly more high in F1, Hs, D, SC and Si scales of MMPI-A than other group in the relation between two combination preferences of MBTI and scale of MMPI-A. The following results were same; IS group in D, Si scales, EN group in Ma scale, IT group in Hs, D, Pt and S scales, IF group in VRIN, D and Si scales, ET in Ma scale, IJ group in D and Si, IP group in F1, F, Hs, D, Hy, Pt, Sc and Si scales, EJ and EP groups in Ma scale. Finally, I preference of MBTI by F1, F2, F, Hs, D, Pt, Sc and Si scales of MMPI-A, E preference of MBTI by Ma scale of MMPI-A, F preference of MBTI by K scale of MMPI-A and P preference of MBTI by Hy scale of MMPI-A were significantly predicted from multiple regression analysis. Limitations of the current study and the suggestions for further research were offered.

• Journal of Korea Water Resources Association
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• v.56 no.3
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• pp.195-210
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• 2023

Additional deposition and erosion in large rivers in South Korea have continued to occur toward morphological stabilization after massive dredging through the four major river restoration project, subsequently requiring precise bathymetry monitoring. Hyperspectral bathymetry method has increasingly been highlighted as an alternative way to estimate bathymetry with high spatial resolution in shallow depth for replacing classical intrusive direct measurement techniques. This study introduced the conventional Optimal Band Ratio Analysis (OBRA) of hyperspectral bathymetry method, and evaluated the performance in a domestic large river in normal turbid and flow condition. Maximum measurable depth was estimated by applying correlation coefficient and root mean square error (RMSE) produced during OBRA with cascadedly applying cut-off depth, where the consequent hyperspectral bathymetry map excluded the region over the derived maximum measurable depth. Also non-linearity was considered in building relation between optimal band and depth. We applied the method to the Nakdong and Hwang River confluence as a large river case and obtained the following features. First, the hyperspectal method showed acceptable performance in morphological mapping for shallow regions, where the maximum measurable depth was 2.5 m and 1.25 m in the Nakdong and Hwang river, respectively. Second, RMSE was more feasible to derive the maximum measurable depth rather than the conventional correlation coefficient whereby considering various scenario of excluding range of in situ depths for OBRA. Third, highly turbid region in Hwang River did not allow hyperspectral bathymetry mapping compared with the case of adjacent Nakdong River, where maximum measurable depth was down to half in Hwang River.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.88-99
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• 2019

This study aims to conduct a depth analysis of motivation and value of local residents and tourists based on means-end chain theory. The sampling of the study was conducted on local residents living near downtown area of Gyeong-ju City, and tourists through soft laddering and hard laddering methods. A mutual correlation model in relation with Hierarchical Value Map (HVM) for each group by conducting the analysis of factor loading (attributes, consequences, value) and cognitive structure (the correlations among attributes, consequences and value) was proposed and the comparisons of HVM for each group was also conducted. The structured questionnaires using Association Pattern Technique (APT) of hard laddering were utilized to analyze the means and end of value chain structures in terms of the attributes, consequences, value of Gyeong-ju Ancient Tombs. The findings propose that local residents are visiting Ancient Tombs Gyeong-ju City Center for 'Rest and take a walk' as the means, which results in 'Relieving stress' and eventually leads to the 'Improvement of historic and cultural cultivation' as the end. On the other hand, tourists also 'Rest and take a walk' as the mean, which also leads to 'Relieving stress'. However, unlike local residents, it eventually leads to 'Self-reflection and healing' as the end. It is expected that the findings of this study not only recommend us to consider preserving and managing cultural heritages and value of ancient tombs in developing "Ancient Tomb Park in Gyoneg-ju City Center" but also provides baseline data for the establishment of reasonable plans of utilizing tombs, historical and cultural heritages.

• Korean Journal of Environment and Ecology
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• v.35 no.4
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• pp.377-386
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• 2021

This study was conducted to provide basic data for habitat management and preservation of Jeongmaek. A total of 18 priority research areas were selected with consideration to terrain and habitat environment, and 54 fixed plots were selected for three types of habits: development, valley, and forest road and ridge. The survey was conducted in each season (May, August, and October), excluding the winter season, from 2016 to 2018. The distribution analysis of birds observed in each habitat type using a self-organizing map (SOM) classified them into a total of four groups (MRPP, A=0.12, and p <0.005). The comparative analysis of the number of species, the number of individuals, and the species diversity index for each SOM group showed that they were all the highest in group III (Kruskal-Wallis, the number species: x² = 13.436, P <0.005; the number of individuals: x² = 8.229, P <0.05; the species diversity index: x² = 17.115, P <0.005). Moreover, the analysis by applying the land cover map to the random forest model to examine the index species of each group and identify the characteristics of the habitat environment showed a difference in the ratio of the habitat environment and the indicator species among the four groups. The index species analysis identified a total of 18 bird species as the indicator species in three groups except for group II. When applying the random forest model and indicator species analysis to the results of classification into four groups using the SOM, the composition of the indicator species by the group showed a correlation with the habitat characteristics of each group. Moreover, the distribution patterns and densities of observed species were clearly distinguished according to the dominant habitat for each group. The results of the analysis that applied the SOM, indicator species, and random forest model together can derive useful results for the characterization of bird habitats according to the habitat environment.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1031-1031
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• 2001

The mammary gland is made up of remarkably sensitive tissue, which has the capability of producing a large volume of secretion, milk, under normal or healthy conditions. When bacteria enter the gland and establish an infection (mastitis), inflammation is initiated accompanied by an influx of white cells from the blood stream, by altered secretory function, and changes in the volume and composition of secretion. Cell numbers in milk are closely associated with inflammation and udder health. These somatic cell counts (SCC) are accepted as the international standard measurement of milk quality in dairy and for mastitis diagnosis. NIR Spectra of unhomogenized composite milk samples from 14 cows (healthy and mastitic), 7days after parturition and during the next 30 days of lactation were measured. Different multivariate analysis techniques were used to diagnose the disease at very early stage and determine how the spectral properties of milk vary with its composition and animal health. PLS model for prediction of somatic cell count (SCC) based on NIR milk spectra was made. The best accuracy of determination for the 1100-2500nm range was found using smoothed absorbance data and 10 PLS factors. The standard error of prediction for independent validation set of samples was 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. It has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. From the spectral changes, we learned that when mastitis occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk. It was consistent with the results we obtained further when applied 2DCOS. Two-dimensional correlation analysis of NIR milk spectra was done to assess the changes in milk composition, which occur when somatic cell count (SCC) levels vary. The synchronous correlation map revealed that when SCC increases, protein levels increase while water and lactose levels decrease. Results from the analysis of the asynchronous plot indicated that changes in water and fat absorptions occur before other milk components. In addition, the technique was used to assess the changes in milk during a period when SCC levels do not vary appreciably. Results indicated that milk components are in equilibrium and no appreciable change in a given component was seen with respect to another. This was found in both healthy and mastitic animals. However, milk components were found to vary with SCC content regardless of the range considered. This important finding demonstrates that 2-D correlation analysis may be used to track even subtle changes in milk composition in individual cows. To find out the right threshold for SCC when used for mastitis diagnosis at cow level, classification of milk samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two levels of SCC - 200 000 cells/$m\ell$ and 300 000 cells/$m\ell$, respectively, were set up and compared as thresholds to discriminate between healthy and mastitic cows. The best detection accuracy was found with 200 000 cells/$m\ell$ as threshold for mastitis and smoothed absorbance data: - 98% of the milk samples in the calibration set and 87% of the samples in the independent test set were correctly classified. When the spectral information was studied it was found that the successful mastitis diagnosis was based on reviling the spectral changes related to the corresponding changes in milk composition. NIRS combined with different ways of spectral data ruining can provide faster and nondestructive alternative to current methods for mastitis diagnosis and a new inside into disease understanding at molecular level.