• Journal of Bio-Environment Control
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• v.22 no.3
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• pp.248-255
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• 2013

This study examined an automated irrigation technique by a frequency domain reflectometry (FDR) sensor for scheduling irrigation for tomato (Solanum lycopersicum L. 'Starbuck F1') cultivation aimed at avoiding effluent from an open hydroponic system with coir substrate containing different ratios of chip-to-dust (v/v) content. Specifically, the objectives were to undertake preliminary measurements of irrigation volumes, leachate volume, volumetric water content and electrical conductivity (EC) in the substrate, plant growth, fruit yield, and water use efficiency resulting from variation in chip content as an initial experiment. Commercial coir substrates containing different percentages of chips and dust (0 and 100%, 30 and 70%, 50 and 50%, or 70 and 30%), two-story coir substrates with different percentages of chips in the lower layer and dust in the upper layer (15 and 85%, 25 and 75%, or 35 and 65%), or rockwool slabs were used. The results showed that a negligible or no leachate was found for all treatments when plants were grown under a technique for scheduling non-drainage irrigation using a frequency domain reflectometry (FDR) sensor. Daily irrigation volume was affected by chip content in both commercial and two-story slabs. The highest plant growth, marketable fruit weight, and water-use efficiency were observed in the plants grown in the commercial coir slab containing 0% chips and 100% dust, indicating that the FDR sensor-auto-mated irrigation may be more useful for tomato cultivation in coir substrate containing 0% chips and 100% dust using water efficiently and minimizing or avoiding leachate and thus increasing yield and reducing pollution. Detailed experiment is necessary to closely focus on determining appropriate irrigation volume at each of irrigation as well as duration of each individual irrigation cycle depending on different physical properties of substrates using an automated irrigation system operated by the FDR sensor.

• Management & Information Systems Review
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• v.36 no.4
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• pp.33-51
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• 2017

With the advent of 'The Forth Industrial Revolution' and the growing demand for quality of life due to economic growth, needs for the quality of medical services are increasing. Artificial intelligence has been introduced in the medical field, but it is rarely used in chronic skin diseases that directly affect the quality of life. Also, atopic dermatitis, a representative disease among chronic skin diseases, has a disadvantage in that it is difficult to make an objective diagnosis of the severity of lesions. The aim of this study is to establish an intelligent severity recognition model of atopic dermatitis for improving the quality of patient's life. For this, the following steps were performed. First, image data of patients with atopic dermatitis were collected from the Catholic University of Korea Seoul Saint Mary's Hospital. Refinement and labeling were performed on the collected image data to obtain training and verification data that suitable for the objective intelligent atopic dermatitis severity recognition model. Second, learning and verification of various CNN algorithms are performed to select an image recognition algorithm that suitable for the objective intelligent atopic dermatitis severity recognition model. Experimental results showed that 'ResNet V1 101' and 'ResNet V2 50' were measured the highest performance with Erythema and Excoriation over 90% accuracy, and 'VGG-NET' was measured 89% accuracy lower than the two lesions due to lack of training data. The proposed methodology demonstrates that the image recognition algorithm has high performance not only in the field of object recognition but also in the medical field requiring expert knowledge. In addition, this study is expected to be highly applicable in the field of atopic dermatitis due to it uses image data of actual atopic dermatitis patients.

• Journal of the Korean earth science society
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• v.26 no.7
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• pp.732-743
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• 2005

The characteristics of precipitation over South Korea from 1973 to 2002 were investigated. The synoptic patterns inducing precipitation are classified by 10 categories, according to the associated surface map analysis. The annual mean frequency of the total precipitation, its duration time and amount for 30 years are 179 times, 2.9 hours, and 7.1 mm, respectively. About $59\%$ of the total precipitation events were associated with a synoptic low. The dominant patterns are identified with respect to seasons: A synoptic mobile low pressure pattern is frequent in spring, fall, and winter, whereas low pressure embedded within the Changma and orography induced precipitation are dominant in summer and in winter. For the amount of precipitation, precipitation originated from tropical air associated with typhoon, tropical convergence, and Changma is more significant than that with other pressure patterns. The statistical elapse time reaching to 80 mm, which is the threshold amount of heavy rainfall watch at KMA, takes 12.9 hours after the onset of precipitation. The probability distribution function of the precipitation shows that the maximum probability for heavy rainfall is located at the south-coastal region of the Korean peninsula. It is also shown that the geographical distribution of the Korean peninsula plays an important role in occurrence of heavy rainfall. For example, heavy precipitation is frequently occurred at Youngdong area, when typhoon passes along the coastal region of the back borne mountains in the peninsula. The climatological classification of synoptic patterns associated with heavy rainfall over South Korea can be used to provide a guidance to operational forecast of heavy rainfall in KMA.

• Journal of the Korean Chemical Society
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• v.64 no.2
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• pp.67-73
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• 2020

The study aimed to investigate in vitro lipid deposition of oleic acid, oleic acid methyl ester and cholesterol on a daily disposable (1-day lenses) and 3-days lenses over 3 days and changes of optical characteristics is also investigated. Artificial tear solutions were prepared to simulate actual tear compositions. Two types of contact lenses (1-day lenses (Senofilcon A) and 3-days lenses (silicone tripolymer)) were soaked in the artificial tear solutions within an incubator at 37 ℃ with 150 rpm for 8, 16, 24 hours. Lipid deposition (oleic acid, oleic acid methyl ester and cholesterol) were measured using high performance liquid chromatography (HPLC) instrument. In addition, measurements of oxygen transmissibility, light transmittance and observation of lens surface were conducted. The amount of lipid deposition on the 1-day lenses were 127.55 ㎍/lens for Day 1, 302.96 ㎍/lens, for Day 2, and 353.30 ㎍/lens for Day 3. The 3-days lenses were 46.22 ㎍/lens for Day 1, 66.07 ㎍/lens for Day 2, and 67.45 ㎍/lens for Day 3. Oxygen transmissibility were 81×10^-9(cm/sec)(ml O₂/ml×mmHg)(Baseline) and 48×10^-9(cm/sec)(ml O₂/ml×mmHg) (Day 3) for the 1-day lenses, it were 13.23×10^-9(cm/sec)(ml O₂/ml×mmHg)(Baseline) and 9.6×10^-9(cm/sec)(ml O₂/ml×mmHg) (Day 3) for the 3-days lenses. Transmittance of each lenses were 97.21% (Baseline) and 94.25% (Day 3) for the 1-day lenses, 97.65% (Baseline) and 95.15% (Day 3) for the 3-days lenses. Observation of surface deposition indicated greatest deposition for the 3-days lenses type on Day 3. Lipid deposition for both lens types increased by day and was greater for the 1-day lenses type. Surface deposition appeared to differ as it was greatest for the 3 days lens type, which may suggest other deposits such as protein may be present.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1447-1460
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• 2021

Urbanization increases the amount of impervious surface and artificial heat emission, resulting in urban heat island (UHI) effect. Local climate zones (LCZ) are a classification scheme for urban areas considering urban land cover characteristics and the geometry and structure of buildings, which can be used for analyzing urban heat island effect in detail. This study aimed to examine the UHI effect by urban structure in Suwon and Daegu using the LCZ scheme. First, the LCZ maps were generated using Landsat 8 images and convolutional neural network (CNN) deep learning over the two cities. Then, Surface UHI (SUHI), which indicates the land surface temperature (LST) difference between urban and rural areas, was analyzed by LCZ class. The results showed that the overall accuracies of the CNN models for LCZ classification were relatively high 87.9% and 81.7% for Suwon and Daegu, respectively. In general, Daegu had higher LST for all LCZ classes than Suwon. For both cities, LST tended to increase with increasing building density with relatively low building height. For both cities, the intensity of SUHI was very high in summer regardless of LCZ classes and was also relatively high except for a few classes in spring and fall. In winter the SUHI intensity was low, resulting in negative values for many LCZ classes. This implies that UHI is very strong in summer, and some urban areas often are colder than rural areas in winter. The research findings demonstrated the applicability of the LCZ data for SUHI analysis and can provide a basis for establishing timely strategies to respond urban on-going climate change over urban areas.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.221-232
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• 2021

This study analyzed co-registration results according to the geometric processing level of reference image, which are Level 1R and Level 1G provided from KOMPSAT-3 and KOMPSAT-3A images. We performed co-registration using each Level 1R and Level 1G image as a reference image, and Level 1R image as a sensed image. For constructing the experimental dataset, seven Level 1R and 1G images of KOMPSAT-3 and KOMPSAT-3A acquired from Daejeon, South Korea, were used. To coarsely align the geometric position of the two images, SURF (Speeded-Up Robust Feature) and PC (Phase Correlation) methods were combined and then repeatedly applied to the overlapping region of the images. Then, we extracted tie-points using the SURF method from coarsely aligned images and performed fine co-registration through affine transformation and piecewise Linear transformation, respectively, constructed with the tie-points. As a result of the experiment, when Level 1G image was used as a reference image, a relatively large number of tie-points were extracted than Level 1R image. Also, in the case where the reference image is Level 1G image, the root mean square error of co-registration was 5 pixels less than the case of Level 1R image on average. We have shown from the experimental results that the co-registration performance can be affected by the geometric processing level related to the initial geometric relationship between the two images. Moreover, we confirmed that the better geometric quality of the reference image achieved the more stable co-registration performance.

• Journal of Life Science
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• v.29 no.3
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• pp.369-375
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• 2019

Microtubules form through the polymerization of ${\alpha}-$ and ${\beta}-tubulin$, and tubulin transport plays an important role in defining the rate of microtubule growth inside cellular appendages, such as the cilia and flagella. Heterotrimeric kinesin 2 is a molecular motor member of the kinesin superfamily (KIF) that moves along the microtubules to transport multiple cargoes. It consists of two motor subunits (KIF3A and KIF3B) and a kinesin-associated protein 3 (KAP3), forming a heterotrimeric complex. Heterotrimeric kinesin 2 interacts with many different binding proteins through the cargo-binding domains of the KIF3s, but these binding proteins have not yet been specified. To identify these proteins for KIF3A, we performed yeast two-hybrid (Y2H) screening and found a specific interaction with ${\beta}2-tubulin$ (Tubb2), a microtubule component. Tubb2 was found to bind to the cargo-binding domain of KIF3A but did not interact with KIF3B, KIF5B, or kinesin light chain 1 in the Y2H assay. The carboxyl-terminal region of Tubb2 is essential for interaction with KIF3A. Other Tubb isoforms, including Tubb1, Tubb3, Tubb4, and Tubb5, also interacted with KIF3A in the Y2H screening. However, ${\alpha}1-tubulin$ (Tuba1) did not interact with KIF3A. In addition, an antibody to KIF3A specifically co-immunoprecipitated the KIF3B and KAP3 associated with Tubb2 from mouse brain extracts. In combination, these results suggest that a heterotrimeric kinesin 2 motor protein is capable of binding to tubulin and may transport it in cells.

• Journal of Nutrition and Health
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• v.51 no.6
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• pp.580-589
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• 2018

Purpose: The purpose of this study was to evaluate the food insecurity status and dietary behavior and examine the association between the food insecurity status and consumption of processed beverage for secondary school students in Vientiane, capital city of Lao PDR. Methods: The study subjects are 714 students (boys = 307 and girls = 407) in four secondary schools (Chao_Anouvong, Phiavat, Saysetha, and Chansavang) of Vientiane, Lao PDR. Data on study subject's demographic characteristics, dietary behavior, food insecurity, and Mini Dietary Assessment (MDA) index were collected. A "Self-Administered Food Security Survey Module for Children Aged 12 Years and Older" developed by the United States Department of Agriculture (USDA) was used for the food insecurity assessment. Results: As a result, 72.7% of the subjects were in a state of food insecurity, and food security was associated with higher socioeconomic status (higher life satisfaction, higher parent's education attainment, higher item ownership, fewer number of siblings, and having more lunches at the school restaurant than at home). Compared to the food insecurity group, the frequency of breakfast, self-rated diet, and the total score of MDA index were higher in the food security group. On the other hand, multiple logistic regression analysis showed that 'food security' was also associated with a higher consumption of processed beverages (OR 1.544; 95% CI 1.078-2.213; p = 0.018). Conclusion: Improving the quality of the diet is essential for adolescents in both the food insecurity and food security groups in Lao PDR. Therefore, it is necessary to provide well organized nutrition education and establish adequate nutrition policy for adolescents in Lao PDR.

• Korean Journal of Environment and Ecology
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• v.33 no.3
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• pp.354-365
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• 2019

This study measured and analyzed the weather characteristics and the air-ion characteristics of walking space by land use type in Chungju, Chungcheongbuk Province during the heat wave. We used the land registration map to classify the type of land use in walking areas in the studied into the production and green area, the residential area, and the commercial area. We then selected 44 measurement points in about 4.1 km. They included 12 walking space points in the green area, 14 in the residential area, and 18 in the commercial area. Moreover, we calculated the ion index by analyzing the impact of weather factors such as temperature, relative humidity, solar radiation, and net radiation in the walking space on the anion generation and cation generation by land use type during the heat wave. Comparison of air ion characteristics in walking space by type of land use during the heat wave showed that the average cation generation was in the order of commercial area ($700.73cations/cm^3$) > residential area ($600.76cations/cm^3$) > green area ($589.73cations/cm^3$). The average anion generation was in the order of green area ($663.95anions/cm^3$) > residential area ($628.48anions/cm^3$) > commercial area ($527.48anions/cm^3$). The average ion index was in the order of green area (1.13) > residential area (1.04) > commercial area (0.75). This study checked the weather characteristics, cation generation, and anion generation in walking space according to the land use type during the heat wave and checked the difference of ion indexes in the walking space according to the land use type. However, there were limitations in the lack of accurate comparison according to the land use due to the moving measurement and the insufficient quantitative comparison according to the change of road width. Therefore, we recommend further studies that consider the road characteristics.

• Science of Emotion and Sensibility
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• v.21 no.4
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• pp.63-76
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• 2018

The purpose of this study was to investigate the effect of contact type textile electrode structure on heart activity signal acquisition for smart healthcare. In this study, we devised six contact type textile electrodes whose electrode size and configuration were manipulated for measuring heart activity signals using computerized embroidery. We detected heart activity signals using a modified lead II and by attaching each textile electrode to the chest band in four healthy male subjects in a standing static posture. We measured the signals four times repeatedly for all types of electrodes. The heart activity signals were sampled at 1 kHz using a BIOPAC ECG100, and the detected original signals were filtered through a band-pass filter. To compare the performance of heart activity signal acquisition among the different structures of the textile electrodes, we conducted a qualitative analysis using signal waveform and size as parameters. In addition, we performed a quantitative analysis by calculating signal power ratio (SPR) of the heart activity signals obtained through each electrode. We analyzed differences in the performance of heart activity signal acquisition of the six electrodes by performing difference and post-hoc tests using nonparametric statistic methods on the calculated SPR. The results showed a significant difference both in terms of qualitative and quantitative aspects of heart activity signals among the tested contact type textile electrodes. Regarding the configurations of the contact type textile electrodes, the three-dimensionally inflated electrode (3DIE) was found to obtain better quality signals than the flat electrode. However, regarding the electrode size, no significant difference was found in performance of heart signal acquisition for the three electrode sizes. These results suggest that the configuration method (flat/3DIE), which is one of the two requirements of a contact type textile electrode structure for heart activity signal acquisition, has a critical effect on the performance of heart activity signal acquisition for wearable healthcare. Based on the results of this study, we plan to develop a smart clothing technology that can monitor high-quality heart activity without time and space constraints by implementing a clothing platform integrated with the textile electrode and developing a performance improvement plan.