• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.2
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• pp.119-127
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• 2021

The objective of this study was to evaluate effects of feeding methods on in vitro ruminal fermentation, total gas and methane production in Hanwoo steers. Six Hanwoo steers fitted with rumen cannula (430 ± 21 kg of body weight) were randomly assigned to one of three feeding systems: 1) feeding forage 1 hour after concentrate, 2) feeding concentrate 1 hour after forage, 3) feeding mixed ration. Rumen fluid sampled from each animals was incubated 24 hours with maize or timothy substrates in in vitro. Ruminal pH was increased in feeding method 2 or maize substrate than that of other methods or timothy substrate (P < 0.001). The production of total volatile fatty acid, acetate, propionate, butyrate, and valerate were increased when steers fed diets using feeding method 1 or rumen fluid was incubated with maize substrate (P < 0.001). Increased production of total gas and methane was observed in feeding method 1 and maize substrate compared to those of other methods or timothy substrate (P < 0.001). Due to the inconsistent results between ruminal fermentation and gas production in this study, further research is required to estimate effects of feeding method on enteric fermentation and gas production in in vivo.

• Journal of Life Science
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• v.31 no.5
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• pp.453-463
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• 2021

Hearing loss is a group of clinically and genetically heterogeneous disorders characterized by congenital- to adult-onset deafness with frequent additional symptoms such as myopathy, nephropathy, and optic disorders. It is commonly divided into two types: syndromic, with no other symptoms, and nonsyndromic, with other symptoms. Autosomal recessive hearing loss is relatively frequent in Pakistan, which may be due in part to frequent consanguineous marriages. This study was performed by whole exome sequencing to determine the genetic causes in two Pakistani consanguineous families with autosomal recessive hearing loss. We identified a pathogenic homozygous variant (p.Leu326Gln in MYO7A) in a family with prelingual-onset hearing loss and two variants of uncertain significance (p.Val3094Ile in GPR98 and p.Asp56Gly in PLA2G6) in a family with early-onset hearing loss concurrent with muscular atrophy. The missense mutations in MYO7A and PLA2G6 were located in the highly conserved sites, and in silico analyses predicted pathogenicity, while the GPR98 mutation was located in the less conserved site, and most in silico analysis programs predicted its nonpathogenic effect. Homozygosity mapping showed that both alleles of the homozygous mutations identified in each family originated from a single founder; spread from this single source might be due to consanguineous marriages. This study will help provide exact molecular diagnosis and treatment for autosomal recessive hearing loss patients in Pakistan.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.151-176
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• 2021

As the information technology industry develops, various kinds of data are being created, and it is now essential to process them and use them in the industry. Analyzing and utilizing various digital data collected online and offline is a necessary process to provide an appropriate experience for customers in the industry. In order to create new businesses, products, and services, it is essential to use customer data collected in various ways to deeply understand potential customers' needs and analyze behavior patterns to capture hidden signals of desire. However, it is true that research using data analysis and UX methodology, which should be conducted in parallel for effective service development, is being conducted separately and that there is a lack of examples of use in the industry. In thiswork, we construct a single process by applying data analysis methods and UX methodologies. This study is important in that it is highly likely to be used because it applies methodologies that are actively used in practice. We conducted a survey on the topic to identify and cluster the associations between factors to establish customer classification and target customers. The research methods are as follows. First, we first conduct a factor, regression analysis to determine the association between factors in the happiness data survey. Groups are grouped according to the survey results and identify the relationship between 34 questions of psychological stability, family life, relational satisfaction, health, economic satisfaction, work satisfaction, daily life satisfaction, and residential environment satisfaction. Second, we classify clusters based on factors affecting happiness and extract the optimal number of clusters. Based on the results, we cross-analyzed the characteristics of each cluster. Third, forservice definition, analysis was conducted by correlating with keywords related to happiness. We leverage keyword analysis of the thumb trend to derive ideas based on the interest and associations of the keyword. We also collected approximately 11,000 news articles based on the top three keywords that are highly related to happiness, then derived issues between keywords through text mining analysis in SAS, and utilized them in defining services after ideas were conceived. Fourth, based on the characteristics identified through data analysis, we selected segmentation and targetingappropriate for service discovery. To this end, the characteristics of the factors were grouped and selected into four groups, and the profile was drawn up and the main target customers were selected. Fifth, based on the characteristics of the main target customers, interviewers were selected and the In-depthinterviews were conducted to discover the causes of happiness, causes of unhappiness, and needs for services. Sixth, we derive customer behavior patterns based on segment results and detailed interviews, and specify the objectives associated with the characteristics. Seventh, a typical persona using qualitative surveys and a persona using data were produced to analyze each characteristic and pros and cons by comparing the two personas. Existing market segmentation classifies customers based on purchasing factors, and UX methodology measures users' behavior variables to establish criteria and redefine users' classification. Utilizing these segment classification methods, applying the process of producinguser classification and persona in UX methodology will be able to utilize them as more accurate customer classification schemes. The significance of this study is summarized in two ways: First, the idea of using data to create a variety of services was linked to the UX methodology used to plan IT services by applying it in the hot topic era. Second, we further enhance user classification by applying segment analysis methods that are not currently used well in UX methodologies. To provide a consistent experience in creating a single service, from large to small, it is necessary to define customers with common goals. To this end, it is necessary to derive persona and persuade various stakeholders. Under these circumstances, designing a consistent experience from beginning to end, through fast and concrete user descriptions, would be a very effective way to produce a successful service.

• Journal of The Korean Society of Grassland and Forage Science
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• v.40 no.4
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• pp.236-243
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• 2020

This study was to evaluate the feed value of whole crop rice silage (WCRS) and to investigate a suitable ratio of the WCRS and concentrate by an analysis of rumen fermentation. A total of 6 treatments were used according to WCRS: concentrate ratio on in vitro rumen fermentation: T1 (100:0), T2 (60:40), T3 (40:60), T4 (20:80), T5 (10:90), and T6 (0:100). The ruminal pH, total gas emission, ammonia nitrogen, and volatile fatty acid (VFA) were determined as fermentation parameters. Total nutrients digestibility trial was conducted by 4 treatments according to WCRS: concentrate ratio at 40:60 (W40), 20:80 (W20), and 10:90 (W10), respectively. Feed value was analyzed according to AOAC (2019) and nutrient digestibility was calculated based on NRC (2001). The levels of crude protein (CP), crude fat, and neutral detergent fiber of the WCRS were 12.29%, 1.67%, and 59.79%, respectively. It was found to be 51.49% as a result of predicting the total digestible nutrient of WCRS using the NRC (2001) model. In vitro rumen fermentation, T4, T5, and T6 treatments showed a greater gas emission and total VFA concentration compared with other treatments (p<0.05). Acetate and acetate to propionate ratio of T4, T5, and T6 were significantly higher than other treatments (p<0.05). There was a significant difference in the level of propionate and butyrate according to the WCRS: concentrate ratio (p<0.05). The digestibility of dry matter and CP was significantly lower in W40 than in other treatments (p<0.05); however, there was no difference in W20 and W10. In conclusion, the 20:80 (WCRS: concentrate) is beneficial for stabilizing the rumen that does not inhibit rumen fermentation and nutrient digestion. This ratio might have a positive effect on the economics of farms as a valuable feed.

• Journal of Life Science
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• v.31 no.8
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• pp.719-728
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• 2021

Melanin pigments are abundantly distributed in mammalian skin, hair, eyes, and nervous system. Under normal physiological conditions, melanin protects the skin against various environmental stresses and acts as a physiological redox buffer to maintain homeostasis. However, abnormal melanin accumulation results in various hyperpigmentation conditions, such as chloasma, freckles, senile lentigo, and inflammatory pigmentation. Tyrosinase, a copper-containing enzyme, plays an important role in the regulation of the melanin pigment biosynthetic pathway. Although several whitening agents based on tyrosinase inhibition have been developed, their side effects, such as allergies, DNA damage, mutagenesis, and cytotoxicity of melanocytes, limit their applications. In this study, we synthesized 4-chromanone derivatives (MHY compounds) and investigated their ability to inhibit tyrosinase activity. Of these compounds, (E)-3-(4-hydroxybenzylidene)chroman-4-one (MHY1294) more potently inhibited the enzymatic activity of tyrosinase (IC₅₀ = 5.1±0.86 μM) than kojic acid (14.3±1.43 μM), a representative tyrosinase inhibitor. In addition, MHY1294 showed competitive inhibitory action at the catalytic site of tyrosinase and had greater binding affinity at this site than kojic acid. Furthermore, MHY1294 effectively inhibited α-melanocyte stimulating hormone (α-MSH)-induced melanin synthesis and intracellular tyrosinase activity in B16F10 melanoma cells. The results of the present study indicate that MHY1294 may be considered as a candidate pharmacological agent and cosmetic whitening ingredient.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.384-392
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• 2022

The objective of this study was to estimated nitrogen content and chlorophyll using RGB, Hyperspectral sensors to diagnose of nitrogen nutrition in apple tree leaves. Spectral data were acquired through image processing after shooting with high resolution RGB and hyperspectral sensor for two-year-old 'Hongro/M.9' apple. Growth data measured chlorophyll and leaf nitrogen content (LNC) immediately after shooting. The growth model was developed by using regression analysis (simple, multi, partial least squared) with growth data (chlorophyll, LNC) and spectral data (SPAD meter, color vegetation index, wavelength). As a result, chlorophyll and LNC showed a statistically significant difference according to nitrogen fertilizer level regardless of date. Leaf color became pale as the nutrients in the leaf were transferred to the fruit as over time. RGB sensor showed a statistically significant difference at the red wavelength regardless of the date. Also hyperspectral sensor showed a spectral difference depend on nitrogen fertilizer level for non-visible wavelength than visible wavelength at June 10th and July 14th. The estimation model performance of chlorophyll, LNC showed Partial least squared regression using hyperspectral data better than Simple and multiple linear regression using RGB data (Chlorophyll R²: 81%, LNC: 81%). The reason is that hyperspectral sensor has a narrow Full Half at Width Maximum (FWHM) and broad wavelength range (400-1,000 nm), so it is thought that the spectral analysis of crop was possible due to stress cause by nitrogen deficiency. In future study, it is thought that it will contribute to development of high quality and stable fruit production technology by diagnosis model of physiology and pest for all growth stage of tree using hyperspectral imagery.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.376-383
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• 2022

The current study, which consisted of two independent studies (laboratory and greenhouse), was carried out to project the hypothesis fungi-spray scheduling for leaf mold and gray leaf spot in tomato, as well as to evaluate the effect of temperature and leaf wet duration on the effectiveness of different fungicides against these diseases. In the first experiment, tomato leaves were infected with 1 × 10⁴ conidia·mL^-1 and put in a dew chamber for 0 to 18 hours at 10 to 25℃ (Fulvia fulva) and 10 to 30℃ (Stemphylium lycopersici). In farm study, tomato plants were treated for 240 hours with diluted (1,000 times) 30% trimidazole, 50% polyoxin B, and 40% iminoctadine tris (Belkut) for protection of leaf mold, and 10% etridiazole + 55% thiophanate-methyl (Gajiran), and 15% tribasic copper sulfate (Sebinna) for protection of gray leaf spot. In laboratory test, leaf condensation on the leaves of tomato plants were emerged after 9 hrs. of incubation. In conclusion, the incidence degree of leaf mold and gray leaf spot disease on tomato plants shows that it is very closely related to formation of leaf condensation, therefore the incidence of leaf mold was greater at 20 and 15℃, while 25 and 20℃ enhanced the incidence of gray leaf spot. The incidence of leaf mold and gray leaf spot developed 20 days after inoculation, and the latency period was estimated to be 14-15 days. Trihumin fungicide had the maximum effectiveness up to 168 hours of fungicides at 12 hours of wet duration in leaf mold, whereas Gajiran fungicide had the highest control (93%) against gray leaf spot up to 144 hours. All the chemicals showed an around 30-50% decrease in effectiveness after 240 hours of treatment. The model predictions in present study could be help in timely, effective and ecofriendly management of leaf mold disease in tomato.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.497-510
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• 2022

Agricultural reservoirs are essential structures for water supplies during dry period in the Korean peninsula, where water resources are temporally unequally distributed. For efficient water management, systematic and effective monitoring of medium-small reservoirs is required. Synthetic Aperture Radar (SAR) provides a way for continuous monitoring of those, with its capability of all-weather observation. This study aims to evaluate the applicability of SAR in monitoring medium-small reservoirs using Sentinel-1 (10 m resolution) and Capella X-SAR (1 m resolution), at Chari (CR), Galjeon (GJ), Dwitgol (DG) reservoirs located in Ulsan, Korea. Water detected results applying Z fuzzy function-based threshold (Z-thresh) and Chan-vese (CV), an object detection-based segmentation algorithm, are quantitatively evaluated using UAV-detected water boundary (UWB). Accuracy metrics from Z-thresh were 0.87, 0.89, 0.77 (at CR, GJ, DG, respectively) using Sentinel-1 and 0.78, 0.72, 0.81 using Capella, and improvements were observed when CV was applied (Sentinel-1: 0.94, 0.89, 0.84, Capella: 0.92, 0.89, 0.93). Boundaries of the waterbody detected from Capella agreed relatively well with UWB; however, false- and un-detections occurred from speckle noises, due to its high resolution. When masked with optical sensor-based supplementary images, improvements up to 13% were observed. More effective water resource management is expected to be possible with continuous monitoring of available water quantity, when more accurate and precise SAR-based water detection technique is developed.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

• Journal of Environmental Impact Assessment
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• v.32 no.1
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• pp.41-48
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• 2023

This study was conducted to confirm the possibility of a new carbon stock in the Sejong National Arboretum, a major urban greenspace in Sejong-si. This study involved field and ground surveys of 1,336 trees, including 794 Pinus densiflora trees with a diameter at breast height (DBH) of above 5.5cm, which are the most planted in the Sejong National Arboretum, Chionanthus retusus 154 trees planted, Metasequoia glyptostroboides 216 trees, and Aesculus turbinata 172 trees as street trees. Measurements were performed from April to November. Based on the results of the survey, the carbon storage and annual carbon stock were calculated using the annual carbon stock estimation equation used in the forest carbon offset projects. As a result of comparing the carbon stock of the 12cm diameter class, which is the most distributed of four major trees, it was found in the order of C. retusus (0.0136tC/tree), P. densiflora (0.0126tC/tree), M. glyptostroboides (0.0092tC/tree), and A. turbinata (0.0076tC/tree). In addition, the field survey measurement data compared with terrestrial LiDAR measurement data for 20 trees showed a difference of 10.0cm in tree height and 1.7cm in diameter at breast height (p<0.05). In the future, additional carbon stock and annual uptake of other species planted in the arboretum are expected to promote the carbon uptake effect of the arboretum and contribute to the achievement of the national NDC. In the long term, it is also necessary to develop the carbon uptake factor of trees and shrubs mainly used to calculate the exact carbon uptake amount of trees mainly used in urban forests and gardens.