• Journal of Life Science
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• v.23 no.11
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• pp.1397-1403
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• 2013

Fructus Sophorae, the dried ripe fruit of Styphnolobium japonicum (L.), is an herbal ingredient used in traditional Oriental medicine. This study was carried out to investigate the effects of Fructus Sophorae extracts (FSE) on immune modulation in a murine RAW 264.7 macrophage model. As immune response parameters, the production of prostaglandin $E_2$ ($PGE_2$) and tumor necrotic $factor-{\alpha}$ ($TNF-{\alpha}$) were evaluated. Our data revealed that FSE increased the macrophage activation and the production of $PGE_2$ and $TNF-{\alpha}$, which was consistently correlated with upregulation of cyclooxygenase-2 (COX-2) and $TNF-{\alpha}$ expression at both transcriptional and translational levels. On comparative cytokine protein array, FSE significantly increased several cytokines, which was associated with phosphorylation of mitogen- activated protein kinases (MAPKs), including extracellular signal-regulated kinase (ERK), p38 MAPK and c-Jun N-terminal kinase (JNK), and Akt in RAW 264.7 cells. However, each inhibitor of these molecules attenuated the FSE-induced $PGE_2$ production. These results indicate that FSE activated macrophages through the activation of MAPKs and phosphatidylinositol-3-kinase (PI3K)/Akt signaling pathways in RAW 264.7 macrophages. These findings suggest that FSE may provide a promising source of an immunoenhancing agent.

• Korean Journal of Ecology and Environment
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• v.42 no.2
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• pp.260-269
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• 2009

Hwabuk Dam has been under construction to reduce flood damage in Nakdong River watershed and to supply stable water for middle area of Gyeongbuk Province. Therefore, fish investigation in up and downstream of the dam was conducted from 2004 to 2008 in order to determine any negative effect on fish community due to dam construction and to use as fundamental data for conserving species diversity and maintaining stream health. According to data analysis on water quality, temperature, dissolved oxygen, pH, suspended solids, and total E-coli had seasonal variation, but they did not significantly differ in sites. However, biological and chemical oxygen demand, chlorophyll-a, nitrogen, and phosphorus representing organic matter and nutrient concentration were higher in upper site and decreased to lower site so that they differed by site. Concentration of arsenic among the heavy metals was less than 0.05 mg $L^{-1}$, which is regulated for protection of human health in water quality standard, except for 0.092 mg $L^{-1}$ in June 2005. During the study period, the total number of fish caught from the 6 sites was 10,263 representing 7 families 19 species. Among them, dominant and subdominant species were Korean chub (Zacco koreanus, 62.5%) and Chinese minnow (Rhynchocypris oxycephalus, 10.6%) which inhabit mostly in mid and upper streams, Korea. Among the 19 species, Korean endemic species were 9 species (47.4%) including Korean slender gudgeon (Squalidus gracilis majimae), Korean dark sleeper (Odontobutis platycephala), and Korean shiner (Coreoleuciscus splendidus). There was several individuals of the $1^{st}$-class endangered species, Naktong nose loach (Koreocobitis nahtongensis), caught in 2005${\sim}$2007, and no introduced species of fish was found in entire sampling period. According to result of community analysis, dominance index decreased toward lower site, but diversity and richness indices increased toward lower site. The equation of length-weight relationship on the dominant species was TW=0.000003$(TL)^{3.2603}$. The parameter b in the equation was greater than 3.0 indicating good nutritional condition in the populations. Compared to populations of Korean chub in other streams, the population in Hwabuk Dam watershed had higher mean of condition factor by size indicating better growth rate. With fish fauna and multi-metric health assessment model in each sampling attempt, index of biotic integrity (IBI) was evaluated and it resulted mostly in good (26${\sim}$35) and excellent (36${\sim}$40) condition in all sites, and the mean of IBI was the highest in site 5. The results indicate that it is very important to study not only environmental impact assessment with fish composition but also stream health assessment in order to conserve healthy aquatic ecosystem.

• Journal of agriculture & life science
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• v.44 no.5
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• pp.55-64
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• 2010

This study was conducted to estimate genetic parameters for reproductive traits using multivariate animal models in Yorkshire breed. For the study, 4,989 records for litter traits collected between the year 2001 and 2005 from Yorkshire pigs in K GGP were used. The effects of environmental factors such as farrowing year, parity, weaning to estrus interval (WEI), and suckling period were statistically significant (p<0.05), but farrowing season was not significant, for reproductive traits. The estimates genetic correlations and phenotypic correlations in total number of born and number of suckling, was shown to highly correlated. The genetic correlations were higher than phenotypic correlation. The estimates of heritabilities for reproductive traits, considering permanent environment effects (PE) were much lower than those obtained when permanent environment effects were not considered (NPE) in the model. The estimates of heritabilities were 0.240 and 0.076 for total number of born and 0.187 and 0.096 for number of suckling in NPE, and PE, respectively. These results itivcate that PE should be considered in the statistical mode to estimate more acco ate breeding values.

• Korean Journal of Remote Sensing
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• v.14 no.2
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• pp.175-195
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• 1998

Automatic lineament extraction algorithms had been developed by various researches for geological purpose using remotely sensed data. However, most of them are designed for a certain topographic model, for instance rugged mountainous region or flat basin. Most of common topographic characteristic in Korea is a mountainous region along with alluvial plain, and consequently it is difficult to apply previous algorithms directly to this area. A new algorithm of automatic lineament extraction from remotely sensed images is developed in this study specifically for geological applications. An algorithm, named as DSTA(Dynamic Segment Tracing Algorithm), is developed to produce binary image composed of linear component and non-linear component. The proposed algorithm effectively reduces the look direction bias associated with sun's azimuth angle and the noise in the low contrast region by utilizing a dynamic sub window. This algorithm can successfully accomodate lineaments in the alluvial plain as well as mountainous region. Two additional algorithms for estimating the individual lineament vector, named as ALEHHT(Automatic Lineament Extraction by Hierarchical Hough Transform) and ALEGHT(Automatic Lineament Extraction by Generalized Hough Transform) which are merging operation steps through the Hierarchical Hough transform and Generalized Hough transform respectively, are also developed to generate geological lineaments. The merging operation proposed in this study is consisted of three parameters: the angle between two lines($\delta$$\beta$), the perpendicular distance($(d_ij)$), and the distance between midpoints of lines(dn). The test result of the developed algorithm using Landsat TM image demonstrates that lineaments in alluvial plain as well as in rugged mountain is extremely well extracted. Even the lineaments parallel to sun's azimuth angle are also well detected by this approach. Further study is, however, required to accommodate the effect of quantization interval(droh) parameter in ALEGHT for optimization.

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.6
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• pp.435-441
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• 2007

Ground-based optical sensing over the crop canopy provides information on the mass of plant body which reflects the light, as well as crop nitrogen content which is closely related to the greenness of plant leaves. This method has the merits of being non-destructive real-time based, and thus can be conveniently used for decision making on application of nitrogen fertilizers for crops standing in fields. In the present study relationships among leaf nitrogen content of rice canopy, crop growth status, and Normalized Difference Vegetation Index (NDVI) values were investigated. We measured Green normalized difference vegetation index($gNDVI=({\rho}0.80{\mu}m-{\rho}0.55{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.55{\mu}m)$) and NDVI($({\rho}0.80{\mu}m-{\rho}0.68{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.68{\mu}m)$) were measured by using two different active sensors (Greenseeker, NTech Inc. USA). The study was conducted in the years 2005-06 during the rice growing season at the experimental plots of National Institute of Agricultural Science and Technology located at Suwon, Korea. The experiments carried out with randomized complete block design with the application of four levels of nitrogen fertilizers (0, 70, 100, 130kg N/ha) and same amount of phosphorous and potassium content of the fertilizers. gNDVI and rNDVI increased as growth advanced and reached to maximum values at around early August, G(NDVI) were a decrease in values of observed with the crop maturation. gNDVI values and leaf nitrogen content were highly correlated at early July in 2005 and 2006. On the basis of this finding we attempted to estimate the leaf N contents using gNDVI data obtained in 2005 and 2006. The determination coefficients of the linear model by gNDVI in the years 2005 and 2006 were 0.88 and 0.94, respectively. The measured and estimated leaf N contents using gNDVI values showed good agreement ($R^2=0.86^{***}$). Results from this study show that gNDVI values represent a significant positive correlation with leaf N contents and can be used to estimate leaf N before the panicle formation stage. gNDVI appeared to be a very effective parameter to estimate leaf N content the rice canopy.

• Korean journal of applied entomology
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• v.57 no.4
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• pp.261-269
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• 2018

The cowpea aphid Aphis craccivora Koch (Hemiptera: Aphididae) is a polyphagous species with a worldwide distribution. We investigated the temperature effects on development periods of nymphs, and the longevity and fecundity of apterous female of A. craccivora. The study was conducted at six constant temperatures of 10.0, 15.0, 20.0, 25, 30.0, and $32.5^{\circ}C$. A. craccivora developed successfully from nymph to adult stage at all temperatures subjected. The developmental rate of A. craccivora increased as temperature increased. The lower developmental threshold (LT) and thermal constant (K) of A. craccivora nymph stage were estimated by linear regression as $5.3^{\circ}C$ and 128.4 degree-days (DD), respectively. Lower and higher threshold temperatures (TL, TH and TH-TL, respectively) were calculated by the Sharpe_Schoolfield_Ikemoto (SSI) model as $17.0^{\circ}C$, $34.6^{\circ}C$ and $17.5^{\circ}C$. Developmental completion of nymph stages was described using a three-parameter Weibull function. Life table parameters were estimated. The intrinsic rate of increase was highest at $25^{\circ}C$, while the net reproductive rate was highest at $20^{\circ}C$. Biological characteristics of A. craccivora populations from different geographic areas were discussed.

• Korean Journal of Poultry Science
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• v.47 no.4
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• pp.267-274
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• 2020

This study was conducted to estimate genetic parameters for growth and egg production traits in Black Korean native chicken (L strain) and Korean White Leghorn (F, K strains) using a multi-traits animal model BLUP. Traits used for this study were body weight at 150 days (BW150) and 270 days (BW270), age at first egg (DAY1st), egg weight at first egg (EW1st) and 270 days (EW270), and number of eggs laid by 270 days (EP270), and included 68,688 pedigree and 123,905 performance records collected from 2001 to 2013. In L, F, K strains, heritability estimates of BW150 were high (0.48, 0.52 and 0.50, respectively); of BW270 were high (0.56, 0.57 and 0.56); of DAY1st were medium to high (0.45, 0.39 and 0.31); of EW1st were low (0.15, 0.16 and 0.15); of EW270 were high (0.58, 0.55 and 0.59) and of EP270 were moderate (0.22, 0.21 and 0.20). The genetic and phenotypic correlation of DAY1st with EP270 were highly negative (-0.73 to -0.63 and -0.48 to -0.42). The genetic and phenotypic correlation of EP270 with BW150 and BW270, respectively were low negative (-0.16 to 0.01 and -0.14 to -0.03) and low to moderate positive (-0.08 to 0.07 and -0.13 to 0.04). The genetic and phenotypic correlation of EW270 with BW150 and BW270, respectively were moderate to high positive (0.39 to 0.49 and 0.36 to 0.46) and (0.29 to 0.33 and 0.34 to 0.37). The study showed that there is a potential for genetic improvement of Korean Indigenous chicken through selection program.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.297-309
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• 2023

The degradation of coastal ecosystems and fishery environments is accelerating due to the recent phenomenon of invertebrate grazers. To effectively monitor and implement preventive measures for this phenomenon, the adoption of remote sensing-based monitoring technology for extensive maritime areas is imperative. In this study, we compared and analyzed the robustness of deep learning-based object detection modelsfor detecting and monitoring invertebrate grazersfrom underwater videos. We constructed an image dataset targeting seven representative species of invertebrate grazers in the coastal waters of South Korea and trained deep learning-based object detection models, You Only Look Once (YOLO)v7 and YOLOv8, using this dataset. We evaluated the detection performance and speed of a total of six YOLO models (YOLOv7, YOLOv7x, YOLOv8s, YOLOv8m, YOLOv8l, YOLOv8x) and conducted robustness evaluations considering various image distortions that may occur during underwater filming. The evaluation results showed that the YOLOv8 models demonstrated higher detection speed (approximately 71 to 141 FPS [frame per second]) compared to the number of parameters. In terms of detection performance, the YOLOv8 models (mean average precision [mAP] 0.848 to 0.882) exhibited better performance than the YOLOv7 models (mAP 0.847 to 0.850). Regarding model robustness, it was observed that the YOLOv7 models were more robust to shape distortions, while the YOLOv8 models were relatively more robust to color distortions. Therefore, considering that shape distortions occur less frequently in underwater video recordings while color distortions are more frequent in coastal areas, it can be concluded that utilizing YOLOv8 models is a valid choice for invertebrate grazer detection and monitoring in coastal waters.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.41-76
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• 2020

This study confirmed factors affecting smart factory technology acceptance through empirical analysis. It is a study on what factors have an important influence on the introduction of the smart factory, which is the core field of the 4th industry. I believe that there is academic and practical significance in the context of insufficient research on technology acceptance in the field of smart factories. This research was conducted based on the Unified Theory of Acceptance and Use of Technology (UTAUT), whose explanatory power has been proven in the study of the acceptance factors of information technology. In addition to the four independent variables of the UTAUT : Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions, Government Assistance Expectancy, which is expected to be an important factor due to the characteristics of the smart factory, was added to the independent variable. And, in order to confirm the technical factors of smart factory technology acceptance, the Task Technology Fit(TTF) was added to empirically analyze the effect on Behavioral Intention. Trust is added as a parameter because the degree of trust in new technologies is expected to have a very important effect on the acceptance of technologies. Finally, empirical verification was conducted by adding Innovation Resistance to a research variable that plays a role as a moderator, based on previous studies that innovation by new information technology can inevitably cause refusal to users. For empirical analysis, an online questionnaire of random sampling method was conducted for incumbents of domestic small and medium-sized enterprises, and 309 copies of effective responses were used for empirical analysis. Amos 23.0 and Process macro 3.4 were used for statistical analysis. For accurate statistical analysis, the validity of Research Model and Measurement Variable were secured through confirmatory factor analysis. Accurate empirical analysis was conducted through appropriate statistical procedures and correct interpretation for causality verification, mediating effect verification, and moderating effect verification. Performance Expectancy, Social Influence, Government Assistance Expectancy, and Task Technology Fit had a positive (+) effect on smart factory technology acceptance. The magnitude of influence was found in the order of Government Assistance Expectancy(β=.487) > Task Technology Fit(β=.218) > Performance Expectancy(β=.205) > Social Influence(β=.204). Both the Task Characteristics and the Technology Characteristics were confirmed to have a positive (+) effect on Task Technology Fit. It was found that Task Characteristics(β=.559) had a greater effect on Task Technology Fit than Technology Characteristics(β=.328). In the mediating effect verification on Trust, a statistically significant mediating role of Trust was not identified between each of the six independent variables and the intention to introduce a smart factory. Through the verification of the moderating effect of Innovation Resistance, it was found that Innovation Resistance plays a positive (+) moderating role between Government Assistance Expectancy, and technology acceptance intention. In other words, the greater the Innovation Resistance, the greater the influence of the Government Assistance Expectancy on the intention to adopt the smart factory than the case where there is less Innovation Resistance. Based on this, academic and practical implications were presented.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.175-191
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• 2011

With the MICE(Meeting, Incentive travel, Convention, Exhibition) industry coming into the spotlight, there has been a growing interest in the domestic exhibition industry. Accordingly, in Korea, various studies of the industry are being conducted to enhance exhibition performance as in the United States or Europe. Some studies are focusing particularly on analyzing visiting patterns of exhibition visitors using intelligent information technology in consideration of the variations in effects of watching exhibitions according to the exhibitory environment or technique, thereby understanding visitors and, furthermore, drawing the correlations between exhibiting businesses and improving exhibition performance. However, previous studies related to booth recommendation systems only discussed the accuracy of recommendation in the aspect of a system rather than determining changes in visitors' behavior or perception by recommendation. A booth recommendation system enables visitors to visit unplanned exhibition booths by recommending visitors suitable ones based on information about visitors' visits. Meanwhile, some visitors may be satisfied with their unplanned visits, while others may consider the recommending process to be cumbersome or obstructive to their free observation. In the latter case, the exhibition is likely to produce worse results compared to when visitors are allowed to freely observe the exhibition. Thus, in order to apply a booth recommendation system to exhibition halls, the factors affecting the performance of the system should be generally examined, and the effects of the system on visitors' unplanned visiting behavior should be carefully studied. As such, this study aims to determine the factors that affect the performance of a booth recommendation system by reviewing theories and literature and to examine the effects of visitors' perceived performance of the system on their satisfaction of unplanned behavior and intention to reuse the system. Toward this end, the unplanned behavior theory was adopted as the theoretical framework. Unplanned behavior can be defined as "behavior that is done by consumers without any prearranged plan". Thus far, consumers' unplanned behavior has been studied in various fields. The field of marketing, in particular, has focused on unplanned purchasing among various types of unplanned behavior, which has been often confused with impulsive purchasing. Nevertheless, the two are different from each other; while impulsive purchasing means strong, continuous urges to purchase things, unplanned purchasing is behavior with purchasing decisions that are made inside a store, not before going into one. In other words, all impulsive purchases are unplanned, but not all unplanned purchases are impulsive. Then why do consumers engage in unplanned behavior? Regarding this question, many scholars have made many suggestions, but there has been a consensus that it is because consumers have enough flexibility to change their plans in the middle instead of developing plans thoroughly. In other words, if unplanned behavior costs much, it will be difficult for consumers to change their prearranged plans. In the case of the exhibition hall examined in this study, visitors learn the programs of the hall and plan which booth to visit in advance. This is because it is practically impossible for visitors to visit all of the various booths that an exhibition operates due to their limited time. Therefore, if the booth recommendation system proposed in this study recommends visitors booths that they may like, they can change their plans and visit the recommended booths. Such visiting behavior can be regarded similarly to consumers' visit to a store or tourists' unplanned behavior in a tourist spot and can be understand in the same context as the recent increase in tourism consumers' unplanned behavior influenced by information devices. Thus, the following research model was established. This research model uses visitors' perceived performance of a booth recommendation system as the parameter, and the factors affecting the performance include trust in the system, exhibition visitors' knowledge levels, expected personalization of the system, and the system's threat to freedom. In addition, the causal relation between visitors' satisfaction of their perceived performance of the system and unplanned behavior and their intention to reuse the system was determined. While doing so, trust in the booth recommendation system consisted of 2nd order factors such as competence, benevolence, and integrity, while the other factors consisted of 1st order factors. In order to verify this model, a booth recommendation system was developed to be tested in 2011 DMC Culture Open, and 101 visitors were empirically studied and analyzed. The results are as follows. First, visitors' trust was the most important factor in the booth recommendation system, and the visitors who used the system perceived its performance as a success based on their trust. Second, visitors' knowledge levels also had significant effects on the performance of the system, which indicates that the performance of a recommendation system requires an advance understanding. In other words, visitors with higher levels of understanding of the exhibition hall learned better the usefulness of the booth recommendation system. Third, expected personalization did not have significant effects, which is a different result from previous studies' results. This is presumably because the booth recommendation system used in this study did not provide enough personalized services. Fourth, the recommendation information provided by the booth recommendation system was not considered to threaten or restrict one's freedom, which means it is valuable in terms of usefulness. Lastly, high performance of the booth recommendation system led to visitors' high satisfaction levels of unplanned behavior and intention to reuse the system. To sum up, in order to analyze the effects of a booth recommendation system on visitors' unplanned visits to a booth, empirical data were examined based on the unplanned behavior theory and, accordingly, useful suggestions for the establishment and design of future booth recommendation systems were made. In the future, further examination should be conducted through elaborate survey questions and survey objects.