• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.271-278
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• 2022

This study attempted to prepare basic data for international students with Vietnamese nationality in Korea to identify positive psychological capital, social support, social presence, and quality of life and to prepare support measures to improve their quality of life. Data collection is from May 1, 2021 to June 30, 2021, and was conducted through an online survey for anonymity and convenience. For data analysis, the IBM SPSS/25 statistical program was used, and the significance level for the results was measured as .05, and the reliability of each measurement tool was calculated. The results of this study are summarized as follows. First, the age of the subjects was '24 years old-27 years old', and women accounted for the majority. In the fourth grade, the fourth grade was the most, with "outgoing" personality, "sometimes" experiences of interpersonal conflict, "more than four years and less than five years" in the period of residence in Korea, and the level of Korean proficiency was "grade three." Second, the average quality of life of Vietnamese international students was 3.52 points (out of 5 points), positive psychological capital was 3.98 points (out of 6 points), social support was 2.96 points (out of 4 points), and social presence was 3.59 points (out of 5 points). Third, in the case of the quality of life of Vietnamese international students, there was a significant difference according to their personality, and as a result of post-verification, the quality of life of the 'extroverted' group was higher than the 'mixed' group. There was a significant difference according to interpersonal conflict), and as a result of post-examination, the "no conflict" group had a higher quality of life than the "conflict frequent" group. Fourth, the factors that most affected the subject's quality of life were social support, positive psychological capital, and personality (extroverted). The explanatory power of the model was 33.2%.

• Asia Marketing Journal
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• v.15 no.4
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• pp.61-101
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• 2014

This study investigates when and how disagreements in online customer ratings prompt more favorable product evaluations. Among the three metrics of volume, valence, and variance that feature in the research on online customer ratings, volume and valence have exhibited consistently positive patterns in their effects on product sales or evaluations (e.g., Dellarocas, Zhang, and Awad 2007; Liu 2006). Ratings variance, or the degree of disagreement among reviewers, however, has shown rather mixed results, with some studies reporting positive effects on product sales (e.g., Clement, Proppe, and Rott 2007) while others finding negative effects on product evaluations (e.g., Zhu and Zhang 2010). This study aims to resolve these contradictory findings by introducing preference heterogeneity as a possible moderator and causal attribution as a mediator to account for the moderating effect. The main proposition of this study is that when preference heterogeneity is perceived as high, a disagreement in ratings is attributed more to reviewers' different preferences than to unreliable product quality, which in turn prompts better quality evaluations of a product. Because disagreements mostly result from differences in reviewers' tastes or the low reliability of a product's quality (Mizerski 1982; Sen and Lerman 2007), a greater level of attribution to reviewer tastes can mitigate the negative effect of disagreement on product evaluations. Specifically, if consumers infer that reviewers' heterogeneous preferences result in subjectively different experiences and thereby highly diverse ratings, they would not disregard the overall quality of a product. However, if consumers infer that reviewers' preferences are quite homogeneous and thus the low reliability of the product quality contributes to such disagreements, they would discount the overall product quality. Therefore, consumers would respond more favorably to disagreements in ratings when preference heterogeneity is perceived as high rather than low. This study furthermore extends this prediction to the various levels of average ratings. The heuristicsystematic processing model so far indicates that the engagement in effortful systematic processing occurs only when sufficient motivation is present (Hann et al. 2007; Maheswaran and Chaiken 1991; Martin and Davies 1998). One of the key factors affecting this motivation is the aspiration level of the decision maker. Only under conditions that meet or exceed his aspiration level does he tend to engage in systematic processing (Patzelt and Shepherd 2008; Stephanous and Sage 1987). Therefore, systematic causal attribution processing regarding ratings variance is likely more activated when the average rating is high enough to meet the aspiration level than when it is too low to meet it. Considering that the interaction between ratings variance and preference heterogeneity occurs through the mediation of causal attribution, this greater activation of causal attribution in high versus low average ratings would lead to more pronounced interaction between ratings variance and preference heterogeneity in high versus low average ratings. Overall, this study proposes that the interaction between ratings variance and preference heterogeneity is more pronounced when the average rating is high as compared to when it is low. Two laboratory studies lend support to these predictions. Study 1 reveals that participants exposed to a high-preference heterogeneity book title (i.e., a novel) attributed disagreement in ratings more to reviewers' tastes, and thereby more favorably evaluated books with such ratings, compared to those exposed to a low-preference heterogeneity title (i.e., an English listening practice book). Study 2 then extended these findings to the various levels of average ratings and found that this greater preference for disagreement options under high preference heterogeneity is more pronounced when the average rating is high compared to when it is low. This study makes an important theoretical contribution to the online customer ratings literature by showing that preference heterogeneity serves as a key moderator of the effect of ratings variance on product evaluations and that causal attribution acts as a mediator of this moderation effect. A more comprehensive picture of the interplay among ratings variance, preference heterogeneity, and average ratings is also provided by revealing that the interaction between ratings variance and preference heterogeneity varies as a function of the average rating. In addition, this work provides some significant managerial implications for marketers in terms of how they manage word of mouth. Because a lack of consensus creates some uncertainty and anxiety over the given information, consumers experience a psychological burden regarding their choice of a product when ratings show disagreement. The results of this study offer a way to address this problem. By explicitly clarifying that there are many more differences in tastes among reviewers than expected, marketers can allow consumers to speculate that differing tastes of reviewers rather than an uncertain or poor product quality contribute to such conflicts in ratings. Thus, when fierce disagreements are observed in the WOM arena, marketers are advised to communicate to consumers that diverse, rather than uniform, tastes govern reviews and evaluations of products.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

• Journal of the Korean Society of Radiology
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• v.82 no.3
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• pp.670-681
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• 2021

Purpose This study aimed to investigate the optimal threshold value in Hounsfield units (HU) on CT to detect the solid components of pulmonary subsolid nodules using pathologic invasive foci as reference. Materials and Methods Thin-section non-enhanced chest CT scans of 25 patients with pathologically confirmed minimally invasive adenocarcinoma were retrospectively reviewed. On CT images, the solid portion was defined as the area with higher attenuation than various HU thresholds ranging from -600 to -100 HU in 50-HU intervals. The solid portion was measured as the largest diameter on axial images and as the maximum diameter on multiplanar reconstruction images. A linear mixed model was used to evaluate bias in each threshold by using the pathological size of invasive foci as reference. Results At a threshold of -400 HU, the biases were lowest between the largest/maximum diameter of the solid portion of subsolid nodule and the size of invasive foci of the pathological specimen, with 0.388 and -0.0176, respectively. They showed insignificant difference (p = 0.2682, p = 0.963, respectively) at a threshold of -400 HU. Conclusion For quantitative analysis, -400 HU may be the optimal threshold to define the solid portion of subsolid nodules as a surrogate marker of invasive foci.

• Korean Journal of Ecology and Environment
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• v.37 no.2 s.107
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• pp.180-192
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• 2004

This study was carried out to assess the seasonal variation of water quality and the effect of pollutant loading from watershed in a shallow eutrophic reservoir (Shingu reservoir) from November 2002 to February 2004, Stable thermocline which was greater than $1^{\circ}C$ per meter of the water depth formed in May, and low DO concentration (< 2 mg $O_2\;L^{-1}$) was observed in the hypolimnion from May to September, 2003. The ratio of euphotic depth to mixing depth ($Z_{eu}/Z_{m}$) ranged 0.2 ${\sim}$ 1.1, and the depth of the mixed layer exceeded that of the photic layer during study period, except for May when $Z_{eu}$ and $Z_{m}$ were 4 and 4.3 m, respectively. Most of total nitrogen, ranged 1.1 ${\sim}$ 4.5 ${\mu}g\;N\;L^{-1}$, accounted for inorganic nitrogen (Avg, 58.7%), and sharp increase of $NH_3$-N Hand $NO_3$-N was evident during the spring season. TP concentration in the water column ranged 43.9 ${\sim}$ 126.5 ${\mu}g\;P\;L^{-1}$, and the most of TP in the water column accounted for POP (Avg. 80%). During the study period, DIP concentration in the water column was &;lt 10 ${\mu}g\;P\;L^{-1}$ except for July and August when DIP concentration in the hypolimnion was 22.3 and 56.7 ${\mu}g\;P\;L^{-1}$, respectively. Increase of Chl. a concentration observed in July (99 ${\mu}g\;L^{-1}$) and November 2003 (109 ${\mu}g\;L^{-1}$) when P loading through two inflows was high, and showed close relationship with TP concentration (r = 0.55, P< 0.008, n = 22). Mean Chl. a concentration ranged from 13.5 to 84.5 mg $L^{-1}$ in the water column, and the lowest and highest concentration was observed in February 2004 (13.5 ${\pm}$ 1.0 ${\mu}g\;L^{-1}$) and November 2003 (84.5 ${\pm}$29.0 ${\mu}g\;L^{-1}$), respectively. TP concentration in inflow water increased with discharge (r = 0.69, P< 0.001), 40.5% of annual total P loading introduced in 25 July when there was heavy rainfall. Annual total P loading from watershed was 159.0 kg P $yr^{-1}$, and that of DIP loading was 126.3 kg P $yr^{-1}$ (77.7% of TP loading. The loading of TN (5.0ton yr-1) was 30 times higher than that of TP loading (159.0 kg P yr-1), and the 78% of TN was in the form of non-organic nitrogen, 3.9 ton $yr^{-1}$ in mass. P loading in Shingu reservoir was 1.6 g ${\cdot}$ $m^{-2}$ ${\cdot}$ $yr^{-1}$, which passed the excessive critical loading of Vollenweider-OECD critical loading model. The results of this study indicated that P loading from watershed was the major factor to cause eutrophication and temporal variation of water quality in Shingu reservoir Decrease by 71% in TP loading (159 kg $yr^{-1}$) is necessary for the improvement of mesotrophic level. The management of sediment where tine anaerobic condition was evident in summer, thus, the possibility of P release that can be utilized by existing algae, may also be considered.

• Radiation Oncology Journal
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• v.22 no.1
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• pp.40-54
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• 2004

Purpose : Captopril (angiotension converting enzyme inhibitor) is known to have a radioproptective effect in the lungs, intestines and skin, but its effect in the heart is unclear. To investigate the radioprotectlve efiect and mechanism of captopril on the heart, the histopathological changes and immunohistochemical stains were compared with radiation alone, and radiation combined with captopril, in the rats. Materials and Methods : The histopathological changes and immunohistochemical stains ($TNF{\alpha}$, $TGF{\beta}1$, PDGF and FGF2) were examined in the radiation alone and the combined captopril and radiation groups, 2 and 8 weeks after irradiation. Each group consisted of 8 to 10 rats (Sprague-Dawley). Irradiation (12.5 Gy) was given to the left hemithorax in a single fraction. Captopril (50 mg/Kg/d) mixed with water, was given orally and continuously from the first week prior to, up to the 8th week of the experiment. Results : In the radiation alone group, the ventricle at 2 weeks after irradiation showed prominent edema (p=0.082) and fibrin deposit (p=0.018) compared to the control group. At 8 weeks, the edema was decreased and fibrosis increased compared to those at 2 weeks. The histopathological changes of the combined group were similar to those of the control group, due to the reduced radiation toxicity at 2 and 8 weeks. The endocardial fibrin deposit (p=0.047) in the atrium, and the interstitial fibrin deposit (p=0.019) and edema (p=0.042) of the ventricle were reduced significantly in the combined group compared to those in the radiation alone group at 2 weeks. The expressions of $TNF-{\alpha}$, $TGF-{\beta}1$, PDGF and FGF-2 in the radiation alone group were more increased than in the control group, especially in the pericardium and endocardium of the atrium at 2 weeks. At 8 weeks, the pericardial $TNF-{\alpha}$ and $TGF-{\beta}1$ in the radiation alone group continuously increased. The expressions of $TNF-{\alpha}$, $TGF-{\beta}1$ and PDGF were decreased in the combined group at 2 weeks. At 8 weeks, the expressions of $TNF-{\alpha}$ in the atrial and ventricular pericardia were markedly reduced (p=0.049, p=0.009). Conclusion : This study revealed that the early heart damage induced by radiation can be reduced by the addition of captopril in a rat model. The expressions of $TNF-{\alpha}$, $TGF-{\beta}1$ and PDGF were further decreased in the combined compared to the radiation alone group at both 2 and 8 weeks. From these results, it may be concluded that these cytokines probably play roles in the radioprotective mechanism of captopril from the radiation-induced heart toxicity, similarly to in other organs.

• Childhood Kidney Diseases
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• v.10 no.1
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• pp.8-17
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• 2006

Purpose : We describe the changes of rat glomerular epithelial cells when exposed to high levels of glucose and advanced glycosylation endproducts(AGE) in the in vitro diabetic condition. We expect morphological alteration of glomerular epithelial cells and permeability changes experimentally and we may correlate the results with a mechanism of proteinuria in DM. Methods : We made 0.2 M glucose-6-phsphate solution mixed with PBS(pH 7.4) containing 50 mg/mL BSA and pretense inhibitor for preparation of AGE. As control, we used BSA. We manufactured and symbolized five culture dishes as follows; B5 - normal glucose(5 mM) + BSA, B30 - high glucose(30 mM) + BSA, A5 - normal glucose(5 mM) + AGE, A30 - high glucose(30 mM) + AGE, A/B 25 - normal glucose(5 mM) + 25 mM of mannitol(osmotic control). After the incubation period of both two days and seven days, we measured the amount of heparan sulfate proteoglycan(HSPG) in each dish by ELISA and compared them with the B5 dish at 2nd and 7th incubation days. We observed the morphological changes of epithelial cells in each culture dish using scanning electron microscopy(SEM). We tried the permeability assay of glomerular epithelial cells using cellulose semi-permeable membrane measuring the amount of filtered BSA through the apical chamber for 2 hours by sandwich ELISA. Results : On the 2nd incubation day, there was no significant difference in the amount of HSPG between the 5 culture dishes. But on the 7th incubation day, the amount of HSPG increased by 10% compared with the B5 dish on the 2nd day except the A30 dish(P<0.05). Compared with the B5 dish on the 7th day the amount of HSPG in A30 and B30 dish decreased to 77.8% and 95.3% of baseline, respectively(P>0.05). In the osmotic control group (A/B 25) no significant correlation was observed. On the SEM, we could see the separated intercellular junction and fused microvilli of glomerular epithelial cells in the culture dishes where AGE was added. The permeability of BSA increased by 19% only in the A30 dish on the 7th day compared with B5 dish on the 7th day in the permeability assay(P<0.05). Conclusion: We observed not only the role of a high level of glucose and AGE in decreasing the production of HSPG of glomerular epithelial cells in vitro, but also their additive effect. However, the role of AGE is greater than that of glucose. These results seems to correlate with the defects in charge selective barrier. Morphological changes of the disruption of intercellular junction and fused microvilli of glomerular epithelial cells seem to correlate with the defects in size-selective barrier. Therefore, we can explain the increased permeability of glomerular epithelial units in the in vitro diabetic condition.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.