• Journal of Nutrition and Health
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• v.47 no.6
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• pp.394-402
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• 2014

Purpose: Dendropanax morifera Leveille (DML) exhibits diverse biological and pharmacological activities, including anti-oxidative effect, anti-cancer activity, hepatoprotection, immunological stimulation, and bone regeneration. As part of the identification for novel functions of DML, we investigated the therapeutic effects of DML on diabetes induced by streptozotocine (STZ) treatment. Methods: First, the four extracts including the water extract of leaf (DLW), the ethanol extract of leaf (DLE), the water extract of stem (DSW), and the ethanol extract of stem (DSE) were collected from the leaf and stem of DML using a hot water and ethanol solvent. Alterations in body weight, glucose concentration, insulin level, and pancreatic islet structure were investigated in diabetic mice after treatment with extracts of DML for 2 weeks. Results: Among four extracts, the highest level of total polyphenols and total flavonoids was detected in DLW, while the lowest level of these was measured in DSE. The radical scavenging activity was also higher in DLW than in the other three extracts at the concentration of $25-100{\mu}g/mL$, although this activity was maintained at a constant level in all groups at the concentration of $500{\mu}g/mL$. Based on the results of anti-oxidant activity, DLW and DLE were selected for examination of anti-diabetic effects in a diabetes model. Body weight was gradually decreased in all STZ treated groups compared with the No treated group. However, four STZ/DML treated groups maintained a high level of body weight during 7-14 days, while the STZ/vehicle treated group showed a gradual decrease of body weight during the same period. Also, a significant decrease or increase in the concentration of glucose and insulin in the blood of the diabetes model was detected in a subset of groups, although the highest increase was detected in the STZ/DLE-200 treated group. In addition, the histological structure of pancreatic islet was significantly recovered after treatment with DLW and DLE. Conclusion: These results suggest that DLW and DLE may contribute to attenuation of clinical symptoms of diabetes as well as prevent the destruction of pancreatic ${\beta}$-cells in STZ-induced diabetes mice.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.351-363
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• 2020

It is well known that alluvial sediment located in coastal region has been easily affected by geohazard like ground subsidence, marine or meteorological disasters which threaten invaluable lives and properties. The subsidence is a sinking of the ground due to underground material movement that mostly related to soil compaction by water extraction. Thus, continuous monitoring is essential to protect possible damage from the ground subsidence in the coastal region. Radar interferometric application has been widely used to estimate surface displacement from phase information of synthetic aperture radar (SAR). Thanks to advanced SAR technique like the Small BAseline Subset (SBAS), a time-series of surface displacement could be successfully calculated with a large amount of SAR observations (>20). Because the ALOS-2 PALSAR-2 L-band observations maintain higher coherence compared with other shorter wavelength like X- or C-band, it has been regarded as one of the best resources for Earth science. However, the number of ALOS-2 PALSAR-2 observations might be not enough for the SBAS application due to its global monitoring observation scenario. Unfortunately, the number of the ALOS-2 PALSAR-2 Stripmap images in area of our interest, Busan which located in the Southeastern Korea, is only 11 which is insufficient to apply the SBAS time-series analysis. Although it is common that the radar interferometry utilizes multiple SAR images collected from same acquisition mode, it has been reported that the ALOS-2 PALSAR-2 Stripmap-ScanSAR interferometric application could be possible under specific acquisition mode. In case that we can apply the Stripmap-ScanSAR interferometry with the other 18 ScanSAR observations over Busan, an enhanced time-series surface displacement with better temporal resolution could be estimated. In this study, we evaluated feasibility of the ALOS-2 PALSAR-2 Stripmap-ScanSAR interferometric application using Gamma software considering differences of chirp bandwidth and pulse repetition frequency (PRF) between two acquisition modes. In addition, we analyzed the interferograms with respect to spectral shift of radar carrier frequency and common band filtering. Even though it shows similar level of coherence regardless of spectral shift in the radar carrier frequency, we found periodic spectral noises in azimuth direction and significant degradation of coherence in azimuth direction after common band filtering. Therefore, the characteristics of spectral bandwidth in the range and azimuth direction should be considered cautiously for the ALOS-2 PALSAR-2 Stripmap-ScanSAR interferometry.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.11
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• pp.4589-4594
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• 2014

The mammalian target of rapamycin (mTOR) signaling pathway is upregulated in the pathogenesis of many cancers, including colorectal cancer (CRC). DEPTOR is an mTOR inhibitor whose expression is negatively regulated by mTOR. However, the role of DEPTOR in the development of CRC is not known. The aim of this study was to investigate the expression of DEPTOR and mTORC1 activity (P-S6) in a subset of CRC patients and determine their relation to tumor differentiation, invasion, nodal metastasis and disease-free survival. Here, Immunohistochemical expression of P-S6 (S235/236) and DEPTOR were evaluated in 1.5 mm tumor cores from 90 CRC patients and in 90 samples of adjacent normal mucosa by tissue microarray. The expression of P-S6 (S235/236) was upregulated in CRC, with the positive rate of P-S6 (S235/236) in CRC (63.3%) significantly higher than that in control tissues (36.7%, 30%) (p<0.05). P-S6 (S235/236) also correlated with high tumor histologic grade (p=0.002), and positive nodal metastasis (p=0.002). In contrast, the expression level of DEPTOR was correlated with low tumor histological grade (p=0.006), and negative nodal metastasis (p=0.001). Interestingly, P-S6 (S235/236) expression showed a significant negative association with the expression of DEPTOR in CRC (p=0.011, R= -0.279). However, upregulation of P-S6 (S235/236) (p=0.693) and downregulation of DEPTOR (p=0.331) in CRC were not significantly associated with overall survival. Thus, we conclude that expression of DEPTOR negatively correlates with mTORC1 activity and tumor progression in CRC. DEPTOR is a potential marker for prognostic evaluation and a target for the treatment of CRC.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.141-149
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• 2008

Recently we frequently analyze multivariate data with quite large number of variables. In such data sets, virtually duplicated variables may exist simultaneously even though they are conceptually distinguishable. Duplicate variables may cause problems such as the distortion of principal axes in principal component analysis and factor analysis and the distortion of the distances between observations, i.e. the input for cluster analysis. Also in supervised learning or regression analysis, duplicated explanatory variables often cause the instability of fitted models. Since real data analyses are aimed often at multiple purposes, it is necessary to reduce the number of variables to a parsimonious level. The aim of this paper is to propose a practical algorithm for selection of a subset of variables from a given set of p input variables, by the criterion of minimum trace of partial variances of unselected variables unexplained by selected variables. The usefulness of proposed method is demonstrated in visualizing the relationship between selected and unselected variables, in building a predictive model with very large number of independent variables, and in reducing the number of variables and purging/merging categories in categorical data.

• Journal of Preventive Medicine and Public Health
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• v.28 no.3 s.51
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• pp.623-639
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• 1995

We have never seen any method to cope basically with complicated situation and problems around medical reimbursement rates here in Korea since 1977 witnessed by the beginning of medical insurance. By the way researchers concerned are beginning to propose some kinds of innovative and detailed ideas to government these days. They are Diagnosis-related group(DRG) and Resource-based .elative value scale(RBRVS). In the light of this situation it is so encouraging that our government can come up with that and move. In case of RBRVS research we have already been reaching even to the level of reviewing and revising methodology for its further development after naive pilot study on internal medicine and general surgery last year. However there might be something different conditions between USA and Korea to apply the same Dr. Hsiao's method and it must be vital to check so called' total work approach' compared with 'intra-service work approach' before expanding to the whole medical fields. According to the' Intra-service approach', the physician's work is supposed to be divided into three sub-works by the name of intraservice work, pre, and post service work. These sub-works, again should be merged together to be the pre-postwork subset through some statistical methods of the estimation process applied by Dr. Hsiao's methodology in RBRVS development later on. But in this paper that estimation process was not taken because we could have real values for all of those surveyed items related to just one specialty, OB & GY. Instead, We used some statistical comparison procedures relevant to demographic characteristics, reliability & validity and correlation analysis with American RVU(Relative value unit) between the total work and merged total work from intraservice work approach. The unit of analysis was individual physicians of OB & GY and 300 physicians were selected for each approach through statistical sampling method based on national population of OB & GY physicians in Korea. And also with the thankful help of Advisory Committee under Korean Association of OB & GY, questionnaires were made and mailed to the subjects, two times. As a result there were not any statistically significant differences in demographic characteristics between the two approaches except for the variable 'Response time for the questionnaires', but in other sections of comparisons, response rate, representative values, reliability & validity test, correlation analysis with American RVU, all showed 'Total approach' was not only more rational and statistically meaningful than 'Intra-service approach' but also had considerable merits. But we are not absolutely sure about this paper's robustness. Because of some limitations, we'd rather like to suggest further researches should be followed. In that sense the first thing would be a research for the influence of doctor's characteristics, especially 'frequency' on the rating of work and the way to define total work more clearly.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.53-61
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• 2008

Public Key Broadcast Encryption (PKBE) allows a sender to distribute a message to a changing set of users over an insecure channel. PKBE schemes should be able to dynamically exclude (i.e., revoke) a certain subset of users from decrypting a ciphertext, so that only remaining users can decrypt the ciphertext. Another important requirement is for the scheme to be forward-secrecy. A forward-secure PKBE (fs-PKBE) enables each user to update his private key periodically. This updated private key prevents an adversary from obtain the private key for certain past period, which property is particularly needed for pay-TV systems. In this paper, we present a fs-PKBE scheme where both ciphertexts and private keys are of $O(\sqrt{n})$ size. Our PKBE construction is based on Boneh-Boyen-Goh's hierarchical identity-based encryption scheme. To provide the forward-secrecy with our PKBE scheme, we again use the delegation mechanism for lower level identities, introduced in the BBG scheme. We prove chosen ciphertext security of the proposed scheme under the Bilinear Diffie-Hellman Exponent assumption without random oracles.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.35-45
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• 2022

Even in recent years, treatment of first-aid patients is still often delayed due to a shortage of medical resources in marginalized areas. Research on automating the analysis of medical data to solve the problems of inaccessibility for medical services and shortage of medical personnel is ongoing. Computer vision-based medical inspection automation requires a lot of cost in data collection and labeling for training purposes. These problems stand out in the works of classifying lesion that are rare, or pathological features and pathogenesis that are difficult to clearly define visually. Anomaly detection is attracting as a method that can significantly reduce the cost of data collection by adopting an unsupervised learning strategy. In this paper, we propose methods for detecting abnormal images on chest X-RAY images as follows based on existing anomaly detection techniques. (1) Normalize the brightness range of medical images resampled as optimal resolution. (2) Some feature vectors with high representative power are selected in set of patch features extracted as intermediate-level from lesion-free images. (3) Measure the difference from the feature vectors of lesion-free data selected based on the nearest neighbor search algorithm. The proposed system can simultaneously perform anomaly classification and localization for each image. In this paper, the anomaly detection performance of the proposed system for chest X-RAY images of PA projection is measured and presented by detailed conditions. We demonstrate effect of anomaly detection for medical images by showing 0.705 classification AUROC for random subset extracted from the PadChest dataset. The proposed system can be usefully used to improve the clinical diagnosis workflow of medical institutions, and can effectively support early diagnosis in medically poor area.

• Parasites, Hosts and Diseases
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• v.31 no.3
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• pp.249-258
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• 1993

Naegleria fowleri is the cause of primary amoebic meningoencephalitis in man, IL-2 levels after stimulation of T lymphocytes by PHA or N.fowleri lysates. the amounts of T lymphocyte subsets and the blastogenic responses of T lymphocytes in mice after Infected with pathogenic N. fowleri were studied comparing between two study groups, one $1{\;}{\times}{\;}10^4$ trophozoites inoculated mice and the other $1{\;}{\times}{\;}10^5$ trophozoites inoculated mice. All experimental samples were obtained on the day 7, 14 and 24 after inoculation. The mice inoculated with $1{\;}{\times}{\;}10^4$ trophozoites showed a 14.3% mortality rate, and 72.2% in the mice inoculated with $1{\;}{\times}{\;}10^5$ trophozoites. The IL-2 levels on day 14 of two experimental groups were significantly decreased as compared with the control group. Thy 1.2+T cells in the total spleen Iymphocytes of $1{\;}{\times}{\;}10^5$ trophozoites inoculated group on day 7 were significantly increased compared with the control group. There was no significant difference between $1{\;}{\times}{\;}10^4$ trophozoites inoculated group and the control group. $L3T4^{+}{\;}T$ cells and $Ly2^{+}$ T cells in the total spleen Iymphocytes of $1{\;}{\times}{\;}10^5$ trophozoites inoculated group on day 7 were sigrlificantly increased compared with the control group. The DNA S fraction of T cells in the spleen of $1{\;}{\times}{\;}10^5$ trophozoites inoculated group was significantly increased on day 7. The amount of S fractions of DNA were sequentially decreased on day 14 and 24 but they were also signiacantly increased compared with the control group. The results obtained in the experiments indicats that cell mediated immunity after N.fowleri infection acts on very important host's protection immunity around the 7th day after infection. IL-2 level was much suppressed on day 14 which resulted from the exhaustion of host immune response. It was observed that the level of IL-2 production ability and the amounts of T lymphocytes subsets and the blastogenic responses of T lymphocytes were not well correlated during the observation period.

• Knowledge Management Research
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• v.17 no.2
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• pp.131-163
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• 2016

The purpose of this study is to empirically analyze how social comparative learning of forum participants affects learning effects with an emphasis on participants' characteristics. As today's society is changing at a fast pace, the desire for new knowledge and information has grown accordingly. To quench this thirst for knowledge and information, seminars, symposiums, conferences, forums, conventions, exhibitions, and more are taking place as part of knowledge sharing events across the world. Also, the increased need for knowledge and information exchange has led the development and growth of the convention industry and Meetings, Incentives, Conferences, and Events (Exhibitions)(MICE) industry. Especially, forum is a type of event which invites professionals and specialists to discuss diverse topics and share their knowledge and experience with the audience. The participants utilize it as an opportunity to get close to information providers and enjoy the pleasure of knowledge exchange. However, there have been few empirical analyses on who the participants are, why they attend forum, how they pick up and learn new information and knowledge, and what kinds of learning effects they achieve after the event. This paper is to analyze how social comparative learning of the forum's participants influences learning effects based on Albert Bandura's Social Learning Theory (1977, 1997, 1982. 2001) and Leon Festinger's Social Comparative Theory (1950, 1954). By dividing the participants into two groups, one with high level of self-efficacy and the other with low level of self-efficacy, we have examined the differences in learning effects between the two groups using them as moderating variables. This study was conducted in 'MBN Y Forum 2016,' which is one of the most representative knowledge exchange forums of South Korea. An online survey was distributed out and, 1,307(39.2%) out of the total participants of 3,338 have completed the survey. The survey included questions about whether the participants have gained positive or negative motivations by comparing themselves to the speakers (upward comparison learning) and other participants (lateral comparison learning). The results have shown the quality of messages that the speakers are presenting as knowledge providers is the most significant factor that acts on learning effects. Particularly, the participants had higher levels of self-efficacy and self-esteem than average people. They had a clear goal to learn from the speakers (upward comparison) and received positive motivations from them. In other words, no negative learning effects had been found. This presents a managerial implication that having a qualified speaker is necessary for a forum to be successful. On the other hand, the results from the comparison with the other participants (lateral comparison) were different. The participants were likely to compare themselves to the other participants through observational learning. They could compare listening attitudes, language skills, or capabilities to ask a question. The results have showed the participants received positive motivations from the lateral group but at the same time were jealous of abilities of the others. When the quality of a question by a participant is not good enough, it can have a negative influence on the participants' learning effects. The first group with high levels of self-efficacy and self-esteem had no correlation to negative learning effects from the speakers. They rather had a strong desire to learn from the speakers. On the contrary, the participants perceived the lateral group as a learning subset and competitor. The second group with low levels of self-efficacy and self-esteem saw the quasi-group as a rival. This presents that the individual learning effects can be different depending on the participants' characteristics.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.321-335
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• 2021

Particulate matter (PM10 and PM2.5 with a diameter less than 10 and 2.5 ㎛, respectively) can be absorbed by the human body and adversely affect human health. Although most of the PM monitoring are based on ground-based observations, they are limited to point-based measurement sites, which leads to uncertainty in PM estimation for regions without observation sites. It is possible to overcome their spatial limitation by using satellite data. In this study, we developed machine learning-based retrieval algorithm for ground-level PM10 and PM2.5 concentrations using aerosol parameters from Geostationary Ocean Color Imager (GOCI) satellite and various meteorological parameters from a numerical weather prediction model during January to December of 2019. Gradient Boosted Regression Trees (GBRT) and Light Gradient Boosting Machine (LightGBM) were used to estimate PM concentrations. The model performances were examined for two types of feature sets-all input parameters (Feature set 1) and a subset of input parameters without meteorological and land-cover parameters (Feature set 2). Both models showed higher accuracy (about 10 % higher in R2) by using the Feature set 1 than the Feature set 2. The GBRT model using Feature set 1 was chosen as the final model for further analysis(PM10: R2 = 0.82, nRMSE = 34.9 %, PM2.5: R2 = 0.75, nRMSE = 35.6 %). The spatial distribution of the seasonal and annual-averaged PM concentrations was similar with in-situ observations, except for the northeastern part of China with bright surface reflectance. Their spatial distribution and seasonal changes were well matched with in-situ measurements.