• Journal of the Korean Geotechnical Society
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• v.22 no.2
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• pp.55-68
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• 2006

For the reliable prediction of spatial geotechnical data, a procedure to build the Geotechnical Information System (GTIS) based on geo-knowledge within the frame of GIS technology was developed by introducing a couple of new concepts of the extended area containing the study area and the additional site visit for acquiring surface geological data. To build the GTIS for Gyeongju as the case study of regional model application, intensive site investigations and pre-existing geotechnical data collections were performed and additional site visit was also carried out for acquiring surface geo-layer data in accordance with the developed procedure. Within the GTIS based on geo-knowledge for Gyeongiu area, the spatially distributed geo-layers across the extended area were predicted using the geostatistical kriging method and those for the study area were extracted. Furthermore, the spatial distribution maps for the thickess of geo-layers and the depth to bedrock were constructed for the practical use in geotechnical field. It was evaluated that the GTIS based on geo-knowledge developed in this study is superior to the conventional geotechnical GIS in terms of both the standard deviation and the geological expert judgment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.549-559
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• 2023

As mobile edge computing (MEC) is gaining attention as a core technology of 5G networks, edge AI technology of 5G network environment based on mobile user data is recently being used in various fields. However, as in traditional AI security, there is a possibility of adversarial interference of standard 5G network functions within the core network responsible for edge AI core functions. In addition, research on data poisoning attacks that can occur in the MEC environment of standalone mode defined in 5G standards by 3GPP is currently insufficient compared to existing LTE networks. In this study, we explore the threat model for the MEC environment using NWDAF, a network function that is responsible for the core function of edge AI in 5G, and propose a feature selection method to improve the performance of detecting data poisoning attacks for Leaf NWDAF as some proof of concept. Through the proposed methodology, we achieved a maximum detection rate of 94.9% for Slowloris attack-based data poisoning attacks in NWDAF.

• Journal of the Korean Wood Science and Technology
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• v.51 no.6
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• pp.555-568
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• 2023

The diffusion strategies of wood culture were established using the analytic hierarchy process, to prepare a diffusion plan of wood culture and wood utilization in response to climate change due to global warming. 'Standardization of wood culture', 'Valuation of wood culture', and 'Habituation of wood culture' were set as three major implementation strategies and priorities were evaluated. As a result, it was analyzed in the following order: 'Development of systematic education programs for each age group for rational and efficient use of eco-friendly wood materials and development of wood education standard guidelines linked to the curriculum', 'Preparation of scientific basis data on human compatibility and eco-friendliness of wood to ensure the reliability of wood and wood products', and 'Establishment of monitoring and improvement plan through the designation as a model school'. Through this, it was determined that an educational environment, changes in public attitudes through publicity, and expanding opportunities to use wood and wood products were necessary for wood culture diffusion. The results of this study can be used as basic data to derive the diffusion strategies of wood culture and establish a roadmap and policy implementation strategy to revitalize wood culture.

• Journal of Animal Science and Technology
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• v.65 no.5
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• pp.1024-1039
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• 2023

In this study, we performed a quantitative microbial risk assessment (QMRA) of Salmonella through intake of egg consumption after cooking (dry-heat, moist-heat, and raw consumption). Egg samples (n = 201) from retail markets were analyzed for the presence of Salmonella. In addition, temperature and time were investigated during egg transit, storage, and display. A predictive model was developed to characterize the kinetic behavior of Salmonella in eggs, and data on egg consumption and frequency were collected. Eventually, the data was simulated to estimate egg-related foodborne illnesses. Salmonella was not found in any of the 201 egg samples. Thus, the estimated initial contamination level was -4.0 Log CFU/g. With R² values of 0.898 and 0.922, the constructed predictive models were adequate for describing the fate of Salmonella in eggs throughout distribution and storage. Eggs were consumed raw (1.5%, 39.2 g), dry-heated (57.5%, 43.0 g), and moist-heated (41%, 36.1 g). The probability of foodborne Salmonella illness from the consumption of cooked eggs was evaluated to be 6.8×10^-10. Additionally, the probability of foodborne illness not applied cooking methods was 1.9×10^-7, indicating that Salmonella can be reduced by cooking. Therefore, the risk of Salmonella infection through consumption of eggs after cooking might be low in S. Korea.

• Journal of Microbiology and Biotechnology
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• v.33 no.12
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• pp.1657-1670
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• 2023

This study aimed to evaluate the effects of Limosilactobacillus fermentum and Lactiplantibacillus plantarum isolated from human feces coordinating with inulin on the composition of gut microbiota and metabolic profiles in db/db mice. These supplements were administered to db/db mice for 12 weeks. The results showed that the Lactobacillaceae coordinating with inulin group (LI) exhibited lower fasting blood glucose levels than the model control group (MC). Additionally, LI was found to enhance colon tissue and increase the levels of short-chain fatty acids. 16S rRNA sequencing revealed that the abundance of Corynebacterium and Proteus, which were significantly increased in the MC group compared with NC group, were significantly decreased by the treatment of LI that also restored the key genera of the Lachnospiraceae_NK4A136_group, Lachnoclostridium, Ruminococcus_gnavus_group, Desulfovibrio, and Lachnospiraceae_UCG-006. Untargeted metabolomics analysis showed that lotaustralin, 5-hydroxyindoleacetic acid, and 13(S)-HpODE were increased while L-phenylalanine and L-tryptophan were decreased in the MC group compared with the NC group. However, the intervention of LI reversed the levels of these metabolites in the intestine. Correlation analysis revealed that Lachnoclostridium and Ruminococcus_gnavus_group were negatively correlated with 5-hydroxyindoleacetic acid and 13(S)-HpODE, but positively correlated with L-tryptophan. 13(S)-HpODE was involved in the "linoleic acid metabolism". L-tryptophan and 5-hydroxyindoleacetic acid were involved in "tryptophan metabolism" and "serotonergic synapse". These findings suggest that LI may alleviate type 2 diabetes symptoms by modulating the abundance of Ruminococcus_gnavus_group and Lachnoclostridium to regulate the pathways of "linoleic acid metabolism", "serotonergic synapse", and" tryptophan metabolism". Our results provide new insights into prevention and treatment of type 2 diabetes.

• Korean Journal of Environmental Agriculture
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• v.24 no.4
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• pp.350-357
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• 2005

This study was conducted to investigate the downward mobility of pesticides using soil columns and to compare the experimental results with values predicted from Convective mobility test model. Nine pesticides such as metolcarb, molinate, fanobucarb, isazofos, diazinon, fenitrothion, dimepiperate, parathion and chlorpyrifos-methyl were used for leaching test in soil column for four soils; Jungdong (upland soil), Gangseo (paddy soil), Yesan (forest soil), and Sineom(upland, volcanic ash-derived soil) series. The peak concentrations leached from 10 cm-columns of three soils except Sineom series ranged 6.5 to 12.6 mg/L for metolcarb, 2.6 to 5.0 mg/L for molinate, 4.5 to 7.8 mg/L for fenobucarb, 0.39 to 1.36 mg/L for dimepiperate, 1.1 to 4.6 mg/L for isazofos, 0.01 to 0.14 mg/L for diazinon, lower than 0.01 to 0.70 mg/L for fenitrothion and lower than 0.01 to 0.44 mg/L for parathion. But chlorpyrifos-methyl was not leached from any soil columns. Elution volumes to reach the peak of metolcarb, molinate, fenobucarb, isazofos, diazinon, and dimepiperate in the leachate ranged 1.1 to 2.1 pore volume (PV), 1.6 to 3.3 PV, 1.6 to 3.3 PV, 2.1 to 4.4 PV, 6 to 15 PV, and 8 to 21 PV, respectively. On the same water flux conditions, convection times estimated by Convective mobility test model were coincided with results from soil column test in most of the soil-pesticide combinations applied. Based on convection times estimated by the model at standard conditions (water flux 1 cm/day), metolcarb was classified as most mobile, molinate, fenobucarb and isazofos as mobile or most mobile, dimepiperate as moderately mobile or mobile, diazinon as mobile, fenitrothion and parathion as slightly mobile or mobile and chlorpyrifos-methyl as immobile or slightly mobile.

• The Korean Journal of Pesticide Science
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• v.6 no.4
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• pp.300-308
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• 2002

This study was conducted to investigate the downward mobility of pesticides using soil colunms and to compare the experimental results with predicted values from Convective mobility test model. Five pesticides including ethoprophos, procymidone, iprobenfos, isoprothiolane, and butachlor were subjected to soil column leaching test for three types of cultivation soils. The concentrations of ethoprophos, iprobenfos, procymidone, isoprothiolane and butachlor leached from soil column of 30 cm depth ranged $0.74{\sim}3.61mg/mL,\;0.36{\sim}1.67mg/L,\;0.16{\sim}0.84mg/L,\;0.16{\sim}0.67mg/L$ and lower than 0.15 mg/L, respectively. Elution volume to reach the peak of ethoprophos, iprobenfos, procymidone, isoprothiolane and butachlor in the leachate ranged $2{\sim}4PV,\;3{\sim}10PV,\;5{\sim}13PV,\;4{\sim}14PV\;and\;19{\sim}61PV$, respectively. Convection times predicted by Convective mobility test model at standard conditions were $9{\sim}18$ days for ethoprophos, $17{\sim}35$ days for iprobenfos, $24{\sim}54$ days for isoprothiolane, $21{\sim}65$ days for procymidone and $105{\sim}279$ days for butachlor. Based on these convection times, ethoprophos was classified as mobile or most mobile, isoprothiolane and procymidone as moderately mobile or mobile and butachlor as slightly mobile. On the same conditions, convection times from the model were coincided with those from soil column test in most of the soil-pesticide combinations applied. Therefore, Convective mobility test model could be applied to predict convection times of pesticides.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.169-177
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• 2020

In South Korea, the results of R&D in science and technology are submitted to the National Science and Technology Information Service (NTIS) in reports that have Korea national science and technology standard classification codes (K-NSCC). However, considering there are more than 2000 sub-categories, it is non-trivial to choose correct classification codes without a clear understanding of the K-NSCC. In addition, there are few cases of automatic document classification research based on the K-NSCC, and there are no training data in the public domain. To the best of our knowledge, this study is the first attempt to build a highly performing K-NSCC classification system based on NTIS report meta-information from the last five years (2013-2017). To this end, about 210 mid-level categories were selected, and we conducted preprocessing considering the characteristics of research report metadata. More specifically, we propose a convolutional neural network (CNN) technique using only task names and keywords, which are the most influential fields. The proposed model is compared with several machine learning methods (e.g., the linear support vector classifier, CNN, gated recurrent unit, etc.) that show good performance in text classification, and that have a performance advantage of 1% to 7% based on a top-three F1 score.

• Korean Journal of Radiology
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• v.21 no.5
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• pp.588-597
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• 2020

Objective: To investigate the value of combined chemical exchange saturation transfer (CEST) and conventional magnetization transfer imaging (MT) in detecting metabolic and structural changes of renal fibrosis in rats with unilateral ureteral obstruction (UUO) at 3T MRI. Materials and Methods: Thirty-five Sprague-Dawley rats underwent UUO surgery (n = 25) or sham surgery (n = 10). The obstructed and contralateral kidneys were evaluated on days 1, 3, 5, and 7 after surgery. After CEST and MT examinations, ¹⁸F-labeled fluoro-2-deoxyglucose positron emission tomography was performed to quantify glucose metabolism. Fibrosis was measured by histology and western blots. Correlations were compared between asymmetrical magnetization transfer ratio at 1.2 ppm (MTR_asym(1.2ppm)) derived from CEST and maximum standard uptake value (SUV_max) and between magnetization transfer ratio (MTR) derived from MT and alpha-smooth muscle actin (α-SMA). Results: On days 3 and 7, MTR_asym(1.2ppm) and MTR of UUO renal cortex and medulla were significantly different from those of contralateral kidneys (p < 0.05). On day 7, MTR_asym(1.2ppm) and MTR of UUO renal cortex and medulla were significantly different from those of sham-operated kidneys (p < 0.05). The MTR_asym(1.2ppm) of UUO renal medulla was fairly negatively correlated with SUV_max (r = -0.350, p = 0.021), whereas MTR of UUO renal medulla was strongly negatively correlated with α-SMA (r = -0.744, p < 0.001). Conclusion: CEST and MT could provide metabolic and structural information for comprehensive assessment of renal fibrosis in UUO rats in 3T MRI and may aid in clinical monitoring of renal fibrosis in patients with chronic kidney disease.