• ETRI Journal
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• v.44 no.4
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• pp.573-587
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• 2022

The agricultural sector is completely different from other sectors since it completely relies on various natural and climatic factors. Climate changes have many effects, including lack of annual rainfall and pests, heat waves, changes in sea level, and global ozone/atmospheric CO₂ fluctuation, on land and agriculture in similar ways. Climate change also affects the environment. Based on these factors, farmers chose their crops to increase productivity in their fields. Many existing agricultural ontologies are either domain-specific or have been created with minimal vocabulary and no proper evaluation framework has been implemented. A new agricultural ontology focused on subdomains is designed to assist farmers using Jaccard relative extractor (JRE) and Naïve Bayes algorithm. The JRE is used to find the similarity between two sentences and words in the agricultural documents and the relationship between two terms is identified via the Naïve Bayes algorithm. In the proposed method, the preprocessing of data is carried out through natural language processing techniques and the tags whose dimensions are reduced are subjected to rule-based formal concept analysis and mapping. The subdomain ontologies of weather, pest, and soil are built separately, and the overall agricultural ontology are built around them. The gold standard for the lexical layer is used to evaluate the proposed technique, and its performance is analyzed by comparing it with different state-of-the-art systems. Precision, recall, F-measure, Matthews correlation coefficient, receiver operating characteristic curve area, and precision-recall curve area are the performance metrics used to analyze the performance. The proposed methodology gives a precision score of 94.40% when compared with the decision tree(83.94%) and K-nearest neighbor algorithm(86.89%) for agricultural ontology construction.

• Korean Journal of Radiology
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• v.23 no.4
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• pp.402-412
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• 2022

Objective: To evaluate the image quality and lesion detectability of lower-dose CT (LDCT) of the abdomen and pelvis obtained using a deep learning image reconstruction (DLIR) algorithm compared with those of standard-dose CT (SDCT) images. Materials and Methods: This retrospective study included 123 patients (mean age ± standard deviation, 63 ± 11 years; male:female, 70:53) who underwent contrast-enhanced abdominopelvic LDCT between May and August 2020 and had prior SDCT obtained using the same CT scanner within a year. LDCT images were reconstructed with hybrid iterative reconstruction (h-IR) and DLIR at medium and high strengths (DLIR-M and DLIR-H), while SDCT images were reconstructed with h-IR. For quantitative image quality analysis, image noise, signal-to-noise ratio, and contrast-to-noise ratio were measured in the liver, muscle, and aorta. Among the three different LDCT reconstruction algorithms, the one showing the smallest difference in quantitative parameters from those of SDCT images was selected for qualitative image quality analysis and lesion detectability evaluation. For qualitative analysis, overall image quality, image noise, image sharpness, image texture, and lesion conspicuity were graded using a 5-point scale by two radiologists. Observer performance in focal liver lesion detection was evaluated by comparing the jackknife free-response receiver operating characteristic figures-of-merit (FOM). Results: LDCT (35.1% dose reduction compared with SDCT) images obtained using DLIR-M showed similar quantitative measures to those of SDCT with h-IR images. All qualitative parameters of LDCT with DLIR-M images but image texture were similar to or significantly better than those of SDCT with h-IR images. The lesion detectability on LDCT with DLIR-M images was not significantly different from that of SDCT with h-IR images (reader-averaged FOM, 0.887 vs. 0.874, respectively; p = 0.581). Conclusion: Overall image quality and detectability of focal liver lesions is preserved in contrast-enhanced abdominopelvic LDCT obtained with DLIR-M relative to those in SDCT with h-IR.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.3
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• pp.129-149
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• 2016

The purpose of this study is to examine in depth the personal experience of Instructor during National Competence Standards (NCS) Curriculum at Department of Library and Information Science. We conducted in depth interview (FGI) with participants who had recently experienced and data analysis was undertaken. We hope this study that an application of NCS would be activated fully in Library, educational institutes and qualifying examination institutes and that diverse feedbacks from related parties would makes leading to a better updated version of NCS development. As a result, First, The instructor had generally familiar with the background and purpose of the NCS. and they issued the inadequacies of job elements, non-reflection of the opinion on field education, the problems of classification of NCS. second, In the experience of NCS curriculum operating, There were the paperwork burden, Problems of methods of evaluation, evaluation period discrimination, the need to well communication with students. Third, In the problems on the NCS Curriculum operating, we found that there were The need on the proper Class size/hour, additional education, re-evaluation, Support system for NCS Curriculum operation, tools for practice, discrimination between relative evaluation and NCS evaluation, Enhancement for Competence/Standards. Fourth, On The ways of improving for NCS curriculum, We found that There were Class size, Support tools for practice, The improvement Competence/elements/standards based on LIS characteristic. The result of this study may contribute for improving the overall environment Based upon FGI analysis, several new directions for NCS education in the filed LIS curriculum are suggested.

• Korean Journal of Radiology
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• v.25 no.1
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• pp.43-54
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• 2024

Objective: To evaluate the added value of diffusion-weighted imaging (DWI)-based quantitative parameters to distinguish uterine sarcomas from atypical leiomyomas on preoperative magnetic resonance imaging (MRI). Materials and Methods: A total of 138 patients (age, 43.7 ± 10.3 years) with uterine sarcoma (n = 44) and atypical leiomyoma (n = 94) were retrospectively collected from four institutions. The cohort was randomly divided into training (84/138, 60.0%) and validation (54/138, 40.0%) sets. Two independent readers evaluated six qualitative MRI features and two DWI-based quantitative parameters for each index tumor. Multivariable logistic regression was used to identify the relevant qualitative MRI features. Diagnostic classifiers based on qualitative MRI features alone and in combination with DWI-based quantitative parameters were developed using a logistic regression algorithm. The diagnostic performance of the classifiers was evaluated using a cross-table analysis and calculation of the area under the receiver operating characteristic curve (AUC). Results: Mean apparent diffusion coefficient value of uterine sarcoma was lower than that of atypical leiomyoma (mean ± standard deviation, 0.94 ± 0.30 10^-3 mm²/s vs. 1.23 ± 0.25 10^-3 mm²/s; P < 0.001), and the relative contrast ratio was higher in the uterine sarcoma (8.16 ± 2.94 vs. 4.19 ± 2.66; P < 0.001). Selected qualitative MRI features included ill-defined margin (adjusted odds ratio [aOR], 17.9; 95% confidence interval [CI], 1.41-503, P = 0.040), intratumoral hemorrhage (aOR, 27.3; 95% CI, 3.74-596, P = 0.006), and absence of T2 dark area (aOR, 83.5; 95% CI, 12.4-1916, P < 0.001). The classifier that combined qualitative MRI features and DWI-based quantitative parameters showed significantly better performance than without DWI-based parameters in the validation set (AUC, 0.92 vs. 0.78; P < 0.001). Conclusion: The addition of DWI-based quantitative parameters to qualitative MRI features improved the diagnostic performance of the logistic regression classifier in differentiating uterine sarcomas from atypical leiomyomas on preoperative MRI.

• The Journal of the Petrological Society of Korea
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• v.10 no.3
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• pp.179-189
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• 2001

The determination of trace concentration of U, Th and Pb was carried out for chemical dating of zircon and monazite by electron microprobe. Detection limit and error range should be considered to measure characteristic X-rays of M-line from those minerals, which are low in the ionization of atom and low peak intensity in the spectrum. The element of U, Th and Pb were simultaneously measured with 3 spectrometers equipped with PET crystal to reduce a total counting time and error due to drift of instrumental operating condition. Detection limit could be improved from increase of the peak/background ratio through adjusting pulse height analyzer about 1000 mv baseline. Under permissible maximum analytical conditions, theoretical detection limit of U, Th and Pb is down to 30 ppm (99% confidence level). The analytical result was maintained at a relative error $\pm$10% ($2{\sigma}$) in 800 ppm Pb, $\pm$5% ($2{\sigma}$) in 2330 ppm U and $\pm$10% ($2{\sigma}$) in dating from a single measurement of zircon at 15 keV and 100 nA. However, for the precise dating of zircon and monazite, if it is considered a 3 $\mu\textrm{m}$ spatial resolution, <100 ppm ($3{\sigma}$) detection limit and <$\pm$10% ($2{\sigma}$) relative error, optimum analytical conditions are given as 15~20 keV accelerating voltage, 100~200 nA beam current and 300~1200 sec total counting time. To reduce material damage by high current, there is need to be up to 3~5 $\mu\textrm{m}$ of electron beam diameter, or to use arithmetic average of multiple measuring at a shorter counting time. A younger or relatively low concentration rocks can be dated chemically by lower detection limit and improved precision resulted from increase of current and measuring time.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.8
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• pp.1035-1041
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• 2013

To evaluate the structural integrity and dynamic characteristic of the knuckle part of a KTX anti-roll bar, an experimental and a numerical approach were used in this study. In the experimental approach, the acceleration and strain data for the knuckle parts of the KTX and KTX-SANCHUN anti-roll bar were respectively measured to evaluate and compare its structural dynamic characteristics under the operating environments of the Honam line. In the numerical approach, the evaluation of its structural integrity was conducted using LS-DYNA 3D, and then, the reliability of the finite element model used was ensured by a comparative evaluation with the experiment. The numerical results showed that the stress and velocity field of the knuckle part composed of a layered structure of a thin steel plate and rubber were more moderate than those of the knuckle part made of only a thick steel block owing to the reduction of relative contact between the knuckle and the connecting rod. It was found that the knuckle part made of a thin steel plate and rubber was recommended as the best solution to improve its structural integrity resulting from the elastic behavior of the KTX anti-roll bar being enabled under a repeating external force.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7575-7581
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• 2014

MicroRNAs (miRNAs) play an essential role in the development and progression of nasopharyngeal carcinomas (NPC). Despite advances in the field of cancer molecular biology and biomarker discovery, the development of clinically validated biomarkers for primary NPC has remained elusive. In this study, we investigated the expression and clinical significance of miRNAs as novel primary NPC diagnostic biomarkers. We used an array containing 2, 500 miRNAs to identify 22 significant miRNAs, and these candidate miRNAs were validated using 67 fresh NPC and 25 normal control tissues via quantitative real-time PCR (qRT-PCR). Expression and correlation analyses were performed with various statistical approaches, in addition to logistic regression and receiver operating characteristic curve analyses to evaluate diagnostic efficacy. qRT-PCR revealed five differentially expressed miRNAs (miR-93-5p, miR-135b-5p, miR-205-5p and miR-183-5p) in NPC tissue samples relative to control samples (p<0.05), with miR-135b-5p and miR-205-5p being of significant diagnostic value (p<0.01). Moreover, comparison of NPC patient clinicopathologic data revealed a negative correlation between miR-93-5p and miR-183-5p expression levels and lymph node status (p<0.05). These findings display an altered expression of many miRNAs in NPC tissues, thus providing information pertinent to pathophysiological and diagnostic research. Ultimately, miR-135b-5p and miR-205-5p may be implicated as novel NPC candidate biomarkers, while miR-93-5p, miR-650 and miR-183-5p may find application as relevant clinical pathology and diagnostic candidate biomarkers.

• The Korean Journal of Financial Management
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• v.25 no.3
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• pp.1-32
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• 2008

This study examines the changes and determinants of cash to assets ratios(cash ratios) by analyzing 14,016 Korean manufacturing firms sample for the period of $1999{\sim}2004$. The major findings can be summarized as follows. First, the average cash ratios for Korean manufacturing firms have increased from 4.7 percent of 1999 to 5.2 percent of 2004. In addition, the average cash holdings per firm also have increased from 4.3 billion Won to 8.0 billion Won during the same period. However, the capital expenditures relative to cash ratios or operating cash flow have decreased significantly, confirming the notion that physical investment of Korean manufacturing sector has been shrinking recently. Second, in regression tests with panel data, the coefficients of target adjustment variables show the expected negative signs, but coefficients of the deficit of fund variables show the unexpected positive signs. Thus, the evidence seems to be supportive of static tradeoff model of cash holdings. Third, in regression tests to find the determinants of cash ratios, most of the variables show similar results as the previous studies. However, in terms of adjusted coefficient of determination and F-statistic, the firm-characteristic variables suggested by static trade-off theory have more explanatory power than the variables suggested by pecking order theory.

• Ecology and Resilient Infrastructure
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• v.2 no.3
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• pp.198-205
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• 2015

Impacts of climate change on aquatic ecosystems range from changes in physiological processes of aquatic organisms to species distribution. In this study, MaxEnt that has high prediction power without nonoccurrence data was used to simulate fish distribution changes in the Geum river watershed according to climate change. The fish distribution in 2050 and 2100 was predicted with RCP 8.5 climate change scenario using fish occurrence data (a total of 47 species, including 17 endemic species) from 2007 to 2009 at 134 survey points and 9 environmental variables (monthly lowest, highest and average air temperature, monthly precipitation, monthly lowest, highest and average water temperature, altitude and slope). The fitness of MaxEnt modeling was successful with the area under the relative operating characteristic curve (AUC) of 0.798, and environmental variables that showed a high level of prediction were as follows: altitude, monthly average precipitation and monthly lowest water temperature. As climate change proceeds until 2100, the probability of occurrence for Odontobutis interrupta and Acheilognathus yamatsuatea (endemic species) decreases whereas the probability of occurrence for Microphysogobio yaluensis and Lepomis macrochirus (exotic species) increases. In particular, five fish species (Gnathopogon strigatus, Misgurnus mizolepis, Erythroculter erythropterus, A. yamatsuatea and A. koreensis) were expected to become extinct in the Geum river watershed in 2100. In addition, the species rich area was expected to move to the northern part of the Geum river watershed. These findings suggest that water temperature increase caused by climate change may disturb the aquatic ecosystem of Geum river watershed significantly.

• Journal of Gastric Cancer
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• v.21 no.3
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• pp.268-278
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• 2021

Purpose: While several prognostic models for the stratification of death risk have been developed for patients with advanced gastric cancer receiving first-line chemotherapy, they have seldom been tested in the Chinese population. This study investigated the performance of these models and identified the optimal tools for Chinese patients. Materials and Methods: Patients diagnosed with metastatic or recurrent gastric adenocarcinoma who received first-line chemotherapy were eligible for inclusion in the validation cohort. Their clinical data and survival outcomes were retrieved and documented. Time-dependent receiver operating characteristic (ROC) and calibration curves were used to evaluate the predictive ability of the models. Kaplan-Meier curves were plotted for patients in different risk groups divided by 7 published stratification tools. Log-rank tests with pairwise comparisons were used to compare survival differences. Results: The analysis included a total of 346 patients with metastatic or recurrent disease. The median overall survival time was 11.9 months. The patients were different into different risk groups according to the prognostic stratification models, which showed variability in distinguishing mortality risk in these patients. The model proposed by Kim et al. showed relative higher predicting abilities compared to the other models, with the highest χ² (25.8) value in log-rank tests across subgroups, and areas under the curve values at 6, 12, and 24 months of 0.65 (95% confidence interval [CI]: 0.59-0.72), 0.60 (0.54-0.65), and 0.63 (0.56-0.69), respectively. Conclusions: Among existing prognostic tools, the models constructed by Kim et al., which incorporated performance status score, neutrophil-to-lymphocyte ratio, alkaline phosphatase, albumin, and tumor differentiation, were more effective in stratifying Chinese patients with gastric cancer receiving first-line chemotherapy.