• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.3
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• pp.244-250
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• 2007

Membrane inlet mass spectrometer (MIMS) has been used to accurately quantify dissolved gases in liquid samples. In this study, the MIMS system was applied to measure dissolved methane in seawater and sediment porewater. To evaluate the accuracy of the measurement, liquid samples saturated with different methane partial pressure were prepared and the methane concentrations were quantified with the MIMS system. The measured values correspond well with the expected values calculated from solubility constants. The standard error of the measurements were $0.13{\sim}0.9%$ of the mean values. The distribution of dissolved methane concentration in seawater of the South Sea of Korea revealed that the physical parameters primarily control the methane concentration in sea water. The MIMS system was effective to resolve the small dissolved methane difference among water masses. The probe type inlet in MIMS system was proven to be effective to measure porewater methane concentration.

• The Journal of the Acoustical Society of Korea
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• v.25 no.5
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• pp.213-221
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• 2006

Phone segmentation of speech waveform is especially important for concatenative text to speech synthesis which uses segmented corpora for the construction of synthetic units. because the quality of synthesized speech depends critically on the accuracy of the segmentation. In the beginning. the phone segmentation was manually performed. but it brings the huge effort and the large time delay. HMM-based approaches adopted from automatic speech recognition are most widely used for automatic segmentation in speech synthesis, providing a consistent and accurate phone labeling scheme. Even the HMM-based approach has been successful, it may locate a phone boundary at a different position than expected. In this paper. we categorized adjacent phoneme pairs and analyzed the mismatches between hand-labeled transcriptions and HMM-based labels. Then we described the dominant error patterns that must be improved for the speech synthesis. For the experiment. hand labeled standard Korean speech DB from ETRI was used as a reference DB. Time difference larger than 20ms between hand-labeled phoneme boundary and auto-aligned boundary is treated as an automatic segmentation error. Our experimental results from female speaker revealed that plosive-vowel, affricate-vowel and vowel-liquid pairs showed high accuracies, 99%, 99.5% and 99% respectively. But stop-nasal, stop-liquid and nasal-liquid pairs showed very low accuracies, 45%, 50% and 55%. And these from male speaker revealed similar tendency.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.203-217
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• 2024

The Land Use, Land-Use Change and Forestry (LULUCF) sector of the National Greenhouse Gas Inventory is crucial for obtaining data on carbon sinks, necessitating accurate estimations. This study analyzes cases of countries applying the LULUCF sector at the Tier 3 level to propose enhanced methodologies for carbon sink estimation. In nations like Japan and Western Europe, satellite spatial information such as SPOT, Landsat, and Light Detection and Ranging (LiDAR)is used alongside national statistical data to estimate LULUCF. However, in Korea, the lack of land use change data and the absence of integrated management by category, measurement is predominantly conducted at the Tier 1 level, except for certain forest areas. In this study, Space-borne LiDAR Global Ecosystem Dynamics Investigation (GEDI) was used to calculate forest canopy heights based on Relative Height 100 (RH100) in the cities of Icheon, Gwangju, and Yeoju in Gyeonggi Province, Korea. These canopy heights were compared with the 1:5,000 scale forest maps used for the National Inventory Report in Korea. The GEDI data showed a maximum canopy height of 29.44 meters (m) in Gwangju, contrasting with the forest type maps that reported heights up to 34 m in Gwangju and parts of Icheon, and a minimum of 2 m in Icheon. Additionally, this study utilized Ordinary Least Squares(OLS)regression analysis to compare GEDI RH100 data with forest stand heights at the eup-myeon-dong level using ArcGIS, revealing Standard Deviations (SDs)ranging from -1.4 to 2.5, indicating significant regional variability. Areas where forest stand heights were higher than GEDI measurements showed greater variability, whereas locations with lower tree heights from forest type maps demonstrated lower SDs. The discrepancies between GEDI and actual measurements suggest the potential for improving height estimations through the application of high-resolution remote sensing techniques. To enhance future assessments of forest biomass and carbon storage at the Tier 3 level, high-resolution, reliable data are essential. These findings underscore the urgent need for integrating high-resolution, spatially explicit LiDAR data to enhance the accuracy of carbon sink calculations in Korea.

• Journal of the Korean Society of Radiology
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• v.82 no.1
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• pp.116-127
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• 2021

Purpose To evaluate the feasibility of texture analysis of gray-scale ultrasound (US) images for staging of hepatic fibrosis. Materials and Methods Altogether, 167 patients who had undergone routine US and laboratory tests for a fibrosis-4 (FIB-4) index were included. Texture parameters were measured using a dedicated in-house software. Regions of interest were placed in five different segments (3, 5, 6, 7, 8) for each patient. The FIB-4 index was used as the reference standard for hepatic fibrosis grade. Comparisons of the texture parameters between different fibrosis groups were performed with the Student's t-test or Mann-Whitney U-test. Diagnostic performance was evaluated by receiver operating curve analysis. Results The study population comprised of patients with no fibrosis (FIB-4 < 1.45, n = 50), mild fibrosis (1.45 ≤ FIB-4 ≤ 2.35, n = 37), moderate fibrosis (2.35 < FIB-4 ≤ 3.25, n = 27), and severe fibrosis (FIB-4 > 3.25, n = 53). Skewness in hepatic segment 5 showed a difference between patients with no fibrosis and mild fibrosis (0.2392 ± 0.3361, 0.4134 ± 0.3004, respectively, p = 0.0109). The area under the curve of skewness for discriminating patients with no fibrosis from those with mild fibrosis was 0.660 (95% confidence interval, 0.551-0.758), with an estimated accuracy, sensitivity, specificity of 64%, 87%, 48%, respectively. Conclusion A significant difference was observed regarding skewness in segment 5 between patients with no fibrosis and patients with mild fibrosis.

• Korean Journal of Radiology
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• v.23 no.2
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• pp.264-270
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• 2022

Objective: This study aimed to investigate the usefulness of bone single-positron emission tomography/computed tomography (SPECT/CT) of the hip in predicting the later occurrence of avascular necrosis (AVN) after slipped capital femoral epiphysis (SCFE) or femoral neck fracture in pediatric patients. The quantitative parameters of SPECT/CT useful in predicting AVN were identified. Materials and Methods: Twenty-one (male:female, 10:11) consecutive patients aged < 18 years (mean age ± standard deviation [SD], 11.0 ± 2.7 years) who underwent surgery for SCFE or femoral neck fracture and postoperative bone SPECT/CT were included. The maximum standardized uptake value (SUV), mean SUV, and minimum SUV of the femoral head were measured. The ratios of the maximum SUV, mean SUV, and minimum SUV of the affected femoral head to the contralateral side were determined. Patients were followed up for > 1 year after the surgery. The SPECT/CT parameters were compared between patients who developed AVN and those who did not. The accuracy of SPECT/CT parameters for predicting AVN was assessed. Results: Six patients developed AVN. There was a significant difference in the ratio of the mean SUV among patients who developed AVN (mean ± SD, 0.8 ± 0.3) and those who did not (1.1 ± 0.2, p = 0.018). However, there were no significant differences in the ratios of the maximum and minimum SUV between the groups (all p = 0.205). For the maximum, mean, and minimum SUVs, no significant differences were observed between the groups (p = 0.519, 0.733, and 0.470, respectively). The cutoff mean SUV ratio of 0.87 yielded a 66.7% sensitivity and 93.2% specificity for predicting AVN. Conclusion: Quantitative bone SPECT/CT is useful for evaluating femoral head viability in pediatric patients with SCFE or femoral neck fractures. Clinicians should consider the high possibility of later AVN development in patients with a decreased mean SUV ratio.

• Korean Journal of Radiology
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• v.20 no.1
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• pp.114-125
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• 2019

Objective: Segmented cardiac cine magnetic resonance imaging (MRI) is the gold standard for cardiac ventricular volumetric assessment. In patients with difficulty in breath-holding or arrhythmia, this technique may generate images with inadequate quality for diagnosis. Real-time cardiac cine MRI has been developed to address this limitation. We aimed to assess the performance of retrospective electrocardiography-gated real-time cine MRI at 3T for left ventricular (LV) volume and mass measurement. Materials and Methods: Fifty-one patients were consecutively enrolled. A series of short-axis cine images covering the entire left ventricle using both segmented and real-time balanced steady-state free precession cardiac cine MRI were obtained. End-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), ejection fraction (EF), and LV mass were measured. The agreement and correlation of the parameters were assessed. Additionally, image quality was evaluated using European CMR Registry (Euro-CMR) score and structure visibility rating. Results: In patients without difficulty in breath-holding or arrhythmia, no significant difference was found in Euro-CMR score between the two techniques (0.3 ± 0.7 vs. 0.3 ± 0.5, p > 0.05). Good agreements and correlations were found between the techniques for measuring EDV, ESV, EF, SV, and LV mass. In patients with difficulty in breath-holding or arrhythmia, segmented cine MRI had a significant higher Euro-CMR score (2.3 ± 1.2 vs. 0.4 ± 0.5, p < 0.001). Conclusion: Real-time cine MRI at 3T allowed the assessment of LV volume with high accuracy and showed a significantly better image quality compared to that of segmented cine MRI in patients with difficulty in breath-holding and arrhythmia.

• Korean Journal of Radiology
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• v.1 no.1
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• pp.25-32
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• 2000

Objective: The purpose of our study was to determine the ability of H-1 MR spectroscopy (MRS) to lateralize the lesion in patients with hippocampal sclerosis. Materials and Methods: Twenty healthy volunteers and 25 patients with intractable temporal lobe epilepsy whose MR imaging diagnosis was unilateral hippocampal sclerosis were included. This diagnosis was based on the presence of unilateral atrophy and/or high T2 signal intensity of the hippocampus. Single-voxel H-1 MRS was carried out on a 1.5-T unit using PRESS sequence (TE, 136 msec). Spectra were obtained from hippocampal areas bilaterally with volumes of interest (VOIs) of 6.0 cm³ and 2.25 cm³ in healthy volunteers, and of either 6.0 cm³ (n = 14) or 2.25 cm³ (n = 11) in patients. Metabolite ratios of NAA/Cho and NAA/Cr were calculated from relative peak height measurements. The capability of MRS to lateralize the lesion and to detect bilateral abnormalities was compared with MR imaging diagnosis as a standard of reference. Results: In healthy volunteers, NAA/Cho and NAA/Cr ratios were greater than 0.8 and 1.0, respectively. In patients, the mean values of these ratios were significantly lower on the lesion side than on the contralateral side, and lower than those of healthy volunteers (p < .05). The overall correct lateralization rate of MRS was 72% (18/25); this rate was lower with a VOI of 6.0 cm³ than of 2.25 cm³ (64% versus 82%, p < .05). Bilateral abnormalities on MRS were found in 24% (6/25) of cases. Conclusion: Although its rate of correct lateralization is low, single-voxel H-1 MRS is a useful and promising diagnostic tool in the evaluation of hippocampal sclerosis, particularly for the detection of bilateral abnormalities. To improve the diagnostic accuracy of H-1 MRS, further investigation, including the use of a smaller VOI and measurement of the absolute amount of metabolites, are needed.

• Journal of the Korean Geosynthetics Society
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• v.23 no.1
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• pp.39-47
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• 2024

In this study, physical property tests and standard consolidation tests were conducted on the marine clay of Busan New Port and North Port, the middle and lower reaches of the Nakdong River including Gimhae and Yangsan, and Ulsan regions. The moisture content, a property unrelated to sample disturbance with small individual test errors, was used for regression analysis with the compression index, virgin compression index, consolidation coefficient, expansion index, and secondary compression index, among others. Subsequently, the correlation and accuracy were evaluated. Upon analyzing the correlation between the moisture content, void ratio, and liquid limit commonly used physical properties for calculating compression indexes, it was confirmed that the liquid limit had the lowest correlation. Through a linear regression analysis of the consolidation constants using the current moisture content in the natural state, a high correlation was demonstrated. Relationship equations were then presented to determine settlement and settlement time. This study suggests that moisture content can be utilized as an alternative for evaluating and calculating consolidation constants when examining ground settlement in sedimentary clays distributed in the Busan and Gyeongnam regions.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.2
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• pp.28-35
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• 2024

Corrosion inside electronic packages significantly impacts the system performance and reliability, necessitating non-destructive diagnostic techniques for system health management. This study aims to present a non-destructive method for assessing corrosion in copper interconnects using the Smith chart, a tool that integrates the magnitude and phase of complex impedance for visualization. For the experiment, specimens simulating copper transmission lines were subjected to temperature and humidity cycles according to the MIL-STD-810G standard to induce corrosion. The corrosion level of the specimen was quantitatively assessed and labeled based on color changes in the R channel. S-parameters and Smith charts with progressing corrosion stages showed unique patterns corresponding to five levels of corrosion, confirming the effectiveness of the Smith chart as a tool for corrosion assessment. Furthermore, by employing data augmentation, 4,444 Smith charts representing various corrosion levels were obtained, and artificial intelligence models were trained to output the corrosion stages of copper interconnects based on the input Smith charts. Among image classification-specialized CNN and Transformer models, the ConvNeXt model achieved the highest diagnostic performance with an accuracy of 89.4%. When diagnosing the corrosion using the Smith chart, it is possible to perform a non-destructive evaluation using electronic signals. Additionally, by integrating and visualizing signal magnitude and phase information, it is expected to perform an intuitive and noise-robust diagnosis.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.219-240
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• 2018

Sentiment analysis, which is one of the text mining techniques, is a method for extracting subjective content embedded in text documents. Recently, the sentiment analysis methods have been widely used in many fields. As good examples, data-driven surveys are based on analyzing the subjectivity of text data posted by users and market researches are conducted by analyzing users' review posts to quantify users' reputation on a target product. The basic method of sentiment analysis is to use sentiment dictionary (or lexicon), a list of sentiment vocabularies with positive, neutral, or negative semantics. In general, the meaning of many sentiment words is likely to be different across domains. For example, a sentiment word, 'sad' indicates negative meaning in many fields but a movie. In order to perform accurate sentiment analysis, we need to build the sentiment dictionary for a given domain. However, such a method of building the sentiment lexicon is time-consuming and various sentiment vocabularies are not included without the use of general-purpose sentiment lexicon. In order to address this problem, several studies have been carried out to construct the sentiment lexicon suitable for a specific domain based on 'OPEN HANGUL' and 'SentiWordNet', which are general-purpose sentiment lexicons. However, OPEN HANGUL is no longer being serviced and SentiWordNet does not work well because of language difference in the process of converting Korean word into English word. There are restrictions on the use of such general-purpose sentiment lexicons as seed data for building the sentiment lexicon for a specific domain. In this article, we construct 'KNU Korean Sentiment Lexicon (KNU-KSL)', a new general-purpose Korean sentiment dictionary that is more advanced than existing general-purpose lexicons. The proposed dictionary, which is a list of domain-independent sentiment words such as 'thank you', 'worthy', and 'impressed', is built to quickly construct the sentiment dictionary for a target domain. Especially, it constructs sentiment vocabularies by analyzing the glosses contained in Standard Korean Language Dictionary (SKLD) by the following procedures: First, we propose a sentiment classification model based on Bidirectional Long Short-Term Memory (Bi-LSTM). Second, the proposed deep learning model automatically classifies each of glosses to either positive or negative meaning. Third, positive words and phrases are extracted from the glosses classified as positive meaning, while negative words and phrases are extracted from the glosses classified as negative meaning. Our experimental results show that the average accuracy of the proposed sentiment classification model is up to 89.45%. In addition, the sentiment dictionary is more extended using various external sources including SentiWordNet, SenticNet, Emotional Verbs, and Sentiment Lexicon 0603. Furthermore, we add sentiment information about frequently used coined words and emoticons that are used mainly on the Web. The KNU-KSL contains a total of 14,843 sentiment vocabularies, each of which is one of 1-grams, 2-grams, phrases, and sentence patterns. Unlike existing sentiment dictionaries, it is composed of words that are not affected by particular domains. The recent trend on sentiment analysis is to use deep learning technique without sentiment dictionaries. The importance of developing sentiment dictionaries is declined gradually. However, one of recent studies shows that the words in the sentiment dictionary can be used as features of deep learning models, resulting in the sentiment analysis performed with higher accuracy (Teng, Z., 2016). This result indicates that the sentiment dictionary is used not only for sentiment analysis but also as features of deep learning models for improving accuracy. The proposed dictionary can be used as a basic data for constructing the sentiment lexicon of a particular domain and as features of deep learning models. It is also useful to automatically and quickly build large training sets for deep learning models.