• The Journal of the Korean Society for Microbiology
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• v.35 no.2
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• pp.181-190
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• 2000

To investigate resistance to lamivudine (3TC), we examined the incidence of M184V in 20 HIV-1 patients treated with 3TC for $13.1{\pm}9$ months. Fourteen of 20 patients had been exposed to zidovudine (ZDV) or didanosine (ddI) prior to 3TC therapy. Nested PCR targeting to reverse transcriptase (RT) and direct sequencing were performed for peripheral blood mononuclear cells sampled serially. There were resistance mutations to ZDV in at least 9 patients at baseline, although there was no resistance mutation to 3TC. We could detect M184V in 6 (30%) out of 20 patients. The incidence of M184V increased as the duration of therapy prolongs (13% in samples <12 months; 47% in samples ${\ge}12$ months). The frequency of mutation M184V was higher in patients with previous mutation to ZDV than in patients with wild type. Resistance mutation was not detected in 7 patients. This study shows that resistance to 3TC tends to develop rapidly in patients with baseline mutations or two drugs combination therapy than in those treated simultaneously with triple drugs. This report is the first on resistance to 3TC in Korean AIDS patients.

• Korean Journal of Remote Sensing
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• v.20 no.2
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• pp.125-137
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• 2004

In case of using image sequence taken from a moving camera along a road in an urban area, general video mosaicing technique based on a single baseline cannot create 2-D image mosaics. To solve the drawback, this paper proposed a new image mosaicing technique through 3-D multi-baselines that can create image mosaics in 3-D space. The core of the proposed method is that each image frame has a dependent baseline, an equation of first order, calculated by using ground control point (GCP) of optical flows. The proposed algorithm consists of 4 steps: calculation of optical flows using hierarchical strategy, calculation of camera exterior orientation, determination of multi-baselines, and seamless image mosaics. This paper realized and showed the proposed algorithm that can create efficient image mosaics in 3-D space from real image sequence.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.35.4-35.4
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• 2019

We have conducted a 22 GHz very long baseline interferometry (VLBI) survey of 281 local (z < 0.05) active galactic nuclei (AGNs) selected from the Swift Burst Alert Telescope (BAT) 70-month ultra hard X-ray (14-195 keV) catalog. The main goal is to investigate the relation between the strengths of black hole accretion and the parsec-scale nuclear jet, which is expected to tightly correlate but has not been observationally confirmed yet. The BAT AGN Spectroscopic Survey (BASS) provides the least biased AGN sample against obscuration including both Seyfert types, hence it makes an ideal parent sample for studying the nuclear jet properties of an overall AGN population. Using the Korean VLBI Network (KVN), the KVN and VERA Array (KaVA), and the Very Long Baseline Array (VLBA), we observed 281 objects with a 22 GHz flux > 30 mJy, detecting 11 targets (~4% of VLBI detection rate). This implies that the fraction of X-ray AGNs which are currently ejecting a strong nuclear jet is very small. Although our 11 sources span a wide range of pc-scale morphological types, from compact to complex, they lie on a tight linear relation between accretion luminosity and nuclear jet luminosity. Our finding may indicate that the power of nuclear jet is directly responsible for the amount of black hole accretion. We also have probed the fundamental plane of black hole activity in VLBI scale (e.g., few milli-arcsecond). The results from our high-frequency VLBI radio study support that the change of jet luminosity and size follows what is predicted by the AGN evolution scenario based on the Eddington ratio (ƛ$_{Edd}$) - column density ($N_H$) plane, proposed by a previous study.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.256-257
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• 2022

In this paper, we introduce a method of extracting three-dimensional feature points through the movement of a single mobile device. Using a monocular camera, a 2D image is acquired according to the camera movement and a baseline is estimated. Perform stereo matching based on feature points. A feature point and a descriptor are acquired, and the feature point is matched. Using the matched feature points, the disparity is calculated and a depth value is generated. The 3D feature point is updated according to the camera movement. Finally, the feature point is reset at the time of scene change by using scene change detection. Through the above process, an average of 73.5% of additional storage space can be secured in the key point database. By applying the algorithm proposed to the depth ground truth value of the TUM Dataset and the RGB image, it was confirmed that the\re was an average distance difference of 26.88mm compared with the 3D feature point result.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.148-155
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• 2024

Despite the increasing importance of irony and sarcasm detection in the field of natural language processing, research on the Korean language is relatively scarce compared to other languages. This study aims to experiment with various models for irony detection in Korean text. The study conducted irony detection experiments using KoBERT, a BERT-based model, and ChatGPT. For KoBERT, two methods of additional training on sentiment data were applied (Transfer Learning and MultiTask Learning). Additionally, for ChatGPT, the Few-Shot Learning technique was applied by increasing the number of example sentences entered as prompts. The results of the experiments showed that the Transfer Learning and MultiTask Learning models, which were trained with additional sentiment data, outperformed the baseline model without additional sentiment data. On the other hand, ChatGPT exhibited significantly lower performance compared to KoBERT, and increasing the number of example sentences did not lead to a noticeable improvement in performance. In conclusion, this study suggests that a model based on KoBERT is more suitable for irony detection than ChatGPT, and it highlights the potential contribution of additional training on sentiment data to improve irony detection performance.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.4
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• pp.1217-1224
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• 2012

Background and Aim: Less than 50% of oral cancer cases are diagnosed at early stages of the disease and this is in part due to poor awareness and lack of knowledge on the signs and symptoms of oral cancer. This study sought to measure the baseline awareness of oral cancer in Malaysia and aimed to increase public awareness and knowledge of oral cancer using a mass media campaign. Methods: Baseline awareness and impact of the campaign was measured using self-administered questionnaires sent via email to individuals. The campaign was aired on two national television channels and the reach was monitored through an independent programme monitoring system. Results: 78.2% of respondents had heard of oral cancer, and this increased significantly after the campaign. However, the ability to recognize signs and symptoms remains unchanged. We found that the level of awareness differed between the distinct ethnic subgroups and the reach of the campaign was not uniform across all ethnicities. Conclusion: This substantial study to measure the oral cancer awareness in Malaysia provides important baseline data for the planning of public health policies. Despite encouraging evidence that a mass media campaign could increase the awareness of oral cancer, further research is required to address the acceptability, comprehensiveness and effectiveness. Furthermore, different campaign approaches may be required for specific ethnic groups in a multi-ethnic country such as Malaysia.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.2301-2305
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• 2016

Background: The early detection of anthracycline- induced cardiotoxicity is very important since it might be useful in prevention of cardiac decompensation. This study was designed with the intent of assessing the usefulness of cardiac troponin T (cTnT) and NT- Pro BNP estimation in early prediction of anthracycline induced cardiotoxicity. Materials and Methods: In this prospective study histologically proven breast cancer patients who were scheduled to receive anthracycline containing combination chemotherapy as a part of multimodality treatment were enrolled. Baseline cardiac evaluation was performed by echocardiography (ECHO) and biomarkers like cardiac troponin T (cTnT) and N terminal- pro brain natriuretic peptide (NT- Pro BNP). All patients underwent cTnT and NT- Pro BNP estimation within 24 hours of each cycle of chemotherapy and were followed up after 6 months of initiation of chemotherapy. Any changes in follow up ECHO were compared to ECHO at baseline and cTnT and NT- Pro BNP levels after each cycle of anthracycline-based chemotherapy. Results: Initial data were obtained for 33 patients. Mean change in left ventricular diastolic diameter (LVDD) within 6 months was $0.154{\pm}0.433cms$ (p value=0.049). Seven out of 33 patients had an increase in biomarker cTnT levels (p value=0.5). A significant change in baseline and follow up LVDD was observed in patients with raised cTnT levels (p value=0.026) whereas no change was seen in ejection fraction (EF) and left atrial diameters (LAD) within 6 months of chemotherapy. NT- Pro BNP levels increased in significant number of patients (p value ${\leq}0.0001$) but no statistically significant change was observed in the ECHO parameters within 6 months. Conclusions: Functional monitoring is a poorly effective method in early estimation of anthracycline induced cardiac dysfunction. Estimation of biomarkers after chemotherapy may allow stratification of patients in various risk groups, thereby opening window for interventional strategies in order to prevent permanent damage to the myocardium.

• Journal of the korean academy of Pediatric Dentistry
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• v.48 no.3
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• pp.245-254
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• 2021

The aim of this study was to evaluate the accuracy of 3 different automatic landmark identification programs on lateral cephalgrams and the clinical acceptability in pediatric dentistry. Sixty digital cephalometric radiographs of 7 to 12 years old healthy children were randomly selected. Fourteen landmarks were chosen for assessment and the mean of 3 measurements of each landmark by a single examiner was defined as the baseline landmarks. The mean difference between an automatically identified landmark and the baseline landmark was measured for each landmark on each image. The total mean difference of 3 automatic programs compared to the baseline landmarks were 2.53 ± 1.63 mm. Errors among 3 programs were not significantly different for 12 of 14 landmarks except Orbitale and Gonion. The automatic landmark identification programs showed significant higher mean detection errors than the manual method. The programs couldn't be used as the 1st tool to replace human examiners. But considering short consuming time, these results indicate that all 3 programs have sufficient validity to be used in pediatric dental clinic.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.479-487
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• 2021

In this paper, we propose an Sound Event Detection (SED) model using self-training based on a noisy student model. The proposed SED model consists of two stages. In the first stage, a mean-teacher model based on an Residual Convolutional Recurrent Neural Network (RCRNN) is constructed to provide target labels regarding weakly labeled or unlabeled data. In the second stage, a self-training-based noisy student model is constructed by applying different noise types. That is, feature noises, such as time-frequency shift, mixup, SpecAugment, and dropout-based model noise are used here. In addition, a semi-supervised loss function is applied to train the noisy student model, which acts as label noise injection. The performance of the proposed SED model is evaluated on the validation set of the Detection and Classification of Acoustic Scenes and Events (DCASE) 2020 Challenge Task 4. The experiments show that the single model and ensemble model of the proposed SED based on the noisy student model improve F1-score by 4.6 % and 3.4 % compared to the top-ranked model in DCASE 2020 challenge Task 4, respectively.

• Korean Journal of Biological Psychiatry
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• v.4 no.1
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• pp.84-94
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• 1997

This study was done to examine changes of plasma homovanillic acid(HVA), 5-hydroxyindoleacetic acid(5-HIAA), and HVA/5-HIAA ratio during an 8-week clozapine trial and to investigate the relationship between the plasma monoamine metabolites and treatment responses. Twenty-seven chronic schizophrenic patiens were treated for 8 weeks with clozapine. The psychopathology was assessed at baseline just clozapine trial and then every 2 weeks until the end of 8-week clozapine treatment using the Positive and Negative Syndrome Scale(PANSS) and the Clinical Global Impression scale(CGI). The plasma HVA and 5-HIAA levels were measured also biweekly using high preformance liquid chromatography with electrochemical detection method. Plasma HVA and 5-HIAA levels were significantly decreased during a 8-week clozapine treatment, although plasma HVA/5-HIAA ratio showed no significant change. The changes of plasma HVA levels were in significant correlations with the changes of PANSS positive scores, of general psychophathology scores, and changes of total socres. The changes of plasma 5-HIAA levels were in signfificant correlations with the changes of PANSS negative scores. But the changes of plasma HVA/5-HIAA ratio had no significant correlation with any PANSS subscale score changes. 48% of the patients treated with clozapine was categorized as responders, who showed at least a 20% decrease in PANSS total socre and a CGI severity score of mildly ill or less(${\leq}3$) at the end pint of the study. The baseline plasma HVA levels and HVA/5-HIAA ratio were significantly higher in responders(N=13) than in nonresponders (N=14). But no significant difference in baseline levels of plasma 5-HIAA was found between responders and nonresponders. At the end point of the study, there was significant difference in the change of plasma HVA between responders(40.3% decrement) and nonresponders(3.1% increment). But no signficant differences in the change of plasma 5-HIAA and the change of plasma HVA/5-HIAA ratio between responders and nonresponders were observed. These results suggest that the antipsychotic effect of clozapine on positive symptoms may be associated with dopaminergic blocking activity, and that on negative symptoms may be associated with serotonergic blocking activity. The baseline plasma HVA levels and the change of HVA levels from baseline may be useful predictors of treatment response with clozapine.