• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.225-225
• /
• 2015

Drought events usually evolve slowly in time and their impacts generally span a long period of time. This indicates that the sequence of drought is not completely random. The Hidden Markov Model (HMM) is a probabilistic model used to represent dependences between invisible hidden states which finally result in observations. Drought characteristics are dependent on the underlying generating mechanism, which can be well modelled by the HMM. This study employed a HMM with Gaussian emissions to fit the Standardized Precipitation Index (SPI) series and make multi-step prediction to check the drought characteristics in the future. To estimate the parameters of the HMM, we employed a Bayesian model computed via Markov Chain Monte Carlo (MCMC). Since the true number of hidden states is unknown, we fit the model with varying number of hidden states and used reversible jump to allow for transdimensional moves between models with different numbers of states. We applied the HMM to several stations SPI data in South Korea. The monthly SPI data from January 1973 to December 2012 was divided into two parts, the first 30-year SPI data (January 1973 to December 2002) was used for model calibration and the last 10-year SPI data (January 2003 to December 2012) for model validation. All the SPI data was preprocessed through the wavelet denoising and applied as the visible output in the HMM. Different lead time (T= 1, 3, 6, 12 months) forecasting performances were compared with conventional forecasting techniques (e.g., ANN and ARMA). Based on statistical evaluation performance, the HMM exhibited significant preferable results compared to conventional models with much larger forecasting skill score (about 0.3-0.6) and lower Root Mean Square Error (RMSE) values (about 0.5-0.9).

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.4
• /
• pp.1502-1520
• /
• 2021

This paper attempts to investigate Korean youth Not in Education, Employment and Training (NEET) and how daily activities and community participation may influence their positive emotions and job search desire. First, we conducted a focus group interview with 16 NEETs who participated in the Kakao NEET Company project. The project allowed participants to experience employment by founding a virtual company in which each participant selected a daily activity to perform as part of the company's operations. Second, the interview responses were categorized and assigned emotional values using the card sorting technique and multi-dimensional analysis (MDS). A total of 11 emotional values were derived through this process. Finally, a social network analysis was conducted in order to measure the density of relations among the emotional values. Results suggest that immersion, confidence, belongingness were the three highest values evaluated by participants. Furthermore, network diagrams imply that the stronger participants perceived social support and belongingness with others, the stronger their responsibility grew, further leading them to establish steady goals. In particular, the high eigenvector score for "desire for job" suggests that emotional values are sequentially connected to the immersion-social support-responsibility-goal-job desire. This sequence suggests that digital services that are developed with the aim to enhance social values such as the Kakao NEET Project may engender motivation and confidence in youth NEETs. The overall results suggest that a systematic approach to policymaking should be considered in order to provide fundamental solutions and expand opportunities for social participation and emotional comfort, as social isolation due to low self-esteem has been reported as one of the reasons for NEETs' failure in the labor market.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.3
• /
• pp.389-395
• /
• 2021

In this paper, we propose a target image exchange model to improve performance of the object tracking algorithm based on a Siamese network. The object tracking algorithm based on the Siamese network tracks the object by finding the most similar part in the search image using only the target image specified in the first frame of the sequence. Since only the object of the first frame and the search image compare similarity, if tracking fails once, errors accumulate and drift in a part other than the tracked object occurs. Therefore, by designing a CNN(Convolutional Neural Network) based model, we check whether the tracking is progressing well, and the target image exchange timing is defined by using the score output from the Siamese network-based object tracking algorithm. The proposed model is evaluated the performance using the VOT-2018 dataset, and finally achieved an accuracy of 0.611 and a robustness of 22.816.

• Journal of The Korean Association of Information Education
• /
• v.24 no.6
• /
• pp.529-537
• /
• 2020

Scratch is Educational Programming Language, and it has been widely used in Elementary school SW Education. Many studies show that Scratch education is helpful for students' computational thinking and problem solving. However, the lower grade students use scratch less than the higher grade students, and the higher grade students have difficulty in understanding basic programming principles such as sequence, repetition, and condition. Therefore, in this study, we developed Scratch electronic blocks and programming education curriculum. We had classes for 2nd grade and 6th grade students, and it was confirmed that the score of 2nd grade students' interest about programming increased from 3.28 to 3.58 and 6th grade students' interest increased from 3.41 to 4.09. As a result of the programming basic principles understanding assessment, 84% of the 2nd grade students solved more than 7 of the 9 questions and 62% of the 6th grade students solved more than 7 of the 9 questions.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.2
• /
• pp.308-313
• /
• 2021

In this study, tweets about the 2019 Koreas-US DMZ Summit were collected along with a time sequence and analyzed by a sequential topic modeling method, Dynamic Topic Modeling(DTM). In microblogging services such as Twitter, unstructured data that mixes news and an opinion about a single event occurs at the same time on a large scale, and information and reactions are produced in the same message format. Therefore, to grasp a topic trend, the contextual meaning can be found only by performing pattern analysis reflecting the characteristics of sequential data. As a result of calculating the DTM after obtaining the topic coherence score and evaluating the Latent Dirichlet Allocation(LDA), 30 topics related to news reports and opinions were derived, and the probability of occurrence of each topic and keywords were dynamically evolving. In conclusion, the study found that DTM is a suitable model for analyzing the trend of integrated topics in a specific event over time.

• Genomics & Informatics
• /
• v.19 no.4
• /
• pp.47.1-47.12
• /
• 2021

Kaposi's sarcoma-associated herpesvirus (KSHV) is one of the few human oncogenic viruses, which causes a variety of malignancies, including Kaposi's sarcoma, multicentric Castleman disease, and primary effusion lymphoma, particularly in human immunodeficiency virus patients. The currently available treatment options cannot always prevent the invasion and dissemination of this virus. In recent times, siRNA-based therapeutics are gaining prominence over conventional medications as siRNA can be designed to target almost any gene of interest. The ORF57 is a crucial regulatory protein for lytic gene expression of KSHV. Disruption of this gene translation will inevitably inhibit the replication of the virus in the host cell. Therefore, the ORF57 of KSHV could be a potential target for designing siRNA-based therapeutics. Considering both sequence preferences and target site accessibility, several online tools (i-SCORE Designer, Sfold web server) had been utilized to predict the siRNA guide strand against the ORF57. Subsequently, off-target filtration (BLAST), conservancy test (fuzznuc), and thermodynamics analysis (RNAcofold, RNAalifold, and RNA Structure web server) were also performed to select the most suitable siRNA sequences. Finally, two siRNAs were identified that passed all of the filtration phases and fulfilled the thermodynamic criteria. We hope that the siRNAs predicted in this study would be helpful for the development of new effective therapeutics against KSHV.

• Genomics & Informatics
• /
• v.19 no.3
• /
• pp.31.1-31.9
• /
• 2021

Leptospirosis is a zoonotic disease caused by spirochetes from the genus Leptospira. In Thailand, Leptospira interrogans is a major cause of leptospirosis. Leptospirosis patients present with a wide range of clinical manifestations from asymptomatic, mild infections to severe illness involving organ failure. For better understanding the difference between Leptospira isolates causing mild and severe leptospirosis, illumina sequencing was used to sequence genomic DNA in both serotypes. DNA of Leptospira isolated from two patients, one with mild and another with severe symptoms, were included in this study. The paired-end reads were removed adapters and trimmed with Q30 score using Trimmomatic. Trimmed reads were constructed to contigs and scaffolds using SPAdes. Cross-contamination of scaffolds was evaluated by ContEst16s. Prokka tool for bacterial annotation was used to annotate sequences from both Leptospira isolates. Predicted amino acid sequences from Prokka were searched in EggNOG and David gene ontology database to characterize gene ontology. In addition, Leptospira from mild and severe patients, that passed the criteria e-value < 10e^-5 from blastP against virulence factor database, were used to analyze with Venn diagram. From this study, we found 13 and 12 genes that were unique in the isolates from mild and severe patients, respectively. The 12 genes in the severe isolate might be virulence factor genes that affect disease severity. However, these genes should be validated in further study.

• Journal of Veterinary Science
• /
• v.21 no.4
• /
• pp.52.1-52.11
• /
• 2020

Background: Intradural-intramedullary intervertebral disc extrusion (IIVDE) is a rare condition of intervertebral disc disease. However, the diagnosis of IIVDE is challenging because the prognosis and imaging characteristics are poorly characterized. Objectives: We aimed to describe the clinical and imaging characteristics of tentatively diagnosed IIVDE in dogs to assess the prognostic utility of neurological grade and magnetic resonance imaging (MRI) findings. Methods: Twenty dogs were included in this retrospective cohort study. Results: Nonchondrodystrophic breeds (n = 16) were more predisposed than chondrodystrophic breeds. Most dogs showed acute onset of clinical signs. Neurological examination at admission showed predominant non-ambulatory paraparesis (n = 9); paresis (n = 16) was confirmed more frequently than paralysis (n = 4). Follow-up neurological examination results were only available for 11 dogs, ten of whom showed neurological improvement and 8 showed successful outcomes at 1 month. The characteristic MRI findings include thoracic vertebra (T)2 hyperintense, T1 hypointense, intramedullary linear tracts with reduced disc volume, and cleft of the annulus fibrosus. None of the MRI measurements were significantly correlated with neurological grade at admission. Neurological grade did not differ according to the presence of parenchymal hemorrhage, parenchymal contrast enhancement, and meningeal contrast enhancement. Neurological grades at admission showed a statistical correlation with those observed at the 1-month follow-up (r = 0.814, p = 0.02). Conclusions: IIVDE is a rare form of disc extrusion commonly experienced after physical activity or trauma and most frequently affects the cranial-cervical and thoracolumbar regions of nonchondrodystrophic dog breeds. Neurological score at admission emerged as a more useful prognostic indicator than MRI findings in dogs with suspected IIVDE.

• Investigative Magnetic Resonance Imaging
• /
• v.1 no.1
• /
• pp.135-141
• /
• 1997

Purpose: To assess the usefulness of breath-hold fast MR imaging of liver with fat suppression (FS) by application of chemical saturation technique in the diagnosis of regional fatty changes suspected in sonography. Materials and Methods: Thirteen patients who had focal lesions with diffuse, homogeneous signal changes after FS through chemical saturation technique without additional changes of imaging parameter during MR imaging of liver were selected. T1-weighted fast low-angle shot and T2-weighted turbo spin-echo sequences were obtained with or without FS during each single breath-holding session. Subjective changes of signal intensity between the pre-FS and the FS images were compared with the sonographic findings in each lesion. Results: Seven lesions of decreased signal intensity after FS on T1 or T2-weighted images, including three lesions only at FS T1 images, were regarded as focal fat infiltration. All seven lesions had compatible sonographic findings as homogenously echogenic areas. Another six lesions of subjectively increased signal intensity including two lesions only at FS T2 images were regarded as focal fat sparing. All six lesions had sonographic findings as homogenous echo poor areas suggesting focal fat sparing. In cases regarded as fat infiltration, score changes were more prominent at FS T1 images than FS T2 images(p=0.0002). In cases regarded as fat sparing, score changes were more prominent at FS T2 images than FS T1 images(p=0.042). Conclusion: Breath-hold fast T1 and T2-weighted MR imaging with and without chemical saturation pre-pulse may be sufficient for characterization of regional fatty changes in the differential diagnosis of focal hepatic lesion found at sonography.

• Journal of the Korean Society of Radiology
• /
• v.81 no.2
• /
• pp.365-378
• /
• 2020

Purpose This study was performed to determine whether the T1 relaxation time of gadoxetic acid-enhanced liver MR imaging is useful for detecting and staging liver fibrosis in patients with chronic liver disease. Materials and Methods One hundred and three patients with suspected focal liver lesion underwent MR imaging and Fibroscan. Fibroscan was chosen as the reference standard for classifying liver fibrosis. T1 relaxation times were acquired before (preT1), 20 minutes after (postT1) contrast administration, and reduction rate of T1 relaxation time (rrT1) on transverse 3D VIBE (volumetric interpolated breath-hold examination) sequence using 3T MR imaging. The optimal cut-off values for the fibrosis staging were determined with ROC analysis. Results PreT1 and postT1 increased and rrT1 decreased constantly with increasing severity of liver fibrosis according to the METAVIR score (F0-F4). There were statistically significant differences between F2 and F3 in preT1 (F2, 836.0 ± 74.7 ms; F3, 888.6 ± 77.5 ms, p < 0.05) and between F3 and F4 in postT1 (F3, 309.0 ± 80.2 ms; F4, 406.6 ± 147.7 ms, p < 0.05) and rrT1 (F3, 65.4 ± 7.7%; F4, 57.3 ± 11.4%, p < 0.05). ROC analysis revealed that combination test (preT1 + postT1) was the best test for predicting liver fibrosis. Conclusion PreT1 and postT1 increased constantly with increasing severity of liver fibrosis. T1 mapping in gadoxetic acid-enhanced liver MR imaging could be a helpful complementary sequence to determine the liver fibrosis stage.