• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2121-2142
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• 2011

In this paper, we propose an e-Learning process control model that aims to graphically describe and automatically generate the manifest of sequencing prerequisites in packaging SCORM's content aggregation models. In specifying the e-Learning activity sequencing, SCORM provides the concept of sequencing prerequisites to be manifested on each e-Learning activity of the corresponding tree-structured content organization model. However, the course developer is required to completely understand the SCORM's complicated sequencing prerequisites and other extensions. So, it is necessary to achieve an efficient way of packaging for the e-Learning content organization models. The e-Learning process control model proposed in this paper ought to be an impeccable solution for this problem. Consequently, this paper aims to realize a new concept of process-driven e-Learning content aggregating approach supporting the e-Learning process control model and to implement its e-Learning process modeling system graphically describing and automatically generating the SCORM's sequencing prerequisites. Eventually, the proposed model becomes a theoretical basis for implementing a SCORM-based e-Learning process management system satisfying the SCORM's sequencing prerequisite specifications. We strongly believe that the e-Learning process control model and its modeling system achieve convenient packaging in SCORM's content organization models and in implementing an e-Learning management system as well.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.69-74
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• 2004

A sequencing problem is to find an ordered sequence of some entities which maximizes (or minimize) the domain specific objective function. As some typical examples of sequencing problems, there are traveling salesman problem, job shop scheduling, flow shop scheduling, and so on. This paper introduces a new type of sequencing problems, named a sequencing problem with fuzzy preference relation, where a fuzzy preference relation is provided for the evaluation of the quality of sequences. It presents how such a problem can be formulated in terms of objective function. It also proposes a genetic algorithm applicable to such a sequencing problem.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.4
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• pp.42-48
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• 2015

This paper has its purpose on constructing a prediction model of the arrival sequencing strategy which reflects the actual sequencing patterns of air traffic controllers. As the first step, we analyzed a pair-wise sequencing of two aircraft entering TMA from different entering points. Based on the historical trajectory data, several traffic factors such as time, speed and traffic density were examined for the model. With statistically significant factors, we constructed a prediction model of arrival sequencing through a binary logistic regression analysis. With the estimated coefficients, the performance of the model was conducted through a cross validation.

• Journal of Microbiology and Biotechnology
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• v.26 no.12
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• pp.2206-2213
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• 2016

Recently, several studies have revealed that commercial microbial identification systems do not accurately identify the uncommon causative species of candidiasis, including Candida famata, Meyerozyma guilliermondii, and C. auris. We investigated the accuracy of species-level identification in a collection of clinical isolates previously identified as C. famata (N = 38), C. lusitaniae (N = 1 2), and M. guilliermondii (N = 5) by the Vitek 2 system. All 55 isolates were re-analyzed by the Phoenix system (Becton Dickinson Diagnostics), two matrix-assisted laser desorption ionization-time of flight mass spectrometry analyzers (a Vitek MS and a Bruker Biotyper), and by sequencing of internal transcribed spacer (ITS) regions or 26S rRNA gene D1/D2 domains. Among 38 isolates previously identified as C. famata by the Vitek 2 system, the majority (27/38 isolates, 71.1%) were identified as C. tropicalis (20 isolates) or C. albicans (7 isolates) by ITS sequencing, and none was identified as C. famata. Among 20 isolates that were identified as C. tropicalis, 17 (85%) were isolated from urine. The two isolates that were identified as C. auris by ITS sequencing originated from ear discharge. The Phoenix system did not accurately identify C. lusitaniae, C. krusei, or C. auris. The correct identification rate for 55 isolates was 92.7% (51/55 isolates) for the Vitek MS and 94.6% (52/55 isolates) for the Bruker Biotyper, as compared with results from ITS sequencing. These results suggest that C. famata is very rare in Korea, and that the possibility of misidentification should be noted when an uncommon Candida species is identified.

• Genomics & Informatics
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• v.16 no.4
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• pp.29.1-29.5
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• 2018

Hybrid capture-based targeted sequencing is being used increasingly for genomic variant profiling in tumor patients. Unique molecular index (UMI) technology has recently been developed and helps to increase the accuracy of variant calling by minimizing polymerase chain reaction biases and sequencing errors. However, UMI-adopted targeted sequencing data analysis is slightly different from the methods for other types of omics data, and its pipeline for variant calling is still being optimized in various study groups for their own purposes. Due to this provincial usage of tools, our group built an analysis pipeline for global application to many studies of targeted sequencing generated with different methods. First, we generated hybrid capture-based data using genomic DNA extracted from tumor tissues of colorectal cancer patients. Sequencing libraries were prepared and pooled together, and an 8-plexed capture library was processed to the enrichment step before 150-bp paired-end sequencing with Illumina HiSeq series. For the analysis, we evaluated several published tools. We focused mainly on the compatibility of the input and output of each tool. Finally, our laboratory built an analysis pipeline specialized for UMI-adopted data. Through this pipeline, we were able to estimate even on-target rates and filtered consensus reads for more accurate variant calling. These results suggest the potential of our analysis pipeline in the precise examination of the quality and efficiency of conducted experiments.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.3
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• pp.8-14
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• 2014

Arrival management is a tool which provides efficient flow of traffic and reduces ATC workload by determining aircraft's sequence and schedules while they are in cruise phase. As a decision support tool, arrival management should advise on air traffic control service based on the understanding of human factor of its user, air traffic controller. This paper proposed a prediction model for air traffic controller sequencing strategy by analyzing the historical trajectory data. Statistical analysis is used to find how air traffic controller decides the sequence of aircraft based on the speed difference and the airspace entering time difference of aircraft. Logistic regression was applied for the proposed model and its performance was demonstrated through the comparison of the real operational data.

• Genomics & Informatics
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• v.18 no.3
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• pp.32.1-32.7
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• 2020

The mitochondrial genome of a species is an essential resource for its effective conservation and phylogenetic studies. In this article, we present sequencing and characterization of the complete mitochondrial genome of a threatened labeonine fish, Cirrhinus reba collected from Khulna region of Bangladesh. The complete mitochondrial genome was 16,597 bp in size, which formed a circular double-stranded DNA molecule containing a total of 37 mitochondrial genes (13 protein-coding genes, 2 ribosomal RNA genes, and 22 transfer RNA genes) with two non-coding regions, an origin of light strand replication (OL) and a displacement loop (D-loop), similar structure with other fishes of Teleostei. The phylogenetic tree demonstrated its close relationship with labeonine fishes. The complete mitogenome of Cirrhinus reba (GenBank no. MN862482) showed 99.96% identity to another haplotype of Cirrhinus reba (AP013325), followed by 90.18% identity with Labeo bata (AP011198).

• Tuberculosis and Respiratory Diseases
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• v.87 no.3
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• pp.252-260
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• 2024

Chronic obstructive pulmonary disease (COPD) affects close to 400 million people worldwide and is the 3rd leading cause of mortality. It is a heterogeneous disorder with multiple endophenotypes, each driven by specific molecular networks and processes. Therapeutic discovery in COPD has lagged behind other disease areas owing to a lack of understanding of its pathobiology and scarcity of biomarkers to guide therapies. Single cell RNA sequencing (scRNA-seq) is a powerful new tool to identify important cellular and molecular networks that play a crucial role in disease pathogenesis. This paper provides an overview of the scRNA-seq technology and its application in COPD and the lessons learned to date from scRNA-seq experiments in COPD.

• Mycobiology
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• v.32 no.3
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• pp.119-122
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• 2004

The intergenic spacer(IGS) sequence of Fusarium oxysporum have been reported to provide reliable information concerning intraspecific variation and phylogeny of fungal species. The eleven strains of Fusarium oxysporum and its formae speciales belonging to section Elegans were compared with sequencing analysis. The direct sequencing of partial IGS was carried out using PCR with primer NIGS1(5'-CTTCGCCTCGATTTCCCCAA-3')/NIGS2(5'-TCGTCGCCGACAGTTTTCTG-3') and internal primer NIGS3(5'-TCGAGGATCGATTCGAGG-3')/NIGS4(5'-CCTCGAATCGATCCTCGA-3'). A single PCR product was found for each strain. The PCR fragments were sequenced and revealed a few within species polymorphisms at the sequence level. The size of partial IGS sequencing of F. oxysporum was divided into three groups; $526{\sim}527$ bp including F. o. f. sp. chrysanthemi, cucumerinum, cyclaminis, lycopersici, and fragariae; $514{\sim}516$ bp including F. o. f. sp. lilii, conglutinans, and raphani; 435 bp for F. o. f. sp. cucumerinum from Korea. Sequence analysis of PCR products showed that transitions were more frequent than transversions as well as the average numbers of substitution per site were range 0.41% to 3.54%.

• Molecules and Cells
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• v.37 no.1
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• pp.36-42
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• 2014

The tomato (Solanum lycopersicum L.) is a model plant for genome research in Solanaceae, as well as for studying crop breeding. Genome-wide single nucleotide polymorphisms (SNPs) are a valuable resource in genetic research and breeding. However, to do discovery of genome-wide SNPs, most methods require expensive high-depth sequencing. Here, we describe a method for SNP calling using a modified version of SAMtools that improved its sensitivity. We analyzed 90 Gb of raw sequence data from next-generation sequencing of two resequencing and seven transcriptome data sets from several tomato accessions. Our study identified 4,812,432 non-redundant SNPs. Moreover, the workflow of SNP calling was improved by aligning the reference genome with its own raw data. Using this approach, 131,785 SNPs were discovered from transcriptome data of seven accessions. In addition, 4,680,647 SNPs were identified from the genome of S. pimpinellifolium, which are 60 times more than 71,637 of the PI212816 transcriptome. SNP distribution was compared between the whole genome and transcriptome of S. pimpinellifolium. Moreover, we surveyed the location of SNPs within genic and intergenic regions. Our results indicated that the sufficient genome-wide SNP markers and very sensitive SNP calling method allow for application of marker assisted breeding and genome-wide association studies.