• The KIPS Transactions:PartD
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• v.16D no.4
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• pp.487-496
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• 2009

This paper addresses an indexing scheme capable of efficiently processing range queries in a large-scale trajectory database. After discussing the drawbacks of previous indexing schemes, we propose a new scheme that divides the temporal dimension into multiple time intervals and then, by this interval, builds an index for the line segments. Additionally, a supplementary index is built for the line segments within each time interval. This scheme can make a dramatic improvement in the performance of insert and search operations using a main memory index, particularly for the time interval consisting of the segments taken by those objects which are currently moving or have just completed their movements, as contrast to the previous schemes that store the index totally on the disk. Each time interval index is built as follows: First, the extent of the spatial dimension is divided onto multiple spatial cells to which the line segments are assigned evenly. We use a 2D-tree to maintain information on those cells. Then, for each cell, an additional 3D $R^*$-tree is created on the spatio-temporal space (x, y, t). Such a multi-level indexing strategy can cure the shortcomings of the legacy schemes. Performance results obtained from intensive experiments show that our scheme enhances the performance of retrieve operations by 3$\sim$10 times, with much less storage space.

• Korean Journal of Remote Sensing
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• v.18 no.6
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• pp.305-317
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• 2002

The purpose of this study is to analyze the land cover environmental changes in the Anmyeon-do. Especially, it centers on the changes in the land cover environment through methods of GIS and remote sensing. The land cover environmental change areas were detected from remote sensing data, and geographic data sets related to land cover environment change were built as a spatial database in GIS. Fuzzy logic was applied for data representation and integration of thematic maps. In the natural, social, and economic environment variables, the altitude, population density, and the national land use planning showed higher fuzzy membership values, respectively. After integrating all thematic maps using fuzzy logic operation, it is possible to predict the change quantitatively. In the study area, a region where land cover change will be likely to occur is the one on a plain near the shoreline. In particular, the hills of less than 5% slope and less than 15m altitude, adjacent to the ocean, were quite vulnerable to the aggravation of coastal environment on account of current, large-scale development. In conclusions, it is expected that the generalized scheme used in this study is regarded as one of effective methodologies for land cover environmental change detection from geographic data.

• Clinical and Experimental Pediatrics
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• v.64 no.9
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• pp.480-488
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• 2021

Background: An adequate large-scale pediatric cohort based on nationwide administrative data is lacking in Korea. Purpose: This study established the National Investigation of Birth Cohort in Korea study 2008 (NICKs-2008) based on data from a nationwide population-based health screening program and data on healthcare utilization for children. Methods: The NICKs-2008 study consisted of the Korean National Health Insurance System (NHIS) and the National Health Screening Program for Infants and Children (NHSPIC) databases comprising children born in 2008 (n=469,248) and 2009 (n=448,459) in the Republic of Korea. The NHIS database contains data on age, sex, residential area, income, healthcare utilization (International Classification of Diseases10 codes, procedure codes, and drug classification codes), and healthcare providers. The NHSPIC consists of 7 screening rounds. These screening sessions comprised physical examination, developmental screening (rounds 2-7), a general health questionnaire, and age-specific anticipatory guidance. Results: During the 10-year follow-up, 2,718 children (0.3%) died, including more boys than girls (hazard ratio, 1.145; P<0.001). A total of 848,048 children participated in at least 1 of the 7 rounds of the NHSPIC, while 96,046 participated in all 7 screening programs. A total of 823 infants (0.1%) weighed less than 1,000 g, 3,177 (0.4%) weighed 1,000-1,499 g, 37,166 (4.4%) weighed 1,500-2,499 g, 773,081 (91.4%) weighed 2,500-4,000 g, and 32,016 (5.1%) weighed over 4,000 g. There were 23,404 premature babies (5.5%) in 2008 compared to 23,368 (5.6%) in 2009. The developmental screening test indicated appropriate development in 95%-98% of children, follow-up requirements for 1%-4% of children, and recommendations for further evaluation for 1% of children. Conclusion: The NICKs-2008, which integrates data from the NHIS and NHSPIC databases, can be used to analyze disease onset prior to hospitalization based on information such as lifestyle, eating habits, and risk factors.

• The Korean journal of internal medicine
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• v.33 no.6
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• pp.1194-1202
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• 2018

Background/Aims: This study evaluated the role of hypomethylating agents (HMA) compared to best supportive care (BSC) for patients with high or very-high (H/VH) risk myelodysplastic syndrome (MDS) according to the Revised International Prognostic Scoring System. Methods: A total of 279 H/VH risk MDS patients registered in the Korean MDS Working Party database were retrospectively analyzed. Results: HMA therapy was administered to 205 patients (73.5%), including 31 patients (11.1%) who then received allogeneic hematopoietic cell transplantation (allo-HCT), while 74 patients (26.5%) received BSC or allo-HCT without HMA. The 3-year overall survival (OS) rates were $53.1%{\pm}10.7%$ for allo-HCT with HMA, $75%{\pm}21.7%$ for allo-HCT without HMA, $17.3%{\pm}3.6%$ for HMA, and $20.8%{\pm}6.9%$ for BSC groups (p < 0.001). In the multivariate analysis, only allo-HCT was related with favorable OS (hazard ratio [HR], 0.356; p = 0.002), while very poor cytogenetic risk (HR, 5.696; p = 0.042), age ${\geq}65years$ (HR, 1.578; p = 0.022), Eastern Cooperative Oncology Group performance status (ECOG PS) 2 to 4 (HR, 2.837; p < 0.001), and transformation to acute myeloid leukemia (AML) (HR, 1.901; p = 0.001) all had an adverse effect on OS. Conclusions: For the H/VH risk group, very poor cytogenetic risk, age ${\geq}65years$, ECOG PS 2 to 4, and AML transformation were poor prognostic factors. HMA showed no benefit in terms of OS when compared to BSC. Allo-HCT was the only factor predicting a favorable long-term outcome. The use of HMA therapy did not seem to have an adverse effect on the transplantation outcomes. However, the conclusion of this study should be carefully interpreted and proven by large scale research in the future.

• Journal of Breast Cancer
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• v.21 no.4
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• pp.363-370
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• 2018

Purpose: Breast cancer is the most commonly occurring cancer among women worldwide, and therefore, improved approaches for its early detection are urgently needed. As microRNAs (miRNAs) are increasingly recognized as critical regulators in tumorigenesis and possess excellent stability in plasma, this study focused on using miRNAs to develop a method for identifying noninvasive biomarkers. Methods: To discover critical candidates, differential expression analysis was performed on tissue-originated miRNA profiles of 409 early breast cancer patients and 87 healthy controls from The Cancer Genome Atlas database. We selected candidates from the differentially expressed miRNAs and then evaluated every possible molecular signature formed by the candidates. The best signature was validated in independent serum samples from 113 early breast cancer patients and 47 healthy controls using reverse transcription quantitative real-time polymerase chain reaction. Results: The miRNA candidates in our method were revealed to be associated with breast cancer according to previous studies and showed potential as useful biomarkers. When validated in independent serum samples, the area under curve of the final miRNA signature (miR-21-3p, miR-21-5p, and miR-99a-5p) was 0.895. Diagnostic sensitivity and specificity were 97.9% and 73.5%, respectively. Conclusion: The present study established a novel and effective method to identify biomarkers for early breast cancer. And the method, is also suitable for other cancer types. Furthermore, a combination of three miRNAs was identified as a prospective biomarker for breast cancer early detection.

• The Journal of Korean Medicine
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• v.44 no.2
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• pp.106-118
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• 2023

Objectives: Network pharmacology is a method of constructing and analyzing a drug-compound-target network to predict potential efficacy and mechanisms related to drug targets. In that large-scale analysis can be performed in a short time, it is considered a suitable tool to explore the function and role of herbal medicine. Thus, we investigated the potential functions and pathways of Chongmyunggongjin-dan (CMGJD) on Alzheimer's disease (AD) via network pharmacology analysis. Methods: Using public databases and PubChem database, compounds of CMGJD and their target genes were collected. The putative target genes of CMGJD and known target genes of AD were compared and found the correlation. Then, the network was constructed using Cytoscape 3.9.1. and functional enrichment analysis was conducted based on the Gene Ontology (GO) Biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways to predict the mechanisms. Results: The result showed that total 104 compounds and 1157 related genes were gathered from CMGJD. The network consisted of 1157nodes and 10034 edges. 859 genes were interacted with AD gene set, suggesting that the effects of CMGJD are closely related to AD. Target genes of CMGJD are considerably associated with various pathways including 'Positive regulation of chemokine production', 'Cellular response to toxic substance', 'Arachidonic acid metabolic process', 'PI3K-Akt signaling pathway', 'Metabolic pathways', 'IL-17 signaling pathway' and 'Neuroactive ligand-receptor interaction'. Conclusion: Through a network pharmacological method, CMGJD was predicted to have high relevance with AD by regulating inflammation. This study could be used as a basis for effects of CMGJD on AD.

• The Journal of the Society of Stroke on Korean Medicine
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• v.7 no.1
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• pp.34-39
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• 2006

Objectives and methods : The Euibujipsung is the one of the huge-scale encyclopedias about Oriental Medicine. To investigate the most frequently used acupoints for hemiparesis after stroke, we used Euibujipsung CR-ROM database with several key words concerned with motor weakness (半身不遂 不遂不隨 癱瘓 中臟 中腑 風痱, etc.). Results : In the result, we found five popular acupoints (GV20, LI11, LI15, ST36 and GB39), and four meridians (Stomach, Gall bladder, Large intestine and Small intestine). We also found that the Yang meridians were cited more frequently than the Yin. Conclusion : Therefore we think that these findings can give further ideas to clinical practice and research fields for stroke rehabilitation in Oriental medicine.

• The Journal of the Society of Stroke on Korean Medicine
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• v.8 no.1
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• pp.28-33
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• 2007

Objectives and methods : The Euibujipsung is one of the huge-scale encyclopedias about Oriental Medicine. To search the most frequently used aupoints for dysarthria after stroke, we used Euibujipsung CD-ROM database with several chinese character keyword concerned with vernal function(語, 言, 音, 啞, 瘖, etc). Results : We found four popular acupoints(PC5, GV20, GV16, TE6), and five meridians (Governor vessel, Gall Bladder, Heart, Large Intestine and Triple Energizer). We also found that the extra meridians were used more frequently than other type of meridians. Conclusion : We think that these findings can give further ideas to clinical practice and research fields for stroke rehabilitation in Oriental medicine.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• 한국균학회소식:학술대회논문집
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• 2015.05a
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• pp.59-59
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• 2015

Cryptococcus neoformans causes life-threatening meningoencephalitis in humans, but the treatment of cryptococcosis remains challenging. To develop novel therapeutic targets and approaches, signaling cascades controlling pathogenicity of C. neoformans have been extensively studied but the underlying biological regulatory circuits remain elusive, particularly due to the presence of an evolutionarily divergent set of transcription factors (TFs) in this basidiomycetous fungus. In this study, we constructed a high-quality of 322 signature-tagged gene deletion strains for 155 putative TF genes, which were previously predicted using the DNA-binding domain TF database (http://www.transcriptionfactor.org/). We tested in vivo and in vitro phenotypic traits under 32 distinct growth conditions using 322 TF gene deletion strains. At least one phenotypic trait was exhibited by 145 out of 155 TF mutants (93%) and approximately 85% of the TFs (132/155) have been functionally characterized for the first time in this study. Through high-coverage phenome analysis, we discovered myriad novel TFs that play critical roles in growth, differentiation, virulence-factor (melanin, capsule, and urease) formation, stress responses, antifungal drug resistance, and virulence. Large-scale virulence and infectivity assays in insect (Galleria mellonella) and mouse host models identified 34 novel TFs that are critical for pathogenicity. The genotypic and phenotypic data for each TF are available in the C. neoformans TF phenome database (http://tf.cryptococcus.org). In conclusion, our phenome-based functional analysis of the C. neoformans TF mutant library provides key insights into transcriptional networks of basidiomycetous fungi and ubiquitous human fungal pathogens.