• Title/Summary/Keyword: Large Scale Data

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Georegistration of Airborne LiDAR Data Using a Digital Topographic Map (수치지형도를 이용한 항공라이다 데이터의 기하보정)

  • Han, Dong-Yeob;Yu, Ki-Yun;Kim, Yong-Il
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.3
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    • pp.323-332
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    • 2012
  • An airborne LiDAR system performs several observations on flight routes to collect data of targeted regions accompanying with discrepancies between the collected data strips of adjacent routes. This paper aims to present an automatic error correction technique using modified ICP as a way to remove relative errors from the observed data of strip data between flight routes and to make absolute correction to the control data. A control point data from the existing digital topographic map were created and the modified ICP algorithm was applied to perform the absolute automated correction on the relatively adjusted airborne LiDAR data. Through such process we were able to improve the absolute accuracy between strips within the average point distance of airborne LiDAR data and verified the possibility of automation in the geometric corrections using a large scale digital map.

PointNet and RandLA-Net Algorithms for Object Detection Using 3D Point Clouds (3차원 포인트 클라우드 데이터를 활용한 객체 탐지 기법인 PointNet과 RandLA-Net)

  • Lee, Dong-Kun;Ji, Seung-Hwan;Park, Bon-Yeong
    • Journal of the Society of Naval Architects of Korea
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    • v.59 no.5
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    • pp.330-337
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    • 2022
  • Research on object detection algorithms using 2D data has already progressed to the level of commercialization and is being applied to various manufacturing industries. Object detection technology using 2D data has an effective advantage, there are technical limitations to accurate data generation and analysis. Since 2D data is two-axis data without a sense of depth, ambiguity arises when approached from a practical point of view. Advanced countries such as the United States are leading 3D data collection and research using 3D laser scanners. Existing processing and detection algorithms such as ICP and RANSAC show high accuracy, but are used as a processing speed problem in the processing of large-scale point cloud data. In this study, PointNet a representative technique for detecting objects using widely used 3D point cloud data is analyzed and described. And RandLA-Net, which overcomes the limitations of PointNet's performance and object prediction accuracy, is described a review of detection technology using point cloud data was conducted.

Broadcast Data Delivery in IoT Networks with Packet Loss and Energy Constraint (IoT 네트워크에서 패킷 손실과 에너지 소모를 고려한 브로드캐스트 데이터 전달 방법)

  • Jeon, Seung Yong;Ahn, Ji Hyoung;Lee, Tae-Jin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.2
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    • pp.269-276
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    • 2016
  • Internet of Things (IoT) is based on wireless networks being able to connect things and people on a large scale. In the IoT environment, reliable broadcast plays an important role to distribute data to a large number of devices. Energy harvesting from a surrounding environment is a key technique to achieve a sustainable IoT network. In IoT networks, a problem of transmission errors and energy shortage should be mitigated for reliable broadcast. In this paper, we propose an energy-efficient and reliable broadcast method to consider packet errors and energy consumption in the environment where a large number of nodes are connected. The proposed scheme can improve data restoration probability by up to 15% and reduce energy consumption by up to 17%.

The Clinical Interchange between Western Medicine and Oriental Medicine: with the Stroke Patient Outcomes Research (일부 한.양방병원 뇌혈관질환 환자의 진료결과 및 만족도의 비교연구 -한양방협진 진료프로토콜의 적용을 중심으로-)

  • Park, Jong-Ku;Kang, Myung-Guen;Lee, Seong-Soo;Kim, Dal-Rae;Choi, Seo-Young;Han, Chang-Ho;Yoo, Jun-Sang;Kim, Min-Gi;Kim, Chun-Bae
    • The Journal of Internal Korean Medicine
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    • v.22 no.4
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    • pp.691-702
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    • 2001
  • Objectives : This study was done to assess the effects of the clinical interchange between the Western Medicine and the Oriental Medicine for ischemic stroke patients. The patient outcomes include changes in neurologic function by modified NIH stoke scale, stroke pattern identification scale, and patient satisfaction, Methods : For the assessment of effects, this study was performed with 178 inpatients who had undergone the stroke care at three hospitals (W Hospital adopted western therapy, S Oriental Hospital adopted Sasang constitution medicine therapy, and H Oriental Hospital adopted mixed therapy according to a joint protocol on Western Oriental medical care) from November 1997 to December 1998. Patients were interviewed or written with self-entered questionnaire forms, and clinical data were obtained, Physicians or oriental doctors wrote clinical questionnaire forms according to the care process. Results : The patient outcomes within three hospitals at 2 stages (at admission and discharge in the modified NIH stroke scale. at admission and second weeks during admission in the stroke pattern identification scale) were found to be decreased, Especially in the results of hierarchical multiple regression analysis, the degree of improvement of modified NIH stroke scale of the stroke patients at W Hospital was significant large than it at S Oriental Hospital. Also, the degree of improvement of stroke pattern identification scale at W Hospital was significantly large than it at other two hospitals. However, the patient's satisfaction score at three hospitals wasn't significantly different. Conclusions : The result of this study suggested that the joint clinical research of Western & Oriental medical practitioners was possible even if there was a conflict between Western Medicine and Oriental Medicine. Therefore Western & Oriental medical practitioners share a mutual responsibility to apply evidence-based practice, to seek scientific empirical proof through randomized clinical trials between the multicenter.

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Bioinformatics services for analyzing massive genomic datasets

  • Ko, Gunhwan;Kim, Pan-Gyu;Cho, Youngbum;Jeong, Seongmun;Kim, Jae-Yoon;Kim, Kyoung Hyoun;Lee, Ho-Yeon;Han, Jiyeon;Yu, Namhee;Ham, Seokjin;Jang, Insoon;Kang, Byunghee;Shin, Sunguk;Kim, Lian;Lee, Seung-Won;Nam, Dougu;Kim, Jihyun F.;Kim, Namshin;Kim, Seon-Young;Lee, Sanghyuk;Roh, Tae-Young;Lee, Byungwook
    • Genomics & Informatics
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    • v.18 no.1
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    • pp.8.1-8.10
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    • 2020
  • The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www. bioexpress.re.kr/.

A Study on Scheduling Algorithm for Refreshing Database (데이터베이스 갱신을 위한 스케줄링 알고리즘에 관한 연구)

  • Park, Hee-Sook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.4
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    • pp.720-726
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    • 2009
  • There are coexisting various kinds of data in the large scale database system, the maintenance problem of freshness of data is emerging important issue that provide correctness and usefulness information to users. Most solution of this problem depends on how execute effectively required refreshing query within timely time. In this paper, we propose the refreshing scheduling algorithm to retain the freshness of data and fairness of starvation of requested refresh queries. Our algorithm recompute a rate of goal refreshing a every period to assign execution time of requested refreshing query so that we can keep the freshness and fairness of data by using proposed algorithm. We implement the web sites to showing the results of refreshing process of dynamic and semi-dynamic and static data.

A data management system for microbial genome projects

  • Ki-Bong Kim;Hyeweon Nam;Hwajung Seo and Kiejung Park
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2000.11a
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    • pp.83-85
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    • 2000
  • A lot of microbial genome sequencing projects is being done in many genome centers around the world, since the first genome, Haemophilus influenzae, was sequenced in 1995. The deluge of microbial genome sequence data demands new and highly automatic data flow system in order for genome researchers to manage and analyze their own bulky sequence data from low-level to high-level. In such an aspect, we developed the automatic data management system for microbial genome projects, which consists mainly of local database, analysis programs, and user-friendly interface. We designed and implemented the local database for large-scale sequencing projects, which makes systematic and consistent data management and retrieval possible and is tightly coupled with analysis programs and web-based user interface, That is, parsing and storage of the results of analysis programs in local database is possible and user can retrieve the data in any level of data process by means of web-based graphical user interface. Contig assembly, homology search, and ORF prediction, which are essential in genome projects, make analysis programs in our system. All but Contig assembly program are open as public domain. These programs are connected with each other by means of a lot of utility programs. As a result, this system will maximize the efficiency in cost and time in genome research.

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Analysis for Onset of Changma Using Ieodo Ocean Research Station Data (이어도 기상 관측 자료를 활용한 장마 시작일 분석)

  • Oh, Hyoeun;Ha, Kyung-Ja;Shim, Jae-Seol
    • Atmosphere
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    • v.24 no.2
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    • pp.189-196
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    • 2014
  • The definition of onset date of Changma is revisited in this study using a quality controlled Ieodo ocean research station data. The Ieodo station has great importance in terms of its southwest location from Korean Peninsula and, hence, makes it possible to predict Changma period in advance with less impact of continents. The onset date of Changma using the Ieodo station data is defined by the time that meridional wind direction changes and maintains from northerly to southerly, and then the zonal wind changes from easterly to westerly after first June. This definition comes from a recognition that the establishment and movement of the western North Pacific subtropical high (WNPSH) cause Changma through southwesterly flow. The onset data of Changma has been determined by large-scale dynamic-thermodynamic characteristics or various meteorological station data. However, even the definition based on circulation data at the Ieodo station has a potential for the improved prediction skill of the onset date of Changma. The differences between before and after Changma, defined as Ieodo station data, are also found in synoptic chart. The convective instability and conspicuous circulations, corresponding low-level southwesterly flow related to WNPSH and strong upper-level zonal wind, are represented during Changma.

Perspectives on Clinical Informatics: Integrating Large-Scale Clinical, Genomic, and Health Information for Clinical Care

  • Choi, In Young;Kim, Tae-Min;Kim, Myung Shin;Mun, Seong K.;Chung, Yeun-Jun
    • Genomics & Informatics
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    • v.11 no.4
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    • pp.186-190
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    • 2013
  • The advances in electronic medical records (EMRs) and bioinformatics (BI) represent two significant trends in healthcare. The widespread adoption of EMR systems and the completion of the Human Genome Project developed the technologies for data acquisition, analysis, and visualization in two different domains. The massive amount of data from both clinical and biology domains is expected to provide personalized, preventive, and predictive healthcare services in the near future. The integrated use of EMR and BI data needs to consider four key informatics areas: data modeling, analytics, standardization, and privacy. Bioclinical data warehouses integrating heterogeneous patient-related clinical or omics data should be considered. The representative standardization effort by the Clinical Bioinformatics Ontology (CBO) aims to provide uniquely identified concepts to include molecular pathology terminologies. Since individual genome data are easily used to predict current and future health status, different safeguards to ensure confidentiality should be considered. In this paper, we focused on the informatics aspects of integrating the EMR community and BI community by identifying opportunities, challenges, and approaches to provide the best possible care service for our patients and the population.

Frequency Analysis of Scientific Texts on the Hypoxia Using Bibliographic Data (논문 서지정보를 이용한 빈산소수괴 연구 분야의 연구용어 빈도분석)

  • Lee, GiSeop;Lee, JiYoung;Cho, HongYeon
    • Ocean and Polar Research
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    • v.41 no.2
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    • pp.107-120
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    • 2019
  • The frequency analysis of scientific terms using bibliographic information is a simple concept, but as relevant data become more widespread, manual analysis of all data is practically impossible or only possible to a very limited extent. In addition, as the scale of oceanographic research has expanded to become much more comprehensive and widespread, the allocation of research resources on various topics has become an important issue. In this study, the frequency analysis of scientific terms was performed using text mining. The data used in the analysis is a general-purpose scholarship database, totaling 2,878 articles. Hypoxia, which is an important issue in the marine environment, was selected as a research field and the frequencies of related words were analyzed. The most frequently used words were 'Organic matter', 'Bottom water', and 'Dead zone' and specific areas showed high frequency. The results of this research can be used as a basis for the allocation of research resources to the frequency of use of related terms in specific fields when planning a large research project represented by single word.