• Title/Summary/Keyword: methods of data collection

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한글 자소의 필기 특징 분석 (Handwriting Feature Analysis of Korean Alphabets)

  • 권오성
    • 정보교육학회논문지
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    • 제4권2호
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    • pp.129-139
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    • 2001
  • 한글 필기의 효과적인 지도를 위해서는 학습자들의 필기샘플을 수집하고, 이를 분석하는 작업이 필요하다. 필기 수집은 교육대학교에 재학 중인 예비교사를 대상으로 하였고, 분석은 글자와 자소 단위로 나누어 수행하였다. 분석은 주로 글자의 획수, 필기 방향, 자소 사이의 위치 관계, 글자의 폭과 높이의 비를 주된 형태 특징 요소를 사용하였다. 본 논문의 분석 자료는 국어과 필기 지도를 위한 참고 자료로 사용될 뿐 아니라 한글 자형 및 정보화 연구에도 긴요히 사용될 수 있을 것이다.

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중독감시체계를 이용한 중독정보 수집 및 분석: 후향적 기초조사 (Research on Poisoning Data Collection using Toxic Exposure Surveillance System: Retrospective Preliminary Survey)

  • 오범진;김원;조규종;강희동;손유동;이재호;임경수
    • 대한임상독성학회지
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    • 제4권1호
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    • pp.32-43
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    • 2006
  • Purpose: Toxic Exposure Surveillance System (TESS) is widely used for poisoning data collection and making a counterplan. But, there were few reports about poisoning data collection using TESS in Korea. The aim was to collect poisoning data using TESS report form and investigate the recognition of emergency physician about the necessity of TESS as preliminary survey. Methods: Retrospectively, we gathered data from hospital records about the patient who admitted hospital emergency room due to poisoning. Date were gathered by paper and/or web client system report form in patients recruited by ICD-10 codes Results: From Jun 2004 to May 2005,3,203 patients were enrolled in 30 hospitals and their mean age was $44.9{\pm}20.3years$ old(male: female = 1,565: 1,638). The most frequent site of exposure was their own residence (73.2%, 2,345/3,203) and most of reported patients were older than 20 years(89.7%, 2,871/3,203). Frequent substances involved in poisoning were medication(41.9%) and pesticide(33.3%). Intentional poisoning was 60.7%(1,954). In fatality, overall frequency was 5.1%(162/3,203) and the most frequent route of exposure was ingestion(96.3%, 156/162) and the most frequent substance was pesticide(85.2%, 138/ 162). Antidotes were administered in 202 patients(2-PAM, atropine, antivenin, N-acetylcystein, vitamin K, flumazenil, ethanol, methylene blue, naloxone, calcium compound). 19 of 20 emergency physicians agreed with necessity of TESS. Conclusion: Data collection using TESS report form showed preliminary poisoning events in Korea. Frequent poisoning substance were medication and pesticide. The fatality was mainly related with pesticide ingestion. Many doctors in emergency room recognized the necessity of TESS.

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보안로그 빅데이터 분석 효율성 향상을 위한 방화벽 로그 데이터 표준 포맷 제안 (For Improving Security Log Big Data Analysis Efficiency, A Firewall Log Data Standard Format Proposed)

  • 배춘석;고승철
    • 정보보호학회논문지
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    • 제30권1호
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    • pp.157-167
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    • 2020
  • 최근 4차 산업혁명 도래의 기반을 제공한 빅데이터와 인공지능 기술은 산업 전반의 혁신을 견인하는 주요 동력이 되고 있다. 정보보안 영역에서도 그동안 효과적인 활용방안을 찾기 어려웠던 대규모 로그 데이터에 이러한 기술들을 적용하여 지능형 보안 체계를 개발 및 발전시키고자 노력하고 있다. 보안 인공지능 학습의 기반이 되는 보안로그 빅데이터의 품질은 곧 지능형 보안 체계의 성능을 결정짓는 중요한 입력 요소라고 할 수 있다. 하지만 다양한 제품 공급자에 따른 로그 데이터의 상이성과 복잡성은 빅데이터 전처리 과정에서 과도한 시간과 노력을 요하고 품질저하를 초래하는 문제가 있다. 본 연구에서는 다양한 방화벽 로그 데이터 포맷 관련 사례와 국내외 표준 조사를 바탕으로 데이터 수집 포맷 표준안을 제시하여 보안 로그 빅데이터를 기반으로 하는 지능형 보안 체계 발전에 기여하고자 한다.

Multivariate Procedure for Variable Selection and Classification of High Dimensional Heterogeneous Data

  • Mehmood, Tahir;Rasheed, Zahid
    • Communications for Statistical Applications and Methods
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    • 제22권6호
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    • pp.575-587
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    • 2015
  • The development in data collection techniques results in high dimensional data sets, where discrimination is an important and commonly encountered problem that are crucial to resolve when high dimensional data is heterogeneous (non-common variance covariance structure for classes). An example of this is to classify microbial habitat preferences based on codon/bi-codon usage. Habitat preference is important to study for evolutionary genetic relationships and may help industry produce specific enzymes. Most classification procedures assume homogeneity (common variance covariance structure for all classes), which is not guaranteed in most high dimensional data sets. We have introduced regularized elimination in partial least square coupled with QDA (rePLS-QDA) for the parsimonious variable selection and classification of high dimensional heterogeneous data sets based on recently introduced regularized elimination for variable selection in partial least square (rePLS) and heterogeneous classification procedure quadratic discriminant analysis (QDA). A comparison of proposed and existing methods is conducted over the simulated data set; in addition, the proposed procedure is implemented to classify microbial habitat preferences by their codon/bi-codon usage. Five bacterial habitats (Aquatic, Host Associated, Multiple, Specialized and Terrestrial) are modeled. The classification accuracy of each habitat is satisfactory and ranges from 89.1% to 100% on test data. Interesting codon/bi-codons usage, their mutual interactions influential for respective habitat preference are identified. The proposed method also produced results that concurred with known biological characteristics that will help researchers better understand divergence of species.

모바일 싱크를 위한 균등 큐잉(FQMS) : 모바일 싱크 기반 무선 센서 네트워크에서 균등한 데이터 수집을 위한 스케줄링 기법 (Fair Queuing for Mobile Sink (FQMS) : Scheduling Scheme for Fair Data Collection in Wireless Sensor Networks with Mobile Sink)

  • 조영태;박총명;이좌형;서동만;임동선;정인범
    • 한국정보과학회논문지:정보통신
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    • 제37권3호
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    • pp.204-216
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    • 2010
  • 고정 싱크를 사용한 센서 네트워크는 싱크 주변 센서 노드에게 많은 부하를 초래하게 되고 이러한 부하는 센서 노드의 배터리 소모로 이어지게 된다. 싱크 주변 센서 노드의 배터리 소모는 전체 센서 네트워크의 수명을 단축시키는 원인이 된다. 이러한 문제를 해결하기 위해 모바일 싱크를 사용하여 싱크주변 노드의 부하를 분산시키는 연구가 활발히 진행되고 있다. 모바일 싱크는 움직이는 특성을 가지고 있기 때문에 센서 노드와 통신 가능한 시간이 제한된다. 또한 통신 중에도 모바일 싱크와 센서 노드 간 거리가 연속적으로 변하기 때문에 통신 환경 역시 변하게 된다. 모바일 싱크를 사용한 센서 네트워크는 이러한 제약 사항을 해결하며 각 센서 노드들로부터 균등한 양의 데이터를 수집할 수 있어야 한다. 균등치 못한 데이터 수집은 실시간적 센서 네트워크 응용분야에서 긴급한 사건 처리를 가능하지 않게 한다. 본 논문에서는 모바일 싱크를 이용한 센서 네트워크에서 센서 노드들로부터 균등한 데이터 수집을 위한 스케줄링 기법인 FQMS를 제안한다. FQMS는 모바일 싱크와 센서 노드 간 통신 환경과 시간 제약을 고려하여 균등한 데이터 수집을 보장한다. 실험을 통해 제안된 FQMS와 기존의 스케줄링 기법들의 성능을 비교 평가한다. 실험 결과를 통해 제안된 기법이 무선 센서 노드들로 부터의 데이터 수집에 있어서 가장 균등한 데이터 수집을 수행함을 보인다.

RAM 분석 정확도 향상을 위한 야전운용 데이터의 이상값과 결측값 처리 방안 (Method of Processing the Outliers and Missing Values of Field Data to Improve RAM Analysis Accuracy)

  • 김인석;정원
    • 한국신뢰성학회지:신뢰성응용연구
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    • 제17권3호
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    • pp.264-271
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    • 2017
  • Purpose: Field operation data contains missing values or outliers due to various causes of the data collection process, so caution is required when utilizing RAM analysis results by field operation data. The purpose of this study is to present a method to minimize the RAM analysis error of the field data to improve the accuracy. Methods: Statistical methods are presented for processing of the outliers and the missing values of the field operating data, and after analyzing the RAM, the differences between before and after applying the technique are discussed. Results: The availability is estimated to be lower by 6.8 to 23.5% than that before processing, and it is judged that the processing of the missing values and outliers greatly affect the RAM analysis result. Conclusion: RAM analysis of OO weapon system was performed and suggestions for improvement of RAM analysis were presented through comparison with the new and current method. Data analysis results without appropriate treatment of error values may result in incorrect conclusions leading to inappropriate decisions and actions.

Efficient Measurement Method for Spatiotemporal Compressive Data Gathering in Wireless Sensor Networks

  • Xue, Xiao;Xiao, Song;Quan, Lei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권4호
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    • pp.1618-1637
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    • 2018
  • By means of compressive sensing (CS) technique, this paper considers the collection of sensor data with spatiotemporal correlations in wireless sensor networks (WSNs). In energy-constrained WSNs, one-dimensional CS methods need a lot of data transmissions since they are less applicable in fully exploiting the spatiotemporal correlations, while the Kronecker CS (KCS) methods suffer performance degradations when the signal dimension increases. In this paper, an appropriate sensing matrix as well as an efficient sensing method is proposed to further reduce the data transmissions without the loss of the recovery performance. Different matrices for the temporal signal of each sensor node are separately designed. The corresponding energy-efficient data gathering method is presented, which only transmitting a subset of sensor readings to recover data of the entire WSN. Theoretical analysis indicates that the sensing structure could have the relatively small mutual coherence according to the selection of matrix. Compared with the existing spatiotemporal CS (CS-ST) method, the simulation results show that the proposed efficient measurement method could reduce data transmissions by about 25% with the similar recovery performance. In addition, compared with the conventional KCS method, for 95% successful recovery, the proposed sensing structure could improve the recovery performance by about 20%.

도시 빅데이터: 모바일 센싱 데이터를 활용한 도시 계획을 위한 사회 비용 분석 (Urban Big Data: Social Costs Analysis for Urban Planning with Crowd-sourced Mobile Sensing Data)

  • 신동윤
    • 한국BIM학회 논문집
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    • 제13권4호
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    • pp.106-114
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    • 2023
  • In this study, we developed a method to quantify urban social costs using mobile sensing data, providing a novel approach to urban planning. By collecting and analyzing extensive mobile data over time, we transformed travel patterns into measurable social costs. Our findings highlight the effectiveness of big data in urban planning, revealing key correlations between transportation modes and their associated social costs. This research not only advances the use of mobile data in urban planning but also suggests new directions for future studies to enhance data collection and analysis methods.

Development of Data-Flow Control Algorithm of Wireless Network for Sewage Disposal Facility

  • Jung, Soonho;Shin, Jaekwon;Kang, Jeongjin;Lee, Seungyoun;Lee, Junghoon
    • International journal of advanced smart convergence
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    • 제4권2호
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    • pp.14-19
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    • 2015
  • Recently, water sewage disposal facilities are able to manage real-time data collection and record management through compact broadband modem LAN switching technology. Therefore, it needs more stable and efficient facility management. So, we required practical use of environmental facilities convergence based on broadband integrated modem. In this paper, we proposed short distance wireless communication network of compact broadband modem for sewage disposal facilities. And it received data inside of water treatment facility using the two communication methods (IEEE802.11x and IEEE802.15.4x). Then, our proposed an data-flow control algorithm of wireless network technology will prioritize processing data when emergency happen through collecting data, analysis data and processing. Lastly, we proved usefulness by experiment and simulation analysis.

Segmentation and Classification of Lidar data

  • Tseng, Yi-Hsing;Wang, Miao
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.153-155
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    • 2003
  • Laser scanning has become a viable technique for the collection of a large amount of accurate 3D point data densely distributed on the scanned object surface. The inherent 3D nature of the sub-randomly distributed point cloud provides abundant spatial information. To explore valuable spatial information from laser scanned data becomes an active research topic, for instance extracting digital elevation model, building models, and vegetation volumes. The sub-randomly distributed point cloud should be segmented and classified before the extraction of spatial information. This paper investigates some exist segmentation methods, and then proposes an octree-based split-and-merge segmentation method to divide lidar data into clusters belonging to 3D planes. Therefore, the classification of lidar data can be performed based on the derived attributes of extracted 3D planes. The test results of both ground and airborne lidar data show the potential of applying this method to extract spatial features from lidar data.

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