• Title/Summary/Keyword: attribute data

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A Study on the Application of Spatiotemporal Data Model for Land Information (토지정보를 위한 시공간 데이터 모델의 적용)

  • Jang, Seng-Ouk;Jo, Myung-Hee
    • Journal of the Korean Association of Geographic Information Studies
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    • v.14 no.2
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    • pp.162-169
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    • 2011
  • Land information is the real-time spatial thing which must be considered with spatial and time factors. This study aims to apply and implement an appropriate spatiotemporal model for land information by exploring spatiotemporal data models which have been suggested in the previous studies. The implemented spatiotemporal model in this study is characterized by time and attribute. In the time aspect, it is divided by valid time and transaction time, and in the attribute aspect, includes the related information such as area and ownership. At the spatial point of view, the model has a spaghetti information structure as reducing information overlapped by managing the spatial information coordinates. The spatiotemporal land information model in this study facilitates representing the quality of attribute, spatial and time information.

Finding Association Rules based on the Significant Rare Relation of Events with Time Attribute (시간 속성을 갖는 이벤트의 의미있는 희소 관계에 기반한 연관 규칙 탐사)

  • Han, Dae-Young;Kim, Dae-In;Kim, Jae-In;Song, Myung-Jin;Hwang, Bu-Hyun
    • The KIPS Transactions:PartD
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    • v.16D no.5
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    • pp.691-700
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    • 2009
  • An event means a flow which has a time attribute such as the a symptom of patients, an interval event has the time period between the start-time-point and the end-time-point. Although there are many studies for temporal data mining, they do not deal with discovering knowledge from interval event such as patient histories and purchase histories. In this paper, we suggest a method of temporal data mining that finds association rules of event causal relationships and predicts an occurrence of effect event based on discovered rules. Our method can predict the occurrence of an event by summarizing an interval event using the time attribute of an event and finding the causal relationship of event. As a result of simulation, this method can discover better knowledge than others by considering a lot of supports of an event and finding the significant rare relation on interval events which means an essential cause of an event, regardless of an occurrence support of an event in comparison with conventional data mining techniques.

Effect of Domestic Futsal Field Selection Attribute on Customer Satisfaction and Participation Intention (국내 풋살장 선택속성이 고객만족 및 참여의도에 미치는 영향)

  • Jin-Ho Shin
    • Journal of the Korean Applied Science and Technology
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    • v.40 no.6
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    • pp.1322-1329
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    • 2023
  • This study attempted to verify how the selection attribute affects customer satisfaction and participation intention to provide basic data for the efficient operation strategy of domestic futsal fields. Therefore, people who used domestic futsal fields were selected as samples, and convenience sampling methods were used. The final analysis used 271 copies of data. The data processing was conducted with the SPSS (ver. 21.0) program, which conducted frequency analysis, factor analysis and reliability analysis, correlation analysis, simple and multiple regression analysis. First, the results of the study showed that domestic futsal field selection attributes had a significant impact on customer satisfaction in the order of service, convenience, price, and facility. Second, customer satisfaction had a significant effect on participation intention. Third, the optional attributes had a significant impact on participation intention in the order of facility, service, convenience, and price. Summarizing the above results, it is believed that domestic futsal courts need to provide facilities and services that allow consumers to enjoy futsal games more conveniently and safely.

A Statistical Program for Measurement Process Capability Analysis based on KS Q ISO 22514-7 Using R (R을 이용한 KS Q ISO 22514-7 측정 프로세스 능력 분석용 프로그램)

  • Lee, Seung-Hoon;Lim, Keun
    • Journal of Korean Society for Quality Management
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    • v.47 no.4
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    • pp.713-723
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    • 2019
  • Purpose: The purpose of this study is to develop a statistical program for capability analysis of measuring system and measurement process based upon KS Q ISO 22514-7. Methods: R is a powerful open source functional programming language that provides high level graphics and interfaces to other languages. Therefore, in this study, we will develop the statistical program using R language. Results: The R program developed in this study consists of the following five modules. ① Measuring system capability analysis with Type 1 study data: MSCA_Type1.R ② Measuring system capability analysis with Linearity study(Type 4 study) data: MSCA_Type4.R ③ Measurement process capability analysis with Type 1 study & Gage R&R study data: MPCA_T1GRR.R ④ Measurement process capability analysis with Type 4 study & Gage R&R study data: MPCA_T4GRR.R ⑤ Attribute measurement processes capability analysis : AttributeMP.R Conclusion: KS Q ISO 22514-7 evaluates measuring systems and measurement processes on the basis of the measurement uncertainty that was determined according to the GUM(KS Q ISO/IEC Guide 98-3). KS Q ISO 22514-7 offers precise procedures, however, computations are more intensive. The R program of this study will help to evaluate the measurement process.

A Study on the prediction dyspnea-induced attributes of linear regression-based Article

  • Lee, Kwang-Keun;Jeon, Gyu-Hyeon
    • Korean Journal of Artificial Intelligence
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    • v.6 no.2
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    • pp.17-22
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    • 2018
  • According to the World Health Organization, the top 10 causes of death worldwide include heart disease. Heart diseases include coronary disease, which induces acute myocardial infarction. Ticagrelor drugs are being used to treat acute alliances, but it has become difficult to breathe due to the drugs. In a related study, Tobias predicted that uric acid causes acute respiratory distress independently of other factors, including BNP. And in the Ahmad study, serum uric acid numbers were related to the left ventricle depending on the level of uric acid. Experimental data are data used after 155 patients who received coronary intervention took ticagrelor. The research methods were leveraged by gradient decent algorithm and linear regression. In order to avoid overfitting in the experiment, training data and test data were separated into 70 and 30 percent respectively. The experimental results lacked the predictability of other attributes except DT in the correlation coefficient and crystal coefficient. However, all attributes related to dyspnea other than DT are determined to be related to causing relaxation of the heart in the left ventricle. Therefore, the attribute causing dyspnea is determined to be an attribute causing relaxation of the heart of the DT and left ventricle.

A Study on Identification of Track Irregularity of High Speed Railway Track Using an SVM (SVM을 이용한 고속철도 궤도틀림 식별에 관한 연구)

  • Kim, Ki-Dong;Hwang, Soon-Hyun
    • Journal of Industrial Technology
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    • v.33 no.A
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    • pp.31-39
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    • 2013
  • There are two methods to make a distinction of deterioration of high-speed railway track. One is that an administrator checks for each attribute value of track induction data represented in graph and determines whether maintenance is needed or not. The other is that an administrator checks for monthly trend of attribute value of the corresponding section and determines whether maintenance is needed or not. But these methods have a weak point that it takes longer times to make decisions as the amount of track induction data increases. As a field of artificial intelligence, the method that a computer makes a distinction of deterioration of high-speed railway track automatically is based on machine learning. Types of machine learning algorism are classified into four type: supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. This research uses supervised learning that analogizes a separating function form training data. The method suggested in this research uses SVM classifier which is a main type of supervised learning and shows higher efficiency binary classification problem. and it grasps the difference between two groups of data and makes a distinction of deterioration of high-speed railway track.

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Influence of Website Attributes on the Visit to Plastic Surgery Websites (성형외과 의원의 웹 방문자 수에 영향을 미치는 웹 사이트 속성)

  • Cho, Yeong-Bin;An, Seong-Hyeon
    • Journal of Information Technology Applications and Management
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    • v.14 no.3
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    • pp.137-149
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    • 2007
  • Most of hospitals, especially small-scale hospitals, have tried to get customers through the Internet as what companies have done recently. There are various attempts that increase visits to one's web-site in plastic surgery hospitals. However, in plastic surgery, there have been few studies on which an attribute contributes to increase the number of web-site visit. In order to derive the important attributes on the number of visit, we compared functional attributes of 30 high-visit plastic surgery web-sites with those of 30 low-visit web-sites using statistical and data mining methods. For analysis, three methods have conducted including Multiple Discriminant Analysis (statistical method), Decision Trees (data mining method), and Artificial Neural Network (data mining method). Furthermore, results of each method have been evaluated one another. The result of this study shows that a few attributes like 'Simulating cyber plastic surgery program', 'recommendation of information' explain the number of the visitors between high and low visit web-site. The methodology employed in this study provides an efficient way of improving satisfaction of visitors of plastic surgery website.

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Deriving Basic Living Service Items and Establishing Spatial Data in Rural Areas (농촌 생활권 기초생활서비스 항목 설정 및 공간데이터 구축을 위한 기초연구)

  • Kim, Suyeon;Kim, Sang-Bum
    • Journal of the Korean Institute of Rural Architecture
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    • v.24 no.3
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    • pp.39-46
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    • 2022
  • This study aims to derive basic living service facility items in rural areas and construct related spatial data. To do this, a literature review on the laws and systems related to the residential environment and services in rural areas, rural spatial planning, and the 'Rural Convention' strategic plan reports for the Jeolla and Gyeongsang Region in 2021 was conducted. Primary data collection and review on the list of basic living service items in rural areas derived from the analysis were conducted. After data collection, 12 sectors and 44 types of rural basic living service items were derived; the data selection was carried out based on the clarity of the subject of data management, whether it was established nationwide, whether it was disclosed and provided, whether it was periodically updated, and whether it was an underlying law. Afterwards, data on the derived rural basic living service items were constructed. Afterwards, spatial data on the derived rural basic living service items were constructed. Because open data provided through various institutions were employed, data structure unification such as data attribute values and code names was needed, and abnormal data such as address errors and omissions were refined. After that, the data provided in text form was converted into spatial data through geocoding, and through comparative review of the distribution status of the converted data and the provided address, spatial data related to rural basic living services were finally constructed for about 540,000 cases. Finally, implications for data construction for diagnosing rural living areas were derived through the data collection and construction process. The derived implications include data unification, data update system establishment, the establishment of attribute values necessary for rural living area diagnosis and spatial planning, data establishment plan for facilities that provide various services, rural living area analysis method, and diagnostic index development. This study is meaningful in that it laid the foundation for data-based rural area diagnosis and rural planning, by selecting the basic rural living service items, and constructing spatial data on the selected items.

Building Large-scale CityGML Feature for Digital 3D Infrastructure (디지털 3D 인프라 구축을 위한 대규모 CityGML 객체 생성 방법)

  • Jang, Hanme;Kim, HyunJun;Kang, HyeYoung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.3
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    • pp.187-201
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    • 2021
  • Recently, the demand for a 3D urban spatial information infrastructure for storing, operating, and analyzing a large number of digital data produced in cities is increasing. CityGML is a 3D spatial information data standard of OGC (Open Geospatial Consortium), which has strengths in the exchange and attribute expression of city data. Cases of constructing 3D urban spatial data in CityGML format has emerged on several cities such as Singapore and New York. However, the current ecosystem for the creation and editing of CityGML data is limited in constructing CityGML data on a large scale because of lack of completeness compared to commercial programs used to construct 3D data such as sketchup or 3d max. Therefore, in this study, a method of constructing CityGML data is proposed using commercial 3D mesh data and 2D polygons that are rapidly and automatically produced through aerial LiDAR (Light Detection and Ranging) or RGB (Red Green Blue) cameras. During the data construction process, the original 3D mesh data was geometrically transformed so that each object could be expressed in various CityGML LoD (Levels of Detail), and attribute information extracted from the 2D spatial information data was used as a supplement to increase the utilization as spatial information. The 3D city features produced in this study are CityGML building, bridge, cityFurniture, road, and tunnel. Data conversion for each feature and property construction method were presented, and visualization and validation were conducted.

A Study on The Marine Geographical Framework Data in Korea (해양기본지리정보 구축에 관한 기초연구)

  • 최윤수;오순복;박병문;김정현;서상현
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.20 no.3
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    • pp.293-301
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    • 2002
  • MGF(Marine Geographical Framework) data are the essential data sets concerning graphical and attribute information on coast and ocean among various marine-related data, which consist of framework data of the National Spatial Data Infrastructure(NSDI). This study did research and analyzed the development of current data, the situation of its usage, related technical environment and case study of foreign countries through the survey on the users and experts. Then the item of marine geographical framework data was selected in accordance with the measures for usage and management of possible MGF data. A map was pilot producted based on selected items and MGF data was presented through making up some problems shown ill the process. The importance of GIS will be growing continuously which can develop, deal with and provide the various data to efficiently manage coast and ocean. Accordingly, the MGF data will be applied to various areas such as Internet or raw data for marine information system.