• Title/Summary/Keyword: data structure

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Data Cleaning and Integration of Multi-year Dietary Survey in the Korea National Health and Nutrition Examination Survey (KNHANES) using Database Normalization Theory (데이터베이스 정규화 이론을 이용한 국민건강영양조사 중 다년도 식이조사 자료 정제 및 통합)

  • Kwon, Namji;Suh, Jihye;Lee, Hunjoo
    • Journal of Environmental Health Sciences
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    • v.43 no.4
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    • pp.298-306
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    • 2017
  • Objectives: Since 1998, the Korea National Health and Nutrition Examination Survey (KNHANES) has been conducted in order to investigate the health and nutritional status of Koreans. The food intake data of individuals in the KNHANES has also been utilized as source dataset for risk assessment of chemicals via food. To improve the reliability of intake estimation and prevent missing data for less-responded foods, the structure of integrated long-standing datasets is significant. However, it is difficult to merge multi-year survey datasets due to ineffective cleaning processes for handling extensive numbers of codes for each food item along with changes in dietary habits over time. Therefore, this study aims at 1) cleaning the process of abnormal data 2) generation of integrated long-standing raw data, and 3) contributing to the production of consistent dietary exposure factors. Methods: Codebooks, the guideline book, and raw intake data from KNHANES V and VI were used for analysis. The violation of the primary key constraint and the $1^{st}-3rd$ normal form in relational database theory were tested for the codebook and the structure of the raw data, respectively. Afterwards, the cleaning process was executed for the raw data by using these integrated codes. Results: Duplication of key records and abnormality in table structures were observed. However, after adjusting according to the suggested method above, the codes were corrected and integrated codes were newly created. Finally, we were able to clean the raw data provided by respondents to the KNHANES survey. Conclusion: The results of this study will contribute to the integration of the multi-year datasets and help improve the data production system by clarifying, testing, and verifying the primary key, integrity of the code, and primitive data structure according to the database normalization theory in the national health data.

Introducing Keyword Bibliographic Coupling Analysis (KBCA) for Identifying the Intellectual Structure (지적구조 규명을 위한 키워드서지결합분석 기법에 관한 연구)

  • Lee, Jae Yun;Chung, EunKyung
    • Journal of the Korean Society for information Management
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    • v.39 no.1
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    • pp.309-330
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    • 2022
  • Intellectual structure analysis, which quantitatively identifies the structure, characteristics, and sub-domains of fields, has rapidly increased in recent years. Analysis techniques traditionally used to conduct intellectual structure analysis research include bibliographic coupling analysis, co-citation analysis, co-occurrence analysis, and author bibliographic coupling analysis. This study proposes a novel intellectual structure analysis method, Keyword Bibliographic Coupling Analysis (KBCA). The Keyword Bibliographic Coupling Analysis (KBCA) is a variation of the author bibliographic coupling analysis, which targets keywords instead of authors. It calculates the number of references shared by two keywords to the degree of coupling between the two keywords. A set of 1,366 articles in the field of 'Open Data' searched in the Web of Science were collected using the proposed KBCA technique. A total of 63 keywords that appeared more than 7 times, extracted from 1,366 article sets, were selected as core keywords in the open data field. The intellectual structure presented by the KBCA technique with 63 key keywords identified the main areas of open government and open science and 10 sub-areas. On the other hand, the intellectual structure network of co-occurrence word analysis was found to be insufficient in the overall structure and detailed domain structure. This result can be considered because the KBCA sufficiently measures the relationship between keywords using the degree of bibliographic coupling.

3-D seismic data processing system for underground investigation (지하 구조 영상화를 위한 3차원 탄성파 자료처리시스템 개발)

  • Sheen, Dong-Hoon;Ji, Jun;Lee, Doo-Sung
    • Proceedings of the Korean Geotechical Society Conference
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    • 2000.11a
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    • pp.585-592
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    • 2000
  • Primary purpose of the system developed in this study is 3-D seismic data processing system for subsurface structure imaging and this system is developed in PC based on Linux for lower-cost computer. Basic data processing modules are originated from SU (Seismic Unix) which is widely used in 2-D seismic data processing and auxilious modules are developed for 3-D data processing. The system which is constructed by using these data processing modules is designed to GUI (Graphic User Interface) in order that one can easily control and for this purpose, GTK (Gimp Tool KiT) conventionally adapted in producing Linux application.

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An Efficient Data Transmission Scheme for Logistics Vehicles (물류 차량을 위한 효율적인 데이터 전송 방법)

  • Kim, Jong-Hyo;Yang, Jung-Min
    • IEMEK Journal of Embedded Systems and Applications
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    • v.13 no.2
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    • pp.93-100
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    • 2018
  • In this paper, we present a novel scheme of data transmission for logistics vehicles connected with 3G mobile communication networks. The proposed method enhances the efficiency of data transmission by varying the packet transmission period according to the vehicle speed and by reducing the amount of transmitted data using a reduced packet structure. The main contribution is to present the experimental verification in which the proposed method is applied to commercial logistics vehicles that operate with networked data transmission modules. Being compared with the existing method, the proposed scheme shows superior performance in terms of data reduction and transmission speed.

Meta Data Modeling for Weapon System Design/Configuration Data Management System (무기체계 설계/형상정보 관리 시스템을 위한 메타 데이터 모델링)

  • Kim Ghiback
    • Journal of the Korea Institute of Military Science and Technology
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    • v.7 no.2 s.17
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    • pp.65-73
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    • 2004
  • In general, weapon system design/configuration data consist of system structure information which is linked to Part information, documents and drawings. For configuration management, version and revision control are necessary and access control of users to information should be managed for information security. Configuration data of weapon systems have various kinds of different meta data which are contained in the structure as well as attributes of parts and documents information. If neutral types of meta data models be used for building configuration management system, they can be applied to many different kinds of weapon systems with a little customization. In this paper, five meta data models are supposed and implementation results of them by using CBD(component based design) methodology are presented.

An Interactive Character Animation and Data Management Tool (대화형 캐릭터 애니메이션 생성과 데이터 관리 도구)

  • Lee, Min-Geun;Lee, Myeong-Won
    • The KIPS Transactions:PartA
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    • v.8A no.1
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    • pp.63-69
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    • 2001
  • In this paper, we present an interactive 3D character modeling and animation including a data management tool for editing the animation. It includes an animation editor for changing animation sequences according to the modified structure of 3D object in the object structure editor. The animation tool has the feature that it can produce motion data independently of any modeling tool including our modeling tool. Differently from conventional 3D graphics tools that model objects based on geometrically calculated data, our tool models 3D geometric and animation data by approximating to the real object using 2D image interactively. There are some applications that do not need precise representation, but an easier way to obtain an approximated model looking similar to the real object. Our tool is appropriate for such applications. This paper has focused on the data management for enhancing the automatin and convenience when editing a motion or when mapping a motion to the other character.

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A Study on Effective Internet Data Extraction through Layout Detection

  • Sun Bok-Keun;Han Kwang-Rok
    • International Journal of Contents
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    • v.1 no.2
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    • pp.5-9
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    • 2005
  • Currently most Internet documents including data are made based on predefined templates, but templates are usually formed only for main data and are not helpful for information retrieval against indexes, advertisements, header data etc. Templates in such forms are not appropriate when Internet documents are used as data for information retrieval. In order to process Internet documents in various areas of information retrieval, it is necessary to detect additional information such as advertisements and page indexes. Thus this study proposes a method of detecting the layout of Web pages by identifying the characteristics and structure of block tags that affect the layout of Web pages and calculating distances between Web pages. This method is purposed to reduce the cost of Web document automatic processing and improve processing efficiency by providing information about the structure of Web pages using templates through applying the method to information retrieval such as data extraction.

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A Federated Multi-Task Learning Model Based on Adaptive Distributed Data Latent Correlation Analysis

  • Wu, Shengbin;Wang, Yibai
    • Journal of Information Processing Systems
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    • v.17 no.3
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    • pp.441-452
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    • 2021
  • Federated learning provides an efficient integrated model for distributed data, allowing the local training of different data. Meanwhile, the goal of multi-task learning is to simultaneously establish models for multiple related tasks, and to obtain the underlying main structure. However, traditional federated multi-task learning models not only have strict requirements for the data distribution, but also demand large amounts of calculation and have slow convergence, which hindered their promotion in many fields. In our work, we apply the rank constraint on weight vectors of the multi-task learning model to adaptively adjust the task's similarity learning, according to the distribution of federal node data. The proposed model has a general framework for solving optimal solutions, which can be used to deal with various data types. Experiments show that our model has achieved the best results in different dataset. Notably, our model can still obtain stable results in datasets with large distribution differences. In addition, compared with traditional federated multi-task learning models, our algorithm is able to converge on a local optimal solution within limited training iterations.

Research on Regional Smart Farm Data Linkage and Service Utilization (지역 스마트팜 데이터 연계 및 서비스 활용에 대한 연구)

  • Won-Goo Lee;Hyun Jung Koo;Cheol-Joo Chae
    • Journal of Practical Agriculture & Fisheries Research
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    • v.26 no.2
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    • pp.14-24
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    • 2024
  • To enhance the usability of smart agriculture, methods for utilizing smart farm data are required. Therefore, this study proposes a scheme for utilizing regional smart farm data by linking it to services. The current status of domestic and foreign smart farm data collection and linkage services is analyzed. To collect and link regional smart farm data, necessary data collection, data cleaning, data storage structure and schema, and data storage and linkage systems are proposed. Based on the standards currently being implemented for regional smart farm internal data storage, a farm schema, environmental information schema, facility control information schema, and growth information schema are designed by extending the crop schema and crop main environmental factor information database schema. A data collection and management system structure based on the Hadoop Ecosystem is designed for data collection and management at regional smart farm data centers. Strategies are proposed for utilizing regional smart farm data to provide smart farm productivity improvement and revenue optimization services, image-based crop analysis services, and virtual reality-based smart farm simulation services.

OMA of model steel structure retrofitted with CFRP using earthquake simulator

  • Kasimzade, Azer A.;Tuhta, Sertac
    • Earthquakes and Structures
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    • v.12 no.6
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    • pp.689-697
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    • 2017
  • Nowadays, there are a great number of various structures that have been retrofitted by using different FRP Composites. Due to this, more researches need to be conducted to know more the characteristics of these structures, not only that but also a comparison among them before and after the retrofitting is needed. In this research, a model steel structure is tested using a bench-scale earthquake simulator on the shake table, using recorded micro tremor data, in order to get the dynamic behaviors. Beams of the model steel structure are then retrofitted by using CFRP composite, and then tested on the Quanser shake table by using the recorded micro tremor data. At this stage, it is needed to evaluate the dynamic behaviors of the retrofitted model steel structure. Various types of methods of OMA, such as EFDD, SSI, etc. are used to take action in the ambient responses. Having a purpose to learn more about the effects of FRP composite, experimental model analysis of both types (retrofitted and no-retrofitted models) is conducted to evaluate their dynamic behaviors. There is a provision of ambient excitation to the shake table by using recorded micro tremor ambient vibration data on ground level. Furthermore, the Enhanced Frequency Domain decomposition is used through output-only modal identification. At the end of this study, moderate correlation is obtained between mode shapes, periods and damping ratios. The aim of this research is to show and determine the effects of CFRP Composite implementation on structural responses of the model steel structure, in terms of changing its dynamical behaviors. The frequencies for model steel structure and the retrofitted model steel structure are shown to be 34.43% in average difference. Finally, it is shown that, in order to evaluate the period and rigidity of retrofitted structures, OMA might be used.