• Title/Summary/Keyword: Automatic Update

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A Study on Automatic Detection of the Gross Errors on DSM Using Stereo Image Analysis (스테레오 영상분석에 기반한 DSM 과대오차영역의 자동검출기법연구)

  • Jeong, Jaehoon;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.29 no.5
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    • pp.487-497
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    • 2013
  • In this paper, a method of using high resolution stereo images is proposed to efficiently detect DSM errors. Automatically generated DSMs from stereo matching can be a useful solution to acquire DSM data in various aspects but they may include many gross errors coming from automatic processing. Therefore, a method to detect the gross errors on DSM is required for efficient DSM update. In this paper, stereo analysis using high resolution stereo images was investigated to represent reliability of DSM grids. The analysis enabled automatic detection of the gross errors which greatly influenced DSM quality. We used the reference DSM to assess reliability of our proposed method. We confirmed from experimental results that our method can be a valuable DSM errors analysis for efficient DSM correction. Our method is useful to analyze and improve DSM accuracy for various types of DSM and DEM. It is expected that our approach can be exploited for achievement of reliable DSM and DEM.

Automated Method for the Efficient Management of DNSSEC Singing Keys in Korea (국내 DNSSEC 서명키의 효율적인 관리를 위한 자동화 방안)

  • Choi, Myung Hee;Kim, Seung Joo
    • KIPS Transactions on Computer and Communication Systems
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    • v.4 no.8
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    • pp.259-270
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    • 2015
  • In this paper, we study and implement ways for users to easily apply and manage the DNSSEC in a domestic environment. DNSSEC is the DNS cache information proposed to address the vulnerability of modulation. However, DNSSEC is difficult to apply and manage due to insufficient domestic applications. In signing keys for efficient and reliable management of DNSSEC, we propose proactive monitoring SW and signing keys. This is an automatic management s/w signing key for DNSSEC efficient and reliable management and to provide a monitoring of the signing key. In addition to the proposed details of how DNSSEC signing key update and monitoring progress smoothly, we expect that the present study will help domestic users to apply and manage DNSSEC easily.

지능형 전문가관리 프레임워크를 위한 주제 분야 계층 자동 생성

  • Yang, Geun-U;Lee, Sang-Ro
    • 한국경영정보학회:학술대회논문집
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    • 2007.11a
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    • pp.294-299
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    • 2007
  • In this paper, we introduce the methodology for the automatic generation of the subject field hierarchy for Intellgent Expert Management Framework using WordNet. Intelligent Expert Management Framework, which is proposed as an appropriate method to manage valuable tacit knowledge within the organization, defines the expert profile structure and proposes the efficient method to automate the process to collect and update the expert profile information based on the profile structure defined. To increase the satisfaction level of users, additional intelligent search features are defined and users can be given the list of experts in related or similar expert fields when they perform expert searches based on the expert database being built. To enable automatic profiling of the organizational experts as well as intelligent expert searches, the subject field hierarchy, upon which the expert profiles are classified and expert searches for similar fields are performed, should be predefined. In this paper, we propose the WordNet library method that first eliminates the ambiguity of the senses of nominal data values, constructs the subject field hierarchy by overlapping the hypernym of the remaining senses, and lastly adjusts the derived hierarchy to the preference of users. Based on the proposed methodology, we expect to avoid the prohibitive costs in building large subject field hierarchies when manually done as well as maintain the objectivity of the hierarchies.

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Development of the web robot system for an efficient information delivery of portal sites classified by the business types (업종별 포탈 사이트의 효율적 정보제공을 위한 웹로봇 시스템 개발에 관한 연구)

  • Kim Gwang Myeong;Baek Sang Gyu;Kim Seon Ho
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2003.05a
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    • pp.98-104
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    • 2003
  • While the impact or internet on our everyday life keeps increasing, the internet users are turning toward the value added information only that suits their purpose instead of just wandering over a sea (pool) or information. Although it is easy to locate the information using various search engines. we still finds it time and cost consuming to update the existing information or to add similar Information. There are several portal sites managed by each industrial types or associations/organizations for the purpose or strengthening the competitiveness or small and medium-sized enterprises And currently, tremendous manpower and expenses are put into the selection and quality improvement or information to satisfy the needs toward the high qualify information by the specialized users in their fields collection and updating or the information is partially available manually during He period or budget allocation by the government it becomes problematic, however, to continue this service when the project expires. This report presents the system for the information collection, analysis and classification of portal sites operated for the special purposes and automatic upload to the proper sites. In addition. expression or web robots and application of robots and several information types are suggested which will eventually accomplish currency or information and automatic updates and addition or documents with the least expenses or maintenance.

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Design for Automobile Parts Management System (자동차 부품관리 시스템 설계)

  • Kim, Gui-Jung
    • Proceedings of the Korea Contents Association Conference
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    • 2008.05a
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    • pp.575-578
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    • 2008
  • Currently the automobile parts manufacturing industry of most, it is difficult in the automobile part development and purchase and production management. And when new regulation it will develop this automobile parts and changing design, it is difficult in new registration and history management. Automatic history management and DB construction about automobile parts is in great demand. The purpose of paper is a design of data retrieval and real-time production integration management for automobile parts. Automatic data update is accomplished as input material changing process for design data change and integration management of history information about parts is possible when input the name of an part and the number of an part.

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AUTOMATIC AS-IS BIM EXTRACTION FOR SUSTAINABLE SIMULATION OF BUILT ENVIRONMENTS

  • Chao Wang;Yong K. Cho
    • International conference on construction engineering and project management
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    • 2013.01a
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    • pp.47-51
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    • 2013
  • Existing buildings now represent the greatest opportunity to improve building energy efficiency. Building performance analysis is becoming increasingly important because decision makers can have a better visualization of their building's performance and quickly make the solution for improving building energy efficiency and reducing environmental impacts. Nowadays, building information models (BIMs) have been widely created during the design phase of new buildings, and it can be easily imported to third party software to conduct various analyses. However, a BIM is not always available for all existing buildings. Even if a BIM is available during the design and construction phases, it is very challenging to keep updating it while a building is aged. A manual process to create or update a BIM is very time consuming and labor intensive. A laser scanning technology has been a popular tool to create as-is BIM. However it still needs labor-intensive manual processes to create a BIM out of point clouds. This paper introduces automatic as-is simplified BIM creation from point clouds for energy simulations. A framework of decision support system that can assist decision makers on retrofits for existing buildings is introduced as well. A case study on a residential house was tested in this study to validate the proposed framework, and the technical feasibility of the developed system was positively demonstrated.

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KONG-DB: Korean Novel Geo-name DB & Search and Visualization System Using Dictionary from the Web (KONG-DB: 웹 상의 어휘 사전을 활용한 한국 소설 지명 DB, 검색 및 시각화 시스템)

  • Park, Sung Hee
    • Journal of the Korean Society for information Management
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    • v.33 no.3
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    • pp.321-343
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    • 2016
  • This study aimed to design a semi-automatic web-based pilot system 1) to build a Korean novel geo-name, 2) to update the database using automatic geo-name extraction for a scalable database, and 3) to retrieve/visualize the usage of an old geo-name on the map. In particular, the problem of extracting novel geo-names, which are currently obsolete, is difficult to solve because obtaining a corpus used for training dataset is burden. To build a corpus for training data, an admin tool, HTML crawler and parser in Python, crawled geo-names and usages from a vocabulary dictionary for Korean New Novel enough to train a named entity tagger for extracting even novel geo-names not shown up in a training corpus. By means of a training corpus and an automatic extraction tool, the geo-name database was made scalable. In addition, the system can visualize the geo-name on the map. The work of study also designed, implemented the prototype and empirically verified the validity of the pilot system. Lastly, items to be improved have also been addressed.

Automated Training from Landsat Image for Classification of SPOT-5 and QuickBird Images

  • Kim, Yong-Min;Kim, Yong-Il;Park, Wan-Yong;Eo, Yang-Dam
    • Korean Journal of Remote Sensing
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    • v.26 no.3
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    • pp.317-324
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    • 2010
  • In recent years, many automatic classification approaches have been employed. An automatic classification method can be effective, time-saving and can produce objective results due to the exclusion of operator intervention. This paper proposes a classification method based on automated training for high resolution multispectral images using ancillary data. Generally, it is problematic to automatically classify high resolution images using ancillary data, because of the scale difference between the high resolution image and the ancillary data. In order to overcome this problem, the proposed method utilizes the classification results of a Landsat image as a medium for automatic classification. For the classification of a Landsat image, a maximum likelihood classification is applied to the image, and the attributes of ancillary data are entered as the training data. In the case of a high resolution image, a K-means clustering algorithm, an unsupervised classification, was conducted and the result was compared to the classification results of the Landsat image. Subsequently, the training data of the high resolution image was automatically extracted using regular rules based on a RELATIONAL matrix that shows the relation between the two results. Finally, a high resolution image was classified and updated using the extracted training data. The proposed method was applied to QuickBird and SPOT-5 images of non-accessible areas. The result showed good performance in accuracy assessments. Therefore, we expect that the method can be effectively used to automatically construct thematic maps for non-accessible areas and update areas that do not have any attributes in geographic information system.

Coastline Extraction from Airborne LiDAR Data (항공라이다데이터를 이용한 해안선 추출)

  • Kim Seong-Joon;Lee Im-Pyeong;Kim Yong-Cheol;Cheong Hyun
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2006.04a
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    • pp.457-462
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    • 2006
  • Coastline has been considered as fundamental geographic information of a nation. Recently, the coastlines of higher resolution and accuracy with less update period ever than before are increasingly required. This requirement cannot be easily satisfied with the most traditional methods based on field survey such as leveling or GPS measurements. The newly developed airborne LIDAR system can be used as a promising alternative since it rapidly acquire numerous three-dimensional points densely sampled from the terrain around the coastline. Hence, in this study we developed a nearly automatic method to extract the coastline from LIDAR data and applied it to real data to verify its performance. From the comparison of the extracted coastlines with those from a digital map, we conclude that the proposed method can provide more accurate and precise lines.

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AUTOMATIC ROAD NETWORK EXTRACTION. USING LIDAR RANGE AND INTENSITY DATA

  • Kim, Moon-Gie;Cho, Woo-Sug
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.79-82
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    • 2005
  • Recently the necessity of road data is still being increased in industrial society, so there are many repairing and new constructions of roads at many areas. According to the development of government, city and region, the update and acquisition of road data for GIS (Geographical Information System) is very necessary. In this study, the fusion method with range data(3D Ground Coordinate System Data) and Intensity data in stand alone LiDAR data is used for road extraction and then digital image processing method is applicable. Up to date Intensity data of LiDAR is being studied. This study shows the possibility method for road extraction using Intensity data. Intensity and Range data are acquired at the same time. Therefore LiDAR does not have problems of multi-sensor data fusion method. Also the advantage of intensity data is already geocoded, same scale of real world and can make ortho-photo. Lastly, analysis of quantitative and quality is showed with extracted road image which compare with I: 1,000 digital map.

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