• Title/Summary/Keyword: Semi-automatic

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A Study on Development of Labor-saving and Automatic Agricultural Machinery for Onions Harvest (노동생력화 전자동 양파수확용 농기계 개발에 관한 연구)

  • 김인주;박창언;윤복현;김일수
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2003.04a
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    • pp.45-49
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    • 2003
  • According to the rising of national economic level, domestic consumption of vegetables having high additive values is increased continuously due to increased consumption of meat in last decade. These vegetables are produced almost in this country and are limited to import from neighbor countries in due of high transportation expenses for storing in refrigerated container. It is very important to mechanize the harvest work, forming more than 30% for their production cost, in order to cultivate variable vegetables at the same time according to their harvesting seasons. In this state its former harvest methods, with using of human power or semi-automatic harvest, caused to increase their production cost due to high labor cost and low working efficiency.

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Off-Line Programming in the Shipbuilding Industry: Open Architecture and Semi-Automatic Approach

  • Lee Ji-Hyoung;Kim Chang-Sei;Hong Keum-Shik
    • International Journal of Control, Automation, and Systems
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    • v.3 no.1
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    • pp.32-42
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    • 2005
  • In this paper, to improve the efficiency of welding and user convenience in the shipbuilding industry, a PC-based off-line programming (OLP) technique and the development of a robot transfer unit are presented. The developed OLP system is capable of not only robot motion simulations but also automatic generations of a series of robot programs. The strength of the developed OLP system lies in its flexibility in handling the changes of the welding robot's target objects. Moreover, for a precise transfer of the robot to a desired location, an auxiliary mobile platform named a robot-origin-transfer-unit (ROTU) was developed. To enhance the cornering capability of the platform in a narrow area, the developed ROTU is equipped with 2 steering wheels and 1 driving wheel. Both the OLP and the ROTU were field­tested and their performances were proven successful.

Mapping Topic Maps using WordNet ontology (워드넷 온톨로지를 이용한 토픽맵 매핑)

  • Yoo, Woo-Jong;Kim, Jin-Woo;Kwon, Ju-Hum
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.10a
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    • pp.175-177
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    • 2004
  • In this paper, we provide a mechanism to map topics between similar Topic Map ontologies, which enlarge the capacities of current Topic Maps. That is, there is no explicit way to map topics across multiple Topic Maps in current technology. Therefore, our approach provide semi-automatic or automatic mapping of topics between Topic Maps. In order to map the topics, we provide precise definitions of mapping properties and mapping rules.

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Development of Rock Slope Survey and Analysis System using GIS

  • Park, H. J.;Chang, B. S.;Lee, S.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.144-146
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    • 2003
  • Techniques for rock slope management and assessment must be developed for the prevention and mitigation of rock fall hazards. To enable this, the rock discontinuity such as fault and joint data must be surveyed, analysed and managed. For this, the discontinuities were detected by automatic and semi-automatic method using DEM and ortho-rectified image of rock slope and the rock slope analysis and management system was developed using GIS. Using the system, slope locations and discontinuities data were constructed to spatial database. The system is consist of ‘Data Management’, ‘Rock Slope DB’, ‘Basic Information’, ‘Image Processing’, ‘Image Analys ing’, ‘Edit’, ‘View’, ‘Theme’, ‘Graphic’, ‘Window’ and ‘Help’. The system was developed using avenue of ArcView 3.2.

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Approaches for Automatic GCP Extraction and Localization in Airborne SAR Images and Some Test Results

  • Tsay, Jaan-Rong;Liu, Pang-Wei
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.360-362
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    • 2003
  • This paper presents simple feature-based approaches for full- and/or semi-automatic extraction, selection, and localization (center-determination) of ground control points (GCPs) for radargrammetry using airborne synthetic aperture radar (SAR) images. Test results using airborne NASA/JPL TOPSAR images in Taiwan verify that the registration accuracy is about 0.8${\sim}$1.4 pixels. In c.a. 30 minutes, 1500${\sim}$3000 GCPs are extracted and their point centers in a SAR image of about 512 ${\times}$ 512 pixels are determined on a personal computer.

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Application of a Distribution Rainfall-Runoff Model on the Nakdong River Basin

  • Kim, Gwang-Seob;Sun, Mingdong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2012.05a
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    • pp.976-976
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    • 2012
  • The applicability of a distributed rainfall-runoff model for large river basin flood forecasts is analyzed by applying the model to the Nakdong River basin. The spatially explicit hydrologic model was constructed and calibrated by the several storm events. The assimilation of the large scale Nakdong River basin were conducted by calibrating the sub-basin channel outflow, dam discharge in the basin rainfall-runoff model. The applicability of automatic and semi-automatic calibration methods was analyzed for real time calibrations. Further an ensemble distributed rainfall runoff model has been developed to measure the runoff hydrograph generated for any temporally-spatially varied rainfall events, also the runoff of basin can be forecast at any location as well. The results of distributed rainfall-runoff model are very useful for flood managements on the large scale basins. That offer facile, realistic management method for the avoiding the potential flooding impacts and provide a reference for the construct and developing of flood control facilities.

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Design and application of effective data extraction technique from Web databases (웹 기반 데이터베이스로부터의 유용한 데이터 추출 기법의 설계 및 응용)

  • Hwang, Doo-Sung
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.6 no.4
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    • pp.309-314
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    • 2005
  • This paper analyzes techniques that extract objective information from distributed web databases for bioinformatics based on relationship among information. Moreover, we discuss the design and implementation of a method for knowledge enhancement in respect of protein information. Web data extractor can be constructed by using a manual, semi-automatic, or automatic way. Data extractor generally makes use of identifiers in order to search and extract targeting information from a specified web page. This paper presents a design and implementation for the protein databases of an organism by utilizing web data extraction techniques.

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A Study on the Safety Management of UAS by Analyzing Its Accident Factors (무인항공기시스템 사고요인 분석을 통한 안전 운용방안 고찰)

  • Wontae Park
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.31 no.1
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    • pp.1-10
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    • 2023
  • This study investigated the accident cases of the U.S. Air Force and the R.O.K. Army. It analyzed the accident factors of the unmanned aircraft system using case analysis on unmanned aircraft system operators of the R.O.K. Air Force. Following the analysis this paper suggested safety operation plans for the R.O.K. Air Force. The risk factors of unmanned aircraft system were summarized by collecting and analyzing accident cases of unmanned aircraft system by the U.S. Air Force, collecting and analyzing accident risk factors of RQ-4 operators of the R.O.K. Air Force. Through the analyzed risk factors, a safety operation plan for the semi-automatic unmanned aircraft system and the fully automatic unmanned aircraft system was presented.

Building a Sentential Model for Automatic Prosody Evaluation

  • Yoon, Kyu-Chul
    • Phonetics and Speech Sciences
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    • v.1 no.4
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    • pp.47-59
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    • 2009
  • The purpose of this paper is to propose an automatic evaluation technique for the prosodic aspect of an English sentence uttered by Korean speakers learning English. The underlying hypothesis is that the consistency of the manual prosody scoring is reflected in an imaginary space of prosody evaluation model constructed out of the three physical properties of the prosody considered in this paper, namely: the fundamental frequency (F0) contour, the intensity contour, and the segmental durations. The evaluation proceeds first by building a prosody evaluation model for the sentence. For the creation of the model, utterances from native speakers of English and Korean learners for the target sentence are manually scored by either native teachers of English or Korean phoneticians in terms of their prosody. Multiple native utterances from the manual scoring are selected as the "model" native utterances against which all the other Korean learners' utterances as well as the model utterances themselves can be semi-automatically evaluated by comparison in terms of the three prosodic aspects [7]. Each learner utterance, when compared to the multiple model native utterances, produces multiple coordinates in a three-dimensional space of prosody evaluation, each axis of which corresponds to the three prosodic aspects. The 3D coordinates from all the comparisons form a prosody evaluation model for the particular sentence and the associated manual scores can display regions of particular scores. The model can then be used as a predictive model against which other Korean utterances of the target sentence can be evaluated. The model from a Korean phonetician appears to support the hypothesis.

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Machine Learning Based Automatic Categorization Model for Text Lines in Invoice Documents

  • Shin, Hyun-Kyung
    • Journal of Korea Multimedia Society
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    • v.13 no.12
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    • pp.1786-1797
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    • 2010
  • Automatic understanding of contents in document image is a very hard problem due to involvement with mathematically challenging problems originated mainly from the over-determined system induced by document segmentation process. In both academic and industrial areas, there have been incessant and various efforts to improve core parts of content retrieval technologies by the means of separating out segmentation related issues using semi-structured document, e.g., invoice,. In this paper we proposed classification models for text lines on invoice document in which text lines were clustered into the five categories in accordance with their contents: purchase order header, invoice header, summary header, surcharge header, purchase items. Our investigation was concentrated on the performance of machine learning based models in aspect of linear-discriminant-analysis (LDA) and non-LDA (logic based). In the group of LDA, na$\"{\i}$ve baysian, k-nearest neighbor, and SVM were used, in the group of non LDA, decision tree, random forest, and boost were used. We described the details of feature vector construction and the selection processes of the model and the parameter including training and validation. We also presented the experimental results of comparison on training/classification error levels for the models employed.