• Title/Summary/Keyword: Generate Data

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Study on Mobile Meteorological Information Services for Urban Area

  • Choi, Jin-Oh
    • Journal of information and communication convergence engineering
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    • v.9 no.1
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    • pp.64-68
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    • 2011
  • On the limited urban area, precise measurement of meteorological data is not easy for the cost problem. The facilities collecting the data require high installment costs. The mobile sources can be a solution in city region. For example, a public bus on which some meteorological sensors are installed can act as moving information gathering station. The information is gathered on a server and aggregated to generate useful information for smart phone application. To implement the services, several obstacles are exists. This paper studies on a design of this mobile meteorological information service system for urban area.

Force Feedback System of Telepresence Robot for Remote Operation (텔레프레전스 로봇의 원격 조작을 위한 포스 피드백 시스템)

  • Hwang, Jung-Uk;Park, Tae-Hyoung
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.4
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    • pp.586-591
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    • 2015
  • This paper proposes a force feedback system of telepresence robot for remote operation. The ultrasonic sensors attached at the robot detect the obstacles, and generate the force to the operation joystick. In order to consider the network delay, we developed the fuzzy control system using ultrasonic data and robot speed. The method to calculate the force vector from the ultrasonic data is also presented to operate the robot more accurately. The simulation and experimental results are presented to verify the safe and accurate operation of the proposed system.

Auto-Generation of Diagnosis Program of PLC-based Automobile Body Assembly Line for Safety Monitoring (PLC기반 차체조립라인의 안전감시를 위한 진단프로그램 생성에 관한 연구)

  • Park, Chang-Mok
    • Journal of the Korea Safety Management & Science
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    • v.12 no.2
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    • pp.65-73
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    • 2010
  • In an automated industry PLC plays a central role to control the manufacturing system. Therefore, fault free operation of PLC controlled manufacturing system is essential in order to maximize a firm's productivity. On the contrary, distributed nature of manufacturing system and growing complexity of the PLC programs presented a challenging task of designing a rapid fault finding system for an uninterrupted process operation. Hence, designing an intelligent monitoring, and diagnosis system is needed for smooth functioning of the operation process. In this paper, we propose a method to continuously acquire a stream of PLC signal data from the normal operational PLC-based manufacturing system and to generate diagnosis model from the observed PLC signal data. Consequently, the generated diagnosis model is used for distinguish the possible abnormalities of manufacturing system. To verify the proposed method, we provided a suitable case study of an assembly line.

Secondary Analysis: Focusing on Qualitative Research (이차분석 : 질적연구를 중심으로)

  • 이명선
    • Journal of Korean Academy of Nursing
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    • v.34 no.1
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    • pp.35-44
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    • 2004
  • Purpose: This article explored issues arising from secondary analysis of qualitative data and analyzed the results of qualitative secondary analysis studies published in English, focusing on the methodological aspects. Method: A total of 29 studies were identified as qualitative secondary analysis studies, retrieving from the CINAHL database from 1982 to 3rd week of April 2003. These studies were analyzed by publication year, research method, and type of approach to secondary analysis. Result: The year that the qualitative secondary analysis study first published was 1992 and the number of the studies using secondary analysis has increased after the middle of 1990s. Grounded theory was the one the most frequently used(n=11, 37.9%) and phenomenological study the second most(n=6, 20.7%). In terms of types of approach, fifteen studies(51.7%) focused on the specific concepts that were not explored in the primary studies. Nine(31.0%) focused on the specific types of participants. Six were aimed to integrate contexts or perspectives to generate more general and abstract analysis of qualitative data. Conclusion: The results of this article will stimulate methodological discussion of qualitative secondary analysis and activate qualitative studies using secondary analysis.

Generation of 3D STEP Model from 2D Drawings Using Feature Definition of Ship Structure (선체구조 특징형상 정의에 의한 2D 도면에서 3D STEP 선체 모델의 생성)

  • 황호진;한순흥;김용대
    • Korean Journal of Computational Design and Engineering
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    • v.8 no.2
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    • pp.122-132
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    • 2003
  • STEP AP218 has a standard schema to represent the structural model of a midship section. While it helps to exchange ship structural models among heterogeneous automation systems, most shipyards and classification societies still exchange information using 2D paper drawings. We propose a feature parameter input method to generate a 3D STEP model of a ship structure from 2D drawings. We have analyzed the ship structure information contained in 2D drawings and have defined a data model to express the contents of the drawing. We also developed a QUI for the feature parameter input. To translate 2D information extracted from the drawing into a STEP AP2l8 model, we have developed a shape generation library, and generated the 3D ship model through this library. The generated 3D STEP model of a ship structure can be used to exchange information between design departments in a shipyard as well as between classification societies and shipyards.

A Two-Phase Approach of Progressive Mesh Reconstruction from Unorganized Point Clouds

  • Zhang, Hongxin;Liu, Hua;Hua, Wei;Bao, Hujun
    • International Journal of CAD/CAM
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    • v.7 no.1
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    • pp.103-112
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    • 2007
  • This paper presents a practical approach for surface reconstruction from unoriented point clouds. Instead of estimating local surface orientation, we first generate a set of depth images from the input point clouds, and a coarse mesh is then generated based on them by space carving techniques. The resultant mesh is progressively refined by local mesh refinement and optimization according to surface distance measure. A manifold mesh approximating the input points within an given tolerance is finally obtained. Our approach is easy to implement, but has the ability to outputs high quality meshes in different resolutions. We show that the proposed approach is not sensitive to several types of data disfigurement and is able to reconstruct models robustly from variance input data.

Experimental Study for Higher Seismic Performance of Confined Masonry Wall System (주변이 RC로 구속된 조적조 벽체의 내진성능향상에 관한 실험적 연구)

  • Kim Kyong-Tae;Seo Soo-Yeon;Yoon Seung-Joe;Yoshimura Koji;Sung Ki-Tae
    • Proceedings of the Korea Concrete Institute Conference
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    • 2004.11a
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    • pp.5-8
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    • 2004
  • In order to investigate the effect of the height of application point of lateral loads and reinforcing steel bars in walls and columns in improving the seismic behavior of confined concrete block masonry walls, an experimental research program is conducted. A total of four one-half scale specimens are tested under repeated lateral loads. Specimens are tested to failure with increasing maximum lateral drifts while a vertical axial load was applied and maintained constant. The constant vertical axial stresses applied are 0, 0.84 and 1.80MPa, while the amount of reinforcements in horizontal and vertical directions are $0\%,\;0.08\%\;and\;0.18\%$ respectively. Test results obtained for each specimen include cracking patterns, load-deflection data, and strains in reinforcement and walls in critical locations. Analysis of test data showed that above parameters generate a considerable effect on the seismic performance of confined concrete block masonry walls.

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Hull Form Generation by Using Fuzzy Model

  • Lee, Yeon-Seung-;Jeong, Seong-Jae;Kim, Su-Young-;Geuntaek-Kang
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1234-1237
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    • 1993
  • This paper discusses the hull form generation from fuzzy model constructed with actual ship data using fuzzy concept. SAC, which is the most important factor in the hull form generation, is expressed by a fuzzy model describing the relationships among design parameters, which have a great influence on SAC, through model identification process with the actual ship data and design parameters. Then, we can infer the SAC of an aimed ship through the process of fuzzy inference and decide the offset of a front view by making the fuzzy model between SAC and offset as well. In conclusion, this paper makes a step forward from the geometrical definition, which has been used for hull form generation so far, to direct mathematical formulae about the relationship between design parameters and offset. So, if the design parameters are given, we can generate the hull form taking such properties into account.

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Comparison of Latin Hypercube Sampling and Simple Random Sampling Applied to Neural Network Modeling of HfO2 Thin Film Fabrication

  • Lee, Jung-Hwan;Ko, Young-Don;Yun, Il-Gu;Han, Kyong-Hee
    • Transactions on Electrical and Electronic Materials
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    • v.7 no.4
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    • pp.210-214
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    • 2006
  • In this paper, two sampling methods which are Latin hypercube sampling (LHS) and simple random sampling were. compared to improve the modeling speed of neural network model. Sampling method was used to generate initial weights and bias set. Electrical characteristic data for $HfO_2$ thin film was used as modeling data. 10 initial parameter sets which are initial weights and bias sets were generated using LHS and simple random sampling, respectively. Modeling was performed with generated initial parameters and measured epoch number. The other network parameters were fixed. The iterative 20 minimum epoch numbers for LHS and simple random sampling were analyzed by nonparametric method because of their nonnormality.

Multi-Sensor Signal based Situation Recognition with Bayesian Networks

  • Kim, Jin-Pyung;Jang, Gyu-Jin;Jung, Jae-Young;Kim, Moon-Hyun
    • Journal of Electrical Engineering and Technology
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    • v.9 no.3
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    • pp.1051-1059
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    • 2014
  • In this paper, we propose an intelligent situation recognition model by collecting and analyzing multiple sensor signals. Multiple sensor signals are collected for fixed time window. A training set of collected sensor data for each situation is provided to K2-learning algorithm to generate Bayesian networks representing causal relationship between sensors for the situation. Statistical characteristics of sensor values and topological characteristics of generated graphs are learned for each situation. A neural network is designed to classify the current situation based on the extracted features from collected multiple sensor values. The proposed method is implemented and tested with UCI machine learning repository data.