• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.3
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• pp.210-216
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• 2006

In the rule based modeling, data partitioning plays crucial role be cause partitioned sub data set implies particular information of the given data set or system. In this paper, we present an empirical study result of the data pattern estimation to find underlying data patterns of the given data. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). In each sequence, the average value of the sum of all inter-distance between centroid and data point. In the sequel, compute the derivation of the weighted average distance to observe a pattern distribution. For the final step, after overall clustering process is completed, weighted average distance value is applied to estimate range of the number of clusters in given dataset. The proposed estimation method and its result are considered with the use of FCM demo data set in MATLAB fuzzy logic toolbox and Box and Jenkins's gas furnace data.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.5
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• pp.199-204
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• 2006

To develop a safety-critical network in nuclear power plants that puts more stringent requirements than the competitive commercial ones do, we establish four design criteria - deterministic communication, explicit separation/isolation structure, reliability, verification & validation. According to those design criteria, the fundamental design elements are chosen as follows - a star topology, point-to-point physical link, connection-oriented link control and fixed allocation access control. After analyzing the design elements, we also build a communication architecture with TDM (Time Division Multiplexing) bus switching scheme. Finally, We develop a DDCNet (Deterministic Data Communication Network) based on the established architecture. The DDCNet is composed of 64 nodes and guarantees the transmission bandwidth of 10Mbps and the delay of 10 msec for each node. It turns out that the DDCNet satisfies the aforementioned design criteria and can be adequately utilized for our purpose.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.963-972
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• 2007

When a control chart signals that a special cause is present, process engineers must initiate a search for and an identification of the special cause. Knowing the time of the process change could lead to identify the special cause more quickly, and to take the appropriate actions immediately to improve quality. In this paper, we propose the maximum likelihood estimator (MLE) for the process change point when a control chart is used in monitoring the parameters of a process in which the observations can be modeled as a first-order autoregressive(AR(1)) process plus an additional random error.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.94.4-94
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• 2002

Traditional control systems that consist of sensors, actuators and a controller centralized and connected with point-to-point links, have become distributed because of their performance limits and maintenance problems. Sensors and actuators are changed to smart devices having a processor and these devices and controllers are connected with fieldbuses such as Profibus, FIP, CAN, LonWorks and so on. Because they are distributed, it takes any delay to transmit data from sensor to controller and data from controller to actuator according to network characteristic. Also, the execution times of tasks in a node are not regular and depend on the node characteristic and the number of tasks and so on...

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.303-308
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• 2004

The acquisition of many control points for SAR data processing is very difficult and time_consuming steps. For resolving the problem about control points, this paper describes satellite orbit refinement method using minimum control point. Accuracy of geocoding according to distribution and number of control points are analyzed and geocoded RADARSAT image was produced in the paper.

• Journal of Biosystems Engineering
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• v.18 no.4
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• pp.328-343
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• 1993

To control depth of tractor implement, an automatic depth control system based upon microcomputer was developed. This system consists of data aquisition system to measure and to record travel speed, draft and depth of the implement, hydraulic system to control the implement depth and 3-point hitch to attach the implement. Program, written in C language, was able to select position control, draft control and mixed control. To analyze parameters affecting this system, the performance of the system was evaluated through use of computer simulation and verified in soil bin experiments. 3-point hitch was lifted by hydraulic pressure and lowered by implement weight. Dead band was one of the important factors which affect the stability and the accuracy of the system. The system became unstable when the flow rate was increased or when the dead band was decreased. The position control mode with on-off control showed the great ability to control the implement at the given plowing depth. With the draft control, the tractor load could be reduced, however the plowing depth was changed unexpectedly when the soil was hard and inconsistent. The mixed control could improve the performance of the system to maintain the plowing depth without overload of the tractor.

• Journal of the Korean Graphic Arts Communication Society
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• v.4 no.1
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• pp.27-35
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• 1986

Following results about Y,M,C Mask are obtained by the Indirect-Screen Color Separation Method. We make use of experimental system which are in use for the student education. In the Camera-Back Method of reflection copy, the results are summerized as follows.

• Korean Journal of Computational Design and Engineering
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• v.6 no.2
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• pp.69-77
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• 2001

This paper describes a method of calculating the feedrate for the constant cutting speed at a CL-point in 5-axis machining. Unlike 3-axis machining, 5-axis machining has the flexibility of the tool motions due to two rotation axes. But the feedrate at joint space differs from the feedrate at a tool tip(the CL-point) of the 3D Euclidean space for the tool motions. The proposed algorithm adjusts the feedrate based on 5-axis NC data, the kinematics of a machine, and the tool length. The following calculations is processed for each NC block to generate the new feedrate; 1) calculating the moving distance at the CL-point, 2) calculating the moving time by the given feedrate, 3) calculating the feedrate of each axis, 4) getting the new feedrate. The proposed algorithm was applied to a 5-axis machine which had a tilting spindle and a rotary table. Totally, the result of the algorithm reduced the machining time and smoothed the cutting-load by the constant cutting speed at the CL-point.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.965-971
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• 2015

This paper suggests a feature point-based Iterative Closest Point (ICP) algorithm to compensate for the disparity error in building a two-dimensional map. The ICP algorithm is a typical algorithm for matching a common object in two different images. In the process of building a two-dimensional map using the laser scanner data, warping and distortions exist in the map because of the disparity between the two sensor values. The ICP algorithm has been utilized to reduce the disparity error in matching the scanned line data. For this matching process in the conventional ICP algorithm, pre-known reference data are required. Since the proposed algorithm extracts characteristic points from laser-scanned data, reference data are not required for the matching. The laser scanner starts from the right side of the mobile robot and ends at the left side, which causes disparity in the scanned line data. By finding the matching points between two consecutive frame images, the motion vector of the mobile robot can be obtained. Therefore, the disparity error can be minimized by compensating for the motion vector caused by the mobile robot motion. The validity of the proposed algorithm has been verified by comparing the proposed algorithm in terms of map-building accuracy to conventional ICP algorithm real experiments.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1013-1025
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• 2020

Unmanned Aerial Vehicle (UAV) platform is being widely used in disaster monitoring and smart city, having the advantage of being able to quickly acquire images in small areas at a low cost. Ground Control Points (GCPs) for positioning UAV images are essential to acquire cm-level accuracy when producing UAV-based orthoimages and Digital Surface Model (DSM). However, the on-site acquisition of GCPs takes considerable manpower and time. This research aims to provide an efficient and accurate way to replace the on-site GNSS surveying with three different sources of geospatial data. The three geospatial data used in this study is as follows; 1) 25 cm aerial orthoimages, and Digital Elevation Model (DEM) based on 1:1000 digital topographic map, 2) point cloud data acquired by Mobile Mapping System (MMS), and 3) hybrid point cloud data created by merging MMS data with UAV data. For each dataset a three-dimensional positional accuracy analysis of UAV-based orthoimage and DSM was performed by comparing differences in three-dimensional coordinates of independent check point obtained with those of the RTK-GNSS survey. The result shows the third case, in which MMS data and UAV data combined, to be the most accurate, showing an RMSE accuracy of 8.9 cm in horizontal and 24.5 cm in vertical, respectively. In addition, it has been shown that the distribution of geospatial GCPs has more sensitive on the vertical accuracy than on horizontal accuracy.