• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.353-356
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• 2005

In Taiwan, there are more the one hundred GPS tracking stations maintained by Ministry of the Interior (MOI), Academia Sinica, Central Weather Bureau and Central Geological Survey. In the further, they may be instead of the GPS controlling points after giving the lawful status. In other words, the engineers don't need to survey on the reference points when they are surveying in the field. They only need to download the GPS data via internet and process the observations in their company. The precise coordinates of the unknown points will be obtained. Therefore, the data qualities of the tracking stations are more and more important. In this study, six data quality indexes were adopted as follows: observations, cycle slips, multipath on L1, multipath on L2, clock offset and frequency stability. Besides, the relationships of the indexes and the positioning precision were found. The frequency stability of GPS receiver is the most important index, the cycle slip is the second index and the mutlipath is the third index. According to the results, the auto-analytical system of GPS data quality was established and the tracking stations were monitored. When the receiver got some problem or the station's environment changed, we hope to find and resolve the problems earlier to make sure the high data quality of the tracking stations. Moreover, we try to design a data quality verification to help users and let the engineers have more and more confidence when they use the data of GPS tracking stations.

• Journal of Astronomy and Space Sciences
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• v.5 no.1
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• pp.31-43
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• 1988

The differential correction process determining osculating orbital elements as correct as possible at a given instant of time from tracking data of artificial satellite was accomplished. Preliminary orbital elements were used as an initial value of the differential correction procedure and iterated until the residual of real observation (O) and computed observation(C) was minimized. Tracking satellite was NOAA-9 or TIROS-N series. Two types of tracking data were prediction data precomputed from mean orbital elements of TBUS and real data obtained from tracking 1.70 GHz HRPT signal of NOAA-9 using 5 meter auto-track antenna in Radio Research Laboratory. Accrding to thacking data either Gause method or Herrick-Gibbs method was applied to preliminary orbit determination. In the differential correction stage we used both of the Escobal(1975)'s analytical method and numerical method using f, g series for the comparision. The results between analytical and numerical ones are nearly consistent. And the differentially corrected orbit converged to the same value in spite of the differences between preliminary orbits of each time span.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.5
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• pp.522-534
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• 2002

In this paper, we propose a new object tracking system using stereo images to improve the performance of the automatic object tracking system. The existing object tracking system has optimum characteristics, but it requires a lot of computation. In the case of the image with a single eye, the system is difficult to estimate and track for the various transformation of the object. Because the stereo image by both eyes is difficult to estimate the translation and the rotation, this paper deals with the tracking method, which has the ability to track the image for translation for real time, with block matching algorithm in order to decrease the calculation. The experimental results demonstrate the usefulness of proposed system with the recognition rate of 88% in the rotation, 89% in the translation, 88% in various image, and with the mean rate of 88.3%.

• Journal of Digital Contents Society
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• v.13 no.2
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• pp.159-167
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• 2012

Eye tracking technology tracks human eyes movements to understand user's intention. This technology has been improving slowly and should be used for a variety of occasions now. For example, it enables persons with disabilities to operate a computer with their eyes. This article will show a typical implementation of an eye tracking system for persons with disabilities, after introducing the design principles and specific implementation details of an eye tracking system. The article discussed the realization of self-adapting regulation algorithm in detail. The self-adapting algorithm is based on feedback signal controlling the lens movements to realize automatic focus, and to get a clear eyes image. This CCD camera automatic focusing method has self-adapting capacity for changes of light intensity on the external environment. It also avoids the trouble of manual adjustment and improves the accuracy of the adjustment.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.421-433
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• 2006

This paper proposes a method to insert virtual objects into a real video stream based on feature tracking and camera pose estimation from a set of single-camera video frames. To insert or modify 3D shapes to target video frames, the transformation from the 3D objects to the projection of the objects onto the video frames should be revealed. It is shown that, without a camera calibration process, the 3D reconstruction is possible using multiple images from a single camera under the fixed internal camera parameters. The proposed approach is based on the simplification of the camera matrix of intrinsic parameters and the use of projective geometry. The method is particularly useful for augmented reality applications to insert or modify models to a real video stream. The proposed method is based on a linear parameter estimation approach for the auto-calibration step and it enhances the stability and reduces the execution time. Several experimental results are presented on real-world video streams, demonstrating the usefulness of our method for the augmented reality applications.

• Journal of the Korean Society of Marine Environment & Safety
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• v.12 no.2 s.25
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• pp.151-155
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• 2006

In these days, welding is the most commonly used metallic connection technology and also is the fundamental production technology of the modem industrial, which is used in various areas of the industrial fields, such as shipbuilding, automobiles, airplanes and plant facilities. However welding process produces strong light, electric currents, and fume gases etc., and the welding automation is not so easy compared to the other works of manufacturing industries which produce the standardized products in large quantities. So it is difficult to weld and detect the all kinds of seams automatically by a specific sensor. In this paper the sensor applying strain gauges is used to detect the seams of triangular wave form. With the auto carriage having the sensor we proposed the experiment to weld and track the seam automatically.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.510-519
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• 2020

Within an intelligent automated cyber-physical system, the realization of the autonomous mechanism for data collection, data integration, and data analysis plays a critical role in the design, development, operation, and maintenance of such a system. This construct is particularly vital for fault-tolerant route-finding systems that rely on the imprecise GPS location of the vehicles to properly operate, timely plan, and continuously produce informative feedback to the user. More essentially, the integration of digital twins with cyber-physical route-finding systems has been overlooked in intelligent transportation services with the capacity to construct the network routes solely from the locations of the operating vehicles. To address this limitation, the present study proposes a conceptual architecture that employs digital twin to autonomously maintain, update, and manage intelligent transportation systems. This virtual management simulation can improve the accuracy of time-of-arrival prediction based on auto-generated routes on which the vehicle's real-time location is mapped. To that end, first, an intelligent transportation system was developed based on two primary mechanisms: 1) an automated route finding process in which predictive data-driven models (i.e., regularized least-squares regression) can elicit the geometry and direction of the routes of the transportation network from the cloud of geotagged data points of the operating vehicles and 2) an intelligent mapping process capable of accurately locating the vehicles on the map whereby their arrival times to any point on the route can be estimated. Afterward, the digital representations of the physical entities (i.e., vehicles and routes) were simulated based on the auto-generated routes and the vehicles' locations in near-real-time. Finally, the feasibility and usability of the presented conceptual framework were evaluated through the comparison between the primary characteristics of the physical entities with their digital representations. The proposed architecture can be used by the vehicle-tracking applications dependent on geotagged data for digital mapping and location tracking of vehicles under a systematic comparison and simulation cyber-physical system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.63-68
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• 2021

Recently there is sharply increasing interest in watching and creating video contents such as YouTube. However, creating such video contents without privacy protection technique can expose other people in the background in public, which is consequently violating their privacy rights. This paper seeks to remedy these problems and proposes a technique that identifies faces and protecting portrait rights by blurring the face. The key contribution of this paper lies on our deep-learning technique with low detection error and high computation that allow to protect portrait rights in real-time videos. To reduce errors, an efficient tracking algorithm was used in this system with face detection and face recognition algorithm. This paper compares the performance of the proposed system with and without the tracking algorithm. We believe this system can be used wherever the video is used.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.1 s.173
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• pp.7-15
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• 2000

This paper suggests an auto-tuning I'll) control algorithm that uses the advantage of PID controller and improves the system performance. The PID gains being designed by th- conventional method are tuned through the plant parameter estimation. The Extended Kalman Filter is used for the estimation. It works as an observer and noise filter. Moreover, as the plant state and the uncertain parameter could be estimated simultaneously, the proposed algorithm is very useful in the tracking control of a system with uncertain parameter. The auto-tuning I'll) controller could maintain the system performance in the case that the plant parameters are uncertain or varying. The proposed control algorithm requires a correct estimation of the plant parameter. The controller stability and the performance is considered through the stability criteria and a servo motor model. The Kalman filter estimates the most sensitive plant parameter, which is determined by the sensitivity analysis.