• The Journal of Information Technology and Database
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• v.7 no.1
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• pp.17-26
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• 2000

To provide highly available services in the distributed object system, it is required to support the object group. The state machine approach and primary-backup approach are proposed as two representative approaches for support of object group. The primary-backup approach does not only give merits such as transparency of object group and non-deterministic execution but also require less resource than state machine approach. This paper describes an extension of CORBA that is required to support of the primary-backup object group. In this paper, the state of backup is synchronized with primary through the atomic multicast protocol whenever the request of client is executed at primary. As a result, it does not require message logging and check pointing. The object group of this paper also provides fast response time in case of failure of the primary since it makes primary election unnecessary. And through an extension of IDL, it makes possible to avoid consistency control depending on characteristic of application. A prototype has been implemented and the performance of object group has been compared with a single object invocation.

• Journal of Astronomy and Space Sciences
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• v.35 no.4
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• pp.287-293
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• 2018

This paper presents a satellite relative navigation strategy for formation flying, which chooses an appropriate navigation algorithm according to the operating environment. Not only global positioning system (GPS) measurements, but laser measurements can also be utilized to determine the relative positions of satellites. Laser data is used solely or together with GPS measurements. Numerical simulations were conducted to compare the relative navigation algorithm using only laser data and laser data combined with GPS data. If an accurate direction of laser pointing is estimated, the relative position of satellites can be determined using only laser measurements. If not, the combined algorithm has better performance, and is irrelevant to the precision of the relative angle data between two satellites in spherical coordinates. Within 10 km relative distance between satellites, relative navigation using double difference GPS data makes more precise relative position estimation results. If the simulation results are applied to the relative navigation strategy, the proper algorithm can be chosen, and the relative position of satellites can be estimated precisely in changing mission environments.

• Journal of Korea Multimedia Society
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• v.24 no.4
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• pp.528-537
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• 2021

Face recognition has gained significant notice because of its application in many businesses: security, healthcare, and marketing. In this paper, we will present the recognition method using the combination of correlation filters (CF) and Support Vector Machine (SVM). Firstly, we evaluate the performance and compared four different correlation filters: minimum average correlation energy (MACE), maximum average correlation height (MACH), unconstrained minimum average correlation energy (UMACE), and optimal-tradeoff (OT). Secondly, we propose the machine learning approach by using the OT correlation filter for features extraction and SVM for classification. The numerical results on National Cheng Kung University (NCKU) and Pointing'04 face database show that the proposed method OT-SVM gets higher accuracy in face recognition compared to other machine learning methods. Our approach doesn't require graphics card to train the image. As a result, it could run well on a low hardware system like an embedded system.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.344-358
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• 2022

Text summarization is the task of producing a shorter version of a long document while accurately preserving the main contents of the original text. Abstractive summarization generates novel words and phrases using a language generation method through text transformation and prior-embedded word information. However, newly coined words or out-of-vocabulary words decrease the performance of automatic summarization because they are not pre-trained in the machine learning process. In this study, we demonstrated an improvement in summarization quality through the contextualized embedding of BERT with out-of-vocabulary masking. In addition, explicitly providing precise pointing and an optional copy instruction along with BERT embedding, we achieved an increased accuracy than the baseline model. The recall-based word-generation metric ROUGE-1 score was 55.11 and the word-order-based ROUGE-L score was 39.65.

• Progress in Medical Physics
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• v.33 no.2
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• pp.11-24
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• 2022

X-ray detection has widely been applied in medical diagnostics, security screening, nondestructive testing in the industry, etc. Medical X-ray imaging procedures require digital flat detectors operating with low doses to reduce radiation health risks. Recently, metal halide perovskites (MHPs) have shown great potential in high-performance X-ray detection because of their attractive properties, such as strong X-ray absorption, high mobility-lifetime product, tunable bandgap, low-temperature fabrication, near-unity photoluminescence quantum yields, and fast photoresponse. In this paper, we review and introduce the development status of new perovskite X-ray detectors and imaging, which have emerged as a new promising high-sensitivity X-ray detection technology. We discuss the latest progress and future perspective of MHP-based X-ray detection in medical imaging. Finally, we compare the conventional detection methods with quantum-enhanced detection, pointing out the challenges and perspectives for future research directions toward perovskite-based X-ray applications.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.5
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• pp.490-498
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• 2010

This paper presents an autonomous target tracking approach and technique for transmitting ground control station image periodically for an unmanned aerial vehicle using onboard gimbaled(pan-tilt) camera system. The miniature rotary UAV which was used in this study has a small, high-performance camera, improved target acquisition technique, and autonomous target tracking algorithm. Also in order to stabilize real-time image sequences, image stabilization algorithm was adopted. Finally the target tracking performance was verified through a real flight test.

• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.16-23
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• 2020

This paper describes an alignment algorithm that estimates the initial heading angle of AUVs (Autonomous Underwater Vehicle) for starting navigation in a sea area. In the basic dead reckoning system, the initial orientation of the vehicle is very important. In particular, the initial heading value is an essential factor in determining the performance of the entire navigation system. However, the heading angle of AUVs cannot be measured accurately because the DCS (Digital Compass) corrupted by surrounding magnetic field in pointing true north direction of the absolute global coordinate system (not the same to magnetic north direction). Therefore, we constructed an experimental constraint and designed an algorithm based on extended Kalman filter using only inertial navigation sensors and a GPS (Global Positioning System) receiver basically. The value of sensor covariance was selected by comparing the navigation results with the reference data. The proposed filter estimates the initial heading angle of AUVs for navigation in a sea area and reflects sampling characteristics of each sensor. Finally, we verify the performance of the filter through experiments.

• Journal of The Korean Astronomical Society
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• v.44 no.3
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• pp.81-87
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• 2011

We carry out 100-GHz band test observations with the newly-constructed KVN 21-m radio telescopes in order to evaluate their performance. The three telescopes have similar performance parameters. The pointing accuracies are about 4" rms for the entire sky. The main beam sizes are about 30" (FWHMs), which is nearly the diffraction limit of the telescopes at the observing frequency (97 GHz). The measured aperture and main-beam efficiencies are about 52% and 46%, respectively, for all three telescopes. The estimated moon efficiency is ~84% for the KVN Tamna telescope. The first sidelobes appear 50" (~1.6${\times}$FWHM) from the main beam centers and the levels are on average -14 dB.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.7
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• pp.517-524
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• 2014

Micro-vibration induced by on-board equipments such as fly-wheel and cryogenic cooler with mechanical moving parts affects the image quality of high-resolution observation satellite. Micro-vibration isolation system has been widely used for enhancing the pointing performance of observation satellites. In general, the micro-vibration isolation system requires a launch locking mechanism additionally to guarantee the structural safety of mission payloads supported by the isolation system with low stiffness under launch environment. In this study, we propose a passive launch and on-orbit vibration isolation system using shape memory alloy mesh washers for the micro-vibration isolation of spaceborne compressor, which does not require the additional launch locking mechanism. The basic characteristics of the isolator were measured in static and free vibration tests of the isolator, and a simple equivalent model of the isolator was proposed. The effectiveness of the isolator design in a launch environment was demonstrated through sine vibration, random vibration and shock tests.

• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.240-247
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• 2020

This paper presents a novel knitted data glove system for pattern classification of hand posture. Several experiments were conducted to confirm the performance of the knitted data glove. To find better sensor materials, the knitted data glove was fabricated with stainless-steel yarn and silver-plated yarn as representative conductive yarns, respectively. The result showed that the signal of the knitted data glove made of silver-plated yarn was more stable than that of stainless-steel yarn according as the measurement distance becomes longer. Also, the pattern classification was conducted for the performance verification of the data glove knitted using the silver-plated yarn. The average classification reached at 100% except for the pointing finger posture, and the overall classification accuracy of the knitted data glove was 98.3%. With these results, we expect that the knitted data glove is applied to various robot fields including the human-machine interface.