• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.359-360
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• 2009

In this study, we propose a practical method to improve the clarity and the period of the beat in a Korean bell. Proper beating in vibration and sound is very important feature in Korean bell. An equivalent ring theory is applied and finite element analysis is performed to determine the condition of the asymmetry of the bell. The clearity and the period of the beat are improved by attaching a counter mass or decreasing local thickness. This paper shows that the improved the attaching a counter mass or decreasing local thickness. This paper of the beat are improved by attaching a counter mass or decreasing local thickness. This paper shows that the amount and position of the local variation for the required beat condition can be predicted by using the equivalent model, The predicted results are verified by the experiment.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.95-100
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• 2017

In this paper, we propose a zone based ad hoc network construction scheme which support ad hoc path between nodes in local IoT networks consisting of IoT devices with the constrained feature, such as low power, the limited transmission rate and low computing capacity. Recently, the various routing protocols have been studied to support ad hoc networking of local IoT environments. This is, because basis RPL protocol is deigned to be used for the connecting service with Internet through gateway, ad hoc path between nodes in local IoT networks is not supported in basis RPL protocol. Thus, in this paper, the proposed routing scheme provides both ad hoc path and Infra path through gateway, supporting basis RPL protocol simultaneously. Through simulation, we show that the proposed routing scheme with zone based path selection scheme improves the performance of the success rate of end-to-end data transmission and the end-to-end delay, compared to basis RPL protocol.

• Nuclear Engineering and Technology
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• v.41 no.6
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• pp.807-812
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• 2009

An ICRF discharge cleaning and a fast wave electron heating experiment were performed. For automated operation and providing the diagnostics of the ICRF system, the ICRF local network was designed and implemented. This internal network provides monitoring, RF protection, remote control, and RF diagnostics. All the functions of the control system were realized by customized DSP units. The DSP units were tied by a local network in parallel. Owing to the distributed feature of the control system, the ICRF local control system is quite flexible to maintain. Developing the subsystem is a more effective approach compared to developing a large controller that governs the entire system. During the first experimental campaign of the KSTAR tokamak, the control system operated as expected without any major problems that would affect the tokamak operation. The transmitter was protected from harmful over-voltage events through reliable operation of the system.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1264-1274
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• 2015

Human action recognition received many interest in the computer vision community. Most of the existing methods focus on either construct robust descriptor from the temporal domain, or computational method to exploit the discriminative power of the descriptor. In this paper we explore the idea of using local action attributes to form an action descriptor, where an action is no longer characterized with the motion changes in the temporal domain but the local semantic description of the action. We propose an novel framework where introduces local action attributes to represent an action for the final human action categorization. The local action attributes are defined for each body part which are independent from the global action. The resulting attribute descriptor is used to jointly model human action to achieve robust performance. In addition, we conduct some study on the impact of using body local and global low-level feature for the aforementioned attributes. Experiments on the KTH dataset and the MV-TJU dataset show that our local action attribute based descriptor improve action recognition performance.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.303-310
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• 2007

Named Entity Recognition (NER) is always limited by its lower recall resulting from the asymmetric data distribution where the NONE class dominates the entity classes. This paper presents an approach that exploits non-local information to improve the NER recall. Several kinds of non-local features encoding entity token occurrence, entity boundary and entity class are explored under Conditional Random Fields (CRFs) framework. Experiments on SIGHAN 2006 MSRA (CityU) corpus indicate that non-local features can effectively enhance the recall of the state-of-the-art NER systems. Incorporating the non-local features into the NER systems using local features alone, our best system achieves a 23.56% (25.26%) relative error reduction on the recall and 17.10% (11.36%) relative error reduction on the F1 score; the improved F1 score 89.38% (90.09%) is significantly superior to the best NER system with F1 of 86.51% (89.03%) participated in the closed track.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.143-151
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• 2012

A new data-driven method for the design of a blind modulation frequency filter that suppresses the slow-varying noise components is proposed. The proposed method is based on the temporal local decorrelation of the feature vector sequence, and is done on an utterance-by-utterance basis. Although the conventional modulation frequency filtering approaches the same form regardless of the task and environment conditions, the proposed method can provide an adaptive modulation frequency filter that outperforms conventional methods for each utterance. In addition, the method ultimately performs channel normalization in a feature domain with applications to log-spectral parameters. The performance was evaluated by speaker-independent isolated-word recognition experiments under additive noise environments. The proposed method achieved outstanding improvement for speech recognition in environments with significant noise and was also effective in a range of feature representations.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.137-140
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• 1996

Finding line segments in an intensity image has been one of the most fundamental issues in computer vision. In complex scenes, it is hard to detect the locations of point features. Line features are more robust in providing greater positional accuracy. In this paper we present a robust "line features extraction" algorithm which extracts line feature in a single pass without using any assumptions and constraints. Our algorithm consists of five steps: (1) edge scanning, (2) edge normalization, (3) line-blob extraction, (4) line-feature computation, and (5) line linking. By using edge scanning, the computational complexity due to too many edge pixels is drastically reduced. Edge normalization improves the local quantization error induced from the gradient space partitioning and minimizes perturbations on edge orientation. We also analyze the effects of edge processing, and the least squares-based method and the principal axis-based method on the computation of line orientation. We show its efficiency with some real images.al images.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.365-370
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• 1997

In this paper we suggest a development of surface defect inspection algorithms for cold mill strip using tree structure. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment, co-occurrence matrix, histogram-ratio features are calculated. The histogram-ratio feature is taken from the gray-level image. For the defect classification, we suggest a tree structure of which nodes are multilayer neural network clasifiers. The proposed algorithm reduced error rate comparing to one stage structure.

• Journal of The Korea Institute of Healthcare Architecture
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• v.14 no.2
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• pp.25-34
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• 2008

The purpose of this study was to spatial organization feature and area composition of the over 500beds general hospital that will be expected construct in Seoul, Gyeonggi-do area after 2000year. From this study, we can suggest architectural planning for the efficiency operating of emergency medical facilities that can be used as preliminary data. The Spatial organization of emergency medical facilities are categorize into 4 session as medical examination and treatment, diagonosticradiology, staff, public and the others. We can find spatial organization system and area composition that compare area composition of 6 hospital the subject of research in a emergency medical facilities. The result of this study were as follows : spatial distribution of its field, grasping of spatial organization factor and recognize its merits and demerits should be researched in advance. Through this kind of recognizing emergency system, realistic medical local and condition architectural planning for spatial organization will be operate.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.468-472
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• 2004

This paper presents an intelligent iris recognition system which consists of quality check, iris localization, feature extraction, and verification. For the quality check, the local statistics on the pupil boundary is used. Gaussian mixture model is used to segment and localized the iris region. The feature extraction method is based on an optimal waveform simplification. For the verification, we use an intelligent variable threshold.