• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.12 s.115
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• pp.1249-1258
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• 2006

Two-dimensional(2-D) radar images, namely, ISAR images from a maneuvering target include unwanted phase errors due to the target's motion. These phase errors make ISAR images to be blurred. The ISAR autofocus technique is required in order to remove these unwanted phase errors. Unless those unwanted phase errors produced by the target's motion are removed prior to target identification, we cannot expect a reliable target identification performance. In this paper, we use the entropy-based ISAR autofocus technique which consists of two steps: range alignment and phase adjustment. We analyze a relationship between the number of sampling point and a image quality in a range alignment algorithm and also analyze a technique for reducing computation time of the SSA(Stage-by-Stage Approachng) algorithm in a phase adjustment.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.7 no.2
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• pp.41-50
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• 1993

This paper describes an effort to develop a microcomputer-based parameter identification system for three phase and two phase brushless DC motor. Back EMF equation is derived from back EMF waveform of three phase and two phase brushless DC motor. In this paper, a new identification algorithm for the brushless DC motor parameters by Pasek's technique is developed. It is found that Pasek's equation is valid for the brushless DC motor, too. The results obtained clearly shows that it is possible to implement the identification system for the determination of the brushless DC motor parameters. To minimize errors due to the ripple component in the measured armature current, digital averaging firis employed. The whole identification process of signal generation, measuring, parameter determination is fully automated. The use of the propod method in the parameter identifition system shows that the averaged current curve is in excellent agreement with the estimated current curve. Therefore, this close agreement confirms the validity of this technique.

• Applied Microscopy
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• v.36 no.spc1
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• pp.47-56
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• 2006

Improvements are made to existing primitive cell volume measurement method to provide a real-time analysis capability for the phase analysis of nanocrystalline materials. Simplification is introduced in the primitive cell volume calculation leading to fast and reliable method for nano-phase identification and is applied to the phase analysis of Mo-Si-N nanocoating layer. In addition, comparison is made between real-time and film measurements for their accuracy of calculated primitive cell volume values and factors governing the accuracy of the method are determined. About 5% accuracy in primitive cell determination is obtained from camera length calibration and this technique is used to investigate the cell volume variation in WC-TiC core-shell microstructure. In addition to chemical compositional variation in core-shell type structure, primitive cell volume variation reveals additional information on lattice coherency strain across the interface.

• Proceedings of the ESK Conference
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• 1996.10a
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• pp.197-205
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• 1996

Unification of neural network with a hierarchical pattern recognition is presented for recognizing large set of objects. A two-step identification procedure is developed for pattern recognition: coarse and fine identification. The coarse identification is designed for finding a class of object while the fine identification procedure is to identify a specific object. During the training phase a course neural network is trained for clustering larger set of reference objects into a number of groups. For training a fine neural network, expert neural network is also trained to identify a specific object within a group. The presented idea can be interpreted as two step identification. Experimental results are given to verify the proposed methodology.

• The Journal of the Petrological Society of Korea
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• v.9 no.4
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• pp.205-210
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• 2000

Measurements of phase identification and degree of orientation for fine-grained (about 0.3 mm in diameter) minerals in rock samples performed by micro-area X-ray diffractometer.$Al_{2}SiO_{5}$ polymorphs (andalusite, kyanite and sillimanite) were chosen for the measurements and target minerals were existed on thin sections. Micro-area X-ray diffractometer is composed of 3(${\omega}\;{\chi}\;{\phi}$)-circle oscillating goniometer and position sensitive proportional counter (PSPC). $CuK_{\alpha}$ radiation was used as X-ray source and a pin hole ($50\;\mu\textrm{m}$$ in diameter) collimator was selected to focus radiation X-ray onto the target minerals. Phase identification and diffracted X-ray peak indexing were carried out by 3(${\omega}\;{\chi}\;{\phi}$)-circle oscillation measurement. Then, 2(${\omega}\;{\phi}$)-circle oscillation measurement was made for the purpose of searching the prevailing lattice plane of the minerals on thin section surface. Finally, for a selected peak by 2-circle oscillation measurement, X-ray pole figure measurement was executed for the purpose of check the degree of orientation of the single lattice direction and examine its pole distribution. As a result of 3-circle oscillation measurement, it was possible that phase identification among $Al_{2}SiO_{5}$ polymorphs. And from the results of 2-circle oscillation measurement and X-ray pole figure measurement, we recognized that poles of andalusite (122), kyanite (200) and sillimanite (310) lattice plances were well developed with direction normal to each mineral surface plane respectively. Therfore, the measurements used with micro-area X-ray diffractometer in this study will be a useful tool of phase identification and degree of orientation measurement for fine-grained rock forming minerals.

• Journal of the Optical Society of Korea
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• v.4 no.1
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• pp.19-22
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• 2000

A new image encoding and identification scheme is proposed for security verification by us-ing a CGH(computer generated hologram), random phase mask, and a correlation technique. The encrypted image, which is attached to the security product, is made by multiplying a QP- CGH(quadratic phase CGI) with a random phase function. The random phase function plays a key role when the encrypted image is decrypted. The encrypted image can be optically recovered by a 2-f imaging system and automatically verified for personal identification by a 4-f correlation system. Simulation results show the proposed method can be used for both the reconstruction of an original image and the recognition of an encrypted image.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.124-126
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• 2001

A reliable fault type identification (phase selection) plays a very important role in transmission line protection, particularly in Extra High Voltage(EHV) networks. The conventional fault type identification algorithm used the phase difference between positive and negative sequence current excluding load current. But, it is difficult to pick out only fault current since we can not know when a fault occurs and identify the fault type in weak-infeed conditions that dominate zero-sequence current in phase current. The proposed algorithm can identify the accurately fault type using the sum of unit vectors which are calculated by positive-sequence votage and negative-sequence voltage.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.91-102
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• 2002

We need a component-based system to reflect software changes in user's requirements, to implement a system at a rapid speed as well as to efficiently manage the system in a maintenance phase and to easily change software. Moreover, the component-based system has a merit in development cost. However, existing component development methodology for implement of component-based system is inefficient in object identification for component identification. Moreover, the existing component development methodology also fails to provide any method to identify system component. It merely provides procedures and methods to identify business component focused on a whole system domain. In addition, it has another problem that it considerably relies on developer's experiences and intuitions for component identification. Therefore, according to this paper, RUP (Rational Unified Process) is applied from a requirement analysis phase to an object identification phase in order to improve the inefficiency of object identification. In addition, this paper procedures and methods for system component identification, and identifies business components based on the identified system component, rather than on the whole system domain. This paper also provides and applies cohesion metric and coupling metric so as to overcome the problem that component identification depends on developer's intuitions and experiences. Accordingly, the component identification method proposed in this paper, may identify components more effectively based on facility of object identification, functional reusability of components, traceability, and independence of components.

• Proceedings of the Korean Nuclear Society Conference
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• 2004.05a
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• pp.108-108
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• 2004

• Bulletin of the Korean Chemical Society
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• v.13 no.2
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• pp.148-155
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• 1992

Computerized interpretation of vapor phase infrared spectra using a novel expert system approach for spectra/structure correlation for vapor phase spectra is introduced. Rapid identification of aromatic functional groups of components in gaseous mixture can be achieved using this expert system.