• Title/Summary/Keyword: Instrumentation Pattern

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An Analysis of Instrumentation Radar's Beacon Tracking Performance Considering a Target Attitude (표적의 자세 변화를 고려한 계측 레이더의 비콘 추적 성능 분석)

  • Ryu, Chung-Ho;Ye, Sung-Hyuck;Hwang, Gyu-Hwan;Seo, Il-Hwan
    • Journal of the Korea Institute of Military Science and Technology
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    • v.13 no.4
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    • pp.561-568
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    • 2010
  • Instrumentation radar in a test range has an important role to measure target's TSPI(time, space, position, information). It is well known that it tracks a target stably using a beacon mode. But it may fail to track a target in a certain region using a beacon mode. In this paper, we modeled a simple missile shape similar to ATCMS with two beacon antenna and analyzed an antenna radiation pattern using MLFMM(Multi Level Fast Multipole Method) method. Using the analyzed result of the radiation pattern of the antenna and the attitude data of target, we simulated beacon tracking performance of an instrumentation radar. As a result of simulation, we showed that an instrumentation radar may lose the target because it tracks a area of the beacon antenna pattern.

Binaural Directivity Pattern Simulation of the KEMAR Head Model with Two Twin Hearing Aid Microphones by Boundary Element Method

  • Jarng Soon Suck;Kwon You Jung;Lee Je Hyeong
    • The Journal of the Acoustical Society of Korea
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    • v.24 no.3E
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    • pp.115-122
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    • 2005
  • Two twin microphones may produce particular patterns of binaural directivity by time delays between twin microphones. The boundary element method (BEM) was used for the simulation of the sound pressure field around the head model in order to quantify the acoustic head effect. The sound pressure onto the microphone was calculated by the BEM to an incident sound pressure. Then a planar directivity pattern was formed by four sound pressure signals from four microphones. The optimal binaural directivity pattern may be achieved by adjusting time delays at each frequency while maintaining the forward beam pattern is relatively bigger than the backward beam pattern.

Data Pattern Estimation with Movement of the Center of Gravity

  • Ahn Tae-Chon;Jang Kyung-Won;Shin Dong-Du;Kang Hak-Soo;Yoon Yang-Woong
    • 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.

A Study of a Lip Print Recognition by the Pattern Kernels (Pattern kernels에 의한 Lip Print인식 연구)

  • Paik, Kyoung-Seok;Chung, Chin-Hyun
    • Proceedings of the KIEE Conference
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    • 1998.07g
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    • pp.2249-2251
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    • 1998
  • This paper presents a lip print recognition by the pattern kernels for a personal identification. A lip print recognition is developed less than the other physical attribute that is a fingerprint, a voice pattern, a retinal blood-vessel pattern, or a facial recognition. A new method by the pattern kernels is pro for a lip print recognition. The pattern kerne function consisted of some local lip print p masks. This function identifies the lip print known person or an unknown person. The results show that the proposed algorithm the pattern kernels can the efficiently realized.

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A Study on The Visual Inspection of Fabric Defects (시각 장치를 이용한 직불 결합 인식에 관한 연구)

  • Kyung, Kye-Hyun;Ko, Myoung-Sam;Lee, Sang-Uk;Lee, Bum-Hee
    • Proceedings of the KIEE Conference
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    • 1987.11a
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    • pp.311-315
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    • 1987
  • This paper describes the automatic visual inspect ion system of fabric defects based on pattern recognition techniques. To extract features for detection of fabric defects, four different techniques such as SGLDM. GCM, decorrelation method, and Laws' texture measure were investigated. From results of computer simulation, it has been found that GCM and decorrelation techniques provide good features. By employing a simple statistical pattern recognition technique, theaccuracy of classification of defect and nondefect was more than 90%. Some experimental results arm also presented.

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A Study of the Pattern Kernels for a Lip Print Recognition

  • Paik, Kyoung-Seok;Chung, Chin-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • 1998.10a
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    • pp.64-69
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    • 1998
  • This paper presents a lip print recognition by the pattern kernels for a personal identification. A lip print recognition is developed less than the other physical attributes of a fingerprint, a voice pattern, a retinal blood/vessel pattern, or a facial recognition. A new method is proposed to recognize a lip print bi the pattern kernels. The pattern kernels are a function consisted of some local lip print pattern masks. This function converts the information on a lip print into the digital data. The recognition in the multi-resolution system is more reliable than recognition in the single-resolution system. The results show that the proposed algorithm by the multi-resolution architecture can be efficiently realized.

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Directivity Pattern Simulation of the Ears with Two Pairs' Hearing Aid Microphone Arrays by BEM

  • Jarng Soon Suck;Kwon You Jung
    • The Journal of the Acoustical Society of Korea
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    • v.24 no.2E
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    • pp.38-45
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    • 2005
  • The noise reduction of the In-The-Ear (ITE) hearing aid (HA) can be achieved by arrays of microphones. Each of the right and the left ears was assumed to have two HA microphones. These arrays of HA microphones produce particular patterns of directivity by some time delay between two microphones. The directivity pattern geometrically increase the S/N ratio. The boundary element method (BEM) was used for the three dimensional simulation of the HA directivity pattern with the two pairs' microphone arrays. The separation between two microphones was fixed to 10 mm. The time delay between the two microphones was calculated to produce the most narrow directivity pattern in the fore front of the head. The variation of the time delay was examined in accordance with input frequencies. This numerical analysis may be then applied for the calculation of the time delay parameter of the digital hearing aid DSP chip.

An Implementation of Lip Print Recognition system using VHDL (VHDL을 이용한 구순문 인식 시스템의 구현 연구)

  • Choi, Woo-Jin;Chung, Chin-Hyun
    • Proceedings of the KIEE Conference
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    • 1999.07g
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    • pp.2935-2937
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    • 1999
  • The human has recognizable part of body such as a fingerprint, a crimson, a blood vessel. This part has been investigated constantly, its confidence for personal recognition is high. In spite of specialized part of human body, a lip print recognition is developed less than the other physical attribute that is a fingerprint. a voice pattern, a retinal blood-vessel pattern, or a facial recognition. This paper is to implement hardware for lip print recognition system using VHDL.

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Detection of Oscillatory Pattern Signals and its Application to the Fault Diagnosis of a Boiler Drum-Level Control System (Oscillatory 파형감지에 의한 보일러 플랜트 드럼수위 제어계통의 고장진단)

  • Kim, Jae-Hwa;Seo, Yeol-Kyu;Jang, Tae-Gyu
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.1
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    • pp.44-51
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    • 1999
  • This paper proposes a new approach of plant fault diagnosis which is based on detecting the characteristic pattern signals and associating them with the corresponding faults. The new approach does not require analytic modeling of the target system but best reflects the expertise embedded in the experienced human operation by mimicking them in a systematic way. This paper intends to illustrate the feasibility of the proposed by developing the algorithms to detect and estimate the typical characteristic pattern signals, I. e., oscillatory patterns, and applying them to the diagnosis of various faults of a 500MW boiler control system including tube rupture, feed-water leak, and controller failure.

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A Study on High Impedance Fault Detection using Wavelet Transform and Neural-Network (웨이브릿 변환과 신경망 학습을 이용한 고저항 지락사고 검출에 관한 연구)

  • Hong, Dae-Seung;Ryu, Chang-Wan;Ko, Jae-Ho;Yim, Wha-Yeong
    • Proceedings of the KIEE Conference
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    • 1999.07b
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    • pp.856-858
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    • 1999
  • The analysis of distribution line faults is essential to the proper protection of power system. A high impedance fault(HIF) dose not make enough current to cause conventional protective device. It is well known that undesirable operating conditions and certain types of faults on electric distribution feeders cannot be detected by using conventional Protection system. This paper describes an algorithm using neural network for pattern recognition and detection of high impedance faults. Wavelet transform analysis gives the time-scale information. Time-scale representation of high impedance faults can detect easily and localize correctly the fault waveform.

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