• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.6
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• pp.700-708
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• 2014

Jet engine modulation(JEM) is a frequency modulation phenomenon of the radar signal induced by electromagnetic scattering from a rotating jet engine turbine. Although JEM can be used as a representative radar target recognition method by providing unique information on the target, its recognition performance may be degraded in the observation range of weakly present JEM. Hence, this paper presents a method for extracting the JEM component by decomposing the radar signal into intrisic mode functions(IMFs) via complex empirical mode decomposition(CEMD) and by combining them based on signal eccentricity. Its application to various signals demonstrated that the proposed method improved the clarity of JEM analysis and could extend the effective observation range of JEM.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.380-388
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• 2019

Jet engine modulation(JEM) signals are widely used for target recognition. These signals coming from a potentially hostile aircraft provide specific information about the jet engine. In order to obtain the number of blades, which is uniquely provided by the JEM signal, one must extract the spool rate, which is the rotation speed of the blades. In this paper, we propose an algorithm to extract the spool rate from a weak JEM signal. A criterion is developed to extract the spool rate from the JEM signal by analyzing the intensity of the JEM signal component. The weak signal is first subjected to a high-pass filtering-based process, which modifies it to facilitate spool rate extraction. We then apply a peak detection process and extract the spool rate. The technique is simpler than the existing CEMD or WD method, is accurate, and greatly reduces the time required.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.12
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• pp.1173-1180
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• 2013

High Resolution Range Profile-Jet Engine Modulation imagery first introduced in 2005 carries out radar target recognition by localizing the position of the jet engine installed on the aircraft target. This paper presents a new approach for estimating the jet engine position in the HRRP-JEM image based on the eccentricity of a complex signal. It can effectively evaluate the contribution of the JEM component to the radar received signal in a range bin of the HRRP-JEM image. Therefore, the localization is expected to be performed more quantitatively and reliably by pinpointing the range bin corresponding to the jet engine position where the JEM contribution is maximized. The simulation results of realistic aircraft models validated the effectiveness of the proposed concept.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.10
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• pp.49-58
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• 2008

Characteristics of JEM(Jet Engine Modulation) are measured and principal meanings are grasped in this paper. This study's object is to measure RCS and JEM for actual aircraft, especially low speed craft. In experiment, various error are generated from unknown cause and for removal these, calibration technique known as IACT(Isolated Antenna Calibration Technique) is used. Experiment is executed at outdoor and target is T-103 which play in beginner course for ROKAF pilot. JEM spectrum of T-103 and frequency characteristics, doppler effects are extracted. X-band used in military aircraft for air-to-air fighting are selected. The data obtained through this study are analyzed to discriminate target especially low speed aircraft for current using radar(X-band)'s performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.6
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• pp.690-699
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• 2014

Jet engine modulation(JEM) is a technique used to identify the jet engine type from the radar target signature modulated by periodic rotation of the jet engine mounted on the aircraft target. As a new approach of JEM, this paper proposes an automatic algorithm for extracting the jet engine information. First, the rotation period of the jet engine is yielded from auto-correlation of the JEM signal preprocessed by complex empirical mode decomposition(CEMD). Then, the final blade number is estimated by introducing the DM(Divisor-Multiplier) rule and the 'Scoring' concept into JEM spectral analysis. Application results of the simulated and measured JEM signals demonstrated that the proposed algorithm is effective in accurate and automatic extraction of the jet engine information.

• Journal of Broadcast Engineering
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• v.22 no.5
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• pp.541-547
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• 2017

The Joint Exploration Model (JEM), which is a reference SW codec of the Joint Video Exploration Team (JVET) exploring the future video standard technology, provides a recursive Quadtree plus Binary Tree (QTBT) block structure. QTBT can achieve enhanced coding efficiency by adding new block structures at the expense of largely increased computational complexity. In this paper, we propose a fast decision algorithm of QTBT block partitioning depth that uses the rate-distortion (RD) cost of the upper and current depth to reduce the complexity of the JEM encoder. Experimental results showed that the computational complexity of JEM 5.0 can be reduced up to 21.6% and 11.0% with BD-rate increase of 0.7% and 1.2% in AI (All Intra) and RA (Random Access), respectively.

• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.495-502
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• 2018

JVET (Joint Video Exploration Team) which explored evolving technologies of video coding with capabilities beyond HEVC (High Efficiency Video Coding), released a references software codec named the Joint Exploration Model (JEM) for performance verification of coding technologies. JEM has 67 intra prediction modes that extend the 35 modes of HEVC for intra prediction. Therefore, the enhancement of the coding performance is limited due to the overhead of prediction mode coding. In this paper, we analyze the probabilities of prediction modes selections, and then we propose a more efficient intra prediction mode coding based on the results of analyzed mode occurrence. In addition, we propose a context modeling for CABAC (Context-Adaptive Binary Arithmetic Coding) of the proposed mode coding. Experimental results show that the BD-rate gain is 0.02% on the AI (All Intra) coding structure compared to JEM 7.0. We need to optimize context modeling for additional coding performance enhancement.

• Safety and Health at Work
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• v.12 no.1
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• pp.74-95
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• 2021

Background: A job-exposure matrix (JEM) is an important surrogate indicator to evaluate past exposure levels. Although a Korean asbestos JEM has been constructed previously, this JEM includes only a few industrial and occupational groups. This study aimed to reconstruct the JEM by integrating the latest organized data to improve its utility. Methods: We used recent Korean standard industry and occupation codes and extracted 36 articles from a systematic literature review to initiate the reconstruction of the previous Korean asbestos JEM. The resulting data consisted of 141 combinations of industrial and occupational groups. Data from the Netherlands's JEM were also reviewed and categorized into 70 industrial and 117 occupational groups by matching with the Korean data. We also utilized Germany's data, which consisted of 10 industrial and 14 occupational groups. Results: The reconstructed Korean asbestos JEM had 141 combinations of industries and occupations. The time periods are from the 1980s to the 2000s in 10-year intervals. Most of the data were distributed between the 1990s and the 2000s. Occupations with high exposure to asbestos included knitting and weaving machine operators, automobile mechanics or assemblers, ship mechanics or assemblers, mineral ore and stone products processing mechanics, and metal casting machine operators or mold makers. Conclusions: The reconstructed Korean asbestos JEM has expanded the type and duration of the occupational groups of the previous JEM and can serve as an important reference tool for evaluating asbestos exposure and designing compensation and prevention policies in Korea.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.06a
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• pp.254-255
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• 2017

HEVC(High Efficiency Video Coding) 보다 뛰어난 압축 성능을 갖는 차세대 비디오 부호화 표준 기술 탐색을 하고 있는 JVET(Joint Video Exploratory Team)에서는 기술 검증을 위한 참조 SW 코덱인 JEM(Joint Exploration Model)을 공개하고 있다. JEM 의 화면내 예측 부호화에서는 67 가지의 예측모드를 사용하고 6 개의 MPM(Most Probable Mode)을 이용하여 예측모드를 부호화 한다. 본 논문에서는 코딩블록에서의 화면내 예측모드의 선택 확률을 바탕으로 보다 효율적인 예측모드 부호화 기법을 제안한다. 실험결과 JEM 5.0 대비 MPM 을 포함한 예측모드 부호화 정보의 CABAC(Context Adaptive Binary Arithmetic Coding) 엔트로피 부호화를 제외하고, AI(All Intra) 부호화 구조에서 0.23% 정도의 BD-rate 감소를 보임을 확일 할 수 있었다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.180-181
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• 2018

본 논문에서는 JEM(Joint Exploration Model)의 부호화기 계산 복잡도 감소를 위한 CU 조기 결정 방법을 제시한다. 기존의 JEM 의 경우 현재 CU(Coding Unit)의 RDO(Rate Distortion Optimization)를 통한 최적의 예측 모드가 Merge SKIP 모드이고 BT(Binary Tree)의 깊이가 2 또는 3 이상일 때 CU 결정을 조기 종료한다. 제안하는 방법에서는 현재 CU 의 최적의 예측모드가 Merge SKIP 이고 BT 일 경우 통계적 분석을 통한 왜곡 값, CU 샘플 수, 시간적 계층 순서, 양자화 파라미터를 고려한 문턱 값을 이용하여 CU 를 조기 결정한다. 실험결과로써 제안하는 방법이 JEM 7.1 대비 Y, U, V 각각 평균 0.86%, 0.08%, 0.18%의 BD-rate 손실이 발생하고 평균 16% 부호화 속도를 개선시킨다.