• 제목/요약/키워드: Input-output decomposition

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CALS를 위한 기능모델링 방법론-IDEF0의 확장 (Functional Modeling Methodology for CALS - IDEF0 Extension)

  • 김철한;우훈식;김중인;임동순
    • 한국전자거래학회:학술대회논문집
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    • 한국전자거래학회 1997년도 한국전자거래학회 종합학술대회지
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    • pp.263-268
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    • 1997
  • Functional Modeling methodology, IDEF0 is widely used for modeling, analysis and description of enterprise system. The limitation of modeling components restricts applicability and give rise to confusion about model. In this paper, we propose new method to extend IDEF0. The first is adding modeling components which are semantic representations. In addition to ICOMs, we add the time and cost component which is required to execute the function. The second is tracing mechanism. When we need some information, we drive the functions related with the information by reverse tracing of the function which produces the information as a output and input. Through the tracing, we find out the bottleneck process or high cost process. Finally, we suggest the final decomposition level. We call the final decomposed function into unit function which has only one output data. We can combine and reconstruct some of functions because an unit function is similar to ‘lego block’. To reach the integrated system, the main problem to be solved is the integration of information produced by different functional subsystem. This can be resolved when the creation of data must be dependent on only one function. Through view integration of function output, we can guarantee the integrity of data.

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모의 분석을 위한 표적 획득 체계의 특성 데이터 산출 (Estimating Characteristic Data of Target Acquisition Systems for Simulation Analysis)

  • 김태윤;한상우;권승만
    • 한국시뮬레이션학회논문지
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    • 제32권1호
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    • pp.45-54
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    • 2023
  • 전투 모의 환경 하에서 실제 모의 대상의 탐지 성능 데이터를 모의 개체에 적절히 입력하는 것은 모의분석 결과에 큰 영향을 미친다. 주요 전투 시뮬레이션 도구에서 개체의 탐지 능력을 모의하기 위한 표적획득모델로 ACQUIRE-Target Task Performance Metric(TTPM)-Target Angular Size(TAS) 모델을 사용하며, 이 모델은 전투 개체의 조우 조건을 입력으로 받아 해당 개체 센서의 분해 곡선을 추정하고, 표적 유형에 따른 탐지 거리를 출력한다. 그런데 사용자가 입력을 원하는 새로운 탐지 개체의 성능을 표적획득모델에 적용하는 것은 쉽지 않다. 사용자는 탐지 거리를 표적획득모델에 입력하길 원하지만, 표적획득모델은 조우 조건에 따른 센서의 분해 곡선 데이터가 필요하기 때문이다. 본 논문에서는 표적에 대한 탐지 거리를 입력으로 하여 표적획득모델의 센서 분해 곡선 데이터를 역으로 도출하는 기법을 제안한다. 여기서 해당 센서 분해 곡선 데이터는 인원, 지상차량, 항공기의 3종류 표적 유형에 대한 각각의 탐지 거리를 동시에 만족한다. 마지막으로 여러 정찰 장비의 탐지 거리를 탐지 개체에 적용하여, 정찰 장비에 따른 탐지 효과도를 분석한다.

산업의 온실가스 배출 행태 이해를 위한 지수분해분석 적합성 실증 연구 (Can Index Decomposition Analysis Give a Clue in Understanding Industry's Greenhouse Gas Footprint?)

  • 정환삼;스스무 토노
    • 자원ㆍ환경경제연구
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    • 제24권1호
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    • pp.55-84
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    • 2015
  • 한국은 OECD 국가 가운데 교토협약에 따른 온실가스 감축의무를 갖지 않는 몇 안 되는 국가이다. 한국은 자발적으로 2015년부터 강력한 온실가스 감축을 단행하기로 하였다. 정부의 현정책들은 온실가스 감축에 따른 경제성장의 저하를 감안하지 않고 있어, 이 정책의 지속성이 제약된다. 이 점에서 산업의 부문별 특성을 감안한 감축전략이 더욱 친환경적 전략이 될 수 있다. 이 연구는 혼합단위를 사용한 에너지 산업연관분석에서부터 온실가스 배출에 유의미한 산업을 선정해 분해분석을 함으로써 유용성을 검증하였다. 유의미한 산업은 '유기화학기초제품군'과 '시멘트 및 콘크리트 산업'을 대상으로 삼았다. 변이는 에너지 소비, 생산, 공정개선 그리고 신시설의 도입 효과로 구분해 실증되었다. 이 연구에서 디비지아 분해분석 결과치들이 부분적으론 불안정적 시계열 패턴을 보였으나, 전체분석 과정으로 보면 일련의 분석과정은 대상산업의 에너지 사용과 온실가스 배출의 행태를 이해하기에 충분한 정보를 제공하였다.

V-BLAST 시스템에서의 BER 성능 향상을 위한 Extended-list SQRD-based Decoder (Extended-list SQRD-based Decoder for Improving BER Performance in V-BLAST Systems)

  • ;;윤기완
    • 한국정보통신학회논문지
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    • 제9권7호
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    • pp.1452-1457
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    • 2005
  • QR Decomposition-based (QRD) decoding class에서는, 시스템 성능이 에러 전송에 민감하다. 그러므로 이전의 layer들을 정확하게 디코딩하는 것이 중요하다. 에러 전송에 민감하지 않도록 하는 접근 방법 중의 하나가 layer들의 최적 디코딩 order를 제안하는 것이다. 본 논문에서는 새로운 extended-list Sorted QRD-based (SQRD) 디코딩 접근 방법을 제안한다. 제안되는 디코딩 방법에는 약간의 첫째 layer들의 solution이 상당히 가능성 있는 solution들의 list로 확장된다. 이렇게 함으로 가장 낮은 layer의 diversity가 증가된다. 결과적으로 시스템 성능이 다른 것들의 에러 전송보다 덜 민감하게 된다. 제안되는 방법은 컴퓨터 시뮬레이션 결과로 증명된다.

CALS 구현을 위한 모델링 방법론의 기능조건 (Functional Requirements about Modeling Methodology for CALS)

  • 김철한;우훈식;김중인;임동순
    • 한국전자거래학회지
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    • 제2권2호
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    • pp.89-113
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    • 1997
  • Modeling methodology has been widely used for analysis and design of a information system. Specially, under the CALS environments, modeling approach is more important because the enterprise functions are inter-related and information sharing speeds up the business. In this paper, we suggest functional requirements about modeling methodology for CALS by surveying the IDEF0 and ARIS. The former is FIPS 183 and the latter is basic methodology of SAP/R3 which is world-wide ERP system. The proposed functional requirements include all semantics of IDEF0 and adds some features. The first is adding modeling components which are semantic representations. In addition to ICOMs, we add the time and cost component which is required to execute the function. The second is tracing mechanism. When we need some information, we drive the functions related with the information by reverse tracing of the function which produces the information as a output and input. Through the tracing, we find out the bottleneck process or high cost process. This approach guarantees the integrity of data by designating the data ownership. Finally, we suggest the final decomposition level. We call the final decomposed function into unit function which has only one output data. We can combine and reconstruct some of functions such as 'lego block' combination.

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독립성분 분석과 신전달 모델을 이용한 근육의 미세한 힘의 추정에 관한 연구 (A Study on the Low Force Estimation of Skeletal Muscle by using ICA and Neuro-transmission Model)

  • 유세근;염두호;이호용;김성환
    • 전기학회논문지
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    • 제56권3호
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    • pp.632-640
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    • 2007
  • The low force estimation method of skeletal muscle was proposed by using ICA(independent component analysis) and neuro-transmission model. An EMG decomposition is the procedure by which the signal is classified into its constituent MUAP(motor unit action potential). The force index of electromyography was due to the generation of MUAP. To estimate low force, current analysis technique, such as RMS(root mean square) and MAV(mean absolute value), have not been shown to provide direct measures of the number and timing of motoneurons firing or their firing frequencies, but are used due to lack of other options. In this paper, the method based on ICA and chemical signal transmission mechanism from neuron to muscle was proposed. The force generation model consists of two linear, first-order low pass filters separated by a static non-linearity. The model takes a modulated IPI(inter pulse interval) as input and produces isometric force as output. Both the step and random train were applied to the neuro-transmission model. As a results, the ICA has shown remarkable enhancement by finding a hidden MAUP from the original superimposed EMG signal and estimating accurate IPI. And the proposed estimation technique shows good agreements with the low force measured comparing with RMS and MAV method to the input patterns.

Combined ML and QR Detection Algorithm for MIMO-OFDM Systems with Perfect ChanneI State Information

  • You, Weizhi;Yi, Lilin;Hu, Weisheng
    • ETRI Journal
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    • 제35권3호
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    • pp.371-377
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    • 2013
  • An effective signal detection algorithm with low complexity is presented for multiple-input multiple-output orthogonal frequency division multiplexing systems. The proposed technique, QR-MLD, combines the conventional maximum likelihood detection (MLD) algorithm and the QR algorithm, resulting in much lower complexity compared to MLD. The proposed technique is compared with a similar algorithm, showing that the complexity of the proposed technique with T=1 is a 95% improvement over that of MLD, at the expense of about a 2-dB signal-to-noise-ratio (SNR) degradation for a bit error rate (BER) of $10^{-3}$. Additionally, with T=2, the proposed technique reduces the complexity by 73% for multiplications and 80% for additions and enhances the SNR performance about 1 dB for a BER of $10^{-3}$.

웨이블릿 해석과 인공 신경회로망을 이용한 원자력발전소의 급수유량 평가 (Feedwater Flow Rate Evaluation of Nuclear Power Plants Using Wavelet Analysis and Artificial Neural Networks)

  • 유성식;서종태;박종호
    • 유체기계공업학회:학술대회논문집
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    • 유체기계공업학회 2002년도 유체기계 연구개발 발표회 논문집
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    • pp.346-353
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    • 2002
  • The steam generator feedwater flow rate in a nuclear power plant was estimated by means of artificial neural networks with the wavelet analysis for enhanced information extraction. The fouling of venturi meters, used for steam generator feedwater flow rate in pressurized water reactors, may result in unnecessary plant power derating. The backpropagation network was used to generate models of signals for a pressurized water reactor. Multiple-input single-output heteroassociative networks were used for evaluating the feedwater flow rate as a function of a set of related variables. The wavelet was used as a low pass filter eliminating the noise from the raw signals. The results have shown that possible fouling of venturi can be detected by neural networks, and the feedwater flow rate can be predicted as an alternative to existing methods. The research has also indicated that the decomposition of signals by wavelet transform is a powerful approach to signal analysis for denoising.

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Application of OMA on the bench-scale earthquake simulator using micro tremor data

  • Kasimzade, Azer A.;Tuhta, Sertac
    • Structural Engineering and Mechanics
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    • 제61권2호
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    • pp.267-274
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    • 2017
  • In this study was investigated of possibility using the recorded micro tremor data on ground level as ambient vibration input excitation data for investigation and application Operational Modal Analysis (OMA) on the bench-scale earthquake simulator (The Quanser Shake Table) for model steel structures. As known OMA methods (such as EFDD, SSI and so on) are supposed to deal with the ambient responses. For this purpose, analytical and experimental modal analysis of a model steel structure for dynamic characteristics was evaluated. 3D Finite element model of the building was evaluated for the model steel structure based on the design drawing. Ambient excitation was provided by shake table from the recorded micro tremor ambient vibration data on ground level. Enhanced Frequency Domain Decomposition is used for the output only modal identification. From this study, best correlation is found between mode shapes. Natural frequencies and analytical frequencies in average (only) 2.8% are differences.

Efficient weight initialization method in multi-layer perceptrons

  • Han, Jaemin;Sung, Shijoong;Hyun, Changho
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 1995년도 추계학술대회발표논문집; 서울대학교, 서울; 30 Sep. 1995
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    • pp.325-333
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    • 1995
  • Back-propagation is the most widely used algorithm for supervised learning in multi-layer feed-forward networks. However, back-propagation is very slow in convergence. In this paper, a new weight initialization method, called rough map initialization, in multi-layer perceptrons is proposed. To overcome the long convergence time, possibly due to the random initialization of the weights of the existing multi-layer perceptrons, the rough map initialization method initialize weights by utilizing relationship of input-output features with singular value decomposition technique. The results of this initialization procedure are compared to random initialization procedure in encoder problems and xor problems.

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