• 제목/요약/키워드: Analysis of the Frequency

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중주파수 응답해석을 위한 축소 기법 (Model Order Reduction for Mid-Frequency Response Analysis)

  • 고진환
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2009년도 정기 학술대회
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    • pp.135-138
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    • 2009
  • Most of the studies use model order reduction for low frequency (LF) response analysis due to their high computational efficiency. In LF response analysis, one of model order reduction, algebraic substructuring (AS) retains all LF modes when using the modal superposition. However, in mid-frequency (MF) response analysis, the LF modes make very little contribution and also increase the number of retained modes, which leads to loss of computational efficiency. Therefore, MF response analysis should consider low truncated modes to improve the computational efficiency. The current work is focused on improving the computational efficiency using a AS and a frequency sweep algorithm. Finite element simulation for a MEMS resonator array showed that the performance of the presented method is superior to a conventional method.

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FSK-주파수 도약 데이터 통신시스템에서의 디지털 주파수 합성기의 영향분석 (Analysis of the effect of Digital frequency synthesizer in FSK-Frequency-hopped data communications)

  • 송인근
    • 한국정보통신학회논문지
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    • 제7권5호
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    • pp.879-886
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    • 2003
  • 주파수 도약 대역확산시스템에서의 광대역 주파수 도약을 위해 주파수 합성기가 널리 이용된다. 따라서 본 논문에서는 효과적인 무선 디지털 데이터 전송 성능을 얻기 위한 FH-FSK 통신에 미치는 주파수 합성기의 영향을 분석하였다. 이를 위해 PLL의 성능을 좌우하는 위상 변화, 스퓨리어스의 발생, PLL의 과도응답 특성에 의해 영향을 받는 주파수 도약율 등 여러 가지 파라미터들에 따른 성능을 분석하였다. 전형적인 PLL을 사용한 주파수 도약 시스템에서는 주파수 도약을 위한 반송파 신호를 국부 발진기에서 만들어낸다. 반송파 간격이 협대역인 협대역 무선 통신 시스템일 경우에는 빠른 주파수 도약을 위한 PLL의 구현이 어렵다. 본 논문에서는 이런 문제점을 해결하기 위해 디지털 주파수 합성기/CPM 변조기를 사용하여 빠른 주파수 도약을 위한 PLL 구현이 가능함을 Matlab tool를 사용한 시뮬레이션 결과를 통해 분석할 수 있었다.

Deep Learning Document Analysis System Based on Keyword Frequency and Section Centrality Analysis

  • Lee, Jongwon;Wu, Guanchen;Jung, Hoekyung
    • Journal of information and communication convergence engineering
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    • 제19권1호
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    • pp.48-53
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    • 2021
  • Herein, we propose a document analysis system that analyzes papers or reports transformed into XML(Extensible Markup Language) format. It reads the document specified by the user, extracts keywords from the document, and compares the frequency of keywords to extract the top-three keywords. It maintains the order of the paragraphs containing the keywords and removes duplicated paragraphs. The frequency of the top-three keywords in the extracted paragraphs is re-verified, and the paragraphs are partitioned into 10 sections. Subsequently, the importance of the relevant areas is calculated and compared. By notifying the user of areas with the highest frequency and areas with higher importance than the average frequency, the user can read only the main content without reading all the contents. In addition, the number of paragraphs extracted through the deep learning model and the number of paragraphs in a section of high importance are predicted.

주파수-변형률 곡선의 개발 및 검증 (Development & Verification of Frequency-Strain Dependence Curve)

  • 정창균;곽동엽;박두희
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2009년도 춘계 학술발표회
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    • pp.146-153
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    • 2009
  • One dimensional site response analysis is widely used in prediction of the ground motion that is induced by earthquake. Equivalent linear analysis is the most widely used method due to its simplicity and ease of use. However, the equivalent linear method has been known to be unreliable since it approximates the nonlinear soil behavior within the linear framework. To consider the nonlinearity of the ground at frequency domain, frequency dependent algorithms that can simulate shear strain - frequency dependency have been proposed. In this study, the results of the modified equivalent linear analysis are compared to evaluate the degree of improvement and the applicability of the modified algorithms. Results show the novel smoothed curve that is proposed by this study indicates the most stable prediction and can enhance the accuracy of the prediction.

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전국 확률강수량 산정을 위한 비정상성 빈도해석 기법의 적용 (Application of a Non-stationary Frequency Analysis Method for Estimating Probable Precipitation in Korea)

  • 김광섭;이기춘
    • 한국농공학회논문집
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    • 제54권5호
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    • pp.141-153
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    • 2012
  • In this study, we estimated probable precipitation amounts at the target year (2020, 2030, 2040) of 55 weather stations in Korea using the 24 hour annual maximum precipitation data from 1973 through 2009 which should be useful for management of agricultural reservoirs. Not only trend tests but also non-stationary tests were performed and non-stationary frequency analysis were conducted to all of 55 sites. Gumbel distribution was chosen and probability weighted moment method was used to estimate model parameters. The behavior of the mean of extreme precipitation data, scale parameter, and location parameter were analyzed. The probable precipitation amount at the target year was estimated by a non-stationary frequency analysis using the linear regression analysis for the mean of extreme precipitation data, scale parameter, and location parameter. Overall results demonstrated that the probable precipitation amounts using the non-stationary frequency analysis were overestimated. There were large increase of the probable precipitation amounts of middle part of Korea and decrease at several sites in Southern part. The non-stationary frequency analysis using a linear model should be applicable to relatively short projection periods.

Bayesian Nonstationary Flood Frequency Analysis Using Climate Information

  • Moon, Young-Il;Kwon, Hyun-Han
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2007년도 학술발표회 논문집
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    • pp.1441-1444
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    • 2007
  • It is now widely acknowledged that climate variability modifies the frequency spectrum of hydrological extreme events. Traditional hydrological frequency analysis methodologies are not devised to account for nonstationarity that arises due to variation in exogenous factors of the causal structure. We use Hierarchical Bayesian Analysis to consider the exogenous factors that can influence on the frequency of extreme floods. The sea surface temperatures, predicted GCM precipitation, climate indices and snow pack are considered as potential predictors of flood risk. The parameters of the model are estimated using a Markov Chain Monte Carlo (MCMC) algorithm. The predictors are compared in terms of the resulting posterior distributions of the parameters associated with estimated flood frequency distributions.

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Blind modal identification of output-only non-proportionally-damped structures by time-frequency complex independent component analysis

  • Nagarajaiah, Satish;Yang, Yongchao
    • Smart Structures and Systems
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    • 제15권1호
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    • pp.81-97
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    • 2015
  • Recently, a new output-only modal identification method based on time-frequency independent component analysis (ICA) has been developed by the authors and shown to be useful for even highly-damped structures. In many cases, it is of interest to identify the complex modes of structures with non-proportional damping. This study extends the time-frequency ICA based method to a complex ICA formulation for output-only modal identification of non-proportionally-damped structures. The connection is established between complex ICA model and the complex-valued modal expansion with sparse time-frequency representation, thereby blindly separating the measured structural responses into the complex mode matrix and complex-valued modal responses. Numerical simulation on a non-proportionally-damped system, laboratory experiment on a highly-damped three-story frame, and a real-world highly-damped base-isolated structure identification example demonstrate the capability of the time-frequency complex ICA method for identification of structures with complex modes in a straightforward and efficient manner.

발전기 탈락에 따른 주파수의 전파속도 해석에 관한 연구 (A Study on Analysis of Propagation Speed of Power Frequency by Generation Drop)

  • 김학만;박철원
    • 전기학회논문지P
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    • 제63권4호
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    • pp.295-300
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    • 2014
  • The frequency is an important operating parameter of a power system. There is an increasing importance of constant monitoring of frequency to achieve stable power supply by WAMS(wide area monitoring system) and FNET(Frequency Monitoring Network). This paper is part of development of a network-based frequency monitoring and failure prediction system for wide-area intelligent protection relaying. In this paper, analysis of propagation speed of power frequency by generation drop using the PSS/E was carried out. For dynamic analysis, the 11 metropolitan areas offices of KEPCO divided into five groups of Seoul, Gangwon, Chungcheong, Honam, and Yeongnam group, study was performed.

동적 특성을 고려한 차량 현가 시스템의 내구해석 기법 (Durability Analysis Technique of Automotive Suspension System Considering Dynamic Characteristics)

  • 한우섭;이혁재;임홍재;이상범
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2003년도 춘계학술대회논문집
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    • pp.336-341
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    • 2003
  • In this paper, resonance durability analysis technique is presented for the fatigue life assessment considering dynamic effect of a vehicle system. In the resonance durability analysis, the frequency response and the dynamic load on frequency domain are used. Multi-body dynamic analysis, finite element analysis, and fatigue life prediction method are applied for the virtual durability assessment. To obtain the frequency response and the dynamic load, the computer simulations running over typical pothole and Belgian road are carried out by utilizing vehicle dynamic model. The durability estimations on the rear suspension system of the passenger car are performed by using the presented technique and compared with the quasi-static durability analysis. The study shows that the fatigue life considering resonant frequency of vehicle system can be effectively estimated in early design stage.

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Term Frequency-Inverse Document Frequency (TF-IDF) Technique Using Principal Component Analysis (PCA) with Naive Bayes Classification

  • J.Uma;K.Prabha
    • International Journal of Computer Science & Network Security
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    • 제24권4호
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    • pp.113-118
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    • 2024
  • Pursuance Sentiment Analysis on Twitter is difficult then performance it's used for great review. The present be for the reason to the tweet is extremely small with mostly contain slang, emoticon, and hash tag with other tweet words. A feature extraction stands every technique concerning structure and aspect point beginning particular tweets. The subdivision in a aspect vector is an integer that has a commitment on ascribing a supposition class to a tweet. The cycle of feature extraction is to eradicate the exact quality to get better the accurateness of the classifications models. In this manuscript we proposed Term Frequency-Inverse Document Frequency (TF-IDF) method is to secure Principal Component Analysis (PCA) with Naïve Bayes Classifiers. As the classifications process, the work proposed can produce different aspects from wildly valued feature commencing a Twitter dataset.