• Title/Summary/Keyword: Auto-regressive

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A Technique for Generation of Template Signal using Stable Minimum-Phase ARMA System Modeling for Coherent Impulse Communication Systems (안정성을 갖는 최소 위상 ARMA시스템 모델링을 이용한 코히어런트 임펄스 통신 수신단 참조 신호 발생 기법)

  • Lee Won Cheol;Park Woon Yong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.12C
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    • pp.1606-1616
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    • 2004
  • This paper introduces a technique for generating an appropriate template signal via modeling of minimum-phase stable ARMA (Auto-Regressive Moving Average) system for coherent impulse communication systems. It has been well known that the transmitted impulse signal becomes deformed because of dispersive and resonant characteristics. Accordingly, in spite of using ideal template signal at the correlator, these impairments degrade overall performance attributed to low level of coherence. To increase the degree of coherence, our proposed scheme realizes A3U system derived by Gaussian pulse signal, which simulates the overall characteristic of transfer function in between transmit and receive wideband antennas so as to generate an appropriate template signal in a form of output. The performance of proposed scheme will be shown in results from computer simulations to verify its affirmative impact on impulse communication system with regarding several distinctively shaped antennas.

A Compensation Technique for Dispersive and Resonant Wideband Antenna using Stable Minimum-Phase ARMA System Modeling for Coherent Impulse Communication Systems (안정성을 갖는 최소 위상 ARMA 시스템 모델링을 이용한 코히어런트 임펄스 통신 시스템의 광대역 안테나 확산 및 공진 특성 보상 기법)

  • Lee Won-Cheol;Park Woon-Yong
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.15 no.10 s.89
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    • pp.983-995
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    • 2004
  • This paper introduces a pre-compensation filter for compensating dispersive and resonant properties experienced along the usage of non-ideal wideband antennas in impulse communication systems. It has been well blown that the transmitted impulse signal becomes deformed because of dispersive and resonant characteristics. Accordingly, in spite of using ideal template signal at the correlator in coherent receiver, these impairments degrade overall performance attributed to low level of coherence. To overcome this problem this paper exploits a realization technique of pre-compensation filter purposely installed at transmitter whose stability is automatically guaranteed because it has an inversion form of minimum-phase ARMA (Auto-Regressive Moving Average) system. The performance of proposed scheme will be shown in results from computer simulations to verify its affirmative impact on impulse communication system with regarding several distinctively shaped antennas.

A Study on the Seoul Apartment Jeonse Price after the Global Financial Crisis in 2008 in the Frame of Vecter Auto Regressive Model(VAR) (VAR분석을 활용한 금융위기 이후 서울 아파트 전세가격 변화)

  • Kim, Hyun-woo;Lee, Du-Heon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.9
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    • pp.6315-6324
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    • 2015
  • This study analyses the effects of household finances on rental price of apartment in Seoul which play a major role in real estate policy. We estimate VAR models using time series data. Economy variables such as sales price of apartment in Seoul, consumer price index, hiring rate, real GNI and loan amount of housing mortgage, which relate to household finances and influence the rental price of apartment, are used for estimation. The main findings are as follows. In the short term, the rental price of apartment is impacted by economy variables. Specifically, Relative contributions of variation in rental price of apartment through structural shock of economy variables are most influenced by their own. However, in the long term, household variables are more influential to the rental price of apartment. These results are expected to contribute to establish housing price stabilization policies through understanding the relationship between economy variables and rental price of apartment.

Structural Health Monitoring of Full-Scale Concrete Girder Bridge Using Acceleration Response (가속도 응답을 이용한 실물 콘크리트 거더 교량의 구조건전성 모니터링)

  • Hong, Dong-Soo;Kim, Jeong-Tae
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.14 no.1
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    • pp.165-174
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    • 2010
  • In this paper, a two-phase structural health monitoring system using acceleration response signatures are presented to firstly alarm the change in structural condition and to secondly detect the changed location for full-scale concrete girder bridges. Firstly, Mihocheon Bridge which is a two-span continuous concrete girder bridge is selected as the target structure. The dynamic response features of Mihocheon Bridge are extracted by forced vibration test using bowling ball. Secondly, the damage alarming occurrence and the damage localization techniques are selected to design two-phase structural health monitoring system for Mihocheon Bridge. As the damage alarming techniques, auto-regressive model using time-domain signatures, correlation coefficient of frequency response function and frequency response ratio assurance criterion are selected. As the damage localization technique, modal strain energy-based damage index method is selected. Finally, the feasibility of two-phase structural health monitoring systems is evaluated from static loading tests using a dump truck.

Feedback Flow Control Using Artificial Neural Network for Pressure Drag Reduction on the NACA0015 Airfoil (NACA0015 익형의 압력항력 감소를 위한 인공신경망 기반의 피드백 유동 제어)

  • Baek, Ji-Hye;Park, Soo-Hyung
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.49 no.9
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    • pp.729-738
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    • 2021
  • Feedback flow control using an artificial neural network was numerically investigated for NACA0015 Airfoil to suppress flow separation on an airfoil. In order to achieve goal of flow control which is aimed to reduce the size of separation on the airfoil, Blowing&Suction actuator was implemented near the separation point. In the system modeling step, the proper orthogonal decomposition was applied to the pressure field. Then, some POD modes that are necessary for flow control are extracted to analyze the unsteady characteristics. NARX neural network based on decomposed modes are trained to represent the flow dynamics and finally operated in the feedback control loop. Predicted control signal was numerically applied on CFD simulation so that control effect was analyzed through comparing the characteristic of aerodynamic force and spatial modes depending on the presence of the control. The feedback control showed effectiveness in pressure drag reduction up to 29%. Numerical results confirm that the effect is due to dramatic pressure recovery around the trailing edge of the airfoil.

A Longitudinal Study about Relationship between Somatic Symptom and Depression of Adolescents (청소년의 신체화 증상과 우울의 관계에 관한 종단연구)

  • Park, So-Youn
    • Journal of Digital Convergence
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    • v.19 no.7
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    • pp.409-417
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    • 2021
  • The purpose of this study is to find out how individual, family, and school factors influence adolescents' depression, and to explore the long-term influence between somatic symptom and depression. To do this, data from two points of the 4th wave (year of 2013) and the 6th wave (year of 2015) of the first-year middle school panel survey (KCYPS) were used and structural equation model analysis was conducted on 1,668 adolescents. As for results, frist, in terms of individual factors, gender, physical health status, and self-resilience significantly affected depression in adolescents. Second, among school factors, learning activities and peer relationship significantly affected depression in adolescents. Third, somatic symptom and depression had effects and auto-regressive effects over time. Based on these results, the prevention and intervention measures for somatic symptom and depression of adolescents were discussed. Future study is needed include varaiables of parental mental health that affect depression in adolescents.

Lactation milk yield prediction in primiparous cows on a farm using the seasonal auto-regressive integrated moving average model, nonlinear autoregressive exogenous artificial neural networks and Wood's model

  • Grzesiak, Wilhelm;Zaborski, Daniel;Szatkowska, Iwona;Krolaczyk, Katarzyna
    • Animal Bioscience
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    • v.34 no.4
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    • pp.770-782
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    • 2021
  • Objective: The aim of the present study was to compare the effectiveness of three approaches (the seasonal auto-regressive integrated moving average [SARIMA] model, the nonlinear autoregressive exogenous [NARX] artificial neural networks and Wood's model) to the prediction of milk yield during lactation. Methods: The dataset comprised monthly test-day records from 965 Polish Holstein-Friesian Black-and-White primiparous cows. The milk yields from cows in their first lactation (from 5 to 305 days in milk) were used. Each lactation was divided into ten lactation stages of approximately 30 days. Two age groups and four calving seasons were distinguished. The records collected between 2009 and 2015 were used for model fitting and those from 2016 for the verification of predictive performance. Results: No significant differences between the predicted and the real values were found. The predictions generated by SARIMA were slightly more accurate, although they did not differ significantly from those produced by the NARX and Wood's models. SARIMA had a slightly better performance, especially in the initial periods, whereas the NARX and Wood's models in the later ones. Conclusion: The use of SARIMA was more time-consuming than that of NARX and Wood's model. The application of the SARIMA, NARX and Wood's models (after their implementation in a user-friendly software) may allow farmers to estimate milk yield of cows that begin production for the first time.

A Study on the Traffic Volume Correction and Prediction Using SARIMA Algorithm (SARIMA 알고리즘을 이용한 교통량 보정 및 예측)

  • Han, Dae-cheol;Lee, Dong Woo;Jung, Do-young
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.6
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    • pp.1-13
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    • 2021
  • In this study, a time series analysis technique was applied to calibrate and predict traffic data for various purposes, such as planning, design, maintenance, and research. Existing algorithms have limitations in application to data such as traffic data because they show strong periodicity and seasonality or irregular data. To overcome and supplement these limitations, we applied the SARIMA model, an analytical technique that combines the autocorrelation model, the Seasonal Auto Regressive(SAR), and the seasonal Moving Average(SMA). According to the analysis, traffic volume prediction using the SARIMA(4,1,3)(4,0,3) 12 model, which is the optimal parameter combination, showed excellent performance of 85% on average. In addition to traffic data, this study is considered to be of great value in that it can contribute significantly to traffic correction and forecast improvement in the event of missing traffic data, and is also applicable to a variety of time series data recently collected.

A study on longitudinal relationship with academic stress, math self-efficacy, and math class engagement : Using auto regressive cross-lagged model (학업스트레스, 수학자기효능감, 수학수업참여에 관한 종단연구 : 자기회귀교차지연모형을 적용하여)

  • Song, Hyo seob;Jung, Hee sun
    • The Mathematical Education
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    • v.61 no.2
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    • pp.359-373
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    • 2022
  • This study aims to examine the differences in the longitudinal relationship between academic stress, mathematics self-efficacy, and engagement in mathematics class according to the math achievement level. According to the results, academic stress, math self-efficacy, and math class engagement were stable over time for the high and low groups. Also, In the high group, math self-efficacy had a negative longitudinal mediation effect in the influence of academic stress to math class engagement. Whereas, in the low group math class engagement had a positive longitudinal mediation effect in the influence of academic stress to math self-efficacy. This means that the academic stress affects differently according to the math achievement level, and mathematics teachers should reflect these results in their teaching/learning strategies so that students can increase their mathematics self-efficacy along with their engagement in mathematics classes.

Are Business Cycles in the Fashion Industry Affected by the News? -An ARIMAX Time Series Correlation Analysis between the KOSPI Index for Textile & Wearing Apparel and Media Agendas- (패션산업의 경기변동은 뉴스의 영향을 받는가? -섬유의복 KOSPI와 미디어 의제의 ARIMAX 시계열 상관관계 분석-)

  • Hyojung Kim;Minjung Park
    • Journal of the Korean Society of Clothing and Textiles
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    • v.47 no.5
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    • pp.779-803
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    • 2023
  • The growth of digital news media and the stock price index has resulted in economic fluctuations in the fashion industry. This study examines the impact of fashion industry news and macroeconomic changes on the Textile & Wearing Apparel KOSPI over the past five years. An auto-regressive integrated moving average exogenous time series model was conducted using the fashion industry stock market index, the news topic index, and macro-economic indicators. The results indicated the topics of "Cosmetic business expansion" and "Digital innovation" impacted the Textile & Wearing Apparel KOSPI after one week, and the topics of "Pop-up store," "Entry into the Chinese fashion market," and "Fashion week and trade show" affected it after two weeks. Moreover, the topics of "Cosmetic business expansion" and "Entry into the Chinese fashion market" were statistically significant in the macroeconomic environment. Regarding the effect relation of Textile & Wearing Apparel KOSPI, "Cosmetic business expansion," "Entry into the Chinese fashion market," and consumer price fluctuation showed negative effects, while the private consumption change rate, producer price fluctuation, and unemployment change rate had positive effects. This study analyzes the impact of media framing on fashion industry business cycles and provides practical insights into managing stock market risk for fashion companies.