• Title/Summary/Keyword: Moving average method

Search Result 545, Processing Time 0.027 seconds

Design of GHz Analog FIR Filter based on a Distributed Amplifier (분산증폭기 기반 GHz 대역 아날로그 FIR 필터 설계)

  • Yeo, Hyeop-Goo
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.16 no.8
    • /
    • pp.1753-1758
    • /
    • 2012
  • This paper introduces analog FIR filters based on a distributed amplifier and analyzes the proposed filter's characteristics. A simple design method of an analog FIR filter based on the digital filter design technique is also introduced. The proposed analog FIR filters are a moving average(MA) and a comb type filters with no multiplier. This simple structures of the proposed filters may enable to operate at multi-GHz frequency range and applicable to combine a filter and an amplifier of RF system. The proposed analog FIR filters were implemented with standard $0.18{\mu}m$ CMOS technology. The designed GHz analog FIR filters are simulated by Cadence Spectre and compared to the results of digital FIR filters obtained from MATLAB simulations. From the simulation results, the characteristics of the proposed analog FIR filters are fairly well matched with those of digital FIR filters.

Climate Change and Expansion of Squid Catches in Korea (한국에서의 기후변화와 오징어 어획의 확장)

  • Kim, Jong-Gyu;Kim, Joong-Soon
    • Journal of Environmental Health Sciences
    • /
    • v.43 no.6
    • /
    • pp.516-524
    • /
    • 2017
  • Objectives: The annual catch of the common squid Todarodes pacificus in Korean coastal waters has gradually increased since the late 1980s. We investigated the long-term effects of climate variability on the variation in catches of the squid in the offshore fisheries of Korea. Methods: Moving average method, correlation analysis, and regression analysis were used to determine the relationship between the environmental factors and fluctuation in the catch of the squid during the past 30 years (1981- 2010). A ten-year moving average was calculated and used for each variable. Results: Squid catches in Korean coastal waters increased over time, and there were significant variations within every ten years (p < 0.001). Air temperature, atmospheric pressure, and wind grade among the meteorological factors, alongside sea surface temperature (SST) and concentrations of phosphate phosphorous, and nitrite/nitrate nitrogen in the sea water increased and were positively related with the catch size of squid (p < 0.001). However, salinity decreased and was negatively related with the catch size (p < 0.001). The increase in air temperature and SST was almost parallel, although there was a time lag between the two factors. Conclusion: These results suggest that there is a causal association between climate change and squid populations. Climate change, especially ocean warming, appears to have been largely favorable for squid range expansion into Korean seas. Although the expansion may be helpful for the human food supply, the safety of the squid caught should be monitored since the concentrations of phosphorous and nitrogen in the sea water increased, which indicates that Korean seas have grown gradually more polluted.

An implementation of performance assessment system based on academic achievement analysis for promotion of self-directed learning ability (자기주도적 학습능력 촉진을 위한 학업성취도 분석 기반의 수행평가 시스템 구현)

  • Kim, Hyun-Jeong;Choi, Jin-Seek
    • Journal of The Korean Association of Information Education
    • /
    • v.13 no.3
    • /
    • pp.313-323
    • /
    • 2009
  • The objective of this paper is an implementation of analysing and predicting functions to promote self-directed learning for student's performance assessment system in programming subjects. By adapting Rubric model, the proposed functions inform a student of the assessment criteria and level to be carried out with respects to two-way specifications such as rational ability, problem solving ability and creativity. The proposed system also provides a graphical results of each ability instead of assessment result, for better understanding and analyzing himself/herself based on to the performance assessment and the result. Moreover, the proposed system contains a method to predict future achievement result with moving average technique. Therefore, an academic achievement can be precisely determined by himself/herself to estimate self-directed learning. The teacher can provide different level of educational resources such as supplement learning, problem explains and private instructor etc., in order to maximize efficiency of education.

  • PDF

Performance Evaluations of Four MAF-Based PLL Algorithms for Grid-Synchronization of Three-Phase Grid-Connected PWM Inverters and DGs

  • Han, Yang;Luo, Mingyu;Chen, Changqing;Jiang, Aiting;Zhao, Xin;Guerrero, Josep M.
    • Journal of Power Electronics
    • /
    • v.16 no.5
    • /
    • pp.1904-1917
    • /
    • 2016
  • The moving average filter (MAF) is widely utilized to improve the disturbance rejection capability of phase-locked loops (PLLs). This is of vital significance for the grid-integration and stable operation of power electronic converters to electric power systems. However, the open-loop bandwidth is drastically reduced after incorporating a MAF into the PLL structure, which makes the dynamic response sluggish. To overcome this shortcoming, some new techniques have recently been proposed to improve the transient response of MAF-based PLLs. In this paper, a comprehensive performance comparison of advanced MAF-based PLL algorithms is presented. This comparison includes HPLL, MPLC-PLL, QT1-PLL, and DMAF-PLL. Various disturbances, such as grid voltage sag, voltage flicker, harmonics distortion, phase-angle and frequency jumps, DC offsets and noise, are considered to experimentally test the dynamic performances of these PLL algorithms. Finally, an improved positive sequence extraction method for a HPLL under the frequency jumps scenario is presented to compensate for the steady-state error caused by non-frequency adaptive DSC, and a satisfactory performance has been achieved.

Study on R-peak Detection Algorithm of Arrhythmia Patients in ECG (심전도 신호에서 부정맥 환자의 R파 검출 알고리즘 연구)

  • Ahn, Se-Jong;Lim, Chang-Joo;Kim, Yong-Gwon;Chung, Sung-Taek
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.12 no.10
    • /
    • pp.4443-4449
    • /
    • 2011
  • ECG consists of various types of electrical signal on the heart, and feature point of these signals can be detected by analyzing the arrhythmia. So far, feature points extraction method for the detection of arrhythmia done in the many studies. However, it is not suitable for portable device using real time operation due to complicated operation. In this paper, R-peak were extracted using R-R interval and QRS width informations on patients. First, noise of low frequency bands eliminated using butterworth filter, and the R-peak was extracted by R-R interval moving average and QRS width moving average. In order to verify, it was experimented to compare the R-peak of data in MIT-BIH arrhythmia database and the R-peak of suggested algorithm. As a results, it showed an excellent detection for feature point of R-peak, even during the process of operation could be efficient way to confirm.

Forecasting the Air Cargo Demand With Seasonal ARIMA Model: Focusing on ICN to EU Route (계절성 ARIMA 모형을 이용한 항공화물 수요예측: 인천국제공항발 유럽항공노선을 중심으로)

  • Min, Kyung-Chang;Jun, Young-In;Ha, Hun-Koo
    • Journal of Korean Society of Transportation
    • /
    • v.31 no.3
    • /
    • pp.3-18
    • /
    • 2013
  • This study develops a forecasting method to estimate air cargo demand from ICN(Incheon International Airport) to all airports in EU with Seasonal Autoregressive Integrated Moving Average (SARIMA) Model using volumes from the first quarter of 2000 to the fourth quarter of 2009. This paper shows the superiority of SARIMA Model by comparing the forecasting accuracy of SARIMA with that of other ARIMA (Autoregressive Integrated Moving Average) models. Given that very few papers and researches focuses on air route, this paper will be helpful to researchers concerned with air cargo.

Time Series Analysis of Wind Pressures Acting on a Structure (구조물에 작용하는 풍압력의 시계열 분석)

  • 정승환
    • Journal of the Computational Structural Engineering Institute of Korea
    • /
    • v.13 no.4
    • /
    • pp.405-415
    • /
    • 2000
  • Time series of wind-induced pressure on a structure are modeled using autoregressive moving average (ARMA) model. In an AR process, the current value of the time series is expressed in terms of a finite, linear combination of the previous values and a white noise. In a MA process, the value of the time series is linearly dependent on a finite number of the previous white noises. The ARMA process is a combination of the AR and MA processes. In this paper, the ARMA models with several different combinations of the AR and MA orders are fitted to the wind-induced pressure time series, and the procedure to select the most appropriate ARMA model to represent the data is described. The maximum likelihood method is used to estimate the model parameters, and the AICC model selection criterion is employed in the optimization of the model order, which is assumed to be a measure of the temporal complexity of the pressure time series. The goodness of fit of the model is examined using the LBP test. It is shown that AR processes adequately fit wind pressure time series.

  • PDF

Long Terms Baseflow Separation Using Moving Average Method (이동평균법을 이용한 장기간 기저유출분석)

  • Lee, Sang-Sin;Lee, Sang-Il;Kim, Joon-Soo
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2010.05a
    • /
    • pp.1233-1237
    • /
    • 2010
  • 강변여과는 지표수와 지하수가 각기 갖는 장점과 제약점을 상호 보완하여 수질이 양호한 상수원수를 대량 확보하기 위한 실제적 대안이다. 자연적인 여과작용에 의해 수질이 개선되는 효과가 있어 경제적이고 안정적으로 확보할 수 있지만, 장기간 취수는 지하수위의 저하를 가져 올 수 있으므로 유역의 수문분석을 통한 기저유출량 산정에 관한 연구가 필요하다. 대상지역으로는 현재 강변여과를 개발중인 창원시 대산정수장 취수장 지역이며, 대상지역의 기저유출량을 산정하기 위해 대상지역 상류에 위치한 낙동강 본포교의 낙동강 유량을 기초로 기저유출량을 산정하여 지하수 함양율을 평가하였다. 수문곡선 분리는 여러 방법 중 다른 방법보다 상대적으로 간편하고 실무에서 많이 사용되는 방법인 수평직선분리법을 사용하여 적정 취수 가능량을 산정하기 위한 최소 기저유출량을 산정하고자 한다. 이에 따라, 보유 자료 중 연 평균 최저 유출량을 보인 2008년 가을 갈수기의 시작(2008년 10월)부터 2009년 가을 갈수기의 시작(2009년 10월)까지의 자료를 분석했다. 본포교 유량 자료는 8일부터 10일 간격으로 측정되고 있기 때문에 결측치는 최인접 두 지점 사이의 선형보간법으로 보완했다. 다소 많은 양의 결측치에 대한 보정과 해당 유역의 연간 유출 특성을 파악하기 위해서 이동평균(moving average)을 적용했으며, 적용 결과 관측 주기에 해당하는 10일 이동평균 유출수문곡선이 가장 적합한 것으로 나타났다. 10일 이동평균에 의한 유출수문곡선에 의하면 상승부의 기점은 2009년 6월 12일로 나타났으며 유출량은 47.87cms로 나타났다. 따라서 총 기저유출량은 상승부 기점의 유출량으로 111일 동안 발생하는 것을 알 수 있었으며 그 총량은 약 45,900만$m^3$으로 나타났다. 본 연구에서의 결과 본포교를 유역출구로 하는 이 유역에는 임의 유출이 생기는 호우사상 시, 기저유출량은 총 유출량의 6.38%를 최소한 기대할 수 있음을 알 수 있다.

  • PDF

Performance for simple combinations of univariate forecasting models (단변량 시계열 모형들의 단순 결합의 예측 성능)

  • Lee, Seonhong;Seong, Byeongchan
    • The Korean Journal of Applied Statistics
    • /
    • v.35 no.3
    • /
    • pp.385-393
    • /
    • 2022
  • In this paper, we consider univariate time series models that are well known in the field of forecasting and we study on forecasting performance for their simple combinations. The univariate time series models include exponential smoothing methods and ARIMA (autoregressive integrated moving average) models, their extended models, and non-seasonal and seasonal random walk models, which is frequently used as benchmark models for forecasting. The median and mean are simply used for the combination method, and the data set used for performance evaluation is M3-competition data composed of 3,003 various time series data. As results of evaluating the performance by sMAPE (symmetric mean absolute percentage error) and MASE (mean absolute scaled error), we assure that the simple combinations of the univariate models perform very well in the M3-competition dataset.

ACA: Automatic search strategy for radioactive source

  • Jianwen Huo;Xulin Hu;Junling Wang;Li Hu
    • Nuclear Engineering and Technology
    • /
    • v.55 no.8
    • /
    • pp.3030-3038
    • /
    • 2023
  • Nowadays, mobile robots have been used to search for uncontrolled radioactive source in indoor environments to avoid radiation exposure for technicians. However, in the indoor environments, especially in the presence of obstacles, how to make the robots with limited sensing capabilities automatically search for the radioactive source remains a major challenge. Also, the source search efficiency of robots needs to be further improved to meet practical scenarios such as limited exploration time. This paper proposes an automatic source search strategy, abbreviated as ACA: the location of source is estimated by a convolutional neural network (CNN), and the path is planned by the A-star algorithm. First, the search area is represented as an occupancy grid map. Then, the radiation dose distribution of the radioactive source in the occupancy grid map is obtained by Monte Carlo (MC) method simulation, and multiple sets of radiation data are collected through the eight neighborhood self-avoiding random walk (ENSAW) algorithm as the radiation data set. Further, the radiation data set is fed into the designed CNN architecture to train the network model in advance. When the searcher enters the search area where the radioactive source exists, the location of source is estimated by the network model and the search path is planned by the A-star algorithm, and this process is iterated continuously until the searcher reaches the location of radioactive source. The experimental results show that the average number of radiometric measurements and the average number of moving steps of the ACA algorithm are only 2.1% and 33.2% of those of the gradient search (GS) algorithm in the indoor environment without obstacles. In the indoor environment shielded by concrete walls, the GS algorithm fails to search for the source, while the ACA algorithm successfully searches for the source with fewer moving steps and sparse radiometric data.