• Title/Summary/Keyword: moving-average method

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Design and Estimation of Cordless Transmitter & Receiver for Measurement of Crane Moving Range (크레인의 이동거리 측정을 위한 무선 송수신기 설계 및 평가)

  • Kim, Tae-Soo;Oh, Inn-Yeal;Chun, Joong-Chang
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.4
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    • pp.808-814
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    • 2007
  • In this paper, the measurement system of crane moving range is concerned with range recognition technology using phase and magnitude of radio wave. By the proposed technology, we design the radio transmitter and receiver and realize the measurement system, and save the data in disk that is earned from 900Mhz RF signal, middle frequency 450khz of analog signal. As a result of RF measurement, we got 9.3 dBm of RF output and 96 dBc@10khz of phase noise. Range information is earned the data through digital signal processing of IF signal. For the estimation of range measured, we analyze the difference between real range and measurement range, and also suggest the method to remove the measurement error using average processing and amplitude properties. A result is 0.12 and 0.00422 deviation in l0mn-30m and within 5m respectively, and then 2.4E-04 deviation in 4m by using compensation of level characteristics lately.

A Study on the Disaggregation Method of Time Series Data (시계열 자료의 분할에 관한 사례 연구)

  • Moon, Sungho;Lee, Jeong-Hyeong
    • Journal of Digital Convergence
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    • v.12 no.6
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    • pp.155-160
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    • 2014
  • When we collect marketing data, we can only obtain the bimonthly or quarterly data but the monthly data be available. If we evaluate or predict monthly market condition or establish monthly marketing strategies, we need to disaggregate these bimonthly or quarterly data to the monthly data. In this paper, for bimonthly or quarterly data, we introduce some methods of disaggregation to monthly data. These disaggregation methods include the simple average method, the growth rate method, the weighting method by the judgment of experts, and variable decomposition method using 12 month moving cumulative sum. In this paper, we applied variable decomposition method to disaggregate for bimonthly data of sum of electronics sales in a European country. We, also, introduce how to use this method to predict the future data.

Implementation of Finger-Gesture Game Controller using CAMShift and Double Circle Tracing Method (CAMShift와 이중 원형 추적법을 이용한 손 동작 게임 컨트롤러 구현)

  • Lee, Woo-Beom
    • Journal of the Institute of Convergence Signal Processing
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    • v.15 no.2
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    • pp.42-47
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    • 2014
  • A finger-gesture game controller using the single camera is implemented in this paper, which is based on the recognition of the number of fingers and the index finger moving direction. Proposed method uses the CAMShift algorithm to trace the end-point of index finger effectively. The number of finger is recognized by using a double circle tracing method. Then, HSI color mode transformation is performed for the CAMShift algorithm, and YCbCr color model is used in the double circle tracing method. Also, all processing tasks are implemented by using the Intel OpenCV library and C++ language. In order to evaluate the performance of the proposed method, we developed a shooting game simulator and validated the proposed method. The proposed method showed the average recognition ratio of more than 90% for each of the game command-mode.

Comparison of Soil Evaporation Using Equilibrium Evaporation, Eddy-Covariance and Surface Soil Moisture on the Forest Hillslope (산림 사면에서 토양수분 실측 자료, 평형증발 및 에디-공분산방법을 이용한 토양증발비교)

  • Gwak, Yong-Seok;Kim, Sang-Hyun;Kim, Su-Jin
    • Journal of Environmental Science International
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    • v.22 no.1
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    • pp.119-129
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    • 2013
  • We compared equilibrium evaporation($E_{equili}$) eddy-covariance($E_{eddy}$) with soil moisture data($E_{SMseries}$) which were measured with a 2 hours sampling interval at three points for a humid forest hillslope from May 5th to May 31th in 2009. Accumulations of $E_{eddy}$, $E_{equili}$ for the study period were estimated as 2.52, 3.28 mm and those of $E_{SMseries}$ were ranged from 1.91 to 2.88 mm. It suggested that the eddy-covariance method considering the spatial heterogeneity of soil evaporation is useful to evaluate the soil evaporation. Method A, B and C were proposed using mean meterological data and daily moisture variation and the computations were compared to eddy-covariance method and equilibrium evaporation. The methods using soil moisture data can describe the variations of soil evaporation from eddy-covariance through simple moving average analysis. Method B showed a good matched with eddy-covariance method. This indicated that Dry Surface Layer (DSL) at 14:00 which was used for method B is important variable for the evaluation of soil evaporation. The total equilibrium evaporation was not significantly different to those of the others. However, equilibrium evaporation showed a problem in estimating soil evaporation because the temporal tendency of $E_{equili}$ was not related with the those of the other methods. The improved understanding of the soil evaporation presented in this study will contribute to the understandings of water cycles in a forest hillslope.

An Empirical Study on Predictive Modeling to enhance the Product-Technical Roadmap (제품-기술로드맵 개발을 강화하기 위한 예측모델링에 관한 실증 연구)

  • Park, Kigon;Kim, YoungJun
    • Journal of Technology Innovation
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    • v.29 no.4
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    • pp.1-30
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    • 2021
  • Due to the recent development of system semiconductors, technical innovation for the electric devices of the automobile industry is rapidly progressing. In particular, the electric device of automobiles is accelerating technology development competition among automobile parts makers, and the development cycle is also changing rapidly. Due to these changes, the importance of strategic planning for R&D is further strengthened. Due to the paradigm shift in the automobile industry, the Product-Technical Roadmap (P/TRM), one of the R&D strategies, analyzes technology forecasting, technology level evaluation, and technology acquisition method (Make/Collaborate/Buy) at the planning stage. The product-technical roadmap is a tool that identifies customer needs of products and technologies, selects technologies and sets development directions. However, most companies are developing the product-technical roadmap through a qualitative method that mainly relies on the technical papers, patent analysis, and expert Delphi method. In this study, empirical research was conducted through simulations that can supplement and strengthen the product-technical roadmap centered on the automobile industry by fusing Gartner's hype cycle, cumulative moving average-based data preprocessing, and deep learning (LSTM) time series analysis techniques. The empirical study presented in this paper can be used not only in the automobile industry but also in other manufacturing fields in general. In addition, from the corporate point of view, it is considered that it will become a foundation for moving forward as a leading company by providing products to the market in a timely manner through a more accurate product-technical roadmap, breaking away from the roadmap preparation method that has relied on qualitative methods.

The Location Estimation Method through Snooping Node for Indoor Environment (실내에서 보정노드를 통한 위치추정 기법)

  • Park, Hyun-Moon;Shin, Soo-Young;NamGung, Jung-Il;Park, Soo-Huyn
    • Journal of Korea Multimedia Society
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    • v.11 no.2
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    • pp.182-196
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    • 2008
  • The location estimation using sensor network has been considerably researched. The methods taking the differences of the forms of location estimation between indoors and outdoors into consideration have been studied. While it is possible for outdoor location to be estimated because outdoor location estimation has a consistent distribution during unit period through the value of RSSI(Received Signal Strength Indication) on outdoor location estimation, Indoor location estimation is difficult since multi-path and interference indoors are higher than those outdoors and indoor location estimation can be affected by other factors. In this paper, we revise the information of RSSI changed by multi-path and interference through the Moving Average method and K-means algorithm and propose the method of estimation for the value of RSSI with reliability in the group of signals received during unit period. We also suggest the way to put some weights on fixed nodes in network using a snooping node on location estimation and then evaluate the efficiency of location awareness as compared with the existing method by implementing proposed method on system through the reconfiguration of network.

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Development of Vehicle Classification Algorithm Using Magnetometer Detector (자석검지기를 이용한 차종인식 알고리즘개발)

  • 김수희;오영태;조형기;이철기
    • Journal of Korean Society of Transportation
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    • v.17 no.4
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    • pp.111-124
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    • 1999
  • The Purpose of this thesis is to develop a vehicle classification algorithm using single Magnetometer detector during presence time of vehicle detection and is to examine a held application from field test. We collected data using Magnetometer detector on freeway and used digital data to change voltage values according to magnetic flux density in analysis. We collected these datum during the presence time and then obtained characteristics from wave form in these datum. Based on these characteristics, We used the following three methods for this a1gorithm :1. Template Matching Method,2. Neural Network Method using Back-propagation Algorithm 3. Complex Method using changed slope points and mixing method 1, 2. Of course, Before processing of over three methods, These data were processed normalizing by 20, 40 of size in only X axis and moving average by 0, 3, 4, 5 of size. Vehicle classification were Processed in three steps ; 2, 3, 5 types classification. In 2 types vehicle classification, recognition rate is 83% by template matching method.

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A Study of Drought Spatio-Temporal Characteristics Using SPI-EOF Analysis (SPI 가뭄지수의 EOF 분석을 이용한 가뭄의 시공간적인 특성 연구)

  • Chang Yung-Yu;Kim Sang-Dan;Choi Gye-Woon
    • Journal of Korea Water Resources Association
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    • v.39 no.8 s.169
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    • pp.691-702
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    • 2006
  • This study introduced a method to evaluate the probability of a specific area to be affected by a drought of a given severity and shows Its potential for investigating agricultural drought characteristics. The method was applied to South Korea as a case study. The proposed procedure included Standardized Precipitation Index(SPI) time series, which were linearly transformed by the Empirical Orthogonal Functions(EOF) method. These EOFs were extended temporally with AutoRegressive Moving Average(ARMA) method and spatially with Kriging method. By performing these simulations, long time series of SPI can be simulated for each designed grid cell in whole area. The probability distribution functions of the area covered by a drought and the drought severity are then derived and combined to produce drought severity-area-frequency(SAF) curves.

Target bit allocation algorithm for generation of high quality static test stream (고화질 정지화 테스트 스트림의 생성을 위한 목표비트 할당 알고리즘)

  • Lee Gwang soon;Han Chan ho;Jang Soo wook;Kim Eun su;Sohng Kyu ik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.3C
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    • pp.147-152
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    • 2005
  • In this paper, we proposed a method for compressing the static video test patterns in high quality to test the picture quality in DTV. In our method, we use the fact that the generated bits and average quantization value have almost identical distribution characteristics per each GOP and we propose a new target bit allocation method suitable for compressing the static test pattern while the target bit allocation method in MPEG-2 TM5 is suitable for the moving picture. The proposed target bit allocation method is to maintain the high quality video continuously by using the normalized complexities which are updated or maintained by means of picture qualities at each GOP. Experiment result showed that the test pattern stream encoded by MPEG-2 software with the proposed algorithm had a stable bit rate and good video quality during the decoding process.

Application of SARIMA Model in Air Cargo Demand Forecasting: Focussing on Incheon-North America Routes (항공화물수요예측에서 계절 ARIMA모형 적용에 관한 연구: 인천국제공항발 미주항공노선을 중심으로)

  • SUH, Bo Hyoun;YANG, Tae Woong;HA, Hun-Koo
    • Journal of Korean Society of Transportation
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    • v.35 no.2
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    • pp.143-159
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    • 2017
  • For forecasting air cargo demand from Incheon National Airport to all of airports in the United States (US), this study employed the Seasonal Autoregressive Integrated Moving Average (SARIMA) method and the time-series data collected from the first quarter of 2003 to the second quarter of 2016. By comparing the SARIMA method against the ARIMA method, it was found that the SARIMA method performs well, relatively with time series data highlighting seasonal periodic characteristics. While existing previous research was generally focused on the air passenger and the air cargo as a whole rather than specific air routes, this study emphasized on a specific air cargo demand to the US route. The meaningful findings would support the future research.