• Title/Summary/Keyword: partial time series data

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A possible application of the PD detection technique using electro-optic Pockels cell with nonlinear characteristic analysis on the PD signals (포켈스 소자를 이용한 PD 신호의 검출 및 비선형적 해석에 관한 연구)

  • Lim, Y.S.;Kang, W.J.;Chang, Y.M.;Koo, J.Y.
    • Proceedings of the KIEE Conference
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    • 2000.07c
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    • pp.1850-1852
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    • 2000
  • In this paper, new Partial Discharge (PD) detection technique using Pockels cell was proposed and considerable apparent chaotic characteristics were discussed. For this purpose, PD was generated from needle-plane electrode in air and detected by optical measuring system using Pockels cell, based on Mach-Zehnder interferometer, consisting of He-Ne laser, single mode optical fiber, 50/50 beam splitter and photo detector. A qualitative analysis was carried out by drawing Return map for the normalized time series of the detected PD signals. The results are as follows:(a) Fixed points, between 0.7 and 1.0, are appeared clearly in the right upper area of the return map as the increase in the number of obtained data.(b) Considerable periodicity have been remarked even though exact period and length can not be determined.(c) The self-similarity can be also observed inasmuch as the late paths do not follow the previous ones. Accordingly, exact quantitative analysis such as embedding dimension, fractal dimension, and Lyapunov exponents should be carried out for deducing the quantitative properties regarding PD phenomena.

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Time-series Analysis of Seawater Temperature in the Garolim Bay, the West Coast of Korea (서해 가로림만 수온의 시계열 분석)

  • Yang, Joon-Yong;Cho, Sunghee;Lee, Joon-Soo;Han, Changhoon;Heo, Seung
    • Journal of Environmental Science International
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    • v.30 no.7
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    • pp.585-595
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    • 2021
  • We used seawater temperature data, measured in the Garolim Bay, to analyze temperature variation on an hourly and daily basis. Lagrange's interpolation using before and after data was applied to restore nonconsecutive missing temperature data. The estimated error of the data restoration was 0.11℃. Spectral analyses of seawater temperature showed significant periodicities of approximately 12.4 h (semidiurnal tide) and 15.0 d (long-period tide), which is close to those of M2 and Mf partial tides. Variation in seawater temperature was correlated more with tidal height than with air temperature around the Garolim Bay. In June and December, when the seawater temperature difference between the inside and outside of the Garolim Bay was very large, the periodicities of 12.4 h and 15.0 d were highly prominent. These results indicate that the exchange of seawater between the inside and outside of the Garolim Bay induced variations in seawater temperature owing to tide. Understanding temperature variation because of tide helps to prevent abnormal mortality of cultured fish and to predict seawater temperature in the Garolim Bay.

A Study of the Abalone Outlook Model Using by Partial Equilibrium Model Approach Based on DEEM System (부분균형모형을 이용한 전복 수급전망모형 구축에 관한 연구)

  • Han, Suk-Ho;Jang, Hee-Soo;Heo, Su-Jin;Lee, Nam-Su
    • The Journal of Fisheries Business Administration
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    • v.51 no.2
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    • pp.51-69
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    • 2020
  • The purpose of this study is to construct an outlook model that is consistent with the "Fisheries Outlook" monthly published by the Fisheries Outlook Center of the Korea Maritime Institute(KMI). In particular, it was designed as a partial equilibrium model limited to abalone items, but a model was constructed with a dynamic ecological equation model(DEEM) system taking into account biological breeding and shipping time. The results of this study are significant in that they can be used as basic data for model development of various items in the future. In this study, due to the limitation of monthly data, the market equilibrium price was calculated by using the recursive model construction method to be calculated directly as an inverse demand. A model was built in the form of a structural equation model that can explain economic causality rather than a conventional time series analysis model. The research results and implications are as follows. As a result of the estimation of the amount of young seashells planting, it was estimated that the coefficient of the amount of young seashells planting from the previous year was estimated to be 0.82 so that there was no significant difference in the amount of young seashells planting this year and last year. It is also meant to be nurtured for a long time after aquaculture license and limited aquaculture area(edge style) and implantation. The economic factor, the coefficient of price from last year was estimated at 0.47. In the case of breeding quantity, it was estimated that the longer the breeding period, the larger the coefficient of breeding quantity in the previous period. It was analyzed that the impact of shipments on the breeding volume increased. In the case of shipments, the coefficient of production price was estimated unelastically. As the period of rearing increased, the estimation coefficient decreased. Such result indicates that the expected price, which is an economic factor variable and that had less influence on the intention to shipments. In addition, the elasticity of the breeding quantity was estimated more unelastically as the breeding period increased. This is also correlated with the relative coefficient size of the expected price. The abalone supply and demand forecast model developed in this study is significant in that it reduces the prediction error than the existing model using the ecological equation modeling system and the economic causal model. However, there are limitations in establishing a system of simultaneous equations that can be linked to production and consumption between industries and items. This is left as a future research project.

A Study on the Volatility Transition of Steel Raw Material Transport Market (제철원료 운송시장의 변동성 전이 분석에 대한 연구)

  • Yo-Pyung Hwang;Ye-Eun Oh;Keun-Sik Park
    • Korea Trade Review
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    • v.47 no.4
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    • pp.215-231
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    • 2022
  • Analysis and forecasting of the Baltic Capsize Index (BCI) is important for managing an entity's losses and risks from the uncertainty and volatility of the fast-changing maritime transport market in the future. This study conducted volatility transition analysis through the GARCH model, using BCI which is highly related to steel raw materials. As for the data, 2,385 monthly data were used from March 1999 to March 2021. In this study, after basic statistical analysis, unit root and cointegration test, the GARCH, EGARCH, and DCC-GARCH models were used for volatility transition analysis. As the results of GARCH and EGARCH model, we confirmed that all variables had no autocorrelation between the standardized residuals for error terms and the square of residuals, that the variability of all variables at this time was likely to persist in the future, and that the variability of the time-series error term impact according to Iron ore trade (IoT). In addition, through the EGARCH model, the magnitude convenience of all variables except the Iron ore price (IOP) and Capesize bulk fleet (BCF) variables was greater than the positive value (+). As a result of analyzing the DCC-GARCH (1,1) model, partial linear combinations were confirmed over the entire period. Estimating the effect of variability transition on BCF and C5 with statistically significant linear combinations with BCI confirmed that the impact of BCF on BCI was greater than the impact of BCI itself.

Filtered Coupling Measures for Variable Selection in Sparse Vector Autoregressive Modeling (필터링된 잔차를 이용한 희박벡터자기회귀모형에서의 변수 선택 측도)

  • Lee, Seungkyu;Baek, Changryong
    • The Korean Journal of Applied Statistics
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    • v.28 no.5
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    • pp.871-883
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    • 2015
  • Vector autoregressive (VAR) models in high dimension suffer from noisy estimates, unstable predictions and hard interpretation. Consequently, the sparse vector autoregressive (sVAR) model, which forces many small coefficients in VAR to exactly zero, has been suggested and proven effective for the modeling of high dimensional time series data. This paper studies coupling measures to select non-zero coefficients in sVAR. The basic idea based on the simulation study reveals that removing the effect of other variables greatly improves the performance of coupling measures. sVAR model coefficients are asymmetric; therefore, asymmetric coupling measures such as Granger causality improve computational costs. We propose two asymmetric coupling measures, filtered-cross-correlation and filtered-Granger-causality, based on the filtered residuals series. Our proposed coupling measures are proven adequate for heavy-tailed and high order sVAR models in the simulation study.

Removal of Intersected Region for Efficient Transmission of Spatial Objects (공간 객체의 효율적 전송을 위한 교차영역의 제거)

  • Lee, Kyung-Mo;Park, Dong-Seon;Kim, Jae-Hong;Bae, Hae-Young
    • Journal of Korea Spatial Information System Society
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    • v.1 no.2 s.2
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    • pp.137-149
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    • 1999
  • Spatial database systems in client-server environment have network overload due to the large amount of spatial data transmission. Users use the window query that loads partial region of a whole map for quick response time in the environment. A series of window query such as screen movement, enlargement or shrinkage requires data in similar region and this increases network overload by re-transmitting the same data in intersected region with the earlier transmitted region. Removing the transmitted data from query results can solve this problem. In this paper, we design and implement a spatial object manager in order to remove the intersected region occurred by a series of window query. The spatial object manager manages the object identifiers of transmitted objects and removes transmitted objects from spatial objects of the query result by using the removal technique of the intersected region for the transmission and comparison. We utilize GEOMania Millennium server, an open client-server spatial database system, as spatial object manager in this paper. The result of the performance evaluation shows that the spatial object manager removes the transmission of the data redundancy, reduces network overload and improves the overall system performance.

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Investigation and Analysis of Shoreline Change using DGPS - Focusing on the Gangnung City Shore in Gangwondo - (DGPS를 이용한 해안선 변화 조사 및 분석 - 강원도 강릉시 연안을 중심으로 -)

  • Lee, Hyung-Seok;Kim, In-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.10 no.2
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    • pp.1-10
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    • 2007
  • The tendency of erosion and accretion of the coast has occurred by the wanton development of a shore so that establishing the plans of nature preservation and development according to shoreline change is in demand. In this study, six DGPS positioning are executed in the periodic interval of about 2 months to choose coastal area of Gangnung, Gangwon-do and the observation data which is post-processed about 50cm accuracies on the Gangnung regular service is compared with digital map in 1998 and digital chart in 2006. Comparing DGPS values with shoreline of digital map, we know that erosion has occurred locally around training dike placed in Gangmun harbor and in southern Namhangjin, many accretions has happened near the breakwater of Namhangjin region and partial accretion is occurring in the other area. Therefore DGPS which is an acquisition method suitable for GIS data input is in use to collect the horizontal data and it could be used effectively to measure the shoreline change of time series through the long-term continuous observation by the coastal development.

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Characteristic Analysis of the Changes of Landscape Architecture Construction Costs in Time-series - Focused on the Cases of Works of Public Institution's at Capital Area - (아파트단지 조경 공사비의 공종별 경년변화 특성 분석 - 공공기관 시행의 수도권 아파트단지를 중심으로 -)

  • Park, Sang-Jin;Cho, Se-Hwan
    • Journal of the Korean Institute of Landscape Architecture
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    • v.43 no.6
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    • pp.150-159
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    • 2015
  • This study was conducted for the purpose of presenting basic data for calculating a more reasonable landscaping project cost in the future through the construction cost calculation ratio of scenic planting and facilities and their time series trend analysis targeting 'J' corporation, a representative Korean public institution that creates apartment complexes. This study targeted scenic planting and the facility construction costs of 37 apartment complexes in the capital area from 2004 to 2012, using statistical analysis methods such as technical analysis, correlation analysis, and regression analysis to analyze the characteristics of the time series change. The conclusion was drawn as follows. First, breaking down the cost of overall landscaping projects to scenic planting and facility construction, the ratio of the average cost of scenic planting to that of facility construction showed 56.1% to 43.9% from 2004 to 2012. Second, the costs of planting construction and facility construction both showed a fluctuation range of about ${\pm}3%$, implying relatively steady costs considering the inflation rate. Third, the landscape construction cost for each type of construction resulted in a fluctuation range from minimum ${\pm}3%$(exercise facility) to maximum ${\pm}5%$(packing facility), reflecting that among the landscaping projects, the facility construction costs tended to show relatively large fluctuations in accordance with the change of time series. Fourth, the comprehensive indication of the ratio of landscaping project costs by time series and landscaping construction type implies that the regional characteristics and positional condition of the apartment complexes were not reflected sufficiently. Fifth, the high level of correlation of landscaping construction types and landscaping construction elements imply that the entire construction costs were controlled through partial adjustment of cost components within the overall frame of construction cost. These results reveal the problems of standardized landscaping cost irrespective of user satisfaction or environmental traits such as the conditions of the apartment complexes.

MEAT SPECIATION USING A HIERARCHICAL APPROACH AND LOGISTIC REGRESSION

  • Arnalds, Thosteinn;Fearn, Tom;Downey, Gerard
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1245-1245
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    • 2001
  • Food adulteration is a serious consumer fraud and a matter of concern to food processors and regulatory agencies. A range of analytical methods have been investigated to facilitate the detection of adulterated or mis-labelled foods & food ingredients but most of these require sophisticated equipment, highly-qualified staff and are time-consuming. Regulatory authorities and the food industry require a screening technique which will facilitate fast and relatively inexpensive monitoring of food products with a high level of accuracy. Near infrared spectroscopy has been investigated for its potential in a number of authenticity issues including meat speciation (McElhinney, Downey & Fearn (1999) JNIRS, 7(3), 145-154; Downey, McElhinney & Fearn (2000). Appl. Spectrosc. 54(6), 894-899). This report describes further analysis of these spectral sets using a hierarchical approach and binary decisions solved using logistic regression. The sample set comprised 230 homogenized meat samples i. e. chicken (55), turkey (54), pork (55), beef (32) and lamb (34) purchased locally as whole cuts of meat over a 10-12 week period. NIR reflectance spectra were recorded over the wavelength range 400-2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. The problem was defined as a series of binary decisions i. e. is the meat red or white\ulcorner is the red meat beef or lamb\ulcorner, is the white meat pork or poultry\ulcorner etc. Each of these decisions was made using an individual binary logistic model based on scores derived from principal component or partial least squares (PLS1 and PLS2) analysis. The results obtained were equal to or better than previous reports using factorial discriminant analysis, K-nearest neighbours and PLS2 regression. This new approach using a combination of exploratory and logistic analyses also appears to have advantages of transparency and the use of inherent structure in the spectral data. Additionally, it allows for the use of different data transforms and multivariate regression techniques at each decision step.

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MEAT SPECIATION USING A HIERARCHICAL APPROACH AND LOGISTIC REGRESSION

  • Arnalds, Thosteinn;Fearn, Tom;Downey, Gerard
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1152-1152
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    • 2001
  • Food adulteration is a serious consumer fraud and a matter of concern to food processors and regulatory agencies. A range of analytical methods have been investigated to facilitate the detection of adulterated or mis-labelled foods & food ingredients but most of these require sophisticated equipment, highly-qualified staff and are time-consuming. Regulatory authorities and the food industry require a screening technique which will facilitate fast and relatively inexpensive monitoring of food products with a high level of accuracy. Near infrared spectroscopy has been investigated for its potential in a number of authenticity issues including meat speciation (McElhinney, Downey & Fearn (1999) JNIRS, 7(3), 145 154; Downey, McElhinney & Fearn (2000). Appl. Spectrosc. 54(6), 894-899). This report describes further analysis of these spectral sets using a hierarchical approach and binary decisions solved using logistic regression. The sample set comprised 230 homogenized meat samples i. e. chicken (55), turkey (54), pork (55), beef (32) and lamb (34) purchased locally as whole cuts of meat over a 10-12 week period. NIR reflectance spectra were recorded over the wavelength range 400-2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. The problem was defined as a series of binary decisions i. e. is the meat red or white\ulcorner is the red meat beef or lamb\ulcorner, is the white meat pork or poultry\ulcorner etc. Each of these decisions was made using an individual binary logistic model based on scores derived from principal component or partial least squares (PLS1 and PLS2) analysis. The results obtained were equal to or better than previous reports using factorial discriminant analysis, K-nearest neighbours and PLS2 regression. This new approach using a combination of exploratory and logistic analyses also appears to have advantages of transparency and the use of inherent structure in the spectral data. Additionally, it allows for the use of different data transforms and multivariate regression techniques at each decision step.

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