• Title/Summary/Keyword: Correlation model

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Using an Intervention Model for Occupational Therapy Service Specialist Based on a Special Education Supporting Center (특수교육지원센터에 기반을 둔 작업치료서비스 전문가의 중재모델 사용)

  • Kim, Se-Yun;Kim, Su-Jung
    • The Journal of the Korea Contents Association
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    • v.11 no.4
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    • pp.225-234
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    • 2011
  • The purpose of this study was to survey the intervention model, intervention settings, intervention time, factors influencing selection of intervention model, relationship between intervention model and areas which supporting center for special education based occupational therapist was using. Study data were provided by 46 therapy supporting service professionals through e-mail and analyzed. The findings indicated that first, the therapy supporting service professionals often employed a direct therapy(individual) focusing on performance component of child. Second, they believed that direct therapy is most effective in improving children's performance and raising awareness of the importance of occupational therapy. Third, when choose intervention model, they took into consideration the child's performance components deficits and mind of team chief. Fourth, no correlation between the application time and the perception of effectiveness of intervention model. Also didn't find correlation between applying time of intervention model and intervention area. When putting the various research result together, the model school-based occupational therapists using was similar to medical model. Therefore it is need a study to develop effective intervention model and apply it in school environment.

A Study on the Wrist Pulse Six Positions Correlation in the Maiyaojingweilun Chapter of the Huangdineijing (『소문(素問)·맥요정미론(脈要精微論)』의 촌구(寸口) 육부정위(六部定位)에 대한 고찰)

  • Jang, Woochang;Nan, Jie
    • Journal of Korean Medical classics
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    • v.34 no.3
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    • pp.101-123
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    • 2021
  • Objectives : To examine the six positions correlation[六部定位] principle that is the basis of the wrist pulse diagnosis in the Neijing. Methods : The basis for argument was established by correcting an interpretation error of the theory of chi (尺) skin diagnosis. In order to accomplish this, the annotations of Yang Shangshan and Wangbing were investigated first, after which the specific meaning and methodology of the chi diagnostic method as written in many chapters of the Neijing were examined. The evidence and reasoning for the six positions correlation[六部定位] was looked into, in relation to Wangbing's annotation of the chapter, Maiyaojingweilun. The theoretical basis of the six positions correlation was searched throughout the entire Neijing, based on the correlation between Liuhe and the six positions, the five elements inter-supporting theory embedded in the six positions correlation as a diagnosis model that integrates zhangfu and meridians/channels, and the meaning of the spacial concepts used when describing the tactile technique within the chapter. Lastly, contents related to the five zhang channels within the Neijing were reviewed, to determine whether the six positions correlation was applied in wrist pulse taking Results & Conclusions : Some interpretations of the verse on matching the positions in the Maiyaojingweilun chapter of the Neijing are erroneous, while the argument that the three positions[cun-guan-chi] cannot be found in the Neijing is false as well. The wrist pulse taking in the Neijing is precisely based on the three positions correlation that divides the cun-guan-chi positions into three, and the correlation verse in the Maiyaojingweilun chapter clearly suggests the principle of matching the zhangfu and meridian/channels to the six positions of the cun-guan-chi of both left and right.

Multidimensional Optimization Model of Music Recommender Systems (음악추천시스템의 다차원 최적화 모형)

  • Park, Kyong-Su;Moon, Nam-Me
    • The KIPS Transactions:PartB
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    • v.19B no.3
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    • pp.155-164
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    • 2012
  • This study aims to identify the multidimensional variables and sub-variables and study their relative weight in music recommender systems when maximizing the rating function R. To undertake the task, a optimization formula and variables for a research model were derived from the review of prior works on recommender systems, which were then used to establish the research model for an empirical test. With the research model and the actual log data of real customers obtained from an on line music provider in Korea, multiple regression analysis was conducted to induce the optimal correlation of variables in the multidimensional model. The results showed that the correlation value against the rating function R for Items was highest, followed by Social Relations, Users and Contexts. Among sub-variables, popular music from Social Relations, genre, latest music and favourite artist from Items were high in the correlation with the rating function R. Meantime, the derived multidimensional recommender systems revealed that in a comparative analysis, it outperformed two dimensions(Users, Items) and three dimensions(Users, Items and Contexts, or Users, items and Social Relations) based recommender systems in terms of adjusted $R^2$ and the correlation of all variables against the values of the rating function R.

Analysis of Urban Heat Island Effect Using Time Series of Landsat Images and Annual Temperature Cycle Model (시계열 Landsat TM 영상과 연간 지표온도순환 모델을 이용한 열섬효과 분석)

  • Hong, Seung Hwan;Cho, Han Jin;Kim, Mi Kyeong;Sohn, Hong Gyoo
    • Journal of Korean Society for Geospatial Information Science
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    • v.23 no.1
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    • pp.113-121
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    • 2015
  • Remote sensing technology using a multi-spectral satellite imagery can be utilized for the analysis of urban heat island effect in large area. However, weather condition of Korea mostly has a lot of clouds and it makes periodical observation using time-series of satellite images difficult. For this reason, we proposed the analysis of urban heat island effect using time-series of Landsat TM images and ATC model. To analyze vegetation condition and urbanization, NDVI and NDBI were calculated from Landsat images. In addition, land surface temperature was calculated from thermal infrared images to estimate the parameters of ATC model. Furthermore, the parameters of ATC model were compared based on the land cover map created by Korean Ministry of Environment to analyze urban heat island effect relating to the pattern of land use and land cover. As a result of a correlation analysis between calculated spectral indices and parameters of ATC model, MAST had high correlation with NDVI and NDBI (-0.76 and 0.69, respectively) and YAST also had correlation with NDVI and NDBI (-0.53 and 0.42, respectively). By comparing the parameters of ATC model based on land cover map, urban area had higher MAST and YAST than agricultural land and grassland. In particular, residential areas, industrial areas, commercial areas and transportation facilities showed higher MAST than cultural facilities and public facilities. Moreover, residential areas, industrial areas and commercial areas had higher YAST than the other urban areas.

The Effect of First Observation in Panel Regression Model with Serially Correlated Error Components

  • Song, Seuck-Heun
    • Communications for Statistical Applications and Methods
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    • v.6 no.3
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    • pp.667-676
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    • 1999
  • We investigate the effects of omission of initial observations in each individuals in the panel data regression model when the disturbances follow a serially correlated one way error components. We show that the first transformed observation can have a relative large hat matrix diagonal component and a large influence on parameter estimates when the correlation coefficient is large in absolute value.

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Performance Analysis of Simulation of Asian Dust Observed in 2010 by the all-Season Dust Forecasting Model, UM-ADAM2 (사계절 황사단기예측모델 UM-ADAM2의 2010년 황사 예측성능 분석)

  • Lee, Eun-Hee;Kim, Seungbum;Ha, Jong-Chul;Chun, Youngsin
    • Atmosphere
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    • v.22 no.2
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    • pp.245-257
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    • 2012
  • The Asian dust (Hwangsa) forecasting model, Asian Dust Aerosol Model (ADAM) has been modified by using satelliate monitoring of surface vegetation, which enables to simulate dusts occuring not only in springtime but also for all-year-round period. Coupled with the Unified Model (UM), the operational weather forecasting model at KMA, UM-ADAM2 was implemented for operational dust forecasting since 2010, with an aid of development of Meteorology-Chemistry Interface Processor (MCIP) for usage UM. The performance analysis of the ADAM2 forecast was conducted with $PM_{10}$ concentrations observed at monitoring sites in the source regions in China and the downstream regions of Korea from March to December in 2010. It was found that the UM-ADAM2 model was able to simulate quite well Hwangsa events observed in spring and wintertime over Korea. In the downstream region of Korea, the starting and ending times of dust events were well-simulated, although the surface $PM_{10}$ concentration was slightly underestimated for some dust events. The general negative bias less than $35{\mu}g\;m^{3}$ in $PM_{10}$ is found and it is likely to be due to other fine aerosol species which is not considered in ADAM2. It is found that the correlation between observed and forecasted $PM_{10}$ concentration increases as forecasting time approaches, showing stably high correlation about 0.7 within 36 hr in forecasting time. This suggests the possibility that there is potential for the UM-ADAM2 model to be used as an operational Asian dust forecast model.

Evolutionary Optimization of Pulp Digester Process Using D-optimal DOE and RSM

  • Chu, Young-Hwan;Chonghun Han
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.395-395
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    • 2000
  • Optimization of existing processes becomes more important than the past as environmental problems and concerns about energy savings stand out. When we can model a process mathematically, we can easily optimize it by using the model as constraints. However, modeling is very difficult for most chemical processes as they include numerous units together with their correlation and we can hardly obtain parameters. Therefore, optimization that is based on the process models is, in turn, hard to perform. Especially, f3r unknown processes, such as bioprocess or microelectronics materials process, optimization using mathematical model (first principle model) is nearly impossible, as we cannot understand the inside mechanism. Consequently, we propose a few optimization method using empirical model evolutionarily instead of mathematical model. In this method, firstly, designing experiments is executed fur removing unecessary experiments. D-optimal DOE is the most developed one among DOEs. It calculates design points so as to minimize the parameters variances of empirical model. Experiments must be performed in order to see the causation between input variables and output variables as only correlation structure can be detected in historical data. And then, using data generated by experiments, empirical model, i.e. response surface is built by PLS or MLR. Now, as process model is constructed, it is used as objective function for optimization. As the optimum point is a local one. above procedures are repeated while moving to a new experiment region fur finding the global optimum point. As a result of application to the pulp digester benchmark model, kappa number that is an indication fur impurity contents decreased to very low value, 3.0394 from 29.7091. From the result, we can see that the proposed methodology has sufficient good performance fur optimization, and is also applicable to real processes.

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Evaluation of dynamic muscle fatigue model to predict maximum endurance time during forearm isometric contraction (전완의 등척성 수축시 최대근지구력시간을 예측하기 위한 동적근피로모델의 평가)

  • Kiyoung, Lee
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.15 no.6
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    • pp.433-439
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    • 2022
  • Muscle fatigue models to predict maximum endurance time (MET) are broadly classified as either 'empirical' or 'theoretical'. Empirical models are based on fitting experimental data and theoretical models on mathematical representations of physiological process. This paper examines the effectiveness of dynamic muscle fatigue model as theoretical model to predict maximum endurance time during forearm isometric contraction. Forty volunteers (20 females, 20 males) are participated in this study. Empirical models (exponential model and power model) and theoretical model (dynamic muscle fatigue model) are used to compare. Mean absolute deviation (MAD), correlation coefficient (r) and intraclass correlation (ICC) are calculated between theoretical model and empirical models. MAD are below 3.5%p, r and ICC are above 0.93 and 0.87, respectively. This results demonstrate that dynamic muscle fatigue model as theoretical model is valid to predict MET.