• Title/Summary/Keyword: statistical approach

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Effects of Muscle Relaxation Approach and Joint Movement Approach on Neck Movement and Comfort of Daily Living in Patients with Tension-type Headache of Forward Head Posture (근육 이완 접근과 관절 가동 접근이 긴장성 두통을 가진 두부 전방 전위 자세 환자의 목의 움직임 및 일상생활 편안함에 미치는 영향)

  • Kim, In-Gyun;Lee, Sang-Yeol
    • Journal of Korean Medicine Rehabilitation
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    • v.29 no.1
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    • pp.7-20
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    • 2019
  • Objectives The purpose of this study was to improve the comfort of daily life such as reduction of headache and increase of movement of neck by using muscle relaxation approach and joint movement approach for office worker with tension type headache of foward head posture sitting over 5 hours. Methods For this, 9 male and 15 female participated in the foward head posture with tension type headache. Each group consisted of 3 male and 5 female. Groups are divided into groups, such as muscle relaxation therapy, joint movement therapy, muscle relaxation and joint movement therapy. After intervention for each group for a month, we measured neck movement and head disability index and neck disability index 2 week. SPSS 23.0 (IBM Corp., Armonk, NY, USA) was used for data analysis. The one-way repeated analysis of variance (ANOVA), one-way ANOVA, compared t-test was used for statistical analysis. Results Three intervention groups have brought improvements in neck movement and daily life comfort. There is significant difference in the improvement of neck extension and change in neck disability index between 2 and 4 weeks in the joint movement approach compared to muscle relaxation approach, muscle relaxation and joint movement approach. Conclusions Office workers are exposed to tension type headache. However, muscle relaxation approach and joint movement approach can improve neck movement and daily life comfort.

Impact Assessment of Climate Change on Hydrologic Components and Water Resources in Watershed (기후변화에 따른 유역의 수문요소 및 수자원 영향평가)

  • Kim Byung Sik;Kim Hung Soo;Seoh Byung Ha;Kim Nam Won
    • Proceedings of the Korea Water Resources Association Conference
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    • 2005.05b
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    • pp.143-148
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    • 2005
  • The main purpose of this study is to suggest and evaluate an operational method for assessing the potential impact of climate change on hydrologic components and water resources of regional scale river basins. The method, which uses large scale climate change information provided by a state of the art general circulation model(GCM) comprises a statistical downscaling approach and a spatially distributed hydrological model applied to a river basin located in Korea. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONU GCM grid-box predictions with coarse resolution of climate change into the site-specific values by statistical downscaling techniques. The values are used to modify the parameters of the stochastic weather generator model for the simulation of the site-specific daily weather time series. The weather series fed into a semi-distributed hydrological model called SLURP to simulate the streamflows associated with other water resources for the condition of $2CO_2$. This approach is applied to the Yongdam dam basin in southern part of Korea. The results show that under the condition of $2CO_2$, about $7.6\% of annual mean streamflow is reduced when it is compared with the observed one. And while Seasonal streamflows in the winter and autumn are increased, a streamflow in the summer is decreased. However, the seasonality of the simulated series is similar to the observed pattern and the analysis of the duration cure shows the mean of averaged low flow is increased while the averaged wet and normal flow are decreased for the climate change.

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Model-Based Survival Estimates of Female Breast Cancer Data

  • Khan, Hafiz Mohammad Rafiqullah;Saxena, Anshul;Gabbidon, Kemesha;Rana, Sagar;Ahmed, Nasar Uddin
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.6
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    • pp.2893-2900
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    • 2014
  • Background: Statistical methods are very important to precisely measure breast cancer patient survival times for healthcare management. Previous studies considered basic statistics to measure survival times without incorporating statistical modeling strategies. The objective of this study was to develop a data-based statistical probability model from the female breast cancer patients' survival times by using the Bayesian approach to predict future inferences of survival times. Materials and Methods: A random sample of 500 female patients was selected from the Surveillance Epidemiology and End Results cancer registry database. For goodness of fit, the standard model building criteria were used. The Bayesian approach is used to obtain the predictive survival times from the data-based Exponentiated Exponential Model. Markov Chain Monte Carlo method was used to obtain the summary results for predictive inference. Results: The highest number of female breast cancer patients was found in California and the lowest in New Mexico. The majority of them were married. The mean (SD) age at diagnosis (in years) was 60.92 (14.92). The mean (SD) survival time (in months) for female patients was 90.33 (83.10). The Exponentiated Exponential Model found better fits for the female survival times compared to the Exponentiated Weibull Model. The Bayesian method is used to obtain predictive inference for future survival times. Conclusions: The findings with the proposed modeling strategy will assist healthcare researchers and providers to precisely predict future survival estimates as the recent growing challenges of analyzing healthcare data have created new demand for model-based survival estimates. The application of Bayesian will produce precise estimates of future survival times.

Korean Part-of-Speech Tagging using Disambiguation Rules for Ambiguous Word and Statistical Information (어휘별 중의성 제거 규칙과 통계 정보를 이용한 한국어 품사 태깅)

  • Ahn, Kwang-Mo;Han, Kyou-Youl;Seo, Young-Hoon
    • The Journal of the Korea Contents Association
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    • v.9 no.2
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    • pp.18-26
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    • 2009
  • A hybrid part-of-speech tagging approaches may be robust, easily extendable, and accurate because they can have the advantages of both statistical approach and rule-based approach. But conventional hybrid part-of-speech tagging systems hardly resolve some morphological ambiguities which can't be resolved by statistical information. It is because the coverage of rules is narrow. So, we define disambiguation rules for individual ambiguous word based on syntax and semantics of surround words. We select words from which the top 50% of ambiguities are occurred in Sejong corpus and build 1,814 rules for them. The accuracy of our hybrid part-of-speech tagging system using those rules is 98.28%.

Implementation of Markov Chain: Review and New Application (관리도에서 Markov연쇄의 적용: 복습 및 새로운 응용)

  • Park, Chang-Soon
    • The Korean Journal of Applied Statistics
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    • v.24 no.4
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    • pp.657-676
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    • 2011
  • Properties of statistical process control procedures may not be derived analytically in many cases; however, the application of a Markov chain can solve such problems. This article shows how to derive the properties of the process control procedures using the generated Markov chains when the control statistic satisfies the Markov property. Markov chain approaches that appear in the literature (such as the statistical design and economic design of the control chart as well as the variable sampling rate design) are reviewed along with the introduction of research results for application to a new control procedure and reset chart. The joint application of a Markov chain approach and analytical solutions (when available) can guarantee the correct derivation of the properties. A Markov chain approach is recommended over simulation studies due to its precise derivation of properties and short calculation times.

Dual Token Bucket based HCCA Scheduler for IEEE 802.11e (IEEE 802.11e WLAN 위한 이중 리키 버킷 기반 HCCA 스케줄러)

  • Lee, Dong-Yul;Lee, Chae-Woo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.11B
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    • pp.1178-1190
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    • 2009
  • IEEE 802.11e proposed by IEEE 802.11 working group to guarantee QoS has contention based EDCA and contention free based HCCA. HCCA, a centralized polling based mechanism of 802.11e, needs a scheduling algorithm to allocate the network resource efficiently. The existing standard scheduler, however, is inefficient to support for QoS guarantee for real-time service having VBR traffic. To efficiently assign resource for VBR traffic, in this paper, we propose TXOP algorithm based on dual leaky bucket using average resource allocation and peak resource allocation. The minimum TXOP of each station is obtained by using statistical approach to maximize number of stations of which performance satisfy QoS target. Simulation results show that the proposed algorithm has much higher performance compared with reference scheduler in terms of throughput and delay.

Reset of Measurement Control Criteria for Monitoring Data through the Analysis of Measured Data (계측데이터 분석을 통한 모니터링 데이터의 계측관리기준 재설정)

  • Chung, Chul-Hun;An, Ho-Hyun;Shin, Soo-Bong;Kim, Yu-Hee
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.18 no.6
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    • pp.105-113
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    • 2014
  • Most operating civil structures measure response data continuously by various types of sensors and evaluate their health conditions. Measurement control criteria for such civil structures are usually defined in the first operating stage by experts working at a construction or engineering company. However, a few studies have been carried to examine the adequacy of these measurement control criteria based on the actual measured data. The paper introduces a systematic way of resetting the measurement control criteria for the measured monitoring data based on the statistical aspects of the measured data. The proposed statistical approach has been examined with actually measured time-history data from a bridge structure.

A Mediation Analysis of Absorption Capacity by Bootstrapping Technique in Multiple Mediator Model (다중매개모델에서 bootstrapping기법을 이용한 흡수능력의 매개효과 분석)

  • Kim, Hyun-Woo;Lee, Hong-Bae;Shin, Yong-Ho
    • Journal of the Korea Society for Simulation
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    • v.24 no.4
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    • pp.89-96
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    • 2015
  • The mediation methods suggested by Baron and Kenny, Sobel, Aroian and Goodman, have widely used to test the mediating effect. However, as there are many problems in statistical test power, as well as statistical accuracy, a bootstrapping technique has been suggested as an alternative. In this paper, we adopt the phantom variables based on the bootstrapping technique to test the mediating effect in multiple mediator model consisting of three or more mediating variables. In particular, we formulate the multiple mediator model for analyzing the relations among organizational resources, the absorption capacity as mediating variables and technology commercialization capabilities. And using the bootstrapping approach, we analyzed the mediating effect of the absorption capacity by setting of phantom variables and calculated total indirect effect size and the statistical significance. The empirical results are as follows. First, we confirmed that the bootstrapping approach and the phantom variable is the very efficient and systematic mediation method. Second, we recognized that there is a difference in the mediating characteristics of the absorption capacity depending on the resource characteristics of human resources and material resources obviously.

A Spatial Statistical Approach on the Correlation between Walkability Index and Urban Spatial Characteristics -Case Study on Two Administrative Districts, Busan- (도시 공간특성과 Walkability Index의 상관성에 관한 공간통계학적 접근 -부산광역시 2개 구를 대상으로-)

  • Choi, Don Jeong;Suh, Yong Cheol
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.32 no.4_1
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    • pp.343-351
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    • 2014
  • The correlation between regional Walkability Index and their physical socio-economic characteristics has evaluated by the spatial statistical analysis to understand the urban pedestrian environments, where has been emerging the significance, recently. Following to the study, the Walkability Indexes were calculated quantitatively from two administrative districts of Busan and measured Global Local spatial autocorrelation indices. Additionally, the Geographically Weighted Regression model was applied to define the correlation between Walkability Indexes and urban environmental variables. The spatial autocorrelation values and clusters on the Walkability Indexes were derived in statistically significant level. Furthermore, the Geographically Weighted Regression model has been derived more improved inference than the OLS regression model, so as the influence of local level pedestrian environment was identified. The results of this study suggest that the spatial statistical approach can be effective on quantitative assessing the pedestrian environment and navigating their associated factors.

Comparison of Ordinary Kriging and Artificial Neural Network for Estimation of Ground Profile Information in Unboring Region (미시추 구간의 지반 층상정보 예측을 위한 정규 크리깅 및 인공신경망 기법의 비교)

  • Chun, Chanjun;Choi, Changho;Cho, Jinwoo
    • Journal of the Korean GEO-environmental Society
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    • v.20 no.3
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    • pp.15-20
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    • 2019
  • A large amount of site investigation data is essential to obtain reliable design value. However, site investigations are generally insufficient due to economic problems. It is important to estimate the ground profile information in unboring region for accurate earthwork-volume prediction, and such ground profile information can be estimated by using the geo-statistical approach. Furthermore, the ground profile information in unboring region can be estimated by training a model via machine learning technique such as artificial neural network. In this paper, artificial neural network-based model estimated the ground profile information in unboring region, and this results were compared with that of ordinary kriging technique, which is referred to the geo-statistical approach. Accordingly, a total of 84 ground profile information in an actual bridge environment was split into 75 training and 9 test databases. The observed ground profile information of the test database was compared with those of the ordinary kriging technique and artificial neural network.