• Proceedings of the Korea Concrete Institute Conference
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• 1999.04a
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• pp.469-474
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• 1999

The object of study is analysis to joint crack behavior of cracked joint concrete pavement. In the new constructing concrete pavement, joint crack behavior was compared general joint depth D/4 with joint depth D/3 and D/5 that it's environmental effects changed temperature and humidity. After joint saw cutting joint section was predicted crack at joint depth D/5 test section from the result for monitoring development of crack. In the setting of data logger system of the joint section, it's data compared see with the naked eye. In the research, development of crack at the joint section should effect to joint saw timing latter than joint depth. This performance could be the minimum of deterioration to the early curing. In this research, At new constructing of joint concrete pavement of highway, the monitoring system be setting after finished paving and joint sawing. The system and see with the naked eye could be analysis to pavement behaviors from collecting data at the test section. This system could be monitoring shot term and long term. In this report, joint section of crack behavior analysis used to collected data during a month after paving and joint sawing.

• Communications for Statistical Applications and Methods
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• v.22 no.3
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• pp.265-276
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• 2015

In this paper, we propose hierarchical cluster analysis and multidimensional scaling for joint distribution valued data. Information technology is increasing the necessity of statistical methods for large and complex data. Symbolic Data Analysis (SDA) is an attractive framework for the data. In SDA, target objects are typically represented by aggregated data. Most methods on SDA deal with objects represented as intervals and histograms. However, those methods cannot consider information among variables including correlation. In addition, objects represented as a joint distribution can contain information among variables. Therefore, we focus on methods for joint distribution valued data. We expanded the two well-known exploratory methods using the dissimilarities adopted Hall Type relative projection index among joint distribution valued data. We show a simulation study and an actual example of proposed methods.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.54-57
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• 2007

Recently, multidimensional joint inversion of geophysical data based on fundamentally different physical properties has been actively studied. Joint inversion can provide a way to much more accurately image the subsurface structure. Through the joint inversion, furthermore, it is possible to directly estimate non-geophysical material properties from geophysical measurements. In this study, I derive the objective functions and normal equations of three different joint inversion approaches: one approach based on the structural similarity using cross-gradient, and the other two using the a priori information on the model parameters and the correlation between material properties. Since all the equations derived in this study are based on the same inversion method (smoothness constrained least-squares), it is possible to mix the joint inversion methods so as to produce a new joint inversion algorithm.

• Journal of muscle and joint health
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• v.23 no.3
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• pp.152-158
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• 2016

Purpose:The purpose of this study was to examine the degree of joint pain, limitation of daily activities, and frequency of outpatient visits. Methods: This secondary analysis study used the data from the fifth Korean National Health and Nutrition Examination Survey (KNHNES). The data about general characteristics, prevalence and treatment of osteoarthritis, limitation of activities of daily living (ADL) and frequency of outpatient visits and hospitalization in 424 osteoarthritis patients over 50 years old were derived from the database. Data were analyzed with complex samples in SPSS ver. 20.0. Results: Among people with knee joint pain, 79.3% reported they had more than 4 out of 10 points of the degree of pain. Meanwhile, 97.3% of people with hip joint pain reported that they had more than 4 out of 10 points of the degree of pain. People reporting 10 out of 10 point of pain were 21.4% of those with knee joint pain and 25% of those with hip joint pain. The mean of the degree of knee joint pain was 6.35, and the mean of the degree of hip joint pain was 6.89 out of 10 points. About 50% of people with osteoarthritis visited an outpatient clinic within the last 2 weeks, and 27% had limitation of ADL. Conclusion: It is necessary to develop an integrated intervention program to improve quality of life in patients with osteoarthritis.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.325-330
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• 2001

In this research, the early-age movements of joint at JPCP(Jointed Plain Concrete Pavement) were measured by field tests. The field tests were carried out for 5 days just after concrete placement, for 1 day after 52 and 72 days on Chung-Ang Expressway construction site in Dan-yang on the 28th and 29th of May 2001. The joint movements were measured by demec gauge and clip gauge. The results of regression analysis for the data measured during early 5 days showed that the joints of No.4, No.5, No.6, No.10, No.13, and No.15 could be considered as a moving joint. From data analysis on july 20, the joints of No.2, No.9, and No.10 showed the significant correlations from the minus value of coefficient of regression. As a result of regression data on August 8, joint movements occurred at all joints. Joint freezing and closure could be judged from the regression analysis using joint opening and total temperature measured at field tests.

• Korean Journal of Applied Biomechanics
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• v.28 no.2
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• pp.127-134
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• 2018

Objective: In a statistical linear model estimating the center of rotation of a human hip joint, which is the parameter related to the mean of response vectors, assumptions of homoscedasticity and independence of position vectors measured repeatedly over time in the model result in an inefficient parameter. We, therefore, should take into account the variance-covariance structure of longitudinal responses. The purpose of this study was to estimate the efficient center of rotation vector of the hip joint by using covariance pattern models. Method: The covariance pattern models are used to model various kinds of covariance matrices of error vectors to take into account longitudinal data. The data acquired from functional motions to estimate hip joint center were applied to the models. Results: The results showed that the data were better fitted using various covariance pattern models than the general linear model assuming homoscedasticity and independence. Conclusion: The estimated joint centers of the covariance pattern models showed slight differences from those of the general linear model. The estimated standard errors of the joint center for covariance pattern models showed a large difference with those of the general linear model.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.1083-1090
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• 2016

In clinical studies, different types of outcomes (e.g. repeated measures data and time-to-event data) for the same subject tend to be observed, and these data can be correlated. For example, a response variable of interest can be measured repeatedly over time on the same subject and at the same time, an event time representing a terminating event is also obtained. Joint modelling using a shared random effect is useful for analyzing these data. Inferences based on marginal likelihood may involve the evaluation of analytically intractable integrations over the random-effect distributions. In this paper we propose a joint HGLM approach for analyzing such outcomes using the HGLM (hierarchical generalized linear model) method based on h-likelihood (i.e. hierarchical likelihood), which avoids these integration itself. The proposed method has been demonstrated using various numerical studies.

• Structural Engineering and Mechanics
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• v.32 no.3
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• pp.447-457
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• 2009

A general analytical method for computing the joint stiffness from the sectional properties of the members that form the joint is derived using Vlasov's thin-walled beam theory. The analytical model of box T-joint under out-of-plane loading is investigated and validated using shell finite element results and experimental data. The analytical model of the T-joint is implemented in a beam finite element model using a revolute joint element. The out-of-plane displacement computed using the beam-joint model is compared with the corresponding shell element model. The results show close correlation between the beam revolute joint model and shell element model.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.10
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• pp.233-239
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• 2003

Three dimensional joint motion data were obtained using X-ray and precise magnetic sensors. Six metal markers were inserted on the femur and the tibia to set the coordinate system. Two magnetic position sensors were used to record motion data and these positions were transformed into the knee motion. The quadriceps muscle was extended in an automatic manner by an extraction machine. Results of the knee joint motion were the same as the clinical data. The proposed method is found to be reasonable in describing the knee motion so that these motion data can be used to simulate the normal knee joint.

• Tunnel and Underground Space
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• v.19 no.1
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• pp.1-10
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• 2009

Site characterization for structural stability in rock masses mainly involves the collection of joint property data, and in the current practice, much of this data is collected by hand directly at exposed slopes and outcrops. There are many issues with the collection of this data in the field, including issues of safety, slope access, field time, lack of data quantity, reusability of data and human bias. It is shown that information on joint orientation, spacing and roughness in rock masses, can be automatically extracted from LIDAR (light detection and ranging) point floods using the currently available Split-FX point cloud processing software, thereby reducing processing time, safety and human bias issues.