• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.36 no.4
• /
• pp.221-232
• /
• 2023

This paper presents a novel convolutional neural network (CNN)-based approach for predicting bolt clamping force in the early bolt loosening state of bolted structures. The approach entails tightening eight bolts with different clamping forces and generating frequency responses, which are then used to create a similarity map. This map quantifies the magnitude and shape similarity between the frequency responses and the initial model in a fully fastened state. Krylov subspace-based model order reduction is employed to efficiently handle the large amount of frequency response data. The CNN model incorporates a regression output layer to predict the clamping forces of the bolts. Its performance is evaluated by training the network by using various amounts of training data and convolutional layers. The input data for the model are derived from the magnitude and shape similarity map obtained from the frequency responses. The results demonstrate the diagnostic potential and effectiveness of the proposed approach in detecting early bolt loosening. Accurate bolt clamping force predictions in the early loosening state can thus be achieved by utilizing the frequency response data and CNN model. The findings afford valuable insights into the application of CNNs for assessing the integrity of bolted structures.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.42 no.2
• /
• pp.197-208
• /
• 2022

The existence of shallow bedrock and the desire to use underground space necessitate the use of blasting methods. The standard blasting method under water after drilling is associated with certain technical difficulties, including reduced detonation power, the use of a fixed charge per delay, and decoupling. However, there is no blasting method to replace the existing blasting method. In this paper, a dry hole charged with ANFO blasting is assessed while employing a dry hole pumping system to remove water from the drill borehole. Additional standard blasting is also utilized to compare the blasting performances of the two methods. The least-squares linear regression method is adopted to analyze the blasting vibration velocity quantitatively using the measured vibration velocity for each blasting method and the vibration velocity model as a function of the scaled distance. The results show that the dry hole charged with ANFO blasting will lead to greater damping of the blasting vibration, more energy dissipation to crush the surrounding rock, and closer distances for the allowable velocity of the blasting vibration. Also, standard blasting shows much longer influencing distances and a wider range of the blasting pattern. The pilot test confirms the blasting efficiency of dry hole charged with ANFO blasting.

• Health Policy and Management
• /
• v.33 no.2
• /
• pp.141-156
• /
• 2023

Background: As the population rapidly ages, older adults are increasingly likely to experience mobility problems. This study aims to explore the characteristics related to an elderly person's willingness to live in a nursing home if they have mobility problems Methods: This study analyzed data from 9,917 older adults (5,976 young-old and 3,941 old-old) obtained from the 2020 National Survey of Older Koreans. The dependent variable was the intended place of residence for older adults with mobility problems. Independent variables included various characteristics: (1) sociodemographic and social support, (2) health and functional status, and (3) residential environment. Rao-Scott chi-square tests and survey logistic regression analyses were performed for the young-old and old-old, respectively. Results: The intention to live in a nursing home was significantly different between the young-old (30.4%) and the old-old (34.7%) (p=0.009). According to fully adjusted multivariable analyses, for the young-old, the odds ratio of intending to live in a nursing home was significantly higher in social security benefit recipients (1.45; 95% confidence interval [CI], 1.06-1.97) compared to other individuals. The odds ratio was higher in unmarried (divorced, separated, widowed, or never-married) individuals for both young-old (1.41; 95% CI, 1.22-1.63) and old-old (1.34; 95% CI, 1.09-1.65) age groups, compared to their respective married counterparts. Conclusion: The results of this study suggest that in an aging society, health and social policies should be designed considering the different characteristics of the elderly to improve their health, function, and quality of life.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.3D
• /
• pp.255-261
• /
• 2010

The evaluation regarding a transportation policy by an evaluation volition viewpoint there is a difference. Consequently the insurgent analysis which is simple compared to against the evaluation object it was accurate, the analysis which leads the order anger probably is necessary. The research which it sees for the evaluation regarding the transportation policy of the metropolis divided in road being understood, public transportation, parking and pedestrian environment, wide area transportation and transportation information and transportation field whole. And against these field it tried the ALSCAL method and MDPREF method which is a Multidimensional Scale method and it analyzed. The regression analysis result for a dimensional analysis ALSCAL method the case of the transportation policy star improvement degree which it follows in introduction presence of intelligence transportation system and MDPREF method it confronted to the transportation policy star improvement degree which it follows in expansion to construction of specific function appeared with the fact that it is the tendency probably. And the evaluation object and evaluation in the object which will cut the positioning one result was each divided in 4 group. And two methods all it was visible a similar tendency. The ALSCAL method currently transportation system construction degree condition in base and, the MDPREF method currently improvement degree of the transportation policy which it follows in traffic system construction appeared with the fact that it is desirable to establish a hereafter traffic policy in base.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.2B
• /
• pp.111-120
• /
• 2009

A local scour around a bridge pier is known as one of important factors of bridge collapse. Two approaches are usually used in estimating a scour depth in practice. One is to use empirical formulas, and the other is to use computational methods. But the use of empirical formulas is limited to predict a scour depth under similar conditions to which the formulas were derived. Computational methods are currently too expensive to be applied to practical engineering problems. This study presented the application of artificial neural networks (ANN) to the prediction of a scour depth around a bridge pier at an equilibrium state. This study also investigated various ANN algorithms for estimating a scour depth, such as Backpropagation Network, Radial Basis Function Network, and Generalized Regression Network. Preliminary study showed that ANN models resulted in very wide range of errors in predicting a scour depth. To solve this problem this study incorporated cluster analysis into ANN. The incorporation of cluster analysis provided better estimations of scour depth up to 42% compared with other approaches.

• 한국노년학
• /
• v.29 no.4
• /
• pp.1327-1340
• /
• 2009

The purposes of the study were (1) to identify the level of successful aging of older people living in a city, (2) to identify associated factors with successful aging, and (3) to identify a risk group for successful aging using classification and regression trees (CART) analysis. One hundred eighty seven older people (>65years) participated in the cross-sectional survey. Trained interviewers collected data with a structured questionnaire on demographic information, Korean geriatric depression score, activity of daily living(ADL), instrumental activity of daily living(IADL), and Young's successful aging instrument in subject's home. A CART analysis split subjects into ten homogeneous small groups based on five determinant factors. Older people who are male, with higher education, living with family, and not receiving Medicaid showed better scores in successful aging than their counter parts. Depression was a strong primary determinant for successful aging. A risk group for successful aging of older people was identified by depression and IADL. An intervention to prevent and manage depression and to improve physical function of older people can be developed to promote successful aging of older people. It is suggested to consider an assessment of depression to develop the policies for older people welfare.

• 한국노년학
• /
• v.29 no.3
• /
• pp.917-933
• /
• 2009

This study examined the factors affecting forms of long-term care service use by elderly and the forms of use are classified facility care service, home care service, and unused. It is used data from the 2nd pilot program for the Long Term Care Insurance scheme and it is analysed 5,497 cases. Multi-nominal regression is used. According to the results, women use formal service more than man do, and wowen use facility care than home care. Those who eligible for National Basic Livelihood Security System(NBLSS) are shown to have higher use of formal care(especially facility care) than the middle income class, and the low income class than the middle income class has lower use of formal care. In addition, higher the family care is available, lower the taking part in the service. The big cities and mid sized cities than rural are used the formal service and moreover mid sized cities are used facility care than home care. Furthermore, the level of care need is determinants of service use and function of ADL, IADL, and abnormal behavior is also determinants of formal service(especially facility care). But nursing need and rehabilitation need are not determinants of formal service use. Based on the results, the recommendations are developed and implemented for the improvement the elderly long-term care insurance.

• Korean Journal of Social Welfare Studies
• /
• v.42 no.3
• /
• pp.267-290
• /
• 2011

This research attempts to analyze the effects of demographic factors, socioeconomic factors, health behaviors and social/familial supports on health inequalities among Korean elderly. For this end, this study adopts the multiple linear regression analysis to process data on population aged over 65 contained in 'The Third Korea Welfare Panel Study' published in 2008. The following are the results. First, the less educated they are, the smaller income they earn, the less they drink, the less satisfied with relationships with their family members, the more they turn out to feel depressed. Second, the less educated they are, the smaller income they earn, the less they drink, the less they are satisfied with relationship with family members, the more they benefit from social welfare services, the worse they turn out to rate their health. Based on these findings, three following suggestions could be forwarded. First, vulnerable aged groups including female elderly, low-income elderly, less-educated elderly need customized social supports. Second, new social policy for households is required to enhance elderly people's satisfaction with their family relationships with the rapid trend of a growing number of nuclear families and aging. Third, social welfare service programs need to be reevaluated to enhance their function for the aged.

• Geomechanics and Engineering
• /
• v.35 no.2
• /
• pp.121-133
• /
• 2023

The demand for cement and limestone crushed materials has increased many folds due to the tremendous increase in construction activities in Pakistan during the past few decades. The number of cement production industries has increased correspondingly, and so the rock-blasting operations at the limestone quarry sites. However, the safety procedures warranted at these sites for the blast-induced ground vibrations (BIGV) have not been adequately developed and/or implemented. Proper prediction and monitoring of BIGV are necessary to ensure the safety of structures in the vicinity of these quarry sites. In this paper, an attempt has been made to predict BIGV using artificial neural network (ANN) at three selected limestone quarries of Pakistan. The ANN has been developed in Python using Keras with sequential model and dense layers. The hyper parameters and neurons in each of the activation layers has been optimized using randomized and grid search method. The input parameters for the model include distance, a maximum charge per delay (MCPD), depth of hole, burden, spacing, and number of blast holes, whereas, peak particle velocity (PPV) is taken as the only output parameter. A total of 110 blast vibrations datasets were recorded from three different limestone quarries. The dataset has been divided into 85% for neural network training, and 15% for testing of the network. A five-layer ANN is trained with Rectified Linear Unit (ReLU) activation function, Adam optimization algorithm with a learning rate of 0.001, and batch size of 32 with the topology of 6-32-32-256-1. The blast datasets were utilized to compare the performance of ANN, multivariate regression analysis (MVRA), and empirical predictors. The performance was evaluated using the coefficient of determination (R²), mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and root mean squared error (RMSE)for predicted and measured PPV. To determine the relative influence of each parameter on the PPV, sensitivity analyses were performed for all input parameters. The analyses reveal that ANN performs superior than MVRA and other empirical predictors, andthat83% PPV is affected by distance and MCPD while hole depth, number of blast holes, burden and spacing contribute for the remaining 17%. This research provides valuable insights into improving safety measures and ensuring the structural integrity of buildings near limestone quarry sites.

• Information Systems Review
• /
• v.25 no.1
• /
• pp.93-110
• /
• 2023

Recently, attempts have been made to convert unstructured text into vectors and to analyze vast amounts of natural language for various purposes. In particular, the demand for analyzing texts in specialized domains is rapidly increasing. Therefore, studies are being conducted to analyze specialized and general-purpose documents simultaneously. To analyze specific terms with general terms, it is necessary to align the embedding space of the specific terms with the embedding space of the general terms. So far, attempts have been made to align the embedding of specific terms into the embedding space of general terms through a transformation matrix or mapping function. However, the linear transformation based on the transformation matrix showed a limitation in that it only works well in a local range. To overcome this limitation, various types of nonlinear vector alignment methods have been recently proposed. We propose a vector alignment model that matches the embedding space of specific terms to the embedding space of general terms through end-to-end learning that simultaneously learns the autoencoder and regression model. As a result of experiments with R&D documents in the "Healthcare" field, we confirmed the proposed methodology showed superior performance in terms of accuracy compared to the traditional model.