• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.11
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• pp.2270-2276
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• 2002

Dynamic stability of a rotary oscillating cantilever beam is presented in this study. Using the stretch deformation instead of the conventional axial deformation, three linear partial differential equations are derived from Hamilton's principle and transformed into dimensionless forms. Stability diagrams of the first order approximate solutions are obtained by using the multiple scale perturbation method. The stability diagrams show that relatively large unstable regions exist near the combination of the first chordwise bending natural frequency and the first stretch natural frequency. This result is verified by using the generalized -$\alpha$ method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11a
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• pp.335-340
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• 2001

Dynamic stability of a rotary oscillating cantilever beam is presented in this study. Using the stretch deformation instead of the conventional axial deformation, three linear partial differential equations are derived from Hamilton's principle and transformed into dimensionless forms. Stability diagrams of the first order approximate solutions are obtained by using the multiple scale perturbation method. The stability diagrams show that relatively large unstable regions exist near the combination of the first chordwise bending natural frequency and the first stretch natural frequency. This result is verified by using the generalized-${\alpha}$ method.

• Journal of Institute of Control, Robotics and Systems
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• v.1 no.1
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• pp.50-57
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• 1995

In this paper, the design and the implementation of the controller for an articulate robot, which is developed in our Automatic Control Laboratory, are mainly discussed. The controller reduces software computational load via distributed processing method using multiple CPU's, and simplifies structures by the time-division control with TMS320C31 DSP chip. The method of control is based on the fuzzy-compensated PID control with scale factor, which compensates for the influence of load variation resulting from the various postures of the robot with conventional PID scheme. The application of the proposed controller to the robot system with DC servo-motors shows some excellent control capabilities. Also, the response characteristics of system for the various trajectory commands verify the superiority of the controller.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.290-291
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• 2007

Barometers can provide height information steady but its accuracy becomes poor as the air data varies due to the vehicles's moving or time's elapsing. In order to keep the accuracy in spite of the air data changes, we propose a filter for the identification of baro-errors. The baro-errors mainly consist of bias and scale factor errors which gradually varies as the air data varies. With GPS height measurements, the scale factor and bias estimator is designed by applying the interacting multiple model (IMM) filtering technique to the baro-error random walk model. The resultant estimates are used to compensate current baro-measurement to supply accurate measurements steadily.

• Journal of applied mathematics & informatics
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• v.29 no.1_2
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• pp.279-292
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• 2011

In this paper, we consider anti-periodic solutions of the following BAM neural networks with multiple delays on time scales: $$\{{x^\Delta_i(t)=-a_i(t)e_i(x_i(t))+{\sum\limits^m_{j=1}}c_{ji}(t)f_j(y_j(t-{\tau}_{ji}))+I_i(t),\atop y^\Delta_j(t)=-b_j(t)h_j(y_j(t))+{\sum\limits^n_{i=1}}d_{ij}(t)g_i(x_i(t-{\delta}_{ij}))+J_j(t),}\$$ where i = 1, 2, ..., n,j = 1, 2, ..., m. Using some analysis skills and Lyapunov method, some sufficient conditions on the existence and exponential stability of the anti-periodic solution to the above system are established.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.19 no.4
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• pp.425-433
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• 2012

Purpose: The purpose of this study was to investigate sleep patterns and predictors of excessive daytime sleepiness (EDS) in university students. Methods: Participants were 120 university students who were attending two universities in S-city and C-city. Data were collected from May 20 to June 15, 2012 using self-report questionnaires which included Johns' Epworth Sleepiness Scale, Yi's Sleep Quality Scale, and Beck Depression Inventory. Data were digitalized and analyzed using frequency, percentages, means and standard deviations, Wilcoxon rank sum test, Chi-square test, Fisher's exact test, and multiple logistic regression with SAS 9.0. Results: Mean total sleep time was 6.6 hours on weekdays, 8.1 hours on weekends. Mean sleep latency was 19.1 minutes and the score for mean sleep quality was 22.6. Prevalence of EDS was 12.5%. Depression was significantly different between EDS and Non-EDS students (t=2.17, p=.030). Multiple logistic regression showed that the only factor associated with EDS was depression (adjusted odds ratio of depression=5.33, 95% Confidence Interval=1.49-19.04). Conclusion: Results of this study indicate that university students experience short sleep time, low sleep quality, and common EDS with depression, suggesting that students with complaints of EDS should be completely assessed for depression as well as sleep problems.

• Journal of Integrative Natural Science
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• v.13 no.1
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• pp.34-40
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• 2020

This study aims to create a model for predicting the number of extinguishment manpower to put out forest fires by taking into account the climate, the situation, and the extent of the damage at the time of the forest fires. Past research has been approached to determine the cause of the forest fire or to predict the occurrence of a forest fire. How to deal with forest fires is also a very important part of how to deal with them, so predicting the number of extinguishment manpower is important. Therefore predicting the number of extinguishment manpower that have been put into the forest fire is something that can be presented as a new perspective. This study presents a model for predicting the number of extinguishment manpower inputs considering the scale of the damage with forest fire on a scale bigger than 0.1 ha as data based on the forest fire annual report(Korea Forest Service; KFS) from 2015 to 2018 using the moderated multiple regression analysis. As a result, weather factors and extinguished time considering the damage show that affect forest fire extinguishment manpower.

• Computers and Concrete
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• v.34 no.1
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• pp.123-135
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• 2024

Strain-hardening cement-based composites (SHCC) under cracked condition exhibits remarkable capillary absorption due to water ingress from multiple cracks. Surface treatment using water repellent agents is an effective way for improving water resistance of SHCC, but the water resistance may remarkably decrease when cracks penetrate impregnation depth. Another way is to add water repellent agents directly into the mixture, offering SHCC integral water repellency even if cracks form later. However, although integral water repellent treatment has been proved feasible by previous studies, there is still lack of simulation work on the treated SHCC for evaluating its durability. This study presents a simulation method for capillary absorption of cracked SHCC with integral treatment based on a multi-scale approach proposed in the authors' previous work. The approach deals with water flows in bulk matrix and multiple cracks using two individual transport equations, respectively, whereas water absorbed from a crack to its adjacent matrix is treated as the mass exchange of the two equations. In this study, the approach is enhanced for the treated SHCC by integrating the influencing of water repellency into the two transport equations as well as the mass exchange term. Using the enhanced approach, capillary absorption of water repellent SHCC under cracked condition is simulated, showing much more reduced water ingress than the untreated concrete, which is consistent with total absorption data from previous tests. This approach is also capable of simulating water spatial distribution with time in treated SHCC reasonably.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.169-175
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• 2011

In this paper, an automatic scoring system of the OMR answer sheet is implemented using Gray Scale and image segmentation method. The proposed method was used to extract the OMR data on multiple-choice answer sheet from captured image. In addition, On-line scoring system is developed and implemented to mark the short-answer type on the reverse side. Therefore, teachers can mark the short-answer type for anytime and anywhere within the available time. There were many advantages to mark of the multiple-choice answer sheet without additional OMR reader. In the future, the grading of short-answer type will be more efficient if it were performed by using an automatic scoring system based on image processing.

• Wind and Structures
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• v.36 no.6
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• pp.367-377
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• 2023

This study proposes a few-shot learning model for extrapolating the wind pressure of scaled experiments to full-scale measurements. The proposed ML model can use scaled experimental data and a few full-scale tests to accurately predict the remaining full-scale data points (for new specimens). This model focuses on extrapolating the prediction to different scales while existing approaches are not capable of accurately extrapolating from scaled data to full-scale data in the wind engineering domain. Also, the scaling issue observed in wind tunnel tests can be partially resolved via the proposed approach. The proposed model obtained a low mean-squared error and a high coefficient of determination for the mean and standard deviation wind pressure coefficients of the full-scale dataset. A parametric study is carried out to investigate the influence of the number of selected shots. This technique is the first of its kind as it is the first time an ML model has been used in the wind engineering field to deal with extrapolation in wind performance prediction. With the advantages of the few-shot learning model, physical wind tunnel experiments can be reduced to a great extent. The few-shot learning model yields a robust, efficient, and accurate alternative to extrapolating the prediction performance of structures from various model scales to full-scale.