• Journal of the Korean earth science society
• /
• v.41 no.1
• /
• pp.48-60
• /
• 2020

The purpose of this study is to analyze the patterns and characteristics of changes in integrated process skills during the process of science high school students' inquiry by using group-based trajectory modeling. 59 students participated in this study. Three hypothetico-deductive inquiry tasks were used as an intervention activity. We asked science high school students to perform those three tasks sequentially and to generate reports of the process and results. We evaluated students' reports by four elements (designing inquiry, collecting data, analyzing data, and forming conclusion) of the integrated process skills according to the scoring rubric developed by Lee and Park (2017), and analyzed the level of changes in integrated process skills in those three inquiry tasks by using group-based trajectory modeling. In addition, we analyzed the characteristics of changes in integrated process skills from several perspectives. The findings are as follows: First, concerning the change patterns of students' integrated process skills, all of the four elements were classified into two groups, but the change patterns were very different by elements. Second, regarding the change characteristics of students' integrated process skills, we found the context-dependency of integrated process skills, variation of learning progression for integrated process skills, and jaggedness of integrated process skills level. Based on these findings, we suggested that a couple of ways be sought to improve the integrated process skills of science high school students.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.12
• /
• pp.507-514
• /
• 2018

This study utilized latent growth curve modeling to investigate the trajectories of adolescent life satisfaction changes in middle and high school students. The effects of self-esteem, career identity, school learning activity, gender, and household earnings on life satisfaction changes were examined. Data was obtained from the Korea Child Youth Panel Survey (KYCPS), a longitudinal study following students for 7 years. Year 3-6 data was utilized. Results found that the life satisfaction trajectory resulted as a quadratic model in which individual differences were significant. Second, school learning activity used as a time variant variable had a positive significant effect on life satisfaction each year. Third, gender and self-esteem as time invariant variables had significant effects on initial levels while self-esteem had effects on the slope and quadratic change. Further implications and research issues are discussed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2016.05a
• /
• pp.285-286
• /
• 2016

We aim to propose the prediction modeling method of ship's position with extracting ship's trajectory model through pattern recognition based on the data that are being collected in VTS centers at real time. Support Vector Machine algorithm was used for data modeling. The optimal parameters are calculated with k-fold cross validation and grid search. We expect that the proposed modeling method could support VTS operators' decision making in case of complex encountering traffic situations.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.5 no.4
• /
• pp.77-86
• /
• 1995

The new architecture that fuzzy logic control(FLC) with difficulties for tuning membership function (MF) is parallel with neural networks(NN) to be learned from the output of FLC is proposed. Therefore proposed scheme has the characteristics to utilize the expert knowledge in design process, to be learned during the operation without any learning mode. In this architecture, the function of the FLC is to supply the sliding surface which is constructed on the phase plane by rule base for giving the desired control characteristics and learning criterion of NN and the stabilization of the control performance before NN is learned, The function of the NN is to let the system trajectory be tracked to the sliding surface and reached to the stable point.

• ETRI Journal
• /
• v.44 no.2
• /
• pp.286-299
• /
• 2022

Human activity recognition in real time is a challenging task. Recently, a plethora of studies has been proposed using deep learning architectures. The implementation of these architectures requires the high computing power of the machine and a massive database. However, handcrafted features-based machine learning models need less computing power and very accurate where features are effectively extracted. In this study, we propose a handcrafted model based on three-dimensional sequential skeleton data. The human body skeleton movement over a frame is computed through joint positions in a frame. The joints of these skeletal frames are projected into two-dimensional space, forming a "movement polygon." These polygons are further transformed into a one-dimensional space by computing amplitudes at different angles from the centroid of polygons. The feature vector is formed by the sampling of these amplitudes at different angles. The performance of the algorithm is evaluated using a support vector machine on four public datasets: MSR Action3D, Berkeley MHAD, TST Fall Detection, and NTU-RGB+D, and the highest accuracies achieved on these datasets are 94.13%, 93.34%, 95.7%, and 86.8%, respectively. These accuracies are compared with similar state-of-the-art and show superior performance.

• ETRI Journal
• /
• v.31 no.5
• /
• pp.565-575
• /
• 2009

This paper concerns the use of support vector regression (SVR), which is based on the kernel method for learning from examples, in identification of walking robots. To handle complex dynamics in humanoid robot and realize stable walking, this paper develops and implements two types of reference natural motions for a humanoid, namely, walking trajectories on a flat floor and on an ascending slope. Next, SVR is applied to model stable walking motions by considering these actual motions. Three kinds of kernels, namely, linear, polynomial, and radial basis function (RBF), are considered, and the results from these kernels are compared and evaluated. The results show that the SVR approach works well, and SVR with the RBF kernel function provides the best performance. Plus, it can be effectively applied to model and control a practical biped walking robot.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.4
• /
• pp.315-319
• /
• 2006

Support vector machines in biped humanoid robot are presented in this paper. The trajectory of the ZMP in biped walking robot poses an important criterion for the balance of the walking robots but complex dynamics involved make robot control difficult. We are establishing empirical relationships based on the dynamic stability of motion using SVMs. SVMs and kernel method have become very popular method for learning from examples. We applied SVM to model the practical humanoid robot. Three kinds of kernels are employed also and each result has been compared. As a result, SVM based on kernel method have been found to work well. Especially SVM with RBF kernel function provides the best results. The simulation results show that the generated ZMP from the SVM can be improve the stability of the biped walking robot and it can be effectively used to model and control practical biped walking robot.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.1 s.94
• /
• pp.200-209
• /
• 1999

This paper presents a precise tracking control scheme for the proposed parallel robot using artificial neural network. This control scheme is composed of three feedback controllers and one feedforward controller. Conventional PD controller and artificial neural network are used as feedback and feedforward controller respectively. A backpropagation learning strategy is applied to the training of artificial neural network, and PD controller outputs are used as target outputs. The PD controllers are designed at the robot dynamics based on inter-relationship between active joints and moving platform. Feedback controllers insure the total stability of system, and feedforward controller generates the control signal for trajectory tracking. The precise tracking performance of proposed control scheme is proved by computer simulation.

• Proceedings of the KSME Conference
• /
• 2007.05a
• /
• pp.1143-1148
• /
• 2007

LRE(Liquid propellant Rocket Engine) is one of the important parts to control the motion of rocket. For operation of rocket in error boundary of the set-up trajectory, it is necessarily to control the thrust of LRE according to the required thrust profile and control the mixture ratio of propellants fed into combustor for the constant mixture ratio. It is not easy to control thrust and mixture ratio of propellants since there are co-interferences among the components of LRE. In this study, the dynamic model of LRE was constructed and the dynamic characteristics were analyzed with control system as PID control and PID+Q-ILC(Iterative Learning Control with Quadratic Criterion) control. From the analysis, it could be observed that PID+Q-ILC control logic is more useful than standard PID control system for control of LRE.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.698-701
• /
• 1996

A novel neural network control scheme is proposed to identify the inverse dynamic model of robot manipulator and to compensate for uncertainties in robot dynamics. The proposed controller is called reference compensation technique(RCT) by compensating at reference input trajectory. The proposed RCT scheme has many benefits due to the differences in compensating position and learning algorithm. Since the compensation is done outside the plant it can be applied to many control systems without modifying the inside controller. It performs well with low controller gain because the operating range of input values is small and the output of the neural network controller is amplified through the controller gain. The back-propagation algorithm is used to train and simulations of three link robot manipulator are carried out to prove the proposed controller's performances.