• Journal of Fisheries and Marine Sciences Education
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• v.28 no.3
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• pp.701-712
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• 2016

The purpose of this study was to investigate the effect of democratic and autocratic behavior type of dance art instructors in elementary dance education on class satisfaction focused on mediations of flow and perceived competence. A total of 500 questionnaires were distributed but insincerely replied or double-replied questionnaires were excluded and finally 453 questionnaires were analyzed for this study. For the analysis of the data, SPSS 18.0 version was used and double mediation model operating in serial, proposed by Hayes and a bootstrapping method were used. First, instructor's democratic behavior type was statistically positive effect on class satisfaction. However autocratic behavior type was statistically negative effect. Second, the indirect effect of instructor's democratic type and autocratic behavior type on class satisfaction through the flow were statistically positive significant. Third, the indirect effect of instructor's democratic behavior type on class satisfaction through the perceived competence was statistically significant. However autocratic behavior type was statistically negative effect. Lastly, the indirect effect of instructor's democratic and autocratic behavior types on class satisfaction through the flow and perceived competence were statistically positive significant.

• Journal of The Korean Association For Science Education
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• v.35 no.2
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• pp.217-229
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• 2015

In this study, we explored the development of scientific model through the social-construction process on "combustion." Students were 8th graders from one middle school class. Each student engaged in small group discussions three times and made a group model on combustion. Discourses between peers and teacher were videotaped, audiotaped, and transcribed. The results show that the small groups constructed an initial concept: 'Conditions of combustion', which they then evaluated and revised the initial concept through combustion experiment. Following the discussions, some small groups evaluated their model and made a revised model. Then, the small groups compared various models and constructed a scientific model through consensus within the small group and as a whole class. Finally, students kept revising their model to 'Burning needs oxygen.' This tells us that the social construction process of scientific model made a meaningful role to build scientific model through diverse discussion between the students and their teacher, although they have had some difficult process to reach the final consensus. The data also showed some group features: the members were open to other's ideas. They analyzed the differences between their own ideas from others and revised their model after the whole class discussion. Lastly, they showed the tendency to make a good use of teacher's guidance. This study implies the importance of having social interaction process for students to understand the scientific model and learn the nature of scientific inquiry in class.

• Annual Conference of KIPS
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• 2024.10a
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• pp.711-714
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• 2024

Facial emotion recognition (FER) is becoming crucial in fields like human-computer interaction and surveillance. Traditional FER systems rely on two-stage models with face alignment preprocessing, which increases complexity and inference time. In this research, we propose a single-stage approach using YOLOv6 combined with weighted class loss to address these inefficiencies. Our method improves computational efficiency while enhancing the detection of minority classes in imbalanced emotion datasets. The experiments demonstrate that although the weighted loss function helps with class detection, it slightly reduces overall accuracy. Nevertheless, the model shows promise for real-time FER applications, balancing accuracy and speed. This work not only introduces a more efficient approach but also highlights the potential of single-stage models in advancing emotion recognition tasks.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.377-386
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• 2021

The A60 class deck penetration piece is a fire-resistant system installed on a horizontal compartment to prevent flame spreading and protect lives in fire accidents in ships and offshore plants. This study deals with approximate optimization using discrete variables for the fire resistance design of an A60 class deck penetration piece using different surrogate models and a genetic algorithm. Transient heat transfer analysis was performed to evaluate the fire resistance design of the A60 class deck penetration piece. For the approximate optimization of the piece, the length, diameter, material type, and insulation density were applied to discrete design variables, and temperature, productivity, and cost constraints were considered. The approximate optimum design problem based on the surrogate models was formulated such that the discrete design variables were determined by minimizing the weight of the piece subjected to the constraints. The surrogate models used in the approximate optimization were the response surface model, Kriging model, and radial basis function-based neural network. The approximate optimization results were compared with the actual analysis results in terms of approximate accuracy. The radial basis function-based neural network showed the most accurate optimum design results for the fire resistance design of the A60 class deck penetration piece.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.40 no.1
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• pp.17-22
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• 2004

This study was carried out at the CWC of Chosun university for the purpose of resistance performance improvement of planing hull, and the results of the tests were confirmed cooperatively with WJFEL. G/T 100 ton class planing hull form was selected, and the improvement of hull form including appendages were performed by using some model test techniques. The model test scope comprises resistance relative tests including wave profile observation, trim and sinkage measurement and flow visualization tests at full load and trial conditions for one bare hull and for two appended hulls. The final wedge and spray strip combined with improved hull form showed about 1.0 knot speed improvement at both of full and trial conditions, and outstanding improvement for fore wave phenomena.

• Near Infrared Analysis
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• v.1 no.2
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• pp.29-33
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• 2000

The identification step of raw drug materials is an indispensible procedure in the GMP manufacturing process within the pharmaceutical industry. However, wet chemistry methods for identification of drug materials, used by the various Pharmacopeia are time-consuming and expensive steps. In this paper, near-infrared spectroscopy (NIRS) has been developed for identifying eleven drug substances including calcium pantothenate, cefaclor, cefoperazone, cephradine, dextromethorphan, ehtambutol, nicotinamide, pyrozinamide, tramadol, vitamin C, and vitamin E. Also the aim of ths work is to consturct a new algorithm for calibration model using soft independence modeling of class analogy (SIMCA) with Malinowskis Indicator Function (IND), which is used for finding the number of principal components of each class of the SIMACA model. The use of NIR technique with pattern recognition to qualify raw materials can make it possible to monitor process in real time as well as to control all procedures in the pharmaceutical industry. As the result, the samples identified of 183 different batches from 11 different compounds were separated clearly by SIMCA with 2nd derivative spectra in the NIR region of 1100∼2400 nm.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.581-587
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• 2023

The purpose of this study was to analyze the change trajectory and latent class types of self-esteem in first to fourth grade elementary school students. For the purpose, the Korean Children's Panel data were analyzed using potential growth model and the growth mixture model. As the results, the linear change model was selected as the most appropriate model. The change trajectory was found to increase slightly as the grade increased. In addition, four latent class groups were derived through: 'high level-maintenance,' 'low level-increase,' 'high level-decrease,' and 'low level-maintenance.' Most children were in the 'high level-maintenance' group, followed by 'high level-decrease,' 'low level-increase,' and 'low level-maintenance' groups. Therefore, based on the results of the study, we suggest that educational institutions and local communities pay attention to trends in elementary school students' self-esteem and provide appropriate support for students in each class.

• Journal of Communications and Networks
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• v.8 no.1
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• pp.21-27
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• 2006

We present and analyze a class of limited sensing random access algorithms with powerful properties. The algorithms are implementable in wireless mobile environments and their operational properties are simple. Their throughput in the worst case of the limit Poisson user model is 0.4297, while this throughput degrades gracefully in the presence of channel feedback errors.

• Communications for Statistical Applications and Methods
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• v.1 no.1
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• pp.87-93
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• 1994

Consider the problem of estimating the parameter of the model in which an observable random variable is represented by a unknown scalar parameter plus another random variable and the parameter, sample, and decision spaces consist of all integers. We first characterize the class of all admissible estimators and then characterize the class of all finitely admissible estimators. Finally, we show that two classes are identical.

• Journal of the Korean Statistical Society
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• v.34 no.1
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• pp.61-71
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• 2005

A class of asymmetric ARCH processes is proposed via binary random power transformations. This class accommodates traditional nonlinear models such as threshold ARCH (Rabemanjara and Zacoian (1993)) and Box-Cox type ARCH models(Higgins and Bera (1992)). Stationarity condition of the model is addressed. Iterative least squares(ILS) and pseudo maximum like-lihood(PML) methods are discussed for estimating parameters and related algorithms are presented. Illustrative analysis for Korea Stock Prices Index (KOSPI) data is conducted.