• The Journal of Korean Association of Computer Education
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• v.20 no.5
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• pp.35-47
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• 2017

The purpose of this study was to develop and apply the elementary teacher training course for educational programming language based on TPACK in order to make elementary school teachers fully equipped with teaching efficacy for SW education. As a result, the informatics teaching efficacy of the teachers in the experimental group who participated in EPL training course developed based on TPACK was statistically more significant than the teachers in the control group(t=4.13, p<.001). The dependent sample t-test of the experimental group showed a statistically significant increase with t=4.57 (p< .001). It proved that TPACK-based teachers' training course is effective to improve teachers' informatics teaching efficacy. It is suggested that the development of SW education teacher training course should be systematically structured considering TPACK framework.

• Science of Emotion and Sensibility
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• v.11 no.3
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• pp.357-364
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• 2008

This study is to find training effect on EEG(Electroencephalography) and EMG(electromyogram) evoked by repetitive movement of a hand. Five university students participated in this study and were asked to perform repetitive movement of right hand for 5 seconds with rest for 10 seconds. They repeated the movement for 48 minutes and for 5 days. EEG and EMG were measured according to every movement. Coherence between EEG and EMG and power spectrum of EEG were analyzed and were tried to observe their changes within a day and between days of the repetitive movement. Training effect according the time of the movement was significantly found in mu and beta frequencies in EEG. However, training effect was not significant between the days of the movement and also, not in coherence between EEG and EMG.

• Journal of Biosystems Engineering
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• v.39 no.4
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• pp.389-399
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• 2014

Purpose: This study was aimed at developing a tractor-driving simulator for the safety training of agricultural tractor operators. Methods: The developed simulator consists of five principal components: mock operator control devices, a data acquisition and processing device, a motion platform, a visual system that displays a computer model of the tractor, a motion platform, and a virtual environment. The control devices of a real tractor cabin were successfully converted into mock operator control devices in which sensors were used for relevant measurements. A 3D computer model of the tractor was also implemented using 3ds Max, tractor dynamics, and the physics of Unity 3D. The visual system consisted of two graphic cards and four monitors for the simultaneous display of the four different sides of a 3D object to the operator. The motion platform was designed with two rotational degrees of freedom to reduce cost, and inverse kinematics was used to calculate the required motor positions and to rotate the platform. The generated virtual environment consisted of roads, traffic signals, buildings, rice paddies, and fields. Results: The effectiveness of the simulator was evaluated by a performance test survey administered to 128 agricultural machinery instructors, 116 of whom considered the simulator as having potential for improving safety training. Conclusions: From the study results, it is concluded that the developed simulator can be effectively used for the safety training of agricultural tractor operators.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.2
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• pp.192-199
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• 2004

Navigation simulators have been used in many marine schools and manne training centers since the early 1960's. But these simulators were very expens~ve and were almost limited only in one engine system. In this paper, a catamaran with twin engine system. controlled by two remote control levers and its economic simulator based on a personal computer shall be introduced. One of the main features of catamaran is to control variously its progressing direction. In the static state, a catamaran can move into all the directions and in the dynamic state, ship can change immediately the heading and speed. Although a good navigator can skillfully operate one engine system, it is difficult to control smoothly the catamaran of twin engine system without any threat for the safety of passengers. Thus. in order to bring up the expert navigators. the development of a simulator which makes the training effective is necessary, Therefore, in this paper, a Fuzzy Inference Technique based Maneuvering Simulator for catamaran with twin engine system was developed. In general. in order to develop a catamaran simulator for effective training, first of all. its mathematical model must be acquired. According to the acquired system modeling. the dynamics of simulator is determined, But the proposed technique can omit a complex and tedious mathematical modeling procedures by using the fuzzy inference, which dependent upon only experiences of an expert and can design an efficient training program for unskillful navigators. This developed simulator was consisted of two fuzzy inference routines and two remote control levers, and was focused on effective training of navigators for the safe maneuvering to avoid a collision in a harbor.

• Speech Sciences
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• v.5 no.1
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• pp.7-21
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• 1999

This paper proposes an improved training procedure in speech recognition based on the continuous density of the Hidden Markov Model (CDHMM). Of the three parameters (initial state distribution probability, state transition probability, output probability density function (p.d.f.) of state) governing the CDHMM model, we focus on the third parameter and propose an efficient algorithm that determines the p.d.f. of each state. It is known that the resulting CDHMM model converges to a local maximum point of parameter estimation via the iterative Expectation Maximization procedure. Specifically, we propose two independent algorithms that can be embedded in the segmental K -means training procedure by replacing relevant key steps; the adaptation of the number of mixture Gaussian p.d.f. and the initialization using the CDHMM parameters previously estimated. The proposed adaptation algorithm searches for the optimal number of mixture Gaussian humps to ensure that the p.d.f. is consistently re-estimated, enabling the model to converge toward the global maximum point. By applying an appropriate threshold value, which measures the amount of collective changes of weighted variances, the optimized number of mixture Gaussian branch is determined. The initialization algorithm essentially exploits the CDHMM parameters previously estimated and uses them as the basis for the current initial segmentation subroutine. It captures the trend of previous training history whereas the uniform segmentation decimates it. The recognition performance of the proposed adaptation procedures along with the suggested initialization is verified to be always better than that of existing training procedure using fixed number of mixture Gaussian p.d.f.

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.175-182
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• 2019

The study was conducted to verify the effect of basic life support training on the skill ability of police officers. The subjects of this study were 10 experimental group and 10 comparative group with voluntary consent after explaining the theory and significance of the training experiment at the police station located in K. The education program used in this study consists of theoretical education and practical training, and the theoretical education is 60 minutes and the practical training is 30 minutes. The measurement tool for basic resuscitation performance was measured based on the 'CPR and ECG Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care' presented by the American Heart Association. The results are as follows. The experimental group showed higher performance skills than the traditional control group in field confirmation performance skills, primary evaluation performance skills (A, B, C, medical evaluation), and BLS performance skills (heart compression, artificial respiration, medical evaluation) which are the basic resuscitation performance skills. In conclusion, this study confirmed that the theory and practice education program is more effective in improving the clinical performance of police officers than the traditional lectures and practice education, so it is possible to apply this simulation education program to the cardiac arrest patient emergency treatment.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.199-206
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• 2020

This study was conducted for the purpose of developing a measurement tool for success and failure factors of education and training of Korean bodyguards. conducted a meeting from the fully open questionnaire at first, and then formed the semi-structured questionnaire, finally carried out the survey from the closed questionnaire and analyzed data from SPSS 21.0, AMOS 21.0 and developed the measurements. It was conducted from May, 2019 to December, 2019. This survey was conducted of 150 security guards after the verification of the content validity though the pilot survey and presented the success attribution factors and standards on the basis of the result form this survey. As a result, the success factors of the training of the bodyguards were accidental education (5 item), vocational mental education (2 item), vocational mental education (2 item), work ability enhancement education (2 item), realistic practical education (2 item) ), Including 4 items, 11 items, The failure factors consisted of 12 item of three factors: formal education and training (5 item), lack of leadership qualities (4 item), and lack of education (3 item).

• Journal of the Korea Society of Computer and Information
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• v.27 no.4
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• pp.193-203
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• 2022

The purpose of this study was to analyze the effect of home training with app on metabolic syndrome risk factors and atherogenic index in on obese middle aged women. It was carried out to present as an intervention method for improving obesity in the pandemic era of COVID-19. The subjects of this study were 33 obese middle aged women, AHTG(n=15) and CG(n=18). Home training using the app for 8 weeks was conducted 3 times a week. The results of this study as follow, metabolic syndrome risk factors was WC(p<.001) significantly decreased, HDL-C(p<.05) significantly increased and atherogenic index was LDL-C/HDL-C(p<.01) significantly increased in the AHTG. In the era of the COVID-19 pandemic, PA plays an important role in alleviating the severe COVID-19 pandemic, in addition to its ameliorating effects on several chronic diseases. The possibility of home training using an app is an effective intervention method for preventing obesity and metabolic syndrome.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.91-98
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• 2022

The purpose of this study is to investigate the effect of online basic clinical training on critical thinking disposition, self determination motivation and learning satisfaction for nursing student in the COVID-19 situation. This study is one group pre-test and post-test design. The subjects of this study were collected using an online questionnaire for third-year nursing students located in G city, and 41 students participated in the final. The results of this study showed that critical thinking disposition(p=.013) and self determination motivation(p=.007) increased statistically significantly after the online basic clinical training. This findings indicate that online basic clinical training is effective in improving critical thinking disposition, self determination motivation. As it is difficult to perform direct nursing in the COVID-19 medical field recently, it is expected that the limitations of online clinical practice can be overcome by using various online contents.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.1015-1024
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• 2021

There are various educational programming environments in which students can train artificial intelligence (AI) using block-based programming languages, such as Entry, Machine Learning for Kids, and Teachable Machine. However, these programming environments are designed so that students can train AI through a separate menu, and then use the trained model in the code editor. These approaches have the advantage that students can check the training process more intuitively, but there is also the disadvantage that both the training menu and the code editor must be used. In this paper, we present a novel artificial intelligence block that can perform both AI training and programming in the code editor. While this AI block is presented as a Scratch block, the training process is performed through a Python server. We describe the blocks in detail through the process of training a model to classify a blue pen and a red pen, and a model to classify a dental mask and a KF94 mask. Also, we experimentally show that our approach is not significantly different from Teachable Machine in terms of performance.