• Korean Journal of Applied Biomechanics
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• v.24 no.4
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• pp.391-397
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• 2014

The purpose of this work is to biomechanically study the effect of the one leg standing pose in yoga.. The work have been done through the evaluation for the left and right symmetry ability of one leg standing pose in the before and after yoga training for the 14 female yoga subject group (height: $164.3{\pm}4.4cm$, mass: $53.4{\pm}6.4kg$, year: $20.0{\pm}0.49yrs$) participated in this experiment. The motions of one leg standing pose were captured with Vicon system and the parameters were calculated with Visual-3D and Ground reaction force system. The results were as followed; - Front and backward COPsd did not show the significant difference, compared the before training with the after. - Left and right COPsd showed the significant difference (p<0.05), compared the before training with the after. - COP distance showed the significant difference (p<0.01), compared the before training with the after. - The asymmetry index of front and backward COPsd did not show the significant difference, compared the before training with the after. - The asymmetry index of left and right COPsd did not show the significant difference, compared the before training with the after. - The asymmetry index of COP distance showed the significant difference (p<0.01), compared the before training with the after. Therefore, the yoga training demonstrated the stable improvement in the one leg standing pose of inferior feet and the positive effect to the left and right symmetry ability.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.4
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• pp.551-560
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• 2010

In this paper, we suggest a localization method of factors affecting the accuracy of Air-to-Ground weapon delivery. The proposed method, called FBEL(Factor-Based Error Localization), is based on the fault localization technique widely utilized in the realm of software engineering field. FBEL localizes the major factors affecting the performance of weapon delivery. To analyze the effectiveness and the applicability of FBEL, we applied FBEL to real firing data and got the major factors caused the errors. We expect that the method could contribute to improve the quality of weapon delivery system. We also expect that it may aid improvement of pilot capability greatly, if it is applied to pilot firing training.

• Korean Journal of Applied Biomechanics
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• v.15 no.2
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• pp.1-10
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• 2005

G. B. LEE, A. S. GWON, The Research for Using methodof GRF (Ground Reaction Force) on Rotational Movement in Arabesque. Korean Journal of Sport Biomechanics, Vol. 15, No. 2, pp.1-10, 2005. As, in relation to all movements of a human being, the movements such as mutually walking, running, rotating, and jumping are attained endlessly through the ground amid the interaction with the ground, in terms of the harmonious movement of the upper limbs and the lower limbs, related to the basic movement in ballet, the type of a movement depends on the size and direction of the force that presses down the ground (Fz, Fx, Fy) amid the interaction with the ground. Therefore, aiming to correctly and efficiently perform a rotational movement in Arabesque, this study analyzed factors of the force manifestation through GRF (Ground Reaction Force), by dividing into preparing, stepping, standing, rotating, and finishing stages (events (1) ${\sim}$ (5)), targeting the subjects of 4 elite female students who majored in ballet. 1. At the No.5 position of the preparing stage, It is necessary that support the ground with left and right foot balance, 2. As the stepping stage is the phase ranging from the event (2), in which a plie movement of bending a knee is started, to the event (3) of stretching a knee, Rebunding motion is not good, and One have a position with ankle and knee flextion condition in order to stretch strengthly in event (3) position 3. At the event (1) position, It is necessary that exert the Fz reaction force at the event (3) position. Because large stretch force help to have a toe on position easily and show a active motion 4. In order to have a stand and rotation motion smoothly, One need a muscle strength training for ankle extension, knee extension, control horizental force

• Korean Journal of Applied Biomechanics
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• v.31 no.1
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• pp.59-63
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• 2021

Objective: Through comparative analysis of muscle activity for whole-body vibration, walking and running movements, it is to verify the training effect of whole-body vibration exercise in terms of amount of exercise and muscle activity characteristics. Method: Flat ground walking and slope walking (10 degrees) at a speed of 5 km/h, flat ground running and slope running (10 degrees) at a speed of 11 km/h for running were performed on treadmill, and squats were maintained at 12 Hz, 20 Hz, and 29 Hz conditions on Whole body vibration exercise equipment (Galileo). Muscle activity was analyzed through EMG analysis device for one minute for each condition. Results: The Anterior Tibialis and Erector Spinae show greater exercise effect in whole-body vibration than walking and running. The Rectus Femoris, Biceps Femoris, and Gluteus Maximus have the best effect of exercise in flat running. Whole-body vibration exercise showed greater muscle activation effect as the frequency increased, and exercise effect similar to walking during the same exercise time. Conclusion: The amount of exercise through Whole-body vibration exercise was similar to that of walking exercise, and the Anterior Tibialis and Erector Spinae shows better exercise effect than walking and running.

• Journal of Platform Technology
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• v.10 no.2
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• pp.20-26
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• 2022

Interest and investment in drones that apply the concept of the 4th industrial revolution and ICT convergence advanced technology are continuing. The purpose of drone operation has been widely spread from the initial military use to the use of various industries such as construction, forestry, facilities, and agricultural support. In these industries, the training of pilots who can actually operate drones is increasing centering on the qualification system. However, the detailed standards including the training place, training place, educational environment, and education method for nurturing pilots are ambiguous, so the education through the oral instruction of the training instructor is continuing at the drone training site. In order to solve this problem, this study conducted a study on a dual control platform in which a training instructor could directly intervene in the pilot's flying drone to execute a map in order to improve the quality of synesthesia, which is essential in the field.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.2
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• pp.147-155
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• 2024

Based on the recently developed deep learning technology, many studies have been conducted on deep learning networks that simultaneously detect and classify targets of interest in synthetic aperture radar(SAR) images. Although numerous research results have been derived mainly with the open SAR ship datasets, there is a lack of work carried out on the deep learning network aimed at detecting and classifying SAR ground targets and trained with the synthetic dataset generated from electromagnetic scattering simulations. In this respect, this paper presents the deep learning network trained with the synthetic dataset and applies it to detecting and classifying real SAR ground targets. With experiment results, this paper also analyzes the network performance according to the composition ratio between the real measured data and the synthetic data involved in network training. Finally, the summary and limitations are discussed to give information on the future research direction.

• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1763-1772
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• 1996

The conventional training set selection methods for the satellite image classification usually depend on the manual selection using data from the direct measurements of the ground or the ground map. However this task takes much time and cost, and some feature values vary in wide ranges even if they are in the same class. Such feature values can increase the robustness of the neural net but learning time becomes longer. In this paper,we propose anew training set selection algorithm using a rule-based method. By the technique proposed, the SPOT multispectral Imagery is classified in 3 bands, and the pixels which satisfy the rule are employed as the training sets for the neutralist classifier. The experimental results show faster initial convergence and almost the same or better classification accuracy. We also showed an improvement of the classification accuracy by using texture features and NDV1.

• Geomechanics and Engineering
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• v.6 no.4
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• pp.359-376
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• 2014

Thermal conductivity of ground has a great influence on the performance of Ground Heat Exchangers (GHEs). In general, the ground thermal conductivity significantly depends on the density (or porosity) and the moisture content since they are decisive factors that determine the interface area between soil particles which is available for heat transfer. In this study, a large number of thermal conductivity experiments were conducted for soils of varying porosity and moisture content, and a database of thermal properties for the weathered granite soils was set up. Based on the database, a 3D Curved Surface Model and an Artificial Neural Network Model (ANNM) were proposed for estimating the thermal conductivity. The new models were validated by comparing predictions by the models with new thermal conductivity data, which had not been used in developing the models. As for the 3D CSM, the normalized average values of training and test data were 1.079 and 1.061 with variations of 0.158 and 0.148, respectively. The predictions became somewhat unreliable in a low range of thermal conductivity values in considering the distribution pattern. As for the ANNM, the 'Logsig-Tansig' transfer function combination with nine neurons gave the most accurate estimates. The normalized average values of training data and test data were 1.006 and 0.954 with variations of 0.026 and 0.098, respectively. It can be concluded that the ANNM gives much better results than the 3D CSM.

• Journal of The Korean Association of Information Education
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• v.14 no.2
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• pp.139-148
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• 2010

This study aimed to develop the teacher training programs to prevent and treat of game addiction. First, we analyzed the existing training programs concerning game addiction and searched for various strategies applicable to game addiction prevention and treatment education programs. On this ground, training programs were divided into three courses that were the prevention program for normal students, the treatment program I for students in the potential-risk group, and the treatment program II for those in the high-risk group. For the prevention program, commonalities were drawn and developed from the existing studies and training programs; and for treatment programs, game addiction clinic centers were analyzed to draw various useful strategies and contents. We also developed the details of those programs in consultation with experts. As a result of content validity about the developed teacher training program to prevent and treat of game addiction, this program was generally appropriate and acceptable. We expect that the developed programs help to treat a student who has game addiction effectively.

• Journal of the Korea Society of Computer and Information
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• v.25 no.11
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• pp.9-16
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• 2020

The TA-50 aircraft is conducting simulated training on various situations, including air-to-air and air-to-ground fire training, in preparation for air warfare. It is also used for pilot training before actual deployment. However, the TA-50 does not have the ability to operate smart weapon forces, limiting training. Therefore, the purpose of this study is to implement the TA-50 aircraft to enable virtual training of one of the smart weapons, the Point Direct Attack Munition (JDAM). First, JDAM functions implemented in FA-50 aircraft, a model similar to TA-50 aircraft, were analyzed. In addition, since functions implemented in FA-50 aircraft cannot be directly utilized by source code, algorithms were extracted using machine learning techniques(TensorFlow). The implementation of this function is expected to enable realistic training without actually having to be armed. Finally, based on the results of this study, we would like to propose ways to supplement the limitations of the research so that it can be implemented in the same way as it is.