• Journal of the Korea Society for Simulation
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• v.30 no.3
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• pp.11-17
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• 2021

The 30mm anti-aircraft gun has been developed with various types of weapon systems such as protective, protective complex, and wheel-type anti-aircraft artillery. The role of this anti-aircraft gun is an important anti-aircraft weapon in charge of air defense. Anti-aircraft weapons are tasked with defending the airspace from aircraft attacks. In particular, anti-aircraft weapons are organized in combination with mechanized units. And anti-aircraft weapons are prone to attack by enemies because they operate on the front lines of the battlefield. The enemy is expected to attack our troops by covering up or concealing as much as possible in order to increase their viability. Therefore, this study analyzed whether our 30mm anti-aircraft bullets could subdue the enemy in cover. This study analyzed the performance of 30mm anti-aircraft bullets using the M&S technique. For this study, live shooting and simulation method by M&S were used for the experiment. In this study, steel plate and plywood were used for the live shooting experiment. In addition, in the simulation process through M&S, this study used the PRODAS model, AUTODYN model, and Split-x model to analyze the trajectory, penetration, and fragmentation capability of 30mm anti-aircraft bullets. According to the experimental results, it has been proven that 30mm anti-aircraft bullets can destroy enemy armored vehicles. 30mm anti-aircraft bullets succeeded in quickly subduing enemies concealed in general buildings or forests. In this way, it was possible to minimize damage to allies in advance.

• Convergence Security Journal
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• v.21 no.1
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• pp.191-200
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• 2021

Artificial intelligence technology is developing in an environment where a lot of data is produced due to the development of computing technology, a cloud environment that can store data, and the spread of personal mobile phones. Among these artificial intelligence technologies, the deep neural network provides excellent performance in image recognition and image classification. There have been many studies on image detection for forest fires and fire prevention using such a deep neural network, but studies on detection of cigarette smoking were insufficient. Meanwhile, military units are establishing surveillance systems for various facilities through CCTV, and it is necessary to detect smoking near ammunition stores or non-smoking areas to prevent fires and explosions. In this paper, by reflecting experimentally optimized numerical values such as activation function and learning rate, we did the detection of smoking pictures and non-smoking pictures in two cases. As experimental data, data was constructed by crawling using pictures of smoking and non-smoking published on the Internet, and a machine learning library was used. As a result of the experiment, when the learning rate is 0.004 and the optimization algorithm Adam is used, it can be seen that the accuracy of 93% and F1-score of 94% are obtained.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.4
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• pp.46-55
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• 2021

Concrete structures can cause various problems as the number of common years increases when exposed to external extreme climate conditions. Among these problems, freezing and thawing occur due to the action of extreme climate factors such as heavy rain and heavy snow, which have become the most problematic in recent years. In this study, we present a rapid freezing and thawing test method of concrete in the air, referring to KS F 2456, as Seoul exhibits very dry weather during the period of freezing and thawing. Concrete test specimens and RC beams were fabricated to perform rapid freezing and thawing of 0, 100, 200, and 300 cycles, and the performance evaluation confirmed the degradation of each subject in material and member units. The design strength of 24 MPa, which performs rapid freezing and thawing in the air up to 300 cycles, decreases by 5.24 MPa (21%), and as rapid freezing and thawing in the air increases the stress burden on reinforced concrete bending members, reducing the energy absorption (dissipation) ability of structures due to earthquakes.

• Journal of the Korea Computer Graphics Society
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• v.27 no.1
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• pp.9-17
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• 2021

In this paper, we present a simple and fast supervised learning framework based on model predictive control so as to learn motion controllers for a physic-based character to track given example motions. The proposed framework is composed of two components: training data generation and offline learning. Given an example motion, the former component stochastically controls the character motion with an optimal controller while repeatedly updating the controller for tracking the example motion through model predictive control over a time window from the current state of the character to a near future state. The repeated update of the optimal controller and the stochastic control make it possible to effectively explore various states that the character may have while mimicking the example motion and collect useful training data for supervised learning. Once all the training data is generated, the latter component normalizes the data to remove the disparity for magnitude and units inherent in the data and trains an artificial neural network with a simple architecture for a controller. The experimental results for walking and running motions demonstrate how effectively and fast the proposed framework produces physics-based motion controllers.

• Korean Journal of Poultry Science
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• v.48 no.4
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• pp.169-176
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• 2021

An experiment was conducted to investigate the effects of varying levels of hydrolyzed yeast on egg production and egg quality in aged laying randomly allotted to three dietary treatments such that egg production was similar in each treatment (6 replicates of 10 birds each). The layers were fed diets containing 0, 0.1, or 0.2% hydrolyzed yeast for eight weeks. No significant difference was observed in egg production during the first half of the experiment. Egg production and daily egg mass in groups fed diets containing hydrolyzed yeast were significantly higher (P<0.05) than those of the control groups during the second half of the experiment. Egg weight was not affected by the dietary treatment. Eggshell strength and thickness in groups fed diets containing hydrolyzed yeast were significantly higher than those of the control groups during the overall experimental period (P<0.05). Although no significant differences were observed in the Haugh units, yolk color in the group fed diets containing 0.1% hydrolyzed yeast was significantly higher than that in the control group (P<0.05). The mammillary layer thickness increased in a linear manner and significantly following treatment with dietary hydrolyzed yeast (P<0.05). Antibody titer against avian influenza virus in the group fed diets containing 0.2% hydrolyzed yeast was significantly higher (P<0.05) than that in the control group. In conclusion, dietary hydrolyzed yeast improved egg production and eggshell quality of laying hens in the late stages of production.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.15-22
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• 2022

In order to improve the accuracy of the deep learning object detection technique, the effect of magnification rate conditions and seasonal factors on detection accuracy in aerial photographs and drone images was analyzed through experiments. Among the deep learning object detection techniques, Mask R-CNN, which shows fast learning speed and high accuracy, was used to detect the vehicle to be detected in pixel units. Through Seoul's aerial photo service, learning images were captured at different screen magnifications, and the accuracy was analyzed by learning each. According to the experimental results, the higher the magnification level, the higher the mAP average to 60%, 67%, and 75%. When the magnification rates of train and test data of the data set were alternately arranged, low magnification data was arranged as train data, and high magnification data was arranged as test data, showing a difference of more than 20% compared to the opposite case. And in the case of drone images with a seasonal difference with a time difference of 4 months, the results of learning the image data at the same period showed high accuracy with an average of 93%, confirming that seasonal differences also affect learning.

• 한국노년학
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• v.29 no.2
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• pp.513-527
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• 2009

The purpose of this study was to verify the effect of senior simulation on geriatric unit nurses' attitude and job satisfaction toward the elderly with one group pretest-posttest design. The subjects of this study were the 30 nurses who are working in geriatric units in a general hospital in Daegu, Korea and who were well informed about the purpose of this study and allowed to join the study. The data were collected from August 23 to September 6, 2006. The experimental procedure was to do activities for daily living for 45 minutes wearing senior simulation suit. Self administered questionnaires were used to ask the nurses' attitude toward the elderly and job satisfaction in their work before, right after, and one week after senior simulation. According to the results of this study, there were significant changes in the geriatric nurses' attitude toward the elderly and job satisfaction after aging simulation implying that senior simulation is an effective intervention to facilitate nurses to do quality care for the elderly with sympathetic understanding and attitude. Senior simulation needs to be applied to geriatric education for the nursing students and health care providers who are involved in care for the elderly.

• Journal of Animal Science and Technology
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• v.65 no.5
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• pp.951-970
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• 2023

This study utilized Italian ryegrass silage (IRGS) - based total mixed ration (TMR) as feedstuff and evaluated its effects on rumen fermentation, growth performance, blood parameters, and bacterial community in growing Hanwoo heifers. Twenty-seven Hanwoo heifers (body weight [BW], 225.11 ± 10.57 kg) were randomly allocated to three experimental diets. Heifers were fed 1 of 3 treatments as follows: TMR with oat, timothy, and alfalfa hay (CON), TMR with 19% of IRGS (L-IRGS), and TMR with 36% of IRGS (H-IRGS). Feeding high levels of IRGS (H-IRGS) and CON TMR to heifers resulted in a greater molar proportion of propionate in the rumen. The impact of different TMR diets on the BW, average daily gain, dry matter intake, and feed conversion ratio of Hanwoo heifers during the growing period did not differ (p > 0.05). Furthermore, the blood metabolites, total protein, albumin, aspartate aminotransferase, glucose, and total cholesterol of the heifers were not affected by the different TMR diets (p > 0.05). In terms of rumen bacterial community composition, 264 operational taxonomic units (OTUs) were observed across the three TMR diets with 240, 239, and 220 OTUs in CON, L-IRGS, and H-IRGS, respectively. IRGS-based diets increased the relative abundances of genera belonging to phylum Bacteroidetes but decreased the abundances of genus belonging to phylum Firmicutes compared with the control. Data showed that Bacteroidetes was the most dominant phylum, while Prevotella ruminicola was the dominant species across the three TMR groups. The relative abundance of Ruminococcus bromii in the rumen increased in heifers fed with high inclusion of IRGS in the TMR (H-IRGS TMR). The relative abundance of R. bromii in the rumen significantly increased when heifers were fed H-IRGS TMR while P. ruminicola increased in both L-IRGS and H-IRGS TMR groups. Results from the current study demonstrate that the inclusion of IRGS in the TMR is comparable with the TMR containing high-quality forage (CON). Thus, a high level of IRGS can be used as a replacement forage ingredient in TMR feeding and had a beneficial effect of possibly modulating the rumen bacterial community toward mainly propionate-producing microorganisms.

• The Journal of the Acoustical Society of Korea
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• v.25 no.5
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• pp.213-221
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• 2006

Phone segmentation of speech waveform is especially important for concatenative text to speech synthesis which uses segmented corpora for the construction of synthetic units. because the quality of synthesized speech depends critically on the accuracy of the segmentation. In the beginning. the phone segmentation was manually performed. but it brings the huge effort and the large time delay. HMM-based approaches adopted from automatic speech recognition are most widely used for automatic segmentation in speech synthesis, providing a consistent and accurate phone labeling scheme. Even the HMM-based approach has been successful, it may locate a phone boundary at a different position than expected. In this paper. we categorized adjacent phoneme pairs and analyzed the mismatches between hand-labeled transcriptions and HMM-based labels. Then we described the dominant error patterns that must be improved for the speech synthesis. For the experiment. hand labeled standard Korean speech DB from ETRI was used as a reference DB. Time difference larger than 20ms between hand-labeled phoneme boundary and auto-aligned boundary is treated as an automatic segmentation error. Our experimental results from female speaker revealed that plosive-vowel, affricate-vowel and vowel-liquid pairs showed high accuracies, 99%, 99.5% and 99% respectively. But stop-nasal, stop-liquid and nasal-liquid pairs showed very low accuracies, 45%, 50% and 55%. And these from male speaker revealed similar tendency.

• Journal of the Korean Chemical Society
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• v.48 no.1
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• pp.77-84
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• 2004

The purpose of this study was to analyze the controversial points in the concepts of materials in the science textbook of middle school and to provide alternatives of teaching method. For this study, units in connected textbooks were analyzed and the teaching method using ball-and-stick models was developed. The subjects were 130 second graders from a middle school in Seoul, Korea. It aimed to compare the effectiveness of using ball-and-stick models for lesson with the one of traditional lessons, in learning concepts concerning materials by cognitive levels and to investigate the difference of scientific concept formation about concepts concerning materials by their cognitive levels between experimental group and control group by using concept formation questionnaires. Before the instructions, a short-version GALT was administered. After instructions, the posttest of concepts and attitude test connected with science subject were administered, and 10 months later, the posttest of concepts was administered to analyze the long-term memory effects. According to the results, the experimental group using the ball-and-stick models had significantly higher scores at conceptual understanding and long-term memory effects than the control group and improved the attitude relevant to science subject, and also had affirmative effects in attitude for science and science work. When analyzing the results according to the cognitive level, the long-term memory effects was high in the concrete operational stage students. From the results of this study, middle school students that are more concrete operational stage and transitional stage than formal operational stage elevates interesting in studying by using ball-and-stick models and making material form concretely. It would be effective in helping the students develope the correct concepts by connecting real world as materials and the particle world as atom.