• Journal of Animal Science and Technology
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• v.56 no.7
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• pp.24.1-24.6
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• 2014

The present study investigated the effects of varying durations of nursery diets differing in percentages of milk products on growth performance of pigs during the nursery phase (NP) and subsequent grow-finish phase (GFP) to find the feasibility of reducing the use of nursery diets containing costly milk products. A total of 204 21-d-old weanling female and castrated male pigs were subjected to one of three nursery phase feeding programs differing in durations on the NP 1 and 2 and GFP diets containing 20%, 7%, and 0% lacrosse and 35%, 8%, and 0% dried whey, respectively, in 6 pens (experimental units) for 33 d: HIGH (NP 1, 2 and 3 diets for 7, 14, and 12 d), MEDIUM (NP 2 and 3 for 14 and 19 d), and LOW (NP 2 and 3 and GFP 1 for 7, 14, and 12 d). Subsequently, 84 randomly selected pigs [14 pigs (replicates)/pen] were fed the GFP 1, 2 and 3 diets during d 54-96, 96-135, and 135-182 of age, respectively. The final body weight (BW) and average daily gain (ADG) of nursery pigs did not differ among the HIGH, MEDIUM, and LOW groups (14.8, 13.3, and 13.7 kg in BW and 273, 225, and 237 g in ADG, respectively). The average daily feed intake during the nursery phase was greater (p < 0.01) in the HIGH group than in the MEDIUM and LOW groups, whereas the gain:feed ratio did not differ across the treatments. The BW on d 182 and ADG during d 54-182 were greater in the HIGH and MEDIUM groups vs. the LOW group (110.0, 107.6, and 99.6 kg in BW, respectively; p < 0.01). The backfat thickness and carcass grade at slaughter on d 183 did not differ across the treatments. In conclusion, the MEDIUM program may be inferior to the commonly used HIGH program in supporting nursery pig growth. Nevertheless, the former appears to be more efficient than the latter in production cost per market pig whereas the LOW program is thought to be inefficient because of its negative effect on post-nursery pig growth.

• Korean Journal of Soil Science and Fertilizer
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• v.27 no.1
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• pp.40-47
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• 1994

The objective of this research was to examine the effect of ammonium thiosulfate(ATS) on urease activity and on biological and chemical properties of flooded paddy soil especially having high organic matter content by comparing with the effect of sodium thiosulfate(STS). The results obtained are summarized as follows. 1. The hydrolysis of urea was inhibited at 3 and 5 days after treatment of thiosulfate(ATS and STS) +glucose and thiosulfate only, respectively. The inhibitory effect of ATS on urea hydrolysis was slightly lower than that of STS in glusoce-added soils, but when the glucose was not added, the effects of ATS and STS were not different significantly. 2. The soil pH and Eh was lowered by 0.3~0.5 units and 30~120 mV, respectively, when incubated flooded soil with ATS and glucose at $25^{\circ}C$. 3. Soil respiration rate in/flooded soil was increased by 10~70% with the treatment of ATS during the 20 day experimental period. 4. The contents of acetic and butyric acid in thiosulfate treatment soil was below $10{\mu}g/g$, which was lower than that($220.3{\mu}g/g$) of critical growth inhibition of rice.

• Clinical and Experimental Reproductive Medicine
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• v.24 no.2
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• pp.153-165
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• 1997

In male reproducible health, fertility and IVF (in-vitro fertilization), semen analysis has been most important. Semen analysis can be divided into concentration, motional and morphological analysis of sperm. The existing method which was developed earlier to analyze semen concentrated on the sperm motility analysis. To provide more useful and precise solutions for clinical problems such as infertility, semen analysis must include sperm morphological analysis. But the traditional tools for semen analysis are subjective, imprecise, inaccurate, difficult to standardize, and difficult to reproduce. Therefore, with the help of development of microcomputers and image processing techniques, we developed a new sperm morphology analyzer to overcome these problems. In this study the agreement on percent normal morphology was studied between different observers and a computerized sperm morphology analyzer on a slide-by-slide basis using strict criteria. Slides from 30 different patients from the SNUH andrology laboratory were selected randomly. Microscopic fields and sperm cells were chosen randomly and percent normal morphology was recorded. The ability of sperm morphology analyzer to repeat the same reading for normal and abnormal cells was studied. The results showed that there was no significant bias between two experienced observers. The limits of agreement were 4.1%${\sim}$-3.8%. The Pearson correlation coefficient between readers was 0.79. Between the manual and sperm morphology analyzer, the same findings were reported. In this experiments the slides were stained by two different methods, PAP and Diff-Quik staining methods. The limits of agreement were 7.2%${\sim}$-5.7% and 6.0%${\sim}$-6.3%, respectively. The Pearson correlation coefficients ware 0.76 and 0.91, respectively. The limits of agreement was tighter below 20% normal forms. In the experiments of repeatability, 52 cells stained by PAP and Diff-Quik staining methods were analyzed three times in succession. Estimating pairwise agreement, the kappa statistic for the pairs were 0.76, 0.81, 0.86, and 0.75, 0.88, 0.88 respectively. In this study it was shown that there was good agreement between manual and computerized assessment of normal and abnormal cells. The repeatability and agreement per slide of computerized sperm morphology analyzer was excellent. The computer's ability to classify normal morphology per slide is promising. Based on results obtained, this system can be of clinical value both in andrology laboratories and IVF units.

• 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.