• Korean Journal of Animal Reproduction
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• v.8 no.1
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• pp.36-45
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• 1984

This study was carried out to investigate the changes in ovary in repeatedly superovulated rabbits. A total of 57 New Zealand White and Californian, 25 mature virgin and 32 immature does were used in this study. For induction of repeated superovulation, PMSG and HCG were injected at 17-day and 30-day intervals for mature does and 17-day intervals for immature ones. The repeatedly superovulated does at 17-day intervals were induced luteolysis of pseudopregnant corpus luteum with PGF2${\alpha}$ on Day 8 to 9 p.c. The effect of repeated superovulation on reproductive organs was investigated on Day 3 p.c. in mature does and on Day 3 and 6 p.c. in immature ones, respectively. 1. In mature virgin does, the number of ovulation points in the 2nd and 3rd superovulation period averaged 7.0 and 5.0 at 17-day intervals and 13.4 and 6.0 at 30-day intervals, respectively. These numbers were statistically similar to 9.5 ovulation points in the control. However, there were less (p<0.05) ovulation points in those periods compared with 22.1 ovulation points in the 1st superovulation period. 2. In immature does, the number of ovulation points in the 2nd and 3rd superovulation period averaged 5.3 and 2.3, respectively. These numbers were significantly (p<0.05) decreased than 17.1 ovulation points in the 1st periods. The number of ovulation points in the 2nd superovulation period was similar to that in the control, but there was a significant (p<0.05) decrease in the number of ovulation points in the 3rd period as compared to the control. 3. In mature virgin does, the number of visible normal and hemorrhagic follicles (>1.0mm diameter) on day 3 p.c. averaged 19.1 and 8.9 in the 1st superovulation period, respectively. In the 2nd 3rd superovulation period, the number of normal follicles averaged 8.3 and 15.5 at 17-day intervals and 17.8 and 14.5 at 30-day intervals. The number of hemorrhagic follicles in the 2nd and 3rd superovulation period averaged 6.3 and 2.0 at 17-day intervals and 5.2 and 7.8 at 30-day intervals, respectively. There was a slight decrease, although not significant, in the number of normal and hemorrhagic follicles in the 2nd and 3rd period at 17-day intervals compared to that in the 1st period. 4. In immature does, the number of visible normal follicles on day 3 and day 6 p.c. in the 1st superovulation period averaged 27:3 and 26.1, respectively. The follicles on day 3 p.c. tended to increase slightly more than that in the cortrol, but the average number of normal follicles on day 6 p.c. did not differ from that in the control. The number of visible hemorrhagic follicles on day 3 and day 6 p.c. in the 1st of follicles in the 1st superovulation period average 10.2 and 9.9, respectively. There was a slight increase in the number of follicles in the 1st period compared to that in the control. In the 2nd and 3rd superovulation period, the number of normal follicles revealed a slight decrease in the 3rd period, but the number of hemorrhagic follicles was not different between periods. 5. The number of growing follicles with incipient intral formation on day 3 p.c. in mature does of the 1st superovulaton period average 29.7 and the average number of growing follicles in the 3rd period was 26.7 at 17-day intervals and 31.0 at 30-day intervals, respectively. These numbers did not differ from that in the control. In immature does, the number of growing follicles averaged 57.7, 45.0 and 59.3 in the 1st, 2nd and 3rd superovulation period, respectively. There was a slight but not significant decrease in the number of growing follicles in the 3rd period compared to that in the control.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.3
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• pp.97-107
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• 1997

Image segmentation is teh important step in image infromation extraction for computer vison sytems. Fuzzy clustering methods have been used extensively in color image segmentation. Most analytic fuzzy clustering approaches are derived from the fuzzy c-means (FCM) algorithm. The FCM algorithm uses th eprobabilistic constraint that the memberships of a data point across classes sum to 1. However, the memberships resulting from the FCM do not always correspond to the intuitive concept of degree of belongingor compatibility. moreover, the FCM algorithm has considerable trouble above under noisy environments in the feature space. Recently, the possibilistic C-mean (PCM) for solving growing for color image segmentation. In the PCM, the membersip values may be interpreted as degrees of possibility of the data points belonging to the classes. So, the problems in the FCM can be solved by the PCM. The clustering results by just PCM are not smoothly bounded, and they often have holes. So, the region growing was used as a postprocessing. In our experiments, we illustrated that the proposed method is reasonable than the FCM in noisy enviironments.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.11
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• pp.937-942
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• 2003

We present a self-localization method for mobile robots using vertical line features of indoor environment. When a 2D map including feature points and color information is given, a mobile robot moves to the destination, and acquires images from the surroundings having vertical line edges by one camera. From the image, vertical line edges are detected, and pattern vectors meaning averaged color values of the left and right regions of the each line are computed by using the properties of the line and a region growing method. The pattern vectors are matched with the feature points of the map by comparing the color information and the geometrical relationship. From the perspective transformation and rigid transformation of the corresponded points, nonlinear equations are derived. Localization is carried out from solving the equations by using Newton's method. Experimental results show that the proposed method using mono view is simple and applicable to indoor environment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.2
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• pp.165-172
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• 2020

There is growing interest in Vision-based video image matching owing to the constantly developing technology of unmanned-based systems. The purpose of this paper is the development of a fast and effective matching technique for the UAV oblique video image. We first extracted initial matching points using NCC (Normalized Cross-Correlation) algorithm and improved the computational efficiency of NCC algorithm using integral image. Furthermore, we developed a triangulation-based outlier removal algorithm to extract more robust matching points among the initial matching points. In order to evaluate the performance of the propose method, our method was quantitatively compared with existing image matching approaches. Experimental results demonstrated that the proposed method can process 2.57 frames per second for video image matching and is up to 4 times faster than existing methods. The proposed method therefore has a good potential for the various video-based applications that requires image matching as a pre-processing.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.6-13
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• 2015

With the spread of various kinds of cameras such as digital cameras and DSLR and a growing interest in high-definition and high-resolution images, a method that synthesizes multiple images is being studied among various methods. High Dynamic Range (HDR) images store light exposure with even wider range of number than normal digital images. Therefore, it can store the intensity of light inherent in specific scenes expressed by light sources in real life quite accurately. This study suggests feature points synthesis algorithm to improve the performance of HDR panorama recognition method (algorithm) at recognition and coordination level through classifying the feature points for image recognition using more than one multi frames.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.656-657
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• 2008

Light Detection and Ranging (LiDAR) data has been used to detect the objects of earth surface from huge point clouds gotten from the laser scanning system equipped on airplane. According to the precision of 3~5 points per square meter, objects like buildings, cars and roads can be easily described and constructed. Many various areas, such as hydrological modeling and urban planning adopt this kind of significant data. Researchers have been engaging in finding accurate road networks from LiDAR data recent years. In this paper, A novel algorithm with regard to extracting road points from LiDAR data has been developed based on the continuity and structural characteristics of road networks.

• Journal of Animal Science and Technology
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• v.64 no.3
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• pp.539-563
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• 2022

Nine pig farms were evaluated for the welfare quality in Korea using animal- and environment-based parameters (particularly air quality parameters) during the winter of 2013. The Welfare Quality^® (WQ^®) protocol consists of 12 criteria within four principles. The WQ^® protocol classifies farms into four categories ranging from 'excellent' to 'not classified'. Each of these criteria has specific measures for calculating scores. Calculations for the welfare scores were conducted online using the calculation model in the WQ^® protocol. Environment-based parameters like microclimate (i.e., temperature, relative humidity, air speed, and particulate matter), bacteria (total airborne bacteria, airborne total coliform, and airborne total Escherichia coli), concentration of gases (carbon dioxide, ammonia, and hydrogen sulfide) were measured to investigate the relationship between animal- and environment-based parameters. Correlations between the results of animal- and environment-based parameters were estimated using spearman correlation coefficient. The overall assessments found that five out of nine farms were 'acceptable', and four farms were 'enhanced'; no farm was 'not classified'. The average score for the four principles across the nine farms, in decreasing order, were 'good feeding' (63.13 points) > 'good housing' (59.26 points) > 'good health' (33.47 points) > 'appropriate behaviors' (25.48 points). In the result of the environment aspect, the relative humidity of farms 2 (93.4%), 3 (100%), and 9 (98%) was much higher than the recommended maximum relative humidity of 80%, and four out of the nine farms had ammonia concentrations greater than 40 ppm. Ammonia had negative correlations with 'positive social behaviors' and positive emotional states: content, enjoying, sociable, playful, lively, happy and it had positive correlations with negative emotional states: aimless, distressed. The concentration of carbon dioxide had negative correlations with positive emotional states; calm, sociable, playful, happy and it had a positive correlation with negative emotional state; aimless. Our results indicate that the control of the environment for growing pigs can help improve their welfare, particularly via good air quality (carbon dioxide, ammonia, hydrogen sulfide).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.111-121
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• 2006

Recently, many studies have been performed to apply airborne LIDAR data to extracting urban models. In order to model efficiently the man-made objects which are the main components of these urban models, it is important to extract automatically planar patches from the set of the measured three-dimensional points. Although some research has been carried out for their automatic extraction, no method published yet is sufficiently satisfied in terms of the accuracy and completeness of the segmentation results and their computational efficiency. This study thus aimed to developing an efficient approach to automatic segmentation of planar patches from the three-dimensional points acquired by an airborne LIDAR system. The proposed method consists of establishing adjacency between three-dimensional points, grouping small number of points into seed patches, and growing the seed patches into surface patches. The core features of this method are to improve the segmentation results by employing the variable threshold value repeatedly updated through a statistical analysis during the patch growing process, and to achieve high computational efficiency using priority heaps and sequential least squares adjustment. The proposed method was applied to real LIDAR data to evaluate the performance. Using the proposed method, LIDAR data composed of huge number of three dimensional points can be converted into a set of surface patches which are more explicit and robust descriptions. This intermediate converting process can be effectively used to solve object recognition problems such as building extraction.

• Journal of East-West Nursing Research
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• v.29 no.1
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• pp.1-5
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• 2023

Traditional Korean medicine and traditional Korean (Hanbang) nursing are very similar disciplines in terms of philosophy, values, and identity. Traditional Korean medicine views that harmonious and balanced human body and mental state can be formed through the flow of Qi and blood using meridians and acupressure points. This view can be applied to research, practice, theory, and education in Hanbang nursing. The meridian is a pathway through which Qi and blood, the energy necessary for life activities, pass through. Acupressure points are important meridians where physical, mental, and psychological health conditions appear as a response. Pressing and stimulating acupressure points to facilitate and communicate the flow of qi and blood in the meridians can create positive effects and enable the treatment of various symptoms and syndromes of our bodies. Hanbang nursing nursing, which is also based on the use of meridians, may be used to control various symptoms and syndromes and prevent and treat diseases. Currently, Hanbang nursing are growing along with the professionalism of Hanbang nursing practice, vitalization of Hanbang nursing research, and the development of Hanbang nursing education and theory. The growth of Hanbang nursing requires active participation of nursing scholars and efforts to converge beyond the walls of medicine and nursing.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.11
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• pp.1445-1454
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• 2010

Two separate animal trials were conducted to evaluate the coincidence of dry matter intake (DMI) and average daily gain (ADG) predicted by the Cornell Net Carbohydrate and Protein System (CNCPS) and observed actually in crossbred growing bulls kept in a traditionally confined feeding system in China. In Trial 1, 45 growing Simmental${\times}$Mongolia crossbred F1 bulls were assigned to three treatments (T1-3) with 15 animals in each treatment. Trial 2 was conducted with 60 Limousin${\times}$Fuzhou crossbred F2 bulls allocated to 4 treatments (t1-4). All of the animals were confined in individual stalls. DMI and ADG for each bull were measured as a mean of each treatment. All of the data about animals, environment, management and feeds required by the CNCPS model were collected, and model predictions were generated for animals on each treatment. Subsequently, model-predicted DMI and ADG were compared with the actually recorded results. In the three treatments in Trial 1, 93.3, 80.0 and 73.3% of points fell within the range from -0.4 to 0.4 kg/d for DMI mean bias; similarly, in the four treatments in Trial 2, about 86.7, 73.3, 73.3 and 80.0% of points fell within the same range. These results indicate that the CNCPS model can accurately predict DMI of crossbred bulls in the traditionally confined feeding system in China. There were no significant differences between predicted and observed ADG for T1 (p = 0.06) and T2 (p = 0.09) in Trial 1, and for t1 (p = 0.07), t2 (p = 0.14) and t4 (p = 0.83) in Trial 2. However, significant differences between predicted and observed ADG values were observed for T3 in Trial 1 (p<0.01) and for t3 in Trial 2 (p = 0.04). By regression analysis, a statistically different value of intercept from zero for the regression equation of DMI (p<0.01) or an identical value of ADG (p = 0.06) were obtained, whereas the slopes were significantly different (p<0.01) from unity for both DMI and ADG. Additionally, small root mean square error (RMSE) values were obtained for the unbiased estimator of the two variances (DMI and ADG). Thus, the present results indicated that the CNCPS model can give acceptable estimates of DMI and ADG of crossbred growing bulls kept in a traditionally confined feeding system in China.