• Korean Journal of Veterinary Research
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• v.36 no.4
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• pp.757-761
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• 1996

The animal bone-remains excavated with earthwares at Cheju Kimnyungri cave site were investigated morphologically and osteometrically. The number of bone remains were 1706 pieces by morphological criteria. Based on the classification of bony pieces excavated in the cave site, the important animal species in Cheju island during the early Tamra period (presumably between A.D.0 - A.D. 500) was as follows; wild boar(75%), deer(17%), cattle(6%), and horse in small percentage. The excavated bone remains imply that the major fauna of animal species are composed of three species, including Sus scrofa, Cervus nippon and Bos taurus. These data suggests that the archaeological remains such as bone pieces are good indicators of the fauna animals, and of zoological entity in the island.

• Korean journal of applied entomology
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• v.61 no.3
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• pp.503-506
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• 2022

Aleiodes conina (Butcher et al., 2012) belonging to the subfamily Rogadinae in the family Braconidae is first reported from Korea. Diagnosis, distribution, and illustration are provided for this species.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.301-304
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• 2007

A realization for image searching engine with moving objects identification and classification is presented in this paper. The identification algorithm is applied to extract difference image between input image and the reference image, and the classification is used the region segmentation. That is made the database for the searching engine. The experimental result of the realized system enables to search for human and animal at time intervals to use a surveillant system at inside environment.

• Journal of Animal Reproduction and Biotechnology
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• v.36 no.2
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• pp.99-105
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• 2021

In horse management, the alarm system with sensors in the foaling period enables the breeder can appropriately prepare the time of the parturition. It is important to prevent losses by unpredictable parturition because there are several high risks such as dystocia and the death of foals and mares during foaling. However, unlike analysis in the alarm system that detects specific motions has been widely performed, analysis of classification following specific behavior patterns or number needs to be more organized. Thus, the objective of this study is to classify signs of the specific behaviors of the mares for the prediction of pre-foaling behaviors. Five Thoroughbred mares (9-20 yrs) were randomly selected for observation of the pre-foaling behaviors. The behaviors were monitored for 90 min that was divided into three different periods as 1) from -90 to -60 min, 2) from -60 to -30 min, 3) from -30 min to the time for the discharge of the amniotic fluid, respectively. The behaviors were divided into two different categories as state and frequent behaviors and each specific behavioral pattern for classification was individually described. In the state behaviors, the number of mares in the standing of the foaling group (3.17 ± 0.18^b) at period 3 was significantly higher than the control group (1.67 ± 0.46^a). In contrast, the number of the mares in the eating of the foaling group (1.17 ± 0.34^b) at period 3 was significantly lower than the control group (3.33 ± 0.46^a). In the frequent behaviors, the weaving of the foaling group was significantly higher than the control group, and looking at the belly of the foaling group was significantly lower than the control group. In period 2, defecation, weaving, and lowering the head of the foaling group were significantly higher than the control group, respectively. In period 3, sitting down and standing up, pawing, weaving, and lowering the head in the foaling group were also significantly higher than the control group. In conclusion, the behavior is significantly different in foaling periods, and the prediction of foaling may be feasible by the detection of the pre-foaling behaviors in the mares.

• The KIPS Transactions:PartD
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• v.10D no.6
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• pp.897-906
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• 2003

The traditional animal phylogenetic tree is to align the body structure of the animal phylums from simple to complex based on the initial development character. Currently, molecular systematics research based on the molecular, it is on the fly, is again estimating prior trend and show the new genealogy and interest of the evolution. In this paper, we generate the training set which is obtained from a DNA sequence ans apply to the classification. We made use of the mitochondrial DNA for the experiment, and then proved the accuracy using the MEGA program which is anaysis program, it is used in the biology field. Although the result of the mining has to proved through biological experiment, it can provede the methodology for the efficient classify and can reduce the time and effort to the experiment.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.8
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• pp.1096-1104
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• 2010

This bio-acoustic study was aimed at classifying the different porcine wasting diseases through sound analysis with emphasis given to differences in the acoustic footprints of coughs in porcine circo virus type 2 (PCV2), porcine reproductive and respiratory syndrome (PRRS) virus and Mycoplasma hyopneumoniae (MH) - infected pigs from a normal cough. A total of 36 pigs (Yorkshire${\times}$Landrace${\times}$Duroc) with average weight ranging between 25-30 kg were studied, and blood samples of the suspected infected pigs were collected and subjected to serological analysis to determine PCV2, PRRS and MH. Sounds emitted by coughing pigs were recorded individually for 30 minutes depending on cough attacks by a digital camcorder placed within a meter distance from the animal. Recorded signals were digitalized in a PC using the Cool Edit Program, classified through labeling method, and analyzed by one-way analysis of variance and discriminant analysis. Input features after classification showed that normal cough had the highest pitch level compared to other infectious diseases (p<0.002) but not statistically different from PRRS and MH. PCV2 differed statistically (p<0.002) from the normal cough and PRRS but not from MH. MH had the highest intensity and all coughs differed statistically from each other (p<0.0001). PCV2 was statistically different from others (p<0.0001) in formants 1, 2, 3 and 4. There was no statistical difference in duration between different porcine diseases and the normal cough (p>0.6863). Mechanisms of cough sound creation in the airway could be used to explain these observed acoustic differences and these findings indicated that the existence of acoustically different cough patterns depend on causes or the animals' respiratory system conditions. Conclusively, differences in the status of lungs results in different cough sounds. Finally, this study could be useful in supporting an early detection method based on the on-line cough counter algorithm for the initial diagnosis of sick animals in breeding farms.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.12
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• pp.1901-1908
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• 2007

The aim of this series of experiments was to examine the opportunity for application of X-ray computer tomography (CT) in cattle production. Firstly, tissue composition of M. longissimus dorsi (LD) cuts between the $11-13^{th}$ ribs (in Exp 1. between the $9-11^{th}$ ribs), was determined by CT and correlated with tissue composition of intact half carcasses prior to dissection and tissue separation. Altogether, 207 animals of different breeds and genders were used in the study. In Exp. 2 and 3, samples were taken from LD cuts, dissected and chemical composition of muscle homogenates was analysed by conventional procedures. Correlation coefficients were calculated among slaughter records, tissues in whole carcasses and tissue composition of rib samples. Results indicated that tissue composition of rib samples determined by CT closely correlated with tissue composition results by dissection of whole carcasses. The findings revealed that figures obtained by CT correlate well with the dissection results of entire carcasses (meat, bone, fat). Close three-way coefficients of correlation (r = 0.80-0.97) were calculated among rib eye area, volume of cut, pixel-sum of adipose tissue determined by CT and intramuscular fat or adipose tissue in entire carcasses. Estimation of tissue composition of carcasses using equations including only CT-data as independent variables proved to be less reliable in prediction of lean meat and bone in carcass ($R^2 = 0.51-0.86$) than for fat (($R^2 = 0.83-0.89$). However, when cold half carcass weight was also included in the equation, the coefficient of determination exceeded $R^2 = 0.90$. In Exp. 3 tissue composition of rib samples by CT were compared to the results of EUROP carcass classification. Findings revealed that CT analysis has higher predictive value in estimation of actual tissue composition of cattle carcasses than EUROP carcass classification.

• Journal of The Korean Society of Grassland and Forage Science
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• v.35 no.3
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• pp.251-256
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• 2015

The study was conducted to determine greenhouse gas (GHG) inventories in grasslands. After 'Low Carbon Green Growth' was declared a national vision on 2008, Medium-term greenhouse gas reduction was anticipated for 30% reduction compared to Business As Usual (BAU) by 2020. To achieve the reduction targets and prepare to enforce emissions trading (2015), national GHG inventories were measured based on the 1996 Intergovernmental Panel on Climate Change Guidelines (IPCC GL). The national Inventory Report (NIR) of Korea is published every year. Grassland sector measurement was officially added in 2014. GHG removal of grassland soil was measured from 1990 to 2012. Grassland area data of Korea was used for farmland area data in the "Cadastral Statistical Annual Report (1976~2012)". Annual grassland area corresponding to the soil classification was used "Soil classification and commentary in Korea (2011)". Grassland area was divided into 'Grassland remaining Grassland' and 'Land converted to Grassland'. The accumulated variation coefficient was assumed to be the same without time series changes in grassland remaining grassland. Therefore, GHG removal of soil carbon was calculated as zero (0) in grassland remaining grassland. Since the grassland area increases constantly, the grassland soil sinks constantly . However, the land converted to grassland area continued to decrease and GHG removal of soil carbon was reduced. In 2012 (127.35Gg $CO_2$), this removal decreased by 76% compared to 1990 (535.71 Gg $CO_2$). GHG sinks are only grasslands and woodlands. The GHG removaled in grasslands was very small, accounting for 0.2% of the total. However, the study provides value by identifying grasslands as GHG sinks along with forests.

• Journal of Korean Library and Information Science Society
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• v.34 no.1
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• pp.239-260
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• 2003

The purpose of this study is to devise a classification scheme to arrange the agricultural information efficiently. In the first part it defines the agricultural science and studies the content and system of the agricultural science. It compares current KDC with DDC, UDC and NDC used to agriculture parts, and it studies AGRICOLA SCC. On the basis of it, this study is displayed the new classification for the agricultural science. The new classification scheme Is classified by the basic theories related to agriculture, agriculture of plants, animal agriculture, food products, and auxiliary disciplines in turn. The number of main divisions are set up 23 items.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.7
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• pp.1015-1026
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• 2019

Objective: The objective of this study was to evaluate three different degrees of white striping (WS) addressing their automatic assessment and customer acceptance. The WS classification was performed based on a computer vision system (CVS), exploring different machine learning (ML) algorithms and the most important image features. Moreover, it was verified by consumer acceptance and purchase intent. Methods: The samples for image analysis were classified by trained specialists, according to severity degrees regarding visual and firmness aspects. Samples were obtained with a digital camera, and 25 features were extracted from these images. ML algorithms were applied aiming to induce a model capable of classifying the samples into three severity degrees. In addition, two sensory analyses were performed: 75 samples properly grilled were used for the first sensory test, and 9 photos for the second. All tests were performed using a 10-cm hybrid hedonic scale (acceptance test) and a 5-point scale (purchase intention). Results: The information gain metric ranked 13 attributes. However, just one type of image feature was not enough to describe the phenomenon. The classification models support vector machine, fuzzy-W, and random forest showed the best results with similar general accuracy (86.4%). The worst performance was obtained by multilayer perceptron (70.9%) with the high error rate in normal (NORM) sample predictions. The sensory analysis of acceptance verified that WS myopathy negatively affects the texture of the broiler breast fillets when grilled and the appearance attribute of the raw samples, which influenced the purchase intention scores of raw samples. Conclusion: The proposed system has proved to be adequate (fast and accurate) for the classification of WS samples. The sensory analysis of acceptance showed that WS myopathy negatively affects the tenderness of the broiler breast fillets when grilled, while the appearance attribute of the raw samples eventually influenced purchase intentions.