• Journal of Animal Science and Technology
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• v.50 no.6
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• pp.819-830
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• 2008

The object of this study was to investigate different levels of extruded rice product(Nutri-RS®) supplementation as an alternative to lactose on growth performance, diarrhea score, fecal E.coli and volatile fatty acid(VFA) in weaning pigs. Treatments were 1) Control(basal), L3(basal+3% extruded rice product), L6(basal+6% extruded rice product). The control diet in Phase I and Phase II contained 16 and 9% of lactose, respectively. For the feeding trial, a total of 81 crossbred pigs, averaging 7.56±1.18 kg body weight, were allotted to three treatments in three replicates with nine pigs per pen by RCBD. The experimental period was total 5 weeks. During the whole experimental period, there were no significant differences in growth performance, diarrhea score, fecal volatile fatty acid concentration among all treatments. Although there were no significant differences, pigs fed diet of L6 tended to show higher BW and ADG, ADFI, and fecal volatile fatty acid concentration compared to other treatments. Treatment L6 showed the lowest fecal E. coli count among all treatments(P<0.05). These results suggested that inclusion of extruded rice product has similar performance a with 6% of lactose in diet for weaning pigs and reduce approximately 9% production cost of weaning pig's diet. Therefore, extruded rice product could be utilized as an alternative feed ingredient to lactose in weaning pig’s diet.

• Journal of Korean Society of Environmental Engineers
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• v.29 no.7
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• pp.820-825
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• 2007

Earthworm casting was the natural fertilizer that contained high concentrations of nutrients such as nitrogen, phosphate and potassium and of over $10^8$ CFU/ml of microorganisms. Greater than 80% of feed was excreted through the fermentation by the intestinal enzyme, after worm had eaten feeds such as fallen leaves and rotten roots under the ground. Also, the soil structure of casting was known to be very efficient in the aspects of the porosity, the water permeability, and deodorizing activities. In this research, the biofilter packed with a biomedia made of casting and waste polyurethane foam, a binder, which helped to improve the durability and perpetuity of casting, was investigated to degrade malodorous hydrogen sulfide gas. The biomedia had no need of extra supply of nutrients and of microbial inoculations. On the beginning of the operations, it showed 100% removal of hydrogen sulfide gas without lag phase. At SV of 50 $h^{-1}$, hydrogen sulfide gas from the outlet of the biofilter was not detected, when inlet concentration increased to 450 ppmv. After that, removal efficiency decreased as increasing inlet hydrogen sulfide concentration. Hydrogen sulfide removal was maintained at almost 93% until inlet concentration was increased up to 950 ppmv, at which the elimination capacity of $H_2S$ was 61.2 g $S{\cdot}m^{-3}{\cdot}h^{-1}$. Maximum elimination capacity guaranteing 90% removal was 61.2, 65.9, 84.7, 89.4 g $S{\cdot}m^{-3}{\cdot}h^{-1}$ at SV ranging from 50 $h^{-1}$ to 300 $h^{-1}$, but was 59.3 g $S{\cdot}m^{-3}{\cdot}h^{-1}$ at SV of 400 $h^{-1}$. The results calculated from Michaelis-Menten equation revealed that $V_m$ increased from 66.04, 88.96, 117.35, 224.15, to 227.54 g $S{\cdot}m^{-3}{\cdot}h^{-1}$ with increasing space velocity in the range of 50 $h^{-1}$ to 400 $h^{-1}$. However, saturation constant$(K_s)$ decreased from 79.97 ppmv to 64.95 and 65.37 ppmv, and then increased to 127.72 and 157.43 ppmv.

• Korean journal of applied entomology
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• v.48 no.4
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• pp.467-477
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• 2009

Host preference was tested on the 7 species plants against ggot-mae-mi, Lycorma delicatula (Hemiptera: Fulgoridae). This insect highly preferred Ailanthus altissima and Vitis vinifera however, didn't choose the other plants preferentially. Both nymphs and adults lived longest in A. altissima and V. vinifera but lived in short and low ecdysis rate against other plants and 3 species fruits. By analyzing the phloem-feeding behavior using EPG, L. delicatula was showed the short time in non-probing phase and it also exhibit the longest feeding time in A. altissima and V. vinifera, but other plants did not feed the phloem at all. In sugar contents analysis, A. altissima existed high sucrose proportion and followed by fructose>glucose, V. vinifera was analyzed by an order of glucose> fructose>maltose>sucrose>rhamnose, Malus pumila was as glucose> fructose, Pyrus calleryana was as glucose>unkown>fructose, Hibiscus syriacus was as sucrose>glucose. Nymphs and adults of L. delicatula lived longest in 5% sucrose solution, and next is in 5% fructose solution. However, they lived short in other sugar solutions. L. delicatula nymph and adult according to the combination of sugar proportion found in original plants lived longer in sugar combination solution of A. altissima and those of V. vinifera was next. Analyzed original sugar proportion from M. pumila, P. calleryana, H. syriacus respectively, L. delicatula lived short period comparing to the A. altissima, V. vinifera. This result was judged that sugar contents affected on choosing the host plants.

• Korean Journal of Veterinary Service
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• v.37 no.2
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• pp.111-122
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• 2014

The present study was designed to explore the antioxidant effect of Bamboo powder and its immunoreactivity in pigs. We investigated the functional properties of Bamboo extracts by means of measuring the contents of total polyphenols and flavonoid as well as determining ABST, DPPH radical scavenging activity, and hydroxyl radical scavenging activity and anticancer activity. The total phenolic compound and flavonoids contents of Bamboo extracts were 171.25 mg/g and 127.5 mg/g, respectively. The DPPH radical, hydroxyl radical, ABST radical scavenging activity of Bamboo extracts were 17.3%, 12.5% and 21.5%, respectively. Evidenced by MTT and cell cycle assay, Bamboo dose-dependently inhibited the cell proliferation and induced G0/G1-phase arrest in CHO cells at concentrations of 100, 250, and 500 ${\mu}g/ml$ Bamboo extracts. More than 80% of apoptotic cells were observed by staining with annexin V in 500 ${\mu}g/ml$ Bamboo-treated CHO cells, indicating that Bamboo had potent anticancer activities. Next, to investigate the effect of Bamboo on cytokine, immunoglobulin concentration, and blood compositions, flatting pigs were fed with Bamboo powder for 38 days. Flatting pigs were divided into 4 groups; basal diet (control), basal diet supplemented with 1% Bamboo powder (T1), 2% Bamboo powder (T2), and 3% Bamboo powder (T3). The level of hemoglobin increased in the all Bamboo-fed groups compared with the normal control group. In particular, platelet levels in the all Bamboo-treated groups increased by approximately 90% compared with the levels from pig on a normal control. Serum levels of immunoglobulins (IgG, IgA) in the pigs fed Bamboo powder were modestly increased, and the interferon-${\gamma}$ level also was strongly increased in 2% or 3% Bamboo-fed groups compared with the levels in control groups. Together, these results demonstrated that Bamboo extracts had an effective capacity of scavenging for ABTS, DPPH, and hydroxyl radicals and showed correlation with potent phenol and flavonoid contents, thus suggesting its antioxidant potential. Moreover, administration of Bamboo in 2~3% improved blood parameters and platelets, and especially immunity-related ones such as IgG, IgA, and interferon-${\gamma}$, leading to be potential feed additives in flatting pigs.

• Journal of Korean Society of Forest Science
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• v.78 no.2
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• pp.177-188
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• 1989

The habitat typing method of classification based on community has been developed on many forested areas in the ROCKY MOUNTAINS of WESTERN NORTH AMERICA, and is being used in providing an objective principle of guide for classification of forest sites, land classification, vertical distribution and multipurpose management of forest. I actually made a trial of forest habitat type classification - The methodology can be segmented into a number of tasks including reconnaissance, selection of stands to be sampled, location of plots, data gathering, preliminary and computer analysis, preparation of key- and map of habitat type and description for each habitat type in a view of forest management - on UNIVERSITY OF MONTANA FORESTS in order to examine whether its application is fit or not in korean forest circumstances : these are composed mainly of artificial forest and forest in the early stage of succession. The main results obtained from this study were summarized as follows 1. A hierarchical classification-Climax, Habitat type and Phases-of forest sites was developed using the habitat typing method of classification. 2. A diagnostic key is provided for field identification of the types based upon presence and number of indicator species, and forest managers could prepare a map of habitat type and classify forest habirat types by reference to it. 3. The classified habitat types were considered to be effective on providing an objective principle of guide for multipurpose management of forest including potential productivity for timber, feed productivity of forage and wildlife, selection of the right species in the right sites, application of method of treatment and so forth. 4. Forest habitat type classifications based upon extrapolation which used relict species and associated stands is considered to be suitable for korean forest circumstances and objective in studying potential vegetation, vertical and horizontal distribution of forest.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.2
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• pp.97-104
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• 2019

This experiment was conducted to investigate the effect of whole crop rice (WCR) based TMR on growth performance and carcass characteristics of Hanwoo steers. WCR "Yeongwoo"was harvested at yellow ripen stage and ensiled for 60 days. The crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), in vitro dry matter digestibility (IVDMD) and total digestible nutrient (TDN) content was 8.4 %, 28.0 %, 53.8 %, 72.4 % and 66.8 %, respectively. For silage quality, pH was 4.37 and lactic and butyric acid content were 2.84 and 0.04 % in DM. Sixteen Hanwoo steers (8-mon-old) were allocated into either a control (commercial TMR) and WCR-TMR (WCR-based TMR) group. The TMR were fed according to the feeding stage phase: growing (Initiate~14 month), early fattening (15 month~21 month) and late fattening (22 month~30 month). The body weight of control group increased (P<0.05) until early fattening stage, but late growing stage of WCR-TMR group was higher than that of control (P<0.05). Average daily gain (ADG) was significantly greater (P<0.05) in WCR-TMR group (total 0.78 kg/head) compared to control (total 0.66 kg/head) except for late fattening stage. The marketing weight and carcass weight were higher in WCR-TMR group (726 vs 765 kg; 417.8 vs 450.4 kg). The back fat thickness (11.75 vs 13.00 mm), Longissimus dorsi area (88.00 vs $89.88cm^2$) and yield index (65.87 vs 64.30) were not different between the two groups (P>0.05) and also no difference in meat yield grade (A : B : C = 2 : 4 : 2). Marbling score (4.00 vs 4.13), meat color (4.75 vs 4.75), fat color (3.13 vs 2.88), texture (1.25 vs 1.50) and maturity (2.00 vs 2.00) were not significant difference between the two groups and meat quality grade ($1^{{+}{+}}:1^+:1:2:3=0:2:4:2:0$) was also not different. In conclusion, TMR feeding based on WCR silage showed superiority in carcass yield and ADG compared to control TMR. It is considered that the use of WCR for feed is a necessary option for the substitution of the imported forages and the government's policy for rice production adjustment.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.205-225
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• 2018

Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.