• Korean Journal of Animal Reproduction
• /
• v.23 no.4
• /
• pp.337-345
• /
• 1999

The present study was conducted to investigate the effects of various co-culture systems and supplemented protein sources on the in vitro development of bovine IVF embryos. Bovine cumulus oocyte complexes (COCs) were matured and fertilized in vitro. Presumptive zygotes with cumulus cells were transferred to TCM-199 or CRlaa containing 10% FBS or 3mg/$m\ell$ BSA, and cultured for 36~40 hr. After primary culture, cleaved embryos were co-cultured with cumulus cells(CC), bovine oviduct epithelial cells(BOEC) or Buffalo rat liver cells (BRLC) in TCM-199 or CRlaa supplemented with FBS or BSA respectively, for further 6 days. Cleavage rate increased with BSA(P＜0.01) in the both TCM-199(79%) or CRlaa(74%) When embryos were co-cultured with CC or BOEC in TCM-199, blastocyst development was enhanced with BSA(40% and 43%) compared to FBS (22% and 29%) , whereas in CRlaa no difference observed between BSA(40% and 39%) and FBS (40% and 42%). When embryos were co-cultured with BRLC monolayer, FBS enhanced the blastocyst development (P＜0.05) compared to BSA in both TCM-199(41% vs 31%) and CRlaa (44% vs 37%). The result of the present study showed that the cleavage rate of bovine IVF embryos increased with BSA, The result also showed that BSA can enhance the development of IVF embryos in co-culture with CC or BOEC in TCM-199, suggesting the in vitro development is affected by the medium and supplemented protein sources in co-culture with somatic cells.

• Journal of Intelligence and Information Systems
• /
• v.12 no.1
• /
• pp.17-31
• /
• 2006

In this paper, passport recognition and face verification methods which can automatically recognize passport codes and discriminate forgery passports to improve efficiency and systematic control of immigration management are proposed. Adjusting the slant is very important for recognition of characters and face verification since slanted passport images can bring various unwanted effects to the recognition of individual codes and faces. Therefore, after smearing the passport image, the longest extracted string of characters is selected. The angle adjustment can be conducted by using the slant of the straight and horizontal line that connects the center of thickness between left and right parts of the string. Extracting passport codes is done by Sobel operator, horizontal smearing, and 8-neighborhood contour tracking algorithm. The string of codes can be transformed into binary format by applying repeating binary method to the area of the extracted passport code strings. The string codes are restored by applying CDM mask to the binary string area and individual codes are extracted by 8-neighborhood contour tracking algerian. The proposed RBF network is applied to the middle layer of RBF network by using the fuzzy logic connection operator and proposing the enhanced fuzzy ART algorithm that dynamically controls the vigilance parameter. The face is authenticated by measuring the similarity between the feature vector of the facial image from the passport and feature vector of the facial image from the database that is constructed with PCA algorithm. After several tests using a forged passport and the passport with slanted images, the proposed method was proven to be effective in recognizing passport codes and verifying facial images.

• Journal of the Korean Professional Engineers Association
• /
• v.28 no.4
• /
• pp.54-75
• /
• 1995

This synthesis has been prepared from a review of literature on Truck Escape Ramps technology and a survey of current practice by state department of transportation. Their locations have been determined usually from a combination of accident experience and en-gineering judgement, but new tools are emerging that can identify needs and sites without waiting for catastrophic accidents to happen. The Grade Severity Rating Systems holds promise in this regard. Design Procedures for truck excape ramps continue to evolve. Gravel arrester beds are clearly the preferred choice across the country Rounded aggregate, uniformly graded in the approximate size range of 13 to 18mm. Tech-nical publications typically have dassified TER types as paved gravity, sandpile, and ar-rester bed ramps. The design speed for vehicle entry into the ramp in critical to the deter-mination of ramp length. An escape ramp should be designed for a minimum entry speed of 130km/hr, a 145km/hr design being preferred. The ramps should be straight and their angle to the roadway align-ment should be as possible. The grade of truck escape ramps show the adjustment of ramp design to local topography, such as the tradeoff of ramp length against earthwork requirements. A width of 9 to 12m would more safety acommodate two or more outof con-trol vehicles. Reguarding comments on the most effective material, most respondents cited their own specification or referred to single graded, rounded pea gravel. The consensus essentially Is that single graded, well -rounded gravel is the most desirable material for use in arrester beds. The arrester beds should be constructed with a minimum aggregate depth of 30cm. Successful ramps have used depths between 30 and 90cm.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.38 no.12
• /
• pp.1699-1706
• /
• 2009

This study was conducted to investigate the antioxidative effects of chungkukjang fermented using Bacillus subtilis DJI (DJI CJ) in rats fed high cholesterol diet. Sprague-Dawley male rats weighing 185-195 g were divided into 6 groups: normal group (N), high cholesterol group (C), high cholesterol and DJI CJ with no salt group (C-CJN), high cholesterol and DJI CJ added with solar salt group (C-CJS), high cholesterol and DJI CJ added with refined salt group (C-CJR), and high cholesterol and commercial CJ group (C-CCJ). The body weight gain and food intake in all four CJ groups were lower than C group. The serum activities of AST and ALT that were elevated by high cholesterol diet were significantly decreased by CJ supplemented. The hepatic activities of catalase and SOD in C group were increased to 20.59% and 18.72%, respectively, compared with N group, but those of C-CJN, C-CJS, C-CJR, and C-CCJ groups were similar to those of N group. Liver TBARS contents were significantly decreased in all CJ groups, compared with C group. The contents of brain lipofuscin in C-CJN, C-CJS, C-CJR, and C-CCJ groups were remarkably inhibited about 20.86%, 22.06%, 14.73%, and 12.88%, respectively, compared with C group. There were no significant differences among DJI CJ groups in antioxidative effects. According to this study, DJI chungkukjang or commercial chungkukjang seems to protect tissues from oxidative stress by stimulating antioxidative systems in rats fed a high cholesterol diet.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.35 no.3
• /
• pp.679-690
• /
• 2015

The need to remove the cause of traffic accidents by improving the engineering system for a vehicle and the road in order to minimize the accident hazard. This is likely to cause traffic accident continue to take a large and significant social cost and time to improve the reliability and efficiency of this generally poor road, thereby generating a lot of damage to the national traffic accident caused by improper environmental factors. In order to minimize damage from traffic accidents, the cause of accidents must be eliminated through technological improvements of vehicles and road systems. Generally, it is highly probable that traffic accident occurs more often on roads that lack safety measures, and can only be improved with tremendous time and costs. In particular, traffic accidents at intersections are on the rise due to inappropriate environmental factors, and are causing great losses for the nation as a whole. This study aims to present safety countermeasures against the cause of accidents by developing an intersection Traffic safety evaluation model. It will also diagnose vulnerable traffic points through BPA (Back -propagation algorithm) among artificial neural networks recently investigated in the area of artificial intelligence. Furthermore, it aims to pursue a more efficient traffic safety improvement project in terms of operating signalized intersections and establishing traffic safety policies. As a result of conducting this study, the mean square error approximate between the predicted values and actual measured values of traffic accidents derived from the BPA is estimated to be 3.89. It appeared that the BPA appeared to have excellent traffic safety evaluating abilities compared to the multiple regression model. In other words, The BPA can be effectively utilized in diagnosing and practical establishing transportation policy in the safety of actual signalized intersections.

• Development and Reproduction
• /
• v.11 no.3
• /
• pp.263-272
• /
• 2007

Contrast to mouse where its in vitro maturation rates are high without specific supplements or presence of the cumulus cells, there are some species, such as porcine, where its in vitro oocyte maturation rates are still very low. This comparative study was conducted to investigate the role of malate dehydrogenase(Mor2) during oocyte maturation by RNAi in the mouse and porcine. The Mor2 double-stranded RNA(dsRNA) was prepared speciesspecifically and microinjected into the cytoplasm of denuded germinal vesicle(GV) oocytes. Oocytes were cultured for 48 h(porcine) and 16 h(mouse) in M199 with 10% porcine follicular fluid, pyruvate, p-FSH, EGF, cystein, and estradiol-$17{\beta}$. We measured changes in oocyte morphology, maturation rates and mRNA levels after Mor2 RNAi. We confirmed gene sequence-specific knock down of Mor2 mRNA in both species after Mor2 RNAi. In contrast to our previous finding that mMor2 RNAi resulted in GV arrest in the mouse, we found that pMor2 RNAi resulted in MI arrest in denuded porcine oocytes(58%), but developed to MII(84.4%) in COCs. To determine whether this difference between mouse and porcine RNAi is due to differences in culture media, we cultured mouse oocytes in the M199 media for 16 h after mMor2 RNAi. Mouse oocytes were developed to MII stage(62%) and there was no statistical difference compared to that of non-injected(76.8%) and buffer-injected(73.3%) control groups. Therefore, we concluded that the mouse and porcine oocytes are having different metabolic systems in relation to malate dehydrogenase for oocyte maturation. This could be a basis for differences in maturation rates in vitro in two species. Further scrutinized studies on the metabolic pathways would led us in finding better culture system to improve oocyte maturation rates in vitro, especially in more challenging species like the porcine.

• Radiation Oncology Journal
• /
• v.16 no.3
• /
• pp.325-335
• /
• 1998

Purpose : Since the mid cranial fossa is composed of various thickness of bone, the tissue inhomogeneity caused by bone would produce dose attenuation in cobalt-60 gamma knife irradiation. The correction factor for bone attenuation of cobalt-60 which is used for gamma knife source is -3.5$\%$. More importantly, nearly all the radiosurgery treatment planning systems assume a treatment volume of unit density: any perturbation due to tissue inhomogeneity is neglected, This study was performed to confirm the bone attenuation in mid cranial fossa using gamma knife. Materials and Methods : Computed tomography was performed after Leksell stereotactic frame had been liked to the Alderson Rando Phantom (human phantom) skull area. Kodak X-omat V film was inserted into two sites of pituitary adenoma point and acoustic neurinoma point, and irradiated by gamma knife with 14mm and 18mm collimator. An automatic scanning densitometer with a 1mm aperture is used to measure the dose profile along the x and y axis. Results : Isodose curve constriction in mid cranial fossa is observed with various ranges. Pituitary tumor point is greater than acoustic neurinoma point (0.2-3.0 mm vs 0.1-1.3 mm) and generally 14 mm collimator is greater than 18mm collimator (0.4-3.0 mm vs. 0.2-2.2 mm) Even though the isodose constriction is found, constriction of 50$\%$ isodose curve which is used for treatment reference line does not exceed 1 mm. This range is too small to influence the treatment planning and treatment results. Conclusion : Radiosurgery planning system of gamma knife does not show significant error to be corrected without consideration of bone attenuation.

• Journal of Korean Society of Environmental Engineers
• /
• v.34 no.6
• /
• pp.414-420
• /
• 2012

In an effort to commercialization of energy saving aeration apparatus, panel-type aeration membranes were prepared from polyurethane sheet of J company in Korea having tensile strength higher than $400kg_f/cm^2$ with thickness of 0.5mm. Micropores of 100 m size were made by poring technique utilizing needles. From lab-tests in 450 L water tank at temperature of $20^{\circ}C$, the performance of aeration panels at 40 L/min aeration rate showed 5 mg/L DO in less than 3 minutes approaching saturation point of 8 mg/L within 8 minutes. The results show very high efficiency with $K_{La(15)}$ ($16.34hr^{-1}$), Standard oxygen transfer efficiency (SOTE 54.7%) and Standard aeration efficienct (SAE 7.88 kg/kwh). Other pilot scale test in a $2m^3$ water tank with water temperature ($19^{\circ}C$) and aeration rate (30 L/min) showed DO exceeding 5 mg/L within 8 minutes along with $K_{La(15)}$ ($5.8hr^{-1}$), SOTE (42.1%) and SAE (6.41 kg/kwh). These efficiencies represent 2~2.5 times higher than conventional aeration devices. Especially, the achievement of higher Oxygen Transfer Rate indicate higher commercial viability. Conventional aeration devices when applied to clean water and wastewater frequently cause problems due to differences in actual Oxygen Transfer Rate. Our actual tests with $40^{\circ}C$ animal farm wastewater resulted very high efficiencies with Oxygen transfer efficiency ($OTE_f$ 22.1%) and $OTE_{pw40}$ (39.6%).

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.5
• /
• pp.195-202
• /
• 2016

The government has run and managed various forms of direct payment systems, such as the paddy and field direct payment, to ease the instability of farm incomes with respect to market opening, and preserve farm income. Direct payments to the agricultural sector is a center in the key policy instrument that plays an important role in income stabilization. Despite the large amount of spending in the farm unit, the status of direct payment, and policy effects the analysis of direct payments, such as stability of income contribution, are insufficient. This paper, using the farm unit DB in 2014 and 2015, performed farm level analysis of direct payment, and derived the implications of the performance evaluation system. As a result, the distribution of direct payment showed considerable bias to the left side compared to the normal distribution curve. Approximately half of the farms (49.3%) in 2014 DB should receive below 100,000 won per year by a direct payment. A larger-scale farm showed a significantly increased income effect and income stabilizing effect because direct payments make higher contributions to farm income in proportional to the area. In the more elderly farmers, a high contribution by direct payment to farm income was found to be an advantage; however, in small-scale farms of less than 0.5ha, direct payment contribution on farm household income was only 3%. In large-scale farms, 10ha or more, the contribution to farm income were found to be 29.4%. The income of large farms was 10 times larger than small farmers, and the direct payment entitlements that were received were 110 times larger. Through this policy, direct payments are required for future improvements and modifications.

• Journal of Intelligence and Information Systems
• /
• v.22 no.2
• /
• pp.127-142
• /
• 2016

Deep learning model is a kind of neural networks that allows multiple hidden layers. There are various deep learning architectures such as convolutional neural networks, deep belief networks and recurrent neural networks. Those have been applied to fields like computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics where they have been shown to produce state-of-the-art results on various tasks. Among those architectures, convolutional neural networks and recurrent neural networks are classified as the supervised learning model. And in recent years, those supervised learning models have gained more popularity than unsupervised learning models such as deep belief networks, because supervised learning models have shown fashionable applications in such fields mentioned above. Deep learning models can be trained with backpropagation algorithm. Backpropagation is an abbreviation for "backward propagation of errors" and a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent. The method calculates the gradient of an error function with respect to all the weights in the network. The gradient is fed to the optimization method which in turn uses it to update the weights, in an attempt to minimize the error function. Convolutional neural networks use a special architecture which is particularly well-adapted to classify images. Using this architecture makes convolutional networks fast to train. This, in turn, helps us train deep, muti-layer networks, which are very good at classifying images. These days, deep convolutional networks are used in most neural networks for image recognition. Convolutional neural networks use three basic ideas: local receptive fields, shared weights, and pooling. By local receptive fields, we mean that each neuron in the first(or any) hidden layer will be connected to a small region of the input(or previous layer's) neurons. Shared weights mean that we're going to use the same weights and bias for each of the local receptive field. This means that all the neurons in the hidden layer detect exactly the same feature, just at different locations in the input image. In addition to the convolutional layers just described, convolutional neural networks also contain pooling layers. Pooling layers are usually used immediately after convolutional layers. What the pooling layers do is to simplify the information in the output from the convolutional layer. Recent convolutional network architectures have 10 to 20 hidden layers and billions of connections between units. Training deep learning networks has taken weeks several years ago, but thanks to progress in GPU and algorithm enhancement, training time has reduced to several hours. Neural networks with time-varying behavior are known as recurrent neural networks or RNNs. A recurrent neural network is a class of artificial neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. Early RNN models turned out to be very difficult to train, harder even than deep feedforward networks. The reason is the unstable gradient problem such as vanishing gradient and exploding gradient. The gradient can get smaller and smaller as it is propagated back through layers. This makes learning in early layers extremely slow. The problem actually gets worse in RNNs, since gradients aren't just propagated backward through layers, they're propagated backward through time. If the network runs for a long time, that can make the gradient extremely unstable and hard to learn from. It has been possible to incorporate an idea known as long short-term memory units (LSTMs) into RNNs. LSTMs make it much easier to get good results when training RNNs, and many recent papers make use of LSTMs or related ideas.