Animal Infectious Diseases Prevention through Big Data and Deep Learning (빅데이터와 딥러닝을 활용한 동물 감염병 확산 차단)
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- Journal of Intelligence and Information Systems
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- v.24 no.4
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- pp.137-154
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- 2018
Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.
The Born approximation is widely used for solving the complex scattering problems in electromagnetics. Approximating total internal electric field by the background field is reasonable for small material contrasts as long as scatterer is not too large and the frequency is not too high. However in many geophysical applications, moderate and high conductivity contrasts cause both real and imaginary part of internal electric field to differ greatly from background. In the extended Born approximation, which can improve the accuracy of Born approximation dramatically, the total electric field in the integral over the scattering volume is approximated by the background electric field projected to a depolarization tensor. The finite difference and elements methods are usually used in EM scattering problems with a 2D model and a 3D source, due to their capability for simulating complex subsurface conductivity distributions. The price paid for a 3D source is that many wavenumber domain solutions and their inverse Fourier transform must be computed. In these differential equation methods, all the area including homogeneous region should be discretized, which increases the number of nodes and matrix size. Therefore, the differential equation methods need a lot of computing time and large memory. In this study, EM modeling program for a 2D model and a 3D source is developed, which is based on the extended Born approximation. The solution is very fast and stable. Using the program, crosshole EM responses with a vertical magnetic dipole source are obtained and the results are compared with those of 3D integral equation solutions. The agreement between the integral equation solution and extended Born approximation is remarkable within the entire frequency range, but degrades with the increase of conductivity contrast between anomalous body and background medium. The extended Born approximation is accurate in the case conductivity contrast is lower than 1:10. Therefore, the location and conductivity of the anomalous body can be estimated effectively by the extended Born approximation although the quantitative estimate of conductivity is difficult for the case conductivity contrast is too high.
This paper presents an algorithm to derive the representative unit hydrograph for the real environment of a watershed. For a given watershed, the conventional methods give several different unit hydrographs by storm events. In this study the LP model is somewhat modified based on the previous study by Mays et also as follows: the objective function is designed to minimize the sum of weighted residuals. An additional constraint of moving average is added to prevent the unit hydrograph from the occurence of oscillation which was not active in Mays's paper. Configuration of rainfall matrix was improved to reduce its dimension in accordance with Diskin's review point. In spite of the superiority of LP approach in terms of representativeness, all the methods were very sensitive to the validity of baseflow separation and rainfall-loss. Several methods of the separations for rainfall excesses and direct runoffs were applied and no preferred methods were identified. This is the matter of judgement considering catchment and rainfall characteristics. This algorithm was applied to a real watershed of the Wi stream in the Nak-dong river. Compared with the IHP results by conventional methods, this optimized representative unit hydrograph demonstrated relatively smaller and shorter values in terms of the peak discharge and the basin lag respectively, and the oscillation of its falling limb successfully eliminated owing to the additional constraints of moving averages.
The skin is an organ that has many important roles, including protection against infection, regulation of temperature and fluid loss, and sensory function. Injury to the skin, wound repair normally involves: (1) balanced activity of inflammation, (2) the re-epithelial phase and (3) the matrix formation of remodeling phase. Thus, skin wound healing is a finely controlled biological process involving a series of complex cellular interactions. Laser therapy is being implemented with increasing frequency in medicine. Low intensity laser is one that is capable of producing an energy density so low that any biologic alterations are the result of direct irradiation effect, not thermal events. This study was designed to evaluate the efficacy of low intensity laser therapy on skin wound healing in rabbits. A total of 10 male rabbits (New Zealand White Rabbit), age 8 weeks were used. Skin wound were surgically created dorso-lateral on the flank of 10 rabbits (2
The wound healing is very complex biological processing including inflammatory, reepithelialization and matrix construction. According to the biological systematic category, the ability of the healing is very different. Generally healing ability of the lower animal group has been known more excellent compared to its higher group. Therefore, lower animals have been used as the experimental model to explore the mechanism of the wound healing or repair. To verify histochemical characteristics of the wound healing, we have used skin of the frog (Bombina orientalis) as known common amphibian. At day 1, 10, and 16, the mucous substance was very actively synthesized and strong positive by PAS and Alcian blue (pH 2.5). Day 10 after wounding, margin of the wound was gradually strong positive by PTAH staining for detection of collagen synthesis. At 3 to 6 hour and day 23 to 27, we have found the cell division was active through the MG-P staining, in which the concentration and division of DNA in nucleus was green to deep blue color.
The theoretical study is developed for predicting the thermal expansion changes of composites which include complex inclusion, which is used three-dimensional ellipsoid model (
Color is an essential visual element that has a significant impact on the formation of a city's image and people's perceptions. Quantitative analysis of color in urban environments is a complex process that has been difficult to implement in the past. However, with recent rapid advances in Machine Learning, it has become possible to analyze city colors using photos shared by tourists. This study selected Dali City, a popular tourist destination in China, as a case study. Photos of Dali City shared by tourists were collected, and a method to measure large-scale city colors was explored by combining machine learning techniques. Specifically, the DeepLabv3+ model was first applied to perform a semantic segmentation of tourist sharing photos based on the ADE20k dataset, thereby separating artificial elements in the photos. Next, the K-means clustering algorithm was used to extract colors from the artificial elements in Dali City, and an adjacency matrix was constructed to analyze the correlations between the dominant colors. The research results indicate that the main color of the artificial elements in Dali City has the highest percentage of orange-grey. Furthermore, gray tones are often used in combination with other colors. The results indicated that local ethnic and Buddhist cultures influence the color characteristics of artificial elements in Dali City. This research provides a new method of color analysis, and the results not only help Dali City to shape an urban color image that meets the expectations of tourists but also provide reference materials for future urban color planning in Dali City.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
In order to determine the antigenic localization in the tissues of the adult Metagonimus yokegawai, immunogoldlabeling method was applied using serum immunoglobulins (IgG) of cats which were infected with isolated metacercariae from Plecoglossus altivelis. The sectioned worm tissue was embedded in Lowicryl HM 20 medium and stained with infected serum IgG and protein A gold complex (particle size: 12 nm) , It was observed by electron microscopy at each tissue of the worm. The gold particles were observed on the tegumental syncytium as well as cytoplasm of tegumental cells and epithelial lamella of the caecum. The gold particles were not observed on the basal lamina of the tegument, interstitial matrix of the parenchyma, the muscle tissue and mitochondria of the tegument. The gold particles were specifically labeled in the secretory granules in the vitelline cells. They were also labeled on the lumen of bladder and egg shell. The above findings showed that antigenic materials in the tissue of adult worms were specifically concentrated on the tegumental syncytium as well as cytoplasm of tegumental cells and epithelial lamella of the caecum.