• Archives of Plastic Surgery
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• v.41 no.6
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• pp.679-685
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• 2014

Background Frontal sinus fractures, particularly anterior sinus fractures, are relatively common facial fractures. Many agree on the general principles of frontal fracture management; however, the optimal methods of reduction are still controversial. In this article, we suggest a simple reduction method using a subbrow incision as a treatment for isolated anterior sinus fractures. Methods Between March 2011 and March 2014, 13 patients with isolated frontal sinus fractures were treated by open reduction and internal fixation through a subbrow incision. The subbrow incision line was designed to be precisely at the lower margin of the brow in order to obtain an inconspicuous scar. A periosteal incision was made at 3 mm above the superior orbital rim. The fracture site of the frontal bone was reduced, and bone fixation was performed using an absorbable plate and screws. Results Contour deformities were completely restored in all patients, and all patients were satisfied with the results. Scars were barely visible in the long-term follow-up. No complications related to the procedure, such as infection, uncontrolled sinus bleeding, hematoma, paresthesia, mucocele, or posterior wall and brain injury were observed. Conclusions The subbrow approach allowed for an accurate reduction and internal fixation of the fractures in the anterior table of the frontal sinus by providing a direct visualization of the fracture. Considering the surgical success of the reduction and the rigid fixation, patient satisfaction, and aesthetic problems, this transcutaneous approach through a subbrow incision is concluded to be superior to the other reduction techniques used in the case of an anterior table frontal sinus fracture.

• Journal of the Korean Society of Food Science and Nutrition
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• v.14 no.1
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• pp.1-12
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• 1985

In an attempt todetermine the optimum heat treatment, the changes in TIS content and in vitro protein digestibility of squid, shrimp, oysterand pollock under various heating conditions were studied. The effect of drying method and cold storage on the in vitro digestibility and TIS content were also studied. Optimal boiling conditions were 1 min, for squid, 0.5min. for oyster(eviscerated), 1 min. for whole oyster, and 5 min. for pollock. Steaming times that yieled products with the highest in vitro digestibility value were: 1 min. at $100^{\circ}C$ for squid, 1 min, at $88^{\circ}C$ for oyster and $1{\sim}2.5min$. at $100^{\circ}C$ for pollock. All of freeze dried samples showed the highest in vitro digestibility value and sundried one were comparble to freeze dried samples except high fat level or noneviscerated samples. Fat content was the nain inhivbitory factor of the seafood enzymic digestion during processing and storage. The multi-enzyme assay, used to predict the quality change of dried seafoods stored in a cold room for long periods of raw seafoods treated with various heating methods, offers many advantages over the convetional methods of determining protein quality.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1244-1244
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from mastitic and healthy cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from mastitic and healthy cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA and FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference, thereby providing a useful means for spectroscopy-based clinic applications.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1042-1042
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from daily monitoring of two Japanese cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from two cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA md FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.305-313
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• 2019

Recently, spatial information is being constructed actively based on the images obtained by drones. Because occlusion areas occur due to buildings as well as many obstacles, such as trees, pedestrians, and banners in the urban areas, an efficient way to resolve the problem is necessary. Instead of the traditional way, which replaces the occlusion area with other images obtained at different positions, various models based on deep learning were examined and compared. A comparison of a type of feature descriptor, HOG, to the machine learning-based SVM, deep learning-based DNN, CNN, and RNN showed that the CNN is used broadly to detect and classify objects. Until now, many studies have focused on the development and application of models so that it is impossible to select an optimal model. On the other hand, the upgrade of a deep learning-based detection and classification technique is expected because many researchers have attempted to upgrade the accuracy of the model as well as reduce the computation time. In that case, the procedures for generating spatial information will be changed to detect the occlusion area and replace it with simulated images automatically, and the efficiency of time, cost, and workforce will also be improved.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.3
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• pp.223-229
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• 2015

Surface modification is a technology to form a new surface layer and overcome the intrinsic properties of the base material by applying thermal energy or stress onto the surface of the material. The purpose of this technique is to achieve anti-corrosion, beautiful appearance, wear resistance, insulation and conductance for base materials. Surface modification techniques may include plating, chemical conversion treatment, painting, lining and surface hardening. Among which, a surface modification process using electrolytes has been investigated for a long time in connection with research on its industrial application. The technology is highly favoured by various fields because it provides not only high productivity and cost reduction opportunities, but also application availability for components with complex geometry. In this study, an electrochemical experiment was performed on the surface of 5083-O Al alloy to determine an optimal electrolyte temperature, which produces surface with excellent corrosion resistance under marine environment than the initial surface. The experiment result, the modified surface presented a significantly lower corrosion current density with increasing electrolyte temperature, except for $5^{\circ}C$ of electrolyte temperature at which premature pores was created.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.1
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• pp.54-58
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• 2007

Purpose: Luciferase is one of the most commonly used reporter enzymes in the field of in vivo optical imaging. D-luciferin, the substrate for firefly luciferase has very high cost that allows this kind of experiment limited to small animals such as mice and rats. In this current study, we validated local injection of D-luciferin in the articular capsule for bioluminescence imaging in rabbits. Materials and Methods: Chondrocytes were cultured and infected by replication-defective adenoviral vector encoding firefly luciferase (Fluc). Chondrocytes expressing Fluc were injected or implanted in the left knee joint. The rabbits underwent optical imaging studies after local injection of D-luciferin at 1, 5, 7, 9 days after cellular administration. We sought whether optimal imaging signals was could be by a cooled CCD camera after local injection of D-luciferin. Results: Imaging signal was not observed from the left knee joint after intraperitoneal injection of D-luciferin (15 mg/kg), whereas it was observed after intraarticular injection. Photon intensity from the left knee joint of rabbits was compared between cell injected and implanted groups after intraarticular injection of D-luciferin. During the period of imaging studies, photon intensity of the cell implanted group was 5-10 times higher than that of the cell injected group. Conclusion: We successfully imaged chondrocytes expressing Fluc after intraarticular injection of D-luciferin. This technique may be further applied to develop new drugs for knee joint disease.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.129-147
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• 2002

This paper presents a variational equality formulation by Providing new dynamic route choice condition for a link-based dynamic traffic assignment model. The concepts of used paths, used links, used departure times are employed to derive a new link-based dynamic route choice condition. The route choice condition is formulated as a time-dependent variational equality problem and necessity and sufficiency conditions are provided to prove equivalence of the variational equality model. A solution algorithm is proposed based on physical network approach and diagonalization technique. An asymmetric network computational study shows that ideal dynamic-user optimal route condition is satisfied when the length of each time interval is shortened. The I-394 corridor study shows that more than 93% of computational speed improved compared to conventional variational inequality approach, and furthermore as the larger network size, the more computational performance can be expected. This paper concludes that the variational equality could be a promising approach for real-time application of a dynamic traffic assignment model based on fast computational performance.

• Magazine of the Korean Society of Agricultural Engineers
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• v.29 no.3
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• pp.125-137
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• 1987

The purpose of this paper is to examine some difficulties in water management of agricultural reservoirs in Korea, for there are approximately more than 15,000 reservoirs which are now being utilized for the purpose of irrigation, along with the much amount of expenses and labors to be invested against droughts and floods periodically occurred. Recently, the effective use of water resources in the agricultural reservoirs with a single purpose, is becomming multiple according to the alterable environment of water use. Therefore, the task to allocate agricultural water rationally and economically must be solved for the multiple use of agricultural reservoirs. On the basis of the above statement, this study aims at suggesting the rational method of water management by introducing an optimal technique to allocate the water in an existing agricultural reservoir rationally, for the sake of maximizing the economic effect. To achieve this objective, a reservoir, called "0-Bongje" as a sample of the case study, is selected for an agricultural water development proiect of medium scale. As a model for the optimum allocation of water in the multi-purpose use of reservoirs a linear programming model is developed and analyzed. As a result, findings of the study are as follows : First, a linear programing model is developed for the optimum allocation of water in the multi-purpose use of agricultural reservoirs. By adopting the model in the case of reservoir called "O-Bongje," the optimum solution for such various objects as irrigation area, the amount of domestic water supply, the size of power generation, and the size of reservoir storage, etc., can be obtained. Second, by comparing the net benefits in each object under the changing condition of inflow into the reservoir, the factors which can most affect the yearly total net benefit can be drawn, and they are in the order of the amount of domestic water supply, irrigation area, and power generation. Third, the sensitivity analysis for the decision variable of irrigation which may have a first priority among the objects indicate that the effective method of water management can be rapidly suggested in accordance with a condition under the decreasing area of irrigation. Fourth, in the case of decision making on the water allocation policy in an existing multi-purpose reservoir, the rapid comparison of numerous alternatives can be possible by adopting the linear programming model. Besides, as the resources can be analyed in connection with various activities, it can be concluded that the linear programing model developed in this study is more quantitative than the traditional methods of analysis. Fifth, all the possible constraint equations, in using a linear programming model for adopting a water allocation problem in the agricultural reservoirs, are presented, and the method of analysis is also suggested in this study. Finally, as the linear programming model in this study is found comprehensive, the model can be adopted in any different kind of conditions of agricultural reservoirs for the purpose of analyzing optimum water allocation, if the economic and technical coefficients are known, and the decision variable is changed in accordance with the changing condition of irrigation area.

• Korean Journal of Environmental Agriculture
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• v.32 no.2
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• pp.102-107
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• 2013

BACKGROUND: Pithy pear fruit are not distinguished externally from sound fruit and thus often cause unexpected economic losses. To find out the cause of pithiness, the pithiness incidence and characteristics of Japanese pear (Pyrus pyrifolia cv. Niitaka) fruit picked from a spot frequently produced pithy fruit in an orchard were compared with those of fruit picked from another spot produced sound fruit every year. And the soil chemical properties of the two spots and mineral contents in fruit, shoots, and leaves of Japanese pear trees cultivated in the two spots were also examined. METHODS AND RESULTS: The pithiness incidence was 0, 8.8, and 11.3% at 7 days before and 0 and 7 days after optimal harvest date, respectively, in the spot frequently produced pithy fruit. Flesh firmness was significantly lower in pithy fruit than in sound fruit, while soluble solids content was slightly higher in pithy fruit than in sound fruit. Unlike other mineral contents, Ca content was significantly lower in pithy fruit than in sound fruit. These results indicate that Ca deficiency in fruit is closely associated with decrease in flesh firmness and thus pithiness development. Ca content in soil of the spot frequently produced pithy fruit was also significantly lower than that in soil of the spot produced sound fruit. However, shoots or leaves did not exhibit significant difference in Ca and/or other mineral contents between the two spots, indicating that Ca deficiency in fruit is dependent on the translocation of Ca within a plant rather than soil Ca status. Although total-N, available $P_2O_5$, K, and Ca contents were significantly lower in soil of the spot frequently produced pithy fruit than in soil of the spot produced sound fruit, Mg and Na contents and pH were not different between the soil conditions. CONCLUSION(S): Fruit maturity and Ca level in fruit are closely related to the incidence of pithiness in 'Niitaka' Japanese pear.