• Food Science of Animal Resources
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• v.38 no.5
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• pp.889-900
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• 2018

Characterization and utilization of the bioactive compounds from natural resources is one of the most concerns to maintain quality properties of foods, especially to prevent the oxidation of lipids in meat products. Phytochemical components and antioxidant activities of Cudrania tricuspidata (CT) leaves extracted using various solvents and their effects on physicochemical properties of pork patties during refrigerated storage were measured. The combined solvents of 80% ethanol, 80% methanol and pure double-distilled (dd)-water obtained the higher total phenolic compounds, flavonoids content, and antioxidant activities as compared to the pure solvent alone. Among the individual antioxidant components, catechin was the predominant polyphenol in CT leaves in all extracts. The addition of CT leaves extracts into pork patties showed high antioxidant activities since thiobarbituric acid-reactive substances (TBARS) values of added CT extracts were lower than those of the control (p<0.05). In conclusion, CT leaf phytochemical components displayed antioxidant activity that varied with the extract solvent used. CT extracts were superior to control in retarding lipid oxidation of pork patties, which was evident as reduced TBARS and peroxide values (POV).

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1251-1258
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• 2019

Intelligent tutoring system enables users to effectively learn by utilizing various artificial intelligence techniques. For instance, it can recommend a proper curriculum or learning method to individual users based on their learning history. To do this effectively, user's characteristics need to be analyzed and classified based on various aspects such as interest, learning ability, and personality. Even though data labeled by the characteristics are required for more accurate classification, it is not easy to acquire enough amount of labeled data due to the labeling cost. On the other hand, unlabeled data should not need labeling process to make a large number of unlabeled data be collected and utilized. In this paper, we propose a semi-supervised learning method based on feedback variational auto-encoder(FVAE), which uses both labeled data and unlabeled data. FVAE is a variation of variational auto-encoder(VAE), where a multi-layer perceptron is added for giving feedback. Using unlabeled data, we train FVAE and fetch the encoder of FVAE. And then, we extract features from labeled data by using the encoder and train classifiers with the extracted features. In the experiments, we proved that FVAE-based semi-supervised learning was superior to VAE-based method in terms with accuracy and F1 score.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.462-466
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• 2005

The extraction and recognition of shipping container's identifier is difficult since the scale or the location of identifiers are not fixed-form and input images have some external noises. In this paper, based on these facts, first, edges are detected from input images using canny masking, and regions of container's Identifiers are extracted by applying horizontal and vertical histogram method to canny masked images. We use a fuzzy thresholding method to binaries the extracted container's identifier regions, and contour tracking algorithm to extract individual identifiers. In experimental results, we confirmed that the proposed method is superior In performance.

• Water Engineering Research
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• v.5 no.2
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• pp.101-109
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• 2004

Aggregating information by combining forecasts from two or more forecasting methods is an alternative to using forecasts from just a single method to improve forecast accuracy. This paper describes the development and use of a monthly inflow forecast model based on an optimal linear combination (OLC) of forecasts derived from naive, persistence, and Ensemble Streamflow Prediction (ESP) forecasts. Using the cross-validation technique, the OLC model made 1-month ahead probabilistic forecasts for the Chungju multi-purpose dam inflows for 15 years. For most of the verification months, the skill associated with the OLC forecast was superior to those drawn from the individual forecast techniques. Therefore this study demonstrates that OLC can improve the accuracy of the ESP forecast, especially during the dry season. This study also examined the value of the OLC forecasts in reservoir operations. Stochastic Dynamic Programming (SDP) derived the optimal operating policy for the Chungju multi-purpose dam operation and the derived policy was simulated using the 15-year observed inflows. The simulation results showed the SDP model that updated its probability from the new OLC forecast provided more efficient operation decisions than the conventional SDP model.

• The Research Journal of the Costume Culture
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• v.12 no.6 s.53
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• pp.945-952
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• 2004

Shrink-resist effects and properties of the knitted fabrics from wool/acrylic(W/A) fiber blends were determined to find out an optimal blending ratio keeping the quality properties of wool products. The test fabrics were knitted by a weft knitting machine with all needle knitting structure ($0{\times}0$ rib) under the same knitting conditions with five different types of yarns: $W100\%,\;A100\%$, and W/A blended yarns(70/30, 50/50, 30/70). Shrinkage during repeated washing, electrostatic propensity, thermal resistance and pilling propensity of W/A knits. The shrink resistance was significantly enhanced on repeated washing of W/A knits, especially, over $50\%$ acrylic blended knits. Addition of strong physical force and alkali detergent applied in this washing experiment brought about superior effects with the low shrinkage rate although it was very severe washing conditions for wool fabrics. The results from the washing experiment implies that W/A blend knits can be machine washed at individual households with other ordinary laundry. There was some changes and variation found in thermal resistance, electrostatic propensity, and pilling. W/A 50/50 blended knits did not bring serious changes to other physical properties comparing with original wool, which helps consumers care wool knitted clothes more conveniently.

• The KSFM Journal of Fluid Machinery
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• v.6 no.3 s.20
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• pp.28-35
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• 2003

This paper presents analysis results for the effect of power control strategies on the part load performance of gas turbine based power generation systems utilizing exhaust heat of the gas turbine such as combined cycle power plants and regenerative gas turbines. For the combined cycle, part load efficiency variations were compared among different single shaft gas turbines representing various technology levels. Power control strategies considered were fuel only control and IGV control. It has been observed that gas turbines with higher design performances exhibit superior part load performances. Improvement of part load efficiency of the combined cycle by adopting air flow modulation was analyzed and it was concluded that since the average combined cycle performance is affected by the range of IGV control as well as its temperature control principle, a control strategy appropriate for the load characteristics of the individual plant should be adopted. For the regenerative gas turbine, it is likewise concluded that maintaining exhaust temperature as high as possible by air flow rate modulation is required to increase part load efficiency.

• Journal of Ecology and Environment
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• v.33 no.2
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• pp.105-114
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• 2010

The principal objective of this study was to characterize the relationships between geographical conditions (e.g., island area, distance to mainland) and landscape structures of uninhabited islands, and to evaluate the effects of islands and their landscape structures on species richness. One hundred randomly selected islands and 5,000 m buffered areas derived from the boundaries of each island were used to summarize the number of observed bird species, and landscape pattern indices, particularly patch density, edge density, shape index, and mean nearest neighboring distance. Spatial arrangements of individual patch type at the class level, which are markedly affected by the distance from an island to the mainland, have a superior ability to explain the variances in species richness, as compared to the geographical conditions and landscape pattern indices at the landscape level. The results demonstrate that the patch type landscape structure is the primary factor affecting species richness, as well as the distance to the mainland. In particular, landscape pattern indices of cropland/pasture and woody cover are statistically significant in terms of explaining species richness, which suggests that food resources and appropriate conditions in landscape structures of habitat types are assumed as important elements in attracting bird species. This study also proposes the importance of evaluation on the landscape structure of each island, in order to designate protected areas and to establish a management plan for species conservation in uninhabited islands.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.53-58
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• 2002

In the construction of successful fuzzy models for nonlinear systems, the identification of an optimal fuzzy model system is an important and difficult problem. Traditionally, sGA(simple genetic algorithm) has been used to identify structures and parameters of fuzzy model because it has the ability to search the optimal solution somewhat globally. But SGA optimization process may be the reason of the premature local convergence when the appearance of the superior individual at the population evolution. Therefore, in this paper we propose a new method that can yield a successful fuzzy model using VmGA(virus messy genetic algorithms). The proposed method not only can be the countermeasure of premature convergence through the local information changed in population, but also has more effective and adaptive structure with respect to using changeable length string. In order to demonstrate the superiority and generality of the fuzzy modeling using VmGA, we finally applied the proposed fuzzy modeling methodof a complex nonlinear system.

• Archives of Plastic Surgery
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• v.45 no.4
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• pp.363-366
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• 2018

Background Camptodactyly refers to permanent flexion contracture at the proximal interphalangeal joint. Most cases are limited to fifth-finger involvement. Although common, the treatment of camptodactyly is controversial. Many published studies have emphasized conservative treatment, while others have described surgical procedures. The problem with this deformity is that it presents in several forms, which means that there is no single model for effective treatment. The aim of this paper is to present the difficulties encountered with this condition and the management thereof on an individual basis. Methods This is a case series of 14 patients (nine males, five females) who underwent surgical treatment. The results were classified using the method from Mayo Clinic as excellent, good, fair, and poor. Results Fourteen patients with 15 fingers underwent surgery, and the results achieved were as follows: excellent, 0; good, 1; fair, 6; poor, 8. The treatment of camptodactyly still remains controversial, and hence proper planning individualized to each patient is needed to achieve the maximal improvement with realistic goals. Conclusions Although we performed individualised surgery, our careful follow-up was not able to identify any method as superior over another with respect to gain in extension and loss of flexion. We therefore propose that the extensor mechanism should not be disturbed during surgery to treat camptodactyly cases.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.3
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• pp.52-58
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• 2002

The purpose of condition monitoring and fault diagnosis is to detect faults occurring in machinery in order to improve the level of safety in plants and reduce operational and maintenance costs. The recognition performance is important not only to gain a high recognition rate bur a1so to minimize the diagnosis failures error rate by using off effective rejection module. We examined the problem of performance evaluation for the rejection scheme considering the accuracy of individual c1asses in order to increase the recognition performance. We use the Smith's method among the previous studies related to rejection method. Nearest neighbor classifier is used for classifying the machine conditions from the vibration signals. The experiment results for the performance evaluation of rejection show the modified optimum rejection method is superior to others.