• Journal of the Korean Wood Science and Technology
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• v.46 no.5
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• pp.610-621
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• 2018

In conservation treatment lacquer has been used variously as a restoration material. However, dealing with Lacquer is very difficult as it dried in high humidity that can be harmful to the base materials. Also being natural varnish, dried lacquer layer is very different from the drying condition and the quality of the lacquer. These make difficult to predict the result of drying lacquer. In this study, using the humidity control machine, firstly, the main contents of the two different type of lacquer was experimented. And these lacquers was cured in various conditions. The duration time was checked until totally hardened. After that, obtained lacquer layers was analyzed to understand optical properties. Therefore, this study made a result about the relationship between characteristics of lacquer layer and the hardening condition. As a result, duration time of the Korean lacquer drying which has average 13.4% more urushiol than the Chinese lacquer is recorded a twice or triple decrease over it of the Chinese one. And, in all types of lacquer, the higher humidity makes the faster a pace of lacquer dried. In same lacquer, the shorter the duration time of drying lacquer is much darker and glossier. However, gloss deteriorated in saturated humidity. In humidity lower than RH 70%, lacquer is not hardened in 336 hours. When the layer totally cured through long period more than 30 days, the drying lacquer is appeared high brightness and almost transparent. Thus, in lower than RH 70%, it is hard to obtain durable layer.

• The Korean Journal of Food And Nutrition
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• v.17 no.1
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• pp.1-7
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• 2004

Yoghurt base was prepared from skim milk added with 0.25∼2.0%(w/v) of chlorella extract powder and fermented with lactic acid bacteria(Streptococcus thermophilus : Lactobacillus casei = 1:1) at 37$^{\circ}C$ for 24 hours. Quality characteristics of the yoghurts were evaluated in terms of acid production, number of viable cell, color, texture property, and sensory property during lactic acid fermentation. The addition of 0.25% chlorella extract powder stimulated the growth of lactic acid bacteria which showed the highest number of viable cell counts(l.46${\times}$10$\^$8/ CFU/mL) after 12 hours incubation, and also enhanced the acid production which was pH 4.33 after 12 hours incubation. The L values(brightness) of the yoghurts containing chlorella extract powder were lower than control group, whereas the b values(yellowness) were higher. The hardness and gumminess of the yoghurt added with 0.25% chlorella extract powder were higher than others. Sensory scores of the yoghurt added with 0.25% chlorella extract powder were significantly higher than other groups in color, chlorella odor, sweet taste, chlorella taste, mouth feel, aftertaste and overall acceptability.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.449-457
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• 2016

At this study, we select five colorful and high-acid fruits: grape, lemon, orange, grapefruit and kiwi, and we made a composite resin specimen and dipped into fruit juice in order to figure out influence that affects on surface corrosion and coloring. We dipped resin specimen into fruit juice by three-day and seven-day interval at $37^{\circ}C$. Control group used the resin that was not dipped into fruit juice. For surface change according to the time, it was observed by using scanning electron microscopy, and it was measured by using spectrophotometer for change of coloring degree. As a result of surface change of resin by using scanning electron microscopy, furrow size between surface particles increased, and rectangular rod-shape structure was emerged, and small prominent particles on bumps disappeared. As a result of coloring degree of resin by measuring spectrophotometer, a difference between experimental group appears with the darkest brightness in the case where it is dipped into grape extracts.

• Food Science and Preservation
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• v.15 no.4
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• pp.505-511
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• 2008

Recipes for cookies and muffins made with soybean paste and sun-dried salt were established and characteristics of the foods were investigated. On Hunter's color scale, 'L' values decreased and brightness was lowered as additive levels increased, whereas the 'a' value(redness) increased and the 'b' value(yellowness) decreased. The hardness of a control muffin was 1843 g and this increased as additive levels rose. Cookies showed the same tendency. Elasticity was not proportional to paste content whereas crispness increased as additive levels increased. Sensory evaluations of cookies and muffins with different soybean paste contents(0-8%, w/v) showed that additive at 1% (w/v) was best and additive at 8%(w/v) was unacceptable. All products scored poorly 48 h after preparation; freshness needs to be investigated further.

• Cartoon and Animation Studies
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• s.39
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• pp.393-412
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• 2015

See and feel the emotion recognition is the image of a person variously changed according to the environment, personal disposition. Thus, the image recognition has been focused on the emotional sensibilities computer you want to control the number studies. However, existing emotional computing model is numbered and the objective is clearly insufficient measurement conditions. Thus, through quantifiable image Emotion Recognition and emotion computing, is a study of the situation requires an objective assessment scheme. In this paper, the sensitivity was represented by numbered sizes quantified according to the image recognition calculation emotion. So apply the principal attributes of the color image emotion recognition as a configuration parameter. In addition, in calculating the color sensitivity by applying a digital computing focused research. Image color emotion computing research approach is the color of emotion attribute, brightness, and saturation reflects the weighted according to importance to the emotional scores. And free-degree by applying the sensitivity point to the image sensitivity formula (X), the tone (Y-axis) is calculated as a number system. There pleasure degree (X-axis), the tension and position the position of the image point that the sensitivity of the emotional coordinate crossing (Y-axis). Image color coordinates by applying the core emotional effect of Russell (Core Affect) is based on the 16 main representatives emotion. Thus, the image recognition sensitivity and compares the number size. Depending on the magnitude of the sensitivity scores demonstrate this sensitivity must change. Compare the way the images are divided up the top five of emotion recognition emotion emotions associated with 16 representatives, and representatives analyzed the concentrated emotion sizes. Future studies are needed emotional computing method of calculation to be more similar sensibility and human emotion recognition.

• Journal of the Korean Wood Science and Technology
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• v.37 no.6
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• pp.566-577
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• 2009

The modification of wood color occurs rapidly during the service period at indoor. It is crucial to investigate the characteristics of color change, chemical and microscopical modification of wood at indoor. Wood products made of Japanese cedar at different years were used for this work. The tests were performed in order to evaluate the degree of color change of wood surface, breakpoint of brightness from surface to inside of wood, chemical analysis with FT-IR, and microscopical characteristics using the LM and TEM. Surface color of cedar wood stored indoor were rapidly changed at early stage, particularly ${\Delta}a$ (yellow), and ${\Delta}b$ (red) values were steeply decreased for one year old indoor wood, ${\Delta}L$ (white) value was dropped until 5 years old indoor wood compared with control sample. Decrease of peaks related to polysaccharide and lignin was noticed, especially, lignin was severely degraded. Although degradation of cell wall limited only to surface layers of indoor wood, degradation pattern of indoor wood showed similar degradation pattern to natural weathering of wood during outdoor weathering or wood behavior under artificial UV irradiation.

• Korean Journal of Food Science and Technology
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• v.34 no.3
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• pp.419-424
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• 2002

Characteristics of curd yogurt containing maesil extract and flesh, and mixed cultures of lactic acid bacteria (Streptococcus thermophilus, Lactobacillus acidophilus, and L. casei) were investigated redundant. The results of sensory evaluation of curd yogurts containing maseil indicated that color, odor, taste, flesh amount, aftertaste, and overall acceptability of the 3% maesil extract crud yogurt added with 20% maesil flesh showed higher preference than others. The contents of free fatty acid and citric acid of curd yogurts added with 3% maesil extract were higher than the specify sample. The Hunter L (brightness) value of curd yogurt added with 3% maesil extract was not significantly different from the control curd yogurt, while the Hunter a (redness) and Hunter b (yellowness) values were higher. The hardness, adhesiveness, and gumminess of 3% maesil extract curd yogurts added with 20% maesil flesh were higher than others.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1181-1194
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• 2018

This study suggests a novel approach of estimating stream flow discharge using the Synthetic Aperture Radar (SAR) images taken from 2015 to 2017 by European Space Agency Sentinel-1 satellite. Fifteen small to medium sized rivers in the Han River basin were selected as study area, and the SAR satellite images and flow data from water level and flow observation system operated by the Korea Institute of Hydrological Survey were used for model construction. First, we apply the histogram matching technique to 12 SAR images that have undergone various preprocessing processes for error correction to make the brightness distribution of the images the same. Then, the flow estimation model was constructed by deriving the relationship between the area of the stream water body extracted using the threshold classification method and the in-situ flow data. As a result, we could construct a power function type flow estimation model at the fourteen study areas except for one station. The minimum, the mean, and the maximum coefficient of determination ($R^2$) of the models of at fourteen study areas were 0.30, 0.80, and 0.99, respectively.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.77-86
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• 2023

Ship detection is widely used in areas such as maritime security, maritime traffic, fisheries management, illegal fishing, and border control, and ship detection is important for rapid response and damage minimization as ship accident rates increase due to recent increases in international maritime traffic. Currently, according to a number of global and national regulations, ships must be equipped with automatic identification system (AIS), which provide information such as the location and speed of the ship periodically at regular intervals. However, most small vessels (less than 300 tons) are not obligated to install the transponder and may not be transmitted intentionally or accidentally. There is even a case of misuse of the ship'slocation information. Therefore, in this study, ship detection was performed using high-resolution optical satellite images that can periodically remotely detect a wide range and detectsmallships. However, optical images can cause false-alarm due to noise on the surface of the sea, such as waves, or factors indicating ship-like brightness, such as clouds and wakes. So, it is important to remove these factors to improve the accuracy of ship detection. In this study, false alarm wasreduced, and the accuracy ofship detection wasimproved by removing wake.As a ship detection method, ship detection was performed using machine learning-based random forest (RF), and convolutional neural network (CNN) techniquesthat have been widely used in object detection fieldsrecently, and ship detection results by the model were compared and analyzed. In addition, in this study, the results of RF and CNN were combined to improve the phenomenon of ship disconnection and the phenomenon of small detection. The ship detection results of thisstudy are significant in that they improved the limitations of each model while maintaining accuracy. In addition, if satellite images with improved spatial resolution are utilized in the future, it is expected that ship and wake simultaneous detection with higher accuracy will be performed.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.29-40
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• 2022

In this paper, we studied a system that detects and analyzes the pathological features of diabetic retinopathy using Mask R-CNN and a Random Forest classifier. Those are one of the deep learning techniques and automatically diagnoses diabetic retinopathy. Diabetic retinopathy can be diagnosed through fundus images taken with special equipment. Brightness, color tone, and contrast may vary depending on the device. Research and development of an automatic diagnosis system using artificial intelligence to help ophthalmologists make medical judgments possible. This system detects pathological features such as microvascular perfusion and retinal hemorrhage using the Mask R-CNN technique. It also diagnoses normal and abnormal conditions of the eye by using a Random Forest classifier after pre-processing. In order to improve the detection performance of the Mask R-CNN algorithm, image augmentation was performed and learning procedure was conducted. Dice similarity coefficients and mean accuracy were used as evaluation indicators to measure detection accuracy. The Faster R-CNN method was used as a control group, and the detection performance of the Mask R-CNN method through this study showed an average of 90% accuracy through Dice coefficients. In the case of mean accuracy it showed 91% accuracy. When diabetic retinopathy was diagnosed by learning a Random Forest classifier based on the detected pathological symptoms, the accuracy was 99%.