• Journal of agriculture & life science
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• v.45 no.6
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• pp.95-108
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• 2011

The food quality characterization and safety Japanese flying fish roe (JFF-R), capelin roe (C-R), Pacific herring roe (PH-R) were investigated. The size of JFF-R was 1.48-1.93 mm, which was longer than those of C-R and PH-R. The moisture content of JFF-R imported from Peru (JFF-R-P) was 70.3%, which was higher than that of JFF-R imported from China (JFF-R-C) (67.4%), while was lower than that of JFF-R imported from Indonesia (JFF-R-I) (83.3%). However, the salinity of JFF-R-P was 13.6%, which was lower than that of JFF-R-C, while was higher that of JFF-R-I (1.8%). The moisture contents and salinities of the other fish roes were 80.4% and 3.2%, respectively, for capalin roe, and 65.4% and 20.0%, respectively, for Pacific herring roe. According to the results of pH, volatile basic nitrogen content, heavy metal content, viable cell count and coliform group, the fish roes could be used as sanitary sources for preparation of seasoned JFF-R. The major fatty acids of fish roes were 16:0 (27.8-30.5%), 18:1n-9 (7.2-8.0%), 20:5n-3 (5.6-8.2%) and 22:6n-3 (22.0-25.6%) in JFF-R, and 16:1n-7 (6.7-9.3%) as well as these fatty acids in C-R and PH-R. Total amino acid contents of fish roes ranged from 9.44 g/100 g to 10.39 g/100 g and their major amino acids were aspartic acid, glutamic acid, leucine and lysine. The mineral content of JFF-R were higher than those of the other fish roes expected for zinc of JFF-R-I. According to the results of sensory evaluation, the color and texture of JFF-R-P were superior to those of the other fish roes. No difference was, however, found in flavor, among JFF-R-P and the other fish roes.

• Food Science and Preservation
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• v.24 no.3
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• pp.464-471
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• 2017

The purpose of this study was to evaluate the effect of superheated steam drying on physicochemical and microbial characteristics of Korean traditional actinidia (Actinidia arguta) leaves. Actinidia leaves were dried at steam temperature of $350^{\circ}C$ and oven temperature of $150^{\circ}C$ for 40-200 sec. Moisture content and water activity decreased with increasing the drying time, while color values including L, a, and b values and total color difference (${\Delta}E$) increased as drying time increased. The relationship between moisture content and water activity showed an exponential fit with high correlation vlaue ($R^2=0.9909$). Total phenolics and flavonoids content and antioxidant activity such as DPPH radical scavenging activity, ABTS radical scavenging activity, and FRAP assay of dried actinidia leaves increased with increasing the drying time up to 160 sec, but dramatically decreased at drying of 200 sec. The numbers of total areobic bacteria of leaves was not detected at drying time over 120 sec and coliform of all the samples was not detected. As a results, the superheated steam was an very effective drying method of increase to the nutritional and sanitary quality of dried Korean traditional actinidia leaves.

• ANNALS OF ANIMAL RESOURCE SCIENCES
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• v.29 no.4
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• pp.172-182
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• 2018

The present study was undertaken to examine if the carcass and pork quality of finishing pigs reared on a low plane of nutrition (LPN) could be improved compared with that of the pigs finished on a high plane of nutrition (HPN). Sixty-eight crossbred (LYD) barrows and 68 LYD gilts weighing approximately 50 kg were fed a diet containing 3.54 Mcal DE/kg with 1.00% lysine (HPN) or 3.02 Mcal DE/kg with 0.68% lysine (LPN) in eight pens up to approximately 120 kg and slaughtered. The belly, loin, ham, and Boston butt were cut out from a total of 20 carcasses, after which physicochemical and sensory quality attributes of the belly and the representative muscle of each of the loin, ham, and Boston butt were evaluated. The ADG, gain:feed ratio, and backfat thickness were less for LPN than for HPN (p<0.05). The cooking loss, hardness, and chewiness values for the Boston butt were less for LPN vs. HPN. In sensory evaluation for fresh meat (muscle), the subjective quality scores were greater for LPN vs. HPN in color, marbling, and acceptability for the loin, the muscle:fat balance score for the belly tending to be greater for LPN (p<0.10). In addition, LPN was superior to HPN in the flavor and juiciness in sensory evaluation for cooked ham. In conclusion, the present results suggest that the carcass and pork quality of finishing pigs could be improved with reduced growth performance by using LPN.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.23-31
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• 2020

This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.32 no.2
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• pp.224-233
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• 1987

Most of the japonica rice varieties preferred for high eating quality are liable to lodging even under moderate rate of nitrogen application. This lodging liability has been a critical limit even for proper evaluation of physio-logical characteristics of those varieties exhibitable under higher nitrogen levels. Use of recent inhibitors of gibberellin biosynthesis such as ‘Pac1obutrazol’ may allow us to overcome this barrier. The responses of four high eating quality varieties to nitrogen application to the level of 150kg N per ha were evaluated with and without use of Paclobutrazol in comparison with a non-lodging, improved short japonica, Dongjin and a non-lodging, high yielding indica x japonica Milyang 23. The four were Damageum (the best eating quality in the 1930s), Nongrim 6 (the best in the 1960s), Chuchung (the best since 1970s), Koshihikari (the best in Japan since 1960s). As expected increased application of nitrogen increased plant height, length of the 3rd internode, and lodg-ing liability, being measured as culm breaking load, in all varieties tested and caused actual lodging in the fiel from the 50kg Nfha level in Damageum and Koshihikari and at the level of l50kg Nfha in Nongrim 6. Applica-tion of Pac1obutrazol (0.6%G) 15 days before heading reduced plant height, length of the 3rd internode and lodging liability being measured as culm breaking load in all varieties tested. However, the application of Pac1obutrazol during active tillering stage resulted in decreased culm breaking load in Damageum, Nongrim 6, and Koshihikari in spite of the decreased plant height and culm length as in the other varieties. Maximum yield was obtained with 100kg Nand 30kg Pac1obutrazol at 15 days before heading in Nongrim 6, 150kg N and 30kg Pac1obutrazol at 15 days before heading in Damageum, and 150kg N and 20kg Paclobutrazol at 20 days after transplanting plus 30kg Paclobutrazol at 15 days before heading in the variety Koshinhikari and Chuchung. Under a sensory evaluation of cooked rice, the four high eating quality varieties were not different in rank and Paclobutrazol treated rice was not distinguished from the untreated in eating quality.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.9-18
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• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.

• Korean journal of food and cookery science
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• v.25 no.4
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• pp.488-495
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• 2009

Pork cutlet is a favorite deep fat fried food item among Korean children, and an excellent protein-containing food, and as well as a simple and economical cuisine. However, the frying process adds a significant amount of calories. We added MC (Methylcellulose) and HPMC (Hydroxypropyl Methylcellulose) to the batter in an effort to reduce oil uptake in prepared pork cutlets. After additions of MC and HPMC at concentrations of 0.5, 1, and 1.5% respectively, we assessed the viscosity of batter, color after frying, the increases in moisture retention and oil uptake, and sensory characteristics, comparing each quality. The viscosity of batter with 0.5% HPMC added (w/w) was similar to that of the controls, but the viscosity of all the batter with added MC was so much higher that it was difficult to use the batter for coating at the same temperature, leading to a failure even to prepare a sample. After frying, the batter with added HPMC provided significantly less oil uptake and more moisture retention than the batter to which MC was added. Additionally, with regard to color and sensory characteristics, the pork cutlet with 0.5% added HPMC was superior to the other samples. According to these results, we concluded that when cellulose derivatives are added in order to reduce oil uptake and to raise the moisture retention of the batter of pork cutlet, HPMC is more useful in this regard than MC. Additionally, the batter with 0.5% HPMC added appears to be the best of the tested choices, for three reasons: first, the viscosity of the batter is similar to that of the controls; second, the taste is not greasy after frying as the result of the reduced oil uptake and higher moisture retention; and third, the sensory characteristics of this sample, such as, color, crispiness, and hardness were the best among samples.