• Journal of the Korean Society of Food Culture
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• v.19 no.2
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• pp.209-216
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• 2004

To investigate physico-chemical changes of mashed red repper and red pepper powder during frozen storage, we analyzed the quality of samples after mashing, mashing and blanching, mashing and addition of vitamin C, mashing and addition of NaCl. The most important quality factor of red pepper is red color. $\alpha$ value of red pepper powder of Pochungchun was 31.51. These results showed that those processing methods were effective to preserve red color. Capsanthin contents of mashed red pepper treated with vitamin C were decreased 1.8% after 180 days of frozen storage. This decrease was the least, showing that addition of vitamin C helped retaining capsanthin contents. Capsaicin and dihydrocapsaicin contents in Pochungchun powder ore decreased 11.9 and 18.3% during frozen storage respectively. These results showed that capsaicin was more stable than dihycrocapsaicin during frozen storage. Generally capsaicin and dihydrocapsaicin in the Pochungchun red pepper frozen-stored after mashing were less decreased than red pepper powder, and addition of vitamin C to the mashed red pepper was the most effective to retain capsicin and dihydrocapsaicin than others. The content of vitamin C in the red pepper frozen-stored after masking and blanching was 12.0 mg/100g, compared with 44.0 mg/100g in the sample stored after only mashing. This suggested that blanching process destroyed vitamin C in the mashed red pepper. Addition of salt in the mashed red pepper showed the same inclination. But, addition of vitamin C to the mashed red pepper was decreased 32.9% compared with 69.0% in the mashed red repper during frozen storage. Theser results indicated that addition of vitamin C could retain vitamin C in the mashed red lopper.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.275-285
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• 2017

National Meteorological Satellite Center(NMSC) has produced Sea Surface Temperature (SST) using Communication, Ocean, and Meteorological Satellite(COMS) data since April 2011. In this study, we have developed a new regional COMS SST algorithm optimized within the North-West Pacific Ocean area based on the Multi-Channel SST(MCSST) method and made a composite SST using polar orbit satellites as well as the COMS data. In order to retrieve the optimized SST at Northwest Pacific, we carried out a colocation process of COMS and in-situ buoy data to make coefficients of the MCSST algorithm through the new cloud masking including contaminant pixels and quality control processes of buoy data. And then, we have estimated the composite SST through the optimal interpolation method developed by National Institute of Meteorological Science(NIMS). We used four satellites SST data including COMS, NOAA-18/19(National Oceanic and Atmospheric Administration-18/19), and GCOM-W1(Global Change Observation Mission-Water 1). As a result, the root mean square error ofthe composite SST for the period of July 2012 to June 2013 was $0.95^{\circ}C$ in comparison with in-situ buoy data.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.93-106
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• 2021

Many recent studies on deep learning-based road crack detection have shown significantly more improved performances than previous works using algorithm-based conventional approaches. However, many deep learning-based studies are still focused on classifying the types of cracks. The classification of crack types is highly anticipated in that it can improve the crack detection process, which is currently relying on manual intervention. However, it is essential to calculate the severity of the cracks as well as identifying the type of cracks in actual pavement maintenance planning, but studies related to road crack detection have not progressed enough to automated calculation of the severity of cracks. In order to calculate the severity of the crack, the type of crack and the area of the crack in the image must be identified together. This study deals with a method of using Mobilenet-SSD that is deep learning-based object detection techniques to effectively automate the simultaneous detection of crack types and crack areas. To improve the accuracy of object-detection for road cracks, several experiments were conducted to combine the U-Net for automatic segmentation of input image and object-detection model, and the results were summarized. As a result, image masking with U-Net is able to maximize object-detection performance with 0.9315 mAP value. While referring the results of this study, it is expected that the automation of the crack detection functionality on pave management system can be further enhanced.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1615-1633
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• 2023

Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.17 no.1
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• pp.24-32
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• 1984

In order to process instant foods which hold appropriate moisture contents and soft texture, four kinds of retort pouched seasoned-oyster products were prepared as control, seasoned products, solid smoked and liquid smoked product after seasoning and their processing conditions and quality stability during 100 days of storage were investigated. The optimum processing conditions of retort pouched seasoned-oyster product were as follows ; namely, raw oyster was seasoned at $105^{\circ}C$ for 10 min with seasoning solution prepared from sugar, sorbitol, salt, monosodium glutamate and 5'-ribonucleotide and then dipped for 30 seconds in Smoke-EZ solution(Alpha Foods Co., Ltd.) after predried for 30 min in hot-air drier. After. smoking, the seasoned and liquid smoked oyster was dried at $40-42^{\circ}C$ for 2.5 hours, vacuum packed in plastic film bag, and sterilized in a hot water circulating retort at $120^{\circ}C$ for 16 min. Comparing their quality before and after sterilization, TBA value of all the products after sterilization slightly decreased and among texture profiles hardness, toughness and chewiness slightly decreased, while elasticity and cohesiveness were rarely changed. Color value (a value) of the product treated with solid smoke or liquid smoke increased after sterilization. During storage pH, VBM and water activity of all products changed little and TBA values of the solid smoked product and liquid smoked one were lower than that of the others. Viable cell count was negative and texture changed little during storage. As for color difference during storage, green meat appeared on the surface of control and seasoned product after 15 days storage, while the masking of green meat could achieved by solid and liquid smoking treatment. And liquid smelling treatment was more effective than solid smoking. As a conclusion, retort pouched seasoned-oyster product treated with liquid smoke kept their good quality during 100 days storage and it seemed to be consumed as one of the instant foods which hold appropriate moisture contents and soft texture.