• Korean Journal of Fisheries and Aquatic Sciences
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• v.15 no.4
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• pp.283-290
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• 1982

Sardine and mackerel so called dark muscled fish have been underutilized due to the disadvantages in bloody meat color, high content of fat, and postmortem instability of protein. Recent efforts were made to overcome these defects and develope new types of product such as texturized protein concentrates and dark muscle eliminated minced fish. Approach of this study is based on the rapid dehydration of foamed fish-starch paste by dielectric heating. In process comminuted sardine meat was washed more than three times by soaking and decanting in chilled water and finally centrifuged. The meat was ground in a stone mortar added Ivith adequate amounts of salt, foaming agent, and other ingredients for aid to elasticity and foam stability. The ground meat paste was extruded in finger shape and heated in a microwave oven to give foamed, expanded, and porous solid structure by dehydration. Dielectric onstant $(\varepsilon')$ and dielect.ic loss $(\varepsilon")$ values of sardine meat paste were influenced by wavelength and moisture level. Those values at 100 KHz and 15 MHz were ranged 2.25-9.86; 2.22-4,18 for E' and 0.24-19.24; 0.16-1.20 for E", respectively, at the moisture levels of $4.2-13.8\%$. For a formula for fish-starch paste preparation, addition of $20-30\%$ starch (potato starch) to the weight of fish meat, $2-4\%$ salt, and $5-10\%$ soybean protein was adequate to yield 4-5 folds of expansion in volume when heated. Addition of e99 yolk was of benefit to micronize foam size and better crispness. In order to provide better foaming and dehydration, addition of $0.2-0.5\%$sodium bicarbonate, foaming agent, was proper to result in foam size of 0.5-0.7 mm and foam density of $200-400\;/cm^2$ which gave a good crispness. Heating time was depended upon the moisture level of fish-starch paste. For a finger shaped paste (1.0cm. $D\times10cm.L$) heating for 150-200 sec. in a microwave oven (700W. 2.45GHz) was sufficient to generate foams, expand, and solidify the porous structure of fish-starch paste. When the moisture content was above $55\%$ browning and scorching was deepened due to over-expansion and over-heating whereas the crispness was hardened by insufficient expansion at lower moisture content. In quality evaluation of the product, chemical composition of $30\%$ starch and $3\%$ salt added product was moisture $8.8\%$, lipid $2.4\%$, carbohydrate $46.7\%$, protein $36.1\%$, and ash $6.0\%$. Eleven membered panel test evaluated that fish-starch paste was acceptable in color, crisp-ness, taste, except a trace of fishy odour which could be masked by the addition of spice extracts.

• Korean Journal of Food Science and Technology
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• v.34 no.3
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• pp.361-364
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• 2002

This study was performed to establish a simple and accurate method for the determination of oxygen that is a processing aid in various beverage. The quantitative determination of dissolved oxygen (DO) contents in 30 cases of samples were performed by traditional titration method and polarography. As a result of the study, the analysis of DO contents in fruit-extract beverages containing oxygen by titration method was time consuming and large sample volumes were needed. Besides, serious interferences with compounds such as hydroxylamine and nitric oxide were observed, leading to false response. Although the polarography is easily affected by $H_2S$, proteins, and various organic compounds, it is a simple and practical method that provides inexpensive and relatively rapid analysis. The polarography is best suited to the routine determination of DO in a large number of samples and it is expected that the polarography can directly be applied to the quality control of the beverages containing added oxygen. The analysis results of DO contents in various fruit-extract beverages with oxygen and without oxygen were as follows: 23.10 ppm to 32.60 ppm for various frutis extract beverages with oxygen, 0.70 pp to 2.54 ppm for mixed beverages without oxygen, 7.63 ppm to 8.28 ppm for drinking water.

• Journal of Mushroom
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• v.19 no.3
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• pp.166-175
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• 2021

In this study, monokaryons of "Heukari" (Pleurotus ostreatus) and "Hosan" (Pleurotus pulmonarius) were separated to remove the cell wall, and a cross-species protoplast fusion was developed through chemical treatment with polyethylene glycol. The protoplast-fused PF160306 and PF160313 strains have a culture period of 10 and 2 days shorter than that of the "Heuktari" and "Hosan" cultivars, respectively. Furthermore, the growth of the strains was faster than that of the existing cultivars. The yield was 135.9 g per bottle, which was approximately 8% higher than that of the commercially available "Hosan" cultivar; however, it was not statistically significant. A growth survey was conducted after treatment at five temperatures (15, 18, 21, 23, and 25℃). The growth of the strains accelerated with the increase in temperature. However, at 21℃, the yellow color of pileus was the brightest. Band pattern, assessed using URP Primer 7, was similar to that of the "Hosan" cultivar. The DPPH radical scavenging capacity and polyphenol content were 62.5% and 43.5 mg/mL, respectively, for "Sunjung" and 65.7% and 49.9 mg/mL, respectively, for PF160313. Furthermore, the antihypertensive activities of the "Sunjung" cultivar and PF160313 were similarly high at 74% and 75%, respectively. In conclusion, cross-species hybridization via the protoplast fusion technique can be used for obtaining primary data for mushroom breeding to develop new varieties. In addition, the protoplast fusion technique might aid in expanding the market for yellow mushrooms.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.25-32
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• 2021

In line with future changes in the marine environment, Aids to Navigation has been used in various fields and their use is increasing. The term "Aids to Navigation" means an aid to navigation prescribed by Ordinance of the Ministry of Oceans and Fisheries which shows navigating ships the position and direction of the ships, position of obstacles, etc. through lights, shapes, colors, sound, radio waves, etc. Also now the use of Aids to Navigation is transforming into a means of identifying and recording the marine weather environment by mounting various sensors and cameras. However, Aids to Navigation are mainly lost due to collisions with ships, and in particular, safety accidents occur because of poor observation visibility due to sea fog. The inflow of sea fog poses risks to ports and sea transportation, and it is not easy to predict sea fog because of the large difference in the possibility of occurrence depending on time and region. In addition, it is difficult to manage individually due to the features of Aids to Navigation distributed throughout the sea. To solve this problem, this paper aims to identify the marine weather environment by estimating sea fog level approximately with images taken by cameras mounted on Aids to Navigation and to resolve safety accidents caused by weather. Instead of optical and temperature sensors that are difficult to install and expensive to measure sea fog level, sea fog level is measured through the use of general images of cameras mounted on Aids to Navigation. Furthermore, as a prior study for real-time sea fog level estimation in various seas, the sea fog level criteria are presented using the Haze Model and Dark Channel Prior. A specific threshold value is set in the image through Dark Channel Prior(DCP), and based on this, the number of pixels without sea fog is found in the entire image to estimate the sea fog level. Experimental results demonstrate the possibility of estimating the sea fog level using synthetic haze image dataset and real haze image dataset.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.