• Culinary science and hospitality research
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• v.20 no.6
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• pp.235-244
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• 2014

The purpose of this study was to investigate the effect of freezing and thawing rate on the physical properties of soybean sprouts to improve the quality of processed soybean sprouts during distribution and storage. Cooked soybean sprouts were frozen by air-blast freezing (ABF) system at $-45^{\circ}C$ or natural air convection freezing (NCF) system at $-24^{\circ}C$, then thawed using microwave oven by varying output power (0, 400, 800 and 1,000 W) until $75^{\circ}C$. The quality of soybean sprouts was measured by the water content, hardness and springiness. In addition, the internal microstructure of soybean sprouts was observed by optical microscope. For results, water content of soybean sprouts thawed by 1,000 W in a microwave showed the lowest value after natural air convection freezing. Springiness of soybean sprouts thawed by all amounts of output power was decreased in comparison with control. Hardness was increased only in soybean sprouts thawed by 1,000 W after air-blast freezing. However the gaps between springiness and hardness were relatively small with control at 1,000 W thawing, after air-blast freezing. Internal microstructure of the soybean sprouts was more damaged as freezing and thawing time were increased. In conclusion, high freezing and thawing rate might improves the quality of soy bean sprout, and IQF freezing and 1,000 W of microwave thawing appears to be the optimum condition for frozen HMR production. From the results freezing and thawing process parameters might can be use as quality control parameters as various type of sprout products processing.

• Journal of the Korean Society of Food Science and Nutrition
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• v.38 no.9
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• pp.1243-1252
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• 2009

We investigated a method to improve anticancer activities of Acer mono by ultra high pressure extraction process. The extract yields by ultra high pressure were 9.49% and 9.87% for 5 min and 15 min processing time, respectively, which were relatively higher than 3$\sim$4% of conventional extraction processes due to their resid bark structure. The extract for 15 minutes extraction (HPE15) showed higher potent scavenging effect as 94.56% than the control, BHA as 93.24%. On SOD-like test, HPE15 also showed the highest activity as 38.6% at 1.0 mg/mL concentration. The cytotoxicity of HPE15 on normal human lung and kidney cell were below 23.54% in adding 1.0 mg/mL. Generally, human cancer cell growth stomach adenocarcinoma (AGS), lung adenocarcinoma (A549), breast adenocarcinoma (MCF-7), colon adenocarcinoma (Caco-2) and liver adenocarcinoma (Hep3B) were inhibited up to 75% with higher selectivity of above 4.0. High antioxidant activity of HPE15 resulted in high anticancer activity, and its activity was also due to higher yields of Acer mono by ultra high pressure extraction process. It was also proved by HPLC comparison analysis.

• 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.1
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• pp.43-50
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• 2002

To develop commercial semi-solid apple baby food, the physicochemical characteristics of apple puree in relation to different preparing methods and the effect of the addition methods of ascorbic acid on browning reaction were investigated. The preparing methods were classified into 3 groups by initial heating treatment: no heating (A), steaming at $120^{\circ}C$ (B), and blancing at $100^{\circ}C$ (C). The viscosity of tested apple puree was $2,600{\sim}5,856\;cp$, and contents of anhydrogalaturonic acid (AGA) and neutral sugar ranged $4.15{\sim}11.92\;mg%$ and $6.18{\sim}10.65\;mg%$, respectively. Among free sugars tested, level of fructose was the highest $(5.43{\sim}8.87%)$, followed by glucose $(2.11{\sim}4.23%)$, sucrose $(1.64{\sim}2.94%)$, in that order. Since small amounts of ascorbic acid were detected $(1.54{\sim}1.83\;mg%)$, it seemed to be lost by heating process in preparing of apple puree. For apple puree A, its lightness was lower and redness was higher than those of apple puree B and C. Its degree of browning of apple puree was so high that sodium ascorbic acid was added as a antibrowning agent. Puree had low sensory score and nutrient quality. The adding methods of ascorbic acid were classified into 4 groups by adding time: dipping, blending (2), heating (3), and blending + heating (4). Considering color and preference evaluation, preparing method B and adding method 2 showed the highest inhibitory activity on apple puree browning and desirable color for retort baby food. After retort sterilization, the viscosity of apple baby food was decreased from 3,477 cp to 2,294 cp, thiamin was destroyed completely, and the contents of riboflavin and ascorbic acid were decreased 41% and 21%, respectively. However, contents of free sugar and free amino acid and sensory parameter were not influenced by retort sterilization. In overall, the preparing method B-adding method 2 was a good processing condition for the retort apple baby food.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.14 no.2
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• pp.197-208
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• 2003

Objective：In this study, we hypothesized that deficit in processing rapid linguistic stimuli is at the heart of Reading Disability(RD) and deficit in response inhibition is at the heart of Attention Deficit/Hyperactivity(ADHD). We conducted experiments to identify the core cognitive characteristics of children either with RD or with ADHD or with both, using attentional tasks and phoneme differential tests. Method：In the study 1, 28 children with ADHD, 16 children with RD+ADHD were individually administered visual/auditory performance tests. Then, the differences of performance on attentional tasks between two groups were compared while IQs of two groups were controlled. In the study 2, 13 children with RD+ADHD/RD, 13 children with ADHD, and 13 normal children were administered computerized phoneme differential tests. Result：Visual attentional tasks did not distinguish an ADHD group from a RD+ADHD group. With auditory attentional tasks, however, the comorbid group showed significantly more difficulties, causing a large variance in reaction time. RD, RD+ADHD, and ADHD groups showed more errors in phoneme differential tests than a normal control group, and each group showed distinctive performance patterns. Discussion：An ADHD group had difficulty in response inhibition and sustained attention, and children who also had RD along with ADHD magnified the auditory attentional difficulties. Even though children with RD had more trouble with responding correctly to target stimuli, their responses were not significantly different from those of children with ADHD.

• Journal of Korean Home Economics Education Association
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• v.17 no.4 s.38
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• pp.133-156
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• 2005

This study clarifies the concept of the education content relevance in order to evaluate the content relevance of Technology & Home Economics in a secondary school, and design its standards based on the preceding study. In other words, four standards such as the amount of studying content, the degree of difficulty, the validity of contents and the sequence of contents are established. Also, a survey on the current status of nationwide units targeting students, teachers, and professors was conducted to collect actual data about relevance evaluation. The results are as follows. First, as for the evaluation in terms of the amount of studying content, the majority of respondents answered that it decreased by about $30\%$ when compared to the 6th Technology & Home Economics Curriculum However, middle school teachers pointed out that the number of classes is not enough considering the fact that it's an activity-oriented subject. So, they acknowledged that the amount of study time during a Technology Sl Home Economics class is 'quite a lot.' Second, the evaluation in the degree of difficulty is divided into two responses. Teachers responded that it's reasonable overall, but according to students, it's difficult. Especially, the chapters that students don't understand well including 'The Elements of Draftsmanship,"' 'Understanding of Machinery,' 'Electronics & Electricity Technology,' and 'Energy & Transportation Technology.' In the Home Economics area, 'The Design of Home Life' is the only chapter that students don't understand well. Third, as for the validity of contents, the chapters that were not considered as important considering the objective of Technology Sl Home Economics Curriculum include 'The Elements of Draftsmanship,' 'Computer & Processing,' and 'The Management of Resources and Environment.' Fourth, as for the sequence of contents, the survey was conducted including the name of the course asone of the survey items. The majority of teachers wanted it as it is, but the Professors of education colleges who wanted the 3rd name to connect the course with the elementary school course was a little more $(50.5\%)$ than the ones who don't want any changes $(45.5\%)$. The follow-up study should correct and complement the standards that this study suggested through analytic and critical review according to the character & goal of the subject. Based on such standards, the evaluation of content relevance should be continued to realize the quality control of the curriculum systematically.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.39-60
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• 2011

Since the introduction of web 2.0 technology, social network service has been recognized as the foundation of an important future information technology. The advent of web 2.0 has led to the change of content creators. In the existing web, content creators are service providers, whereas they have changed into service users in the recent web. Users share experiences with other users improving contents quality, thereby it has increased the importance of social network. As a result, diverse forms of social network service have been emerged from relations and experiences of users. Social network is a network to construct and express social relations among people who share interests and activities. Today's social network service has not merely confined itself to showing user interactions, but it has also developed into a level in which content generation and evaluation are interacting with each other. As the volume of contents generated from social network service and the number of connections between users have drastically increased, the social network extraction method becomes more complicated. Consequently the following problems for the social network extraction arise. First problem lies in insufficiency of representational power of object in the social network. Second problem is incapability of expressional power in the diverse connections among users. Third problem is the difficulty of creating dynamic change in the social network due to change in user interests. And lastly, lack of method capable of integrating and processing data efficiently in the heterogeneous distributed computing environment. The first and last problems can be solved by using FOAF, a tool for describing ontology-based user profiles for construction of social network. However, solving second and third problems require a novel technology to reflect dynamic change of user interests and relations. In this paper, we propose a novel method to overcome the above problems of existing social network extraction method by applying FOAF (a tool for describing user profiles) and RSS (a literary web work publishing mechanism) to OLAP system in order to dynamically innovate and manage FOAF. We employed data interoperability which is an important characteristic of FOAF in this paper. Next we used RSS to reflect such changes as time flow and user interests. RSS, a tool for literary web work, provides standard vocabulary for distribution at web sites and contents in the form of RDF/XML. In this paper, we collect personal information and relations of users by utilizing FOAF. We also collect user contents by utilizing RSS. Finally, collected data is inserted into the database by star schema. The system we proposed in this paper generates OLAP cube using data in the database. 'Dynamic FOAF Management Algorithm' processes generated OLAP cube. Dynamic FOAF Management Algorithm consists of two functions: one is find_id_interest() and the other is find_relation (). Find_id_interest() is used to extract user interests during the input period, and find-relation() extracts users matching user interests. Finally, the proposed system reconstructs FOAF by reflecting extracted relationships and interests of users. For the justification of the suggested idea, we showed the implemented result together with its analysis. We used C# language and MS-SQL database, and input FOAF and RSS as data collected from livejournal.com. The implemented result shows that foaf : interest of users has reached an average of 19 percent increase for four weeks. In proportion to the increased foaf : interest change, the number of foaf : knows of users has grown an average of 9 percent for four weeks. As we use FOAF and RSS as basic data which have a wide support in web 2.0 and social network service, we have a definite advantage in utilizing user data distributed in the diverse web sites and services regardless of language and types of computer. By using suggested method in this paper, we can provide better services coping with the rapid change of user interests with the automatic application of FOAF.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.9
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• pp.1293-1301
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• 2016

Hulled oat (Chohan) and naked oat (Choyang) flours were analyzed according to particle size to investigate nutritional components and physicochemical properties. Particle size of naked oat flours was larger than that of hulled oat flours. As the mesh of the crushed ones decreased, particle sizes increased in value. The content of total ${\beta}$-glucan was highest in hulled oat flour (4.23%) with 60 mesh and in naked oat flour (4.26%) with 100 mesh. Most total ${\beta}$-glucan was soluble ${\beta}$-glucan in both flours (over 76%). Total starch of hulled oat flours (63.64~69.82%) was higher than that of naked oat flours (52.45~63.71%). Whereas amylose contents showed a negative correlation with total starch contents. Contents of free amino acids increased according to particle size, and each component was dependent on each type of amino acid. Moreover, while fatty acid composition was not significant, the content of most naked oats was higher than that of hulled oats. Besides, the ratio of unsaturated fatty acids (oleic acid and linoleate) in both types of oat flours was relatively higher than that of other grains. The pasting properties of peak viscosity, trough, and breakdown showed the highest value in both oats with 100 mesh. Further, the values of final viscosity and the setback were higher with relatively larger particle size. In addition, peak time exhibited a lower value with larger particle size, whereas it showed the opposite value for pasting temperature. Starch digestibility did not show any specific trend according to particle size, whereas expected glycemic index of hulled oats was lower than that of naked oats. Moreover, lower values were investigated at larger particle sizes. The results of this study provide basic useful information for processing of oat products to improve consumption of oats grown in Korea.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.6
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• pp.13-24
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• 2017

The purpose of this study is to examine the effect of the management of receivables on the management performance of micro manufacturing industries. The results of the survey are as follows. First, among the factors of management of pre- and post-trade receivables in the micro manufacturing industries, management organization and regulations, contract execution management, bad debt control, which are the subordinate factors of credit control, are positive (+) significant effect on stability. In terms of profitability, management organizations and regulations, which are subordinate factors of credit control management, have a positive (+) significant effect on profitability. The recovery management, which is a factor of management of post - receivable receivables, did not have a significant effect on the stability and profitability of financial management performance. Second, the effect of financial performance on organizational satisfaction is positively related to stability, while profitability has no significant effect on organizational satisfaction. The implication of this study is that pre - trade receivables management is more important than post - trade receivables management in the management of accounts receivables of micro manufacturing industries. Proactive credit management refers to the procedure of establishing and managing personal guarantees and physical guarantees in order to smooth the execution of the obligations at the same time as the contract is concluded through processes such as credit investigation, analysis and evaluation, and sales decision before the contract is concluded. Post receivables management based on the assumption of default is a receivables management procedure from receipt of receivables that are already defaulted to bad debts to bad debt processing. If the collection of receivables is delayed or bad debt is increased, Furthermore, a corporation may be subject to bankruptcy risk (insolvency by paper profits). Therefore, it is meaningful that this study suggests direction to induce change of contract type in advance by understanding the possibility of settlement of accounts receivable and recovery of bad debts within the day of transition in case of contract of micro manufacturing industries.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.