• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.11
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• pp.1358-1365
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• 2017

This study evaluated the quality characteristics of muffins prepared with different amounts (0%, 10%, 20%, 30%, 50%) of fucoidan red yeast (Monascus purpureus) rice powder (FRYR). The weight and pH of muffins increased as the amount of FRYR increased. The height and baking loss rate of muffins significantly decreased when amounts of FRYR increased (P<0.05), whereas moisture content was not significantly different between all samples. L value and b value of muffins significantly decreased when amounts of FRYR increased (P<0.05). However, a value of muffins significantly increased when amounts of FRYR increased (P<0.05). Hardness, chewiness, and brittleness increased with increasing FRYR concentration. Cohesiveness was higher with 30% FRYR, whereas springiness was not significantly different between the samples. In the sensory evaluation, the appearance and crumb color of muffins was higher in groups containing 0% FRYR, whereas flavor, taste, texture, and overall acceptability scores were highest for muffins with 50% FRYR added. The total polyphenol content and 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity of muffins significantly increased with increasing addition of FRYR (P<0.05). Therefore, addition of FRYR could satisfy the sensory function and functional requirements of muffins. Furthermore, this study proposes the development of various products using fucoidan red yeast rice.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.3
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• pp.143-150
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• 2012

A simulation methodology and corresponding program based on it is to be discussed for analyzing the effects of the networking operation of existing DHC system in connection with CHP system on-site. The practical simulation for arbitrary areas with various building compositions is carried out for the analysis of operational features in both systems, and the various aspects of thermal energy grids with connecting operation are highlighted through the detailed assessment of predicted results. The intrinsic operational features of CHP prime movers, gas engine, gas turbine etc., are effectively implemented by realizing the performance data, i.e. actual operation efficiency in the full and part loads range. For the sake of simplicity, a simple mathematical correlation model is proposed for simulating various aspects of change effectively on the existing DHC system side due to the connecting operation, instead of performing cycle simulations separately. The empirical correlations are developed using the hourly based annual operation data for a branch of the Korean District Heating Corporation (KDHC) and are implicit in relation between main operation parameters such as fuel consumption by use, heat and power production. In the simulation, a variety of system configurations are able to be considered according to any combination of the probable CHP prime-movers, absorption or turbo type cooling chillers of every kind and capacity. From the analysis of the thermal network operation simulations, it is found that the newly proposed methodology of mathematical correlation for modelling of the existing DHC system functions effectively in reflecting the operational variations due to thermal energy grids with connecting operation. The effects of intrinsic features of CHP prime-movers, e.g. the different ratio of heat and power production, various combinations of different types of chillers (i.e. absorption and turbo types) on the overall system operation are discussed in detail with the consideration of operation schemes and corresponding simulation algorithms.

• Journal of the Korean Society of International Agriculture
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• v.30 no.4
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• pp.328-338
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• 2018

Central Asia (Uzbekistan, Kazakhstan, Kyrgyzstan) is a hot and arid continental climate, with most areas (68%) consisting of barren vegetation, desert, and meadows. The main agricultural areas for crop production include irrigated farmland, non-irrigated farmland, grassland, prairie and mountain. We are experiencing climate change with recent climate variability increasing. Agriculture is one of major economic sectors and provides a means of livings for the rural population of Central Asia, especially the poor. In the past two decades, Central Asia has experienced a high population growth rate, with Kazakhstan at 16.8%, Uzbekistan at 34.5% and Kyrgyzstan at 28.4%. As a major industry, Kazakhstan has the largest share of exports of agricultural products followed by petroleum, mineral resources, steel, and chemicals. Uzbekistan is the fifth largest cotton exporter as well as the sixth largest cotton producer in the world. Kyrgyzstan exports ores, stones, cultured pearls, and minerals. These three countries are rich in mineral resources, agricultural products, and energy resources. However, not only do they have difficulties in economic development due to the weakness of logistics and industrial infrastructure, but they also have imperceptible cooperation and investment among countries due to insufficient research and development. Through this study, we will investigate national outlook, economic indicators, major agricultural products, import and export status, and agricultural technology cooperation status, and study how Korean agricultural industry advances into these countries through SWOT analysis. Through this, we hope to contribute to the basic data of Central Asian studies and cooperation and investment in agriculture in each country. In addition, in order to increase cooperative exchange and investment in these countries, we will prepare a Central Asia logistics hub for the rapidly changing interKorean railroad era.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.31 no.1
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• pp.8-15
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• 2021

TiO2 has been used in various fields such as solar cells, dental implants, and photocatalysis, because it has high physical and chemical stability and is harmless to the body. TiO2 nanofibers which have a large specific surface area also show a good reactivity in bio-friendly products and excellent photocatalysis in air and water purification. To fabricate TiO2 nanofibers, an electrospinning method was used. To observe the diameter of TiO2 nanofibers with fabrication variables, the fabrication variables was divided into precursor composition variables and process variables and microstructure was analyzed. The concentrations of PVP (Polyvinylpyrrolidone) and TTIP (Titanium(IV) isopropoxide) were selected as precursor composition variables, and inflow velocity and voltage were also selected as process variables. Microstructure and crystal structure of TiO2 nanofibers were analyzed using FE-SEM (Field emission scanning electron microscope) and XRD (X-ray diffraction), respectively. As-spun TiO2 nanofibers with an average diameter of about 0.27 ㎛ to 1.31 ㎛ were transformed to anatase TiO2 nanofibers with an average diameter of about 0.22 ㎛ to 0.78 ㎛ after heat treatment of 3 hours at 450℃. Anatase TiO2 nanofibers with an average diameter of 0.22 ㎛ can be expected to improve the photocatalytic properties by increasing the specific surface area. To change the average diameter of TiO2 nanofibers, the control of precursor composition variables such as concentrations of PVP and TTIP is more efficient than the control of electrospinning process variables such as inflow velocity and voltage.

• Journal of Food Hygiene and Safety
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• v.39 no.2
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• pp.72-82
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• 2024

This study aimed to develop a scientifically and systematically standardized xylooligosaccharide analytical method that can be applied to products with various formulations. The analysis method was conducted using HPLC with Cadenza C₁₈ column, involving pre-column derivatization with 1-phenyl-3-methyl-5-pyrazoline (PMP) and UV detection at 254 nm. The xylooligosaccharide content was analyzed by converting xylooligosaccharide into xylose through acid hydrolysis. The pre-treated methods were compared and evaluated by varying sonication time, acid hydrolysis time, and concentration. Optimal equipment conditions were achieved with a mobile phase consisting of 20 mM potassium phosphate buffer (pH 6)-acetonitrile (78:22, v/v) through isocratic elution at a flow rate of 0.5 mL/min (254 nm). Furthermore, we validated the advanced standardized analysis method to support the suitability of the proposed analytical procedure such as specificity, linearity, detection limits (LOD), quantitative limits (LOQ), accuracy, and precision. The standardized analysis method is now in use for monitoring relevant health-functional food products available in the market. Our results have demonstrated that the standardized analysis method is expected to enhance the reliability of quality control for healthy functional foods containing xylooligosaccharide.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.69-93
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• 2017

The development of ICT has leaded the diversification and changes of supplies and demands in markets. It also caused the creations of a variety of values which are differentiated from those in the existing market. Therefore, a new-type market is created, which can include multi-value chains which are from ICT-based created markets as well as the existing markets. We defined the platform as the new-type market. In the platform, the multi-value chains can be coexisted with multi-values. In true market, when a new-type value chain entered into an existing market, it is general that it can be conflicted with the existing value chain in the market. The conflicted problem among multi-value chains in a market is caused by the sharing of limited market resources like suppliers, consumers, services or products among the value chains. In other words, if there are multi-value chains in the platform, then it is possible to have conflictions, overlapping, creations or losses of values among the value chains. To solve the problem, we introduce coexistence factors to reduce the conflictions to reach market equilibrium in the platform. In the other hand, it is possible to lead the creations of differentiated values from the existing market and to augment the total market values in the platform. In the early era of ICT development, ICT was introduced for improvement of efficiency and effectiveness of the value chains in the existing market. However, according to the changed role of ICT from the supporter to the promotor of the market, ICT became to lead the variations of the value chains and creations of various values in the markets. For instance, Uber Taxi created a new value chain with ICT-based new-type service or products with new resources like new suppliers and consumers. When Uber and Traditional Taxi services are playing at the same time in Taxi service platform, it is possible to create values or make conflictions among values between the new and old value chains. In this research, like Uber and traditional taxi services, if there are conflictions among the multi-value chains, then it is necessary to minimize the conflictions in the platform for the coexistence of multi-value chains which can create the value-added values in the platform. So, it is important to predict and discuss the possible conflicted problems between new and old value chains. The confliction should be solved to reach market equilibrium with multi-value chains in the platform. That is, we discuss the possibility of the coexistence of multi-value chains in the platform which are comprised of a variety of suppliers and customers. To do this, especially we are focusing on the healthcare markets. Nowadays healthcare markets are popularized in global market as well as domestic. Therefore, there are a lot of and a variety of healthcare services like Traditional-, Tele-, or Intelligent- healthcare services and so on. It shows that there are multi-suppliers, -consumers and -services as components of each different value chain in the same platform. The platform can be shared by different values that are created or overlapped by confliction and loss of values in the value chains. In this research, as was said, we focused on the healthcare services to show if a platform can be shared by different value chains like traditional-, tele-healthcare and intelligent-healthcare services and products. Additionally, we try to show if it is possible to increase the value of each value chain as well as the total value of the platform. As the result, it is possible to increase of each value of each value chain as well as the total value in the platform. Finally, we propose a coexistence model to overcome such problems and showed the possibility of coexistence between the value chains through experimentation.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.

• Proceedings of the Safety Management and Science Conference
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• 2004.11a
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• pp.355-380
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• 2004

I test the hypothesis that the gradual diffusion of information across asset markets leads to cross-asset return predictability in Korea. Using thirty-six industry portfolios and the broad market index as our test assets, I establish several key results. First, a number of industries such as semiconductor, electronics, metal, and petroleum lead the stock market by up to one month. In contrast, the market, which is widely followed, only leads a few industries. Importantly, an industry's ability to lead the market is correlated with its propensity to forecast various indicators of economic activity such as industrial production growth. Consistent with our hypothesis, these findings indicate that the market reacts with a delay to information in industry returns about its fundamentals because information diffuses only gradually across asset markets. Traditional theories of asset pricing assume that investors have unlimited information-processing capacity. However, this assumption does not hold for many traders, even the most sophisticated ones. Many economists recognize that investors are better characterized as being only boundedly rational(see Shiller(2000), Sims(2201)). Even from casual observation, few traders can pay attention to all sources of information much less understand their impact on the prices of assets that they trade. Indeed, a large literature in psychology documents the extent to which even attention is a precious cognitive resource(see, eg., Kahneman(1973), Nisbett and Ross(1980), Fiske and Taylor(1991)). A number of papers have explored the implications of limited information- processing capacity for asset prices. I will review this literature in Section II. For instance, Merton(1987) develops a static model of multiple stocks in which investors only have information about a limited number of stocks and only trade those that they have information about. Related models of limited market participation include brennan(1975) and Allen and Gale(1994). As a result, stocks that are less recognized by investors have a smaller investor base(neglected stocks) and trade at a greater discount because of limited risk sharing. More recently, Hong and Stein(1999) develop a dynamic model of a single asset in which information gradually diffuses across the investment public and investors are unable to perform the rational expectations trick of extracting information from prices. Hong and Stein(1999). My hypothesis is that the gradual diffusion of information across asset markets leads to cross-asset return predictability. This hypothesis relies on two key assumptions. The first is that valuable information that originates in one asset reaches investors in other markets only with a lag, i.e. news travels slowly across markets. The second assumption is that because of limited information-processing capacity, many (though not necessarily all) investors may not pay attention or be able to extract the information from the asset prices of markets that they do not participate in. These two assumptions taken together leads to cross-asset return predictability. My hypothesis would appear to be a very plausible one for a few reasons. To begin with, as pointed out by Merton(1987) and the subsequent literature on segmented markets and limited market participation, few investors trade all assets. Put another way, limited participation is a pervasive feature of financial markets. Indeed, even among equity money managers, there is specialization along industries such as sector or market timing funds. Some reasons for this limited market participation include tax, regulatory or liquidity constraints. More plausibly, investors have to specialize because they have their hands full trying to understand the markets that they do participate in

• Korean Chemical Engineering Research
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• v.53 no.5
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• pp.590-596
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• 2015

Estimating potential of $CO_2$ emission reduction of non-capture $CO_2$ utilization (NCCU) technology was evaluated. NCCU is sodium bicarbonate production technology through the carbonation reaction of $CO_2$ contained in the flue gas. For the estimating the $CO_2$ emission reduction, process simulation using process simulator (PRO/II) based on a chemical plant which could handle $CO_2$ of 100 tons per day was performed, Also for the estimation of the indirect $CO_2$ reduction, the solvay process which is a conventional technology for the production of sodium carbonate/sodium bicarbonate, was studied. The results of the analysis showed that in case of the solvay process, overall $CO_2$ emission was estimated as 48,862 ton per year based on the energy consumption for the production of $NaHCO_3$ ($7.4GJ/tNaHCO_3$). While for the NCCU technology, the direct $CO_2$ reduction through the $CO_2$ carbonation was estimated as 36,500 ton per year and the indirect $CO_2$ reduction through the lower energy consumption was 46,885 ton per year which lead to 83,385 ton per year in total. From these results, it could be concluded that sodium bicarbonate production technology through the carbonation reaction of $CO_2$ contained in the flue was energy efficient and could be one of the promising technology for the low $CO_2$ emission technology.