• Korean Journal of Food Science and Technology
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• v.31 no.4
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• pp.945-951
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• 1999

A simple and practical method for the determination of gardenia yellow in foods was developed. In this method, analysis of gardenia yellow in food products has been carried out by the detection of crocetin and/or geniposide as indicator compounds. As a new analytical method for gardenia yellow, we adopted crocetin, which is produced from colored components of gardenia yellow by alkaline hydrolysis, as an indicator compound. The analysis of gardenia yellow was performed by reverse phase high performance liquid chromatography using a Capcell pak $C_{18}$ column at wave length 240 nm (geniposide) and 435 nm (crocetin). The recovery rates of geniposide and crocetin were found to be 93.4% and 87.8% for Dan Mu Ji, 90.2% and 85.9% for milk, 92.8% and 86.5% for snack, respectively. With this method, the range of crocetin and geniposide contents $({\mu}g/g)$ were as follows: $ND{\sim}1.7$ and $ND{\sim}14.1$ for Dan Mu Ji, $ND{\sim}0.2$ and $ND{\sim}13.6$ for milk, $ND{\sim}1.6$ and $ND{\sim}0.9$ for snack, respectively. The detection limits of crocetin and geniposide were 0.07 ${\mu}g/g$ and 0.05 ${\mu}g/g$, respectively.

• Journal of Food Hygiene and Safety
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• v.35 no.4
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• pp.291-303
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• 2020

Marine organism-derived toxins have negative effects not only on human health but also in aquaculture, fisheries, and marine ecosystems. However, traditional analytical methods are insufficient in preventing this threat. In this paper, we reviewed new rapid methods of toxin detection, which have been improved by adopting diverse types of nanomaterials and technologies. Moreover, we herein describe the main strategies for toxin detection and their related sensing performance. Notably, to popularize and commercialize these newly developed technologies, simplifying the process of pre-treating real samples real samples is very important. As part of these efforts, numerous studies have reported pretreatment methods based on the antibody-immobilized magnetic nanoparticles, and some cases have applied nanoparticles to enhance the sensing performance by utilizing the intrinsic catalytic activity. Furthermore, some reports have introduced fluorescent nanoparticles, such as quantum dots, to represent the lower detection limits of conventional enzyme-based colorimetric methods and lateral flow assays. Some studies using electrochemical measurements based on aptamer-nanoparticle complexes have also been announced. In addition, as the response to new toxins generated by changes in the marine environment is still lacking, further research on diagnostic and detection is also greatly needed for these kinds of marine toxins and their derivatives.

• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.10
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• pp.1186-1194
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• 2017

Recently, many people have demanded reliable nutritional data even for minor-components. On the other hand, an analytical method for the analyses of vitamin $B_5$ and $B_6$ is lacking. Therefore, this study attempted to validate with accuracy and precision the analysis of vitamin $B_5$ and $B_6$ using a high-performance liquid chromatography (HPLC) method. The vitamin $B_5$ and $B_6$ contents were analyzed using an Agilent 1260 series HPLC system. YMC-Pack ODS-AM ($250{\times}4.6mm$ I.D.) and YMC-Pack Pro RS $C_{18}$ ($250{\times}4.6mm$ I.D.) columns were used for the analyses of vitamin $B_5$ and $B_6$, respectively. In the case of vitamin $B_5$, the flow rate was set to 1.0 mL/min by isocratic elution using the 50 mM $KH_2PO_4$ solution (pH 3.5)/acetonitrile (ACN) (95:5, v/v) with monitoring at 200 nm using HPLC/DAD, whereas the flow rate for vitamin $B_6$ was set to 1.0 mL/min of flow rate by isocratic elution using a 20 mM $CH_3CO_2Na$ solution (pH 3.6)/ACN (97:3, v/v) with monitoring by excitation at 290 nm and emission at 396 nm using HPLC/FLD. The column temperature was set to $30^{\circ}C$. The injection volume was $20{\mu}L$ for each experiment. The specificity of the accuracy and precision for vitamin $B_5$ and $B_6$ were also validated by HPLC. The results showed high linearity in the calibration curve for vitamin $B_5$ ($R^2=0.9998^{{\ast}{\ast}}$), the limit of detection (LOD) and limit of quantitation (LOQ) were 0.4 mg/L and 1.3 mg/L, respectively, In contrast, for the calibration curve of vitamin $B_6$, which showed high linearity ($R^2=0.9999^{{\ast}{\ast}}$), the LOD and LOQ were 0.006 mg/L and 0.02 mg/L, respectively.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.11
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• pp.1610-1616
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• 2016

This study aimed to establish an optimal extraction process and high performance liquid chromatography-ultraviolet (HPLC-UV) analytical method for determination of 3,5-dicaffeoylquinic acid (3,5-DCQA) as a part of materials standardization for the development of a xanthine oxidase inhibitor as a health functional food. The quantitative determination method of 3,5-DCQA as a marker compound was optimized by HPLC analysis using a Luna RP-18 column, and the correlation coefficient for the calibration curve showed good linearity of more than 0.9999 using a gradient eluent of water (1% acetic acid) and methanol as the mobile phase at a flow rate of 1.0 mL/min and a detection wavelength of 320 nm. The HPLC-UV method was applied successfully to quantification of the marker compound (3,5-DCQA) in Aster glehni extracts after validation of the method with linearity, accuracy, and precision. Ethanolic extracts of A. glehni (AGEs) were evaluated by reflux extraction at 70 and $80^{\circ}C$ with 30, 50, 70, and 80% ethanol for 3, 4, 5, and 6 h, respectively. Among AGEs, 70% AGE at $70^{\circ}C$ showed the highest content of 3,5-DCQA of $52.59{\pm}3.45mg/100g$ A. glehni. Furthermore, AGEs were analyzed for their inhibitory activities on uric acid production by the xanthine/xanthine oxidase system. The 70% AGE at $70^{\circ}C$ showed the most potent inhibitory activity with $IC_{50}$ values of $77.01{\pm}3.13{\sim}89.96{\pm}3.08{\mu}g/mL$. The results suggest that standardization of 3,5-DCQA in AGEs using HPLC-UV analysis would be an acceptable method for the development of health functional foods.

• Cartoon and Animation Studies
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• s.36
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• pp.237-257
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• 2014

This study is the process of performing the interdisciplinary fusion study between multiple fields by identifying the status on the previous artistic education considering the brain scientific mechanism of image creativity and brain-based learning principles. In recent years, producing the educational methods of each field as the fusion study activities are emerging as the trend and thanks to such, the results of brain-based educational fusion studies are being presented for each field. It includes artistic fields such as music, art and dance. In other words, the perspective is that by understanding the operating principles of the brain while creativity and learning is taking place, when applying various principles that can develop the corresponding functions as a teaching method, it can effectively increase the artistic performance ability and creativity. Since the animation drawing should be able to intuitively recognize the elements of movement and produce the communication with the target beyond the delineative perspective of simply drawing the objects to look the same, it requires the development of systematic educational method including the methods of communication, elements of higher cognitive senses as well as the cognitive perspective of form implementation. Therefore, this study proposes a literature study results on the artistic education applied with brain-based principles in order to design the educational model considering the professional characteristics of animation drawing. Therefore, the overseas and domestic trends of the cases of brain-based artistic education were extracted and analyzed. In addition, the cases of artistic education studies applied with brain-based principles and study results from cases of drawing related education were analyzed. According to the analyzed results, the brain-based learning related to the drawing has shown a common effect of promoting the creativity and changes of positive emotion related to the observation, concentration and image expression through the training of the right brain. In addition, there was a case of overseas educational application through the brain wave training where the timing ability and artistic expression have shown an enhancement effect through the HRV training, SMR, Beta 1 and neuro feedback training that strengthens the alpha/seta wave and it was proposing that slow brain wave neuro feedback training contributes significantly in overcoming the stress and enhancing the creative artistic performance ability. The meaning of this study result is significant in the fact that it was the case that have shown the successful application of neuro feedback training in the environment of artistic live education beyond the range of laboratory but the use of the machine was shown to have limitations for being applied to the teaching methods so its significance can be found in providing the analytical foundation for applying and designing the brain-based learning principles for future animation drawing teaching methods.

• Journal of Applied Biological Chemistry
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• v.64 no.2
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• pp.113-119
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• 2021

Olive (Olea europaea L.) leaves, a raw material for health functional foods and cosmetics have abundant polyphenols including oleuropein (major bioactive compound) with various biological activities: antioxidant, antibacterial, antiviral, anticancer activity, and inhibit platelet activation. Oleuropein has been reported as skin protectant, antioxidant, anti-ageing, anti-cancer, anti-inflammation, anti-atherogenic, anti-viral, and anti-microbial activity. Despite oleuropein is the important compound in olive leaves, there is still no quantitative approach to reveal oleuropein content in commercial products. Therefore, a validated method of analysis has to develop for oleuropein. In this study, the components and oleuropein content in 10 types of products were analyzed using a developed method with ultra-performance liquid chromatography to quadrupole time-of-flight mass spectrometry, charge of aerosol detector, and photodiode array. The total of 18 compounds including iridoids (1, 3, 4, 14, and 16-18), coumarin (2), phenylethanoids (5, 9, and 11), flavonoids (6-8, 10, 12, and 13), lignan (15), were tentatively identified in the leaves extract based high resolution mass spectrometry data, and the content of oleuropein in each product was almost identical between two detection methods. The oleuropein in three commercial product (A, G, H) was contained more over the suggested content, and it of five products (B, E, H, I, J) were analyzed within 5-10% error range. However, the two products (C, D) were found far lower than suggested contents. This study provides that analytical results of oleuropein could be a potential information for the quality control of leaf extract for a manufactured functional food.

• (The) Research of the performance art and culture
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• no.22
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• pp.253-285
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• 2011

The number of "Performing Arts Festivals" is growing increasingly in South Korea. This trend is mainly held in large cities which are difficult to communicate closely among residents. South Korea, while the pace of city life and speed of development are very fast, increasing number of "Performing Arts Festivals" with communal characteristics is in the natural process of festival evolution in large cities. In the evolution of the contemporary festival, it is natural to see some increase of modern festival after the development of traditional and folk festivals. It is important that the "Performing Arts Festivals" express the two elements, artistic character and festivity, not only in distinctively but also in harmony. The "Performing Arts Festivals" should consider the process of the organization, human resources, networking systems of the human communication process, resource use, etc. For the success of the festival, we must obtain the complementary effects between two attributes:festival characteristics and artistic senses. Therefore, we chose the 'Festival d'Avignon' as the reference of the total representation of artistic characteristics and festivity. From the case of the Festival d'Avignon, we get the implications of the development of performing arts festival in South Korea. To explain the festival value and artistic significance of the Festival d'Avignon, we explained the spontaneity and openness to public participation, the relationship between spectators and works, the representation of memory and communicative image, etc. To explain the artistic attributes of the 'Festival d'Avignon', we explained the mission to reconcile the artistic and the popular, to promote the artistic know-how, understanding how to communicate with the public, to consider more artistic quality than commercial benefits. Essentially, this study shows the meaning and the vision to forecast the future as well as the recent proliferation in various fields of Performing Arts Festivals. This study may help to improve analytical precision of Performing Arts Festivals.

• Information Systems Review
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• v.20 no.2
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• pp.39-62
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• 2018

Thanks to the growth of computing power and the recent development of data analytics, researchers have started to work on the data produced by users through the Internet or social media. This study is in line with these recent research trends and attempts to adopt data analytical techniques. We focus on the impact of "internal marketing" factors on firm performance, which is typically studied through survey methodologies. We looked into the job review platform Jobplanet (www.jobplanet.co.kr), which is a website where employees and former employees anonymously review companies and their management. With web crawling processes, we collected over 40K data points and performed morphological analysis to classify employees' reviews for internal marketing data. We then implemented econometric analysis to see the relationship between internal marketing and market capitalization. Contrary to the findings of extant survey studies, internal marketing is positively related to a firm's market capitalization only within a limited area. In most of the areas, the relationships are negative. Particularly, female-friendly environment and human resource development (HRD) are the areas exhibiting positive relations with market capitalization in the manufacturing industry. In the service industry, most of the areas, such as employ welfare and work-life balance, are negatively related with market capitalization. When firm size is small (or the history is short), female-friendly environment positively affect firm performance. On the contrary, when firm size is big (or the history is long), most of the internal marketing factors are either negative or insignificant. We explain the theoretical contributions and managerial implications with these results.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1041-1043
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• 1993

Fuzzy logic based Control Theory has gained much interest in the industrial world, thanks to its ability to formalize and solve in a very natural way many problems that are very difficult to quantify at an analytical level. This paper shows a solution for treating membership function inside hardware circuits. The proposed hardware structure optimizes the memoried size by using particular form of the vectorial representation. The process of memorizing fuzzy sets, i.e. their membership function, has always been one of the more problematic issues for the hardware implementation, due to the quite large memory space that is needed. To simplify such an implementation, it is commonly [1,2,8,9,10,11] used to limit the membership functions either to those having triangular or trapezoidal shape, or pre-definite shape. These kinds of functions are able to cover a large spectrum of applications with a limited usage of memory, since they can be memorized by specifying very few parameters ( ight, base, critical points, etc.). This however results in a loss of computational power due to computation on the medium points. A solution to this problem is obtained by discretizing the universe of discourse U, i.e. by fixing a finite number of points and memorizing the value of the membership functions on such points [3,10,14,15]. Such a solution provides a satisfying computational speed, a very high precision of definitions and gives the users the opportunity to choose membership functions of any shape. However, a significant memory waste can as well be registered. It is indeed possible that for each of the given fuzzy sets many elements of the universe of discourse have a membership value equal to zero. It has also been noticed that almost in all cases common points among fuzzy sets, i.e. points with non null membership values are very few. More specifically, in many applications, for each element u of U, there exists at most three fuzzy sets for which the membership value is ot null [3,5,6,7,12,13]. Our proposal is based on such hypotheses. Moreover, we use a technique that even though it does not restrict the shapes of membership functions, it reduces strongly the computational time for the membership values and optimizes the function memorization. In figure 1 it is represented a term set whose characteristics are common for fuzzy controllers and to which we will refer in the following. The above term set has a universe of discourse with 128 elements (so to have a good resolution), 8 fuzzy sets that describe the term set, 32 levels of discretization for the membership values. Clearly, the number of bits necessary for the given specifications are 5 for 32 truth levels, 3 for 8 membership functions and 7 for 128 levels of resolution. The memory depth is given by the dimension of the universe of the discourse (128 in our case) and it will be represented by the memory rows. The length of a world of memory is defined by: Length = nem (dm(m)＋dm(fm) Where: fm is the maximum number of non null values in every element of the universe of the discourse, dm(m) is the dimension of the values of the membership function m, dm(fm) is the dimension of the word to represent the index of the highest membership function. In our case then Length=24. The memory dimension is therefore 128*24 bits. If we had chosen to memorize all values of the membership functions we would have needed to memorize on each memory row the membership value of each element. Fuzzy sets word dimension is 8*5 bits. Therefore, the dimension of the memory would have been 128*40 bits. Coherently with our hypothesis, in fig. 1 each element of universe of the discourse has a non null membership value on at most three fuzzy sets. Focusing on the elements 32,64,96 of the universe of discourse, they will be memorized as follows: The computation of the rule weights is done by comparing those bits that represent the index of the membership function, with the word of the program memor . The output bus of the Program Memory (μCOD), is given as input a comparator (Combinatory Net). If the index is equal to the bus value then one of the non null weight derives from the rule and it is produced as output, otherwise the output is zero (fig. 2). It is clear, that the memory dimension of the antecedent is in this way reduced since only non null values are memorized. Moreover, the time performance of the system is equivalent to the performance of a system using vectorial memorization of all weights. The dimensioning of the word is influenced by some parameters of the input variable. The most important parameter is the maximum number membership functions (nfm) having a non null value in each element of the universe of discourse. From our study in the field of fuzzy system, we see that typically nfm 3 and there are at most 16 membership function. At any rate, such a value can be increased up to the physical dimensional limit of the antecedent memory. A less important role n the optimization process of the word dimension is played by the number of membership functions defined for each linguistic term. The table below shows the request word dimension as a function of such parameters and compares our proposed method with the method of vectorial memorization[10]. Summing up, the characteristics of our method are: Users are not restricted to membership functions with specific shapes. The number of the fuzzy sets and the resolution of the vertical axis have a very small influence in increasing memory space. Weight computations are done by combinatorial network and therefore the time performance of the system is equivalent to the one of the vectorial method. The number of non null membership values on any element of the universe of discourse is limited. Such a constraint is usually non very restrictive since many controllers obtain a good precision with only three non null weights. The method here briefly described has been adopted by our group in the design of an optimized version of the coprocessor described in [10].