• 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.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• Journal of the Korean Geographical Society
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• v.31 no.2
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• pp.138-159
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• 1996

There has been a tendency for Geomorphology and Climatology to be dominant in Physical Geography for 50 years in Korea. Physical Geography is concerned with the study of the totality of natural environment through the integrated approaches. But, an overall direction or a certain paradigm could not be found, because major sub-divisions of Physical Geography have been studied individually and the subjects and the approaches in studying Physical Geography are enormously diverse. A consensus of opinion could not also exist in deciding what kind of the sub-divisions should be included in the physical geography in general and how those should be summarized. Furthermore it would be considered imprudent to survey the studies of Physical Geography besides those of Geomorphology and Climatology due to the small number of researchers. Assuming that the rest of Physical Geographical studies with the exception of Geomorphological and Climatological studies are the Physical Geography in general, the studies of Physical Geogrpahy in general are summarized and several aspects are drown out as follows. First the descliption of all possible factors of natural environments was the pattern of early studies of Physical Geography and the tendency is maintained in the various kinds of research and project reports. Recently Physical Geographers have published several introductory textbooks or research monographs. In those books, however, the integrated approaches to Physical Geography were not suggested and the relationship between man and nature are dealt with in the elementary level. Second, the authentic soil studies of Physical Geographers are insignificant, because the studies of soil in Physical Geography have been mostly considered as the subsidiary means of Geomorphology Summarizing the studies of Soil Gegraphy by physical geographers and other Pedologists, the subjects are classified as soil-forming processes, soil erosions, soil in the tidal flat and reclaimed land, and soil pollution. Physical Geographers have focused upon the soil-forming processes in order to elucidate the geomorphic processes and the past climatic environment. The results of other subjects are trifling. Thirdy Byogeygrayhers and the results of studies are extremely of small number and the studies of Biogeography in Korea lines in the starting point. But, Biogeography could be a more unifying theme for the Physical-human Geography interface, and it would be expected to play an active part in the field of environmental conservation and resource management. Forth, the studies of Hydrogeography (Geographical Hydrology) in Korea have run through the studies of water balance and the morphometric studies such as the drainage network analysis and the relations of various kinds of morphometric elements in river. Recently, the hydrological model have introduced and developed to predict the flow of sediment, discharge, and ground water. The growth of groundwater studies is worthy of close attention. Finally, the studies on environmental problems was no mole than the general description about environmental destruction, resource development, environmental conservation, etc. until 1970s. The ecological perspectives on the relationship between man and nature were suggested in some studies of natural hazard. The new environmentalism having been introduced since 1980s. Human geographers have lead the studies of Environmental Perception. Environmental Ethics, Environmental Sociology, environmental policy. The Physical geographers have stay out of phase with the climate of the time and concentrate upon the publication of introductory textbooks. Recently, several studies on the human interference and modification of natural environments have been made an attempt in the fields of Geomorphology and climatology. Summarizing the studies of Physical Geography for 50 years in Korea, the integrated approaches inherent in Physical Geography disappeared little by little and the majol sub-divisions of Physical Ceography have develop in connection with the nearby earth sciences such as Geology, Meteorology, Pedology, Biology, Hydrology, etc been rediscovered by non-geographers under the guise of environmental science. It is expected that Physical Geography would revive as the dominant subject to cope with environmental problems, rearming with the innate integrated approaches.