• Journal of Intelligence and Information Systems
• /
• v.23 no.3
• /
• pp.1-27
• /
• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

• Korean Journal of Poultry Science
• /
• v.7 no.2
• /
• pp.54-76
• /
• 1980

A survey was conducted to determine the status of health and productivity of poultry farms in Korea. Area included Was Kyunggido where exist nearly 50% of national poultry population. From this area, 41 layer and 34 broiler farms covering 21 Countries were selected randomly for the survey. When farms were divided in the operation size, 95.1% of layer and 82.3% of broiler farms were classified as business or industrial level while the rest were managed in a small scale as part time job. Generally layer farms had been established much earlier than broiler farms. Geographically 10.7% of layer farms were sited near the housing area such as field foreast and rice field. No farms were located near the seashore. The distance from one farm from the other was very close, being 80% of the farms within the distance of 1km and as many as 28% of the farms within loom. This concentrated poultry farming in a certain area created serious problems for the sanitation and preventive measures, especially in case of outbreak of infectious diseases. Average farm size was 5,016${\times}$3.3㎡ for layers and 1,037${\times}$3.3㎡ for broilers. 89.5% of layer ana 70.6% of broiler farms owned the land for farming while the rest were on lease. In 60% of layer farms welters were employed for farming while in the rest their own labour was used. Majority of farms were equipped poorly for taking necessary practice of hygiene and sanitation. The amount of disinfectant used by farms was considerably low. As many as 97.6% of lave. farms were practised with Newcastle(ND) and fowl pox(F$.$pox) vaccine, whereas only 43.6% and 5.1% of broiler farms were practised with ND and F$.$pox vaccine, respectively. In 17-32.7% of farms ND vaccine was used less than twice until 60 days of age and in only 14.6% of farms adult birds were vaccinated every 4months. Monthly expense for preventive measures was over 200,000W in 32% of farms. Only 4.9-2.7% of vaccine users were soaking advice from veterinarians before practising vaccination, 85% of the users trusted the efficacy of the vaccines. Selection of medicine was generally determined by the farm owner rather than by veterinarans on whom 33.3% of farms were dependant. When diseases outbroke, 49.3% of farms called for veterinary hospital and the rest were handled by their own veterinarians, salesmen or professionals. Approximately 70% of farms were satisfied with the diagnosis made by the veterinarians. Frequency of disease outbreaks varied according to the age and type of birds. The livabilities of layers during the period of brooding, rearing ana adultwere 90.5, 98.9 and 75.2%, respectively while the livalibility of broilers until marketing was 92.2%. In layers, average culling age, was 533.3 day and hen housed eggs were 232.7. Average feed conversion rates of layers and broilers were 3.30 and 2.48, respectively. Those figures were considerably higher than anticipated but still far lower than those in developed countries.

• Korean Journal of Soil Science and Fertilizer
• /
• v.21 no.3
• /
• pp.254-263
• /
• 1988

Contents and distribution of amino acids in the humic acid and fulvic acid fractions of different types ($R_p$, B, A, P) were investigated. Extracted humic and fulvic acids were purified and analyzed. The results are summarized as the following: (1) Composition of Humus The total humus ($H_T$), amount of humic acid (a), amount of fulvic acid (b), and ${\Delta}logK$ all decrease in the order of $R_p$ > B > A > P type. The same trend was observed in the total nitrogen and carbon. (2) Contents and composition of amino acids in humic acids. 1) The total amounts of amino acids in the humic acid fraction of different types were in the following order for soils under coniferous forest trees: $R_p$ > B > A > P type, but for soils under deciduous forest trees the order was P > A > $R_p$ > B type. There were positive correlationships between total amino acids and total carbon and ${\Delta}logK$ for humic acids from soils under coniferous forest trees, but a negative correlationship was existed. between total amino acids and C/N ratios. No significant correlation was found for samples taken from soils under deciduous forest trees. 2) The ratios of one group of amino acids to the others were compared. The ratios of acidic amino acids were in the order of P > $R_p$ > B > A type. those of neutral amino acids followed the order of $R_p$ > B > A > P type and those of the basic amino acids were in the order of B > A >$R_p$ > P type for soils under coniferous forest trees. Contents of total amino acids were in the order of the neutral > the acidic > the basic amino acids. For the soils under deciduous forest trees the order of the ratio was different. Acidic amino acids followed the order of A > P > B > $R_p$ type, neutral ones followed the order of P > $R_p$ > A > B type, and the basic amino acids did the order of $$P{\geq_-}$$ A > B $$\geq_-$$ $-R_p$ type where the difference was very small. 3) In general aspartic aicd, glycine and glutamic acid were the major components in all samples. Histidine, tyrosine and methionine belonged to the group contained in a small amount. (3) Contents and composition of amino acids in fulvic acids. 1) The total amounts of amino acids of different types of fulvic acids were in the order of $R_p$ > B > P > A type regardless of origin of samples. There were positive correlationships observed between the toal amino acids and total carbon and ${\Delta}logK$ for soils under coniferous forest trees. For soils under deciduous forest trees, positive correlationships were observed among total amino aicds, total nitrogen, total humus ($H_T$), total humic aicd (a), and ${\Delta}logK$, but a negative correlationship existed between total amino acids and C/N ratio. 2) Thr ratio among acidic amino acids, neutral amino acids and basic amino acids of different types were $R_p$ > B > P > A type. In this respect there was no difference between the two soils. 3) In general glycine, aspartic acid, and alanine were the major constituents in all samples of different types, while tyrosine and methionine were contained in a small amount. Virtually no amount of arginine was measured.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.21 no.1
• /
• pp.39-43
• /
• 2017

Purpose Thyroglobulin (Tg) is a biologic marker of differentiated thyroid carcinoma (DTC), produced by normal thyroid tissue or thyroid cancer tissue. Therefore, the Tg values of DTC patients is the most specific indicator for judging whether recurrence occur or whether the remaining thyroid cancer is present. Thyroid cancer is currently the most common cancer in Korea, of which 90% is differentiated thyroid cancer. The number of patients with thyroid disease of this application also increased, and an accurate and prompt results are required. However, the incubation time of the Tg commonly takes about 24 hours in our hospital, and the result reporting time is delayed, and We could not satisfied with the requirements of clinical departments and patients. In order to fulfill these requirements, experiments were conducted by shortening the incubation time between company B's Kit currently in use and company C's Kit used in other hospitals. Through these experiments, we could perform the correlation with the original method and shortening method, and could find the optimum reaction time to satisfy the needs of the departments and the patients, and we will improve the competitiveness with the EIA examination. Materials and Methods In September 2016, we tested 65 patients company B's kit and company C's kit by three incubation ways. First method $37^{\circ}C$ shaking 2hr/2hr, Second method RT shaking 3hr/2hr, Third method 1hr/1hr shaking at $37^{\circ}C$. Fourth method RT shaking 3hr method which is the original method of Company C's Kit. Fifth method, the incubation time was shortened under room temperature shaking 2hr, Sixth method $37^{\circ}C$ shaking 2hr. And we performed and compared the correlation and coefficient of each methods. Results As a result of performing shortening method on company B currently in use, when comparing the Original method of company B kit, First method $37^{\circ}C$ shaking 2hr/2hr was less than Tg 1.0 ng/mL and the ratio of $R^2=0.5906$, above 1.0 ng/mL In the value, $R^2=0.9597$. Second method RT shaking 3hr/2hr was $R^2=0.7262$ less than value of 1.0 ng/mL, $R^2=0.9566$ above than value of 1.0 ng/mL. Third method $37^{\circ}C$ shaking 1hr/1hr was $R^2=0.7728$ less than value of 1.0 ng/mL, $R^2=0.8904$ above than value of 1.0 ng/mL. Forth, Company C's The original method, RT shaking 3hr was $R^2=0.7542$ less than value of 1.0 ng/mL, and $R^2=0.9711$ above than value of 1.0 ng/mL. Fifth method RT shaking 2hr was $R^2=0.5477$ less than value of 1.0 ng/mL, $R^2=0.9231$ above than value of 1.0 ng/mL. Sixth method $37^{\circ}C$ shaking 2hr showed $R^2=0.2848$ less than value of 1.0 ng/mL, $R^2=0.9028$ above than value of 1.0 ng/mL. Conclusion Samples with both values of 1.0 ng/mL or higher in both of the six methods showed relatively high correlation, but the correlation was relatively low less than value of 1.0 ng/mL. Especially, the $37^{\circ}C$ shaking 2hr method of company C showed a sharp fluctuation from the low concentration value of 1.0 ng/mL or less. Therefore, we are planning to continuously test the time, equipment, incubation temperature and so on for the room temperature shaking 2hr method and $37^{\circ}C$ shaking 1hr/1hr of company C which showed a relatively high correlation. After that, we can search for an appropriate shortening method through additional experiments such as recovery test, dilution test, sensitivity test, and provide more accurate and prompt results to the department of medical treatment, It is competitive with EIA test.

• Journal of Food Hygiene and Safety
• /
• v.21 no.4
• /
• pp.231-237
• /
• 2006

Nowadays the teabag is worldwide used for various products including green tea, tea, coffee, etc. since it is convenient for use. In case of outer packaging printed, however, there is a possibility that the plasticizers which is used for improvement in adhesiveness of printing ink may shift to inner tea bag. In this study, in order to monitor residual levels of plasticizers in teabags, we have established the simultaneous analysis method of 9 phthalates and 7 adipates plasticizers using gas chromatography (GC). These compounds were also confirmed using gas chromatography-mass spectrometry (GC-MSD). The recoveries of plasticizers analyzed by GC ranged from 82.7% to 104.6% with coefficient of variation of $0.6\sim2.7%$ and the correlation coefficients of each plasticizer was $0.9991\sim0.9999$. Therefore this simultaneous analysis method was showed excellent reproducibility and linearity. And limit of detection (LOD) and limit of quantitation (LOQ) on individual plasticizer were $0.1\sim3.5\;ppm\;and\;0.3\sim11.5\;ppm$ respectively. When 143 commercial products of teabag were monitored, no plasticizers analysed were detected in filter of teabag products. The migration into $95^{\circ}C$ water as food was also examined and the 16 plasticizers are not detected. In addition we carried out analysis of heavy metals, lead (Pb), cadmium (Cd), arsenic (As) and aluminum (Al) in teabag filters using ICP/AES. $Trace\sim23{\mu}g$ Pb per teabag and $0.6\sim1718{\mu}g$ Al per teabag were detected in materials of samples and Cd and As are detected less than LOQ (0.05 ppm). The migration levels of Pb and Al from teabag filter to $95^{\circ}C$ water were upto $11.5{\mu}g\;and\;20.8{\mu}g$ per teabag, respectively and Cd and As were not detected in exudate water of all samples. Collectively, these results suggest that there is no safety concern from using teabag filter.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.167-194
• /
• 2019

This research starts from the four basic concepts of incentive incompatibility, limited information, myopia and decision variable which are confronted when making decisions in keyword bidding. In order to make these concept concrete, four framework approaches are designed as follows; Strategic approach for the incentive incompatibility, Statistical approach for the limited information, Alternative optimization for myopia, and New model approach for decision variable. The purpose of this research is to propose the statistical optimization model in constructing the portfolio of Sponsored Search Advertising (SSA) in the Sponsor's perspective through empirical tests which can be used in portfolio decision making. Previous research up to date formulates the CTR estimation model using CPC, Rank, Impression, CVR, etc., individually or collectively as the independent variables. However, many of the variables are not controllable in keyword bidding. Only CPC and Rank can be used as decision variables in the bidding system. Classical SSA model is designed on the basic assumption that the CPC is the decision variable and CTR is the response variable. However, this classical model has so many huddles in the estimation of CTR. The main problem is the uncertainty between CPC and Rank. In keyword bid, CPC is continuously fluctuating even at the same Rank. This uncertainty usually raises questions about the credibility of CTR, along with the practical management problems. Sponsors make decisions in keyword bids under the limited information, and the strategic portfolio approach based on statistical models is necessary. In order to solve the problem in Classical SSA model, the New SSA model frame is designed on the basic assumption that Rank is the decision variable. Rank is proposed as the best decision variable in predicting the CTR in many papers. Further, most of the search engine platforms provide the options and algorithms to make it possible to bid with Rank. Sponsors can participate in the keyword bidding with Rank. Therefore, this paper tries to test the validity of this new SSA model and the applicability to construct the optimal portfolio in keyword bidding. Research process is as follows; In order to perform the optimization analysis in constructing the keyword portfolio under the New SSA model, this study proposes the criteria for categorizing the keywords, selects the representing keywords for each category, shows the non-linearity relationship, screens the scenarios for CTR and CPC estimation, selects the best fit model through Goodness-of-Fit (GOF) test, formulates the optimization models, confirms the Spillover effects, and suggests the modified optimization model reflecting Spillover and some strategic recommendations. Tests of Optimization models using these CTR/CPC estimation models are empirically performed with the objective functions of (1) maximizing CTR (CTR optimization model) and of (2) maximizing expected profit reflecting CVR (namely, CVR optimization model). Both of the CTR and CVR optimization test result show that the suggested SSA model confirms the significant improvements and this model is valid in constructing the keyword portfolio using the CTR/CPC estimation models suggested in this study. However, one critical problem is found in the CVR optimization model. Important keywords are excluded from the keyword portfolio due to the myopia of the immediate low profit at present. In order to solve this problem, Markov Chain analysis is carried out and the concept of Core Transit Keyword (CTK) and Expected Opportunity Profit (EOP) are introduced. The Revised CVR Optimization model is proposed and is tested and shows validity in constructing the portfolio. Strategic guidelines and insights are as follows; Brand keywords are usually dominant in almost every aspects of CTR, CVR, the expected profit, etc. Now, it is found that the Generic keywords are the CTK and have the spillover potentials which might increase consumers awareness and lead them to Brand keyword. That's why the Generic keyword should be focused in the keyword bidding. The contribution of the thesis is to propose the novel SSA model based on Rank as decision variable, to propose to manage the keyword portfolio by categories according to the characteristics of keywords, to propose the statistical modelling and managing based on the Rank in constructing the keyword portfolio, and to perform empirical tests and propose a new strategic guidelines to focus on the CTK and to propose the modified CVR optimization objective function reflecting the spillover effect in stead of the previous expected profit models.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.25-38
• /
• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Korean Journal of Heritage: History & Science
• /
• v.44 no.1
• /
• pp.196-221
• /
• 2011

The Royal Private Shrines or the Samyo(私廟), were dedicated to members of Choseon's royal family who could not be enshrined at the (official) Royal Ancestral Shrine, the Jongmyo(宗廟). The Samyo were constructed at the national level and were systematically managed as such. Because these private Shrines were dedicated to those who couldn't belong to the Jongmyo but were still very important, such as the ruling king's biological father or mother. The details of all royal constructions were included in the State Event Manuals, and with them, the two-dimensional layouts of the Samyo also. From the remaining "Hyunsa-gung Private Tomb Construction Layout Record(顯思宮別廟營建都監儀軌)" of 1824, which is the construction record of Gyeongwoo-gung Shrine(景祐宮) dedicated to Subin, the mother of King Sunjo(純祖), it became possible to investigate the so far unknown "The Painting of Gyeongwoo-gung Shrine", in terms of the year produced, materials used and other situational contexts. The investigation revealed that the "The Painting of Gyeongwoo-gung Shrine" is actually the "Hyunsa-gung Private Tomb Layout" produced by the Royal Construction Bureau. The bureau painted this to build Hyunsa-gung Private Shrine in a separately prepared site outside the court in 1824, according to the royal verdict to close down and move the temporary shrine inside the courtyard dedicated to Subin who had passed away in 1822. As the Construction Bureau must have also produced the Gyeongwoo-gung Shrine Layout, the painter(s) of this layout should exist among the official artists listed in the State Event Manual, but sadly, as their paintings have not survived to this day, we cannot compare their painting styles. The biggest stylistic character of the Painting of Gyeongwoo-gung Shrine is its perfect diagonal composition method and detailed and neat portrayalof the many palace buildings, just as seen in Donggwoldo(東闕圖, Painting of a panoramic view for Changdeokgung and Changgyeonggung Palaces). A well-perceiving architectural painting employs a specific point of view chosen to fit the purpose of the painting, or it can opt to the multi-viewpoint. Korean traditional architectural paintings in early ages utilized the diagonal composition method, the bird-eye viewpoint, or the multi-viewpoint. By the 18th century, detailed but also artistic architectural paintings utilizing the diagonal method are observed. In the early 19th century, the peak of such techniques is exhibited in Donggwoldo(Painting of a panoramic view for Changdeokgung and Changgyeonggung Palaces). From the perfect diagonal composition method employed and the details of the palace buildings numbering almost two hundreds, we can determine that the Painting of Gyeongwoo-gung Shrine also belongs to the same category of the highly technical architectural paintings as Donggwoldo(Painting of a panoramic view for Changdeokgung and Changgyeonggung Palaces). We can also confirm this hypothesis by comparing the painting techniques employed in these two paintings in detailthe way trees and houses are depicted, and the way ground texture is expressed, etc. The unique characteristic of the Painting of Gyeongwoo-gung Shrine is, however, that the area surrounding the central shrine building(正堂), the most important area of the shrine, is drawn using not the diagonal method but the bird-eye viewpoint with the buildings lying flat on both the left and right sides, just as seen in the "Buildings Below the Central Shrine(正堂以下諸處)" in the State Event Manual's Painting Method section. The same viewpoint method is discovered in some other concurrent paintings of common residential buildings, so it is not certain that this particular viewpoint had been a distinctive feature for shrine paintings in general. On the other hand, when the diagonalmethod pointing to the left direction is chosen, the top-left and bottom-right sections of the painting become inevitably empty. This has been the case for the Painting of Gyeongwoo-gung Shrine, but in contrast, Donggwoldo shows perfect screen composition with these empty margins filled up with different types of trees and other objects. Such difference is consistent with the different situational contexts of these two paintings: the Painting of Gyeongwoo-gung Shrine is a simple single-sheet painting, while Donggwoldo is a perfected work of painting book given an official title. Therefore, if Donggwoldo was produced to fulfill the role of depiction and documentation as well as the aesthetic purpose, contrastingly, the Painting of Gyeongwoo-gung Shrine only served the purpose of copying the circumstances of the architecture and projecting them onto the painting.

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

• Tuberculosis and Respiratory Diseases
• /
• v.45 no.4
• /
• pp.861-869
• /
• 1998

Backgrounds: The injury of a tissue results in the infalmmation, and the imflammed tissue is replaced by the normal parenchymal cells during the process of repair. But, constitutional or repetitive damage of a tissue causes the deposition of collagen resulting in the loss of its function. These lesions are found in the lung of patients with idiopathic pulmonary fibrosis, complicated fibrosis after diffuse alveolar damage (DAD) and inorganic dust-induced lung fibrosis. The tissue from lungs of patients undergoing episodes of active and/or end-stage pulmonary fibrosis shows the accumulation of inflammatory cells, such as mononuclear cells, neutrophils, mast cells and eosinophils, and fibroblast hyperplasia. In this regard, it appears that the inflammation triggers fibroblast activation and proliferation with enhanced matrix synthesis, stimulated by inflammatory mediators such as interleukin-1 (IL-1) and/or tumor necrosis factor (TNF). It has been well known that TGF-$\beta$ enhance the proliferation of fibroblasts and the production of collagen and fibronectin, and inhibit the degradation of collagen. In this regard, It is likely that TGF-$\beta$ undergoes important roles in the pathogenesis of pulmonary fibrosis. Nevertheless, this single cytokine is not the sole regulator of the pulmonary fibrotic response. It is likely that the balance of many cytokines including TGF-$\beta$, IL-1, IL-6 and TNF-$\alpha$ regulates the pathogenesis of pulmonary fibrosis. In this study, we investigate the interaction of TGF-$\beta$, IL-1$\beta$, IL-6 and TNF-$\alpha$ and their effect on the proliferation of fibroblasts. Methods: We used a human fibroblast cell line, MRC-5 (ATCC). The culture of MRC-5 was confirmed by immunofluorecent staining. First, we determined the concentration of serum in cuture medium, in which the proliferation of MRC-5 is supressed but the survival of MRC-5 is retained. Second, we measured optical density after staining the cytokine-stimulated cells with 0.5% naphthol blue black in order to detect the effect of cytokines on the proliferation of MRC-5. Result: In the medium containing 0.5% fetal calf serum, the proliferation of MRC-5 increased by 50%, and it was maintained for 6 days. IL-1$\beta$, TNF-$\alpha$ and IL-6 induced the proliferation of MRC-5 by 45%, 160% and 120%, respectively. IL-1$\beta$ and TNF-$\alpha$ enhanced TGF-$\beta$-induced proliferation of MRC-5 by 64% and 159%, but IL-6 did not affect the TGF-$\beta$-induced proliferation. And lNF-$\alpha$-induced proliferation of MRC-5 was reduced by IL-1$\beta$ in 50%. TGF-$\beta$, TNF-$\alpha$ and both induced the proliferation of MRC-5 to 89%, 135% and 222%, respectively. Conclusions: TNF-$\alpha$, TGF-$\beta$ and IL-1$\beta$, in the order of the effectiveness, showed the induction of MRC-5 proliferation of MRC-5. TNF-$\alpha$ and IL-1$\beta$ enhance the TGF-$\beta$-induced proliferation of MRC-5, but IL-6 did not have any effect TNF-$\alpha$-induced proliferation of MRC-5 is diminished by IL-1, and TNF-$\alpha$ and TGF-$\beta$ showed a additive effect.