• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.143-174
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• 2023

With the development of deep learning technologies, Artificial Intelligence powered Optical Character Recognition (AI-OCR) has evolved to read multiple languages from various forms of images accurately. For the financial industry, where a large number of diverse documents are processed through manpower, the potential for using AI-OCR is great. In this study, we present a configuration and a design of an AI-OCR modality for use in the financial industry and discuss the platform construction with application cases. Since the use of financial domain data is prohibited under the Personal Information Protection Act, we developed a deep learning-based data generation approach and used it to train the AI-OCR models. The AI-OCR models are trained for image preprocessing, text recognition, and language processing and are configured as a microservice architected platform to process a broad variety of documents. We have demonstrated the AI-OCR platform by applying it to financial domain tasks of document sorting, document verification, and typing assistance The demonstrations confirm the increasing work efficiency and conveniences.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.287-310
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• 2022

Companies' interest in developing AI-based intelligent new products is increasing. Recently, the main concern of companies is to innovate customer experience and create new values by developing new products through the effective use of Artificial intelligence technology. However, due to the nature of products based on radical technologies such as artificial intelligence, intelligent products differ from existing products and development methods, so it is clear that there is a limitation to applying the existing development methodology as it is. This study proposes a new research method based on KANO-TOPSIS for the successful development of AI-based intelligent new products by using car voice assistants as an example. Using the KANO model, select and evaluate functions that customers think are necessary for new products, and use the TOPSIS method to derives priorities by finding the importance of functions that customers need. For the analysis, major categories such as vehicle condition check and function control elements, driving-related elements, characteristics of voice assistant itself, infotainment elements, and daily life support elements were selected and customer demand attributes were subdivided. As a result of the analysis, high recognition accuracy should be considered as a top priority in the development of car voice assistants. Infotainment elements that provide customized content based on driver's biometric information and usage habits showed lower priorities than expected, while functions related to driver safety such as vehicle condition notification, driving assistance, and security, also showed as the functions that should be developed preferentially. This study is meaningful in that it presented a new product development methodology suitable for the characteristics of AI-based intelligent new products with innovative characteristics through an excellent model combining KANO and TOPSIS.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• Journal of Radiation Protection and Research
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• v.41 no.1
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• pp.71-79
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• 2016

Background: It is necessary to analyze radioactivity of naturally occurring radioactive materials (NORM) in products to ensure radiological safety required by Natural Radiation Safety Management Act. The pretreatments for the existing analysis methods require high technology and time. Such destructive pretreatments including grinding and dissolution of samples make impossible to reuse products. We developed a rapid and simple procedure of radioactivity analysis for thorium series in the products containing NORM. Materials and Methods: The developed method requires non-destructive or minimized pretreatment. Radioactivity of the product without pretreatment is initially measured using gamma spectroscopy and then the measured radioactivity is adjusted by considering material composition, mass density, and geometrical shape of the product. The radioactivity adjustment can be made using scaling factors, which is derived by radiation transport Monte Carlo simulation. Necklace, bracelet, male health care product, and tile for health mat were selected as representative products for this study. The products are commonly used by the public and directly contacted with human body and thus resulting in high radiation exposure to the user. Results and Discussion: The scaling factors were derived using MCNPX code and the values ranged from 0.31 to 0.47. If radioactivity of the products is measured without pretreatment, the thorium series may be overestimated by up to 2.8 times. If scaling factors are applied, the difference in radioactivity estimates are reduced to 3-24%. Conclusion : The developed procedure in this study can be used for other products with various materials and shapes and thus ensuring radiological safety.

• Journal of Chest Surgery
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• v.35 no.1
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• pp.1-10
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• 2002

Background: Despite the relatively high mortality rates in the chronic heart failure model induced by coronary artery ligation are relatively high, this model has been a subject of continuos research because of its clinical correlation. Chronic heart failure model of large-sized animals is very useful to analyse mechanical or biological effects on circulatory system which is difficult in small-sized animals. The purpose of this study is to establish the heart failure model by coronary artery ligation in sheep. Material and Method: Among 9 Corridale sheep, the homonymous artery and the diagonal branch were ligated simultaneously in 2 sheep and remaining 7 sheep were assigned to successive ligation of both arteries at an interval of 1 hour. Both coronary arteries were ligated from the point 40% proximal to the apex of the heart. Hemodynamic and echocardiographic parameters were analyzed before the ligation of the coronary artery, after the ligation of the homonymous artery, and after additional ligation of the diagonal branch. The experimental animals were sacrificed after 2 or 3 months of growth and histopathologic studies were performed Result: Immediate postoperative death occurred in the 2 sheep that had received simultaneous ligation of the homonymous artery and diagonal branch. On the other hand, all the 7 sheep that were lifated in succession were survived up to 3 months. Arterial pressure was sifnificantly decreased immediately after ligation of the homonymous artery(p<0.05), and the cardiac output was decreased and pulmonary capillary wedge pressure was increased after further ligation of the diagonal branch(p<0.05). Central venous pressure, pulmonary artery pressure, pulmonary capillary wedge pressure, left ventricular end-diastolic dimension and end-systolic dimension were markedly increased 3 months after ligation of coronary arteries. Anteroseptal akinesia or dyskinesia was developed after the ligation of coronary arteries. Histopathologic study revealed we]1-demarcated ischemic area of fibrosis. Conclusion: Using methods of successive ligation of the homonymous artery and diagonal branch, chronic heart failure model could be reliably established in sheep.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.31 no.1
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• pp.98-107
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• 2013

Big and old trees in the scenic spots with the attributes of remote villas are vulnerable to man-made damages and very sensitive to the external environment such as soil conditions, so the corresponding management plans are required. Thus this study has been conducted to survey the big and old trees in the scenic remote villas and suggest the ideal management plans. The results can be summarized as follows. First, regarding the tree heath above the ground, transformation of tree, death of branches, and death of barks are closely related to tree vigor. Particularly, the areas receiving many visitors require prompt countermeasures against the dried and dead tress above the ground and the areas in which dried and dead tress occurred and also the safety measures for the visitors and facilities. Second, regarding the soil environment, visitor traffic is closely related to the tree vigor. In 15 remote villa gardens, 64% of trees are exposed to heavy traffic and the tree vigor has declined due to an increase of visitor. Thus, there is a need to give positive consideration the installation of the complementary facilities and the plantation of herbal plants in the congested areas to form the ground surface that can tolerate the heavy visitor traffic. Third, remote gardens are in general located adjacent to ponds and mountain streams and thus the trees in the waterfront areas require the prompt countermeasures against the decline of growth due to the excess-moisture in the soil. Further the blockage of the sewage system due to the heavy rains dampens the surrounding soil, which results in lethal damages to the trees. Thus, there is a need of the maintenance of the waterfront areas and sewage system before and after the rainy season. In addition, there is a need to establish medium-long term management polices through the recognition of the importance of the main trees of remote villa gardens in scenic spots and prepare the tree management manual depending on the attributes of the corresponding areas. I strongly suggest making manuals for the systematic management as well as the extensive PR activities and education for the preservation of tress on a long-term basis; and furthermore securing the budget and manpower for the research and development of a systematic management system.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.107-120
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• 2017

There are many wildfire risk indices worldwide, but objective comparisons between such various wildfire risk indices and surface dryness indices have not been conducted for the wildfire cases in Korea. This paper describes a sensitivity analysis on the wildfire risk indices and surface dryness indices for Korea using LDAPS(Local Analysis and Prediction System) meteorological dataset on a 1.5-km grid and MODIS(Moderate-resolution Imaging Spectroradiometer) satellite images on a 1-km grid. We analyzed the meteorology-based wildfire risk indices such as the Australian FFDI(forest fire danger index), the Canadian FFMC(fine fuel moisture code), the American HI(Haines index), and the academically presented MNI(modified Nesterov index). Also we examined the satellite-based surface dryness indices such as NDDI(normalized difference drought index) and TVDI(temperature vegetation dryness index). As a result of the comparisons between the six indices regarding 120 wildfire cases with the area damaged over 1ha during the period between January 2013 and May 2017, we found that the FFDI and FFMC showed a good predictability for most wildfire cases but the MNI and TVDI were not suitable for Korea. The NDDI can be used as a proxy parameter for wildfire risk because its average CDF(cumulative distribution function) scores were stably high irrespective of fire size. The indices tested in this paper should be carefully chosen and used in an integrated way so that they can contribute to wildfire forecasting in Korea.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.109-135
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• 2021

his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.

• The Korean Journal of Archival Studies
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• no.55
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• pp.39-71
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• 2018

The purpose of this study is to examine the reality of the records management of the National Assembly members and suggest a desirable alternative. Until the Public Records Management Act was enacted in 1999, the level of the records management in the National Assembly was not beyond that of the document management in both the administration and the legislature. Rather, the National Assembly has maintained a records management tradition that systematically manages the minutes and bills since the Constitutional Assembly. After the Act was legislated in 2000, the National Assembly Records Management Regulation was enacted and enforced, and the Archives was established in the form of a subsidiary organ of the Secretariat of the National Assembly, even though its establishment is not obligatory. In addition, for the first time, an archivist was assigned as a records and archives researcher in Korea, whose role is to respond quickly in accordance with the records schedule of the National Assembly, making its service faster than that of the administration. However, the power of the records management of the National Assembly Archives at the time of the Secretariat of the National Assembly was greatly reduced, so the revision of the regulations in accordance with the revised Act in 2007 was not completed until 2011. In the case of the National Assembly, the direct influence of the executive branch was insignificant. As the National Assembly had little direct influence on the administration, it had little positive influence on records management innovation under Roh Moo-Hyun Administration. Even within the National Assembly, the records management observed by its members is insignificant both in practice and in theory. As the National Assembly members are excluded from the Act, there is no legal basis to enforce a records management method upon them. In this study, we analyze the records management problem of the National Assembly members, which mainly concerns the National Assembly records management plan established in the National Archives. Moreover, this study proposes three kinds of records management methods for the National Assembly members, namely, the legislation and revision of regulations, the records management consulting of the National Assembly members, and the transfer of the dataset of administrative information systems and websites.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.436-445
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• 2023

Methane (CH₄) emissions from rice paddies are mainly observed using the closed chamber method or the eddy covariance method. In this study, a new observation technique combining a portable gas analyzer (Model LI-7810, LI-COR, Inc., USA) and an automatic opening/closing chamber (Model Smart Chamber, LI-COR, Inc., USA) was introduced based on the strengths and weaknesses of the existing measurement methods. A cylindrical collar was manufactured according to the maximum growth height of rice and used as an auxiliary measurement tool. All types of measured data can be monitored in real time, and CH₄ flux is also calculated simultaneously during the measurement. After the measurement is completed, all the related data can be checked using the software called 'SoilFluxPro'. The biggest advantage of the new observation technique is that time-series changes in greenhouse gas concentrations can be immediately confirmed in the field. It can also be applied to small areas with various treatment conditions, and it is simpler to use and requires less effort for installation and maintenance than the eddy covariance system. However, there are also disadvantages in that the observation system is still expensive, requires specialized knowledge to operate, and requires a lot of manpower to install multiple collars in various observation areas and travel around them to take measurements. It is expected that the new observation technique can make a significant contribution to understanding the CH₄ emission pathways from rice paddies and quantifying the emissions from those pathways.