• Information Systems Review
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• v.21 no.4
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• pp.143-156
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• 2019

Types of innovation can be categorized into simplification, information, automation, and intelligence. Intelligence is the highest level of innovation, and RPA can be seen as one of intelligence. Robotic Process Automation(RPA), a software robot with artificial intelligence, is an example of intelligence that is suited for simple, repetitive, large-scale transaction processing tasks. The RPA, which is already in operation in many companies in Korea, shows what needs to be done to naturally focus on the core tasks in a situation where the need for a strong organizational culture is increasing and the emphasis is on voluntary leadership, strong teamwork and execution, and a professional working culture. The introduction was considered naturally according to the need to find. Robotic Process Automation, or RPA, is a technology that replaces human tasks with the goal of quickly and efficiently handling structural tasks. RPA is implemented through software robots that mimic humans using software such as ERP systems or productivity tools. RPA robots are software installed on a computer and are called robots by the principle of operation. RPA is integrated throughout the IT system through the front end, unlike traditional software that communicates with other IT systems through the back end. In practice, this means that software robots use IT systems in the same way as humans, repeat the correct steps, and respond to events on the computer screen instead of communicating with the system's application programming interface(API). Designing software that mimics humans to communicate with other software can be less intuitive, but there are many advantages to this approach. First, you can integrate RPA with virtually any software you use, regardless of your openness to third-party applications. Many enterprise IT systems are proprietary because they do not have many common APIs, and their ability to communicate with other systems is severely limited, but RPA solves this problem. Second, RPA can be implemented in a very short time. Traditional software development methods, such as enterprise software integration, are relatively time consuming, but RPAs can be implemented in a relatively short period of two to four weeks. Third, automated processes through software robots can be easily modified by system users. While traditional approaches require advanced coding techniques to drastically modify how they work, RPA can be instructed by modifying relatively simple logical statements, or by modifying screen captures or graphical process charts of human-run processes. This makes RPA very versatile and flexible. This RPA is a good example of the application of digital to intelligence(D2I).

• Information Systems Review
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• v.21 no.4
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• pp.99-123
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• 2019

The software industry is a high value-added industry in the knowledge information age, and its importance is growing as it not only plays a key role in knowledge creation and utilization, but also secures global competitiveness. Among various SW available in today's business environment, Open Source Software(OSS) is rapidly expanding its activity area by not only leading software development, but also integrating with new information technology. Therefore, the purpose of this research is to empirically examine and analyze the effect of factors on the switching behavior to OSS. To accomplish the study's purpose, we suggest the research model based on "Push-Pull-Mooring" framework. This study empirically examines the two categories of antecedents for switching behavior toward OSS. The survey was conducted to employees at various firms that already switched OSS. A total of 268 responses were collected and analyzed by using the structural equational modeling. The results of this study are as follows; first, continuous maintenance cost, vender dependency, functional indifference, and SW resource inefficiency are significantly related to switch to OSS. Second, network-oriented support, testability and strategic flexibility are significantly related to switch to OSS. Finally, the results show that willingness to secures SW competitiveness has a moderating effect on the relationships between push factors and pull factor with exception of improved knowledge, and switch to OSS. The results of this study will contribute to fields related to OSS both theoretically and practically.

• Information Systems Review
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• v.19 no.2
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• pp.1-19
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• 2017

Original scripts of e-learning lectures for the CEOs of corporation S were analyzed using topic analysis, which is a text mining method. Twenty-two topics were extracted based on the keywords chosen from five-year records that ranged from 2011 to 2015. Research analysis was then conducted on various issues. Promising topics were selected through evaluation and element analysis of the members of each topic. In management and economics, members demonstrated high satisfaction and interest toward topics in marketing strategy, human resource management, and communication. Philosophy, history of war, and history demonstrated high interest and satisfaction in the field of humanities, whereas mind health showed high interest and satisfaction in the field of in lifestyle. Studies were also conducted to identify topics on the proportion of content, but these studies failed to increase member satisfaction. In the field of IT, educational content responds sensitively to change of the times, but it may not increase the interest and satisfaction of members. The present study found that content production for CEOs should draw out deep implications for value innovation through technology application instead of simply ending the technical aspect of information delivery. Previous studies classified contents superficially based on the name of content program when analyzing the status of content operation. However, text mining can derive deep content and subject classification based on the contents of unstructured data script. This approach can examine current shortages and necessary fields if the service contents of the themes are displayed by year. This study was based on data obtained from influential e-learning companies in Korea. Obtaining practical results was difficult because data were not acquired from portal sites or social networking service. The content of e-learning trends of CEOs were analyzed. Data analysis was also conducted on the intellectual interests of CEOs in each field.

• Information Systems Review
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• v.25 no.2
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• pp.145-162
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• 2023

Asset management is a complex and difficult field that requires insight into numerous variables and even human psychology. Thus, it has traditionally been the domain of professionals, and these services have been expensive to obtain. Changes are taking place in these markets, and the driving force is the digital revolution, so-called the fourth industrial revolution. Among them, the Robo-Advisor service using artificial intelligence technology is the highlight. The reason is that it is possible to popularize investment advisory services with convenient accessibility and low cost. This study aims to clarify what factors are critically important when selecting robo-advisors for service users and providers in Korea, and what perception differences exist in the selection factors between user and provider groups. The framework of the study was based on the marketing mix 4C model, and the design and analysis of the model used Delphi survey and AHP. Through the study design, 4 main criteria and 15 sub-criteria were derived, and the findings of the study are as follows. First, the importance of the four main criteria was in the order of customer needs > customer convenience > customer cost > customer communication for both groups. Second, looking at the 15 sub-criteria, it was found that investment purpose coverage, investment propensity coverage, fee level and accessibility factors were the most important. Third, when comparing between groups, the user group found that the fee level and accessibility factors were the most important, and the provider group recognized the investment purpose coverage and investment propensity coverage factors as important. This study derived useful implications in practice. First, when designing for the spread of the robo-advisor service, the basis for constructing a user-oriented system was prepared by considering the priority of importance according to the weight difference between the four main criteria and the 15 sub-criteria. In addition, the difference in priority of each sub-criteria shown in the group comparison and the cause of the sub-criteria with large weight differences were identified. In addition, it was suggested that it is very important to form a consensus to resolve the difference in perception of factors between those in charge of strategy and marketing and system development within the provider group. Academically, it is meaningful in that it is an early study that presented various perspectives and perspectives by deriving a number of robo-advisor selection factors. Through the findings of this study, it is expected that a successful user-oriented robo-advisor system can be built and spread in Korea to help users.

• Journal of Applied Biological Chemistry
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• v.66
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• pp.447-454
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• 2023

In the environment in which humans live, there are various antigens that invade the human body and interfere with humans leading a healthy life, so the immune system recognizes the antigen then removes them through a complex mechanism. Macrophages are widely distributed immune cells involved in the innate immune system, and produce various immune modulators such as inducible nitric oxide synthase-induced nitric oxide, cyclooxygenase-2 induced prostaglandin E2 and proinflammatory cytokines such as tumor necrosis factor-alpha. On the other hand, Protaetia brevitarsis seulensis larvae are a type of edible insect that have emerged as an alternative to the future food supply problem. The immuno-modulatory effect through the activation of murine macrophage RAW264.7 cell via mitogen-activated protein kinases (MAPKs)/nuclear factor-kappa B (NF-κB) signaling pathways has been reported. Based on this report, in this study, we confirmed how the expression of immune modulators induced by Protaetia brevitarsis seulensis larvae extracts in RAW264.7 cells was changed by treatment with pharmacological inhibitors of toll-like receptor 4 (TLR4), MAPKs and NF-κB signaling pathways. As a result, reduction of immune modulators was confirmed in the c-Jun N-terminal kinase (JNK) inhibitor treatment group and NF-κB inhibitor treatment group among the Protaetia brevitarsis seulensis larvae-treated RAW264.7 cell. Furthermore, in the TLR4 inhibitor-treated group, decreases in phosphorylation of JNK and NF-κB factors were confirmed in Protaetia brevitarsis seulensis larvae-treated RAW264.7 cell, as well as decreases in immune modulators. This results suggest that Protaetia brevitarsis seulensis larvae activates RAW264.7 cells by the engagement of TLR4-JNK/NF-κB signaling pathway.

• Korean Journal of Plant Resources
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• v.37 no.4
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• pp.411-422
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• 2024

Naked oat is particularly vulnerable to cold weather among cereal crops, and frequent lodging due to their long culm length. Also it is difficult to cultivate in double cropping system with rice because of late maturity in Korea. In this study, we charaterized 71 naked oat germplasms including two control varieties with agronomic traits, to select superior resources and use them for the improvement of exsiting varieties. The maturity date was May 26th for 'Joyang' and June 1st for 'Daeyang', and there were 5 resources including IT302003, which was earlier than Daeyang. In the case of culm length, the distribution ranged from 62 to 124 cm, and there were 13 resources, including IT209241, that were shorter than 'Joyang' (84 cm) and 'Daeyang' (83 cm). In correlation analysis of agronomic traits, the highest positive correlation (r=0.89) was observed between days to heading and days to maturity. In addition, culm length and spike length (r=0.72) and days to heading (r=0.50) showed a positive correlation. However, Barley yellow dwarf virus(BYDV) and grain yield (r=-0.30), lodging tolerance and liter weight (r=-0.37) showed a negative correlation. Cluster analysis, resources with similar traits such as liter weight, husk ratio, days to heading, and days to maturing were subclassified. Through this analysis, 6 resources, including IT302002 (X345-1-B4-20-1), which had short culm length, early maturity, and cold tolerance compared to 'Joyang' and 'Daeyang', were selected. Among the selected excellent resources, the avenanthramide content of the four resources was IT302002 (325.18 ㎍/g), K000010 (557.3㎍/g), K253299 (447.33 ㎍/g), and K253301 (440.49 ㎍/g), respectively, which was higher than 'Daeyang' (301.97 ㎍/g). These excellent resources will be used as breeding materials for the development of new varieties in the future.

• Journal of Environmental Impact Assessment
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• v.33 no.4
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• pp.143-154
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• 2024

Heat waves caused by climate change are rapidly increasing health damage to vulnerable groups, and to prevent this, the national, regional, and local governments are establishing climate crisis adaptation policy. A representative climate crisis adaptation policy to reduce heat wave damage is to expand the number of cooling centers. Because it is highly effective in a short period of time, most metropolitan local governments, except Jeonbuk, include the project as an adaptation policy. However, the criteria for selecting a cooling centers are different depending on the budget and non-budget, so the utilization rate and effectiveness of the cooling centers are all different. Therefore, in this study, we developed logistic regression models that can predict and evaluate areas with a high probability of expanding cooling centers in order to implement adaptation policy in local governments. In Incheon Metropolitan City, which consists of various heat wave-vulnerable environments due to the coexistence of the old city and the new city, a logistic model was developed to predict areas where heat waves can be cooling centered by dividing it into Ganghwa·Ongjin-gun and other regions, taking into account socioeconomic and environmental differences. As a result of the study, the statistical model for the Ganghwa·Ogjin-gun region showed that the higher the ground surface temperature and the more and more the number of elderly people over 65 years old, the higher the possibility of location of cooling centers, and the prediction accuracy was about 80.93%. The developed logistic regression model can predict and evaluate areas with a high potential as cooling centers by considering regional environmental and social characteristics, and is expected to be used for priority selection and management when designating additional cooling centers in the future.

• Journal of the Korean Society of Radiology
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• v.18 no.5
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• pp.531-540
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• 2024

Recently, research and development on automatic diagnosis solutions in the medical imaging field using deep learning are actively underway. In this study, we sought to find a fast and accurate classification deep learning modeling for classification of pneumonia in chest images using Inception V3, a deep learning model based on a convolutional artificial neural network. For this reason, after applying the optimization algorithms AdaGrad, RMS Prop, and Adam to deep learning modeling, deep learning modeling was implemented by selectively applying learning rates of 0.01 and 0.001, and then the performance of chest X-ray image pneumonia classification was compared and evaluated. As a result of the study, in verification modeling that can evaluate the performance of the classification model and the learning state of the artificial neural network, it was found that the performance of deep learning modeling for classification of the presence or absence of pneumonia in chest X-ray images was the best when applying Adam as the optimization algorithm with a learning rate of 0.001. I was able to. And in the case of Adam, which is mainly applied as an optimization algorithm when designing deep learning modeling, it showed excellent performance and excellent metric results when selectively applying learning rates of 0.01 and 0.001. In the metric evaluation of test modeling, AdaGrad, which applied a learning rate of 0.1, showed the best results. Based on these results, when designing deep learning modeling for binary-based medical image classification, in order to expect quick and accurate performance, a learning rate of 0.01 is preferentially applied when applying Adam as an optimization algorithm, and a learning rate of 0.01 is preferentially applied when applying AdaGrad. I recommend doing this. In addition, it is expected that the results of this study will be presented as basic data during similar research in the future, and it is expected to be used as useful data in the health and bio industries for the purpose of automatic diagnosis of medical images using deep learning.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.2
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• pp.22-27
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• 2014

Purpose There is the recent PET/CT scan in tendency that use low dose to reduce patient's exposure along with development of equipments. We diminished $^{18}F$-FDG dose of patient to reduce patient's exposure after setting up GE Discovery 690 PET/CT scanner (GE Healthcare, Milwaukee, USA) establishment at this hospital in 2011. Accordingly, We evaluate acquisition time per proper bed by change of infusion dose to maintain quality of image of PET/CT scanner. Materials and Methods We inserted Air, Teflon, hot cylinder in NEMA NU2-1994 phantom and maintained radioactivity concentration based on the ratio 4:1 of hot cylinder and back ground activity and increased hot cylinder's concentration to 3, 4.3, 5.5, 6.7 MBq/kg, after acquisition image as increase acquisition time per bed to 30 seconds, 1 minute, 1 minute 30 seconds, 2 minute, 2 minutes 30 seconds, 3 minutes, 3 minutes 30 seconds, 4 minutes, 4 minutes 30 seconds, 5 minutes, 5 minutes 30 seconds, 10 minutes, 20 minutes, and 30 minutes, ROI was set up on hot cylinder and back radioactivity region. We computated standard deviation of Signal to Noise Ratio (SNR) and BKG (Background), compared with hot cylinder's concentration and change by acquisition time per bed, after measured Standard Uptake Value maximum ($SUV_{max}$). Also, we compared each standard deviation of $SUV_{max}$, SNR, BKG following in change of inspection waiting time (15minutes and 1 hour) by using 4.3 MBq phantom. Results The radioactive concentration per unit mass was increased to 3, 4.3, 5.5, 6.7 MBqs. And when we increased time/bed of each concentration from 1 minute 30 seconds to 30 minutes, we found that the $SUV_{max}$ of hot cylinder acquisition time per bed changed seriously according to each radioactive concentration in up to 18.3 to at least 7.3 from 30 seconds to 2 minutes. On the other side, that displayed changelessly at least 5.6 in up to 8 from 2 minutes 30 seconds to 30 minutes. SNR by radioactive change per unit mass was fixed to up to 0.49 in at least 0.41 in 3 MBqs and accroding as acquisition time per bed increased, rose to up to 0.59, 0.54 in each at least 0.23, 0.39 in 4.3 MBqs and in 5.5 MBqs. It was high to up to 0.59 from 30 seconds in radioactivity concentration 6.7 MBqs, but kept fixed from 0.43 to 0.53. Standard deviation of BKG (Background) was low from 0.38 to 0.06 in 3 MBqs and from 2 minutes 30 seconds after, low from 0.38 to 0 in 4.3 MBqs and 5.5 MBqs from 1 minute 30 seconds after, low from 0.33 to 0.05 in 6.7 MBqs at all section from 30 seconds to 30 minutes. In result that was changed the inspection waiting time to 15 minutes and 1 hour by 4.3 MBq phantoms, $SUV_{max}$ represented each other fixed values from 2 minutes 30 seconds of acquisition time per bed and SNR shown similar values from 1 minute 30 seconds. Conclusion As shown in the above, when we increased radioactive concentration per unit mass by 3, 4.3, 5.5, 6.7 MBqs, the values of $SUV_{max}$ and SNR was kept changelessly each other more than 2 minutes 30 seconds of acquisition time per bed. In the same way, in the change of inspection waiting time (15 minutes and 1 hour), we could find that the values of $SUV_{max}$ and SNR was kept changelessly each other more than 2 minutes 30 seconds of acquisition time per bed. In the result of this NEMA NU2-1994 phantom experiment, we found that the minimum acquisition time per bed was 2 minutes 30 seconds for evaluating values of fixed $SUV_{max}$ and SNR even in change of inserting radioactive concentration. However, this acquisition time can be different according to features and qualities of equipment.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.2
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• pp.54-61
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• 2016

Purpose Precocious Puberty is defined as the development of secondary sexual characteristics in girls younger than 8 years, and boys 9 years. Cause premature closure of the epiphysis is a disease that eventually decreases the final adult height. In this study, we retrospectively analyzed to evaluate the diagnostic difference the GnRH (Gonado-tropin-releasing Hormone) stimulation test results with medical records of precocious puberty in girls. Materials and Methods From February 2015 to December 2015 it was enrolled in the girls 118 people who visited the Seoul National University Bundang Hospital, Pediatrics, Endocrinology Internal Medicine. True precocious puberty group (n=57), early puberty group (n=39), were divided into Premature thelarche (n=22) group. A Tanner stage, chronological age, bone age, height, body weight for each group was determined by examining the mean${\pm}$standard deviation. GnRH test result was compared LH (Basal, 30 min, 45 min, 60 min), FSH (Basal, 30 min, 60 min) for each group, Each group LH, FSH Peak value distribution, the mean${\pm}$standard deviation was calculated for the peak LH/LH basal ratio, peak LH/Peak FSH ratio. The significance probability (P-value) between the value of each third group was determined. Results The average height of the true precocious puberty group $131{\pm}14.85$, the mean weight was $28.80{\pm}4.93$, the average chronological age $7.1{\pm}0.81$, the mean bone age was $9.9{\pm}0.9$, The average height of early puberty group was $134{\pm}5.10$, the average weight $28.50{\pm}4.43$, the average chronological age $8.05{\pm}0.03$, the mean bone age was $10.0{\pm}0.62$, The average height of Premature thelarche $129{\pm}6,01$, the average weight was $28.65{\pm}5.98$, the average chronological age $7.02{\pm}0.58$, the mean bone age was $8.04{\pm}1.29$. There was no significant difference when compared to the height and weight. There was a significant difference between the groups in the chronologic age and bone age difference (P <0.0002) True precocious puberty group showed peak LH levels at 30'(82.5%), 45'(12.3%), 60'(5.3%), in Peak FSH 30'(8.8%), 60'(91.2%). Early Puberty group showed high values in Peak LH at 30'(79.5%), 45'(17.9%), 60'(2.6%), in peak FSH levels at 30'(7.7%), 60'(92.32%). In Premature thelarche Group it showed the Peak LH levels at 30'(30%), 45'(59%), 60'(9.09%), Peak FSH levels at 30'(0%) 60'(100%). When compared with the The Peak LH/basal LH ratio, True precocious puberty group was $19.09{\pm}17.15$, early puberty group was $15.23{\pm}10.88$, Premature thelarche group showed significant differences between the three groups as $4.93{\pm}4.36$.(P <0.0001) LH Peak/FSH Peak ratio, true precocious puberty group was $1.222{\pm}0.77$, early puberty group was $1.34{\pm}1.23$, Premature thelarche group showed significant differences between the three groups as $0.3{\pm}0.09$(P <0.0001) Conclusion In order to diagnose the true precocious puberty have a diagnostic value when the LH peak after GnRH stimulation is increased by more than two to three times compared to baseline or a predetermined level or more than 5~10 IU/L increases. GnRH Test is a test for a long time and the patient discomfort due to repeated blood sampling, but the hypothalamus-pituitary gland- gonad axis activity evaluate and is the most basic accurate test in the differential diagnosis of precocious puberty disorders.