• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.71-90
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• 2020

Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.

• Journal of Korean society of Dental Hygiene
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• v.8 no.4
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• pp.19-30
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• 2008

This study reached the following conclusions as a result of carrying out the questionnaire survey of self-descriptions for the satisfaction after the citizens of Daejon uses the dental clinics, in order to identify the factors of satisfaction to the medical services of such dental clinics to be utilized in the patient management by dental hygienists, provide the basic data to provide the medical services desired by patients. 1. 43.9% men responded to the facilities and 56.1% women to the atmosphere for the standards of selection of dental clinics by general characteristic, and the college graduates or more to the kindness (38.2%), high-school graduates (43.2%) and middle-school graduates (25.9%) or less to the close distance for the level of educational attainment (p=0.009), which was meant to have a statistical significance. 2. The execution of reservation system for the dental clinics showed 54.7%, the reserved time was observed upon the execution of such reservation system, the dental clinics where they practice such system were 40.6%, and the confirmation methods was done through the telephone with 62.5%. 3. The experience of fear upon the dental treatment showed 74.6%. The type of fear showed the machine sound (48.7%) for men and cry of others for women (70.8%) at the highest. 70% of those under 30 at the age responded to the sharp instruments at the highest. 83.3% of Yousung-gu showed the highest by responding to the cry of others for the residential areas. The statistically significant difference was shown in both the age and residential area (p=0.000). 4. Women showed higher in the distribution of gender for the sterilization of instruments for the external satisfaction of dental clinics(p=0.000) and those under 30 at the age showed the highest with 2.98${\pm}$0.95(p=0.001). Seo-gu (3.48${\pm}$0.77) was the highest for the residential area (p=0.000), and there was statistically significant differences in the gender, age and residential area. 5. Men showed higher satisfaction than women in the clean state and the statistically significant differences were shown (p=0.000) at the age as the high satisfaction was shown for those under 30 at the age (2.35${\pm}$0.79), those having the income not less than 10 million won and not more than 20 million won (2.43${\pm}$0.78), and Seo-gu (2.63 ${\pm}$0.69) for the residential area. 6. For the internal satisfaction of dental clinic by users for the medical services in the dental clinics, 61.1% women responded to no in the ability of solving the inconvenience in the service process, and showed low ability of solving the inconvenience from 30 at the age (26.2%) and by responding to Dong-gu (22.1%) for the residential area, showing statically significant differences(p=0.000). For the re-use of dental clinics, 46.6% men (p=0.043) for the gender, 24.3% under 30 at the age and 22.9% of Dong-gu for the residential area responded to the re-use, showing statistically significant differences for the gender and residential area (p=0.000). 7. The dissatisfaction showed a high rate of 69.5% for the satisfaction to the medical services of dental clinics. 46.2% men responded to the pain and women to the feeling of foreign substance for the reason of dissatisfaction while those under 30 at the age showed 55.6% for others, those between 50 and 59 41.7% for the feeling of foreign substance. 86.3% carried out the education for cautions after the treatments and most people turned out that they do not carry out the continuous health management of mouth as 20.5% responded to that they carry out such health management.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2551-2562
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• 2013

Since 2006, an Intelligent Excavation Robot which automatically performs the earth-work without operator has been developed in Korea. The technologies for automatically recognizing the terrain of work environment and detecting the objects such as obstacles or dump trucks are essential for its work quality and safety. In several countries, terrestrial 3D laser scanner and stereo vision camera have been used to model the local area around workspace of the automated construction equipment. However, these attempts have some problems that require high cost to make the sensor system or long processing time to eliminate the noise from 3D model outcome. The objectives of this study are to analyze the advantages of the existing 3D modeling sensors and to examine the applicability for practical use by using Analytic Hierarchical Process(AHP). In this study, 3D modeling quality and accuracy of modeling sensors were tested at the real earth-work environment.

• Journal of the HCI Society of Korea
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• v.8 no.2
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• pp.21-27
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• 2013

Recently, the use of floating hologram has increased in many different aspects, such as exhibitions, education, advertisements, and so on. Especially, the floating hologram that makes use of half-mirror is widely used. Nevertheless, half-mirror, unfortunately, cannot lead users to the perfect three dimensional hologram experience. Even though it can make the vision look to be up on the air, it does not have the capacity to display itself up on the air, which is the ultimate goal of hologram. In addition, it looks inconsistent when a real object is located behind the half-mirror in order to show the convergence of the two (object and the half-mirror). In this paper, we did the study on comparison of 3D space perception for the stereoscopic AR holography. At first, we applied stereoscopic technology to the half-mirror hologram system for the accurate and realistic AR environment. Then, the users can feel as if the real 3D object behind half-mirror and the reflected virtual image are converged much better in the 3D space. Furthermore, by using depth camera, the location and direction of graphics can be controlled to change depending on the user's point of view. This is the effective way to produce augmented stereoscopic images simply and accurately through half-mirror film without any additional devices. What we saw from the user test were applying 3D images and user interaction leads the users to have 3D spatial awareness and realism more effectively and accurately.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.433-440
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• 2018

As government research and development projects become more important, such as the creation of future-oriented growth engines and expansion of budgets, the future vision of R&D is presented through paradigm shifts such as efficiency, investment direction and strategy. On the other hand, research and interest in sanctions are poor, and this paper examines legal grounds, comparative analysis of laws, and cases outside the country, draws implications for domestic applications, have. In addition, we will contribute to the prevention of damages caused by neglect, or the transparency of the execution of research funds. This study was conducted by comparing the characteristics of government R&D and sanctions with the sanctions for the top three R&D investment related SMEs. In Korea, starting with the introduction of sanctions in 2001, the moral hazard of research and development has been prevented through the cumulative violation of aggravation, expansion of the period of restriction of participation, and the introduction of a strikeout system. Nevertheless, fraudulent use of business expenses is constantly being detected. In order to ensure maximum autonomy and stronger responsibility than strong institutions, the willingness of the researchers to execute transparent business expenses, the moral approach to public resources, Precedence of recognition conversion is important.

• Journal of Biomedical Engineering Research
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• v.28 no.5
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• pp.590-600
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• 2007

We performed experimental studies on the muscle activities in the lower limbs for the different movement patterns on an unstable platform. A training system for postural control using an unstable platform that we previously developed was applied for the experiments. This unstable platform provides 360 degrees of movement allowing for training of posture in various directions and provides simultaneous excitations to visual sensory, somatic sensation and vestibular organs. Compare with the stable platform, keeping body balance on the unstable platform requests more effective sensation from vision, vestibular sense and somatic sense. Especially, the somatosensory inputs from the muscle proprioceptors and muscle force are crucial. To study the muscle activities for the different movement patterns and find the best training method for improving the ability of postural control through training and improving the lower extremity muscular strength, fifteen young healthy participants went through trainings and experiments. The participants were instructed to move the center of pressure following the appointed movement pattern while standing on the unstable platform. The electromyographies of the muscles in the lower limbs were recorded and analyzed in the time and the frequency domain. Our experimental results showed the significant differences in muscle activities for the different movement patterns. Especially, the spectral energy of electromyography signals in muscle for the movement pattern in anterior-posterior direction was significantly higher than those occurred in the other patterns. The muscles in the lower leg, especially tibialis anterior and gastrocnemius were more activated compared to the others for controlling the balance of body on the unstable platform. The experimental results suggest that, through the choice of different movement pattern, the training for lower extremity strength could be performed on specific muscles in different intensity. And, the ability of postural control could be improved by the training for lower extremity strength.

• Journal of KIISE:Software and Applications
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• v.36 no.4
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• pp.253-260
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• 2009

Many algorithms for computer vision and pattern recognition have recently been implemented on GPU (graphic processing unit) for faster computational times. However, the implementation has two problems. First, the programmer should master the fundamentals of the graphics shading languages that require the prior knowledge on computer graphics. Second, in a job that needs much cooperation between CPU and GPU, which is usual in image processing and pattern recognition contrary to the graphic area, CPU should generate raw feature data for GPU processing as much as possible to effectively utilize GPU performance. This paper proposes more quick and efficient implementation of neural networks on both GPU and multi-core CPU. We use CUDA (compute unified device architecture) that can be easily programmed due to its simple C language-like style instead of GPU to solve the first problem. Moreover, OpenMP (Open Multi-Processing) is used to concurrently process multiple data with single instruction on multi-core CPU, which results in effectively utilizing the memories of GPU. In the experiments, we implemented neural networks-based text extraction system using the proposed architecture, and the computational times showed about 15 times faster than implementation on only GPU without OpenMP.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.253-263
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• 2018

Textile fashion industry is a core foundation industry, having the majority of companies with 10 or more workers, in Northern Gyeonggi Province. however the industry is mostly comprised of small unit-stream enterprises, orders are greatly reduced due to lately accelerated overseas expansion of medium/large-sized vendors and the growth-inhibiting vicious circle has being set in, as this situation causes the reduction of investment. For resolving the problems, this study proposes required political factors and concrete policy proposals by designing AHP research model(4 layers and 36 elements), based on grasp of the transitional aspect of industrial scale and business environment through analysis of various industrial statistics, preceding research such as related literature search and (industrial/academic/R&D/government) specialist opinion investigation, and then calculating relative importance and priority of each factor(element) within each layer. And for raising usefulness and availability of the research result by concretely suggesting the vision, strategies, core tasks and detailed projects in which the research model and deduced result are reflected.

• BMB Reports
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• v.53 no.8
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• pp.400-412
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• 2020

The world has witnessed unimaginable damage from the coronavirus disease-19 (COVID-19) pandemic. Because the pandemic is growing rapidly, it is important to consider diverse treatment options to effectively treat people worldwide. Since the immune system is at the hub of the infection, it is essential to regulate the dynamic balance in order to prevent the overexaggerated immune responses that subsequently result in multiorgan damage. The use of stem cells as treatment options has gained tremendous momentum in the past decade. The revolutionary measures in science have brought to the world mesenchymal stem cells (MSCs) and MSC-derived exosomes (MSC-Exo) as therapeutic opportunities for various diseases. The MSCs and MSC-Exos have immunomodulatory functions; they can be used as therapy to strike a balance in the immune cells of patients with COVID-19. In this review, we discuss the basics of the cytokine storm in COVID-19, MSCs, and MSC-derived exosomes and the potential and stem-cell-based ongoing clinical trials for COVID-19.