• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.97-103
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• 2018

In oriental paintings, there is Luo-kuan that expressed in a single picture by compressing the artist's information. Such Luo-kuan includes various information such as the title of the work or the name of the artist. Therefore, information about Luo-kuan is considered important to those who collect or enjoy oriental paintings. However, most of the letters in the Luo-kuan are difficult kanji, kanzai, or various shapes, so it is difficult for the ordinary people to interpret. In this paper, we developed an Luo-kuan search application to easily check the information of the Luo-kuan. The application uses a search algorithm that analyzes the captured Luo-kuan image and sends it to the server to output information about the Luo-kuan candidates that are most similar to the Luo-kuan images taken from the database in the server. We also compared and analyzed the accuracy of the algorithm based on 170 Luo-kuan data in order to find out the ranking of the Luo-kuan that matched the Luo-kuan among the candidates. Accuracy Analysis Experimental Results The accuracy of the search algorithm of this application is confirmed to be about 90%, and it is anticipated that it will be possible to develop a platform to automatically analyze and search images in a big data environment by supplementing the optimizing algorithm and multi-threading algorithm.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.23-31
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• 2009

The border of the shorelines in a nation is an important factor in determining the border of a national territory, but Korea's shorelines are rapidly changing due to the recent rise in sea level from global warming and growth-centered economic policy over the decades of years. This research was done centering on the areas having well-preserved shorelines as they naturally are and other areas having damaged shorelines in their vicinities due to artificial structures at the two beaches located at the neighboring areas and having mutually homogeneous ocean conditions with each other. First, this research derived the shorelines using the aerial photographies taken from 1947 until 2007 and revised the tidal levels sounding data obtained from a hydrographical survey automation system consisting of Echosounder[Echotrac 3100] and Differential Global Positioning System[Beacon]by using topographical data and ships on land obtained by applying post-processing Kinematic GPS measuring method. In addition, this research evaluated the changes and dimensional variations for the last 60 years by dividing these determined shorelines into 5 sections. As a result, the Haewundae Beach showed a total of 29% decrease rate in dimension as of the year 2007 in comparison with the year 1947 due to a rapid dimensional decline centering on its west areas, while the dimension of the Gwanganri Beach showed an increase in its dimension amounting to a total of 69% due to the decrease in flow velocity by artificial structures built on both ends of the beach-forming accumulation; thus, it was found that there existed a big difference in deposition & accumulation tendency depending on neighboring environment in spite of the homogeneous ocean conditions.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.8
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• pp.359-368
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• 2017

What is the term "intelligence information society", which is a term that has been continuously discussed recently? This means that the automation beyond the limits of human ability in the whole societies based on intelligent information technology is a universalized social future. In particular, it is a concept that minimizes human intervention and continuously pursues evolution to data (or big data) -based automation. For example, autonomous automation is constantly aiming at unmanned vehicles with artificial intelligence as a key element. However, until now, intelligent information research has focused on the intelligence itself and has made an effort to improve intelligence logic and replace human brain and intelligence. On the other hand, in order to replace the human labor force, we have continued to make efforts to replace workers with robots by analyzing the working principles of workers and developing optimized simple logic. This study proposes important strategies and directions to implement intelligent information education policy and intelligent information technology research strategy by suggesting access strategy, education method and detailed policy road map for intelligent information technology research strategy and educational service. In particular, we propose a phased approach to intelligent information education such as basic intelligence education, intelligent content education, and intelligent application education. In addition, we propose education policy plan for the improvement of intelligent information technology, intelligent education contents, and intelligent education system as an important factor for success and failure of the 4th industrial revolution, which is centered on intelligence and automation.

• Journal of Korea Entertainment Industry Association
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• v.15 no.2
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• pp.123-135
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• 2021

The data processing of this study is focused on keywords related to 'Corona 19 and professional baseball' and 'Corona 19 and professional baseball no spectators', using text mining and social network analysis of textom program to identify problems and view quality. It was used to set the variable of For quantitative analysis, a questionnaire on viewing quality was constructed, and out of 270 survey respondents, 250 questionnaires were used for the final study. As a tool for securing the validity and reliability of the questionnaire, exploratory factor analysis and reliability analysis were conducted, and IPA analysis (importance-satisfaction) was conducted based on the questionnaire that secured validity and reliability, and the results and strategies were presented. As a result of IPA analysis, factors related to the image (image composition, image coloration, image clarity, image enlargement and composition, high-quality image) were found in the first quadrant, and the second quadrant was the game situation (support team game level, support player game level, star). Player discovery, competition with rival teams), game information (match schedule information, player information check, team performance and player performance, game information), interaction (consensus with the supporting team), and some factors appeared. The factors of commentator (baseball-related knowledge, communication ability, pronunciation and voice, use of standard language, introduction of game-related information) and interaction (real-time communication with the front desk, sympathy with viewers, information exchange such as chatting) appeared.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.79-93
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• 2015

With the rapid development of information technology, the ways of usage have changed drastically. The ways and efficiency of traditional service application to data processing already could not satisfy the requirements of modern users. Nowadays, users have already understood the importance of data. Therefore, the processing and saving of big data have become the main research of the Internet service company. In China, with the rise and explosion of 115 Cloud leads to other technology companies have began to join the battle of cloud services market. Although currently Chinese cloud services are still mainly dominated by cloud storage service, the series of service contents based on cloud storage service have been affirmed by users, and users willing to try these new ways of services. Thus, how to let users to keep using cloud services has become a topic that worth for exploring and researching. The academia often uses the TAM model with statistical analysis to analyze and check the attitude of users in using the system. However, the basic TAM model obviously already could not satisfy the increasing scale of system. Therefore, the appropriate expansion and adjustment to the TAM model (i. e. TAM2 or TAM3) are very necessary. This study has used the status of Chinese internet users and the related researches in other areas in order to expand and improve the TAM model by adding the brand influence, hardware environment and external environments to fulfill the purpose of this study. Based on the research model, the questionnaires were developed and online survey was conducted targeting the cloud services users of four Chinese main cities. Data were obtained from 210 respondents were used for analysis to validate the research model. The analysis results show that the external factors which are service contents, and brand influence have a positive influence to perceived usefulness and perceived ease of use. However, the external factor hardware environment only has a positive influence to the factor of perceived ease of use. Furthermore, the perceived security factor that is influenced by brand influence has a positive influence persistent intention to use. Persistent intention to use also was influenced by the perceived usefulness and persistent intention to use was influenced by the perceived ease of use. Finally, this research analyzed external variables' attributes using other perspective and tried to explain the attributes. It presents Chinese cloud service users are more interested in fundamental cloud services than extended services. In private cloud services, both of increased user size and cooperation among companies are important in the study. This study presents useful opinions for the purpose of strengthening attitude for private cloud service users can use this service persistently. Overall, it can be summarized by considering the all three external factors could make Chinese users keep using the personal could services. In addition, the results of this study can provide strong references to technology companies including cloud service provider, internet service provider, and smart phone service provider which are main clients are Chinese users.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• 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 Tunnelling and Underground Space Association
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• v.19 no.6
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• pp.915-936
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• 2017

In this study, current status of Korean hazard mitigation guideline for tunnel operation is summarized. It shows that requirement for CCTV installation has been gradually stricted and needs for tunnel incident detection system in conjunction with the CCTV in tunnels have been highly increased. Despite of this, it is noticed that mathematical algorithm based incident detection system, which are commonly applied in current tunnel operation, show very low detectable rates by less than 50%. The putative major reasons seem to be (1) very weak intensity of illumination (2) dust in tunnel (3) low installation height of CCTV to about 3.5 m, etc. Therefore, an attempt in this study is made to develop an deep-learning based tunnel incident detection system, which is relatively insensitive to very poor visibility conditions. Its theoretical background is given and validating investigation are undertaken focused on the moving vehicles and person out of vehicle in tunnel, which are the official major objects to be detected. Two scenarios are set up: (1) training and prediction in the same tunnel (2) training in a tunnel and prediction in the other tunnel. From the both cases, targeted object detection in prediction mode are achieved to detectable rate to higher than 80% in case of similar time period between training and prediction but it shows a bit low detectable rate to 40% when the prediction times are far from the training time without further training taking place. However, it is believed that the AI based system would be enhanced in its predictability automatically as further training are followed with accumulated CCTV BigData without any revision or calibration of the incident detection system.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.1-36
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• 2020

This study is to reveal the acceptance factors of the Market Sentiment Index (MSI) created by reflecting the investor sentiment extracted by processing unstructured big data. The research model was established by exploring exogenous variables based on the rational behavior theory and applying the Technology Acceptance Model (TAM). The acceptance of MSI provided to investors in the stock market was found to be influenced by the exogenous variables presented in this study. The results of causal analysis are as follows. First, self-efficacy, investment opportunities, Innovativeness, and perceived cost significantly affect perceived ease of use. Second, Diversity of services and perceived benefits have a statistically significant impact on perceived usefulness. Third, Perceived ease of use and perceived usefulness have a statistically significant effect on attitude to use. Fourth, Attitude to use statistically significantly influences the intention to use, and the investment opportunities as an independent variable affects the intention to use. Fifth, the intention to use statistically significantly affects the final dependent variable, the intention to use continuously. The mediating effect between the independent and dependent variables of the research model is as follows. First, The indirect effect on the causal route from diversity of services to continuous use intention was 0.1491, which was statistically significant at the significance level of 1%. Second, The indirect effect on the causal route from perceived benefit to continuous use intention was 0.1281, which was statistically significant at the significance level of 1%. The results of the multi-group analysis are as follows. First, for groups with and without stock investment experience, multi-group analysis was not possible because the measurement uniformity between the two groups was not secured. Second, the analysis result of the difference in the effect of independent variables of male and female groups on the intention to use continuously, where measurement uniformity was secured between the two groups, In the causal route from usage attitude to usage intention, women are higher than men. And in the causal route from use intention to continuous use intention, males were very high and showed statistically significant difference at significance level 5%.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.147-157
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• 2022

This study tried to propose a smart farm technology strategy suitable for the domestic situation, focusing on the differentiation suitable for the domestic situation of ICT technology. In the case of advanced countries in the overseas agricultural industry, it was confirmed that they focused on the development of a specific stage that reflected the geographical characteristics of each country, the characteristics of the agricultural industry, and the characteristics of the people's demand. Confirmed that no enemy development is being performed. Therefore, in response to problems such as a rapid decrease in the domestic rural population, aging population, loss of agricultural price competitiveness, increase in fallow land, and decrease in use rate of arable land, this study aims to develop smart farm ICT technology in the future to create quality agricultural products and have price competitiveness. It was suggested that the smart farm should be promoted by paying attention to the excellent performance, ease of use due to the aging of the labor force, and economic feasibility suitable for a small business scale. First, in terms of economic feasibility, the ICT technology is configured by selecting only the functions necessary for the small farm household (primary) business environment, and the smooth communication system with these is applied to the ICT technology to gradually update the functions required by the actual farmhouse. suggested that it may contribute to the reduction. Second, in terms of performance, it is suggested that the operation accuracy can be increased if attention is paid to improving the communication function of ICT, such as adjusting the difficulty of big data suitable for the aging population in Korea, using a language suitable for them, and setting an algorithm that reflects their prediction tendencies. Third, the level of ease of use. Smart farms based on ICT technology for the development of the Industry6.0 (1.0(Agriculture, Forestry) + 2.0(Agricultural and Water & Water Processing) + 3.0 (Service, Rural Experience, SCM)) perform operations according to specific commands, finally suggested that ease of use can be promoted by presetting and standardizing devices based on big data configuration customized for each regional environment.