• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.519-525
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• 2023

The human brain constantly emits electrical impulses, which is called brain waves, and brain waves can be defined as the electrical activity of the brain generated by the flow of ions generated by the biochemical interaction of brain cells. There is a study that emotion is one of the factors that can cause stress. Brain waves are the most used in the study of emotions. This paper is a study on whether emotions affect stress, and showed two images of fear and joy to four experimenters and divided them into three stages before, during, and after watching. As a measurement tool, brain waves at the positions of Fp1 and Fp2 were measured using the NeuroBrain System, a system that can automate brain wave measurement, analysis, brain wave reinforcement, and suppression training with remote control. After obtaining the brain wave data for each emotion, the average value was calculated and the study was conducted. As for the frequency related to stress, the values of Alpha and SMR, Low Beta, and High Beta were analyzed. Brainwave analysis affects stress depending on the emotional state, and "fear" emotions cause anxiety by raising Beta levels, resulting in higher Mind Stress levels, while "joy" emotions lower Beta levels, resulting in a significant drop in Mind Stress.

• Knowledge Management Research
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• v.24 no.4
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• pp.103-129
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• 2023

This study aims to analyze the network structure of technological innovation resources in SMEs, especially manufacturing firms, and reveal the differences between innovative and non-innovative firms. The study first analyzes connection centrality, flow-mediated centrality, and power centrality for all firms, and derives structural equivalence through CONCOR analysis. Then, the network structure of innovative and non-innovative firms was compared and analyzed according to innovation performance and creation. The results show that entrepreneurship and corporate innovation strategy have a significant impact on the analysis of technological innovation resources of all firms. According to the CONCOR analysis, the innovation resources of SMEs are organized into seven clusters, which can be defined as intrinsic product innovation resources, competitive advantage promotion resources, cooperative activities resources, information system resources, and innovation protection resources. The network analysis of innovative and non-innovative firms showed that innovative firms focused on enhancing competitiveness and improving quality, while non-innovative firms tended to focus more on existing products and customers. In addition, innovative firms had eight clusters, while non-innovative firms had six clusters, suggesting that innovative firms utilize resources diversely to pursue structural change and new value creation, while non-innovative firms operate technological innovation resources in a more stable form. This study emphasizes the importance of entrepreneurship and corporate innovation strategy in SMEs' technological innovation, and suggests that strong internal efforts are needed to increase innovativeness. These findings have important implications for strategy formulation and policy development for technological innovation in SMEs.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.1-9
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• 2024

This paper analyzes the trends in generative AI technology based on patent application documents. To achieve this, we selected 5,433 generative AI-related patents filed in South Korea, the United States, and Europe from 2003 to 2023, and analyzed the data by country, technology category, year, and applicant, presenting it visually to find insights and understand the flow of technology. The analysis shows that patents in the image category account for 36.9%, the largest share, with a continuous increase in filings, while filings in the text/document and music/speech categories have either decreased or remained stable since 2019. Although the company with the highest number of filings is a South Korean company, four out of the top five filers are U.S. companies, and all companies have filed the majority of their patents in the U.S., indicating that generative AI is growing and competing centered around the U.S. market. The findings of this paper are expected to be useful for future research and development in generative AI, as well as for formulating strategies for acquiring intellectual property.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.82-96
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• 2024

While analyzing traffic flow, speed, traffic volume, and density are important macroscopic indicators, and acceleration and spacing are the important microscopic indicators. The speed and traffic volume can be collected with the currently installed traffic information collection devices. However, acceleration and spacing data are necessary for safety and autonomous driving but cannot be collected using the current traffic information collection devices. 'You Look Only Once'(YOLO), an object recognition technique, has excellent accuracy and real-time performance and is used in various fields, including the transportation field. In this study, to measure acceleration and spacing using YOLO, we developed a model that measures acceleration and spacing through changes in vehicle speed at each interval and the differences in the travel time between vehicles by setting the measurement intervals closely. It was confirmed that the range of acceleration and spacing is different depending on the traffic characteristics of each point, and a comparative analysis was performed according to the reference distance and screen angle to secure the measurement rate. The measurement interval was 20m, and the closer the angle was to a right angle, the higher the measurement rate. These results will contribute to the analysis of safety by intersection and the domestic vehicle behavior model.

• Information Systems Review
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• v.21 no.1
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• pp.135-152
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• 2019

Recently there are many development and support policies for start-up companies because of successful venture companies related to ICT services. However, as these policies have focused on the support for the initial stage of start-up, many start-up companies have difficulties to continuously grow up. The main reason for these difficulties is that they recognize start-up tasks as independent activities. However, many experts or related articles say that start-up tasks are composed of related processes from the initial stage to the stable stage of start-up firms. In this study, we models the start-up processes based on the survey collected by the start-up companies, and analyze the start-up process of ICT service companies with process mining techniques. Through process mining analysis, we can draw a sequential flow of tasks for start-ups and the characteristics of them. The analysis of start-up businessman, idea derivation, creating business model, business diversification processes are resulted as important processes, but marketing activity and managing investment funds are not. This result means that marketing activity and managing investment funds are activities that need ongoing attention. Moreover, we can find temporal and complementary tasks which could not be captured by independent individual-level activity analysis. Our process analysis results are expected to be used in simulation-based web-intelligent system to support start-up business, and more cumulated start-up business cases will be helpful to give more detailed individual-level personalization service. And our proposed process model and analyzing results can be used to solve many difficulties for start-up companies.

• Information Systems Review
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• v.21 no.4
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• pp.69-97
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• 2019

Knowledge service firms are able to have higher 'Organizational Performance (OP)' by improving efficiency in management processes on customer problem solving. This study explores the role of inefficiency that has been overlooked up to now compared to the management process efficiency. We also suggest in this study 'Hierarchical Culture (HC)' and 'IT Relatedness (IR)' as the factors influencing the inefficiency of management processes, and propose the moderating effect of 'Task Difficulty (TD)' on the relationship between independent factors and 'Inefficiency of Business Process(IP)'. The results of analysis show that 'HC' has a positive effect on 'IP', and 'IR' has a negative effect on 'IP'. 'TD' was significant moderator of between independent variables and 'IP'. 'IP' was shown to play a full mediating role between independent factors and 'OP'. In conclusion, knowledge service firms are desired to reduce 'HC' and enhance 'IR' by minimizing unnecessary formal procedures, securing flexibility in decision making through appropriate empowerment, creating a smooth flow of knowledge, and enhancing the level of IT resource management and utilization. In addition, in order to effectively reduce 'IP', it is required that a company with a high degree of 'TD' to more reduce a 'HC' and a company with a low degree of 'TD' to more enhance a 'IR'.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.2
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• pp.109-118
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• 2010

This study aims to propose practical strategies for the new urban ideal of regeneration. A book review highlights the emergence of new trends of urbanization in knowledge-information industrial society beyond the new town Ideal of the industrial society. The meaning of ‘landscape’ in landscape urbanism represents not the visual and decorative pictures, but the dynamic process in the context of changes and evolutions. Also, knowledge-information industrial society and landscape have a meaning in the same context of flow and process with changes of velocity. Finally, these key words convey a meaning with the new urban trends of urbanization in knowledge-information industrial society in the context of value-oriented characteristics of dynamics and process. Urban regeneration is emerging as the new urban ideal in the knowledge-information industrial society, beyond the new town ideal of industrial society. It is in the same context as landscape urbanism with respect to green infrastructure buildings and designs for the transformation of urban surfaces covered with concrete and asphalt into the ecological surface, and of the ecological surfaces into the cultural surface that could be communicated with human beings. This research revealed the six strategies for urban regeneration as follows. The First, the strategies for the transformation of urban surfaces into ecological surfaces, the second, the strategies for the transformation of ecological surfaces into cultural surfaces, the third, the introduction of mixed and convergence land use, the forth, the transformation of former sites(e.g. military and factory) into urban parks, the fifth, the introduction of waterfront park zones that have the function of ecological and park-oriented mixed land use and, the sixth, the building and design of green infrastructure in the residential and commercial complex in CBD. These strategies call for the reforms of development laws and regulations to restrict building coverage ratio, building heights, and the introduction of park-oriented mixed zoning regulations. Another method for implementating the above listed strategies was the introduction of a strategic planning system instead of the traditional master plan system. This system uses a value planning approach and brand making by imagery. It is able to construct the meaning of an image and its creativeness directly.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.52-63
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• 2009

Recently in Korea, in the case of metropolis, the urban signalized intersections are controlled by traffic information center or ITS center. Cheon-an City also established traffic information center through the 1st.-$\sim$3rd. ITS public construction and has managed this center that includes bus information service, traffic information collection and providing service, parking information service, and traffic responsive control system. In the Cheon-an metropolitan traffic signal operation, traffic signal controllers were grouped by the each main traffic flow axes and performed with coordinated signal timing for the signalized arterials, and also cycle and split changed by realtime traffic demands. Cheon-an urban traffic responsive control system was evaluated by intersection delay and speed, then it was verified that the delay decreased and vehicle speed improved. However, the rural signal control system to connect adjacency town was evaluated to have lower status than urban area due to the unimproved TOD (Time of day) plan. Therefore actuated signal control was examined for substitutive control system in isolated signal intersection. The aim of this article is to compare actuated signal control with TOD mode in the rural intersection of Cheon-an and to fine superiority of these two control mode, with evaluation of vehicle delay by using HCM(2000) method and by micro-simulation CORSlM. The result of field test show that actuated signal control gave better performance in delay comparison than the existing TOD signal control. And simulation outcome verified that non-optimized TOD has higher delay than optimized TOD mode, non-optimal actuated mode, and optimal actuated signal control mode. Particularly, these three modes delays had not different values according to the paired sample t-test. This is because small traffic demands were loaded in each links. This suggested actuated signal control is expected to be more effective than TOD mode in some rural isolated intersections which frequently need to survey for traffic volume.

• The Korean Journal of Archival Studies
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• no.16
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• pp.97-146
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• 2007

Those days when people used paper to make up and manage all kinds of documents in the process of their jobs are gone now. Today electronic types of documents have replaced paper. Unlike paper documents, electronic ones contribute to the maximum job efficiency with their convenience in production and storage. But they too have some disadvantages; it's difficult to distinguish originals and copies like paper documents; it's not easy to examine if there is a change or damage to the documents; they are also prone to alteration and damage by the external influences in the electronic environment; and electronic documents require enormous amounts of workforce and costs for immediate measures to be taken according to the changes to the S/W and H/W environment. Despite all those weaknesses, however, electronic documents increasingly account for more percentage in the current job environment thanks to their job convenience and efficiency of production costs. Both the government and private sector have made efforts to come up with plans to maximize their advantages and minimize their risks at the same time. One of the methods is the Authorized Retention Center which is described in the study. There are a couple of prerequisites for its smooth operation; they should guarantee the legal validity of electronic documents in the administrative aspects and first secure the reliability and authenticity of electronic documents in the technological aspects. Responding to those needs, the Ministry of Commerce, Industry and Energy and the Korea Institute for Electronic Commerce, which were the two main bodies to drive the Authorized Retention Center project, revised the Electronic Commerce Act and supplemented the provisions to guarantee the legal validity of electronic documents in 2005 and conducted researches on the ways to preserve electronic documents for a long term and secure their reliability, which had been demanded by the users of the center, in 2006. In an attempt to fulfill those goals of the Authorized Retention Center, this study researched technical standard for electronic record information package of the center and applied the ISO 14721 information package model that's the standard for the long-term preservation of digital data. It also suggested a process to produce and manage information package so that there would be the SIP, AIP and DIP metadata features for the production, preservation, and utilization by users points of electronic documents and they could be implemented according to the center's policies. Based on the previous study, the study introduced the flow charts among the production and progress process, application methods and packages of technical standard for electronic record information package at the center and suggested some issues that should be consistently researched in the field of records management based on the results.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.