• Journal of Information Technology Services
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• v.20 no.1
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• pp.93-115
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• 2021

Various policy declarations and institutional experiments involving artificial intelligence are being made in most countries. Depending on how the artificial intelligence policy changes, the role of the government, the scope of the policy, and the policy means used may vary, which can lead to the success or failure of the policy. This study proposed a perspective on AI(Artificial Intelligence) in policy research, investigated the theory of path change, and derived the characteristics of path change in AI policy. Since AI policy is related to a wide range of policy areas and the policy making is at the start points, this study is based on the neo-institutional path theory about the types of institutional changes. As a result of this study, AI policy showed the characteristics of path creation, and in detail presented the conflict relationship between institutional design elements, the scalability of policy areas, policy stratification and policy mix, the top policy characteristics transcending the law, and the experiment for regulatory innovation. Since AI can also be used as a key tool for policy innovation in the future, research on the path and characteristics of AI policy will provide a new direction and approach to government policy or institutional innovation seeking digital transformation.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.73-88
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• 2023

Brain tumors can also be an abnormal collection or accumulation of cells in the brain that can be life-threatening due to their ability to invade and metastasize to nearby tissues. Accurate diagnosis is critical to the success of treatment planning, and resonant imaging is the primary diagnostic imaging method used to diagnose brain tumors and their extent. Deep learning methods for computer vision applications have shown significant improvements in recent years, primarily due to the undeniable fact that there is a large amount of data on the market to teach models. Therefore, improvements within the model architecture perform better approximations in the monitored configuration. Tumor classification using these deep learning techniques has made great strides by providing reliable, annotated open data sets. Reduce computational effort and learn specific spatial and temporal relationships. This white paper describes transfer models such as the MobileNet model, VGG19 model, InceptionResNetV2 model, Inception model, and DenseNet201 model. The model uses three different optimizers, Adam, SGD, and RMSprop. Finally, the pre-trained MobileNet with RMSprop optimizer is the best model in this paper, with 0.995 accuracies, 0.99 sensitivity, and 1.00 specificity, while at the same time having the lowest computational cost.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.34-37
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• 2007

Face recognition is still a challenging problem in pattern recognition field which is affected by different factors such as facial expression, illumination, pose etc. The facial feature such as eyes, nose, and mouth constitute a complete face. Mouth feature of face is under the undesirable effect of facial expression as many factors contribute the low performance. We proposed a new approach for face recognition under facial expression applying two cascaded classifiers to improve recognition rate. All facial expression images are treated by general purpose classifier at first stage. All rejected images (applying threshold) are used for adaptation using GA for improvement in recognition rate. We apply Gabor Wavelet as a general classifier and Gabor wavelet with Genetic Algorithm for adaptation under expression variance to solve this issue. We have designed, implemented and demonstrated our proposed approach addressing this issue. FERET face image dataset have been chosen for training and testing and we have achieved a very good success.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.1
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• pp.55-64
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• 2022

This study analyzes the success factors of OTT original content through big data, and intends to suggest scenarios, casting, fun, and moving elements when producing the next work. In addition, I would like to offer suggestions for the success of 'Squid Game Season 2'. The success factor of 'Squid Game' through big data is first, it is a simple psychological experimental game. Second, it is a retro strategy. Third, modern visual beauty and color. Fourth, it is simple aesthetics. Fifth, it is the platform of OTT Netflix. Sixth, Netflix's video recommendation algorithm. Seventh, it induced Binge-Watch. Lastly, it can be said that the consensus was high as it was related to the time to think about 'death' and 'money' in a pandemic situation. The suggestions for 'Squid Game Season 2' are as follows. First, it is a fusion of famous traditional games of each country. Second, it is an AI-based planned MD product production and sales strategy. Third, it is casting based on artificial intelligence big data. Fourth, secondary copyright and copyright sales strategy. The limitations of this study were analyzed only through external data. Data inside the Netflix platform was not utilized. In this study, if AI big data is used not only in the OTT field but also in entertainment and film companies, it will be possible to discover better business models and generate stable profits.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.129-139
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• 2022

This study aims to identify which factors affect successful big data system construction, identify the relationship between the factors, and identify the success model and success factors necessary for public institutions to build big data systems. Therefore, the preceding and related studies related to this study were reviewed, and success factors for the establishment of a big data system were derived based on this. As a research method, a survey was conducted on users of institutions that have established or planned to build a big data system, and a structural equation (AMOS) was conducted to verify the impact relationship between success factors. As a result of the analysis, organizational support factors, development support factors, user support factors, information quality, service quality, system quality, use, and net benefit were derived as success factors for building big data systems, and a success model was presented. This can be seen as significant and academic contributions in that it is the first study of the success model for building an information system reflecting big data characteristics, and it is expected that this study will be used as basic data for building a big data system in public institutions in the future.

• Journal of Science Education
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• v.38 no.3
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• pp.612-624
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• 2014

The purpose of this study was to analyze successful intelligence and learning strategies for the scientific gifted and the general students in elementary school. For this purpose, we conducted a survey targeting 327(including 159 gifted students) 5th - 6th grader elementary students in Incheon Metropolitan City. We were utilized to evaluate the students' successful intelligence(Song, 2002) and learning strategies(Kim, 2005). The results of this study were as follows. First, successful intelligence and learning strategies of the scientific gifted students in elementary school were higher than the regular class students, it was a significant difference statistically(p < .001). Second, when compared according to grade level, the scientific gifted students class higher than the general class students, it was a significant difference statistically(p < .001). Third, when compared according to gender, the scientific gifted students were higher than the general class in both men and women, it was a significant difference statistically(p < .001)

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.2
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• pp.431-448
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• 2008

The change of management paradigm is that information technology change according to technology evolution at present is applied to corporate management, is that management level must be adapted to uncertainty management environment with activity and be made decision based on analyzed real time information through information system. This produces the effective target achievement and efficiency business productivity guarantee. At the present day, importation of business intelligence like enterprise information system has been the essential factor in business activities. Therefore, It is very important to give lessons the enterprises for building the business intelligence selecting the major success factors of more influence to managing results. In this paper, to authorize the research model and research constructions through theory study of literatures and surveying statics analysis prove the relational influences among the influencing factors related business intelligence system buliding.

• Journal of Intelligence and Information Systems
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• v.5 no.2
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• pp.79-97
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• 1999

Knowledge management (KM) is emerging as a robust management mechanism with which an organization can remain highly intelligent and competitive in a turbulent market. Organization knowledge is at the heart of KM success. As a vehicle of acquiring organizational knowledge in a distributed decision-making environment, we applied a fuzzy cognitive map (FMM) technique and proved its effectiveness in a distributed knowledge management environment. Our approach was applied to the financial statement analysis problem, yielding a robust result.

• Smart Media Journal
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• v.13 no.1
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• pp.24-35
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• 2024

The combination of Artificial Intelligence and the Internet of Things (AIoT) has gained significant popularity. Deep neural networks (DNNs) have demonstrated remarkable success in various applications. However, deploying complex AI models on embedded boards can pose challenges due to computational limitations and model complexity. This paper presents an AIoT-based system for smart parking lots using edge devices. Our approach involves developing a detection model and a decision tree for occupancy status classification. Specifically, we utilize YOLOv5 for car license plate (LP) detection by verifying the position of the license plate within the parking space.

• International Commerce and Information Review
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• v.19 no.1
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• pp.127-152
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• 2017

One of the biggest challenges in export activities of SME is the increasingly cultural diversity that requires especially export managers to adapt their doing business in many different kinds of cross-cultural situations effectively. A relative newly developed concept 'Cultural Intelligence' has been evaluated as a key element for the success in international business activities. This study aims to investigate empirically the role of Cultural Intelligence(CQ), one component of cultural competence, on export marketing adaptation. The statistical method used to test the hypotheses was Structural Equation Modeling using PLS. The results of this study are follows. The moderating role of Cultural Intelligence between information seeking and information using abilities is more stronger in marketing rather than relationship adaptation. Cultural Intelligence moderates between them. Critical factors affecting Cultural Intelligence are also discussed; foreign language fluency, business travels in abroad, characteristics of the business travels, multi-lingual ability, pre-education related cultural subjects, and visit experience in foreign countries. Especially, export managers' foreign language ability leads to much stronger influence on cultural intelligence. The result of the empirical study provides important implications for export SME and export supporting organizations. Export firms and supporting organizations must expand programs widely in multi cultural training and education to help managers gain a better understanding in a various export environment.