• 한국IT서비스학회:학술대회논문집
• /
• 한국IT서비스학회 2006년도 추계학술대회
• /
• pp.491-497
• /
• 2006

최근 유비쿼터스를 비롯한 정보기술의 급격한 발전에 따라 GIS를 통하여 누구나 일상 속에서 직접 지리정보를 활용할 수 있게 되면서 공공분야 및 연관 산업분야에 큰 파급효과를 가져오고 있다. 특히, 지리정보의 유통 방식이 기존의 공급자가 제공하는 지리정보에 대해 조회 위주에서 벗어나 현장에서 실시간으로 지리정보를 가공하고 직접 갱신할 수 있는 양방향 서비스로 진화하면서, GIS는 u-City 구현에 필수적인 위치기반 공공서비스 인프라 구현을 통해 민간의 내비게이션, 텔레매틱스 등 관련분야 시장규모가 해마다 급속히 성장하고 있다. 하지만 이러한 상승세에도 불구하고 여전히 기관마다 서로 유사한 서비스를 제공하는 경우가 빈번하고, 민간의 대다수 유관업체들 역시 아직 지속적인 수익모델을 찾지 못해 단말기 제조 등 특정 분야에만 머무르고 있는 실정이다. 따라서 업종특성에 맞는 보다 구체적이고 유망한 신규 사업모델의 개발이 시급하다. 본 연구는 GIS 특성에 근거하여 사업모델 개발에 필요한 성공요인을 도출하고 그 타당성을 분석함으로서, 이를 통해 다양한 성공적인 지리정보 활용 비즈니스 모델의 구현과 평가에 기여하고자 한다.

• 한국정보시스템학회지:정보시스템연구
• /
• 제27권4호
• /
• pp.229-249
• /
• 2018

Purpose The purpose of this paper is to conduct exploratory comparative research on the determinants of successful crowdfunding projects, focusing on multiple crowdfunding platforms in Korea, U.S., and Japan. Design/methodology/approach This study collected data from three representative crowdfunding platforms: Wadiz (Korea), Kickstarter (U.S.), and Readyfor (Japan). Based on 1,906 crowdfunding projects from Wadiz, 3,864 projects from Kickstarter, and 3,060 projects from Readyfor, multiple regression models were applied. Findings Focusing on the crowdfunding projects which have overly achieved goal amount, the analysis results show that the number of comments, the number of Facebook likes and the number of backers have an positive impact on the performance of crowdfunding projects, while target amount has a negative impact. Comparatively, word counts of project description have an impact on funding performance in U.S. and Japan, while the number of images in project description affects funding performance in Korea and U.S. Meanwhile, video clips in project description has little impact on crowdfunding performance in all of the three funding platforms.

• 산업융합연구
• /
• 제14권1호
• /
• pp.39-45
• /
• 2016

This paper deals with the consideration of mathematical models with regards to growth of cluster and firms by reviewing the Metcalf and Breuner's articles. prior studies have been argued the phenomenon of local industrial clusters and districts. Several concepts have been adopted to support the success of and changes to these clusters and firm growth. Through the review of two papers, evolution of both cluster and firm growth may be achieved in terms of utilizations of the different local aspects and mechanisms. This paper supports the theoretical back bone with regards to the regional cluster policy implementing in Korea for the purpose of regional developments. In particular, a mathematical model that, on a more abstract level, captures the fundamental dynamic structure of all the observed mechanisms. On the basis of this model, the emergence and evolution of local clusters can be described. Also this model has given that the knowledge sharing between firms has an important role to firms and cluster' growth.

• 한국정보통신학회:학술대회논문집
• /
• 한국해양정보통신학회 2009년도 춘계학술대회
• /
• pp.872-875
• /
• 2009

In a bankruptcy prediction model, the accuracy is one of crucial performance measures due to its significant economic impacts. Ensemble is one of widely used methods for improving the performance of classification and prediction models. Two popular ensemble methods, Bagging and Boosting, have been applied with great success to various machine learning problems using mostly decision trees as base classifiers. In this paper, we analyze the performance of boosted neural networks for improving the performance of traditional neural networks on bankruptcy prediction tasks. Experimental results on Korean firms indicated that the boosted neural networks showed the improved performance over traditional neural networks.

• Asian Journal of Innovation and Policy
• /
• 제11권1호
• /
• pp.50-68
• /
• 2022

Innovation is broadly defined as the creation or adoption of new ideas and technologies, which has become an instrumental tool to determine the success and development level of a country as it leads to competitiveness and productivity of companies. Innovation is influenced by many factors including geographic and socio-economic factors as well as a political framework. In fact, innovation is systemic in nature, and it focuses on interactions amongst a nexus of processes such as Research and Development (R&D), production, business, and education, amongst other factors. However, not all innovation ecosystems have the same architectural models or internal collaboration. This paper aims to review the structure of the National Innovation Ecosystem by highlighting the different actions taken by the Government of Mauritius over the years. The multipronged approach of the government will be demonstrated through the different lines of actions to boost the innovation culture and offers a foundation for other small island developing state to follow to be at par with other innovative economies.

• Medical Lasers
• /
• 제9권1호
• /
• pp.1-5
• /
• 2020

Hearing organs have unique characteristics and have a role in processing external sensory signals. Sensory hair cells and nerve fibers in the organ of Corti can be damaged by various causes and they do not regenerate themselves. Medication used for clinical treatment for the inner ear is limited due to the anatomical structure of the inner ear. Photobiomodulation (PBM) is a therapeutic approach that uses various sources of light and the success of PBM therapy is highly reliant on the parameters of the light sources. The positive effects of PBM have been reported in various clinical fields. This paper summarizes the previously reported research on PBM for the treatment of hearing damage in animal models.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권3호
• /
• pp.853-873
• /
• 2021

In recent years, deep reinforcement learning (DRL) models are enjoying great interest as their success in a variety of challenging tasks. Deep Q-Network (DQN) is a widely used deep reinforcement learning model, which trains an intelligent agent that executes optimal actions while interacting with an environment. This model is well known for its ability to surpass skilled human players across many Atari 2600 games. Although DQN has achieved excellent performance in practice, there lacks a clear understanding of why the model works. In this paper, we present a visual analytics system for understanding deep Q-network in a non-blind matter. Based on the stored data generated from the training and testing process, four coordinated views are designed to expose the internal execution mechanism of DQN from different perspectives. We report the system performance and demonstrate its effectiveness through two case studies. By using our system, users can learn the relationship between states and Q-values, the function of convolutional layers, the strategies learned by DQN and the rationality of decisions made by the agent.

• 한국방송∙미디어공학회:학술대회논문집
• /
• 한국방송∙미디어공학회 2022년도 추계학술대회
• /
• pp.171-174
• /
• 2022

Weakly-supervised learning is a widely adopted approach in video anomaly detection whereby only video labels are utilized instead of expensive frame-level annotations. Since the success of multi-instance learning (MIL), almost all recent approaches are based on maximizing the margin between the set of abnormal video snippets and those of normal video snippets. In this work, we present a simple contrastive approach for weakly supervised video anomaly detection (WS-VAD) with aims to enhance the performance of existing models. The method is generic in nature and introduces a loss function to encourage attraction of output features from the same video class and repel those from different video classes. Experimental results demonstrate our method can be applied to existing algorithms to improve detection accuracy in public video anomaly dataset.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2022년도 추계학술발표대회
• /
• pp.402-404
• /
• 2022

Recent research has shown that deep learning models are vulnerable to adversarial attacks not only in the digital but also in the physical domain. This becomes very critical for applications that have a very high safety concern, such as self-driving cars. In this study, we propose a physical adversarial attack technique for one of the common tasks in self-driving cars, namely segmentation of the urban scene. Our method can create a texture on a wall so that it can be misclassified as a road. The demonstration of the technique on a state-of-the-art cityscape pretrained model shows a fairly high success rate, which should raise awareness of more potential attacks in self-driving cars.

• 유통과학연구
• /
• 제22권1호
• /
• pp.61-67
• /
• 2024

Purpose: The study has identified factors affecting dynamic capabilities and the distribution of competitive advantage under the impact of dynamic capabilities of Vietnamese fintech businesses. Research design, data, and methods: The method used in this study is a survey analysis of 120 Vietnamese fintech businesses to test the hypothesized relationships of the research model as well as evaluate its effectiveness. The study uses the Cronbach alpha analysis, factor analyses, and structural equation modeling to assess the research's measurement and structural models. Results: Research results show that 3 critical success factors: "Capacity to develop financial service ideas," "Ability to develop a platform," and "Business capacity" have a positive impact on "Dynamic capabilities." In addition, the study also evaluates the effect of "dynamic capabilities" on the "competitive advantage" of fintech businesses. Conclusion: Theoretically, this result contributes to discovering new, specific factors affecting the dynamic capabilities of fintech businesses. In practice, the research results are empirical evidence of the distribution of competitive advantages of Vietnamese Fintech businesses and their impact on dynamic capabilities.