• Journal of Digital Convergence
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• v.14 no.4
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• pp.139-147
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• 2016

The purpose of this study is to identify the relationships between AI education characteristics and psychological capital, psychological capital and flow, AI characteristics and flow through meditating effect of psychological capital in the digital convergence society. There are three AI characteristics: correctness, usefulness, easy of use. This empirical study was examined by 282 questionnaires to the three universities that teach accounting information system. It was performed by three-step method of the hierarchical regression analysis for the multiple regression analysis and parameter using the SPSS 22.0. The results and implications by analysis are as follows. First, AI characteristics and psychological capital have statistically significant positive influence. From AI attribute, correctness was established as the most important element. Second, psychological capital positively(+) influences flow. It allowed for the developed in flow. Third, psychological capital was shown as the major meditative variable between AI characteristics and flow. Through these, this paper suggests to reinforce self-efficacy, hope, resilience, optimism.

• 한국벤처창업학회:학술대회논문집
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• 2021.04a
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• pp.61-65
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• 2021

세계적으로 창업 생태계가 구축되면서 기술창업 분야가 두각을 보이고 있다. 기술창업은 기술력을 통한 지속력뿐 아니라 혁신적으로 변화를 진행시키므로 기술에 대한 투자 동향을 날이갈수록 높아지고 있다. 하지만 기술이 발전하면서 함께 주목되고 있는 분야가 사회적 가치를 가지고 있는 소셜벤처이다. 특히 UN에서 발표한 지속가능한 발전목표(SDGs)의 경우 필수적으로 사업 비즈니스 모델적으로 채택된 분야를 갖고 있어야하며 비재무적성과를 판단하는 기준인 ESG 또한 필수적인 사회적 가치 요소로 떠오르고 있다. 이러한 흐름 속에서 기술 역량을 내세웠을 때와 사회적 가치를 내세웠을 때 투자자들은 어떤 역량과 특성을 더 선호하며 투자 유무가 결정되는지를 분석해보고자 한다. 결국 기술 역량 또는 사회적 가치 둘중 하나를 내세운다는 것은 기업의 이미지를 나타내는것과 같은 의미이다. 이에 기술역량과 사회적 가치가 기업이미지를 유능 또는 따뜻함 중 어떻게 나타나는지 알아보고 투자 유무에 미치는 영향을 보고자 한다. 본 연구에서는 기술창업 기업 기술 범위를 인공지능(AI), 빅데이터, 사물인터넷(IoT), 바이오(Bio)로 총 4개로 분류하였다. 기술 창업의 기술범위를 독립변수로 설정하였으며 기술창업에서 기술역량 또는 사회적 특성을 내세웠을 때 기업이미지가 유능하게 보여지는지 따뜻하게 보여지는지를 알아보고자 한다. 기업이미지가 유능함 또는 따뜻함으로 비춰졌을 때 벤처투자에서 투자 유무가 결정되는지를 검증하고자 한다. 검증 방법에서는 벤처투자자가 아닌 창업교육을 이수하는 대학생들을 대상으로 모의투자를 통해 연구를 진행하고자 한다.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.79-84
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• 2022

This paper presents an enhancement method of document restoration capability which is robust for security, loss, and contamination, It is based on two methods, that is, encryption and DnCNN(DeNoise Convolution Neural Network). In order to implement this encryption method, a mathematical model is applied as a spatial frequency transfer function used in optics of 2D image information. Then a method is proposed with optical interference patterns as encryption using spatial frequency transfer functions and using mathematical variables of spatial frequency transfer functions as ciphers. In addition, by applying the DnCNN method which is bsed on deep learning technique, the restoration capability is enhanced by removing noise. With an experimental evaluation, with 65% information loss, by applying Pre-Training DnCNN Deep Learning, the peak signal-to-noise ratio (PSNR) shows 11% or more superior in compared to that of the spatial frequency transfer function only. In addition, it is confirmed that the characteristic of CC(Correlation Coefficient) is enhanced by 16% or more.

• Knowledge Management Research
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• v.25 no.1
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• pp.21-41
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• 2024

The global Industry has been shaped by start-ups that originated with knowledge-based innovative strategies or technologies in the 21st century. Specifically, laboratory start-ups that rely on research papers or patents for new technology development are recognized for their high survival rate and the creation of employment opportunities. Our study concentrated on 'I-Corps', which also introduced in Korea, standing for innovation corps is a laboratory startup program launched in 2011 by the NSF(National Research Foundation) to commercialize R&D results and foster entrepreneurship as part of the policy to build a start-up system at the national innovation level. In this study, we proposed and empirically tested a research model focusing on teams participating in the I-Corps program to determine how startup team diversity, among the team characteristics of laboratory startups, affected patent performance. As a result of the analysis, among the proposed variables, age diversity, educational background diversity, and value diversity had a significant impact on patent performance. The results of this study are expected to further strengthen the theoretical and practical foundations of researchers or practitioners of the I-Corps program, as well as related areas involving technology & laboratory startups, intellectual property and knowledge management fields in the future.