• Asia pacific journal of information systems
• /
• 제10권4호
• /
• pp.57-75
• /
• 2000

Most current literature on knowledge and technology transfer(Appropriability Model, Dissemination Model, and Knowledge Utilization Model), describe the process of transfer in details, but has limitation in terms of their application in contemporary high-tech industries since most studies have not provided plausible explanation on levels and factors affecting transfer of knowledge and/or technology. To overcome these limitations, the four levels of knowledge and technology transfer are suggested: Knowledge and Technology Creation(Level I), Sharing(Level II), Implementation(Level III), and Commercialization(Level IV). Comprehensive literature identifies sixteen variables affecting the process and results of knowledge and technology transfer. The survey results show four key factors in knowledge and technology transfer: Communication, Distance, Equivocality, and Motivation, Communication refers to the degree to which a medium is able to efficiently and accurately conveys task-relevant information and media while distance involves both physical and cultural proximity. Equivocality refers to the degree of concreteness of knowledge and technology to be transferred while motivation involves incentives for and the recognition of the importance of knowledge and technology transfer activities. Further analysis shows that there are four distinctive clusters and they show very contrasting characteristics in terms of four key factors. The careful mapping of the four clusters on the four key factors show very informative knowledge and technology transfer patterns, the Knowledge and Technology Transfer Grid. Finally, actions to increase communication interactivity and motivation, and to reduce cultural distance and equivocality are suggested.

• 한국언어정보학회지:언어와정보
• /
• 제18권1호
• /
• pp.77-97
• /
• 2014

Multilingual machine translation means the machine translation that is for more than two languages. Common transfer means the transfer in which we can reuse the transfer rules among similar languages according to linguistic typology. Therefore, the multilingual machine translation based on common transfer is the multilingual machine translation that can share the transfer rules among languages with similar linguistic typology. This paper describes the linguistic modeling for multilingual machine translation based on common transfer under development. This linguistic modeling consists of the linguistic devices such as 1) multilingual common Part-of-Speech set, 2) multilingual common transfer format, 3) multilingual common transfer chunking, and 4) multilingual common transfer rules based on linguistic typology. Validity of this linguistic modeling for multilingual machine translation is shown in the simulation. The multilingual machine translation system based on common transfer including Korean, English, Chinese, Spanish, and French will be developed till 2018.

• Asia pacific journal of information systems
• /
• 제15권3호
• /
• pp.9-39
• /
• 2005

Recently, knowledge transfer has been recognized as one of the major factors for success of IT projects but little investigated in Information Systems research. IT project, which needs collaboration between organization's IT project team and external partner, is an critical source for a firm to acquire external knowledge and to achieve its competitive advantage. Based on this recognition on knowledge transfer under IT project, we investigate a mediation role of knowledge transfer to IT project performance after identifying its antecedents such as project team capabilities and partner capabilities. The research model is tested by analyzing 161 sample data gathered from firms' employees who have participated IT projects within last two years. The results reveal that knowledge transfer has full-mediation effect between its antecedents and IT project performance. Moreover, project team capabilities have more impacts on knowledge transfer than partner capabilities do.

• 한국ITS학회 논문지
• /
• 제7권4호
• /
• pp.1-12
• /
• 2008

대중교통시설 및 수단간의 비효율적 교통연계에 따른 환승불편으로 인한 대중교통 이용률 저하와 국가 교통시설의 운영효율성 개선을 위하여 IT와 정보통신 등 첨단기술을 활용하여 대중교통 서비스 고급화 방안에 대한 검토가 필요하다. 본 연구에서는 사용자 위치기반 환승정보서비스를 제안하며 국가 ITS 아키텍쳐 개발방법론을 준용하여 사용자 위치기반 환승정보서비스를 위한 개념 및 요구사항 도출, 세부 사용자 서비스 정의, 서브시스템 도출, 논리아키텍척를 제시하였다. 환승교통센터와 주차유도 및 보행자경로안내서비스 서브시스템 논리아키텍쳐는 모바일 매체를 활용한 다양한 서비스 컨텐츠 개발과 ISP, TSP 등 Contents Provider의 비즈니스 모델 창출에 기여할 것으로 판단된다. 아울러, 대중교통의 연계 환승은 도시규모나 대중교통 수단유형에 따라 각각의 특성이 차별화 되므로 본 연구에서 제시한 기본 개념을 바탕으로 대중교통 및 환승정보 서비스를 위한 다양한 유형의 서비스 모델 제시가 가능할 것으로 기대된다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권4호
• /
• pp.1464-1485
• /
• 2021

Emotional style of multimedia art works are abstract content information. This study aims to explore emotional style transfer method and find the possible way of matching music with appropriate images in respect to emotional style. DCNNs (Deep Convolutional Neural Networks) can capture style and provide emotional style transfer iterative solution for affective image generation. Here, we learn the image emotion features via DCNNs and map the affective style on the other images. We set image emotion feature as the style target in this style transfer problem, and held experiments to handle affective image generation of eight emotion categories, including dignified, dreaming, sad, vigorous, soothing, exciting, joyous, and graceful. A user study was conducted to test the synesthesia emotional image style transfer result with ground truth user perception triggered by the music-image pairs' stimuli. The transferred affective image result for music-image emotional synesthesia perception was proved effective according to user study result.

• 정보관리연구
• /
• 제32권3_4호
• /
• pp.123-145
• /
• 2001

본 연구는 지식정보를 활용하고 지원할 수 있는 기술가치평가 시스템의 개발에 관한 것이다. 정형화된 특허정보와 기술에 의한 제품시장정보를 제공함으로써 기술의 잠재사업이익 추정을 지원하며, 산업특성 및 기술혁신단계를 분석하여 기술기여도를 산출하고, 실물옵션법을 이용하여 최종 기술가치를 산출하는 단계로 개발된 기술가치평가 시스템을 소개하였다.

• Journal of information and communication convergence engineering
• /
• 제2권2호
• /
• pp.119-122
• /
• 2004

In this paper, we examine the necessity and the role of technology transfer/diffusion in the frame of national technology innovation system. On the base of this, we present a construction plan of technology transfer/diffusion system to make the national electric industry for 21st century to possess the competitive power. To achieve above purpose, we examine the relations between theory of technology transfer/diffusion structure and policy. Furthermore, we try to find the necessity for construction of technology transfer ＆ diffusion system and a driving plan. Then, it is analyzed that expected design requirements for the construction of electric technology transfer ＆ diffusion system. Finally, construction and activation plan for electric technology transfer ＆ diffusion system are presented, which would strengthen the national technology competitiveness.

• Asia pacific journal of information systems
• /
• 제25권3호
• /
• pp.445-472
• /
• 2015

Although knowledge transfer between two different parties occurs in IS development projects, the majority of prior studies focused on knowledge transfer from IT consultants to clients. Considering two parts of knowledge transfer in IS development projects, we must consider both 'where knowledge is transferred from' and 'where it is transferred to'. Therefore, in this study, we attempt to describe two different routes of knowledge transfer, such as knowledge transfer from an IT consultant to a client and knowledge transfer from a client to an IT consultant. In this regard, we have examined the effect of two different routes of knowledge transfer on system implementation success in IS development project. Specifically, we adopted the knowledge stock-flow theory to examine the causal relationship between IT consulting firms and clients in terms of knowledge transfer and eventual system implementation success. Survey data collected from 213 pairs of individuals (both clients and IT consultants) were used to test the model using three different analytic approaches such as PLS (partial least squares) and two types of mediated regression techniques. We found that knowledge transfers partially mediated both the relationships between IT consultants' IT skills (project members' business knowledge) and system implementation success. Furthermore, the effects of each knowledge transfer were distinguished by depending on the types of system, such as ERP or groupware. Our attempts have significant implications for both research and practice given the importance of effective knowledge transfer to IT consulting.

• Journal of information and communication convergence engineering
• /
• 제17권2호
• /
• pp.105-116
• /
• 2019

Recently, there has been an increase in research on wireless sensor networks (WSNs) because they are easy to deploy in applications such as internet-of-things (IoT) and body area networks. However, WSNs have constraints in terms of power, quality-of-service (QoS), computation, and others. To overcome the power constraint issues, wireless energy harvesting has been introduced into WSNs, the application of which has been the focus of many studies. Additionally, to improve system performance in terms of achievable rate, cooperative networks are also being explored in WSNs. We present a review on current research in the area of energy harvesting in WSNs, specifically on the application of simultaneous wireless information and power transfer (SWIPT) in a cooperative sensor network. In addition, we discuss possible future extensions of SWIPT and cooperative networks in WSNs.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제18권2호
• /
• pp.420-437
• /
• 2024

There are some problems in network traffic classification (NTC), such as complicated statistical features and insufficient training samples, which may cause poor classification effect. A NTC architecture based on one-dimensional Convolutional Neural Network (CNN) and transfer learning is proposed to tackle these problems and improve the fine-grained classification performance. The key points of the proposed architecture include: (1) Model classification--by extracting normalized rate feature set from original data, plus existing statistical features to optimize the CNN NTC model. (2) To apply transfer learning in the classification to improve NTC performance. We collect two typical network flows data from Youku and YouTube, and verify the proposed method through extensive experiments. The results show that compared with existing methods, our method could improve the classification accuracy by around 3-5%for Youku, and by about 7 to 27% for YouTube.