• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.877-893
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• 2022

With the development of deep learning, face inpainting has been significantly enhanced in the past few years. Although image inpainting framework integrated with generative adversarial network or attention mechanism enhanced the semantic understanding among facial components, the issues of reconstruction on corrupted regions are still worthy to explore, such as blurred edge structure, excessive smoothness, unreasonable semantic understanding and visual artifacts, etc. To address these issues, we propose a Learnable Structure Knowledge of Fusion Network (LSK-FNet), which learns a prior knowledge by edge generation network for image inpainting. The architecture involves two steps: Firstly, structure information obtained by edge generation network is used as the prior knowledge for face inpainting network. Secondly, both the generated prior knowledge and the incomplete image are fed into the face inpainting network together to get the fusion information. To improve the accuracy of inpainting, both of gated convolution and region normalization are applied in our proposed model. We evaluate our LSK-FNet qualitatively and quantitatively on the CelebA-HQ dataset. The experimental results demonstrate that the edge structure and details of facial images can be improved by using LSK-FNet. Our model surpasses the compared models on L1, PSNR and SSIM metrics. When the masked region is less than 20%, L1 loss reduce by more than 4.3%.

• Information Systems Review
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• v.6 no.2
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• pp.137-159
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• 2004

The next generation information appliances are those that can be connected with other appliances through a wired or wireless network in order to make it possible for them to transmit and receive data between them and to be remotely controlled from inside or outside of the home. Many electronic companies have aggressively invested in developing new information appliances to take the initiative in upcoming home networking era. They require systematic methods for developing new information appliances and sharing the knowledge acquired from the methods. This paper stored the knowledge acquired from developing the information appliances and developed a knowledge management system that supports the companies to use the knowledge and develop their own information appliances. In order to acquire the knowledge, this paper applied two methods for User-Centered Design in stead of using the general ones for knowledge acquisition. This paper suggested new product ideas by analyzing and observing user actions and stored the knowledge in knowledge bases, which included Knowledge from Analyzing User Actions and Knowledge from Observing User Actions. Seven new product ideas, suggested from the User-Centered Design, were made into design mockups and their videos were produced to show the real situations where they would be used in home of the future, which were stored in the knowledge base of Knowledge from Producing New Emotive Life Videos. Finally, data on present development states of future homes in Europe and Japan and newspapers articles from domestic newspapers were collected and stored in the knowledge base of Knowledge from Surveying Technology Developments. This paper developed a web-based knowledge management system that supports the companies to use the acquired knowledge. Knowledge users can get the knowledge required for developing new information appliances and suggest their own product ideas by using the knowledge management system. This will make the results from this research not confined to a case study of product development but extended to playing a role of facilitating the development of the next generation information appliances.

• Journal of KIISE
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• v.43 no.5
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• pp.579-589
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• 2016

Currently, corporations have introduced the knowledge management system that utilizes knowledge effectively for practical purpose and development of core ability. However, existing knowledge systems have failed to share the knowledge content due to lack of elements that encourage the members to participate in the system. In this study, we designed a novel knowledge management system that employs the structure of social network service (SNS). More precisely, screen layout according to function and several algorithms to improve user friendliness and produce integrated knowledge content are recommended. The proposed SNS-based knowledge management system encourages the enterprise members to participate in the system to produce and share valuable knowledge contents.

• Journal of the Korean housing association
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• v.18 no.1
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• pp.53-60
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• 2007

Storytelling approach is the way to formulate and solve problems using stories. Story is a means to understand and react everyday life that can be regarded as multi-dimensional problems. The approach becomes popular in various fields in conjunction with digital technology. In particular, it is used to solve problems in relation to whole context. In design, storytelling approach is used to clarify design constraints. It can be used to clarify and communicate thoughts for design artifacts, and to understand how the artifacts might be used in particular circumstances. In particular, the approach is useful to use under uncertain circumstances. In architecture, storytelling approach can be used in the area of design generation, design critique and capturing design knowledge. In design generation, it can be used to describe and formulate design experiences rather than simple designing artifacts. The approach formalizes design based on stories of user experiences. Digital technology such as virtual reality can be used to experience designed spaces for design modifications. In design critique area, it can be used to fill uncertain facts for historical buildings as welt as different from present status. Such stories can be used to build digital modeling and used to open criticism. Stories can be used to formalize knowledge in architectural domain as a form of implicit knowledge for certain projects. In architecture, it often is required to design types of environment never experienced before as well as to accomodate fast changing technologies. Storytelling methodology can be used as a method to cope with uncertainty and complexity in design requirements along with accumulating design knowledge.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.68-74
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• 2008

Application areas of Knowledge Discovery in Database(KDD) have been expanded to many R&D management processes including technology trends analysis, forecasting and evaluation etc. Established research field such as informetrics (or scientometrics) has utilized techniques or methods of KDD. Various systems have been developed to support works of analyzing large-scale R&D related databases such as patent DB or bibliographic DB by a few researchers or institutions. But extant systems have some problems for korean users to use. Their prices is not moderate, korean language processing is impossible, and user's demands not reflected. To solve these problems, Korea Institute of Science and Technology Information(KISTI) developed stand-alone type information analysis system named as KnowledgeMatrix. KnowledgeMatrix system offer various functions to analyze retrieved data set from databases. KnowledgeMatrix's main operation unit is composed of user-defined lists and matrix generation, cluster analysis, visualization, data pre-processing. Matrix generation unit help extract information items which will be analyzed, and calculate occurrence, co-occurrence, proximity of the items. Cluster analysis unit enable matrix data to be clustered by hierarchical or non-hierarchical clustering methods and present tree-type structure of clustered data. Visualization unit offer various methods such as chart, FDP, strategic diagram and PFNet. Data pre-processing unit consists of data import editor, string editor, thesaurus editor, grouping method, field-refining methods and sub-dataset generation methods. KnowledgeMatrix show better performances and offer more various functions than extant systems.

• Journal of The Korean Association For Science Education
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• v.23 no.5
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• pp.458-469
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• 2003

Hypothesis is defined as a proposition intended as a possible explanation for an observed phenomenon. The purpose of this study was to generate a grounded theory on the process of undergraduate students' generating hypothesis-knowledge about scientific episodes. Three hypothesis-generating tasks were administered to four college students majored in science education. The present study showed that college students represented five types of intermediate knowledge in the process of hypothesis generation, such as question situation, hypothetical explicans, experienced situation, causal explicans, and final hypothetical knowledge. Furthermore, students used six types of thinking methods, such as searching knowledges, comparing a question situation and an experienced situation, borrowing explicans, combining explicans, selecting an explican, and confirming explicans. In addition, hypothesis-generating process involves inductive and deductive reasoning as well as abductive reasoning. This study also discusses the implications of these findings for teaching and evaluating in science education.

• Asia Marketing Journal
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• v.22 no.3
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• pp.51-69
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• 2020

This study empirically examines the link between marketing knowledge management and innovation performance focusing on the moderating role of business environmental volatility. We define marketing knowledge management as the integration of knowledge generation, knowledge dissemination and knowledge storage. Using a unique data set that consists of 439 employees at 156 firms in China, we find that knowledge dissemination and knowledge storage have a positive effect on innovation performance. Also found is the negative moderating effect of business environmental volatility on innovation performance. Our findings suggest that firms should strengthen their marketing knowledge management to improve innovation performance and stay flexible to cope with the ever-changing and often volatile market environments.

• Education of Primary School Mathematics
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• v.19 no.1
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• pp.79-112
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• 2016

The purpose of this research is to find the effects of learner-centered instruction based on constructivism (LCIC) on their knowledge generation level and reasoning ability. To look for them, after fraction units are re-planed for implementing LCIC, instructions using it provide students in a class. From the data, some conclusions can be drawn as follows: LCIC has more positive influence of students on recall ability, generation ability, and reasoning ability than tractional instruction method. With the data it can be said that the interaction exists between learners' reasoning ability and generation level.

• Knowledge Management Research
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• v.23 no.1
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• pp.27-46
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• 2022

The current era's focus is on the surge in real estate prices triggered by the global economic downturn. This study advocated STO-based dispersed investment for the MZ generation, who has less capital than earlier generations. Existing real estate investment methods were categorized into online, offline, and hybrid formats and the effectiveness of the suggested STO was given in this study through case analysis domestically and overseas. The entry of STO into the financial industry was positively proved, and the efficacy of blockchain technology was validated, through the investigation of the STO framework. The findings of this study are projected to revitalize the new real estate sector by actively supporting the access of the MZ generation into the current inflexible real estate investment market by the application of blockchain and reflecting MZ generation's investment propensity.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.99-106
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• 2014

Generation and analysis methods have been proposed in recent years, such as using a natural language and formal language processing, artificial intelligence algorithms based knowledge model is effective meaning. its semantic based knowledge model has been used effective decision making tree and problem solving about specific context. and it was based on static generation and regression analysis, trend analysis with behavioral model, simulation support for macroeconomic forecasting mode on especially in a variety of complex systems and social network analysis. In this study, in this sense, integrating knowledge-based models, This paper propose a text mining derived from the inter-Topic model Integrated formal methods and Algorithms. First, a method for converting automatically knowledge map is derived from text mining keyword map and integrate it into the semantic knowledge model for this purpose. This paper propose an algorithm to derive a method of projecting a significant topic map from the map and the keyword semantically equivalent model. Integrated semantic-based knowledge model is available.