• KIPS Transactions on Software and Data Engineering
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• v.6 no.12
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• pp.549-564
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• 2017

Not only services that are provided by a single system have been various with the development of the Internet of Things and autonomous software but also new services that are not possible before are provided through collaboration between systems. The collaboration between autonomous systems is similar to the ecosystem configuration in terms of biological viewpoints. Thus, it is called the IT Ecosystem, and this concept has arisen newly in recent years. The IT Ecosystem refers to a concept that achieves a mission of each of a number of heterogeneous systems rather than a single system utilizing their own autonomy as well as achieving the objectives of the overall system simultaneously in order to meet a single common goal. In our previous study, we proposed architecture of elementary level and as well as basic several meta-models to implement the IT Ecosystem. This paper proposes comprehensive reference architecture framework to implement the IT Ecosystem by cleansing the previous study. Among them, a utility function based on cost-benefit model is proposed to solve the dynamic re-configuration problem of system components. Furthermore, a measure of using genetic algorithm is proposed as a solution to reduce the dynamic re-configuration overhead that is increased exponentially according to the expansion of the number of entities of components in the IT Ecosystem. Finally, the utilization of the proposed orchestration framework is verified quantitatively through probable case studies on IT Ecosystem for unmanned forestry management.

• Spatial Information Research
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• v.5 no.2
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• pp.147-160
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• 1997

"The "Map Algebra", beeing recognized as a viable theoretical framework for GIS (Geographica Infonnation System), models map layers as "operands" which are the basic unit of geo-processing, and a variety of GIS commands as "operators." In this paper, we attempt at lifting some limitations of map algebras proposed in GIS literature. First, we model map layer as "function" such that we may employ the notion of meta operator (or, higher-order funtion) available in the functional programming paradigm. This approach provides map algebraic language with "programmability" needed in GIS user language. Second, we extend the semantics of, and improve on the sytactic structure of map algebraic language. Mer the data model and language associated with map algebra are formalized, we proceed to design and implement a prototype of map algebraic processor. The parser of the language in our prototype plays the role of transforming the native and heterogeneous user language of current GISs into a canonical map algebraic language. The prototype, named "MapSee" is a proof-of-concept system for the ideas we propsed in this paper. We believe that the uniform interface based on the map algebraic language will make promising infrastructure to support "Internet GIS." This is because the uniform but powerful interface through the Web clients allow access to both geo-data and geo-processing resources distributed over the network.to both geo-data and geo-processing resources distributed over the network.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.11
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• pp.1123-1129
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• 2015

A pair of two-way valves typically is used in automotive washing machines, where the water flow direction is frequently reversed and highly pressurized clean water is sprayed to remove the oil and dirt remaining on machined engine and transmission blocks. Although this valve system has been widely used because of its competitive price, its application is sometimes restricted by surging effects, such as pressure ripples occurring in rapid changes in water flow caused by inaccurate valve control. As an alternative, one three-way reversing valve can replace the valve system because it provides rapid and accurate changes to the water flow direction without any precise control device. However, a cavitation effect occurs because of the complicated bottom plug shape of the valve. In this study, the cavitation index and percent of cavitation (POC) were introduced to numerically evaluate fluid flows via computational fluid dynamics (CFD) analysis. To reduce the cavitation effect generated by the bottom plug, the optimal shape design was carried out through a parametric study, in which a simple computer-aided engineering (CAE) model was applied to avoid time-consuming CFD analysis and difficulties in achieving convergence. The optimal shape design process using full factorial design of experiments (DOEs) and an artificial neural network meta-model yielded the optimal waist and tail length of the bottom plug with a POC value of less than 30%, which meets the requirement of no cavitation occurrence. The optimal waist length, tail length and POC value were found to 6.42 mm, 6.96 mm and 27%, respectively.

• Journal of KIISE
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• v.42 no.5
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• pp.591-600
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• 2015

SLA (Service Level Agreement) is an essential factor that must be guaranteed to provide a reliable and consistent service to user in cloud computing environment. Especially, a contract between user and service provider with SLA is important in an environment using a cloud service brokerage. The cloud computing is classified into IaaS, PaaS, and SaaS according to IT resources of the various cloud service. The existing SLA is difficult to reflect the quality factors of service, because it only considers factors about the physical Network environment and have no methodological approach. In this paper, we suggested a method to specify the quality characteristics of software and proposed a mechanism and structure that can exchange SLA specification between the service provider and consumer. We defined a meta-model for the SLA specification in the SaaS level, and quality requirements of the SaaS were described by the proposed specification language. Through case studies, we verified proposed specification language that can present a variety of software quality factors. By using the UDDI-based mediation process and architecture to interchange this specification, it is stored in the repository of quality specifications and exchanged during service binding time.

• Journal of Korean Philosophical Society
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• v.123
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• pp.209-244
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• 2012

In this paper I undertake to define what is mind, as a partial project of the philosophical foundation of the Mind Humanities. To this end I ask myself, where can be found the field, to which the various or whole psychological concepts and discourses generally relate, and then I identify the correct field to be the field of existential activities of human beings as being-in-the-world. When human beings as being-in-the-world live their lives, her life is built up out of the internal biological activities, the worlds of space and time, and actions. While the various scenes of individual life of man produced by a dynamic coordination of those worldly components, the basis of the mechanism of that coordination is explained by a biological model of self-sufficiency system that I developed here. On the basis of this model, I show step by step, how and through which (logical) way organisms configures their living, as it is. With respect to those steps of the life-construction of the organism, or in light of each step corresponding to each configuration, I construct different types of mind, i.e. impulsive mind, manipulative mind, meta-mind, collective consciousness/mind and finally personality, while every mind is further subdivided. Finally, I define mind, in light of its function in human life and with respect to the generalized sense of the whole processes as outlined above, as an organ which weaves (above mentioned) worldly components to Dasein, and sublimates and expands it to a better living.

• Korean Journal of Schizophrenia Research
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• v.21 no.2
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• pp.43-50
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• 2018

Objectives : Genome-wide association studies (GWASs) and meta-analyses indicate that single-nucleotide polymorphisms (SNPs) in the a-1C subunit of the L-type voltage-dependent calcium channel (CACNA1C) gene increase the risk for schizophrenia and bipolar disorders (BDs). We investigated the association between the genetic variants on CACNA1C and schizophrenia and/or BDs in the Korean population. Methods : A total of 582 patients with schizophrenia, 336 patients with BDs consisting of 179 bipolar I disorder (BD-I) and 157 bipolar II disorder (BD-II), and 502 healthy controls were recruited. Based on previous results from other populations, three SNPs (rs10848635, rs1006737, and rs4765905) were selected and genotype-wise association was evaluated using logistic regression analysis under additive, dominant and recessive genetic models. Results : rs10848635 showed a significant association with schizophrenia (p=0.010), the combined schizophrenia and BD group (p=0.018), and the combined schizophrenia and BD-I group (p=0.011). The best fit model was dominant model for all of these phenotypes. The association remained significant after correction for multiple testing in schizophrenia and the combined schizophrenia and BD-I group. Conclusion : We identified a possible role of CACNA1C in the common susceptibility of schizophrenia and BD-I. However no association trend was observed for BD-II. Further efforts are needed to identify a specific phenotype associated with this gene crossing the current diagnostic categories.

• Journal of Industrial Convergence
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• v.21 no.9
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• pp.89-102
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• 2023

This study was a one group, pre-post test design experimental study to identify the effects of problem-based learning applied to adult nursing subjects on meta-cognition, problem solving, professional self-concept and self-directed learning of nursing students. The participants were 60 fourth grade students who had registered for adult nursing class from a nursing university in D metropolitan city, the data were collected from September to December, 2022. The adult nursing class model was designed based on the ADDIE model suitable for PBL. The class period was conducted for 15 weeks, with 8 weeks of lectures, 2 weeks of exams, and 5 weeks of Barrow and Myers 5-step PBL learning. The collected data were analyzed using the SPSS/WIN 20.0 Program, and paired t-test was used to test the differences between variables before and after the intervention. There was a statistically significant difference in metacognition(t=-8.04, p<.001), problem solving(t=-4.08, p<.001), professional self-concept(t=-4.67, p<.001) and self-directed learning(t=-4.69, p<.001) between pre and post problem based learning. Therefore, our result recommend that to apply problem-based learning in various major subjects to strengthen nursing students' metacognition, problem-solving, professional self-concept, and self-directed learning skills.

• The Mathematical Education
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• v.62 no.3
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• pp.435-455
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• 2023

This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was utilized to construct a comprehensive academic research network in mathematics education. This academic network was built by integrating five sub-networks: 'paper and its citation network', 'paper and author network', 'paper and journal network', 'co-authorship network', and 'author and affiliation network'. The Random Forest machine learning model was employed to evaluate the impact of individual papers within the mathematics education research network. The SHAP, an XAI model, was used to analyze the reasons behind the AI's assessment of impactful papers. Key features identified for determining impactful papers in the field of mathematics education through the XAI included 'paper network PageRank', 'changes in citations per paper', 'total citations', 'changes in the author's h-index', and 'citations per paper of the journal'. It became evident that papers, authors, and journals play significant roles when evaluating individual papers. When analyzing and comparing domestic and international mathematics education research, variations in these discernment patterns were observed. Notably, the significance of 'co-authorship network PageRank' was emphasized in domestic mathematics education research. The XAI model proposed in this study serves as a tool for determining the impact of papers using AI, providing researchers with strategic direction when writing papers. For instance, expanding the paper network, presenting at academic conferences, and activating the author network through co-authorship were identified as major elements enhancing the impact of a paper. Based on these findings, researchers can have a clear understanding of how their work is perceived and evaluated in academia and identify the key factors influencing these evaluations. This study offers a novel approach to evaluating the impact of mathematics education papers using an explainable AI model, traditionally a process that consumed significant time and resources. This approach not only presents a new paradigm that can be applied to evaluations in various academic fields beyond mathematics education but also is expected to substantially enhance the efficiency and effectiveness of research activities.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.5
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• pp.13-35
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• 2020

Startup accelerators are a new type of investors providing a certain amount of shares for imparting education, mentoring, networking, and providing space and seed money that can directly resolve the difficulties faced by nascent entrepreneurs (Clarysse, 2016). Startup accelerators have expanded worldwide as their influence over the startup ecosystem has increasingly been established (Pauwels et al., 2016; Cohen & Hochberg, 2014). This study was conducted to derive investment determinants of startup accelerators that are emerging as major investment players around the world. To this end, the accelerator-type determinants of investment were derived. As previous research on this topic is nonexistent, this process involved qualitative meta-synthesis, literature reviews, observation, and in-depth interviews. First, more than 30 research papers were examined for the determinants of investment for firms at an early stage of their foundation, and the categories and determinants of investment in the relevant studies were comparatively analyzed using qualitative meta-synthesis. Further, related data were investigated to identify the characteristics of accelerators, and the startup evaluation process of US accelerators was studied. The more than 100 questions raised during this process were coded to examine the determinants of investment that accelerators considered important. In-depth interviews were conducted with four US accelerators to identify the characteristics of accelerators and key determinants of investment. Ultimately, 5 categories of accelerator-type determinants of investment and 26 subordinate determinants of investment were derived. The results were verified and supplemented by consulting with seven accelerators in Korea. The results were confirmed after pilot tests and verification by seven domestic accelerators. After confirming the accelerator-type determinants, the reliability of them was verified by examining the importance and priority of each category through the quantitative survey of Korean accelerators. The research that elicited the accelerator-type investment determinants is the first research and is expected to be a major reference to the progress of subsequent studies. This research that systematically derived the investment determinants of the accelerator is expected to make major contributions to the progress of follow-up studies, the process of selecting startups, and the investment decision-making process of the accelerators.

• Journal of Venture Innovation
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• v.4 no.3
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• pp.125-139
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• 2021

As the 4th industrial revolution progresses, new technologies and services are being born, growing, and maturing. Now, beyond the mobile era, the metaverse is being discussed as a new paradigm. Therefore, in this study, in preparation for the metaverse era, we tried to analyze what factors have an important influence when consumers want to use new technologies. In particular, the research was conducted focusing on how the context in which consumers use the technology changes depending on whether they are B2C or B2B. For this, augmented reality (AR) was selected in the B2C context by linking the research subject with the metaverse era, and the smart factory was selected in the B2B context. The research model for the analysis was established by deriving and setting common influence variables by reflecting the characteristics of the research target technology based on the modified extended unified theory of acceptance and use of technology. A survey was conducted for empirical analysis, and 150 AR and 150 smart factory subjects were analyzed. The empirical study results are as follows. The relationship between performance expectancy and intention to use, technology readiness and intention to use was found to have a significant positive (+) effect on both AR and smart factory. On the other hand, it was found that effort expectancy, social influence, and trust had a positive (+) effect on intention to use only in AR. Only in smart factory, facilitating conditions had a significant positive (+) effect on intention to use. It was also found that the perceived risk had a significant negative (-) effect on the intention to use only in the smart factory. The results of this study are academically significant in that we empirically test that influencing factors of technology use varies depending on the context in which it is used by consumers. In practice, it provided an implication of what to focus on first is being implemented.