• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.53-73
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• 2023

Although it is mandatory to wear a seat belt that can minimize human injury when traffic accident occurs, the number of traffic accident casualties not wearing seat belts still accounts for a significant proportion.The seat belt wearing detection system for all seats is a system that identifies whether all seat passengers wear a seat belt and encourages their usage, also it can be a useful technical countermeasure. Firstly, this study established the viability of system implementation by assessing the factors influencing the severity of injuries in traffic accidents through the development of an ordered probit model. Analysis results showed that the use of seat belts has statistically significant effects on the severity of traffic accidents, reducing the probability of death or serious injury by 0.054 times in the event of a traffic accident. Secondly, a meta-analysis was conducted based on prior research related to seat belts and injuries in traffic accidents to estimate the expected reduction in accident severity upon the implementation of the system.The analysis of the effect of accident severity reduction revealed that wearing seat belts would lead to a 63.3% decrease in fatal accidents, with the front seats showing a reduction of 75.7% and the rear seats showing a reduction of 58.1% in fatal accidents. Lastly, Using the results of the meta-analysis and traffic accident statistics, the expected decrease in the number of traffic accident casualties with the implementation of the system was derived to analyze the traffic safety effects of the proposed detection system. The analysis demonstrated that with an increase in the adoption rate of the system, the number of casualties in accidents where seat belts were not worn decreased. Specifically, at a system adoption rate of 60%, it is anticipated that the number of fatalities would decrease by more than three times compared to the current scenario. Based on the analysis results, operational strategies for the system were proposed to increase seat belt usage rates and reduce accident severity.

• Restorative Dentistry and Endodontics
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• v.31 no.5
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• pp.390-397
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• 2006

The purpose of this study was to evaluate the accuracy and the consistency of four different electronic apex locators in an in vitro model. Fourty extracted premolars were used for the study. Four electronic apex locators (EAL) were Root ZX, Smarpex, Elements Diagnostic Unit (EDU), and E-Magic Finder Deluxe (EMF). After access preparation, the teeth were embedded in an alginate model and the length measurements were carried out at '0.5' and 'Apex' mark using four EALs. The file was cemented at the location of the manufacturers' instruction (Root ZX, EDU, EMF: 0.5 mark, SmarPex: Apex mark). The apical 4mm of the apex was exposed and the distance from the file tip to the major foramen was measured by Image ProPlus (${\times}100$). The distance from the file tip to the major foramen was calculated at 0.5 and Apex mark and the consistency of 0.5 and Apex mark was compared by SD and Quartile of Box plots. In this study, Root ZX and EMF located the apical constriction accurately within ${\pm}0.5 mm$ in 100%, whereas SmarPex and EDU located in 90% and in 70% respectively. For Root ZX and EMF, there was no significant difference between the consistency of 0.5 and Apex mark. However, for the EDU and SmarPex, Apex mark was more consistent than 0.5 mark. From the evaluation of the consistency in this study, for Root ZX and EMF, both 0.5 and Apex mark can be used as a standard mark. And for EDU and SmarPex, the Apex mark can be recommended to be used as a standard mark.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.

• Journal of Science of Art and Design
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• v.1
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• pp.189-226
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• 1999

The purpose of this paper is to examine the common characteristics of late 20th century interior design style and the post-modern thinking system. A period has its own predominant spirit which determine the tendency of art, and the ubiquitous power in the spirit decides the period's pattern of art. Therefore the interior design style belongs to general art sphere that has its own individual character derived from the dominant power of the controlling system. Paying special attention to this understanding, the auther has processed this paper by combining the post-modem thinking with special characteristics of each of the 20th century interior design style. Until now, researches have been focused on the individual style of post-modern design; however, a general research comprising the whole characteristics of expression has not been made. Accordingly, the rationale of emphasizing the general point of view is establshed. Also, this study suggests a model applicable to studies concerning other art area. This type of methodology is receving more attention as an approach investigating new art ideology for researching post-modern thinking and late 20th century art styles. The conclusions are as follows: First, the distinctive expressions of postmodernism appear to be characteristic of illusion, metaphor, pluralism, decoration, and symmetry, Those of late modernism appear to be the characteristic of complicated simplicity and symplified complexity, passiveness of symbolism and harmony, indeterminacy of form and space, and unintentional decorativeness. And the characteristics of deconstructionism are spatial difference and temporal defferal, and un-reductive and non formal abstractiveness of the space, unfinishness, chance, and secretiveness of individual style. Second, the disinctive expression seems to share common characteristics with postmodern thinking. The best examples are pluralism, non-formalism, populism, and historicism, originating from the deconstruction of 'meta-narrative'. Third, based on the second conclusion, general distinctive expression could be simplified as chacteristics of plurality, hybridity, and indeterminacy. These expressive chacteristics appear to be automatically connected with general postmodern thinking. Last, in consideration of the above conclusion, the extreme generality could be distinctively clarified as 'textural co-exsistence'. Accordingly, the author might confirm that 'textural co-existence' originated from the text that comes from postmodern thinking. In conclusion, design expression of late 20th century interior design accepts the ?universal theme of ubiquitous postmodern thinking. And universal expressions and supreme generality can be common analysis tools for understanding and studying complicated late 20th century interior design.

• Journal of KIISE:Databases
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• v.37 no.5
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• pp.258-266
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• 2010

In this paper, we introduce a novel method to predict next update of blogs. The number of RSS feeds registered on meta-blogs is on the order of several million. Checking for updates is very time consuming and imposes a heavy burden on network resources. Since blog search engine has limited resources, there is a fix number of blogs that it can visit on a day. Nevertheless we need to maximize chances of getting new data, and the proposed method which predicts update probability on blogs could bring better chances for it. Also this work is important to avoid distributed denial-of-service attack for the owners of blogs. Furthermore, for the internet as whole this work is important, too, because our approach could minimize traffic. In this study, we assumed that there is a specific pattern to when a blogger is actively posting, in terms of days of the week and, more specifically, hours of the day. We analyzed 15,119 blogs to determine a blogger's posting preference. This paper proposes a method to predict the update probability based on a blogger's posting history and preferred days of the week. We applied proposed method to 12,115 blogs to check the precision of our predictions. The evaluation shows that the model has a precision of 0.5 for over 93.06% of the blogs examined.

• Journal of KIISE
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• v.41 no.10
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• pp.762-773
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• 2014

As the web of data is increasingly producing large RDFS datasets, it becomes essential in building scalable reasoning engines over large triples. There have been many researches used expensive distributed framework, such as Hadoop, to reason over large RDFS triples. However, in many cases we are required to handle millions of triples. In such cases, it is not necessary to deploy expensive distributed systems because logic program based reasoners in a single machine can produce similar reasoning performances with that of distributed reasoner using Hadoop. In this paper, we propose a scalable RDFS reasoner using logical programming methods in a single machine and compare our empirical results with that of distributed systems. We show that our logic programming based reasoner using a single machine performs as similar as expensive distributed reasoner does up to 200 million RDFS triples. In addition, we designed a meta data structure by decomposing the ontology triples into separate sectors. Instead of loading all the triples into a single model, we selected an appropriate subset of the triples for each ontology reasoning rule. Unification makes it easy to handle conjunctive queries for RDFS schema reasoning, therefore, we have designed and implemented RDFS axioms using logic programming unifications and efficient conjunctive query handling mechanisms. The throughputs of our approach reached to 166K Triples/sec over LUBM1500 with 200 million triples. It is comparable to that of WebPIE, distributed reasoner using Hadoop and Map Reduce, which performs 185K Triples/sec. We show that it is unnecessary to use the distributed system up to 200 million triples and the performance of logic programming based reasoner in a single machine becomes comparable with that of expensive distributed reasoner which employs Hadoop framework.

• The Journal of Korean Academic Society of Nursing Education
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• v.15 no.1
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• pp.32-43
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• 2009

Purpose: The purpose of this study was to identify the trend of nursing research by analyzing the doctoral dissertations in one college of nursing in Korea. Method: The areas of research, the methodological characteristics, and theories used in the research were explored in all doctoral dissertations (n=120) published from 1989 to 2006. Result: Mainly "Nursing" has been studied (44.9%) among four meta-paradigms of nursing science. The "client" domain (46.7%) and the "practice" domain (41.7%) were most frequently studied in type of nursing knowledge. The main purpose of the thesis was to develop nursing interventions and examine the effectiveness of the practice (40.8%) in quantitative research. Almost all (94.7%) of the qualitative dissertation studies were to explore phenomena in the nursing field. Almost half of the dissertations (43.9%) were an experimental design, 34.7% were a model construction, and 15.8% were a qualitative design. The majority of dissertations (83.3%) were to apply the specific theory and almost half (43.8%) studied borrowed theories from other fields. Conclusion: It is necessary to develop more rigorous and various research designs such a longitudinal design, or randomized controlled trial and this will lead to expanding the body of nursing knowledge.