• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.244-251
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• 2020

This paper presents a design of the Meta-Class Repository (MCR) which maintain syntactically analyzed and structured meta-class information from UML diagrams, and then proposes 'meta-class,' also known as super-class, to construct structured information analyzed syntactically. The MCR is a collection of these meta-classes which contains the information extracted from diagrams. This paper also presents a design of the Code Generation Engine (CGE) which roles generating codes corresponding classes from UML diagrams based on the MCR maintaining a collection of meta-classes which is syntactically-analyzed and constructed in previous process. The logics of CGE are designed to generate codes collaborated with MCR and CGE with integration. The logics of CGE mechanism is presented with the form of finite state machine to present the algorithms of code generation formally and have the advantages of simplicity and easiness in development.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1773-1793
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• 2023

Automated machine learning, often referred to as "AutoML," is the process of automating the time-consuming and iterative procedures that are associated with the building of machine learning models. There have been significant contributions in this area across a number of different stages of accomplishing a data-mining task, including model selection, hyper-parameter optimization, and preprocessing method selection. Among them, preprocessing method selection is a relatively new and fast growing research area. The current work is focused on the recommendation of preprocessing methods, i.e., feature subset selection (FSS) algorithms. One limitation in the existing studies regarding FSS algorithm recommendation is the use of a single learner for meta-modeling, which restricts its capabilities in the metamodeling. Moreover, the meta-modeling in the existing studies is typically based on a single group of data characterization measures (DCMs). Nonetheless, there are a number of complementary DCM groups, and their combination will allow them to leverage their diversity, resulting in improved meta-modeling. This study aims to address these limitations by proposing an architecture for preprocess method selection that uses ensemble learning for meta-modeling, namely AutoFE-Sel. To evaluate the proposed method, we performed an extensive experimental evaluation involving 8 FSS algorithms, 3 groups of DCMs, and 125 datasets. Results show that the proposed method achieves better performance compared to three baseline methods. The proposed architecture can also be easily extended to other preprocessing method selections, e.g., noise-filter selection and imbalance handling method selection.

• Journal of Information Technology Applications and Management
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• v.11 no.4
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• pp.1-23
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• 2004

This study identifies communication patterns of groups using synchronous text communication medium for their group decision-making, and examines how these patterns are associated with creative solutions to problems. Our research suggests that certain communication behavior of groups, when appropriately organized, can be of help in enhancing creative production of outcomes. A qualitative study was conducted on communication patterns based on an analysis of text-based electronic conversation protocols. Specifically this research tried to overcome existing studies on electronic groups by focusing on interactive process of communication among participants. The major study conclusion; are: (1) The production of creative outcome may depend on the process or sequence of discussion among group members with synchronous text communication medium. That is, proper interactive responses and appropriate control of the discussion process are essential to obtain a high level of performance. (2) It is importantto make discuss rules based on meta-cognitive and interactive protocols in the early stage. Explicit rules relating to internal group processes as well as communication medium use are even more important to groups with electronic communication medium than face-to-face groups.

• Journal of Information Technology Applications and Management
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• v.19 no.1
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• pp.37-46
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• 2012

The scheduling problem of large products like ships, airplanes, space shuttles, assembled constructions, and automobiles is very complex in nature. To reduce inherent computational complexity, we often design scheduling systems that the original problem is decomposed into small sub-problems, which are scheduled independently and integrated into the original one. Moreover, the steep growth of communication technology and logistics makes it possible to produce a lot of multi-nation corporation by which products are produced across more than one plant. Therefore vertical and lateral coordination among decomposed scheduling systems is necessary. In this research, we suggest an agent-based coordinating mechanism for multi-level scheduling systems in supply chain. For design of a general coordination mechanism, at first, we propose a grammar to define individual scheduling agents which are responsible to their own plants, and a meta-level coordination agent which is engaged to supervise individual scheduling agents. Second, we suggest scheduling agent communication protocols for each scheduling agent topology which is classified according to the system architecture, existence of coordinator, and direction of coordination. We also suggest a scheduling agent communication language which consists of three layers : Agent Communication Layer, Scheduling Coordination Layer, Industry-specific Layer. Finally, in order to improve the efficiency of communication among scheduling agents we suggest a rough capacity coordination model which supports to monitor participating agents and analyze the status of them. With this coordination mechanism, we can easily model coordination processes of multiple scheduling systems. In the future, we will apply this mechanism to shipbuilding domain and develop a prototype system which consists of a dock-scheduling agent, four assembly-plant-scheduling agents, and a meta-level coordination agent. A series of experiment using the real-world data will be performed to examine this mechanism.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1637-1646
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• 2009

Recently many researchers have been studying various methods for data integration. Among the integration methods that the researchers have studied, there are a method using metadata repository, and Topic Map which identifies the relationships between the data. This study suggests Meta-Topic Map to create Topic Map about search keyword by applying metadata and Topic Map, and the XMDR as a way to connect Meta-Topic Map with metadata in the legacy system. Considering the semantic relationship of user's keyword in the legacy system, the Meta-Topic Map provides the Topic Map format and generates the Topic Map about user's keyword. The XMDR performs structural integration through solving the problem of heterogeneity among metadata in the legacy system. The suggested svides isproves the interoperability among existing Relational Database constructed in the legacy system and the search efficiency and is efficient in expanding the system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.689-696
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• 2015

In this study, a learning system based on smart learning is proposed so that students with learning disabilities can learn the effective use of meta-cognitive to solve problems arising during the learning process. The features of the proposed system are as follow. First, it is possible to achieve students' individualized learning by use of smart devices and smart education system. Second, it is possible to provide the constant repetition learning for students. Third, students can improve their achievement using the proposed app. The proposed smart education system using meta-cognition was applied to some learning disabilities students. The following results were obtained. First, the disabled students could have an interest in learning math and improve confidence. Second, the student's mathematical problem-solving skills have improved. Third, students' individualized and self-directed learning was achieved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.191-193
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• 2015

Recently, with the economy and the information communication technology developed, the e-commerce market grows continuously. A meta-analysis refers to a statistical literature synthesis method from the quantitative results of many known empirical studies. We conducted a meta-analysis and review of between perceived risk to criterion variable on e-commerce researches. This study focused a total of 25 research papers that established causal relationships in between perceived risk to criterion variable on e-commerce published in Korean academic journals during 2000 and 2014. The result of the meta-analysis might be summarized that the effect size in the path from perceived risk to the criterion variable with the effect size -0.251. Based on these findings, several theoretical and practical implications were suggested and discussed with the difference from previous researches.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.848-854
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• 2014

A Meta-analysis refers to a statistical literature synthesis method from the quantitative results of many known empirical studies. We conducted a meta-analysis and review of external factors based on the technology acceptance model for Smartphone-related researches. This study surveyed 106 research papers that established causal relationships in the technology acceptance model published in Korean academic journals during 2008 and 2013. The result of the meta-analysis might be summarized that the playfulness has the highest effect size in the path from external factors to the perceived usefulness, with the effect size(0.536). Also the self efficacy showed the highest effect size(0.626) in the path from external factors to the perceived ease of use. Based on these findings, several theoretical and practical implications were suggested and discussed with the difference from previous researches.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.586-593
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• 2009

As most of the data configuration at distributed environment has a tree structure following the hierarchical classification, relative data retrieve is limited. Among these data, the data stored in a database has a problem in integration and efficient retrieve. Accordingly, we suggest the system that uses XMDR for distributed database integration and links XMDR to TopicMap for efficient retrieve of knowledge expressed hierarchically. We proposes a plan for efficient integration retrieve through using the XMDR which is composed of Meta Semantic Ontology, Instance Semantic Ontology and meta location, solves data heterogeneity and metadata heterogeneity problem and integrates them, and replaces the occurrence of the TopicMap with the Meta Location of the XMDR, which expresses the resource location of TopicMap by linking Meta Semantic Ontology and Instance Semantic Ontology of XMDR to the TopicMap.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1711-1718
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• 2015

A Meta-analysis refers to a statistical literature synthesis method from the quantitative results of many known empirical studies. Recently, the convergence of knowledge-based society and, information telecommunication technologies has a rapid impact on politics, economics and various fields. A meta-analysis was conducted to identify the relationships among satisfaction, trust, and loyalty in e-commerce studies. A total of 57 research papers published in Korean academic journals during 2002 and 2013 were reviewed and the causal relationships among satisfaction, trust, and loyalty in e-commerce were established. The result of the meta-analysis might be summarized that the highest effect size (r =. 591) was in the path from the satisfaction to the trust. The second biggest effect size (r =. 554) was found in the path between the satisfaction to the loyalty. The third biggest effect size (r =. 552) was found in the path between the trust to the loyalty. By the way, the smallest effect size (r =. 484) was found in the path between the trust to the satisfaction.