• International Journal of Knowledge Content Development & Technology
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• v.5 no.2
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• pp.75-101
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• 2015

In this paper, we investigate the notion of error correction memory applied to technical texts. The main purpose is to introduce flexibility and context sensitivity in the detection and the correction of errors related to Constrained Natural Language (CNL) principles. This is realized by enhancing error detection paired with relatively generic correction patterns and contextual correction recommendations. Patterns are induced from previous corrections made by technical writers for a given type of text. The impact of such an error correction memory is also investigated from the point of view of the technical writer's cognitive activity. The notion of error correction memory is developed within the framework of the LELIE project an experiment is carried out on the case of fuzzy lexical items and negation, which are both major problems in technical writing. Language processing and knowledge representation aspects are developed together with evaluation directions.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.2
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• pp.15-24
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• 2000

An intelligent software system which can support efficiently and systematically machine tool design by utilizing deign knowledge is described in this paper. The process of embodiment design of a machining center was modelled represented by IDEF0 and embedded in the system. A hybrid type inference engine has been introduced so that the system can effec-tively deal with knowledge represented in diversified forms The design system was developed on the basis of object-ori-ented programming and has been coded into one software system which can be ported on Windows NT.

• Journal of Biosystems Engineering
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• v.18 no.2
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• pp.133-143
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• 1993

In developing an Expert System(ES), there are two ways. One is to develop an ES using AI(artificial Intelligence) languages and another using ES-development tools. CLIPS is an ES-development tool and has a powerful inference engine in it. Using the tool like CLIPS, knowledge engineer can concentrate on constructing a knowledge base without wasting time in developing an inference engine. However, CLIPS is lack of user-friendly interfaces for both knowledge enginners and users. Because CLIPS was developed in USA, it can not afford to use Korean language. Therefore, several user-friendly interfaces including hmenu, htille, hpcxdisplay were develpoed and added to CLIPS. CLIPS with the interfaces is called HCLIPS(Hangul CLIPS) in this paper. HCLIPS provides a new I/O device to be utilized for expert systems in Korean. HCLIPS can be efficiently used for developing expert systems in agriculture and consulting farmers interactively who are not familiar with computer programming and ES itself.

• Korean Management Science Review
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• v.14 no.1
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• pp.205-227
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• 1997

Higher level representation splay an important role in model management systems. The role is to make decision makers friendly represent their problem using the representations. In this research, we address higher level representations including five distinctivenesses: Objective, Node, Link, Topological Constraint including five components, and Decision, Therefore, it is developed a system called HLRNET that implements the building procedure of network models using structural knowledge and object data The paper particularly elaborates all components included in each of distinctiveness extracted from structural characteristics of a lot of telecommunication network models. Higher level representations represented with five destinctivenesses should be converted into base level representations which are employed for semantic representations of linear and integer programming problems in a knowledge-assisted optimization modeling system. The system is illustrated with an example of the local access network model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4007-4024
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• 2020

It is tremendously important to construct decision trees to use as a tool for knowledge representation from a given decision table. However, the usual algorithms may split the decision table based on each value, which is not efficient for numerical attributes. The methodology of this paper is to split the given decision table into binary groups as like the CART algorithm, that uses binary split to work for both categorical and numerical attributes. The difference is that it uses split for each attribute established by the directed acyclic graph in a dynamic programming fashion whereas, the CART uses binary split among all considered attributes in a greedy fashion. The aim of this paper is to study the effect of binary splits in comparison with each value splits when building the decision trees. Such effect can be studied by comparing the number of nodes, local and global misclassification rate among the constructed decision trees based on three proposed algorithms.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.2
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• pp.103-116
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• 2017

In this paper, we present the design and implementation of a large-scale qualitative spatial reasoner, which can derive new qualitative spatial knowledge representing both topological and directional relationships between two arbitrary spatial objects in efficient way using Aparch Spark SQL. Apache Spark SQL is well known as a distributed parallel programming environment which provides both efficient join operations and query processing functions over a variety of data in Hadoop cluster computer systems. In our spatial reasoner, the overall reasoning process is divided into 6 jobs such as knowledge encoding, inverse reasoning, equal reasoning, transitive reasoning, relation refining, knowledge decoding, and then the execution order over the reasoning jobs is determined in consideration of both logical causal relationships and computational efficiency. The knowledge encoding job reduces the size of knowledge base to reason over by transforming the input knowledge of XML/RDF form into one of more precise form. Repeat of the transitive reasoning job and the relation refining job usually consumes most of computational time and storage for the overall reasoning process. In order to improve the jobs, our reasoner finds out the minimal disjunctive relations for qualitative spatial reasoning, and then, based upon them, it not only reduces the composition table to be used for the transitive reasoning job, but also optimizes the relation refining job. Through experiments using a large-scale benchmarking spatial knowledge base, the proposed reasoner showed high performance and scalability.

• Journal of The Korean Association of Information Education
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• v.21 no.1
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• pp.13-22
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• 2017

Recently, the emphasis on education of informatics gifted elementary students is to make creative leader in knowledge-based society. It need the high mental faculties and problem solving ability to solve many problem situations for students. In this paper, we developed App Inventor programming education plan. We taught this plan to gifted elementary students and observed the effects of their problem solving ability, self-efficacy and achievement of programing process. In order to achieve the research goals, we designed the appropriate App Inventor programming plan for gifted elementary students and we changed the Learning Model of Renzulli's three step for gifted students to achieve this research goals. Designed learning program was utilized by twenty informatics gifted elementary students for 15 times during five weeks period. In conclusion, we confirmed that App Inventor programming education for gifted elementary students affected the problem solving ability, self-efficacy and achievement of programing process positively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2497-2503
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• 2012

In this study an educational robot for programming education was designed and implemented. The robot in this study is composed of hardware containing a sensor, a processor, and a motor driver circuit, software to control the educational robot, machine parts to manufacture the robot structure, and a teaching material containing educational contents and the manufacturing manual. This robot is characterized by direct programming without a computer, which gives no spatial restrictions on robot education and enables dynamic program education beyond limitations of the existing static computer program education since students' programming results are found in the robot's movements. User-centered functional commands, which make it possible to control the robot with simple knowledge concerning hardware and basic commands, were used to enable even students who first accessed a robot or computer program to make access with ease.

• Journal of The Korean Association of Information Education
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• v.18 no.2
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• pp.255-264
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• 2014

Information and knowledge society in the 21st century creativeness education is very important. The core of creativity education is software education that is to make something based on the creative thinking. Each country has already emphasizes software education. And Software education for elementary school students reflect the curriculum. Software education can be divided into four areas which are information, problem solving, algorithms, and programming. In this study, I propose criteria for the achievement of a computer program for elementary school students. The proposed criteria of programming education are fulfilled in other subjects curriculum of korea and other national software curriculum. This study is analyzed by the validity of the Delphi analysis of primary school teachers. The result of this study is that elementary school students when teaching computer programming that is very reasonable results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.165-172
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• 2017

Recently, many supports about the education linked with industrial field have been provided in technical specialized high schools. In order to keep pace with the global trend to emphasize software education and to move away from traditional grammar-based programming learning, various physical computing tools have been used in the education fields. For this study, we conducted a programming class using Raspberry Pi for technical high school students. In the class, students were instructed to produce actual results based on the knowledge they had learned. Project-based learning was used to help students create products and thus they performed tasks while discussing and collaborating on a team-by-team basis. In particular, self-regulation learning strategies were considered to provide effective project-based instruction. After the class, we interviewed the students' satisfaction with it. The results showed that the students' satisfaction was high, and the fellow teachers also had a lot of possibilities and expectations about the programming instruction and project-based learning using Raspberry Pi.