• Journal of KIISE
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• v.43 no.12
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• pp.1365-1375
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• 2016

One of the most important capabilities for autonomous service robots working in living environments is to recognize and understand the correct context in dynamically changing environment. To generate high-level context knowledge for decision-making from multiple sensory data streams, many technical problems such as multi-modal sensory data fusion, uncertainty handling, symbolic knowledge grounding, time dependency, dynamics, and time-constrained spatio-temporal reasoning should be solved. Considering these problems, this paper proposes an effective dynamic context management and spatio-temporal reasoning method for intelligent service robots. In order to guarantee efficient context management and reasoning, our algorithm was designed to generate low-level context knowledge reactively for every input sensory or perception data, while postponing high-level context knowledge generation until it was demanded by the decision-making module. When high-level context knowledge is demanded, it is derived through backward spatio-temporal reasoning. In experiments with Turtlebot using Kinect visual sensor, the dynamic context management and spatio-temporal reasoning system based on the proposed method showed high performance.

• International Journal of Safety
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• v.4 no.2
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• pp.12-17
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• 2005

This paper aims at the development of an knowledge base for an electrical fire cause diagnosis system using the entity relation database. The relation database which provides a very simple but powerful way of representing data is widely used. The system focused on database construction and cause diagnosis can diagnose the causes of electrical fires easily and efficiently. In order to store and access to the information concerned with electrical fires, the key index items which identify electrical fires uniquely are derived out. The knowledge base consists of a case base which contains information from the past fires and a rule base with rules from expertise. To implement the knowledge base, Access 2000, one of DB development tools under windows environment and Visual Basic 6.0 are used as a DB building tool. For the reasoning technique, a mixed reasoning approach of a case based inference and a rule based inference has been adopted. Knowledge-based reasoning could present the cause of a newly occurred fire to be diagnosed by searching the knowledge base for reasonable matching. The knowledge-based database has not only searching functions with multiple attributes by using the collected various information(such as fire evidence, structure, and weather of a fire scene), but also more improved diagnosis functions which can be easily wed for the electrical fire cause diagnosis system.

• Journal of The Korean Digital Architecture Interior Association
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• v.11 no.3
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• pp.53-59
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• 2011

In creative design, it is necessary to understand the characteristic of architectural design. In the world of design problem, a distinction can be made between those that are well-defined and those that are ill-defined. Well-defined problems are those for which the ends or goal, are already prescribed and apparent, their solution requires the provision of appropriate means. For ill-defined problems, on the other hand, both the ends and the means of solution are unknown at the outset of the problem solving exercise, at least in their entirety. Most of design problems is ill-defined, which is unknown at the beginning of the problem solving exercise. In order to solve the design problem, Designers take advantage of the search methods of problem space, such as global-search-methods(depth-first-methods, breath-first-methods), local-search-methods(generate and test, heuristics, hill-climbing, reasoning) and visual thinking, which is represented through sketching. Sketching is a real part of design reasoning and it does so through a special kind of visual imagery. Also in the design problem solving it have been an important means of problem exploration and solution generation. By sketching, they represent images held in the mind as well as makes graphic images which help generate mental images of entity that is being designed. The search methods of problem space and a visual thinking have been crucially considered in the architectural design. The purpose of this paper is to explore the property of design by means of the pre-existed-experiment data and literature research. The findings will help design the architectural design for more creative results.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.803-810
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• 2005

Information retrieval is one of the most challenging areas in which the ontology technology is effectively used. Among them image retrieval using the image meta data and ontology is the one that can substitute the keyword-based image retrieval. In the paper, the retrieval of visual media such as the art image and photo picture is handled. It is assumed that there are more than one service providers of the visual media and also there is one central service broker that mediates the user's query. Given the user's query the first step that must be done in the service broker is to get the list of candidate service providers that fit the query. This is done by defining various ontologies such as the service ontology and matching the query against the ontology and providers. A novel matching method based on the ASN.1. The experiment shows that the method is more effective than existing tree-based and interval-based methods. Ontology merging issue is also handled that can happen when the service providers register their service into the service broker. An effective method is also proposed.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.12
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• pp.485-496
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• 2018

So far, the deep learning, a field of artificial intelligence, has achieved remarkable results in solving problems from unstructured data. However, it is difficult to comprehensively judge situations like humans, and did not reach the level of intelligence that deduced their relations and predicted the next situation. Recently, deep neural networks show that artificial intelligence can possess powerful relational reasoning that is core intellectual ability of human being. In this paper, to analyze and observe the performance of Relation Networks (RN) among the neural networks for relational reasoning, two types of RN-based deep neural network models were constructed and compared with the baseline model. One is a visual question answering RN model using Sort-of-CLEVR and the other is a text-based question answering RN model using bAbI task. In order to maximize the performance of the RN-based model, various performance improvement experiments such as hyper parameters tuning have been proposed and performed. The effectiveness of the proposed performance improvement methods has been verified by applying to the visual QA RN model and the text-based QA RN model, and the new domain model using the dialogue-based LL dataset. As a result of the various experiments, it is found that the initial learning rate is a key factor in determining the performance of the model in both types of RN models. We have observed that the optimal initial learning rate setting found by the proposed random search method can improve the performance of the model up to 99.8%.

• School Mathematics
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• v.13 no.4
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• pp.581-598
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• 2011

Given the growing agreement that algebra should be taught in the early stage of the curriculum, considerable studies have been conducted with regard to early algebra in the elementary school. However, there has been lack of research on how to organize mathematic lessons to develop of algebraic reasoning ability of the elementary school students. This research attempted to gain specific and practical information on effective algebraic teaching and learning in the elementary school. An exploratory qualitative case study was conducted to the fourth graders. This paper focused on the associative law of the multiplication. This paper showed what kinds of activities a teacher may organize following three steps: (a) focus on the properties of numbers and operations in specific situations, (b) discovery of the properties of numbers and operations with many examples, and (c) generalization of the properties of numbers and operations in arbitrary situations. Given the steps, this paper included an analysis on how the students developed their algebraic reasoning. This study provides implications on the important factors that lead to the development of algebraic reasoning ability for elementary students.

• Architectural research
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• v.17 no.2
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• pp.57-64
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• 2015

In architectural planning, previous cases of similar spatial program provide important data for architectural design. Case-based reasoning (CBR) paradigm in the field of architectural design is closely related to the designing behavior of a planner who makes use of similar architectural designs and spatial programs in the past. In CBR, spatial graph can be constituted with most fundamental data, which can provide a method of searching spatial program by using visual graphs. This study developed a system for CBR that can analyze the similarity through graph comparison and search for buildings. This is an integrated system that is able to compare space similarity of different buildings and analyze their types, in addition to the analysis on a space within a single structure.

• Journal of The Korean Association For Science Education
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• v.38 no.2
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• pp.161-170
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• 2018

Various forms of visual representations enable scientific discovery and scientific reasoning when scientists conduct research. Similarly, in science education, visual representations are important as a means to promote students' understanding of science concepts and scientific thinking skills. To provide a framework that could facilitate the effective use of visual representations in science classroom and systemic science education research, a visual representation competence taxonomy (VRC-T) was developed in this study. VRC-T includes two dimensions: the type of visual representation, and the cognitive process of visual representation. The initial categories for each dimension were developed based on literature review. Then validation and revision was made by conducting teachers' workshop and survey to experts. The types of visual representations were grouped into 3 categories (descriptive, procedural, and explanative representations) and the cognitive processes were grouped into 3 categories (interpretation, integration, and construction). The sub categories of each dimension and the validation process would be explained in detail.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.289-297
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• 2012

It is a recent trend to utilize a variety of visual tools(process map, mindmap, ERD) to create, when we create the design of information system or business models. Theses visual tool is standardized tools as process map or BPMN, on the other hand, there is also a non-standardized tools as mindmap. The utilization of the non-standardized tools as mindmap in startups is a increasing trend, because of the order the release of creative thinking to design new business model. Mindmaps can be divided into pen-based mindmap(of hand-written) and computer-based mindmap. This study was conducted under the premise of a different thinking pattern, when you take advantage of pen-based mindmap and computer-based mindmap. In other words, the pen-based mindmap is a tool for deductive reasoning and the computer-based mindmap is a tool would be more appropriate for inductive thinking. The purpose of this study is to investigate these relationships through experiments. In this study propose guidelines how visual tools, when designing a social media business models.

• Journal of the Korean School Mathematics Society
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• v.11 no.3
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• pp.513-541
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• 2008

The purposes of the study were to investigate whether the use of the Geometer's Sketchpad(GSP) is more effective than the use of traditional tools such as ruler and protractor to enhance eighth- grade students' understanding of quadrilaterals and geometric reasoning ability and to examine how the use of the software affects on the development of students' understanding and reasoning ability. According to the results of the posttest, there was a significant difference in student achievement between students using GSP and students using ruler and protractor. Students using GSP significantly outperformed students using ruler and protractor on the posttest. Student interview data showed that the use of the GSP was more effective in developing students' geometric reasoning ability. Students using GSP achieved higher degrees of acquisition for van Hiele level 2 and 3 than students using ruler and protractor. Dynamic visual representations and hands-on experiences provided in GSP learning environment helped students approach quadrilateral concepts more conceptually and realize their pre-existing conceptual errors and re-conceptualize their mathematical ideas.