• Journal of information and communication convergence engineering
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• v.1 no.2
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• pp.82-87
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• 2003

We are able to work on the shared virtual space in Web-based Collaborative Design System using only Internet and Web browser. Then the users will share 3D objects and must be able to pick the objects effectively which they want to manipulate. In this paper, picking is implemented not only by computing intersection of mouse pointer with the objects of the virtual world, but also by using capabilities and attributes of scene graph node, by setting bounds intersection testing instead of geometric intersection testing, by limiting the scope of the pick testing, using Java 3D. These methods can reduce the computation of picking and can pick 3D objects effectively and easily using the system of hierarchy.

• Journal of information and communication convergence engineering
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• v.17 no.2
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• pp.142-148
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• 2019

Relatively few countries provide separate bicycle lanes for cyclists. Hence, tools for suggesting cycling routes are essential for a safe and pleasant cycling experience. This study aims to develop a mobile application to build cycling routes based on user preferences, specifically location, search radius, ride distance, and number of optimal routes. Our application calls the Strava API to retrieve Strava cycling segments crowdsourced from the cycling community. Then, it creates a graph consisting of the start and end points of these segments. Beginning from a user-specified location, the depth-first search algorithm (DFS) is applied to find routes that conform to the user's preferences. Next, a set of optimal routes is obtained by computing a trade-off ratio for every discovered route. This ratio is calculated from the lengths of all segments and the lengths of all connecting paths. The connected routes can be displayed on a map on an Android device or exported as a GPX file to a bike computer. Future work must be performed to improve the design of the user interface and user experience.

• East Asian mathematical journal
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• v.35 no.4
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• pp.407-427
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• 2019

The six core competencies included in the mathematics curriculum revised in 2015 are problem solving, reasoning, communication, attitude and practice, creativity and convergence, information processing. In particular, the problem solving is very important for students' enhancing much higher mathematical thinking. Based on this competency, this study selected the four elements of the problem solving such as problem solving process, cooperative problem solving, mathematical modeling, problem posing. And also this study selected the domain of function which is comprised of the content of the coordinate plane, the graph, proportionality in the seventh grade mathematics textbook. By the subject of the ten kinds of textbook, this study examined how the four elements of the problem solving competency were shown in each textbook.

• Journal of Advanced Information Technology and Convergence
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• v.8 no.2
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• pp.89-99
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• 2018

Due to global warming, various natural disasters such as floods and droughts are increasing. If we can detect the possibility of natural disasters in advance, we can prevent massive damages caused by natural disasters. Recent advances in visual sensor technologies have enabled remote monitoring of a variety of natural environments, including lakes, rivers, and shores. In this paper, we propose a method to segment an image obtained from video sensor networks into regions in order to monitor the environment effectively. In the proposed method, we first partition the image into superpixels and model the connections between superpixels as a graph. Then, initial seeds for each region are set by using the prior information, and the initial seeds are expanded to form regions using agglomerative clustering. Experimental results show that the proposed method extracts the regions from natural environment images easily and accurately.

• East Asian mathematical journal
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• v.37 no.2
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• pp.149-167
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• 2021

The six core competencies included in the mathematics curriculum revised in 2015 are problem solving, reasoning, communication, attitude and practice, creativity and convergence, information processing. In particular, the reasoning is very important for students' enhancing much higher mathematical thinking. Based on this competency, this study selected the four elements of investigation and fact guess, justification, the logical performance of mathematical content and process, reflection of reasoning process, And also this study selected the domain of function which is comprised of the content of the coordinate plane, the graph, proportionality in the seventh grade mathematics textbook. By the subject of the ten kinds of textbook, this study examined how the four elements of the reasoning competency were shown in each textbook.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.56-61
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• 2021

Neighbor path selection is to pre-select alternate routes in case geographically correlated failures occur simultaneously on the communication network. Conventional heuristic-based algorithms no longer improve solutions because they cannot sufficiently utilize historical failure information. We present a novel solution model for neighbor path selection by using machine learning technique. Our proposed machine learning neighbor path selection (ML-NPS) model is composed of five modules- random graph generation, data set creation, machine learning modeling, neighbor path prediction, and path information acquisition. It is implemented by Python with Keras on Tensorflow and executed on the tiny computer, Raspberry PI 4B. Performance evaluations via numerical simulation show that the neighbor path communication success probability of our model is better than that of the conventional heuristic by 26% on the average.

• Journal of Korea Entertainment Industry Association
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• v.14 no.4
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• pp.349-354
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• 2020

This paper, firstly, propose a new Clustering scheme Based on Conceptual graphs (CBC) that can describe objects freely and can perform clustering efficiently. The conceptual clustering is one of machine learning technique. The similarity among the objects in conceptual clustering are decided on the bases of concept membership, unlike the general clustering scheme which decide the similarity without considering the context or environment of the objects. A new conceptual clustering scheme, CBC, which can perform efficient conceptual clustering by describing various objects freely with conceptual graphs is introduced in this paper.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.75-88
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• 2023

In a specific domain, experts have different understanding of domain knowledge or different purpose of constructing ontology. These will lead to multiple different ontologies in the domain. This phenomenon is called the ontology heterogeneity. For research fields that require cross-ontology operations such as knowledge fusion and knowledge reasoning, the ontology heterogeneity has caused certain difficulties for research. In this paper, we propose a novel ontology matching model that combines word embedding and a concatenated continuous bag-of-words model. Our goal is to improve word vectors and distinguish the semantic similarity and descriptive associations. Moreover, we make the most of textual and structural information from the ontology and external resources. We represent the ontology as a graph and use the SimRank algorithm to calculate the structural similarity. Our approach employs a similarity queue to achieve one-to-many matching results which provide a wider range of insights for subsequent mining and analysis. This enhances and refines the methodology used in ontology matching.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.557-559
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• 2022

최근 딥러닝의 기술발전으로 자연어 처리 분야에서 Q&A, 문장추천, 개체명 인식 등 다양한 연구가 진행 되고 있다. 딥러닝 기반 자연어 처리에서 좋은 성능을 보이는 트랜스포머 기반 BERT 모델의 성능향상에 대한 다양한 연구도 함께 진행되고 있다. 본 논문에서는 토픽모델인 잠재 디리클레 할당을 이용한 토픽별 지식그래프 분류와 입력문장의 토픽을 추론하는 방법으로 K-BERT 모델을 학습한다. 분류된 토픽 지식그래프와 추론된 토픽을 이용해 K-BERT 모델에서 대용량 지식그래프 사용의 효율적 방법을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.583-585
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• 2022

기존 군사 분야 영상 판독 시스템은 영상 판독관들의 작업 부담이 크고, 판독관들의 경험과 숙련도에 의존적이다. 이전 연구에서 판독관들의 부담을 줄이고 경험 및 숙련 의존도를 낮추기 위해 문장 추천 시스템을 제안하였다. 하지만 학습에 사용된 데이터의 양이 적고, 학습에 사용되지 않은 장비 혹은 지역 등의 단어가 등장 시 제대로 동작하지 않는 한계점이 있었다. 이를 해결하기 위해 학습 데이터 단계와 디코딩 단계에 지식그래프를 적용하여 문장의 다양성과 확장성을 확보하고, 데이터 부족 문제를 완화하였다. 이 연구는 추후 판독관들의 업무 과부화를 완화하고 업무 효율을 높일 수 있을 것이다.