• Journal of the Korean Society for information Management
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• v.34 no.1
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• pp.177-195
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• 2017

This study attempts to infer research fronts using factor graph model based on heterogeneous features. The model suggested by this study infers research fronts having documents with the potential to be cited multiple times in the future. To this end, the documents are represented by bibliographic, network, and content features. Bibliographic features contain bibliographic information such as the number of authors, the number of institutions to which the authors belong, proceedings, the number of keywords the authors provide, funds, the number of references, the number of pages, and the journal impact factor. Network features include degree centrality, betweenness, and closeness among the document network. Content features include keywords from the title and abstract using keyphrase extraction techniques. The model learns these features of a publication and infers whether the document would be an RF using sum-product algorithm and junction tree algorithm on a factor graph. We experimentally demonstrate that when predicting RFs, the FG predicted more densely connected documents than those predicted by RFs constructed using a traditional bibliometric approach. Our results also indicate that FG-predicted documents exhibit stronger degrees of centrality and betweenness among RFs.

• Communications of Mathematical Education
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• v.37 no.4
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• pp.569-590
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• 2023

The purpose of this case study is to compare and analyze the covariational reasoning levels of two middle school students revealed in the process of solving and generalizing algebra word problems. A class was conducted with two middle school students who had not learned quadratic equations in school mathematics. During the retrospective analysis after the class was over, a noticeable difference between the two students was revealed in solving algebra word problems, including situations where speed changes. Accordingly, this study compared and analyzed the level of covariational reasoning revealed in the process of solving or generalizing algebra word problems including situations where speed is constant or changing, based on the theoretical framework proposed by Thompson & Carlson(2017). As a result, this study confirmed that students' covariational reasoning levels may be different even if the problem-solving methods and results of algebra word problems are similar, and the similarity of problem-solving revealed in the process of solving and generalizing algebra word problems was analyzed from a covariation perspective. This study suggests that in the teaching and learning algebra word problems, rather than focusing on finding solutions by quickly converting problem situations into equations, activities of finding changing quantities and representing the relationships between them in various ways.

• School Mathematics
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• v.19 no.2
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• pp.345-367
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• 2017

The purpose of this study is to investigate the proportional reasoning of middle school students during the process of expressing and interpreting the graphs. We collected data from a teaching experiment with four 7th grade students who participated in 23 teaching episodes. For this study, the differences between student A and student B-who joined theteaching experiment from the $1^{st}$ teaching episode through the $8^{th}$ -in understanding graphs are compared and the reason for their differences are discussed. The results showed different proportional solving strategies between the two students, which revealed in the course of adjusting values of two given variables to seek new values; student B, due to a limited ability for proportional reasoning, had difficulty in constructing graphs for given situations and interpreting given graphs.

• Journal of IKEEE
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• v.18 no.1
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• pp.57-63
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• 2014

This paper is to technically implement the sensing platform for Home-Wellness Robot. The self-Localization of indoor mobile robot is very important for the sophisticated trajectory control. In this paper, the robot's self-localization algorithm is designed by RF sensor network and fuzzy inference. The robot realizes its self-localization, using RFID sensors, through the collaboration algorithm which uses fuzzy inference for combining the strengths of triangulation and triangulation. For the triangulation self-Localization, RSSI is implemented. TOA method is used for realizing the triangulation self-localization. The final improved position is, through fuzzy inference, made by the fusion algorithm of the resultant coordinates from trilateration and triangulation in real time. In this paper, good performance of the proposed self-localization algorithm is confirmed through the results of a variety of experiments in the base of RFID sensor network and reader system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1693-1705
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• 2013

To restore old aqueduct in Korea which is a irrigation bridge to supply water in paddy field area, it is needed to estimate approximate costs of restoration because the basic design for estimation of construction costs is often ruled out in current system. In this paper, estimating models of construction costs were developed on the basis of performance data for restoration of RC aqueduct bridges since 2003. The regression analysis (RA) model and case-based reasoning (CBR) model for the estimation of construction costs were developed respectively. Error rate of simple RA model was lower than that of multiple RA model. CBR model using genetic algorithm (GA) has been applied in the estimation of construction costs. In the model three factors like attribute weight, attribute deviation and rank of case similarity were optimized. Especially, error rate of estimated construction costs decreased since limit ranges of the attribute weights were applied. The results showed that error rates between RA model and CBR models were inconsiderable statistically. It is expected that the proposed estimating method of approximate costs of aqueduct restoration will be utilized to support quick decision making in phased rehabilitation project.

• Journal of Educational Research in Mathematics
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• v.23 no.1
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• pp.1-16
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• 2013

The primary purpose of this study is to survey multiplicative thinking levels and its characteristics of third graders in elementary school and to analyze how to use it when they solve the proportional problems. As results, the transition thinking ranked the highest among the four kinds of thinking levels when the $3^{rd}$ graders solved the multiplication problems. It means that the largest numbers of students still can not distinguish the additive and multiplicative situations completely and remain in the transition thinking, which thinks both additively and multiplicatively. In addition, the performance of solving proportional problems was distinguished from the levels of thinking. Through this study, we can give some implications of the importance of multiplicative thinking and instructional methods related to multiplication.

• Journal of the Korea Society for Simulation
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• v.26 no.2
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• pp.59-65
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• 2017

Along with the development of M&S, modeling research utilizing AI technology is attracting attention because of the fact that the needs of fields including human decision making such as defense M&S are increased. Obviously AI is a way to solve complex problems. However, AI did not consider logical time such as input time and processing time required by M&S. Therefore, in this paper we proposed a "time-based expert system" which redesigned the representative AI technology rule-based expert system. It consists of a rule structure "IF-THEN-AFTER" and an inference engine, takes logical time into consideration. We also tried logical analysis using a simple example. As a result of the analysis, the proposal Time-based Expert System proved that the result changes according to the input time point and inference time.

• Journal of The Korean Association For Science Education
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• v.29 no.8
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• pp.898-909
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• 2009

In this study, we investigated the influences of the role-playing analogy in chemistry concept learning on mapping understanding and mapping errors by analogical reasoning ability level. Seventh-graders (N=151) at a middle school were assigned to the comparison group and the experimental group. The students of the experimental group were taught with the 'running in the circle' role-playing analogy. After the students were taught about 'the relation between volume and pressure of gas', the test of mapping understanding in the next class and the retention test four weeks later were administered. The students with typical mapping errors were also interviewed to investigate their mapping processes. The results revealed that the role-playing analogy in chemistry concept learning improved mapping understanding and its retention regardless of analogical reasoning ability level. It was also found that the students in the experimental group had fewer mapping errors than those in the comparison group. However, there were similar patterns of mapping errors in both groups, and there were no significant differences in the frequencies of each type of mapping errors by analogical reasoning ability level. Educational implication of these findings are discussed.

• Tunnel and Underground Space
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• v.9 no.3
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• pp.214-220
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• 1999

In this study, the validity of items of RMR system is evaluated and the applicability of this system to the data measured in Korean sites if discussed. Database was constructed from 139 sites, which are composed of subways, railway tunnels and road tunnels. These sites are located nationwide. Analysis shows that original classification of Bieniawski is valid although it was derived empirically. But it has considerable rating difference (error) in the result of Korean application. Thus new classification systems of KRMRI and KRMR2 are suggested, which are deduced from the Korean database. The former includes adjusted ratings and the latter adopts two more items. These are deduced by artificial neural network because it is difficult to select \`characteristic value'to estimate rock quality.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.165-165
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• 2021

전 세계적으로 하천 수질이 저하되고 있다. 이는 수생태계의 손상을 야기하고 인류를 위한 하천의 물 공급원 기능에 저해 요소로 작용한다. 오염된 수생태계에 대한 효과적인 맞춤형 관리전략을 수립하려면 수질의 시공간적 변동 요인을 이해하는 것이 중요하다. 시간적 및 공간적 변동성이 모두 중요하지만, 본 연구에서는 낙동강 전체 유역에서 나타나는 공간적인 변동성에 집중하여 하천 수질의 공간적 차이에 영향을 미치는 요인을 식별하고 그들의 상대적 중요성을 분석하고자 하였다. 분석을 위해 낙동강 유역 전역의 40개 수질오염총량관리 단위유역에서 5년 동안 수집된 하천 총인 농도와 유역특성 자료를 사용하였다. 총인 농도의 공간적 변동성에 영향을 미치는 주요 유역특성을 식별하기 위한 통계모델 선정을 위해 완전 탐색 접근법과 베이지안 추론이 적용되었다. 완전 탐색은 두 단계에 걸쳐 진행되었으며, 1 단계 완전 탐색의 결과로 유역특성 자료들의 중요도가 선정되었으며 2 단계 완전탐색 결과로 통계모델이 우선 선정되었다. 우선 선정된 통계모델은 베이지안 추론을 통해 모델의 정확도와 불확실성이 분석되었고 공간적 변동성 분석을 위한 최적 모델이 선정되었다. 본 연구의 결과로 낙동강 하천 총인 농도의 공간적 변동성에 영향을 미치는 주요 유역특성에 대한 통찰력이 제공된다. 또한 식별된 주요 유역특성은 유역특성 변화에 대한 하천의 수질 반응을 예측하는데 사용될 수 있을 것으로 기대된다.