• 한국수학교육학회지시리즈D:수학교육연구
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• 제25권2호
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• pp.135-158
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• 2022

This study aimed to building models to understand the relationships between reasoning resources and content knowledge. We applied Support Vector Machine and linear models to the data including fifth graders' scores in the Cornel Critical Thinking Test and the Iowa Assessments, demographic information, and learning science approach (a student-centered approach to learning called the Science Writing Heuristic [SWH] or traditional). The SWH model showing the relationships between critical thinking domains and academic achievement at grade 5 was developed, and its validity was tested across different learning environments. We also evaluated the stability of the model by applying the SWH models to the data of the grade levels. The findings can help mathematics educators understand how critical thinking and achievement relate to each other. Furthermore, the findings suggested that reasoning in mathematics classrooms can promote performance on standardized tests.

• 전자통신동향분석
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• 제38권6호
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• pp.1-11
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• 2023

Large language models seem promising for handling reasoning problems, but their underlying solving mechanisms remain unclear. Large language models will establish a new paradigm in artificial intelligence and the society as a whole. However, a major challenge of large language models is the massive resources required for training and operation. To address this issue, researchers are actively exploring compact large language models that retain the capabilities of large language models while notably reducing the model size. These research efforts are mainly focused on improving pretraining, instruction tuning, and alignment. On the other hand, chain-of-thought prompting is a technique aimed at enhancing the reasoning ability of large language models. It provides an answer through a series of intermediate reasoning steps when given a problem. By guiding the model through a multistep problem-solving process, chain-of-thought prompting may improve the model reasoning skills. Mathematical reasoning, which is a fundamental aspect of human intelligence, has played a crucial role in advancing large language models toward human-level performance. As a result, mathematical reasoning is being widely explored in the context of large language models. This type of research extends to various domains such as geometry problem solving, tabular mathematical reasoning, visual question answering, and other areas.

• 한국수학교육학회지시리즈A:수학교육
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• 제55권3호
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• pp.251-279
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• 2016

There are many studies on 'how' students solve mathematical problems, but few of them sufficiently explained 'why' they have to solve the problems in their own different ways. As quantitative reasoning is the basis for algebraic reasoning, to scrutinize a student's way of dealing with quantities in a problem situation is critical for understanding why the student has to solve it in such a way. From our teaching experiments with two ninth-grade students, we found that emergences of a certain level of covariational reasoning were highly consistent across different types of problems within each participating student. They conceived the given problem situations at different levels of covariation and constructed their own quantity-structures. It led them to solve the problems with the resources accessible to their structures only, and never reconciled with the other's solving strategies even after having reflection and discussion on their solutions. It indicates that their own structure of quantities constrained the whole process of problem solving and they could not discard the structures. Based on the results, we argue that teachers, in order to provide practical supports for students' problem solving, need to focus on the students' way of covariational reasoning of problem situations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권6호
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• pp.1599-1618
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• 2024

Access control has always been one of the effective methods to protect data security. However, in new computing environments such as big data, data resources have the characteristics of distributed cross-domain sharing, massive and dynamic. Traditional access control mechanisms are difficult to meet the security needs. This paper proposes CACM-MMSR to solve distributed cross-domain access control problem for massive resources. The method uses blockchain and smart contracts as a link between different security domains. A permission decision model migration method based on access control logs is designed. It can realize the migration of historical policy to solve the problems of access control heterogeneity among different security domains and the updating of the old and new policies in the same security domain. Meanwhile, a semantic reasoning-based permission decision method for unstructured text data is designed. It can achieve a flexible permission decision by similarity thresholding. Experimental results show that the proposed method can reduce the decision time cost of distributed access control to less than 28.7% of a single node. The permission decision model migration method has a high decision accuracy of 97.4%. The semantic reasoning-based permission decision method is optimal to other reference methods in vectorization and index time cost.

• 인터넷정보학회논문지
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• 제16권6호
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• pp.57-67
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• 2015

This paper proposes an Fuzzy-based Risk Reasoning Driving Strategy on VANET. Its first reasoning phase consists of a WC_risk reasoning that reasons the risk by using limited road factors such as current weather, density, accident, and construction, a DR_risk reasoning that reasons the risk by combining the driving resistance with the weight value suitable for the environment of highways and national roads, a DS_risk reasoning that judges the collision risk by using the travel direction, speed. and distance of vehicles and pedestrians, and a Total_risk reasoning that computes a final risk by using the three above-mentioned reasoning. Its second speed reduction proposal phase decides the reduction ratio according to the result of Total_risk and the reduction ratio by comparing the regulation speed of road to current vehicle's speed. Its third risk notification phase works in case current driving speed exceeds regulation speed or in case the Total_risk is higher than AV(Average Value). The Risk Notification Phase informs rear vehicles or pedestrians around of a risk according to drivers's response. If drivers use a brake according to the proposed speed reduction, the precedent vehicles transfers Risk Notification Messages to rear vehicles. If they don't use a brake, a current driving vehicle transfers a Risk Message to pedestrians. Therefore, this paper not only prevents collision accident beforehand by reasoning the risk happening to pedestrians and vehicles but also decreases the loss of various resources by reducing traffic jam.

• 한국가정과교육학회지
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• 제12권3호
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• pp.115-127
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• 2000

The purpose of this study is to develop lesson plans. teaching guide, and teaching materials applying practical reasoning teaching model in the area of ’human development and family relationship’in middle school home economics. The practical reasoning teaching model consists of five factors: Desired results, Awareness of context, Alternative approaches, Consequences of action, and Action. This study based on practical reasoning has following process: Curriculum development. Developing lesson pan, teaching material, an teaching guide, Experimental teaching and evaluation. Feedback, Production of CD-Rom. Teaching guide includes lesson plan, workbook multimedia materials and teaching resources. Especially teaching guide in CD-Rom can be used effectively in the actual teaching. In the classroom, this teaching model accomplished active and interesting participation of teachers and students. It is proposed that practical reasoning teaching model should be applied to other areas of home economics. In addition various teaching materials based on practical reasoning need to developed.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2008년도 춘계 종합학술대회 논문집
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• pp.489-493
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• 2008

유비쿼터스 컴퓨팅의 주요 목적 가운데 하나는 지능 공간에 존재하는 다양한 자원들을 공유하고 최적의 자원을 추론하여 사용자를 위한 효과적인 서비스를 구성하는 것이다. 그러나 각 응용들은 서로 다른 표현 방법으로 자원과 서비스들을 기술하고 있으며 이러한 이질적인 정보 표현 형식은 공유와 추론을 어렵게 하는 요인이 된다. 그러므로 자원 공유를 위해 필요한 정보를 단일화하는 것이 필요하며 온톨로지는 이를 표현하기위한 한 가지 방안이다. 본 논문에서는 유비쿼터스 지능 공간 내에서 제공 가능한 서비스들을 정의하고 이를 위한 온톨로지를 제안한다. 또한 서비스를 구성하기 위하여 주변의 자원을 공유하기 위한 자원 온톨로지를 정의한다. 이렇게 정의된 우리의 온톨로지들은 유비쿼터스 지능 공간에서 사용자에게 효과적인 서비스를 구성하기위한 자원 집합을 추론하기위해서 사용된다.

• 한국컴퓨터정보학회논문지
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• 제22권3호
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• pp.35-43
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• 2017

In IoT(Internet of Things) environment, users want to receive customized service by users' personal device such as smart watch and pendant. To fulfill this requirement, the mobile device should support a lot of functions. However, the miniaturization of mobile devices is another requirement and has limitation such as tiny display. limited I/O, and less powerful processors. To solve this limitation problem and provide customized service to users, this paper proposes a collaboration system for sharing various computing resources. The paper also proposes the method for reasoning and recommending suitable resources to compose the user-requested service in small device with limited power on expected time. For this goal, our system adopts MBTI(Myers-Briggs Type Indicator) to analyzes user's behavior pattern and recommends personalized resources based on the result of the analyzation. The evaluation in this paper shows that our approach not only reduces recommendation time but also increases user satisfaction with the result of recommendation.

• Earthquakes and Structures
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• 제14권2호
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• pp.143-153
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• 2018

Correlation among different factors must be considered for selection of influencing factors in safety monitoring of high dam including positive correlation of variables. Therefore, a new factor selection method was constructed based on Copula entropy and mutual information theory, which was deduced and optimized. Considering the small sample size in high dam monitoring and distribution of daily monitoring samples, a computing method that avoids causality of structure as much as possible is needed. The two-dimensional normal information diffusion and fuzzy reasoning of pattern recognition field are based on the weight theory, which avoids complicated causes of the studying structure. Hence, it is used to dam safety monitoring field and simplified, which increases sample information appropriately. Next, a complete system integrating high dam monitoring and uncertainty prediction method was established by combining Copula entropy theory and information diffusion theory. Finally, the proposed method was applied in seepage monitoring of Nuozhadu clay core-wall rockfill dam. Its selection of influencing factors and processing of sample data were compared with different models. Results demonstrated that the proposed method increases the prediction accuracy to some extent.

• Asia pacific journal of information systems
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• 제16권2호
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• pp.69-84
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• 2006

Importance of Today's diffusion of integrated hospital information systems is that various and huge amount of data is being accumulated in their database systems. Many researchers have studied utilizing such hospital data. While most researches were conducted mainly for medical diagnosis, there have been insufficient studies to develop medical care cost prediction model, especially using machine learning techniques. In this research, therefore, we built a medical care cost prediction model for cancer patients using CBR (Case-Based Reasoning), one of the machine learning techniques. Its performance was compared with those of Neural Networks and Decision Tree models. As a result of the experiment, the CBR prediction model was shown to be the best in general with respect to error rate and linearity between real values and predicted values. It is believed that the medical care cost prediction model can be utilized for the effective management of limited resources in hospitals.