• Communications of Mathematical Education
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• v.23 no.2
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• pp.429-459
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• 2009

The purpose of this study was to help the students deepen their mathematical understanding and practitioner improve her mathematics lessons. The teacher-researcher developed mathematical situation based problem solving instruction model which was modified from PBL(Problem Based Learning instruction model). Three lessons were performed in the cycle of reflection, plan, and action. As a result of performance, reflective knowledges were noted as followed points; students' mathematical understanding, mathematical situation based problem solving instruction model, improvement of mathematics teachers.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.184-188
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• 2022

The article considers the improved method and model of automated air situation assessment using a decision support system based on fuzzy networks of target installations. The advanced method of automated assessment of the air situation using the decision support system is based on the methodology of reflexive control of the first rank. With this approach, the process of assessing the air situation in the framework of the formulated task can be reduced to determining the purpose, probabilistic nature of actions and capabilities of the air target. The use of a homogeneous functional network for the formal presentation of air situation assessment processes will formally describe the process of determining classes of events during air situation assessment and the process of determining quantitative and qualitative characteristics of recognized air situation situations. To formalize the patterns of manifestation of the values of quantitative and symbolic information, it is proposed to use the mathematical apparatus of fuzzy sets.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.390-396
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• 2007

Fuzzy-CBR Collision Avoidance Support System is a system that finds a solution from past knowledge retrieved from the database and adapted to a new situation. Its algorithm has resulted to an adapting a solution for a new situation. However, ontology is needed in identifying concepts, relations and instances that are involved in a situation in order to improve and facilitate the efficient retrieval of similar cases from the CBR database. This paper proposes the way to apply ontology for identifying the concepts involved in a new environment and use them as inputs, for a ship collision avoidance support system., Similarity will be obtained through document articulation and using abstraction levels. A conceptual model of a maneuvering situation will be built using these ontologies.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.31-37
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• 2017

There are lots of combined battlefield elements which complete the war. It looks problematic when collecting and analyzing these elements and then predicting the situation of war. Commander's experience and military power assessment have widely been used to come up with these problems, then simulated combat training program recently supplements the war-game models through recording real-time simulated combat data. Nevertheless, there are challenges to assess winning factors of combat. In this paper, we characterize the combat element (ce) by clustering simulated combat data, and then suggest multi-layered artificial neural network (ANN) model, which can comprehend non-linear, cross-connected effects among ces to assess mission completion degree (MCD). Through our ANN model, we have the chance of analyzing and predicting winning factors. Experimental results show that our ANN model can explain MCDs through networking ces which overperform multiple linear regression model. Moreover, sensitivity analysis of ces will be the basis of predicting combat situation.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.17-29
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• 2017

IRecently, researches on the recognition of indoor user situations through various sensors in a smart home environment are under way. In this paper, the case study was conducted to determine the operation of the robot vacuum cleaner by inferring the user 's indoor situation through the operation of home appliances, because the indoor situation greatly affects the operation of home appliances. In order to collect learning data for indoor situation awareness model learning, we received feedbacks from user when there was a mistake about the cleaning situation. In this paper, we propose a semi-supervised learning method using user feedback data. When we receive a user feedback, we search for the labels of unlabeled data that most fit the feedbacks collected through genetic algorithm, and use this data to learn the model. In order to verify the performance of the proposed algorithm, we performed a comparison experiments with other learning algorithms in the same environment and confirmed that the performance of the proposed algorithm is better than the other algorithms.

• Journal of Computing Science and Engineering
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• v.3 no.4
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• pp.238-259
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• 2009

In this paper we discuss personal data management with mobile devices, an activity requiring the composition of services offered by standard suites of applications. We propose a data model and an interface model that allows users to define activities, tasks and services, to navigate among them according to the evolution of the personal situation as perceived and interpreted by the users themselves. The interface model acts as a lens exploring the situation, zooming into the details, covering different areas of the personal data, supporting the user in the role of a composer of personal services.

• The Journal of Korea Robotics Society
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• v.3 no.1
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• pp.42-51
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• 2008

Robots need to understand as much as possible about their environmental situation and react appropriately to any event that provokes changes in their behavior. In this paper, we pay attention to topological relations between spatial objects and propose a model of robotic cognition that represents and infers temporal relations. Specifically, the proposed model extracts specified features of the cooccurrence matrix represents from disparity images of the stereo vision system. More importantly, a habituation model is used to infer intrinsic spatial relations between objects. A preliminary experimental investigation is carried out to verify the validity of the proposed method under real test condition.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.7
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• pp.738-742
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• 2008

The user model is an indispensable factor for providing users with personalized. services in the ubiquitous computing environment. In general user models, services which users prefer should be described in advance so that the system can recognize and interpret them automatically. Also, user's preferences as to the change of situation are not reflected in general user models due to their ignoring the situation. In this paper, we propose the self-growing user model which learns user experience and the system which automatically provides personalized community services through extracting user preferring services by situation.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.186-198
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• 2021

Security control using surveillance cameras is established when people observe all surveillance videos directly. However, this task is labor-intensive and it is difficult to detect all abnormal situations. In this paper, we propose a deep neural network model, called AT-Net, that automatically detects abnormal situations in the surveillance video, and introduces an automatic video surveillance system developed based on this network model. In particular, AT-Net alleviates the ambiguity of existing abnormal situation detection methods by mapping features representing relationships between people and objects in surveillance video to the new tensor structure based on sparse coding. Through experiments on actual surveillance videos, AT-Net achieved an F1-score of about 89%, and improved abnormal situation detection performance by more than 25% compared to existing methods.

• Journal of the Korean School Mathematics Society
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• v.1 no.1
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• pp.131-138
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• 1998

The aims of mathematical education are to improve uniformity and rigidity, and to apply to an information age which our society demands. One of the educational aims in the 6th educational curriculum emphasizes on the expansion of mathematical thought and utility, But, The change of contents in the text appears little. This means that mathematical teachers must actively develop the new types of problems. That the interests and concerns about mathematics lose the popularity and students recognize mathematics burdensome is the problems of not only teaching method, unrealistically given problems but abstractiveness and conceptions. Mathematical Modeling is classified exact model, almost exact theory based model and impressive model in accordance with the realistic situation and its equivalent degree of mathematical modeling. Mathematical Modeling is divided into normative model and descriptive model according to contributed roles of mathematics. The Modeling Applied Problems in the present text are exact model and stereotyped problems. That the expansion of mathematical thought in mathematics teaching fell into insignificance appears well in the result of evaluating students. For example, regardless of easy or hard problems, students tend to dislike the new types of mathematical problems which students can solve with simple thought and calculation. The ratings of the right answer tend to remarkably go down. If mathematical teachers entirely treat present situation, and social and scientific situation, students can expand the systematic thought and use the knowledge which is taught in the class. Through these abilities of solving problems, students can cultivate their general thought and systematic thought. So it is absolutely necessary for students to learn the Modeling Applied Problems.