• The Mathematical Education
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• v.50 no.2
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• pp.149-164
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• 2011

The purpose of this study was to analyze the perception of elementary school teachers about situation-contextual problem and to show efforts on order to enable students to improve their problem solving ability and thinking skills. In this research, two hundred elementary school teachers in Seoul were surveyed and three elementary school teachers were interviewed to determine their perception and the status about situation-contextual problem. As a result, most of teachers replied that situation-contextual problem would be useful and applicable to improve students' problem solving and creative thinking skill.

• Journal of KIISE:Software and Applications
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• v.33 no.3
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• pp.316-334
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• 2006

In the traditional computing paradigm, developers design software to run in a fixed and well-defined environment. The real environment, however, is too complicated to analyze all situations perfectly. Consequently, traditional software, which is implemented only for what is wanted as input, often fails badly in real environment. As a new approach, self-adaptive software can avoid runtime failures adapting to unpredictable situations. Self-adaptive software must firstly evaluate the contextual situation to determine the need for adaptation. Existing researches do not support the abstraction mechanism for identifying contextual problem. Consequently, they can have troubles with identifying the contextual problem as the execution environment is getting complex. In addition, they cannot support the expandability for contextual problems, which software can evaluate. This paper suggests the goal-based evaluation method of contextual situation for coping with the limitations of existing researches.

• Journal of the Korean Chemical Society
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• v.65 no.5
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• pp.333-346
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• 2021

In this study, we developed education materials using history of science related to the experiment of 'Boyle's air pump' and the Boyle and Hobbs' debate of vacuum to find out the perceptions of NOS by pre-service chemistry teachers. For the study, 29 pre-service chemistry teachers at a college of education in Chungcheongbuk-do were selected. As RFN items that were related to the contextual situation developed in this study, items in the categories of 'Aims and Values', 'Scientific practices', 'Scientific Methods among Educational Applications' and 'Social-Institutional Aspects among Educational Applications' were selected. Through the items of RFN, the perceptions of pre-service teachers in non-contextual situations were investigated. Then we presented the pre-service teachers with the situation related to Boyle's experiment on air pump and Boyle and Hobbes' debate over vacuum. In addition, their perception of NOS was examined in contextual situations related to RFN items. Responses to the items, experimental results related to Boyle's Law, group discussion, and interview data were collected as data. As a result of the study, it was found that pre-service teachers had informed perceptions in most of the items, but cases with naive views or mixed views were found in context experimental situations. This study can contribute to the NOS education for pre-service chemistry teachers by development of context situation education materials related to NOS and by finding out their perceptions in the non-contextual and contextual situation.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.7-21
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• 2024

There are various machine learning techniques such as Reinforcement Learning, Deep Learning, Neural Network Learning, and so on. In recent, Large Language Models (LLMs) are popularly used for Generative AI based on Reinforcement Learning. It makes decisions with the most optimal rewards through the fine tuning process in a particular situation. Unfortunately, LLMs can not provide any explanation for how they reach the goal because the training is based on learning of black-box AI. Reinforcement Learning as black-box AI is based on graph-evolving structure for deriving enhanced solution through adjustment by human feedback or reinforced data. In this research, for mutually exclusive decision-making, Mutually Exclusive Learning (MEL) is proposed to provide explanations of the chosen goals that are achieved by a decision on both ends with specified conditions. In MEL, decision-making process is based on the tree-based structure that can provide processes of pruning branches that are used as explanations of how to achieve the goals. The goal can be reached by trade-off among mutually exclusive alternatives according to the specific contextual conditions. Therefore, the tree-based structure is adopted to provide feasible solutions with the explanations based on the pruning branches. The sequence of pruning processes can be used to provide the explanations of the inferences and ways to reach the goals, as Explainable AI (XAI). The learning process is based on the pruning branches according to the multi-dimensional contextual conditions. To deep-dive the search, they are composed of time window to determine the temporal perspective, depth of phases for lookahead and decision criteria to prune branches. The goal depends on the policy of the pruning branches, which can be dynamically changed by configured situation with the specific multi-dimensional contextual conditions at a particular moment. The explanation is represented by the chosen episode among the decision alternatives according to configured situations. In this research, MEL adopts the tree-based learning model to provide explanation for the goal derived with specific conditions. Therefore, as an example of mutually exclusive problems, employment process is proposed to demonstrate the decision-making process of how to reach the goal and explanation by the pruning branches. Finally, further study is discussed to verify the effectiveness of MEL with experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.3036-3044
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• 2010

With the rapid growth of video data service, demand to provide advertisements or additional information with regard to a particular video scene is increasing. However, the direct use of automated visual analysis or speech recognition on videos virtually has limitations with current level of technology; the metadata of video such as title, category information, or summary does not reflect the content of continuously changing scenes. This work presents a new video contextual advertising system that serves relevant advertisements on a given scene by leveraging the scene's situation information inferred from video scripts. Experimental results show that the use of situation information extracted from scripts leads to better performance and display of more relevant advertisements to the user.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.633-635
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• 2022

If an error occurs during operation of the video wall controller, the control system creates a log file and records the log. In order to minimize the load on the system due to log recording, the log level is set so that the log is not recorded as much as possible under normal operating conditions. When an error occurs, detailed logs are recorded by changing the log level to analyze and respond to the cause of the error. So work efficiency is reduced, and operator intervention is inevitable to change the log level. In this paper, we propose a model that automatically sets the log level according to the operating situation using Contextual Bandit.

• Journal of KIISE
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• v.43 no.10
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• pp.1154-1164
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• 2016

To prevent the use of one's smartphone by another user, the authentication checks the owner in several ways. However, whenever the owner does use his/her smartphone, this authentication requires an unnecessary action, and sometimes he/she finally decides not to use an authentication method. This can cause a fatal problem in the smartphone's security. We propose a sustainable android platform-based authentication mode to solve this security issue and to facilitate secure authentication. In the proposed model, a smartphone identifies the current situation and then performs the authentication. In order to define the risk of the situation, we conducted a survey and analyzed the survey results by age, location, behavior, etc. Finally, a demonstration program was implemented to show the relationship between risk and security authentication methods.

• Education of Primary School Mathematics
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• v.15 no.3
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• pp.219-233
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• 2012

Practicality and value of mathematics can be verified when different problems that we face in life are resolved through mathematical knowledge. This study intends to identify whether the fraction teaching is being taught and learned at current elementary schools for students to recognize practicality and value of mathematical knowledge and to have the ability to apply the concept when solving problems in the real world. Accordingly, contextual problems and noncontextual problems are proposed around fractional arithmetic area, and compared and analyze the achievement level and problem solving processes of them. Analysis showed that there was significant difference in achievement level and solving process between contextual problems and noncontextual problems. To instruct more meaningful learning for student, contextual problems including historical context or practical situation should be presented for students to experience mathematics of creating mathematical knowledge on their own.

• Journal of the Korean housing association
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• v.25 no.2
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• pp.89-98
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• 2014

The purpose of this study was to analyze the environmental privacy on the perspective of integration and segregation of spatial areas in facilities for the elderly, through investigating required environmental privacy at each hierarchical space, the contextual situation and counterplan for the privacy. For the study, a content analysis for 35 foreign academic journal articles published from 1990 to August of 2013 was conducted. The results of the study were as follows: First, four hierarchical spaces had somewhat integrated characteristics as being required various types of privacy beyond the original features of each space. Especially semi-public and public spaces were needed the privacy similar to in private or semi-private areas. Second, the contextual situation for the privacy was mainly from undesirable access and psychological pressure of other residents, staff and etc. to the residents' personal space, stuff, and behaviors. The other was from no space (no sitting) or no equipments for privacy. Third, the counterplan for privacy was categorized as improvements of physical environments and making defensible space or keeping physical distance of the elderly. It is suggested that welfare of the aged act in Korea about the room capacity for the elderly facilities needs to be reconsidered for the privacy in their individual rooms and the privacy in semi-public and public area must be considered to make the behavior scope of the elderly extended.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.15-28
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• 2015

As personal devices and pervasive technologies for interacting with networked objects continue to proliferate, there is an unprecedented world of scattered pieces of contextualized information available. However, the explosive growth and variety of information ironically lead users and service providers to make poor decision. In this situation, recommender systems may be a valuable alternative for dealing with these information overload. But they failed to utilize various types of contextual information. In this study, we suggest a methodology for context-aware recommender systems based on the concept of contextual boundary. First, as we suggest contextual boundary-based profiling which reflects contextual data with proper interpretation and structure, we attempt to solve complexity problem in context-aware recommender systems. Second, in neighbor formation with contextual information, our methodology can be expected to solve sparsity and cold-start problem in traditional recommender systems. Finally, we suggest a methodology about context support score-based recommendation generation. Consequently, our methodology can be first step for expanding application of researches on recommender systems. Moreover, as we suggest a flexible model with consideration of new technological development, it will show high performance regardless of their domains. Therefore, we expect that marketers or service providers can easily adopt according to their technical support.