• School Mathematics
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• v.14 no.1
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• pp.135-150
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• 2012

This paper analyzes the activities for (fraction) ${\times}$(fraction) in Korean elementary textbooks focusing on the connection between visual models and the algorithm. New Korean textbook attempts a new approach to use length model (as well as rectangular area model) for developing the standard algorithm for the multiplication of fractions, $\frac{a}{b}{\times}\frac{d}{c}=\frac{a{\times}d}{b{\times}c}$. However, activities with visual models in the textbook are not well connected to the algorithm. To bridge the gap between activities with models and the algorithm, distributive strategy should be emphasized. A wealth of experience of solving problems of fraction multiplication using the distributive strategy with visual models can serve as a strong basis for developing the algorithm for the multiplication of fractions.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.579-586
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• 2018

With the beginning of the new era of bigdata, information extraction or prediction are an important research area. Here, we present the acquisition of semi-automatically curated large-scale biological database and the prediction of enzyme reaction annotation for analyzing the pharmacological activities of drugs. Because the xenobiotic metabolism of pharmaceutical drugs by cellular enzymes is an important aspect of pharmacology and medicine. In this study, we apply and analyze similarity models to predict bimolecular reactions between human enzymes and their corresponding substrates. Thirteen models select to reflect the characteristics of each cluster in the similarity model. These models compare based on sensitivity and AUC. Among the evaluation models, the Simpson coefficient model showed the best performance in predicting the reactivity between the enzymes. The whole similarity model implement as a web service. The proposed model can respond dynamically to the addition of reaction information, which will contribute to the shortening of new drug development time and cost reduction.

• Archives of design research
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• v.18 no.2 s.60
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• pp.273-282
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• 2005

In this study, we proposed Context Cube as a conceptual model of user context, and a Multi-modal Interaction Design framework to develop ubiquitous service through understanding user context and analyzing correlation between context awareness and multi-modality, which are to help infer the meaning of context and offer services to meet user needs. And we developed a case study to verify Context Cube's validity and proposed interaction design framework to derive personalized ubiquitous service. We could understand context awareness as information properties which consists of basic activity, location of a user and devices(environment), time, and daily schedule of a user. And it enables us to construct three-dimensional conceptual model, Context Cube. Also, we developed ubiquitous interaction design process which encloses multi-modal interaction design by studying the features of user interaction presented on Context Cube.

• Journal of KIISE:Software and Applications
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• v.36 no.10
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• pp.816-824
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• 2009

In the face space, face images due to illumination and pose variations have a nonlinear distribution. Active Appearance Models (AAM) based on the linear model have limits to the nonlinear distribution of face images. In this paper, we assume that a few clusters of face images are given; we build local AAMs according to the clusters of face images, and then select a proper AAM model during the fitting phase. To solve the problem of updating fitting parameters among the models due to the model changing, we propose to build in advance relationships among the clusters in the parameter space from the training images. In addition, we suggest a gradual model changing to reduce improper model selections due to serious fitting failures. In our experiment, we apply the proposed model to Yale Face Database B and compare it with the previous method. The proposed method demonstrated successful fitting results with strongly illuminated face images of deep shadows.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.369-377
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• 2010

In vocabulary recognition systems based on HMM(Hidden Markov Model)s, training process unseen model bring on show a low recognition rate. If recognition vocabulary modify and make an addition then recreated modeling of executed database collected and training sequence on account of bring on additional expenses and take more time. This study suggest efficient context dependent process modeling method using decision tree-based state tying. On study suggest method is reduce recreated of model and it's offered that robustness and accuracy of context dependent acoustic modeling. Also reduce amount of model and offered training process unseen model as concerns context dependent a likely phoneme model has been used unseen model solve the matter. System performance as a result of represent vocabulary dependence recognition rate of 98.01%, vocabulary independence recognition rate of 97.38%.

• Journal of the Korea Society for Simulation
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• v.24 no.3
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• pp.77-87
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• 2015

Defense M&S (Modeling & Simulation) is utilized as a realistic method to analyze MOE (Measure of Effectiveness) of weapon systems by modeling weapons and their operational environment on the computer, and simulating them under various war scenarios. As weapon systems become complex in their structure and dynamics, model engineering are experiencing difficulties to construct simulation models on a computer. A model repository helps model developers to save model development time and cost by systematically storing predefined and already validated models. However, most repositories for Defense M&Shave not been successful partly due to limited accessability, vulnerability to security threats, and low level of dependability. In this paper, we propose W-Cloud (Weapon Cloud), a cloud model repository for reusing predefined weapon models. Clients can access W-Cloud on any platforms and various devices, yet security and confidentiality concerns are guaranteed by employing multi-tier information protection mechanism.

• Journal of The Korean Association For Science Education
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• v.33 no.1
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• pp.30-45
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• 2013

In this study, we developed a model for analyzing scientists' creative thinking processes, and analyzed Archimedes' thinking process in solving the golden crown problem. As results show, scientists' complex problem solving processes could be represented as a repeating circular model, and the fusion of processes of diverse thinking required for scientists' creativity could be analyzed from the case. Also in this study, we represented the role of experiments in scientists' creative discovery, and investigated the reasons for the difference between the viewpoints of textbooks and historic facts. We found the importance of abductive reasoning and advance knowledge in creative thinking. Archimedes solved the golden crown problem creatively by crossing the scientific thought of dynamics and the daily thought of baths. In this process, abductive reasoning and advance knowledge played an important role. Besides Archimedes' case, if we would reconstruct the creative discovery processes of diverse scientists' in textbooks, students could raise their creative thinking ability by experiencing these processes as educational steps.

• Journal of The Korean Association For Science Education
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• v.44 no.4
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• pp.325-341
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• 2024

This study examined how specific aspects of epistemic cognition are developed in elementary students during modeling activities, using the Apt-AIR framework. The study focused on a class unit titled 'Shall We Find Out What the Landscape of a Riverside Looks Like?' which is part of the land chapter in the third-grade Korean elementary science curriculum. Ambitious Science Teaching (AST) was applied as a teaching strategy to enhance students' model construction. Seven science classes were conducted in line with the core practices of AST, with 29 elementary school students participating in the study. The classes were organized into four stages: initial model composition, inquiry activity, group model composition-sharing, and final model construction. The class activities at each stage were analyzed using both the AIR model, i.e., epistemic aim and value (A), epistemic ideals (I), and reliable epistemic processes (R), and the multi-faceted framework for epistemic thinking from the Apt-AIR framework. The results of the study revealed that in science classes emphasizing modeling activities based on the core practices of AST, the elementary students progressively developed more sophisticated explanatory models that included causal relationships explaining the topographic differences between the upstream and downstream sections of a river. This result was due to their engagement in constructing initial models to describe phenomena, supplementing the initial models using data collected in the model experiment, and participating in discussions to share and evaluate group models. Additionally, from the perspective of the Apt-AIR framework, the aspects of epistemic cognition demonstrated by the elementary students in their modeling activities were appropriate for engaging with cognitive processes related to epistemic aims and values, epistemic ideals, and reliable processes. The other four aspects of the Apt-AIR framework, however, were not performed as effectively. In particular, the application of reliable epistemic processes for knowledge construction required more improvement.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.145-155
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• 2007

본 연구는 21세기 새로운 패러다임인 웹 2.0에서 중요한 마케팅 모델로 인식되고 있는 AISAS 모델을 이용하여 인터넷 쇼핑몰 유형에 따른 적용을 알아보고, 현재 정체기에 있는 인터넷 마케팅의 한계를 해결하는 방법으로, RSS 적용 마케팅과 이를 AISAS 모델에 활용하는 방법에 관한 연구이다. 이 마케팅으로 제안되는 RSS를 이용할 경우 기존의 웹환경(웹 1.0)에서와는 달리, 실시간으로 업데이트 정보를 제공할 수 있으며, 사용자들의 커뮤니케이션 활동에 적극 개입을 할 수 있는 환경을 조성할 수 있다. 그리고 이미 정보의 바다라고 표현되며, 수많은 정보가 있는 인터넷 환경을 그대로 옮길 수 있는 RSS의 특징으로 인해 기업에서는 제품 홍보에 필요한 비용절감 효과가 있으며, 사용자에게는 복잡한 과정에 아닌, 단순한 포맷 변환만으로 누구든지 어떤 사이트의 정보라도 손쉽게 정보를 취득할 수 있다. 이런 RSS의 장점을 활용하여 인터넷의 새로운 마케팅 모델로 제시되는 AISAS의 5단계 구매과정에 각각 적용을 하여, 개인이 원하는 정보만을 실시간으로 제공하여, 클릭 한 두번만으로 구매까지 이어지게 하는 구조도를 제시한다. 아울러, RSS의 장점인 정보 공유를 이용해, 바이러스 마케팅 (WOM)의 시너지 효과를 최대한 높이고, 사용자는 제품에 대한 넓고 다양한 정보를 얻게 되므로 제품의 신뢰도를 높이고, 친근감이 상승하는 효과를 함께 가져 올 수 있을 것이다.[1].

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6A
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• pp.589-599
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• 2004

Most models assume the complete debugging environments by requiring a complete software correction in quantitative evaluation of software reliability. But, in many case, new faults are involved in debugging works, for complete software correction is impossible. In this paper, software growth model is proposed about incomplete debugging environments by considering the possibility of new faults involvements, and software faults occurrence status are also mentioned about NHPP by considering software faults under software operation environments and native faults owing to the randomly involved faults in operation before test. While, effective quantitative measurements are derived in software reliability evaluation, applied results are suggested by using actual data, and fitnesswith existing models are also compared and analyzed.