• Journal of Educational Research in Mathematics
• /
• v.20 no.3
• /
• pp.275-292
• /
• 2010

In this study, we discussed the way to teach algebra earlier through investigating to research trends of Early Algebra and researching about nature of subject involving algebra. There is a strong view that arithmetic and algebra have analogous forms and that algebra is on extension to arithmetic. Nevertheless, it is also possible to present a perspective that the fundamental goal and role of symbols and letters are difference between arithmetic and algebra. And, we could recognize that geometry was starting point of algebra trough historical perspectives. To consider these, we extracted some of possible directions to approaches to teach algebra earlier. To access to teaching algebra earlier, following ways are possible. (1) To consider informal strategy of young children. (2) Arithmetic reasoning considered of the algebraic relation. (3) Starting to algebraic reasoning in the context of geometrical problem situation. (4) To present young students to tool of letters and formular.

• The Korean Journal of Applied Statistics
• /
• v.22 no.4
• /
• pp.735-744
• /
• 2009

In this paper, we introduce a fast approach for Bayesian detection of change points in long-memory processes. Since a heavy computation is needed to evaluate the likelihood function of long-memory processes, a method for simplifying the computational process is required to efficiently implement a Bayesian inference. Instead of estimating the parameter, we consider selecting a element from the set of possible parameters obtained by categorizing the parameter space. This approach simplifies the detection algorithm and reduces the computational time to detect change points. Since the parameter space is (0, 0.5), there is no big difference between the result of parameter estimation and selection under a proper fractionation of the parameter space. The analysis of Nile river data showed the validation of the proposed method.

• Journal of Intelligence and Information Systems
• /
• v.13 no.3
• /
• pp.141-160
• /
• 2007

User interface has been regarded as a crucial issue to increase the acceptance of mobile services. In special, even though to what extent the machine as speaker communicates with human as listener in a timely and polite manner is important, fundamental studies to come up with these issues have been very rare. Hence, the purpose of this paper is to propose a methodology of estimating politeness level in a certain context-aware setting and then to design a context-aware system for polite mobile interface. We will focus on Korean language for the polite level estimation simply because the polite interface would highly depend on cultural and linguistic characteristics. Nested Minkowski aggregation model, which amends Minkowski aggregation model, is adopted as a privacy-preserving similarity evaluation for case retrieval under distributed computing environment such as ubiquitous computing environment. To show the feasibility of the methodology proposed in this paper, simulation-based experiment with drama cases has performed to show the performance of the methodology proposed in this paper.

• Science of Emotion and Sensibility
• /
• v.16 no.2
• /
• pp.149-156
• /
• 2013

In this study, the Model of Emotion Evaluation, an emotional analysis actively applied in environmental assessment, was divided into two parts, the abbreviated model and the inferential model, through pilot study and experiment. In addition, an analysis was conducted through the experiment on the attributes of the evaluation vocabularies of two additional types of representative models, the EPA Model and PAD Model, and the results show a huge difference in the development approach and lexical constitution of the two models. It was also identified through factor analysis that the vocabularies were abbreviated according to the respective models. Similarity relationships were analyzed using multidimensional scaling and the results show that mutual relationship was established to some degree. Based on this, we can conclude that, rather than a biased use of the Model of Emotion Evaluation in emotion evaluation, a more objective image analysis is possible by analyzing the characteristics of the model before applying it. In this study, the evaluation target was confined only to the environmental assessment of streetscape and continuous research on the Model of Emotion Evaluation that allows for the comparison of evaluation models in various areas is needed.

• Korean Journal of Cognitive Science
• /
• v.24 no.4
• /
• pp.323-338
• /
• 2013

There are multiple process mechanism in causal reasoning, which is estimation of the causal strength between cause and result. Further, because these mechanisms operate on different time phase during causal reasoning, it is highly possible that different individual difference factors are related to individual mechanisms of causal reasoning. Especially, the phenomena of conditionalization and discounting reflect attention to multiple potential causes when people infer the relationship between cause and effect. In this study, we manipulated self-construal which is an individual difference factor that reflects context sensitivity in cognition. As results, no difference was observed in conditionalization between individuals with an independent self-construal and those with an interdependent self-construal. However, independent self-construal group was observed to be lower in discounting than the interdependent self-construal group. The results indicate that conditionalization and discounting are independent cognitive process in human causal reasoning.

• Journal of Korea Society of Industrial Information Systems
• /
• v.16 no.2
• /
• pp.73-83
• /
• 2011

In the manufacturing system, production-planning is very important in effective management for expensive production facilities and machineries. To enhance efficiency of Manufacturing Execution System(MES), a manufacturing system that reduces the difference between planning and execution, certain production-planning needs a dispatching rule that is properly designed for characteristic of work information and there should be a appropriate selection for the rule as well. Therefore, in this paper dispatching rule will be selected by several simulations based on characteristics of work information derived from process planning data. By constructing information that are from simulation into ontology, one of the knowledge-based-reasoning, production planning platform based on the selection of dispatching rule will be demonstrated. The platform has strength in its wider usage that is not limited to where it is applied. To demonstrate the platform, RacerPro and Prot$\acute{e}$g$\acute{e}$ are used in parts of ontology reasoning, and JAVA and FlexChart were applied for production-planning simulation.

• Journal of the Korea Computer Graphics Society
• /
• v.26 no.3
• /
• pp.87-97
• /
• 2020

In this paper, we propose a novel neural relighting that infers a relighted rendering image based on the user-guided specular highlight map. The proposed network utilizes a pre-trained neural renderer as a backbone network learned from the rendered image of a 3D scene with various lighting conditions. We jointly optimize a 3D light position and its associated relighted image by back-propagation, so that the difference between the base image and the relighted image is similar to the user-guided specular highlight map. The proposed method has the advantage of being able to explicitly infer the 3D lighting position, while providing the artists' preferred 2D screen-space interface. The performance of the proposed network was measured under the conditions that can establish ground truths, and the average error rate of light position estimations is 0.11, with the normalized 3D scene size.

• Journal of the Korean earth science society
• /
• v.30 no.6
• /
• pp.759-772
• /
• 2009

The purpose of this study was to understand characteristics of eighth graders' conclusions presented in their self-directed scientific inquiry reports. We developed a framework, Analysis of Conclusions of Self-Directed Scientific Inquiry, to analyze students' conclusions. We then compared the conclusions with the inquiry questions students generated to find out whether the questions affected students' conclusions. In addition, we analyzed students' responses from the survey about their perceptions of drawing conclusions. According to the results, the conclusions were characterized into two categories, i.e., scientific basic assumption and scientific explanation. Almost half of the students' conclusions fall under the scientific basic assumptions. Most of the scientific explanations were deductive explanations and inductive explanations. Then, the kinds of conclusions were affected by the inquiry questions because the scientific explanations were made more than the scientific basic assumptions in answering the inquiry questions. Some students couldn't recognize differences between conclusions and experiment results.

• Education of Primary School Mathematics
• /
• v.21 no.2
• /
• pp.131-150
• /
• 2018

The structure of a mathematics task shapes the aspects of learning of those who solve the task. This study explores the process of understandings on the statistical variability of primary school students. Students were given two problems with different degrees of structuring - a well-structured problem (WSP) and an ill-structured problem (ISP) - and discussed in a group to solve each task. The highest level of development achieved in both cases appeared to be similar. However, when given the ISP, students dynamically proposed ideas and justified the conclusion based on their hypothesis. Furthermore, all students actively participated in solving the ISP until the end whereas some students were marginalized while solving the WSP. This discrepancy results from the difference in the degrees of task structuring.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.1
• /
• pp.93-98
• /
• 2021

Due to the development of deep learning and AI, the scale of the model has grown, and it has been integrated into other fields to blend into our lives. However, in environments with limited resources such as embedded devices, it is exist difficult to apply the model and problems such as power shortages. To solve this, lightweight methods such as clouding or offloading technologies, reducing the number of parameters in the model, or optimising calculations are proposed. In this paper, quantization of learned models is applied to ONNX models used in various framework interchange formats, neural network structure and inference performance are compared with existing models, and various module methods for quantization are analyzed. Experiments show that the size of weight parameter is compressed and the inference time is more optimized than before compared to the original model.