• Communications of Mathematical Education
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• v.29 no.3
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• pp.313-330
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• 2015

The classification is an important activity that is directly related to concept formation. Thus it will need to be made meaningful learning to classification through learner-centered teaching. But we doubts weather teaching and learning to the classification are reflected in the constructivist philosophy of 'learner-centered' well or not. The purpose of this study was to analyze critically the content of elementary textbooks and guidebook for teachers relating to the classification of angles and triangles in terms of constructivism. As a result, there is a problem in the classification of angles that are not provided a reasonable chance to set criteria by agreement of the communities. There is a problem in the classification of triangles that has the characteristics of radical development in terms of diversity. In addition, response of students was predicted like anyone who already acquired knowledge. And it has the shortcomings that the opportunity to have a choice and a discussion to hierarchical and partition classification are not provided. The followings are proposed based on such features; faithful reflection of 'Learner-centered' principle, careful prediction of student response, teaching that focus on process than results.

• Journal of Educational Research in Mathematics
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• v.27 no.3
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• pp.431-449
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• 2017

Acute triangles and obtuse triangles are defined according to the classification of triangles by angles. The definitions of acute triangles and obtuse triangles are difficult for students because they are related to different logical elements. The purpose of this study is to seek desirable methods for teaching the classification of triangles by angles related to logic. To do this, based on the theoretical consideration and the longitudinal analysis of the elementary mathematics textbooks, some implications are found for teaching. And then the lesson was planned and applied to $4^{th}$ graders. After the lesson, we reviewed and analyzed their worksheets and test results for examining the effects by teaching methods. Based on the result, we discussed and made some didactical suggestions for teaching the classification of triangles by angles.

• Education of Primary School Mathematics
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• v.18 no.1
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• pp.45-59
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• 2015

This study focused on the classification of triangles by angles in elementary school mathematics. We examined Korean national mathematics curriculum from the past to the present. We also examined foreign textbooks and the Euclid's . As a result, it showed that the classification is not indispensable from the mathematical and the perceptual viewpoint. It is rather useful for students to know the names of triangles when studying upper level mathematics in middle and high schools. This study also suggested that the classification be introduced in elementary school mathematics in the context of reasoning and inquiring as shown foreign textbooks, and example topics for the reasoning and inquiring.

• Tunnel and Underground Space
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• v.34 no.4
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• pp.330-354
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• 2024

In site characterization of high-level radioactive waste, discontinuity(joint) distribution and rock mass classification, which are key evaluation parameters in the rock engineering field, were evaluated using deep boreholes in the Wonju granite and Chuncheon granite, which belong to Mesozoic Jurassic era. To evaluate joint distribution characteristics, fracture zones and joint surfaces extracted from ATV data were used, and major joint sets were evaluated along with joint frequency according to depth, dip direction, and dip. Both the Wonju and Chuncheon granites that were studied showed a tendency for the frequency of joints to increase linearly with depth, and joints with high angles were relatively widely distributed. In addition, relatively large amounts of weathering tended to occur even in deep depth due to groundwater inflow through high-angle joints. RQD values remained consistently low even at considerable depth. Meanwhile, joint groups with low angles showed different joint characteristics from joint sets with high angles. Rock mass classification was performed based on RMR system, and along with rock mass classification for 50 m intervals where uniaxial compressive strength was performed, continuous rock mass classification according to depth was performed using velocity log data and geostatistical techniques. The Wonju granite exhibited a superior rock mass class compared to the Chuncheon granite. In the 50 m interval and continuous rock mass classification, the shallow part of the Wonju granite showed a higher class than the deep part, and the deep part of the Chuncheon granite showed a higher class than the shallow part.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1738-1741
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• 1997

This paper addresses the issue fo target classification and localization with a SONAR for mobiler robot indoor navigation. In particular, multiple refetions of SONAR sound are used actively and interntionally. As for the SONAR sensor, the multiple reflection has been generally considered as one of the noisy phenomena, which is inevitable in the indoor environments. However, these multiple reflections can be a clue for classifying and localizing targets in the indoor environment if those can be controlled and used well. This paper develops a new SONAR sensor module with a reflection plane which can actively create the multiple refection. This paper also intends to suggest a new target classification emthod which uses the multiple refectiions. We approximate the world as being two dimensional and assume that the targets consisting of the indoor environment are pland, corner, and edge. Multiple reflection paths of an acoustic bean by a SONAR are analyzed, by simulations and the patterns of the TOPs (Time Of Flight) and angles of multiple reflections from each target are also analyzed. In addition, a new algorithm for target classification and localization is proposed.

• Current Optics and Photonics
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• v.7 no.6
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• pp.597-607
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• 2023

Volumetric 3D displays generate voxels to enable users to watch three-dimensional virtual objects from various angles, and they have a significant advantage over other types of 3D displays in terms of realism and the absence of vergence-accommodation conflict (VAC). By virtue of these advantages, various volumetric 3D display technologies incorporating novel approaches have been introduced competitively. As a result, the conventional classification criteria for volumetric 3D technology often fall short in categorizing these innovative methods. In this study, we present an improved classification framework capable of accommodating these new technologies. We expect that a new classification may offer some intuition to identify areas of technical deficiency and contribute to improving the technology.

• The Journal of the Acoustical Society of Korea
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• v.8 no.4
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• pp.44-52
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• 1989

The UCERSS (Unit Circle Eigendecomposition Rational Signal Subspace) algorithm has extended MUSIC (MUltiple Signal Classification ) by using eigendecomposition on the unit circle in order to estimate incident angles of multiple wide band signals. The purpose of this thesis is to further extend the UCERSS to be able to estimate the direction of arrivals of multiple wide band signals in very low SNR . The wide band ESPRIT (Estimation of Signal Parameter via Rotational Invariance Technique) uses covariance difference matrices to reduce noise components. In this paper the wide band ESPRIT which combines the ideas of UCERSS and ESPRIT Is proposed. Computer simulation results Indicate that the performances of the proposed approaches are superior to those of the UCERSS in very low SNR.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.1
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• pp.15-23
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• 2003

This paper proposes a fast direction of arrival (DOA) estimation algorithm that can rapidly estimate incidence angles of incoming signals using a pseudo covariance matrix. The conventional subspace DOA estimation methods such as MUSIC (multiple signal classification) algorithms need many sample signals to acquire covariance matrix of input signals. Thus, it is difficult to estimate the DOAs of signals because they cannot perform DOA estimation during receiving sample signals. Also if the D0As of signals are changing rapidly, conventional algorithms cannot estimate incidence angles of signals exactly. The proposed algorithm obtains bearing response and directional spectrum after acquiring pseudo covariance matrix of each snapshot. The incidence angles can be exactly estimated by using the bearing response and directional spectrum. The proposed DOA estimation algorithm uses only concurrent snapshot so as to obtain covariance matrix. Compared to conventional DOA estimation methods. The proposed algorithm has an advantage that can estimate DOA of signal rapidly.

• The KIPS Transactions:PartB
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• v.17B no.4
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• pp.309-316
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• 2010

This paper introduces a new model based method for facial expression recognition that uses facial grid angles as feature space. In order to be able to recognize the six main facial expression, proposed method uses a grid approach and therefore it establishes a new feature space based on the angles that each gird's edge and vertex form. The way taken in the paper is robust against several affine transformations such as translation, rotation, and scaling which in other approaches are considered very harmful in the overall accuracy of a facial expression recognition algorithm. Also, this paper demonstrates the process that the feature space is created using angles and how a selection process of feature subset within this space is applied with Wrapper approach. Selected features are classified by SVM, 3-NN classifier and classification results are validated with two-tier cross validation. Proposed method shows 94% classification result and feature selection algorithm improves results by up to 10% over the full set of feature.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4290-4309
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• 2020

In recent years, advancements in machine learning capabilities have allowed it to see widespread adoption for tasks such as object detection, image classification, and anomaly detection. However, despite their promise, a limitation lies in the fact that a network's performance quality is based on the data which it receives. A well-trained network will still have poor performance if the subsequent data supplied to it contains artifacts, out of focus regions, or other visual distortions. Under normal circumstances, images of the same scene captured from differing points of focus, angles, or modalities must be separately analysed by the network, despite possibly containing overlapping information such as in the case of images of the same scene captured from different angles, or irrelevant information such as images captured from infrared sensors which can capture thermal information well but not topographical details. This factor can potentially add significantly to the computational time and resources required to utilize the network without providing any additional benefit. In this study, we plan to explore using image fusion techniques to assemble multiple images of the same scene into a single image that retains the most salient key features of the individual source images while discarding overlapping or irrelevant data that does not provide any benefit to the network. Utilizing this image fusion step before inputting a dataset into the network, the number of images would be significantly reduced with the potential to improve the classification performance accuracy by enhancing images while discarding irrelevant and overlapping regions.