• School Mathematics
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• v.14 no.1
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• pp.1-28
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• 2012

The purpose of the study are to identify factors of mathematical visualization through the thirty students of highschool 2nd year and to investigate how each visualization factor is used in mathematics problem solving process. Specially, this study performed the qualitative case study in terms of the five of thirty students to obtain the high grade in visuality assessment. As a result of the analysis, visualization factors were categorized into mental images, external representation, transformation or operation of images, and spacial visualization abilities. Also, external representation, transformation or operation of images, and spacial visualization abilities were subdivided more specifically.

• Structural Engineering and Mechanics
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• v.75 no.4
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• pp.477-485
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• 2020

Finite element (FE) model based structural damage detection (SDD) methods play vital roles in effectively locating and quantifying structural damages. Among these methods, structural model updating should be conducted before SDD to obtain benchmark models of real structures. However, the characteristics of updating parameters are not reasonably considered in existing studies. Inspired by the l_∞ norm regularization, a novel anti-sparse representation method is proposed for structural model updating in this study. Based on sensitivity analysis, both frequencies and mode shapes are used to define an objective function at first. Then, by adding l_∞ norm penalty, an optimization problem is established for structural model updating. As a result, the optimization problem can be solved by the fast iterative shrinkage thresholding algorithm (FISTA). Moreover, comparative studies with classical regularization strategy, i.e. the l₂ norm regularization method, are conducted as well. To intuitively illustrate the effectiveness of the proposed method, a 2-DOF spring-mass model is taken as an example in numerical simulations. The updating results show that the proposed method has a good robustness to measurement noises. Finally, to further verify the applicability of the proposed method, a six-storey aluminum alloy frame is designed and fabricated in laboratory. The added mass on each storey is taken as updating parameter. The updating results provide a good agreement with the true values, which indicates that the proposed method can effectively update the model parameters with a high accuracy.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.54-61
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• 2008

This paper presents a new TIQ based CMOS flash 6-bit ADC to process digital signal in real time. In order to improve the conversion speed of ADC by designing new logic or layout of ADC circuits, a new design method is proposed in encoding logic circuits. The proposed encoding circuits convert analog input into digitally encoded double base number system(DBNS), which uses two bases unlike the normal binary representation scheme. The DBNS adopts binary and ternary radix to enhance digital arithmetic processing capability. In the DBNS, the addition and multiplication can be processed with just shift operations only. Finding near canonical representation is the most important work in general DBNS. But the main disadvantage of DBNS representation in ADC is the fan-in problem. Thus, an equal distribution algorithm is developed to solve the fan-in problem after assignment the prime numbers first. The conversion speed of simulation result was 1.6 GSPS, at 1.8V power with the Magna $0.18{\mu}m$ CMOS process, and the maximum power consumption was 38.71mW.

• Journal of Digital Contents Society
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• v.18 no.2
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• pp.347-356
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• 2017

It is well-known that the face recognition method via sparse representation has been proved very robust and showed good performance. Its weakness is, however, that its time complexity is very high because it should solve $L_1$-minimization problem to find the sparse solution. In this paper, we propose to use the ROMP(Regularized Orthogonal Matching Pursuit) method for the sparse solution, which solves the $L_2$-minimization problem with regularization condition using the greed strategy. In experiments, we shows that the proposed method is comparable to the existing best $L_1$-minimization solver, Homotopy, but is 60 times faster than Homotopy. Also, we proposed C-SCI method for classification. The C-SCI method is very effective since it considers the sparse solution only without reconstructing the test data. It is shown that the C-SCI method is comparable to, but is 5 times faster than the existing best classification method.

• Communications of Mathematical Education
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• v.24 no.2
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• pp.475-502
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• 2010

In this paper, the ability to use mathematical representations in solving math problem was analyzed according to student assessment levels using 113 first-year high school students, and the characteristics of their representation usage according to student assessment levels were also examined. For this purpose, problems were presented that could be solved using various mathematical representations, and the students were asked to solve them using a maximum of three different methods. Also, based on the comparative analysis results of a paper evaluation, six students were selected and interviewed, and the reasons for their representation usage differences were analyzed according to their student assessment levels. The results of the analysis show that over 50% of high ranking students used two or more representations in all questions to solve problems, but with middle ranking students, there were deviations depending on the difficulty of the questions. Low ranking students failed to use representation in diverse ways when solving problems. As for characteristics of symbol usage, high ranking students preferred using formulas and used mathematical representations efficiently while solving problems. In contrast, middle and low ranking students mostly used tables or pictures. Even when using the same representations, high ranking students' representations were expressed in a more structurally refined manner than those by middle and low ranking students.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.2 no.2
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• pp.11-18
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• 1991

In this paper, the analysis of arbitrarily shaped microstrip antennas is described. The analysis method is based on the transmission - line matrix representation for the interior problem and the moment method for the problem along the peripheries of the patch. Using this method, the input impedance and other antenna parameters are calculated and compared with experimental results for a circular and an equilateral triangular microstrip antenna. For all of the results, theoretical and expreimental results are in good agreement and the validity of the method is confirmed. This analysis can also be used to analyze microstrip antennas with shorting pins.

• Journal of Electrical Engineering and Technology
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• v.2 no.3
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• pp.312-319
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• 2007

The solution of the power flow is one of the most important problems in electrical power systems. These traditional methods such as Gauss-Seidel method and Newton-Raphson (NR) method have had drawbacks up to now such as initial values, abnormal operating solutions and divergences in heavy loads. In order to overcome theses problems, the power flow solution incorporating genetic algorithm (GA) is introduced in this paper. General operator of genetic algorithm, arithmetic crossover, and non-uniform mutation operator of GA are suggested to solve the power flow problem. While abnormal solution cannot be obtained by a NR method, multiple power flow solution can be obtained by a GA method. With a heavy load, both normal solution and abnormal solution can be obtained by a proposed method. In this paper, a floating number representation instead of the binary number representation is introduced for accuracy. Simulation results have been compared with traditional methods.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.23-28
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• 2002

A fundamental problem in building an intelligent agent is that an agent does not understand the meaning of its perception or its action. One reason that an agent cannot understand the world is partially caused by a syntactic approach that converts a semantic feature into a simple string. To solve this problem, Cohen introduces a semantic approach that an agent autonomously learns a meaningful representation of physical schemas, on which some advanced conceptual structures are built, from physically interacting with environment using its own sensors and effectors. However, Cohen does not deal with a meta level of conceptual primitive that makes recognizing a schema possible. We propose that negation is a meta schema that enables an agent to recognize a physical schema. We prove some semantic aspects of negation.

• Journal of Biomedical Engineering Research
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• v.26 no.4
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• pp.199-205
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• 2005

When recording single-unit responses from neural systems, a common problem is the accurate detection of spikes (action potentials) in the presence of competing unwanted (noise) signals. While some sources of noise can be readily dealt with through filtering or 'template subtraction' techniques, other sources present a more difficult problem. In particular, noise components introduced by power supplies, which contain harmonics of the power-line frequency, can be particularly troublesome in that they can mimic the shape of the desired spikes. Thus, standard 'template subtraction' techniques or notch-filtering approaches are not appropriate. In this study, we propose the use of a novel template-subtraction scheme that involves estimating the power-line noise waveform and using cross-correlation techniques to subtract them from the recordings. This technique requires two key steps: (1) cross-correlation analysis of each recorded waveform extracts a robust representation of the power-line noise waveform and (2) a second level of cross-correlation to successfully subtract that representation from each recorded waveform. This paper describes this algorithm and provides examples of its implementation using actual recorded waveforms that are contaminated with these noise signals. An improvement (reduction) in the noise level is reported, as are suggestions for future implementation of this strategy.

• The Journal of Society for e-Business Studies
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• v.13 no.2
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• pp.1-21
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• 2008

Telematics services are being widely used recently. However, data sharing is restricted because data representations among telematics severs and terminals are not yet standardized. Moreover, changes of some data items can cause the modification of telematics software. To resolve the problem, we define an XML-based markup language, called tele-XML, for the standard representation of telematics data, and design a framework and related schema for the tele-XML. We also implement API libraries and program modules for the processing of tele-XML documents. By using the proposed representation and processing scheme, the previous problem can be resolved.