• Education of Primary School Mathematics
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• v.25 no.3
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• pp.251-278
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• 2022

The purpose of this study is to obtain implications for mathematical education by analyzing how the multiplication and division of decimal numbers are presented in the elementary mathematics textbooks in Korea, Japan, Singapore, and Finland. Compared to the fact that students often have misconceptions about multiplication and division of decimal numbers, there have been not many comparative studies in recent elementary mathematics textbooks. For this study, we selected elementary mathematics textbooks those are widely used in Japan, Singapore, and Finland along with Korean elementary mathematics textbooks. We chose the textbooks because the students in the selected countries have scored high in international achievement studies such as TIMSS and PISA. The analysis was examined in terms of elementary mathematics curriculum related to multiplication and division of decimal numbers, introduction and content, real-life situations, use of visual models, and formalization methods of algorithms. As a result of the study, the mathematics curricula related to multiplication and division of decimal numbers includes estimation in Korea and Finland, while Japan and Singapore emphasize real-life connections more, and Finland completes the operations in secondary schools. The introduction and content are intensively provided in a short period of time or distributed in various grades and semesters. The real-life situations are presented in a simple sentence format in all countries, and the use of visual models or formalization of algorithms is linked to the operations of natural numbers in unit conversions. Suggestions were made for textbook development and teacher training programs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1593-1600
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• 2009

There are two major algorithms to find a square root of floating point number, one is the Newton_Raphson algorithm and GoldSchmidt algorithm which calculate it approximately by iterating multiplications and the other is SRT algorithm which calculates it exactly by iterating subtractions. This paper proposes an exact floating point square root algorithm using only multiplication. At first an approximate inverse square root is calculated by Newton_Raphson algorithm, and then an exact square root algorithm by reducing an error in it and a compensation algorithm of it are proposed. The proposed algorithm is verified to calculate all of numbers in a single precision floating point number and 1 billion random numbers in a double precision floating point number. The proposed algorithm requires only the multipliers without another hardware, so it can be widely used in an embedded system and mobile production which requires an efact square root of floating point number.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.46-55
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• 2007

The Newton-Raphson's algorithm for finding a floating point reciprocal and inverse square root calculates the result by performing a fixed number of multiplications. In this paper, an improved Newton-Raphson's algorithm is proposed, that performs multiplications a variable number. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications per an operation is derived from many reciprocal and inverse square tables with varying sizes. The superiority of this algorithm is proved by comparing this average number with the fixed number of multiplications of the conventional algorithm. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a reciprocal and inverse square root unit. Also, it can be used to construct optimized approximate tables. The results of this paper can be applied to many areas that utilize floating point numbers, such as digital signal processing, computer graphics, multimedia, scientific computing, etc.

• Communications of Mathematical Education
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• v.33 no.3
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• pp.255-273
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• 2019

In order to help students to understand the essence of prime concepts, this study looked at the history of prime concept development and analyzed how to introduce the concept of textbooks. In ancient Greece, primes were multiplicative atoms. At that time, the unit was not a number, but the development of decimal representations led to the integration of the unit into the number, which raised the issue of primality of 1. Based on the uniqueness of factorization into prime factor, 1 was excluded from the prime, and after that, the concept of prime of the atomic context and the irreducible concept of the divisor context are established. The history of the development of prime concepts clearly reveals that the fact that prime is the multiplicative atom is the essence of the concept. As a result of analyzing the textbooks, the textbook has problems of not introducing the concept essence by introducing the concept of prime into a shaped perspectives or using game, and the problem that the transition to analytic concept definition is radical after the introduction of the concept. Based on the results of the analysis, we have provided several pedagogical implications for helping to focus on a conceptual aspect of prime number.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.839-842
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• 2006

대부분의 불리언 행렬에 대한 연구는 두 불리언 행렬의 곱셈에 초점을 두고 있으며 모든 불리언 행렬을 대상으로 한 곱셈에 대한 연구는 최근에야 극히 소수의 연구결과가 보이고 있다. 이 연구들은 모든 불리언 행렬 사이의 곱셈 실행시간을 개선시켰으나 연속된 세 개의 모든 lxn, nxm, mxk 불리언 행렬에 대한 곱셈은 아직 많은 개선이 필요하다. 본 논문은 모든 $l{\times}n,\;n{\times}m,\;m{\times}k$ 불리언 행렬의 곱셈 실행시간을 보다 개선할 수 있는 이론을 제시하고 이를 적용한 불리언 행렬 연속곱셈의 실행결과에 대하여 논한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.494-496
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• 2022

엣지 디바이스에서 딥러닝을 활용하기 위하여 CNN 경량화 연구들이 진행되고 있다. 경량 CNN 은 대부분 고정 소수점을 사용하며, 계층에 따라 정밀도는 달라진다. 본 논문에서는 경량 CNN 을 지원하기 위하여, 사용 계층에 따라 정밀도를 선택할 수 있는 가변 정밀도 곱셈기를 제안한다. 제안하는 가변 정밀도 곱셈기는 낮은 정밀도 곱셈기를 병합하는 구조로, 정밀도가 낮을 때는 병렬 처리를 통해 효율을 높인다. 제안하는 곱셈기를 Verilog HDL로 설계하고 ModelSim 에서 동작을 확인하였다. 설계된 곱셈기는 계층별로 정밀도가 다른 CNN 가속기에서 효율적으로 적용될 것으로 기대된다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.380-389
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• 2005

The Goldschmidt iterative algorithm for a floating point divide calculates it by performing a fixed number of multiplications. In this paper, a variable latency Goldschmidt's divide algorithm is proposed, that performs multiplications a variable number of times until the error becomes smaller than a given value. To calculate a floating point divide '$\frac{N}{F}$', multifly '$T=\frac{1}{F}+e_t$' to the denominator and the nominator, then it becomes ’$\frac{TN}{TF}=\frac{N_0}{F_0}$'. And the algorithm repeats the following operations: ’$R_i=(2-e_r-F_i),\;N_{i+1}=N_i{\ast}R_i,\;F_{i+1}=F_i{\ast}R_i$, i$\in${0,1,...n-1}'. The bits to the right of p fractional bits in intermediate multiplication results are truncated, and this truncation error is less than ‘$e_r=2^{-p}$'. The value of p is 29 for the single precision floating point, and 59 for the double precision floating point. Let ’$F_i=1+e_i$', there is $F_{i+1}=1-e_{i+1},\;e_{i+1}',\;where\;e_{i+1}, If '$[F_i-1]<2^{\frac{-p+3}{2}}$ is true, ’$e_{i+1}<16e_r$' is less than the smallest number which is representable by floating point number. So, ‘$N_{i+1}$ is approximate to ‘$\frac{N}{F}$'. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications per an operation is derived from many reciprocal tables ($T=\frac{1}{F}+e_t$) with varying sizes. 1'he superiority of this algorithm is proved by comparing this average number with the fixed number of multiplications of the conventional algorithm. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a divider. Also, it can be used to construct optimized approximate reciprocal tables. The results of this paper can be applied to many areas that utilize floating point numbers, such as digital signal processing, computer graphics, multimedia, scientific computing, etc

• The KIPS Transactions:PartA
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• v.12A no.2 s.92
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• pp.95-102
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• 2005

The Newton-Raphson iterative algorithm for finding a floating point reciprocal which is widely used for a floating point division, calculates the reciprocal by performing a fixed number of multiplications. In this paper, a variable latency Newton-Raphson's reciprocal algorithm is proposed that performs multiplications a variable number of times until the error becomes smaller than a given value. To find the reciprocal of a floating point number F, the algorithm repeats the following operations: '$'X_{i+1}=X=X_i*(2-e_r-F*X_i),\;i\in\{0,\;1,\;2,...n-1\}'$ with the initial value $'X_0=\frac{1}{F}{\pm}e_0'$. The bits to the right of p fractional bits in intermediate multiplication results are truncated, and this truncation error is less than $'e_r=2^{-p}'$. The value of p is 27 for the single precision floating point, and 57 for the double precision floating point. Let $'X_i=\frac{1}{F}+e_i{'}$, these is $'X_{i+1}=\frac{1}{F}-e_{i+1},\;where\;{'}e_{i+1}, is less than the smallest number which is representable by floating point number. So, $X_{i+1}$ is approximate to $'\frac{1}{F}{'}$. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications per an operation is derived from many reciprocal tables $(X_0=\frac{1}{F}{\pm}e_0)$ with varying sizes. The superiority of this algorithm is proved by comparing this average number with the fixed number of multiplications of the conventional algorithm. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a reciprocal unit. Also, it can be used to construct optimized approximate reciprocal tables. The results of this paper can be applied to many areas that utilize floating point numbers, such as digital signal processing, computer graphics, multimedia scientific computing, etc.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.952-954
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• 2005

D-클래스는 $n{\times}n$ 불리언 행렬의 집합에서 특정 관계(relation)에 따딸라 동치(equivalent) 관계에 있는 불리언 행렬의 집합으로 구성된다. D-클래스 계산은 $n{\times}n$ 불리언 행렬의 전체 집합을 대상으로 이 집합에서 조합할 수 있는 모든 두 $n{\times}n$ 불리언 행렬 사이의 곱셈을 기본적으로 요구한다. 그러나 불리언 행렬에 대한 대부분의 연구는 두 개의 불리언 행렬에 대한 효율적인 곱셈에 집중되었으며 모든 $n{\times}n$ 불리언 행렬 사이의 곱셈에 대한 연구는 최근에야 소수가 보이고 있다. 두개의 $n{\times}n$ 불리언 행렬 곱셈에 대해 최적화된 알고리즘은 현재 알려져 있으나, 모든 $n{\times}n$ 불리언 행렬 사이의 곱셈에 대해 제시된 알고리즘은 아직 실행시간이 크게 향상되지 못하고 있으며 많은 개선과 연구가 필요하다. 본 논문은 개별적인 $n{\times}n$ 불리언 행렬 곱셈 대신 하나의 $n{\times}n$ 불리언 행렬과 불리언 행렬 집합과의 곱셈을 다루고 또한 이 곱셈에서 계산되는 모든 $n{\times}n$ 불리언 행렬을 집합으로 표현하는 방법을 통해 D-클래스 계산을 보다 효율적으로 할 수 있는 알고리즘에 대해 논한다.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.389-392
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• 2005

Boolean matrices are applied to a variety of areas and used successfully in many applications. There are many researches on the application and multiplication of boolean matrices. Most researches deal with the multiplication of boolean matrices, but all of them focus on the multiplication of just two boolean matrices and very few researches deal with the multiplication of many pairs of two boolean matrices. The paper discusses it is not suitable to use for the multiplication of many pairs of two boolean matrices the algorithm for the multiplication of two boolean matrices that is considered optimal up to now, and suggests a method that can improve the multiplication of a $n{\times}m$ boolean matrix and all $m{\times}k$ boolean matrices.