• Review of KIISC
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• v.9 no.4
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• pp.81-87
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• 1999

Density'(밀도)가 비교적 높은 Chor-Rivest 암호체계는 기존의 LLL과 같은 유형의 공격법이 아니라 비밀키를 일부 찾아내므로 써 공격이 가능하고 '98 Crypto에 처음 발표되 고 '99 Crypto에 그의 공격법과 안전성이 논의된 hidden subset sum problem은 기존의 knapsack 유형의 암호체계와 마찬가지로 밀도가 높을 때 안전하고 밀도가 낮으면 공격이 가능하다 따라서 두 암호체계의 접목을 통하여 안전한 암호체계가 가능한지를 살펴보는 것 도 의미가 있을 것이다, 결론적으로 이야기하면 두암호체계의 접목은 여러 가지 문제점을 포함하고 있기 때문에 어려우리라 생각된다. 제1장에서의 hidden subset sum problem을 살 펴보고 제2장에서는 Chor-Rivest 암호체계를 분석해보고 제 3장에서 Chor-Rivest 암호체계 의 변경 가능한 요소들을 살펴보고 제4장에서 Chor-Rivest 암호체계에 hidden subset sum problem의 활용이 가능한지를 살펴보도록한다. knapsack 유형의 암호체계들중 비교적 최근 까지 안전하다고 하는 암호체계들을 살펴봄으로써 이런 유형들의 개발여부를 생각해 볼수 있는 기회가 되리라 기대된다.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.4
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• pp.259-267
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• 2018

The subset-sum problem is to find out whether or not the element sum of a subset within a finite set of numbers is equal to a given value. The problem is a well-known NP-complete problem, which is difficult to solve within a polynomial time. Genetic algorithm is a method for finding the optimal solution of a given problem through operations such as selection, crossover, and mutation. Dynamic programming is a method of solving a given problem from one or several subproblems. In this paper, we design and implement a genetic algorithm that solves the subset-sum problem, and experimentally compared the time performance to find the answer with the case of dynamic programming method. We selected a total of 17 test cases considering the difficulty in a set with 63 elements of positive number, and compared the performance of the two algorithms. The presented genetic algorithms showed time performance improved by 84% on 13 of 17 problems when compared with dynamic programming.

• Bulletin of the Korean Mathematical Society
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• v.59 no.6
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• pp.1339-1348
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• 2022

Let A = {a₁ < a₂ < ⋯} be a sequence of integers and let P(A) = {Σε_ia_i : a_i ∈ A, ε_i = 0 or 1, Σε_i < ∞}. Burr posed the following question: Determine conditions on integers sequence B that imply either the existence or the non-existence of A for which P(A) is the set of all non-negative integers not in B. In this paper, we focus on some problems of subset sum related to Burr's question.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.9-14
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• 2022

This paper presents a subset sum problem (SSP) algorithm which takes the time complexity of O(nlogn). The SSP can be classified into either super-increasing sequence or random sequence depending on the element of Set S. Additive algorithm that runs in O(nlogn) has already been proposed to and utilized for the super-increasing sequence SSP, but exhaustive Brute-Force method with time complexity of O(n2ⁿ) remains as the only viable algorithm for the random sequence SSP, which is thus considered NP-complete. The proposed subtractive algorithm basically selects a subset S comprised of values lower than target value t, then sets the subset sum less the target value as the Residual r, only to remove from S the maximum value among those lower than t. When tested on various super-increasing and random sequence SSPs, the algorithm has obtained optimal solutions running less than the cardinality of S. It can therefore be used as a general algorithm for the SSP.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.680-689
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• 2013

In recent, much attention has been paid to the educational serious games that provide both fun and learning effects. However, most educational games have been targeted at the infants and children, and it is still hard to use such games in higher education. On the contrary, this paper aims to develop an educational game for teaching mathematical programming to the undergraduates. It is well known that most puzzle games can be transformed into associated optimization problem and vice versa, and this paper proposes a simple educational game based on the subset sum problem. This game enables the users to play the puzzle and construct their own mathematical programming model for solving it. Moreover, the users are provided with appropriate instructions for modeling and their models are evaluated by using the data automatically generated. It is expected that the educational game in this paper will be helpful for teaching basic programming models to the students in industrial engineering or management science.

• Journal of the Korean Mathematical Society
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• v.55 no.6
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• pp.1337-1358
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• 2018

In this paper, we study the solvability of the nonlinear Dirichlet problem with sum of the operators of independent non standard growths $$-div\({\mid}{\nabla}u{\mid}^{p_1(x)-2}{\nabla}u\)-\sum\limits^n_{i=1}D_i\({\mid}u{\mid}^{p_0(x)-2}D_iu\)+c(x,u)=h(x),\;{\in}{\Omega}$$ in a bounded domain ${\Omega}{\subset}{\mathbb{R}}^n$. Here, one of the operators in the sum is monotone and the other is weakly compact. We obtain sufficient conditions and show the existence of weak solutions of the considered problem by using monotonicity and compactness methods together.

• Kyungpook Mathematical Journal
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• v.45 no.2
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• pp.293-299
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• 2005

Let ${\cal{L}}$ be a commutative subspace lattice on a Hilbert space ${\cal{H}}$ and X and Y be operators on ${\cal{H}}$. Let $${\cal{M}}_X=\{{\sum}{\limits_{i=1}^n}E_{i}Xf_{i}:n{\in}{\mathbb{N}},f_{i}{\in}{\cal{H}}\;and\;E_{i}{\in}{\cal{L}}\}$$ and $${\cal{M}}_Y=\{{\sum}{\limits_{i=1}^n}E_{i}Yf_{i}:n{\in}{\mathbb{N}},f_{i}{\in}{\cal{H}}\;and\;E_{i}{\in}{\cal{L}}\}.$$ Then the following are equivalent. (i) There is an operator A in $Alg{\cal{L}}$ such that AX = Y, Ag = 0 for all g in ${\overline{{\cal{M}}_X}}^{\bot},A^*A=AA^*$ and every E in ${\cal{L}}$ reduces A. (ii) ${\sup}\;\{K(E, f)\;:\;n\;{\in}\;{\mathbb{N}},f_i\;{\in}\;{\cal{H}}\;and\;E_i\;{\in}\;{\cal{L}}\}\;<\;\infty,\;{\overline{{\cal{M}}_Y}}\;{\subset}\;{\overline{{\cal{M}}_X}}$and there is an operator T acting on ${\cal{H}}$ such that ${\langle}EX\;f,Tg{\rangle}={\langle}EY\;f,Xg{\rangle}$ and ${\langle}ET\;f,Tg{\rangle}={\langle}EY\;f,Yg{\rangle}$ for all f, g in ${\cal{H}}$ and E in ${\cal{L}}$, where $K(E,\;f)\;=\;{\parallel}{\sum{\array}{n\\i=1}}\;E_{i}Y\;f_{i}{\parallel}/{\parallel}{\sum{\array}{n\\i=1}}\;E_{i}Xf_{i}{\parallel}$.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.3
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• pp.1-15
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• 2000

In this paper, we propose a practical cut generation method based on the Chvatal-Gomory procedure for the (0, 1)-Knapsack problem with a variable capacity. For a given set N of n items each of which has a positive integral weight and a facility of positive integral capacity, a feasible solution of the problem is defined as a subset S of N along with the number of facilities that can satisfy the sum of weights of all the items in S. We first derive a class of valid inequalities for the problem using Chvatal-Gomory procedure, then analyze the associated separation problem. Based on the results, we develop an affective cut generation method. We then analyze the theoretical strength of the inequalities which can be generated by the proposed cut generation method. Preliminary computational results are also presented which show the effectiveness of the proposed cut generation method.

• Convergence Security Journal
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• v.14 no.7
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• pp.59-64
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• 2014

We investigate $p(n){\cdot}2^{O(\sqrt{n})}$ algorithm for 0/1 knapsack problem where x is the total bit length of a list of sizes of n objects. The algorithm is adaptable of method that achieves a similar complexity for the partition and Subset Sum problem. The method can be applied to other optimization or decision problem based on a list of numerics sizes or weights. 0/1 knapsack problem can be used to solve NP-Complete Problems with pseudo-polynomial time algorithm. We try to apply this technique to bio-informatics problem which has pseudo-polynomial time complexity.

• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.503-510
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• 2004

Given vectors x and y in a Hilbert space, an interpolating operator is a bounded operator T such that Tx = y. An interpolating operator for n vectors satisfies the equation $Tx_i\;=\;y_i,\;for\;i\;=\;1,\;2,\;\cdots,\;n$. In this paper the following is proved: Let H be a Hilbert space and L be a commutative subspace lattice on H. Let H and y be vectors in H. Let $M_x\;=\;\{{\sum{n}{i=1}}\;{\alpha}_iE_ix\;:\;n\;{\in}\;N,\;{\alpha}_i\;{\in}\;{\mathbb{C}}\;and\;E_i\;{\in}\;L\}\;and\;M_y\;=\;\{{\sum{n}{i=1}}\;{\alpha}_iE_iy\;:\;n\;{\in}\;N,\;{\alpha}_i\;{\in}\;{\mathbb{C}}\;and\;E_i\;{\in}\;L\}. Then the following are equivalent. (1) There exists an operator A in AlgL such that Ax = y, Af = 0 for all f in ${\overline{M_x}}^{\bot}$, AE = EA for all $E\;{\in}\;L\;and\;A^{*}\;=\;A$. (2) $sup\;\{\frac{{\parallel}{{\Sigma}_{i=1}}^{n}\;{\alpha}_iE_iy{\parallel}}{{\parallel}{{\Sigma}_{i=1}}^{n}\;{\alpha}_iE_iy{\parallel}}\;:\;n\;{\in}\;N,\;{\alpha}_i\;{\in}\;{\mathbb{C}}\;and\;E_i\;{\in}\;L\}\;<\;{\infty},\;{\overline{M_u}}\;{\subset}{\overline{M_x}}$ and < Ex, y >=< Ey, x > for all E in L.