• The KIPS Transactions:PartC
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• v.9C no.4
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• pp.453-458
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• 2002

Recently, the number of hacking, that use buffer overflow vulnerabilities, are increasing. Although the buffer overflow Problem has been known for a long time, for the following reasons, it continuos to present a serious security threat. There are three defense method of buffer overflow attack. First, allow overwrite but do not allow unauthorized change of control flow. Second, do not allow overwriting at all. Third, allow change of control flow, but prevents execution of injected code. This paper is for allowing overwrites but do not allow unauthorized change of control flow which is the solution of extending compiler. The previous defense method has two defects. First, a program company with overhead because it do much thing before than applying for the method In execution of process. Second, each time function returns, it store return address in reserved memory created by compiler. This cause waste of memory too much. The new proposed method is to extend compiler, by processing after compiling and linking time. To complement these defects, we can reduce things to do in execution time. By processing additional steps after compile/linking time and before execution time. We can reduce overhead.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.9
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• pp.477-486
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• 2003

In combinatorial auctions buyers nay bid for arbitrary combinations of goods. But determining the winners of combinatorial auctions who maximize the profit of a seller is known to be NP-complete. A branch-and-bound method can be one of practical algorithm for winner determination. However, bid selection heuristics play a very important role in the efficiency of a branch-and-bound method. In this paper, we designed and implemented an algorithm which used a branch-and-bound method and Linear Programming for winner determination in combinatorial auctions. We propose new bid selection heuristics which consider a branching bid and conflicting bids simultaneously to select a branching bid in the algorithm. In addition, upper bounds are reused to reduce the running time in specific cases. We evaluated the performance of the algorithm by experiments with five data distributions and compared our method with others. The algorithm using heuristics showed a superior efficiency in two data distributions and a similar efficiency in three distributions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.137-146
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• 2017

For the competitive business environment under purchase dependence, this paper proposes a new approximate calculation of order fill rate which is a probability of satisfying a customer order immediately using the existing inventory. Purchase dependence is different to demand dependence. Purchase dependence treats the purchase behavior of customers, while demand dependence considers demand correlation between items, between regions, or over time. Purchase dependence can be observed in such areas as marketing, manufacturing systems, and distribution systems. Traditional computational methods have a difficulty of the curse of dimensionality for the large cases, when deriving the stationary joint distribution which is utilized to calculate the order fill rate. In order to escape the curse of dimensionality and protect the solution from diverging for the large cases, we develop a greedy iterative search algorithm based on the Gauss-Seidel method. We show that the greedy iterative search algorithm is a dependable algorithm to derive the stationary joint distribution of on-hand inventories in the retailer system by conducting a comparison analysis of a greedy iterative search algorithm with the simulation. In addition, we present some managerial insights such as : (1) The upper bound of order fill rate can be calculated by the one-item pure system, while the lower bound can be provided by the pure system that consists of all items; (2) As the degree of purchase dependence declines while other conditions remain same, it is observed that the difference between the lower and upper bounds reduces, the order fill rate increases, and the order fill rate gets closer to the upper bound.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1114-1122
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• 2018

In this paper, we propose a theoretical framework for provisioning marginal resources in wired and wireless computer networks which include Internet. In more detail, we propose a mathematical model for the upper bounds of marginal capacity in grid networks, where the resource is designed a priori by normal traffic estimation and marginal resource is prepared for unexpected events such as natural disasters and abrupt flash crowd in public affairs. To be specific, we propose a method to evaluate an upper bound for minimum marginal capacity for an arbitrary grid topology using the concept of a strong Roman domination number. To that purpose, we introduce a graph theory to model and analyze the characteristics of general grid structure networks. After that we propose a new tight upper bound for the strong Roman domination number. Via a numerical example, we show the validity of the proposition.

• Journal of the Earthquake Engineering Society of Korea
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• v.2 no.1
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• pp.79-93
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• 1998

The eigenvalue problem is presented for the building with added viscoelastic dampers by using component mode method. The Lagrange multiplier formulation is used to derive the eigenvalue problem which is expressed with the natural frequencies of the building, the mode components at which the dampers are added, and the viscoelastic property of the damper. The derived eigenvalue problem has a nonstandard form for determining the eigenvalues. Therefore, the problem is examined by the graphical depiction to give new insight into the eigenvalues for the building with added viscoelastic dampers. Using the present approach the exact eigenvalues can be found and also upper and lower bounds of the eigenvalues can be obtained.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.1-11
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• 2016

Entani and Tanaka (2007) presented a new approach for obtaining interval evaluations suitable for handling uncertain data. Above all, their approach is characterized by the normalization of interval data and thus the elimination of redundant bounds. Further, interval global weights in AHP are derived by using such normalized interval data. In this paper, we present a heuristic method for finding extreme points of interval data, which basically extends the method by Entani and Tanaka (2007), and also helps to obtain normalized interval data. In the second part of this paper, we show that the solutions to the linear program for interval global weights can be obtained by a simple inspection. In the meantime, the absolute dominance proposed by the authors is extended to pairwise dominance which makes it possible to identify at least more dominated alternatives under the same information.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.2
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• pp.169-172
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• 2019

Frequency-modulated continuous wave(FMCW) radars with array antennas are widely used because of their light weight and relatively high resolution. A usual approach for the joint range and angle estimation of a target using an array FMCW radar is to create a range-angle matrix with the deramped received signal, and subsequently apply two-dimensional(2D) frequency estimation methods such as 2D fast Fourier transform on the range-angle matrix. However, such frequency estimation approaches cause bias errors since the frequencies in the range-angle matrix are not independent. Therefore, we propose a new maximum likelihood-based algorithm for joint range and angle estimation of targets using array FMCW radar, and demonstrate that the proposed algorithm achieves the Cram?r-Rao bounds, both for range as well as angle estimation.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.93-103
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• 2019

We introduce a geometric processing method for freeform surfaces based on high-precision torus patch approximation, a new spatial data structure for efficient geometric operations on freeform surfaces. A torus patch fits the freeform surface with flexibility: it can handle not only positive and negative curvature but also a zero curvature. It is possible to precisely approximate the surface regardless of the convexity/concavity of the surface. Unlike the traditional method, a torus patch easily bounds the surface normal, and the offset of the torus becomes a torus again, thus helps the acceleration of various geometric operations. We have shown that the torus patch's approximation accuracy of the freeform surface is high by measuring the upper bound of the two-sided Hausdorff distance between the freeform surface and set of torus patches. Using the method, it can be easily processed to detect an intersection curve between two freeform surfaces and find the offset surface of the freeform surface.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.1-22
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• 2017

Analysis of future business or investment opportunities, such as business feasibility analysis and company or technology valuation, necessitate objective estimation on the relevant market and expected sales. While there are various ways to classify the estimation methods of these new sales or market size, they can be broadly divided into top-down and bottom-up approaches by benchmark references. Both methods, however, require a lot of resources and time. Therefore, we propose a data-based intelligent demand forecasting system to support evaluation of new business. This study focuses on analogical forecasting, one of the traditional quantitative forecasting methods, to develop sales forecasting intelligence systems for new businesses. Instead of simply estimating sales for a few years, we hereby propose a method of estimating the sales of new businesses by using the initial sales and the sales growth rate of similar companies. To demonstrate the appropriateness of this method, it is examined whether the sales performance of recently established companies in the same industry category in Korea can be utilized as a reference variable for the analogical forecasting. In this study, we examined whether the phenomenon of "mean reversion" was observed in the sales of start-up companies in order to identify errors in estimating sales of new businesses based on industry sales growth rate and whether the differences in business environment resulting from the different timing of business launch affects growth rate. We also conducted analyses of variance (ANOVA) and latent growth model (LGM) to identify differences in sales growth rates by industry category. Based on the results, we proposed industry-specific range and linear forecasting models. This study analyzed the sales of only 150,000 start-up companies in Korea in the last 10 years, and identified that the average growth rate of start-ups in Korea is higher than the industry average in the first few years, but it shortly shows the phenomenon of mean-reversion. In addition, although the start-up founding juncture affects the sales growth rate, it is not high significantly and the sales growth rate can be different according to the industry classification. Utilizing both this phenomenon and the performance of start-up companies in relevant industries, we have proposed two models of new business sales based on the sales growth rate. The method proposed in this study makes it possible to objectively and quickly estimate the sales of new business by industry, and it is expected to provide reference information to judge whether sales estimated by other methods (top-down/bottom-up approach) pass the bounds from ordinary cases in relevant industry. In particular, the results of this study can be practically used as useful reference information for business feasibility analysis or technical valuation for entering new business. When using the existing top-down method, it can be used to set the range of market size or market share. As well, when using the bottom-up method, the estimation period may be set in accordance of the mean reverting period information for the growth rate. The two models proposed in this study will enable rapid and objective sales estimation of new businesses, and are expected to improve the efficiency of business feasibility analysis and technology valuation process by developing intelligent information system. In academic perspectives, it is a very important discovery that the phenomenon of 'mean reversion' is found among start-up companies out of general small-and-medium enterprises (SMEs) as well as stable companies such as listed companies. In particular, there exists the significance of this study in that over the large-scale data the mean reverting phenomenon of the start-up firms' sales growth rate is different from that of the listed companies, and that there is a difference in each industry. If a linear model, which is useful for estimating the sales of a specific company, is highly likely to be utilized in practical aspects, it can be explained that the range model, which can be used for the estimation method of the sales of the unspecified firms, is highly likely to be used in political aspects. It implies that when analyzing the business activities and performance of a specific industry group or enterprise group there is political usability in that the range model enables to provide references and compare them by data based start-up sales forecasting system.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.1
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• pp.15-25
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• 2005

Embedded systems have a set of tasks to execute. These tasks can be implemented either on application specific hardware or as software running on a specific processor. The design of an embedded system involves the selection of hardware software resources, Partition of tasks into hardware and software, and performance evaluation. An accurate estimation of execution time for extreme cases (best and worst case) is important for hardware/software codesign. A tighter estimation of the execution time bound nay allow the use of a slower processor to execute the code and may help lower the system cost. In this paper, we consider an ARM-based embedded system and developed a tool to estimate the tight boundary of execution time of a task with loop bounds and any additional program path information. The tool we developed is based on an exiting timing analysis tool named 'Cinderella' which currently supports i960 and m68k architectures. We add a module to handle ARM ELF object file, which extracts control flow and debugging information, and a module to handle ARM instruction set so that the new tool can support ARM processor. We validate the tool by comparing the estimated bound of execution time with the run-time execution time measured by ARMulator for a selected bechmark programs.