• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.895-900
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• 2023

We study low-complexity graph sampling which selects a subset of nodes from graph nodes so as to reconstruct the original signal from the sampled one. To achieve complexity reduction, we propose a graph sampling algorithm with thresholding which selects a node with a cost lower than a given threshold at each step without fully searching all of the remaining nodes to find one with the minimum cost. Since it is important to find the threshold as close to a minimum cost as possible to avoid degradation of the reconstruction performance, we present a mathematical expression to compute the threshold at each step. We investigate the performance of the different sampling methods for various graphs, showing that the proposed algorithm runs 1.3 times faster than the previous method while maintaining the reconstruction performance.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.2
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• pp.177-185
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• 2010

Ray-object intersection is an important element in ray tracing that takes up a substantial amount of computing time. In general, such spatial data structure as kd-tree has been frequently used for static scenes to accelerate the intersection computation. Recently, a few variants of kd-tree traversal have been proposed suitable for the GPU that has a relatively restricted computing architecture compared to the CPU. In this article, we propose yet another two implementation techniques that can improve those previous ones. First, we present a cached stack method that is aimed to reduce the costly global memory access time needed when the stack is allocated to global memory. Secondly, we present a rope-with-short-stack method that eases the substantial memory requirement, often necessary for the previous rope method. In order to show the effectiveness of our techniques, we compare their performances with those of the previous GPU traversal methods. The experimental results will provide prospective GPU ray tracer developers with valuable information, helping them choose a proper kd-tree traversal method.

• Journal of Korean Society of Transportation
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• v.18 no.3
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• pp.77-86
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• 2000

The shortest path problem is one of the mathematical Programming models that can be conveniently solved through the use of networks. The common shortest Path Problem is to minimize a single objective function such as distance, time or cost between two specified nodes in a transportation network. The sing1e objective model is not sufficient to reflect any Practical Problem with multiple conflicting objectives in the real world applications. In this paper, we consider the shortest Path Problem under multiple objective environment. Wile the shortest path problem with single objective is solvable in Polynomial time, the shortest Path Problem with multiple objectives is NP-complete. A genetic a1gorithm approach is developed to deal with this Problem. The results of the experimental investigation of the effectiveness of the algorithm are also Presented.

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.117-125
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• 2004

The berth and crane scheduling problem in a container terminal encompasses the whole process of assigning berth to each ship. determining the duration of berthing, assigning container cranes to each ship, and determining the specific start and end time of each crane service, for all the ships scheduled to be arriving at the terminal during a certain scheduling horizon. This problem is basically a constraint satisfaction problem in which all the constraints should be satisfied. However, it is also an optimization problem because the requested arrival and departure time should be met for as many of the scheduled ships as possible. while the operation cost of the terminal should be minimized. In this paper. I present an effective approach to solving this problem, which combines both constraint satisfaction search and iterative improvement search. I test this method on a real world container terminal problem and the results show that the method can produce better results than any other existing method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.1C
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• pp.69-77
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• 2002

Sine digital signal processing for motion pictures requires huge amount of data computation to store, manipulate and transmit, more effective data compression is necessary. Therefore, the ITU-T recommended H.26x as data compression standards for digital motion pictures. The data compression method that eliminates time redundancies by motion estimation using relationship between picture frames has been widely used. Most video conding systems employ block matching algorithm for the motion estimation and compensation, and the algorithm is based on the minimun value of cast functions. Therefore, fast search algorithm rather than full search algorithm is more effective in real time low data rates encodings such as H.26x. In this paper, motion estimation employing the Nearest-Neighbors algorithm is designed to reduce search time using FPGA, coded in VHDL, and simulated and verified using Xilink Foundation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.137-141
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• 2005

Optimal path search algorithm should consider traffic flows of the roads as well as the distance between a departure and destination, The existing path search algorithms, however, usually don't apply the continuously changed traffic flows. In this paper, we propose a new optimal path search algorithm. the algorithm takes the current flows into consideration in order to reduce the cost to get destination. It decomposes the road networks into Fixed Grid to get variable heuristics. We also carry out the experiments with Dijkstra and $A^*$ algorithm in terms of the execution time, the number of node accesses and the accuracy of path. The results obtained from the experimental tests show the proposed algorithm outperforms the others. The algorithm is highly expected to be useful in a advanced telematics systems.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.77-88
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• 2006

The purpose of this study is to Propose the time dependent K-least time path algorithm applicable to a real-time based operation strategy in multi-modal transportation network. For this purpose, we developed the extended method based on entire path deletion method which was used in the static K-least time path algorithm. This method was applied to time dependent K-least time path algorithm to find k least time paths in order based on both time dependant mode-link travel time and transfer cost In particular, this algorithm find the optimal solution, easily describing transfer behavior, such as walking and waiting for transfer by applying a link-based time dependent label. Finally, we examined the verification and application of the Proposed algorithm through case study.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.826-829
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• 2008

모바일 환경에서는 모바일 기기의 제한된 에너지를 효율적으로 사용하는 것이 요구된다. 특히 모바일 Peer-to-Peer(P2P) 시스템에서 모바일 기기가 피어로서 저장된 에너지를 모두 소모하면 더 이상파일 탐색 등과 같은 작업에 참여할 수 없게 된다. 또한 에너지가 없는 피어가 증가하게 되면 파일탐색 실패율이 증가하게 되고, 결국 파일탐색이 불가능하게 된다. 슈퍼피어(super peer)를 기반으로 한 계층적 P2P 시스템은 기존 단일 계층 P2P 시스템보다 더 적은 양의 메시지로 파일탐색을 가능하게 해준다. 하지만 하나의 슈퍼피어가 관리하는 서브피어(sub-peer)가 많을 경우, 서브피어의 관리 비용과 파일 탐색 요청의 증가로 슈퍼피어의 에너지 소모 비율이 크게 증가하게 되며, 이로 인해 네트워크 참여 시간이 줄어들게 된다. 이는 전체 네트워크 유지시간 감소에 영향을 미친다. 본 논문은 무선 통신 기반의 모바일 환경에서 슈퍼피어를 기반으로 한 계층적 P2P 시스템을 기반으로, 슈퍼피어가 관리하는 서브피어들의 수를 제한하고, 만약 일정한 수를 초과하였을 경우, 초과한 슈퍼피어의 서브피어들 중에서 새로운 슈퍼피어를 선정하고, 기존 슈퍼피어로부터 일부 서브피어들을 분배하여 관리하게 하는 시스템을 제안하였다. 실험을 통해 성능을 평가 하였으며, 실험 결과 파일 탐색 요청을 위한 네트워크 유지시간이 더 오래 지속됨을 확인하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.1
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• pp.79-87
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• 2013

This study proposed a method to analyze the economic benefit of the national map revision program using the replacement cost method. The replacement cost method measures the benefit of a project as the minimum cost to replace functions of the project with those of alternative goods or services in an existing market. Thus, the demands on 1/5,000 topographic map revision in 18 administrative tasks such as city and district management planning were surveyed in three local autonomous entities. Then the cost to alternatively fulfill the demands was estimated with the standard construction estimating system for the field surveying and surveying results in commercial GIS companies for the site investigation. With this cost estimation model, the benefit of the current national map revision program to the local autonomous entities was estimated as 265,960,999 won. And cost benefit ratios according to several revision frequencies from 0.5 to 4 year were also compared to find the optimal frequency.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.554-560
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• 2019

In this study, after applying the finite failure NHPP Rayleigh distribution model and NHPP Inverse Rayleigh distribution model which are widely used in the field of software reliability to the software development cost model, the attributes of development cost and optimal release time were compared and analyzed. To analyze the attributes of software development cost, software failure time data was used, parametric estimation was applied to the maximum likelihood estimation method, and nonlinear equations were calculated using the bisection method. As a result, it was confirmed that Rayleigh model is relatively superior to Inverse Rayleigh model because software development cost is relatively low and software release time is also fast. Through this study, the development cost attributes of the Rayleigh model and the Inverse Rayleigh model without the existing research examples were newly analyzed. In addition, we expect that software developers will be able to use this study as a basic guideline for exploring software reliability improvement method and development cost attributes.