• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.4
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• pp.61-70
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• 2005

In this Paper, we develop an improved branch and bound algorithm for the (un)weighted unconstrained two-dimensional cutting problem. In the proposed algorithm, we improve the branching strategies of the existing exact algorithm and reduce the size of problem by removing the dominated pieces from the problem. We apply the newly Proposed definition of dominated cutting pattern and it can reduce the number of nodes that must be searched during the algorithm procedure. The efficiency of the proposed algorithm is presented through comparison with the exact algorithm known as the most efficient.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.504-510
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• 2009

Recently, personalized-adaptive services became the center of interest in the world. However the services about music are not widely diffused out. That is because the analyzing of music information is more difficult than analyzing of text information. In this paper, we propose a music recommendation system which provides personalized services. The system keeps a user's listening list and analyzes it to select pieces of music similar to the user's preference. For analysis, the system extracts properties from the sound wave of music and the time when the user listens to music. Based on the properties, a piece of music is mapped into a point in the property space and the time is converted into the weight of the point. At this time, if we select and analyze the group which is selected by user frequently, we can understand user's taste. However, it is not easy to predict how many groups are formed. To solve this problem, we apply the K-means clustering algorithm to the weighted points. We modified the K-means algorithm so that the number of clusters is dynamically changed. This manner limits a diameter so that we can apply this algorithm effectively when we know the range of data. By this algorithm we can find the center of each group and recommend the similar music with the group. We also consider the time when music is released. When recommending, the system selects pieces of music which is close to and released contemporarily with the user's preference. We perform experiments with one hundred pieces of music. The result shows that our proposed algorithm is effective.

• Spatial Information Research
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• v.20 no.4
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• pp.83-92
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• 2012

Location-based services (LBS) are increasingly popular due to the improvement of geo-positioning capabilities and wireless communication technology. However, in order to enjoy LBS services, a user requesting a query must send his/her exact location to the LBS provider. Therefore, it is a key challenge to preserve user's privacy while providing LBS. To solve this problem, the existing method employs a 2PASS cloaking framework that not only hides the actual user location but also reduces bandwidth consumption. However, 2PASS does not fully guarantee the actual user privacy because it does not take the real user distribution into account. Hence, in this paper, we propose a nearest neighbor query processing algorithm that supports K-anonymity property based on the weighted adjacency graph(WAG). Our algorithm not only preserves the location of a user by guaranteeing k-anonymity in a query region, but also improves a bandwidth usage by reducing unnecessary search for a query result. We demonstrate from experimental results that our algorithm outperforms the existing one in terms of query processing time and bandwidth usage.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.108-115
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• 2007

This paper proposes a new optimization algorithm prescribed by GBNSGA(Goal-Pareto Based Non-dominated Sorting Genetic Algorithm) whose result satisfies the user's needs and goals to enhance the performance of optimization. Typically, lots of real-world engineering problems encounter simultaneous optimization subject to satisfying prescribed multiple objectives. Unfortunately, since these objectives might be mutually competitive, it is hardly to find a unique solution satisfying every objectives. Instead, many researches have been investigated in order to obtain an optimal solution with sacrificing more than one objectives. This paper introduces a novel optimization scheme named by GBNSGA obeying both goals as well as objectives as possible as it can via allocating candidated solutions on Pareto front, which enhances the performance of Pareto based optimization. The performance of the proposed GBNSGA will be compared with that of the conventional NSGA and weighted-sum approach.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.913-917
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• 2009

Flash memories have asymmetric I/O costs for read and write in terms of latency and energy consumption. However, the ratio of these costs is dependent on the type of storage. Moreover, it is becoming more common to use two flash memories on a system as an internal memory and an external memory card. For this reason, buffer cache replacement algorithms should consider I/O costs of device as well as possibility of reference. This paper presents WWCLOCK(Write-Weighted CLOCK) algorithm which directly uses I/O costs of devices along with recency and frequency of cache blocks to selecting a victim to evict from the buffer cache. WWCLOCK can be used for wide range of storage devices with different I/O cost and for systems that are using two or more memory devices at the same time. In addition to this, it has low time and space complexity comparable to CLOCK algorithm. Trace-driven simulations show that the proposed algorithm reduces the total I/O time compared with LRU by 36.2% on average.

• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.339-346
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• 2000

Medical image is analyzed to get an anatomical information for diagnostics. Segmentation must be preceded to recognize and determine the lesion more accurately. In this paper, we propose automatic segmentation algorithm for MR brain images using T1-weighted, T2-weighted and PD images complementarily. The proposed segmentation algorithm is first, extracts cerebrum images from 3 input images using cerebrum mask which is made from PD image. And next, find 3D clusters corresponded to cerebrum tissues using scale filtering and 3D clustering in 3D space which is consisted of T1, T2, and PD axis. Cerebrum images are segmented using FCM algorithm with its initial centroid as the 3D cluster's centroid. The proposed algorithm improved segmentation results using accurate cluster centroid as initial value of FCM algorithm and also can get better segmentation results using multi spectral analysis than single spectral analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1A
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• pp.122-131
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• 2000

In this paper, we propose a cell scheduling algorithm for input queueing ATM switch. The input queueing architecture is attractive for building an ultra-high speed ATM (Asynchronous Transfer Mode) switch. We proposea WMUCS (Weighted Matrix Unit Cell Scheduler) based on the MUCS which resolves HOL blocking and outputport contention. The MUCS algorithm selects an optimal set of entries as winning cells from traffic matrix (weightmatrix). Our WMUCS differs from the MUCS in generating weight matrices. This change solves the starvationproblem and it reduces the cell loss variance. The performance of the proposed algorithm is evaluated by thesimulation program written in C++. The simulation results show that the maximum throughput, the average celldelay, and the cell loss rate are significantly improved. We can see that the performance of WMUCS is excellentand the cost-effective implementation of the ATM switch using proposed cell scheduling algorithm.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.4
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• pp.93-100
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• 2021

The Ethereum shard system for solving the scalability problem of the blockchain has a load balancing issue, which is modeled as a graph partitioning problem. In this paper, we propose an adaptive online weighted graph partitioning algorithm that can negotiate between two utility of the shard system using the game theory's bargaining solution. The bargaining solution is an axiomatic solution that can fairly determine the points of conflict of utility. The proposed algorithm was improved to apply the existing online graph partitioning algorithm to the weighted graph, and load balancing was performed efficiently through the design considering the situation of the sharding system using the extension of Nash bargaining solution, which is extended to apply solution to non-convex feasible set of bargaining problem. As a result of the experiment, it showed up to 37% better performance than typical load balancing algorithm of shard system.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.1
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• pp.44-49
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• 2022

Abstract Recently, with the development of IoT technology and communication media, various video equipment is being used in industrial fields. Image data acquired from cameras and sensors are easily affected by noise during transmission and reception, and noise removal is essential as it greatly affects system reliability. In this paper, we propose a weight filter algorithm based on the pixel value distribution pattern to preserve details in the process of restoring images damaged in AWGN. The proposed algorithm calculates weights according to the pixel value distribution pattern of the image and restores the image by applying a filtering mask. In order to analyze the noise removal performance of the proposed algorithm, it was simulated using enlarged image and PSNR compared to the existing method. The proposed algorithm preserves important characteristics of the image and shows the performance of efficiently removing noise compared to the existing method.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.129-137
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• 2010

Currently used shortest path search algorithms involve graphs with vertices and weighted edges between each vertex. However, when finding the shortest path with a randomly shaped obstacle(an island, for instance) positioned in between the starting point and the destination, using such algorithms involves high memory inefficiency and is significantly time consuming - all positions in the map should be considered as vertices and every line connecting any of the two adjacent vertices should be considered an edge. Therefore, we propose a new method for finding the shortest path in such conditions without using weighted graphs. This algorithm will allow finding the shortest obstacle bypass given only the positions of the obstacle boundary, the starting point and the destination. When the row and column size of the minimum boundary rectangle to include an obstacle is m and n, respectively, the proposed algorithm has the maximum time complexity, O(mn). This performance shows the proposed algorithm is very efficient comparing with the currently used algorithms.