• Journal of Construction Engineering and Project Management
• /
• v.7 no.2
• /
• pp.1-10
• /
• 2017

The Clonal Selection Algorithm (CSA) is an algorithm inspired by the human immune system mechanism. In CSA, several parameters needs to be optimized by large amount of sensitivity analysis for the optimal results. They limit the accuracy of the results due to the uncertainty and subjectivity. Adaptive Clonal Selection (ACS), a modified version of CSA, is developed as an algorithm without controls by pre-defined parameters in terms of selection process and mutation strength. In this paper, we discuss the ACS in detail and present its implementation in construction site utilization planning (CSUP). When applied to a developed model published in research literature, it proves that the ACS are capable of searching the optimal layout of temporary facilities on construction site based on the result of objective function, especially when the parameterization process is considered. Although the ACS still needs some improvements, obtaining a promising result when working on a same case study computed by Genetic Algorithm and Electimze algorithm prove its potential in solving more complex construction optimization problems in the future.

• Proceedings of the IEEK Conference
• /
• 1999.11a
• /
• pp.1097-1100
• /
• 1999

Due to the significant computation of full search in motion estimation, extensive research in fast motion estimation algorithms has been carried out. However, most of the algorithms have the degradation in predicted images compared with the full search algorithm. To reduce an amount of significant computation while keeping the same prediction quality of the full search, we propose a fast block-matching algorithm based on gradient magnitude of reference block without any degradation of predicted image. By using Taylor series expansion, we show that the block matching errors between reference block and candidate block are proportional to the gradient magnitude of matching block. With the derived result, we propose fast full search algorithm with adaptively determined scan direction in the block matching. Experimentally, our proposed algorithm is very efficient in terms of computational speedup and has the smallest computation among all the conventional full search algorithms. Therefore, our algorithm is useful in VLSI implementation of video encoder requiring real-time application.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.35C no.1
• /
• pp.15-24
• /
• 1998

This paper proposes a new template matching algorithm and its chip design. The CC and SAD algorithms require the massive amount of computation. Hence, several algorithms using quantization schemes have been proposed to reduce the amount of computation and its hardware cost. the proposed algorithm called the EMPPM improves at least 22% of the noise margin compared with the MPPM algorithm. In addition, the proposed architecture can reduce the gate count by more than 60% of that used in the SAD algorithm without usig quantization schemes and 28% of the MPPM algorithm. The VHDL models have been simulated by using the CADANCETEX>$^{TM}$ and logic synthesis has been performed by using the SYNOPSYSTEX>$^{TM}$ with $0.6\mu\textrm{m}$ SOG(sea-of-gate) cell library. The implemented chip consists of 35,829 gates, operates at 100 MHz (worst case 53 MHz) and performs the template maching with the speed of 200 Mpixels/sec.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.8
• /
• pp.15-23
• /
• 2017

In this paper, the block reweighting and global offset initialization methods are proposed to complement the improved IRLMS algorithm which is the effective algorithm in registration based SBNUC algorithm. Proposed block weighting method reweights the error map whose abnormal data are excluded. The global offset initialization method compensates the global nonuniformity initially. The ordinary registration based SBNUC algorithm is hard to compensate global nonuniformity because of low scene motion. We employ the proposed methods to improved IRLMS algorithm, and apply it to real-world infrared raw image stream. The result shows that new implementation provides 3.5~4.0dB higher PSNR and convergence speed 1.5 faster then the improved IRLMS algorithm.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.12
• /
• pp.137-143
• /
• 2017

In this paper, we propose optimal route searching algorithm using ANN(Artificial Neural Network) and implement route searching system. Our proposed scheme shows that the route using artificial neural network is almost same as the route using Dijkstra's algorithm but the time in our propose algorithm is shorter than that of existing Dijkstra's algorithm. Proposed route searching method using artificial neural network has better performance than exiting route searching method because it use several weight value in making different routes. Through simulation, we show that our proposed routing system improves the performance and reduces time to make route irrespective of the number of hidden layers.

• Journal of the Korean Institute of Telematics and Electronics A
• /
• v.28A no.1
• /
• pp.60-73
• /
• 1991

This paper presents an efficient algorithm for incremental and hierarchical design rule checking of VLSI layouts, and describes the implementation of a layout editor using the proposed algorithm. Tracing the sliced edges divided by the intersection of the edges either ina polygon or in two polygons (Sliced-Edge Trace), the algorithm performs VLSI pattern operations like resizing and other Boolean operations. The algorithm is not only fast enough to check the layouts of full-custom designs in real-time, but is general enough to be used for arbitrarily shaped polygons. The proposed algorithm was employed in developingt a layout editor on engineering workstations running UNIX. The editor has been successfully used for checking, generating and resizing of VLSI layouts.

• Journal of the Institute of Electronics Engineers of Korea TE
• /
• v.42 no.1
• /
• pp.1-6
• /
• 2005

Channel routing is a problem assigning each net to a track after global routing and minimizing the track that assigned each net. In this paper we propose a genetic algorithm searching solution space for 4-layer channel routing problem. We compare the performance of proposed genetic algorithm(GA) for channel routing with that of other 4-layer channel routing algorithm by analyzing the results of each implementation.

• Journal of Korea Multimedia Society
• /
• v.20 no.2
• /
• pp.163-169
• /
• 2017

There are various algorithms evaluating a threshold for image segmentation. Among them, Otsu's algorithm sets a threshold based on the histogram. It finds the between-class variance for all over gray levels and then sets the largest one as Otsu's optimal threshold, so we can see that Otsu's algorithm requires a lot of the computation. In this paper, we improved the amount of computational needs by using estimated Otsu's threshold rather than computing for all the threshold candidates. The proposed algorithm is compared with the original one in computation amount and accuracy. we confirm that the proposed algorithm is about 29 times faster than conventional method on single processor and about 4 times faster than on parallel processing architecture machine.

• Journal of Advanced Navigation Technology
• /
• v.14 no.5
• /
• pp.618-624
• /
• 2010

This paper address the problem of tracking multiple objects encountered in many situations in developing condensation algorithms. The difficulty lies on the fact that the implementation of condensation algorithm is not easy for the general users. We propose an automatic code generation program for condensation algorithm using MATLAB tool. It will help for general user who is not familiar with condensation algorithm to apply easily for real system. The merit of this program is that a that a general industrial engineer can easily simulate the designed system and confirm the its performance on the fly.

• Proceedings of the KIPE Conference
• /
• 1998.07a
• /
• pp.384-387
• /
• 1998

This paper presents a newly developed speed sensorless drive using RLS(Recursive Least Squares) based on Neural Network Training Algorithm. The proposed algorithm based on the RLS has just the time-varying learning rate, while the well-known back-propagation (or generalized delta rule) algorithm based on gradient descent has a constant learning rate. The number of iterations required by the new algorithm to converge is less than that of the back-propagation algorithm. The RLS based on NN is used to adjust the motor speed so that the neural model output follows the desired trajectory. This mechanism forces the estimated speed to follow precisely the actual motor speed. In this paper, a flux estimation strategy using filter concept is discussed. The theoretical analysis and experimental results to verify the effectiveness of the proposed analysis and the proposed control strategy are described.