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TWR based Cooperative Localization of Multiple Mobile Robots for Search and Rescue Application (재난 구조용 다중 로봇을 위한 GNSS 음영지역에서의 TWR 기반 협업 측위 기술)

  • Lee, Chang-Eun;Sung, Tae-Kyung
    • The Journal of Korea Robotics Society
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    • v.11 no.3
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    • pp.127-132
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    • 2016
  • For a practical mobile robot team such as carrying out a search and rescue mission in a disaster area, the localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a global positioning system (GPS) is unavailable. The proposed architecture supports localizing robots seamlessly by finding their relative locations while moving from a global outdoor environment to a local indoor position. The proposed schemes use a cooperative positioning system (CPS) based on the two-way ranging (TWR) technique. In the proposed TWR-based CPS, each non-localized mobile robot act as tag, and finds its position using bilateral range measurements of all localized mobile robots. The localized mobile robots act as anchors, and support the localization of mobile robots in the GPS-shadow region such as an indoor environment. As a tag localizes its position with anchors, the position error of the anchor propagates to the tag, and the position error of the tag accumulates the position errors of the anchor. To minimize the effect of error propagation, this paper suggests the new scheme of full-mesh based CPS for improving the position accuracy. The proposed schemes assuring localization were validated through experiment results.

Statistical Image Feature Based Block Motion Estimation for Video Sequences (비디오 영상에서 통계적 영상특징에 의한 블록 모션 측정)

  • Bae, Young-Lae;Cho, Dong-Uk;Chun, Byung-Tae
    • The Journal of the Korea Contents Association
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    • v.3 no.1
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    • pp.9-13
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    • 2003
  • We propose a block motion estimation algorithm based on a statistical image feature for video sequences. The statistical feature of the reference block is obtained, then applied to select the candidate starting points (SPs) in the regular starting points pattern (SPP) by comparing the statistical feature of reference block with that of blocks which are spread ower regular SPP. The final SPs are obtained by their Mean Absolute Difference(MAD) value among the candidate SPs. Finally, one of conventional fast search algorithms, such as BRGDS, DS, and three-step search (TSS), has been applied to generate the motion vector of reference block using the final SPs as its starting points. The experimental results showed that the starting points from fine SPs were as dose as to the global minimum as we expected.

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Active Distribution System Planning Considering Battery Swapping Station for Low-carbon Objective using Immune Binary Firefly Algorithm

  • Shi, Ji-Ying;Li, Ya-Jing;Xue, Fei;Ling, Le-Tao;Liu, Wen-An;Yuan, Da-Ling;Yang, Ting
    • Journal of Electrical Engineering and Technology
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    • v.13 no.2
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    • pp.580-590
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    • 2018
  • Active distribution system (ADS) considering distributed generation (DG) and electric vehicle (EV) is an effective way to cut carbon emission and improve system benefits. ADS is an evolving, complex and uncertain system, thus comprehensive model and effective optimization algorithms are needed. Battery swapping station (BSS) for EV service is an essential type of flexible load (FL). This paper establishes ADS planning model considering BSS firstly for the minimization of total cost including feeder investment, operation and maintenance, net loss and carbon tax. Meanwhile, immune binary firefly algorithm (IBFA) is proposed to optimize ADS planning. Firefly algorithm (FA) is a novel intelligent algorithm with simple structure and good convergence. By involving biological immune system into FA, IBFA adjusts antibody population scale to increase diversity and global search capability. To validate proposed algorithm, IBFA is compared with particle swarm optimization (PSO) algorithm on IEEE 39-bus system. The results prove that IBFA performs better than PSO in global search and convergence in ADS planning.

A Novel Algorithm for Optimal Location of FACTS Devices in Power System Planning

  • Kheirizad, Iraj;Mohammadi, Amir;Varahram, Mohammad Hadi
    • Journal of Electrical Engineering and Technology
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    • v.3 no.2
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    • pp.177-183
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    • 2008
  • The particle swarm optimization(PSO) has been shown to converge rapidly during the initial stages of a global search, but around global optimum, the search process becomes very slow. On the other hand, the genetic algorithm is very sensitive to the initial population. In fact, the random nature of the GA operators makes the algorithm sensitive to initial population. This dependence to the initial population is in such a manner that the algorithm may not converge if the initial population is not well selected. In this paper, we have proposed a new algorithm which combines PSO and GA in such a way that the new algorithm is more effective and efficient and can find the optimal solution more accurately and with less computational time. Optimal location of SVC using this hybrid PSO-GA algorithm is found. We have also found the optimal place of SVC using GA and PSO separately and have compared the results. It has been shown that the new algorithm is more effective and efficient. An IEEE 68 bus test system is used for simulation.

Implementation and Application of Multiple Local Alignment (다중 지역 정렬 알고리즘 구현 및 응용)

  • Lee, Gye Sung
    • The Journal of the Convergence on Culture Technology
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    • v.5 no.3
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    • pp.339-344
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    • 2019
  • Global sequence alignment in search of similarity or homology favors larger size of the sequence because it keeps looking for more similar section between two sequences in the hope that it adds up scores for matched part in the rest of the sequence. If a substantial size of mismatched section exists in the middle of the sequence, it greatly reduces the total alignment score. In this case a whole sequence would be better to be divided into multiple sections. Overall alignment score over the multiple sections of the sequence would increase as compared to global alignment. This method is called multiple local alignment. In this paper, we implement a multiple local alignment algorithm, an extension of Smith-Waterman algorithm and show the experimental results for the algorithm that is able to search for sub-optimal sequence.

Accurate Detection of a Defective Area by Adopting a Divide and Conquer Strategy in Infrared Thermal Imaging Measurement

  • Jiangfei, Wang;Lihua, Yuan;Zhengguang, Zhu;Mingyuan, Yuan
    • Journal of the Korean Physical Society
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    • v.73 no.11
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    • pp.1644-1649
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    • 2018
  • Aiming at infrared thermal images with different buried depth defects, we study a variety of image segmentation algorithms based on the threshold to develop global search ability and the ability to find the defect area accurately. Firstly, the iterative thresholding method, the maximum entropy method, the minimum error method, the Ostu method and the minimum skewness method are applied to image segmentation of the same infrared thermal image. The study shows that the maximum entropy method and the minimum error method have strong global search capability and can simultaneously extract defects at different depths. However none of these five methods can accurately calculate the defect area at different depths. In order to solve this problem, we put forward a strategy of "divide and conquer". The infrared thermal image is divided into several local thermal maps, with each map containing only one defect, and the defect area is calculated after local image processing of the different buried defects one by one. The results show that, under the "divide and conquer" strategy, the iterative threshold method and the Ostu method have the advantage of high precision and can accurately extract the area of different defects at different depths, with an error of less than 5%.

Solving the Travelling Salesman Problem Using an Ant Colony System Algorithm

  • Zakir Hussain Ahmed;Majid Yousefikhoshbakht;Abdul Khader Jilani Saudagar;Shakir Khan
    • International Journal of Computer Science & Network Security
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    • v.23 no.2
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    • pp.55-64
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    • 2023
  • The travelling salesman problem (TSP) is an important combinatorial optimization problem that is used in several engineering science branches and has drawn interest to several researchers and scientists. In this problem, a salesman from an arbitrary node, called the warehouse, starts moving and returns to the warehouse after visiting n clients, given that each client is visited only once. The objective in this problem is to find the route with the least cost to the salesman. In this study, a meta-based ant colony system algorithm (ACSA) is suggested to find solution to the TSP that does not use local pheromone update. This algorithm uses the global pheromone update and new heuristic information. Further, pheromone evaporation coefficients are used in search space of the problem as diversification. This modification allows the algorithm to escape local optimization points as much as possible. In addition, 3-opt local search is used as an intensification mechanism for more quality. The effectiveness of the suggested algorithm is assessed on a several standard problem instances. The results show the power of the suggested algorithm which could find quality solutions with a small gap, between obtained solution and optimal solution, of 1%. Additionally, the results in contrast with other algorithms show the appropriate quality of competitiveness of our proposed ACSA.

Improvement of Hybrid Vision Correction Algorithm for Water Resources Engineering Problem (수자원공학 문제 적용을 위한 Hybrid Vision Correction Algorithm의 개량)

  • Ryu, Yong Min;Lee, Eui Hoon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.196-196
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    • 2021
  • 상수관망은 많은 관을 통해 물의 수요가 있는 곳으로 물을 공급해주는 역할을 하는 사회기반 시설물이다. 상수관망 설계의 요점은 두 가지로 구분할 수 있다. 첫 번째 요점은 다양한 종류의 관배치로 인한 상수관망 설계안의 많은 경우의 수이다. 두 번째 요점은 상수관망 내 절점의 최저 요구수압 등의 제약조건이다. 두 가지 요점이 있는 상황에서 상수관망 설계비용의 최소화를 위한 상수관망 최적설계는 많은 계산이 요구된다. 많은 계산이 요구되기 때문에 상수관망 최적설계에 최적화 기법을 적용할 수 있다. 본 연구에서 상수관망 최적설계를 위해 적용된 최적화 기법은 Hybrid Rate(HR)를 개선한 Hybrid Vision Correction Algorithm(HVCA)이다. HVCA는 Vision Correction Algorithm(VCA)을 기반으로 추가적인 전역탐색을 실행하는 Centralized Global Search(CGS)의 적용 및 자가적응형 매개변수인 Hybrid Rate(HR)를 적용하여 사용성과 성능을 개량한 알고리즘이다. HVCA의 기존 HR은 선형적으로 증가하는 형태이다. 선형적으로 증가하는 HR로 인해 HVCA는 최적해 탐색과정에서 지역해에 빠지는 문제가 발생하였다. HVCA의 문제를 해결하기 위해 HR을 비선형적으로 증가하는 형태로 개량하였다. HR이 개량된 HVCA를 수자원공학 문제인 상수관망 최적설계 문제에 적용하여 결과를 비교하였다. 적용결과 HR이 개량된 HVCA가 기존의 HVCA보다 낮은 설계 비용을 나타내었다. 상수관망 최적설계 적용결과를 바탕으로 HR이 개량된 HVCA는 상수관망 최적설계 이외의 수자원공학 문제에도 적용가능할 것이다.

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Global Online Leadership Strategies for Public and Private Sectors (공공기관 및 수출기업 글로벌 온라인 홍보전략)

  • Jeong, Euiseob;Moon, SunJoo;Kim, Chanho;Yun, Insik;Park, Boyana
    • Journal of Korea Technology Innovation Society
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    • v.16 no.1
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    • pp.1-19
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    • 2013
  • A myriad of information production channels and medium including internet, social media, and multi media channels emerged, often with conflicting interests, disseminate unwanted and inaccurate information which could result in sudden severe public relations damage to the global companies with world class products if not dealt with in the professional way. Properly crafted and managed public relations thus should become the integral part of all organizations. In particular online public relations leadership becomes even more important to public organizations responsible for national branding and interests and to private sectors expanding into the global markets. The research aims to increase global competitiveness of the pubic and exporters by presenting the online leadership strategy 101. For this purpose, locally produced web sites are analysed both from technical and global marketing perspectives. From the research all web sites were classified into three types of ghost, wreck, and moron. The 2012 research showed that 99% was moron, followed by 67% wreck and 1% ghost. The research presents must strategies for global public relations and marketing. They include strategic planning, public relation training, white hat search engine optimization, web standards, web accessibility, mobile web site and the inbound marketing strategies.

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Calibration of a Network Link Travel Cost Function with the Harmony Search Algorithm (화음탐색법을 이용한 교통망 링크 통행비용함수 정산기법 개발)

  • Kim, Hyun Myung;Hwang, Yong Hwan;Yang, In Chul
    • Journal of Korean Society of Transportation
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    • v.30 no.5
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    • pp.71-82
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    • 2012
  • Some previous studies adopted a method statistically based on the observed traffic volumes and travel times to estimate the parameters. Others tried to find an optimal set of parameters to minimize the gap between the observed and estimated traffic volumes using, for instance, a combined optimization model with a traffic assignment model. The latter is frequently used in a large-scale network that has a capability to find a set of optimal parameter values, but its appropriateness has never been demonstrated. Thus, we developed a methodology to estimate a set of parameter values of BPR(Bureau of Public Road) function using Harmony Search (HS) method. HS was developed in early 2000, and is a global search method proven to be superior to other global search methods (e.g. Genetic Algorithm or Tabu search). However, it has rarely been adopted in transportation research arena yet. The HS based transportation network calibration algorithm developed in this study is tested using a grid network, and its outcomes are compared to those from incremental method (Incre) and Golden Section (GS) method. It is found that the HS algorithm outperforms Incre and GS for copying the given observed link traffic counts, and it is also pointed out that the popular optimal network calibration techniques based on an objective function of traffic volume replication are lacking the capability to find appropriate free flow travel speed and ${\alpha}$ value.