• Title/Summary/Keyword: Computational intelligence

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Efficient and User-Friendly Image Retrieval System Based on Query by Visual Keys

  • Serata, M.;Sakuma, K.;Stejic, Z.;Kawamoto, K.;Nobuhara, H.;Yoshida, S.;Hirota, K.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.451-454
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    • 2003
  • A new query method, called query by visual keys, is proposed to aim easy operation and efficient region-based image retrieval (RBIR). Visual keys are constructed from representative regions/subimages in a given image database, and the database is indexed with visual keys. A system on PC is presented, where text retrieval techniques are applied to the image retrieval with visual keys. Experimental results show that one retrieval is done within 4ms and that the proposed system achieves the comparable retrieval precision (with user-friendly operation and low computational cost) to conventional region based image retrieval systems

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Adaptive Weight Collaborative Complementary Learning for Robust Visual Tracking

  • Wang, Benxuan;Kong, Jun;Jiang, Min;Shen, Jianyu;Liu, Tianshan;Gu, Xiaofeng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.1
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    • pp.305-326
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    • 2019
  • Discriminative correlation filter (DCF) based tracking algorithms have recently shown impressive performance on benchmark datasets. However, amount of recent researches are vulnerable to heavy occlusions, irregular deformations and so on. In this paper, we intend to solve these problems and handle the contradiction between accuracy and real-time in the framework of tracking-by-detection. Firstly, we propose an innovative strategy to combine the template and color-based models instead of a simple linear superposition and rely on the strengths of both to promote the accuracy. Secondly, to enhance the discriminative power of the learned template model, the spatial regularization is introduced in the learning stage to penalize the objective boundary information corresponding to features in the background. Thirdly, we utilize a discriminative multi-scale estimate method to solve the problem of scale variations. Finally, we research strategies to limit the computational complexity of our tracker. Abundant experiments demonstrate that our tracker performs superiorly against several advanced algorithms on both the OTB2013 and OTB2015 datasets while maintaining the high frame rates.

A Quasi-optimal Restaurant Work Scheduling Based-on Genetic Algorithm with Fuzzy Logic

  • Watanabe, Makoto;Nobuhara, Hajime;Kawamoto, Kazuhiko;Yoshida, Shin-ichi;Hirota, Kaoru
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.517-520
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    • 2003
  • A quasi-optimization algorithm for generating a chain restaurant work scheduling (WS) is proposed based on Genetic Algorithm with fuzzy logic, where the whole weekly chain restaurant WS problem is decomposed to 7 daily WS problems and a combined weekly WS problem. Experimental result shows that a weekly schedule for 15 workers and 24 hours in a chain restaurant is produced in 6 minutes using the proposed algorithm implemented with C++ and executed on a PC(Athlon XP 1900+), where the quality of WS is satisfactorily evaluated by professional experts.

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A Study on Learner's Characteristics and Programming Skill in Computational Literacy Education - Focus on learning style and multiple intelligence - (Computational Literacy 교육에서 프로그래밍 능력과 학습자 특성에 관한 연구 - 학습스타일과 다중지능을 중심으로 -)

  • Kim, Soo-Hwan;Han, Seon-Kwan;Kim, Hyeon-Cheol
    • The Journal of Korean Association of Computer Education
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    • v.13 no.2
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    • pp.15-23
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    • 2010
  • Computational Literacy education is being required in current digital age, but the educational strategy of it is lacking. In traditional education, instructors have been teaching by considering learners' characteristics for effective learning. It is necessary to investigate their characteristics for applying this method to computational literacy education. Therefore, we taught programming that is main area on computational literacy, and analyzed learners' characteristics focused on Felder's learning style and multiple intelligence. That is, we taught 194 university students computational literacy with scratch that was one of the popular educational programming languages, and analyzed the relation among learning style, multiple intelligence and the students' programming performance. Also, we found considerations through comparing students' characteristics with experts' ones.

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Automatic Parameter Tuning for Simulated Annealing based on Threading Technique and its Application to Traveling Salesman Problem

  • Fangyan Dong;Iyoda, Eduardo-Masato;Kewei Chen;Hajime Nobuhara;Kaoru Hirota
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.439-442
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    • 2003
  • In order to solve the difficulties of parameter settings in SA algorithm, an improved practical SA algorithm is proposed by employing the threading techniques, appropriate software structures, and dynamic adjustments of temperature parameters. Threads provide a mechanism to realize a parallel processing under a disperse environment by controlling the flux of internal information of an application. Thread services divide a process by multiple processes leading to parallel processing of information to access common data. Therefore, efficient search is achieved by multiple search processes, different initial conditions, and automatic temperature adjustments. The proposed are methods are evaluated, for three types of Traveling Salesman Problem (TSP) (random-tour, fractal-tour, and TSPLIB test data)are used for the performance evaluation. The experimental results show that the computational time is 5% decreased comparing to conventional SA algorithm, furthermore there is no need for manual parameter settings. These results also demonstrate that the proposed method is applicable to real-world vehicle routing problems.

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An Intelligent Residual Resource Monitoring Scheme in Cloud Computing Environments

  • Lim, JongBeom;Yu, HeonChang;Gil, Joon-Min
    • Journal of Information Processing Systems
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    • v.14 no.6
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    • pp.1480-1493
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    • 2018
  • Recently, computational intelligence has received a lot of attention from researchers due to its potential applications to artificial intelligence. In computer science, computational intelligence refers to a machine's ability to learn how to compete various tasks, such as making observations or carrying out experiments. We adopted a computational intelligence solution to monitoring residual resources in cloud computing environments. The proposed residual resource monitoring scheme periodically monitors the cloud-based host machines, so that the post migration performance of a virtual machine is as consistent with the pre-migration performance as possible. To this end, we use a novel similarity measure to find the best target host to migrate a virtual machine to. The design of the proposed residual resource monitoring scheme helps maintain the quality of service and service level agreement during the migration. We carried out a number of experimental evaluations to demonstrate the effectiveness of the proposed residual resource monitoring scheme. Our results show that the proposed scheme intelligently measures the similarities between virtual machines in cloud computing environments without causing performance degradation, whilst preserving the quality of service and service level agreement.

COMPUTATIONAL INTELLIGENCE IN NUCLEAR ENGINEERING

  • UHRIG ROBERT E.;HINES J. WESLEY
    • Nuclear Engineering and Technology
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    • v.37 no.2
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    • pp.127-138
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    • 2005
  • Approaches to several recent issues in the operation of nuclear power plants using computational intelligence are discussed. These issues include 1) noise analysis techniques, 2) on-line monitoring and sensor validation, 3) regularization of ill-posed surveillance and diagnostic measurements, 4) transient identification, 5) artificial intelligence-based core monitoring and diagnostic system, 6) continuous efficiency improvement of nuclear power plants, and 7) autonomous anticipatory control and intelligent-agents. Several changes to the focus of Computational Intelligence in Nuclear Engineering have occurred in the past few years. With earlier activities focusing on the development of condition monitoring and diagnostic techniques for current nuclear power plants, recent activities have focused on the implementation of those methods and the development of methods for next generation plants and space reactors. These advanced techniques are expected to become increasingly important as current generation nuclear power plants have their licenses extended to 60 years and next generation reactors are being designed to operate for extended fuel cycles (up to 25 years), with less operator oversight, and especially for nuclear plants operating in severe environments such as space or ice-bound locations.

Effect of Multiple Intelligence-based Strategy in Computational Literacy Education (Computational Literacy 교육에서 다중지능전략 교육방법의 효과)

  • Kim, Soo-Hwan;Han, Seon-Kwan;Han, Hee-Seop;Kim, Hyeon-Cheol
    • The Journal of Korean Association of Computer Education
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    • v.14 no.6
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    • pp.11-18
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    • 2011
  • The purpose of this paper was to suggest multiple intelligence-based strategies in CL(Computational Literacy) education with scratch and to verify the effectiveness of it. First, we suggested multiple intelligence-based strategy for novice in programming education and apply it to CL education. Next, we conducted a field experiment to analyze the effectiveness of the educational strategy. 44 students participated in the experiment. Computational problem sloving test, multiple intelligence test, and survey were performed to analyze students' capability. Also, we tested students' programming capability through scratch project. The result shows that interest of programming and CL capability of students were different between treatment group and control group. It was found from the result that the strategy facilitate interest and motivation of students and contribute to effect of programming education.

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