• Title/Summary/Keyword: Intelligent techniques

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College Students' Needs and Perception Assessment to Apply Virtual Reality(VR) Techniques to Library Services (가상현실(VR) 기술의 도서관서비스 적용에 대한 대학생들의 인식 및 요구 조사)

  • Kwon, Sun-young
    • Journal of the Korea Convergence Society
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    • v.10 no.5
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    • pp.141-148
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    • 2019
  • The study aims to assess college students' perception and needs for applying virtual reality(VR) techniques to library services. To achieve the purpose of the study, the study broadly reviewed previous studies related to applying various intelligent information technology including VR techniques to the core tasks and services in the fields of library. The study also examined total 563 college students' needs and perception regarding to applying VR techniques to current library services by using the survey method. On the basis of the survey findings, the study suggested some strategies for re-educating and preparing current librarains and library workers who can utilize new intelligent information technologies and contents including VR in the fields of library.

SD-MTD: Software-Defined Moving-Target Defense for Cloud-System Obfuscation

  • Kang, Ki-Wan;Seo, Jung Taek;Baek, Sung Hoon;Kim, Chul Woo;Park, Ki-Woong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.3
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    • pp.1063-1075
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    • 2022
  • In recent years, container techniques have been broadly applied to cloud computing systems to maximize their efficiency, flexibility, and economic feasibility. Concurrently, studies have also been conducted to ensure the security of cloud computing. Among these studies, moving-target defense techniques using the high agility and flexibility of cloud-computing systems are gaining attention. Moving-target defense (MTD) is a technique that prevents various security threats in advance by proactively changing the main attributes of the protected target to confuse the attacker. However, an analysis of existing MTD techniques revealed that, although they are capable of deceiving attackers, MTD techniques have practical limitations when applied to an actual cloud-computing system. These limitations include resource wastage, management complexity caused by additional function implementation and system introduction, and a potential increase in attack complexity. Accordingly, this paper proposes a software-defined MTD system that can flexibly apply and manage existing and future MTD techniques. The proposed software-defined MTD system is designed to correctly define a valid mutation range and cycle for each moving-target technique and monitor system-resource status in a software-defined manner. Consequently, the proposed method can flexibly reflect the requirements of each MTD technique without any additional hardware by using a software-defined approach. Moreover, the increased attack complexity can be resolved by applying multiple MTD techniques.

Anti-swing and Position Control of Crane Using Intelligent Technique (지능제어를 이용한 크레인의 진동 및 위치 제어에 관한 연구)

  • Lee, Eun-Gyung;Lee, Suk
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1995.10a
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    • pp.524-527
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    • 1995
  • In most cases, a crane is controlled by an open-loop technique. That is, the controller tries to follow a given velocity profile that is designed to minimize the swing of rope and the transfer time. But such a system is not capable of handling various disturbances such as changing rope length and wind effect. In order to overcome this kind of difficulty, this research focuses on the design of a feedback controller using intelligent techniques such as fuzzy logic and neural network. These intelligent techniques has been emplyoyed in order to represent human knowledge and to imitate human learning. The deveped controllers have been evaluated via computer simulation

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Multiple Interactive Visualization Techniques for Information (복합상호작용 시각화기법을 통한 정보 표출)

  • Kang, Sang-Goo;Nam, Doohee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.11 no.5
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    • pp.56-61
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    • 2012
  • Several Visualization techniques have been applied in traffic information area. This work is the basic research for applying of interactive visualization techniques when the traffic information is provided to users. Design of interactive visualization techniques were applied to traffic information services. Previous studies for information visualization with interactive visualization techniques were investigated, and the traffic information services currently provided were analyzed. There are many types of interactive visualization techniques, but this study is mainly focused on selecting, querying, linking, filtering and rearranging techniques. The users can obtain the proper and more suitable information for theie needs, because each interactive visualization techniques support interaction between information and users. The traffic information which has one of interactive techniques can be more effective for decision making and utilization. More attention is given to interactive visualization of data and information techniques in transportation field. By this research, it is expected that traffic information services is more effective and can be a foundation work for various interactive visualization techniques in traffice inforamtion.

Applications of Data Mining Techniques to Operations Planning for Real Time Order Confirmation (실시간 주문 확답을 위한 데이터 마이닝 기반 운용 계획 모델)

  • Han Hyun-Soo;Oh Dong-Ha
    • Korean Management Science Review
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    • v.21 no.3
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    • pp.101-113
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    • 2004
  • In the rapidly propagating Internet based electronic transaction environment. the importance of real time order confirmation has been more emphasized, In this paper, using data mining techniques, we develop intelligent operations decision model to allow real time order confirmation at the time the customer places an order with required delivery terms. Among various operation plannings used for order fulfillment. mill routing is the first interface decision point to link the order receiving at the marketing with the production planning for order fulfillment. Though linear programming based mathematical optimization techniques are mostly used for mill routing problems, some early orders should wait until sufficient orders are gathered for optimization. And that could effect longer order fulfillment lead-time, and prevent instant order confirmation of delivery terms. To cope with this problem, we provide the intelligent decision model to allow instant order based mill routing decisions. Data mining techniques of decision trees and neural networks. which are more popular in marketing and financial applications, are used to develop the model. Through diverse computational trials with the industrial data from the steel company. we have reported that the performance of the proposed approach is effective compared to the present heuristic only mill routing results. Various issues of data mining techniques application to the mill routing problems having linear programming characteristics are also discussed.

Introducing the Concept of Intelligent Financial Inclusion

  • Anam Yasir;Alia Ahmed
    • International Journal of Computer Science & Network Security
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    • v.23 no.4
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    • pp.103-110
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    • 2023
  • Financial inclusion is the safe and timely access of formal financial services to people at affordable costs. Various barriers of legacy financial system hinder the involvement of all segments of populations in the financial sector. The journey from financial exclusion to financial inclusion has to be achieved with the implementation of technological breakthroughs. Covid-19 has also raised the need for technology in all sectors of the economy. This research paper introduces the concept of intelligent financial inclusion which is the provision of financial services to people with the help of intelligent systems. This intelligent system will take the concepts from the human mind, cognitive sciences, and artificial intelligence tools and techniques. For achieving the optimal level of financial inclusion, economies must shift their financial sector from traditional means to intelligent financial systems. In this way, intelligent financial inclusion will achieve the target of involving all people in the financial sector.

IMAGE PROCESSING TECHNIQUES FOR LANE-RELATED INFORMATION EXTRACTION AND MULTI-VEHICLE DETECTION IN INTELLIGENT HIGHWAY VEHICLES

  • Wu, Y.J.;Lian, F.L.;Huang, C.P.;Chang, T.H.
    • International Journal of Automotive Technology
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    • v.8 no.4
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    • pp.513-520
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    • 2007
  • In this paper, we propose an approach to identify the driving environment for intelligent highway vehicles by means of image processing and computer vision techniques. The proposed approach mainly consists of two consecutive computational steps. The first step is the lane marking detection, which is used to identify the location of the host vehicle and road geometry. In this step, related standard image processing techniques are adapted for lane-related information. In the second step, by using the output from the first step, a four-stage algorithm for vehicle detection is proposed to provide information on the relative position and speed between the host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenarios. Herein, experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.

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.

An Efficient Low Complexity Blind Equalization Using Micro-Genetic Algorithm

  • Kim, Sung-Soo;Kang, Jee-Hye
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.3
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    • pp.283-287
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    • 2004
  • In this paper, a method of designing the efficient batch blind equalization with low complexity using a micro genetic algorithm (GA), is presented. In general, the blind equalization techniques that are focused on the complexity reduction might be carried out with minor effect on the performance. Among the advanced various subjects in the field of GAs, a micro genetic algorithm is employed to identity the unknown channel impulse response in order to reduce the search space effectively. A new cost function with respect to the constant modulus criterion is suggested considering its relation to the Wiener criterion. We provide simulation results to show the superiority of the proposed techniques compared to other existing techniques.

Fuzzy Control as Self-Organizing Constraint-Oriented Problem Solving

  • Katai, Osamu;Ida, Masaaki;Sawaragi, Tetsuo;Shimamoto, Kiminori;Iwai, Sosuke
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.887-890
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    • 1993
  • By introducing the notion of constraint-oriented fuzzy inference, we will show that it provides us ways of fuzzy control methods that has abilities of adaptation, learning and self-organization. The basic supporting techniques behind these abilities are“hard”processing by Artificial Intelligence or traditional computational framework and“soft”processing by Neural Network or Genetic Algorithm techniques. The reason that these techniques can be incorporated to fuzzy control systems is that the notion of“constraint”itself has two fundamental properties, that is, the“modularity”property due to its declarativeness and the“logicality”property due to its two-valuedness. From the former property, the modularity property, decomposing and integrating constraints can be done easily and efficiently, which enables us to carry out the above“soft”processing. From the latter property, the logicality property, Qualitative Reasoning and Instance Generalization by Symbolic Reasoning an be carried out, thus enabling the“hard”processing.

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