• Title/Summary/Keyword: 유연한 알고리즘

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A Study on Research Scheme for Peer-to-Peer Network Using Smart Network (스마트 네트워크 구조를 활용한 Peer-to-Peer 기반 콘텐츠 검색 기법 연구)

  • Kang, Mi-Young;Nam, Ji-Seung
    • KIPS Transactions on Computer and Communication Systems
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    • v.3 no.2
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    • pp.57-62
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    • 2014
  • In order to provide real-time multimedia streaming service, a lot of system resources and network bandwidth required. Thus each computer is any computer other equivalent has the ability to act as a client and a server Peer-to-Peer(P2P) architecture with much interest. In this paper, techniques of P2P content that requires a user to efficiently retrieve the desired time in the streaming service have placed the focus of the research techniques. In a number present in the P2P contents, the user requests to find out the desired amount of time the content streaming services in order to provide seamless lookup latency contents search algorithm to minimize the study. P2P based smart network system and the structure of the super-node and the peer node is composed of super-gateway. Smart network system architecture proposed by performing a content search algorithm. The user requests a desired content, the service can be retrieved within the provided the flexibility.

Weighted Fuzzy Reasoning Using Weighted Fuzzy Pr/T Nets (가중 퍼지 Pr/T 네트를 이용한 가중 퍼지 추론)

  • Cho, Sang-Yeop
    • The KIPS Transactions:PartB
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    • v.10B no.7
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    • pp.757-768
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    • 2003
  • This paper proposes a weighted fuzzy reasoning algorithm for rule-based systems based on weighted fuzzy Pr/T nets, where the certainty factors of the fuzzy production rules, the truth values of the predicates appearing in the rules and the weights representing the importance of the predicates are represented by the fuzzy numbers. The proposed algorithm is more flexible and much closer to human intuition and reasoning than other methods : $\circled1$ calculate the certainty factors using by the simple min and max operations based on the only certainty factors of the fuzzy production rules without the weights of the predicates[10] : $\circled2$ evaluate the belief of the fuzzy production rules using by the belief evaluation functions according to fuzzy concepts in the fuzzy rules without the weights of the predicates[12], because this algorithm uses the weights representing the importance of the predicates in the fuzzy production rules.

Effective Design of Pixel-type Frequency Selective Surfaces using an Improved Binary Particle Swarm Optimization Algorithm (개선된 이진 입자 군집 최적화 알고리즘을 적용한 픽셀 형태 주파수 선택적 표면의 효율적인 설계방안 연구)

  • Yang, Dae-Do;Park, Chan-Sun;Yook, Jong-Gwan
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.30 no.4
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    • pp.261-269
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    • 2019
  • This study investigates a method of designing pixel-type frequency selective surfaces(FSS) with flexibility while considering factors, such as polarization and incident angle. Among the various methods used to solve the discrete space problem when designing a pixel-type FSS, the binary particle swarm optimization(BPSO) algorithm is one of the most applicable techniques to determine the periodic structure pattern of an FSS. Therefore, a method of efficiently designing FSS with roll-off band pass characteristics using an improved BPSO algorithm is proposed. To solve the convergence problem in the fitness function design to induce particles in the desired solution, FSS with desired roll-off wave characteristics can be easily obtained by applying a fitness function using "slope" as an input parameter.

Q-Learning Policy and Reward Design for Efficient Path Selection (효율적인 경로 선택을 위한 Q-Learning 정책 및 보상 설계)

  • Yong, Sung-Jung;Park, Hyo-Gyeong;You, Yeon-Hwi;Moon, Il-Young
    • Journal of Advanced Navigation Technology
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    • v.26 no.2
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    • pp.72-77
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    • 2022
  • Among the techniques of reinforcement learning, Q-Learning means learning optimal policies by learning Q functions that perform actionsin a given state and predict future efficient expectations. Q-Learning is widely used as a basic algorithm for reinforcement learning. In this paper, we studied the effectiveness of selecting and learning efficient paths by designing policies and rewards based on Q-Learning. In addition, the results of the existing algorithm and punishment compensation policy and the proposed punishment reinforcement policy were compared by applying the same number of times of learning to the 8x8 grid environment of the Frozen Lake game. Through this comparison, it was analyzed that the Q-Learning punishment reinforcement policy proposed in this paper can significantly increase the learning speed compared to the application of conventional algorithms.

UAV-MEC Offloading and Migration Decision Algorithm for Load Balancing in Vehicular Edge Computing Network (차량 엣지 컴퓨팅 네트워크에서 로드 밸런싱을 위한 UAV-MEC 오프로딩 및 마이그레이션 결정 알고리즘)

  • A Young, Shin;Yujin, Lim
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.12
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    • pp.437-444
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    • 2022
  • Recently, research on mobile edge services has been conducted to handle computationally intensive and latency-sensitive tasks occurring in wireless networks. However, MEC, which is fixed on the ground, cannot flexibly cope with situations where task processing requests increase sharply, such as commuting time. To solve this problem, a technology that provides edge services using UAVs (Unmanned Aerial Vehicles) has emerged. Unlike ground MEC servers, UAVs have limited battery capacity, so it is necessary to optimize energy efficiency through load balancing between UAV MEC servers. Therefore, in this paper, we propose a load balancing technique with consideration of the energy state of UAVs and the mobility of vehicles. The proposed technique is composed of task offloading scheme using genetic algorithm and task migration scheme using Q-learning. To evaluate the performance of the proposed technique, experiments were conducted with varying mobility speed and number of vehicles, and performance was analyzed in terms of load variance, energy consumption, communication overhead, and delay constraint satisfaction rate.

Design of Reconfigurable Processor for Information Security System (정보보호 시스템을 위한 재구성형 프로세서 설계)

  • Cha, Jeong-Woo;Kim, Il-Hyu;Kim, Chang-Hoon;Kim, Dong-Hwi
    • Proceedings of the Korea Information Processing Society Conference
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    • 2011.04a
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    • pp.113-116
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    • 2011
  • 최근 IT 기술의 급격한 발전으로 개인정보, 환경 등 다양한 정보를 수시로 수집 및 관리하면서 사용자가 원할시 즉각적인 정보서비스를 제공하고 있다. 그러나 유 무선상의 데이터 전송은 정보의 도청, 메시지의 위 변조 및 재사용, DoS(Denial of Service)등 외부의 공격으로부터 쉽게 노출된다. 이러한 외부 공격은 개인 프라이버시를 포함한 정보서비스 시스템 전반에 치명적인 손실을 야기 시킬 수 있기 때문에 정보보호 시스템의 필요성은 갈수록 그 중요성이 부각되고 있다. 현재까지 정보보호 시스템은 소프트웨어(S/W), 하드웨어(ASIC), FPGA(Field Progr- ammable Array) 디바이스를 이용하여 구현되었으며, 각각의 구현방법은 여러 가지 문제점이 있으며 그에 따른 해결방법이 제시되고 있다. 본 논문에서는 다양한 환경에서의 정보보호 서비스를 제공하기 위한 재구성형 SoC 구조를 제안한다. 제안된 SoC는 비밀키 암호알고리즘(AES), 암호학적 해쉬(SHA-256), 공개키 암호알고리즘(ECC)을 수행 할 수 있으며, 마스터 콘트롤러에 의해 제어된다. 또한 정보보호 시스템이 요구하는 다양한 제약조건(속도, 면적, 안전성, 유연성)을 만족하기 위해 S/W, ASIC, FPGA 디바이스의 모든 장점을 최대한 활용하였으며, MCU와의 효율적인 통신을 위한 I/O 인터페이스를 제안한다. 따라서 제안된 정보보호 시스템은 기존의 시스템보다 다양한 정보보호 알고리즘을 지원할 뿐만 아니라 속도 및 면적에 있어 상충 관계를 개선하였기 때문에 저비용 응용뿐만 아니라 고속 통신 장비 시스템에도 적용이 가능하다.

Design of Face with Mask Detection System in Thermal Images Using Deep Learning (딥러닝을 이용한 열영상 기반 마스크 검출 시스템 설계)

  • Yong Joong Kim;Byung Sang Choi;Ki Seop Lee;Kyung Kwon Jung
    • Convergence Security Journal
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    • v.22 no.2
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    • pp.21-26
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    • 2022
  • Wearing face masks is an effective measure to prevent COVID-19 infection. Infrared thermal image based temperature measurement and identity recognition system has been widely used in many large enterprises and universities in China, so it is totally necessary to research the face mask detection of thermal infrared imaging. Recently introduced MTCNN (Multi-task Cascaded Convolutional Networks)presents a conceptually simple, flexible, general framework for instance segmentation of objects. In this paper, we propose an algorithm for efficiently searching objects of images, while creating a segmentation of heat generation part for an instance which is a heating element in a heat sensed image acquired from a thermal infrared camera. This method called a mask MTCNN is an algorithm that extends MTCNN by adding a branch for predicting an object mask in parallel with an existing branch for recognition of a bounding box. It is easy to generalize the R-CNN to other tasks. In this paper, we proposed an infrared image detection algorithm based on R-CNN and detect heating elements which can not be distinguished by RGB images.

3D Tunnel Shape Fitting by Means of Laser Scanned Point Cloud (레이저 스캐닝 측점군에 의한 터널 3차원 형상의 재현)

  • Kwon, Kee Wook;Lee, Jong Dal
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.4D
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    • pp.555-561
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    • 2009
  • In lieu of section profile data, a fitting of the bored tunnel shape is more significant confirmation for maintenance of a tunnel. Before the permit on the completion of a tunnel, deformation of the completed tunnel with respect to the design model are considered. And deformation can be produced at continuously along the entire of the tunnel section. This study firstly includes an analysis of algebraic approach and test it with an observed field data. And then a number of methods, line search method, genetic algorithm, and pattern search methods, are compared with the 3D tunnel shape fitting. Algebraic methods can solve a simple circular cylinder type as like a railway tunnel. However, a more complex model (compound circular curve and non circular) as like a highway tunnel has to be solved with soft computing tools in the cause of conditional constraints. The genetic algorithm and pattern search methods are computationally more intensive, but they are more flexible at a complex condition. The line search method is fastest, but it needs a narrow bounds of the initial values.

Patch-based Texture Synthesis for Marker Concealment (마커 은닉을 위한 패치 기반 텍스쳐 합성)

  • Yun, Kyung-Dahm;Woo, Woon-Tack
    • Journal of the HCI Society of Korea
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    • v.2 no.2
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    • pp.11-18
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    • 2007
  • We propose a novel method to conceal fiducial markers observed in augmented scenes using patch-based texture synthesis. Despite the efficiency for simple object recognition and tracking, the markers deliver inherent obtrusiveness. They do not only reduce immersiveness, but also severely degrade usability of augmented reality. The proposed method constructs alternative images in real time to overlay markers present in the sequence of images. The global characteristics of background textures are retained and the results are more adaptive to illumination changes.

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A Study on the Parallel & Distributed Routing to support PCS Mobility in ATM/B-ISDN (ATM/B-ISDN통신망에서의 PCS Mobility 지원을 위한 병렬.분산 라우팅 기법연구)

  • Shin, Sang-Heon;Koo, Soo-Yong;Kim, Young-Tak
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10a
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    • pp.246-247
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    • 1998
  • PCS를 포함한 차세대 이동통신은 ATM/B-ISDN을 core network으로 하여 다양한 서비스를 제공하는 방향으로 발전할 것으로 예상된다. 이러한 유.무선 통합환경에서 PCS mobility를 효율적으로 제공하기 위해서 TINA와 같은 계층적 연결관리 구조와 이 구조에 적합한 라우팅 기법이 필요하다. 본 논문에서는 ATM/B-ISDNTINA통신망에서 기존의 라우팅 기법에 비해 장점을 가지면서, TINA의 계층적 연결관리 구조를 기바능로 하는 병렬.분산 라우팅 기법을 제안한다. 제안된 병렬.분산 라우팅 기법은 라우팅 알고리즘이 서브네트워트 단위로 병렬적, 계층적으로 실행되어 사용자가 원하는 QoS연결을 제한된 시간내에 빠르게 설정할 수 있으므로, PCS mobility지원을 위한 빈번한 경로 재설정 요구에 유연하게 대처 할수 있다. 또한, 연결관리 체계가 계층적으로 이루어져 있어 TMN/TNA를 통한 체계적인 통신망 관리에도 효율적이다.

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