• Title/Summary/Keyword: Hierarchical algorithm

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Implementation and Performance Analysis of FDNN Using Quantization Triangularity Fuzzy Function (양자화 삼각 퍼지 함수를 이용한 FDNN 구현 및 성능 분석)

  • 변오성;이철희;문성용
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.36C no.11
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    • pp.84-91
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    • 1999
  • In this paper, we could analyze the comparison with applied WFM to the quantization triangularity fuzzy function and triangularity Fuzzy function. In order to improve on a fault which not remove completely noise included image according to a peculiarity of noise, we got to realize FDNN of the high speed weight eliminating noise included image, minimizing the lost of information, obtaining information of suitability owing to applied Fuzzy Algorithm to DBNN of a hierarchical structure. We could analyze the comparison with a power of WFM and FDNN using simulation We could find to superiority the proposed FDNN )n a result which was the comparison of MSE for the boats image.

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3D Tunnel Modeling by Parametric Representation of Geometry (매개변수식 기하 표현법에 의한 3차원 터널 모델링)

  • 이형우;신대석
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.15 no.1
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    • pp.33-42
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    • 2002
  • A method of automatic 3D tunnel modeling is proposed. The proposed method used the parametric representation of geometry and a hierarchical and relational data structure. These two bases provide the generalization and extension for 3D tunnel modeling. Especially, these two fundamentals ion the basis iota representing the characteristics of the tunnel structure for analysis. The constant-curvature characteristic is exploited to generate 3D mesh on the tunnel surface. This is attributed to the advantage that any 2D automatic mesh generation algorithm can be applied to 3D mesh modeling.

Unequal Loss Protection Using Layer-Based Recovery Rate (ULP-LRR) for Robust Scalable Video Streaming over Wireless Networks

  • Quan, Shan Guo;Ha, Hojin;Ran, Rong
    • Journal of information and communication convergence engineering
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    • v.14 no.4
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    • pp.240-245
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    • 2016
  • Scalable video streaming over wireless networks has many challenges. The most significant challenge is related to packet loss. To overcome this problem, in this paper, we propose an unequal loss protection (ULP) method using a new forward error correction (FEC) mechanism for robust scalable video streaming over wireless networks. For an efficient FEC assignment considering video quality, we first introduce a simple and efficient performance metric, the layer-based recovery rate (LRR), for quantifying the unequal error propagation effects of the temporal and quality layers on the basis of packet losses. LRR is based on the unequal importance in both the temporal and the quality layers of a hierarchical scalable video coding structure. Then, the proposed ULP-LRR method assigns an appropriate number of FEC packets on the basis of the LRR to protect the video layers against packet lossy network environments. Compared with conventional ULP algorithms, the proposed ULP-LRR algorithm demonstrates a higher performance for various error-prone wireless channel statuses.

Windowed Wavelet Stereo Matching Using Shift ability (이동성(shift ability)을 이용한 윈도우 웨이블릿 스테레오 정합)

  • 신재민;이호근;하영호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.1C
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    • pp.56-63
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    • 2003
  • In this paper, a wavelet-based stereo matching algorithm to obtain an accurate disparity map in wavelet transformed domain by using a shift ability property, a modified wavelet transform, the similarities for their sub-bands, and a hierarchical structure is proposed. New approaches for stereo matching by lots of feature information are to utilize translation-variant results of the sub-bands in the wavelet transformed domain because they cannot literally expect translation invariance in a system based on convolution and sub-sampling. After the similarity matching for each sub-band, we can easily find optimal matched-points because the sub-bands appearance of the shifted signals is definitely different from that of the original signal with no shift.

A QoS-based Multicast Protocol in Hierarchical Encoding Environment (계층화된 인코딩 환경에서 서비스 품질 보장을 지원하는 멀티캐스트 프로토콜)

  • Im, Yu-Jin;Choe, Jong-Won
    • Journal of KIISE:Computer Systems and Theory
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    • v.26 no.9
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    • pp.1112-1125
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    • 1999
  • 최근 들어 멀티미디어를 지원하는 응용들의 서비스 품질 보장과 멀티캐스트 지원에 대한 요구가 증가되고 있으나 기존의 멀티캐스트 프로토콜로는 이러한 요구를 수용할 수 없는 문제가 발생하고 있다. 현재 인터넷에서 사용되고 있는 라우팅 메커니즘은 네트워크 자원 정보나 세션의 QoS 요구사항을 고려하지 않고 단순히 종단간의 연결에만 초점을 맞추고 있기 때문이다. 따라서 본 논문에서는 멀티캐스트 환경에서 서비스 품질보장을 지원하기 위한 새로운 프로토콜, LayeredQoS을 제안한다. 다중의 CP (Central Point)를 채택하고 각각의 CP에 적절한 QoS 레벨을 부여하여 사용함으로써 대역폭의 공유정도를 높일 뿐만 아니라 전체 트리 비용을 감소시켜 궁극적으로 네트워크 처리량이 증가되도록 하였다. 또한 시뮬레이션 방법을 통하여 다른 프로토콜보다 나은 성능을 가지는 것으로 평가하였다.Abstract Many emerging multimedia applications often require a guaranteed quality of service and multicast connection. But the traditional multicast protocol can't meet the needs since the routing mechanisms deployed in today's Internet are focused on connectivity, not on resource availability in the network or QoS requirements of flows. In this paper, we present LayeredQoS, a new QoS-based multicast routing algorithm. We adopt the multiple CPs(Central Points) and allocate QoS-levels for each CP in order to improve the degree of resource sharing and decrease the total tree cost, and then network throughput is increased. The proposed protocol is verified by simulations and it is shown that the performance of LayeredQoS is much better than the existing protocols.

Statistical Approach to Noisy Band Removal for Enhancement of HIRIS Image Classification

  • Huan, Nguyen Van;Kim, Hak-Il
    • Proceedings of the KSRS Conference
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    • 2008.03a
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    • pp.195-200
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    • 2008
  • The accuracy of classifying pixels in HIRIS images is usually degraded by noisy bands since noisy bands may deform the typical shape of spectral reflectance. Proposed in this paper is a statistical method for noisy band removal which mainly makes use of the correlation coefficients between bands. Considering each band as a random variable, the correlation coefficient measures the strength and direction of a linear relationship between two random variables. While the correlation between two signal bands is high, existence of a noisy band will produce a low correlation due to ill-correlativeness and undirectedness. The application of the correlation coefficient as a measure for detecting noisy bands is under a two-pass screening scheme. This method is independent of the prior knowledge of the sensor or the cause resulted in the noise. The classification in this experiment uses the unsupervised k-nearest neighbor algorithm in accordance with the well-accepted Euclidean distance measure and the spectral angle mapper measure. This paper also proposes a hierarchical combination of these measures for spectral matching. Finally, a separability assessment based on the between-class and within-class scatter matrices is followed to evaluate the performance.

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Empirical Comparison of Word Similarity Measures Based on Co-Occurrence, Context, and a Vector Space Model

  • Kadowaki, Natsuki;Kishida, Kazuaki
    • Journal of Information Science Theory and Practice
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    • v.8 no.2
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    • pp.6-17
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    • 2020
  • Word similarity is often measured to enhance system performance in the information retrieval field and other related areas. This paper reports on an experimental comparison of values for word similarity measures that were computed based on 50 intentionally selected words from a Reuters corpus. There were three targets, including (1) co-occurrence-based similarity measures (for which a co-occurrence frequency is counted as the number of documents or sentences), (2) context-based distributional similarity measures obtained from a latent Dirichlet allocation (LDA), nonnegative matrix factorization (NMF), and Word2Vec algorithm, and (3) similarity measures computed from the tf-idf weights of each word according to a vector space model (VSM). Here, a Pearson correlation coefficient for a pair of VSM-based similarity measures and co-occurrence-based similarity measures according to the number of documents was highest. Group-average agglomerative hierarchical clustering was also applied to similarity matrices computed by individual measures. An evaluation of the cluster sets according to an answer set revealed that VSM- and LDA-based similarity measures performed best.

Motion Planning for Legged Robots Using Locomotion Primitives in the 3D Workspace (3차원 작업공간에서 보행 프리미티브를 이용한 다리형 로봇의 운동 계획)

  • Kim, Yong-Tae;Kim, Han-Jung
    • The Journal of Korea Robotics Society
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    • v.2 no.3
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    • pp.275-281
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    • 2007
  • This paper presents a motion planning strategy for legged robots using locomotion primitives in the complex 3D environments. First, we define configuration, motion primitives and locomotion primitives for legged robots. A hierarchical motion planning method based on a combination of 2.5 dimensional maps of the 3D workspace is proposed. A global navigation map is obtained using 2.5 dimensional maps such as an obstacle height map, a passage map, and a gradient map of obstacles to distinguish obstacles. A high-level path planner finds a global path from a 2D navigation map. A mid-level planner creates sub-goals that help the legged robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. A local obstacle map that describes the edge or border of the obstacles is used to find the sub-goals along the global path. A low-level planner searches for a feasible sequence of locomotion primitives between sub-goals. We use heuristic algorithm in local motion planner. The proposed planning method is verified by both locomotion and soccer experiments on a small biped robot in a cluttered environment. Experiment results show an improvement in motion stability.

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Progress Report : Quantifying and Classifying Peculiarity of Cluster Galaxies

  • Oh, Seulhee;Yi, Sukyoung K.;Sheen, Yun-Kyeong;Kyeong, Jaemann;Sung, Eon-Chang;Ho, Luis C.;Kim, Minjin;Park, Byeong-Gon
    • The Bulletin of The Korean Astronomical Society
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    • v.38 no.1
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    • pp.42.1-42.1
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    • 2013
  • In the LCDM paradigm, hierarchical merging is thought to play a key role in the formation and evolution of massive galaxies. Theoretical and observational studies suggest that massive galaxies started forming at high redshifts and were assembled via numerous mergers. Galaxy clusters are the sites where the most massive galaxies are found and the most dramatic merger histories are embedded. The previous work of Sheen et al. (2012) identified via visual inspection many massive galaxies with merger features in clusters, which surprised the community. In this study we aim to quantify peculiarity of galaxies to pin down the merger frequency in cluster environments more objectively. We have performed optical deep imaging of 4 Abell clusters by using IMACS f/2 on a Magellan Badde 6.5-m telescope. For the galaxies in our data, we applied GALFIT algorithm, which fits analytic models to galaxy data, and we analyzed their residuals. We present the preliminary results of our sample galaxies.

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Automatic Detection of Texture-defects using Texture-periodicity and Jensen-Shannon Divergence

  • Asha, V.;Bhajantri, N.U.;Nagabhushan, P.
    • Journal of Information Processing Systems
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    • v.8 no.2
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    • pp.359-374
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    • 2012
  • In this paper, we propose a new machine vision algorithm for automatic defect detection on patterned textures with the help of texture-periodicity and the Jensen-Shannon Divergence, which is a symmetrized and smoothed version of the Kullback-Leibler Divergence. Input defective images are split into several blocks of the same size as the size of the periodic unit of the image. Based on histograms of the periodic blocks, Jensen-Shannon Divergence measures are calculated for each periodic block with respect to itself and all other periodic blocks and a dissimilarity matrix is obtained. This dissimilarity matrix is utilized to get a matrix of true-metrics, which is later subjected to Ward's hierarchical clustering to automatically identify defective and defect-free blocks. Results from experiments on real fabric images belonging to 3 major wallpaper groups, namely, pmm, p2, and p4m with defects, show that the proposed method is robust in finding fabric defects with a very high success rates without any human intervention.