• Title/Summary/Keyword: adaptive algorithm

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Performance Analysis of Underwater Acoustic Communication Systems Using Underwater Channel Simulation Tool (수중채널 시뮬레이터를 활용한 수중음향통신 시스템 성능 분석)

  • Oh, Se-Hyun;Kim, Hyeon-Su;Kim, J.S.;Cho, Jung-Hong;Chung, Jae-Hak;Song, H.C.
    • The Journal of the Acoustical Society of Korea
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    • v.31 no.6
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    • pp.373-383
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    • 2012
  • The performance of underwater acoustic communication system is sensitive to the Doppler shift and ISI(Inter-Symbol Interference). Therefore, the simulation algorithm needs to consider time-spread due to multipath arrivals which cause the ISI, and time-varying Doppler shift along with moving source and receiver. For this purpose, VirTEX(Virtual Time series EXperiment) based on Ray model has been developed. In this paper, VirTEX is used to compare the characteristics of ocean waveguide from the experimental data and illustrate the performance. The CIR(Channel Impulse Response) that characterizes the multipath arrivals with representative time-spread due to multipath arrivals is compared between numerically simulated and experimental probe signal. Also, the communication performance analysis for BER(Bit Error Rate) is compared between numerically simulated and experimental data signal. As a result, VirTEX can be useful as a simulation tool for evaluating the performance of underwater acoustic communication system.

Additive hazards models for interval-censored semi-competing risks data with missing intermediate events (결측되었거나 구간중도절단된 중간사건을 가진 준경쟁적위험 자료에 대한 가산위험모형)

  • Kim, Jayoun;Kim, Jinheum
    • The Korean Journal of Applied Statistics
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    • v.30 no.4
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    • pp.539-553
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    • 2017
  • We propose a multi-state model to analyze semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the three states of the illness-death model: healthy, disease, and dead. The 'diseased' state can be considered as the intermediate event. Two more states are added into the illness-death model to incorporate the missing events, which are caused by a loss of follow-up before the end of a study. One of them is a state of the lost-to-follow-up (LTF), and the other is an unobservable state that represents an intermediate event experienced after the occurrence of LTF. Given covariates, we employ the Lin and Ying additive hazards model with log-normal frailty and construct a conditional likelihood to estimate transition intensities between states in the multi-state model. A marginalization of the full likelihood is completed using adaptive importance sampling, and the optimal solution of the regression parameters is achieved through an iterative quasi-Newton algorithm. Simulation studies are performed to investigate the finite-sample performance of the proposed estimation method in terms of empirical coverage probability of true regression parameters. Our proposed method is also illustrated with a dataset adapted from Helmer et al. (2001).

An Object-Based Image Retrieval Techniques using the Interplay between Cortex and Hippocampus (해마와 피질의 상호 관계를 이용한 객체 기반 영상 검색 기법)

  • Hong Jong-Sun;Kang Dae-Seong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.4 s.304
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    • pp.95-102
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    • 2005
  • In this paper, we propose a user friendly object-based image retrieval system using the interaction between cortex and hippocampus. Most existing ways of queries in content-based image retrieval rely on query by example or query by sketch. But these methods of queries are not adequate to needs of people's various queries because they are not easy for people to use and restrict. We propose a method of automatic color object extraction using CSB tree map(Color and Spatial based Binary をn map). Extracted objects were transformed to bit stream representing information such as color, size and location by region labelling algorithm and they are learned by the hippocampal neural network using the interplay between cortex and hippocampus. The cells of exciting at peculiar features in brain generate the special sign when people recognize some patterns. The existing neural networks treat each attribute of features evenly. Proposed hippocampal neural network makes an adaptive fast content-based image retrieval system using excitatory learning method that forwards important features to long-term memories and inhibitory teaming method that forwards unimportant features to short-term memories controlled by impression.

Robust Orientation Estimation Algorithm of Fingerprint Images (노이즈에 강인한 지문 융선의 방향 추출 알고리즘)

  • Lee, Sang-Hoon;Lee, Chul-Han;Choi, Kyoung-Taek;Kim, Jai-Hie
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.1
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    • pp.55-63
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    • 2008
  • Ridge orientations of fingerprint image are crucial informations in many parts of fingerprint recognition such as enhancement, matching and classification. Therefore it is essential to extract the ridge orientations of image accurately because it directly affects the performance of the system. The two main properties of ridge orientation are 1) global characteristic(gradual change in whole part of fingerprint) and 2) local characteristic(abrupt change around core and delta points). When we only consider the local characteristic, estimated ridge orientations are well around singular points but not robust to noise. When the global characteristic is only considered, to estimate ridge orientation is robust to noise but cannot represent the orientation around singular points. In this paper, we propose a novel method for estimating ridge orientation which represents local characteristic specifically as well as be robust to noise. We reduce the noise caused by scar using iterative outlier rejection. We apply adaptive measurement resolution in each fingerprint area to estimate the ridge orientation around singular points accurately. We evaluate the performance of proposed method using synthetic fingerprint and FVC 2002 DB. We compare the accuracy of ridge orientation. The performance of fingerprint authentication system is evaluated using FVC 2002 DB.

A Frame Unit Based Adaptive Pruning Algorithm for the East Speech Recognition (음성인식의 고속화를 위한 프레임 단위 적응 프루닝 알고리즘)

  • Hwang Cheol-Jun;Oh Se-Jin;Kim Bum-Koog;Jung Ho-Youl;Chung Hyun-Yeol
    • Proceedings of the Acoustical Society of Korea Conference
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    • autumn
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    • pp.183-186
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    • 2000
  • 본 논문에서는 인식이 진행되는 동안 탐색 공간을 효과적으로 줄임으로써 음성인식의 고속화를 달성할 수 있는 새로운 프레임 단위 적응 프루닝 알고리즘을 제안하고 실험을 통하여 그 유효성을 확인하였다. 이것은 앞 프레임과 뒤 프레임 사이의 최대확률은 높은 상관성을 가지므로 프루닝 문턱치를 앞 프레임의 최대 확률로부터 효과적으로 구할 수 있다는 사실에 근거를 두고있다. 이 방법에서는 앞 프레임의 최대 우도 확률과 후보 확률들의 조합으로 현재 프레임의 프루닝 문턱치를 갱신함으로써 현재 프레임의 문턱치를 인식 과정 중에 얻을 수 있기 때문에, 인식 태스크가 바뀌어도 문턱치를 구하기 위한 사전 실험을 수행할 필요가 없게 된다. 또한, 프레임 단위로 적응적으로 얻어진 문턱치는 다른 환경 하에서도 인식 속도의 향상을 가져올 수 있게 된다. 제안된 알고리즘의 유효성을 확인하여 위하여 한국어 주소 인식 시스템에 적용하였다. 본 시스템은 48개의 유사음소단위(PLUs)를 인식의 기본단위로 하고, 적응알고리즘으로는 최대사후확률추정법((MAP: Maximum A Posteriori Probability Estimation)을, 인식 알고리즘으로는 OPDP(One Pass Dynamic Programming)법을 이용하였다 남성화자 3인이 25개의 연결 주소명을 대상으로 인식 실험을 수행한 결과, 제안된 프레임단위 적응프루닝 문턱치를 적용한 경우를 기존의 고정 프루닝 문턱치와 가변 프루닝 문턱치를 적용한 경우와 비교하였을 때 인식률의 변화 없이 탐색공간이 상대적으로 각각 $14.4\%$9.14\%가 감소되어 제안된 프레임 단위 적응 프루닝 알고리즘의 유효성을 확인할 수 있었다. 시,공간적 분포 특성이 구체적으로 규명되면 보다 정확한 음장변화 추정이 이뤄져야 할 것으로 보인다. 또한 내부파와 음파의 상대적인 진행 방향에 따라 음장변화가 크게 다를 것이 예상되므로 이를 규명하기 위해서는 궁극적으로 3차원적인 음장분포 연구가 필요하다. 음향센서를 해저면에 매설할 경우 수충의 수온변화와 센서 주변의 수온변화 사이에는 어느 정도의 시간지연이 존재하게 되므로 이에 대한 영향을 규명하는 것도 센서의 성능예측을 위해서 필요하리라 사료된다.가지는 심부 가스의 개발 성공률을 증가시키기 위하여 심부 가스가 존재하는 지역의 지질학적 부존 환경 및 조성상의 특성과 생산시 소요되는 생산비용을 심도에 따라 분석하고 생산에 수반되는 기술적 문제점들을 정리하였으며 마지막으로 향후 요구되는 연구 분야들을 제시하였다. 또한 참고로 현재 심부 가스의 경우 미국이 연구 개발 측면에서 가장 활발한 활동을 전개하고 있으며 그 결과 다수의 신뢰성 있는 자료들을 확보하고 있으므로 본 논문은 USGS와 Gas Research Institute(GRI)에서 제시한 자료에 근거하였다.ऀĀ耀Ā삱?⨀؀Ā Ā?⨀ጀĀ耀Ā?돀ꢘ?⨀硩?⨀ႎ?⨀?⨀넆돐쁖잖⨀쁖잖⨀/ࠐ?⨀焆덐瀆倆Āⶇ퍟ⶇ퍟ĀĀĀĀ磀鲕좗?⨀肤?⨀⁅Ⴅ?⨀쀃잖⨀䣙熸ጁ↏?⨀

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An Analysis on BitTorrent Performance Based on the Number of Unchoked Peers (Unchoked Peer 개수에 따른 BitTorrent 성능 분석)

  • Chung, Tae-Joong;Han, Jin-Young;Kim, Hyun-Chul;Kwon, Tae-Kyoung;Choi, Yang-Hee
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.8B
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    • pp.1197-1203
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    • 2010
  • A strength of BitTorrent, which is widely used for file sharing today, is due to its peer selection mechanism which is designed to encourage peers to contribute data. In the peer selection phase in BitTorrent, peers to upload the file in a swarm are selected by determining which peers upload the most to themselves. However, the number of peers to upload (i.e., number of unchoked peers) is fixed to four in its peer selection mechanism of BitTorrent, which yields inefficiency because the situation of the swarm may vary frequently (e.g., number of peers in the swarm, download rates, and upload rates). In this paper, we analyze the swarming system performance when the number of unchoked in BitTorrents is not static, but dynamic. For empirical investigation, we established a testbed in Seoul National University by modifying an open-source BitTorrent client, which is popular. Through our experiments, we show that an adaptive mechanism to adjust the number of unchoked peers considering the situation of the swarm is needed to improve the performance of BitTorrent.

A Cell Loss Constraint Method of Bandwidth Renegotiation for Prioritized MPEG Video Data Transmission in ATM Networks (ATM망에서 우선 순위가 주어진 MPEG 비디오 데이터 전송시 대역폭 재협상을 통한 셀 손실 방지 기법)

  • Yun, Byoung-An;Kim, Eun-Hwan;Jun, Moon-Seog
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.7
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    • pp.1770-1780
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    • 1997
  • Our problem is improvement of image quality because it is inevitable cell loss of image data when traffic congestion occurs. If cells are discarded indiscriminately in transmission of MPEG video data, it occurs severe degradation in quality of service(QOS). In this paper, to solve this problem, we propose two method. The first, we analyze the traffic characteristics of an MPEG encoder and generate high priority and low priority data stream. During network congestion, only the least low priority cells are dropped, and this ensures that the high priority cells are successfully transmitted, which, in turn, guarantees satisfactory QoS. In this case, the prioritization scheme for the encoder assigns components of the data stream to each priority level based on the value of a parameter ${\beta}$. The second, Number of high priority cells are increased when value of ${\beta}$ is large. It occurs the loss of high priority cell in the congestion. To prevent it, this paper is regulated to data stream rate as buffer occupancy with UPC controller. Therefore, encoder's bandwidth can be calculated renegotiation of the encoder and networks. In this paper, the encoder's bandwidth requirements are characterized by a usage parameter control (UPC) set consisting of peak rate, burstness, and sustained rate. An adaptive encoder rate control algorithm at the Networks Interface Card(NIC) computes the necessary UPC parameter to maintain the user specified quality of service. Simulation results are given for a rate-controlled VBR video encoder operating through an ATM network interface which supports dynamic UPC. These results show that dynamic bandwidth renegotiation of prioritized data stream could provided bandwidth saving and significant quality gains which guarantee high priority data stream.

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Neighbor Caching for P2P Applications in MUlti-hop Wireless Ad Hoc Networks (멀티 홉 무선 애드혹 네트워크에서 P2P 응용을 위한 이웃 캐싱)

  • 조준호;오승택;김재명;이형호;이준원
    • Journal of KIISE:Information Networking
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    • v.30 no.5
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    • pp.631-640
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    • 2003
  • Because of multi-hop wireless communication, P2P applications in ad hoc networks suffer poor performance. We Propose neighbor caching strategy to overcome this shortcoming and show it is more efficient than self caching that nodes store data in theirs own cache individually. A node can extend its caching storage instantaneously with neighbor caching by borrowing the storage from idle neighbors, so overcome multi-hop wireless communications with data source long distance away from itself. We also present the ranking based prediction that selects the most appropriate neighbor which data can be stored in. The node that uses the ranking based prediction can select the neighbor that has high possibility to keep data for a long time and avoid caching the low ranked data. Therefore the ranking based prediction improves the throughput of neighbor caching. In the simulation results, we observe that neighbor caching has better performance, as large as network size, as long as idle time, and as small as cache size. We also show the ranking based prediction is an adaptive algorithm that adjusts times of data movement into the neighbor, so makes neighbor caching flexible according to the idleness of nodes

A Research of LEACH Protocol improved Mobility and Connectivity on WSN using Feature of AOMDV and Vibration Sensor (AOMDV의 특성과 진동 센서를 적용한 이동성과 연결성이 개선된 WSN용 LEACH 프로토콜 연구)

  • Lee, Yang-Min;Won, Joon-We;Cha, Mi-Yang;Lee, Jae-Kee
    • The KIPS Transactions:PartC
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    • v.18C no.3
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    • pp.167-178
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    • 2011
  • As the growth of ubiquitous services, various types of ad hoc networks have emerged. In particular, wireless sensor networks (WSN) and mobile ad hoc networks (MANET) are widely known ad hoc networks, but there are also other kinds of wireless ad hoc networks in which the characteristics of the aforementioned two network types are mixed together. This paper proposes a variant of the Low Energy Adaptive Cluster Hierarchy (LEACH) routing protocol modified to be suitable in such a combined network environment. That is, the proposed routing protocol provides node detection and route discovery/maintenance in a network with a large number of mobile sensor nodes, while preserving node mobility, network connectivity, and energy efficiency. The proposed routing protocol is implemented with a multi-hop multi-path algorithm, a topology reconfiguration technique using node movement estimation and vibration sensors, and an efficient path selection and data transmission technique for a great many moving nodes. In the experiments, the performance of the proposed protocol is demonstrated by comparing it to the conventional LEACH protocol.

Design and Implementation of CW Radar-based Human Activity Recognition System (CW 레이다 기반 사람 행동 인식 시스템 설계 및 구현)

  • Nam, Jeonghee;Kang, Chaeyoung;Kook, Jeongyeon;Jung, Yunho
    • Journal of Advanced Navigation Technology
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    • v.25 no.5
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    • pp.426-432
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    • 2021
  • Continuous wave (CW) Doppler radar has the advantage of being able to solve the privacy problem unlike camera and obtains signals in a non-contact manner. Therefore, this paper proposes a human activity recognition (HAR) system using CW Doppler radar, and presents the hardware design and implementation results for acceleration. CW Doppler radar measures signals for continuous operation of human. In order to obtain a single motion spectrogram from continuous signals, an algorithm for counting the number of movements is proposed. In addition, in order to minimize the computational complexity and memory usage, binarized neural network (BNN) was used to classify human motions, and the accuracy of 94% was shown. To accelerate the complex operations of BNN, the FPGA-based BNN accelerator was designed and implemented. The proposed HAR system was implemented using 7,673 logics, 12,105 registers, 10,211 combinational ALUTs, and 18.7 Kb of block memory. As a result of performance evaluation, the operation speed was improved by 99.97% compared to the software implementation.