• Title/Summary/Keyword: Processing Parameter

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Analysis for Data Traffic Characteristics in Internet (인터넷에서의 데이터 트래픽 특성분석)

  • Lim, Seog-Ku;Lee, Jong-Kyu
    • Proceedings of the Korea Information Processing Society Conference
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    • 2003.05b
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    • pp.1401-1404
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    • 2003
  • 현재 제공되는 인터넷 서비스들의 동작 특성은 기존에 고려되던 트래픽 특성과는 완전히 다른 자기 유사성(Self·similarity)이라는 성질을 가진다는 것이 증명되었다. 자기 유사성은 장기간 의존성으로 표현되는데, 이것은 단기간 의존성 성질을 갖는 기존의 모델인 포아송(Poisson) 모델과는 상반되는 개념이다. 따라서 차세대 통신망의 설계 및 디멘져닝을 위해서는 무엇보다도 데이터 트래픽의 주요 특성인 버스트성(Burstiness)과 자기유사성이 반영된 트래픽 모델이 요구된다. 여기서 자기유사성은 허스트 파라미터(Hurst Parameter)로 특성화 될 수 있다. 이러한 관점에서 본 논문에서는 데이터 트래픽 특성이 서로 다른 다수의 데이터 트래픽의 통합되어 통신망에 입력되는 경우 주요 파라미터인 Hurst Parameter의 변화를 다양한 환경 하에서 분석하였고 이를 시뮬레이션 결과와도 비교하였다.

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Parameter Estimation of Linear-FM with Modified sMLE for Radar Signal Active Cancelation Application

  • Choi, Seungkyu;Lee, Chungyong
    • IEIE Transactions on Smart Processing and Computing
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    • v.3 no.6
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    • pp.372-381
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    • 2014
  • This study examined a radar signal active cancelation technique, which is a theoretical way of achieving stealth by employing a baseband process that involves sampling the incoming hostile radar signal, analyzing its characteristics, and generating countermeasure signals to cancel out the linear-FM signal of the hostile radar signal reflected from the airborne target. To successfully perform an active cancelation, the effects of errors in the countermeasure signal were first analyzed. To generate the countermeasure signal that requires very fast and accurate processing, the down-sampling technique with the suboptimal maximum likelihood estimation (sMLE) scheme was proposed to improve the speed of the estimation process while preserving the estimation accuracy. The simulation results showed that the proposed down-sampling technique using a 2048 FFT size yields substantial power reduction despite its small FFT size and exhibits similar performance to the sMLE scheme using the 32768 FFT size.

Power-aware Ad hoc On-Demand Distance Vector Routing for prolonging network lifetime of MANETs

  • Hoang, Xuan-Tung;Ahn, So-Yeon;Lee, Young-Hee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2002.11b
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    • pp.1317-1320
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    • 2002
  • We present in this paper a new version of AODV that incorporates with "Minimizing Maximum node cost" by formulating that metric as a cost function of residual energy of nodes. An additional parameter is added to the cost function to consider the routing performance along with power-efficiency. The motivation of adding that new parameter is originated from the trace off between power-saving behaviors and routing performance.

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A Study on Parameter Tuning for Redis via Parameter Classification and Phased Bayesian Optimization (Redis 파라미터 분류 및 단계적 베이지안 최적화를 통한 파라미터 튜닝 연구)

  • Jo, Seong-Woon;Park, Sang-Hyun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.476-479
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    • 2021
  • DBMS 파라미터 튜닝이란 데이터베이스에서 제공하는 다양한 파라미터의 값을 조율하여, 최적의 성능을 도출하는 과정이다. 데이터베이스 종류에 따라 파라미터 개수가 수십 개에서 수백 개로 다양하며, 각 기능이 모두 다르기 때문에 최적의 조합을 찾는 것은 쉽지 않다. 선행 연구에서는 BO 기법을 사용하여 적절한 파라미터 값을 추출했지만, 파라미터 개수에 비례하여 차원이 커지는 문제가 발생한다. 본 논문에서는 통계적으로 파라미터를 분류하여 탐색 공간을 줄인 다음 단계적으로 BO 를 수행하는 PBO 방식을 제안한다. 파라미터 값을 랜덤하게 할당하여 벤치마킹한 결과값을 군집화한 후, 각 군집별로 파라미터와의 연관성을 분석해 높은 상관관계를 가진 파라미터를 매칭시켜 분류한다. 제안하는 방법론을 검증하기 위하여 8 가지 회귀 모델과의 비교 실험을 통해 제안한 방법론의 우수성을 검증하였다.

Data-Driven Batch Processing for Parameter Calibration of a Sensor System (센서 시스템의 매개변수 교정을 위한 데이터 기반 일괄 처리 방법)

  • Kyuman Lee
    • Journal of Sensor Science and Technology
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    • v.32 no.6
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    • pp.475-480
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    • 2023
  • When modeling a sensor system mathematically, we assume that the sensor noise is Gaussian and white to simplify the model. If this assumption fails, the performance of the sensor model-based controller or estimator degrades due to incorrect modeling. In practice, non-Gaussian or non-white noise sources often arise in many digital sensor systems. Additionally, the noise parameters of the sensor model are not known in advance without additional noise statistical information. Moreover, disturbances or high nonlinearities often cause unknown sensor modeling errors. To estimate the uncertain noise and model parameters of a sensor system, this paper proposes an iterative batch calibration method using data-driven machine learning. Our simulation results validate the calibration performance of the proposed approach.

Multi-Level Fusion Processing Algorithm for Complex Radar Signals Based on Evidence Theory

  • Tian, Runlan;Zhao, Rupeng;Wang, Xiaofeng
    • Journal of Information Processing Systems
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    • v.15 no.5
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    • pp.1243-1257
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    • 2019
  • As current algorithms unable to perform effective fusion processing of unknown complex radar signals lacking database, and the result is unstable, this paper presents a multi-level fusion processing algorithm for complex radar signals based on evidence theory as a solution to this problem. Specifically, the real-time database is initially established, accompanied by similarity model based on parameter type, and then similarity matrix is calculated. D-S evidence theory is subsequently applied to exercise fusion processing on the similarity of parameters concerning each signal and the trust value concerning target framework of each signal in order. The signals are ultimately combined and perfected. The results of simulation experiment reveal that the proposed algorithm can exert favorable effect on the fusion of unknown complex radar signals, with higher efficiency and less time, maintaining stable processing even of considerable samples.

The MLMEX Design and Implemention for Vehicle Communication Technology (차량 통신 기술을 위한 MLMEX 설계 및 구현)

  • Lee, Dae Sik;Lee, Yong Kwon
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.9 no.1
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    • pp.103-110
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    • 2013
  • WAVE system is a vehicle communication technology. The system provides the services to prevent vehicle accidents that might occur during driving. Also, it is used to provide various services such as monitoring vehicle management and system failure. In this paper, we divide module that manages WAVE MAC state into a WSMP base MLME module and IP base module and we design and implement a parameter environment between WME module to manage the state of the WAVE system and MLMEX module to mange IP base of WAVE MAC therefore the date to be processed.Also, in order to verify the validity, we have carried out experiments to compare the speed of data processing by dividing data of 5Mbyte, 10Mbyte, 20Mbyte into the packets of 2KByte and 4KByte. Therefore, in WAVE system, the Parameter environments and data processing speed between WME and MLMEX module can be utilized in the various service of vehicle communication technology depending on the speed of data processing.

결함검출을 위한 실험적 연구

  • 목종수
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1996.03a
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    • pp.24-29
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    • 1996
  • The seniconductor, which is precision product, requires many inspection processes. The surface conditions of the semiconductor chip effect on the functions of the semiconductors. The defects of the chip surface is crack or void. Because general inspection method requires many inspection processes, the inspection system which searches immediately and preciselythe defects of the semiconductor chip surface. We propose the inspection method by using the computer vision system. This study presents an image processing algorithm for inspecting the surface defects(crack, void)of the semiconductor test samples. The proposed image processing algorithm aims to reduce inspection time, and to analyze those experienced operator. This paper regards the chip surface as random texture, and deals with the image modeling of randon texture image for searching the surface defects. For texture modeling, we consider the relation of a pixel and neighborhood pixels as noncasul model and extract the statistical characteristics from the radom texture field by using the 2D AR model(Aut oregressive). This paper regards on image as the output of linear system, and considers the fidelity or intelligibility criteria for measuring the quality of an image or the performance of the processing techinque. This study utilizes the variance of prediction error which is computed by substituting the gary level of pixel of another texture field into the two dimensional AR(autoregressive model)model fitted to the texture field, estimate the parameter us-ing the PAA(parameter adaptation algorithm) and design the defect detection filter. Later, we next try to study the defect detection search algorithm.

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A Modified Gaussian Model-based Low Complexity Pre-processing Algorithm for H.264 Video Coding Standard (H.264 동영상 표준 부호화 방식을 위한 변형된 가우시안 모델 기반의 저 계산량 전처리 필터)

  • Song, Won-Seon;Hong, Min-Cheol
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.2C
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    • pp.41-48
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    • 2005
  • In this paper, we present a low complexity modified Gaussian model based pre-processing filter to improve the performance of H.264 compressed video. Video sequence captured by general imaging system represents the degraded version due to the additive noise which decreases coding efficiency and results in unpleasant coding artifacts due to higher frequency components. By incorporating local statistics and quantization parameter into filtering process, the spurious noise is significantly attenuated and coding efficiency is improved for given quantization step size. In addition, in order to reduce the complexity of the pre-processing filter, the simplified local statistics and quantization parameter are introduced. The simulation results show the capability of the proposed algorithm.