• 제목/요약/키워드: High accurate prediction

검색결과 505건 처리시간 0.03초

Surface Mass Imaging Technique for Nano-Surface Analysis

  • Lee, Tae Geol
    • 한국진공학회:학술대회논문집
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    • 한국진공학회 2013년도 제44회 동계 정기학술대회 초록집
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    • pp.113-114
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    • 2013
  • Time-of-flight secondary ion mass spectrometry (TOF-SIMS) imaging is a powerful technique for producing chemical images of small biomolecules (ex. metabolites, lipids, peptides) "as received" because of its high molecular specificity, high surface sensitivity, and submicron spatial resolution. In addition, matrix-assisted laser desorption and ionization time-of-flight (MALDI-TOF) imaging is an essential technique for producing chemical images of large biomolecules (ex. genes and proteins). For this talk, we will show that label-free mass imaging technique can be a platform technology for biomedical studies such as early detection/diagnostics, accurate histologic diagnosis, prediction of clinical outcome, stem cell therapy, biosensors, nanomedicine and drug screening [1-7].

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Optimization of SWAN Wave Model to Improve the Accuracy of Winter Storm Wave Prediction in the East Sea

  • Son, Bongkyo;Do, Kideok
    • 한국해양공학회지
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    • 제35권4호
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    • pp.273-286
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    • 2021
  • In recent years, as human casualties and property damage caused by hazardous waves have increased in the East Sea, precise wave prediction skills have become necessary. In this study, the Simulating WAves Nearshore (SWAN) third-generation numerical wave model was calibrated and optimized to enhance the accuracy of winter storm wave prediction in the East Sea. We used Source Term 6 (ST6) and physical observations from a large-scale experiment conducted in Australia and compared its results to Komen's formula, a default in SWAN. As input wind data, we used Korean Meteorological Agency's (KMA's) operational meteorological model called Regional Data Assimilation and Prediction System (RDAPS), the European Centre for Medium Range Weather Forecasts' newest 5th generation re-analysis data (ERA5), and Japanese Meteorological Agency's (JMA's) meso-scale forecasting data. We analyzed the accuracy of each model's results by comparing them to observation data. For quantitative analysis and assessment, the observed wave data for 6 locations from KMA and Korea Hydrographic and Oceanographic Agency (KHOA) were used, and statistical analysis was conducted to assess model accuracy. As a result, ST6 models had a smaller root mean square error and higher correlation coefficient than the default model in significant wave height prediction. However, for peak wave period simulation, the results were incoherent among each model and location. In simulations with different wind data, the simulation using ERA5 for input wind datashowed the most accurate results overall but underestimated the wave height in predicting high wave events compared to the simulation using RDAPS and JMA meso-scale model. In addition, it showed that the spatial resolution of wind plays a more significant role in predicting high wave events. Nevertheless, the numerical model optimized in this study highlighted some limitations in predicting high waves that rise rapidly in time caused by meteorological events. This suggests that further research is necessary to enhance the accuracy of wave prediction in various climate conditions, such as extreme weather.

Whole Frame Error Concealment with an Adaptive PU-based Motion Vector Extrapolation for HEVC

  • Kim, Seounghwi;Lee, Dongkyu;Oh, Seoung-Jun
    • IEIE Transactions on Smart Processing and Computing
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    • 제4권1호
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    • pp.16-21
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    • 2015
  • Most video services are transmitted in wireless networks. In a network environment, a packet of video is likely to be lost during transmission. For this reason, numerous error concealment (EC) algorithms have been proposed to combat channel errors. On the other hand, most existing algorithms cannot conceal the whole missing frame effectively. To resolve this problem, this paper proposes a new Adaptive Prediction Unit-based Motion Vector Extrapolation (APMVE) algorithm to restore the entire missing frame encoded by High Efficiency Video Coding (HEVC). In each missing HEVC frame, it uses the prediction unit (PU) information of the previous frame to adaptively decide the size of a basic unit for error concealment and to provide a more accurate estimation for the motion vector in that basic unit than can be achieved by any other conventional method. The simulation results showed that it is highly effective and significantly outperforms other existing frame recovery methods in terms of both objective and subjective quality.

Bioinformatic approaches for the structure and function of membrane proteins

  • Nam, Hyun-Jun;Jeon, Jou-Hyun;Kim, Sang-Uk
    • BMB Reports
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    • 제42권11호
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    • pp.697-704
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    • 2009
  • Membrane proteins play important roles in the biology of the cell, including intercellular communication and molecular transport. Their well-established importance notwithstanding, the high-resolution structures of membrane proteins remain elusive due to difficulties in protein expression, purification and crystallization. Thus, accurate prediction of membrane protein topology can increase the understanding of membrane protein function. Here, we provide a brief review of the diverse computational methods for predicting membrane protein structure and function, including recent progress and essential bioinformatics tools. Our hope is that this review will be instructive to users studying membrane protein biology in their choice of appropriate bioinformatics methods.

Electricity Price Prediction Model Based on Simultaneous Perturbation Stochastic Approximation

  • Ko, Hee-Sang;Lee, Kwang-Y.;Kim, Ho-Chan
    • Journal of Electrical Engineering and Technology
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    • 제3권1호
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    • pp.14-19
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    • 2008
  • The paper presents an intelligent time series model to predict uncertain electricity market price in the deregulated industry environment. Since the price of electricity in a deregulated market is very volatile, it is difficult to estimate an accurate market price using historically observed data. The parameter of an intelligent time series model is obtained based on the simultaneous perturbation stochastic approximation (SPSA). The SPSA is flexible to use in high dimensional systems. Since prediction models have their modeling error, an error compensator is developed as compensation. The SPSA based intelligent model is applied to predict the electricity market price in the Pennsylvania-New Jersey-Maryland (PJM) electricity market.

A Plasma-Etching Process Modeling Via a Polynomial Neural Network

  • Kim, Dong-Won;Kim, Byung-Whan;Park, Gwi-Tae
    • ETRI Journal
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    • 제26권4호
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    • pp.297-306
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    • 2004
  • A plasma is a collection of charged particles and on average is electrically neutral. In fabricating integrated circuits, plasma etching is a key means to transfer a photoresist pattern into an underlayer material. To construct a predictive model of plasma-etching processes, a polynomial neural network (PNN) is applied. This process was characterized by a full factorial experiment, and two attributes modeled are its etch rate and DC bias. According to the number of input variables and type of polynomials to each node, the prediction performance of the PNN was optimized. The various performances of the PNN in diverse environments were compared to three types of statistical regression models and the adaptive network fuzzy inference system (ANFIS). As the demonstrated high-prediction ability in the simulation results shows, the PNN is efficient and much more accurate from the point of view of approximation and prediction abilities.

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발전용 터빈 로우터의 수명예측을 위한 열응력 해석 (Thermal Stress Analysis for Life Prediction of Power Plant Turbine Rotor)

  • 임종순;허승진;이규봉;유영면
    • 대한기계학회논문집
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    • 제14권2호
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    • pp.276-287
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    • 1990
  • In this paper research result of transient thermal stress analysis of power plant turbine rotors for life prediction under severs operating conditions is presented. Galerkin's recurrence scheme is used for numerical solution of discretized FEM equation of transient heat conduction equation. Boundary conditions for the equation and operating conditions are intensively investigated for accurate life prediction of turbine rotors in operation. A computer program for on-site application is developed and tested. Distribution of thermal stress in turbine rotors during various operating condition is analyzed with the program and it is found that the peak thermal stress appears during cold stage conditions at the first stage of high pressure rotors.

Numerical simulation of shaking table tests on 3D reinforced concrete structures

  • Bayhan, Beyhan
    • Structural Engineering and Mechanics
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    • 제48권2호
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    • pp.151-171
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    • 2013
  • The current paper presents the numerical blind prediction of nonlinear seismic response of two full-scale, three dimensional, one-story reinforced concrete structures subjected to bidirectional earthquake simulations on shaking table. Simulations were carried out at the laboratories of LNEC (Laboratorio Nacional de Engenharia Civil) in Lisbon, Portugal. The study was motivated by participation in the blind prediction contest of shaking table tests, organized by the challenge committee of the 15th World Conference on Earthquake Engineering. The test specimens, geometrically identical, designed for low and high ductility levels, were subjected to subsequent earthquake motions of increasing intensity. Three dimensional nonlinear analytical models were implemented and subjected to the input base motions. Reasonably accurate reproduction of the measured displacement response was obtained through appropriate modeling. The goodness of fit between analytical and measured results depended on the details of the analytical models.

유전프로그래밍에 의한 초고압 송전선로 환경설계용 코로나 소음 예측계산식 개발 (Development of Audible Noise Prediction Formulas Applied to HVAC Transmission Lines Design by Using Genetic Programming)

  • 양광호;황기현;박준호;박종근
    • 대한전기학회논문지:전력기술부문A
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    • 제50권5호
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    • pp.234-240
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    • 2001
  • Audible noise (AN) produced by corona discharges from high voltage transmission lines is one of the more important considerations in line design. Therefore, line designers must pre-determine the AN using prediction formulas. This paper presents the results of applying evolutionary computation techniques using AN data from lines throughout the world to develop new, highly accurate formulas for predicting a A-weighted AN during heavy rain and stable rain from overhead ac lines. Calculated ANs using these new formulas and existing formulas are compared with measured data.

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CAE를 이용한 자동차용 휠(wheel)의 피로수명 예측기법 연구 (The Study on the Fatigue Life Prediction on Wheels through CAE)

  • 김만섭;고길주;김정헌;양창근;김관묵
    • 한국자동차공학회논문집
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    • 제12권2호
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    • pp.117-122
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    • 2004
  • The fatigue life in wheels was predicted by simulating the experimental method using Finite-Element analysis. Based on a high frequency fatigue property, calculations of the stresses in wheels were performed by simulating the rotating bending fatigue test. Wheels made of an aluminum alloy(A356.2) were tested using a bending fatigue tester. Results from bending fatigue test showed a linear correlation between bending moment and stress amplitude. Consequently, Finite-Element calculations were performed by a linear analysis. In order to find stress-cycles curves, spoke parts of wheel were tested using a rotary bending fatigue tester. Also, highly accurate Finite-Element analysis requires regression lines and confidence intervals from these results. In conclusion, if the fatigue data related to the material and manufacturing procedure are reliable, the prediction on fatigue lift in wheels can be carried out with high accuracy.