• 제목/요약/키워드: Data Speed

검색결과 8,918건 처리시간 0.038초

태풍시기의 강풍피해 예측을 위한 지상풍 산정에 관한 연구(I) (The Study on the Strong Wind Damage Prediction for Estimation Surface Wind Speed of Typhoon Season(I))

  • 박종길;정우식;최효진
    • 한국환경과학회지
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    • 제17권2호
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    • pp.195-201
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    • 2008
  • Damage from typhoon disaster can be mitigated by grasping and dealing with the damage promptly for the regions in typhoon track. What is this work, a technique to analyzed dangerousness of typhoon should be presupposed. This study estimated 10 m level wind speed using 700 hPa wind by typhoon, referring to GPS dropwindsonde study of Franklin(2003). For 700 hPa wind, 30 km resolution data of Regional Data Assimilation Prediction System(RDAPS) were used. For roughness length in estimating wind of 10 m level, landuse data of USGS are employed. For 10 m level wind speed of Typhoon Rusa in 2002, we sampled AWS site of $7.4{\sim}30km$ distant from typhoon center and compare them with observational data. The results show that the 10 m level wind speed is the estimation of maximum wind speed which can appear in surface by typhoon and it cannot be compared with general hourly observational data. Wind load on domestic buildings relies on probability distributions of extreme wind speed. Hence, calculated 10 m level wind speed is useful for estimating the damage structure from typhoon.

시공간적 영향력을 반영한 딥러닝 기반의 통행속도 예측 모형 개발 (Development of Traffic Speed Prediction Model Reflecting Spatio-temporal Impact based on Deep Neural Network)

  • 김영찬;김준원;한여희;김종준;황제웅
    • 한국ITS학회 논문지
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    • 제19권1호
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    • pp.1-16
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    • 2020
  • 4차 산업혁명 시대가 도래함에 따라 빅데이터를 활용하는 딥러닝에 대한 관심이 높아졌으며 다양한 분야에서 딥러닝을 이용한 연구가 활발하게 진행되고 있다. 교통 분야에서도 교통빅데이터를 많이 활용하는 만큼 딥러닝을 연구에 이용한다면 많은 이점이 있을 것이다. 본 연구에서는 통행속도를 예측하기 위하여 딥러닝 기법인 LSTM을 이용한 단기 통행속도 예측 모형을 구축하였다. 예측에 활용한 데이터인 통행속도 데이터가 시계열 데이터인 것을 고려하여 시계열 예측에 적합한 LSTM 모델을 선택하였다. 통행속도를 보다 정확하게 예측하기 위하여 시간적, 공간적 영향을 모두 반영하는 모형을 구축하였으며, 모형은 1시간 이후를 예측하는 단기 예측모형이다. 분석데이터는 서울시 교통정보센터에서 수집한 5분 단위 통행속도를 활용하였고 분석구간은 교통이 혼잡한 강남대로 일부구간으로 선정하여 연구를 수행하였다.

결정 궤환 구조를 갖는 차동 위상 검출기의 고속 데이터 처리를 위한 VLSI 설계 (A VLSI Design for High-speed Data Processing of Differential Phase Detectors with Decision Feedback)

  • 김창곤;정정화
    • 대한전자공학회논문지SD
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    • 제39권5호
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    • pp.74-86
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    • 2002
  • 본 논문은 결정 궤환 구조를 갖는 차동 위상 검출기의 고속 데이터 처리를 위한 VLSI 구조를 제안한다. 기존 차동 위상 검출 방식의 낮은 BER 성능을 극복하기 위해 DF-DPD, DPD-RGPR, DFDPD-SA 등의 다중 심볼 검출 방식이 제시되었다. 이러한 검출 방식들은 참조 위상으로 사용되는 이전 심볼에서의 잡음 효과를 작게 하기 위하여 검출된 위상을 궤환시키는 구조를 갖고 있다. 하지만, 검출된 위상을 궤환시키는 작용은 데이터 처리 속도를 기존의 차동 위상 검출기보다 느리게 한다. 본 논문에서는 결정 궤환 구조를 갖는 차동 위상 검출기가 기존의 차동 위상 검출 방식처럼 고속으로 데이터를 처리할 수 있는 VLSI 구조를 제안하였다. 제안된 구조는 'M-1' 번째 과정에서 'M' 번째 과정을 미리 계산하는 선계산(pre-calculation) 방식과 'M-1'번째 과정에서 예견 위상들을 궤환시키는 선결정 궤환(pre-decision feedback) 방식을 갖는다. 본 논문에서 제안된 구조는 VHDL(Very-high-speed-IC Hardware Description Language)를 사용하여 RTL(Register Transfer Level)로 구현되었다. 시뮬레이션 결과, 제안된 구조는 고속으로 데이터를 처리함을 확인하였다.

Ultrasonic Speed and Isentropic Compressibility of 2-propanol with Hydrocarbons at 298.15 and 308.15 K

  • Gahlyan, Suman;Verma, Sweety;Rani, Manju;Maken, Sanjeev
    • Korean Chemical Engineering Research
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    • 제55권5호
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    • pp.668-678
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    • 2017
  • Intermolecular interactions were studied for binary mixtures of 2-propanol + cyclohexane, n-hexane, benzene, toluene, o-, m- and p-xylenes by measuring ultrasonic speeds (u) over the entire range of composition at 298.15 K and 308.15 K. From these results the deviation in ultrasonic speed was calculated. These results were fitted to the Redlich-Kister equation to derive the binary coefficients along with standard deviations between the experimental and calculated data. Acoustic parameters such as excess isentropic compressibility ($K_s^E$), intermolecular free length ($L_f$) and available volume ($V_a$) were also derived from ultrasonic speed data and Jacobson's free length theory. The ultrasonic speed data were correlated by Nomoto's relation, Van Dael's mixing relation, impedance dependence relation, and Schaaff's collision factor theory. Van Dael's relation gives the best prediction of u in the binary mixtures containing aliphatic hydrocarbons. The ultrasonic speed data and isentropic compressibility were further analyzed in terms of Jacobson's free length theory.

Investigation on vibration behavior of a high-speed railway bridge based on monitoring data

  • Qingxin Zhu;Hao Wang;Billie F. Spencer Jr
    • Smart Structures and Systems
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    • 제31권6호
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    • pp.585-599
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    • 2023
  • Field monitoring techniques offer an attractive approach for understanding bridge behavior under in-service loads. However, the investigations on bridge behavior under high-speed train load using field monitoring data are limited. The focus of this study is to explore the structural behavior of an in-service long-span steel truss arch bridge based on field monitoring data. First, the natural frequencies of the structure, as well as the train driving frequencies, are extracted. Then, the train-induced bearing displacement and structural strain are explored to identify the effects of train loads and bearings. Subsequently, a sensitivity analysis is performed for the impact factor of strain responses with respect to the train speed, train weight, and temperature to identify the fundamental issues affecting these responses. Additionally, a similar sensitivity analysis is conducted for the peak acceleration. The results indicate that the friction force in bearings provides residual deformations when two consecutive trains are in opposite directions. In addition, the impact factor and peak acceleration are primarily affected by train speed, particularly near train speeds that result in the resonance of the bridge response. The results can provide additional insight into the behavior of the long-span steel truss bridges under in-service high-speed train loads.

한반도 바람자원의 시공간적 분포 (Spatial and temporal distribution of Wind Resources over Korea)

  • 김도우;변희룡
    • 대기
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    • 제18권3호
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    • pp.171-182
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    • 2008
  • In this study, we analyzed the spatial and temporal distribution of wind resources over Korea based on hourly observational data recorded over a period of 5 years from 457 stations belonging to Korea Meteorological Administration (KMA). The surface and 850 hPa wind data obtained from the Korea Local Analysis and Prediction System (KLAPS) and the Regional Data Assimilation and Prediction System (RDAPS) over a period of 1 year are used as supplementary data sources. Wind speed is generally high over seashores, mountains, and islands. In 62 (13.5%) stations, mean wind speeds for 5 years are greater than $3ms^{-1}$. The effects of seasonal wind, land-sea breeze, and mountain-valley winds on wind resources over Korea are evaluated as follows: First, wind is weak during summer, particularly over the Sobaek Mountains. However, over the coastal region of the Gyeongnam-province, strong southwesterly winds are observed during summer owing to monsoon currents. Second, the wind speed decreases during night-time, particularly over the west coast, where the direction of the land breeze is opposite to that of the large-scale westerlies. Third, winds are not always strong over seashores and highly elevated areas. The wind speed is weaker over the seashore of the Gyeonggi-province than over the other seashores. High wind speed has been observed only at 5 stations out of the 22 high-altitude stations. Detailed information on the wind resources conditions at the 21 stations (15 inland stations and 6 island stations) with high wind speed in Korea, such as the mean wind speed, frequency of wind speed available (WSA) for electricity generation, shape and scale parameters of Weibull distribution, constancy of wind direction, and wind power density (WPD), have also been provided. Among total stations in Korea, the best possible wind resources for electricity generation are available at Gosan in Jeju Island (mean wind speed: $7.77ms^{-1}$, WSA: 92.6%, WPD: $683.9Wm^{-2}$) and at Mt. Gudeok in Busan (mean wind speed: $5.66ms^{-1}$, WSA: 91.0%, WPD: $215.7Wm^{-2}$).

MZI를 이용한 전광 직렬-병렬 데이터 형식 변환기 구현과 활용 방안 (Implementation of All-Optical Serial-Parallel Data Converters Using Mach-Zehnder Interferometers and Applications)

  • 이성철
    • 디지털산업정보학회논문지
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    • 제7권2호
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    • pp.59-65
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    • 2011
  • All-optical signal processing is expected to offer advantages in speed and power consumption against over electronics signal processing. It has a potential to solve the bottleneck issues of ultra-high speed communication network nodes. All-optical serial-to-parallel and parallel-to-serial data converters would make it possible to easily process the serial data information of a high-speed optical packet without optical-to-electronic-to-optical data conversion. In this paper, we explain the principle of simple and easily expandable all-optical serial-to-parallel and parallel-to-serial data converters based on Mach-Zehnder interferometers. We experimentally demonstrate these data converters at 10Gbit/s serial data rate. They are useful all-optical devices for the all-optical implementations of label decoding, self-routing, control of variable packets, bit-wise logical operation, and data format conversion.

개인 건강 정보 처리를 위한 배치 어플리케이션에서 데이터 질의 속도 향상을 위한 PHDItemReader 설계 및 구현 (Desgin and Implementation of PHDItemReader to Speed up Data Query in Batch Application for Processing Personal Health Record)

  • 전동철;황희정
    • 한국멀티미디어학회논문지
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    • 제23권12호
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    • pp.1496-1506
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    • 2020
  • With the progress of miniaturization and high performance of various sensors, a lot of data is generated in various fields and being collected in real-time, but the use of such large-capacity data is often unable to keep up with the collection technology. In the medical field, health data is collected and managed by platform, which causes inconvenience to users in searching their own health data and receiving medical services. In this paper, in order to solve these problems, we designed and implemented PHDItemReader to improve the speed of data query in a batch application environment that can integrate and process health data having various data expression formats. The experiment compared and analyzed 3 types of query speed based on 1,000,000 hypothetical health data, and as a result of the experiment, it was verified that the PHDItemReader implemented in this paper improved up to about 21% compared to the existing one.

Detecting artefacts in analyses of extreme wind speeds

  • Cook, Nicholas J.
    • Wind and Structures
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    • 제19권3호
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    • pp.271-294
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    • 2014
  • The impact of artefacts in archived wind observations on the design wind speed obtained by extreme value analysis is demonstrated using case studies. A signpost protocol for detecting candidate artefacts is described and its performance assessed by comparing results against previously validated data. The protocol targets artefacts by exploiting the serial correlation between observations. Additional "sieve" algorithms are proposed to identify types of correctable artefact from their "signature" in the data. In extreme value analysis, artefacts displace valid observations only when they are larger, hence always increase the design wind speed. Care must be taken not identify large valid values as artefacts, since their removal will tend to underestimate the design wind speed.

신경회로망을 이용한 소결기 팰릿 속도 제어 (Pallet speed control in a sintering plant using neural networks)

  • 장민;조성준
    • 한국데이타베이스학회:학술대회논문집
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    • 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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    • pp.261-270
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    • 1999
  • Sintering transforms powdered ore into lumped ore so that the latter can be used in a blast furnace. The powdered ore combined with coke and other materials is loaded into a container and moved along by a pallet while the ignited coke bums. The speed by which the pallet moves determines how much sintering takes place. Since the process is complicated and lacks an accurate mathematical model, human operators manually control the speed by monitoring various factors in the plant. In this paper, we propose a neural network-based pallet speed controller which copies human operator knowledge. Actual process data were collected from a sintering plant fer eight months and preprocessed to remove noisy and inconsistent data. A multilayer perceptron was trained using a back-propagation learning algorithm. In on-line testing at the sinter plant, the proposed model reliably controlled pallet speed during normal operation without the help of human operators. Moreover, the duality and productivity was as good as with human operators.

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