• 제목/요약/키워드: Short-Term

검색결과 5,963건 처리시간 0.031초

단기 풍관측에 의한 교량현장 기본풍속 추정 (Estimation of Basic Wind Speed at Bridge Construction Site Based on Short-term Measurements)

  • 이성로;김상우
    • 대한토목학회논문집
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    • 제33권4호
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    • pp.1271-1279
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    • 2013
  • 본 논문에서는 단기 관측자료를 활용하여 장대교량 현장의 기본풍속을 추정하는 방법에 대한 연구를 수행하였다. 기상관측소로부터 거리가 먼 장대교량의 내풍설계시 현장의 기본 풍속을 추정하기 위해 현장의 장기 풍속자료를 통계처리하는 것이 필요하다. 현장에 풍관측탑을 설치하고 단기간의 풍관측 자료를 확보하였고 선형회귀분석 및 MCP 방법을 이용하여 인근 기상관측소와의 상관관계를 분석하였다. 기상관측소의 장기풍자료를 지형보정을 한 후 상관관계식에 의해 현장의 장기 풍속자료를 얻었고 풍속자료의 극치 확률분포 분석에 의해 기본풍속 산정을 할 수 있었다. 연구결과에서는 선형회귀분석의 방법이 MCP 방법에 비해 풍속을 낮게 추정하고 있으며, 향후 여러 현장에서 일련의 상관관계 분석을 수행한다면 종합적으로 두 방법에 의한 기본풍속 산정의 차이를 보다 명확히 보여줄 것이다. 또한, 장기자료의 질 관리가 풍속추정에 매우 중요하다는 것을 보여주고 있다.

Outcomes of dental implant treatment in patients with generalized aggressive periodontitis: a systematic review

  • Kim, Kyoung-Kyu;Sung, Hun-Mo
    • The Journal of Advanced Prosthodontics
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    • 제4권4호
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    • pp.210-217
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    • 2012
  • PURPOSE. The purpose of this study was to analyze the current literatures and to assess outcomes of implant treatment in patients with generalized aggressive periodontitis. MATERIALS AND METHODS. Studies considered for inclusion were searched in Pub-Med. The literature search for studies published in English between 2000 and 2012 was performed. Our findings included literature assessing implant treatment in patients with a history of generalized aggressive periodontitis (GAP). All studies were screened according to inclusion criteria. The outcome measures were survival rate of superstructures, marginal bone loss around implant and survival rate of implants. All studies were divided into two follow-up period: short term study (< 5 years) and long term study (${\geq}5$ years). RESULTS. Seven prospective studies were selected, including four short-term and three long-term studies. The survival rates of the superstructures were generally high in patients with GAP, i.e. 95.9-100%. Marginal bone loss around implant in patients with GAP as compared with implants in patients with chronic periodontitis or periodontally healthy patients was not significantly greater in short term studies but was significantly greater in long term studies. In short term studies, the survival rates of implants were between 97.4% and 100% in patients with GAP-associated tooth loss, except one study. The survival rates of implants were between 83.3% and 96% in patients with GAP in long term studies. CONCLUSION. Implant treatment in patients with GAP is not contraindicated provided that adequate infection control and an individualized maintenance program are assured.

An adaptive neuro-fuzzy inference system (ANFIS) model to predict the pozzolanic activity of natural pozzolans

  • Elif Varol;Didem Benzer;Nazli Tunar Ozcan
    • Computers and Concrete
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    • 제31권2호
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    • pp.85-95
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    • 2023
  • Natural pozzolans are used as additives in cement to develop more durable and high-performance concrete. Pozzolanic activity index (PAI) is important for assessing the performance of a pozzolan as a binding material and has an important effect on the compressive strength, permeability, and chemical durability of concrete mixtures. However, the determining of the 28 days (short term) and 90 days (long term) PAI of concrete mixtures is a time-consuming process. In this study, to reduce extensive experimental work, it is aimed to predict the short term and long term PAIs as a function of the chemical compositions of various natural pozzolans. For this purpose, the chemical compositions of various natural pozzolans from Central Anatolia were determined with X-ray fluorescence spectroscopy. The mortar samples were prepared with the natural pozzolans and then, the short term and the long term PAIs were calculated based on compressive strength method. The effect of the natural pozzolans' chemical compositions on the short term and the long term PAIs were evaluated and the PAIs were predicted by using multiple linear regression (MLR) and adaptive neuro-fuzzy inference system (ANFIS) model. The prediction model results show that both reactive SiO2 and SiO2+Al2O3+Fe2O3 contents are the most effective parameters on PAI. According to the performance of prediction models determined with metrics such as root mean squared error (RMSE) and coefficient of correlation (R2), ANFIS models are more feasible than the multiple regression model in predicting the 28 days and 90 days pozzolanic activity. Estimation of PAIs based on the chemical component of natural pozzolana with high-performance prediction models is going to make an important contribution to material engineering applications in terms of selection of favorable natural pozzolana and saving time from tedious test processes.

Simulation Study on Silicon-Based Floating Body Synaptic Transistor with Short- and Long-Term Memory Functions and Its Spike Timing-Dependent Plasticity

  • Kim, Hyungjin;Cho, Seongjae;Sun, Min-Chul;Park, Jungjin;Hwang, Sungmin;Park, Byung-Gook
    • JSTS:Journal of Semiconductor Technology and Science
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    • 제16권5호
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    • pp.657-663
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    • 2016
  • In this work, a novel silicon (Si) based floating body synaptic transistor (SFST) is studied to mimic the transition from short-term memory to long-term one in the biological system. The structure of the proposed SFST is based on an n-type metal-oxide-semiconductor field-effect transistor (MOSFET) with floating body and charge storage layer which provide the functions of short- and long-term memories, respectively. It has very similar characteristics with those of the biological memory system in the sense that the transition between short- and long-term memories is performed by the repetitive learning. Spike timing-dependent plasticity (STDP) characteristics are closely investigated for the SFST device. It has been found from the simulation results that the connectivity between pre- and post-synaptic neurons has strong dependence on the relative spike timing among electrical signals. In addition, the neuromorphic system having direct connection between the SFST devices and neuron circuits are designed.

Identification of Niche Conditions Supporting Short-term Culture of Spermatogonial Stem Cells Derived from Porcine Neonatal Testis

  • Park, Min Hee;Park, Ji Eun;Kim, Min Seong;Lee, Kwon Young;Yun, Jung Im;Choi, Jung Hoon;Lee, Eunsong;Lee, Seung Tae
    • 한국수정란이식학회지
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    • 제29권3호
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    • pp.221-228
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    • 2014
  • Despite that porcine spermatogonial stem cells (pSSCs) have been regarded as a practical tool for preserving eternally genetic backgrounds derived from pigs with high performance in the economic traits or phenotypes of specific human diseases, there were no reports about precise definition of niche conditions promoting proliferation and maintenance of pSSCs. Accordingly, we tried to determine niche conditions supporting proliferation and maintenance of undifferentiated pSSCs for short-term. For these, undifferentiated pSSCs were progressively cultured in different composition of culture medium, seeding density of pSSCs, type of feeder cells and concentration of growth factors, and then total number of and alkaline phosphatase (AP) activity of pSSCs were investigated at post-6 day culture. As the results, the culture of $4{\times}10^5$ pSSCs on mitotically in activated $2{\times}10^5$ STO cells in the mouse embryonic stem cell culture medium (mESCCM) supplemented with 30 ng/ml glial cell line-derived neurotrophic factor (GDNF) was identified as the best niche condition supporting effectively the short-term maintenance of undifferentiated pSSCs. Moreover, the optimized short-term culture system will be a basis for developing long-term culture system of pSSCs in the following researches.

Prediction Oil and Gas Throughput Using Deep Learning

  • Sangseop Lim
    • 한국컴퓨터정보학회논문지
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    • 제28권5호
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    • pp.155-161
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    • 2023
  • 우리나라 수출의 97.5%, 수입의 87.2%가 해상운송으로 이뤄지며 항만이 한국 경제의 중요한 구성요소이다. 이러한 항만의 효율적인 운영을 위해서는 항만 물동량의 단기 예측을 통해 개선시킬 수가 있으며 과학적인 연구방법이 필요하다. 이전 연구는 주로 장기예측을 기반으로 대규모 인프라투자를 위한 연구에 중점을 두었으며 컨테이너 항만물동량에만 집중한 측면이 크다. 본 연구는 국내 대표적인 석유항만인 울산항의 석유 및 가스화물 물동량에 대한 단기 예측을 수행하였으며 딥러닝 모델인 LSTM(Long Short Term Memory) 모델을 사용하여 RMSE기준으로 예측성능을 확인하였다. 본 연구의 결과는 석유 및 가스화물 물동량 수요 예측의 정확도를 높여 항만 운영의 효율성을 개선하는 근거가 될 수 있을 것으로 기대된다. 또한 기존 연구의 한계로 컨테이너 항만 물동량뿐만 아니라 석유 및 가스화물 물동량 예측에도 LSTM의 활용할 수 있다는 가능성을 확인할 수 있으며 향후 추가 연구를 통해 일반화가 가능할 것으로 기대된다.

Short Term Interest Rate Model Using Box-Cox Transformation

  • Choi, Young-Soo;Lee, Yoon-Dong
    • Communications for Statistical Applications and Methods
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    • 제14권1호
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    • pp.241-254
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    • 2007
  • This paper propose a new short-term interest rate model having a different nonlinear drift function and the same diffusion coefficient with Chan et al. (1992) model. The fractional polynomial power of the drift function in our model is linked to the local volatility elasticity of the diffusion coefficient. While the nonlinear drift function estimated by $A\"{\i}t$-Sahalia (1996a) and others has a feature that higher interest rates tend to revert downward and low rates upward, the drift function estimated by our nonlinear model shows that higher interest rate mean-reverts strongly, but, medium rates has almost zero drift and low rates has a very small drift. This characteristic coincides the empirical result based on the nonparametric methodology by Stanton (1997) and the implication by the scatter plot of the short rate data.

코호넨 신경회로망과 웨이브릿 변환을 이용한 단기부하예측 (Short-term load forecasting using Kohonen neural network and wavelet transform)

  • 김창일;김봉태;김우현;유인근
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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    • pp.239-241
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    • 1999
  • This paper proposes a novel wavelet transform and Kohonen neural network based technique for short-time load forecasting of power systems. Firstly. Kohonen Self-organizing map(KSOM) is applied to classify the loads and then the Daubechies D2, D4 and D10 wavelet transforms are adopted in order to forecast the short-term loads. The wavelet coefficients associated with certain frequency and time localisation are adjusted using the conventional multiple regression method and then reconstructed in order to forecast the final loads through a four-scale synthesis technique. The outcome of the study clearly indicates that the proposed composite model of Kohonen neural network and wavelet transform approach can be used as an attractive and effective means for short-term load forecasting.

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An Approach for Stock Price Forecast using Long Short Term Memory

  • K.A.Surya Rajeswar;Pon Ramalingam;Sudalaimuthu.T
    • International Journal of Computer Science & Network Security
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    • 제23권4호
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    • pp.166-171
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    • 2023
  • The Stock price analysis is an increasing concern in a financial time series. The purpose of the study is to analyze the price parameters of date, high, low, and news feed about the stock exchange price. Long short term memory (LSTM) is a cutting-edge technology used for predicting the data based on time series. LSTM performs well in executing large sequence of data. This paper presents the Long Short Term Memory Model has used to analyze the stock price ranges of 10 days and 20 days by exponential moving average. The proposed approach gives better performance using technical indicators of stock price with an accuracy of 82.6% and cross entropy of 71%.

아동의 전자게임 활동이 시각적 병행처리에 미치는 영향 (The Effects of Playing Video Games on Children's Visual Parallel Processing)

  • 김숙현;최경숙
    • 아동학회지
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    • 제20권3호
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    • pp.231-244
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    • 1999
  • This study examined the effects of short and long term playing of video gamer on children's visual parallel processing. All of the 64 fourth grade subjects were above average in IQ. They were classified into high and low video game users. Instruments were a visual parallel processing task consisting of imagery integration items, computers, and the arcade video game, Pac-Man. Subjects were pre-tested with a visual parallel processing task. After one week, the experimental group played video games for 15 minutes, but the control group didn't play. Immediately following this, all children were post-tested by the same task used on the pretest. The data was analyzed by ANCOVA and repeated measures ANOVA. The results showed that relaying short-term video games improved visual parallel processing and that long term experience with video games also affected visual parallel processing. there were no differences between high and low users in visual parallel processing after playing short term video games.

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