• 제목/요약/키워드: Short-Term

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내부 최적화를 이용한 화학 센서의 단기 드리프트 분석 및 보정 (Short Term Sensor's Drift Analysis and Compensation Using Internal Normalization)

  • 전진영;백종현;변형기
    • 센서학회지
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    • 제24권4호
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    • pp.270-273
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    • 2015
  • One of the main problems when working the chemical sensor is the lack of repeatability and reproducibility of the sensor response. If the problem is not properly taken into consideration, the stability and reliability of the system using chemical sensors would be decreased. In this paper we analyzed the sensor's drift of short term and proposed a compensation method for reducing the effects of the drift in order to improve the stability and the reliability of the chemical sensor. The sensor drift was analyzed by a trend line graph and CV(coefficient of variation) was used to quantify. And we compensated for the drift by using the internal normalization. As a result it was found that the value of CV was decreased after compensation.

Short-term ICT Training Program for Non-Computer Science Major Teachers in Developing Countries for Improving ICT Teaching Efficacy

  • Jeon, Yongju;Song, Ki-Sang
    • International journal of advanced smart convergence
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    • 제7권2호
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    • pp.73-85
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    • 2018
  • The purpose of this study is to develop a short-term ICT training course that helps teachers from non-computing disciplines in developing countries acquire flipped-learning content creation skills. A field application is performed by applying the developed ICT training course to secondary school teachers of non-ICT subject specialisms in Laos. In the field study, participating teachers' teaching efficacy on ICT and satisfaction toward the training course are measured. The result of t-test on ICT teaching efficacy showed statistically significant increases in teachers' self-efficacy related to ICT use, both personal efficacy and outcome expectancy. The satisfaction survey performed after training showed that trainees were highly satisfied with the training course. The results of this field study could be used to propose a short-term teacher education model that could be applicable to teachers in other developing countries.

Short-term Electric Load Forecasting Based on Wavelet Transform and GMDH

  • Koo, Bon-Gil;Lee, Heung-Seok;Park, Juneho
    • Journal of Electrical Engineering and Technology
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    • 제10권3호
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    • pp.832-837
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    • 2015
  • The group method of data handling (GMDH) algorithm has proven to be a powerful and effective way to extract rules or polynomials from an electric load pattern. However, because it is nonstationary, the load pattern needs to be decomposed using a discrete wavelet transform. In addition, if a load pattern has a complicated curve pattern, GMDH should use a higher polynomial, which requires complex computing and consumes a lot of time. This paper suggests a method for short-term electric load forecasting that uses a wavelet transform and a GMDH algorithm. Case studies with the proposed algorithm were carried out for one-day-ahead forecasting of hourly electric loads using data during the years 2008-2011. To prove the effectiveness of our proposed approach, the results were evaluated and compared with those obtained by Holt-Winters method and artificial neural network. Our suggested method resulted in better performance than either comparison group.

Short-Term Load Forecasting Based on Sequential Relevance Vector Machine

  • Jang, Youngchan
    • Industrial Engineering and Management Systems
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    • 제14권3호
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    • pp.318-324
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    • 2015
  • This paper proposes a dynamic short-term load forecasting method that utilizes a new sequential learning algorithm based on Relevance Vector Machine (RVM). The method performs general optimization of weights and hyperparameters using the current relevance vectors and newly arriving data. By doing so, the proposed algorithm is trained with the most recent data. Consequently, it extends the RVM algorithm to real-time and nonstationary learning processes. The results of application of the proposed algorithm to prediction of electrical loads indicate that its accuracy is comparable to that of existing nonparametric learning algorithms. Further, the proposed model reduces computational complexity.

변곡점 및 단구간 에너지평가에 의한 음성의 천이구간 특징분석 (Analysis of Transient Features in Speech Signal by Estimating the Short-term Energy and Inflection points)

  • 최일홍;장승관;차태호;최웅세;김창석
    • 음성과학
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    • 제3권
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    • pp.156-166
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    • 1998
  • In this paper, I would like to propose a dividing method by estimating the inflection points and the average magnitude energy in speech signals. The method proposed in this paper gave not only a satisfactory solution for the problems on dividing method by zero-crossing rate, but could estimate the feature of the transient period after dividing the starting point and transient period in speech signals before steady state. In the results of the experiment carried out with monosyllabic speech, it was found that even through speech samples indicated in D.C. level, the staring and ending point of the speech signals were exactly divided by the method. In addition to the results, I could compare with the features, such as the length of transient period, the short term energy, the frequency characteristics, in each speech signal.

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유역 유출 예측 시스템 개발 (Development of Rainfall-Runoff forecasting System)

  • 황만하;맹승진;고익환;류소라
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2004년도 학술발표회
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    • pp.709-712
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    • 2004
  • The development of a basin-wide runoff analysis model is to analysis monthly and daily hydrologic runoff components including surface runoff, subsurface runoff, return flow, etc. at key operation station in the targeted basin. h short-term water demand forecasting technology will be developed fatting into account the patterns of municipal, industrial and agricultural water uses. For the development and utilization of runoff analysis model, relevant basin information including historical precipitation and river water stage data, geophysical basin characteristics, and water intake and consumptions needs to be collected and stored into the hydrologic database of Integrated Real-time Water Information System. The well-known SSARR model was selected for the basis of continuous daily runoff model for forecasting short and long-term natural flows.

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O1factory and Sexual Attractiveness of Western Mosquitofish (Gambusia affinis) Exposed to the Commonly Used Insecticide Endosulfan

  • Park, Daesik;Propper, Catherine R.;Park, Shi-Ryong
    • Animal cells and systems
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    • 제6권2호
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    • pp.153-157
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    • 2002
  • To know whether a short-term exposure to a commonly used insecticide induces subtle negative toxic effects, female western mosquitofish, Gam-busia affinis, were exposed to 0.1, 0.5, and 1 pub endosulfan for one week and subsequently examined for their olfactory and sexual attractiveness to conspecific males. A short-term exposure to endosulfan did not impair the physical conditions investigated in this study nor did it disrupt olfactory attractiveness of female mosquitofish. However, 1 ppb endosulfan significantly reduced sexual attractiveness of exposed females. Test males showed significantly less copulation attempts with the exposed females. Our results suggest that in the field, a short term exposure of endosulfan may disrupt mating processes in non-targeted aquatic organisms.

민간환경보전운동단체의 장.단기 목표 및 추진방안 (The Goals and the Short and Long Term Plan for Non-Government Environmental Protection Organigations)

  • 이범홍
    • 한국환경교육학회지:환경교육
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    • 제2권1호
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    • pp.107-116
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    • 1991
  • In this study, the goals and the short and long term plan to attain the goals were set up through the analysis of non-government environmental protection organizations actual conditions which were grasped through interview and questionnaire. The goals and the plan were modified and elaborated through 3 times environment experts conferences and a public hearing. The goals were as follows: a) Laying down the guidelines on the organizations. b) Establishing a view of environment. c) Paying a public attention to importance of environment. d) Activations the practice in environmental protection movement. e) Harmonizing the relations between the organizations themselves. government and the organizations, industries and the organizations. f) Establishing the government support system to the organizations in leagal. administrative and financial aspects. g) Enhancing the potentialities on research and development in environmental protection technology. In the short and long term plan, the specific activities to be driven up to the year 2000 were presented by stages.

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지형을 고려한 단기 대기확산모형의 평가에 관한 연구 (A Study on the Evaluation of the Short-term Atmospheric Dispersion Models with Terrain Adjustment)

  • 최일경;전의찬;김정욱
    • 한국대기환경학회지
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    • 제6권2호
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    • pp.125-134
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    • 1990
  • The purpose of this study is to assess the performance of Short-term atmospheric dispersion models --- ISCST, MPTER, VALLEY --- with terrain adjustment. The models are evaluated through correlation analysis, paired analysis and log-normal culmulative analysis between the measured and predicted concentrations in Samcheonpo area. The correlation coefficients between the measured and predicted concentrations turn out to be higher with terrain adjustment than those without terrain adjustment. In paired analysis, the mean differences and average absolute gross errors of concentrations do not change significantly with terrain adjustment. But the variances of the residuals become much smaller when the terrain is adjusted. Through the log-normal cumulative analysis, it is found that the terrain adjustment improve the prediction performance of MPTER and VALLEY, but do not affect significantly that of ISCST. Overall, it is concluded that the performance of short term atmospheric dispersion models improve when the terrain is considered in computation, especially in MPTER and VALLEY.

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LSTM 기법을 적용한 UTD 데이터 행동 분류 (Classification of Behavior of UTD Data using LSTM Technique)

  • 정겨운;안지민;신동인;원건;박종범
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2018년도 추계학술대회
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    • pp.477-479
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    • 2018
  • 본 연구는 인공신경망의 한 종류인 LSTM(Long Short-Term Memory) 기법을 활용하기 위하여 진행하였다. UTD(University of Texas at Dallas)가 공개한 27종 동작 데이터 중 3축 가속도 및 각속도 데이터를 기본 LSTM 및 Deep Residual Bidir-LSTM 기법에 적용하여 행동을 분류해 보았다.

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