• 한국식품과학회지
• /
• 제22권3호
• /
• pp.325-331
• /
• 1990

소시지의 세조공정 중의 주 공정인 쿠킹공정에서 가장 영향을 많이 미치는 인자는 쿠킹온도와 상대습도이다. 따라서 쿠킹공정에서 에너지의 효율성을 높이기 위해 상기 인자와 소시지 직경의 변화에 따른 쿠킹시간을 측정하여 쿠킹시간 예측모델식을 수립하였다. 또한 쿠킹 전후의 일반성분 분석과 중량변화 및 각 온도와 상대습도에서의 TPA 분석을 하였다. 쿠킹시간 예측모델식을 SPSS computer program을 이용하여 가장 오차가 적은 범위에서의 예측모델식을 얻었다. 쿠킹시간 예측모델식을 쿠킹온도와 상대습도와 소시지 직경에 대한 각각의 함수관계를 Scattergram을 작성하여 R-square값을 가장 높은 함수를 취하여 각각의 모델식을 수립한 후 독립변수와의 관계를 종합하여 예측값을 구할 수 있는 최종적인 예측모델식을 수립하였다. 또한 소시지 직경 1.5cm에 대한 쿠킹 동안 중량변화는 온도와 상대습도가 적게 소모되어 소시지의 중량변화가 적게 일어남을 알 수 있었다. 물성치를 측정해 본 결과 온도와 상대습도의 변화에 따른 경도와 응집력의 값은 크게 변화가 일어났으나 반면에 탄성과 저작성의 값은 그 변화가 다소 적게 일어남을 알 수 있었다.

• 한국농공학회지
• /
• 제41권6호
• /
• pp.44-53
• /
• 1999

The statistical characteristics of the factors related to the daily rainfall prediction model are analyzed . Records of daily precipitation, mean air temperature, relative humidity , dew-point temperature and air pressure from 1973∼1998 at 8 meteorological sttions in south-western part of Korea were used. 1. Serial correlatino of daily precipitaiton was significant with the lag less than 1 day. But , that of other variables were large enough until 10 day lag. 2. Crosscorrelation of air temperature, relative humidity , dew-point temperature showed similar distribution wiht the basin contrours and the others were different. 3. There were significant correlation between the meteorological variables and precipitation preceded more than 2 days. 4. Daily preciption of each station were treated as a truncated continuous random variable and the annual periodic components, mean and standard deviation were estimated for each day. 5. All of the results could be considered to select the input variables of regression model or neural network model for the prediction of daily precipitation and to construct the stochastic model of daily precipitation.

• 한국농업기계학회:학술대회논문집
• /
• 한국농업기계학회 2017년도 춘계공동학술대회
• /
• pp.135-135
• /
• 2017

Greenhouse have been developed to provide the plants with good environmental conditions for cultivation crop, two major factors of which are the inside air temperature and humidity. The inside temperature are influenced by the heating systems, ventilators and for systems among others, which in turn are geverned by some type of controller. Likewise, humidity environment is the result of complex mass exchanges between the inside air and the several elements of the greenhouse and the outside boundaries. Most of the existing models are based on the energy balance method and heat balance equation for modelling the heat and mass fluxes and generating dynamic elements. However, greenhouse are classified as complex system, and need to make a sophisticated modeling. Furthermore, there is a difficulty in using classical control methods for complex process system due to the process are non linear and multi-output(MIMO) systems. In order to predict the time evolution of conditions in certain greenhouse as a function, we present here to use of recurrent neural networks(RNN) which has been used to implement the direct dynamics of the inside temperature and inside humidity of greenhouse. For the training, we used algorithm of a backpropagation Through Time (BPTT). Because the environmental parameters are shared by all time steps in the network, the gradient at each output depends not only on the calculations of the current time step, but also the previous time steps. The training data was emulated to 13 input variables during March 1 to 7, and the model was tested with database file of March 8. The RMSE of results of the temperature modeling was $0.976^{\circ}C$, and the RMSE of humidity simulation was 4.11%, which will be given to prove the performance of RNN in prediction of the greenhouse environment.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제53권5호
• /
• pp.374-379
• /
• 2004

This paper proposes an algorithm for human sensibility evaluation using 4-channel EEG signals of the prefrontal and the parietal lobes. The algorithm uses an artificial neural network and the multiple templates. The linear prediction coefficients are used as the feature parameters of human sensibility. Comfortableness for chairs and temperature/humidity are evaluated. Many conventional researches have emphasized that a wave of left prefrontal lobe is activated in case of positive sensibility and that of right prefrontal lobe is activated in case of negative sensibility. So the power ratio of a wave is obtained from FFT computation and the results are compared. The results of the comfortableness evaluation for temperature and humidity showed that the outputs of the proposed algorithm coincided with corresponding sensibilities depending on the task of the temperature and the humidity. The . conventional method using a wave is hardly related with comfortableness. And it is also observed that the uncomfortable state due to the high temperature and humidity can be easily changed to the comfortable state by small drop of the temperature and the humidity. It seems to be good results to get 66.7％ of evaluation performance in spite of using EEG and the subject independent approach.

• 마이크로전자및패키징학회지
• /
• 제20권3호
• /
• pp.7-10
• /
• 2013

This study presents an approach to predict insulation resistance failure of multilayer ceramic capacitors (MLCCs) using non-linear modeling. A capacitance aging model created by non-linear modeling allowed for the prediction of insulation resistance failure. The MLCC data tested under temperature-humidity-bias testing conditions showed that a change in capacitance, when measured against a capacitance aging model, was able to provide a prediction of insulation resistance failure.

• 한국콘텐츠학회논문지
• /
• 제11권11호
• /
• pp.42-48
• /
• 2011

본 논문에서는 교량구간의 도로 결빙예측 및 감지를 위한 시스템 설계를 제안하였다. 센서 노드의 하드웨어는 마이크로프로세서, 온도 센서, 습도 센서, 그리고 Zigbee 무선 통신으로 구성되었다. 관제센터의 소프트웨어는 관제센터에 수집된 교량 온도, 습도 데이터로 관찰하기 위하여 구현되었다. 교량 노면의 결빙은 노면의 온도가 이슬점 온도 이하이면서 영하일 때 발생한다. 제안된 시스템을 이용하여 도로면의 온도 및 습도 분포를 측정하였다. 측정 데이터는 도로 결빙이 발생하는 시점을 예측하기 위하여 사용되었다. 실제 결빙되는 것보다 최소 30분 이전에 결빙시점을 예측하여 경고가 이루어진다. 이 결과로 결빙으로 인한 교통사고를 방지하기 위하여 사용 할 수 있다.

• 한국건축시공학회:학술대회논문집
• /
• 한국건축시공학회 2021년도 가을 학술논문 발표대회
• /
• pp.158-159
• /
• 2021

When the porous concrete is exposed to the external environment, the internal relative humidity changes from time to time due to the inflow and outflow of moisture. This change in moisture is affected by temperature. The temperature and humidity of concrete is dominant in the carbonation rate, the largest cause of deterioration of concrete. In this study, actual weather data were used as boundary conditions. A carbonization model of concrete temperature and humidity and calcium hydroxide was constructed to perform long-term analysis. There is a slight error in the carbonation formula of the Japanese Academy of Architecture applying the Kishtani coefficient, a representative experimental formula related to carbonization, and the analysis result values. However, considering that it behaves very similarly, it is thought that a fairly reliable numerical analysis model has been established. A slight error is believed to be due to the fact that the amount of residual calcium hydroxide in the carbonated site has not yet been clearly identified.

• 한국대기환경학회지
• /
• 제14권3호
• /
• pp.177-190
• /
• 1998

The concentrations of air pollutants In large cities such as Pusan area have been increased every year due to the increasing of fuels consumption at factories and by vehicles as well as the gravitation of the population. In addition to the pollution sources, time and spatial variation of air pollutants concentration and meteorological factors have a great influence on the air pollution problem. Especially , its concentration is governed by wind direction, wind speed, precipitation, solar radiation, temperature, humidity and cloud amounts, etc. In this study, we have analyzed various data of meteorological factors using typical patterns of the air pressure to investigate how the concentration of air pollutants is varied with meteorological condition. Using the relationship between meteorological factors (air temperature, relative humidity, wind speed and solar radiation) and the concentration of air pollutants (SO2, O3) , experimental prediction formulas for their concentration were obtained. Therefore, these prediction formulas at each meteorological factor in a pressure pattern may be roughly used to predict the air pollutants concentration and contributed to estimate the variation of its value according to the weather condition in Pusan city.

• 대기
• /
• 제27권2호
• /
• pp.235-249
• /
• 2017

This paper describes methodology verifying near-surface predictability of numerical weather prediction models against the surface synoptic weather station network (SYNOP) observation. As verification variables, temperature, wind, humidity-related variables, total cloud cover, and surface pressure are included in this tool. Quality controlled SYNOP observation through the pre-processing for data assimilation is used. To consider the difference of topographic height between observation and model grid points, vertical inter/extrapolation is applied for temperature, humidity, and surface pressure verification. This verification algorithm is applied for verifying medium-range forecasts by a global forecasting model developed by Korea Institute of Atmospheric Prediction Systems to measure the near-surface predictability of the model and to evaluate the capability of the developed verification tool. It is found that the verification of near-surface prediction against SYNOP observation shows consistency with verification of upper atmosphere against global radiosonde observation, suggesting reliability of those data and demonstrating importance of verification against in-situ measurement as well. Although verifying modeled total cloud cover with observation might have limitation due to the different definition between the model and observation, it is also capable to diagnose the relative bias of model predictability such as a regional reliability and diurnal evolution of the bias.

• 한국포장학회지
• /
• 제4권1호
• /
• pp.23-32
• /
• 1997

The change in moisture content of moisture sensitive products in moisture-semipermeable packages was investigated for the purpose of predicting the shelf life of a product-package combination. A mathematical model, and a computer program based on the physiochemical properties of the product and the moisture permeability of the package was developed. The moisture content for products in moisture-semipermeable packages was determined under various environmental conditions and the results were compared with the predicted values by means of the simulation model. These experimental studies demonstrated that the prediction of the change in moisture content of packaged products over time by the simulation model is accurate, within a practical range of temperature and relative humidity values. The developed semi-empirical model is considered to have applications in industry, since it provides product shelf life information for a range of temperature and relative humidity conditions, with a limited number of experimentally obtained data points.