• 제목/요약/키워드: Food prediction

검색결과 490건 처리시간 0.024초

시중 즉석 조리 면의 Back Extrusion 텍스처 데이터에 대한 Partial Least Square Regression 분석 (Analysis of Partial Least Square Regression on Textural Data from Back Extrusion Test for Commercial Instant Noodles)

  • 김수경;이승주
    • 산업식품공학
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    • 제14권1호
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    • pp.75-79
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    • 2010
  • 시중 즉석 면류의 관능적 성질과 back extrusion test 데이터에 대하여 partial least square regression(PLSR)을 실시하였다. 즉석유탕면 8종과 즉석비유탕면 2종에 대한 관능적 속성으로서 경도(A), 탄성(B), 껄끄러운 정도(C), 이에 박히는 정도(D), 굵기감(E)를 검사하였고, 실험 데이터로 힘-변형 곡선 전체를 사용하였다. PLSR의 회귀계수는 힘-변형곡선의 압착단계, 항복단계, 압출단계로 크게 구분되어 각관능속성에 대한 특유의 양 또는 음의 효과를 나타냈다. PLSR의 상관계수는 E>D>A>B>C, 오차(root mean square error of prediction expressed in sensory units)는 D>C>E>B>A, 예측능(relative ability of prediction)는 D>C>E>B>A 로 나타나 종합적으로 '이에 박히는 정도'가 PLSR의 적용에 가장 우수하게 나타났다. '경도'는 예측능은 낮았지만 상관성은 높아서 시료간 순위의 결정에 합당하게 평가되었다.

식품의 동결시간 예측 및 동결시간에 영향을 미치는 요인에 관한 연구 (Studies on the Freezing Time Prediction and Factors Influencing Freezing Time Prediction)

  • 공재열;정진웅;김민용
    • 한국식품과학회지
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    • 제20권6호
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    • pp.827-833
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    • 1988
  • 본 연구는 식품의 동결시간에 영향을 미치는 요인에 대해 비교 검토하고. 시료 두께에 따른 동결시간 예측 모델을 유도하기 위해 정지공기식 동결법을 이용하여 피조개 등 4종의 시료에 대하여 실험하였다. 그 결과, 시료의 두께가 두꺼울수록, 표면열전달계수 및 초기온도에 의한 영향은 상당히 급증하였으며, 표면열전달계수의 값이 낮을수록 시료 두께에 미치는 영향은 크며. $150W/m^2^{\circ}C$ 이상에서는 동결시간에 미치는 영향이 거의 유사하게 나타났다. 또한 각 시료에 있어 초기 빙결점이 낮을수록 초기 수분함량이 많을수록, 밀도가 높을수록 동결시간이 길게 나타났고. 열적 물성치의 영향은 밀도, 수분함량, 비열 및 열전도도의 순으로 나타났다. 그리고 시료 초기온도, 초기 빙결점, 동결매체 온도에 따른 시료 두께별 동결 시간을 예측할 수 있는 중직선 회귀방정식을 유도한 결과 실험치와 비교하여 ${\pm}5%$의 오차를 보여 주었다.

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농림수산식품분야 정보처리를 위한 적응하는 분기히스토리 길이를 갖는 분기예측 메커니즘 (A Branch Prediction Mechanism With Adaptive Branch History Length for FAFF Information Processing)

  • 고광현;조영일
    • 현장농수산연구지
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    • 제13권1호
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    • pp.3-17
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    • 2011
  • Pipelines of processor have been growing deeper and issue widths wider over the years. If this trend continues, branch misprediction penalty will become very high. Branch misprediction is the single most significant performance limiter for improving processor performance using deeper pipelining. Therefore, more accurate branch predictor becomes an essential part of modem processors for FAFF(Food, Agriculture, Forestry, Fisheries)Information Processing. In this paper, we propose a branch prediction mechanism, using variable length history, which predicts using a bank having higher prediction accuracy among predictions from five banks. Bank 0 is a bimodal predictor which is indexed with the 12 least significant bits of the branch PC. Banks 1,2,3 and 4 are predictors which are indexed with different global history bits and the branch PC. In simulation results, the proposed mechanism outperforms gshare predictors using fixed history length of 12 and 13, up to 6.34% in prediction accuracy. Furthermore, the proposed mechanism outperforms gshare predictors using best history lengths for benchmarks, up to 2.3% in prediction accuracy.

식품용수 수질자료를 이용한 지하수 오염 예측 모델 개발 및 소규모 유역에서의 검증 (Development of Prediction Model of Groundwater Pollution based on Food Available Water and Validation in Small Watersheds)

  • 남성우;박은규;이명재;전선금;정혜민;김정우
    • 한국지하수토양환경학회지:지하수토양환경
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    • 제26권6호
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    • pp.165-175
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    • 2021
  • Groundwater is used in many areas in food industry such as food manufacturing, food processing, cooking, and liquor industry etc. in Korea. As groundwater occupies a large portion of food industry, it is necessary to predict deterioration of water quality to ensure the safety of food water since using undrinkable groundwater has a ripple effect that can cause great harm or anxiety to food users. In this study, spatiotemporal data aggregation method was used in order to obtain spatially representative data, which enable prediction of groundwater quality change in a small watershed. In addition, a highly reliable predictive model was developed to estimate long-term changes in groundwater quality by applying a non-parametric segmented regression technique. Two pilot watersheds were selected where a large number of companies use groundwater for food water, and the appropriateness of the model was assessed by comparing the model-produced values with those obtained by actual measurements. The result of this study can contribute to establishing a customized food water management system utilizing big data that respond quickly, accurately, and preemptively to changes in groundwater quality and pollution. It is also expected to contribute to the improvement of food safety management.

초등학교 운동선수를 대상으로 대표 신체활동의 에너지 소비량 및 활동 강도 추정을 위한 가속도계의 정확도 검증 (Accuracy of Accelerometer for the Prediction of Energy Expenditure and Activity Intensity in Athletic Elementary School Children During Selected Activities)

  • 최수지;안해선;이모란;이정숙;김은경
    • 대한지역사회영양학회지
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    • 제22권5호
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    • pp.413-425
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    • 2017
  • Objectives: Accurate assessment of energy expenditure is important for estimation of energy requirements in athletic children. The objective of this study was to evaluate the accuracy of accelerometer for prediction of selected activities' energy expenditure and intensity in athletic elementary school children. Methods: The present study involved 31 soccer players (16 males and 15 females) from an elementary school (9-12 years). During the measurements, children performed eight selected activities while simultaneously wearing the accelerometer and carrying the portable indirect calorimeter. Five equations (Freedson/Trost, Treuth, Pate, Puyau, Mattocks) were assessed for the prediction of energy expenditure from accelerometer counts, while Evenson equation was added for prediction of activity intensity, making six equations in total. The accuracy of accelerometer for energy prediction was assessed by comparing measured and predicted values, using the paired t-test. The intensity classification accuracy was evaluated with kappa statistics and ROC-Curve. Results: For activities of lying down, television viewing and reading, Freedson/Trost, Treuth were accurate in predicting energy expenditure. Regarding Pate, it was accurate for vacuuming and slow treadmill walking energy prediction. Mattocks was accurate in treadmill running activities. Concerning activity intensity classification accuracy, Pate (kappa=0.72) had the best performance across the four intensities (sedentary, light, moderate, vigorous). In case of the sedentary activities, all equations had a good prediction accuracy, while with light activities and Vigorous activities, Pate had an excellent accuracy (ROC-AUC=0.91, 0.94). For Moderate activities, all equations showed a poor performance. Conclusions: In conclusion, none of the assessed equations was accurate in predicting energy expenditure across all assessed activities in athletic children. For activity intensity classification, Pate had the best prediction accuracy.

Prediction for Quality Traits of Porcine Longissimus Dorsi Muscle Using Histochemical Parameters

  • Ryu, Youn-Chul;Choi, Young-Min;Kim, Byoung-Chul
    • Food Science and Biotechnology
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    • 제14권5호
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    • pp.628-633
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    • 2005
  • Muscle fiber characteristics were evaluated for predictability of meat quality traits using 231 crossbred pigs. Muscle $pH_{45min}$, R-value, and $pH_{24hr}$ were selected to estimate regression equation model of drip loss and lightness, although variances of coefficient estimates could only account for small part of drip loss (about 16.3 to 25.3%) and lightness (about 16.9 to 31.7%). Muscle $pH_{24hr}$ was represented to drip loss and lightness, which explained corresponding 25.3 and 31.7% of estimation in drip loss and lightness, respectively. Area percentage of type IIb fiber significantly contributed to prediction of metabolic rate and meat quality. However, equations predicting meat quality traits based on area percentage of type IIb fiber alone are less useful than ones based on early postmortem parameters. These results suggest estimated model using both metabolic properties of muscle and postmortem metabolic rate could be used for prediction of pork quality traits.

A Comparative Study Between Linear Regression and Support Vector Regression Model Based on Environmental Factors of a Smart Bee Farm

  • Rahman, A. B. M. Salman;Lee, MyeongBae;Venkatesan, Saravanakumar;Lim, JongHyun;Shin, ChangSun
    • 스마트미디어저널
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    • 제11권5호
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    • pp.38-47
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    • 2022
  • Honey is one of the most significant ingredients in conventional food production in different regions of the world. Honey is commonly used as an ingredient in ethnic food. Beekeeping is performed in various locations as part of the local food culture and an occupation related to pollinator production. It is important to conduct beekeeping so that it generates food culture and helps regulate the regional environment in an integrated manner in preserving and improving local food culture. This study analyzes different types of environmental factors of a smart bee farm. The major goal of this study is to determine the best prediction model between the linear regression model (LM) and the support vector regression model (SVR) based on the environmental factors of a smart bee farm. The performance of prediction models is measured by R2 value, root mean squared error (RMSE), and mean absolute error (MAE). From all analysis reports, the best prediction model is the support vector regression model (SVR) with a low coefficient of variation, and the R2 values for Farm inside temperature, bee box inside temperature, and Farm inside humidity are 0.97, 0.96, and 0.44.

수분활성과 온도변화에 따른 커피의 흡착특성 및 흡착량 예측모델 (Adsorption Characteristics and Moisture Content Prediction Model of Coffee with Water Activity and Temperature)

  • 윤광섭;최용희
    • 한국식품과학회지
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    • 제22권6호
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    • pp.690-695
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    • 1990
  • 커피의 저장 중 흡착에 가장 많은 영향을 미치는 인자로는 수분활성 및 온도이다. 따라서 커피의 제조공정 중 추출시 건조방법의 차이에 따른 세 종류의 제품에 대한 흡착 특성을 조사하고 수분활성, 온도 및 시간의 변화에 따른 흡착량을 측정하여 조건변수의 변화에 따른 흡착량의 변화를 예측할 수 있는 예측모델식을 수립하였다. 흡착거동은 전형적인 Sigmoid 형태를 나타냈으며 평형수분함량과 단분자층 수분함량은 동결 건조제품이 가장 높게 나타났으며 이는 건조방법에 의해 생성된 다공성구조에 기인된 것으로 사료된다. 기 발표된 여러 형태의 등온흡착곡선 모델식에 적용시켜 본 결과 Halsey 모델식의 상관계수 r값이 $0.98{\sim}0.99$로 가장 적합하였다. 또한 예측모델식은 SPSS COMPUTER PROGRAM을 이용하여 가장 오차가 적은 범위에서 수분활성, 온도 및 시간의 변화에 따른 흡착량의 변화를 예측할 수 있는 최종적인 모델식을 수립하였다.

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