• Title/Summary/Keyword: 독립 성분 분석

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Effects of Processing Temperature and Relative Humidities on the Sausage Cooking Time and Prediction Models of Cooking Time (공정온도와 상대습도가 소시지 쿠킹시간에 미치는 영향 및 쿠킹시간 예측모델)

  • Hur, Sang-Sun;Choi, Yong-Hee
    • Korean Journal of Food Science and Technology
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    • v.22 no.3
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    • pp.325-331
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    • 1990
  • The most important factors in the cooking process which is a main process in the sausage manufacture are cooking temperature and relative humidity. In order to design energy efficient processes in cooking, accurate data for the process parameters are necessary. Therefore, texture profiles were analysed and weight losses were measured at different process conditions of the forementioned factors and at different sizes of sausage, The prediction model for the sausage cooking time was then developed by the SPSS computer program The models were developed as a function of cooking temperature, relative humidity and the diameter of sausage by analyszing the scattergram. Then the model obtained could predict the values within 2.5% error. The higher temperature and relative humidity are the less changes of weight during sausage cooking. As the results of measuring physical properties, the values of hardness and cohesiveness at different temperatures and humidities were so much changed, while the values of elasticity and chewiness had little differences.

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Combined Analysis Using Functional Connectivity of Default Mode Network Based on Independent Component Analysis of Resting State fMRI and Structural Connectivity Using Diffusion Tensor Imaging Tractography (휴지기 기능적 자기공명영상의 독립성분분석기법 기반 내정상태 네트워크 기능 연결성과 확산텐서영상의 트랙토그래피 기법을 이용한 구조 연결성의 통합적 분석)

  • Choi, Hyejeong;Chang, Yongmin
    • Journal of Korea Multimedia Society
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    • v.24 no.5
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    • pp.684-694
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    • 2021
  • Resting-state Functional Magnetic Resonance Imaging(fMRI) data detects the temporal correlations in Blood Oxygen Level Dependent(BOLD) signal and these temporal correlations are regarded to reflect intrinsic cortical connectivity, which is deactivated during attention demanding, non-self referential tasks, called Default Mode Network(DMN). The relationship between fMRI and anatomical connectivity has not been studied in detail, however, the preceded studies have tried to clarify this relationship using Diffusion Tensor Imaging(DTI) and fMRI. These studies use method that fMRI data assists DTI data or vice versa and it is used as guider to perform DTI tractography on the brain image. In this study, we hypothesized that functional connectivity in resting state would reflect anatomical connectivity of DMN and the combined images include information of fMRI and DTI showed visible connection between brain regions related in DMN. In the previous study, functional connectivity was determined by subjective region of interest method. However, in this study, functional connectivity was determined by objective and advanced method through Independent Component Analysis. There was a stronger connection between Posterior Congulate Cortex(PCC) and PHG(Parahippocampa Gyrus) than Anterior Cingulate Cortex(ACC) and PCC. This technique might be used in several clinical field and will be the basis for future studies related to aging and the brain diseases, which are needed to be translated not only functional connectivity, but structural connectivity.

Comparative Study of Data Preprocessing and ML&DL Model Combination for Daily Dam Inflow Prediction (댐 일유입량 예측을 위한 데이터 전처리와 머신러닝&딥러닝 모델 조합의 비교연구)

  • Youngsik Jo;Kwansue Jung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.358-358
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    • 2023
  • 본 연구에서는 그동안 수자원분야 강우유출 해석분야에 활용되었던 대표적인 머신러닝&딥러닝(ML&DL) 모델을 활용하여 모델의 하이퍼파라미터 튜닝뿐만 아니라 모델의 특성을 고려한 기상 및 수문데이터의 조합과 전처리(lag-time, 이동평균 등)를 통하여 데이터 특성과 ML&DL모델의 조합시나리오에 따른 일 유입량 예측성능을 비교 검토하는 연구를 수행하였다. 이를 위해 소양강댐 유역을 대상으로 1974년에서 2021년까지 축적된 기상 및 수문데이터를 활용하여 1) 강우, 2) 유입량, 3) 기상자료를 주요 영향변수(독립변수)로 고려하고, 이에 a) 지체시간(lag-time), b) 이동평균, c) 유입량의 성분분리조건을 적용하여 총 36가지 시나리오 조합을 ML&DL의 입력자료로 활용하였다. ML&DL 모델은 1) Linear Regression(LR), 2) Lasso, 3) Ridge, 4) SVR(Support Vector Regression), 5) Random Forest(RF), 6) LGBM(Light Gradient Boosting Model), 7) XGBoost의 7가지 ML방법과 8) LSTM(Long Short-Term Memory models), 9) TCN(Temporal Convolutional Network), 10) LSTM-TCN의 3가지 DL 방법, 총 10가지 ML&DL모델을 비교 검토하여 일유입량 예측을 위한 가장 적합한 데이터 조합 특성과 ML&DL모델을 성능평가와 함께 제시하였다. 학습된 모형의 유입량 예측 결과를 비교·분석한 결과, 소양강댐 유역에서는 딥러닝 중에서는 TCN모형이 가장 우수한 성능을 보였고(TCN>TCN-LSTM>LSTM), 트리기반 머신러닝중에서는 Random Forest와 LGBM이 우수한 성능을 보였으며(RF, LGBM>XGB), SVR도 LGBM수준의 우수한 성능을 나타내었다. LR, Lasso, Ridge 세가지 Regression모형은 상대적으로 낮은 성능을 보였다. 또한 소양강댐 댐유입량 예측에 대하여 강우, 유입량, 기상계열을 36가지로 조합한 결과, 입력자료에 lag-time이 적용된 강우계열의 조합 분석에서 세가지 Regression모델을 제외한 모든 모형에서 NSE(Nash-Sutcliffe Efficiency) 0.8이상(최대 0.867)의 성능을 보였으며, lag-time이 적용된 강우와 유입량계열을 조합했을 경우 NSE 0.85이상(최대 0.901)의 더 우수한 성능을 보였다.

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The Effect of Body Mass Index, Fat Percentage, and Fat-free Mass Index on Pulmonary Function Test -With Particular Reference to Parameters Derived from Forced Expiratory Volume Curve- (신체질량지수 및 체지방률, 그리고 제지방지수가 폐기능 검사에 미치는 영향 -노력성 호기곡선을 중심으로-)

  • Park, Ji Young;Pack, Jong Hae;Park, Hye Jung;Bae, Seong Wook;Shin, Kyeong Cheol;Chung, Jin Hong;Lee, Kwan Ho
    • Tuberculosis and Respiratory Diseases
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    • v.54 no.2
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    • pp.210-218
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    • 2003
  • Background : Sex specific cross sectional reference values for the lung function indices usually employ a linear model with a term for age and height. The purpose of this study was to determine the effects of the body mass index (BMI), the fat percentage of the body mass and the fat-free mass index (FFMI) on the forced expiratory volume curve. Methods : Between January 2000 and December 2001, a total of 300 subjects, 150 men and 150 women (mean age : $45{\pm}13$ years), with a normal lung function were enrolled in the study sample. This study measured the $FEV_1$, FVC and $FEF_{25-75%}$ from the forced expiratory volume curve by a spirometer and the body composition by a bioelectrical impedance method in all subjects. Multiple regression analysis was used in order to examine the effects of the body composition on the parameters derived from the forced expiratory volume curve. Results : After adjusting for age, the BMI and Fat percentage improved the descriptions of the FVC (p<0.05, $r^2=0.491$) and $FEV_1$ (p<0.05, $r^2=0.654$) in women. In contrast, the FFMI contributed significantly to the FVC (p<0.05, $r^2=0.432$) and $FEV_1$ (p<0.05, $r^2=0.567$) in men. The $FEF_{25-75%}$ correlated with the fat percentage in women (p<0.05, $r^2=0.337$). Conclusion : These results suggest that the BMI, the fat percentage and the FFMI are significant determinants of the forced expiratory volume curve. The plmonary function test, when considering the BMI, the fat percentage and the FFMI, might be useful in clinical applications.

A PN-code Acquisition method Using Array Antenna Systems for CDMA2000 1x (CDMA2000 1x용 배열 안테나 시스템에서 PN 동기 획득 방법)

  • Jo, Hee-Nam;Yun, Yu-Suk;Choi, Seung-Won
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.42 no.8 s.338
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    • pp.33-40
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    • 2005
  • This paper presents a structure of the searcher using a diversity in array antenna systems operating in the cdma2000 1x signal environments. The new technique exploits the fact that the In-phase and quadrature components of interferers can respectively be viewed as an independent gaussian noise at each antnna element in most practical cdma signal environments. The proposed PN acquisition scheme is a singles-dwell PN acquisition system consisting of two stages, that is, the searching stage and the verification stage. The searching stage independently correlates the receiver multiple signals with PN generator of each antenna element for obtaining the synchronous energy at the entire region. Then, the searching results of each antenna element are non-coherently combinind. The verification stage compares the searching energy with the optimal threshold, which is predesigned in the lock detector, and decides whether the acquisition is successful or fail. In this paper, we analyzed the effect of tile diversity order to determine the mean acquisition time. In general, it is known that the mean acquisition time significantly decrease as the number of antenna elements increases. But, as the diversity order goes up, the enhancement of the performance is saturated. Therefore, to decrease the mean acquisition time of the searcher, we must design the optimal array antenna systems by considering the operating SNR range of the receiver, the probability of detection $P_D$ and that of false alarm $P_{FA}$ . The Performance of the proposed PN acquisition scheme is analyzed in frequency selective Rayleigh fading channels. In this paper, the effect of the number of antenna elements on PN acquisition scheme is shown according to the probability of detection $P_D$ and that of false alarm $P_{FA}$.

Optimization of Fermentation Conditions for Burdock Vinegar Using Response Surface Methodology (반응표면분석법을 이용한 우엉식초 발효조건 최적화)

  • Kim, Yi-Seul;Kim, Seong-Ho
    • Journal of the Korean Society of Food Science and Nutrition
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    • v.46 no.8
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    • pp.986-996
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    • 2017
  • In this study, we optimized fermentation conditions for burdock vinegar by response surface methodology. We confirmed the fermentation characteristics and major components of burdock vinegar. Alcohol fermentation of burdock extract added with 15% apple concentrates for vinegar production was performed. Consequently, 6.4% alcohol was produced after 5 days of fermentation. Central composite design was applied to investigate the effects of two independent variables, fermentation time (5~17 days; X1) and fermentation temperature ($26{\sim}34^{\circ}C$; X2), on fermentation of burdock vinegar. Fermentation conditions were optimized using characteristics of fermentation broth as a dependent variable. Acetic acid contents of dependent variables were 3.85~4.73% during acetic acid fermentation. The correlation coefficient ($R^2$) of the derived equation from the response surface regression for acetic acid contents was 0.9850 with significance level of 1%. Arctiin contents of all fermentation samples were 0.37~0.50 mg/100 mL, with an $R^2$ value of 0.8380 and significance level of 5%. We elicited a regression equation for each variable and superimposed the optimum area of fermentation conditions for characteristics and effective constituent contents of the fermentation broth. The predicted values for the optimum fermentation conditions for burdock vinegar were at $31^{\circ}C$ and 16 days.

Study of Optimized Simultaneous Extraction Conditions for Active Component of Ginseng Berry using Response Surface Methodology (반응표면분석을 이용한 진생베리의 활성 성분 최적 추출 조건에 관한 연구)

  • Go, Hee Kyoung;Park, Junseong
    • Journal of the Society of Cosmetic Scientists of Korea
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    • v.46 no.2
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    • pp.185-194
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    • 2020
  • This study was conducted to find out the optimal extraction conditions to obtain extracts with a high content of ginsenosides and antioxidant activity using the ginseng berry. After extraction by stirring, ultrasound and microwave method using 70% ethanol and distilled water as solvents, the results of considering the content of ginsenoside Re and Rb1, total polyphenol content, antioxidant activity, and whether it is an environmentally friendly manufacturing method, it was confirmed that the microwave method using distilled water is good method of extraction. The optimization of extraction conditions for microwave method were made by response surface methodology (RSM). Microwave power (50 ~ 200 W, X1), solvent and ginseng berry ratio (5 ~ 20 times, X2) and the extraction time (30 ~ 120 s, X3) were used as independent variables. The model showed a good fit having a determination coefficient of the regression equation of 0.9 or more and a p-value less than 0.05. Estimated conditions for the maximized extraction of ginsenoside contents and total polyphenols were 200 w in microwave power, 20 times in solvent and ginseng berry ratio, and 90 s in extraction time. Predicted values at the optimum conditions were total polyphenols of 6.23 mg GAE/g, ginsenoside Re of 17.69 mg/g, and ginsenoside Rb1 of 16.01 mg/g. In the verification of the actual measurement the obtained values showed 6.33 mg GAE/g, 17.79 mg/g, and 15.59 mg/g, respectively, in good agreement with predicted values.

Extraction of Antioxidants from Lonicera japonica and Sophora japonica L.: Optimization Using Central Composite Design Model (금은화와 회화나무꽃으로부터 항산화성분의 추출 : 중심합성계획모델을 이용한 최적화)

  • Han, Kyongho;Zuo, Chengliang;Hong, In Kwon
    • Applied Chemistry for Engineering
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    • v.30 no.3
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    • pp.337-344
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    • 2019
  • In this study, an antioxidant was extracted from Lonicera japonica and Sophora japonica L, which was optimized by using the central composite design (CDD) model of response surface methodology (RSM). The response value of CDC model establishes the extraction yield and the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity. The extraction time, volume ratio of ethanol/ultrapure water, and extraction temperature were selected as quantitative factors. According to the result of CDC, optimal extraction conditions of Lonicera japonica were as follows; the extraction time of 2.08 h, volume ratio of ethanol/ultrapure water of 41.53 vol.%, and extraction temperature of $55.08^{\circ}C$. At these conditions the expected results indicated that the yield and DPPH radical scavenging activity were estimated as 37.88 wt% and 40.37%, respectively. On the other hand, optimal extraction conditions of Sophora japonica L. could be found as the extraction time of 2.13 h, volume ratio of ethanol/ultrapure water of 62.89 vol.%, and temperature of $50.42^{\circ}C$. Under the conditions, the (possible) maximum values of yield and DPPH radical scavenging activity were found as 35.43 wt% and 55.7%, respectively.

Dermal Papilla Cells Proliferation Constituent of Schisandra chinensis Fruits and Optimization Using Response Surface Methodology (오미자의 모유두세포 증식 활성성분과 반응표면분석을 이용한 추출조건의 최적화)

  • Cho, Hyun Dae;Jeong, JiYeon;Ryu, Hwa Sun;Lee, JungNo;Park, Sung-Min
    • Journal of the Society of Cosmetic Scientists of Korea
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    • v.46 no.4
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    • pp.415-424
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    • 2020
  • In the present study, we have refined gomisin N, which represents activity in the proliferation of dermal papilla cells (HFDPCs) from the fruit of Schisandra chinensis (S. chinensis), and have identified optimal extraction conditions for obtaining extracts with high content of gomisin N. The activity of the extracts and fractions was evaluated, and the results indicated approximately 29% proliferation activity in the group treated with 1 ㎍/mL of n-hexane fraction. Column chromatography was used to assess the active ingredient in the n-hexane fraction, and two compounds, namely gomisin N(1) and schisandrin(2), were isolated and identified. When the HFDPCs proliferation activity was tested for the isolated compounds, gomisin N exhibited ≥ 20% proliferation activity. Thus, via response surface methodology (RSM), the optimum extraction conditions to obtain the maximum level of gomisin N from the fruit of S. chinensis were determined, where ethanol proportion, extraction time, and extraction temperature were used as the independent variables. The results revealed coefficient of determination ≥ 0.95 and p-value ≤ 0.05, which confirmed the fit of the model. The optimum extraction conditions to achieve the maximum content of gomisin N were as follows: ethanol proportion 83.8%, extraction temperature 80 ℃, and extraction time 8.7 h. The content of gomisin N using these conditions was predicted as 378,300 ppm, and a mean value close to the predicted value (376,884 ppm) was obtained while validating the aforementioned conditions.

The Process Control Using Modeling Technique in A2O Sewage Treatment Process (모델링기법을 이용한 A2O 하수처리공정에서 주요 공정관리에 관한 연구)

  • Park, Jung Soo;Kim, Sung Duk;Seung, Dho Hyon
    • Journal of Korean Society of Disaster and Security
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    • v.13 no.2
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    • pp.65-75
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    • 2020
  • The efficiency of sewage treatment was ananlyzed selecting a sewage treatment plant in Gyeonggi-do where A2O process was applied. Statistical techniques based on the operation data of the sewage treatment were used. The main factors directly affecting the efficiency of the treatment process were analyzed using a GPS-X model. The correlation analysis and one-way ANOVA were performed. The T-N and NH4+-N values of the effluent did not generate statistically significant level (p-value:>0.05) when compared with C/N ration values. Removel of nitrogen components form sewage treatment plants were affected by temperature, HRT, SRT and DO. In the case of BOD, all operating factors were affected, while COD was affecte by factors of HRT, STR and DO. In simulations using GPS-X, the parameters that greatly influence was included the maximum sedimentation rate, the dependent nutrient microbial yield (anoxic), the phosphorus saturation coefficient, the dependent nutrient microbial killing rate, the dependent nutrient microbial maximum growth rate, and the independent trophic microorganisms. The maximum growth rate and the maximum setting rate were identified.