• Title/Summary/Keyword: Prediction density

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Study on the Modeling Technique for Prediction about Pressure Drop of an Intravenous Lung Assist Device (혈관 내 폐 보조장치의 압력손실 예측을 위한 모델링기법에 관한 연구)

  • 김기범;권대규;정경락
    • Journal of Biomedical Engineering Research
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    • v.24 no.4
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    • pp.293-299
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    • 2003
  • In this paper, the correlation of Pressure drop about the Newtonian and non-Newtonian fluid was investigated experimentally for vibrating intravascular lung assist device (VIVLAD) and we determined correlation equation to make a prediction about Pressure drop for designing VIVLAD. Design conditions to predict the pressure drop of the modules were studied through an experimental modeling before inserting the artificial lung assist device into as venous. Experiments were performed by distilled water, glycerol/water mixed solution(40% glycerol) of Newtonian fluids. and the bovine blood of non-Newtonian fluids. These fluids were flowed outside and parallel of hollow fiber membranes. Also we measured pressure drop according to the number of the fiber membranes which ware inserted into the inside diameter of shell of 3 cm, and developed the prediction equations by curve fitting method based on correlation between the experimental pressure drop and the frontal area or the packing density of device. The result showed that the Pressure drop and the friction factor of the water/glycerol mixed solution were similar to that of bovine blood. It was showed that the water/glycerol mixed solution (40% glycerol) could be used for measuring the pressure drop and the friction factor instead of the bovine blood. Also, we could estimate the prediction equation of pressure drop and friction factor as the function of Packing density at the number of hollow fibers. We obtained the reliance of the prediction equations because the pressure drop and the friction factor measured from the experiments were similar to that from the prediction equation. These results may be used to further usefulness for the design of VIVLAD.

High Efficiency Life Prediction and Exception Processing Method of NAND Flash Memory-based Storage using Gradient Descent Method (경사하강법을 이용한 낸드 플래시 메모리기반 저장 장치의 고효율 수명 예측 및 예외처리 방법)

  • Lee, Hyun-Seob
    • Journal of Convergence for Information Technology
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    • v.11 no.11
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    • pp.44-50
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    • 2021
  • Recently, enterprise storage systems that require large-capacity storage devices to accommodate big data have used large-capacity flash memory-based storage devices with high density compared to cost and size. This paper proposes a high-efficiency life prediction method with slope descent to maximize the life of flash memory media that directly affects the reliability and usability of large enterprise storage devices. To this end, this paper proposes the structure of a matrix for storing metadata for learning the frequency of defects and proposes a cost model using metadata. It also proposes a life expectancy prediction policy in exceptional situations when defects outside the learned range occur. Lastly, it was verified through simulation that a method proposed by this paper can maximize its life compared to a life prediction method based on the fixed number of times and the life prediction method based on the remaining ratio of spare blocks, which has been used to predict the life of flash memory.

Prediction of Permeation Flux and Sorption Characteristics of Volatile Organic Solvents on PDMS Membrane (휘발성 유기용매의 PDMS막에 대한 투과 플럭스와 수착특성 예측)

  • 오한기;장화익;이광래
    • Membrane Journal
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    • v.10 no.1
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    • pp.30-38
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    • 2000
  • Prediction method of permeation flux and sorption characteristics in pervaporation through a polydimethylsiloxane(PDMS) memrane was suggested. The amount of sorption and permeation flux of chloroform, toluene, methanol and n-butanol were calculated with this method and compared with this method and compared with experimetal data. The calculated values of permeation flux and the amount of sorption of good solvents, that is, toluene and chloroform were well agreed with the experimental data. The lower the density of PDMS membrane is, the more permeation flux and sorption quantity were increased. However, the experimental data of poor solvents, that is, methanol and n-butanol were no so well agreed with the calculated values. It is shown that the prediction method suggested in this study may be used without experimetnal for the prediction of permeation flux and sorption quantity of the good solvent on PDMS membrane.

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Treatment of cutting-oily wastewater by electrocoagulation-flotation (ECF) process: Modeling approach

  • Chawaloesphosiya, Nattawin;Mongkolnauwarat, Jittrapa;Prommajun, Chayanin;Wongwailikhit, Kritchart;Painmanakul, Pisut
    • Environmental Engineering Research
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    • v.20 no.4
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    • pp.392-396
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    • 2015
  • This work aims to investigate the oily wastewater treatment by the electrocoagulation-flotation (ECF) and propose a mathematical model for the efficiency prediction. Cutting oil was used to prepare the synthetic oily wastewater with submicron droplet sizes. The chemical coagulation by aluminium sulfate was firstly tested following by the electrocoagulation-flotation with aluminium electrodes. Both processes gave the effective treatment performance with the efficiencies higher than 90%. However, the ECF consumed less aluminium dosage as well as produced less sludge, which were its advantage on the chemical coagulation. The performance of the ECF was found to be affected by the current density, oil concentration, and reaction time according to the analysis by the design of experiment (DOE). Finally, the prediction model was proposed by two approaches, including linear and logarithm function. The latter model gave more accuracy prediction results in terms of treatment efficiency and duration in the lag and stable stages.

Empirical Bayesian Prediction Analysis on Accelerated Lifetime Data (가속수명자료를 이용한 경험적 베이즈 예측분석)

  • Cho, Geon-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.8 no.1
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    • pp.21-30
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    • 1997
  • In accelerated life tests, the failure time of an item is observed under a high stress level, and based on the time the performances of items are investigated at the normal stress level. In this paper, when the mean of the prior of a failure rate is known in the exponential lifetime distribution with censored accelerated failure time data, we utilize the empirical Bayesian method by using the moment estimators in order to estimate the parameters of the prior distribution and obtain the empirical Bayesian predictive density and predictive intervals for a future observation under the normal stress level.

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Incidence, Risk Factors, and Prediction of Myocardial Infarction and Stroke in Farmers: A Korean Nationwide Population-based Study

  • Lee, Solam;Lee, Hunju;Kim, Hye Sim;Koh, Sang Baek
    • Journal of Preventive Medicine and Public Health
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    • v.53 no.5
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    • pp.313-322
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    • 2020
  • Objectives: This study was conducted to determine the incidence and risk factors of myocardial infarction (MI) and stroke in farmers compared to the general population and to establish 5-year prediction models. Methods: The farmer cohort and the control cohort were generated using the customized database of the National Health Insurance Service of Korea database and the National Sample Cohort, respectively. The participants were followed from the day of the index general health examination until the events of MI, stroke, or death (up to 5 years). Results: In total, 734 744 participants from the farmer cohort and 238 311 from the control cohort aged between 40 and 70 were included. The age-adjusted incidence of MI was 0.766 and 0.585 per 1000 person-years in the farmer and control cohorts, respectively. That of stroke was 0.559 and 0.321 per 1000 person-years in both cohorts, respectively. In farmers, the risk factors for MI included male sex, age, personal history of hypertension, diabetes, current smoking, creatinine, metabolic syndrome components (blood pressure, triglycerides, and high-density lipoprotein cholesterol). Those for stroke included male sex, age, personal history of hypertension, diabetes, current smoking, high γ-glutamyl transferase, and metabolic syndrome components (blood pressure, triglycerides, and high-density lipoprotein cholesterol). The prediction model showed an area under the receiver operating characteristic curve of 0.735 and 0.760 for MI and stroke, respectively, in the farmer cohort. Conclusions: Farmers had a higher age-adjusted incidence of MI and stroke. They also showed distinct patterns in cardiovascular risk factors compared to the general population.

Non-invasive hematocrit measurement (혈액중 non-invasive hematocrit 분석)

  • Yoon, Gil-Won;Jeon, Kye-Jin;Park, Kun-Kook;Lee, Jong-Youn;Hwang, Hyun-Tae;Yeo, Hyung-Seok;Kim, Hong-Sig
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2002.11a
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    • pp.59-62
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    • 2002
  • Wavelength selection and prediction algorithm for determining hematocrit are investigated. A model based on the difference in optical density induced by the pulsation of heart beat is developed by taking approximation of Twersky's theory on the assumption that the variation of blood vessel size is small during arterial pulsing[1]. A device is constructed with a five-wavelength LED array as light source. The selected wavelengths are two isobestic points and three in compensation for tissue scattering. Data are collected from 549 out-patients who are randomly grouped as calibration and prediction sets. The range of percent hematocrit was 19.3∼51.8. The ratio of the variations of optical density between systole and diastole at two different wavelengths is used as a variable. We selected several such variables that show high reproducibility among all variables. Multiple linear regression analysis is made. The relative percent error is 8% and the standard deviation is 3.67 for the calibration set. The relative % error and standard deviation of the prediction set are 8.2% and 3.69 respectively. We successfully demonstrate the possibility of non-invasive hematocrit measurement, particularly, using the wavelengths below 1000nm.

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Tribological Properties and Friction Coefficient Prediction Model of 200μm Surfaces Micro-Textured on AISI 4140 in Soybean Crusher (콩 분쇄기의 AISI 4140에서 200μm 미세 패턴 표면의 마찰 계수 및 마찰 계수 예측 모델)

  • Choi, Wonsik;Pratama, Pandu Sandi;Supeno, Destiani;Byun, Jaeyoung;Lee, Ensuk;Woo, Jihee;Yang, Jiung;Keefe, Dimas Harris Sean;Chrysta, Maynanda Brigita;Okechukwu, Nicholas Nnaemeka;Lee, Kangsam
    • Journal of the Korean Society of Industry Convergence
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    • v.21 no.5
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    • pp.247-255
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    • 2018
  • In this research, the effect of normal load, sliding velocity, and texture density on thefriction coefficient of surfaces micro-textured on AISI 4140 under paraffin oil lubrication were investigated. The predicted tribological behavior by numerical calculation can be serves as guidance for the designer during the machine development stage. Therefore, in this research friction coefficient prediction model based on response surface methodology (RSM), support vector machine (SVM), and artificial neural network (ANN) were developed. The experimental result shows that the variation of load, speed and texture density were influence the friction coefficient. The RSM, ANN and SVM model was successfully developed based on the experimental data. The ANN model can effectively predict the tribological characteristics of micro-textured AISI 4140 in paraffin oil lubrication condition compare to RSM and SVM.

Prediction of Carcass Fat, Protein, and Energy Content from Carcass Dry Matter and Specific Gravity of Broilers

  • Wiernusz, C.J.;Park, B.C.;Teeter, R.G.
    • Asian-Australasian Journal of Animal Sciences
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    • v.12 no.1
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    • pp.42-48
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    • 1999
  • Three experiments were conducted to develop and test equations for predicting carcass composition. In the first study using 52 d-old Cobb ${\times}$ Cobb male broilers, twenty four carcasses were selected from 325 processed birds based upon visual appraisal for abdominal fat (low, medium, high) and assayed for specific gravity (SG), dry matter (DM), fat, protein, and ash. In experiment 2, 120 birds were fed rations containing 2 caloric densities (2,880 and $3,200kcal\;ME_n/kg$ diet) and assayed as described above on weeks 2,3,4,5, and 6. Carcass fat was elevated (p < 0.05) with increased caloric density. In both studies predictive variables were significantly correlated with chemically determined carcass fat, protein, and ash contents. Pooled across the 2 studies, data were used to form SG, DM, and or age based equations for predicting carcass composition. Results were tested in experiment 3, where 576 birds reared to 49-d consumed either 2,880, 3,200, or $3,574kcal\;ME_n/kg$ diet while exposed to constant $24^{\circ}C$ or cycling 24 to $35^{\circ}C$ ambient temperatures. Both dietary and environmental effects impacted (p < 0.05) carcass composition. The fat content analyzed chemically was enhanced from 12.4 to 15.7%, and predicted fat was also elevated from 13.4 to 14.8% with increasing caloric density. Heat distress reduced (p < 0.05) analyzed carcass protein (18.9 vs 18.3%) and predicted protein (18.2 vs 17.5%). Predicted equation values for carcass fat, protein, ash, and energy were correlated with the chemically analyzed values at r=0.96, 0.77, 0.86, and 0.79, respectively. Results suggest that prediction equations based on DM and SG may be used to estimate carcass fat, protein, ash, and energy contents of broilers consuming diets that differ in caloric density (2,800 to $3,574kcal\;ME_n/kg$) and for broilers exposed to either constant ($24^{\circ}C$) or cycling high (24 to $35^{\circ}C$) ambient temperatures during 49-d rearing period tested in the present study.

Evaluations on the Characteristics of Pressure Drop f3r the Design of Intravascular Artificial Lung Assist Device (혈관 내 폐 보조장치 설계를 위한 압력손실 특성 평가)

  • 김기범;권대규;박재관;정경락;이삼철
    • Membrane Journal
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    • v.13 no.1
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    • pp.20-28
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    • 2003
  • In this study, we try to formularize simultaneous equations to make a prediction about pressure drop for designing intravascular artificial lung assist device. Designing parameters to predict the effect of pressure drop and designed modules under various conditions were studied through an experimental modeling before inserting the artificial lung assist device into as venous. We measured pressure drop in various number of hollow fiber membranes, when the inside diameter of shell is fixed in 3 cm, and tried to develope the prediction equations by curve fitting based on the correlation between the experimental pressure drop and the device frontal area or packing density. The results showed that pressure drop increased with 2nd order functional formula as the liquid flow rate, the frontal area, and the packing density increased. Also, we can estimate the pressure drop as a function of the frontal area or packing density. The pressure drop obtained from the experiment was similar to that from the equation, confirming the usefulness of the equation.