• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.24-34
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• 2021

This paper predicts the speed-power-rpm relationship in regular head waves using various indirect methods: load variation, direct powering, resistance and thrust identity, torque and revolution, thrust and revolution, and Taylor expansion methods. The subject ship is KVLCC2. The wave conditions are the regular head waves of λ/LPP = 0.6 and 1.0 with three wave steepness ratios at three ship speeds of 13.5, 14.5 and 15.5 knots (design speed). In the case of λ/LPP = 0.6 at design speed, two more wave steepness ratios have been taken into consideration. The indirect methods have been evaluated through comparing the speed-power-rpm relationships with those obtained from the resistance and self-propulsion tests in calm water and in waves. The load variation method has been applied to predict propulsive performances in waves, and to derive overload factors (ITTC, 2018). The overload factors have been applied to obtain propulsive efficiency and propeller revolution. The thrust and revolution method (ITTC, 2014) has been modified.

• Tribology and Lubricants
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• v.3 no.1
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• pp.31-38
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• 1987

This paper describes a theoretical model for the prediction of the spacing profile between a flexible magnetic tape tensioned around a rotating drum and a protruding head mounted on the drum. The analysis is based on the coupled equations controlling the elastic deformation of the tape and the hydrodynamic pressure of the gas film. Some results are presented for a cylindrical head.

• 한국기계연구소 소보
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• s.9
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• pp.133-140
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• 1982

• Asian-Australasian Journal of Animal Sciences
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• v.7 no.3
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• pp.441-448
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• 1994

Postweaning performance data were obtained on 187 group fed purebred Angus calves from 12 selected sires (six high and six low feed conversion sires) in 1985 and 1986. The objective of this portion of the study was to develop prediction equations for feed conversion from a stepwise regression analysis. Variables measured were on-test weight (ONTSTWT), on-test age (ONTSTAG), five weights by 28-d periods, seven linear body measurements: heart girth (HG), hip height (HH), head width (HDW), head length (HDL), muzzle circumference (MC), length between hooks and pins (HOPIN) and length between shoulder and hooks (SHHO), and backfat thickness (BF). Stepwise regressions for maintenance adjusted feed conversion (ADJFC) and unadjusted feed conversion (UNADFC) over the first 140 d of the test, and total feed conversion (FC) until progeny reached 8.89 mm of back fat were obtained separately by conversion groups and sexes and for combined feed conversion groups and sexes. In general, weights were more important than linear body measurements in prediction of feed utilization. To some extent this was expected as weight is related directly to gain which is a component of feed conversion. Weight at 112 d was the most important variable in prediction of feed conversion when data from both feed conversion groups and sexes were combined. Weights at 84 and 140 d were important variables in prediction of UNADFC and FC, respectively, of bulls. ONTSTWT and weight at 140 d had the highest standardized partial regression coefficients for UNADFC and ADJFC, respectively, of heifers. Results indicated that linear measurements, such as MC, HDL and HOPIN, are useful in prediction of feed conversion when feed in takes are unavailable.

• Journal of Embryo Transfer
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• v.23 no.3
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• pp.155-160
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• 2008

Serial ultrasonographic examinations were performed to establish a prediction table of parturition date in pregnant Maltese, Yorkshire Terrier, Shih-tzu and Miniature Schnauzer bitches. The inner chorionic cavity diameter and fetal head diameter in 45 pregnant bitches were converted retrospectively based on the day of parturition. The data of inner chorionic cavity diameter obtained from Day-44 to Day-25 and fetal head diameter obtained from Day-25 to Day-1 were used to compile a equations of prediction of parturition date. The 70 pregnant bitches with unknown mating time were examined to assess an accuracy of the equations established in this study. And these results were applied to the prediction of parturition date and compared to actual parturition date. The accuracy for parturition date within 0, $\pm$1, and $\pm$2 days interval using the equations of prediction of parturition date were 64.3%, 22.8% and 12.8%, respectively. The overall accuracy of prediction table of parturition day based on the ICCD and HD was 100% accurate within $\pm$2 days. Therefore, the prediction table seems to be a useful tool of the prediction of parturition day in practice.

• The Journal of Korea Robotics Society
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• v.5 no.3
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• pp.262-269
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• 2010

This paper presents a probabilistic head tracking method, mainly applicable to face recognition and human robot interaction, which can robustly track human head against various variations such as pose/scale change, illumination change, and background clutters. Compared to conventional particle filter based approaches, the proposed method can effectively track a human head by regularizing the sample space and sequentially weighting multiple visual cues, in the prediction and observation stages, respectively. Experimental results show the robustness of the proposed method, and it is worthy to be mentioned that some proposed probabilistic framework could be easily applied to other object tracking problems.

• The Transactions of the Korea Information Processing Society
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• v.13 no.5
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• pp.209-216
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• 2024

Real estate market prices are determined by various factors, including macroeconomic variables, as well as the influence of a variety of unstructured text data such as news articles and social media. News articles are a crucial factor in predicting real estate transaction prices as they reflect the economic sentiment of the public. This study utilizes sentiment analysis on news articles to generate a News Sentiment Index score, which is then seamlessly integrated into a real estate price prediction model. To calculate the sentiment index, the content of the articles is first summarized. Then, using AI, the summaries are categorized into positive, negative, and neutral sentiments, and a total score is calculated. This score is then applied to the real estate price prediction model. The models used for real estate price prediction include the Multi-head attention LSTM model and the Vector Auto Regression model. The LSTM prediction model, without applying the News Sentiment Index (NSI), showed Root Mean Square Error (RMSE) values of 0.60, 0.872, and 1.117 for the 1-month, 2-month, and 3-month forecasts, respectively. With the NSI applied, the RMSE values were reduced to 0.40, 0.724, and 1.03 for the same forecast periods. Similarly, the VAR prediction model without the NSI showed RMSE values of 1.6484, 0.6254, and 0.9220 for the 1-month, 2-month, and 3-month forecasts, respectively, while applying the NSI led to RMSE values of 1.1315, 0.3413, and 1.6227 for these periods. These results demonstrate the effectiveness of the proposed model in predicting apartment transaction price index and its ability to forecast real estate market price fluctuations that reflect socio-economic trends.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.278-291
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• 2021

This paper applies load variation method to predict speed-power-rpm relationship along with propulsive performances in regular head waves, and to derive overload factors (ITTC, 2018). 'Calm-water tests' and 'resistance test in waves' are used. The modified overload factors are proposed taking non-linearity into consideration, and applied to the direct powering, and resistance and thrust identity method. These indirect methods are evaluated through comparing the speed-power-rpm relationships with those obtained from the resistance and self-propulsion tests in calm water and in waves. The objective ship is KVLCC2. The load variation method predicts well the speed-power-rpm relationship and propulsion performances in waves. The direct powering method with modified overload factors also predicts well. The resistance and thrust identity method with modified overload factor predicts with a little difference. The direct powering method with overload factors predicts with a relatively larger difference.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.3
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• pp.244-250
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• 2008

The purpose of this study was to measure fundamental data required for the prediction of milling ratios, and to develop regression models to predict the head rice ratio of milled rice using NIR spectra of hulled rice. A total of 81 rice samples used in this study were collected from Jeongeup, Jeonbuk province in 2006. NIR spectra were measured using one mode of measurement, reflection. The reflectance spectra were measured in the wavelength region of 400-2500 nm with an NIR spectrophotometer "NIRSystems 6500" (Foss, Silverspring, USA). Calibration equations were developed by the modified partial least squares (MPLS), partial least squares (PLS), and principal components regression (PCR). Math treatments were 1-4-4-1, 1-10-10-1, 2-4-4-1, and 2-10-10-1. The software used was WinISI (Infrasoft International, State College, USA). Automatic head rice production and quality checking system used was "SY2000-AHRPQCS" (Ssangyong, Korea). The calibration was made with the first derivative and the spectrum designated was in 8 nm interval. The determination coefficients of head rice ratios were 0.8353, 0.8416 and 0.5277 for the MPLS, PLS and PCR, respectively. Those obtained with 20 nm interval were 0.8144, 0.8354 and 0.6908 for the MPLS, PLS and PCR, respectively. The calibration was made with second derivative that spectrum designated was 8 nm in interval. The determination coefficients of head rice ratios were 0.7994, 0.8017 and 0.4473 for the MPLS, PLS and PCR, respectively. Those with 20 nm interval were 0.8004, 0.8493 and 0.6609 for the MPLS, PLS and PCR, respectively. These results indicate that the accuracy of determination coefficient for MPLS and PLS is higher than that of PCR.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1412-1420
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• 2018

An experiment was performed using the large-scale test facility (LSTF), which simulated a 1% vessel upper head small-break loss-of-coolant accident with an accident management (AM) measure under an assumption of total-failure of high-pressure injection (HPI) system in a pressurized water reactor (PWR). In the LSTF test, liquid level in the upper head affected break flow rate. Coolant was manually injected from the HPI system into cold legs as the AM measure when the maximum core exit temperature reached 623 K. The cladding surface temperature largely increased due to late and slow response of the core exit thermocouples. The AM measure was confirmed to be effective for the core cooling. The RELAP5/MOD3.3 code indicated insufficient prediction of primary coolant distribution. The author conducted uncertainty analysis for the LSTF test employing created phenomena identification and ranking table for each component. The author clarified that peak cladding temperature was largely dependent on the combination of multiple uncertain parameters within the defined uncertain ranges.