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Gotowe bibliografie tematyczne / CCPP DATA

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Gotowa bibliografia na temat „CCPP DATA”

Autor: Grafiati

Data publikacji: 11 września 2023

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Artykuły w czasopismach na temat "CCPP DATA"

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Selim, Abdelfattah, Ameer Megahed, Sahar Kandeel, Abdullah D. Alanazi, and Hamdan I. Almohammed. "Determination of Seroprevalence of Contagious Caprine Pleuropneumonia and Associated Risk Factors in Goats and Sheep Using Classification and Regression Tree." Animals 11, no. 4 (2021): 1165. http://dx.doi.org/10.3390/ani11041165.

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Classification and Regression Tree (CART) analysis is a potentially powerful tool for identifying risk factors associated with contagious caprine pleuropneumonia (CCPP) and the important interactions between them. Our objective was therefore to determine the seroprevalence and identify the risk factors associated with CCPP using CART data mining modeling in the most densely sheep- and goat-populated governorates. A cross-sectional study was conducted on 620 animals (390 sheep, 230 goats) distributed over four governorates in the Nile Delta of Egypt in 2019. The randomly selected sheep and goat

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Kyotos, Kitoga Byalungwa, Jemimah Oduma, Raphael Githaiga Wahome, et al. "Gendered Barriers and Opportunities for Women Smallholder Farmers in the Contagious Caprine Pleuropneumonia Vaccine Value Chain in Kenya." Animals 12, no. 8 (2022): 1026. http://dx.doi.org/10.3390/ani12081026.

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Most rural women smallholder farmers in Kenya generate income from the sale of small ruminant animals. However, diseases such as Contagious Caprine Pleuropneumonia (CCPP) prevent them from optimizing earnings. A crucial aspect for the control of CCPP is vaccination. In Kenya, CCPP vaccines are distributed through a government delivery mechanism. This study examines gaps and barriers that prevent women smallholder farmers from accessing CCPP vaccines. Qualitative data collection tools used were focus groups discussions, focus meals, jar voices and key informant interviews. Using outcome mapping

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Rosas-Sánchez, Gustavo Armando, Zorba Josué Hernández-Estrada, Mirna Leonor Suárez-Quiroz, Oscar González-Ríos, and Patricia Rayas-Duarte. "Coffee Cherry Pulp by-Product as a Potential Fiber Source for Bread Production: A Fundamental and Empirical Rheological Approach." Foods 10, no. 4 (2021): 742. http://dx.doi.org/10.3390/foods10040742.

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Effects of substituting of wheat flour with coffee cherry pulp powder (CCPP) (coffee by-product as fiber source) at 0, 1.2, 2.3, and 4.7% dry basis (0, 1.25, 2.5, and 5% wet basis) on dough and gluten rheological properties and baking quality were investigated. Rheological properties were analyzed during mixing, compression recovery, and creep-recovery. A rheological approach was adopted to study the viscoelasticity of dough enriched with fiber. The data obtained were analyzed with the Kelvin–Voigt model and the parameters were correlated to bread volume and crumb firmness to assess the effect

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4

Zhu, Shun-Ye, Min-Lian Du, and Ting-Ting Huang. "An Analysis of Predictive Factors for the Conversion from Premature Thelarche into Complete Central Precocious Puberty." Journal of Pediatric Endocrinology and Metabolism 21, no. 6 (2008): 533–38. http://dx.doi.org/10.1515/jpem-2008-210607.

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Abstract Aim: To determine the predictive factors for the conversion of premature thelarche (PT) into complete central precocious puberty (CCPP) in girls. Design: Prospective. Methods: One hundred and fifty-one girls with PT referred consecutively for evaluation of clinical, laboratory, and ultrasound data. Results: Twenty-one and a half percent of girls with PT converted into CCPP at a chronological age of 7.1 ± 0.7 years and bone age of 9.0 ± 1.1 years. Using logistic regression analysis, longitudinal diameter of uterus (OR = 1.215), Tanner breast stage at the time of first physical examinat

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Arferiandi, Yondha Dwika, Wahyu Caesarendra, and Herry Nugraha. "Heat Rate Prediction of Combined Cycle Power Plant Using an Artificial Neural Network (ANN) Method." Sensors 21, no. 4 (2021): 1022. http://dx.doi.org/10.3390/s21041022.

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Heat rate of a combined cycle power plant (CCPP) is a parameter that is typically used to assess how efficient a power plant is. In this paper, the CCPP heat rate was predicted using an artificial neural network (ANN) method to support maintenance people in monitoring the efficiency of the CCPP. The ANN method used fuel gas heat input (P1), CO2 percentage (P2), and power output (P3) as input parameters. Approximately 4322 actual operation data are generated from the digital control system (DCS) in a year. These data were used for ANN training and prediction. Seven parameter variations were dev

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6

Afzal, Asif, Saad Alshahrani, Abdulrahman Alrobaian, Abdulrajak Buradi, and Sher Afghan Khan. "Power Plant Energy Predictions Based on Thermal Factors Using Ridge and Support Vector Regressor Algorithms." Energies 14, no. 21 (2021): 7254. http://dx.doi.org/10.3390/en14217254.

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This work aims to model the combined cycle power plant (CCPP) using different algorithms. The algorithms used are Ridge, Linear regressor (LR), and upport vector regressor (SVR). The CCPP energy output data collected as a factor of thermal input variables, mainly exhaust vacuum, ambient temperature, relative humidity, and ambient pressure. Initially, the Ridge algorithm-based modeling is performed in detail, and then SVR-based LR, named as SVR (LR), SVR-based radial basis function—SVR (RBF), and SVR-based polynomial regression—SVR (Poly.) algorithms, are applied. Mean absolute error (MAE), R-s

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7

Mohamed Abdi, Omar. "Sero-Prevalence of Contagious Caprine Pleuropneumonia in Goats in Afgoye District Lower Shabelle Region, Somalia." Open Access Journal of Veterinary Science & Research 5, no. 2 (2020): 1–4. http://dx.doi.org/10.23880/oajvsr-16000203.

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Background: Contagious caprine pleuropneumonia (CCPP), caused by Mycoplasma capricolum subsp. Capripneumoniae (Mccp), is one of the most important goat diseases causing high morbidity and mortality, these results in heavy economic losses to countries like Somalia, which is a country affected the civil war of the 1990s. Objective: Generally, the disease presence has been reported in the country. However, there is no quantitative data on the prevalence and distribution of the disease has been scientifically reported in the country. Methods: A cross-sectional study was conducted from September 20

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He, Dakuo, Zhengsong Wang, Le Yang, and Zhizhong Mao. "Optimization Control of the Color-Coating Production Process for Model Uncertainty." Computational Intelligence and Neuroscience 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/9731823.

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Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the mod

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9

Yi, Qiu, Hanqing Xiong, and Denghui Wang. "Predicting Power Generation from a Combined Cycle Power Plant Using Transformer Encoders with DNN." Electronics 12, no. 11 (2023): 2431. http://dx.doi.org/10.3390/electronics12112431.

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With the development of the Smart Grid, accurate prediction of power generation is becoming an increasingly crucial task. The primary goal of this research is to create an efficient and reliable forecasting model to estimate the full-load power generation of a combined-cycle power plant (CCPP). The dataset used in this research is a subset of the publicly available UCI Machine Learning Repository. It contains 9568 items of data collected from a CCPP during its full load operation over a span of six years. To enhance the accuracy of power generation forecasting, a novel forecasting method based

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10

Utami, Louise Indah, Ika Yuliyani, Yanti Suprianti, and Purwinda Iriani. "Load optimization on the performance of combined cycle power plant Block 4 PT Indonesia Power Priok POMU." Journal of Mechatronics, Electrical Power, and Vehicular Technology 13, no. 1 (2022): 24–35. http://dx.doi.org/10.14203/j.mev.2022.v13.24-35.

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Combined cycle power plant (CCPP) is a closed-cycle power plant, where the heat from the gas turbine’s (GT) exhaust gas will be streamed to the heat recovery steam generator (HRSG) to be utilized by steam turbine (ST). CCPP Block 4 (Jawa-2) PT Indonesia Power Priok POMU has an installed capacity of 880 MW, consists of 2 GT units (301.5 MW each) and 1 ST unit (307.5 MW). The performance of a power plant depends on its load, as the efficiency of the turbine generator is low when operated at low loads. The data as of July 2019 showed that 2.2.1 (2 GT, 2 HRSG, 1 ST) configuration has been used in

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