Gotowe bibliografie tematyczne / Adjusted R2

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Gotowa bibliografia na temat „Adjusted R2”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Adjusted R2"

Ohtani, Kazuhiro. "Bootstrapping R2 and adjusted R2 in regression analysis." Economic Modelling 17, no. 4 (2000): 473–83. http://dx.doi.org/10.1016/s0264-9993(99)00034-6.

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Robert Wall, Emerson. "Regression Analysis and Adjusted R2." Journal of Visual Impairment & Blindness 114, no. 4 (2020): 332–33. http://dx.doi.org/10.1177/0145482x20939786.

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Mittlböck, Martina. "Calculating adjusted R2 measures for Poisson regression models." Computer Methods and Programs in Biomedicine 68, no. 3 (2002): 205–14. http://dx.doi.org/10.1016/s0169-2607(01)00173-0.

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Heinzl, Harald, and Martina Mittlböck. "Adjusted R2 Measures for the Inverse Gaussian Regression Model." Computational Statistics 17, no. 4 (2002): 525–44. http://dx.doi.org/10.1007/s001800200125.

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Kim, Sung-Woo, Hun-Young Park, Won-Sang Jung, and Kiwon Lim. "Predicting Heart Rate Variability Parameters in Healthy Korean Adults: A Preliminary Study." INQUIRY: The Journal of Health Care Organization, Provision, and Financing 58 (January 2021): 004695802110562. http://dx.doi.org/10.1177/00469580211056201.

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The purpose of the study was to examine the development of a multiple linear regression model to estimate heart rate variability (HRV) parameters using easy-to-measure independent variables in preliminary experiments. HRV parameters (time domain: SDNN, RMSSD, NN50, pNN50; frequency domain: TP, VLF, LF, HF) and the independent variables (e.g., sex, age, body height, body weight, BMI, HR, HRmax, HRR) were measured in 75 healthy adults (male n = 27, female n = 48) for estimating HRV. The HRV estimation multiple linear regression model was developed using the backward elimination technique. The re

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Kim, Sung-Woo, Hun-Young Park, Hoeryong Jung, Sin-Ae Park, and Kiwon Lim. "Development of a Heart Rate Variability Prediction Equation Through Multiple Linear Regression Analysis Using Physical Characteristics and Heart Rate Variables." INQUIRY: The Journal of Health Care Organization, Provision, and Financing 60 (January 2023): 004695802311694. http://dx.doi.org/10.1177/00469580231169416.

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Heart rate variability (HRV) is an effective tool for objectively evaluating physiological stress indices in psychological states. This study aimed to develop multiple linear regression equations to predict HRV variables using physical characteristics, body composition, and heart rate (HR) variables (eg, sex, age, height, weight, body mass index, fat-free mass, percent body fat, resting HR, maximal HR, and HR reserve) in Korean adults. Six hundred eighty adults (male, n = 236, female, n = 444) participated in this study. HRV variable estimation multiple linear regression equations were develop

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Ohtani, Kazuhiro, and Hisashi Tanizaki. "Exact Distributions of R2 and Adjusted R2 in a Linear Regression Model with Multivariate t Error Terms." JOURNAL OF THE JAPAN STATISTICAL SOCIETY 34, no. 1 (2004): 101–9. http://dx.doi.org/10.14490/jjss.34.101.

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Farkas, Gary J., Phillip S. Gordon, Nareka Trewick, et al. "Comparison of Various Indices in Identifying Insulin Resistance and Diabetes in Chronic Spinal Cord Injury." Journal of Clinical Medicine 10, no. 23 (2021): 5591. http://dx.doi.org/10.3390/jcm10235591.

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The purpose of this screening and diagnostic study was to examine the accord among indices of glucose metabolism, including the Homeostatic Model Assessment for Insulin Resistance (HOMA), HOMA2, Matsuda Index, Quantitative Insulin-sensitivity Check Index (QUICKI), hemoglobin A1C (HbA1C), and fasting plasma glucose (FPG) against intravenous glucose tolerance test-measured insulin sensitivity (Si) in individuals with chronic motor complete SCI. Persons with chronic (≥12-months post-injury) SCI (n = 29; 79% men; age 42.2 ± 11.4; body mass index 28.6 ± 6.4 kg/m2; C4-T10) were included. Measures we

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Surianastutiningtyas, Angela Maricilia, and Susiswo Susiswo. "Implementasi regresi komponen utama dan regresi stepwise terhadap faktor-faktor kepuasan nasabah (Studi Kasus di BPR Nusamba Wlingi)." Jurnal MIPA dan Pembelajarannya 2, no. 9 (2023): 5. http://dx.doi.org/10.17977/um067v2i92022p5.

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Faktor-faktor yang mempengaruhi mutu pelayanan terhadap kepuasan nasabah dapat ditentukan oleh analisis regresi, seperti analisis regresi komponen utama dan analisis regresi stepwise. Model yang diperoleh dari kedua metode tersebut kemudian dibandingkan dengan melihat nilai adjusted R2 karena kemungkinan perbedaan jumlah variabel yang dihasilkan. Analisis regresi komponen utama menghasilkan model Y = -1.013 + 0.1408X1 + 0.1638X2 + 0.1939X3 + 0.1665X4 + 0.1677X5 dengan nilai adjusted R2 sebesar 0,817 sedangkan analisis regresi stepwise menghasilkan model Y = -1,092 + 0,143X1 + 0,181X2 + 0,250X3

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Laouane, Adil, and Mohamed Torra. "Analysis of the contribution of IFRS to improving the relevance of financial performance measures: A comparative study with Moroccan Accounting Standards." Investment Management and Financial Innovations 20, no. 3 (2023): 251–63. http://dx.doi.org/10.21511/imfi.20(3).2023.21.

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The implementation of the international accounting framework has led to a new philosophy of estimating and valuing the financial performance of companies. In this respect, the accounting indicators derived from financial statements constitute the classic measures of performance evaluation, such as ROE, ROA, BPA, and Payout. However, their usefulness is contested in the face of market-based indicators like TSR, MVA, PBR, and dividend yield. This paper aims to assess the effect of adopting IFRS on the relevance of financial performance measures through a comparative approach with Moroccan GAAP.

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Części książek na temat "Adjusted R2"

Singh, Hari, Piyush Sewal, and Dinesh Chander Verma. "A Predictive Analysis of the COVID-19 Pandemic for Traditional and Tree-Based Regression Algorithms." In Advances in Medical Technologies and Clinical Practice. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-5237-3.ch011.

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A lot of works exist in the literature that compares regression algorithms on different datasets. This chapter presents a model that uses best subset selection approach for the predictors and performs an exhaustive empirical comparison of eight regression algorithms Linear Regression, Multi-Linear Regression, Polynomial Regression, K-Nearest Neighbors, Lasso, Ridge, Decision Tree, Gradient Boost Tree, and Random Forest Regression algorithms on various predictors from Covid-19 dataset. The model is evaluated for train accuracy on metrics R2, Root Mean Square Error, and Mean Absolute Error. The

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Hunstein, Dirk, and Madlen Fiebig. "Staff Management with AI: Predicting the Nursing Workload." In Studies in Health Technology and Informatics. IOS Press, 2024. http://dx.doi.org/10.3233/shti240142.

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The effective management of human resources in nursing fundamental to ensuring high-quality care. The necessary staffing levels can beis derived from the nursing-related health status. Our approach is based on the use of artificial intelligence (AI) and machine learning (ML) to recognize key workload-driving predictors from routine clinical data in the first step and derive recommendations for staffing levels in the second step. The study was a multi-center study with data provided by three hospitals. The SPI (Self Care Index = sum score of 10 functional/cognitive items of the epaAC) was ident

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Hunstein, Dirk, Lena Frischen, and Madlen Fiebig. "Development of a Data Model to Predict Nursing Workload Using Routine Clinical Data." In Studies in Health Technology and Informatics. IOS Press, 2024. http://dx.doi.org/10.3233/shti240588.

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The effective management of human resources in nursing is fundamental to ensuring high-quality care. The necessary staffing levels can be derived from the nursing-related health status. Our approach is based on the use of artificial intelligence (AI) and machine learning (ML) to recognize key workload-driving predictors from routine data in the first step and derive recommendations for staffing levels in the second step. The precedent analysis was a multi-center study with data provided by three hospitals. The SPI (Self Care Index = sum score of 10 functional/cognitive items of the epaAC (epaA

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Huang, Boling, Xuan Wang, Tingting Yang, et al. "Fitting Analysis of RGB Model of the Turquoise." In Advances in Transdisciplinary Engineering. IOS Press, 2022. http://dx.doi.org/10.3233/atde220075.

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In order to overcome the disadvantages of poor repeatability and strong subjectivity brought by traditional artificial experience classification and realize the quantitative intelligent classification of turquoise, RGB model needs to be fitted. By fitting the RGB model of turquoise classification with linear function and polynomial function, it is proved that after fitting the model with polynomial function, the Adjusted R-Square (R2) reach more than 0.99. Using this method, the RGB model of optimal turquoise classification can be obtained, and improve the measurement accuracy of the color par

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Çırak, Mustafa. "Improvement of RSM Prediction and Optimization by Using Box-Cox Transformation." In Advances in Computational Intelligence and Robotics. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-4766-2.ch008.

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Electrocoagulation can be effectively used in the elimination of the colloids from the tailings of the mineral industries. Owing to the numerous operational parameters of this physicochemical process, the best engineering technique for the characterization of the process is RSM. In this chapter, a non-transformed quadratic model is firstly formed considering the supernatant turbidity of the electrocoagulation experiments as a function of temperature, pH, and electrical current. Then, the non-normality and the heteroscedasticity of this initial model was indicated. These drawbacks were improved

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Azeez, Rasheed Olawale, and Foluso Ilesanmi Jayeoba. "Micro-Wellness Interventions and Well-Being of Medical Doctors in Lagos State, Nigeria." In Advances in Ethical Work Climate and Employee Well-Being. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-8819-8.ch020.

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This study examines the effect of micro-wellness interventions such as microsteps, microbreaks, and microchillers on the well-being of medical doctors in Lagos State. Using the descriptive survey research design, data was collected from 249 medical doctors using a structured questionnaire. Four hypotheses were stated and tested using Pearson's Product Moment Correlation Coefficient and multiple regression. Results show that there is a moderate and statistically significant relationship between microsteps and physical well-being, microbreaks and mental well-being and microchillers and the socia

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Anderson, Raymond A. "Stats & Maths & Unicorns." In Credit Intelligence & Modelling. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192844194.003.0011.

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This chapter covers basic statistical concepts. Most statistics relate to hypothesis testing, and others to variable selection and model fitting. The name is because an exact match between a theoretical and empirical distribution is as rare as a unicorn. (1) Dispersion—measures of random variations—variance and its inflation factor, covariance and correlations {Pearson’s product-moment, Spearman’s rank order}, and the Mahalanobis distance. (2) Goodness-of-fit—do observations match expectations? This applies to both continuous dependent variables {R-squared and adjusted R2} and categorical {Pea

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Guleryuz, Didem. "Prediction of Capacity Utilization Rate for Turkey Using Adaptive Neuro-Fuzzy Inference System With Particle Swarm Optimization and Genetic Algorithm." In Handbook of Research on Advances and Applications of Fuzzy Sets and Logic. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-7979-4.ch013.

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This chapter aims to propose prediction models to estimate Turkey's manufacturing sector's capacity utilization rate between 2008-2019 monthly basis using the adaptive neuro-fuzzy inference system (ANFIS) with genetic algorithm (GA) and particle swarm optimization (PSO) via determined indicators. The model's accuracy will be tested using some of the performance evaluation criteria, namely mean absolute error (MAE), root mean square error (RMSE), and the coefficient of determination (R2) values were used to compare the prediction ability. The coefficient of determination for GA-ANFIS, PSO-ANFIS

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Yang, Yang, Shu-Feng Tsao, Mohammad A. Basri, Helen H. Chen, and Zahid A. Butt. "Digital Disease Surveillance for Emerging Infectious Diseases: An Early Warning System Using the Internet and Social Media Data for COVID-19 Forecasting in Canada." In Caring is Sharing – Exploiting the Value in Data for Health and Innovation. IOS Press, 2023. http://dx.doi.org/10.3233/shti230290.

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Background: Emerging Infectious Diseases (EID) are a significant threat to population health globally. We aimed to examine the relationship between internet search engine queries and social media data on COVID-19 and determine if they can predict COVID-19 cases in Canada. Methods: We analyzed Google Trends (GT) and Twitter data from 1/1/2020 to 3/31/2020 in Canada and used various signal-processing techniques to remove noise from the data. Data on COVID-19 cases was obtained from the COVID-19 Canada Open Data Working Group. We conducted time-lagged cross-correlation analyses and developed the

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Yuan, Xue, Hu Dan, Ye Qiuyin, Zeng Wenjun, Yang Jing, and Rao Min. "Analysis and Prediction of the SARIMA Model for a Time Interval of Earthquakes in the Longmenshan Fault Zone." In Natural Hazards - New Insights [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.109174.

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Based on the catalog data of earthquakes with Ms ≥ 2.5 in the Longmenshan fault zone from January 2012 to September 2021, we establish an earthquake time interval series grouped by earthquake magnitude and then use the SARIMA model to predict the series in different periods. By analyzing the fitting effect of the models, the optimal model parameters of different magnitude sequences and the corresponding period values are obtained. Among them, the adjusted R2 values of each model with Ms ≥ 2.5 and Ms ≥ 3.0 sequences are more than 0.86, up to 0.911; the short-time prediction effects are good, an

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Streszczenia konferencji na temat "Adjusted R2"

Ai, Zijian, Guoliang Qin, Xuefei Chen, Jingxiang Lin, and Wenqiang He. "Speed Matching of the Second Rotor in a Counter-Rotating Fan Under Off-Design Conditions." In ASME 2017 Power Conference Joint With ICOPE-17 collocated with the ASME 2017 11th International Conference on Energy Sustainability, the ASME 2017 15th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2017 Nuclear Forum. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/power-icope2017-3232.

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A method for speed matching of the second rotor (R2) with equal power for two rotors was proposed to improve the performance of the counter-rotating fan under off-design conditions. In this method, the speed of R2 is adjusted until the power of R2 is equal to the power of the first rotor (R1). The fan performance during constant speed operation and during R2 speed matching operation is presented and discussed using theoretical analysis, numerical simulation, and experimental research. The results show that R2 speed matching improves the power and efficiency characteristics of R2. Thus, the pre

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Morris, Daniel, and Christopher Pretty. "An Experimental Study of Drag Coefficients of a Quadrotor Airframe." In ASME 2023 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/detc2023-114020.

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Abstract This paper investigates the aerodynamic drag coefficients of a standard cross-geometry quadrotor airframe at varying pitch and yaw angles, using a wind tunnel. The quadrotor airframe was mounted in the wind tunnel at fixed pitch and yaw angles, and subjected to a range of wind flow speeds. Drag forces created by the mounting systems used were measured and removed from subsequent drag force measurements. The drag force on the airframe at these speeds and attitudes was measured, and used to identify lumped drag-area coefficients. The variability of these coefficients was observed both w

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P, Kanthasamy, Arul Mozhi Selvan, and Shanmugam P. "Optimization of Biodiesel Production from Tannery Industry Fleshing Wastes Using Response Surface Methodology." In Advances in Design, Materials, Manufacturing and Surface Engineering for Mobility (ADMMS’25). SAE International, 2025. https://doi.org/10.4271/2025-28-0115.

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<div class="section abstract"><div class="htmlview paragraph">In response to rising emissions and pollutants, an alternative and environmentally friendly synthesis is gaining prominence on the energy sources. The leather industries generate substantial amount of waste and fleshing oil extracted from fleshing which is rich in lipids and presents a viable feedstock for biodiesel production. In this research work, Response Surface Methodology (RSM) is used to optimize the conversion of leather fleshing oil into biodiesel using three parameters such as operating temperature, reaction t

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Mardhatillah, Mutia Kharunisa, Muhammad Aslam Md Yusof, Alva Andhika Sa'id, Iqmal Irsyad Mohammad Fuad, Yens Adams Sokama Neuyam, and Nur Asyraf Md Akhir. "Predictive Modelling of Carbon Dioxide Injectivity Using SVR-Hybrid." In Offshore Technology Conference Asia. OTC, 2022. http://dx.doi.org/10.4043/31472-ms.

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Abstract Southeast Asia is increasingly gaining attention as a promising geological site for permanent CO2 sequestration in deep saline aquifers. During CO2 injection into saline reservoirs, the reaction between injected CO2, the resident formation brine, and the reservoir rock could cause injectivity change due to salt precipitation, mineral dissolution, and fine particles migration. The underlying mechanisms have been extensively studied, both experimentally and numerically and the governing parameters have been identified and studied. However, the current models that have been widely adopte

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Laalam, A., O. S. Tomomewo, H. Khalifa, et al. "Comparative Analysis Between Empirical Correlations and Time Series Models for the Prediction and Forecasting of Unconventional Bakken Wells Production." In Asia Pacific Unconventional Resources Symposium. SPE, 2023. http://dx.doi.org/10.2118/217297-ms.

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Abstract Accurately forecasting oil and gas well production, especially in complex unconventional reservoirs, is vital. Leveraging advanced techniques like machine learning and deep learning is becoming more common due to ample historical data availability. While traditional methods work for conventional reservoirs, they struggle in unconventional scenarios. Modern machine and deep learning models excel in such challenges, offering insights while bypassing temporary disruptions or pressure issues. This study compares ten empirical production forecast models with state-of-the-art deep learning

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Khassaf, Ahmed K., Zainab M. Al-hameed, Noor R. Al-Mohammedawi, et al. "Physics-Informed Machine Learning for Enhanced Permeability Prediction in Heterogeneous Carbonate Reservoirs." In Offshore Technology Conference. OTC, 2025. https://doi.org/10.4043/35892-ms.

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Abstract Physics-informed-machine-learning (PIML) techniques enhance permeability prediction in carbonate reservoirs. Accurate permeability estimation is crucial for reservoir characterization, fluid flow modeling, and oil/gas production optimization. However, traditional empirical models and conventional machine learning techniques often fail to capture the complex nonlinear relationships governing permeability, particularly in heterogeneous carbonate formations. To address this challenge, this research integrates physics-based constraints into machine learning models, thereby improving their

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Kusumawati, Eny, and Alfina Shinta Dilas Chaniago. "Analisis Faktor Penentu Financial Distress Pada Perusahaan Jasa Yang Terdaftar Di Bei." In SEMINAR NASIONAL DAN CALL FOR PAPER 2020 FAKULTAS EKONOMI DAN BISNIS UNIVERSITAS MUHAMMADIYAH JEMBER. UM Jember Press, 2021. http://dx.doi.org/10.32528/psneb.v0i0.5202.

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Penelitian ini bertujuan untuk menganalisis faktor penentu terjadinya financial distress dengan analisis Model Altman Z-Score pada perusahaan sektor perdagangan, jasa dan investasi yang terdaftar di Bursa Efek Indonesia periode 2014-2019. Penelitian ini menganalisis pengaruh variabel profitabilitas yang diproksikan dengan return on assets (ROA). Likuiditas yang diwakili oleh current ratio (CR). Solvabilitas (leverage) yang diproksikan dengan debt equity ratio (DER). Komite audit yang diproksikan dengan jumlah komite audit. Kepemilikan institusional diproksikan dengan kepemilikan saham perusaha

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Holme, S., W. A. Heaton, and P. Hartman. "INDIUM-111 PLATELET SURVIVAL STUDIES ON PLATELET CONCENTRATES (PCVSTORED FOR UP TO 14 DAYS." In XIth International Congress on Thrombosis and Haemostasis. Schattauer GmbH, 1987. http://dx.doi.org/10.1055/s-0038-1644690.

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The effect of extended storage on platelet in vitro and in vivo viability was investigated to determine the reliability and efficacy of Indium-111-oxine radiolabeling of long-term stored platelets. The fitness of various mathematical models for measurement of platelet survival and recovery was also evaluated.33 CPDA-1 PC were prepared and stored for various periods of time (see below) according to standard blood bank methods. The volume of the PC was adjusted to 65-75 mL to prevent pH fall with extended storage. After storage, samples were taken for in vitro assays and for radiolabeling witn I

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Barghi Golezani, Farshad, Jiayuan Li, Logan Pirnstill, and Chirag Kharangate. "Machine Learning Algorithms for Predicting Condensation Pressure Drop in Mini/Micro Channels." In ASME 2024 Heat Transfer Summer Conference collocated with the ASME 2024 Fluids Engineering Division Summer Meeting and the ASME 2024 18th International Conference on Energy Sustainability. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/ht2024-131476.

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Abstract Recent years have seen a big increase in the amount of heat that needs to be dissipated within small systems. This means that single-phase heat transfer is no longer good enough. Because of this, two-phase heat transfer, which can get rid of more heat since liquid changing to vapor takes up latent heat, has become crucial. However, two-phase systems have higher pressure drops than single-phase ones, which decreases overall efficiency. So being able to accurately predict the pressure drop is really important for efficiency and reliability. Currently available models for two-phase flow

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Sunwoong, Kim. "Predictive Validity of the Vehicle Seat Comfort Score by Using the Seat Design and Testing Factors." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003794.

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Vehicle seat comfort engineering is one of the most important things among vari-ous seat engineering fields. Many seat engineers want to make it easier to predict and improve comfort. There were several attempts, but it was not easy to predict due to the highly subjective nature of comfort. In this study, we tried to confirm the feasibility of developing a tool that can easily predict comfort by utilizing the main design factors of seats and vehicle packages. As Consumer’s various expe-riences while using cars were defined as comfort factors and models to predict them were developed. A total o

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