Abstract

 A surface fitting model is developed based on calorimeter data for two famous brands of household compressors. Correlation equations of ten coefficient polynomials were found as a function of refrigerant saturating and evaporating temperatures in range of (-35℃ to -10℃) using Matlab software for cooling capacity, power consumption, and refrigerant mass flow rate.

Additional correlations equations for these variables as a quick choice selection for a proper compressor use at ASHRAE standard that cover a range of swept volume range (2.24-11.15) cm³.

The result indicated that these surface fitting models are accurate with in ± 15% for 72 compressors model of cooling cap

We have studied Bayesian method in this paper by using the modified exponential growth model, where this model is more using to represent the growth phenomena. We focus on three of prior functions (Informative, Natural Conjugate, and the function that depends on previous experiments) to use it in the Bayesian method. Where almost of observations for the growth phenomena are depended on one another, which in turn leads to a correlation between those observations, which calls to treat such this problem, called Autocorrelation, and to verified this has been used Bayesian method.

The goal of this study is to knowledge the effect of Autocorrelation on the estimation by using Bayesian method. F

It is through a review of conversion of vegetable oils into glycidyl ethers focusing on their roles in achieving sustainability and improved epoxy resin performance. It involves functionalization of triglycerides in the form of epoxidation followed by glycidylation and yields bio-based monomers having improved mechanical as well as thermal properties. The review covers the underlying chemistry, production drivers, industrial applications, and future issues, supported by quantitative data and comparative studies. In addition, it integrates recent data on catalyst choice, feedstock flexibility, and environmental performance factors of bio-based resins, indicating their suitability for replacing traditional petroleum-based components.<

The study aimed to assess the frequency of invasive fungal infection in patients with respiratory diseases by conventional and molecular methods. This study included 117 Broncho alveolar lavage (BAL) samples were collected from patients with respiratory disease (79 male and 38 female) with ages ranged between (20-80) years, who attended Medicine Baghdad Teaching hospital and AL-Emamain AL-Khadhymian Medical City, during the period from September 2019 to April 2020. The results in PCR versus culture methods in this study showed that out of 117 samples of fungal infections 30(25.6 %) were detected by culture method, while the 24(20.5%) samples were detected by PCR technique, the most commonly diagnosed pathogenic fungi is Candida spp.

This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai