In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

The spread of novel coronavirus disease (COVID-19) has resulted in chaos around the globe. The infected cases are still increasing, with many countries still showing a trend of growing daily cases. To forecast the trend of active cases, a mathematical model, namely the SIR model was used, to visualize the spread of COVID-19. For this article, the forecast of the spread of the virus in Malaysia has been made, assuming that all Malaysian will eventually be susceptible. With no vaccine and antiviral drug currently developed, the visualization of how the peak of infection (namely flattening the curve) can be reduced to minimize the effect of COVID-19 disease. For Malaysians, let’s ensure to follow the rules and obey the SOP to lower the

Abstract

  The logistic regression model is one of the nonlinear models that aims at obtaining highly efficient capabilities, It also the researcher an idea of the effect of the explanatory variable on the binary response variable.                                                                                  &nb

Two molecular imprinted polymer (MIP) membranes for Levofloxacin (LEV) were prepared based on PVC matrix. The imprinted polymers were prepared by polymerization of styrene (STY) as monomer, N,N methylene di acrylamide as a cross linker ,benzoyl peroxide (BPO) as an initiator and levofloxacin as a template. Di methyl adepate (DMA) and acetophenone (AOPH) were used as plasticizers , the molecular imprinted membranes and the non molecular imprinted membranes were prepared.  The slopes and detection limits of the liquid electrodes ranged from -21.96 – -19.38 mV/decade and 2×10^-4M- 4×10^-4M, and Its response time was around 1 minute, respectively. The liquid  electrodes were packed with 0.1 M standar

Human Adenosine deaminase is an essential enzyme for modulating the bioactivity of thyroid hormones, and It is important for the maturation and differentiation of lymphocytes, although its clinical importance in thyroid diseases have yet to be identified. Objective: The aim of the current study is to determine the Adenosine deaminase concentration in healthy controls, and in autoimmune thyroid diseases such as Graves' Disease, and Hashimoto's Thyroiditis. Patients and methods: A total of 183 serum specimens of 103 female patients with autoimmune thyroid diseases and 80 healthy control groups were included in this study and collected from the Baghdad Medical City, Iraq. Quantitative Human Adenosine Deaminase ELISA kits were used to estimate

This research has come out with that, function-based responsibility accounting system has harmful side – effects preventing it of achieving its controlling objective, that is, goal congruence, which are due to its un integrated measures, its focus on measuring measurable behaviors while neglecting behaviors that are hardly measured, and its dependence on standard operating procedures.

In addition, the system hypotheses and measures are designed to fit previous business environment, not the current environment.

The research has also concluded that the suggestive model, that is, activity-based responsibility accounting is designed to get ride of harmful side – effects of functi

This paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF

This work aimed to investigate the prevalence of pathogenic fungi and evaluate the antifungal activity of Trichoderma orientale FMR12486 crude extract against pathogenic fungi isolated from patients attending the National Center for Thoracic and Respiratory Diseases (having a history of tuberculosis) and consultant of Dermatology of Baghdad hospital, Iraq. A total of 80 clinical specimens were collected: 20 skin scrapings specimens and 60 sputum specimens. The results of direct examination by KOH 10% and culture showed that 11 (55%) cases from 20 skin specimens were positive for fungal infections, while in the sputum specimens, 28 (47%) cases from 60 were positive. Candida albicans represented the most common fungal infection isolat