In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.

The effect of 532nm Diode Pumped Solid State (DPSS) laser at power density of 5.234 W/cm2 on the growth of Gram-negative Pseudomonas aeruginosa and Gram-positive Staphylococcus aureus was evaluated. These bacteria were isolated from samples taken from burn and infected wound areas of 55 patients admitted to the burn-wound unit in Al-Kindy teaching hospital in Baghdad during the period from October 2012 to March 2013. Each isolate was identified using microscopic, cultural and biochemical methods. A standard bacterial suspension was prepared for each isolate. Serial dilutions were then prepared and a dilution of 10-5 was selected. Irradiation experiments included four groups: (L-P-) bacterial suspension in saline solution, (L-P+) bacteria

Maintaining the quality of apricot fruits during storage is not an easy task due to the changes in their physical and chemical properties, so it is necessary to use less expensive, easy to apply, environmentally friendly, and safer preservatives to maintain the nutritional value of apricot. The damage to some fruits during storage can be a source of infection, which leads to the damage of healthy fruits more quickly, which requires building an intelligent model to detect damaged fruits. The aim of the research is to study the effect of immersing apricots in lemon juice once and sugar-water solution again on the quality properties of apricots, including sweetness, color, hardness, and water content. On the other hand, the YOLOv7 algorithm wa

Background: Oral pyogenic granuloma (PG) is a clinicopathological entity that could develop due to the reaction to a variety of stimuli, such as low-grade local irritation, traumatic damage, and hormonal stimulation. There are two histopathological types of pyogenic granuloma; lobular type -capillary hemangioma (LCH) and non-lobular type; with PG,LCH has highly vascular, diffuse capillary growth while non- lobular variant mimicking granulation tissue with heavily inflammated stroma. The study aims were to review the clinical  and histopathological spectrum of an oral pyogenic granuloma from different intraoral sites in order to avoid diagnostic pitfalls associated with similar morphological lesions and to determine

Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed  method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi

Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

This study explores the barriers to adopting green environmental criteria in Supplier Selection (SS) within the Iraqi food industry. It aims to enhance the understanding of sustainable supply chain management in developing nations, with a particular focus on the Iraqi context. A case study approach was utilized to identify eleven key green environmental criteria and 54 sub-criteria, alongside seven major barriers to their adoption. The Best–Worst Method (BWM) was employed to rank the criteria, and Fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) was used to prioritize the barriers. The analysis revealed that Environmental Management Systems are the most critical criterion for SS. On the other hand, legislation and policies emerged