In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

Objective: The aim of the study to evaluate the nursing care management for diabetes mellitus patient
with total hip replacement after fractured hip.
Methodology: A field study carried out on patients with diabetes mellitus and have total hip
replacement after fractured hip in orthopedic ward at the hospital of surgical specialization (malefemale)during
January 2002 to January 2003.Physical and psychological nursing
assessment
immediately after the surgery was done for the both subjects (control and experimental) and then a
scientific management with daily nursing care were provided to the experimental subject with daily
nursing care to the patient condition by using a scientific and practical methods and leave th

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

Breast cancer is highlighted in recent research as one of the most prevalent types of cancer. Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on may greatly improve the chances of recovery by accurately predicting outcomes and developing suitable treatment plans. Grading breast cancer properly, especially evaluating nuclear atypia, is difficult owing to faults and inconsistencies in slide preparation and the intricate nature of tissue patterns. This work explores the capability of deep learning to extract characteristics from histopathology photos of breast cancer. The research introduces a new method called SMOTE-based Convolut

The implementation of the concept of project scheduling in the organizations generally requires a set of procedures and requirements, So, most important of all is the understanding and knowledge of the tools and techniques which are called the methods of scheduling projects. Consequently, the projects of the municipality administration in the holy governorate of Karbala suffer from the problem of delaying their projects and chaos in the ways of implementation. To provide assistance to this directorate and to demonstrate how to schedule projects using one of the advanced scientific methods that proved their ability to schedule any project and its potential to accelerate the time of completion, as well as ease of use and effectiven

Introduction: The association between acute stroke and
renal function is well known. The aim of this study is to
know which group of patients with acute stroke is more
likely to have undiagnosed Chronic Kidney Disease and
which risk factors are more likely to be associated with.
Methods:We studied 77 patients who were diagnosed to
have an acute stroke.Patients were selected between
April2011andJune 2011 using the " 4-variable
Modification of
Diet in Renal Disease Formula " which estimates
Glomerular Filtration Rate using four variables :serum
creatinine ,age ,race and gender.
Results :The study included 38 male and 39 females
patients ,aged (35-95) years. Glomerular Filtration Rate in
patients wi