The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura

Objective: The aim of this study is to determine the means and the difficulties faced by students of
nursing maternal and child health nursing / College of Nursing / University of Baghdad in obtaining scientific
information in practical training.
Methodology: A purposive sample of (100) Nursing college student - Maternal and Child Health Nursing
Department were selected. Data were collected through the use of the questionnaire form during the
period from the November 2010 to April 2011. Descriptive statistical procedures were used to analyze the
data.
Results: The results showed that the highest percentage of members of the study sample aged between
(20-21 years), females are the most inhabitants of the city of Ba

conventional FCM algorithm does not fully utilize the spatial information in the image. In this research, we use a FCM algorithm that incorporates spatial information into the membership function for clustering. The spatial function is the summation of the membership functions in the neighborhood of each pixel under consideration. The advantages of the method are that it is less
sensitive to noise than other techniques, and it yields regions more homogeneous than those of other methods. This technique is a powerful method for noisy image segmentation. 

Based on analyzing the properties of Bernstein polynomials, the extended orthonormal Bernstein polynomials, defined on the interval [0, 1] for n=7 is achieved. Another method for computing operational matrices of derivative and integration D_b and R_(n+1)^B respectively is presented. Also the result of the proposed method is compared with true answers to show the convergence and advantages of the new method.

In this work, using GPS which has best accuracy that can be established set of GCPs, also two satellite images can be used, first with high resolution QuickBird, and second has low resolution Landsat image and topographic maps with 1:100,000 and 1:250,000 scales. The implementing of these factors (GPS, two satellite images, different scales for topographic maps, and set of GCPs) can be applying. In this study, must be divided this work into two parts geometric accuracy and informative accuracy investigation. The first part is showing geometric correction for two satellite images and maps.
The second part of the results is to demonstrate the features (how the features appearance) of topographic map or pictorial map (image map), Where i

Alkaloids are regarded as important nitrogen-containing chemical compounds that serve as a rich source for discovering and developing new drugs where most plant-origin alkaloids have antiproliferation effects on different kinds of cancers. Alkaloids’ continence of Calotropis procera leaves are detected by two biochemical alkaloid reagents. Also GC-MS analysis for leaf alkaloid extract was done that showed the existence of one type of alkaloid compound at retention time12.8min detected as colchicine (C₂₂H₂₅N0₆( by comparing it with colchicine standard reference (Sigma Aldrich) with M.wt 399g/mol and percentage area 7.1%. Furthermore, identification, separation, and purification

The research aims to measure the impact of knowledge management processes individually and in total in the innovative marketing.

We depart search of a problem expressed in a number of intellectual and practical questions, the application of this research in the General Company for Vegetable Oil Industry, represented composed a sample of (63) (Director General and Deputy Director General and Director of the Department and the Division) in the company researched, it has been designed measuring instrument to collect the necessary data either statistical means they are the percentage and the arithmetic mean and standard deviation and coefficient of variation and the coefficient of simple correlation and model

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol