The current research aims to train students to take benefit of their studies to analyze and taste the artistic works as one of the most important components of the academic structure for students specializing in visual arts; then to activate this during training them the methods of teaching. Consequently, the capabilities of mind maps were employed as a tool that would be through freeing each student to analyze a model of artistic work and think about his analytical principles according to what he knows. Then, a start-up with a new stage revolves around the possibility of transforming this analysis into a teaching style by thinking about how the student would do. The same person who undertook the technical analysis should offer this work

Objective(s): To assess the practices of early childhood’s mothers regarding toilet training and to find out the relationship between mothers’ practices and their socio-demographic characteristics and their children’s demographic characteristics.
Methodology: A descriptive study is conducted at primary health care centers in Al-Rusafa District in Baghdad City for the period of September 19th 2020 to March 16th 2021. Non probability “convenient” sample of (225) early childhood’s mothers is selected. A questionnaire format is designed and composed of two parts: the first part includes mothers’ socio-demographic characteristics and their children and the second part includes structured close-ended questions to assess the p

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

In this study, the kinematic analysis including the forward and inverse kinematic developed for a 5 degree of freedom robotic arm. The forward kinematic is elaborated using Denavit-Hartenberg (DH) convention. Inverse Kinematic is established using Deep Neural Network (DNN) model with five hidden layer each contain 50 neurons fully connected using ReLu activation. A data of inputs and outputs are created and trained. The inputs are the end-effector position and orientation. The outputs are the joint angles of the manipulator. The data is generated by the forward kinematics, where a set of joint angles that limited by their corresponding ranges are inserted to the forward kinematic equations to result the end-effector positions and or

Community detection is useful for better understanding the structure of complex networks. It aids in the extraction of the required information from such networks and has a vital role in different fields that range from healthcare to regional geography, economics, human interactions, and mobility. The method for detecting the structure of communities involves the partitioning of complex networks into groups of nodes, with extensive connections within community and sparse connections with other communities. In the literature, two main measures, namely the Modularity (Q) and Normalized Mutual Information (NMI) have been used for evaluating the validation and quality of the detected community structures. Although many optimization algo

Vagrancy is global problem, but its geographical distribution differs from one society
to another and from one place to another inside the same society.Till now there isn't a real factor that can explain the phenomenon, spite that economy plays aconstituent and distinguishing part, and spite the fact that Vagrancy is considered a realdeviation that can be compared with criminality level, and cannot be separated from its effecton family, local society and school. In addition to unprecedented work under heavily pressurethat attack to a minimum protection and safety. Vagrant may be a child, a teen, a young, or
even an old man. Vagrancy thus means different people with different ages and not onlyprecisely children. Vagrant is not neces