The present work aims to validate the experimental results of a new test rig built from scratch to evaluate the thermal behavior of the brake system with the numerical results of the transient thermal problem. The work was divided into two parts; in the first part, a three-dimensional finite-element solution of the transient thermal problem using a new developed 3D model of the brake system for the selected vehicle is SAIPA 131, while in the second part, the experimental test rig was built to achieve the necessary tests to find the temperature distribution during the braking process of the brake system. We obtained high agreement between the results of the new test rig with the numerical results based on the developed model of the brake

The applications of Multilevel Converter (MLC) are increased because of the huge demand for clean power; especially these types of converters are compatible with the renewable energy sources. In addition, these new types of converters have the capability of high voltage and high power operation. A Nine-level converter in three modes of implementation; Diode Clamped-MLC (DC-MLC), Capacitor Clamped-MLC (CC-MLC), and the Modular Structured-MLC (MS-MLC) are analyzed and simulated in this paper. Various types of Multicarrier Modulation Techniques (MMTs) (Level shifted (LS), and Phase shifted (PS)) are used for operating the proposed Nine level - MLCs. Matlab/Simulink environment is used for the simulation, extracting, and ana

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

Self-Assertion is the individual ability to express any emotion well, except the anxiety. The decrease of the individuals asserting behavior makes them face many difficulties that prevent their social adjustment. Moreover it reflexes many negative behavioral and physical cases. The individual, who fails to express his or her negative feelings in required situations, feels with dissatisfaction, loneliness, depression, anxiety, social anxiety, conflict, and psychological disorder.
Accordingly, the importance of this study is represented in studying the self-assertion and studying the university students who reflect the strength of society.
The following are the two aims of the study:
1. Construct an asserting behavior scale.
2.

there is a need to use the teardown Technique in a various fields and different motives and used often by economic units as a technique to help other techniques for example, used by some economic units for the analysis of other economic units of products in order to work on the development of products and look for opportunities to improve product quality and avoid product errors competitor or reduce its costs, in addition to the services provided by quality control is used ISO 17025 integration with unassembled analysis to adjust the quality of the product by comparing the pieces produced with designed models that are also the product as a whole compared with the original design

In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T

DBNRHM Sami, International Journal of Research in Social Sciences and Humanities, 2020

The current research tackles the self-efficacy and its relation to the cognitive assessment for the daily disturbances for the University of Baghdad students. Two criteria have been adopted to achieve the objectives of the research. The sample of this study consists of 200 male and female students who were chosen randomly. The data were analyzed statistically, revealing that the university students owned their own self-efficacy as well as a cognitive assessment for the daily disturbances and they recognized them as self-threatening. The results also indicated the existence of a prediction activity in the field of the cognitive assessment to the daily disturbances selection. In light of the acquired results, the study recommends the neces