The dependence of the energy losses or the stopping power for the ion contribution in D- T hot plasma fuels upon the corresponding energies and the related penetrating factorare arrive by using by a theoretical approximation models. In this work we reach a compatible agreement between our results and the corresponding experimental results.

The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

The objective of this work is to investigate the performance of a conventional three phase induction motor supplied by unbalanced voltages. An effort to study the motor steady state performance under this disturbance is introduced. Using per phase equivalent circuit analysis with the concept of symmetrical components approach, the steady state performance is theoretically calculated. Also, a model for the induction motor with the MATLAB/Simulink SPS tools has been implemented and steady state results were obtained. Both results are compared and show good correlation as well. The simulation model is introduced to support and enhance electrical engineers with a complete understanding for the steady state performance of a fully loaded induc

Abstract

The researcher seeks, through different aspects of the search, to reach a set of objective concerning in content creation a clear vision about conceptual and practical dimension of relation and effects between (Leader-Member Exchange, and Organizational Commitment) to construct a framework of a pragmatic model as a solution to research problem and it questions. The theoretical problem is derived basically from the scarcity of Arab studies and researches that deal by study and analyses for such important of The two variables blend. The practical problem depends in deriving from reality of every day work in the Iraqi ministry of defense.

On this basis, a formula of research problem for pur

This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota

The paper presents research results of the vibration transmitted from the steering wheel of the tractor with a 2-wheel drive to the driver’s hands. The vibration measurements were carried out on the tractor randomly chosen from the collage of agriculture / university of Baghdad. Before testing the tractor was examined and adjusted following the producer’s recommendations. The vibration levels were measured during the operation tillage at idling and at full load .The field was 31.7 m above level sea. Soil was treated at soil constant moisture (17-20 %) with depth of plowing (17 cm). During operation the weather temperature was measured (15 C) and humidity was ( 27 % ) The vibration level on the steering wheel was measured and analyzed .T

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve