This paper details the process of designing, analysing, manufacturing, and testing an integrated solid-state hydrogen storage system. Analysis is performed to optimise flow distribution and pressure drop through the channels, and experimental investigations compare the effects of profile shape on the overall power output from the fuel cell. The storing of hydrogen is given much attention in the selection of a storage medium, and the effect of a cooling system to reduce the recharging time of the hydrogen storage vessel. The PTFE seal performed excellently, holding pressure over 60 bar, despite requiring changing each time the cell is opened. The assembly of the vessel was simple and straightforward, and there was no indication of pressure

This paper introduces experimental results of eighteen simply supported reinforced concrete beams of cross sections ( ) and length 3000 mm to study the effect of lacing reinforcement on the performance of such beams under static and fatigue loads. Twelve reinforced concrete beams (two of them are casted with vertical shear reinforcement used as control beams) are tested under four points bending loading with displacement control technique and six laced reinforced concrete beams were exposed to high frequency (10 Hz) by fixing the fatigue load in each cycle. Three parameters are used in the designed beams, which are: lacing bar diameter (4mm, 6mm, and 8mm), lacing bar inclination angle to horizontal , and lacing steel rat

Abstract

The aim of the research is to clarify the requirements of the qualification of the external auditor in Iraq and the extent of their impact on the quality of the professional performance of the audit process. The research was based on analyzing the results of the questionnaire prepared for the impact of qualifications on the quality of professional performance. The researcher has reached a number of conclusions, the most important of which is that a highly qualified and unethical auditor has a greater negative impact on the quality of professional performance than those with low qualifications. The most important recommendations of the research were the need to pay

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

The research aims to identify how to enhance the quality of the human resources, focusing on four dimensions (efficiency, effectiveness, flexibility, and reliability), by adopting an adventure learning method that combines theoretical and applied aspects at the same time, when developing human resources and is applied using information technology, and that Through its dimensions, which are (cooperation, interaction, communication, and understanding), as the research problem indicated a clear deficiency in the cognitive perception of the mechanism of employing adventure learning dimensions in enhancing human resources quality, so the importance of research was to present treatments and proposals to reduce this problem. To achieve

Personalized Medicine represents a recent revolution in healthcare practice, focusing on tailoring different therapies to be precise for a specific individual; this is aided by exploring the number of genetic predispositions and lifestyle choices that fit each individual. In this article, the authors utilize and gather recent literature and opinions to discuss the impact of personalized medicine on chronic disease management and patient quality of life. Additional attention is paid to limits and possible ethical issues. Chronic diseases such as Hypertension, Diabetes, and chronic kidney diseases adversely affect multiple health indicators, including Quality of Life (QoL) and well-being. This will have additional impacts on physical

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par