Concrete structures are exposed to aggressive environmental conditions that lead to corrosion of the embedded reinforcement and pre-stressing steel. Consequently, the safety of concrete structures may be compromised, and this requires a significant budgets to repair and maintain critical infrastructure. Prediction of structural safety can lead to significant reductions in maintenance costs by maximizing the impact of investments. The aim of this paper is to establish a framework to assess the reliability of existing post-tensioned concrete bridges. A time-dependent reliability analysis of an existing post-tensioned involving the assessment of Ynys-y-Gwas bridge has been presented in this study. The main cause of failure of this bridge was c

Purpose:  the purpose of study is estimate the Risk premium, Interest rate, Inflation and FDI in the through of Coronavirus in the MENA countries.   Theoretical framework: The theoretical framework included the study of the main variables, which are risk premium, interest rate, inflation, and foreign direct investment during the Corona virus pandemic.   Design/methodology/approach:  Concentrating on “COVID-19”, as an effective factor on the Foreign direct investment (FDI), I employ data of “MENA (Middle East and Northern Africa)” countries from 2000 to 2021 to investigate the impact of COVID-19, financial and macroeconomic indicators on FDI relying on the analytic research approach of Static panel data regression, includ

Many objective optimizations (MaOO) algorithms that intends to solve problems with many objectives (MaOP) (i.e., the problem with more than three objectives) are widely used in various areas such as industrial manufacturing, transportation, sustainability, and even in the medical sector.  Various approaches of MaOO algorithms are available and employed to handle different MaOP cases. In contrast, the performance of the MaOO algorithms assesses based on the balance between the convergence and diversity of the non-dominated solutions measured using different evaluation criteria of the quality performance indicators. Although many evaluation criteria are available, yet most of the evaluation and benchmarking of the MaOO with state-of-art a

The statistical distributions study aimed to obtain on best descriptions  of variable sets phenomena, which each of them got one behavior of that distributions .  The estimation operations study for that distributions considered of important things which could n't canceled in variable behavior study, as result  this research came as trial for reaching to best method for information distribution estimation which is generalized linear failure rate distribution, throughout studying the theoretical sides by depending on statistical posteriori methods  like greatest ability, minimum squares method and Mixing method (suggested method).        

The research

Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of

The aim of this research is controlling the amount of the robotic hand catching force using the artificial muscle wire as an actuator to achieve the desired response of the robotic hand in order to catch different things without destroying or dropping them; where the process is to be similar to that of human hand catching way. The proper selection of the amount of the catching force is achieved through out simulation using the fuzzy control technique. The mechanism of the arrangement of the muscle wires is proposed to achieve good force selections. The results indicate the feasibility of using this proposed technique which mimics human reasoning where as the weight of the caught peace increases, the force increases also with approximatel

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Image is an important digital information that used in many internet of things (IoT) applications such as transport, healthcare, agriculture, military, vehicles and wildlife. etc. Also, any image has very important characteristic such as large size, strong correlation and huge redundancy, therefore, encrypting it by using single key Advanced Encryption Standard (AES) through IoT communication technologies makes it vulnerable to many threats, thus, the pixels that have the same values will be encrypted to another pixels that have same values when they use the same key. The contribution of this work is to increase the security of transferred image. This paper proposed multiple key AES algorithm (MECCAES) to improve the security of the tran

In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor

Objective: The study aims at evaluating the psychological support and discharge plan from the hospital provided by nurses for woman undergone hysterectomy.
Methodology: The study uses descriptive design and non-probability (convenient) sample which is consisted of (40) nurses from (8) teaching hospitals in the City of Baghdad within the maternity wards. The study is carried out from 11 November 2020 to 27 June 2021. A observational tool is developed to evaluate the psychological support and the discharge plan after surgery. Content validity and internal consistency reliability are determined through pilot study. Data are collected through the use of the questionnaire and data are analyzed through the use of descriptive and inferentia