The research aims to find out the impact of wages and benefits systems on the performance of employees, which included the research community on a sample of employees in the company, and the sample consisted of (50) employees and an employee, A questionnaire composed as prepared (23) paragraph, use the promised statistically methods in data collected by the questionnaire analysis. The research reached a number of results, the most prominent of which were: There is a correlation between wage systems, benefits and performance of employees, and the presence of the impact of the systems of wages and benefits to the performance of employees. The research was presented a set of recommendations including: increasing the effectiveness of

Nitrogen (N) is a key growth and yield-limiting factor in cultivated rice areas. This study has been conducted to evaluate the effects of different conditions of N application on rice yield and yield components (Shiroudi cultivar) in Babol (Mazandaran, Iran) during the 2015- 2016 season. A factorial experiment executed of a Randomized Complete Block Design (RCBD) used in three iterations. In the first factor, treatments were four N amounts (including 50, 90, 130, and 170 kg N ha^-1), while in the second factor, the treatments consisted of four different fertilizer splitting methods, including T₁:70 % at the basal stage + 30 % at the maximum tillering stage, T₂:1/3 at the basal stage + 1/3 at the maximum ti

Introduction: Sleep, an essential therapeutic part of human physiology, Sleep problems was widespread among students in medical colleges, and excessive stress and the pressure of holding grades can affect their sleep quality. The relationship between sleep, stress and cognition/learning is far more complex than perceived. Material and Method: Cross sectional study was conducted in Al-Kindy College of Medicine, during the period from (2022 to 2023) academic year. The electronic questionnaire was distributed among all students. Analysis of data was carried out using IBM SPSS version 24. Results: A total of (500) medical students' online surveys were analyzed from AL-Kindy College of Medicine, The highest number of participants was fro

This study was conducted in the field of the Poultry Research Station of the animal resources Department / office of Agricultural Research / Ministry of Agriculture from the period 4th April to16th May2021.This study was aimed to investigate the effect of using avocado and chia oil and their mixture in broiler diets on the final productive performance and meat cholesterol concentration and measuring meat oxidation indicators after storing it for 60 days. 300 one-day-old (Ross308) chicks were fed on diets that used avocado oil and chia with percentages of 0, 0.2, 0.4, 0.6%, respectively, and their mixture consisting of 0.0, 0.1, 0.2, 0.3 each of avocado and chia oil (50% avocado + 50% chia oil). The experiment included 10 treatments

This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform wit

Photodetector based on Rutile and Anatase TiO₂ nanostructures/n-Si Heterojunction

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature