34 research outputs found

    Design and Performance Analysis of 250 kW Grid-Connected Photovoltaic System in Iraqi Environment Using PVsyst Software

    Get PDF
    A 250 kW grid-connected photovoltaic (PV) plant systems have been installed at the Ministry of Electricity in Baghdad and penetrated to the Iraqi national grid since November 2017. This is the first high power grid-connected PV system that has been installed in Iraq and it’s one of the four parts 1MW large-scale PV systems that should be completed in early of 2019. This paper presents the design and performance analysis of this system using a PVsyst software package. The performance ratio and different losses that occurred in the system are also calculated. The results show that the performance ratio is 75% using 1428 photovoltaic panels type (Sharp 175Wp) spread over an area of 1858 m². The total energy injected into the grid is (346692 kWh/year) .Based on the simulation results that developed in this paper, the practical PV grid-tied system has been implemented in Baghdad site

    Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

    Get PDF
    Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

    Cost-aware task scheduling in cloud computing environment

    Get PDF
    Cloud computing is a new generation of computing environment which delivers the applications as a service to users over the internet. The users can select any service from a list provided by service providers depending on their demands or needs. The nature of this new computing environment leads to tasks scheduling and load balancing problems which become a booming research area. In this paper, we have proposed Scheduling Cost Approach (SCA) that calculates the cost of CPU, RAM, bandwidth, storage available. In this approach, the tasks will be distributed among the VMs based on the priority given by user. The priority depends on the user budget satisfaction. The proposed SCA will try to improve the load balance by selecting suitable VM for each task. The results of SCA are compared with the results of FCFS and SJF algorithms which proves that, the proposed SCA approach significantly reduces the cost of CPU, RAM, bandwidth, storage compared to FCFS and SJF algorithms
    corecore