Photovoltaic (PV) devices are widely used renewable energy resources and have been increasingly manufactured by many firms and trademarks. This condition makes the selection of right product difficult and requires the development of a fast, accurate and easy setup that can be implemented to test available samples and select the cost effective, efficient, and reliable product for implementation. An automated test setup for PV panels using LabVIEW and several microcontroller-based embedded systems were designed, tested, and implemented. This PV testing system was fully automated, where the only human intervention required was the instalment of PV panel and set up of required testing conditions. The designed and implemented system was

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

RA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2

This research is devoted to study the strengthening technique for the existing reinforced concrete beams using external post-tensioning. An analytical methodology is proposed to predict the value of the effective prestress force for the external tendons required to close cracks in existing beams. The external prestressing force required to close cracks in existing members is only a part from the total strengthening force.
A computer program created by Oukaili (1997) and developed by Alhawwassi (2008) to evaluate curvature and deflection for reinforced concrete beams or internally prestressed concrete beams is modified to evaluate the deflection and the stress of the external tendons for the externally strengthened beams using Matlab

The availability of low- cost adsorbent namely Al-Khriet ( a substance found in the legs of Typha  Domingensis) as an agricultural waste material, for the removal of lead and cadmium from aqueous solution was investigated. In the batch tests experimental parameters were studied, including adsorbent dosage between (0.2-1) g, initial metal ions concentration between (50-200) ppm (single and binary) and contact time (1/2-6) h. The removal percentage of each ion onto Al-Khriet reached equilibrium in about 4 hours. The highest adsorption capacity was for lead (96%) while for cadmium it was (90%) with 50 ppm ions concentration, 1 g dosage of adsorbent and pH 5.5. Adsorption capacity in the binary mixture were reduce at about 8% for lead a

This study looks into the many methods that are used in the risk assessment procedure that is used in the construction industry nowadays. As a result of the slow adoption of novel assessment methods, professionals frequently resort to strategies that have previously been validated as being successful. When it comes to risk assessment, having a precise analytical tool that uses the cost of risk as a measurement and draws on the knowledge of professionals could potentially assist bridge the gap between theory and practice. This step will examine relevant literature, sort articles according to their published year, and identify domains and qualities. Consequently, the most significant findings have been presented in a manne

A series of new imides compounds[1-4] were synthesized from reaction of tetrachlorophthalic anhydride or nitro phthalic anhydride or malic anhydride or Succinic anhydride  with  4-amino benzene thiol under fusion conditions. Chloroacetic acid has been added after compounds [1-4] reacted with distilled H2O and Na2CO3, producing compounds [5-8]. In benzene, compounds [5-8] also interacted with the thionyl chloride to produce [9-12]. Poly (vinyl alcohol) was chemically modified by reacting PVA with compounds [9-12] and dimethyl formamide to produce compounds [13-16]. Iron oxide nanoparticles (IONPs) are mixed with modified PVA [13-16] to create nanocomposites [17-20]. Spectral and analytical data from synthesized compounds, such as 1

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

Deep drawing process to produce square cup is very complex process due to a lot of process parameters which control on this process, therefore associated with it many of defects such as earing, wrinkling and fracture. Study of the effect of some process parameters to determine the values of these parameters which give the best result, the distributions for the thickness and depths of the cup were used to estimate the effect of the parameters on the cup numerically, in addition to experimental verification just to the conditions which give the best numerical predictions in order to reduce the time, efforts and costs for producing square cup with less defects experimentally is the aim of this study. The numerical analysis is used to study

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