Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

In this paper, two new simple, fast and efficient block matching algorithms are introduced, both methods begins blocks matching process from the image center block and moves across the blocks toward image boundaries. With each block, its motion vector is initialized using linear prediction that depending on the motion vectors of its neighbor blocks that are already scanned and their motion vectors are assessed. Also, a hybrid mechanism is introduced, it depends on mixing the proposed two predictive mechanisms with Exhaustive Search (ES) mechanism in order to gain matching accuracy near or similar to ES but with Search Time ST less than 80% of the ES. Also, it offers more control capability to reduce the search errors. The experimental tests

In this paper two axis sun tracking method is used to absorb maximum power from the sun's rays on the solar panel via calculating the sun’s altitude and azimuth angles, which describe the solar position on the Iraqi capital Baghdad for the hours 6:00, 7:00, 8:00, 9:00, 12:00, 15:00 and 17:00 per day. The angles were calculated in an average approach within one month, so certain values were determined for each month. The daily energy achieved was calculated for the solar tracking method compared with the fixed tracking method. Designed, modeled and simulated a control circuit consisting of reference position truth table, PI Controller and two servomotors that tracked the sun position to adjust the PV panel perpendicular

The present work aims to validate the experimental results of a new test rig built from scratch to evaluate the thermal behavior of the brake system with the numerical results of the transient thermal problem. The work was divided into two parts; in the first part, a three-dimensional finite-element solution of the transient thermal problem using a new developed 3D model of the brake system for the selected vehicle is SAIPA 131, while in the second part, the experimental test rig was built to achieve the necessary tests to find the temperature distribution during the braking process of the brake system. We obtained high agreement between the results of the new test rig with the numerical results based on the developed model of the brake

Littoral and benthic invertebrates from Roundwood Reservoir System were sampled. Oligochaetes and molluscs were the dominant organisms in the littoral and benthic areas Trichopterans and chironomids were the most abundant insect groups. Scuba diving samples reinforced that view. Other groups of macroinvertebrates were poorly represented. Vertical and horizontal hauls of zooplankton revealed that there were twelve species of zooplankton present. Daphnia hyalina Leydig and Bosmina coregoni Baird were the two dominant species.

A QR code is a type of barcode that can hold more information than the familiar kind scanned at checkouts around the world. The “QR” stands for “Quick Response”, a reference to the speed at which the large amounts of information they contain can be decoded by scanners. They are being widely used for advertising campaigns, linking to company websites, contest sign-up pages and online menus. In this paper, we propose an efficient module to extract QR code from background and solve problem of rotation in case of inaccurate image taken from mobile camera.