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The deficit in electricity and high diesel costs affects the pumping requirements of community water supplies and irrigation; so using solar energy for water pumping is a promising alternative to conventional electricity and diesel based pumping systems. Water pumping system has a long history, so many methods have been developed to pump water. Manual pumping is the common method for many years, but it is impractical for many applications, such as unmanned or remote wells. Many pumping systems require an independent power source like an engine or electric power. Engines can provide the higher amount of the water, but they are requiring the fuel and regular maintenance. Due to minimize the cost the alternative source is used such as solar energy. This paper presents the study of a water pumping system powered by photovoltaics (PV) solar. The purpose of this article is to design, optimum sizing the batteries and the PV modules for the water pumping system and also to study about the characteristic of charging and discharging the batteries. Optimum sizing from SANDIA National Laboratories were used in sizing this system. The system based on the standalone system configuration which contains PV module, charge controller, batteries, and load. Based on this research, the design and sizing are able to running the system within the desired autonomy. The pattern of charging and discharging also been captured during this research. [ABSTRACT FROM AUTHOR]

The network lifetime is a vital research area of wireless sensor networks (WSNs), K-means are potential solutions that prolongs the network lifetime. However, there are limitations hampering these algorithms, such as the number of clusters is a fixed value and the initial positions of the cluster centroids are predetermined locations. A bad choice of initial centroids leads to a bad clustering and a high energy consumption, thus this paper proposes two phases optimization of initial centroids called X-means; first K-means cluster formed then they are slit into multiple clusters. In general, clusters constructed using tentative CHs selected by K-means algorithm as an initial phase, After that, each cluster gives birth to children, then these children compete to form clusters and the surviving children are the final clusters. The simulation results showed that X-means outperforms the traditional K-means algorithm and it has reduced energy consumption by optimizing clusters initial positions. [ABSTRACT FROM AUTHOR]

One of Von Neumann architecture's most important limitations is the minimal memory-processor bandwidth. In the processor itself, the cost of moving data back and forth between memory and processor is significantly higher than the processing. This architecture has a significant impact on the Big Data and data-intensive application, such as data encryption and decryption analysis that spends most of the processing time moving data. The principle of in-memory processing, which is based on the ability to perform the logic operation on the physical memory structure using a crossbar topology and non-volatile resistive-switching memristor technology, has recently been proposed. This paper presents a scheme to map the digital magnitude comparator circuit on the memristive memory crossbar array. Memristor-aided logic is used to map the 2-bit, 4-bit, 8-bit, 16-bit, 32-bit, and 64-bit magnitude comparator circuit on the memristive memory crossbar array. The simulation results show that, for the 64-bit word size, the parallel mapping exhibits 1.8 better performance in total ex×ecution time than sequential mapping but has a trade-off in terms of energy consumption and area utilization. Meanwhile, the total crossbar area can be reduced by 1.4 for sequential mapping and 2.5 for parallel mapping both by using the overlapping technique. [ABSTRACT FROM AUTHOR]