<p>Energy and memory limitations are considerable constraints of sensor nodes in wireless sensor networks (WSNs). The limited energy supplied to network nodes causes WSNs to face crucial functional limitations. Therefore, the problem of limited energy resource on sensor nodes can only be addressed by using them efficiently. In this research work, an energy-balancing routing scheme for in-network data aggregation is presented. This scheme is referred to as Energy-aware and load-Balancing Routing scheme for Data Aggregation (hereinafter referred to as EBR-DA). The EBRDA aims to provide an energy efficient multiple-hop routing to the destination on the basis of the quality of the links between the source and destination. In view of this goal, a link cost function is introduced to assess the quality of the links by considering the new multi-criteria node weight metric, in which energy and load balancing are considered. The node weight is considered in constructing and updating the routing tree to achieve dynamic behavior for event-driven WSNs. The proposed EBR-DA was evaluated and validated by simulation, and the results were compared with those of InFRA and DRINA by using performance metrics for dense static networks.</p>
This work involves the calculation of the cooling load in Iraqi building constructions taking in account the effect of the convective heat transfer inside the buildings. ASHRAE assumptions are compared with the Fisher and Pedersen model of estimation of internal convective heat transfer coefficient when the high rate of ventilation from ceiling inlet configuration is used. Theoretical calculation of cooling load using the Radiant Time Series Method (RTSM) is implemented on the actual tested spaces. Also the theoretical calculated cooling loads are experimentally compared by measuring the cooling load in these tested spaces. The comparison appears that using the modified Fisher and Pedersen model when large ventilation ra
... Show MoreBy using precipitation polymerization, liquid electrodes of polymers imprinted with Mebeverine hydrochloride and metronidazole benzoate were created whereas the imprinted polymer (MIP) and non imprinted (NIP) polymers were prepared by using Mebeverine hydrochloride and Metronidazole benzoate qua a template. In the polymerization process, 2-Acrylamido-2-methyl-1-propane Sulphonic acid (AMPS) or 1-Vinylimidazole (VIZ) was used qua monomer, pentaerythritol triacrylate (PETRA) or Divinylbanzene (DVB) was used qua a cross-linker while benzoyl peroxide (BPO) was used as an initiator. The MIP membranes and the membranes of NIP were created by using Dibutyl Sebacate (DBS) and Tris(2-ethylhexyl)phosphate(TEHP) qua plasticizers
... Show MoreDiscriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.
In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.
This research includes the use of an artificial intelligence algorithm, which is one of the algorithms of biological systems which is the algorithm of genetic regulatory networks (GRNs), which is a dynamic system for a group of variables representing space within time. To construct this biological system, we use (ODEs) and to analyze the stationarity of the model we use Euler's method. And through the factors that affect the process of gene expression in terms of inhibition and activation of the transcription process on DNA, we will use TF transcription factors. The current research aims to use the latest methods of the artificial intelligence algorithm. To apply Gene Regulation Networks (GRNs), we used a progr
... Show MoreThis paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).
Iraq, home of the Tigris and Euphrates rivers, has survived an extreme deficiency of surface water assets over the years. The gap is due to the decline of the Iraqi water share every year, as well as a high demand for water use from different sectors, particularly agriculture.
Dam development has long given significant economic benefits to Iraq in circulating low‐priced electricity and supporting low‐income farmers by supplying them with a free irrigation system (Zakaria et al, 2012). This encouraged domestic consumption and investment.
Despite the fact that numerous advantages are expected from dam construction, it should be painstakingly assessed, utilizing cost