In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

        In this paper, new transform with fundamental properties are presented. The new transform has many interesting properties and applications which make it rival to other transforms.

Furthermore, we generalize all existing differentiation, integration, and convolution theorems in the existing literature. New results and new shifting theorems are introduced. Finally, comprehensive list of this transforms of functions will be providing.

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

A land magnetic survey was carried out along regional profile, which is located at the north part of the Iraqi western desert. It starts from al –Qaam City (at north) toward Rutba City (at south) with a total length of 238km. The survey was carried out along the paved road between the two cities, About 113 measuring points were done with inter-station distance of 2 km (for 198 km) and 2 to 5km (for 40km). Two proton magnetometers were used in this survey. One of them is used for base station monitoring, which was fixed as of Salah Aldin field (Akkas). Its readings were used for diurnal corrections. All magnetic measurements were corrected for normal and topographic corrections. The readings were reduced to a certain base level. The resu

Finite Element Approach is employed in this research work to solve the governing differential equations related to seepage via its foundation's dam structure. The primary focus for this reason is the discretization of domain into finite elements through the placement of imaginary nodal points and the discretization of governing equations into an equation system; An equation for each nodal point or part, and unknown variables are solved. The SEEP / W software (program) is a sub-program of the Geo-Studio software, which is used by porous soil media to compensate for the problems of seepage. To achieve the research goals, a study was carried out on Hemrin dam, which located in the Diyala River 100 km northeast of Baghdad, Iraq. Thus, o

Two dimensional meso-scale concrete modeling was used in finite element analysis of plain concrete beam subjected to bending. The plane stress 4-noded quadrilateral elements were utilized to model coarse aggregate, cement mortar. The effect of aggregate fraction distribution, and pores percent of the total area – resulting from air voids entrapped in concrete during placement on the behavior of plain concrete beam in flexural was detected. Aggregate size fractions were randomly distributed across the profile area of the beam. Extended Finite Element Method (XFEM) was employed to treat the discontinuities problems result from double phases of concrete and cracking that faced during the finite element analysis of concrete beam. Crac

In this paper, a least squares group finite element method for solving coupled Burgers' problem in   2-D is presented. A fully discrete formulation of least squares finite element method is analyzed, the backward-Euler scheme for the time variable is considered, the discretization with respect to space variable is applied as biquadratic quadrangular elements with nine nodes for each element. The continuity, ellipticity, stability condition and error estimate of least squares group finite element method are proved.  The theoretical results  show that the error estimate of this method is . The numerical results are compared with the exact solution and other available literature when the convection-dominated case to illustrate the effic