The important device in the Wireless Sensor Network (WSN) is the Sink Node (SN). That is used to store, collect and analyze data from every sensor node in the network. Thus the main role of SN in WSN makes it a big target for traffic analysis attack. Therefore, securing the SN position is a substantial issue. This study presents Security for Mobile Sink Node location using Dynamic Routing Protocol called (SMSNDRP), in order to increase complexity for adversary trying to discover mobile SN location. In addition to that, it minimizes network energy consumption. The proposed protocol which is applied on WSN framework consists of 50 nodes with static and mobile SN. The results havw shown in each round a dynamic change in the route to reach mobi

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

In this study, the kinematic analysis including the forward and inverse kinematic developed for a 5 degree of freedom robotic arm. The forward kinematic is elaborated using Denavit-Hartenberg (DH) convention. Inverse Kinematic is established using Deep Neural Network (DNN) model with five hidden layer each contain 50 neurons fully connected using ReLu activation. A data of inputs and outputs are created and trained. The inputs are the end-effector position and orientation. The outputs are the joint angles of the manipulator. The data is generated by the forward kinematics, where a set of joint angles that limited by their corresponding ranges are inserted to the forward kinematic equations to result the end-effector positions and or

Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification. Different

Conveyor belt systems facilitate the movement of goods and materials, making them an essential part of various fields. Deep learning control methods are therefore indispensable to assure their energy efficiency and optimal motor speed. Here, training is conducted via a convolutional neural network with transfer learning using VGG16 base net. Feature extraction layers are fixed, whilst fully connected layers are replaced. Thirty-three appropriate object classes are considered for classification, and images are acquired using an overhead camera. The obtained weight values are transmitted to Arduino that uses these data to control the stepper motor speed for optimal performance and minimum energy consumption, achieving approximate esti

The Accommodation industry in Iraq suffers from many problems, especially after 2003, when the Accommodation industry was exposed to many crises due to the security and political situation in Iraq, which negatively affected the administrative operations inside the industry and created many problems, the most important of which are deterioration, high costs and poor performance, so some hotel administrations sought To find alternative solutions that help in the advancement of hotels, one of the proposals is to go to technology, as technology is currently one of the most important solutions to solve large complex problems, as the world has turned to automation to solve complex problems such as increasing production, reducing costs, and rai

The research acquires its importance by motivating the behavioural side of the employees to apply modern technology in the work, because of its great importance in increasing the efficiency of employees’ performance and excellence. The research was based on two main hypotheses to show the relationship and impact between the variables through the adoption of a questionnaire to collect data and information related to the research, which consisted of (50) people from administrators working at different levels, based on personal interviews and field visits to collect research data. The data collection process was subjected to statistical analysis using the statistical program (SPSS) (Statistical package for social science) to reach

      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

Abstract 

The catalytic cracking conversion of Iraqi vacuum gas oil was studied on large and medium pore size (HY, HX, ZSM-22 and ZSM-11) of zeolite catalysts. These catalysts were prepared locally and used in the present work. The catalytic conversion performed on a continuous fixed-bed laboratory reaction unit. Experiments were performed in the temperature range of 673 to 823K, pressure range of 3 to 15bar, and LHSV range of 0.5-3h^-1. The results show that the catalytic conversion of vacuum gas oil increases with increase in reaction temperature and decreases with increase in LHSV. The catalytic activity for the proposed catalysts arranged in the following order:

HY>H