The Next-generation networks, such as 5G and 6G, need capacity and requirements for low latency, and high dependability. According to experts, one of the most important features of (5 and 6) G networks is network slicing. To enhance the Quality of Service (QoS), network operators may now operate many instances on the same infrastructure due to configuring able slicing QoS. Each virtualized network resource, such as connection bandwidth, buffer size, and computing functions, may have a varied number of virtualized network resources. Because network resources are limited, virtual resources of the slices must be carefully coordinated to meet the different QoS requirements of users and services. These networks may be modified to achieve QoS using Artificial Intelligence (AI) and machine learning (ML). Developing an intelligent decision-making system for network management and reducing network slice failures requires reconfigurable wireless network solutions with machine learning capabilities. Using Spiking Neural Network (SNN) and prediction, we have developed a 'Buffer-Size Management' model for controlling network load efficiency by managing the slice's buffer size. To analyze incoming traffic and predict the network slice buffer size; our proposed Buffer-Size Management model can intelligently choose the best amount of buffer size for each slice to reduce packet loss ratio, increase throughput to 95% and reduce network failure by about 97%.
This 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).
Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.
The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme
... Show MoreHeat transfer performance of two horizontal parallel plates subjected to discrete heating from the upper plate is studied and analyzed under the condition of different gap size between the heating elements with water as the working fluid. The investigation includes the variation of Reynolds number and the heat flux along with the position of the heating elements to discover the effect of different boundary conditions on the gap size variation. Results show that gap size between the heating elements has a crucial impact on the heat transfer process inside the channel, when the gap size increased a remarkable enhancement is achieved. This result is also confirmed with the investigated range of Reynolds number and the heating value. Results al
... Show MoreA study of the effects of the discharge (sputtering) currents (60-75 mA) and the thickness of copper target (0.037, 0.055 and 0.085 mm) on the prepared samples was performed. These samples were deposited with pure copper on a glass substrate using dc magnetron sputtering with a magnetic flux density of 150 gauss at the center. The effects of these two parameters were studied on the height, diameter, and size of the deposition copper grains as well as the roughness of surface samples using atomic force microscopy (AFM).The results of this study showed that it is possible to control the specifications of copper grains by changing the discharge currents and the thickness of the target material. The increase in discharge curre
... Show MoreThe purpose of this research is to find the estimator of the average proportion of defectives based on attribute samples. That have been curtailed either with rejection of a lot finding the kth defective or with acceptance on finding the kth non defective.
The MLE (Maximum likelihood estimator) is derived. And also the ASN in Single Curtailed Sampling has been derived and we obtain a simplified Formula All the Notations needed are explained.
The size and the concentration of the gold nanoparticles (GNPs)
synthesized in double distilled deionized water (DDDW) have been
found to be affected by the laser energy and the number of pulses.
The absorption spectra of the nanoparticles DDDW, and the
surface plasmon resonance (SPR) peaks were measured, and found to
be located between (509 and 524)nm using the UV- Vis
spectrophotometer. SPR calculations, images of transmission
electron microscope, and dynamic light scattering (DLS) method
were used to determine the size of GNPs, which found to be ranged
between (3.5 and 27) nm. The concentrations of GNPs in colloidal
solutions found to be ranged between (37 and 142) ppm, and
measured by atomic absorptio
Bruggeman's symmetric effective-medium model of vanadium oxide is introduced, in which the transmittance was studied because of its importance in the subject of smart windows, it was studied from ( 5 nm-1000 nm) for each of the regions of the electromagnetic spectrum, the ultraviolet and visible region, and the near and medium sub-regions of the infrared and the results showed that the importance of studying the transmittance of vanadium oxide as a good candidate For this kind of industries. Our results showed that the small sizes of the material guarantee an almost constant and high transmittance to the visible region; this is due to the agreement of the direction of the dipoles in the material with the direction of the internal el
... Show MoreRadiotherapy is medical use of ionizing radiation, and commonly applied to the cancerous tumor because of its ability to control cell growth. The amount of radiation used in photon radiation therapy called dose (measured in grey unit), which depend on the type and stage of cancer being treated. In our work, we studied the dose distribution given to the tumor at different depths (zero-20 cm) treated with different field size (4×4- 23×23 cm). Results show that the deeper treated area has less dose rate at the same beam quality and quantity. Also it has been noted increasing in the field increasing in the depth dose at the same depth even if the radiation energy is constant. Increasing in radiation dose attributed to the scattere
... Show MoreSynthetic polymers such as polyurethane are used widely in the field of biomedical applications such as implants or part of implant systems.
This paper focuses on the preparation of base polymer matrix composite materials by (Hand Lay-Up) method, and studying the effect of selected grain size (32, 53, 63, 75, and 90) µm of (Reenia) particles on some properties of the prepared composite.
Mechanical tests were used to evaluate the prepared system (Tensile, Compression, Impact, and Hardness) tests, and a physical test of (Water absorption %), and all tests were accomplished at room temperature.
Where results showed tensile test (maximum tensile strength and modulus of elasticity) high at small grain size while
... Show More