This research examines the future of television work in light of the challenges posed by artificial intelligence (AI). The study aims to explore the impact of AI on the form and content of television messages and identify areas where AI can be employed in television production. This study adopts a future-oriented exploratory approach, utilizing survey methodology. As the research focuses on foresight, the researcher gathers the opinions of AI experts and media specialists through in-depth interviews to obtain data and insights. The researcher selected 30 experts, with 15 experts in AI and 15 experts in media. The study reveals several findings, including the potential use of machine learning, deep learning, and na

IN this work, a titanium dental implant was modified by electro-polymerized of 4-allyl-2-methoxyphenol (Eugenol) using direct current lower than 3.5 volt. The modification of titanium dental implant was achieved to improve its corrosion resistant. Fourier transform infrared spectroscopy (FTIR) was employed to confirm the electro-polymerization of Eugenol to Poly Eugenol (PE) on pure titanium. Deposition of PE on titanium was confirmed by X-ray diffraction and was characterized by thermogravimetric analysis (TGA). The surface morphology of polymeric film were examined through scanning electron microscopy (SEM). Coated titanium by (PE) revealed a good corrosion protection efficiency even at temperature ranged (293-323)K in artificial saliva.

The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

<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

<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

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

The research aims to assess the claystone exposed in the Nfayil Formation (Middle Miocene) for Portland cement (P.C.) manufacturing based on mineralogy and geochemistry. The importance of the study is to avoid the miming of the agricultural soils that are mining now for the cement industry. Claystones of Nfayil Formation and the limestone of the Euphrates Formation were used to design the raw mixture as clay to limestone (1:3). The chemical composition (%) of the designed mixture was calculated using the Alligation Alternative Method (A.A.M.) as CaO (65.52), MgO (1.05), SiO2 (21.65), Al2O3 (7.43), Fe2O3 (2.62), Na2O3+K2O (1.52) and SO3 (0.26), which are suitable for P.C. The lime saturation factor (LSF = 92.8), silica saturation fac

New biscarboxylato zwitterionic ligands, namely bis(N-carboxylatoethyl)-4,4 -dipyridinum) L1 and bis(Ncarboxylatopropyl)-)-4,4 -dipyridinum) L2, were synthesized from the reaction of 4,4 -dipyridine with 3-bromopropanoic acid and 4-bromobutanoic acid, respectively. The reaction of these ligands and the azido coligand with some metal ions resulted in the formation of polymeric complexes of general formulae [Cr2(Ln)(N3)4]Cl2·H2O and [M2(Ln)(N3)4] xH2O, where (M = Mn(II), Fe(II), Co(II), Ni(II), Cu(II), Zn(II) and Cd(II); n = 1, 2; x = 1, 1, 1, 1, 0, 1, and 1, respectively.) The oxygens of the carboxylato group are coordinated to the metal ion in a bidentate fashion. The mode of bonding and overall geometry of the complexes were determin

The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu