Cleft / palate is one of the common congenital deformities in craniofacial region, associated with different types of dental anomalies like (Tooth agenesis, impaction, and supernumerary teeth) with marked changes in palatal dimensions. This study aimed to determine the prevalence of teeth agenesis and dental anomalies in cleft lip/palate patients using CBCT, and to compare the palatal dimension of cleft group with control subjects. Twenty-eight cleft cases collected during the period from 2015 to 2022, CBCT images evaluated, the study sample classified into two groups (14 bilateral and 14 unilateral cleft lip/palate) and the non-cleft control group (14 CBCT images). The presence of dental anomalies was assessed in relation to clef

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

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Background: the novel coronavirus (2019-ncov), formally known as severe acute respiratory syndrome coronavirus 2 (sars-cov-2), the etiological cause of the (corona virus disease 2019) covid-19, appeared in wuhan, hubei province, china. On 11 march 2020, the world health organization (who) declared this disease as a pandemic. As new information on the clinical characteristics, treatment options, and outcomes for covid-19 emerges approximately every hour, physicians should keep themselves up-to-date on this topic.
Objective: to study the demographic features, clinical signs and symptoms and certain vital and laboratory findings of covid-19 hospitalized cases; and to identify the used medication, complications, length of stay at the hosp

Image steganography is undoubtedly significant in the field of secure multimedia communication. The undetectability and high payload capacity are two of the important characteristics of any form of steganography. In this paper, the level of image security is improved by combining the steganography and cryptography techniques in order to produce the secured image. The proposed method depends on using LSBs as an indicator for hiding encrypted bits in dual tree complex wavelet coefficient DT-CWT. The cover image is divided into non overlapping blocks of size (3*3). After that, a Key is produced by extracting the center pixel (pc) from each block to encrypt each character in the secret text. The cover image is converted using DT-CWT, then the p

  In this paper, we introduce and study the concept of S-coprime submodules, where a proper submodule N of an R-module M is called S-coprime submodule if M N is S-coprime Rmodule. Many properties about this concept are investigated.

PC-based controller is an approach to control systems with Real-Time parameters by controlling selected manipulating variable to accomplish the objectives. Shell and tube heat exchanger have been identified as process models that are inherently nonlinear and hard to control due to unavailability of the exact models’ descriptions. PC and analogue input output card will be used as the controller that controls the heat exchanger hot stream to the desired temperature.
The control methodology by using four speed pump as manipulating variable to control the temperature of the hot stream to cool to the desired temperature.
In this work, the dynamics of cross flow shell and tube heat exchanger is modeled from step changes in cold water f

Acute lymphoblastic leukemia (ALL) is one of the most common diseases , so in this study the serum level of malondialdehyde and its relationship with metanephrine was investigated in acute lymphoblastic leukemia patients over one month of treatment. Some biochemical parameters (serum glucose , total serum protein , malondialdehyde ,vitamin C, and metanephrine) changed as well as white blood cell count and blood hemoglobinlevelswere analyzed in sixty patients diagnosed with acute lymphoblastic leukemia over one month of treatment compared to healthy control group.Statistically significant increases (p<0.01) in white blood cell (WBC) count, mean concentrations of malondialdehyde (MDA) (p< 0.05) and metanephrine (p< 0.001) were observed in

This paper presents a proposed neural network algorithm to solve the shortest path problem (SPP) for communication routing. The solution extends the traditional recurrent Hopfield architecture introducing the optimal routing for any request by choosing single and multi link path node-to-node traffic to minimize the loss. This suggested neural network algorithm implemented by using 20-nodes network example. The result shows that a clear convergence can be achieved by 95% valid convergence (about 361 optimal routes from 380-pairs). Additionally computation performance is also mentioned at the expense of slightly worse results.

Binuclear copper, nickel, cobalt, manganese and mercury complexes of the Schiff base H2L (C40H28N2O4) obtained by condensation of 2-benzoyl benzoic acid with benzidine.  The Schiff base and their complexes have been subjected to[ FT-IR, elemental analysis ,UV-Vis, 1H and 13C NMR ] spectral studies, molar conductivity, magnetic moment and HPLC measurements. All the complexes showed tetrahedral geometries with the general structure [M2(L)2].  Generality of the synthesized components offer antibacterial efficiency to (Staphylococcu saureus), (Escherichia coli),(Bacillus subtilis) and(Pseudomonas aeruginosa).
 

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that