The purpose of this study is designate quenching and tempering heat treatment by using Taguchi technique to determine optimal factors of heat treatment (austenitizing temperature, percentage of nanoparticles, type of base media, nanoparticles type and soaking time) for increasing hardness, wear rate and impact energy properties of 420 martensitic stainless steel. An (L₁₈) orthogonal array was chosen for the design of experiment. The optimum process parameters were determined by using signal-to-noise ratio (larger is better) criterion for hardness and impact energy while (Smaller is better) criterion was for the wear rate. The importance levels of process parameters that effect on hardness, wear rate and impact energy propertie

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

The uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers. Based on 112 batch experiments, the effect of contact time (10-240 min), initial pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05-2 g/100 ml), agitation speed (0-250 rpm) and temperature (20-60ºC) were studied. The maximum uptake (=92 %) of Cd(II) was achieved at optimum parameters of 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.

Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlatio

Background: Oral lichen planus (OLP) is a chronic inflammatory disease with an autoimmune inflammatory pathogenesis. The purpose of this study was to evaluate the role of angiogenesis in the pathogenesis of OLP, using CD34 stain to highlight the blood vessels for measuring the microvessel density (MVD) as well as to evaluate the relation of this marker with the degree of inflammation Materials and Methods: Immunohistochemical (IHC) staining technique was used to evaluate angiogenesis using CD34 in 46 paraffin blocks 10 of them obtained from normal mucosa and 36 from cases diagnosed as lichen planus , 20 of them diagnosed as Reticular type while 16 as erosive type. Severity of inflammation was divided into mild, moderate and severe accordi

Copula modeling is widely used in modern statistics. The boundary bias problem is one of the problems faced when estimating by nonparametric methods, as kernel estimators are the most common in nonparametric estimation. In this paper, the copula density function was estimated using the probit transformation nonparametric method in order to get rid of the boundary bias problem that the kernel estimators suffer from. Using simulation for three nonparametric methods to estimate the copula density function and we proposed a new method that is better than the rest of the methods by five types of copulas with different sample sizes and different levels of correlation between the copula variables and the different parameters for the function. The

Hepatitis, a condition of liver’s inflammation that can be self-limiting or, in certain chances, it may lead to liver cancer, fibrosis or cirrhosis. Hepatitis viruses mainly cause hepatitis in the world. People with hepatitis C have predominant chances to develop diabetes as HCV virus participates in causing type 2 diabetes. HCV virus causes pathogenesis in two ways: it either directly destroys the β cells of pancreas or contributes to the specific autoimmunity of β cells. The present cross sectional study was done in Wazirabad Tahsil of Gujranwala District to analyze the percentage of patients suffering from hepatitis C who had the risk of diabetes mellitus. For this research work, demographic information and data about any other me

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

Background: This study was conducted to evaluate the hard palate bone density and thickness during 3rd and 4th decades and their relationships with body mass index (BMI) and compositions, to allow more accurate mini-implant placement. Materials and method: Computed tomographic (CT) images were obtained for 60 patients (30 males and 30 females) with age range 20-39 years. The hard palate bone density and thickness were measured at 20 sites at the intersection of five anterioposterior and four mediolateral reference lines with 6 and 3 mm intervals from incisive foramen and mid-palatal suture respectively. Diagnostic scale operates according to the bioelectric impedance analysis principle was used to measure body weight; percentages of body fa

The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.

Analysis the economic and financial phenomena and other requires to build the appropriate model, which represents the causal relations between factors. The operation building of the model depends on Imaging conditions and factors surrounding an in mathematical formula and the Researchers target to build that formula appropriately. Classical linear regression models are an important statistical tool, but used in a limited way, where is assumed that the relationship between the variables illustrations and response variables identifiable. To expand the representation of relationships between variables that represent the phenomenon under discussion we used Varying Coefficient Models