Most systems are intelligent and the industrial world is moving now towards
technology. Most industrial systems are now computerized and offer a high speed.
However, Face recognition is a biometric system that can identify people from their
faces. For few number of people to be identified, it can be considered as a fast
system. When the number of people grew to be bigger, the system cannot be adopted
in a real-time application because its speed will degrade along with its accuracy.
However, the accuracy can be enhanced using pre-processing techniques but the
time delay is still a challenge. A series of experiments had been done on AT&TORL
database images using Enhanced Face Recognition System (EFRS) that is

The main aim of this research is to introduce financing cost optimization and different financing alternatives. There are many studies about financing cost optimization. All previous studies considering the cost of financing have many shortcomings, some considered only one source of financing as a credit line without taking into account different financing alternatives. Having only one funding alternative powers, restricts contractors and leads to a very specific financing model. Although it is beneficial for the contractor to use a long-term loan to minimize interest charges and prevent a substantial withdrawal from his credit line, none of the existing financial-based planning models have considered long-term loans in

In this research, nanofibers have been prepared by using an electrospinning method. Three types of polymer (PVA, VC, PMMA) have been used with different concentration. The applied voltage and the gap length were changed. It was observed that VC is the best polymer than the other types of polymers.

The emergence of new dangerous diseases worldwide has led to the need to think about the possibility of enhancing prevention by using new technologies. One of the most important requirements emphasized in the recent studies is the effectiveness of the masks against pathogenic bacteria. In this study, the efficiency of anti-infection protective face masks against bacteria was enhanced by using gold nanoparticles prepared by the chemical precipitation method. The absorption spectrum of the prepared gold suspension shows a clear plasmonic peak at 522 nm. The measurements showed that the sample was made of polypropylene fibers, where X-ray diffraction tests showed peaks matching its crystalline structure. Immersion with gold suspension led t

     This research aims to study the effect of different pH values on the growth of CdTe nanoparticles during specific times. The reflux method has been used as a method for preparing CdTe quantum dots. A difference in absorbance and intensities of peaks at pH 10.5 and 11.5 was observed during the reaction period. The growth rate of the NPs (nucleation) was irregular at low pH values. Optical examinations showed that the best growth rate of NPs was at pH value 12.

In this paper, a new procedure is introduced to estimate the solution for the three-point boundary value problem which is instituted on the use of Morgan-Voyce polynomial. In the beginning, Morgan-Voyce polynomial along with their important properties is introduced. Next, this polynomial with aid of the collocation method utilized to modify the differential equation with boundary conditions to the algebraic system. Finally, the examples approve the validity and accuracy of the proposed method.

In this study, we investigate about the estimation improvement for Autoregressive model of the third order, by using Levinson-Durbin Recurrence (LDR) and Weighted Least Squares Error ( WLSE ).By generating time series from AR(3) model when the error term for AR(3) is normally and Non normally distributed and when the error term has ARCH(q) model with order q=1,2.We used different samples sizes and the results are obtained by using simulation. In general, we concluded that the estimation improvement for Autoregressive model for both estimation methods (LDR&WLSE), would be by increasing sample size, for all distributions which are considered for the error term , except the lognormal distribution. Also we see that the estimation improve

          The aim of this paper is to translate the basic properties of the classical complete normed algebra to the complete fuzzy normed algebra at this end a proof of multiplication fuzzy continuous is given. Also a proof of every fuzzy normed algebra  without identity can be embedded into fuzzy normed algebra  with identity  and  is an ideal in  is given. Moreover the proof of the resolvent set of a non zero element in complete fuzzy normed space is equal to the set of complex numbers is given. Finally basic properties of the resolvent space of a complete fuzzy normed algebra is given.

     is at an all-time high in the modern period, and the majority of the population uses the Internet for all types of communication. It is great to be able to improvise like this. As a result of this trend, hackers have become increasingly focused on attacking the system/network in numerous ways. When a hacker commits a digital crime, it is examined in a reactive manner, which aids in the identification of the perpetrators. However, in the modern period, it is not expected to wait for an attack to occur. The user anticipates being able to predict a cyberattack before it causes damage to the system. This can be accomplished with the assistance of the proactive forensic framework presented in this study. The proposed system combines

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac