In this paper we present the theoretical foundation of forward error analysis of numerical algorithms under;• Approximations in "built-in" functions.• Rounding errors in arithmetic floating-point operations.• Perturbations of data.The error analysis is based on linearization method. The fundamental tools of the forward error analysis are system of linear absolute and relative a prior and a posteriori error equations and associated condition numbers constituting optimal of possible cumulative round – off errors. The condition numbers enable simple general, quantitative bounds definitions of numerical stability. The theoretical results have been applied a Gaussian elimination, and have proved to be very effective means of both a prior

One of the most important methodologies in operations research (OR) is the linear programming problem (LPP). Many real-world problems can be turned into linear programming models (LPM), making this model an essential tool for today's financial, hotel, and industrial applications, among others. Fuzzy linear programming (FLP) issues are important in fuzzy modeling because they can express uncertainty in the real world. There are several ways to tackle fuzzy linear programming problems now available. An efficient method for FLP has been proposed in this research to find the best answer. This method is simple in structure and is based on crisp linear programming. To solve the fuzzy linear programming problem (FLPP), a new ranking function (R

In this paper we show that if ? Xi is monotonically T2-space then each Xi is monotonically T2-space, too. Moreover, we show that if ? Xi is monotonically normal space then each Xi is monotonically normal space, too. Among these results we give a new proof to show that the monotonically T2-space property and monotonically normal space property are hereditary property and topologically property and give an example of T2-space but not monotonically T2-space.

Groundwater is considered as one of the most important sources of fresh-water, on which many regions around the world depend, especially in semi-arid and arid regions. Protecting and maintaining groundwater is a difficult process, but it is very important to maintain an important source of water. The current study aims to assess the susceptibility of groundwater to pollution using the DRASTIC model along with the GIS environments and its tool boxes. A vulnerability map was created by relying on data collected from 55 wells surveyed by the researchers as well as archived records from governmental institutions and some international organizations. The results indicate that the region falls into three vulnerability functional zones , namely

Blockchain is an innovative technology that has gained interest in all sectors in the era of digital transformation where it manages transactions and saves them in a database. With the increasing financial transactions and the rapidly developed society with growing businesses many people looking for the dream of a better financially independent life, stray from large corporations and organizations to form startups and small businesses. Recently, the increasing demand for employees or institutes to prepare and manage contracts, papers, and the verifications process, in addition to human mistakes led to the emergence of a smart contract. The smart contract has been developed to save time and provide more confidence while dealing, as well a

    Hepatitis-B (HBV) is a viral disease cause liver damage, cirrhosis, fibrosis and hepatocellular carcinoma. Present study attempted to elucidate the biochemical and haematological markers other than Australia antigen, of hepatitis,B,vairusV (HBsAg) for better assessment of HBV infection.  The present study was conducted on 76 men, 50 of them were found to be HBeAg positive and 26 were negative, mean age was53±5.7years. Haematological parameters such as Absolute  Erythrocyte( Abs  Eryt), Absolute Leukocyte(Abs Leuk) , Haemoglobin(Hb), Packed Cell Volume(PCV),Mean Corpuscular Volume (MCV), Red Cell Distribution Width (RDW), Mean  Corpuscular  Haemoglobin (MCH),MCH Concentration(MCHC) ,Neutrophi

The main objective of" this paper is to study a subclass of holomrphic and univalent functions with negative coefficients in the open unit disk U= defined by Hadamard Product. We obtain coefficients estimates, distortion theorem , fractional derivatives, fractional integrals, and some results.

      In this paper, we study the impact of the variable rotation and different variable on mixed convection peristaltic flow of incompressible viscoplastic fluid. This is investigated in two dimensional asymmetric channel, such as the density, viscosity, rate flow, Grashof number, Bingham number, Brinkman number and tapered, on the mixed convection heat transfer analysis for the peristaltic transport of viscoplastic fluid with consideration small Reynolds number and long wavelength, peristaltic transport in asymmetric channel tapered horizontal channel and non-uniform boundary walls to possess different amplitude wave and phases. Perturbation technique is used to get series solutions. The effects of different values of these parame

     This review explores the Knowledge Discovery Database (KDD) approach, which supports the bioinformatics domain to progress efficiently, and illustrate their relationship with data mining. Thus, it is important to extract advantages of Data Mining (DM) strategy management such as effectively stressing its role in cost control, which is the principle of competitive intelligence, and the role of it in information management. As well as, its ability to discover hidden knowledge. However, there are many challenges such as inaccurate, hand-written data, and analyzing a large amount of variant information for extracting useful knowledge by using DM strategies. These strategies are successfully applied in several applications as data wa

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of