One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first

Metallic nanoparticles are increasingly studied for their biomedical applications due to their unique physicochemical and catalytic properties. Here, a broccoli-mediated gold/platinum nanohybrid (Au@Pt NH) was synthesized using an ultrasound-assisted green method with an aqueous extract of Brassica oleracea var. italica for multifunctional biomedical evaluation. XRD and TEM confirmed a crystalline nanohybrid with an average crystallite size of 7.56 nm and a mean particle diameter of 13.08 ± 7.58 nm. The broccoli extract produced no inhibition zones, whereas Au@Pt NH inhibited Staphylococcus aureus (18 mm), Staphylococcus epidermidis (21 mm), Escherichia coli (18 mm), Klebsiella pneumoniae (20 mm), and Candida albicans (21 mm). In vivo,

 5-Fluorouracil is one of the commonly used chemotherapy drugs in anticancer therapy; unfortunately treatment with 5-FU by solely has many drawbacks  low lipophilicity, low permeability, low molecular weight, and its relatively poor plasma protein binding; also a brief half-life therefore frequent administration is required to maintain the optimal therapeutic plasma level which in addition to its poor selectivity, drug resistance and limited penetration to cancer cells; leads to increased incidence of side-effects to healthy cells/tissues and low response rates. In order to minimize these drawbacks; 5-FU was chemically  conjugated with pyrrolidine dithiocarbamate (PDTC) in a mutual prodrug moiety (S-(9H-purin-6-yl) 3-(

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

Abstract
A two electrode immersion electrostatic lens used in the design
of an electron gun, with small aberration, has been designed using
the finite element method (FEM). By choosing the appropriate
geometrical shape of there electrodes the potential V(r,z) and the
axial potential distribution have been computed using the FEM to
solve Laplace's equation.
The trajectory of the electron beam and the optical properties of
this lens combination of electrodes have been computed under
different magnification conditions (Zero and infinite magnification
conditions) from studying the properties of the designed electron
gun can be supplied with Abeam current of 5.7*10-6 A , electron
gun with half acceptance