Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

Discriminant analysis is a technique used to distinguish and classification an individual to a group among a number of  groups based on a linear combination of a set of relevant variables know discriminant function. In this research  discriminant analysis used to analysis data from repeated measurements design. We  will  deal  with the problem of  discrimination  and  classification in the case of  two  groups by assuming the Compound Symmetry covariance structure  under  the  assumption  of  normality for  univariate  repeated measures data.

Various industrial applications include the dyeing of textiles, paper, leather, and food products, as well as the cosmetics industry. Physic-chemical methods are required to breakdown dyes because they are known to be harmful and persistent in the environment. Many companies' treated effluents contain small amounts of dyes. When it comes to removing dye from wastewater, adsorption has verified to be aneconomical alternative to more traditional treatment procedures. It's important to degrade color impurities in industrial effluents since they constitute a serious health and environmental concern. One way that's been tried is using clay minerals as an adsorbent. Using adsorption for removing

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Urbanization led to significant changes in the properties of the land surface. That appends additional heat loads at the city, which threaten comfort and health of people. There is unclear understanding represent of the relationship between climate indicators and the features of the early virtual urban design. The research focused on simulation capability, and the affect in urban microclimate. It is assumed that the adoption of certain scenarios and strategies to mitigate the intensity of the UHI leads to the improvement of the local climate and reduce the impact of global warming. The aim is to show on the UHI methods simulation and the programs that supporting simulation and mitigate the effect UHI. UHI reviewed has been conducted the for

Reactive oxygen species (ROS) are produced as a result of biochemical processes that are not in balance with the body's antioxidant defense mechanism. This metabolic dysfunction is referred to the oxidative stress (OS).  Metabolic dysfunction-associated diseases are affected by changes in the redox balance. It is now widely recognized that oxidative stress significantly affects diabetes mellitus (DM), particularly type 2 diabetes. The biochemical changes associated with  DM could  disturb the oxidative milieu, leading to several microvascular complications in diabetic patients. Thus, DM is a perfect disease to explore the harmful consequences of oxidative stress and how to treat it. Oxidative stress triggered by hyperglycemia is

Introduction: All-ceramic crowns are widely used in prosthodontics and cosmetic dentistry due to their good esthetic and proper physical properties. Chipping of ceramic is one of the most common post-insertion complications, that can be fixed either extraoral or intraorally. The latter is time time-effective alternative, less traumatic, and low-cost. A newer objective method of laser is a surface modification of ceramics to increase surface roughness. The aim of this study is to provide a review of Er,Cr;YSGG (2960nm) in intraoral repair and shear bond strength (SBS). Method: A thorough search considering Google Scholar and PubMed published data and ten articles found wh

Economic analysis plays a pivotal role in managerial decision-making processes. This analysis is predicated on deeply understanding economic forces and market factors influencing corporate strategies and decisions. This paper delves into the role of economic data analysis in managing small and medium-sized enterprises (SMEs) to make strategic decisions and enhance performance. The study underscores the significance of this approach and its impact on corporate outcomes. The research analyzes annual reports from three companies: Al-Mahfaza for Mobile and Internet Financial Payment and Settlement Services Company Limited, Al-Arab for Electronic Payment Company, and Iraq Electronic Gateway for Financial Services Company. The paper concl