Currently and under the COVID-19 which is considered as a kind of disaster or even any other natural or manmade disasters, this study was confirmed to be important especially when the society is proceeding to recover and reduce the risks of as possible as injuries. These disasters are leading somehow to paralyze the activities of society as what happened in the period of COVID-19, therefore, more efforts were to be focused for the management of disasters in different ways to reduce their risks such as working from distance or planning solutions digitally and send them to the source of control and hence how most countries overcame this stage of disaster (COVID-19) and collapse. Artificial intelligence should be used when there is no practica

Baghdad (the capital of the Abbasid Caliphate, and his legacy oldest civilizations in history, with glory ethyl). 1. benediction this city landmarks archaeological evidence of their own Kkabbab mosques and forms gates and (Aelchenachel) 2, which adorn the walls of buildings and Chaababeckha high and palm trees, all these vocabulary inspired artists embody Baghdad warmest dissolved in their artwork and all those who lived and grew up in Baghdad embodied in his memory for the nights Beauties and their lights and Hoa_khasha. Ceramic Arts art one who embodied the most important symbols that represent the beauty and credited with Baghdad. And many Iraqis potters inspired single Baghdadi in their work, notably ceramists late arrows Saudi which

This paper is concerned with pre-test single and double stage shrunken estimators for the mean (?) of normal distribution when a prior estimate (?0) of the actule value (?) is available, using specifying shrinkage weight factors ?(?) as well as pre-test region (R). Expressions for the Bias [B(?)], mean squared error [MSE(?)], Efficiency [EFF(?)] and Expected sample size [E(n/?)] of proposed estimators are derived. Numerical results and conclusions are drawn about selection different constants included in these expressions. Comparisons between suggested estimators, with respect to classical estimators in the sense of Bias and Relative Efficiency, are given. Furthermore, comparisons with the earlier existing works are drawn.

Metal nanoparticles can serve as an efficient nano-heat source with confinement photothermal effects. Thermo-plasmonic technology allows researchers to control the temperature at a nanoscale due to the possibility of precise light propagation. The response of opto-thermal generation of single gold-silica core-shell nanoparticle immersed in water and Poly-vinylpyrrolidone surrounding media is theoretically investigated. Two lasers (CW and fs pulses) at the plasmonic resonance (532 nm) are utilized. For this purpose, finite element method is used via COMSOL multiphysics to find a numerical computation of absorption cross section for the proposed core –shell NP in different media. Thermo-plasmonic response for both lasers is studied. The

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

Aim: To learn more about Oral Lichen Planus Iraqi patients, including their background information, symptoms, and prognosis. Materials and Methods: From the Oral and Maxillofacial Pathology Department, College of Dentistry, Baghdad University, we retrospectively reviewed the medical records of 68 patients with a histologically confirmed clinical diagnosis of oral lichen planus and subsequently contacted the patients by phone to evaluate their prognosis. Results: Females were more likely than males to experience severe pain; the reticular form of Oral Lichen Planus was the most prevalent at 38.2%, but the erosive type was more prevalent among females. Only 53 of 68 patients responded to phone calls. More than 37% of those respondents reporte

Background: The most crucial mechanism of genetic variation in N. meningitidis is the slipped strand mispairing, this mechanism generates Phase variation using simple sequence repeat (SSR) and is commonly used by the N. meningitidis to escape the immune system despite its function in eradicating the pathogenic and commensal bacteria. Some of simple sequence repeats (SSRs) that located within the genome works as phase variation while other SSRs have no role in generating phase variation mechanisms. Therefore, Aim: the main goal of the current in silico study was to detect the probability of SSR to enroll with phase variation for the entire N. meningitidis genome. Methods: Different criteria were used to judge SSR as

have suffered from deteriorating residential neighborhoods, poor economic, social and urban living conditions of the population and deteriorating the infrastructural and superior services. These problems were the secretions of these cities' rapid urbanization. Based on the principles of sustainable urban planning and in order to achieve adequate opportunities for the lives of the population and provide them with sustainable livelihoods, policies have emerged to upgrade along the lines of community participation and programmes to reform and develop those neighbourhoods, raise their efficiency and make them livable. Thus, the problem of research was identified "The absence of a comprehensive cognitive perception of the most prominent facto

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen