The City of Ember is a very interesting novel that is although intended for young readers, have so many layers and messages that are misunderstood. In this research, both the novel and the film adaptation are studied with the intent to decode the warning messages that the novelist and the director tried to introduce to the audience. The research studies four vital messages; the first message is that history repeats itself for the novel has many allusions to the history of Jews and their painful holocaust and even goes back in history the days of Moses and the Exodus, the second message tackles the conspiracy theory that states nothing happens by accident and that everything is planned and connected hence comes the third message

A detailed experimental study was devoted to the anodic oxidation of oxalic acid using manganese dioxide rotating cylinder anode with the objective to evaluate in a systematic way the effect on the oxalic acid oxidation process of several relevant parameters, including the presence of sodium chloride, the current density (J), the rotation speed, the temperature, and the initial concentration of oxalic acid. Thin manganese dioxide film on graphite substrate has been prepared by electrochemical oxidation from MnSO4-H2SO4 electrolyte. The morphology of this electrode was investigated by XRD, SEM, EDS and AFM techniques. The results show that a firm γ-structure of MnO2 film on graphite rod can be obtained successfully. The results indicate tha

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

HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

        This paper deals with social responsibility visible to the media and the role they play in spreading the culture of environmental protection, and make research on a sample of the University of Baghdad consisting students from 150 students, male and female were distributed questionnaire form on the sample to obtain the required information has been questionnaire included axes distributed questions achieve the objectives of the search, and after the form data were analyzed using statistical program spss results show that the visual media and its role in spreading the culture of environmental protection form averages arithmetic high, indicating a rise in the influence of th