هدفت الدراسة الى تحليل محتوى كتاب الرياضيات للصف الاول متوسط على وفق مكونات المعرفة الرياضية (المفاهيم الرياضية , التعميمات الرياضية, المهارات الرياضية والمسائل الرياضية )

وتفرعت منه الاسئلة الاتية :

مانسبة المفاهيم الرياضية المتضمنة في كل فصل من فصول كتاب الرياضيات للصف الاول متوسط  وللكتاب ككل ؟

مانسبة المهارات الرياضية المتضمنة في كل فص

The pandemic of coronavirus disease 2019 (COVID-19), first reported in China, in December 2019 and since then the digestive tract involvement of  COVID-19 has been progressively described. In this review, I summed recent studies, which have addressed the pathophysiology of COVID-19-induced gastrointestinal symptoms, their prevalence, and bowel pathological and radiological findings of infected patients. The effects of gut microbiota on SARS-CoV-2 and the challenges of nutritional therapy of the infected patients are depicted.  Moreover, I provide a concise summary of the recommendations on the management of inflammatory bowel disease, colorectal cancer, and performing endoscopy in the COVID era. Finally, the COVID pancreatic re

For the most reliable and reproducible results for calibration or general testing purposes of two immiscible liquids, such as water in engine oil, good emulsification is vital. This study explores the impact of emulsion quality on the Fourier transform infrared (FT-IR) spectroscopy calibration standards for measuring water contamination in used or in-service engine oil, in an attempt to strengthen the specific guidelines of ASTM International standards for sample preparation. By using different emulsification techniques and readily available laboratory equipment, this work is an attempt to establish the ideal sample preparation technique for reliability, repeatability, and reproducibility for FT-IR analysis while still considering t

Twitter data analysis is an emerging field of research that utilizes data collected from Twitter to address many issues such as disaster response, sentiment analysis, and demographic studies. The success of data analysis relies on collecting accurate and representative data of the studied group or phenomena to get the best results. Various twitter analysis applications rely on collecting the locations of the users sending the tweets, but this information is not always available. There are several attempts at estimating location based aspects of a tweet. However, there is a lack of attempts on investigating the data collection methods that are focused on location. In this paper, we investigate the two methods for obtaining location-based dat

Assessing performance efficiency is critical to the management need for oversight, planning, and continuous periodic evaluation of the multiple activities of Northern Cement State Company in order to determine the level of achievement of the objectives set, and to correct the deviations and delays that the evaluation shows and limitation of liability. What cannot be measured cannot be managed. The aim of this research is to highlight the impact of using BSC, financial and non-financial, to give comprehensive and clear picture of the company's performance and to measure the quality of its performance by using six-sigma and the level of deviations in achieving the planned goals. Therefore, four-key hypotheses were formulated for th

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

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

The public procurement crisis in Iraq plays a fundamental role in the delay in the implementation of construction projects at different stages of project bidding (pre, during, and after). The procurement system of any country plays an important role in economic growth and revival. The paper aims to use the fuzzy logic inference model to predict the impact of the public procurement crisis (relative importance index and Likert scale) was carried out at the beginning to determine the most important parameters that affect construction projects, the fuzzy analytical hierarchy process (FAHP) to set up, and finally, the fuzzy decision maker's (FDM) verification of the parameter for comparison with reality. Sixty-five