Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

objective  the research to diagnosis and interpretation of the nature of the effect between the  basic elements of knowledge management (tecgnology , structure , culture , process , human resource ) and the strategic performance of the Iraqi private banks, the research community and the level dimensions, and I've tested this research in the private banking sector represented by (7), especially in Baghdad, Iraqi banks, and applied research on sample consisting of 100 distributors in several administrative levels Director (Director, Director of the department, branch manager), and use the researcher questionnaire Head to collect data and information tool, and some private banks annual reports, has sought research to test

هدفت هذه الدراسة إلى التعرف على درجة استخدام معلمات الرياضيات لأدوات التقويم البديل من وجهة نظرهن، وتحديد إذا كانت توجد فروق ذات دلالة إحصائية تعزى لمتغير سنوات الخبرة التدريسية، ولتحقيق أهداف الدراسة تم استخدام المنهج الوصفي. وتكونت عينة الدراسة من 37 معلمة من معلمات الرياضيات في الحلقة الثانية من التعليم الأساسي في محافظة ظفار في سلطنة عُمان. وتم بناء استبانة مكونة من (21) فقرة موزعة على (4) محاور تمثل أدوات

This research aims to predict the value of the maximum daily loss that the fixed-return securities portfolio may suffer in Qatar National Bank - Syria, and for this purpose data were collected for risk factors that affect the value of the portfolio represented by the time structure of interest rates in the United States of America over the extended period Between 2017 and 2018, in addition to data related to the composition of the bonds portfolio of Qatar National Bank of Syria in 2017, And then employing Monte Carlo simulation models to predict the maximum loss that may be exposed to this portfolio in the future. The results of the Monte Carlo simulation showed the possibility of decreasing the value at risk in the future due to the dec

In this paper, the deterministic and the stochastic models are proposed to study the interaction of the Coronavirus (COVID-19) with host cells inside the human body. In the deterministic model, the value of the basic reproduction number   determines the persistence or extinction of the COVID-19. If   , one infected cell will transmit the virus to less than one cell, as a result,  the person carrying the Coronavirus will get rid of the disease .If   the infected cell  will be able to infect  all  cells that contain ACE receptors. The stochastic model proves that if  are sufficiently large then maybe  give  us ultimate disease extinction although ,  and this  facts also proved by computer simulation.

The study aimed to explore the school principals’ servant leadership practices for primary teachers’ perspectives in the Sultanate of Oman, furthermore to investigate the differences in those practices attributable to variables (gender, qualification, educational stage, years of experience, governorate). The study relied on the descriptive approach, by employing the survey research design using the questionnaire as a main tool for data collection, which included five dimensions of servant leadership (altruism, humility, enhancing teacher development, emotional healing, commitment to community development), Data collected from (1094) teachers in basic education schools, and they were chosen randomly. The results of the study indicated

In this paper, a compartmental differential epidemic model of COVID-19 pandemic transmission is constructed and analyzed that accounts for the effects of media coverage. The model can be categorized into eight distinct divisions: susceptible individuals, exposed individuals, quarantine class, infected individuals, isolated class, infectious material in the environment, media coverage, and recovered individuals. The qualitative analysis of the model indicates that the disease-free equilibrium point is asymptotically stable when the basic reproduction number R0 is less than one. Conversely, the endemic equilibrium is globally asymptotically stable when R0 is bigger than one. In addition, a sensitivity analysis is conducted to determine which

This study examines traveling wave solutions of the SIS epidemic model with nonlocal dispersion and delay. The research shows that a key factor in determining whether traveling waves exist is the basic reproduction number R0. In particular, the system permits nontrivial traveling wave solutions for σ≥σ∗ for R0>1, whereas there are no such solutions for σ<σ∗. This is because there is a minimal wave speed σ∗>0. On the other hand, there are no traveling wave solutions when R0≤1. In conclusion, we provide several numerical simulations that illustrate the existence of TWS.

The aim of this study was to identify the effectiveness of using generative learning model in learning kinetic series on rings and horizontal bar in artistic gymnastics for men ,Also, the two groups were better in learning the two series of movements on the rings and horizontal bar . The experimental method was used to design two parallel groups with pretested and posttest .The sample included third graders at the College of Physical Education and Sports Sciences - University of Baghdad ,The third class (d) was chosen to represent the control group that applied the curriculum in the college, with (12) students per group. After conducting the tribal tests, the main experiment was carried out for (8) weeks at the rate of two units per week di

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se