In the present paper, an eco-epidemiological model consisting of diseased prey consumed by a predator with fear cost, and hunting cooperation property is formulated and studied. It is assumed that the predator doesn’t distinguish between the healthy prey and sick prey and hence it consumed both. The solution’s properties such as existence, uniqueness, positivity, and bounded are discussed. The existence and stability conditions of all possible equilibrium points are studied. The persistence requirements of the proposed system are established. The bifurcation analysis near the non-hyperbolic equilibrium points is investigated. Numerically, some simulations are carried out to validate the main findings and obtain the critical values of th

The judgment enjoys many potential sources. If we look at these sources with analytical view that enable us to identify the potentials of strength in them which is the existence of features that distinct each place from the other one, which can be considered opportunities that provide the designer and the planner the possibility to design and planning which is based on subs taken from the reality of the available data of the location.
At this point outstands the role of development sources as one of the processes of re-configuring the place which appear as a result of a reality that requires setting new goals for the society and to achieve these goals it takes observations dealing with the place policies that should be taken, so this

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

The objective of the research , is to shed light on the most important treatment of the problem of missing values of time series data and its influence in simple linear regression. This research deals with the effect of the missing values in independent variable only. This was carried out by proposing missing value from time series data which is complete originally and testing the influence of the missing value on simple regression analysis of data of an experiment related with the effect of the quantity of consumed ration on broilers weight for 15 weeks. The results showed that the missing value had not a significant effect as the estimated model after missing value was consistent and significant statistically. The results also

This paper proposes and studies an ecotoxicant system with Lotka-Volterra functional response for predation including prey protective region. The equilibrium points and the stability of this model have been investigated analytically both locally and globally. Finally, numerical simulations and graphical representations have been utilized to support our analytical findings

The aim of this research is to identify the level of mental mindfulness among female students of the College of Education at Umm Al-Qura University, as well as to identify the statistically significant differences in the level of mental mindfulness according to academic level, specialization, and academic achievement. A mental mindfulness scale was designed to cover five dimensions. The study employed the analytic descriptive approach applied to a random sample of (217) female students from various academic specializations. The findings indicated that the level of mental mindfulness was average among female students. Statistically significant differences were attributable to the academic level, academic specializations, and academic achi

Facial recognition has been an active field of imaging science. With the recent progresses in computer vision development, it is extensively applied in various areas, especially in law enforcement and security. Human face is a viable biometric that could be effectively used in both identification and verification. Thus far, regardless of a facial model and relevant metrics employed, its main shortcoming is that it requires a facial image, against which comparison is made. Therefore, closed circuit televisions and a facial database are always needed in an operational system. For the last few decades, unfortunately, we have experienced an emergence of asymmetric warfare, where acts of terrorism are often committed in secluded area with no

Background: During the COVID-19 outbreak, the number of patients who have developed acute coronary syndromes (ACS) has soared rapidly, cardiovascular disease and mortality are influenced by the elevated inflammatory biomarkers. The aim of this study is to compare inflammatory markers between patients with ACS who hadn’t previously had COVID-19 and those who’d be infected within the preceding three months; as well as, evaluating the effect of statins on inflammatory biomarkers.

Methods: This is a comparative cross-sectional study of 42 patients who presented with ACS and had previously had COVID-19 and 48 patient who had never had CO

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo