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

Previous reports demonstrated the effectiveness of silibinin hemisuccinate as a potential intraocular pressure-lowering agent. The exact mechanism by which silibinin exerted this effect has not yet been documented, but might suggested to interfere with aqueous humor formation. The present study was designed to evaluate the comparative efficacy of silibinin as IOP lowering agent to that of betaxolol in normotensive rabbits, and the interaction of silibinin with betaxolol as a way for investigating the possible mechanism of action of silibinin in this respect. The effects of instillation of 0.75% silibinin solution and 0.5% betaxolol eye drops in the eyes of normotensive rabbits were evaluated using indentation tonometry. The results showe

Potentially inappropriate prescribing is the prescribing of a medication that may cause more harm than benefit, the elderly population aged 65 years or older is more prone to potentially inappropriate prescribing because of alterations in their physiology, pharmacokinetics, and pharmacodynamics as well as polypharmacy and comorbidities, Beers list is a screening tool that help doctors to detect potentially inappropriate prescribing in geriatric patients and is designed to solve this problem, the aim of this study is to measure the prevalence of potentially inappropriate prescribing among psychiatric patients using the Beers criteria as an assessment tool and find the relationship between duration of hospitalization, comorbidities and pol

Producing pseudo-random numbers (PRN) with high performance is one of the important issues that attract many researchers today. This paper suggests pseudo-random number generator models that integrate Hopfield Neural Network (HNN) with fuzzy logic system to improve the randomness of the Hopfield Pseudo-random generator. The fuzzy logic system has been introduced to control the update of HNN parameters. The proposed model is compared with three state-ofthe-art baselines the results analysis using National Institute of Standards and Technology (NIST) statistical test and ENT test shows that the projected model is statistically significant in comparison to the baselines and this demonstrates the competency of neuro-fuzzy based model to produce

The evaluation of subsurface formations as applied to oil well drilling started around 50 years ago. Generally, the curent review articule includes all methods for coring, logging, testing, and sampling. Also the methods for deciphering logs and laboratory tests that are relevant to assessing formations beneath the surface, including a look at the fluids they contain are discussed. Casing is occasionally set in order to more precisely evaluate the formations; as a result, this procedure is also taken into account while evaluating the formations. The petrophysics of reservoir rocks is the branch of science interested in studying chemical and physical properties of permeable media and the components of reservoir rocks which are associated

This paper offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark

Background: Chronic suppurative otitis media (CSOM) is the result of an initial episode of acute otitis media and is characterized by a persistent discharge from the middle ear through a tympanic perforation for at least 2 weeks duration. It is an important cause of preventable hearing loss, particularly in the developing world.Objective: To get an overview on the bacterial ear infection profile in general and to assess the antibiotic resistance of Pseudomonal infection (PS) particularly since it is usually the commonest infection to cause otitis media and the most difficult to treat due to the problem of multi drug resistance..Methods: A cross sectional study was done which included 405 patients of CSOM patients, 196 (48%) case were mal

Background: Chronic suppurative otitis media (CSOM) is the result of aninitial episode of acute otitis media and is characterized by a persistent discharge from the middle ear through a tympanic perforation for at least 2 weeks duration. It is an important cause of preventable hearing loss, particularly in the developing world.Methods. 1. To get an overview on the bacterial ear infection profile in general 2. To assess the antibiotic resistance of Pseudomonal infection (PS) particularly since it is usually the commonest infection to cause otitis media and the most difficult to treat due to the problem of multi drug resistance... A cross sectional study was done which included 405 patient of CSOM patients196 (48%) case were males ,209 (52