The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

Recent research has shown that a Deoxyribonucleic Acid (DNA) has ability to be used to discover diseases in human body as its function can be used for an intrusion-detection system (IDS) to detect attacks against computer system and networks traffics. Three main factor influenced the accuracy of IDS based on DNA sequence, which is DNA encoding method, STR keys and classification method to classify the correctness of proposed method. The pioneer idea on attempt a DNA sequence for intrusion detection system is using a normal signature sequence with alignment threshold value, later used DNA encoding based cryptography, however the detection rate result is very low. Since the network traffic consists of 41 attributes, therefore we proposed the

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

fields of the College of Agricultural Engineering Sciences, University of Baghdad/Al-Jadriya, in the fall season 2021-2022. With three sowing dates (26 July, 4 August, 12 August), The experiment was implemented according to a randomized complete block design (RCBD) with three replications. The aim is to detect the expression of the INCW1 gene associated with sucrose-to-glucose analysis, which is critical for many metabolic functions in different sink tissues, and determine the amount of fold gene expression to find out which of the genotypes contain the invertase gene, and which ones have a high level of gene expression based on the fold of gene expression. The results showed significant differences in the invertase enzyme activity for the

The current study was designated to investigate the effect ofAllium sativumon some physiological and immunological parameters in rats. thirty adult rats were divided into three groups (10 rat for each). G1: served as healthy control, G2 :rats were treated with 150 mg\kg of Allium sativum, G3: treated with 300 mg\kg of Allium sativum. All treated animals were givenorally for 30 days. The aspartate , ) ALT ( alanine transaminase on some parameters were investigated such as garlic effects of total and differential counts of white blood , ) LDH ( lactate dehydrogenase ), AST ( transaminase cells(WBC) like Lymphocyte, Monocyte, Neutrophil, Basophil, Eosinophil,as

The objective of this study is to evaluate the level of parathyroid hormone, Co enzyme Q and total antioxidant status in serum’s women with fibromyalgia syndrome firstly, then to demonstrate if these biochemical markers affected by age and obesity.

      This study was performed at Rheumatology and Rehabilitation Consultation Unit in Baghdad Teaching Hospital. Venous blood sample were drawn from (59) female with FMS and (30) control (without FMS). The serum was obtained after on standing in order to coagulate then centrifuged. The mean age± SD of FMS group was (42.22±15.34) years and for control was (40.7±18.22) years. Those participants were subdivided into four different groups acc

Some feline intestinal parasites such as Toxocara, Giardia, and Cryptosporidium can spread to humans through feces. Therefore, it is important to prevent exposure of family members by screening cat fecal samples twice per year for potential treatment regimes. This study was initiated to compare and identify gastrointestinal parasites of domestic and stray cats (Felis domesticus) in Baghdad City, Iraq. Parasite eggs and oocysts were identified under light microscopy by applying standard laboratory techniques (flotation and sedimentation). Overall, 59 of 121 (48.7%) fecal samples were positive for intestinal parasites. The rate of infection by Toxoplasma gondii was (3.31%), Isospora spp. (6.61%), Cryptosporidium spp. (31.4%), and Toxocara spp

      Detecting and subtracting the Motion objects from backgrounds is one of the most important areas. The development of cameras and their widespread use in most areas of security, surveillance, and others made face this problem. The difficulty of this area is unstable in the classification of the pixels (foreground or background). This paper proposed a suggested background subtraction algorithm based on the histogram. The classification threshold is adaptively calculated according to many tests. The performance of the proposed algorithms was compared with state-of-the-art methods in complex dynamic scenes.

A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.