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

Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM

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

In Present study, 25 clinical isolates of Proteus spp. of clinical samples, urine, wounds and burns collected from different hospitals in Baghdad city, all isolates were identified as Proteus mirabilis using different bacteriological media, biochemical assays and Vitek-2 system. It was found that 15 (60%) isolates were identifying as P. mirabilis. The susceptibility of P. mirabilis isolates to cefotaxime was 66.6 %, while to ceftazidime was 20%. Extended spectrum β-lactamses producing Proteus was 30.7 %. DNA of 5 isolates of P. mirabilis was extracted and detection for blaVEB-1 gene by using multiplex polymerase chain reaction (PCR). Results showed that the presence of this gene in all tested isolates, as an important indicator for increas

The purpose of the study is the city of Baghdad, the capital of Iraq, was chosen to study the spectral reflection of the land cover and to determine the changes taking place in the areas of the main features of the city using the temporal resolution of multispectral bands of the satellite Landsat 5 and 8 for MSS and OLI sensors respectively belonging to NASA and for the period 1999-2021, and calculating the increase and decrease in the basic features of Baghdad. The main conclusions of the study were, This study from 1999 to 2021 and in two different seasons: the Spring of the growing season and Summer the dry season. When using the supervised classification method to determine the differences, the results showed remarkable changes. Where h

Community detection is useful for better understanding the structure of complex networks. It aids in the extraction of the required information from such networks and has a vital role in different fields that range from healthcare to regional geography, economics, human interactions, and mobility. The method for detecting the structure of communities involves the partitioning of complex networks into groups of nodes, with extensive connections within community and sparse connections with other communities. In the literature, two main measures, namely the Modularity (Q) and Normalized Mutual Information (NMI) have been used for evaluating the validation and quality of the detected community structures. Although many optimization algo

Gastrointestinal diseases and especially chronic gastritis are mainly induced by Helicobacter pylori infection, and provides the basis for gastric carcinogenesis and colorectal cancer. The study involved the detection of serum anti-H. pylori IgG and IgA antibody of  and some serum biomarkers ;CEA and CA19-9 in patients with gastrointestinal diseases. Fifty eight serum samples were collected from 25 males and 33 females .Peripheral venous blood was collected from each patient and sera obtained  by centrifugation. Serum anti-H. pylori IgG and IgA ,serum CEA and  CA19-9 were evaluated by enzyme-linked immunoadsorbent assays (ELISA).Forty eight serum samples were positive for IgG (82.7% ) divided int