In this work laser detection and tracking system (LDTS) is designed and implemented using a fuzzy logic controller (FLC). A 5 mW He-Ne laser system and an array of nine PN photodiodes are used in the detection system. The FLC is simulated using MATLAB package and the result is stored in a lock up table to use it in the real time operation of the system. The results give a good system response in the target detection and tracking in the real time operation.

This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio

To determine the relationship between Helicobacter pylori infection and reproduction disorder (recurrent spontaneous abortion), twenty women patients who undergo spontaneous abortion during first trimester of pregnancy (20-38) years and have been investigated from 2015/12/1 -2016/3/1 and compared to fifteen healthy individuals. All subjects were carried out to measure anti-H. pylori IgA and anti- H. pylori IgG antibodies by enzyme linked immunosorbent assay (ELISA). There was significant elevation (p≤ 0.05) in concentration of anti- H. pylori IgG Abs (6.30± 0.99) compared to control group (4.48± 0.61) and IgA Abs (5.42 ± 0.90 U /ml) as compared to control group (3.92 ± 0.41 U/ml). The percentage of H. pylori IgG and IgA was 20% and 25

Klebsiella pneumoniae is an adaptable pathogen that forms biofilms on a variety of surfaces. This study's objective was to identify the presence of fimbrial genes (types 1 and 3) in K. pneumoniae strains isolated from various clinical sources based on their antibiotic resistance and ability to form biofilms. According to identification utilizing the vitek 2 technology and confirmation by molecular identification targeting the 16S rRNA gene with a particular primer, forty isolates were identified from clinical specimens. The vitek 2 compact system was utilized to evaluate the antibiotic susceptibility of all the isolates. The findings revealed a range of resistance percentages, including 52.5% for Penicillin, 40.5% for Trimethoprim/S

Pseudomonas aeruginosa has variety of virulence factors that contribute to its pathogenicity. Therefore, rapid detection with high accuracy and specificity is very important in the control of this pathogenic bacterium. To evaluate the accuracy and specificity of Polymerase Chain Reaction (PCR) assay, ETA and gyrB genes were targeted to detect pathogenic strains of P. aeruginosa. Seventy swab samples were taken from patients with infected wounds and burns in two hospitals in Erbil and Koya cities in Iraq. The isolates were traditionally identified using phenotypic methods, and DNA was extracted from the positive samples, to apply PCR using the species specific primers targeting ETA, the gene encoding for exotoxin A, and gyrB gene. The res

The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorder. To determine the metabolic disorders in women with PCOS, (25) women with PCOS ages (15 - 47) years have been investigated and compared with (20) healthy individuals. All the studied groups were carried out to measure fasting blood sugar, (anti-GAD Ab, anti β-islet cell Ab by IFAT) and measured insulin level by ELISA. There was significant elevation in the concentration of fasting blood sugar than in control groups (p ≤ 0.05) and there was negative results for anti-GAD Ab and anti β-islet cell Ab by IFAT test for serum of women with PCOS, while there was significant differences in the insulin level for women with PCOS compared with control groups (p ≤ 0.05),