Iraqi Journal of Science and Technology

The population increases played a fundamental role in the use of energy to sustain the new civil life, and this led to high rates of environmental pollution through the emission of carbon dioxide and combustion products and its impact on the climate change. Today, clean energy is one of the solutions that developing countries seek to reduce the emission of carbon dioxide and combustion products for industrial processes, which includes solar energy, wind energy, hydroelectric energy, and nuclear energy. During this study, we review the most important uses of alternative energy and their applications for maintaining a clean environment free of pollutants, in addition to providing energy sustainability to reduce the accumulated risks from combustion products and preserve health and environment human.

The research aimed to try to isolate Salmonella bacteria from people suffering from diarrhea and study their resistance to antibiotics . 65 Salmonella isolates were isolated and diagnosed from infected people visiting different laboratories in the city of Baghdad for the period from Oct./2022 to March/2023. The sensitivity of Salmonella bacteria to (8) antibiotics was studied. The results showed that salmonella is one of the most common causes of diarrhea, especially in the age group under one year. The infection was more in males than in females, as the isolated bacteria gave resistance to more than one antibiotic, and the percentages of their resistance to antibiotics varied as they were resistant by. (23, 53.8, 64.6, 69.2, 44.6, 58.4, 55.3 and 53.8)% to antibiotics (Ciprofloxacine, Azithromycin, Sulfamethoxazole, Cefotaxime, Nalidixic acid, Chloramphenicol). Ofloxacin, Ceftriaxone) respectively.

As a result of rapid growth for microorganisms which causes many widespread diseases, if has become necessary to search for new environmentally friendly treatment techniques to reduce microbial contamination in water. Magnetic fields are a physical factor that affects micro organisms, gram negative and gram positive bacteria. Used static magnetic fields with magnetic intensity (500, 2000, 2750, 4700 and 6500 Gauss) and rotating speed of sample (60, 100, 200, 300, 400 and 500 rpm). Results of research indicate that use of magnetic technology simultaneously with sample rotating. Magnetic intensity of 6500 Gauss has most effect on Staphylococcus Aureus and E- Coli bacteria during first hour of treatment time, where percentage of reduction was (92%, 94%), respectively, in case of using rotation of sample within magnetic field, it was observed that effect on staphylococcus Aureus and Escherichia-Coli bacteria increased, at a speed of 400 rpm, which increase process of killing bacteria in percentage of 100% and 98%, respectively.

To address concerns like power outages, rising prices, poor power quality, and the need to employ renewable energy sources, the traditional electricity system has evolved into what is now known as the \"Smart Grid\" (SG). Critical to this goal is the development and rollout of a Smart Grid Communication Network (SGCN) that can reliably and securely transmit data across the grid. With this study, we hope to present a comprehensive overview of SGCN, including its essential characteristics, necessary communication infrastructure, and promising technological developments and practical uses. This study begins with an examination of those communication needs, then provides a high-level overview of SG applications by employing a multi-layer method and separating the communication layer into Home Area Networks, Neighbor Area Networks, and Wide Area Networks. Next, the current wireless and wired communication techniques, as well as new techniques like Cognitive Radio (CR), TV White Spaces (TVWS), and Smart Utility Networks (SUN), that are ideal for the SG environment, are compared in detail. Finally, the proposed CR based network architecture for SGCN is presented, along with its salient features. After that, the article ends with a few suggestions for how to move forward.

The exponential growth of Internet of Things (IOT) devices has introduced complexity into network traffic management and security. This study investigates the efficacy of machine learning techniques in classifying diverse IOT device types based on their network traffic patterns. A comprehensive dataset comprising traffic data from various IoT devices is collected and analyzed. Supervised and unsupervised machine learning models are then deployed for classification, leveraging feature extraction and selection methods. Results reveal promising accuracy rates, with XGBoost achieving the highest accuracy at 91.2%, closely followed by Random Forest at 90.9%. The Decision Tree algorithm also performs well, with an accuracy score of 90%, and the Gradient Boosting algorithm has an accuracy of 87%. These findings underscore the potential of machine learning in bolstering network security, optimizing resource allocation, and enhancing IOT ecosystem management.

This paper explores recent advancements in industrial microcontroller platforms, with a specific emphasis on the Kerduino microcontroller. The investigation systematically examines distinctive features of Kerduino, encompassing considerations in system design, voltage regulation, board programming interfaces, and mechanical robustness. The Kerduino microcontroller is highlighted for its outstanding performance in industrial settings, characterized by a wide voltage tolerance range (12-30 V), a robust power output of 5A (25W), and notable durability under challenging environmental conditions, facilitated by robust wiring connections and anti-vibration mechanisms. The study delves into the engineering intricacies of Kerduino's design, accentuating its adaptability and customization capabilities for seamless integration with diverse sensors, actuators, and shields. Moreover, the paper underscores Kerduino's open-source nature, promoting collaborative and transparent development. Through a comparative analysis, the paper positions Kerduino as a versatile, dependable, and resilient choice for industrial microcontroller applications, presenting innovative advancements that significantly contribute to the evolving field of industrial automation and control systems. The separate delineation of the Kerduino platform's development methodology further affirms its systematic approach, optimizing design, refinement processes, and expediting time-to-market, thus solidifying its standing as an innovative solution in industrial microcontroller technology.

The hyperspectral imaging is efficiently discriminating between different types of land cover because it utilizes narrow bands of the electromagnetic spectrum. However, the spatial resolution of hyperspectral images might not match their spectral resolution due to certain manufacturing limitation. In order to solve this issue, research was aim of improving the hyperspectral images spatial resolution by using of Principal Component (PC) fusion method. In particular, the research focused on fusing the hyperspectral image which obtained from Hyperion sensor on the Earth Observation one (EO-1) satellite, it has a spatial resolution of (30) meters, with the panchromatic image obtained from the Operational Land Imager (OLI) sensor on the Landsat-8 satellite, which has a high spatial resolution of (15) meters. The research study area located between 395632.4994 - 401212.3000 East and 3789142.5003 - 3780952.6126 North in the Samarra region of Salah Al-Din province. Many preprocessing techniques have been applied on hyperspectral image, involving the elimination of bad bands and bad columns, in addition to the application of radiometric, atmospheric, and geometric corrections. The results were supported by both visual and quantitative assessments of the fusion outcomes for red, green and blue bands. Where blue band shows the highest correlation and the best information.

A total of 35 bacterial isolates were collected from Al-Kadhimiya Teaching Hospital between December 2015 and March 2016, sourced from various clinical cases. The isolates were cultured on blood and MacConkey media to facilitate bacterial isolation and identification, , which were further confirmed using microscopic and biochemical tests.
Eight bacterial genera were identified with diferent numbers of isolates: Pseudomonas aeruginosa (6 isolates), Enterobacter sp. (6 isolates), Acinetobacter baumannii (2 isolates), Staphylococcus aureus (7 isolates), Staphylococcus epidermidis (1 isolate), and Escherichia coli (8 isolates). Escherichia coli type1 (1 isolate) Klebsiella pneumoniae (4 isolate). Antibiotic resistance testing revealed significant resistance among the isolates, with all exhibiting resistance to Carbenicillin and Cloxacillin. Notably, only one isolate demonstrated resistance to Imipenem, which was the most effective antibiotic in this study. Biofilm formation, a critical factor contributing to bacterial pathogenicity and resistance to host defenses and antibiotics, was also evaluated using the Congo Red agar test. All isolates of Klebsiella pneumoniae and Enterobacter sp., also, 6 of the 7 isolates of Staphylococcus aureus, and, 5 of the 8 isolates of Escherichia coli demonstrated positive biofilm formation