Fingerprints are commonly utilized as a key technique and for personal recognition and in identification systems for personal security affairs. The most widely used fingerprint systems utilizing the distribution of minutiae points for fingerprint matching and representation. These techniques become unsuccessful when partial fingerprint images are capture, or the finger ridges suffer from lot of cuts or injuries or skin sickness. This paper suggests a fingerprint recognition technique which utilizes the local features for fingerprint representation and matching. The adopted local features have determined using Haar wavelet subbands. The system was tested experimentally using FVC2004 databases, which consists of four datasets, each set holds

Due to the large population of motorway users in the country of Iraq, various approaches have been adopted to manage queues such as implementation of traffic lights, avoidance of illegal parking, amongst others. However, defaulters are recorded daily, hence the need to develop a mean of identifying these defaulters and bring them to book. This article discusses the development of an approach of recognizing Iraqi licence plates such that defaulters of queue management systems are identified. Multiple agencies worldwide have quickly and widely adopted the recognition of a vehicle license plate technology to expand their ability in investigative and security matters. License plate helps detect the vehicle's information automatically ra

Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a

Computer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc

This research aimed to explore the use of foamed concrete (FC), a lightweight concrete, by replacing sand with crushed plastic from washing machines to improve environmental and thermal properties. The primary components included traditional materials like cement, water, and a foaming agent, along with the innovative use of waste plastic (WP). Utilizing Minitab software, the study applied the Response Surface Method to optimize mix designs, reducing the experimental mixtures to 31, which were then tested for dry density, porosity, water absorption, shrinkage, compressive strength, splitting tensile strength, and thermal conductivity. Results indicated a significant 24% reduction in dry density when using plastic as fine and coarse aggregate

Silver nanoparticles synthesized by different species

Introduction and Aim: Klebsiella pneumoniae is a Gram-negative bacterium responsible for a wide range of infections, including respiratory tract infections (RTIs). This research was aimed to study the antibacterial and antibiofilm effect of AgNPs produced by Gram positive and negative bacteria on RTIs associated with K. pneumoniae. Materials and Methods: The biofilm formation of K. pneumoniae was determined by tube method qualitatively from select bacterial species characterized by UV-Visible spectroscopy. The antibacterial susceptibility of the bacteria AgNPs was tested for their antibacterial and antibiofilm activity on a clinical isolate of K. pneumoniae. Results: K. pneumoniae isolated from RTIs were strong biofilm producers. The ant

Introduction and Aim: Klebsiella pneumoniae is a Gram-negative bacterium responsible for a wide range of infections, including respiratory tract infections (RTIs). This research was aimed to study the antibacterial and anti-biofilm effect of AgNPs produced by Gram positive and negative bacteria on RTIs associated with K. pneumoniae.   Materials and Methods: The biofilm formation of K.  pneumoniae was determined by tube method qualitatively from select bacterial species characterized by UV-Visible spectroscopy. The antibacterial susceptibility of the bacteria AgNPs was tested for their antibacterial and antibiofilm activity on a clinical isolate of K. pneumoniae.   Results: K. pneumoniae isolated from RTIs were strong biofilm prod

This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K