Building a system to identify individuals through their speech recording can find its application in diverse areas, such as telephone shopping, voice mail and security control. However, building such systems is a tricky task because of the vast range of differences in the human voice. Thus, selecting strong features becomes very crucial for the recognition system. Therefore, a speaker recognition system based on new spin-image descriptors (SISR) is proposed in this paper. In the proposed system, circular windows (spins) are extracted from the frequency domain of the spectrogram image of the sound, and then a run length matrix is built for each spin, to work as a base for feature extraction tasks. Five different descriptors are generated fro

Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa

Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition

Abstract: Background: Prediabetes and are increasing in prevalence all over the world, they each carry risks to the future development of diabetes mellitus and cardiovascular disease. These risks will be greatly exaggerated if they occur together in the same individual. The aim of the study was to find the prevalence and the association of prediabetes and metabolic syndrome, in addition to analyzing the correlation of the risk factors that lead to their development. Material and Methods: This was a cross-sectional, simple random study that included 300 Iraqi individuals, aged between 30-75 years, who accepted to take part in this study were recruited. Result: Prevalence of prediabetes and metabolic syndrome was (33.66%) and (42%) r

Banks represents financial institutions that influence the economy of any country and their evolution and development is the need to seek all states , communities, maintain and control a guarantee of the beneficiaries investors and to promote confidence, so the specialized organizations trying to set principles and rules must be adhered to and are Basel (II) of the necessary effects to be introduced and work on their application.  Banks exposed by various risks one of them operational risks that have multiple effects on the activity of the institution itself, as well as the national economy, so this study was to find out what those effects and to find solutions and appropriate proposals to avoid Iraqi banks from the effects of risk,