Accurate Reader Identification for the Arabic Holy Quran Recitations Based on an Enhanced VQ Algorithm

The Speaker identification process is not a new trend; however, for the Arabic Holy Quran recitation, there are still quite improvements that can make this process more accurate and reliable. This paper collected the input data from 14 native Arabic reciters, consisting of “Surah Al-Kawthar” speech signals from the Holy Quran. Moreover, this paper discusses the accuracy rates for 8 and 16 features. Indeed, a modified Vector Quantization (VQ) technique will be presented, in addition to realistically matching the centroids of the various codebooks and measuring systems’ effectiveness. Note that the VQ technique will be utilized to generate the codebooks by clustering these features into a finite number of centroids. The proposed system’s software was built and executed using MATLAB®. The proposed system’s total accuracy rate was 97.92% and 98.51% for 8 and 16 centroids codebooks, respectively. However, this study discussed two validation tactics to ensure that the outcomes are reliable and can be reproduced. Hence, the K-mean clustering algorithm has been used to validate the obtained results and discuss the outcomes of this study. Finally, it has been found that the improved VQ method gives a better result than the K-means method

Comprehensive Study of a Diabetes Mellitus Mathematical Model Using Numerical Methods with Stability and Parametric Analysis

Diabetes is sweeping the world as a silent epidemic, posing a growing threat to public health. Modeling diabetes is an effective method to monitor the increasing prevalence of diabetes and develop cost-effective strategies that control the incidence of diabetes and its complications. This paper focuses on a mathematical model known as the diabetes complication (DC) model. The DC model is analyzed using different numerical methods to monitor the diabetic population over time. This is by analyzing the model using five different numerical methods. Furthermore, the effect of the time step size and the various parameters affecting the diabetic situation is examined. The DC model is dependent on some parameters whose values play a vital role in the convergence of the model. Thus, parametric analysis was implemented and later discussed in this paper. Essentially, the Runge–Kutta (RK) method provides the highest accuracy. Moreover, Adam–Moulton’s method also provides good results. Ultimately, a comprehensive understanding of the development of diabetes complications after diagnosis is provided in this paper. The results can be used to understand how to improve the overall public health of a country, as governments ought to develop effective strategic initiatives for the screening and treatment of diabetes