Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attentio

This study aims to track and analysis Hitler's personality by explaining the impact of the social environment in shaping his behavior and addressing the defeat of Germany in the World War 1 and its impact on building his political personality and included his political activism and his policy to get rid of the terms of the Versailles Military Treaty in the light of his plans in his book ( Kifahi) The nature of the study had to be divided into an introduction and two topics followed by the conclusion of the most important results, in addition to a list of references and a summary in English and from God the Good luck.

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class

تعد فعالية دفع الثقل واحده من الفعاليات المميزة بألعاب القوى، وهي أحدى فعاليات الرمي الأربعة (رمي الرمح, رمي القرص, أطاحة المطرقة, دفع الثقل) وتطلب قدرات بدنية وقابليات حركية خاصة والتي تعتمد بشكل فعَال ومؤثر على النواحي البايوميكانيكية, خصوصا عندما يتعلق الأمر بذوي الأعاقة ومنهم فئة (40f) والذين يتمتعون بدعم كبير من المجتمع الدولي بصورة عامة وفي بلدانهم بصورة خاصة وأمكانية تطوير أنجازاتهم لرفع أسم بلدانه