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-attention-based convolutional neural network (CNN) model. To address age ambiguity, we evaluate the effects of different loss functions such as focal loss and Kullback-Leibler (KL) divergence loss. Additionally, we evaluate the accuracy of the estimation at different durations of speech. Experimental results from the Common Voice dataset underscore the efficacy of our approach, showcasing an accuracy of 87% for male speakers, 91% for female speakers and 89% overall accuracy, and an accuracy of 99.1% for gender prediction.
This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward
... Show MoreIn this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.
Social media and news agencies are major sources for tracking news and events. With these sources' massive amounts of data, it is easy to spread false or misleading information. Given the great dangers of fake news to societies, previous studies have given great attention to detecting it and limiting its impact. As such, this work aims to use modern deep learning techniques to detect Arabic fake news. In the proposed system, the attention model is adapted with bidirectional long-short-term memory (Bi-LSTM) to identify the most informative words in the sentence. Then, a multi-layer perceptron (MLP) is applied to classify news articles as fake or real. The experiments are conducted on a newly launched Arabic dataset called the Ara
... Show MoreDue to the lack of vehicle-to-infrastructure (V2I) communication in the existing transportation systems, traffic light detection and recognition is essential for advanced driver assistant systems (ADAS) and road infrastructure surveys. Additionally, autonomous vehicles have the potential to change urban transportation by making it safe, economical, sustainable, congestion-free, and transportable in other ways. Because of their limitations, traditional traffic light detection and recognition algorithms are not able to recognize traffic lights as effectively as deep learning-based techniques, which take a lot of time and effort to develop. The main aim of this research is to propose a traffic light detection and recognition model based on
... Show MoreThe process of evaluating data (age and the gender structure) is one of the important factors that help any country to draw plans and programs for the future. Discussed the errors in population data for the census of Iraqi population of 1997. targeted correct and revised to serve the purposes of planning. which will be smoothing the population databy using nonparametric regression estimator (Nadaraya-Watson estimator) This estimator depends on bandwidth (h) which can be calculate it by two ways of using Bayesian method, the first when observations distribution is Lognormal Kernel and the second is when observations distribution is Normal Kernel
... Show MoreBackground: The Infraorbital foramen is an anatomical structure with an important location in the maxilla, position of foramen in maxillofacial area is necessary in clinical situation requiring regional nerve blocks that are performed in children undergoing facial surgeries to avoid injury to corresponding nerve. The aim of study was to determine the position of the Infraorbital foramen and to correlate Infraorbital foramen position with age and gender using computed tomography. Subjects, Materials, and Methods: The sample consist of prospective study for 50 Iraqi subjects (21 male and 29 female) with age ranged from (5-17) years. The examination was performed on Multi – Slice Spiral Tomography scanner in Al-Karakh General Hospital. Using
... Show MoreThis study aims to reveal the similarities and differences between Iraqi and Malay university learners and their genders in producing the supportive moves of criticism. To this end, 30 Iraqi and 30 Malay university learners have participated in this study. A Discourse Completion Test (DCT) and a Focus Group Interview (FGI) are conducted to elicit responses from the participants. Nguyen’s (2005) classification of criticism supportive moves is adapted to code the data. The data are analysed qualitatively and quantitatively. Overall, the findings unveil that both groups use similar categories of supportive moves, but Iraqis produce more of these devices than Malays in their criticisms. Although both females and males of both groups use id
... Show MoreBackground: There is controversy about the upper normal value of QRS complex amplitude in adult population under the age of 40 years. Most of the left ventricular hypertrophy voltage criteria were designed or tested for people above 40 years. In addition to age, QRS amplitude is also affected by gender and racial factors.
Objectives: To evaluate the impact of age on QRS amplitude in each gender separately in healthy adults.
Patients and Methods: Electrocardiograms from 563 overtly healthy adults (386 male and 177 female) aged 18-40 years were obtained using Cardios PC based ECG machine, 12-lead ECGs were recorded and QRS amplitude was measured as the sum of (SV1+RV5) and
... Show MoreBackground: the integrity of cardiovascular reflexes & autonomic activities can be assessed by different tests and different techniques. However most of these studies carried out on male subject & usually on young group only .very little researches available concerning the differences in cardiovascular reflexes between male & female in different age group.
Aim of study: is to investigate the differences in cardiovascular reflexes in young , old male & female in response to go head up tilting using totally non- invasive system .
Sub. & Methods: this study was carried out in AL-Najaf teaching hospital on 85 normal sub. , 41 males c6 44 females they were divided into two age groups (20-40 years) & (41-60 years)