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BEYOND WORDS: HARNESSING SPEECH SOUND FOR SPEAKER AGE AND GENDER DETECTION USING 1D CNN ARCHITECTURE WITH SELF-ATTENTION MECHANISM
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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.

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Publication Date
Mon Feb 14 2022
Journal Name
Journal Of Educational And Psychological Researches
Social Skills and its Relationship with Self-Regulation of Gifted Students According to the academic Stage and Gender
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This study aimed at investigating the level of social skills and its relationship with self-regulation among gifted students according to the academic stage and gender. The sample consisted of (417) male and female students at King Abdullah II School for Excellence in Salt, Jordan. Two instruments were used to collect the data; A scale of social skills and a scale of self-regulation. The results revealed that the level of social skills was high among gifted students. There were statistically significant differences in the social skills among gifted students according to their academic stage in favor of the secondary stage and according to their gender in favor of female students. There were statistically signific

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Publication Date
Thu Mar 14 2024
Journal Name
2024 11th International Conference On Reliability, Infocom Technologies And Optimization (trends And Future Directions) (icrito)
Beyond Containers: Orchestrating Microservices with Minikube, Kubernetes, Docker, and Compose for Seamless Deployment and Scalability
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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

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Publication Date
Tue Dec 24 2024
Journal Name
Journal Of Baghdad College Of Dentistry
Salivary gland tumors: A review of 171 cases, with particular reference to histological types, site, age and gender distribution
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Background: Salivary tumors are uncommon, being of low incidence worldwide. This study aimed to assess cases collected in this series of salivary gland tumors in regard to histopathological typing, in relation to age, site and gender. Materials and methods: This is a retrospective study; cases were collected from public and private laboratories. A total number of 171 cases were collected. The slides were reviewed and reclassified for histopathological typing according to WHO classification 2005. Results: Benign tumors were more common than malignant tumors. The most common histological type was benign mixed tumor, followed by Warthin’s tumor. The most common malignant tumor was adenoid cystic carcinoma. One hundred twenty three cases ou

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Publication Date
Sat Jul 01 2023
Journal Name
International Journal Of Intelligent Engineering And Systems
An Efficient Cryptosystem for Image Using 1D and 2D Logistic Chaotic Maps
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Publication Date
Tue Oct 08 2024
Journal Name
Technology In Agronomy
Harnessing automation techniques for supporting sustainability in agriculture
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Automation is one of the key systems in modern agriculture, providing potential solutions to the challenges related to the growing world population, demographic shifts, and economic situation. The present article aims to highlight the importance of precision agriculture (PA) and smart agriculture (SA) in increasing agricultural production and the importance of environmental protection in increasing production and reducing traditional production. For this purpose, different types of automation systems in the field of agricultural operations are discussed, as well as smart agriculture technologies including the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), big data analysis, in addition to agricultural robots,

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Publication Date
Fri Jul 01 2022
Journal Name
Rawal Medical Journal
Macular thickness correlation with gender and age in a sample of healthy eyes of Iraqi population utilizing optical coherence tomography
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Publication Date
Wed Feb 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Diagnose COVID-19 by using hybrid CNN-RNN for Chest X-ray
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<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

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Publication Date
Tue Dec 20 2022
Journal Name
2022 4th International Conference On Current Research In Engineering And Science Applications (iccresa)
Noise Detection and Removing in Heart Sound Signals via Nuclear Norm Minimization Problems
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Heart sound is an electric signal affected by some factors during the signal's recording process, which adds unwanted information to the signal. Recently, many studies have been interested in noise removal and signal recovery problems. The first step in signal processing is noise removal; many filters are used and proposed for treating this problem. Here, the Hankel matrix is implemented from a given signal and tries to clean the signal by overcoming unwanted information from the Hankel matrix. The first step is detecting unwanted information by defining a binary operator. This operator is defined under some threshold. The unwanted information replaces by zero, and the wanted information keeping in the estimated matrix. The resulting matrix

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Natural And Applied Sciences Ural
Electron Microscope Study of Human Cerebral Cortex (Left Superior Temporal Gyrus), in Different Age Groups and Gender Electron Microscope Study of Human Cerebral Cortex (Left Superior Temporal Gyrus), in Different Age Groups and Gender
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Human cerebral cortex is the outer folded neuronal layer and represents major part of the cerebrum with enormous functions. It is a laminar structure, easily visualized grossly. Previous studies showed that the Superior Temporal gyrus is one of the thickest cerebral cortex regions, reaching (about 4 mm). The Electron microscope study was made on 6 samples taken to measure the neuronal soma dimension of the large pyramidal cells present in the internal pyramidal cortical layer V in different age groups and gender. Aging process was obvious on the large pyramidal cells of the cerebral cortex, in which their neuronal soma dimensions showed shrinkage with age progression. But statistically there was no differences in the values between males an

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