A Comprehensive Introduction to Cloud Computing Revolution DOI

A. Ashwini,

S. Balasubramaniam,

Seifedine Kadry

и другие.

Advances in healthcare information systems and administration book series, Год журнала: 2024, Номер unknown, С. 1 - 26

Опубликована: Окт. 18, 2024

Cloud computing can be considered as a revolution of how commercial enterprises obtain and use computational services. In narrow sense, cloud means the rent services over Internet with its characteristics such storage, computing, applications. An organization host an application in minutes run it without having to invest week or month procuring necessary hardware setting up help cloud. This is made possible by flexibility brought about pay you go, eliminating cases where firms incur bills resources they did not will require. Privacy essential aspect within that still emerging. done through nurturance proper encryption, security check risk analysis, creation organizational standards compliance other standards. These risks should well understood all organizations make sure measures are employed hinder adoption this technology holds great promises for growth their business processes.

Язык: Английский

MNAFH-Net: Maxout neuron attention forward harmonic network for human stress level detection DOI

Sreelekha Ponugoti,

S. P. Rajagopalan

Biomedical Signal Processing and Control, Год журнала: 2025, Номер 103, С. 107442 - 107442

Опубликована: Янв. 5, 2025

Язык: Английский

Процитировано

0
Enhanced smart weather prediction through advanced atmospheric analysis and forecasting techniques using binarized spiking neural networks DOI

M. Amanullah,

K Ananthajothi,

D. Divya

и другие.

Knowledge and Information Systems, Год журнала: 2025, Номер unknown

Опубликована: Янв. 25, 2025

Язык: Английский

Процитировано

0
Rat swarm political optimizer based deep learning approach for lung lobe segmentation and lung cancer detection using CT images DOI
V. Nagarajan,

R. Rajeswari,

Satuluri Naganjaneyulu

и другие.

Biomedical Signal Processing and Control, Год журнала: 2025, Номер 105, С. 107612 - 107612

Опубликована: Фев. 4, 2025

Язык: Английский

Процитировано

0
Hybrid Greylag Goose deep learning with layered sparse network for women nutrition recommendation during menstrual cycle DOI Creative Commons

E. Logapriya,

Surendran Rajendran,

Mohammad Zakariah

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 18, 2025

A complex biological process involves physical changes and hormonal fluctuation in the menstrual cycle. The traditional nutrition recommendation models often offer general guidelines but fail to address specific requirements of women during various cycle stages. This paper proposes a novel Optimization Hybrid Deep Learning (OdriHDL) model provide personalized health for their It pre-processing data through Missing Value Imputation, Z-score Normalization, One-hot encoding. Next, feature extraction is accomplished using Layered Sparse Autoencoder Network. Then, extracted features are utilized by Attention-based Bidirectional Convolutional Greylag Goose Gated Recurrent Network (HABi-ConGRNet) nutrient recommendation. hyper-parameter tuning HABi-ConGRNet carried out Algorithm enhance performance. Python platform used simulation collected data, several performance metrics employed analyze OdriHDL demonstrates superior performance, achieving maximum accuracy 97.52% enhanced precision rate contrast existing methods, like RNN, CNN-LSTM, attention GRU. findings suggest that captures patterns between nutritional needs symptoms provides robust solutions unique physiological experienced women.

Язык: Английский

Процитировано

0
Exploring the structural features of Triangular fractal antenna for detection of brain tumor DOI Creative Commons

P. Bini Palas,

K. Rahimunnisa

Ain Shams Engineering Journal, Год журнала: 2025, Номер 16(5), С. 103369 - 103369

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0
Hybrid of DSR-GAN and CNN for Alzheimer disease detection based on MRI images DOI Creative Commons
Samy E. Oraby, Ahmed A. Emran, Basel Mounir El Saghir

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 13, 2025

In this paper, we propose a deep super-resolution generative adversarial network (DSR-GAN) combined with convolutional neural (CNN) model designed to classify four stages of Alzheimer's disease (AD): Mild Dementia (MD), Moderate (MOD), Non-Demented (ND), and Very (VMD). The proposed DSR-GAN is implemented using PyTorch library uses dataset 6,400 MRI images. A (SR) technique applied enhance the clarity detail images, allowing refine particular image features. CNN undergoes hyperparameter optimization incorporates data augmentation strategies maximize its efficiency. normalized error matrix area under ROC curve are used experimentally evaluate CNN's performance which achieved testing accuracy 99.22%, an 100%, rate 0.0516. Also, assessed three different metrics: structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), multi-scale (MS-SSIM). SSIM score 0.847, while PSNR MS-SSIM percentage 29.30 dB 96.39%, respectively. combination models provides rapid precise method distinguish between various disease, potentially aiding professionals in screening AD cases.

Язык: Английский

Процитировано

0
Metaheuristic optimizers integrated with vision transformer model for severity detection and classification via multimodal COVID-19 images DOI Creative Commons

V. Padmavathi,

G. Kavitha

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 22, 2025

Язык: Английский

Процитировано

0
Remote and Urban Environmental Area Sensing, Connectivity Issues, and Solutions Based on Emerging Technologies DOI

M. Abinaya,

G. Vadivu,

S. Balasubramaniam

и другие.

Опубликована: Фев. 2, 2025

Язык: Английский

Процитировано

0
A novel optimized machine learning approach with texture rectified cross-attention based transformer for COVID-19 detection DOI

C. Binu Jeya Schafftar,

Aiswaryah Radhakrishnan,

C. Emmy Prema

и другие.

Biomedical Signal Processing and Control, Год журнала: 2024, Номер 101, С. 107136 - 107136

Опубликована: Ноя. 17, 2024

Язык: Английский

Процитировано

1
A Comprehensive Introduction to Cloud Computing Revolution DOI

A. Ashwini,

S. Balasubramaniam,

Seifedine Kadry

и другие.

Advances in healthcare information systems and administration book series, Год журнала: 2024, Номер unknown, С. 1 - 26

Опубликована: Окт. 18, 2024

Cloud computing can be considered as a revolution of how commercial enterprises obtain and use computational services. In narrow sense, cloud means the rent services over Internet with its characteristics such storage, computing, applications. An organization host an application in minutes run it without having to invest week or month procuring necessary hardware setting up help cloud. This is made possible by flexibility brought about pay you go, eliminating cases where firms incur bills resources they did not will require. Privacy essential aspect within that still emerging. done through nurturance proper encryption, security check risk analysis, creation organizational standards compliance other standards. These risks should well understood all organizations make sure measures are employed hinder adoption this technology holds great promises for growth their business processes.

Язык: Английский

Процитировано

0