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- Angular-axes features (1)
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- Deep learning (1)
- Discrete Wavelet Transform (1)
- Image Hiding (1)
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- Keywords: Freezing of Gait (FoG) (1)
- LU factorization (1)
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- Spectrogram (1)
- Steganography (1)
- Web-Based E-Learning (1)
Articles 1 - 5 of 5
Full-Text Articles in Computer Engineering
The Factors Influencing The Acceptance Of Web-Based E-Learning System Among Academic Staffs Of Saudi Arabia, Ikhlas Zamzami
The Factors Influencing The Acceptance Of Web-Based E-Learning System Among Academic Staffs Of Saudi Arabia, Ikhlas Zamzami
Future Computing and Informatics Journal
It is possible to learn more quickly and effectively with e-learning software development because it provides learners with convenient and flexible learning environments. This allows them to progress further in their careers. Reports on web-based e-learning systems for in-service education have frequently neglected to include the viewpoint of the instructor. In order to conduct quantitative research, a sample of 50 academic staff members was selected. The purpose of this study was to investigate various factors that influence the intention to use web-based e-learning, with the theoretical foundation being provided by university lecturers. According to the findings of the study, the …
Image Hiding Using Qr Factorization And Discrete Wavelet Transform Techniques, Reham Ahmed El-Shahed, Maryam Al-Berry, Hala Ebied, Howida Shedeed
Image Hiding Using Qr Factorization And Discrete Wavelet Transform Techniques, Reham Ahmed El-Shahed, Maryam Al-Berry, Hala Ebied, Howida Shedeed
Future Computing and Informatics Journal
Steganography is one of the most important tools in the data security field as there is a huge amount of data transferred each moment over the internet. Hiding secret messages in an image has been widely used because the images are mostly used in social media applications. The proposed algorithm is a simple algorithm for hiding an image in another image. The proposed technique uses QR factorization to conceal the secret image. The technique successfully hid a gray and color image in another one and the performance of the algorithm was measured by PSNR, SSIM and NCC. The PSNR for …
Review Of Data Mining Techniques For Detecting Churners In The Telecommunication Industry, Mahmoud Ewieda, Mohamed Ismail Roushdy, Essam Shaaban
Review Of Data Mining Techniques For Detecting Churners In The Telecommunication Industry, Mahmoud Ewieda, Mohamed Ismail Roushdy, Essam Shaaban
Future Computing and Informatics Journal
The telecommunication sector has been developed rapidly and with large amounts of data obtained as a result of increasing in the number of subscribers, modern techniques, data-based applications, and services. As well as better awareness of customer requirements and excellent quality that meets their satisfaction. This satisfaction raises rivalry between firms to maintain the quality of their services and upgrade them. These data can be helpfully extracted for analysis and used for predicting churners. Researchers around the world have conducted important research to understand the uses of Data mining (DM) that can be used to predict customers' churn. This …
Multilayer Perceptron With Auto Encoder Enabled Deep Learning Model For Recommender Systems, Subhashini Narayan
Multilayer Perceptron With Auto Encoder Enabled Deep Learning Model For Recommender Systems, Subhashini Narayan
Future Computing and Informatics Journal
In this modern world of ever-increasing one-click purchases, movie bookings, music, health- care, fashion, the need for recommendations have increased the more. Google, Netflix, Spotify, Amazon and other tech giants use recommendations to customize and tailor their search engines to suit the user’s interests. Many of the existing systems are based on older algorithms which although have decent accuracies, require large training and testing datasets and with the emergence of deep learning, the accuracy of algorithms has further improved, and error rates have reduced due to the use of multiple layers. The need for large datasets has declined as well. …
Deep Feature Learning For Fog Episodes Prediction In Patients With Pd, Hadeer Elziaat, Nashwa El-Bendary, Ramdan Mowad
Deep Feature Learning For Fog Episodes Prediction In Patients With Pd, Hadeer Elziaat, Nashwa El-Bendary, Ramdan Mowad
Future Computing and Informatics Journal
A common symptom of Parkinson's Disease is Freezing of Gait (FoG) that causes an interrupt of the forward progression of the patient’s feet while walking. Therefore, Freezing of Gait episodes is always engaged to the patient's falls. This paper proposes a model for Freezing of Gait episodes detection and prediction in patients with Parkinson's Disease. Predicting Freezing of Gait in this paper considers as a multi-class classification problem with 3 classes namely, FoG, pre-FoG, and walking episodes. In this paper, the extracted feature scheme applied for the detection and the prediction of FoG is Convolutional Neural Network (CNN) spectrogram time-frequency …