COVID-19 affected the entire world due to the unavailability of the vaccine. The social distancing was a contributing factor that gave rise to the usage of Online Social Networks. It has been seen that people share the information that comes to them without verifying its source . One of the common forms of information that is disseminated that have a radical purpose is propaganda. Propaganda is organized and conscious method of molding conclusions and impacting an individual's contemplations to accomplish the ideal aim of proselytizer. For this paper, different propagandistic tweets were shared in the COVID-19 Era. Data regarding COVID-19 propaganda was extracted from Twitter. Labelling of data was performed manually using different propaganda identification techniques and Hybrid feature engineering was used to select the essential features. Ensemble machine learning classifiers were used for performing the binary classification. Adaboost shows an accuracy of 98.7%, which learns from a weak learning algorithm by updating the weights.
There are many techniques for face recognition which compare the desired face image with a set of faces images stored in a database. Most of these techniques fail if faces images are exposed to high-density noise. Therefore, it is necessary to find a robust method to recognize the corrupted face image with a high density noise. In this work, face recognition algorithm was suggested by using the combination of de-noising filter and PCA. Many studies have shown that PCA has ability to solve the problem of noisy images and dimensionality reduction. However, in cases where faces images are exposed to high noise, the work of PCA in removing noise is useless, therefore adding a strong filter will help to im
... Show MoreInformation processing has an important application which is speech recognition. In this paper, a two hybrid techniques have been presented. The first one is a 3-level hybrid of Stationary Wavelet Transform (S) and Discrete Wavelet Transform (W) and the second one is a 3-level hybrid of Discrete Wavelet Transform (W) and Multi-wavelet Transforms (M). To choose the best 3-level hybrid in each technique, a comparison according to five factors has been implemented and the best results are WWS, WWW, and MWM. Speech recognition is performed on WWS, WWW, and MWM using Euclidean distance (Ecl) and Dynamic Time Warping (DTW). The match performance is (98%) using DTW in MWM, while in the WWS and WWW are (74%) and (78%) respectively, but when using (
... Show MoreThis paper aims to propose a hybrid approach of two powerful methods, namely the differential transform and finite difference methods, to obtain the solution of the coupled Whitham-Broer-Kaup-Like equations which arises in shallow-water wave theory. The capability of the method to such problems is verified by taking different parameters and initial conditions. The numerical simulations are depicted in 2D and 3D graphs. It is shown that the used approach returns accurate solutions for this type of problems in comparison with the analytic ones.
The great progress in information and communication technology has led to a huge increase in data available. Traditional systems can't keep up with this growth and can't handle this huge amount of data. Recommendation systems are one of the most important areas of research right now because they help people make decisions and find what they want among all this data. This study looked at the research trends published in Google Scholar within the period 2018-2022 related to recommending, reviewing, analysing, and comparing ebooks research papers. At first, the research papers were collected and classified based on the recommendation model used, the year of publication, and then they were compared in terms of techniques, datasets u
... Show MoreIn this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent root-
... Show MoreIn this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent r
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