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63 results for “Embedding”
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Research ArticleOpen accessIn the abstractA Robust Video Watermarking AlgorithmTahani Al-Khatib, Ali Al-Haj, Lama Rajab, Hiba MohammedProblem statement: Video watermarking is well known as the process of embedding copyright information in video bit streams. It had been proposed in recent years to solve the problem of illegal manipulation and distribution of digital video. Approach: In this study, an effective, robust and imperceptible video watermarking algorithm was proposed. This algorithm was based on a cascade of two … …Journal of Computer Science, Vol. 4, Issue 11 · 30 Nov 2008 · 6,870 accessesView PDFCite
Research ArticleOpen accessIn the abstractColored Digital Image Watermarking using the Wavelet TechniqueMohammed F. Al-Hunaity, Salam A. Najim, Ibrahiem M. El-EmaryWith the revolution of information technology and Wide Area Networking, data has become less and less private where the access of media as well as the attempts to change and manipulate the contents of media data have become a common case. For that, we need to use a watermarking technique to protect the copyright of the media as well as … …American Journal of Applied Sciences, Vol. 4, Issue 9 · 30 Sep 2007 · 6,661 accessesView PDFCite
Research ArticleOpen accessIn the abstractOne Algebra of New Generalized FunctionsSabra RamadanThe space of new Generalized functions ζ (Π(R)) has been constructed. The operation of associative multiplication Θ has been defined on ζ (Π(R)).The embedding Jπ : ζ(S(R))→ ζ( (R)) has been constructed. …Journal of Mathematics and Statistics, Vol. 3, Issue 1 · 31 Mar 2007 · 7,115 accessesView PDFCite
Research ArticleOpen accessIn the abstractEW-GAT: Edge-Weighted Graph Attention Framework for Patient-Aware Heart Disease Classification Using Feature-to-Feature Similarity GraphsRamakrishna Reddy Badveli, Nijaguna Gollara Siddappa, Sundeep Kumar KanipakapatnamHeart disease remains an important cause of global death, requiring accurate and clinically interpretable prediction models. However, traditional Machine Learning (ML) methods often fail to capture meaningful dependencies among clinical features and lack robustness across diverse patient populations. To overcome these issues, this research introduces an Edge-Weighted Graph Attention Network (EW-GAT) for patient-aware heart disease classification. The approach first models … …Journal of Computer Science, Vol. 22, Issue 7 · 25 Jul 2026 · 912 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Sentiment-Based Evaluation of Museum Display Design through Hybrid IndoBERT and Rule-Based LexiconErneza Dewi Krishnasari, Yaddarabullah, Bayyinah Nurrul Haq et al.Traditional museums remain vital cultural institutions but face persistent challenges in engaging contemporary audiences. The Wayang Museum in Indonesia, despite partial digital renovation, continues to rely heavily on static, text-based displays that often hinder visual comfort and informational comprehension. Conventional sentiment analysis techniques have demonstrated limitations in accurately capturing the subtle feedback from visitors, particularly within the culturally nuanced contexts … …Journal of Computer Science, Vol. 22, Issue 5 · 30 May 2026 · 1,326 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Sentiment-Aware Hybrid Ensemble Clustering Framework for Social Network Content Analysis and Community DiscoveryDhimesh Pravinbhai Parmar, Paresh TannaSocial media stages produce huge volumes of short, familiar, and sentiment-rich content that offerings significant encounter for community discovery and thematic analysis. Traditional clustering approach struggle with sparsity, noise, and limited surroundings information present in such texts. To address these limitations, this study introduces a sentiment-aware hybrid ensemble clustering framework designed openly for social network content analysis. The planned method … …Journal of Computer Science, Vol. 22, Issue 5 · 26 May 2026 · 1,271 accessesView PDFCite
Research ArticleOpen accessIn the abstractArabic Fake News Detection Across Generational Text Representations: From Traditional Models to Transformer-Based MethodologiesNoor M. AlkudahThe rapid proliferation of fake news on Arabic social media has amplified societal and political risks, yet research on automatic detection in Arabic remains limited due to scarce datasets, morphological complexity, and underexplored preprocessing strategies. This study presents a comprehensive benchmark for Arabic fake news detection, unifying seven Machine Learning (ML) algorithms, three Deep Learning (DL) models, and a transformer-based … …Journal of Computer Science, Vol. 22, Issue 4 · 17 Apr 2026 · 1,873 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Context Aware Deep Learning Framework for Multi-Level Arabic Fake News Detection Using Hybrid Linguistic RepresentationsNoor Mahmoud Alkudah, Somia Abufakher, Raja Masadeh et al.The rapid spread of false information on social media has made it even more important to be able to spot false news, especially in Arabic-speaking areas where language is more complicated and news is organized in a hierarchy. Recent research show that deep learning and transformer-based models work well, but most of them only look at performance metrics and don't … …Journal of Computer Science, Vol. 22, Issue 3 · 27 Mar 2026 · 1,566 accessesView PDFCite
Research ArticleOpen accessIn the abstractAraSenti-MARBERT-DynGCN: An Advanced Framework for Sarcasm Detection in Arabic TextBassma M Mousa, Mohammed H. Haggag, Mervat GheithSarcasm detection in Arabic texts is challenging because of the complexity in Arabic morphology, the multitudes of dialects used by native speakers, and its strong reliance on context. The lack of standardized orthography in most written forms of Arabic, combined with the frequent use of colloquialisms and metaphorical expressions, makes the task all the more difficult when trying to detect … …Journal of Computer Science, Vol. 21, Issue 11 · 12 Feb 2026 · 1,562 accessesView PDFCite
Research ArticleOpen accessIn the abstractEthioLSocMDMTLM: Exploring Application of Topic Modeling for Building Ethiopian Language Social Media Data-Based Multilingual Transformer Language Models for Multilingual Hateful Content DetectionNaol Bakala Defersha, Kula Kekeba Tune, Solomon Teferra AbateThis study proposes topic modeling techniques to develop Ethiopian Language Social Media Data Based Multilingual Transformer Language Models for multilingual hateful content detection. We modified various multilingual pretrained models, investigated the challenges of using pre-trained transformer language models, and built multilingual hateful content detection models. Topic words with rows of 1561, 70, and 1044 extracted from Afaan Oromo, Tigrigna, and … …Journal of Computer Science, Vol. 21, Issue 2 · 31 Dec 2024 · 5,204 accessesView PDFCite