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Research ArticleOpen accessIn the abstractHybrid CNN-Based Transformer Pipeline With Radiomic Fusion for Multi-Class Lung Cancer DetectionAanchal Vij, Kuldeep Singh Kaswan, Anand NayyarEarly detection of lung cancer remains challenging due to high intra-class variation and inter-class similarity in Computed Tomography (CT) images. In this paper, we propose a hybrid deep learning model that combines convolutional, attention-based, and transformer-guided representations to address these challenges in multi-class lung cancer classification. For deep feature extraction, we use the EfficientNetV2-S architecture augmented with a Convolutional Block … …Journal of Computer Science, Vol. 22, Issue 6 · 3 Jun 2026 · 1,528 accessesView PDFCite
Research ArticleOpen accessIn the abstractPreparation and Properties Study of PCM@ECD BilayerYan Zhao, Heng Zhang, Yanfei Zhao et al.This study reports the fabrication of a core-shell active bilayer membrane (PCM@ECD) via a combined tape-casting and layer-transfer methodology. The inner core layer comprised Pectin-Chitosan (PC) microcapsules, synthesized by complex coacervation, encapsulating Orange Peel Essential Oil (OPEOM) with an embedding efficiency of 83.08%. The outer shell layer consisted of Ethyl Cellulose (EC) doped with zinc-doped carbon dots (Zn-CDs, average size: … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 1 · 8 May 2026 · 1,600 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassifcation of Social Media Posts X For Mental Health Symptoms Identification Using NLP Techniques and Transformers ModelAndika Dwi Asmoro Wicaksono, RojaliThe increasing use of social media has enabled large-scale analysis of user-generated content to monitor mental health trends. This study focuses on sentiment prediction of mental health-related posts on platform X using transformer-based models, specifically IndoBERT, DistilBERT, and IndoRoBERTa. The goal is to evaluate the effectiveness of these models in classifying social media posts into positive, negative, and neutral sentiment … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,851 accessesView PDFCite
Research ArticleOpen accessIn the abstractAssessing Bi-LSTM Model’s Performance in Identifying AI Generated Text in Digital MediaTinashe Crispen Garidzira, William Tichaona Vambe, Courage MatoboboThe rapid growth of AI-generated content from ChatGPT, Gemini, and many others poses significant challenges in digital media. There are increasing instances of text generated by machine learning models being indistinguishable from human-written text. This calls for an effective way of detecting and distinguishing text generated by AI from human text. Using a Cross-Industry Standard Process for Data Mining (CRISP-DM) … …Journal of Computer Science, Vol. 21, Issue 8 · 8 Oct 2025 · 2,416 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementation of Single Candidate Loss Optimization Algorithm for Loss Optimization of Bhojpuri-English Machine Translation ModelRituraj Dixit, Sarabjeet Singh Bedi, Ibrahim Aljubayri, Mohammad Zubair KhanMachine translation of low-resource Indian languages is necessary as most of the regions still know and speak their specific dialects and are still not comfortable understanding the English language. Indian languages are morphologically rich, due to which there are two big challenges, Ambiguity and Domain adaption, which are faced by researchers during the translation. Lack of data also increases the … …Journal of Computer Science, Vol. 21, Issue 5 · 17 Apr 2025 · 5,151 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comprehensive Survey on Fake News Detection Using Machine LearningShraddha Shah, Sachin PatelIn the age of information data surplus and social media impact, the propagation of fake news has developed a significant societal concern. This challenge requires robust tools and methodologies for addressing, with machine learning emerging as a promising approach. The paper reviews different machine learning techniques in fake news detection, including supervised, unsupervised and semi-supervised methods. Supervised methods utilize labelled … …Journal of Computer Science, Vol. 21, Issue 4 · 20 Mar 2025 · 9,212 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Text Data Hiding Technique Using Cryptography and SteganographyNor Fazlida Mohd Sani, Mohamad Adreen NujjaidSteganography serves as a technique for covertly embedding confidential information within other data, ensuring that both the existence and content of this hidden data remain undisclosed to unauthorized parties. Its applications span diverse domains, including military operations, online payment systems, and the Internet of Things (IoT). Steganography proves highly adaptable in concealing data, as information with an unknown presence escapes … …Journal of Computer Science, Vol. 21, Issue 1 · 3 Dec 2024 · 5,986 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Nested Digital Watermarking Scheme Using GARN with DWTEdward Yellakour Baagyere, Peter Awonnatemi Agbedemnab, Mohammed Akolgo, Strato Angsoteng BayitaaCopyright infringement is undoubtedly one of the major challenges in the film and TV industries over the years but has become even more pervasive lately as a result of technological advancement. This has made it possible to decode hitherto, hard-encoded, or encrypted multimedia content resulting in a lot of losses to companies in such industries. Digital watermarking, which is, a … …Journal of Computer Science, Vol. 20, Issue 10 · 30 Jul 2024 · 4,793 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving Arabic Named Entity Recognition with a Modified Transformer EncoderHamid Sadeq Mahdi Alsultani, Ahmed H. AliwyThis article investigates the use of a transformer encoder for Arabic Named Entity Recognition (NER). The classic transformer that was originally proposed for machine translation adopts the absolute sinusoidal position embedding which is aware of distance but unfortunately is not aware of the directionality. However, in the NER task, both distance and orientation are crucial. Therefore, in this study, instead … …Journal of Computer Science, Vol. 19, Issue 5 · 10 Apr 2023 · 5,330 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Regularization Mechanism for Combating Class Imbalance Problem in Intrusion Detection System for Defending DDoS Attack in SDNNarender M, Yuvaraju B NIntegration of deep learning into Intrusion Detection Systems (IDS) for Software Defined Networking (SDN) is an emerging field of research. Most of the datasets used to build IDS are highly imbalanced, especially in the case of DDoS attacks, which account for a larger percentage of malicious samples than normal traffic. As a result of a class imbalance, the classification result … …Journal of Computer Science, Vol. 19, Issue 3 · 24 Feb 2023 · 5,659 accessesView PDFCite