Mohib Ullah

From GPT-3 to GPT-5: Mapping their capabilities, scope, limitations, and consequences

Hina Afridi, Habib Ullah, Sultan Daud Khan, Mohib Ullah

We present the progress of the GPT family from GPT-3 through GPT-3.5, GPT-4, GPT-4 Turbo, GPT-4o, GPT-4.1, and the GPT-5 family. Our work is comparative rather than merely historical. We investigates how the family evolved in technical framing, user interaction, modality, deployment …

From GPT-3 to GPT-5: Mapping their capabilities, scope, limitations, and consequences

Hina Afridi, Habib Ullah, Sultan Daud Khan, Mohib Ullah

We present the progress of the GPT family from GPT-3 through GPT-3.5, GPT-4, GPT-4 Turbo, GPT-4o, GPT-4.1, and the GPT-5 family. Our work is comparative rather than merely historical. We investigates how the family evolved in technical framing, user interaction, modality, deployment …

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Distinguishing Human-Generated and AI-Generated Academic Writing: A Machine Learning Benchmark Study

Ali Raza, Mohib Ullah, Rafiullah Khan, Adeem Ali Anwar et autres

The rapid adoption of large language models (LLMs) such as ChatGPT has raised critical questions about authorship, originality, and integrity in academic writing. Unlike conventional plagiarism testing tools, AI-generated or AI-rephrased text can preserve the original meaning and context of the text …

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Large Language Models as a Cyber Range

Muhammad Mudassar Yamin, Basel Katt, Saira Yamin, Mohib Ullah et autres

The Cyber ranges function as platforms designed to educate individuals on managing technical systems through systematic procedures within a Cyber security domain. They offer areas to experiment with and also to validate various cyber security concepts without exposure to actual risks. Furthermore, …

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SELFIE-Net: Self-supervised Learning and Feature-Intensified Emotion Network for Facial Emotion Recognition

Saif Al-Deen H. Hassan, Ehtesham Hashmi, Ghulam Mujtaba, Muhammad Mudassar Yamin et autres

As the requirement for the strong Facial Emotion Recognition (FER) systems in different applications increases, both in healthcare and security, it is important to address issues such as multiple facial expressions and complicated backgrounds. This paper proposes a new FER framework called …

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AI‐Driven SMS Intelligence Framework for Detecting Fraud, Disinformation, and Threat Patterns in Pakistan’s Communication Networks

Maryam Zaman, Mohib Ullah, Rafiullah Khan, Irfan Ullah Khan et autres

Fraudulent SMS messages are a significant threat in Pakistan, impacting financial security, identity theft, and misinformation and enabling exploitation by adversaries. This study proposes a localized AI‐based framework for SMS fraud detection, utilizing machine learning (logistic regression [LR], random forest [RF], support …

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From Contrast to Non-Contrast: Enhancing Cardiac Segmentation in Non-Contrast CT Scans

Muhammad Fahad, Øyvind Nordbø, Ali Shariq Imran, Faouzi Alaya Cheikh et autres

Contrast-Enhanced Computed Tomography (CECT) is extensively utilized in cardiac imaging due to its superior anatomical detail, enabling accurate segmentation of cardiac structures. However, the use of contrast agents poses risks for patients with pre-existing medical conditions such as allergies. Non-Contrast Computed Tomography …

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Militarised Narratives and Retaliatory Rhetoric: A Comparative CDA of the 2025 India-Pakistan War

Rabeea Maryam, Mohib Ullah

This paper presents a comparative critical discourse analysis (CDA) of official military press conferences by India and Pakistan in the 2025 War. Grounded in Fairclough’s Three-Dimensional Model, Van Dijk’s Ideological Square, and Entman’s Framing Theory, this paper investigates how India and Pakistan …

Screening of bacterial strains for heavy metal stress tolerance, antimicrobial potential, and optimum growth at a wide range of pH and temperatures

Mohib Ullah, Sondos A. Alhajouj, Abdul Basit, Hazrat Ullah et autres

Enhancing Interpretability in Gastrointestinal Disease Detection: A Comparative Analysis of Deep Learning Architectures and Explainable AI

Muhammad Fahad, Saif Al-Deen H. Hassan, Faouzi Alaya Cheikh, Mohib Ullah

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Stacked LSTM Model for Contextual Correlation Detection Among Multiple Emotions

Aqsa Younas, Shazia Riaz, Saqib Ali, Rafiullah Khan et autres

Emotions are closely tied to human behavior and play a critical role in daily life. With the widespread use of social media, individuals frequently express their feelings online, making emotion extraction from social networks an active area of research. This has applications …

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Unveiling Biodiesel Production: Exploring Reaction Protocols, Catalysts, and Influential Factors

Zahoor Ullah, Mohamad Azmi Bustam, Mohib Ullah, Mamoon‐Ur‐Rashid et autres

Abstract An environmentally responsible and sustainable replacement for finite fossil fuels is biodiesel. Because of its amazing qualities, biodiesel is becoming more and more popular as a renewable fuel around the globe. The many approaches, feedstocks, catalysts, comparison standards, reaction kinetics, final …

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