Hasan Ali Khattak

MetaResNet: Enhancing Microbiome-Based Disease Classification through Colormap Optimization and Imbalance Handling

Awais Qureshi, Abdul Wahid, Shams Qazi, Hasan Ali Khattak et autres

Image-based representations of metagenomic data enable convolutional neural network (CNN) applications for microbiome disease classification. However, the impact of colormap selection on model performance remains unexplored. Current approaches arbitrarily select visualization parameters despite evidence that colormap choices can suppress minority-class features in …

Zimbabwe, pk, ae, au (code pays fourni par la source)

Efficient fruit disease diagnosis on resource-constrained agriculture devices

Sadaf Iftikhar, Hasan Ali Khattak, Ahsan Saadat, Zoobia Ameer et autres

Climate change in recent years has caught the attention of researchers worldwide, with drastic effects on many economic sectors, especially agriculture and livestock. Due to global warming and declining water levels, food security is becoming an increasingly urgent concern. The situation is …

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Domain-Adapted Captioning Framework for Accessibility and Assistive Technologies

Enkhmend Nergui, Sukhjargalmaa Avirmed, Dorjpagma Dorjderem, Nandintsetseg Damdinsuren et autres

AI-based image captioning has emerged as a cornerstone of next-generation assistive technologies, enabling visually impaired users to access and understand their surroundings through natural language. Despite rapid advances in vision–language models, no existing work has systematically evaluated these systems under the real-world …

A Calibrated Clinicogenomic Framework for Glioblastoma Survival Prediction

Qinghua Li, Zhihui Liu, Ken Benedict Alemanio, Angela Bautista et autres

Glioblastoma (GBM) remains the most lethal primary brain tumour, motivating calibrated clinicogenomic risk models that can guide treatment escalation. Existing studies often rely on single modalities, leading to optimistic discrimination, poor calibration, and limited clinical utility. We assembled a matched TCGA cohort …

Beyond Traditional Methods: A NLP and Knowledge Graph Approach to Cyber Threat Detection and Visualization

Muhammad Qaisar, Bilal Ali, Hasan Ali Khattak

Cyber threat detection, analysis, and mitigation are becoming more and more complex, as traditional signature-based cybersecurity methods tend to be limited in their effectiveness against evolving threats. This work presents a novel framework for real-time threat detection and visualisation leveraging Natural Language …

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Demand response for efficient power generation in smart grids using hyper–local weather prediction

Faraz Shaikh, Hasan Ali Khattak, Hasan Sohaib Alavi, Haleem Farman et autres

Optimizing power generation is crucial in the evolving smart grid and urban ecosystem landscape. Efficient energy use is vital in today’s tech-driven world, with smart grids leading the way in managing energy consumption and distribution. Given the link between climate and energy …

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Combining UAV Multispectral Data & Crop Morphological Features for Sunflower Oil Content Estimation

Muhammad Ali, Usama Athar, Zuhair Zafar, Hasan Ali Khattak et autres

Accurate pre-harvest estimation of seed composition is imperative for advancing field management practices and refining plant phenotyping approaches. This research pioneers the utilization of artificial intelligence (AI) methods built upon crop morphological and unmanned aerial vehicle (UAV) multispectral data to estimate sunflower …

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Comprehensive review of academic search systems: evolution, analysis, and future research directions

Shah Khalid, Sulaiman Sulmi Almutairi, Abdallah Namoun, Jawad Khan et autres

Abstract Most countries today emphasize scientific research and invest heavily in it. As a result, the number of scholarly documents has increased dramatically. Both academics and industry professionals seek to retrieve relevant papers efficiently. However, identifying relevant documents on a given topic …

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Current Trends and Advances in Extractive Text Summarization: A Comprehensive Review

Shah Khalid, Sulaiman Sulmi Almutairi, Hasan Ali Khattak, Abdallah Namoun et autres

Given the rapid increase of textual data in various fields, text summarization has become essential for efficient information handling. Over recent decades, numerous methods have been proposed to enhance summarization processes, and various review papers and books have been published to encapsulate …

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Corrigendum to “Towards an effective model for lung disease classification Using Dense Capsule Nets for early classification of lung diseases” Appl. Soft Comput. 124 (2022) 109077

Faizan Karim, Munam Ali Shah, Hasan Ali Khattak, Zoobia Ameer et autres

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Retraction Note: A hybrid machine learning framework to predict mortality in paralytic ileus patients using electronic health records (EHRs)

Fahad Shabbir Ahmed, Liaqat Ali, Raza Ul Mustafa, Hasan Ali Khattak et autres

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Towards Blockchain-based Decentralized Employee Transfer System

Alam Zaib, Ehzaz Mustafa, Ahsan Raza Khan, Hasan Ali Khattak et autres

Employees are the main driving force in organizations that undergo recruitment, promotion, and transfer. There are many employee management systems, but most of them are centralized. Centralization leads to problems such as lack of transparency, auditability issues, vulnerability, and a single point …

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