Waqas Ali

SliceFL: Dependency-Aware Fault Localization via Backward Program Slicing

Waqas Ali, Xiaobing Sun, Lili Bo, Anisha Ali

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Agent based adaptive risk aware access control for air traffic control system

Hanaa Nafea, Awais Qasim, Syed Mustaghees Abbas, Waqas Ali

The increasing complexity and critical nature of air traffic control systems demand robust and scalable security mechanisms to ensure the safe and efficient management of airspace. This research proposes a novel approach that uses multi-agent systems with adaptive risk-aware access control for …

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Bit Pattern based Sindhi Character Recognition using Neural Network

Saima Siraj, Shamshad Lakho, Waqas Ali, Akhtar Hussain Jalbani

In this paper, bit pattern based character recognition for Sindhi language has been presented. The characters of sindhi language are very much complexed to recognize for particular domain. Although there are many studies that have already been done in this recognition but …

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Leveraging Deep Learning with Multi-Head Attention for Accurate Extraction of Medicine from Handwritten Prescriptions

Sahil Ranmbail, Muhammad Sajid Nadeem, Hamid Ishfaq, Muhammad Umer Ramzan et autres

Extracting medication names from handwritten doctor prescriptions is challenging due to the wide variability in handwriting styles and prescription formats. This paper presents a robust method for extracting medicine names using a combination of Mask R-CNN and Transformer-based Optical Character Recognition (TrOCR) …

Leveraging Deep Learning With Multi-Head Attention for Accurate Extraction of Medicine From Handwritten Prescriptions

Usman Ali, Sahil Ranmbail, Muhammad Sajid Nadeem, Hamid Ishfaq et autres

Extracting medication names from handwritten doctor prescriptions is challenging due to the wide variability in handwriting styles and prescription formats. This paper presents a robust method for extracting medicine names using a combination of Mask R-CNN and Transformer-based Optical Character Recognition (TrOCR) …

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Adaptive Bug Localization Framework for Precision-Driven Bug Localization in Software Engineering

Waqas Ali, Saima Siraj, Shamshad Lakho, Nadeem Naeem Bhatti et autres

Software development always looks for automated methods to improve productivity and accuracy in issue detection. The paper conducts a comparative examination of several machine-learning techniques to tackle the bug localization difficulty. Our study compared the performance of Logistic Regression (LR), Random Forest …

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Envisioning the Future of Debugging: The Advent of ABERT for Adaptive Neural Localization of Software Anomalies

Waqas Ali, Saima Siraj, Shamshad Lakho, Shahid Iqbal

Locating bugs is a crucial but difficult aspect of program maintenance. An improved machine learning approach called Adaptive Bidirectional Encoder Representations from Transformers (ABERT) is presented in this work to improve the conventional bug localization procedure. ABERT utilizes an adaptive attention mechanism …

Cross-Platform Bug Localization Strategies: Utilizing Machine Learning for Diverse Software Environment Adaptability

Waqas Ali, Mariam Sabir

This paper introduces a novel hybrid machine learning model that combines Long Short-Term Memory (LSTM) networks and SHapley Additive exPlanations (SHAP) to enhance bug localization across multiple software platforms. The aim is to adapt to the variability inherent in different operating systems …

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Software bug localization based on optimized and ensembled deep learning models

Waqas Ali, Lili Bo, Xiaobing Sun, Xiaoxue Wu et autres

Abstract An automated task for finding the essential buggy files among software projects with the help of a given bug report is termed bug localization. The conventional approaches suffer from the challenges of performing lexical matching. Particularly, the terms utilized for describing …

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Evaluating the rice genotypes at various growth stages under agro-climatic conditions of Dera Ismail Khan

Aamir Roheen, Muhammad Safdar Baloch, Muhammad Ishaq, Rashid Abbas et autres

This research study was conducted for evaluation of 5 genotypes of rice (KANGNI-27, MATHRA, E-107, E-94, and IRRI-06) for different traits at various growth stages. The experiment was done at the Agriculture Research Institute, Dera Ismail Khan during the kharif season of …

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Automated software bug localization enabled by meta-heuristic-based convolutional neural network and improved deep neural network

Waqas Ali, Lili Bo, Xiaobing Sun, Xiaoxue Wu et autres

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Artificial Intelligence and IoT-Based Autonomous Hybrid Electric Vehicle with Self-Charging Infrastructure

Aaqib Raza, Mazhar Hussain Baloch, Irfan Ali, Waqas Ali et autres

Electric vehicles (EVs) are increasing day by day across the world. Due to zero CO2emission and being environmentally friendly, electric vehicles are steadily gaining in popularity. Energy storage and charging systems are one of the main issues that should be removed completely. …

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