Muhammad Siddique
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View article: Advanced fault diagnosis in milling cutting tools using vision transformers with semi-supervised learning and uncertainty quantification
Advanced fault diagnosis in milling cutting tools using vision transformers with semi-supervised learning and uncertainty quantification Open
This study proposes a semi-supervised fault diagnosis framework based on vision transformers (ViTs) to enhance the diagnostic accuracy and generalization in machine cutting tools (MCT), particularly under the constraint of limited labeled …
View article: A Hybrid Deep Learning Framework for Fault Diagnosis in Milling Machines
A Hybrid Deep Learning Framework for Fault Diagnosis in Milling Machines Open
This paper presents a hybrid fault-diagnosis framework for milling cutting tools designed to address three persistent challenges in industrial monitoring: noisy vibration signals, limited fault labels, and variability across operating cond…
View article: Knowledge, Attitude, and Practice towards Needle Stick Injury among Nursing Students of Saida Waheed FMH College of Nursing, Lahore
Knowledge, Attitude, and Practice towards Needle Stick Injury among Nursing Students of Saida Waheed FMH College of Nursing, Lahore Open
Needle stick injuries (NSIs) pose a serious occupational hazard for healthcare workers, including nursing students during clinical training. Despite having basic knowledge, the translation of this knowledge into safe practices remains inco…
View article: An intelligent intrusion detection system for cyber-physical systems using GAN-LSTM networks
An intelligent intrusion detection system for cyber-physical systems using GAN-LSTM networks Open
Cyber-Physical Systems (CPS) face increasing cybersecurity threats, demanding advanced intrusion detection methods. This research proposes a novel GAN-LSTM hybrid model to enhance anomaly detection in CPS by addressing key limitations of t…
View article: A Hybrid Deep Learning Approach for Bearing Fault Diagnosis Using Continuous Wavelet Transform and Attention-Enhanced Spatiotemporal Feature Extraction
A Hybrid Deep Learning Approach for Bearing Fault Diagnosis Using Continuous Wavelet Transform and Attention-Enhanced Spatiotemporal Feature Extraction Open
This study presents a hybrid deep learning approach for bearing fault diagnosis that integrates continuous wavelet transform (CWT) with an attention-enhanced spatiotemporal feature extraction framework. The model combines time-frequency do…
View article: Acoustic Emission-Based Pipeline Leak Detection and Size Identification Using a Customized One-Dimensional DenseNet
Acoustic Emission-Based Pipeline Leak Detection and Size Identification Using a Customized One-Dimensional DenseNet Open
Effective leak detection and leak size identification are essential for maintaining the operational safety, integrity, and longevity of industrial pipelines. Traditional methods often suffer from high noise sensitivity, limited adaptabilit…
View article: US-China space rivalry, implications for Japan's national security and space policy
US-China space rivalry, implications for Japan's national security and space policy Open
With major ramifications for Japan's national protection and space coverage, the growing US-China opposition in area is a defining thing of cutting-edge geopolitical dynamics. Both China and America are pushing the limits in their technolo…
View article: A Deep Learning Approach for Fault Diagnosis in Centrifugal Pumps through Wavelet Coherent Analysis and S-Transform Scalograms with CNN-KAN
A Deep Learning Approach for Fault Diagnosis in Centrifugal Pumps through Wavelet Coherent Analysis and S-Transform Scalograms with CNN-KAN Open
View article: Design of Double Integral Sliding Mode Controller for Energy Storage System of a Novel Multisource Hybrid Electric Vehicle
Design of Double Integral Sliding Mode Controller for Energy Storage System of a Novel Multisource Hybrid Electric Vehicle Open
View article: Developments and Trends in Water Level Forecasting Using Machine Learning Models—A Review
Developments and Trends in Water Level Forecasting Using Machine Learning Models—A Review Open
Water level forecasting in rivers, lakes, and reservoirs is crucial for effective water resource management, flood control, and environmental planning. This review examines the latest developments and trends in water level forecasting rese…
View article: Hybrid Deep Learning Model for Fault Diagnosis in Centrifugal Pumps: A Comparative Study of VGG16, ResNet50, and Wavelet Coherence Analysis
Hybrid Deep Learning Model for Fault Diagnosis in Centrifugal Pumps: A Comparative Study of VGG16, ResNet50, and Wavelet Coherence Analysis Open
Significant in various industrial applications, centrifugal pumps (CPs) play an important role in ensuring operational efficiency, yet they are susceptible to faults that can disrupt production and increase maintenance costs. This study pr…
View article: Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization
Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization Open
This paper presents a fault diagnosis technique for milling machines based on acoustic emission (AE) signals and a hybrid deep learning model optimized with a genetic algorithm. Mechanical failures in milling machines, particularly in crit…
View article: Unlocking the Potential: Factors Driving the Competitiveness of Citrus Exports from Pakistan
Unlocking the Potential: Factors Driving the Competitiveness of Citrus Exports from Pakistan Open
Pakistan's agriculture industry is vital to the country's economy since it has confined exportation goods and markets and struggles with a lingering trade imbalance. This study shed light on the modern economic notion of competitiveness by…
View article: Pipeline Leak Detection System for a Smart City: Leveraging Acoustic Emission Sensing and Sequential Deep Learning
Pipeline Leak Detection System for a Smart City: Leveraging Acoustic Emission Sensing and Sequential Deep Learning Open
This study explores a novel approach utilizing acoustic emission (AE) signaling technology for pipeline leakage detection and analysis. Pipeline leaks are a significant concern in the liquids and gases industries, prompting the development…
View article: Inflammatory risk and cardiovascular events in patients without obstructive coronary artery disease: the ORFAN multicentre, longitudinal cohort study
Inflammatory risk and cardiovascular events in patients without obstructive coronary artery disease: the ORFAN multicentre, longitudinal cohort study Open
View article: Adult Medicine—New South Wales, Australian Capital Territory
Adult Medicine—New South Wales, Australian Capital Territory Open
View article: Fabrication Challenges in Synthesizing Porous Ceramic Membrane to Effective Flue Gas Treatment
Fabrication Challenges in Synthesizing Porous Ceramic Membrane to Effective Flue Gas Treatment Open
Global warming is a serious concern worldwide, while there are many contributors to rise the temperature of earth. One major source to it, is air pollution. It is of utmost importance to apply the necessary remedial actions to address the …
View article: LegoNet: Alternating Model Blocks for Medical Image Segmentation
LegoNet: Alternating Model Blocks for Medical Image Segmentation Open
Since the emergence of convolutional neural networks (CNNs), and later vision transformers (ViTs), the standard paradigm for model development has been using a set of identical block types with varying parameters/hyper-parameters. To lever…
View article: Structurally Different Neural Network Blocks for the Segmentation of Atrial and Aortic Perivascular Adipose Tissue in Multi-centre CT Angiography Scans
Structurally Different Neural Network Blocks for the Segmentation of Atrial and Aortic Perivascular Adipose Tissue in Multi-centre CT Angiography Scans Open
Since the emergence of convolutional neural networks (CNNs) and, later, vision transformers (ViTs), deep learning architectures have predominantly relied on identical block types with varying hyperparameters. We propose a novel block alter…
View article: Centrifugal Pump Fault Diagnosis Based on a Novel SobelEdge Scalogram and CNN
Centrifugal Pump Fault Diagnosis Based on a Novel SobelEdge Scalogram and CNN Open
This paper presents a novel framework for classifying ongoing conditions in centrifugal pumps based on signal processing and deep learning techniques. First, vibration signals are acquired from the centrifugal pump. The acquired vibration …
View article: Deep-Learning for Epicardial Adipose Tissue Assessment With Computed Tomography
Deep-Learning for Epicardial Adipose Tissue Assessment With Computed Tomography Open
Automated assessment of EAT volume is possible in CCTA, including in patients who are technically challenging; it forms a powerful marker of metabolically unhealthy visceral obesity, which could be used for cardiovascular risk stratificati…
View article: Constructing custom-made radiotranscriptomic signatures from CT angiograms: an application in COVID-19 vascular inflammation
Constructing custom-made radiotranscriptomic signatures from CT angiograms: an application in COVID-19 vascular inflammation Open
Background Advances in computational methodologies have enabled processing of large datasets originating from imaging studies. However, most imaging biomarkers suffer from a lack of direct links with underlying biology, as they are only ob…
View article: Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19
Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19 Open
View article: A human arterial transcriptomic signature predicts major adverse cardiac events and identifies novel, redox-related therapeutic targets within the vascular wall
A human arterial transcriptomic signature predicts major adverse cardiac events and identifies novel, redox-related therapeutic targets within the vascular wall Open
Background The transcriptomic profile of the human vascular wall is implicated in a range of pathologies. RNA sequencing technologies allow for interrogation of gene expression patterns that are associated with clinical outcomes and can gu…
View article: Automated quantification of epicardial adipose tissue on CCTA via deep-learning detection of the pericardium: clinical implications
Automated quantification of epicardial adipose tissue on CCTA via deep-learning detection of the pericardium: clinical implications Open
Background Epicardial adipose tissue (EAT) is a visceral fat deposit within the pericardial sac which surrounds the heart myocardium and coronary arteries. EAT volume has been demonstrated to be strongly associated with the development and…
View article: Microbiology and clinical characteristics of acute cholangitis with their impact on mortality; A retrospective cross-sectional study.
Microbiology and clinical characteristics of acute cholangitis with their impact on mortality; A retrospective cross-sectional study. Open
Early identification of risk factors, administration of appropriate antibiotics and establishing early biliary drainage were found to be the key management steps to reduce cholangitis-related mortality.
View article: Non-invasive classification of non-small cell lung cancer: a comparison between random forest models utilising radiomic and semantic features
Non-invasive classification of non-small cell lung cancer: a comparison between random forest models utilising radiomic and semantic features Open
Objective: Non-invasive distinction between squamous cell carcinoma and adenocarcinoma subtypes of non-small-cell lung cancer (NSCLC) may be beneficial to patients unfit for invasive diagnostic procedures or when tissue is insufficient for…
View article: Adaptive statistical iterative reconstruction (ASIR) affects CT radiomics quantification in primary colorectal cancer
Adaptive statistical iterative reconstruction (ASIR) affects CT radiomics quantification in primary colorectal cancer Open
• Incremental levels of ASIR determine a significant change in most statistical (first-, second- and high-order) CT radiomics features measured in primary colorectal cancer, best described by a linear relationship. • First-order statistica…
View article: Reply: Relevance of Measurement Uncertainty for Quantitative Response Assessment of Breast Cancer Bone Metastases with <sup>18</sup>F-Fluoride
Reply: Relevance of Measurement Uncertainty for Quantitative Response Assessment of Breast Cancer Bone Metastases with <sup>18</sup>F-Fluoride Open
REPLY: We thank Laffon and Marthan for their interest in our study ([1][1]). They discuss the influence of measurement uncertainty on the ability to detect changes in measurements. We refer them to previous work by members of our group ([2…