Mobyen Uddin Ahmed
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View article: Attention-based fuzzy neural networks for self-supervised data annotation
Attention-based fuzzy neural networks for self-supervised data annotation Open
View article: Privacy-preserving ground-truth data for evaluating additive feature attribution in regression models with additive CBR and CQV
Privacy-preserving ground-truth data for evaluating additive feature attribution in regression models with additive CBR and CQV Open
View article: Interpretable Self-Supervised Learning for Fault Identification in Printed Circuit Board Assembly Testing
Interpretable Self-Supervised Learning for Fault Identification in Printed Circuit Board Assembly Testing Open
Fault identification in Printed Circuit Board Assembly (PCBA) testing is essential for assuring product quality; nevertheless, conventional methods still have difficulties due to the lack of labeled faulty data and the “black box” nature o…
View article: Role of Multi-modal Machine Learning, Explainable AI and Human-AI Teaming in Trusted Intelligent Systems for Remote Digital Towers
Role of Multi-modal Machine Learning, Explainable AI and Human-AI Teaming in Trusted Intelligent Systems for Remote Digital Towers Open
International audience
View article: Balancing Fairness: Unveiling the Potential of SMOTE-Driven Oversampling in AI Model Enhancement
Balancing Fairness: Unveiling the Potential of SMOTE-Driven Oversampling in AI Model Enhancement Open
View article: Combining Ontology and Large Language Models to Identify Recurring Machine Failures in Free-Text Fields
Combining Ontology and Large Language Models to Identify Recurring Machine Failures in Free-Text Fields Open
Companies must enhance total maintenance effectiveness to stay competitive, focusing on both digitalization and basic maintenance procedures. Digitalization offers technologies for data-driven decision-making, but many maintenance decision…
View article: Chip Analysis for Tool Wear Monitoring in Machining: A Deep Learning Approach
Chip Analysis for Tool Wear Monitoring in Machining: A Deep Learning Approach Open
Recent strides in integrating artificial intelligence (AI) with production systems align with the trend towards highly automated manufacturing, demanding smarter machinery. This dovetails with the overarching vision of Industry 4.0, moving…
View article: Examining Decision-Making in Air Traffic Control: Enhancing Transparency and Decision Support Through Machine Learning, Explanation, and Visualization: A Case Study
Examining Decision-Making in Air Traffic Control: Enhancing Transparency and Decision Support Through Machine Learning, Explanation, and Visualization: A Case Study Open
Artificial Intelligence (AI) has recently made significant advancements and is now pervasive across various
\napplication domains. This holds true for Air Transportation as well, where AI is increasingly involved in
\ndecision-making proce…
View article: iXGB: Improving the Interpretability of XGBoost Using Decision Rules and Counterfactuals
iXGB: Improving the Interpretability of XGBoost Using Decision Rules and Counterfactuals Open
Tree-ensemble models, such as Extreme Gradient Boosting (XGBoost), are renowned Machine Learning models which have higher prediction accuracy compared to traditional tree-based models. This higher accuracy, however, comes at the cost of re…
View article: Neurophysiological mental fatigue assessment for developing user-centered Artificial Intelligence as a solution for autonomous driving
Neurophysiological mental fatigue assessment for developing user-centered Artificial Intelligence as a solution for autonomous driving Open
The human factor plays a key role in the automotive field since most accidents are due to drivers' unsafe and risky behaviors. The industry is now pursuing two main solutions to deal with this concern: in the short term, there is the devel…
View article: Synthetic Datasets from the Article titled Privacy-preserving Ground-truth Data for Evaluating Additive Feature Attribution in Regression Models with Additive CBR and CQV
Synthetic Datasets from the Article titled Privacy-preserving Ground-truth Data for Evaluating Additive Feature Attribution in Regression Models with Additive CBR and CQV Open
Synthetic datasets were generated as benchmarks capturing the intrinsic characteristics of original data to investigate the performance of additive feature attribution methods for regression tasks. The synthetic datasets were generated bas…
View article: Synthetic Datasets from the Article titled Privacy-preserving Ground-truth Data for Evaluating Additive Feature Attribution in Regression Models with Additive CBR and CQV
Synthetic Datasets from the Article titled Privacy-preserving Ground-truth Data for Evaluating Additive Feature Attribution in Regression Models with Additive CBR and CQV Open
Synthetic datasets were generated as benchmarks capturing the intrinsic characteristics of original data to investigate the performance of additive feature attribution methods for regression tasks. The synthetic datasets were generated bas…
View article: Multi-scale Data Fusion and Machine Learning for Vehicle Manoeuvre Classification
Multi-scale Data Fusion and Machine Learning for Vehicle Manoeuvre Classification Open
Vehicle manoeuvre analysis is vital for road safetyas it helps understand driver behaviour, traffic flow, and roadconditions. However, classifying data from in-vehicleacquisition systems or simulators for manoeuvre recognition iscomplex, r…
View article: When a CBR in Hand is Better than Twins in the Bush
When a CBR in Hand is Better than Twins in the Bush Open
AI methods referred to as interpretable are often discredited as inaccurate by supporters of the existence of a trade-off between interpretability and accuracy. In many problem contexts however this trade-off does not hold. This paper disc…
View article: Supplementary files for the article "A Systematic Literature Review on Multimodal Machine Learning"
Supplementary files for the article "A Systematic Literature Review on Multimodal Machine Learning" Open
All included data was used for this review study. Data contains information from collected articles. Results of the analysis of each article are also available. All files are related to each other. A file named "All Articles Selected And R…
View article: Supplementary files for the article "A Systematic Literature Review on Multimodal Machine Learning"
Supplementary files for the article "A Systematic Literature Review on Multimodal Machine Learning" Open
All included data was used for this review study. Data contains information from collected articles. Results of the analysis of each article are also available. All files are related to each other. A file named "All Articles Selected And R…
View article: Interpretable Machine Learning for Modelling and Explaining Car Drivers' Behaviour: An Exploratory Analysis on Heterogeneous Data
Interpretable Machine Learning for Modelling and Explaining Car Drivers' Behaviour: An Exploratory Analysis on Heterogeneous Data Open
View article: A Systematic Literature Review on Multimodal Machine Learning: Applications, Challenges, Gaps and Future Directions
A Systematic Literature Review on Multimodal Machine Learning: Applications, Challenges, Gaps and Future Directions Open
Multimodal machine learning (MML) is a tempting multidisciplinary research area where heterogeneous data from multiple modalities and machine learning (ML) are combined to solve critical problems. Usually, research works use data from a si…
View article: Quantitative Performance Analysis from Discrete Perspective: A Case Study of Chip Detection in Turning Process
Quantitative Performance Analysis from Discrete Perspective: A Case Study of Chip Detection in Turning Process Open
View article: User validation on Flight Delay Prediction
User validation on Flight Delay Prediction Open
A Flight Delay Prediction tool has been developed using the Artificial intelligence method. EUROCONTROL provided the dataset as the External Advisory Board (EAB) and suggested addressing the issue of explanation for delay propagation. Thre…
View article: User validation on Flight Delay Prediction
User validation on Flight Delay Prediction Open
A Flight Delay Prediction tool has been developed using the Artificial intelligence method. EUROCONTROL provided the dataset as the External Advisory Board (EAB) and suggested addressing the issue of explanation for delay propagation. Thre…
View article: CODE: A Moving-Window-Based Framework for Detecting Concept Drift in Software Defect Prediction
CODE: A Moving-Window-Based Framework for Detecting Concept Drift in Software Defect Prediction Open
Concept drift (CD) refers to data distributions that may vary after a minimum stable period. CD negatively influences models’ performance of software defect prediction (SDP) trained on past datasets when applied to the new datasets. Based …
View article: Toward a more transparent and explainable conflict resolution algorithm for air traffic controllers
Toward a more transparent and explainable conflict resolution algorithm for air traffic controllers Open
Recently, Artificial intelligence (AI) algorithms have received increasable interest in various application domains including in Air Transportation Management (ATM). Different AI in particular Machine Learning (ML) algorithms are used to p…
View article: Toward a more transparent and explainable conflict resolution algorithm for air traffic controllers
Toward a more transparent and explainable conflict resolution algorithm for air traffic controllers Open
Recently, Artificial intelligence (AI) algorithms have shown increasable interest in various application domains including in Air Transportation Management (ATM). Different AI in particular Machine Learning (ML) algorithms are used to prov…
View article: When a CBR in Hand is Better than Twins in the Bush
When a CBR in Hand is Better than Twins in the Bush Open
AI methods referred to as interpretable are often discredited as inaccurate by supporters of the existence of a trade-off between interpretability and accuracy. In many problem contexts however this trade-off does not hold. This paper disc…
View article: Machine-Learning-Based Digital Twin in Manufacturing: A Bibliometric Analysis and Evolutionary Overview
Machine-Learning-Based Digital Twin in Manufacturing: A Bibliometric Analysis and Evolutionary Overview Open
The Digital Twin (DT) concept in the manufacturing industry has received considerable attention from researchers because of its versatile application potential. Machine Learning (ML) adds a new dimension to DT by enhancing its functionalit…
View article: Machine Learning Based Digital Twin in Manufacturing: A Bibliometric Analysis and Evolutionary Overview
Machine Learning Based Digital Twin in Manufacturing: A Bibliometric Analysis and Evolutionary Overview Open
The data files include bibliometric file. data extracted from bibliometric data.
View article: Machine Learning Based Digital Twin in Manufacturing: A Bibliometric Analysis and Evolutionary Overview
Machine Learning Based Digital Twin in Manufacturing: A Bibliometric Analysis and Evolutionary Overview Open
The data files include bibliometric file. data extracted from bibliometric data.
View article: A Systematic Review of Explainable Artificial Intelligence in Terms of Different Application Domains and Tasks
A Systematic Review of Explainable Artificial Intelligence in Terms of Different Application Domains and Tasks Open
Artificial intelligence (AI) and machine learning (ML) have recently been radically improved and are now being employed in almost every application domain to develop automated or semi-automated systems. To facilitate greater human acceptab…
View article: A Systematic Review of Explainable Artificial Intelligence in Terms of Different Application Domains and Tasks
A Systematic Review of Explainable Artificial Intelligence in Terms of Different Application Domains and Tasks Open
Artificial intelligence (AI) and machine learning (ML) have recently been radically improved and are now being employed in almost every application domain to develop automated or semi-automated systems. To facilitate greater human acceptab…