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The ethics of personalised digital duplicates: a minimally viable permissibility principle
With recent technological advances, it is possible to create personalised digital duplicates. These are partial, at least semi-autonomous,...
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A hyperparameter study for quantum kernel methods
Quantum kernel methods are a promising method in quantum machine learning thanks to the guarantees connected to them. Their accessibility for...
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Toward fair graph neural networks via real counterfactual samples
Graph neural networks (GNNs) have become pivotal in various critical decision-making scenarios due to their exceptional performance. However,...
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3D-Scene-Former: 3D scene generation from a single RGB image using Transformers
3D scene generation requires complex hardware setups, such as multiple cameras and depth sensors. To address this challenge, there is a need for...
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Dual-view graph convolutional network for multi-label text classification
Multi-label text classification refers to assigning multiple relevant category labels to each text, which has been widely applied in the real world....
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Aspect-based drug review classification through a hybrid model with ant colony optimization using deep learning
The task of aspect-level sentiment analysis is intricately designed to determine the sentiment polarity directed towards a specific target within a...
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Reading Between the Lines: Machine Learning Ensemble and Deep Learning for Implied Threat Detection in Textual Data
With the increase in the generation and spread of textual content on social media, natural language processing (NLP) has become an important area of...
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CommentClass: A Robust Ensemble Machine Learning Model for Comment Classification
Enormous amounts of data are generated in the form of feedback or comments from online platforms such as social media, e-commerce, education, and...
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Scientific Inference with Interpretable Machine Learning: Analyzing Models to Learn About Real-World Phenomena
To learn about real world phenomena, scientists have traditionally used models with clearly interpretable elements. However, modern machine learning...
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A Multi-strategy Slime Mould Algorithm for Solving Global Optimization and Engineering Optimization Problems
Aiming at the problems of slow convergence, low accuracy, and easy to fall into local optimum of the slime mould algorithm (SMA), we propose an...
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Cooperative coati optimization algorithm with transfer functions for feature selection and knapsack problems
Coatis optimization algorithm (COA) has recently emerged as an innovative meta-heuristic algorithm (MA) for global optimization, garnering...
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Cognitive differences in product shape evaluation between real settings and virtual reality: case study of two-wheel electric vehicles
Product shape evaluation is an important part of new product development. In the shape design stage, design schemes are often presented through...
