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Unravelling multi-agent ranked delegations
We introduce a voting model with multi-agent ranked delegations. This model generalises liquid democracy in two aspects: first, an agent’s delegation...
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Designing a Meta Learning Classifier for Sensor-Enabled Healthcare Applications
Being one of the fastest growing industries in recent times, healthcare has witnessed a complete transition in the last decade. Rapid technological...
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On Social Consensus Mechanisms for Federated Learning Aggregation
The possibility of training Machine Learning models in a decentralized way has always been a challenge when maintaining data privacy and accuracy....
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A weighted ensemble classifier based on WOA for classification of diabetes
Due to the threat and increasing trend to diabetes, different approaches to diagnose it have been proposed, so that classification is one of the main...
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A voting ensemble machine learning based credit card fraud detection using highly imbalance data
Long gone is the time when people preferred using only cash. In recent years, cashless transactions have gained much popularity, be it using UPI apps...
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Skin lesion detection using an ensemble of deep models: SLDED
Skin cancer is a major public health concern and the most common type of cancer among the other types. Reliable automated classification systems will...
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Social media discourse and voting decisions influence: sentiment analysis in tweets during an electoral period
In a time where social media is fundamental for any political campaign and to share a message with an electoral audience, this study searches for a...
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Classification of urban functional zones through deep learning
Nowadays, artificial neural networks (ANN) are models widely used in many areas; one of these is the classification of urban areas. This work aims to...
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BRL-ETDM: Bayesian reinforcement learning-based explainable threat detection model for industry 5.0 network
To enhance the universal adaptability of the Real-Time deployment of Industry 5.0, various machine learning-based cyber threat detection models are...
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Why polls fail to predict elections
In the past decade we have witnessed the failure of traditional polls in predicting presidential election outcomes across the world. To understand...
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Heterogeneous Ensemble for Classifying Electrical Load Reduction in South Africa
Electricity outages in South Africa have become a growing concern for businesses and individuals. Despite improvements in supply, planned outages are...
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Drawing the Same Bounding Box Twice? Co** Noisy Annotations in Object Detection with Repeated Labels
The reliability of supervised machine learning systems depends on the accuracy and availability of ground truth labels. However, the process of human...
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COBRA: Comparison-Optimal Betting for Risk-Limiting Audits
Risk-limiting audits (RLAs) can provide routine, affirmative evidence that reported election outcomes are correct by checking a random sample of cast...
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Classification Algorithm Using Branches Importance
Ensemble methods have attracted a wide attention, as they are learning algorithms that construct a set of classifiers and then classify new data...
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Fake news and its electoral consequences: a survey experiment on Mexico
This study examined the effect of fake news on electoral outcome. Using post-election surveys, previous studies found associations between exposure...
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On the use of the descriptive variable for enhancing the aggregation of crowdsourced labels
The use of crowdsourcing for annotating data has become a popular and cheap alternative to expert labelling. As a consequence, an aggregation task is...
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Quantitative and Qualitative Analysis of 18 Deep Convolutional Neural Network (CNN) Models with Transfer Learning to Diagnose COVID-19 on Chest X-Ray (CXR) Images
Coronavirus disease 2019 (COVID-19) is a disease caused by a novel strain of coronavirus, severe acute respiratory syndrome coronavirus 2...
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Machine Learning Based Incipient Fault Diagnosis of Induction Motor
An induction motor is the most important machine used in all industries, so the health of the machine is checked regularly by the machine learning...
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Beyond the echo chamber: modelling open-mindedness in citizens’ assemblies
A Citizens’ assembly (CA) is a democratic innovation tool where a randomly selected group of citizens deliberate a topic over multiple rounds to...
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The Unique Chain Rule and Its Applications
Most existing Byzantine fault-tolerant State Machine Replication (SMR) protocols rely explicitly on either equivocation detection or quorum...