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James Oduor Oyoo, Jael Sanyanda Wekesa and Kennedy Odhiambo Ogada
Road traffic collisions are among the world?s critical issues, causing many casualties, deaths, and economic losses, with a disproportionate burden falling on developing countries. Existing research has been conducted to analyze this situation using diff...
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AlsharifHasan Mohamad Aburbeian and Manuel Fernández-Veiga
Securing online financial transactions has become a critical concern in an era where financial services are becoming more and more digital. The transition to digital platforms for conducting daily transactions exposed customers to possible risks from cyb...
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Ibrahim Ba?abbad and Omar Batarfi
Several malware variants have attacked systems and data over time. Ransomware is among the most harmful malware since it causes huge losses. In order to get a ransom, ransomware is software that locks the victim?s machine or encrypts his personal informa...
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Annwesha Banerjee Majumder, Somsubhra Gupta, Dharmpal Singh, Biswaranjan Acharya, Vassilis C. Gerogiannis, Andreas Kanavos and Panagiotis Pintelas
Heart disease is a leading global cause of mortality, demanding early detection for effective and timely medical intervention. In this study, we propose a machine learning-based model for early heart disease prediction. This model is trained on a dataset...
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Jacques Demongeot, Joël Gardes, Christophe Maldivi, Denis Boisset, Kenza Boufama and Imène Touzouti
Background: In present genomes, current relics of a circular RNA appear which could have played a central role as a primitive catalyst of the peptide genesis. Methods: Using a proximity measure to this circular RNA and the distance, a new unsupervised cl...
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Andrei Konstantinov, Lev Utkin and Vladimir Muliukha
A new random forest-based model for solving the Multiple Instance Learning problem under small tabular data, called the Soft Tree Ensemble Multiple Instance Learning, is proposed. A new type of soft decision trees is considered, which is similar to the w...
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Marian Bucos and Bogdan Dragulescu
Misinformation poses a significant challenge in the digital age, requiring robust methods to detect fake news. This study investigates the effectiveness of using Back Translation (BT) augmentation, specifically transformer-based models, to improve fake n...
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Artyom V. Gorchakov, Liliya A. Demidova and Peter N. Sovietov
In this paper we consider the research and development of classifiers that are trained to predict the task solved by source code. Possible applications of such task detection algorithms include method name prediction, hardware?software partitioning, prog...
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Yisha Wang, Gang Yang and Hao Lu
Rapid and accurate tree-crown detection is significant to forestry management and precision forestry. In the past few decades, the development and maturity of remote sensing technology has created more convenience for tree-crown detection and planting ma...
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João A. Bastos
Credit scoring models help lenders decide whether to grant or reject credit to applicants. This paper proposes a credit scoring model based on boosted decision trees, a powerful learning technique that aggregates several decision trees to form a classifi...
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