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Lowri Williams, Eirini Anthi and Pete Burnap
The performance of emotive text classification using affective hierarchical schemes (e.g., WordNet-Affect) is often evaluated using the same traditional measures used to evaluate the performance of when a finite set of isolated classes are used. However,...
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Jean-Sébastien Dessureault, Félix Clément, Seydou Ba, François Meunier and Daniel Massicotte
The field of interior home design has witnessed a growing utilization of machine learning. However, the subjective nature of aesthetics poses a significant challenge due to its variability among individuals and cultures. This paper proposes an applied ma...
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Aquib Raza, Thien-Luan Phan, Hung-Chung Li, Nguyen Van Hieu, Tran Trung Nghia and Congo Tak Shing Ching
Knee osteoarthritis (KOA) is a leading cause of disability, particularly affecting older adults due to the deterioration of articular cartilage within the knee joint. This condition is characterized by pain, stiffness, and impaired movement, posing a sig...
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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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Yahya Tashtoush, Noor Abu-El-Rub, Omar Darwish, Shorouq Al-Eidi, Dirar Darweesh and Ola Karajeh
Code readability and software complexity are considered essential components of software quality. They significantly impact software metrics, such as reusability and maintenance. The maintainability process consumes a high percentage of the software life...
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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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Chintan M. Bhatt, Parth Patel, Tarang Ghetia and Pier Luigi Mazzeo
The diagnosis and prognosis of cardiovascular disease are crucial medical tasks to ensure correct classification, which helps cardiologists provide proper treatment to the patient. Machine learning applications in the medical niche have increased as they...
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Amrita Dutta, Scott P. Breloff, Dilruba Mahmud, Fei Dai, Erik W. Sinsel, Christopher M. Warren and John Z. Wu
Awkward kneeling in sloped shingle installation operations exposes roofers to knee musculoskeletal disorder (MSD) risks. To address the varying levels of risk associated with different phases of shingle installation, this research investigated utilizing ...
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Sibel Kapan and Efnan Sora Gunal
In phishing attack detection, machine learning-based approaches are more effective than simple blacklisting strategies, as they can adapt to new types of attacks and do not require manual updates. However, for these approaches, the choice of features and...
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Francisco Javier López-Escudero, Joaquín Romero, Rocío Bocanegra-Caro and Antonio Santos-Rufo
Developing models to understand disease dynamics and predict the risk of disease outbreaks to facilitate decision making is an integral component of plant disease management. However, these models have not yet been developed for one of the most damaging ...
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