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Binita Kusum Dhamala, Babu R. Dawadi, Pietro Manzoni and Baikuntha Kumar Acharya
Graph representation is recognized as an efficient method for modeling networks, precisely illustrating intricate, dynamic interactions within various entities of networks by representing entities as nodes and their relationships as edges. Leveraging the...
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Nirmal Acharya, Padmaja Kar, Mustafa Ally and Jeffrey Soar
Significant clinical overlap exists between mental health and substance use disorders, especially among women. The purpose of this research is to leverage an AutoML (Automated Machine Learning) interface to predict and distinguish co-occurring mental hea...
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Majdi Sukkar, Madhu Shukla, Dinesh Kumar, Vassilis C. Gerogiannis, Andreas Kanavos and Biswaranjan Acharya
Effective collision risk reduction in autonomous vehicles relies on robust and straightforward pedestrian tracking. Challenges posed by occlusion and switching scenarios significantly impede the reliability of pedestrian tracking. In the current study, w...
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Vivek Kumar Prasad, Debabrata Dansana, Madhuri D. Bhavsar, Biswaranjan Acharya, Vassilis C. Gerogiannis and Andreas Kanavos
With the proliferation of IoT devices, there has been exponential growth in data generation, placing substantial demands on both cloud computing (CC) and internet infrastructure. CC, renowned for its scalability and virtual resource provisioning, is of p...
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Manav Garg, Pranshav Gajjar, Pooja Shah, Madhu Shukla, Biswaranjan Acharya, Vassilis C. Gerogiannis and Andreas Kanavos
The musical key serves as a crucial element in a piece, offering vital insights into the tonal center, harmonic structure, and chord progressions while enabling tasks such as transposition and arrangement. Moreover, accurate key estimation finds practica...
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Bijay Regmi, Samir Kunwar, Tri Dev Acharya and Purushottam Gyawali
Malnutrition, hunger, and rural poverty in Nepal are prevalent issues that have been exacerbated by the negative impacts of climate change on crop production. To create a more sustainable and resilient food system, it is crucial to explore alternative op...
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Minmeng Tang, Tri Dev Acharya and Deb A. Niemeier
Black carbon (BC) is a significant source of air pollution since it impacts public health and climate change. Understanding its distribution in the complex urban environment is challenging. We integrated a land use model with four machine learning models...
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Gaurav Parajuli, Shankar Neupane, Sandeep Kunwar, Ramesh Adhikari and Tri Dev Acharya
Flood is one of the most frequently occurring and devastating disasters in Nepal. Several locations in Nepal are at high risk of flood, which requires proper guidance on early warning and safe evacuation of people to emergency locations through optimal r...
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Jayashree Piri, Puspanjali Mohapatra, Raghunath Dey, Biswaranjan Acharya, Vassilis C. Gerogiannis and Andreas Kanavos
The efficiency and the effectiveness of a machine learning (ML) model are greatly influenced by feature selection (FS), a crucial preprocessing step in machine learning that seeks out the ideal set of characteristics with the maximum accuracy possible. D...
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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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