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Hichem Tahraoui, Selma Toumi, Amel Hind Hassein-Bey, Abla Bousselma, Asma Nour El Houda Sid, Abd-Elmouneïm Belhadj, Zakaria Triki, Mohammed Kebir, Abdeltif Amrane, Jie Zhang, Amin Aymen Assadi, Derradji Chebli, Abdallah Bouguettoucha and Lotfi Mouni
Monitoring stations have been established to combat water pollution, improve the ecosystem, promote human health, and facilitate drinking water production. However, continuous and extensive monitoring of water is costly and time-consuming, resulting in l...
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Weiqing Zhuang and Yongbo Cao
In the previous research on traffic flow prediction models, most of the models mainly studied the time series of traffic flow, and the spatial correlation of traffic flow was not fully considered. To solve this problem, this paper proposes a method to pr...
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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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Muhammad Talha Siddique, Paraskevas Koukaras, Dimosthenis Ioannidis and Christos Tjortjis
The Smart Readiness Indicator (SRI) is a newly developed framework that measures a building?s technological readiness to improve its energy efficiency. The integration of data obtained from this framework with data derived from Building Information Model...
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Nureni Ayofe Azeez and Emad Fadhal
Background: Internet social media platforms have become quite popular, enabling a wide range of online users to stay in touch with their friends and relatives wherever they are at any time. This has led to a significant increase in virtual crime from the...
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