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Saeed Samadianfard, Salar Jarhan, Ely Salwana, Amir Mosavi, Shahaboddin Shamshirband and Shatirah Akib
Advancement in river flow prediction systems can greatly empower the operational river management to make better decisions, practices, and policies. Machine learning methods recently have shown promising results in building accurate models for river flow...
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Gilbert Hinge, Mohamed A. Hamouda and Mohamed M. Mohamed
In recent years, there has been a growing interest in flood susceptibility modeling. In this study, we conducted a bibliometric analysis followed by a meta-data analysis to capture the nature and evolution of literature, intellectual structure networks, ...
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Anik Baul, Gobinda Chandra Sarker, Prokash Sikder, Utpal Mozumder and Ahmed Abdelgawad
Short-term load forecasting (STLF) plays a crucial role in the planning, management, and stability of a country?s power system operation. In this study, we have developed a novel approach that can simultaneously predict the load demand of different regio...
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Lei Li, Xiaobao Zeng, Xinpeng Pan, Ling Peng, Yuyang Tan and Jianxin Liu
Microseismic monitoring plays an essential role for reservoir characterization and earthquake disaster monitoring and early warning. The accuracy of the subsurface velocity model directly affects the precision of event localization and subsequent process...
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Heeseong Cho and Taeseok Kim
In hybrid SSDs (solid-state drives) consisting of SLC (single-level cell) and QLC (quad-level cell), efficiently using the limited SLC cache space is crucial. In this paper, we present a practical data placement scheme, which determines the placement loc...
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Aravind Kolli, Qi Wei and Stephen A. Ramsey
In this work, we explored computational methods for analyzing a color digital image of a wound and predicting (from the analyzed image) the number of days it will take for the wound to fully heal. We used a hybrid computational approach combining deep ne...
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Waseem Abbas, Zuping Zhang, Muhammad Asim, Junhong Chen and Sadique Ahmad
In the ever-expanding online fashion market, businesses in the clothing sales sector are presented with substantial growth opportunities. To utilize this potential, it is crucial to implement effective methods for accurately identifying clothing items. T...
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Ive Botunac, Jurica Bosna and Maja Matetic
Investment decision-makers increasingly rely on modern digital technologies to enhance their strategies in today?s rapidly changing and complex market environment. This paper examines the impact of incorporating Long Short-term Memory (LSTM) models into ...
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Peter K. K. Loh, Aloysius Z. Y. Lee and Vivek Balachandran
The rise in generative Artificial Intelligence (AI) has led to the development of more sophisticated phishing email attacks, as well as an increase in research on using AI to aid the detection of these advanced attacks. Successful phishing email attacks ...
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MohammadHossein Reshadi, Wen Li, Wenjie Xu, Precious Omashor, Albert Dinh, Scott Dick, Yuntong She and Michael Lipsett
Anomaly detection in data streams (and particularly time series) is today a vitally important task. Machine learning algorithms are a common design for achieving this goal. In particular, deep learning has, in the last decade, proven to be substantially ...
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