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Yaxin Dong, Hongxiang Ren, Yuzhu Zhu, Rui Tao, Yating Duan and Nianjun Shao
To effectively address the increase in maritime accidents and the challenges posed by the trend toward larger ships for maritime safety, it is crucial to rationally allocate the limited maritime search and rescue (MSAR) resources and enhance accident res...
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Danilo Pau, Andrea Pisani and Antonio Candelieri
In the context of TinyML, many research efforts have been devoted to designing forward topologies to support On-Device Learning. Reaching this target would bring numerous advantages, including reductions in latency and computational complexity, stronger ...
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Sanaz Gheibi, Tania Banerjee, Sanjay Ranka and Sartaj Sahni
This paper proposes a new time-respecting graph (TRG) representation for contact sequence temporal graphs. Our representation is more memory-efficient than previously proposed representations and has run-time advantages over the ordered sequence of edges...
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Audrone Janaviciute, Agnius Liutkevicius, Gedas Dabu?inskas and Nerijus Morkevicius
Online shopping has become a common and popular form of shopping, so online attackers try to extract money from customers by creating online shops whose purpose is to compel the buyer to disclose credit card details or to pay money for goods that are nev...
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Alireza Rezvanian, S. Mehdi Vahidipour and Ali Mohammad Saghiri
Artificial immune systems (AIS), as nature-inspired algorithms, have been developed to solve various types of problems, ranging from machine learning to optimization. This paper proposes a novel hybrid model of AIS that incorporates cellular automata (CA...
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Haibo Chu, Zhuoqi Wang and Chong Nie
Accurate and reliable monthly streamflow prediction plays a crucial role in the scientific allocation and efficient utilization of water resources. In this paper, we proposed a prediction framework that integrates the input variable selection method and ...
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Antonio Lopez-Martinez-Carrasco, Jose M. Juarez, Manuel Campos and Bernardo Canovas-Segura
Subgroup Discovery (SD) is a supervised data mining technique for identifying a set of relations (subgroups) among attributes from a dataset with respect to a target attribute. Two key components of this technique are (i) the metric used to quantify a su...
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Saif Ur Rehman, Muhammad Altaf Khan, Habib Un Nabi, Shaukat Ali, Noha Alnazzawi and Shafiullah Khan
The regular frequent pattern mining (RFPM) approaches are aimed to discover the itemsets with significant frequency and regular occurrence behavior in a dataset. However, these approaches mainly suffer from the following two issues: (1) setting the frequ...
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Martin Paralic, Kamil Zelenak, Patrik Kamencay and Robert Hudec
The paper introduces an approach for detecting brain aneurysms, a critical medical condition, by utilizing a combination of 3D convolutional neural networks (3DCNNs) and Convolutional Long Short-Term Memory (ConvLSTM). Brain aneurysms pose a significant ...
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Weijian Huang, Qi Song and Yuan Huang
Short-term power load forecasting is of great significance for the reliable and safe operation of power systems. In order to improve the accuracy of short-term load forecasting, for the problems of random fluctuation in load and the complexity of load-in...
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