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Yongzhao Yan, Zhenqian Sun, Yueqi Hou, Boyang Zhang, Ziwei Yuan, Guoxin Zhang, Bo Wang and Xiaoping Ma
Unmanned aerial vehicle (UAV) swarms offer unique advantages for area search and environmental monitoring applications. For practical deployments, determining the optimal number of UAVs required for a given task and defining key performance metrics for t...
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Nguyen Duy Tan, Duy-Ngoc Nguyen, Hong-Nhat Hoang and Thi-Thu-Huong Le
The Internet of Things (IoT) integrates different advanced technologies in which a wireless sensor network (WSN) with many smart micro-sensor nodes is an important portion of building various IoT applications such as smart agriculture systems, smart heal...
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Shuzhen Yang, Bocai Jia, Tao Yu and Jin Yuan
In view of the difficulties of fruit cluster identification, the specific harvesting sequence constraints of aggregated fruits, and the balanced harvesting task assignment for the multiple arms with a series-increasing symmetric shared (SISS) region, thi...
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Xingxing Xiao and Haining Huang
Because of the complicated underwater environment, the efficiency of data transmission from underwater sensor nodes to a sink node (SN) is faced with great challenges. Aiming at the problem of energy consumption in underwater wireless sensor networks (UW...
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Lin Zhang, Yian Zhu and Xianchen Shi
Unmanned aerial vehicles (UAVs) received an unprecedented surge of people?s interest worldwide in recent years. This paper investigates the specific problem of cooperative mission planning for multiple UAVs on the battlefield from a hierarchical decision...
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Nancy Awad, Jean-Francois Couchot, Bechara Al Bouna and Laurent Philippe
Data publishing is a challenging task for privacy preservation constraints. To ensure privacy, many anonymization techniques have been proposed. They differ in terms of the mathematical properties they verify and in terms of the functional objectives exp...
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Laith Abualigah, Amir H. Gandomi, Mohamed Abd Elaziz, Abdelazim G. Hussien, Ahmad M. Khasawneh, Mohammad Alshinwan and Essam H. Houssein
Text clustering is one of the efficient unsupervised learning techniques used to partition a huge number of text documents into a subset of clusters. In which, each cluster contains similar documents and the clusters contain dissimilar text documents. Na...
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