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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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Mishall Al-Zubaidie and Ghanima Sabr Shyaa
Technology advancements have driven a boost in electronic commerce use in the present day due to an increase in demand processes, regardless of whether goods, products, services, or payments are being bought or sold. Various goods are purchased and sold ...
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Ou Ruan, Changwang Yan, Jing Zhou and Chaohao Ai
Multiparty Private Set Intersection (MPSI) is dedicated to finding the intersection of datasets of multiple participants without disclosing any other information. Although many MPSI protocols have been presented, there are still some important practical ...
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Wenwen Wang, Mingyu Wu, Zhihua Chen and Xiaoli Liu
This study applies deep-reinforcement-learning algorithms to integrated guidance and control for three-dimensional, high-maneuverability missile-target interception. Dynamic environment, reward functions concerning multi-factors, agents based on the deep...
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Suhana Omar, Rosnani Abd Ghani, Noriza Khalid, Márton Jolánkai, Ákos Tarnawa, Attila Percze, Péter Pál Mikó and Zoltán Kende
After wheat and rice, maize is one of the most significant cereal crops worldwide. However, high-quality seed materials are prerequisites for stable yields, and low-quality maize seeds significantly contribute to low yields and deteriorate over time. The...
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Hao Sun, Yuejin Du and Qi Li
Amid the incessant evolution of the Internet, an array of cybersecurity threats has surged at an unprecedented rate. A notable antagonist within this plethora of attacks is the SQL injection assault, a prevalent form of Internet attack that poses a signi...
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Nino Cauli and Diego Reforgiato Recupero
In most Computer Vision applications, Deep Learning models achieve state-of-the-art performances. One drawback of Deep Learning is the large amount of data needed to train the models. Unfortunately, in many applications, data are difficult or expensive t...
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Juliana Castaneda, Mattia Neroni, Majsa Ammouriova, Javier Panadero and Angel A. Juan
Many real-life combinatorial optimization problems are subject to a high degree of dynamism, while, simultaneously, a certain level of synchronization among agents and events is required. Thus, for instance, in ride-sharing operations, the arrival of veh...
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Franz Aurenhammer, Christoph Ladurner and Michael Steinkogler
We show that the so-called motorcycle graph of a planar polygon can be constructed by a randomized incremental algorithm that is simple and experimentally fast. Various test data are given, and a clustering method for speeding up the construction is prop...
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Christoph Laroque, Madlene Leißau, Pedro Copado, Christin Schumacher, Javier Panadero and Angel A. Juan
Based on a real-world application in the semiconductor industry, this article models and discusses a hybrid flow shop problem with time dependencies and priority constraints. The analyzed problem considers a production where a large number of heterogeneo...
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