1.222   Artículos

 
en línea
Luis M. de Campos, Juan M. Fernández-Luna, Juan F. Huete, Francisco J. Ribadas-Pena and Néstor Bolaños    
In the context of academic expert finding, this paper investigates and compares the performance of information retrieval (IR) and machine learning (ML) methods, including deep learning, to approach the problem of identifying academic figures who are expe... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Mojtaba Nayyeri, Modjtaba Rouhani, Hadi Sadoghi Yazdi, Marko M. Mäkelä, Alaleh Maskooki and Yury Nikulin    
One of the main disadvantages of the traditional mean square error (MSE)-based constructive networks is their poor performance in the presence of non-Gaussian noises. In this paper, we propose a new incremental constructive network based on the correntro... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Yilei Wang, Yuelin Hu, Wenliang Xu and Futai Zou    
Dark web vendor identification can be seen as an authorship aliasing problem, aiming to determine whether different accounts on different markets belong to the same real-world vendor, in order to locate cybercriminals involved in dark web market transact... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Jinghua Groppe, Sven Groppe, Daniel Senf and Ralf Möller    
Given a set of software programs, each being labeled either as vulnerable or benign, deep learning technology can be used to automatically build a software vulnerability detector. A challenge in this context is that there are countless equivalent ways to... ver más
Revista: Information    Formato: Electrónico

 
en línea
Junlin Lou, Burak Yuksek, Gokhan Inalhan and Antonios Tsourdos    
In this study, we consider the problem of motion planning for urban air mobility applications to generate a minimal snap trajectory and trajectory that cost minimal time to reach a goal location in the presence of dynamic geo-fences and uncertainties in ... ver más
Revista: Aerospace    Formato: Electrónico

 
en línea
Jin Wang, Peng Zhao, Zhe Zhang, Ting Yue, Hailiang Liu and Lixin Wang    
The upset state is an unexpected flight state, which is characterized by an unintentional deviation from normal operating parameters. It is difficult for the pilot to recover the aircraft from the upset state accurately and quickly. In this paper, an ups... ver más
Revista: Aerospace    Formato: Electrónico

 
en línea
Tamás Kegyes, Alex Kummer, Zoltán Süle and János Abonyi    
We analyzed a special class of graph traversal problems, where the distances are stochastic, and the agent is restricted to take a limited range in one go. We showed that both constrained shortest Hamiltonian pathfinding problems and disassembly line bal... ver más
Revista: Information    Formato: Electrónico

 
en línea
Jiacun Wang, Guipeng Xi, Xiwang Guo, Shujin Qin and Henry Han    
The scheduling of disassembly lines is of great importance to achieve optimized productivity. In this paper, we address the Hybrid Disassembly Line Balancing Problem that combines linear disassembly lines and U-shaped disassembly lines, considering multi... ver más
Revista: Information    Formato: Electrónico

 
en línea
Mingxin Zou, Yanqing Zhou, Xinhua Jiang, Julin Gao, Xiaofang Yu and Xuelei Ma    
Field manual labor behavior recognition is an important task that applies deep learning algorithms to industrial equipment for capturing and analyzing people?s behavior during field labor. In this study, we propose a field manual labor behavior recogniti... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Alvin Lee, Suet-Peng Yong, Witold Pedrycz and Junzo Watada    
Drones play a pivotal role in various industries of Industry 4.0. For achieving the application of drones in a dynamic environment, finding a clear path for their autonomous flight requires more research. This paper addresses the problem of finding a nav... ver más
Revista: Algorithms    Formato: Electrónico

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