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Generative Adversarial Networks and Data Clustering for Likable Drone Design [PDF]
Novel applications for human-drone interaction demand new design approaches, such as social drones that need to be perceived as likable by users. However, given the complexity of the likability perception process, gathering such design information from ...
Lee J. Yamin, Jessica R. Cauchard
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Urban Road Surface Discrimination by Tire-Road Noise Analysis and Data Clustering [PDF]
The surface condition of roadways has direct consequences on a wide range of processes related to the transportation technology, quality of road facilities, road safety, and traffic noise emissions.
Carlos Ramos-Romero +3 more
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Data Clustering Using Moth-Flame Optimization Algorithm [PDF]
A k-means algorithm is a method for clustering that has already gained a wide range of acceptability. However, its performance extremely depends on the opening cluster centers.
Tribhuvan Singh +5 more
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Evaluating Clustering Algorithms: An Analysis using the EDAS Method [PDF]
Data clustering is frequently utilized in the early stages of analyzing big data. It enables the examination of massive datasets encompassing diverse types of data, with the aim of revealing undiscovered correlations, concealed patterns, and other ...
Siva Shankar S. +3 more
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Introduction. Requirements for the quality of information about the trajectory of moving objects provided by sensor networks are increasingly becoming more stringent.
Nguyen Phung Bao, Quang Hieu Dang
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Renewable energy sources (RES) are seen as a means of the fuel and energy complex carbon footprint reduction but the stochastic nature of generation complicates RES integration with electric power systems.
P. V. Matrenin +6 more
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Investigation the motion data clustering of lung tumor on its position estimation at external surrogates’ radiotherapy [PDF]
Among thorax tumors, lung tumors move mainly due to respiration. In order to enhance the precision of radiotherapy, one solution is estimating tumor motion from external motion of chest wall and abdomen regions. For this aim, consistent prediction models
Ahmad Esmaili Torshabi
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Lithofacies Identification from Wire-Line Logs Using an Unsupervised Data Clustering Algorithm
Stratigraphic identification from wire-line logs and core samples is a common method for lithology classification. This traditional approach is considered superior, despite its significant financial cost.
Md Monjur Ul Hasan +5 more
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Improved Deep Embedding Clustering with Ensemble Learning
Recently the rapid development of the deep learning technique has provided a powerful tool for the clustering research, and has given rise to quite a number of deep neural network-based clustering methods.
HUANG Yuxiang, HUANG Dong, WANG Changdong, LAI Jianhuang
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Hypergraph-Regularized Lp Smooth Nonnegative Matrix Factorization for Data Representation
Nonnegative matrix factorization (NMF) has been shown to be a strong data representation technique, with applications in text mining, pattern recognition, image processing, clustering and other fields.
Yunxia Xu +3 more
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