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Mohamed Shenify, Fokrul Alom Mazarbhuiya and A. S. Wungreiphi
There are many applications of anomaly detection in the Internet of Things domain. IoT technology consists of a large number of interconnecting digital devices not only generating huge data continuously but also making real-time computations. Since IoT d...
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Lucio Pinello, Omar Hassan, Marco Giglio and Claudio Sbarufatti
An increase in aircraft availability and readiness is one of the most desired characteristics of aircraft fleets. Unforeseen failures cause additional expenses and are particularly critical when thinking about combat jets and Unmanned Aerial Vehicles (UA...
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Peng Chen and Huibing Wang
Semi-supervised metric learning intends to learn a distance function from the limited labeled data as well as a large amount of unlabeled data to better gauge the similarities of any two instances than using a general distance function. However, most exi...
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Panos Nikitas and Efthymia Nikita
This paper assesses algorithms proposed for constructing confidence ellipses in multidimensional scaling (MDS) solutions and proposes a new approach to interpreting these confidence ellipses via hierarchical cluster analysis (HCA). It is shown that the m...
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Cristian Minoccheri, Olivia Alge, Jonathan Gryak, Kayvan Najarian and Harm Derksen
Over the past decades, there has been an increase of attention to adapting machine learning methods to fully exploit the higher order structure of tensorial data. One problem of great interest is tensor classification, and in particular the extension of ...
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Lijun Liu, Xin Zhang, Ying Lei and Zhupeng Zheng
Due to the unpredictability of seismic excitation, the data-driven damage identification method, which only depends on the monitoring response data, has a good development prospect in structural health monitoring. In recent years, damage identification m...
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Ming Li, Jun Tian, Yuliang Wang, Haiyang Zhang, Dongping Yang and Meng Lei
Realizing the rapid measurement of coal moisture content (MC) is of great significance. However, existing measurement methods are time-consuming and damage the original properties of the samples. To address these concerns, a coal MC intelligent measureme...
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Weipeng Zhang, Bo Zhao, Liming Zhou, Jizhong Wang, Conghui Qiu, Kang Niu and Fengzhu Wang
The combine harvester is the main machine for fieldwork during the harvest season. When the harvester fails and cannot continue to work, this indirectly affects the harvest time and the yield in the field. The emergency maintenance service of agricultura...
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Jiahao Guo, Xiaohuo Yu and Lu Wang
Industrial quality control is an important task. Most of the existing vision-based unsupervised industrial anomaly detection and segmentation methods require that the training set only consists of normal samples, which is difficult to ensure in practice....
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Chan-Uk Yeom and Keun-Chang Kwak
In this paper, we propose context-based GK clustering and design a CGK-based granular model and a hierarchical CGK-based granular model. Existing fuzzy clustering generates clusters using Euclidean distances. However, there is a problem in that performan...
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