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Rolling element bearings play an important role in ensuring the availability of industrial machines. Unexpected bearing failures in such machines during field operation can lead to machine breakdown, which may have some pretty severe implications. However, the insufficiency of labeled samples is major problem for handling fault diagnosis problem. To address such concern, we propose a semi-supervised...
Wireless sensor network (WSN) has become widely used in different applications. Fault detection of sensors is importance for maintaining a reliable WSN operation. And identification of faulty nodes in a WSN can be transformed into a pattern classification problem. In this paper, we introduce an effective label propagation procedure using semi-supervised local kernel density estimation. The proposed...
Dementia is one of the most common neurological disorders among the elderly. Identifying those who are of high risk suffering dementia is important for early diagnosis in order to slow down the disease progression and help preserve some cognitive functions of the brain. To achieve accurate classification, significant amount of subject feature information are involved. Hence identification of demented...
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