Empowering Predictive Maintenance: A Hybrid Method to Diagnose Abnormal Situations

Using K-Nearest Neighbor Classification to Diagnose Abnormal Lung Sounds

A reported 30% of people worldwide have abnormal lung sounds, including crackles, rhonchi, and wheezes. To date, the traditional stethoscope remains the most popular tool used by physicians to diagnose such abnormal lung sounds, however, many problems arise with the use of a stethoscope, including the effects of environmental noise, the inability to record and store lung sounds for follow-up or...

A hybrid KNN-MLP algorithm to diagnose bipolar disorder

In this paper an attempt has been made to the other corner of the power of neural networks. According to the neural network in the diagnosis of diseases, we use neural network models for diagnosing bipolar disorder; bipolar disorder is the common disorder of depression mood. We have used two neural network models: MLP & KNN. With different percentages of the implementation of neural network mod...

Predictive Maintenance

Hybrid Wikis: Empowering Users to Collaboratively Structure Information

Wikis are increasingly used for collaborative enterprise information management since they are flexibly applicable and encourage the contribution of knowledge. The fact that ordinary wiki pages contain pure text only limits how the information can be processed or made accessible to users. Semantic wikis promise to solve this problem by capturing knowledge in structured form and offering advance...

Predictive maintenance using FMECA method and NHPP models

Most of predictive maintenance technologies are inaccessible to small scale and medium scale industries due to their demanding cost. This paper proposes a predictive maintenance policy using failure mode effect and criticality analysis (FMECA) and non-homogeneous Poisson process (NHPP) models which require minimal use of advanced monitoring technologies and sophisticated data acquisition system...