Search
Now showing items 1-10 of 113
Automatic sleep staging in obstructive sleep apnea patients using photoplethysmography, heart rate variability signal and machine learning techniques
(Springer, 2018)
It is extremely significant to identify sleep stages accurately in the diagnosis of obstructive sleep apnea. In the study, it was aimed at determining sleep and wakefulness using a practical and applicable method. For this ...
A Novel data preprocessing method for the modeling and prediction of freeze-drying behavior of apples: multiple output-dependent data scaling (MODDS)
(Taylor & Francis Inc, 2012)
In the present study, the freeze drying behavior of apples have been modeled and predicted. Because freeze-drying is a very expensive and complex process, modeling of the freeze-drying process is a challenging task. In ...
Improved binary dragonfly optimization algorithm and wavelet packet based non-linear features for infant cry classification
(Elsevier Ireland Ltd, 2018)
Background and objective: Infant cry signal carries several levels of information about the reason for crying (hunger, pain, sleepiness and discomfort) or the pathological status (asphyxia, deaf, jaundice, premature condition ...
Special issue: Soft computing in software engineering preface
(Elsevier Science Bv, 2016)
Assoftware-intensive systems become more and more complex,more intelligent approaches are needed to solve several challeng-ing problems in this domain. Soft computing has many applicationsinthedisciplineofSoftwareEnginee ...
Repetitive neural network (RNN) based blood pressure estimation using PPG and ECG signals
(Ieee, 2018)
In this study, a new hybrid prediction model was proposed by combining ECG (Electrocardiography) and PPG (Photoplethysmographic) signals with a repetitive neural network (RNN) structure to estimate blood pressure continuously. ...
TSCBAS: A novel correlation based attribute selection method and application on telecommunications churn analysis
(Ieee, 2018)
Attribute selection has a significant effect on the performance of the machine learning studies by selecting the attributes having significant effect on result, reducing the number of attributes, and reducing the calculation ...
A hybrid expert system approach for telemonitoring of vocal fold pathology
(Elsevier Science Bv, 2013)
Acoustical parameters extracted from the recorded voice samples are actively pursued for accurate detection of vocal fold pathology. Most of the system for detection of vocal fold pathology uses high quality voice samples. ...
Data weighting method on the basis of binary encoded output to solve multi-class pattern classification problems
(Pergamon-Elsevier Science Ltd, 2013)
Data weighting is of paramount importance with respect to classification performance in pattern recognition applications. In this paper, the output labels of datasets have been encoded using binary codes (numbers) and by ...
A novel feature ranking algorithm for biometric recognition with PPG signals
(Pergamon-Elsevier Science Ltd, 2014)
This study is intended for describing the application of the Photoplethysmography (PPG) signal and the time domain features acquired from its first and second derivatives for biometric identification. For this purpose, a ...
A new hybrid intelligent system for accurate detection of Parkinson's disease
(Elsevier Ireland Ltd, 2014)
Elderly people are commonly affected by Parkinson's disease (PD) which is one of the most common neurodegenerative disorders due to the loss of dopamine-producing brain cells. People with PD's (PWP) may have difficulty in ...
