AIMC Topic: Principal Component Analysis

Clear Filters Showing 691 to 700 of 712 articles

Qualitative analysis of biological tuberculosis samples by an electronic nose-based artificial neural network.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease
OBJECTIVE: To apply an e-nose system for monitoring headspace volatiles in biological samples from Egyptian patients with active pulmonary tuberculosis (TB) and healthy controls (HCs) and compare them with standard sputum analysis.

Epileptic seizure detection in EEG signal with GModPCA and support vector machine.

Bio-medical materials and engineering
BACKGROUND AND OBJECTIVE: Epilepsy is one of the most common neurological disorders caused by recurrent seizures. Electroencephalograms (EEGs) record neural activity and can detect epilepsy. Visual inspection of an EEG signal for epileptic seizure de...

Identification of self-interacting proteins by exploring evolutionary information embedded in PSI-BLAST-constructed position specific scoring matrix.

Oncotarget
Self-interacting Proteins (SIPs) play an essential role in a wide range of biological processes, such as gene expression regulation, signal transduction, enzyme activation and immune response. Because of the limitations for experimental self-interact...

Principal component analysis can decrease neural networks performance for incipient falls detection: A preliminary study with hands and feet accelerations.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Fall-related accidents constitute a major problem for elderly people and a burden to the health-care national system. It is therefore important to design devices (e.g., accelerometers) and machine learning algorithms able to recognize incipient falls...

Classification of EEG based-mental fatigue using principal component analysis and Bayesian neural network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper presents an electroencephalography (EEG) based-classification of between pre- and post-mental load tasks for mental fatigue detection from 65 healthy participants. During the data collection, eye closed and eye open tasks were collected be...

Detection of steering direction using EEG recordings based on sample entropy and time-frequency analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Monitoring driver's intentions beforehand is an ambitious aim, which will bring a huge impact on the society by preventing traffic accidents. Hence, in this preliminary study we recorded high resolution electroencephalography (EEG) from 5 subjects wh...

[Study on Sleep Staging Methods Based on Heart Rate Variability Analysis].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
In order to realize sleep staging automatically and conveniently,we used support vector machine(SVM)to analyze the correlation between heart rate variability and sleep stage experimentally.R-R intervals(RRIs)from 33 cases of sleep clinical data of Ti...

Preliminary research on abnormal brain detection by wavelet-energy and quantum- behaved PSO.

Technology and health care : official journal of the European Society for Engineering and Medicine
It is important to detect abnormal brains accurately and early. The wavelet-energy (WE) was a successful feature descriptor that achieved excellent performance in various applications; hence, we proposed a WE based new approach for automated abnormal...

[The Identification of Lettuce Varieties by Using Unsupervised Possibilistic Fuzzy Learning Vector Quantization and Near Infrared Spectroscopy].

Guang pu xue yu guang pu fen xi = Guang pu
To solve the noisy sensitivity problem of fuzzy learning vector quantization (FLVQ), unsupervised possibilistic fuzzy learning vector quantization (UPFLVQ) was proposed based on unsupervised possibilistic fuzzy clustering (UPFC). UPFLVQ aimed to use ...

The antioxidant and phenolic profiles of five green vegetables grown in Southern Nigeria.

Acta scientiarum polonorum. Technologia alimentaria
BACKGROUND: Regular consumption of vegetables has been associated with reduced risk of chronic diseases. The phenolic and free radical scavenging properties of five green vegetables grown in southern Nigeria were determined.