In this paper the accuracy of two machine learning algorithms including SVM and Bayesian Network are investigated as two important algorithms in diagnosis of Parkinson’s disease. We use Parkinson's disease data in the University of California, Irvine (UCI). In order to optimize the SVM algorithm, different kernel functions and C parameters have been used and our results show that SVM with C par...

manual fingerprint classification algorithms are very time consuming, and usually not accurate. fast and accurate fingerprint classification is essential to each afis (automatic fingerprint identification system). this paper investigates a fingerprint classification algorithm that reduces the complexity and costs associated with the fingerprint identification procedure. a new structural algorit...

Manual fingerprint classification algorithms are very time consuming, and usually not accurate. Fast and accurate fingerprint classification is essential to each AFIS (Automatic Fingerprint Identification System). This paper investigates a fingerprint classification algorithm that reduces the complexity and costs associated with the fingerprint identification procedure. A new structural algorit...

classification of heart arrhythmia is an important step in developing devices for monitoring the health of individuals. this paper proposes a three module system for classification of electrocardiogram (ecg) beats. these modules are: denoising module, feature extraction module and a classification module. in the first module the stationary wavelet transform (swf) is used for noise reduction of ...

concurrency control is one of the important problems in operation systems. various studies have been reported to present different algorithms to address this problem, although a few attempts have been made to represent an overall view of the characteristics of these algorithms and comparison of their capabilities to each other. this paper presents a survey of the current methods for controlling...