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Most machine-learning classifiers output label predictions for new instances without indicating how reliable the predictions are. The applicability of these classifiers is limited in critical domains where incorrect predictions have serious consequences, like medical diagnosis. Further, the default assumption of equal misclassification costs is most likely(More)
Ma-Zi-Ren-Wan (MZRW) is a classic Chinese formula which has been used to treat human constipation in China for over 2000 years. In order to make good and rational use of this formula in the future, this paper presents the first attempt to track the pharmacokinetic features of MZRW in rat using rapid and sensitive ultra-performance liquid(More)
This paper introduces an absolute calibration algorithm of RDSS (radio determination satellite service) channel. The RDSS signal is used as the test signal. The input and output for RDSS are sampled in synchronization. Digital signal processing based on SDR (Software Defined Receiver) has been made with the sampling data of RDSS channel input and output.(More)
Many computational approaches have been used for target prediction, including machine learning, reverse docking, bioactivity spectra analysis, and chemical similarity searching. Recent studies have suggested that chemical similarity searching may be driven by the most-similar ligand. However, the extent of bioactivity of most-similar ligands has been(More)
Lots of error sources affect the microarray image quality, especially the noise. An image may contain different type noises which will produce distinct influence on image processing, so it doesn’t need to remove all. This paper analyzed the affection of different noises to automatic gridding and proposed grid line number for quantitive evaluation. A(More)
An absolute calibrate of BOC signal transmitting channel on navigation satellite based on software defined radio is addressed. At first, the BOC navigation signal and the pulse per second (PPS) generated by navigation time keeping system are sampled synchronously. After the sampling data of BOC signal is preprocessed, a serial-to-parallel transform is done(More)
The class imbalance problem is of great importance to network intrusion detection data. Previous studies on feature selection always evaluate the performance of feature selection process according to the model performance and the size of selected feature subset, which neglect the stability of feature selection. We investigate the problem of the stability of(More)
BACKGROUND Inflammatory bowel disease (IBD), denominated by Crohn's disease and ulcerative colitis, is often associated with abdominal pain, diarrhea and bloody stool. The standard protocols for treating colitis conditions are not satisfactory; thus, complementary and alternative medicines have been increasingly accepted by IBD sufferers worldwide. In this(More)
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