Feature extraction is a very important preprocessing step for classification of hyperspectral images. The linear discriminant analysis (LDA) method fails to work in small sample size situations. Moreover, LDA has poor efficiency for non-Gaussian data. LDA is optimized by a global criterion. Thus, it is not sufficiently flexible to cope with the multi-modal distributed data. We propose a new fea...

The recently introduced Oxford Nanopore MinION platform generates DNA sequence data in real-time. This opens immense potential to shorten the sample-to-results time and is likely to lead to enormous benefits in rapid diagnosis of bacterial infection and identification of drug resistance. However, there are very few tools available for streaming analysis of real-time sequencing data. Here, we pr...

The miniaturization of a real time PCR amplification systems are key to genetic point-of-care (POC) diagnostics to offer sample-in answer-out analysis. Actually, miniaturization typically enables shorter analysis times, reduces reagent consumption, minimizes risk of sample contamination, and often enhances assay performance. Here we present the genetic real time PCR PoC system based on silicon ...

The recently introduced Oxford Nanopore MinION platform generates DNA sequence data in real-time. This opens immense potential to shorten the sample-to-results time and is likely to lead to enormous benefits in rapid diagnosis of bacterial infection and identification of drug resistance. However, there are very few tools available for streaming analysis of real-time sequencing data. Here, we pr...

From now on we will work with sets A ⊂ X within a fixed rectangle X ⊂ R. Elementary sets in X make an algebra. Definition 1.8. The outer measure of a setA ⊂ X is μ∗(A) = inf ∑∞ i=1Area(Ri) where the infimum is taken over all countable covers of A by rectangles, A ⊂ ∪i=1Ri. Definition 1.9. The inner measure of a set A ⊂ X is μ∗(A) = Area(X)− μ∗(Ac) where A = X \ A is the complement of A. Lemma. ...

in the mathematical analysis, there are some theorems and definitions that established for both real and fuzzy numbers. in this study, we try to prove  bernoulli's inequality in fuzzy real numbers with some of its applications. also, we prove two other theorems in fuzzy real numbers which are proved before, for real numbers.