An Optimization Clustering Algorithm Based on Texture Feature Fusion for Color Image Segmentation

We introduce a multi-feature optimization clustering algorithm for color image segmentation. The local binary pattern, the mean of the min-max difference, and the color components are combined as feature vectors to describe the magnitude change of grey value and the contrastive information of neighbor pixels. In clustering stage, it gets the initial clustering center and avoids getting into local optimization by adding mutation operator of genetic algorithm to particle swarm optimization. Compared with well-known methods, the proposed method has an overall better segmentation performance and can segment image more accurately by evaluating the ratio of misclassification.© 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

An improved non-local means filter for color image denoising

Non-local means filter is a special case of non-linear filter. It performs well for filtering Gaussian noise while preserving edges and details of the original images. In this paper, we propose an improved filter for color image denoising based on combining the advantages of non-local means filter and bilateral filter. To compare the similarity of patches, a new weight value is computed by adding texture information into weights. The experimental results of color image filtering show that the proposed method has a better performance for reducing Gaussian noise and mixture noise

Soot particle size distribution measurements in laminar diffusion flames of n-heptane with oxygenated aromatic fuel additives by time-resolved laser-induced incandescence

Soot particle size profiles of a laminar co-flow diffusion flame were determined using time-resolved laser-induced incandescence (TiRe-LII) for various fuels. In the fuel matrix, both the level (0-20 vol %) and type (oxygenated versus non-oxygenated) of aromaticity was varied. Motivation for this study was earlier engine research, which demonstrated that the addition of certain aromatic oxygenates, among which anisole and veratrole, to diesel fuel manifested in lower engine out particle emissions. The co-flow burner research conducted in this study may conclude that the presence of oxygenated aromatics, although less detrimental than the non-oxygenated variety, toluene, still manifested in both greater soot volume fractions and particle sizes than was the case for the aliphatic base fuel, n-heptane. Hereby, the effectiveness of aromatic ring oxygenation was most pronounced for the first functional oxygen group. The addition of a second functional oxygen had little impact on the results

Experimental study of polycyclic aromatic hydrocarbons (PAHs) in n-Heptane laminar diffusion flames from1.0 to 3.0 bar

As PAHs (Polycyclic Aromatic Hydrocarbons) are the main precursor of soot formation during the combustion, the investigation of PAHs formation is essential for the understanding of the soot formation and soot reduction in combustion. In this study, a specially designed burner and the corresponding fueling system was used to stabilize a laminar diffusion flame of n-heptane up to 3.0 bar before it becomes unstable. Using the combination of LII (Laser Induced Incandescence) and LIF (Laser Induced Fluorescence) techniques, the PAHs and soot formation and their distributions in the studied flames were obtained and explained. The results showed that PAHs were almost surrounded by soot and were present in the lower part of the flame. Moreover, the integral soot and PAH intensities exhibited a power law dependence on the pressure, being proportional to pn with n of 1.38 ± 0.32 and 1.49 ± 0.25 respectively under the pressure range of 1.0–3.0 bar

Soot particle size distribution measurements in laminar diffusion flames of n-heptane with oxygenated aromatic fuel additives by time-resolved laser-induced incandescence

\u3cp\u3eSoot particle size profiles of a laminar co-flow diffusion flame were determined using time-resolved laser-induced incandescence (TiRe-LII) for various fuels. In the fuel matrix, both the level (0-20 vol %) and type (oxygenated versus non-oxygenated) of aromaticity was varied. Motivation for this study was earlier engine research, which demonstrated that the addition of certain aromatic oxygenates, among which anisole and veratrole, to diesel fuel manifested in lower engine out particle emissions. The co-flow burner research conducted in this study may conclude that the presence of oxygenated aromatics, although less detrimental than the non-oxygenated variety, toluene, still manifested in both greater soot volume fractions and particle sizes than was the case for the aliphatic base fuel, n-heptane. Hereby, the effectiveness of aromatic ring oxygenation was most pronounced for the first functional oxygen group. The addition of a second functional oxygen had little impact on the results.\u3c/p\u3

Completely Free from PAM Limitations: Asymmetric RPA with CRISPR/Cas12a for Nucleic Acid Assays

Experimentally, Cas12a can recognize multiple protospacer adjacent motif (PAM) sequences and is not restricted to the “TTTN”. However, the application of the CRISPR/Cas12a system is still limited by the PAM for double-stranded DNA (dsDNA). Here, we developed asymmetric RPA (Asy-RPA) to completely break the limitations of PAM. Asy-RPA not only achieved efficient amplification but also converted dsDNA to single-stranded DNA (ssDNA) without complicated steps. The ssDNA products activated the trans-cleavage activity of Cas12a, outputting signals. The application of Asy-RPA completely freed Cas12a from the PAM, which can be more widely used in nucleic acid detection, such as lumpy skin disease virus, with an actual detection limit as low as 1.21 × 101 copies·μL–1. More importantly, Cas12a was intolerant to mutations on ssDNA. This provided technical support for the detection and identification of wild-type Mycobacterium tuberculosis (WT-TB) and rifampin-resistant mutant-type M. tuberculosis (MT-TB). The detection limit was as low as 1 fM for 1% mixed samples. The detection and availability of different treatment options for treatment-resistant and WT-TB were significant for the elimination of TB. In summary, the platform consisting of Asy-RPA and CRISPR/Cas12a was suitable for the detection of various viruses and bacteria and was a boon for the detection of dsDNA without recognizable PAM