A Fast Multilevel Fuzzy Transform Image Compression Method

We present a fast algorithm that improves on the performance of the multilevel fuzzy transform image compression method. The multilevel F-transform (for short, MF-tr) algorithm is an image compression method based on fuzzy transforms that, compared to the classic fuzzy transform (F-transform) image compression method, has the advantage of being able to reconstruct an image with the required quality. However, this method can be computationally expensive in terms of execution time since, based on the compression ratio used, different iterations may be necessary in order to reconstruct the image with the required quality. To solve this problem, we propose a fast variation of the multilevel F-transform algorithm in which the optimal compression ratio is found in order to reconstruct the image in as few iterations as possible. Comparison tests show that our method reconstructs the image in at most half of the CPU time used by the MF-tr algorithm

Infectious agents in atherosclerotic cardiovascular diseases through oxidative stress

Accumulating evidence demonstrates that vascular oxidative stress is a critical feature of atherosclerotic process, potentially triggered by several infectious agents that are considered as risk co-factors for the atherosclerotic cardiovascular diseases (CVDs). C. pneumoniae has been shown to upregulate multiple enzymatic systems capable of producing reactive oxygen species (ROS) such as NADPH oxidase (NOX) and cyclooxygenase in vascular endothelial cells, NOX and cytochrome c oxidase in macrophages as well as nitric oxide synthase and lipoxygenase in platelets contributing to both early and late stages of atherosclerosis. P. gingivalis seems to be markedly involved in the atherosclerotic process as compared to A. actinomycetemcomitans contributing to LDL oxidation and foam cell formation. Particularly interesting is the evidence describing the NLRP3 inflammasome activation as a new molecular mechanism underlying P. gingivalis-induced oxidative stress and inflammation. Amongst viral agents, immunodeficiency virus-1 and hepatitis C virus seem to have a major role in promoting ROS production, contributing, hence, to the early stages of atherosclerosis including endothelial dysfunction and LDL oxidation. In conclusion, oxidative mechanisms activated by several infectious agents during the atherosclerotic process underlying CVDs are very complex and not well-known, remaining, thus, an attractive target for future research

Max-Min Fuzzy Relation Equations for a Problem of Spatial Analysis

We implement an algorithm that uses a system of max-min fuzzy  relation equations (SFRE) for solving a problem of spatial analysis. We integrate this algorithm in a Geographical information Systems (GIS) tool. We apply our  process to determine the symptoms after that an expert sets the SFRE with the values of the impact coefficients related to some parameters of a geographic zone under study. We also define an index of evaluation about the reliability of the results

A Multilevel Fuzzy Transform Method for High Resolution Image Compression

The Multilevel Fuzzy Transform technique (MF-tr) is a hierarchical image compression method based on Fuzzy Transform, which is successfully used to compress images and manage the information loss of the reconstructed image. Unlike other lossy image compression methods, it ensures that the quality of the reconstructed image is not lower than a prefixed threshold. However, this method is not suitable for compressing massive images due to the high processing times and memory usage. In this paper, we propose a variation of MF-tr for the compression of massive images. The image is divided into tiles, each of which is individually compressed using MF-tr; thereafter, the image is reconstructed by merging the decompressed tiles. Comparative tests performed on remote sensing images show that the proposed method provides better performance than MF-tr in terms of compression rate and CPU time. Moreover, comparison tests show that our method reconstructs the image with CPU times that are at least two times less than those obtained using the MF-tr algorithm

Fuzzy Entropy-Based Spatial Hotspot Reliability

Cluster techniques are used in hotspot spatial analysis to detect hotspots as areas on the map; an extension of the Fuzzy C-means that the clustering algorithm has been applied to locate hotspots on the map as circular areas; it represents a good trade-off between the accuracy in the detection of the hotspot shape and the computational complexity. However, this method does not measure the reliability of the detected hotspots and therefore does not allow us to evaluate how reliable the identification of a hotspot of a circular area corresponding to the detected cluster is; a measure of the reliability of hotspots is crucial for the decision maker to assess the need for action on the area circumscribed by the hotspots. We propose a method based on the use of De Luca and Termini’s Fuzzy Entropy that uses this extension of the Fuzzy C-means algorithm and measures the reliability of detected hotspots. We test our method in a disease analysis problem in which hotspots corresponding to areas where most oto-laryngo-pharyngeal patients reside, within a geographical area constituted by the province of Naples, Italy, are detected as circular areas. The results show a dependency between the reliability and fluctuation of the values of the degrees of belonging to the hotspots

Attribute dependency data analysis for massive datasets by fuzzy transforms

We present a numerical attribute dependency method for massive datasets based on the concepts of direct and inverse fuzzy transform. In a previous work, we used these concepts for numerical attribute dependency in data analysis: Therein, the multi-dimensional inverse fuzzy transform was useful for approximating a regression function. Here we give an extension of this method in massive datasets because the previous method could not be applied due to the high memory size. Our method is proved on a large dataset formed from 402,678 census sections of the Italian regions provided by the Italian National Statistical Institute (ISTAT) in 2011. The results of comparative tests with the well-known methods of regression, called support vector regression and multilayer perceptron, show that the proposed algorithm has comparable performance with those obtained using these two methods. Moreover, the number of parameters requested in our method is minor with respect to those of the cited in the above two algorithms

A Novel Image Similarity Measure Based on Greatest and Smallest Eigen Fuzzy Sets

A novel image similarity index based on the greatest and smallest fuzzy set solutions of the max–min and min–max compositions of fuzzy relations, respectively, is proposed. The greatest and smallest fuzzy sets are found symmetrically as the min–max and max–min solutions, respectively, to a fuzzy relation equation. The original image is partitioned into squared blocks and the pixels in each block are normalized to [0, 1] in order to have a fuzzy relation. The greatest and smallest fuzzy sets, found for each block, are used to measure the similarity between the original image and the image reconstructed by joining the squared blocks. Comparison tests with other well-known image metrics are then carried out where source images are noised by applying Gaussian filters. The results show that the proposed image similarity measure is more effective and robust to noise than the PSNR and SSIM-based measures

Chlamydia pneumoniae and oxidative stress in cardiovascular disease. State of the art and prevention strategies.

Chlamydia pneumoniae, a pathogenic bacteria responsible for respiratory tract infections, is known as the most implicated infectious agent in atherosclerotic cardiovascular diseases (CVDs). Accumulating evidence suggests that C. pneumoniae-induced oxidative stress may play a critical role in the pathogenesis of CVDs. Indeed, the overproduction of reactive oxygen species (ROS) within macrophages, endothelial cells, platelets and vascular smooth muscle cells (VSMCs) after C. pneumoniae exposure, has been shown to cause low density lipoprotein oxidation, foam cell formation, endothelial dysfunction, platelet adhesion and aggregation, and VSMC proliferation and migration, all responsible for the typical pathological changes of atherosclerotic plaque. The aim of this review is to improve our insight into C. pneumoniae-induced oxidative stress in order to suggest potential strategies for CVD prevention. Several antioxidants, acting on multi-enzymatic targets related to ROS production induced by C. pneumoniae, have been discussed. A future strategy for the prevention of C. pneumoniae-associated CVDs will be to target chlamydial HSP60, involved in oxidative stress