Selected ion flow tube – mass spectrometry (SIFT-MS) is based on chemical reactivity of analytes with reactant ions. The complete understanding all the ion–molecule reactions key to deployment this technology for direct and rapid analysis VOCs in gas phase. In present work, we focused carboxylic acids esters, compounds involved many biochemical processes. negative precursor ions (OH–, O●−, O2●−...

RATIONALE It has been proposed that malondialdehyde (MDA) reflects free oxygen-radical lipid peroxidation and can be useful as a biomarker to track this process. For the analysis of MDA molecules in humid air by selected ion flow tube mass spectrometry (SIFT-MS), the rate coefficients and the ion product distributions for the reactions of the SIFT-MS reagent ions with volatile MDA in the presen...

First of all, we downloaded 8 directories from Caltech 101, and used “sift.m” as a function by David Lowe to get SIFT descriptors from each image. However, it took almost forever when we used 8 directories. Therefore, we ended up using only 3 directories: anchors, elephants, and helicopters. By using function ‘sift’ we gathered many descriptors for each image. Some of the images and their SIFT ...

Matching feature points between images is one of the most fundamental issues in computer vision tasks. As the number of feature points increases, the feature matching rapidly becomes a bottleneck. In this paper, a novel method is presented to accelerate features matching by two modifications of the popular SIFT algorithm. The first modification is based on splitting the SIFT features into two t...

The paper proposes the modified-SIFT algorithm which will be a modified form of the scale invariant feature transform. The modification consists of considering successive groups of 8 rows of pixel, along the height of the image. These are used to construct 8 bin histograms for magnitude as well as orientation individually. As a result the number of feature descriptors is significantly less (95%...

The Scale Invariant Feature Transform (SIFT) is an algorithm used to detect and describe scale-, translationand rotation-invariant local features in images. The original SIFT algorithm has been successfully applied in general object detection and recognition tasks, panorama stitching and others. One of its more recent uses also includes face recognition, where it was shown to deliver encouragin...

In recent years the environmental and human health impacts of volatile organic compounds (VOCs) have become more apparent, resulting in increased analysis demand. The gold-standard chromatographic techniques continue to be employed for most laboratory analyses. However, they made only modest gains productivity over years, these are primarily due automated sample preparation injection. Alternati...

This paper introduces a framework for relational schema navigation via a Web-based browser application that uses Formal Concept Analysis as the metaphor for analysis and interaction. Formal Concept Analysis is a rich framework for data analysis based on applied lattice and order theory. The application we develop, D-SIFT, is intended to provide users untrained in Formal Concept Analysis with pr...

Detection and description of local features are a classical problem in image processing and multimedia content analysis. Based on the inhomogeneity of visual orientation in human visual system, we propose a novel algorithm S-SIFT to detect and describe local image features. In three stages of SSIFT, the information from the least discriminability orientation is omitting. Compared with the stand...