A multi-sequences MRI deep framework study applied to glioma classfication

Multimedia Tools and Applications - Glioma is one of the most important central nervous system tumors, ranked 15th in the most common cancer for men and women. Magnetic Resonance Imaging (MRI)...     

Simulated evaluation of faceted browsing based on feature selection

In this paper we explore the limitations of facet based browsing which uses sub-needs of an information need for querying and organising the search process in video retrieval. The underlying assumption of this approach is that the search effectiveness will be enhanced if such an approach is employed for interactive video retrieval using textual and visual features. We explore the performance bounds of a faceted system by carrying out a simulated user evaluation on TRECVid data sets, and also on the logs of a prior user experiment with the system. We first present a methodology to reduce the dimensionality of features by selecting the most important ones. Then, we discuss the simulated evaluation strategies employed in our evaluation and the effect on the use of both textual and visual features. Facets created by users are simulated by clustering video shots using textual and visual features. The experimental results of our study demonstrate that the faceted browser can potentially improve the search effectiveness.     

Improving retrieval framework using information gain models

Content-based image retrieval systems are meant to retrieve the most similar images of a collection to a query image. One of the most well-known models widely applied for this task is the bag of visual words (BoVW) model. In this paper, we introduce a study of different information gain models used for the construction of a visual vocabulary. In the proposed framework, information gain models are used as a discriminative information to index image features and select the ones that have the highest information gain values. We introduce some extensions to further improve the performance of the proposed framework: mixing different vocabularies and extending the BoVW to bag of visual phrases. Exhaustive experiments show the interest of information gain models on our retrieval framework.     

Solid-phase microextraction coupled with high performance liquid chromatography: a complementary technique to solid-phase microextraction-gas chromatography for the analysis of pesticide residues in strawberries

Solid-phase microextraction coupled with high performance liquid chromatography has been studied for the analysis of methiocarb, napropamide, fenoxycarb and bupirimate in strawberries. The strawberries were blended and centrifuged. Then, an aliquot of the resulting extracting solution was subjected to solidphase microextraction (SPME) on a 60 μm polydimethylsiloxane /divinylbenzen e (PDMS/DVB) fibre for 45 min at room temperature. The extracted pesticides on the SPME fibre were desorbed into SPME/ high performance liquid chromatography (HPLC) interface for HPLC analysis with diode-array detection (DAD). The method is organic solvent-free for the whole extraction process and is simple and easy to manipulate. The detection limits were shown to be at low μg kg^-1 level and the linear response covered the range from 0.05 to 2 mg kg^-1 of pesticides in strawberries with a regression coefficient larger than 0.99. A good repeatability with RSDs between 2.92 and 9.25% was obtained, depending on compounds.     

Solid phase microextraction of pesticide residues from strawberries.

A new solid phase microextraction method for the determination of pesticide residues in strawberries for 16 commonly used compounds was described. The strawberries were crushed and centrifuged. An aliquot of the well agitated aqueous supernatant (4 ml) was extracted with a fibre coated with polydimethylsiloxane (PDMS, 100 microns) for 45 min at room temperature. Identification and quantification were achieved using a gas chromatography-mass spectrometry (GC-MS) system and selective ion monitoring (SIM). The method was tested for the following pesticides: carbofuran, diethofencarb, penconazole, hexaconazole, metalaxyl, folpet, bromopropylate, dichlofluanid, alpha-endosulfan, beta-endosulfan, parathion ethyl, procymidone, iprodione, vinclozolin, myclobutanil and chlorothalonil. Limits of detection, repeatability and linearity for standard calibration in strawberries were obtained. Positive and negative effects of the matrix between the extracting solution of strawberries and water were observed. Stabilities of these compounds in the extracting solution of strawberries were determined. The solvent-free SPME procedure was found to be quicker and more cost effective than the solvent extraction methods commonly used.     

Vector space model adaptation and pseudo relevance feedback for content-based image retrieval

Image retrieval is an important problem for researchers in computer vision and content-based image retrieval (CBIR) fields. Over the last decades, many image retrieval systems were based on image representation as a set of extracted low-level features such as color, texture and shape. Then, systems calculate similarity metrics between features in order to find similar images to a query image. The disadvantage of this approach is that images visually and semantically different may be similar in the low level feature space. So, it is necessary to develop tools to optimize retrieval of information. Integration of vector space models is one solution to improve the performance of image retrieval. In this paper, we present an efficient and effective retrieval framework which includes a vectorization technique combined with a pseudo relevance model. The idea is to transform any similarity matching model (between images) to a vector space model providing a score. A study on several methodologies to obtain the vectorization is presented. Some experiments have been undertaken on Wang, Oxford5k and Inria Holidays datasets to show the performance of our proposed framework.     

Redox effect on volatile compound formation in wine during fermentation by Saccharomyces cerevisiae

Although redox state is a well-known key process parameter in microbial activity, its impact on wine volatile aroma compounds produced during fermentation has not been studied in detail. In this study we report the effect of reductive and microaerobic conditions on wine aroma compound production using different initial amounts of yeast assimilable nitrogen (YAN: 180 and 400 mg N/l) in a simil grape must defined medium and two S. cerevisiae strains commonly used in wine-making. In batch fermentation culture conditions, reductive conditions were obtained using flasks plugged with Muller valves filled with sulphuric acid; while microaerobic conditions were attained with defined cotton plugs. It was found that significant differences in redox potential were obtained using the different plugs, and with variation of over 100 mV during the main fermentation period.     

A robust CBIR framework in between bags of visual words and phrases models for specific image datasets

One objective of the Content Based Image Retrieval research field is to propose new methodologies and tools to manage the increasing number of images available. Linked to a specific context of small expert datasets without prior knowledge, our research work focuses on improving the discriminative power of the image representation while keeping the same efficiency for retrieval. Based on the well-known bag of visual words model, we propose three different methodologies inspired by the visual phrase model effectiveness and a compression technique which ensures the same effectiveness for retrieval than the BoVW model. Our experimental results study the performance of our proposals on different well known benchmark datasets and show its good performance compared to other recent approaches.