Boolean factors as a means of clustering of interestingness measures of association rules

Measures of interestingness play a crucial role in association rule mining. An important methodological problem, on which several papers appeared in the literature, is to provide a reasonable classification of the measures. In this paper, we explore Boolean factor analysis, which uses formal concepts corresponding to classes of measures as factors, for the purpose of clustering of the measures. Unlike the existing studies, our method reveals overlapping clusters of interestingness measures. We argue that the overlap between clusters is a desired feature of natural groupings of measures and that because formal concepts are used as factors in Boolean factor analysis, the resulting clusters have a clear meaning and are easy to interpret. We conduct three case studies on clustering of measures, provide interpretations of the resulting clusters and compare the results to those of the previous approaches reported in the literature.     

Individual cell lag time distributions of Cronobacter (Enterobacter sakazakii) and impact of pooling samples on its detection in powdered infant formula

Cells of six strains of Cronobacter were subjected to dry stress and stored for 2.5 months at ambient temperature. The individual cell lag time distributions of recovered cells were characterized at 25 °C and 37 °C in non-selective broth. The individual cell lag times were deduced from the times taken by cultures from individual cells to reach an optical density threshold. In parallel, growth curves for each strain at high contamination levels were determined in the same growth conditions. In general, the extreme value type II distribution with a shape parameter fixed to 5 (EVIIb) was the most effective at describing the 12 observed distributions of individual cell lag times. Recently, a model for characterizing individual cell lag time distribution from population growth parameters was developed for other food-borne pathogenic bacteria such as Listeria monocytogenes. We confirmed this model’s applicability to Cronobacter by comparing the mean and the standard deviation of individual cell lag times to populational lag times observed with high initial concentration experiments. We also validated the model in realistic conditions by studying growth in powdered infant formula decimally diluted in Buffered Peptone Water, which represents the first enrichment step of the standard detection method for Cronobacter. Individual lag times and the pooling of samples significantly affect detection performances.     

Hybrid verification integrating HOL theorem proving with MDG model checking

In this paper, we describe a hybrid tool for hardware formal verification that links the HOL (higher-order logic) theorem prover and the MDG (multiway decision graphs) model checker. Our tool supports abstract datatypes and uninterpreted function symbols available in MDG, allowing the verification of high-level specifications. The hybrid tool, HOL-MDG, is based on an embedding in HOL of the grammar of the hardware modeling language, MDG-HDL, as well as an embedding of the first-order temporal logic L_mdg used to express properties for the MDG model checker. Verification with the hybrid tool is faster and more tractable than using either tools separately. We hence obtain the advantages of both verification paradigms.     

Thymoquinone effects on DMH-induced erythrocyte oxidative stress and haematological alterations during colon cancer promotion in rats

The effect of thymoquinone (TQ), the abundant component of black cumin seed (Nigella sativa) oil extract, was evaluated on 1,2-dimethylhydrazine (DMH)-induced erythrocyte oxidative stress and haematological perturbations during colon cancer promotion in rats. Two TQ approaches, the pre- and post-treatment, were used. DMH promoted erythrocyte oxidative damage in rats by enhancing lipid peroxidation (30%) and decreasing antioxidant enzymes activities (20–35%). This was associated with the decline of erythrocyte count, haemoglobin concentration and haematocrit (20%) and the count increase of white blood cell (60%) and platelet (180%). TQ pre-treatment repaired DMH-induced erythrocyte oxidative stress, anaemia, leukocytosis, and thrombocytosis and allowed a 60% of tumour incidence decline. TQ post-treatment exerted a slight effect on erythrocyte oxidative stress and reduced colon cancer incidence by 30% only. Thus, TQ efficacy in preventing DMH-induced colon cancer promotion was related to its virtue antioxidant effect on erythrocyte oxidative stress.     

An end-to-end neural network for detecting hidden people in images based on multiple attention network

Camouflaged people like soldiers on the battlefield or even camouflaged objects in the natural environments are hard to be detected because of the strong resemblances between the hidden target and the background. That’s why seeing these hidden objects is a challenging task. Due to the nature of hidden objects, identifying them require a significant level of visual perception. To overcome this problem, we present a new end-to-end framework via a multi-level attention network in this paper. We design a novel inception module to extract multi-scale receptive fields features aiming at enhancing feature representation. Furthermore, we use a dense feature pyramid taking advantage of multi-scale semantic features. At last, to locate and distinguish the camouflaged target better from the background, we develop a multi-attention module that generates more discriminative feature representation and combines semantic information with spatial information from different levels. Experiments on the camouflaged people dataset show that our approach outperformed all state-of-the-art methods.

     

A combined support vector machine-FCGS classification based on the wavelet transform for Helitrons recognition in C.elegans

Multimedia Tools and Applications - The Helitrons, an important sub-class of the transposable elements (TEs) class II, have been revealed in diverse eukaryotic genomes. They are mobile elements...