Extracting the overlapped sub-regions in wireless sensor networks

In wireless sensor networks, the overlapped sub-regions (faces) are generated due to the intersections among the sensing ranges of nodes. The faces play a significant role in solving the three problems k-coverage (i.e., all the points in the interested field should be covered by at least k active nodes while maintaining connectivity between all active nodes), coverage scheduling and cover sets. To find the faces and discover their coverage degrees, this article presents a distributed algorithm that runs in three steps. First, a colored graph called Intersection Points Colored Graph (IPCG) is proposed, in which the vertices are defined by the range-intersections of nodes-devices and are colored according to the position of these intersections in relation to the ranges of the nodes. The vertex that located on perimeter of the node’s range is colored by red, while the green vertex is an intersection of two ranges inside the range of a third node. The edge that joins two red vertices is colored by red and the edge that joins two green vertices is colored by green while the edge that joins two distinct colored vertices is colored by blue. Second, based on their properties and distinct features, the faces in IPCG are classified into five classes (simple, negative, red, green and positive). Third, based on faces classification, the Three Colored Trees algorithm is proposed to extract the faces in linear time in terms of the number of vertices and edges in IPCG.

     

Urchin like CuO hollow microspheres for selective high response ethanol sensor application: Experimental and theoretical studies

Herein, the synthesis, characterizations and gas sensor application of nano-textured urchin like CuO hollow microspheres (HM) were reported. The detailed characterizations confirmed the uniform growth and nanocrystalline monoclinic structure of urchin like CuO HM. The synthesized urchins like CuO HM were utilized to fabricate resistive sensor devices which exhibited elevated response towards ethanol with high selectivity. The optimization of operating temperature was carried out for the highest ethanol response and the effect of different concentrations were also recorded. The sensor device showed 1241% response at an operating temperature of 225 °C for 100 ppm ethanol concentration. The lowest ethanol was detected at 25 ppm having the response of 49% by the fabricated CuO sensor device. Transient responses as well as stability of the sensor were analyzed. The selectivity of CuO sensor device was studied for NO₂, CO₂, CH₄ and H₂ gases and remarkably it was seen that the developed gas sensor devices demonstrated outstanding selectivity towards ethanol gas. Finally, the density functional theory (DFT) computational quantum modelling was utilized in order to understand the adsorption phenomenon of ethanol and oxygen molecules in the sensing application. An ethanol sensing mechanism using CuO sensor was also elucidated.     

D2F: discriminative dense fusion of appearance and motion modalities for end-to-end video classification

Recently, two-stream networks with multi-modality inputs have shown to be of vital importance for state-of-the-art video understanding. Previous deep systems typically employ a late fusion strategy, however, despite its simplicity and effectiveness, the late strategy might experience insufficient fusion due to that it performs fusion across modalities only once and treats each modality equally without discrimination. In this paper, we propose a Discriminative Dense Fusion (D²F) network, addressing these limitations by densely inserting an attention-based fusion block at each layer. We experiment with two typical action classification benchmarks and three popular classification backbones, where our proposed module consistently outperforms state-of-the-art baselines by noticeable margins. Specifically, the two-stream VGG16, ResNet and I3D achieve accuracy of [93.5%, 69.2%], [94.6%, 70.5%], [94.1%, 72.3%] with D²F on [UCF101, HMDB51], respectively, with absolute gains of [5.5%, 9.8%], [5.13%, 9.91%], and [0.7%, 5.9%] compared with their late fusion counterparts. The qualitative performance also demonstrates that our model can learn more informative complementary representation.

     

A survey of botnet detection based on DNS

Neural Computing and Applications - Botnet is a thorny and a grave problem of today’s Internet, resulting in economic damage for organizations and individuals. Botnet is a group of...     

Effects of trace metal elements on ultrastructural features of hepatopancreas of Armadillidium granulatum Brandt, 1833 (Crustacea,Isopoda)

This study was conducted to compare metals bioaccumulation in the terrestrial isopod Armadillidium granulatum collected from Ghar El Melh lagoon. We focused on recognizing the effects of trace elements on hepatopancreas functional role. To this end, isopod specimens were exposed for 3 weeks to sediments contaminated with cadmium, copper, zinc, mercury, and nickel. Three concentrations were used in duplicate for each experimental condition. At the end of the experiment, metal body burdens were determined using flame atomic absorption spectrometry. Results of the bioaccumulation factor (BAF) showed that the species A. granulatum was classified as a Cu macroconcentrator (BAF > 2) and a Zn deconcentrator (BAF < 2). Dose dependent morphological and histological changes were observed in the hepatopancreas cells using transmission electron microscopy. The predominant features were: microvillus border disruption, condensation of the cytoplasm with increasing endoplasmic reticulum, mitochondria, lysosomes and granules that accumulated metals in B and S cells. The number of lipid droplets decreased especially after Cd, Zn, Hg, and Ni treatments. This study demonstrated that the terrestrial isopod A. gramulatum could be a good indicator of soil metal contamination.     

An enhanced opinion retrieval approach via implicit feature identification

Journal of Intelligent Information Systems - Recently, there has been an enormous increase in the number of reviews of popular products. Therefore, opinion analysis has become a tedious task for...     

Differential Impact of Sex on Seasonal Changes in Mantle and Tentacle Phospholipids and Triacylglycerols in Sepia officinalis

The aim of the present work was to study the effect of season on phospholipids and triacylglycerols (TAG) of mantle and tentacles of female and male wild Sepia officinalis. The identified phospholipids were phosphatidylethanolamine (PtdEtn), phosphatidylcholine (PtdCho), phosphatidylserine (PtdSer), and phosphatidylinositol (PtdIns), and PtdEtn was the major fraction. Results showed apparent seasonal variation of phospholipid content, particularly with female samples. Fatty acid composition of phospholipid classes showed a differentiation much more in the proportions than in the diversity of fatty acids. Results showed that the major saturated fatty acids were 16:0 and 18:0, the major monounsaturated fatty acids were 18:1 and 20:l, and the major polyunsaturated fatty acids were docosahexaenoic acid (22:6n-3) (DHA) and eicosapentaenoic acid (20:5n-3) (EPA). The results relative to TAG demonstrated significant variations. Principal component analysis confirmed the seasonal and sexual effects. This study could be appropriate for the improvement of consistent monitoring of phospholipid and TAG accumulation in cephalopod, which might be important for both physiological studies and food industries.