A Lightweight Image Encryption Algorithm for Secure Communications in Multimedia Internet of Things

Wireless Personal Communications - Devices in the Internet of Things (IoT) have resource constraints in terms of energy, computing power, and memory that make them vulnerable to some security...     

Video-based isolated hand sign language recognition using a deep cascaded model

In this paper, we propose an efficient cascaded model for sign language recognition taking benefit from spatio-temporal hand-based information using deep learning approaches, especially Single Shot Detector (SSD), Convolutional Neural Network (CNN), and Long Short Term Memory (LSTM), from videos. Our simple yet efficient and accurate model includes two main parts: hand detection and sign recognition. Three types of spatial features, including hand features, Extra Spatial Hand Relation (ESHR) features, and Hand Pose (HP) features, have been fused in the model to feed to LSTM for temporal features extraction. We train SSD model for hand detection using some videos collected from five online sign dictionaries. Our model is evaluated on our proposed dataset (Rastgoo et al., Expert Syst Appl 150: 113336, 2020), including 10’000 sign videos for 100 Persian sign using 10 contributors in 10 different backgrounds, and isoGD dataset. Using the 5-fold cross-validation method, our model outperforms state-of-the-art alternatives in sign language recognition

     

Selective molecularly imprinted polymer nanofiber sorbent for the extraction of bisphenol A in a water sample

Novel molecularly imprinted polymer nanofibers (MIP‐NFs) were prepared for the adsorption of bisphenol A (BPA) in a water sample using the sol–gel process and the electrospinning technique. The effects of a number of synthesis parameters on the adsorption efficiency were investigated. The successful removal of BPA from MIP‐NFs was studied using UV–visible spectroscopy. The prepared MIP‐NFs were characterized by Fourier transform infrared, field emission SEM, TEM and energy dispersive X‐ray analysis. The results showed that the required molar ratio of 3‐aminopropyltriethoxysilane (APTES) to BPA was 15:1, which indicates a good performance in the rebinding test. Likewise, the molar ratio of APTES:acid:water was 1:2:9. The nylon 6 polymer solution, with a concentration of 12 wt%, showed a maximum adsorption capacity for BPA due to a decrease in the nanofiber diameter and an increase in the accessible sites. Furthermore, the maximum adsorption capacity of BPA was achieved at pH 7. Concerning the binding of BPA on MIP‐NFs, the experimental data matched well with the pseudo‐second‐order kinetics data and the Sips isotherm model. The saturated binding capacity for MIP‐NFs was predicted to be 115.1 mg g^?1, which was more than twice as high as that for non‐imprinted polymer nanofibers (46.82 mg g^?1). The results obtained in this study confirmed that the prepared MIP‐NFs showed considerable binding specificity for BPA in comparison with similar structural compounds such as phenol, naphthol and Naphthol AS, in aqueous solution. The binding capacity of MIP‐NFs remained almost constant after five cycles of reuse. The real sample analysis indicated that MIP‐NFs could be utilized as a useful sorbent material for the extraction of BPA from a water sample.     

ERES: an extended regular expression signature for polymorphic worm detection

Journal of Computer Virology and Hacking Techniques - The quick spreading of modern sophisticated polymorphic worms poses a serious threat to the internet security. So far, several signature...     

Evaluation of the localized corrosion on Mg electrode surface by electrochemical noise technique

The symmetrical and asymmetrical electrodes made of Mg were studied in 0.1-M NaCl electrolyte adjusted at pH 12. The statistical and wavelet methods were employed for analyzing the electrochemical current noise (ECN) signals. The asymmetric configuration was used for electrochemical detection of filiform corrosion on Mg electrode. The real time scale of the dominant transients of the asymmetric electrodes was detected on the basis of the maximum peak in the SDPS plots. The SDPS values of the real time scale crystals of the ECN signals resulting from asymmetrical electrodes increased with the increase in immersion time due to the onset of filiform corrosion.     

Preparation,morphology and conductivity of polyacrylonitrile/multi-wall carbon nanotubes composite nanofibers

Composite nanofibers of polyacrylonitrile/multi-wall carbon nanotubes (PAN/MWCNTs) were prepared via electrospinning. Samples contained 0, 0.5, 1, 2, 3, and 3.5 wt% of MWCNTs. The viscosity and electrical conductivity of electrospinning solutions were measured. Results revealed that, with the addition of multi-wall carbon nanotubes, viscosity was increased and electrical conductivity was improved. Rheological behavior was studied using two different viscometers. Moreover, morphology and diameters of the composite nanofibers were studied by scanning electron microscopy (SEM) and nanofiber diameter distributions were presented. SEM micrographs showed that by adding MWCNTs, the average diameter of nanofibers was increased. Furthermore, the effect of MWCNTs on glass transition temperature, T _g, was investigated using differential scanning calorimetry (DSC) technique. The results showed that T _g was increased with the addition of MWCNTs. In addition, Fourier transform infrared spectroscopy (FTIR) results showed that MWCNTs can affect the orientation ability of polymer chains. The effects of adding salt, increasing voltage and changing the tip-to-collector distance on the morphology and diameters of composite nanofibers were examined. The electrical conductivity results of electrospun mats were measured by a two-probe method. Electrical conductivity was increased by addition of MWCNTs and its behavior followed the percolation theory. Finally, it was observed that mats with smaller diameters have higher electrical conductivity.     

Hand pose aware multimodal isolated sign language recognition

Multimedia Tools and Applications - Isolated hand sign language recognition from video is a challenging research area in computer vision. Some of the most important challenges in this area include...     

Effects of Raw Material Molar Ratio and Addition of Mg on Titanium Aluminide–Alumina Composite Formation Mechanism

Powder Metallurgy and Metal Ceramics - In this study, the effects of molar ratio of the raw materials (TiO2 and Al) and the addition of Mg on the titanium aluminide–alumina composite...