Elaboration of stimuli responsive core-shell magnetic latexes from oil in water ferrofluid emulsion

AbstractThis manuscript describes the elaboration of temperature sensitive highly magnetic latex particles. The particle core is crosslinked polymer matrix containing iron oxide nanoparticles. The shell is a combination of highly crosslinked hydrophobic polymer and crosslinked stimuli responsive hydrophilic polymer. The polymerization was performed in two steps: the elaboration of seed magnetic latex particles for oil in water magnetic emulsion and (ii) the functionalization of the obtained magnetic latexes via seed polymerization in the presence of water soluble reactants. The obtained final core-shell latexes exhibit the following properties: The iron oxide content is above 50 wt.%. The size distribution is governed by the size distribution of the used oil in water magnetic emulsion. The thermal sensitivity of the shell is due to the presence of poly(N-isopropylacrylamide). The cationic character of the outer layer shell is due to the use of cationic initiator and amino containing monomer.</jats:p

Evaluation of deep learning and conventional approaches for image steganalysis

Steganography is the technique that's used to embed secret messages into digital media without changing their appearances. As a countermeasure to steganography, steganalysis detects the presence of hidden data in a digital content. For the last decade, the majority of image steganalysis approaches can be formed by two stages. The first stage is to extract effective features from the image content and the second is to train a classifier in machine learning by using the features from stage one. Ultimately the image steganalysis becomes a binary classification problem. Since Deep Learning related architecture unify these two stages and save researchers lots of time designing hand-crafted features, the design of a CNN-based steganalyzer has therefore received increasing attention over the past few years. In this paper, we will examine the development in image steganalysis, both in spatial domain and in JPEG domain, and discuss the future directions