Abstract
Multimedia content production is nowadays widespread due to technological advances, namely supported by smartphones and social media. Although the massive amount of media content brings new opportunities to the industry, it also obfuscates the relevance of marketing content, meant to maintain and lure new audiences. This leads to an emergent necessity of producing these kinds of contents as quickly and engagingly as possible. Creating these automatically would decrease both the production costs and time, particularly by using static media for the creation of short storytelling animated clips. We propose an innovative approach that uses context and content information to transform a still photo into an appealing context-aware video clip. Thus, our solution presents a contribution to the state-of-the-art in computer vision and multimedia technologies and assists content creators with a value-added service to automatically build rich contextualized multimedia stories from single photographs.

Abstract
The study of sensing materials to the detection of carbon dioxide (CO2) was achieved using p-nitrophenol (pNPh) as a colorimetric indicator. The sensing material was polymerized (NPLn), functionalized with 3-triethoxysilyl propyl isocyanate (IPTES) which sensitivity was tested in the form of a membrane as is and encapsulated in hollow silica nanoparticles. The sensing membranes were tested in a closed gas system comprising very precise flow controllers to deliver different concentrations of CO2 (vs. N2). The combination of the sensing membranes with multimode optical fibers and a dual-wavelength diode (LED) allows the measurement of the CO2 through the analysis of the induced absorbance changes with a self-referenced ratiometric scheme. The analysis of the sensing materials have shown significant changes in their chemical and physical properties and the results attest these materials with a strong potential for assessing CO2 dynamics in environmental, medical, and industrial applications.

Abstract

Abstract
Transportation electrification has become a prominent area of research and investment, especially in the last decades, regarding the increasing concerns for environmental sustainability. In this manner, there are different studies realized on electric vehicles (EVs), especially from the power system integration point of view to enable a more extensive penetration without causing adverse impacts on system operation. Different approaches for the direct and indirect management of EVs based charging demand in power systems have already been proposed in the literature as well as employed in the industry. In this study, from an indirect management point of view, a smart dynamic pricing approach based on a fuzzy logic controller based decision-making structure is proposed for EV charging in a distribution system. The proposed new decision-making method considers dynamically varying as well as static operational issues together with the social welfare of EV owners to provide real-time decisions compared to existing studies considering the wider EV charging service pricing topic from a different perspective. © 2020 IEEE.

Abstract

Abstract