Tallinn University of Technology

About: Tallinn University of Technology is a education organization based out in Tallinn, Estonia. It is known for research contribution in the topics: European union & Computer science. The organization has 3688 authors who have published 10313 publications receiving 145058 citations. The organization is also known as: Tallinn Technical University & Tallinna Tehnikaülikool.

Towards Disaster Resilient Smart Cities: Can Internet of Things and Big Data Analytics Be the Game Changers?

Abstract: Disasters (natural or man-made) can be lethal to human life, the environment, and infrastructure. The recent advancements in the Internet of Things (IoT) and the evolution in big data analytics (BDA) technologies have provided an open opportunity to develop highly needed disaster resilient smart city environments. In this paper, we propose and discuss the novel reference architecture and philosophy of a disaster resilient smart city (DRSC) through the integration of the IoT and BDA technologies. The proposed architecture offers a generic solution for disaster management activities in smart city incentives. A combination of the Hadoop Ecosystem and Spark are reviewed to develop an efficient DRSC environment that supports both real-time and offline analysis. The implementation model of the environment consists of data harvesting, data aggregation, data pre-processing, and big data analytics and service platform. A variety of datasets (i.e., smart buildings, city pollution, traffic simulator, and twitter) are utilized for the validation and evaluation of the system to detect and generate alerts for a fire in a building, pollution level in the city, emergency evacuation path, and the collection of information about natural disasters (i.e., earthquakes and tsunamis). The evaluation of the system efficiency is measured in terms of processing time and throughput that demonstrates the performance superiority of the proposed architecture. Moreover, the key challenges faced are identified and briefly discussed.

Presence of fluoroquinolones and sulfonamides in urban sewage sludge and their degradation as a result of composting

Abstract: The concentrations of some widely used pharmaceuticals, namely fluoroquinolones (ciprofloxacin C17 H18FN3O3, norfloxacin C17 H18FN3O3 and ofloxacin C18 H20FN3O4 and sulfonamides (sulfadimethoxine C12 H14N4O4s and sulfamethoxazole C10 H11N3O3S were determined in urban sewage sludge utilized for making compost. The levels of degradation of these pharmaceuticals resulting from sludge treatment were assessed. The concentrations of the studied pharmaceuticals sufficiently varied both in sewage sludge and in compost and due to this phenomenon the possible danger resulting from the presence of pharmaceuticals in sewage sludge, used for composting, can not be ignored. The concentrations of the studied pharmaceuticals were lower in compost, if compared to the relevant concentrations in sewage sludge. The highest pharmaceutical concentration in sewage sludge — 426 μg/kg — was detected in the case of ciprofloxacin. The highest concentrations present in compost were 22 μg/kg of norfloxacin and 20 μg/kg of ciprofloxacin. Results show that before using the sewage sludge for making compost or before using the compost a fertilizer for food plants, they should be carefully tested against the content of commonly used pharmaceuticals.

QSPR modeling of flash points: An update

Abstract: Quantitative structure–property relationship (QSPR) models for the flash points of 758 organic compounds are developed using geometrical, topological, quantum mechanical and electronic descriptors calculated by CODESSA PRO software. Multilinear regression models link the structures to their reported flash point values. We also report a nonlinear model based on an artificial neural network. The results are discussed in the light of the main factors that influence the property under investigation and its modeling.