This paper describes our proposed solutions designed for a STS core track within the Se-mEval 2016 English Semantic Textual Similarity (STS) task. Our method of similarity detection combines recursive autoencoders with a WordNet award-penalty system that accounts for semantic relatedness, and an SVM classifier, which produces the final score from similarity matrices. This solution is further supported by an ensemble classifier, combining an aligner with a bi-directional Gated Recurrent Neural Network and additional features, which then performs Linear Support Vector Regression to determine another set of scores.

No abstract

No abstract

No abstract

Nature-based solutions (NBS) include actions that are inspired and/or powered by nature. The level of human intervention can vary from no or minimum intervention to the creation of the entire new ecosystems. One of the types of such solutions are natural water reservoirs (NWRs) with recreational and bathing functions, in which natural water self-purification processes are used. Mechanical, biological, and chemical self-purification processes are used to filter water in natural swimming pools. The elimination of nutrients (nutrients) and bacterial contamination takes place through the use of biological filter beds, usually planted with aquatic vegetation. Implementation of natural water reservoirs also showed a multitude of positive effects on the environment benefits including: enhancing the natural capital, promoting biodiversity, creating new habitats, mitigating water runoff, enhancing water resilience, contribution to urban heat island (UHI) mitigation, increasing air quality, and improvement of local climate.