Effective pedagogical strategies are important for e-learning environments. While it is assumed that an effective learning environment should craft and adapt its actions to the user’s needs, it is often not clear how to do so. In this paper, we used a Natural Language Tutoring System named Cordillera and applied Reinforcement Learning (RL) to induce pedagogical strategies directly from pre-exis...

Extracting biomedical relations such as drug-drug interaction (DDI) from text is an important task in biomedical NLP. Due to the large number of complex sentences in biomedical literature, researchers have employed some sentence simplification techniques to improve the performance of the relation extraction methods. However, due to difficulty of the task, there is no noteworthy improvement in t...

Redundant and irrelevant features in high dimensional data increase the complexity in underlying mathematical models. It is necessary to conduct pre-processing steps that search for the most relevant features in order to reduce the dimensionality of the data. This study made use of a meta-heuristic search approach which uses lightweight random simulations to balance between the exploitation of ...

This article presents a deep learning framework applied for Acoustic Scene Classification (ASC), the task of classifying different environments from sounds they produce. To successfully develop framework, we firstly carry out comprehensive analysis spectrogram representation extracted sound scene input, then propose best multi-spectrogram combination front-end feature extraction. In terms back-...

Global digitalization, the introduction of digital technologies in almost all spheres human life, rapidly changing conditions labor market pose task mastering fundamentally new competencies a short time and professional self­determination young people.
 Young people modern are main socio­demographic group that uses from early childhood is able to quickly adapt their change.

Transcription factors bind DNA by recognizing specific sequence motifs, which are typically 6–12 bp long. A motif can occur many thousands of times in the human genome, but only a subset those sites actually bound. Here we present machine-learning framework leveraging existing convolutional neural network architectures and model interpretation techniques to identify interpret context features m...