Success Stories

Named Entity Recognition for Address Extraction in Speech-to-Text Transcriptions Using Synthetic Data 22 Dec - Many businesses spend large amounts of resources for communicating with clients. Usually, the goal is to provide clients with information, but sometimes there is also a need to request specific information from them. In addressing this need, there has been a significant effort put into the development of chatbots and voicebots, which on one hand serve the purpose of providing information to clients, but they can also be utilized to contact a client with a request to provide some information. A specific real-world example is to contact a client, via text or via phone, to update their postal address. The address may have possibly changed over time, so a business needs to update this information in its internal client database.
Anomaly Detection in Time Series Data: Gambling prevention using Deep Learning 28 Jun - Gambling prevention of online casino players is a challenging ambition with positive impacts both on player’s well-being, and for casino providers aiming for responsible gambling. To facilitate this, we propose an unsupervised deep learning method with an objective to identify players showing signs of problem gambling based on available data in a form of time series. We compare the transformer-based autoencoder architecture for anomaly detection proposed by us with recurrent neural network and convolutional neural network autoencoder architectures and highlight its advantages. Due to the fact that the players’ clinical diagnosis was not part of the data at hand, we evaluated the outcome of our study by analyzing correlation of anomaly scores obtained from the autoencoder and several proxy indicators associated with the problem gambling reported in the literature.
Measurement of microcapsule structural parameters using artificial intelligence (AI) and machine learning (ML) 30 Jun - The main aim of collaboration between the National Competence Centre for HPC (NCC HPC) and the Institute of Polymers of SAV (IP SAV) was design and implementation of a pilot software solution for automatic processing of polymer microcapsules images using artificial intelligence (AI) and machine learning (ML) approach. The microcapsules consist of semi-permeable polymeric membrane which was developed at the IP SAV.
Use case: Transfer and optimization of CFD calculations workflow in HPC environment 15 May - Shark Aero company designs and manufactures ultralight sport aircrafts with two-seat tandem cockpit. For design development they use popular open-source software package openFOAM [1]. The CFD (Computational Fluid Dynamics) simulations use the Finite Elements Method (FEM). After the model is created, using a Computer-Aided Design (CAD) software, it is divided into discrete cells, so called “mesh”. The simulation accuracy depends strongly on mesh density with the computational and memory requirements rising with the 3rd power of the number of mesh vertices. For some simulations the computational demands can be a limiting factor. Workflow transfer into High-Performance Computing (HPC) environment was thus undertaken, with a special focus on the investigation of computational tasks parallelization efficiency for a given model type.
MEMO98 12 Apr - MEMO98 is a non-profit non-government organisation that has been monitoring the media in context of elections and other events for more than 20 years, and has carried out its activities in more than 50 countries. Recently, the organisation has also been dealing with the impact of social media on the integrity of electoral processes.