Localized convolutional neural networks for geospatial wind forecasting

Convolutional Neural Networks (CNN) possess many positive qualities when it comes to spatial raster data. Translation invariance enables CNNs to detect features regardless of their position in the scene. However, in some domains, like geospatial, not all locations are exactly equal. In this work, we propose localized convolutional neural networks that enable convolutional architectures to learn local features in addition to the global ones. We investigate their instantiations in the form of learnable inputs, local weights, and a more general form. They can be added to any convolutional layers, easily end-to-end trained, introduce minimal additional complexity, and let CNNs retain most of their benefits to the extent that they are needed. In this work we address spatio-temporal prediction: test the effectiveness of our methods on a synthetic benchmark dataset and tackle three real-world wind prediction datasets. For one of them, we propose a method to spatially order the unordered data. We compare the recent state-of-the-art spatio-temporal prediction models on the same data. Models that use convolutional layers can be and are extended with our localizations. In all these cases our extensions improve the results, and thus often the state-of-the-art. We share all the code at a public repository

Research of the certification programme on skills of ensuring children safety using internet

The main purpose of the paper is to develop a certification programme on Skills ensuring children safety using Internet. In order to acheve this goal, five tasks were formed: • Explore current ECDL certification programmes aiming to specialized programmes. • Explore the standards of new ECDL programmes developement. • Develop the e-Guardian programme syllabus which would be as much hardware platform and software independent as possible. • Develop the e-Guardian certification programme questions test base for automotive testing. • Place the e-Guardian certification programme questions test base on the ECDL-Lithuania testing system. • Examine ECDL Foundation quality management requirements of the e-Guardian syllabus and AQTB. To achieve these tasks such research methods as nonfiction analysis and summation, expert and user surveys, observation, experiments, statistical analysis were used. The theoretical part explores ECDL certification programmes, ECDL programme development standards, e-Guardian programme part among the ECDL Foundation products. The methods for developing ECDL programmes are described in second part. These methods include ECDL Foundation product authorization standards, certification programme syllabus and questions test base development. Third part includes descriptions of the two researches. e-Guardian syllabus and questions test base are developed in the first of them and corrections for the test base questions are made in the second research by making a survey with experts. Experiment results are used for developing questions test base. The main results are: • Current specialized ECDL certification programmes reviewed. • New specialized ECDL Foundation programme development standard and quality management system analysis is made, e-Guardian programme part among the ECDL Foundation programmes is set. • The certification Programme syllabus is developed. • Questions test base is developed according to the syllabus. • e-Guardian product endorsement standards form is filled and given for the ECDL Foundation, which agreed with e-Guardian being very important. • The trial version of the certification programme is placed on ECDL-Lithuania testing system in order to estimate testing characteristics and valuation parameters. Researches are made proving quality of the certification programme syllabus and questions test base. Learning programmes teach how to protect computer data, software and hardware, also children using Internet, but there are no certification programmes developed. The e-Guardian is aiming to become ECDL Foundation endorsed certification programme on skills of ensuring children safety using internet. The programme‘s syllabus and questions test base is now developed, endorsement form is filled and given to the ECDL Foundation, which recognized e-Guardian as a very important certification programme seeking ECDL endorsement. The volume of the paper is 82 pages. In the main parts there are 1 table and 9 pictures

Deep-Learning-Based Estimation of the Spatial QRS-T Angle from Reduced-Lead ECGs

The spatial QRS-T angle is a promising health indicator for risk stratification of sudden cardiac death (SCD). Thus far, the angle is estimated solely from 12-lead electrocardiogram (ECG) systems uncomfortable for ambulatory monitoring. Methods to estimate QRS-T angles from reduced-lead ECGs registered with consumer healthcare devices would, therefore, facilitate ambulatory monitoring. (1) Objective: Develop a method to estimate spatial QRS-T angles from reduced-lead ECGs. (2) Approach: We designed a deep learning model to locate the QRS and T wave vectors necessary for computing the QRS-T angle. We implemented an original loss function to guide the model in the 3D space to search for each vector’s coordinates. A gradual reduction of ECG leads from the largest publicly available dataset of clinical 12-lead ECG recordings (PTB-XL) is used for training and validation. (3) Results: The spatial QRS-T angle can be estimated from leads {I, II, aVF, V2} with sufficient accuracy (absolute mean and median errors of 11.4° and 7.3°) for detecting abnormal angles without sacrificing patient comfortability. (4) Significance: Our model could enable ambulatory monitoring of spatial QRS-T angles using patch- or textile-based ECG devices. Populations at risk of SCD, like chronic cardiac and kidney disease patients, might benefit from this technology

Correcting Diacritics and Typos with a ByT5 Transformer Model

Due to the fast pace of life and online communications and the prevalence of English and the QWERTY keyboard, people tend to forgo using diacritics, make typographical errors (typos) when typing in other languages. Restoring diacritics and correcting spelling is important for proper language use and the disambiguation of texts for both humans and downstream algorithms. However, both of these problems are typically addressed separately: the state-of-the-art diacritics restoration methods do not tolerate other typos, but classical spellcheckers also cannot deal adequately with all the diacritics missing.In this work, we tackle both problems at once by employing the newly-developed universal ByT5 byte-level seq2seq transformer model that requires no language-specific model structures. For a comparison, we perform diacritics restoration on benchmark datasets of 12 languages, with the addition of Lithuanian. The experimental investigation proves that our approach is able to achieve results (>98%) comparable to the previous state-of-the-art, despite being trained less and on fewer data. Our approach is also able to restore diacritics in words not seen during training with >76% accuracy. Our simultaneous diacritics restoration and typos correction approach reaches >94% alpha-word accuracy on the 13 languages. It has no direct competitors and strongly outperforms classical spell-checking or dictionary-based approaches. We also demonstrate all the accuracies to further improve with more training. Taken together, this shows the great real-world application potential of our suggested methods to more data, languages, and error classes