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With increasing competition in the global education sphere, the only way to a decent functioning of the Higher Educational Institutions of Ukraine — to match the high international standards. This cannot be achieved without active international activities aimed at the development of international educational programs. In the Admiral Makarov National University of Shipbuilding, Mykolayiv successfully...
Robust detection of the smallest circulating cerebral microemboli is an efficient way of preventing cerebrovascular accidents (CVA). Transcranial Doppler ultrasound is widely considered as the most convenient system for the detection of microemboli. Standard detection used in commercial device is achieved through the whole Doppler energy spectrum where constant empirical thresholds are implemented...
Deep Neural Networks (DNNs) have emerged as a core tool for machine learning. The computations performed during DNN training and inference are dominated by operations on the weight matrices describing the DNN. As DNNs incorporate more stages and more nodes per stage, these weight matrices may be required to be sparse because of memory limitations. The GraphBLAS.org math library standard was developed...
Obtaining ultrafast images using steered plane wave (PW) imaging remains a challenge due to the trade-off between image quality and frame rate. PW imaging indeed relies on compounding in order to preserve a good image quality, usually using multiple successive emissions, which in turn yields a decrease of the frame rate. As opposed to this classical approach, we propose a new strategy to reduce the...
Robust detection of the smallest circulating cerebral micro-emboli is an efficient way of preventing Cerebrovascular Accidents. Transcranial Doppler ultrasound is widely considered as the most convenient system for the detection of micro-emboli. Commercially realized standard detection is achieved through the whole Doppler energy spectrum where constant empirical thresholds are implemented. In this...
Echocardiograms are acquired from standard views to ensure correct assessment of cardiac function. There is an increasing use of quantitative tools where specific views are required. Further, non-expert users of echocardiography are increasing, and thus a need for quality assurance during imaging. The aim of this project is to develop automatic and robust real-time classification of cardiac views...
In this article, we develop two visual impression models: recognition model and generalization model to simulate the cognition process of human visual systems. We show how the visual impression learned with a deep neural network can be efficiently transferred to other visual recognition tasks. By reusing the hidden layers trained in an unsupervised way, we show that we can largely reduce the number...
Meaningless identifiers as well as inconsistent use of identifiers in the source code might hinder code readability and result in increased software maintenance efforts. Over the past years, effort has been devoted to promoting a consistent usage of identifiers across different parts of a system through approaches exploiting static code analysis and Natural Language Processing (NLP). These techniques...
In this paper we study the problem of key phrase extraction from short texts written in Russian. As texts we consider messages posted on Internet car forums related to the purchase or repair of cars. The main assumption made is: the construction of lists of stop words for key phrase extraction can be effective if performed on the basis of a small, expert-marked collection. The results show that even...
Discusses the concept of quality of education, highlights the criteria and indicators of assessing its quality in the framework of theoretical and methodological research. Highlights the main requirements to level of preparation of graduates.
The state-of-the art education system should be in time for the knowledge-intensive technologies, that are developing with a high pace and be as mobile and effective as possible. The development of science-intensive technologies is developing with a tremendous pace, so the knowledge obtained in the university is quickly becoming obsolete, therefore the modernization of equipment should go in synchronism...
Problems of new international standards on projects and programs managers competencies implementation were considered, “learning through practice” approach for master's programs in project management was proposed and tested. Interaction model of such projects on the basis of e-learning, that joint to IT business laboratories and using the international system of business incubators to improve professional...
Spectral band power features are one of the most widely used features in the studies of electroencephalogram (EEG)-based emotion recognition. The power spectral density of EEG signals is partitioned into different bands such as delta, theta, alpha and beta band etc. Though based on neuroscientific findings, the partition of frequency bands is somewhat on an ad-hoc basis, and the definition of frequency...
The City4age project combines Internet of Things, data from smart cities and powerful schemes for sending messages, to develop sustainable prevention of MCI/Frailty in aging population. To do so, it combines detection (for early spotting of symptoms) and intervention (for suggesting positive changes of behavior).
This paper carries out a large dimensional analysis of the standard regularized quadratic discriminant analysis (QDA) classifier designed on the assumption that data arise from a Gaussian mixture model. The analysis relies on fundamental results from random matrix theory (RMT) when both the number of features and the cardinality of the training data within each class grow large at the same pace. Under...
Paraphrase Detection is the task of examining if two sentences convey the same meaning or not. Here, in this paper, we have chosen a sentence embedding by unsupervised RAE vectors for capturing syntactic as well as semantic information. The RAEs learn features from the nodes of the parse tree and chunk information along with unsupervised word embedding. These learnt features are used for measuring...
The electroencephalography (EEG) data records vast amounts of human cerebral activity yet is still reviewed primarily by human readers. Most of the times, the data is contaminated with non-cerebral originated signals, called artifacts, which could be very difficult to visually detect and, undiscovered, could damage the neural information analysis. The purpose of our work is to detect the artifacts...
In this paper, we present a new method for detecting professional skills (as noun phrases) from resumes written in natural language. The proposed method uses an ontology of skills, the Wikipedia encyclopedia, and a set of standard multi word part-of-speech patterns in order to detect the professional skills. First, the method checks to see if there are, in the text of the resumes, skills that are...
The standard LSTM recurrent neural networks while very powerful in long-range dependency sequence applications have highly complex structure and relatively large (adaptive) parameters. In this work, we present empirical comparison between the standard LSTM recurrent neural network architecture and three new parameter-reduced variants obtained by eliminating combinations of the input signal, bias,...
Epilepsy is defined as a collection of symptoms and clinical signs are emerging due to intermittent brain dysfunction, which occur due to loose or excessive abnormal electrical discharges of neurons in paroxysmal with various etiologies. In this article the implemented software detection of disease epilepsy, characteristics which will represent in the detection of epilepsy and not epilepsy are from...
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