Patient-adapted and inter-patient ecg classification using neural network and gradient boosting

Heart disease diagnosis is an important non-invasive technique. Therefore, there exists an effort to increase the accuracy of arrhythmia classification based on ECG signals. In this work, we present a novel approach of heart arrhythmia detection. The model consists of two parts. The first part extracts important features from raw ECG signal using Auto-Encoder Neural Network. Extracted features obtained by Auto-Encoder represent an input for the second part of the model, the Gradient Boosting and Feedforward Neural Network classifiers. For comparison purposes, we evaluated our approach by using MIT-BIH ECG database and also following recommendations of the Association for the Advancement of Medical Instrumentation (AAMI) for ECG class labeling. We divided our experiment into two scenarios. The first scenario represents the classification task for the patient-adapted paradigm and the second one was dedicated to the inter-patient paradigm. We compared the measured results to the state-of-the-art methods and it shows that our method outperforms the state-of-the art methods in the Ventricular Ectopic (VEB) class for both paradigms and Supraventricular Ectopic (SVEB) class in the inter-patient paradigm.Web of Science28325424

Enhancement of dronogram aid to visual interpretation of target objects via intuitionistic fuzzy hesitant sets

In this paper, we address the hesitant information in enhancement task often caused by differences in image contrast. Enhancement approaches generally use certain filters which generate artifacts or are unable to recover all the objects details in images. Typically, the contrast of an image quantifies a unique ratio between the amounts of black and white through a single pixel. However, contrast is better represented by a group of pix- els. We have proposed a novel image enhancement scheme based on intuitionistic hesi- tant fuzzy sets (IHFSs) for drone images (dronogram) to facilitate better interpretations of target objects. First, a given dronogram is divided into foreground and background areas based on an estimated threshold from which the proposed model measures the amount of black/white intensity levels. Next, we fuzzify both of them and determine the hesitant score indicated by the distance between the two areas for each point in the fuzzy plane. Finally, a hyperbolic operator is adopted for each membership grade to improve the pho- tographic quality leading to enhanced results via defuzzification. The proposed method is tested on a large drone image database. Results demonstrate better contrast enhancement, improved visual quality, and better recognition compared to the state-of-the-art methods.Web of Science500866

Prediction and evaluation of zero order entropy changes in grammar-based codes

The change of zero order entropy is studied over different strategies of grammar production rule selection. The two major rules are distinguished: transformations leaving the message size intact and substitution functions changing the message size. Relations for zero order entropy changes were derived for both cases and conditions under which the entropy decreases were described. In this article, several different greedy strategies reducing zero order entropy, as well as message sizes are summarized, and the new strategy MinEnt is proposed. The resulting evolution of the zero order entropy is compared with a strategy of selecting the most frequent digram used in the Re-Pair algorithm.Web of Science195art. no. 22

Clustering and closure coefficient based on k-CT components

Real-world networks contain many cliques since they are usually built from them. The analysis that goes behind the cliques is fundamental because it discovers the real structure of the network. This article proposed new high-order closed trail clustering and closure coefficients for evaluation of the network structure. These coefficients are able to describe the inner structure of the network concerning its randomized or organized behavior. Moreover, the coefficients can cluster networks with similar structures together. The experiments show that the coefficients are useful in both the local and global context.Web of Science810115210114

Cliques are bricks for k-CT graphs

Many real networks in biology, chemistry, industry, ecological systems, or social networks have an inherent structure of simplicial complexes reflecting many-body interactions. Over the past few decades, a variety of complex systems have been successfully described as networks whose links connect interacting pairs of nodes. Simplicial complexes capture the many-body interactions between two or more nodes and generalized network structures to allow us to go beyond the framework of pairwise interactions. Therefore, to analyze the topological and dynamic properties of simplicial complex networks, the closed trail metric is proposed here. In this article, we focus on the evolution of simplicial complex networks from clicks and k-CT graphs. This approach is used to describe the evolution of real simplicial complex networks. We conclude with a summary of composition k-CT graphs (glued graphs); their closed trail distances are in a specified range.Web of Science911art. no. 116

Automation of cleaning and ensembles for outliers detection in questionnaire data

This article is focused on the automatic detection of the corrupted or inappropriate responses in questionnaire data using unsupervised outliers detection. The questionnaire surveys are often used in psychology research to collect self-report data and their preprocessing takes a lot of manual effort. Unlike with numerical data where the distance-based outliers prevail, the records in questionnaires have to be assessed from various perspectives that do not relate so much. We identify the most frequent types of errors in questionnaires. For each of them, we suggest different outliers detection methods ranking the records with the usage of normalized scores. Considering the similarity between pairs of outlier scores (some are highly uncorrelated), we propose an ensemble based on the union of outliers detected by different methods. Our outlier detection framework consists of some well-known algorithms but we also propose novel approaches addressing the typical issues of questionnaires. The selected methods are based on distance, entropy, and probability. The experimental section describes the process of assembling the methods and selecting their parameters for the final model detecting significant outliers in the real-world HBSC dataset.Web of Science206art. no. 11780

Experimental analysis on dissimilarity metrics and sudden concept drift detection

International audienceLearning from non-stationary data presents several new challenges. Among them, a significant problem comes from the sudden changes in the incoming data distributions, the so-called concept drift. Several concept drift detection methods exist, generally based on distances between distributions, either arbitrarily selected or context-dependent. This paper presents a straightforward approach for detecting concept drift based on a weighted dissimilarity metric over posterior probabilities. We also evaluate the performance of three well-known dissimilarity metrics when used by the proposed approach. Experimental evaluation has been done over ten datasets with injected sudden drifts in a binary classification context. Our results first suggest choosing the Kullback-Leibler divergence, and second, they show that our drift detection procedure based on dissimilarity measures is pretty efficient

Behaviour associated with the presence of a school sports ground: Visual information for policy makers

The planning and development of sports infrastructure is a complex process that has a broad and long-term impact on health and well-being in communities. It involves many different stake- holders and usually requires significant public or private investments. Its framework is outlined by policies that define the general social goals of such development. To ensure the maximum alignment between the goals and the development activities, it is important to support the policy making process by high-quality information based on real-world data and presented in a clear and focused way. This work introduces a new pipeline of methods for processing and interpretation of data on physical activity and lifestyle in adolescents. The data is extracted from the Health Behaviour in School-aged Children (HBSC) study and analyzed by modern machine learning methods. We identify behavioural patterns associated with the presence and absence of a school sports ground in different sex and age groups of adolescent in the Czech Republic. The patterns are presented by concise graphical models that ease their use by stake- holders without expert knowledge in sociology, statistics, mathematical modelling, etc. They enable intuitive visual assessment of situation in different regions and highlight the specific similarities and differences among them. Together, the proposed methods contribute towards objective evidence-based policy making in sports management and development.Web of Science128art. no. 10615

Komprese dat blokovým tříděním

Import 20/04/2006Prezenční výpůjčkaVŠB - Technická univerzita Ostrava. Fakulta elektrotechniky a informatiky. Katedra (456) informatik

Proposal for modification of a part of a watercourse Hodoňovický náhon

Tato bakalářská práce se zabývá návrhem úpravy části vodního toku Hodoňovický náhon. V teoretické části bude čtenář seznámen se zájmovým územím, důvody návrhu úpravy ve vybrané lokalitě a teoretickými poznatky problematiky úpravy toku. V praktické části bude detailně zpracován vybraný úsek toku s hydrologickými výpočty a výkresovou dokumentací v programu AutoCAD. Na závěr bude shrnuto ekonomické zhodnocení navrhnuté úpravy.This bachelor's thesis deals with the design of a part of the watercourse Hodoňovický náhon. In the theoretical part, the reader will be introduced to the area of interest, theoretical knowledge of the issue of stream regulation and the reasons for the proposed regulation in the selected locality. In the practical part, a selected section of the flow will be processed in detail with hydrological calculations and drawing documentation in the AutoCAD program. The economic evaluation of the proposed modifications will be summarized at the end.546 - Katedra environmentálního inženýrstvívýborn