## About

117

Publications

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Introduction

Tomasz Górecki received the M.Sc. degree in mathematics from the Faculty of Mathematics and Computer Science of the Adam Mickiewicz University in Poznań in 2001. There, in 2005, he obtained the Ph.D. degree. Currently he is a professor at this University. His research interests include machine learning, times series classification and data mining.

Additional affiliations

October 2018 - present

August 2015 - May 2016

October 2005 - September 2018

Education

October 1996 - June 2001

October 1996 - June 2000

## Publications

Publications (117)

As injury prevention in football is one of the main aspects of physical preparation, it has also become an important issue addressed by researchers and analysts. They use machine learning methods, rule-based decision systems, or statistical analysis, however, taking into account the complexity of injury prediction, the proposed methods still need t...

According to Maslach and Leiter, burnout syndrome consists of three elements: exhaustion, cynicism, and a sense of ineffectiveness experienced by individuals in the work environment. However, burnout does not only apply to professional activity but can also be experienced by students pursuing higher education. This is important because the conseque...

There is a lack of data on resources used and food produced at urban farms. This hampers attempts to quantify the environmental impacts of urban agriculture or craft policies for sustainable food production in cities. To address this gap, we used a citizen science approach to collect data from 72 urban agriculture sites, representing three types of...

The growing intensity and frequency of matches in professional football leagues are related to the increasing physical player load. An incorrect training model results in over- or undertraining, which is related to a raised probability of an injury. This research focuses on predicting non-contact lower body injuries coming from over- or undertraini...

Classifieds provide many challenges for recommendation methods, due to the limited information regarding users and items. In this paper, we explore recommendation methods for classifieds using the example of OLX Jobs. The goal of the paper is to benchmark different recommendation methods for jobs classifieds in order to improve advertisements' conv...

The aim was to present the results of the valorization of the fiber content in the stem in the collection of Linum usitatissimum L. genetic resources. The research material comprised 79 flax accessions from 5 continents. Genotypes from Europe constituted the most numerous group − 77.2%. The field experiment was carried out at the experimental stati...

Collaborative filtering recommendation systems are traditionally trained in a batch manner and are designed to produce personalized recommendations for a large number of users at the same time. However, in many industrial use cases, it is reasonable to produce recommendations in real time, taking account of very recent user interactions. In this wo...

Genetic resources of flax from different geographical regions have been gathered in Poland since the 1930s. The aim of the research was to evaluate morphological and agricultural traits of 20 flax accessions, to determine the ranges of variability, and to develop the results in the form required for International Flax Database (IFDB) development. O...

The COVID-19 pandemic, as an external factor, quite strongly disrupted the existing trends in the development of unemployment in the Polish-German borderland. The objective of the article is to analyse the resilience of Polish and German Local Administrative Units (LAU) to the COVID-19 pandemic. The authors hypothesised that large differences in un...

When selling goods abroad or bringing them into the country from foreign partners, we face the problem of delivery. The division of responsibilities related to this between the manufacturer and the recipient sometimes varies. In such a situation, it is reasonable to use the services of a forwarding company. Then a forwarding contract is concluded,...

Objectives
Many tinnitus subjects report problems with communication, in particular, difficulties with the intelligibility of speech when it is presented in the background of noise. The type of tinnitus (tone-like, noise, etc.), its location and range in the frequency domain, and the type and degree of accompanying hearing loss can affect speech in...

The flax and hemp genetic resources collection gathered by the IWNiRZ – PIB the Institute of Natural Fibres & Medicinal Plants – National Research Institute (iNNi R2) is very important for protection of biodiversity (http://www.biodiv. org). Presently, the flax collection of IWNiRZ Gene Bank comprises 829 accessions, including wild forms and landra...

The article presents a proposal for a research tool that might assess the ecological activity of municipalities, with particular emphasis on those that lie on national boundaries. With climate change, it has become necessary to take into account the principles of sustainable growth while maintaining high living standards in the long term. Systemati...

This article discusses the results of research conducted in the Polish-German borderland region regarding
the ecological maturity of municipalities in 2020. Our main thesis is that the ecological strength of
municipalities lies in the diversity of approaches taken towards solving problems related to environmental
protection, and in the continuous a...

Green smart cities. Analiza aktywności ekologicznej gmin na pograniczu polsko-niemieckim Wstęp Zmiany klimatu wymuszają na gminach długofalowe działania strategiczne, które będą służyć wzmocnieniu zrównoważonego rozwoju i poprawie tych słabych stron rozwoju gmin, które związane są z gospodarką wodną, odpadami, zanieczyszczeniem powietrza, sprawami...

The aim of the study was to analyse the quality of soil in urban allotment gardens in the context of the production of home-grown vegetables. The study was conducted on six allotment gardens (31 individual plots) in Gorzów Wielkopolski, a medium-sized Polish city with an average level of industrialisation. The following soil characteristics were an...

The idea of a smart city is widely discussed in literature but is associated to a lesser extent with the idea of mov-ing towards a green smart city. Authors debate the critique of this type of approach and are of the opinion that climate change forces the construction of green models Like businesses, municipalities must be systematically assessed t...

The ecological activity of communes can be a very important element in increasing their
attractiveness, for example in terms of tourism, economy, as a place to invest. Modern possibilities
of digital technologies allow the use of intelligent solutions and implementation of many economic
and social demands from a perspective of, for example, environ...

In this paper, measures of mutual independence of many-vector random processes were defined. Based on these measures, permutation tests of mutual independence of these random processes were also given. The properties of the described methods were presented using simulation studies for univariate and multivariate processes.

The aim of this study was to evaluate and compare potential of different optical spectroscopic techniques for quality assessment of apple juices. The calibration partial least squares (PLS) regression models were developed and optimized for determination of quality parameters of apple juice non-destructively from the NIR spectra of fruit or directl...

The paper presents a novel method of finding a fragment in a long temporal sequence similar to the set of shorter sequences. We are the first to propose an algorithm for such a search that does not rely on computing the average sequence from query examples. Instead, we use query examples as is, utilizing all of them simultaneously. The introduced m...

This article discusses the results of research conducted in the Polish-German borderland region regarding the ecological maturity of municipalities in 2020. Our main thesis is that the ecological strength of municipalities lies in the diversity of approaches taken towards solving problems related to environmental protection, and in the continuous a...

New variable selection method is considered in the setting of classification with multivariate functional data (Ramsay and Silverman, Functional data analysis, 2005). The variable selection is a dimensionality reduction method which leads to replace the whole vector process, with a low-dimensional vector still giving a comparable classification err...

The article presents a proposal for a research tool that might assess the ecological activity of municipalities, with particular emphasis on those that lie on national boundaries. With climate change, it has become necessary to take into account the principles of sustainable growth while maintaining high living standards in the long term. Systemati...

The topic presented in this article fits within what may be broadly understood as issues of sustainable and intelligent local development. The article presents the concept of a “green smart city” model, which may become a new development paradigm for municipalities. The concept of eco-transformation was introduced in relation to the “green smart ci...

Sewage sludge, the most important by-product of biological wastewater treatment, is considered an important source of secondary pollution in environments. Simultaneously, sewage sludge is rich in nutrients and organic matter, therefore it is proposed for natural use. However, before such an application, sewage sludge should be properly prepared, so...

There is a growing need to analyze data sets characterized by several sets of variables observed on the same set of individuals. Such complex data structures are known as multiblock (or multiple-set) data sets. Multi-block data sets are encountered in diverse fields including bioinformatics, chemometrics, food analysis, etc. Generalized Canonical C...

The paper is concerned with testing normality in samples of curves and error curves estimated from functional regression models. We propose a general paradigm based on the application of multivariate normality tests to vectors of functional principal components scores. We examine finite sample performance of a number of such tests and select the be...

In the case of vector data, Gretton et al.( Algorithmic learning theory.Springer, Berlin, pp 63-77, 2005) defined Hilbert-Schmidt independence criterion, and next Cortes et al. (J.Mach Learn Res 13:795-828, 2012) introduced concept of the centered kernel target alignment (KTA). In this paper we generalize these mesures of dependence to the case of...

The aim of this study was to test the usability of fluorescence spectroscopy to evaluate the stability of cold-pressed rapeseed oil during storage. Freshly-pressed rapeseed oil was stored in colorless and green glass bottles exposed to light, and in darkness for a period of 6 months. The quality deterioration of oils was evaluated on the basis of s...

The aim of this study was to evaluate the influence of intrinsic product characteristics and extrinsic packaging-related factors on the food quality perception. Sensory and visual attention methods were used to study how consumers perceive the quality of commercial apple juices from four product categories: clear juices from concentrate, cloudy jui...

In the past two decades, interest in the area of time series has soared and many distance measures for time series have been proposed. The problem of pairwise similarity of time series is based on the underlying distance measure (which is not necessarily metric or even dissimilarity measure) and is common in many time series areas. To the best of o...

The relationship between two sets of variables can be defined in multiple ways. Although the problem in case of multivariate data has been already described in the literature in a comprehensive way, there is still a need to investigate relationships between multivariate functional data. At the moment we know how to compute functional ρV coefficient...

Functional data, i.e., observations represented by curves or functions, frequently arise in various fields. The theory and practice of statistical methods for such data is referred to as functional data analysis (FDA) which is one of major research fields in statistics. The practical use of FDA methods is made possible thanks to availability of spe...

A new variable selection method is considered in the setting of classification with multivariate functional data (Ramsay and Silverman (2005)). The variable selection is a dimensionality reduction method which leads to replace the whole vector process, with a low-dimensional vector still giving a comparable classification error. Various classifiers...

A key component of many types of time series classification methods is an appropriate dissimilarity measure. Elastic measures like DTW, LCS, ERP and EDR are methods that have long been known in the time series community. The methods have flourished, particularly in the last decade, and have been applied to many real problems in a variety of branche...

This paper presents a simple but general and effective method to debug the output of machine learning (ML) supervised models, including neural networks. The algorithm looks for features that lower the evaluation metric in such a way that it cannot be ascribed to chance (as measured by their p-values). Using this method – implemented as GEval tool –...

The paper is devoted to examining the dependence between the two groups of the characteristics : infrastructure and market size in European countries in 2008-2015. This dependence is measured by four coefficients: rho-vector, distance correlation(dCov), Hilbert-schmidt Independence Criterion (HSIC) and Kernel Target Alignment (KTA).

Data in the form of a continuous vector function on a given interval are referred to as multivariate functional data. These data are treated as realizations of multivariate random processes. The paper is devoted to three statistical dimension reduction techniques for multivariate data. For the first one, principal components analysis, the authors p...

We develop tests of normality for time series of functions. The tests are related to the commonly used Jarque–Bera test. The assumption of normality has played an important role in many methodological and theoretical developments in the field of functional data analysis. Yet, no inferential procedures to verify it have been proposed so far, even fo...

In practice, it often happens that there are a number of classification methods. We are not able to clearly determine which method is optimal. We propose a combined method that allows us to consolidate information from multiple sources in a better classifier. Stacked regression (SR) is a method for forming linear combinations of different classifie...

In practice, it often happens that there are a number of classification methods. We are not able to clearly determine which method is optimal. We propose a combined method that allows us to consolidate information from multiple sources in a better classifier. Stacked regression (SR) is a method for forming linear combinations of different classifie...

The relationship between two sets of real variables defined for the same individuals can be evaluated by few different correlation coefficients. For the functional data we have only one important tool: the canonical correlations. It is not immediately straightforward to extend other similar measures to the context of functional data analysis. In th...

In the domain of time series, different dissimilarity measures are applied for comparing sequences, the most successful ones being based on dynamic programming. Such measures include Longest Common SubSequence (LCSS) and Dynamic Time Warping (DTW). In this paper, a novel method is proposed to measure the dissimilarity of time series. We propose a p...

Many time series exhibit changes both in level and in variability. Generally, it is more important to detect a change in the level, and changing or smoothly evolving variability can confound existing tests. This paper develops a framework for testing for shifts in the level of a series which accommodates the possibility of changing variability. The...

Functional data are being observed frequently in many scientific fields, and therefore most of the standard statistical methods are being adapted for functional data. The multivariate analysis of variance problem for functional data is considered. It seems to be of practical interest similarly as the one-way analysis of variance for such data. For...

Currently a wide range of differently processed apple juices is available on the market. In this study the quality of commercial apple juices from four product categories was evaluated on the basis of their chemical profiles (total soluble solids - TSS, pH, titratable acidity - TA, ratio of soluble solids to acidity - TSS/TA, sugars, total phenolic...

The relationship between two sets of real variables defined for the same individuals can be evaluated by a few different correlation coefficients. For the functional data we have one important tool: canonical correlations. It is not immediately straightforward to extend other similar measures to the context of functional data analysis. In this work...

The relationship between two sets of real variables defined for the same individuals can be evaluated by a few different correlation coefficients. For the functional data we have one important tool: canonical correlations. It is not immediately straightforward to extend other similar measures to the context of functional data analysis. In this work...

Multivariate functional data
analysis
is an effective approach to dealing with multivariate and complex data. These data are treated as realizations of multivariate random processes; the objects are represented by functions. In this paper we discuss different types of regression model: linear and logistic. Various methods of representing functional...

The physicochemical (color, turbidity, total soluble solids, sucrose, d ‐glucose and d ‐fructose content, pH, acidity, total phenolic content and antioxidant activity) and sensory quality and consumer perception of differently processed clear and cloudy commercial apple juices were studied. Among eight studied juices, freshly squeezed juices were l...

Linear Discriminant Analysis (LDA) and the related Fisher's linear discriminant are very important techniques used for classification and for dimensionality reduction. A certain complication occurs in applying these methods to real data. We have to estimate the class means and common covariance matrix, which are not known. A problem arises if the n...

The relationship between two sets of real variables defined for the same individuals can be evaluated by a few different correlation coefficients. For the functional data we have one important tool: canonical correlations. It is not immediately straightforward to extend other similar measures to the context of functional data analysis. In this work...

Celem badań była ocena motywów wyboru produktów
spożywczych przez konsumentów soków. Badania
pilotażowe przeprowadzono na grupie 96 konsumentów soków,
wykorzystując kwestionariusz wyboru żywności (Food
Choice Questionnaire). Narzędzie to umożliwia systematyczny
pomiar istotności różnych motywów wyboru żywności.
Dla uzyskanych danych przeprowadzono...

As no single classification method outperforms other classification methods under all circumstances, decision-makers may solve a classification problem using several classification methods and examine their performance for classification purposes in the learning set. Based on this performance, better classification methods might be adopted and poor...

Data in the form of a continuous vector function on a given interval are referred to as multivariate functional data. These data are treated as realizations of multivariate random processes. We use multivariate functional regression techniques for the classification of multivariate functional data. The approaches discussed are illustrated with an a...

Data in the form of a continuous vector function on a given interval are referred to as multivariate functional data. These data are treated as realizations of multivariate random processes. We use multivariate functional regression techniques for the classification of multivariate functional data. The approaches discussed are illustrated with an a...

In practice, it often happens that we have a number of base methods of classification. We are not able to clearly determine which method is optimal in the sense of the smallest error rate. Then we have a combined method that allows us to consolidate information from multiple sources in a better classifier. I propose a different approach, a sequenti...

In this paper, some new tests based on the idea of the B-spline test (Shen and Faraway in Stat Sin 14:1239-1257, 2004) for the one-way ANOVA problem for functional data are proposed. Eleven existing tests for this problem are also reviewed. Exhaustive simulation studies are presented to compare all of the tests considered. The simulations are based...

Multivariate time series (MTS) data are widely used in a very broad range of fields, including medicine, finance, multimedia and engineering. In this paper a new approach for MTS classification, using a parametric derivative dynamic time warping distance, is proposed. Our approach combines two distances: the DTW distance between MTS and the DTW dis...

Over recent years the popularity of time series has soared. Given the widespread use of modern information technology, a large number of time series may be collected. As a consequence there has been a dramatic increase in the amount of interest in querying and mining such data. A vital component in many types of time series analyses is the choice o...

In this article there is proposed a new two-parametrical variant of the gravitational classification method. We use the general idea of objects' behavior in a gravity field. Classification depends on a test object's motion in a gravity field of training points. To solve this motion problem, we use a simulation method. This classifier is compared to...

In our previous work, we developed a new distance function based on a derivative and showed that our algorithm is effective. In contrast to well-known measures from the literature, our approach considers the general shape of a time series rather than standard distance of function (value) comparison. The new distance was used in classification with...

In this article we propose a new method of construction of discriminant coordinates and their kernel variant based on the regularization (ridge regression). Moreover, we compare the case of discriminant coordinates, functional discriminant coordinates and the kernel version of functional discriminant coordinates on 20 data sets from a wide variety...

A new type of discriminant space for functional data is presented, combining the advantages of a functional discriminant coordinate space and a functional principal component space. In order to provide a comprehensive comparison, we conducted a set of experiments, testing effectiveness on 35 functional data sets (time series). Experiments show that...

In classical data analysis, objects are characterized by many features observed at one point of time. We would like to present them graphically, to see their configuration, eliminate outlying observations, observe relationships between them or to classify them. In recent years methods for representing data by functions have received much attention....

The aim of this paper is to present a statistical methodology to assess patterns of cultivars' adaptive response to agricultural environments (agro-ecosystems) on the basis of complete Genotype x Crop Management x Location x Year (GxMxLxY) data obtained from 3-year multi-location two-factor trials conducted within the framework of the Polish post-r...

The Linear Discriminant Analysis (LDA) technique is an important and well-developed area of classification, and to date many linear (and also nonlinear) discrimination methods have been put forward. A complication in applying LDA to real data occurs when the number of features exceeds that of observations. In this case, the covariance estimates do...

The article describes the use of functional GDP principal components analysis from the exploratory point of view. This analysis is designed to show the variation in the entire sample, not only discrete observations. This is a technique that is often used as an introduction (e.g., dimensionality reduction and data visualization) for further analysis...

In this article, a sequential correction of two linear methods: linear discriminant analysis (LDA) and perceptron is proposed. This correction relies on sequential joining of additional features on which the classifier is trained. These new features are posterior probabilities determined by a basic classification method such as LDA and perceptron....

Over recent years the popularity of time series has soared. Given the widespread use of modern information technology, a large number of time series may be collected during business, medical or biological operations, for example. As a consequence there has been a dramatic increase in the amount of interest in querying and mining such data, which in...

Artykuł ma charakter teoretyczno-empiryczny. W opracowaniu zaprezentowano metodologię badań procesów konwergencji oraz skupiono uwagę na jednej z metod analizy konwergencji regionalnej za pomocą łańcuchów Markowa. W końcowej części artykułu zaprezentowano wyniki analizy łańcuchów Markowa na przykładzie polskich podregionów w latach 1999-2008. Do ce...

Abstract. The analysis of concentration and specialization processes in Poland according to NUTS- 2 in 1996-2008. The empirical and and theoretial research is presented in the given article. Authors synthetically introduced statistical methods reviewing processes of concentration and specialization. A level of concentration and specialization (NUTS...

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