Krzysztof Dyczkowski

• Ph.D., D.Sc.
• Professor (Associate) at Adam Mickiewicz University in Poznań

This paper introduces an integrated pipeline for detecting, classifying, and tracking key objects within soccer match footage. Our research uses datasets from KKS Lech Poznań, SoccerDB, and SoccerNet, considering various stadium environments and technical conditions, such as equipment quality and recording clarity. These factors mirror the real-wor...

This study introduces an innovative interval-valued fuzzy inference system (IFIS) integrated with federated learning (FL) to enhance posture detection, with a particular emphasis on fall detection for the elderly. Our methodology significantly advances the accuracy of fall detection systems by addressing key challenges in existing technologies, suc...

Quantifying defensive actions, which offensive indicators have historically overshadowed, is challenging in football analysis. This study presents a novel approach using XGBoost and neural networks to evaluate defensive play using On-Ball Value (OBV), Valuing Actions by Estimating Probabilities (VAEP), and eXpected Threat (xT) indicators. The propo...

This paper presents a novel framework for integrating artificial empathy into robot swarms to improve communication and cooperation. The proposed model uses fuzzy state vectors to represent the knowledge and environment of individual agents, accommodating uncertainties in the real world. By utilizing similarity measures, the model compares states,...

This paper introduces an innovative framework for the integration of artificial empathy into robot swarms to enhance communication and cooperation. The proposed model relies on fuzzy state vectors to represent the knowledge and environment of individual agents, accommodating uncertainties in the real world. Utilizing similarity measures, the model...

Data is the new oil of the digital economy. Many business organizations are gathering and using their data to optimize their business performance. However, in some cases, an individual organization may not have a sufficient amount of data or data quality to build a well-performing model, especially in a dynamic environment. In some cases, the compa...

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...

The article presents a fuzzy system which has been used in an adaptive e-learning content on effective cooperation with a Chinese business partner. The content adapts to the identified level of the student's intercultural competence and directs them to the specified education path. During the decision-making process, six variables are taken into ac...

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...

This paper presents the application of optimistic and pessimistic similarity measures of interval-valued fuzzy sets (IVFS) to the problem of selecting relevant attributes as input to classification algorithms. The paper presents a modified IV-Relief algorithm using the aforementioned measures. The theoretical considerations are supported by the ana...

Recommendation systems play an important role in e-commerce turnover by presenting personalized recommendations. Due to the vast amount of marketing content online, users are less susceptible to these suggestions. In addition to the accuracy of a recommendation, its presentation, layout, and other visual aspects can improve its effectiveness. This...

We consider the problem of measuring the degree of inclusion and similarity between interval-valued fuzzy sets. We propose a new idea for constructing indicators of inclusion and similarity measures based on the precedence relation, aggregation and uncertainty assessment. Furthermore, we examine selected properties of the suggested measures and the...

In this contribution the concept how to solve the problem of comparability in the interval-valued fuzzy setting and its application in medical diagnosis is presented. Especially, we consider comparability of interval-valued fuzzy sets cardinality, where order of its elements is most important. We propose an algorithm for comparing interval-valued f...

This chapter details the implementation of the intelligent decision support system OvaExpert for the diagnosis of ovarian tumors. The individual diagnostic modules are discussed and an analysis of the efficacy of the decision-making methods is presented.

In this Chapter we introduce not fully determined fuzzy sets i.e. interval-valued fuzzy sets and Intuitionistic Atanassov’s fuzzy sets. We defined notions and methods describing cardinalities of such sets together with multiple examples. We presented methods for their application in decision-making algorithms with uncertain information. The Chapter...

In this chapter we present the basics of medical decision support systems, indicating their types and elements they should include. We also introduce the basic information on ovarian tumors as well as existing models supporting their differentiation. The techniques used to evaluate the efficacy of prediction methods are also discussed. We point to...

In this chapter we presented basic notions and definitions constituting the basis of fuzzy set theory. Particular attention has been paid to cardinality of fuzzy sets, and we presented various approaches to defining it. We also introduced the notion of aggregation operator and presented the most important types of aggregators.

In the paper we describe a computer system that store and process uncertain data in such a way as to be able to obtain information essential to make an effective diagnosis while also indicating the uncertainty level of that diagnosis. We consider the problem of incompleteness and imprecision of medical data and discuss some issues connected with su...

This article presents a new approach to making decisions when information, possibly incomplete, is provided by many sources. The proposed method is based on IVFS scalar cardinality (sigma f-count). First a general algorithm is introduced, and next an application in supporting medical decisions in ovarian tumor differentiation (based on multiple dia...

This book discusses computer-supported medical diagnosis with a particular focus on ovarian tumor diagnosis – since ovarian cancer is difficult to diagnose and has high mortality rates, especially in Central and Eastern Europe. It presents the theoretical foundations (both medical and mathematical) of the intelligent OvaExpert system, which support...

In this paper we present OvaExpert, an intelligent system for ovarian tumor diagnosis. We give an overview of its features and main design assumptions. As a theoretical framework the system uses fuzzy set theory and other soft computing techniques. This makes it possible to handle uncertainty and incompleteness of the data, which is a unique featur...

In the paper we present OvaExpert - a unique tool for supporting gynecologists in the diagnosis of ovarian tumor, combining classical diagnostic scales with modern methods of machine learning and soft computing. A distinguishing feature of the system is its comprehensiveness, which makes it usable at any stage of a diagnostic process. We gather all...

Objectives: The external, two-center validation of the IOTA ADNEX model for differential diagnosis of adnexal tumors. Methods: A total of 204 patients with adnexal masses (134 benign and 70 malignant) treated at the Division of Gynecologic Surgery, Poznan University of Medical Sciences, Poland (Center I), and 123 patients (89 benign and 34 maligna...

This paper presents an approach to making accurate and high-quality decisions under incomplete information. Our comprehensive approach includes interval modeling of incomplete data, uncertaintification of classical models and aggregation of incomplete results. We conducted a thorough evaluation of our approach using medical data for ovarian tumor d...

The aim of the present paper is to give an overview of the investigation of the phonic articulatory systems of Polish on the basis of the detailed articulatory descriptions existent in phonetic literature and with the use computational tools. First the theoretical foundations of the phonetic grammar are briefly introduced, then the main problem of...

In the paper we present experimental results on the problem of an effective decision making on incomplete data. In order to investigate this problem we examined a variety of interval aggregation methods. Exemplary results are based on a medical diagnosis support system. Our research shows that an application of the aggregation in this problem leads...

We state a problem concerning how to make an effective and proper decision in the presence of data incompleteness. As an example we consider a medical diagnostic system where the problem of missing data is commonly encountered. We propose and evaluate an approach that makes it possible to reduce the influence of missing data on the final result and...

In measurement systems one of the components affecting its variation is a human factor. Man-as a process operator-measures or rates the product. Since his decisions may have significant impact on the customer satisfaction, his reliability and usefulness for the measuring tasks should be evaluated. This article describes authors proposal for a new m...

This article describes the fundamentals of an intelligent decision support system for the diagnosis of ovarian tumors. The system is designed to support diagnosis by less experienced gynecologists, and to gather data for continuous improvement of the quality of diagnosis. The theoretical basis for the construction of the system is the IF-sets frame...

In this paper we propose a new method for classifying uncertain data, modeled as interval-valued fuzzy sets. We develop the notion of an interval-valued prototype-based fuzzy classifier, with the idea of preserving full information including the uncertainty factor about data during the classification process. To this end, the classifier was based o...

Artykuł opisuje rozważania na temat sposobów wyznaczania i interpretacji współczynników typu Kappa w szacowaniu poziomu zgodności ocen operatorów i eksperta w kontroli wizualnej. Autorzy opisują swoje obserwacje i doświadczenia z badań prowadzonych w przedsiębiorstwach produkcyjnych, wskazują na problemy i wyzwania. Autorzy zauważają, że współczynn...

Objectives The aim of this study was to externally validate the diagnostic performance of the International Ovarian Tumor Analysis logistic regression models (LR1 and LR2, 2005) and other popular prognostic models including the Timmerman logistic regression model (1999), the Alcazar model (2003), the risk of malignancy index (RMI, 1990), and the ri...

In this paper we consider applications of bipolarity in modelling problems encountered in ovarian tumor diagnosis. We focus on imprecision of data obtained by a gynaecologist during examinations. We also present a wide range of predictive diagnostic models and propose a new idea for their improvement.

Streszczenie: W pracy przedstawiono przewidywane kierunki rozwoju obszaru analizy systemów pomiarowych dla oceny alternatywnej. Wskazano na możliwość zastosowania w tego typu ocenie elementów logiki rozmytej. W dalszej części pracy zaprezentowano podstawowe metody i procedury stosowane w analizie systemów pomiarowych, a także wskazano na aspekty ic...

This paper is devoted to the problem of measuring similarity between pieces of uncertain (incomplete) information in the framework of I-fuzzy set theory (Atanassov's intuitionistic fuzzy sets and interval-valued fuzzy sets). We propose a way of determining an interval-valued similarity measure of I-fuzzy sets that preserves information about the op...

The article presents a system of election recommendation in which both candidate’s and voter’s preferences can be described in an imprecise way. The model of the system is based on IF-set theory which can express hesitation or lack of knowledge. Similarity measures of IF-sets and linguistic quantifiers are used in the decision-making process.

The article presents a system of election recommendation in which both candidate's and voter's preferences can be described in an imprecise way. The model of the system is based on IF-set theory which can express hesitation or lack of knowledge. Similarity measures of IF-sets and linguistic quantifiers are used in the decision-making process.

This paper presents a computer system that de-tects traffic signs in the input video stream and tries to recognize them using a knowledge base. Detection is done in the HSB colorspace using fuzzy color segmentation. Afterwards, detected segments are analyzed by a fuzzy rule-based system which checks whether a pair of segments represents the same si...

This article presents an outline of a research project which deals with visual speech recognition based on the movements of the lips. In particular, for comparison of lip shapes, we propose a similarity/disimilarity measure, based on IF-Sets. A~method of encoding lip shapes is presented and a comparison of numerical representations of lips based on...

This paper is an attempt to apply a similarity/disimilarity measure based on Atanassov IF-Sets to the comparison of lip shapes. A method of encoding lip shapes is presented and a comparison of numerical representations of lips based on the applied measure type is suggested.

The aim of this paper is to indicate problems of imprecision in the infor-mation appearing in phonetics particularly in articulatory description of speech sounds of a given language. We like to show how fuzzy sets and interval-valued fuzzy sets can shed new light on the description of pho-netic phenomena.

The aim of this paper is to present the notion of a hierarchy of articulatory dimensions and its application in phonetic typology. To calculate the hierarchies a computer application was designed, and preliminary counts were carried out on the phonetic repertories of Chinese, Hindi and Polish. The theoretical foundation of the calculus is based on...

The aim of the paper is to present an application supporting language analysis within the framework of the phonetic grammar. The notion of the phonetic grammar has been concisely introduced and the basic potential of the application and the algorithms employed in it are briefly discussed. The application is to enable a uniform description and a com...

The aim of this paper is to present an application supporting language analysis within the framework of phonetic grammar. The notion of phonetic grammar is concisely introduced and the basic potential of the application and the algorithms employed in it are briefly discussed. The application is intended to enable a uniform description and comparati...

Finding sequential patterns is one of imp ortant issues in data mining. This paper deals with linguistic (fuzzy) sequential patterns. The existing algorithms for discovering such patterns do involve usual sigma counts of fuzzy sets as measure of supp ort. Unfortunately, a well-known side effect is then an undesirable cumulation of small membership...

There are three basic types of triangular norm-based generalized cardinals of fuzzy sets, namely generalized FGCounts, FLCounts and FECounts. All of them are convex fuzzy sets of usual cardinal numbers. Our attention will be focused on generalized FECounts. If nonstrict Archimedean triangular norms are involved, generalized FECounts of many fuzzy s...

Fuzzy sets with triangular norms and their cardinalities understood as convex fuzzy sets pf usual cardinal numbers are subject of this paper. It appears that if nonstrict Archimedean triangular norms are involved, some fuzzy sets become totally dissimilar to any set of any cardinality. In other words, they become singular with respect to cardinalit...