Adam Kiersztyn

Lublin University of Technology · Institute of Computer Science

The COVID-19 pandemic has affected almost every aspect of life. The patterns of interpersonal contacts, the ways of doing business and the methods of school education have changed. A significant part of worldwide business has migrated to the virtual world, and the global supply chains have been disrupted. On the other hand, this new situation creat...

This study considers a very important issue, which is the impact of preprocessing on model performance. On the example of data describing taxicab trips in New York City, a model predicting the average speed of a trip was built. The effectiveness of the obtained model was examined using relative error. The results were compared with the models obtai...

We show that if among the tested hypotheses the number of true hypotheses is not equal to the number of false hypotheses, then Neyman-Pearson theory of testing hypotheses does not warrant minimal epistemic reliability (the feature of driving to true conclusions more often than to false ones). We also argue that N-P does not protect from the possibl...

Ecological datasets often contain gaps, outliers or even incorrect data. Ignoring the problem of missing data can lead to reduction in the statistical power of the models used, estimation of biased parameters and incorrect conclusions about the phenomenon studied. In this study, using simulated and real ecological data (seven-year monitoring of off...

Nowadays, in the era of automation of ecological measurements, more and more often we are dealing with large data sets in which various unexpected anomalies may occur. Their detection is often crucial for a proper assessment of ecological trends and processes. Therefore, methods allowing for identification of anomalous data are especially important...

Anomaly detection is one of the most important problems of modern data science due to the threat to the security of information systems as well as their users. This applies in particular to logistic data which is used to predict costs, times, organization of travel routes, etc. Data anomalies may endanger the welfare and safety of transport users,...

Wraz z wprowadzeniem do nauki paradygmatu obliczeń ziarnistych, w szczególności ziaren informacji, sposób myślenia o danych stopniowo się zmieniał. Zarówno specjaliści, jak i naukowcy przestali skupiać się na samych rekordach pojedynczych danych, ale zaczęli patrzeć na analizowane dane w szerszym kontekście, bliższym ludzkiemu myśleniu. Ten rodzaj...

Estimating travel time is one of the most important processes in logistics as well as in everyday life. In particular, when it comes to transportation services, efficient time management can be a competitive advantage, not to mention customer satisfaction, which can be easily translated into business success. Therefore, in this study we analyze var...

Neyman and Pearson's theory of testing hypotheses does not warrant minimal epistemic reliability: the feature of driving to true conclusions more often than to false ones. The theory does not protect from the possible negative effects of the pragmatic value-laden unequal setting of error probabilities on the theory's epistemic reliability. Most imp...

Anomaly (outlier) detection is one of the most important problems of modern data analysis. The sources of anomalies are varying. They can be the results of database users' mistakes, operational errors or just missing values. The problem is very important because of the fast growth of large data sets. Therefore, in this study, we present detailed re...

The choice of electricity tariff directly affects the final cost of electricity for the consumer. The proper selection of the appropriate tariff may result in economically measurable benefits in the long term. It is essential to take into account the real rate of energy consumption depending on the time of day, week, etc. The aim of the publication...

The problem of finding anomalies (outliers) in databases is one of the most important issues in modern data analysis. One of the reasons is the occurrence of this issue in almost every type of database, including numerical, categorical, time, mixed, or graphic data. There are currently many methods often dedicated to specific data analysis. Finally...

Saaty’s analytic hierarchy process (AHP) is widely used in many decision-making problems such as a choice of alternatives, prioritization, or ranking. Despite being a valuable tool based on pairwise comparisons of a set of alternatives the method is strongly connected with numeric or linguistic descriptors of the preferences. This can form a limita...

Behavioral traits play a major role in successful adaptation of wildlife to urban conditions. However, there are few studies showing how urban conditions affect the social behavior of urban animals during their direct encounters. It is generally believed that the higher density of urban populations translates into increased aggression between indiv...

One of the most challenging problems of modern data mining and Computational Intelligence society has been the task of anomaly detection in large datasets, particularly containing mixed data, namely categorical, spatial, or spatio-temporal. In this study, we discuss various versions of the well-known Isolation Forest method as a efficient tool for...

In this paper, we examine whether N-P can be seen as principally satisfying, in a minimal sense, some general epistemic standards and how pragmatic value-laden uneven setting of error probabilities can influence it. Using the concept of predictive value it is shown that Neyman-Pearson's theory of testing hypothesis offers at least minimal epistemic...

In this study, we propose an approach based on the advanced fuzzy techniques such as Fuzzy C-Means and Fuzzy Cognitive Maps to cluster the birds species, based on the information of first arrival date, into more coherent and uniform groups. The birds are very suitable subject for modelling the climate changes. Very popular indicator to forecast bir...

One of the main challenges faced by people who use data from empirical research in their work is missing data. In many scientific disciplines and industries there are references to time series. The suitability of several methods to imputation of the missing data in the study of mutual links between the analysed time series have been presented and t...

The task of anomaly detection in data is one of the main challenges in data science because of the wide plethora of applications and despite a spectrum of available methods. Unfortunately, many of anomaly detection schemes are still imperfect i.e., they are not effective enough or act in a non-intuitive way or they are focused on a specific type of...

As a result of the widespread use of camera-traps, the analysis of the daily activity of animals based on field data has become a common practice, which is addressed in ecological studies. The more frequent consideration of this issue in ecological research, however, has not led to any advancement in the techniques of analysis of these activity pat...

Answers are still being sought to the question of how to plan cities to ensure good living conditions for humans while also protecting urban biodiversity. We asked what is the minimum city size that causes the depletion of wildlife biodiversity, and how quickly does this process develop? We summarized data for wild ground-dwelling small mammals (Ro...

Detecting and removing anomalies in the time series describing physical phenomena is a big challenge faced by scientists from many fields. The aim of the article is to present the assumptions of a tool for the detection of anomalies related to any issue. The proposed universal solution based on fuzzy logic and multicriteria can be applied to any ti...

The problem of aggregation of the classification results is one of the most important task in image recognition or decision-making theory. There are many approaches to solve this problem as well as many operators and algorithms proposed such as voting, scoring, averages, and more advanced ones. In this paper, we examine the well-known existing and...

The managers of the telecommunication infrastructure face the challenge of detecting and removing anomalies in the area of energy consumption. New technologies such as smart meters present new possibilities for the control and optimization of energy consumption. The aim of the article is to present the framework of a tool for the detection of anoma...

The managers of the telecommunication infrastructure face the challenge of detecting and removing anomalies in the area of energy consumption. New technologies such as smart meters present new possibilities for the control and optimization of energy consumption. The aim of the article is to present the framework of a tool for the detection of anoma...

- Application - Decision Support System for process monitoring, anomaly detection, diagnosis and optimization. - Fault detection in complex systems based on energy consumption patterns.

In this study, we propose linguistic descriptors-based approach to the problem of face identification realized by both humans and computers. This approach is motivated by an evident observation that linguistic descriptors offer an ability to formalize and exploit important pieces of knowledge describing human’s face. These entities are used by peop...

In this study, we develop a process of estimation of importance of features considered in face recognition by making use of the analytic hierarchy process (AHP). The AHP method of pairwise comparisons realized at three levels of hierarchy becomes crucial to realize a comprehensive weighting of cues so that sound estimates of weights associated with...

In this study, we introduce a recent multicriteria decision theory concept of a new, generalized form of Choquet integral function and its application, in particular to the problem of face classification based on the aggregation of classifiers. Such function may be constructed by a simple replacement of the product used under the Choquet integral s...

In this paper, we analyze the properties and performance of the Choquet integral and fuzzy measure, particularly \(\lambda \)–fuzzy measure in the context of an aggregation of classifiers based on various facial areas. The fuzzy measure and Choquet integral have been shown to be an efficient aggregation techniques. However, in practice reported so...

Local descriptors are widely used technique of feature extraction to obtain information about both local and global properties of an object. Here, we discuss an application of the Chain Code-Based Local Descriptor to face recognition by focusing on various datasets and considering different variants of this description method. We augment the generi...

Face recognition by computers in recent years has been a topic of intensive studies. In this problem, we witness several challenges: one has to cope with large data sets, solve problems of data extraction, and deal with poor quality of images caused by e.g., poor lighting of the subject. There have been a lot of algorithms and classifiers developed...

In this paper, we discuss an application of the linguistic descriptions obtained directly from experts’ and treated as the votes when characterizing facial images to carry out face classification. Despite various automated face recognition techniques, the expert’s opinion plays a pivotal role in making classification decisions when recognizing face...

Local descriptors have been one of the most intensively examined mechanisms of image analysis. In this paper, we propose a new chain code-based local descriptor. Unlike many other descriptors existing in the literature, this descriptor is based on string values, which are obtained when starting from a particular point of the image and searching for...

People are highly efficient in recognizing faces. However, it is almost impossible for them to cope with huge datasets of facial images without any computational support. On the other hand, the way people describe the facial features using quite commonly encountered descriptors such as “long nose”, “small eyes” and also allude to their feelings acc...

Free access until July 25, 2015 - http://authors.elsevier.com/a/1R8-A5m5d7V7xe The world is becoming increasingly urban. Tools to support urban planning and management are necessary to reconcile needs to develop buildings, to ensure a high quality of life and to protect urban biodiversity. In this paper, we present a tool based on algorithms of Hel...