Grzegorz Baron

Grzegorz Baron
Silesian University of Technology · Institute of Computer Science

PhD Eng

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29
Publications
3,569
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160
Citations

Publications

Publications (29)
Chapter
When data is incomplete and inconsistent, an approximation of concepts can be obtained by applying the rough set theory. The classical approach allows to recognise only nominal attributes, and only nominal classification is possible. To ensure that the inferred rules are of the highest quality, it is beneficial to have access to all available infor...
Article
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Supervised discretisation is widely considered as far more advantageous than unsupervised transformation of attributes, because it helps to preserve the informative content of a variable, which is useful in classification. After discretisation, based on employed criteria, some attributes can be found irrelevant, and all their values can be represen...
Article
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The nature of the input features is one of the key factors indicating what kind of tools, methods, or approaches can be used in a knowledge discovery process. Depending on the characteristics of the available attributes, some techniques could lead to unsatisfactory performance or even may not proceed at all without additional preprocessing steps. T...
Chapter
The paper demonstrates the research methodology focused on observations of relations between attribute relevance, displayed by rankings, and discretisation. Instead of transforming all continuous attributes before data exploration, the variables were gradually processed, and the impact of such a change on the performance of a classifier was studied...
Article
Stylometric analysis of texts relies on learning characteristic traits of writing styles for authors. Once these patterns are discovered, they can be compared to the ones present in other text samples, to recognise their authorship. This recognition can be compromised if input datasets are prepared without taking into consideration possible stratif...
Article
Cross-validation is a popularly used approach to evaluation of performance for classifiers. It relies on random selection of independent samples for training and testing, and assumes that if any similarities among samples exist, they do not lead to known grouping of datapoints in the input space. If these conditions are violated, as it may happen f...
Article
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The present paper describes the problem and effects of water scarcity and the possibility of rational use of this resource in the idea of a Circular Economy (CE) and sustainable development. Rational water management requires innovation, due to the growing demand for this raw material. It seems that water is widely available, e.g., in Poland, there...
Article
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Typically discretisation procedures are implemented as a part of initial pre-processing of data, before knowledge mining is employed. It means that conclusions and observations are based on reduced data, as usually by discretisation some information is discarded. The paper presents a different approach, with taking advantage of discretisation execu...
Article
Full-text available
Discretisation often constitutes a part of initial data preparation stage. It translates continuous domain of features into granular, by assigning a number of intervals to represent attributes’ values by nominal categories. Typically all real-valued features are subjected to transformations, regardless of their characteristics. The paper presents r...
Chapter
It is well known that discretisation of datasets in some cases may improve the quality of a decision system. Such effects were observed many times during experiments conducted in stylometry domain when authorship attribution tasks were performed. However, some experiments delivered results worse than expected when all attributes in datasets were di...
Conference Paper
In authorship attribution domain single classifiers are often employed in research as elements of decision system. On the other hand, there is intuitive prediction that the use of multiple classifier with fusion of their outcomes may improve the quality of the investigated system. Additionally, discretization can be applied for input data which can...
Article
Full-text available
When discretization is used for preprocessing datasets in a decision system different representations of data can be taken into consideration. Typical approach is to use data as it is returned by discretizer, namely as nominal values. But in specific cases such form of data cannot be utilized by next modules of the decision system. Then the possibl...
Conference Paper
Full-text available
The presented paper addresses problem of evaluation of decision systems in authorship attribution domain. Two typical approaches are cross-validation and evaluation based on specially created test datasets. Sometimes preparation of test sets can be troublesome. Another problem appears when discretization of input sets is taken into account. It is n...
Chapter
The paper describes research on ways of datasets discretization, when test datasets are used for evaluation of a classifier. Three different approaches of processing for training and test datasets are presented: “independent”—where discretization is performed separately for both sets assuming that the same algorithm parameters are used; “glued”—whe...
Article
Full-text available
Authorship attribution is one of the research areas in data mining domain and various methods can be employed for performing that task. The paper presents results of research on influence of data discretization on efficiency of Naive Bayes classifier. The analysis has been carried on datasets founded on texts of two male and two female authors usin...
Article
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Modern sensing technologies create new possibilities to control mobile robots without any dedicated manipulators. In this article authors present a novel method that enables driving of the Mindstorms NXT artificial arm with Microsoft Kinect, using gesture recognition and hand tracking. To imitate the movement of an artificial robotic arm, an algori...
Conference Paper
Modern sensing technologies create new possibilities to control mobile robots without any dedicated manipulators. In this article authors present a novel method that enables driving of the Mindstorms NXT artificial arm with Microsoft Kinect, using gesture recognition. To imitate movement of an artificial robotic arm, an algorithm of the human-compu...
Conference Paper
Full-text available
The Project is a three devices Microsoft Kinect, Mobile Lego NXT Robot integrated system - and computer. These are controlled in a single application which enables the user to control the NXT Robot remotely by tracking calibration using voice commands.
Article
A new method of contour and its characteristic feature extraction form noisy image is presented. For image smoothing, the image convolution with a Gaussian function has been used. Then an inflexion point of an image function in the direction of the image gradient vector has been used as a new contour definition. Behavior of this image gradient give...

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