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1
Content available Zastosowanie mikrotomografii komputerowej do badania orientacji klastów w glinach lodowcowych
100%
Hermanowski P. , Duda P.
Przegląd Geologiczny
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2019
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tom Vol. 67, nr 8
653--661
EN
Limitations of macroscopic measurements and observations of glacial tills, no matter how informative they are, have contributed to the development of micromorphological analysis first in thin sections, since the 80’s using X-ray computed tomography, and recently X-ray computed microtomography (μ-CT). The цCT has found wide applications in science including earth sciences where is used for imagining various geological samples in the 3D view. The sampling procedure and preparation of samples do not generate much effort, and eventually, allow analysis of samples with a preserved undisturbed structure. Herein, we present a short review and methodology of μCT as well as its application to the study of glacial tills. For example, we analyzed a subglacial till sample from the lee side of a drumlin located in the Stargard drumlin field area, NW Poland. The results show a distinctive bimodal pattern of clast fabrics which is interpreted as a result of subglacial till squeezing. Smaller clasts are obliquely oriented to the major direction of the ice flow whereas the larger clasts orientation is approximately in accordance with the major shear stress direction. Overall, our data emphasize the potential of the μ-CT in glacial till studies.
2
Content available Identification of the liquid turbulent flow based on experimental methods
100%
Talaga J. , Duda P.
Archives of Thermodynamics
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2020
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tom Vol. 41, no 3
91--102
EN
This paper presents the results of experimental testing of parameters of the flow of an agitated liquid in a stirred tank with an eccentrically positioned shaft and with a Rushton turbine. The investigations were focused on the impact of the stirrer shaft shift in relation to the stirred tank vertical axis on the agitated liquid mean velocities and the liquid turbulent velocity fluctuations, as well as on the turbulence intensity in the tank. All the experiments were carried out in a stirred tank with the inner diameter of 286 mm and a flat bottom. The adopted values of the shaft eccentricity were zero (central position) and half the tank radius. The liquid flow instantaneous velocities were measured using laser Doppler anemometry.
3
Content available Noise robust illumination invariant face recognition via bivariate wavelet shrinkage in logarithm domain
80%
Chen G. Y. , Krzyżak A. , Duda P. , Cader A.
Journal of Artificial Intelligence and Soft Computing Research
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2022
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tom Vol. 12, No. 3
169--180
EN
Recognizing faces under various lighting conditions is a challenging problem in artificial intelligence and applications. In this paper we describe a new face recognition algorithm which is invariant to illumination. We first convert image files to the logarithm domain and then we implement them using the dual-tree complex wavelet transform (DTCWT) which yields images approximately invariant to changes in illumination change. We classify the images by the collaborative representation-based classifier (CRC). We also perform the following sub-band transformations: (i) we set the approximation sub-band to zero if the noise standard deviation is greater than 5; (ii) we then threshold the two highest frequency wavelet sub-bands using bivariate wavelet shrinkage. (iii) otherwise, we set these two highest frequency wavelet sub-bands to zero. On obtained images we perform the inverse DTCWT which results in illumination invariant face images. The proposed method is strongly robust to Gaussian white noise. Experimental results show that our proposed algorithm outperforms several existing methods on the Extended Yale Face Database B and the CMU-PIE face database.
4
Content available On training deep neural networks using a streaming approach
80%
Duda P. , Jaworski M. , Cader A. , Wang L.
Journal of Artificial Intelligence and Soft Computing Research
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2020
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tom Vol. 10, No. 1
15--26
EN
In recent years, many deep learning methods, allowed for a significant improvement of systems based on artificial intelligence methods. Their effectiveness results from an ability to analyze large labeled datasets. The price for such high accuracy is the long training time, necessary to process such large amounts of data. On the other hand, along with the increase in the number of collected data, the field of data stream analysis was developed. It enables to process data immediately, with no need to store them. In this work, we decided to take advantage of the benefits of data streaming in order to accelerate the training of deep neural networks. The work includes an analysis of two approaches to network learning, presented on the background of traditional stochastic and batch-based methods.
5
Content available Impact sound reduction measurement method for lightweight floor screed
80%
Pilch A. , Duda P. , Rubacha J.
Vibrations in Physical Systems
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2021
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tom Vol. 32, nr 1
art. no. 2021114
EN
Development and implementation of a new product in the form of a lightweight screed with high impact sound reduction require a lot of measurements of different aggregates of lightweight elements and filling. The manufacturing process influences the final parameters of the solutions as well. This is why a method was developed, that allowed a comparison of many different samples within one measurement session. The measured samples must therefore be small and easy to move. In the paper, various possibilities of impact sound reduction measurements were analyzed being different variants of the normative methods and those existing in the literature on the subject. Based on the obtained results, it was shown that for lightweight floor screeds, sound pressure level measurement is more reliable than vibration acceleration measurements. The top vinyl layer used between the tapping machine and the sample did not influence the results significantly and protected the sample from being distorted by the tapping machine hammers.
6
Content available Lightweight floor screed with increased impact sound reduction
80%
Pilch A. , Duda P. , Rubacha J.
Vibrations in Physical Systems
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2023
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tom Vol. 34, nr 1
art. no. 2023103
EN
Increasing users’ requirements force to provide better and better solutions for reducing impact sounds. A lightweight floor screed can be a favorable solution for existing buildings with limited ceiling load capacity, where typical highly effective floating floors are too heavy to be used. In the paper further development of the impact sound reduction measurement method for small lightweight floor screed samples is presented. In order to protect the top layer of the sample from the hammers of the tapping machine, a thin concrete layer was coupled with the sample. What is more, a thin layer of sand below the sample was tested in order to improve the connection between the sample and the concrete floor. Based on obtained results, the concrete top layer and the sand bottom layer reduce slightly the effectiveness of the screed but decrease the uncertainty of the results significantly.
7
Content available A novel drift detection algorithm based on features’ importance analysis in a data streams environment
80%
Duda P. , Przybyszewski K. , Wang L.
Journal of Artificial Intelligence and Soft Computing Research
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2020
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tom Vol. 10, No. 4
287--298
EN
The training set consists of many features that influence the classifier in different degrees. Choosing the most important features and rejecting those that do not carry relevant information is of great importance to the operating of the learned model. In the case of data streams, the importance of the features may additionally change over time. Such changes affect the performance of the classifier but can also be an important indicator of occurring concept-drift. In this work, we propose a new algorithm for data streams classification, called Random Forest with Features Importance (RFFI), which uses the measure of features importance as a drift detector. The RFFT algorithm implements solutions inspired by the Random Forest algorithm to the data stream scenarios. The proposed algorithm combines the ability of ensemble methods for handling slow changes in a data stream with a new method for detecting concept drift occurrence. The work contains an experimental analysis of the proposed algorithm, carried out on synthetic and real data.
8
Content available A new approach to image-based recommender systems with the application of heatmaps maps
80%
Woldan P. , Duda P. , Cader A. , Laktionov I.
Journal of Artificial Intelligence and Soft Computing Research
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2023
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tom Vol. 13, No. 2
63--72
EN
One of the fundamental issues of modern society is access to interesting and useful content. As the amount of available content increases, this task becomes more and more challenging. Our needs are not always formulated in words; sometimes we have to use complex data types like images. In this paper, we consider the three approaches to creating recommender systems based on image data. The proposed systems are evaluated on a real-world dataset. Two case studies are presented. The first one presents the case of an item with many similar objects in a database, and the second one with only a few similar items
9
Content available (µ + λ) evolution strategy with socio-cognitive mutation
51%
Urbanczyk A. , Kucaba K. , Wojtulewicz M. , Kisiel-Dorohinicki M. , Rutkowski L. , Duda P. , Kacprzyk J. , Yao X. , Chong S. Y. , Byrski A.
Journal of Automation Mobile Robotics and Intelligent Systems
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2024
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tom Vol. 18, No. 1
1--11
EN
Socio-cognitive computing is a paradigm developed for the last several years in our research group. It consists of introducing mechanisms inspired by inter-individual learning and cognition into metaheuristics. Different versions of the paradigm have been successfully applied in hybridizing Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Genetic Algorithms, Differential Evolution, and Evolutionary Multi-agent System (EMAS) metaheuristics. In this paper, we have followed our previous experiences in order to propose a novel mutation based on socio-cognitive mechanism and test it based on Evolution Strategy (ES). The newly constructed versions were applied to popular benchmarks and compared with their reference versions.
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