Książki, monografie, podręczniki, rozdziały (WFTIiMS)
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Pozycja Wybrane zagadnienia statystyki i rachunku prawdopodobieństwa z przykładami w programie R(Wydawnictwo Politechniki Łódzkiej, 2020) Dems-Rudnicka, Katarzyna; Jóźwik, Izabela; Terepeta, Małgorzata; Kałuszka, Marek (Rec.)Znaczenie metod statystycznych w naukach przyrodniczych i technicznych systematycznie wzrasta. Znajomość podstawowych technik statystyki opisowej i matematycznej jest niezbędnym elementem wykształcenia absolwenta uczelni wyższej, nie tylko technicznej. Opracowanie zebranych danych i wyciągniecie wniosków z przeprowadzonych obliczeń jest integralna częścią wielu badań, publikacji naukowych, a także prac dyplomowych z obszaru niemal wszystkich dyscyplin badawczych. Niniejszy podręcznik został przygotowany z myślą o studentach, głównie uczelni technicznych, ale może być wykorzystywany przez wszystkie zainteresowane osoby do samodzielnego opracowywania danych doświadczalnych. W zwięzły sposób przedstawiono w nim podstawowe zagadnienia rachunku prawdopodobieństwa oraz statystyki opisowej i matematycznej.Pozycja Wykłady z analizy matematycznej 2 dla informatyków(Wydawnictwo Politechniki Łódzkiej, 2023) Galewski, Marek; Gasiński, LeszekPrzedkładany Czytelnikowi podręcznik w jakiejś mierze stanowi odzwierciedlenie wykładów z przedmiotu ’Analiza matematyczna 2’ dla studentów pierwszego stopnia informatyki stosowanej. Notatki do wykładów istniały już wcześniej w różnej postaci i postanowiłem je połączyć w pewną całość. Mam świadomość, iż wprowadzane przeze mnie podejście nie jest w żadnej mierze nowatorskie, ale tak zredagowany podręcznik może być przydatny dla studentów Politechniki Łódzkiej [...]Pozycja Semi-formal Methods for Security Informed Safety Assessment of Robotic Systems(Wydawnictwo Politechniki Łódzkiej, 2023) Kharchenko, Vyacheslav; Abakumov, Artem; Yakovlev, SergiyPozycja Simulation of the Quantum Heat Engine in the Quantum Register(Wydawnictwo Politechniki Łódzkiej, 2023) Ostrowski, MarcinThis paper investigates whether a quantum computer can efficiently simulate the transfer of excitation between a pair of quantum systems with energy loss caused by photon or phonon emission. The main contribution of our work is an algorithm that enables the simulation of time evolution of such a system, implemented on a standard two-input gates. The paper examines the properties of the proposed algorithm and then compares the obtained results with theoretical predictions.Pozycja MPTCP Congestion Control Algorithms for Streaming Applications – Performance Evaluation in Public Networks(Wydawnictwo Politechniki Łódzkiej, 2023) Łuczak, Łukasz Piotr; Ignaciuk, Przemysław; Morawski, MichałEfficient data transfer for high-quality streaming requires fast speed, low latency, and stable transmission parameters. Utilizing multiple communication paths is a promising solution for improving performance. This paper evaluates the most common MPTCP congestion control algorithms in the context of streaming applications in the open Internet. The results show that the BALIA algorithm is the most effective CC algorithm for multi-path streaming. This algorithm achieves the lowest path delay and Head-of-Line blocking degree with consistent throughput. Conversely, the MPTCP CC algorithm wVegas exhibits the weakest performance.Pozycja Local Energy Redistribution Units for Space Dimensionality Reduction in Data Classification(Wydawnictwo Politechniki Łódzkiej, 2023) Puchała, DariuszIn this paper, we present locally trained 2-input to 2-output neurons called Local Energy Redistribution Units (LERUs), which enable to transfer most of the input data energy to the selected output, and when organized into properly designed networks, allow for the energy accumulation in lower-indexed elements of output vectors. This property can be used to reduce the dimensionality of the input data space, resulting in a reduction in the number of weights and disk space needed to store neural network models. We test the effectiveness of the proposed approach experimentally in the task of data classification using the well-known MNIST dataset.Pozycja Dynamic Mutation Control in Continuous Genetic Algorithms(Wydawnictwo Politechniki Łódzkiej, 2023) Wieczorek, Łukasz; Ignaciuk, PrzemysławIn this paper the adaptability of the mutation operation in continuous genetic algorithms (CGAs) is taken into consideration from an analytical perspective. For this purpose, based on the notation that has previously been used to analyze the classical, binary genetic algorithm, a dynamic system model of CGA has been created. In order to adapt the mutation probability in successive generations, a linear controller has been applied. It allows one to accelerate the evolution process. As a result, faster convergence is obtained, as required in computationally intensive optimization problems.Pozycja A Novel Learning Multi-Swarm Particle Swarm Optimization(Wydawnictwo Politechniki Łódzkiej, 2023) Borowska, BożenaParticle swarm optimization (PSO) is one of the metaheuristic optimization methods. Because of its many advantages, it is often used to solve real-world engineering problems. However, in case of complex, multidimensional tasks, PSO faces some problems related to premature convergence and stagnation in local optima. To eliminate this inconveniences, in this paper, a new learning multi-swarm particle swarm optimization method (LMPSO) with local search operator has been proposed. The presented approach was tested on a set of nonlinear functions and a CEC2015 test suite. The obtained results were compared with other optimization methods.Pozycja Increasing Skin Lesions Classification Rates using Convolutional Neural Networks with Invariant Dataset Augmentation and the Three-Point Checklist of Dermoscopy(Wydawnictwo Politechniki Łódzkiej, 2023) Milczarski, Piotr; Borowski, Norbert; Beczkowski, MichałIn the paper, we show how to tackle the problem of lack of the rotation invariance in CNN networks using the authors’ Invariant Dataset Augmentation (IDA) method. The IDA method allows to increase the classification rates taking into account as an example the classification of the skin lesions using a small image set. In order to solve the problem of the lack of rotation invariance, IDA method was used and the dataset was increased in an eightfold and invariant way. In the research, we applied the IDA methods and compared the results of VGG19, XN and Inception-ResNetv2 CNN networks in three skin lesions features classification defined by wellknown dermoscopic criterions e.g. the Three-Point Checklist of Dermoscopy or the Seven-Point Checklist. Due to Invariant Dataset Augmentation, the classification rate parameters like true positive rate by almost 20%, false positive rate as well as the F1 score and Matthews correlation coefficient have been significantly increased opposite to type II error that has significantly decreased. In the paper, the confusion matrix parameters result in: 98-100% accuracy, 98-100% true positive rate, 0.0-2.3% false positive rate, tests F1=0.95 and MCC=0.95. That general approach can provide higher results while using CNN networks in other applications.Pozycja Building Energy Use Intensity Prediction with Artificial Neural Networks(Wydawnictwo Politechniki Łódzkiej, 2023) Stokfiszewski, Kamil; Sztoch, Przemysław; Sztoch, Ryszard; Wosiak, AgnieszkaIn this paper the authors propose the construction and examine the performance of the artificial neural network for energy use intensity prediction for residential buildings. The network’s type is the standard multilayer perceptron and its training dataset contains the data of 768 residential buildings where the training pattern for an individual building consists of 8 parameters describing the building’s geometry along with its lighting and glazing conditions while the only output value is the building’s actual energy use intensity characteristics. Experimental study shows that the mean absolute percentage error of prediction of the energy use intensity evaluated for buildings data present in the network’s test set does not exceed 1.8%, what might be considered a highly satisfactory result.