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Search results for: FEATURE-BASED OPTIMIZATION
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Połączenie G3 dwóch kierunków prostych z użyciem krzywej NURBS
PublicationW artykule przedstawiono nową metodę projektowania układu geometrycznego toru kolejowego opartą na zastosowaniu krzywych NURBS (Non-Uniform Rational B-Spline) do opisu krzywizny. Punkty kontrolne krzywej NURBS wyznaczane są w procesie optymalizacji za pomocą algorytmu genetycznego. Jako kryterium optymalizacji przyjęto minimalizację oddziaływań dynamicznych występujących w układzie tor-pojazd przy spełnieniu warunków geometrycznych...
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Looking through the past: better knowledge retention for generative replay in continual learning
PublicationIn this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained...
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Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
PublicationThis paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...
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Adaptive Positioning Systems Based on Multiple Wireless Interfaces for Industrial IoT in Harsh Manufacturing Environments
PublicationAs the industrial sector is becoming ever more flexible in order to improve productivity, legacy interfaces for industrial applications must evolve to enhance efficiency and must adapt to achieve higher elasticity and reliability in harsh manufacturing environments. The localization of machines, sensors and workers inside the industrial premises is one of such interfaces used by many applications. Current localization-based systems...
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublicationControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Rozkład naprężeń mechanicznych w łyżce o szerokości 500 mm, przeznaczonej do koparki podsiębiernej
PublicationW artykule zaprezentowano optymalizację kształtu łyżki koparki przedsiębiernej z wykorzystaniem analizy wytrzymałościowej. Analizę oparto na trójwymiarowym modelu konstrukcji łyżki z zastosowaniem metody elementów skończonych (MES). Opracowanie wspomnianej metody pozwoliło na modyfikację konstrukcji łyżki, która dała w efekcie obniżenie naprężeń złożonych w newralgicznych obszarach konstrukcji łyżki. Przedstawiona analiza okazała...
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Face Recognition: Shape versus Texture
PublicationThis paper describes experiments related to the application of well-known techniques of the texture feature extraction (Local Binary Patterns and Gabor filtering) to the problem of automatic face verification. Results of the tests show that simple image normalization strategy based on the eye center detection and a regular grid of fiducial points outperforms the more complicated approach, employing active models that are able to...
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Local Texture Pattern Selection for Efficient Face Recognition and Tracking
PublicationThis paper describes the research aimed at finding the optimal configuration of the face recognition algorithm based on local texture descriptors (binary and ternary patterns). Since the identification module was supposed to be a part of the face tracking system developed for interactive wearable computer, proper feature selection, allowing for real-time operation, became particularly important. Our experiments showed that it is...
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ISSUES OF CLASSIFICATION FUNCTION CONTINUITY IN ENDOSCOPIC VIDEO CLASSIFICATION
PublicationIn the article a new way of analyzing the properties of feature vector functions (FVF) and classiers of images in a video stream is proposed. The general idea is based on focusing of the perceived continuity of the FVF and classier functions. Issues related to creating an exact mathematical model are discussed and a simplied solution is proposed. An exemplary algorithm is evaluated on three exemplary video sequences. The acquired...
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Device-independent quantum key distribution based on measurement inputs
PublicationWe provide an analysis of a family of device-independent quantum key distribution (QKD) protocols that has the following features. (a) The bits used for the secret key do not come from the results of the measurements on an entangled state but from the choices of settings. (b) Instead of a single security parameter (a violation of some Bell inequality) a set of them is used to estimate the level of trust in the secrecy of the key....
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Analiza czynników wpływających na prędkość pojazdów transportu zbiorowego na przykładzie Gdańska
PublicationW referacie przedstawiono istotę problemu szacowania prędkości pojazdów transportu zbiorowego w szczególności w zakresie modelowania ruchu. Przedstawiono i omówiono wyniki przeprowadzonych w maju ubiegłego roku pomiarów czasu przejazdu pojazdów transportu zbiorowego na obszarze Gdańska w ramach budowy systemu sterowania ruchem TRISTAR. Otrzymane wyniki zestawiono w celu zaprezentowania statystyki oraz zidentyfikowania czynników...
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A modelling approach to the transport support for the harvesting and transportation complex under uncertain conditions
PublicationThe article proposes a modelling approach based on structural and parametric identification of the transport support of the harvesting and transportation complex. The efficiency and effectiveness of the proposed methods of structural and parametric identification for the development of a system for harvesting and transportation complex operation has been proved. A mathematical model based on fuzzy logic has been developed. It reflects...
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A nine-input 1.25 mW, 34 ns CMOS analog median filter for image processing in real time
PublicationIn this paper an analog voltage-mode median filter, which operates on a 3 × 3 kernel is presented. The filter is implemented in a 0.35 μm CMOS technology. The proposed solution is based on voltage comparators and a bubble sort configuration. As a result, a fast (34 ns) time response with low power consumption (1.25 mW for 3.3 V) is achieved. The key advantage of the configuration is relatively high accuracy of signal processing,...
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Towards Cancer Patients Classification Using Liquid Biopsy
PublicationLiquid biopsy is a useful, minimally invasive diagnostic and monitoring tool for cancer disease. Yet, developing accurate methods, given the potentially large number of input features, and usually small datasets size remains very challenging. Recently, a novel feature parameterization based on the RNA-sequenced platelet data which uses the biological knowledge from the Kyoto Encyclopedia of Genes and Genomes, combined with a classifier...
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Support Vector Machine Applied to Road Traffic Event Classification
PublicationThe aim of this paper is to present results of road traffic event signal recognition. First, several types of systems for road traffic monitoring, including Intelligent Transport System (ITS) are shortly described. Then, assumptions of creating a database of vehicle signals recorded in different weather and road conditions are outlined. Registered signals were edited as single vehicle pass by. Using the Matlab-based application...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublicationMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Optymalizacja doboru prawa konstytutywnego membrany o strukturze plecionej
PublicationCelem niniejszej dysertacji jest opracowanie zagadnienia optymalizacyjnego pozwalającego dobrać model konstytutywny opisujący mechaniczne zachowanie membrany technicznej. Do analizy wybrano membrany plecione, stosowane w medycynie, tzw. siatki chirurgiczne. W celu wykonania identyfikacji praw konstytutywnych, wykonano dwuosiowe rozciąganie próbek materiałów, otrzymując wskazanie na nieliniowe anizotropowe zachowanie materiałów....
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Optymalizacja strategii sieci inteligentnych agentów za pomocą programowania genetycznego w systemie rozproszonym realizującym paradygmat volunteer computing
PublicationDynamicznie rosnąca złożoność i wymagania w odniesieniu do rozproszonych systemów informatycznych utrudnia zarządzanie dostępnymi zasobami sprzętowymi i programistycznymi. Z tego powodu celem rozprawy jest opracowanie wielokryterialnej metody programowania genetycznego, która pozwala na optymalizację strategii zespołu inteligentnych agentów programistycznych w zakresie zarządzania systemem realizującym paradygmat volunteer computing....
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublicationBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks
PublicationThe visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases...
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Integrated Three-Level Dual-Phase Inverter
PublicationIn view of reducing the number of inverter legs that provide dual-phase, three-level output voltages (as may be needed in an uninterruptible power supply), and that also provide a wide range of output frequencies (as needed in an advanced motor drive system with wide speed ranges), a three-level, dual-phase inverter topology is presented in this paper. Its three-level attribute was based on the F-type inverter topological concept,...
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Szybka identyfikacja harmonicznych na podstawie oszczędnego próbkowania
PublicationW pracy przedstawiono implementację szybkiego algorytmu rekonstrukcji sygnału, opartego na teorii oszczędnego próbkowania, który może wykrywać harmoniczne w sygnale wejściowym. Zagadnienie rekonstrukcji sygnału jest problemem optymalizacyjnym rozwiązywanym za pomocą algorytmu programowania liniowego. Dodatkowo, aby przyspieszyć zbieżność rozwiązania zastosowano w rzadkiej dziedzinie sygnału filtr typu K-rank-order. Przeprowadzona...
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Use of Modified Cuckoo Search algorithm in the design process of integrated power systems for modern and energy self-sufficient farms
PublicationIn the face of increasingly stringent pollutant emission regulations, designing an agricultural holding becomes a difficult challenge of connecting a large number of coefficients that describe an energy system of a farm in regard to its ecological and economic efficiency. One way to cope with this issue is to design an energy self-sufficient farm that integrates various technologies, including renewable energy. However, the selection...
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Asymmetrical-Slot Antenna with Enhanced Gain for Dual-Band Applications
PublicationDual-band operation is an important feature of antennas to be applied in modern communication systems. Although high gain of radiators is rarely of concern in urban areas with densely located broadcasting stations, it becomes crucial for systems operating in more remote environments. In this work, a dual-band antenna with enhanced bandwidth is proposed. The structure consists of a driven element in the form of an asymmetrical radiator/slot...
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Supercomputing Grid-Based Services for Hearing Protection and Acoustical Urban Planning, Research and Education
PublicationSpecific computational environments, so-called domain grids, are developed within the PLGrid Plus project in order to prepare specialized IT solutions, i.e., dedicated software implementations and hardware (infrastructure adaptation), suited for particular research group demands. One of the PLGrid Plus domain grids, presented in this paper, is Acoustics. The article describes in detail two kinds of the acoustic domain services....
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Evaluation of a Novel Approach to Virtual Bass Synthesis Strategy
PublicationThe aim of this paper is to present a novel approach to the Virtual Bass Synthesis (VBS) strategy applied to portable computers. The developed algorithms involve intelligent, rule-based settings of bass synthesis parameters with regard to music genre of an audio excerpt and the type of a portable device in use. The Smart VBS algorithm performs the synthesis based on a nonlinear device (NLD) with artificial controlling synthesis...
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The Hough transform in the classification process of inland ships
PublicationThis article presents an analysis of the possibilities of using image processing methods for feature extraction that allows kNN classification based on a ship’s image delivered from an on-water video surveillance system. The subject of the analysis is the Hough transform which enables the detection of straight lines in an image. The recognized straight lines and the information about them serve as features in the classification...
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Identification of volatile compounds based on the electrocatalytic gas sensor responses
PublicationMeasured response in case of electrocatalytic gas sensors is in form of a voltamperometric characteristic. Current-voltage (I-V) response shape depends on the gas type and its concentration. Such response contains significantly more information comparing with typical electrochemical sensors, but is quite difficult to analyze. When I-V curve contains current peaks, position of such peaks can be used...
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Zaufanie do siebie jako jeden z aspektów zaufania w aktywności przedsiębiorczej
PublicationArtykuł prezentuje znaczenie zaufania do samego siebie na tle zaufania w relacjach budowanych przez przedsiębiorcę w jego otoczeniu społecznym i biznesowym. Wyjaśniono koncepcję zaufania do samego siebie, odnosząc się do zróżnicowanych typów zaufania, na przykład: kalkulacyjnego, opartego na wiedzy i identyfikacyjnego. Wskazano jego potencjalne źródła i konsekwencje w kontekście budowania własnego wizerunku, podejmowania decyzji...
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Zastosowanie metod eksploracji danych do analizy odpowiedzi czujników gazu
PublicationZagadnienia poruszane w niniejszej rozprawie dotyczą zastosowania metod eksploracji danych do analizy odpowiedzi czujników gazu, umożliwiających poprawną identyfikację składu mieszaniny gazowej w elektronicznych systemach rozpoznawania gazu. Elektroniczne systemy rozpoznawania gazu to urządzenia wykorzystujące czujniki gazu oraz odpowiednio dobrane metody analizy danych pomiarowych, zdolne do określenia składu mierzonej mieszaniny...
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Reverse vaccinology-based prediction of a multi-epitope SARS-CoV-2 vaccine and its tailoring to new coronavirus variants
PublicationThe genome feature of SARS-CoV-2 leads the virus to mutate and creates new variants of concern. Tackling viral mutations is also an important challenge for the development of a new vaccine. Accordingly, in the present study, we undertook to identify B- and T-cell epitopes with immunogenic potential for eliciting responses to SARS-CoV-2, using computational approaches and its tailoring to coronavirus variants. A total of 47 novel...
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Implementation of IMS/NGN Transport Stratum Based on the SDN Concept
PublicationThe paper presents the development and verification of software and a testbed aiming to demonstrate the ability of two telecommunication network concepts—Next Generation Network (NGN) and Software-Defined Networking (SDN)—to cooperate. The proposed architecture includes components of the IP Multimedia Subsystem (IMS) in its service stratum and of the SDN (controller and programmable switches) in its transport stratum, providing...
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High Dynamic Range Microwave Displacement and Rotation Sensors Based on the Phase of Transmission in Groove Gap Waveguide Technology
PublicationThis research is focused on the design and realization of displacement sensors in gap waveguide technology. It is shown that with a small but fundamental change in the structure of a conventional gap waveguide, a linear displacement can be sensed. To this end, a unique feature of gap waveguides, i.e. the fact that no electrical connection between the top and bottom parts of the gap waveguide is required, is used. It is further shown...
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Online sound restoration system for digital library applications
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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METODA WIELOKRYTERIALNEJ OCENY PRZEBUDOWY UKŁADÓW TOROWYCH NA SZLAKACH
PublicationRozprawa doktorska dotyczy zagadnienia projektowania układów geometrycznych toru kolejowego w procesie modernizacji linii kolejowych. Scharakteryzowano główne cechy dotyczące tej tematyki w oparciu o literaturę polską i zagraniczną, w tym przepisy branżowe. Przedstawiono czynniki wpływające na projektowanie modernizacji linii kolejowych. Określono wartości dopuszczalne parametrów kinematycznych i geometrycznych. Specyfika omawianego...
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ZAPEWNIENIE SYNCHORNIZACJI CZASU PRZY CZĘŚCIOWYM WSPARCIU SIECI
PublicationCelem badań zaprezentowanych w artykule było sprawdzenie czy możliwe jest zapewnienie dużej dokładności synchronizacji czasu przy częściowym wsparciu sieci w oparciu o model HRM-1 składający się z 12 szeregowo podłączonych urządzeń sieciowych wraz z wygenerowanym ruchem sieciowym. Badania wykazały, że dla obecnie stosowanych technologii mobilnych takich jak LTE TDD możliwe jest zapewnienie odpowiedniej jakości synchronizacji czasu....
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublicationNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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Localization of impulsive disturbances in audio signals using template matching
PublicationIn this paper, a new solution to the problem of elimination of impulsive disturbances from audio signals, based on the matched filtering technique, is proposed. The new approach stems from the observation that a large proportion of noise pulses corrupting audio recordings have highly repetitive shapes that match several typical “patterns”. In many cases a representative set of exemplary pulse waveforms can be extracted from the...
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Assessment of Wide-Sense Stationarity of an Underwater Acoustic Channel Based on a Pseudo-Random Binary Sequence Probe Signal
PublicationThe performances of Underwater Acoustic Communication (UAC) systems are strongly related to the specific propagation conditions of the underwater channel. Designing the physical layer of a reliable data transmission system requires a knowledge of channel characteristics in terms of the specific parameters of the stochastic model. The Wide-Sense Stationary Uncorrelated Scattering (WSSUS) assumption simplifies the stochastic description...
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Considerations of Computational Efficiency in Volunteer and Cluster Computing
PublicationIn the paper we focus on analysis of performance and power consumption statistics for two modern environments used for computing – volunteer and cluster based systems. The former integrate computational power donated by volunteers from their own locations, often towards social oriented or targeted initiatives, be it of medical, mathematical or space nature. The latter is meant for high performance computing and is typically installed...
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Comparative molecular modelling of biologically active sterols
PublicationMembrane sterols are targets for a clinically important antifungal agent – amphotericin B. The relatively specific antifungal action of the drug is based on a stronger interaction of amphotericin B with fungal ergosterol than with mammalian cholesterol. Conformational space occupied by six sterols has been defined using the molecular dynamics method to establish if the conformational features correspond to the preferential interaction...
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Semantic OLAP with FluentEditor and Ontorion Semantic Excel Toolchain
PublicationSemantic technologies appear as a step on the way to creating systems capable of representing the physical world as real time computational processes. In this context, the paper presents a toolchain for an ontology based knowledge management system. It consists of the ontology editor, FluentEditor and the distributed knowledge representation system, Ontorion. FluentEditor is a comprehensive tool for editing and manipulating complex...
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What entrepreneurs think about tax optimization?
Open Research DataThe study conducted on a group of 259 entrepreneurs concerned the behavioral attitudes of business owners regarding their opinion on tax optimization. From the study we will learn, among others, how tax optimization is defined according to entrepreneurs, their attitude towards it, as well as what optimization actions they have taken so far.
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A spline-based FE approach to modelling of high frequency dynamics of 1-D structures
PublicationIn this paper a computational methodology leading to the development of a new class of FEs, based on the application of continuous and smooth approximation polynomials, being splines, has been presented. Application of the splines as appropriately defined piecewise elemental shape functions led the authors to the formulation of a new approach for FEM, named as spFEM, where contrary to the well-known NURBS approach, the boundaries...
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Brain-computer interaction based on EEG signal and gaze-tracking information = Analiza interackji mózg-komputer wykorzystująca sygnał EEg i informacje z systemu śledzenia punktu fiksacji wzroku
PublicationThe article presents an attempt to integrate EEG signal analysis with information about human visual activities, i.e. gaze fixation point. The results from gaze-tracking-based measurement were combined with the standard EEG analysis. A search for correlation between the brain activity and the region of the screen observed by the user was performed. The preliminary stage of the study consists in electrooculography (EOG) signal processing....
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublicationIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublicationThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Numbers, Please: Power- and Voltage-Related Indices in Control of a Turbine-Generator Set
PublicationThis paper discusses the proper selection and interpretation of aggregated control performance indices values mirroring the quality of electrical energy generation by a turbine-generator set cooperating with a power system. Typically, a set of basic/classical and individual indices is used in energy engineering to ensure the mirroring feature and is related to voltage, frequency and active or reactive power deviations from their...
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Modelling of heat transfer in supercritical pressure recuperators
PublicationIn the paper presented is analysis of convective flow heat transfer at supercritical pressure in channels of heat exchanger working in the thermodynamic cycle. The modelling is based on the division of the flow into three regions, namely the heavy fluid, a two phase flow consisting of the heavy and light fluids and finally the light fluid flow. Modelling is concentrated on the region of simultaneous flow of two fluids divided into...
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Vehicle detector training with minimal supervision
PublicationRecently many efficient object detectors based on convolutional neural networks (CNN) have been developed and they achieved impressive performance on many computer vision tasks. However, in order to achieve practical results, CNNs require really large annotated datasets for training. While many such databases are available, many of them can only be used for research purposes. Also some problems exist where such datasets are not...