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Search results for: ACTIVE%20LEARNING
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublicationBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublicationText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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VSC converters control for offshore wind farms HVDC grid connection
PublicationThe paper proposes a voltage sourced converter (VSC) new control method. A well-known in the electric power systems correlation between voltage angle and active power and correlation between voltage and reactive power is used instead of feedforward control. This allows for a fast and almost independent control of active and reactive power flow.
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Effects of Post-Harvest Elicitor Treatments with Ultrasound, UV- and Photosynthetic Active Radiation on Polyphenols, Glucosinolates and Antioxidant Activity in a Waste Fraction of White Cabbage (Brassica oleracea var. capitata)
PublicationBiosynthesis of phytochemicals in leaves of Brassica can be initiated by abiotic factors. The aim of the study was to investigate elicitor treatments to add value to waste of cabbage. A leaf waste fraction from industrial trimming of head cabbage was exposed to UV radiation (250–400 nm, 59 and 99 kJ m-2, respectively), photosynthetic active radiation (PAR, 400–700 nm, 497 kJ m-2), and ultrasound in water bath (35 kHz, at 15, 30...
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Experimental validation and comparison of a SiC MOSFET based 100 kW 1.2 kV 20 kHz three-phase dual active bridge converter using two vector groups
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Corrigendum to “Synthesis and photoelectrochemical behaviour of hydrogenated titania nanotubes modified with conducting polymer infiltrated by redox active network” [Electrochim. Acta 222 (20 December) (2016) 1281–1292]
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2,7-Dihydro-3H-pyridazino[5,4,3-kl]acridin-3-one derivatives, novel type of cytotoxic agents active on multidrug-resistant cell lines. Synthesis and biological evaluation.
PublicationOtrzymano serię pirydazyno akrydyn-3-onów w reakcji 9-okso-9,10-dihydroakrydyno-1-karboksylanu etylu z POCl3, następnie dodanie odpowiedniej alkiloaminoalkilohydrazyny. Badane związki wykazują w porównaniu z referencyjnymi cytostatykami DX, MIT niższe wartości indeksu RI, a także niższe aktywności cytotoksyczne.
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СИЛОВОЙ ПРЕОБРАЗОВАТЕЛЬ С АКТИВНЫМ ПОДАВЛЕНИЕМ ВЫСШИХ ГАРМОНИК ДЛЯ СИСТЕМ ЭЛЕКТРОСНАБЖЕНИЯ ЛЕТАТЕЛЬНЫХ АППАРАТОВ (Power converter with active suppression of higher harmonics for aircraft power supply systems)
PublicationПредставлены два алгоритма активной фильтрации для силового преобразователя с активным подавлением высших гармоник. Первый алгоритм основан на дискретном преобразовании Фурье: посредством синтезированной системы управления инвертированные измеренные высшие гармоники напряжения поступают на вход инвертора. Второй метод управления основан на алгоритме с использованием принципов самообучения, что значительно снижает потребность в...
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Evaluation of the significance of the effect of the active cross-sectional area of the inlet air channel on the specific enthalpy of the exhaust gas of a diesel engine using statistics F of the Fisher-Snedecor distribution
PublicationThis paper presents the application of Fisher-Snedecor distribution F statistics to assess the significance of the influence of changes in the active cross-sectional area of the inlet air channel (Adol) flow in a diesel engine on the observed diagnostic parameter determined on the basis of measurements of the quick changing exhaust gas temperature in the outlet channel, which is the specific enthalpy of the exhaust gas stream within...
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The community involvement of courts: an action research study in the context of the Polish justice system
PublicationPurpose – As a rule, common courts are hermetic organizations, separated from their stakeholders by procedures based on legal provisions. For these reasons, they are often perceived as unreliable and non-transparent, and as such, they do not inspire trust among stakeholders. The authors posit that the court’s community involvement may lead to the increased accountability and legitimacy of courts, which should in turn result in...
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Unsteady aerodynamic forces acting on the rotor blades in the turbine stagewith steam extraction.
PublicationPrzeprowadzono analizę niestacjonarnych wymuszeń działających na łopatki wirnikowe w stopniu z upustem turbiny 13UC100. Niestacjonarne siły zostały wyznaczone dla 4 punktów pracy upustu. Wskazano na możliwą przyczynę zaistniałego zniszczenia łopatek wirnikowych turbiny.
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Action of an Antiserum to a-Tocoquinone on Photosystem II-Particle Preparations of N icotiana tabacum
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The effect of electromagnetic field on reactive oxygen species production in human neutrophilsin vitro
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Experimental economics in business education: Using simple games to achieve multifaceted effects
PublicationEconomics differs from other sciences not only because of its normative part, but also because of very limited use of experiments. In this way, economics is often perceived as being methodologically more similar to astronomy or meteorology rather than physics or chemistry. Over last decades, however, experimental economics has been significantly developed. This chapter presents some of the possibilities for academic teachers to...
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Effect of native air-formed oxidation on the corrosion behavior of AA7075 aluminum alloys
PublicationThe microstructure of aluminum alloys plays a key role in their corrosion resistance. In particular, the presence of intermetallic precipitates differing in the potential from the alloy matrix induces local corrosion. The study presents the effect of native air-formed oxidation on the corrosion behavior of AA 7075 aluminum alloy. Various microscopic and spectroscopic techniques were used to examine the changes occurring in the...
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Chain Action - How Do Countries Add Value Through Digital Government?
PublicationThis study examineshow countries develop and benefit from Digital Government(DG).The literature proposes various conceptualizations of the value-adding logic of DG, but the benchmarking practice is not respondingto such proposals.For instance, the United Nations’E-Government Surveycombines the readiness and uptake indicatorsand failsto cover any impactindicators;thus,its diagnostic valueis limited. To overcome...
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Reactive extrusion of biodegradable aliphatic polyesters in the presence of free-radical-initiators: A review
PublicationNowadays, growing attention is being paid to the environment and sustainability, what fully justified research works focused on modification of biodegradable polymers and their composites. In this field of research reactive extrusion seems to be the most promising approach, which fits well to sustainable development strategy. In In the present work, the in-situ modification of biodegradable aliphatic polyesters and the compatibilization...
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Starch-grafted-N-vinylformamide copolymers manufactured by reactive extrusion: synthesis and characterization
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Knowledge sharing in manufacturing subsidiaries: proactive and reactive perspective in knowledge exploitation context
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Evaluation of Analytes Characterized with Potential Protective Action after Rat Exposure to Lead
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Isothiocyanates as effective agents against enterohemorrhagic Escherichia coli: insight to the mode of action
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Various modes of action of dietary phytochemicals, sulforaphane and phenethyl isothiocyanate, on pathogenic bacteria
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Study of pozzolanic action of ground waste expanded perlite by means of thermal methods
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How to achieve sustainability?-Employee's point of view on company's culture and CSR practice
PublicationThe people are the company. This study aims to examine the structure of relationships between company culture, performance, corporate social responsibility (CSR), and reputation, as seen from the employee's perspective, to determine which company culture factors most influence CSR practice and, as a result, sustain a company's development and improve its performance. To accomplish this goal, we conducted a survey among employees...
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Analysing Ways to Achieve a New Urban Agenda-Based Sustainable Metropolitan Transport
PublicationThe New Urban Agenda (NUA) sets a new vision of sustainable urban development to help cities deal with the challenges of changing demography. While numerous articles have addressed how the NUA can be implemented at different levels and in different areas, this article points out the potential limitations in incorporating the NUA into metropolitan transport policies. The relevance of the limitations can be seen in three main fields:...
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Novel therapeutic compound acridine–retrotuftsin action on biological forms of melanoma and neuroblastoma
PublicationPURPOSE: As a continuation of our search for anticancer agents, we have synthesized a new acridine-retrotuftsin analog HClx9-[Arg(NO2)-Pro-Lys-Thr-OCH3]-1-nitroacridine (named ART) and have evaluated its activity against melanoma and neuroblastoma lines. Both tumors develop from cells (melanocytes, neurons) of neuroectodermal origin, and both are tumors with high heterogeneity and unsatisfactory susceptibility to chemotherapies....
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Elimination of Impulsive Disturbances From Archive Audio Signals Using Bidirectional Processing
PublicationIn this application-oriented paper we consider the problem of elimination of impulsive disturbances, such as clicks, pops and record scratches, from archive audio recordings. The proposed approach is based on bidirectional processing—noise pulses are localized by combining the results of forward-time and backward-time signal analysis. Based on the results of specially designed empirical tests (rather than on the results of theoretical analysis),...
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RENOVATION OF ARCHIVE AUDIO RECORDINGS USING SPARSE AUTOREGRESSIVE MODELING AND BIDIRECTIONAL PROCESSING
PublicationThe paper presents a new approach to elimination of broadband noise and impulsive disturbances from archive audio recordings. The proposed adaptive Kalman-like algorithm, based on a sparse autoregressive model of the audio signal, simultaneously detects noise pulses, interpolates the irrevocably distorted samples and performs signal smoothing. It is shown that bidirectional (forward-backward) processing of the archive signal improves...
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Interior Point Method Evaluation for Reactive Power Flow Optimization in the Power System
PublicationThe paper verifies the performance of an interior point method in reactive power flow optimization in the power system. The study was conducted on a 28 node CIGRE system, using the interior point method optimization procedures implemented in Power Factory software.
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Localization of impulsive disturbances in archive audio signals using predictive matched filtering
PublicationThe problem of elimination of impulsive disturbances from archive audio signals is considered and its new solution, called predictive matched filtering, is proposed. The new approach is based on the observation that a large percentage of noise pulses corrupting archive audio recordings have highly repetitive shapes that match several typical “patterns”, called click templates. To localize noise pulses, click templates can be correlated...
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Elimination of clicks from archive speech signals using sparse autoregressive modeling
PublicationThis paper presents a new approach to elimination of impulsivedisturbances from archive speech signals. The proposedsparse autoregressive (SAR) signal representation is given ina factorized form - the model is a cascade of the so-called formantfilter and pitch filter. Such a technique has been widelyused in code-excited linear prediction (CELP) systems, as itguarantees model stability. After detection of noise pulses usinglinear...
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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublicationMachine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublicationTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublicationPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change: with Focus on Organizational Culture and Organizational Learning
PublicationTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublicationRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublicationBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change with Focus on Organizational Culture and Organizational Learning
PublicationTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublicationPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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Assessment Of the Relevance of Best Practices in The Development of Medical R&D Projects Based on Machine Learning
PublicationMachine learning has emerged as a fundamental tool for numerous endeavors within health informatics, bioinformatics, and medicine. However, novices among biomedical researchers and IT developers frequently lack the requisite experience to effectively execute a machine learning project, thereby increasing the likelihood of adopting erroneous practices that may result in common pitfalls or overly optimistic predictions. The paper...
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Project-Based Learning as a Method for Interdisciplinary Adaptation to Climate Change—Reda Valley Case Study
PublicationThe challenges of the global labour market require university authorities to extend traditional forms of education into more innovative and effective solutions. Project-based learning (PjBL) is one of highly effective methods for acquiring knowledge and teaching “soft” skills to future employees. This article describes an experimental use of PjBL at a university with a long history of teaching based on traditional methods—the Gdansk...
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SELECTING A REPRESENTATIVE DATA SET OF THE REQUIRED SIZE USING THE AGENT-BASED POPULATION LEARNING ALGORITHM
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Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
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Perception of Pathologists in Poland of Artificial Intelligence and Machine Learning in Medical Diagnosis—A Cross-Sectional Study
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Diversity of Students’ Unethical Behaviors in Online Learning Amid COVID-19 Pandemic: An Exploratory Analysis
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