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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublikacjaTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublikacjaBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublikacjaThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublikacjaIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublikacjaThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Looking through the past: better knowledge retention for generative replay in continual learning
PublikacjaIn 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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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublikacjaEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublikacjaGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublikacjaFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublikacjaThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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LOS and NLOS identification in real indoor environment using deep learning approach
PublikacjaVisibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...
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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublikacjaIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Machine learning approach to packaging compatibility testing in the new product development process
PublikacjaThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublikacjaComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublikacjaIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublikacjaThis work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublikacjaIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublikacjaHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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The effects of relational and psychological capital on work engagement: the mediation of learning goal orientation
PublikacjaPurpose – This paper proposes a research model in which learning goal orientation (LGO) mediates the impacts of relational capital and psychological capital (PsyCap) on work engagement. Design/methodology/approach – Data obtained from 475 managers and employees in the manufacturing and service industries in Poland were utilized to assess the linkages given above. Common method variance was controlled by the unmeasured latent method...
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublikacjaWe present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predict affinities obtained with techniques as different as uPBM, gcPBM and HT-SELEX with an excellent performance, much better than existing algorithms. Due to its nature, the method can...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublikacjaPlasmonic nanostructures based on AuAg nanoalloys were fabricated by thermal annealing of metallic films in an argon atmosphere. The nanoalloys were chosen because they can extend the wavelength range in which plasmon resonance occurs and thus allow the design of plasmonic platforms with the desired parameters. The influence of initial fabrication parameters and experimental conditions on the formation of nanostructures was investigated....
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Wisdom from Experience Paradox: Organizational Learning, Mistakes, Hierarchy and Maturity Issues
PublikacjaOrganizations often perceive mistakes as negligence and low-performance indicators, yet they can be a precious learning resource. However, organizations cannot learn from mistakes if they have not accepted them. This study aimed to explore how organizational hierarchy and maturity levels influence the relationship between mistakes acceptance and the ability to change. A sample composed of 380 Polish employees working in knowledge-driven...
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Supervised-learning-based development of multi-bit RCS-reduced coding metasurfaces
PublikacjaCoding metasurfaces have been introduced as efficient tools allowing meticulous control over the electromagnetic (EM) scattering. One of their relevant application areas is radar cross section (RCS) reduction, which principally relies on the diffusion of impinging EM waves. Despite its significance, careful control of the scattering properties poses a serious challenge at the level of practical realization. This article is concerned...
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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublikacjaTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublikacjaThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublikacjaThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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The use of eLearning strategies among travel agents in the United Kingdom, India and New Zealand
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Travel agents and destination management organizations: eLearning as a strategy to train tourism trade partners.
PublikacjaThis article offers an overview of the existing online courses run by national destination management organizations (DMOs) in order to better equip travel agents and tour operators in the sales activities of the tourism destinations. These online courses represent one of the B2B offers by DMOs and an interesting opportunity for travel agents, who are trying to find their identity and competitive advantage within the context of...
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Contribution of UDP-glucuronosyltransferases (UGTs) in metabolism of acridinone antitumor agents, C-1311, C-1305, and their less active structural analogues, C-1330 and C-1299
PublikacjaCelem prowadzonych badań było określenie roli UDP-glukuronylotransferaz, uważanych za najważniejsze enzymy detoksykujące, w metabolizmie pochodnych imidazo- i triazoloakrydonu. Wykazano, że najbardziej aktywne przeciwnowotworowo związki z obu grup, tj. C-1311 i C-1305 są transformowane do O-glukuronidów, w przeciwieństwie do ich metoksylowych analogów, odpowiednio związku C-1330 i C-1299. Analiza składu mieszanin reakcyjnych zawierających...
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A New Expression System Based on Psychrotolerant Debaryomyces macquariensis Yeast and Its Application to the Production of Cold-Active β-D-Galactosidase from Paracoccus sp. 32d
PublikacjaYeasts provide attractive host/vector systems for heterologous gene expression. The currently used yeast-based expression platforms include mesophilic and thermotolerant species. A eukaryotic expression system working at low temperatures could be particularly useful for the production of thermolabile proteins and proteins that tend to form insoluble aggregates. For this purpose, an expression system based on an Antarctic psychrotolerant...
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Thermal self-action effects of acoustic beam in a vibrationally relaxing gas
PublikacjaThermal self-action of acoustic beam in a molecular gas with excited internal degrees of molecules’ freedom, is studied. This kind of thermal self-action differs from that in a Newtonian fluid. Heating or cooling of a medium takes place due to transfer of internal vibrational energy. Equilibrium and non-equilibrium gases, which may be acoustically active, are considered. A beam in an acoustically active gas is self-focusing unlike...
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Thermal Self-Action of Acoustic Beams Containing Several Shock Fronts
PublikacjaThermal self-action of an acoustic beam with one discontinuity or several shock fronts is studied in a Newtonian fluid. The stationary self-action of a single sawtooth wave with discontinuity (or some integer number of these waves), symmetric or asymmetric, is considered in the cases of self-focusing and self- defocusing media. The results are compared with the non-stationary thermal self-action of the periodic sound. Thermal self-action...
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Expansion of the self of activists and nonactivists involved in mass gatherings for collective action
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Improvement of electrochemical action of zinc-rich paints by addition of nanoparticulate zinc
PublikacjaThe influence of nanosized particles on electrochemical action of standard zinc-rich paints by means of SEM as well as potential and impedance measurements has been investigated. The motivation for doing this was to obtain additional electrical connection between the spherical microparticles themselves and zinc particles and steel substrate. Overall zinc content was at the level of 92% by weight. Samples with different concentration...
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C-reactive protein as a diagnostic and prognostic factor in inflammatory bowel diseases
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Molecular action of isoflavone genistein in the human epithelial cell line HaCaT
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The molecular mechanism of genistein action in lysosomal storage diseases: A transcriptomic approach
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Agomelatine's antiglycoxidative action—In vitro and in silico research and systematic literature review
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New Thiophene Imines Acting as Hole Transporting Materials in Photovoltaic Devices
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State Interventionism in Tax System - Example of Action in a COVID-19 Crisis
PublikacjaThe following article presents and classifies changes in tax systems of selected countries as well as counts them as the response to the emergence of the crisis caused by the COVID-19 pandemic. Such actions were undertaken the context of state interventionism in the tax system. In order to achieve the objective of presenting the state interventionism in the context of tax rates, an analysis of the literature on the phenomenon described,...
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Analysis of efficiency of phosphates sorption by different granulation of selected reactive material
PublikacjaIn the light of the need to find an effective way to remove phosphorus from wastewater, studies on the suitability of sorption materials in this process should be conducted. The aim of the study was to examine the potential benefits of using selected adsorbents to reduce orthophosphates from the model solution under steady conditions. The study was conducted on a laboratory scale using synthetic wastewater with concentration of...
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Comparative Analysis of Reactive Power Compensation Devices in a Real Electric Substation
PublikacjaA constant worldwide growing load stress over a power system compelled the practice of a reactive power injection to ensure an efficient power network. For this purpose, multiple technologies exist in the knowledge market out of which this paper emphasizes the usage of the flexible alternating current transmission system (FACTS) and presents a comparative study of the static var compensator (SVC) with the static synchronous compensator...
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EFFECT OF ANTIOXIDANTS ON THE STABILITY OF PITCH- BASED POLYMER TO THERMO-OXIDATIVE ACTION
PublikacjaThe influence of stabilizers – hydrogen donors – on the processes of thermooxidative destruction of pitch-based polymer has been investigated. It is shown that Irganox has not stabilizing effect on pitch-based polymer and melamine slightly retards the destructive process. A mixture of melamine and Irganox exhibits synergetic stabilizing effect and at the optimum ratio it can be used to prevent unwanted thermooxidative processes...
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Two-step mechanism of J-domain action in driving Hsp70 function
PublikacjaJ-domain proteins (JDPs), obligatory Hsp70 cochaperones, play critical roles in protein homeostasis. They promote key allosteric transitions that stabilize Hsp70 interaction with substrate polypeptides upon hydrolysis of its bound ATP. Although a recent crystal structure revealed the physical mode of interaction between a J-domain and an Hsp70, the structural and dynamic consequences of J-domain action once bound and how Hsp70s...
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Action Research: Cooperation of Practitioners and Researchers for Knowledge Development in Public Organisations
PublikacjaAction Research (AR) is not only a research method or a research strategy for solving a research problem, but also an effective tool for developing knowledge and implementing changes in the organization. The aim of AR is to bring about a change within the studied area and get participants to initiate changes, in which the researcher and the recipient collaborate in investigating the problem and developing a relevant solution. AR...
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More on the poly(L-lactide) prepared using ferrous acetate as catalyst
PublikacjaPolilaktydy przygotowano w syntezie polegajacej na otworzeniu pierścienia (ROP). Syntezę przeprowadzono w bloku z różną ilością octanu żelaza, użytego jako katalizatora. Zbadano przebieg krystalizacji polilaktydów i podatnośc na biodegradację w osadzie czynnym.
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A geophysical, geochemical and microbiological study of a newly discovered pockmark with active gas seepage and submarine groundwater discharge (MET1-BH, central Gulf of Gdańsk, southern Baltic Sea)
PublikacjaHigh-resolution bathymetric data were collected with a multi-beam echosounder in the southern part of the Baltic Sea (region MET1, Gulf of Gdańsk) revealing the presence of a 10 m deep and 50 m in diameter pockmark (MET1-BH) on the sea bottom (78.7 m). To date, no such structures have been observed to reach this size in the Baltic Sea. The salinity of the near-bottom water in the pockmark was about 2 PSU (about 31.22 mmol/l...
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Photoelectrochemically Active N‐Adsorbing Ultrathin TiO2 Layers for Water‐Splitting Applications Prepared by Pyrolysis of Oleic Acid on Iron Oxide Nanoparticle Surfaces under Nitrogen Environment
PublikacjaHighly performing photocatalytic surfaces are nowadays highly desirable in energy fields, mainly due to their applicability as photo water‐splitting electrodes. One of the current challenges in this field is the production of highly controllable and efficient photoactive surfaces on many substrates. Atomic layer deposition has allowed the deposition of photoactive TiO2 layers over wide range of materials and surfaces. However,...
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Experimental Evaluation of the Agent-Based Population Learning Algorithm for the Cluster-Based Instance Selection
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