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Publicly available lecture webcasts - e-learning or promotion tool? case study
PublicationThis paper aims to show how universities interact with Internet users by webcasting selected courses. Paper has exploratory case-study character, presenting example of Berkeley Webcast initiative of University of California, Berkeley, webcasting undergraduate courses and on-campus events. On the base of short introduction to webcasting usage as an e-learning and promotional tool, the analysis of 3 purposely chosen different courses...
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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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Leading with Understanding: Cultivating Positive Relationships between Neurotypical Leaders and Neurodivergent Employees
PublicationNeurodivergent employees have atypical needs that require distinctive leadership approaches. In this study, the specific nature of a relationship between neurodivergent employees and their neurotypical leaders is explored through the lens of the Leader-Member-Exchange (LMX) theory. This two-phased qualitative study builds on 12 semi-structured interviews with neurodivergent employees and an unstructured focus group with 15 individuals...
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BACTERIAL INACTIVATION VIA LASER-DRIVEN GOLD NANOPARTICLE HEATING: SIMULATION AND ANALYSIS
PublicationThis study utilizes CFD technique to simulate the inactivation of E. coli bacteria within a microfluidic chamber, employing gold nanoparticles irradiated by a laser beam. Employing a single-phase model, the presence of bacteria is considered by treating thermal properties in the governing equations as effective, combining those of water and bacteria using established correlations from scientific literature. The conversion of light...
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Gender as a Moderator of the Double Bias of Mistakes – Knowledge Culture and Knowledge Sharing Effects
PublicationThere is no learning without mistakes. The essence of the double bias of mistakes is the contradiction between an often-declared positive attitude towards learning from mistakes, and negative experiences when mistakes occur. Financial and personal consequences, shame, and blame force desperate employees to hide their mistakes. These adverse outcomes are doubled in organizations by the common belief that managers never make mistakes,...
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DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors
PublicationWe 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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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublicationBiochar 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
PublicationThis 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
PublicationIn 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
PublicationThe 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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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublicationThe 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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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis 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
PublicationIn 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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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublicationEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublicationThe process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between...
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo 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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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublicationGrasping 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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A general theory for anisotropic Kirchhoff–Love shells with in-plane bending of embedded fibers
PublicationThis work presents a generalized Kirchhoff–Love shell theory that can explicitly capture fiber-induced anisotropy not only in stretching and out-of-plane bending, but also in in-plane bending. This setup is particularly suitable for heterogeneous and fibrous materials such as textiles, biomaterials, composites and pantographic structures. The presented theory is a direct extension of classical Kirchhoff–Love shell theory to incorporate...
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On the use of leading safety indicators in maritime and their feasibility for Maritime Autonomous Surface Ships
PublicationAlthough the safety of prospective Maritime Autonomous Surface Ships will largely depend on their ability to detect potential hazards and react to them, the contemporary scientific literature lacks the analysis of how to achieve this. This could be achieved through an application of leading safety indicators. The aim of the performed study was to identify the research directions of leading safety indicators in three safety-critical...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublicationEEG-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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Machine learning approach to packaging compatibility testing in the new product development process
PublicationThe 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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AUTOMATIC LEARNING OF STRATEGY AND RULES IN CARD GAMES USING IMAGE FROM CAMERA
PublicationBelow work tries to answer a question: if it is possible to replace real human with computer system in social games. As a subject for experiments, card games were chosen, because they require a lot of player interaction (playing and taking cards), while their rules are easy to present in form of clear list of statements. Such a system, should allow real players to play without constant worrying about guiding or helping computer...
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The effects of relational and psychological capital on work engagement: the mediation of learning goal orientation
PublicationPurpose – 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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Social Media and Knowledge Sharing – What Do We Know So Far?
PublicationThe aim of this paper is to examine previous studies on topic of social media and how it influences knowledge sharing online and thereafter establish respective body of knowledge. The background investigation has been organized as a theoretical review with qualitative premises. The multi-layered Systematic Literature Review process has been utilized and carried out to fetch the most relevant peer-reviewed researches in the past....
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Optimization of the efficiency of braking energy recovery in rail transport by changing arrival time
PublicationThe article refers to the previous work of the authors, in which the model of traffic organization of cooperating trains including the optimization of the use of energy returned to the catenary was presented. In the presented article, the model was modified by changing the main control variable, which affects the efficient use of energy. Departure time was changed for the arrival time of the train to the stop or station. The optimization...
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LOS and NLOS identification in real indoor environment using deep learning approach
PublicationVisibility 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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Evaluation of Asphalt Mixture Low-Temperature Performance in Bending Beam Creep Test
PublicationLow-temperature cracking is one of the most common road pavement distress types in Poland. While bitumen performance can be evaluated in detail using bending beam rheometer (BBR) or dynamic shear rheometer (DSR) tests, none of the normalized test methods gives a comprehensive representation of low-temperature performance of the asphalt mixtures. This article presents the Bending Beam Creep test performed at temperatures from −20...
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Wisdom from Experience Paradox: Organizational Learning, Mistakes, Hierarchy and Maturity Issues
PublicationOrganizations 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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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublicationFollowing 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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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublicationIn 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
PublicationHuman-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 influence of IT-competency dimensions on job satisfaction, knowledge sharing and performance across industries
PublicationPurpose – Technology makes knowledge management easier. Knowledge sharing is essential for organizational development. Job satisfaction fosters knowledge sharing. Hence, this study aims to develop an understanding of the mutual relationship between knowledge sharing and job satisfaction when both are predicted by information technology (IT)-competency dimensions such as IT-operations, IT-knowledge and IT-infrastructure in the context...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublicationThe 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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Analysis of temporary steel grandstand with different bracing systems exposed to crowd load
PublicationGrandstands are structures which are regularly subjected to dynamic loads generated by crowd motions. It is a dangerous situation when spectators induce rhythmic jumping, dancing, stamping, etc. If the synchronized movement of spectators excites a natural frequency of the structure, resonant response might occur. To avoid such situations, temporary steel grandstands are commonly strengthened using additional elements that create...
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublicationThis 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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Developing Novel Solutions to Realise the European Energy - Information Sharing & Analysis Centre
PublicationFor more effective decision making in preparation for and response to cyberevents in the energy sector, multilevel situation awareness, from technical to strategic is essential. With an uncertain picture of evolving threats, sharing of the latest cybersecurity knowledge among all sector stakeholders can inform and improve decisions and responses. This paper describes two novel solutions proposed during the formation of the European...
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The Mediation Function of Job Satisfaction's between Organizational Culture Dimensions and Knowledge Sharing
PublicationIt is commonly acknowledged that organizational culture is a valuable element of intellectual capital and as a hidden source of competitive advantage can considerably affect the achieving of strategic business goals. The axiological dimension of organizational culture is mostly identified with a set of shared assumptions and values, while work practices mainly define its behavioral dimension. Both these dimensions influence, among...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn 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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Dynamic analysis of temporary steel grandstand equipped with different types of bracing system
PublicationIn the paper, behaviour of a temporary steel grandstand equipped with two different types of bracing system has been analysed through the numerical study. A typical solution concerning application of a diagonal tubular members has been compared with elements proposed by authors and called polymer dampers. A polymer element consists of two L-shape steel members bonded with polymer mass. The aim of the paper is to verify the effectiveness...
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On Nonlinear Bending Study of a Piezo-Flexomagnetic Nanobeam Based on an Analytical-Numerical Solution
PublicationAmong various magneto-elastic phenomena, flexomagnetic (FM) coupling can be defined as a dependence between strain gradient and magnetic polarization and, contrariwise, elastic strain and magnetic field gradient. This feature is a higher-order one than piezomagnetic, which is the magnetic response to strain. At the nanoscale, where large strain gradients are expected, the FM effect is significant and could be even dominant. In...
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On Effective Bending Stiffness of a Laminate Nanoplate Considering Steigmann–Ogden Surface Elasticity
PublicationAs at the nanoscale the surface-to-volume ratio may be comparable with any characteristic length, while the material properties may essentially depend on surface/interface energy properties. In order to get effective material properties at the nanoscale, one can use various generalized models of continuum. In particular, within the framework of continuum mechanics, the surface elasticity is applied to the modelling of surface-related...
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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublicationTraffic-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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Optical flow method for measuring deformation of soil specimen subjected to torsional shearing
PublicationIn this study optical flow method was used for soil small deformation measurement in laboratory tests. The main objective was to observe how the deformation distributes along the whole height of cylindrical soil specimen subjected to torsional shearing (TS test). The experiments were conducted on dry non-cohesive soil specimens under two values of isotropic pressure. Specimens were loaded with low-amplitude cyclic torque to analyze...
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Effect of surface on the flexomagnetic response of ferroic composite nanostructures; nonlinear bending analysis
PublicationOur analysis incorporates the geometrically nonlinear bending of the Euler-Bernoulli ferromagnetic nanobeam accounting for a size-dependent model through assuming surface effects. In the framework of the flexomagnetic phenomenon, the large deflections are investigated referring to von-Kármán nonlinearity. Employing the nonlocal effects of stress coupled to the gradient of strain generates a scale-dependent Hookean stress-strain...
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Experimental tuning of AuAg nanoalloy plasmon resonances assisted by machine learning method
PublicationPlasmonic 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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Supervised-learning-based development of multi-bit RCS-reduced coding metasurfaces
PublicationCoding 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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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublicationComplexity 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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Heating caused by a non periodic ultrasound. Theory and calculations on pulse and stationary sources.
PublicationPrzedstawiono teorię ewolucji ogrzewania na skutek przejścia fali akustycznej każdego typu. Przedyskutowano obliczenia na podstawie nowych wzorów dla fali impulsowej i uderzeniowej. Wzory zgadzają się z klasycznymi w wypadku fal okresowych.
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SIMULATIONS OF FRACTURE IN CONCRETE BEAMS UNDER BENDING USING A CONTINUUM AND DISCRETE APPROACH
PublicationThe paper describes two-dimensional meso-scale results of fracture in notched concrete beams under bending. Concrete was modelled as a random heterogeneous 4-phase material composed of aggregate particles, cement matrix, interfacial transitional zones and air voids. Within continuum mechanics, the simulations were carried out with the finite element method based on a isotropic damage constitutive model enhanced by a characteristic...
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Instantaneous power signal measurements for bearing diagnostics
Open Research DataBearing diagnostics can be carried out based on the method, which relies on the measurement and analysis of the variability of the signal instantaneous power, defined as the product of instantaneous current and voltage power supplied to the engines. Bearing damage causes the appearance of deformations, which are in the form of additional harmonic components...