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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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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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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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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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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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Water-Lubricated Journal Bearings Marine Applications, Design, and Operational Problems and Solutions
PublicationWater-Lubricated Journal Bearings: Marine Applications, Design, and Operational Problems and Solutions provides cutting-edge design solutions, common problems and methods for avoiding them, and material selection considerations for the use of water-lubricated journal bearings in marine environments. These bearings have many advantages, including the absence of the potential for oil contamination. They are also sensitive, and their...
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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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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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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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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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Concept for interpretation and assessment of slide bearings operation in Diesel enfines in probabilistic approach
PublicationW artykule zaproponowano interpretację wartościującą działania, które (podobnie jak przedstawione w mechanice klasycznej działania Hamiltona i Maupertiusa oraz działanie wynikające ze zmiany pędu ciała) jest rozpatrywane jako wielkość fizyczna o jednostce miary zwanej''dżulosekundą''. Przedstawiono propozycję ilościowej interpretacji działania dowolnego poprzecznego łożyska ślizgowego, w którym zachodzą oddziaływania energetyczne...
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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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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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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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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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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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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublicationThis 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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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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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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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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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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Advanced Hysteretic Model of a Prototype Seismic Isolation System Made of Polymeric Bearings
PublicationThe present paper reports the results of acomprehensive study designed to verify the effectiveness of an advanced mathematical model in simulating the complex mechanical behaviour of a prototype seismic isolation system made of polymeric bearings (PBs). Firstly, in order to construct the seismic bearings considered in this research, a specially prepared flexible polymeric material with increased damping properties was employed....
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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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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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Tacit Knowledge Sharing and Creativity. How to Derive Innovation from Project Teams?
PublicationModern companies are increasingly likely to work in a project management environment, which ensures their success in the implementation of innovation. The aim of the study is to prove that tacit knowledge is a mediator for creativity and project performance. Creativity as one of the crucial sources of innovation is stimulated by tacit knowledge. Bearing this fact in mind, the authors studied relations between tacit knowledge, creativity...
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Trust, Collaborative Culture and Tacit Knowledge Sharing in Project Management–a Relationship Model
PublicationThe aim of this research is to study the relationship between Trust, Collaborative Culture, and Tacit Knowledge Sharing in Project Management as a source of Team Creativity in the context of delivering value through knowledge. For this purpose authors conducted a study of 514 Polish professionals with different functions and experience in managing projects in construction industry. The data collected during the study has been analysed...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublicationThis 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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Experimental Study on Effectiveness of a Prototype Seismic Isolation System Made of Polymeric Bearings
PublicationSeismic isolation is identified as one of the most popular and effective methods of protecting structures under strong dynamic excitations. Base isolators, such as Lead Rubber Bearings, High Damping Rubber Bearings, and Friction Pendulum Bearings, are widely used in practice in many earthquake-prone regions of the world to mitigate structural vibrations, and therefore minimize loss of life and property damage during seismic events....
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Induction motor bearings diagnostic indicators based on MCSA and normalized triple covariance
PublicationInduction motors are one of the most widely used electrical machines. Statistics of bearing failures of induction motors indicate, that they constitute more than 40% of induction motor damage. Therefore, bearing diagnosis is so important for trouble-free work of induction motors. The most common methods of bearing diagnosis are based on vibration signal analysis. The main disadvantage of those methods is the need for physical access...
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Current based Normalized Triple Covariance as a bearings diagnostic feature in induction motor
PublicationDiagnosis of induction motors, conducted remotely by measuring and analyzing the supply current is attractive with the lack of access to the engine. So far there is no solution, based on analysis of current, the credibility of which allow use in industry. Statistics of IM bearing failures of induction motors indicate, that they constitute more than 40% of IM damage, therefore bearing diagnosis is so important. The article provides...
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OPERATING CONDITIONS OF SLIDE BEARINGS OF MILLS USED IN KGHM POLSKA MIEDŹ S.A.
PublicationThe paper contains the results from a tec hnical analysis of the conditions of the operation of hydrodynamic bearings supporting the drums of ore processing mills at KGHM Polska Mied ź S.A. A theoretical analysis was performed on the grounds of onsite examination and measurem ents of principal dimensions of the bearings of interest. The computer simulation covered the characteristics of the oil film in the bearings...
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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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Discrepancies in determination of biogenic amines in beer samples by reversed phase and hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry
PublicationBiogenic amines (BAs) are nitrogenous organic bases occurring mainly in fermented food and beverages as a result of free amino acids bacterial decarboxylation. The reversed phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC) based methods were compared in terms of usefulness for determination of BAs in beer samples. Analysis of BAs with the use of RPLC method were carried out after their...
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TiO2-C nanocomposite synthesized via facile surfactant-assisted method as a part of less energy-consuming LED-based photocatalytic system for environmental applications
PublicationA novel facile method was used to incorporate carbon into the titania structure. An alternative synthesis method of carbon-doped TiO2 has been proposed by using a widely used and cheap surfactant. During the process, cetyltrimethylammonium bromide plays a dual role, as a morphology modifier and as a carbon source. The presented approach allows obtained TiO2-C nanostructures to be anatase nanocrystals with carbon being deposited...
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Wpływ olejów smarowych na wytrzymałość zmęczeniową stopów łożyskowych = Lubricating oil influence on fatigue strength of bearing alloys
PublicationBadano wpływ olejów smarowych na wytrzymałość zmęczeniową stopów łożyskowych. Obiektem badań były cienkościenne bimetalowe panwie łożyskowe poddawane zginaniu w różnych ośrodkach podczas testów zmęczeniowych na stanowisku badawczym SKMR-2. Zaobserwowano wyraźny wpływ rodzaju oleju i czynników związanych z wymuszeniami mechanicznymi i cieplnymi na wytrzymałość zmęczeniową warstwy ślizgowej. Przedstawiono wnioski z badań oraz program...
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Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublicationLine heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the...
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Comparison of endotracheal intubation performed with 3 devices by paramedics wearing chemical, biological, radiological, and nuclear personal protective equipment
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Condition Monitoring of Horizontal Sieving Screens—A Case Study of Inertial Vibrator Bearing Failure in Calcium Carbonate Production Plant
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Ecological bearing systems for water turbines - two research programs aimed at making water turbines more "eco-friendly".
PublicationW pracy opisano próby wyeliminowania ropopochodnych środków smarowych z układów łożyskowania turbin wodnych. Próby dotyczą zastosowania bezsmarowych łożysk kierownic i smarowanych wodą łożysk wałów turbin. Wprowadzanie bezsmarowych łożysk kierownic wymaga stworzenia metod prognozowania ich trwałości w warunkach małych oscylacji. Do stosowania w łożyskach wałów zaproponowano smarowane wodą łożyska ceramiczne o oryginalnej konstrukcji,...
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Ekonomična efektivnist` teplovoï pompi v sistemi opalennâ = Economical efficiency of heat pump system in heating system
PublicationW artykule opisano wynik porównawczych obliczeń kosztów ogrzewania budynku jednorodzinnego. Porównano koszty konwencjonalnego ogrzewania z kotłem olejowym jako źródłem ciepła z kosztami ogrzewania układem hybrydowym, w którym współpracują ze sobą dwa żródła ciepła: konwencjonalny kocioł olejowy i sprężarkowa pompa ciepła. Wykonano studium parametryczne kosztów ogrzewania z wykorzystaniem metody kosztów narastających.
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Dry bearing sliding layer transverse flexibility effects on real sliding distance for reciprocating microoscillatory movement of flatcontact surface.
PublicationW referacie omówiono wpływ właściwości mechanicznych i kształtu warstwy ślizgowej z bezsmarowego materiału łożyskowego. Wcześniej omówione i publikowane wyniki badań doświadczalnych i analizy numerycznej wyjaśniły i potwierdziły, dlaczego rzeczywista droga tarcia jest znacznie mniejsza od nominalnej w warunkach mikrooscylacji. Wyniki przeprowadzonej analizy numerycznej pozwoliły możliwie najlepiej ukształtować powierzchnię ślizgania...