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Limitations of Emotion Recognition from Facial Expressions in e-Learning Context
PublikacjaThe paper concerns technology of automatic emotion recognition applied in e-learning environment. During a study of e-learning process the authors applied facial expressions observation via multiple video cameras. Preliminary analysis of the facial expressions using automatic emotion recognition tools revealed several unexpected results, including unavailability of recognition due to face coverage and significant inconsistency...
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Assessment of student language skills in an e-learning environment
PublikacjaThis article presents the role of various assessment structures that can be used in a VLE. e-Learning language courses offer tutors a wide range of traditional and computer-generated formative and summative assessment procedures and tools. They help to evaluate each student’s progress, monitor their activities and provide varied support, which comes from the tutor, the course structure and materials as well as other participants....
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Learning from Mistakes. A Study on Maturity and Adaptability to Change
PublikacjaLearning culture matters; company culture must support continuous improvement. Organizational learning is a process of identifying and modifying mistakes that result from interactions between co-workers. The article aims to explore the learning power via errors, using the level of organizational maturity as a moderator. Companies need to know how organizational maturity may moderate the adaptability to change via the acceptance...
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Assesment of operation of ship main diesel engine using the theory of semi-markovian and markov processes.
PublikacjaTo precisely determine the task it is necessary to specify also its duration time, apart from conditions in which it will be realized. When considering propulsion engine, i.e. the main element of ship propulsion system, especially important becomes not only the problem which amount of energy could be at one's disposal but also within which time interval it could be delivered. Therefore apart from applying the commonly used reliability...
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Processes of enhancing the intelligence of Learning Organizations on the basis of Competence Centers
PublikacjaThe process of organizational learning and proper knowledge management became today one of the major challenges for the organization acting in the knowledge-based economy. According to the observations of the authors of this paper the demand for formalization of knowledge management processes and organizational learning is particularly evident in research institutions, established either by the universities, or the companies. The...
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Testing and sampling devices for monitoring volatile and semi-volatile organic compounds in indoor air
PublikacjaAdults spend most of their time in enclosed spaces (e.g., apartment, office and public buildings). According to research conducted by scientists, air quality indoors is much worse than the ambient air quality outdoors. Hazardous chemicals found in air indoors can adversely affect the functioning of the human body and cause many respiratory and circulatory diseases. Harmful chemical compounds (mainly volatile organic compounds and...
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The Cultures of Knowledge Organizations: Knowledge, Learning, Collaboration (KLC)
PublikacjaThis book focuses on seeing, understanding, and learning to shape an organization’s essential cultures. The book is grounded on a fundamental assumption that every organization has a de facto culture. These “de facto cultures” appear at first glance to be serendipitous, vague, invisible, and unmanaged. An invisible and unrecognized de facto culture can undermine business goals and strategies and lead to business failures. The authors...
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Designing acoustic scattering elements using machine learning methods
PublikacjaIn the process of the design and correction of room acoustic properties, it is often necessary to select the appropriate type of acoustic treatment devices and make decisions regarding their size, geometry, and location of the devices inside the room under the treatment process. The goal of this doctoral dissertation is to develop and validate a mathematical model that allows predicting the effects of the application of the scattering...
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Social media for e-learning of citizens in smart city
PublikacjaThe rapid development of social media can be applied for citizens’ e-learning in a smart city. Big cities have to cope with several open issues like a growing population or a traffic congestion. Especially, a home and public space is supposed to be used in more efficient way. Sustainable homes and buildings can be planned with using some modern techniques. Even currently, there is a huge problem with a lack of key resources like...
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Assessing the attractiveness of human face based on machine learning
PublikacjaThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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Application Isssues of the Semi-Markov Reliability Model
PublikacjaPredicting the reliability of marine internal combustion engines, for instance, is of particular importance, as it makes it possible to predict their future reliability states based on the information on the past states. Correct reliability prediction is a complex process which consists in processing empirical results obtained from operating practice, complemented by analytical considerations. The process of technical state changes...
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Ecology and Conservation of Steppes and Semi-Natural Grasslands
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Investigations of transverse stability of semi-displacement ships
PublikacjaPrzedstawiono wyniki eksperymentalnych badań modelowych poprzecznej stateczności jednostek półślizgowych, których celem było określenie wpływu prędkości oraz parametrów kształtu kadłuba na stateczność poprzeczną. Na podstawie wyników badań opracowano algorytmy, uwzględniające zmiany ramienia prostującego w funkcji prędkości, kąta przechyłu i parametrów geometrycznych kadłuba które mogą być wykorzystane do oceny stateczności poprzecznej...
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Semi-Markov Approach to the Shipping Safety Modelling
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Evaluation of ChatGPT Applicability to Learning Quantum Physics
PublikacjaChatGPT is an application that uses a large language model. Its purpose is to generate answers to various questions as well as provide information, help solve problems and participate in conversations on a wide range of topics. This application is also widely used by students for the purposes of learning or cheating (e.g., writing essays or programming codes). Therefore, in this contribution, we evaluate the ability of ChatGPT...
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Loosely-Tied Distributed Architecture for Highly Scalable E-Learning System
PublikacjaVast majority of modern e-learning products are based on client-server architecture and utilization of web-based technologies (WBT). Such approach permits easy creation of e-learning systems that do not require a complex, operating system dependant client software. Unfortunately there are also drawbacks of such solution. Because of the majority of mechanisms are located on the server, its usage levels trend to build up quickly...
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Informal Workplace Learning and Employee Development. Growing in the Organizational New Normal
PublikacjaThe new paradigm in employee development assumes that employees should proactively direct their learning and growth. Most workplace learning is basically informal and occurs through daily work routines, peer-to-peer interactions, networking, and typically brings about significant positive outcomes to both individuals and organizations. Yet, workplace learning always occurs in a pre-defined context and this context has recently...
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A semi-empirical model for flow boiling heat transfer with account of the reduced pressure effect
PublikacjaIn the present study the attention was focused on the influence of reduced pressure on the predictions of heat transfer during flow boiling at the extensive range of pressures. The results of calculations were to test the sensitivity of the in-house flow boiling model with respect to the selection of the appropriate two-phase flow multiplier, which is one of the distinctive elements of that model. For this purpose a few two-phase...
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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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COMPARATIVE ANALYSIS OF RESULTS OF APPLICATION OF MARKOV AND SEMI-MARKOV PROCESSES TO RELIABILITY MODELS OF MULTI-STATE TECHNICAL OBJECTS
PublikacjaDuring rational operation of technical objects and systems various operational decisions are made and decision-making process itself should be consisted in selecting that considered most favourable out of all possible to be taken. Choice of such decision is possible after taking into account many different information items but it never be completely correct without accounting for data and indices dealing with reliability. In...
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The time of the first transition of the semi-Markov process in the evaluation of diesel engine operation
PublikacjaW referacie przedstawiono rozwinięcie prezentowanej w literaturze metody ilościowej oceny działania na przykładzie okrętowego silnika głównego z zapłonem samoczynnym. Według tej interpretacji, działanie silnika może zostać przedstawione jako wielkość fizyczna. W tym aspekcie, na przykładzie okrętowego silnika napędu głównego dokonano oceny przydatności tej wielkości do opisu własności niezawodnościowych silnika. Precyzyjne określenie...
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Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublikacjaThe acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...
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Data augmentation for improving deep learning in image classification problem
PublikacjaThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Internet photogrammetry as a tool for e-learning
PublikacjaAlong with Internet development, there were interactive applications which allow for remote sensing and photogrammetric analysis. An example of an application that can provide Earth images and make it possible to measure distances in these images is Google Earth. The authors, who have experience from 2001-2015 argue that it is possible and it is important to create more advanced photogrammetric network applications. In this there...
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Innovative e-learning approach in teaching based on case studies - Innocase project
PublikacjaThe article presents the application of innovative e-learning approach for the creation of case study content. Case study methodology is becoming more and more widely applied in modern education, especially in business and management field. Although case study methodology is quite well recognized and used in education, there are still few examples of developing e-learning content on the basis of case studies. This task is to be...
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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublikacjaThis study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...
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Explainable machine learning for diffraction patterns
PublikacjaSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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Semi-transparent ordered TiO2 nanostructures prepared by anodization of titanium thin films deposited onto the FTO substrate
PublikacjaIn a significant amount of cases, the highly ordered TiO2nanotube arrays grow through anodic oxidationof a titanium metal plate immersed in electrolyte containing fluoride ions. However, for some practicalapplications, e.g. solar cells or electrochromic windows, the semi-transparent TiO2formed directly onthe transparent, conductive substrate is very much desired. This work shows that high-quality Ti coatingcould be formed at room...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublikacjaWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
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Measurement of the Development of a Learning IT Organization Supported by a Model of Knowledge Acquisition and Processing
PublikacjaThe paper presents a model of knowledge acquisition and processing for the development of learning organizations. The theory of a learning organization provides neither metrics nor tools to measure its development The authors' studies in this field are based on their experience gathered after projects realized in real IT organizations. The authors have described the construction of the model and the methods of its verification...
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Towards Scalable Simulation of Federated Learning
PublikacjaFederated learning (FL) allows to train models on decentralized data while maintaining data privacy, which unlocks the availability of large and diverse datasets for many practical applications. The ongoing development of aggregation algorithms, distribution architectures and software implementations aims for enabling federated setups employing thousands of distributed devices, selected from millions. Since the availability of...
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A model of fuel combustion process in the marine reciprocating engine work space taking into account load and wear of crankshaft-piston assembly and the theory of semi-Markov processes
PublikacjaThe ar ticle analyses the operation of reciprocal internal combu stion engines, with mar ine engines u sed a s an example. The analysis takes into account types of energy conversion in the work spaces (cylinders) of these engines, loads of their crankshaft-piston assemblies, and types of fuel combustion which can take place in these spaces during engine operation. It is highlighted that the analysed time-dependent loads of marine...
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Organizational Wisdom: The Impact of Organizational Learning on the Absorptive Capacity of an Enterprise
PublikacjaPurpose: In this article, we analyze the concept of organizational wisdom, indicating its key elements and verifieng the relationships between them. Design/Methodology/Approach: The study was conducted at Vive Textile Recycling Sp. z o.o in Poland. Empirical data was collected from 138 managers using the PAPI technique. Structural equation modelling (SEM) was performed to test the research hypotheses. Additionally, the significance...
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Morphology and local chain structure of polyamide 6 modified in the solid state with a semi-aromatic nylon salt
PublikacjaStructural and conformational differences between the polyamide 6 (PA6) homopolymer and two copolymers of PA6 modified in the solid state with 20 and 30 wt% of the semi-aromatic nylon salt of 1,5-diamino-2-methylpentane (Dytek A) and isophthalic acid (IPA) in the feed were investigated. Room temperature wide-angle X-ray diffraction (WAXD) analysis together with 13C{1H} cross-polarization/magic-angle spinning solid-state (CP/MAS)...
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A Highly Scalable, Modular Architecture for Computer Aided Assessment e-Learning Systems
PublikacjaIn this chapter, the authors propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. The authors' research proved that such architecture, while well suited for didactic content distribution systems is ill-suited for knowledge...
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E-Learning Service Management System For Migration Towards Future Internet Architectures
PublikacjaAs access to knowledge and continuous learning are among the most valuable assets in modern, technological society, it is hardly surprising that e-learning solutions can be counted amongst the most important groups of services being deployed in modern network systems. Based on analysis of their current state-of-the-art, we decided to concentrate our research and development work on designing and implementing a management system...
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Semi-adaptive feedback active control of MRI noise
PublikacjaA feedback controller is proposed for cancellation of magnetic resonance imaging (MRI) noise. The design of the controller takes into account specific features of the MRI noise signal. Simulation results show that a considerable rejection rate of the MRI noise can be obtained.
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Semi-Markov model of diesel engines' operating process.
PublikacjaNajistotniejszym problemem eksploatacji silników o zapłonie samoczynnym jest problem racjonalnego (a zwłaszcza optymalnego) sterowania procesem eksploatacji tych silników. Sterowanie takie może ułatwić zastosowanie iteracyjnego algorytmu wyznaczania optymalnych strategii opracowanego przez R.A. Howarda. Wykorzystanie jednak tego algorytmu do sterowania procesem eksploatacji silników wymaga między innymi opracowania modelu procesu...
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Incremental and Semi-Incremental Construction of Pseudo-Minimal Automata
PublikacjaPrzedstawione zostają modyfikacje trzech algorytmów przyrostowego i półprzyrostowego tworzenia automatów minimalnych w taki sposób, aby tworzyły automaty pseudominimalne. Istniejący od dawna algorytm Revuza tworzy takie automaty szybciej i zużywając mniej pamięci, ale wymaga kłopotliwego sortowania. Nie nadaje się też do dodawania nowych słów do automatu - ważnej czynności w realizacji dynamicznej doskonałej funkcji mieszającej....
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Semi-incremental addition of strings to a cyclic finite automaton
PublikacjaMaszyny o skończonej liczbie stanów są szeroko stosowane jako słowniki w przetwarzaniu języka naturalnego. Odznaczają się szybkim czasem przetwarzania i małymi wymaganiami pamięciowymi. Przedstawiamy nowy algorytm dodawania nowych słów do języka cyklicznego automatu skończonego. Algorytm jest rozszerzeniem na automaty cykliczne półprzyrostowego algorytmu Watsona dla automatów acyklicznych. Przekształcenie jest dokonane w duchu...
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Semi complex navigation with an active optical gesture sensor
PublikacjaThis paper presents the methods of diversified touchless interactions between a user and a mobile platform utilizing the optical gesture sensor. The sensor uses 8 photodiodes to measure the reflected light in the active mode (using embedded LEDs) or it measures shadows caused by fingers in the passive mode. Several algorithms were implemented: automatic mode switching, adaptive illumination level compensation, resolution improvements...
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Continuous learning as a method of raising qualifications – the perspective of workers, employers and training organizations
PublikacjaContinuous learning is discussed in strategic documents of Poland and the European Union. In Poland, the idea of continuous learning is not very popular. However, in the context of strong competition in the labour market and the progressive globalization processes, the skills issue takes on new meaning — both for employees and employers. In order to adapt skills to labour market needs it is necessary to conduct adequate studies...
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Divide and not forget: Ensemble of selectively trained experts in Continual Learning
PublikacjaClass-incremental learning is becoming more popular as it helps models widen their applicability while not forgetting what they already know. A trend in this area is to use a mixture-of-expert technique, where different models work together to solve the task. However, the experts are usually trained all at once using whole task data, which makes them all prone to forgetting and increasing computational burden. To address this limitation,...
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Multimedia industrial and medical applications supported by machine learning
PublikacjaThis article outlines a keynote paper presented at the Intelligent DecisionTechnologies conference providing a part of the KES Multi-theme Conference “Smart Digital Futures” organized in Rome on June 14–16, 2023. It briefly discusses projects related to traffic control using developed intelligent traffic signs and diagnosing the health of wind turbine mechanisms and multimodal biometric authentication for banking branches to provide...
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Determination of rectification corrections for semi gantry crane rail axes in the local 3D coordinate system
PublikacjaElectronic tacheometers are currently the standard instruments used in geodetic work, including also geodetic engineering measurements. The main advantage connected with this equipment is among others high accuracy of the measurement and thus high accuracy of the final determinations represented for example by the points’ coordinates. One of many applications of the tacheometers is the measurement of crane rail axes. This measurement...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Bandwidth-Controllable Third-Order Band Pass Filter Using Substrate Integrated Full- and Semi-Circular Cavities
PublikacjaThe article presents a novel circular substrate integrated waveguide (SIW) bandpass filter (BPF) with controllable bandwidth. The proposed BPF is configured using two microstrip feedlines, semi- circular SIW cavities, capacitive slots, and inductive vias. The circular cavity is bisected into two halves, with the two copies thereof being cascaded. Two bisected and cascaded structures obtained this way are subsequently connected...
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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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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublikacjaMusic analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...
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Necessity for and possibility of application of the theory of semi-markov processes to determine reliability of diagnising systems
PublikacjaW opracowaniu uzasadniono konieczność określenia niezawodności systemów diagnozujących (SDG) do sformułowania diagnozy o stanie dowolnego urządzenia technicznego jako systemu diagnozowanego (SDN). Wykazano, że znajomość niezawodności SDG umożliwia określenie wiarygodności diagnozy. Przyjęto, że wiarygodność diagnozy może być określona jako właściwość diagnozy określająca stopień rozpoznania przez system diagnozujący (SDG) rzeczywistego...
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Enhancing Seismic Performance of Semi-rigid Connection Using Shape Memory Alloy Bolts Considering Nonlinear Soil–Structure Interaction
PublikacjaSteel Moment-Resisting Frames (SMRFs) have their lateral resistance for their rigid connections, while real conditions have shown that the rigidity of a connection depends on the bolts and the end-plate thickness, which may not provide the assumed rigidity in design process. In this research, the main goal is to enhance the semi-rigid connections using shape memory alloy (SMA) bolts and explore their effects on the seismic limit-state...
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The influence of phosphorus fractions in bottom sediments on phosphate removal in semi-natural systems as the 3rd stage of biological wastewater treatment
PublikacjaThe research was carried out in two semi-natural systems (the polishing ponds in Swarzewo and the free water surface constructed wetland in Zarnowiec) in Poland. They were built as the 3rd stage of a conventional mechanical–biological wastewater treatment plant. These systems were built to improve the quality of the effluent of treated wastewater. In the polishing ponds and FWS wetland system, suspended solids, organic matter as...
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Study on effective front region thickness of PCM in thermal energy storage using a novel semi-theoretical model
PublikacjaThermal energy storage in mobile applications, particularly battery of electric vehicles, is currently gaining a lot of importance. In this paper, a semi-theoretical time-dependent mathematical model of the phase change in a double shell thermal energy storage module has been developed where the inner tube is a heat exchange surface. An effective front region thickness for the melting and solidification process has been studied....
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Computational Simulation of the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis chapter investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organisational culture results in better mistake management and thus better organisational learning, (2) Effective organisational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning...
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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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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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An integrated e-learning services management system providing HD videoconferencing and CAA services
PublikacjaIn this paper we present a novel e-learning services management system, designed to provide highly modifiable platform for various e-learning tools, able to fulfill its function in any network connectivity conditions (including no connectivity scenario). The system can scale from very simple setup (adequate for servicing a single exercise) to a large, distributed solution fit to support an enterprise. Strictly modular architecture...
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublikacjaThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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WEB-CAM AS A MEANS OF INFORMATION ABOUT EMOTIONAL ATTEMPT OF STUDENTS IN THE PROCESS OF DISTANT LEARNING
PublikacjaNew methods in education become more popular nowadays. Distant learning is a good example when teacher and student meet in virtual environment. Because interaction in this virtual world might be complicated it seems necessary to assure as much methods of conforming that student is still engaged in the process of learning as it is possible. We would like to present assumption that by means of web-cam we will be able to track facial...
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Deep learning for ultra-fast and high precision screening of energy materials
PublikacjaSemiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...
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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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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublikacjaBiometric 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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Ammonia amendment promotes high rate lactate production and recovery from semi-continuous food waste fermentation
PublikacjaIn this study, a reliable approach using ammonia nitrogen was proposed to increase lactate production during semi-continuous food waste (FW) fermentation under mesophilic conditions. Both free ammonia nitrogen (FAN) and ammonium ion (NH4+-N) were present in mesophilic reactors, with a wide FAN/NH4+-N ratio variation due to the intermittent pH control. The investigation of responsible mechanisms revealed that the increased production...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublikacjaCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Modelling of saturated, subcooled and post-dryout flow boiling with the energy dissipation based semi-empirical model
PublikacjaA comprehensive semi-empirical model for saturated, subcooled and post dryout heat transfer is presented based on considerations of energy dissipation in the flow. The fundamental hypothesis in the model is the fact that heat transfer during flow boiling can be treated as a sum of two contributions constituting the total energy dissipation in the flow, namely the energy dissipation due to the shearing flow without the bubbles and...
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THE ONLINE APPLICATION AND E-LEARNING IN THE COMPETENCE-BASED MANAGEMENT IN PUBLIC ADMINISTRATION ORGANIZATIONS
PublikacjaThe integration of effective management of work-related processes and utilization of human resources potential leads to the development of organization. The purpose of this paper was to examine how the principles of competences-based management can be introduced to enhance organization’s effectiveness in human resources management. A model of assessment and development of competences-based management, embracing an online application...
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Visually validated semi-automatic high-frequency oscillation detection aides the delineation of epileptogenic regions during intra-operative electrocorticography
PublikacjaOBJECTIVE: To test the utility of a novel semi-automated method for detecting, validating, and quantifying high-frequency oscillations (HFOs): ripples (80-200 Hz) and fast ripples (200-600 Hz) in intra-operative electrocorticography (ECoG) recordings. METHODS: Sixteen adult patients with temporal lobe epilepsy (TLE) had intra-operative ECoG recordings at the time of resection. The computer-annotated ECoG recordings were visually...
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Concrete mix design using machine learning
PublikacjaDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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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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Deep learning based thermal image segmentation for laboratory animals tracking
PublikacjaAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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A semi-Markov model of fuel combustion process in a Diesel engine
PublikacjaW artykule przedstawiono czterostanowy model procesu spalania w przestrzeniach roboczych (cylindrach) silników o zapłonie samoczynnym w formie procesu semimarkowskiego, dyskretnego w stanach i ciągłego w czasie. Wartościami tego procesu są stany odpowiadające powszechnie akceptowanym rodzajom spalania w tego rodzaju silnikach a mianowicie takie stany procesu jak: spalanie pełne (całkowite i zupełne), spalanie niezupełne, spalanie...
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Supporting First Year Students Through Blended-Learning - Planning Effective Courses and Learner Support
PublikacjaHigher education has been actively encouraged to find more effective and flaxible delivery models to provide all students with access to good quality learning experiences. This paper describes students opinion about using e-learning techniques and their participation in courses provided in different ways as additional help and expectations of first year students.
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Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublikacjaConcrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...
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Determination of Vehicles Load Equivalency Factors for Polish Catalogue of Typical Flexible and Semi-rigid Pavement Structures
PublikacjaThe new Polish Catalog of Typical Flexible and Semi-rigid Pavement Structures was introduced to use in practice in 2014. Much of works were focused on actualization of vehicles load equivalency factors. For this purpose data delivered from weigh-inmotion were analyzed. Four methods of determination of load equivalency factors for pavement structure design were compared. The analysis showed that fourth power equation, AASHTO 1993...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change: with Focus on Organizational Culture and Organizational Learning
PublikacjaTransformative 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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Adaptive Dynamical Systems Modelling of Transformational Organizational Change with Focus on Organizational Culture and Organizational Learning
PublikacjaTransformative 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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Open source solution LMS for supporting e-learning/blended learning engineers
PublikacjaW artykule zaprezentowano darmowe systemy zarządzania kształceniem na odległość wspomagające e-learningowe/mieszane nauczanie inżynierów. Pierwszy system TeleCAD został opracowany w ramach projektu Leonardo da Vinci (1998-2001). System TeleCAD był propozycją w projekcie V Ramowy CURE (2003-2006). W roku 2003 dzięki projektowi Leonardo da Vinci EMDEL (2001-2005) Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej wybrało system...
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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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Distance learning trends: introducing new solutions to data analysis courses
PublikacjaNowadays data analysis of any kind becomes a piece of art. The same happens with the teaching processes of statistics, econometrics and other related courses. This is not only because we are facing (and are forced to) teach online or in a hybrid mode. Students expect to see not only the theoretical part of the study and solve some practical examples together with the instructor. They are waiting to see a variety of tools, tutorials,...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublikacjaA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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Reinforcement Learning Algorithm and FDTD-based Simulation Applied to Schroeder Diffuser Design Optimization
PublikacjaThe aim of this paper is to propose a novel approach to the algorithmic design of Schroeder acoustic diffusers employing a deep learning optimization algorithm and a fitness function based on a computer simulation of the propagation of acoustic waves. The deep learning method employed for the research is a deep policy gradient algorithm. It is used as a tool for carrying out a sequential optimization process the goal of which is...
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Detecting Lombard Speech Using Deep Learning Approach
PublikacjaRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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User -friendly E-learning Platform: a Case Study of a Design Thinking Approach Use
PublikacjaE-learning systems are very popular means to support the teaching process today. These systems are mainly used by universities as well as by commercial training centres. We analysed several popular e-learning platforms used in Polish universities and find them very unfriendly for the users. For this reason, the authors began the work on the creation of a new system that would be not only useful, but also usable for students, teachers...
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The semi-Markov model of the process of appearance of sea-going ship propupsion system ability and inability states in application to determining the reliablity of these systems
PublikacjaThe article presents possible application of the theory of semi-Markov processes in creating the eight-state model of the process of appearance of the propulsion systems ability and inability states on sea-going vessels performing transportation tasks in a relatively long operating time t (t → ∞). The model has been proved to be able to be successfully used for determining the reliability of the abovementioned systems. The probability...
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Training of Deep Learning Models Using Synthetic Datasets
PublikacjaIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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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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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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Unconventional and user-friendly sampling techniques of semi-volatile organic compounds present in an indoor environment: An approach to human exposure assessment
PublikacjaThe commonly applied solutions used to assess the potential risk of human exposure to semi-volatile organic compounds (SVOCs) are based on the investigation of biological samples collected in an invasive or non-invasive manner. For SVOCs, which are typically introduced to humans through the respiratory system, dermal adsorption, or digestive system, sampling solutions generally used in the indoor environments are classified as...
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APPLICATION OF THE THEORY OF SEMI-MARKOV PROCESSES TO DETERMINE A LIMITING DISTRIBUTION OF THE PROCESS OF CHANGES OF ABILITY AND INABILITY STATES OF FUEL SUPPLY SYSTEMS IN HEAVY FUEL DIESEL ENGINES
PublikacjaThe paper presents applicability of the theory of semi-Markov processes to determine a limiting distribution of the process of changes of technical states of fuel systems for marine engines running on heavy fuel oils. The proposed study of this process includes the components of such fuel systems like: 1 - injectors, 2 - high pressure hoses, 3 - injection pumps, 4 - low pressure hoses, 5 – fine filters, 6 - coarse filters, 7 – fuel-feed...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublikacjaHigher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...
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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublikacjaMachine 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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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader's behavior must align for the best learning effects....
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublikacjaThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning effects....
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublikacjaMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublikacjaThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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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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Can Evaluation Patterns Enable End Users to Evaluate the Quality of an e-learning System? An Exploratory Study.
PublikacjaThis paper presents the results of an exploratory study whose main aim is to verify if the Pattern-Based (PB) inspection technique enables end users to perform reliable evaluation of e-learning systems in real work-related settings. The study involved 13 Polish and Italian participants, who did not have an HCI background, but used e-learning platforms for didactic and/or administrative purposes. The study revealed that the participants...