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Search results for: ISLE DATASET
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Enabling Deeper Linguistic-based Text Analytics – Construct Development for the Criticality of Negative Service Experience
PublicationSignificant progress has been made in linguistic-based text analytics particularly with the increasing availability of data and deep learning computational models for more accurate opinion analysis and domain-specific entity recognition. In understanding customer service experience from texts, analysis of sentiments associated with different stages of the service lifecycle is a useful starting point. However, when richer insights...
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Data regarding a new, vector-enzymatic DNA fragment amplification-expression technology for the construction of artificial, concatemeric DNA, RNA and proteins, as well as biological effects of selected polypeptides obtained using this method
PublicationApplications of bioactive peptides and polypeptides are emerging in areas such as drug development and drug delivery systems. These compounds are bioactive, biocompatible and represent a wide range of chemical properties, enabling further adjustments of obtained biomaterials. However, delivering large quantities of peptide derivatives is still challenging. Several methods have been developed for the production of concatemers –...
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Noise profiling for speech enhancement employing machine learning models
PublicationThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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Machine learning applied to acoustic-based road traffic monitoring
PublicationThe 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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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublicationAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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Material characterisation of biaxial glass-fibre non-crimp fabrics as a function of ply orientation, stitch pattern, stitch length and stitch tension
PublicationDue to their high density-specific stiffnesses and strength, fibre reinforced plastic (FRP) composites are particularly interesting for mobility and transport applications. Warp-knitted non-crimp fabrics (NCF) are one possible way to produce such FRP composites. They are advantageous because of their low production costs and the ability to tailor the properties of the textile to the reinforcement and drape requirements of the application....
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Hey student, are you sharing your knowledge? A cluster typology of knowledge sharing behaviours among students
PublicationKnowledge Sharing (KS) is crucial for all organisations to better face current and future challenges. It is justifiable to assume that after graduation, students will have to face the coming challenges at societal and business levels, and that they will need the adequate KS skills to do so. Though the importance of KS is established, the understanding of how students pass on their knowledge is still fragmented and underdeveloped....
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Applying the Lombard Effect to Speech-in-Noise Communication
PublicationThis study explored how the Lombard effect, a natural or artificial increase in speech loudness in noisy environments, can improve speech-in-noise communication. This study consisted of several experiments that measured the impact of different types of noise on synthesizing the Lombard effect. The main steps were as follows: first, a dataset of speech samples with and without the Lombard effect was collected in a controlled setting;...
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Emotion Recognition from Physiological Channels Using Graph Neural Network
PublicationIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...
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Machine learning applied to acoustic-based road traffic monitoring
PublicationThe 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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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublicationArtificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained...
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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublicationHandwriting biometrics applications in e-Security and e-Health are addressed in the course of the conducted research. An automated graphomotor analysis method for the dynamic electronic representation of the handwritten signature authentication was researched. The developed algorithms are based on dynamic analysis of electronically handwritten signatures employing neural networks. The signatures were acquired with the use of the...
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Motors of influenza vaccination uptake and vaccination advocacy in healthcare workers: A comparative study in six European countries
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Wieloobszarowa rozmyta regulacja PIλDµ mocy reaktora jądrowego
PublicationWartykule przedstawiono wieloobszarowy regulator rozmyty z lokalnymi regulatorami PIλDµ niecałkowitego rzędu. Regulator ten ostał zaprojektowany do sterowania mocą reaktora jądrowego typu PWR (Pressurized Water Reactor). Do syntezy wieloobszarowego regulatora PIλDµ wykorzystano model matematyczny reaktora PWR o parametrach skupionych obejmujący procesy generacji i wymiany ciepła oraz efektów reaktywnościowych. Nastawy lokalnych...
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Wieloobszarowa rozmyta regulacja PIλDμ mocy reaktora jądrowego
PublicationW artykule przedstawiono wieloobszarowy regulator rozmyty z lokalnymi regulatorami PIλDμ niecałkowitego rzedu. Regulator ten został zaprojektowany do sterowania mocą reaktora jądrowego typu PWR (Pressurized Water Reactor). Do syntezy wieloobszarowego regulatora PIDμ wykorzystano model matematyczny reaktora PWR o parametrach skupionych obejmujący procesy generacji i wymiany ciepła oraz efektów reaktywnościowych. Nastawy lokalnych...
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Absencja chorobowa - szacunek niewytworzonego PKB
PublicationKoszty pośrednie spowodowane absencją chorobową bądź prezenteizmem pracowników są sporadycznie uwzględniane w polskich analizach ekonomicznych. Nie szacuje się wielkości utraconego PKB na skutek chorób, przedwczesnych zgonów, długiego dochodzenia do zdrowia oraz nie uwzględnia w wycenach farmakoekonomicznych. Brakuje jednolitej metodologii obliczania kosztów pośrednich. Celem opracowania jest oszacowanie, ile gospodarka narodowa...
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OCENA KLIMATU PRACY W ZESPOLE WIELOKULTUROWYM
PublicationArtykuł dotyczy tematyki zespołów wielokulturowych, które ze względu na specyfikę globalnego rynku odgrywają coraz ważniejszą rolę we współczesnych organizacjach. Skoncentrowano się na kształtowaniu klimatu pracy zespołowej, który pozwala wykorzystać potencjał zespołu zróżnicowanego kulturowo, podkreślając potencjalne utrudnienia i ich źródła. Zaprezentowano wyniki badań kwestionariuszowych, których celem było sprawdzenie, na ile...
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Standardy IEEE wspierające koncepcje Ethernet End-to-End
PublicationW pracy wykazano, że ostatnie prace komitetów IEEE 802.1 i 802.3 znacznie przybliżyły realizację koncepcji Ethernet End-to-End. Wskazano, że o ile problemy skalowalności zostały w dużej mierze rozwiązane, o tyle inne zagadnienia związane m.in. z niezawodnością i zarządzaniem wymagają jeszcze dużego wysiłku standaryzacyjnego. Jednakże niektóre przedstawione w pracy propozycje IEEE są już na ukończeniu i możliwość realizacji sieci...
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Weryfikacja algorytmów MPPT dla modułów fotowoltaicznych w warunkach przesłonięcia
PublicationIntensywny rozwój technologii powoduje obniżenie ceny modułów fotowoltaicznych i dedykowanych przetwornic. Podstawą opłacalności jest wysoka sprawność całego układu na którą składają się sprawności modułów, przetwornic oraz algorytmu śledzenia maksymalnej mocy (MPPT - Maximum Power Point Tracking). Znane i stosowane algorytmy mają MPPT sprawności od ok. 95 do 99%, o ile ogniwa mają identyczne parametry i są jednakowo nasłonecznione....
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Algorytmy MPPT dla modułów fotowoltaicznych w warunkach przesłonięcia
PublicationIntensywny rozwój technologii powoduje obniżenie ceny modułów fotowoltaicznych i dedykowanych przetwornic. Podstawą opłacalności jest wysoka sprawność całego układu na którą składają się sprawności modułów, przetwornic oraz algorytmu śledzenia maksymalnej mocy (MPPT - Maximum Power Point Tracking). Znane i stosowane algorytmy mają MPPT sprawności od ok. 95 do 99%, o ile ogniwa mają identyczne parametry i są jednakowo nasłonecznione....
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Porównanie heurystyk dla problemu szeregowania zadań czasowo-zależnych o wspólnym podstawowym czasie wykonywania
PublicationW pracy rozważany jest następujący, jednoprocesorowy problem szeregowania zadań czasowo-zależnych. danych jest n+1 zadań o czasach wykonywania postaci pi = a + bisi, gdzie si oznacza czas rozpoczęcia wykonywania i-tego zadania, a > 0, bi > 0, i = 0, 1, ..., n. wszystkie zadania są niepodzielne i dostępne w chwili t0 = 0. należy znaleźć harmonogram minimalizujący łączny czas zakończenia. w pracy przedstawiono algorytm, który, o...
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Rating mathematical models for first-pass of tracer in pCT lung studies
PublicationThis paper presents a comparison of model based on the Gauss function and the most commonly used Gamma-variate model in perfusion computed tomography (pCT) lung studies. It also verifies whether used model affects value of blood volume parameter. Three mean concentration-time curves were created from actual pCT measurements: arterial input function, blood vessels in lungs and lung parenchyma. On the basis of these mean curves we...
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublicationBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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Impact of Visual Image Quality on Lymphocyte Detection Using YOLOv5 and RetinaNet Algorithms
PublicationLymphocytes, a type of leukocytes, play a vital role in the immune system. The precise quantification, spatial arrangement and phenotypic characterization of lymphocytes within haematological or histopathological images can serve as a diagnostic indicator of a particular lesion. Artificial neural networks, employed for the detection of lymphocytes, not only can provide support to the work of histopathologists but also enable better...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Going all in or spreading your bet: a configurational perspective on open innovation interaction channels in production sectors
PublicationUsing different interaction channels within open innovation partnerships holds the potential to enhance the chance of success in production sectors. However, our comprehension of how open innovation partnerships are affected by varying combinations of interaction channels, and how this corelates with their level of open innovation output, remains limited. There are discrepancies in the current literature regarding the individual...
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Investigating Feature Spaces for Isolated Word Recognition
PublicationMuch attention is given by researchers to the speech processing task in automatic speech recognition (ASR) over the past decades. The study addresses the issue related to the investigation of the appropriateness of a two-dimensional representation of speech feature spaces for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and timefrequency signal representation...
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Semantic URL Analytics to Support Efficient Annotation of Large Scale Web Archives
PublicationLong-term Web archives comprise Web documents gathered over longer time periods and can easily reach hundreds of terabytes in size. Semantic annotations such as named entities can facilitate intelligent access to the Web archive data. However, the annotation of the entire archive content on this scale is often infeasible. The most efficient way to access the documents within Web archives is provided through their URLs, which are...
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Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublicationIn the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...
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Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data
PublicationThis paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult financial situation that may lead to consumer bankruptcy. In the face of the current global pandemic crisis, the future of household finances...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublicationMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Towards application of uncertainty quantification procedure combined with experimental procedure for assessment of the accuracy of the DEM approach dedicated for granular flow modeling
PublicationThere is a high demand for accurate and fast numerical models for dense granular flows found in many industrial applications. Nevertheless, before numerical model can be used its need to be always validated against experimental data. During the validation, it is important to consider how the measurement data sets, as well as the numerical models, are affected by errors and uncertainties. In this study, the uncertainty quantification...
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Urban scene semantic segmentation using the U-Net model
PublicationVision-based semantic segmentation of complex urban street scenes is a very important function during autonomous driving (AD), which will become an important technology in industrialized countries in the near future. Today, advanced driver assistance systems (ADAS) improve traffic safety thanks to the application of solutions that enable detecting objects, recognising road signs, segmenting the road, etc. The basis for these functionalities...
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Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift
PublicationWhile recent computer vision algorithms achieve impressive performance on many benchmarks, they lack robustness - presented with an image from a different distribution, (e.g. weather or lighting conditions not considered during training), they may produce an erroneous prediction. Therefore, it is desired that such a model will be able to reliably predict its confidence measure. In this work, uncertainty estimation for the task...
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Laboratory investigation with subbottom parametric echosounder SES-2000 standard with an emphasis on reflected pure signals analysis
PublicationThe main goal of the paper is to describe correlations between measurements results of trials taken on Gulf of Gdańsk bottom sounded with parametric echosounder SES-2000 Standard and laboratory research where collected during survey sediments were measured. Stationary tests took place at Gdansk University of Technology where 30 meters long 1.8 meter deep and 3 meters wide water tank is located. Main lobe of antenna was directed...
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Mechanical response of human thoracic spine ligaments under quasi-static loading: An experimental study
PublicationPurpose This study aimed to investigate the geometrical and mechanical properties of human thoracic spine ligaments subjected to uniaxial quasi-static tensile test. Methods Four human thoracic spines, obtained through a body donation program, were utilized for the study. The anterior longitudinal ligament (ALL), posterior longitudinal ligament (PLL), capsular ligament (CL), ligamenta flava (LF), and the interspinous ligament and...
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Badania spawalności stali S460N w środowisku wodnym z wykorzystaniem próby Tekken
PublicationSpawanie w środowisku wodnym niesie ze sobą wiele problemów, wśród których najważniejszym jest skłonność stali do powstawania pęknięć zimnych. O ile w przypadku spawania na powietrzu istnieje wiele metod zapobiegania tym pęknięciom, o tyle pod wodą zastosowanie tych metod jest ograniczone. Z tego powodu konieczne jest określenie skłonności danego materiału do pękania zimnego. W pracy oceniono spawalność drobnoziarnistej...
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Rzeczywiste charakterystyki czasowo-prądowe wyłączników różnicowoprądowych 30 mA przy prądzie sinusoidalnym
PublicationPrzedstawiono wymagania norm odnoszące się do charakterystyki czasowo-prądowej wyłączników różnicowoprądowych o znamionowym prądzie różnicowym zadziałania równym 30 mA. Zaprezentowano wyniki badań laboratoryjnych czasu wyłączania takich wyłączników przy sinusoidalnym prądzie różnicowym i oceniono je z punktu widzenia tych wymagań. Badania wykazały, że czasy wyłączania dwóch lub większej liczby porównywanych wyłączników różnicowoprądowych...
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Projekt UPGRID
PublicationMiędzynarodowy projekt UPGRID realizowany jest w ramach programu Horyzont 2020 (H2020). Program ten to największy jak dotąd program Unii Europejskiej (UE) w zakresie badań naukowych i innowacji. W projekcie UPGRID uczestniczy 17 partnerów z 9 krajów EU. Głównym celem projektu UPGRID jest rozwój funkcjonalności, które służą integracji sieci nn oraz SN ze stroną konsumencką. W ramach projektu wybrane technologie Inteligentnych Sieci...
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SUBIEKTYWNE POSTRZEGANIE RÓŻNORODNOŚCI ZESPOŁU – PERSPEKTYWA MENADŻERA
PublicationZarządzanie zespołami zróżnicowanymi powinno przejawiać się aktywnym i świadomym działaniem prowadzącym do pełnego wykorzystania potencjału zespołu. To, czy potencjał ten zostanie wykorzystany, zależy od wielu czynników. Wydaje się, że jednym z najważniejszych jest nie tyle rzeczywiste,obiektywne zróżnicowanie członków zespołu, ile to, w jaki sposób różnorodność ta jest subiektywnie postrzegana. Artykuł przedstawia wyniki badań...
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Ciśnienie statyczne a ciśnienie spiętrzenia w modelach strumienia objętości wykorzystujących współczynnik wymiarowy Kv
PublicationJedną z wielkości wykorzystywanych do opisu właściwości przepływowych elementu pneumatycznego jest współczynnik wymiarowy Kv. Jego znajomość umożliwia wyznaczenie wartości strumienia objętości powietrza, o ile znane są wartości ciśnień statycznych przed i za elementem. W pracy przedstawiono wpływ zastąpienia wartości ciśnienia statycznego na dopływie do elementu wartością ciśnienia spiętrzenia i zastąpienia wartości ciśnienia statycznego...
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Porównywanie topologii drzew i sieci filogenetycznych z wykorzystaniem metryki błędu
PublicationPodstawowymi modelami historii ewolucji organizmów są drzewa i sieci filogenetyczne. Ponieważ algorytmy konstrukcji filogenów zwracają różne wyniki dla tych samych danych wejściowych, powstaje problem oceny, który filogen najlepiej reprezentuje historię ewolucji dla zadanego zbioru gatunków. W pracy podano definicję metryki dla przestrzeni drzew o n liściach, zwanej metryką błędu. Dokonano przeglądu miar odległości na przestrzeni...
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Non-invasive investigation of a submerged medieval harbour, a case study from Puck Lagoon
PublicationThis study presents an innovative approach to underwater archaeological prospection using non-invasive methods of seabed exploration. The research focuses on the Puck medieval harbour, a cultural heritage site, and utilises acoustic and optical underwater remote-sensing technology. The primary objectives include optimising the use of Airborne Laser Bathymetry in underwater archaeology, enhancing the filtration process for mapping...
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Web-based 3D processing and dissemination of multibeam sonar data
PublicationThe continuous detailed surveys of the various water bodies over time produce a large and ever-increasing volume and density of underwater sounding data. Three-dimensional data, such as those obtained by multibeam sonar systems, are quite complex to manage, and thus their growing numbers increase the pressure on development of new solutions dedicated to processing them. This paper presents a concept system for web-based dissemination...
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Top k Recommendations using Contextual Conditional Preferences Model
PublicationRecommender systems are software tools and techniques which aim at suggesting to users items they might be interested in. Context-aware recommender systems are a particular category of recommender systems which exploit contextual information to provide more adequate recommendations. However, recommendation engines still suffer from the cold-start problem, namely where not enough information about users and their ratings is available....
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Novel approach to ecotoxicological risk assessment of sediments cores around the shipwreck by the use of self-organizing maps
PublicationMarine and coastal pollution plays an increasingly important role due to recent severe accidents which drew attention to the consequences of oil spills causing widespread devastation of marine ecosystems. All these problems cannot be solved without conducting environmental studies in the area of possible oil spill and performing chemometric evaluation of the data obtained looking for similar patterns among pollutants and optimize...
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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublicationThis work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...
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Federated Learning in Healthcare Industry: Mammography Case Study
PublicationThe paper focuses on the role of federated learning in a healthcare environment. The experimental setup involved different healthcare providers, each with their datasets. A comparison was made between training a deep learning model using traditional methods, where all the data is stored in one place, and using federated learning, where the data is distributed among the workers. The experiment aimed to identify possible challenges...
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Organic syntheses greenness assessment with multicriteria decision analysis
PublicationGreen chemistry requires a metrics system that is comprehensive by the criteria included and simple in the application at the same time. We propose the application of multicriteria decision analysis for com- parative greenness assessment of organic synthesis procedures. The assessment is based on 9 criteria (the reagent, reaction efficiency, atom economy, temperature, pressure, synthesis time, solvent, catalyst and reactant) for...
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Transfer learning in imagined speech EEG-based BCIs
PublicationThe Brain–Computer Interfaces (BCI) based on electroencephalograms (EEG) are systems which aim is to provide a communication channel to any person with a computer, initially it was proposed to aid people with disabilities, but actually wider applications have been proposed. These devices allow to send messages or to control devices using the brain signals. There are different neuro-paradigms which evoke brain signals of interest...