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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
PublikacjaApplications 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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Optimization algorithm and filtration using the adaptive TIN model at the stage of initial processing of the ALS point cloud
PublikacjaAirborne laser scanning (ALS) provides survey results in the form of a point cloud. The ALS point cloud is a source of data used primarily for constructing a digital terrain model (DTM). To generate a DTM, the set of ALS observations must be first subjected to the point cloud processing methodology. A standard methodology is composed of the following stages: acquisition of the ALS data, initial processing (including filtration),...
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Automated Valuation Model based on fuzzy and rough set theory for real estate market with insufficient source data
PublikacjaObjective monitoring of the real estate value is a requirement to maintain balance, increase security and minimize the risk of a crisis in the financial and economic sector of every country. The valuation of real estate is usually considered from two points of view, i.e. individual valuation and mass appraisal. It is commonly believed that Automated Valuation Models (AVM) should be devoted to mass appraisal, which requires a large...
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Application 2D Descriptors and Artificial Neural Networks for Beta-Glucosidase Inhibitors Screening
PublikacjaBeta-glucosidase inhibitors play important medical and biological roles. In this study, simple two-variable artificial neural network (ANN) classification models were developed for beta-glucosidase inhibitors screening. All bioassay data were obtained from the ChEMBL database. The classifiers were generated using 2D molecular descriptors and the data miner tool available in the STATISTICA package (STATISTICA Automated Neural...
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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublikacjaHandwriting 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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The Verification of the Usefulness of Electronic Nose Based on Ultra-Fast Gas Chromatography and Four Different Chemometric Methods for Rapid Analysis of Spirit Beverages
PublikacjaSpirit beverages are a diverse group of foodstuffs. They are very often counterfeited which cause the appearance of low quality products or wrongly labelled products on the market. It is important to find a proper quality control and botanical origin method enabling the same time preliminary check of the composition of investigated samples, which was the main goal of this work. For this purpose, the usefulness of electronic nose...
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Independent dynamics of slow, intermediate, and fast intracranial EEG spectral activities during human memory formation
PublikacjaA wide spectrum of brain rhythms are engaged throughout the human cortex in cognitive functions. How the rhythms of various low and high frequencies are spatiotemporally coordinated across the human brain during memory processing is inconclusive. They can either be coordinated together across a wide range of the frequency spectrum or induced in specific bands. We used a large dataset of human intracranial electroencephalography...
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Clothes Detection and Classification Using Convolutional Neural Networks
PublikacjaIn this paper we describe development of a computer vision system for accurate detection and classification of clothes for e-commerce images. We present a set of experiments on well established architectures of convolutional neural networks, including Residual networks, SqueezeNet and Single Shot MultiBox Detector (SSD). The clothes detection network was trained and tested on DeepFashion dataset, which contains box annotations...
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Hey student, are you sharing your knowledge? A cluster typology of knowledge sharing behaviours among students
PublikacjaKnowledge 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
PublikacjaThis 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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Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublikacjaCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
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Bimodal deep learning model for subjectively enhanced emotion classification in films
PublikacjaThis research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....
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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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Weryfikacja algorytmów MPPT dla modułów fotowoltaicznych w warunkach przesłonięcia
PublikacjaIntensywny 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
PublikacjaIntensywny 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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Absencja chorobowa - szacunek niewytworzonego PKB
PublikacjaKoszty 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
PublikacjaArtykuł 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
PublikacjaW 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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Porównanie heurystyk dla problemu szeregowania zadań czasowo-zależnych o wspólnym podstawowym czasie wykonywania
PublikacjaW 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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Wieloobszarowa rozmyta regulacja PIλDµ mocy reaktora jądrowego
PublikacjaWartykule 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
PublikacjaW 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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Impact of Visual Image Quality on Lymphocyte Detection Using YOLOv5 and RetinaNet Algorithms
PublikacjaLymphocytes, 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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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublikacjaBrain–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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Rating mathematical models for first-pass of tracer in pCT lung studies
PublikacjaThis 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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Urban scene semantic segmentation using the U-Net model
PublikacjaVision-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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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublikacjaMachine 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
PublikacjaThere 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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Investigating Feature Spaces for Isolated Word Recognition
PublikacjaMuch 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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Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift
PublikacjaWhile 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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Semantic URL Analytics to Support Efficient Annotation of Large Scale Web Archives
PublikacjaLong-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
PublikacjaIn 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
PublikacjaThis 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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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublikacjaDesigning 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
PublikacjaUsing 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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Laboratory investigation with subbottom parametric echosounder SES-2000 standard with an emphasis on reflected pure signals analysis
PublikacjaThe 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
PublikacjaPurpose 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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Rzeczywiste charakterystyki czasowo-prądowe wyłączników różnicowoprądowych 30 mA przy prądzie sinusoidalnym
PublikacjaPrzedstawiono 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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Porównywanie topologii drzew i sieci filogenetycznych z wykorzystaniem metryki błędu
PublikacjaPodstawowymi 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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Projekt UPGRID
PublikacjaMiędzynarodowy 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
PublikacjaZarządzanie 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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Badania spawalności stali S460N w środowisku wodnym z wykorzystaniem próby Tekken
PublikacjaSpawanie 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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Ciśnienie statyczne a ciśnienie spiętrzenia w modelach strumienia objętości wykorzystujących współczynnik wymiarowy Kv
PublikacjaJedną 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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Federated Learning in Healthcare Industry: Mammography Case Study
PublikacjaThe 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
PublikacjaGreen 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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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublikacjaThis 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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Web-based 3D processing and dissemination of multibeam sonar data
PublikacjaThe 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
PublikacjaRecommender 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
PublikacjaMarine 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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Non-invasive investigation of a submerged medieval harbour, a case study from Puck Lagoon
PublikacjaThis 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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Categorization of emotions in dog behavior based on the deep neural network
PublikacjaThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...