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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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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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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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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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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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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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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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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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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublicationThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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Categorization of emotions in dog behavior based on the deep neural network
PublicationThe 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...
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Independent dynamics of low, intermediate, and high frequency spectral intracranial EEG activities during human memory formation
PublicationA wide spectrum of brain rhythms are engaged throughout the human cortex in cognitive functions. How the rhythms of various frequency ranges are coordinated across the space of the human cortex and time of memory processing is inconclusive. They can either be coordinated together across the frequency spectrum at the same cortical site and time or induced independently in particular bands. We used a large dataset of human intracranial...
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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...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublicationIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Grid-Forming Operation of Energy-Router Based on Model Predictive Control with Improved Dynamic Performance
PublicationThe focus of this study is on the grid-forming operation of the Energy Router (ER) based on Model Predictive Control (MPC). ER is regarded as a key component of microgrids. It is a converter that interfaces the microgrid (s) with the utility grid. The ER has a multiport structure and bidirectional energy flow control. The ER concept can be implemented in Nearly Zero-Energy Buildings (NZEB) to provide flexible energy control. A...
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Rynki akcji w krajach BRIC: podobieństwa i różnice
PublicationKraje BRIC (Brazylia, Rosja, Indie i Chiny) stały się w ostatnich latach ważną częścią globalnego systemu gospodarczego i finansowego. Kraje te różnią się jednak istotnie pod względem osiągniętych poziomów rozwoju gospodarczego, w tym w sferze finansowej. Celem tekstu jest omówienie i porównanie zmian w krajach BRIC w pierwszych kilkunastu latach XXI w., które miały miejsce na jednej z najważniejszych części systemu finansowego,...
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Konkurs o Pomorską Nagrodę Jakości w czasach Gospodarki Opartej na Wiedzy
PublicationCelem autorki jest analiza wpływu aspektu zarządzania wiedzą u uczestników XXII edycji Konkursu o Pomorską Nagrodę Jakości na wynik oraz uzyskanie wyróżnienia. Konkurs składa się z kilku etapów, m.in. samooceny oraz weryfikacji w siedzibie uczestnika przeprowadzonej przez ekspertów Polskiego Rejestru Statków. Po udziale w konkursie organizacja biorąca w nim udział, poza aspektami marketingowymi uzyskuje informacje zwrotną w postaci...
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STARZENIE SIĘ LUDNOŚCI – PERSPEKTYWA LOKALNA
PublicationPostępujące starzenie się ludności determinuje zmiany społeczne i ekonomiczne. W literaturze przedmiotu ich charakter, przebieg i skutki najczęściej poddaje się analizie i ocenie w skali makro. Tymczasem zmiany demograficzne mają swoje istotne konsekwencje również w perspektywie lokalnych jednostek terytorialnych i stanowią wyzwanie dla działań władz lokalnych. Celem artykułu jest wskazanie szans i zagrożeń powodowanych postępującym...
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Prowadzenie działalności gospodarczej przez małe przedsiębiorstwa
PublicationGłównymi fundamentami decydującymi o rozwoju przedsiębiorczości są regulacje prawne oraz instytucje odpowiedzialne za ich respektowanie i egzekwowanie. O ile, przeważnie duże i średnie przedsiębiorstwa dobrze radzą sobie nawet w skomplikowanym otoczeniu prawnym, o tyle mikro i mali przedsiębiorcy mają z tym wiele problemów.Zmienność, niejasność i interpretowalność prawa związanego z zakładaniem, prowadzeniem i zarazem opodatkowaniem...
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Zabezpieczanie małych transformatorów SN/nn - ocena skuteczności stosowanych środków.
PublicationW dyskusji o celowości zabezpieczania małych transformatorów SN/nn, co jakiś czas następuje zmiana poglądów: raz uznaje się, że zabezpieczenia są zbyteczne, raz - że są niezbędne. Wynika to ze zmian priorytetów, warunków ekonomicznych oraz możliwości technicznych. W publikacji porównuje się skutki różnych koncepcji zabezpieczania transformatora SN/nn od strony wn: przy pomocy bezpieczników gazowydmuchowych, piaskowych, jak i wyłącznikiem...
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Ionophores in polymeric membranes for selective ion recognition:impedance studies
PublicationW pracy badano dwa typy elektrod: membranowe elektrody jonoselektywne (ISE) oraz elektrody nowego typu all-solid-state (AAS). Elektrody AAS zawierają przewodzącą warstwę polimerową na węglu szklistym lub platynie, na który nałożona jest membrana zawierająca jonofor. Do badań użyto dwa jonofory: p-tert-butylokaliks[4]aren-korona-4 (L1) selektywnie kompleksująca jony Na+ oraz kaliks[4]aren-korona-6 (L2) selektywnie kompleksująca...
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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublicationWe proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...
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Machine Learning and Electronic Noses for Medical Diagnostics
PublicationThe need for noninvasive, easy-to-use, and inexpensive methods for point-of-care diagnostics of a variety of ailments motivates researchers to develop methods for analyzing complex biological samples, in particular human breath, that could aid in screening and early diagnosis. There are hopes that electronic noses, that is, devices based on arrays of semiselective or nonselective chemical sensors, can fill this niche. Electronic...
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Review of Shoreline Extraction Methods from Aerial Laser Scanning
PublicationAutonomous technologies are increasingly used in various areas of science. The use of unmanned vehicles for hydrographic surveys in shallow coastal areas requires accurate estimation of shoreline position. This is a nontrivial task, which can be performed using a wide range of sensors and methods. The aim of the publication is to review shoreline extraction methods based solely on data from aerial laser scanning (ALS). This narrative...
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Programmatic Simulation of Laser Scanning Products
PublicationThe technology of laser scanning is widely used for producing three-dimensional digital representations of geographic features. The measurement results are usually available in the form of 3D point clouds, which are often used as a transitional data model in various remote sensing applications. Unfortunately, while the costs of Light Detection And Ranging scanners have dropped significantly in recent years, they are still considered...
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Spectral Clustering Wikipedia Keyword-Based search Results
PublicationThe paper summarizes our research in the area of unsupervised categorization of Wikipedia articles. As a practical result of our research, we present an application of spectral clustering algorithm used for grouping Wikipedia search results. The main contribution of the paper is a representation method for Wikipedia articles that has been based on combination of words and links and used for categoriation of search results in this...
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Entrepreneurship Vulnerability to Business Cycle. A New Methodology for Identification Pro-cyclical and Counter-cyclical Patterns of Entrepreneurial Activity
PublicationIn literature, there is ongoing discussion whether entrepreneurial activity, approximated by, for instance, changes in self-employment, tends to behave pro-cyclically, counter-cyclically or rather is a-cyclical. Thus far, both theoretical and empirical evidence, where various multiple methodological approaches are used, does not provide clear answer to the latter; while widely offered explanations are scattered and lack robustness....
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1D convolutional context-aware architectures for acoustic sensing and recognition of passing vehicle type
PublicationA network architecture that may be employed to sensing and recognition of a type of vehicle on the basis of audio recordings made in the proximity of a road is proposed in the paper. The analyzed road traffic consists of both passenger cars and heavier vehicles. Excerpts from recordings that do not contain vehicles passing sounds are also taken into account and marked as ones containing silence....
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Oxylipin profiling for clinical research: Current status and future perspectives
PublicationOxylipins are potent lipid mediators with increasing interest in clinical research. They are usually measured in systemic circulation and can provide a wealth of information regarding key biological processes such as inflammation, vascular tone, or blood coagulation. Although procedures still require harmonization to generate comparable oxylipin datasets, performing comprehensive profiling of circulating oxylipins in large studies...
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Impact of optimization of ALS point cloud on classification
PublicationAirborne laser scanning (ALS) is one of the LIDAR technologies (Light Detection and Ranging). It provides information about the terrain in form of a point cloud. During measurement is acquired: spatial data (object’s coordinates X, Y, Z) and collateral data such as intensity of reflected signal. The obtained point cloud is typically applied for generating a digital terrain model (DTM) and a digital surface model (DSM). For DTM...
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The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification
PublicationDeveloping of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and...
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublicationThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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Emissions and toxic units of solvent, monomer and additive residues released to gaseous phase from latex balloons
PublicationThis study describes the VOCs emissions from commercially available latex balloons. Nine compounds are determined to be emitted from 13 types of balloons of different colors and imprints in 30 and 60°C. The average values of total volatile organic compounds (TVOCs) emitted from studied samples ranged from 0.054 up to 7.18 μg∙g-1 and from 0.27 up to 36.13 μg∙g-1 for 30oC and 60oC, respectively. The dataset is treated with principal...
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Magnetic Signature Description of Ellipsoid-Shape Vessel Using 3D Multi-Dipole Model Fitted on Cardinal Directions
PublicationThe article presents a continuation of the research on the 3D multi-dipole model applied to the reproduction of magnetic signatures of ferromagnetic objects. The model structure has been modified to improve its flexibility - model parameters determined by optimization can now be located in the cuboid contour representing the object's hull. To stiffen the model, the training dataset was expanded to data collected from all four cardinal...
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Know your safety indicator – A determination of merchant vessels Bow Crossing Range based on big data analytics
PublicationEven in the era of automatization maritime safety constantly needs improvements. Regardless of the presence of crew members on board, both manned and autonomous ships should follow clear guidelines (no matter as bridge procedures or algorithms). To date, many safety indicators, especially in collision avoidance have been proposed. One of such parameters commonly used in day-to-day navigation but usually omitted by researchers is...
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Interrelations between Travel Patterns and Urban Spatial Structure of the Largest Russian Cities
PublicationThe study presented within this dissertation involves the analysis of the relationship between urban spatial structure and travel patterns in the largest Russian cities. It is an empirical investigation of how the spatial structure, formed during the Soviet and post-Soviet periods, affects the travel patterns in the largest cities of contemporary Russia. It aims to determine what measures, both urban structure and transportation...
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Diurnal variability of atmospheric water vapour, precipitation and cloud top temperature across the global tropics derived from satellite observations and GNSS technique
PublicationThe diurnal cycle of convection plays an important role in clouds and water vapour distribution across the global tropics. In this study, we utilize integrated moisture derived from the global navigation satellite system (GNSS), satellite precipitation estimates from TRMM and merged infrared dataset to investigate links between variability in tropospheric moisture, clouds development and precipitation at a diurnal time scale. Over...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublicationA 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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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublicationThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Detecting type of hearing loss with different AI classification methods: a performance review
PublicationHearing is one of the most crucial senses for all humans. It allows people to hear and connect with the environment, the people they can meet and the knowledge they need to live their lives to the fullest. Hearing loss can have a detrimental impact on a person's quality of life in a variety of ways, ranging from fewer educational and job opportunities due to impaired communication to social withdrawal in severe situations. Early...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Dependent self-employed individuals: are they different from paid employees?
PublicationThis study focuses on dependent self-employment, which covers a situation where a person works for the same employer as a typical worker while on a self-employment contractual basis, i.e., without a traditional employment contract and without certain rights granted to "regular" employees. The research exploits the individual-level dataset of 35 European countries extracted from the 2017 edition of the European Labour Force Survey...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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Super-resolved Thermal Imagery for High-accuracy Facial Areas Detection and Analysis
PublicationIn this study, we evaluate various Convolutional Neural Networks based Super-Resolution (SR) models to improve facial areas detection in thermal images. In particular, we analyze the influence of selected spatiotemporal properties of thermal image sequences on detection accuracy. For this purpose, a thermal face database was acquired for 40 volunteers. Contrary to most of existing thermal databases of faces, we publish our dataset...
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ELECTRICAL CONDUCTIVITY AND pH IN SURFACE WATER AS TOOL FOR IDENTIFICATION OF CHEMICAL DIVERSITY
PublicationIn the present study, the creeks and lakes located at the western shore of Admiralty Bay were analysed. The impact of various sources of water supply was considered, based on the parameters of temperature, pH and specific electrolytic conductivity (SEC25). All measurements were conducted during a field campaign in January-February 2017. A multivariate dataset was also created and a biplot of SEC25 and pH of the investigated waters...
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublicationAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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Stanowisko monitoringu odbieraków prądu w warunkach ruchowych
PublicationKonserwacja i regulacja odbieraków prądu odbywa się podczas okresowych przeglądów technicznych lokomotyw i zespołów trakcyjnych. Stany rozregulowania lub nawet uszkodzenia odbieraków prądu, zagrażające ich poprawnej współpracy z siecią jezdną, mogą wystąpić pomiędzy przeglądami. Wskazane jest zatem częstsze kontrolowanie stanu technicznego odbieraków. Powyższy cel można osiągnąć bez zmniejszania dostępności pojazdów, poprzez kontrolę...
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Solid-contact lead(II) ion-selective electrodes for potentiometric determination of lead(II) in presence of high concentrations of Na(I), Cu(II), Cd(II), Zn(II), Ca(II) and Mg(II)
PublicationLead and its compounds are a serious threat to the environment. Monitoring of this toxic heavy metal is a driving force for the continuous development of novel lead(II) ionophores to be applied in ion-selective electrodes. In this work a highly selective lead(II) ionophore, namely 25,26,27,28-tetrakis(piperidinylthiocarbonylmethylene)-p-tert-butylcalix[4]arene, was used in solid-contact ion-selective electrodes for determination...
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Two-Step Model Based Adaptive Controller for Dissolved Oxygen Control in Sequencing Wastewater Batch Reactor
PublicationDissolved Oxygen (DO) concentration is a crucial parameter for efficient operation of biological processes taking place in the activated sludge Wastewater Treatment Plant (WWTP). High-quality DO control is difficult to achieve because of complex nonlinear behavior of the plant and substantial influent disturbances. A method to improve the Direct Model Reference Adaptive Control (DMRAC) technology in application to DO tracking for...