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Deep learning-enabled integration of renewable energy sources through photovoltaics in buildings
PublicationInstalling photovoltaic (PV) systems in buildings is one of the most effective strategies for achieving sustainable energy goals and reducing carbon emissions. However, the requirement for efficient energy management, the fluctuating energy demands, and the intermittent nature of solar power are a few of the obstacles to the seamless integration of PV systems into buildings. These complexities surpass the capabilities of rule-based...
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Comparison of Deep Neural Network Learning Algorithms for Mars Terrain Image Segmentation
PublicationThis paper is dedicated to the topic of terrain recognition on Mars using advanced techniques based on the convolutional neural networks (CNN). The work on the project was conducted based on the set of 18K images collected by the Curiosity, Opportunity and Spirit rovers. The data were later processed by the model operating in a Python environment, utilizing Keras and Tensorflow repositories. The model benefits from the pretrained...
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UV-assisted fluctuation-enhanced gas sensing by ink-printed MoS2 devices
PublicationIn this work, MoS2 flakes were printed on ceramic substrates and investigated toward 1–10 ppm of nitrogen dioxide (NO2), 2–12 ppm of ammonia (NH3), and 2–12 ppm acetone (C3H6O) under UV light (275 nm). The structure of overlapping MoS2 flakes and UV light assistance affected high responsivity to NO2 when DC resistance was monitored, and superior sensitivity to NH3 was obtained from the low-frequency noise spectra. MoS2 exhibited...
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Bearing capacity of monotonically installed tapered piles in medium dense Fontainebleau sand
PublicationA series of installation of tapered piles in medium-dense Fontainebleau sand were performed in the geotechnical centrifuge at Gustave Eiffel University. The models of piles with three different shapes - straight profile (S), and with taper angle of 0.70 degrees (T1), and 1.4 degrees (T2) were used. The piles were instrumented with fiber optic wires on the shaft and load cell at the base. After monotonic installation, the models were...
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Combining visual and acoustic modalities to ease speech recognition by hearing impaired people
PublicationArtykuł prezentuje system, którego celem działania jest ułatwienie procesu treningu poprawnej wymowy dla osób z poważnymi wadami słuchu. W analizie mowy wykorzystane zostały parametry akutyczne i wizualne. Do wyznaczenia parametrów wizualnych na podstawie kształtu i ruchu ust zostały wykorzystane modele Active Shape Models. Parametry akustyczne bazują na współczynnikach melcepstralnych. Do klasyfikacji wypowiadanych głosek została...
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Prototype of an opto-capacitive probe for non-invasive sensing cerebrospinal fluid circulation
PublicationIn brain studies, the function of the cerebrospinal fluid (CSF) awakes growing interest, particularly related to studies of the glymphatic system in the brain, which is connected with the complex system of lymphatic vessels responsible for cleaning the tissues. The CSF is a clear, colourless liquid including water (H2O) approximately with a concentration of 99 %. In addition, it contains electrolytes, amino acids, glucose, and...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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The influence of time of hearing aid use on auditory perception in various acoustic situations
PublicationThe assessment of sound perception in hearing aids, especially in the context of benefits that a prosthesis can bring, is a complex issue. The objective parameters of the hearing aids can easily be determined. These parameters, however, do not always have a direct and decisive influence on the subjective assessment of quality of the patient’s hearing while using a hearing aid. The paper presents the development of a method for...
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublicationIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublicationThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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Looking through the past: better knowledge retention for generative replay in continual learning
PublicationIn this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained...
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublicationIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
PublicationEvery year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...
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Technology-Enhanced Environmental Learning: Co-design of Educational Mobile Application Case
PublicationThe process of co-creating an educational mobile application to support environmentally friendly behavior is presented in this paper. The research material consisted of quantitative data collected on the application during the first testing phase by early adopters. The results suggest that the most frequently used features of the app were related to transport and educational activities. While women tended to split their time between...
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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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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Combining MUSHRA Test and Fuzzy Logic in the Evaluation of Benefits of Using Hearing Prostheses
PublicationAssessing the effectiveness of hearing aid fittings based on the benefits they provide is crucial but intricate. While objective metrics of hearing aids like gain, frequency response, and distortion are measurable, they do not directly indicate user benefits. Hearing aid performance assessment encompasses various aspects, such as compensating for hearing loss and user satisfaction. The authors suggest enhancing the widely used...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublicationBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Machine learning approach to packaging compatibility testing in the new product development process
PublicationThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublicationComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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LOS and NLOS identification in real indoor environment using deep learning approach
PublicationVisibility 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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Enhanced gas sensing by graphene-silicon Schottky diodes under UV irradiation
PublicationThe effect of ultraviolet (UV) or blue irradiation on graphene/n-doped silicon Schottky junctions toward gas sensing was investigated. Schottky diodes were subjected to oxidizing nitrogen dioxide (NO2, 1–3 ppm) and reducing tetrahydrofuran (THF, 50–200 ppm), showing significantly different responses observed on the currentvoltage (I-V) characteristics, especially under UV light (275 nm). NO2 affected the resistive part of the forward region...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Fluctuation-enhanced and conductometric gas sensing with nanocrystalline NiO thin films: A comparison
PublicationNanocrystalline thin films of NiO were prepared by advanced reactive gas deposition, and their responses to formaldehyde, ethanol and methane gases were studied via fluctuation-enhanced and conductometric methods Thin films with thicknesses in the 200–1700-nm range were investigated in as-deposited form and after annealing at 400 and 500 °C. Morphological and structural analyses showed porous deposits with NiO nanocrystals having...
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Nickel Oxide Thin Film Sensor for Fluctuation-Enhanced Gas Sensing of Formaldehyde
PublicationNanocrystalline nickel-oxide-based thin films were prepared by advanced reactive gas deposition, and the response of these films to formaldehyde was studied by fluctuationenhanced sensing. Morphological and structural analyses showed porous deposits of nickel oxide particles with face-centered cubic structure. Resistance fluctuations were measured upon exposure to ethanol, formaldehyde and methane at 200 °C. Power density spectra...
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UV-Light-Induced Fluctuation Enhanced Sensing by WO3-Based Gas Sensors
PublicationWO3-based gas sensors were investigated under UV-light irradiation and at different working temperatures with the object of achieving superior sensitivity and selectivity. Resistance fluctuations in the WO3 layer were studied together with dc resistance measurements. The data were taken in synthetic air, ethanol, nitrogen dioxide, and mixtures of these gases. We conclude that UV irradiation can easily be applied to enhance the...
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Analysis of sloping brace stiffness influence on stability and load bearing capacity of a truss
PublicationThe paper is focused on the numerical study of stability and load bearing capacity of a truss with side elastic braces. The structure is made in reality. The rotational and sliding brace stiffnesses were taken into account. Linear buckling analysis and non-linear static analysis with geometric and material nonlinearity were performed for the beam and shell model of the truss with respect to the angle of sloping braces. As a result...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublicationEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Modeling of bearing capacity of footings on sand within stochastic micro-polar hypoplasticity.
PublicationAnalizowano numerycznie efekt wstępnego rozkładu wskaźnika porowatości na wytrzymałość i strefy ścinania w problemach fundamentów na piasku w skali modelowej. Obliczenia wykonano przy zastosowaniu stochastycznej metody elementów skończonych i mikropolarnego modelu hipoplastycznego. Wskaźnik porowatości miał formę skorelowanych pól stochastycznych. Dodatkowo obliczono efekt skali dla 3 różnych szerokości fundamentów.
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Wykorzystanie technik GC×GC-TOF-MS i olfaktometrii terenowej do oceny uciążliwości zapachowej powietrza atmosferycznego na obszarach przyległych do terenu składowiska odpadów komunalnych
PublicationUciążliwość zapachowa jest poważnym problemem środowiskowym i jednym z powodów skarg ludności dotyczących złej jakości powietrza atmosferycznego. Źródłem emisji nieprzyjemnych zapachów do środowiska (odorów) są obiekty gospodarki komunalnej, w tym składowiska odpadów komunalnych. Ze względu na negatywny wpływ emisji substancji zapachowych na zdrowie i życie człowieka, konieczne jest stosowanie odpowiednich narzędzi analitycznych...
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Pro-death signaling of cytoprotective heat shock factor 1: upregulation of NOXA leading to apoptosis in heat-sensitive cells
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On Raman optical activity sign-switching between the ground and excited states leading to an unusual resonance ROA induced chirality
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The accuracy assessment of determining the axis of railway track basing on the satellite surveying
PublicationW 2009 roku na Politechnice Gdańskiej rozpoczęto badania nad wykorzystaniem serwisu pomiarów fazowych NAVGEO aktywnej sieci geodezyjnej ASG-EUPOS dla przeprowadzania ciągłych pomiarów przebiegu trasu kolejowej. Celem kontynuowanych badań jest próba oceny możliwości zastosowania pomiarów fazowych GNSS, realizowanych przez kilka odbiorników, dla projektowania oraz inwentaryzacji toru kolejowego. Do oceny dokładności określenia osi...
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WYKORZYSTANIE TECHNIK OLFAKTOMETRII TERENOWEJ I GC×GC-TOFMS DO OCENY UCIĄŻLIWOŚCI ZAPACHOWEJ POWIETRZA ATMOSFERYCZNEGO NA OBSZARACH PRZYLEGŁYCH DO SKŁADOWISKA ODPADOW KOMUNALNYCH W GDAŃSKU SZADÓŁKACH
PublicationW artykule przedstawiono wyniki badań przeprowadzonych na obszarach sąsiadujących ze składowiskiem odpadów komunalnych w Gdańsku-Szadółkach. Do oceny uciążliwości zapachowej powietrza atmosferycznego wykorzystano technikę olfaktometrii terenowej. Narzędziami, których wykorzystanie umożliwia badanie właściwości zapachowych odorantów występujących w powietrzu atmosferycznym in-situ są olfaktometry terenowe, których zastosowanie umożliwia...
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Mathematical analysis of the lasing eigenvalue problem for the optical modes in a layered dielectric cavity with a quantum well and distributed Bragg reflectors
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Piperine Targets Different Drug Resistance Mechanisms in Human Ovarian Cancer Cell Lines Leading to Increased Sensitivity to Cytotoxic Drugs
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Polymer membranes loaded with lipids for taste sensing: electrochemical impedance spedance spectroscopy studies
PublicationZcharakteryzowano metodą impedancyjnej spektroskopii elektrochemicznej membrany polichlorku winilu z lipidami zanurzone w roztworze kwasu cytrynowego. Badano membrany elektrod dodatnio naładowanych (heksadecyloamina, chlorek, benzyloheksadecylodimetyloamoniowy) i ujemne naładowanych (kwas elaidynowy, cholesterol, l-dodekonol). Badania impedacyjne pozwoliły na rozróznienie czterech stałych czasowych: rezystancja wysokiej częstotliwości,...
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Does Treatment of Sudden Sensorineural Hearing Loss in Patients With COVID-19 Require Anticoagulants?
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Electrodes Based on a Titanium Dioxide Nanotube–Spherical Silver Nanoparticle Composite for Sensing of Proteins
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Impact of Housing System on Health and Rearing of Calves Based on Examination of Nasal Cavity Swabs
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Drug-Releasing Antibacterial Coating Made from Nano-Hydroxyapatite Using the Sonocoating Method
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Exploring the meaning of night shift placement in nursing education: A European multicentre qualitative study
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Deep learning model for automated assessment of lexical stress of non-native english speakers
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Machine Learning for Control Systems Security of Industrial Robots: a Post-covid-19 Overview
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The Effectiveness of Using a Pretrained Deep Learning Neural Networks for Object Classification in Underwater Video
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Stability and bearing capacity of arch-shaped corrugated shell elements: experimental and numerical study
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Application of GIS and Remote Sensing Techniques in Multitemporal Analyses of Soil Properties in the Foreland of the Carpathians
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