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Search results for: AIR POLLUTION, LOW-COST SENSOR CALIBRATION, MACHINE LEARNING, DATA PRE-PROCESSING, NEURAL NETWORKS
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublicationDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Association between the long-term exposure to air pollution and depression
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A new approach in the calibration of passive samplersA new approach on the calibration of passive dosimeters for studies of indoor air (....--------ROZBIEŻNOŚĆ TYTUŁÓW-------------------------------------
PublicationPrzedstawiono problematykę kalibracji próbników pasywnych wykorzystywanych w Katedrze Chemii Analitycznej Wydz. Chemicznego PG do monitoringu jakości powietrza wewnętrznego. Proponowane podejście pozwala na oszacowanie wartości stałych kalibracyjnych, a tym samym oznaczenia stężeń związków od heksanu do dodekanu. Tak więc permeacyjne dozymetry pasywne mogą być wykorzystane w analogicznym zakresie jak próbniki aktywne.
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublicationRNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA....
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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Document transformations for data processing in information systems
PublicationAtrykuł przedstawia podejście do automatyzacji transformacjidokumentów użytkownika bazujące na technologii XML. W artykuleprzedstawiony został system Endoscopy Recommender System.ERS wykorzystuje dedykowane transformacje XML Schema do Java, Java dodokumentów XML. Dzięki tym transformacjom procesy pobierania iprzechowywania danych zostały w pełni zautomatyzowane.Zaimplementowane podejście XML data binding umożliwia walidacjępodstawowych...
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Methods of deep modification of low-bearing soil for the foundation of new and spare air runways
PublicationAfter analyzing the impact of aircraft on the airport pavement (parking spaces, runways, startways), it was considered advisable to consider the problem of deep improvement or strengthening of its subsoil. This is especially true for low-bearing soil. The paper presents a quick and effective method of strengthening the subsoil intended for the construction of engineering structures used for civil...
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Innovation and new technologies in mineral processing
EventsZapraszamy Państwa na webinarium nt. innowacji i nowych technologii w przetwórstwie surowców mineralnych z dyrektorem globalnym firmy FLSmidth Flotation. Obowiązuje rejestracja.
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Multi-fidelity EM simulations and constrained surrogate modelling for low-cost multi-objective design optimisation of antennas
PublicationIn this study, a technique for low-cost multi-objective design optimisation of antenna structures has been proposed. The proposed approach is an enhancement of a recently reported surrogate-assisted technique exploiting variable-fidelity electromagnetic (EM) simulations and auxiliary kriging interpolation surrogate, the latter utilised to produce the initial approximation of the Pareto set. A bottleneck of the procedure for higher-dimensional...
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PAH diagnostic ratios for the identification of pollution emission sources
PublicationPolycyclic aromatic hydrocarbon (PAH) diagnostic ratios have recently come into common use as a toolfor identifying and assessing pollution emission sources. Some diagnostic ratios are based on parentPAHs, others on the proportions of alkyl-substituted to non-substituted molecules. The ratios areapplicable to PAHs determined in different environmental media: air (gas þ particle phase), water,sediment, soil, as well as biomonitor...
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Pin-on-Substrate Gap Waveguide: An Extremely Low-Cost Realization of High-Performance Gap Waveguide Components
PublicationConsidering the limitations of currently available technologies for the realization of microwave components and antennas, a trade-off between different factors including the efficiency and fabrication cost is required. The main objective of this letter is to propose a novel method for the realization of gap waveguides (GWGs) that take advantage of conventional PCB fabrication technology, thus are low cost and light weight. Moreover,...
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Processing of Marine Satellite Data in WEB-BASED GIS
PublicationGIS systems are important modern word. They allow to quickly analyse and corelate various data bound to their geographical context. The paper describes Web-base GIS with ability to integrate and analyse data from many sources such as: satellite imagery, threat simulation models, marine vessels Automatic Identification System, raster and vector topographic charts. Some details of system architecture and implementation are presented...
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Features extraction from the electrocatalytic gas sensor responses
PublicationOne of the types of gas sensors used for detection and identification of toxic-air pollutant is an electrocatalytic gas sensor. The electrocatalytic sensors are working in cyclic voltammetry mode, enable detection of various gases. Their response are in the form of I-V curves which contain information about the type and the concentration of measured volatile compound. However,...
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Zdzisław Kowalczuk prof. dr hab. inż.
PeopleZdzislaw Kowalczuk received his M.Sc. degree in 1978 and Ph.D. degree in 1986, both in Automatic Control from Technical University of Gdańsk (TUG), Gdańsk, Poland. In 1993 he received his D.Sc. degree (Dr Habilitus) in Automatic Control from Silesian Technical University, Gliwice, Poland, and the title of Professor from the President of Poland in 2003. Since 1978 he has been with Faculty of Electronics, Telecommunications and Informatics...
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Resource constrained neural network training
PublicationModern applications of neural-network-based AI solutions tend to move from datacenter backends to low-power edge devices. Environmental, computational, and power constraints are inevitable consequences of such a shift. Limiting the bit count of neural network parameters proved to be a valid technique for speeding up and increasing efficiency of the inference process. Hence, it is understandable that a similar approach is gaining...
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Foundations and Trends in Machine Learning
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Machine Learning and Knowledge Extraction
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Machine Learning-Science and Technology
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Miniaturization of ESPAR Antenna Using Low-Cost 3D Printing Process
PublicationIn this paper, the miniaturized electronically steerable parasitic array radiator (ESPAR) antenna is presented. The size reduction was obtained by embedding its active and passive elements in polylactic acid (PLA) plastic material commonly used in low-cost 3D printing. The influence of 3D printing process imperfections on the ESPAR antenna design is investigated and a simple yet effective method to...
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Calibration-Free Single-Anchor Indoor Localization Using an ESPAR Antenna
PublicationIn this paper, we present a novel, low-cost approach to indoor localization that is capable of performing localization processes in real indoor environments and does not require calibration or recalibration procedures. To this end, we propose a single-anchor architecture and design based on an electronically steerable parasitic array radiator (ESPAR) antenna and Nordic Semiconductor nRF52840 utilizing Bluetooth Low Energy (BLE)...
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Application of thin diamond films in low-coherence fiber-optic Fabry Pérot displacement sensor
PublicationThe novel fiber-optic low coherence sensor with thin diamond films is demonstrated. The undoped and boron-doped diamond films were elaborated by the use of the microwave plasma enhanced chemical vapor deposition (μPE CVD) system. The optical signal from the Fabry–Pérot cavity made with the application of those thin films is sensitive to displacement. The sensor characterization was made in the range of 0–600 μm. The measurements...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Anna Zielińska-Jurek prof. dr hab. inż.
People2018 DSc in technical sciences in the field of chemical technology Chemical Faculty, Gdansk University of Technology, Title: “Functionalized titanium(IV) oxide as a photocatalyst for environmental purification” 2011 Ph. D. in technical sciences in the field of chemical technology Chemical Faculty, Gdansk University of Technology, Title of the dissertation:...
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Pedestrian detection in low-resolution thermal images
PublicationOver one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...
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Efficient uncertainty quantification using sequential sampling-based neural networks
PublicationUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
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Different Ways to Apply a Measurement Instrument of E-Nose Type to Evaluate Ambient Air Quality with Respect to Odour Nuisance in a Vicinity of Municipal Processing Plants
PublicationThis review paper presents different ways to apply a measurement instrument of e-nose type to evaluate ambient air with respect to detection of the odorants characterized by unpleasant odour in a vicinity of municipal processing plants. An emphasis was put on the following applications of the electronic nose instruments: monitoring networks, remote controlled robots and drones as well as portable devices. Moreover, this paper presents...
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Detecting Lombard Speech Using Deep Learning Approach
PublicationRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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The In-House Method of Manufacturing a Low-Cost Heat Pipe with Specified Thermophysical Properties and Geometry
PublicationVarious types of heat pipes are available to purchase off the shelf, from various manufacturers, but most of them have strictly defined geometry and technical parameters. However, when there is a need to use a heat pipe (HP) with an unusual size and shape or working conditions other than the standard ones, it becomes very costly to order them from manufacturers, especially in small quantities, and only a few producers are willing...
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Low-cost performance-driven modelling of compact microwave components with two-layer surrogates and gradient kriging
PublicationUtilization of electromagnetic (EM) simulation tools has become indispensable for reliable evaluation of microwave components. As the cost of an individual analysis may already be considerable, the computational overhead associated with EM-driven tasks that require massive simulations (e.g., optimization) may turn prohibitive. One of mitigation methods is the employment of equivalent network models. Yet, they are incapable of accounting...
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublicationIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublicationIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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Design aspects of a low-cost prosthetic arm for people with severe movement disabilities
PublicationIn this paper the main aspects of mechanical design behind the low-cost prosthetic arm are presented. The fundamentals of a proper design has been defined to obtain functional 3D printed 5 degree of freedom (DOF) prosthesis. The designed prosthetic arm is a part of the hybrid interface with eye tracking movement control. The main focus was to create affordable but usable prosthesis which corresponds in size and weights to the human...
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The Progress in Electron Microscopy Studies of Particulate Matters to Be Used as a Standard Monitoring Method for Air Dust Pollution
PublicationThe present article reviews studies on air solid particles carried out with the use of electron microscopy. Particle analysis combining scanning and transmission electron microscopy (SEM and TEM) can be used to derive size-resolved information of the composition, mixing state, morphology, and complex refractive index of atmospheric aerosol particles. It seems that electron microscopy is more widely used in atmospheric particulate...
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Michał Wasilczuk prof. dr hab. inż.
PeopleMichał Wasilczuk received his M.Sc. (1986), Ph.D. (1994) and D.Sc. (2004) from the Gdansk University of Technology. In 2016 was nominated Professor Currently he is a Full Professor and Head of the Department of Machine Design and Automotive Engineering at the Faculty of Mechanical Engineers at GUT Bearing systems and tribology are the main fields of his scientific and engineering interest - starting from the Ph.D. devoted to...
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Electrochemical sensor for measurement of volatile organic compounds in air
PublicationPrzedstawiono rezultaty badań prototypowego czujnika do oznaczania mrówczanu etylu i formaldehydu w powietrzu. Określono czułość wskazań czujnika i jego granice oznaczalności wykorzystując jako techniki detekcyjne pulsową woltamperometrię różnicową (DPV) oraz woltamperometrię fali prostokątnej (SWV). Elektrodę roboczą i przeciwelektrodę stanowiły elektrody z Pt. Elektrolitem wewnętrznym była ciecz jonowa (chlorek 1-heksylo,3-metyloimidazolinowy)....
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Analysis of exhaled breath for dengue disease detection by low-cost electronic nose system
PublicationThis paper presents a procedure and a set-up of an electronic nose system analyzing exhaled breath to detect the patients suffering from dengue – a mosquito-borne tropical disease. Low-power resistive gas sensors (MiCS-6814, TGS8100) were used to detect volatile organic compounds (VOCs) in the exhaled breath. The end-tidal phase of patients exhaled breath was collected with a BioVOCTM breath sampler. Two strategies were assessed...
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Blockchain based Secure Data Exchange between Cloud Networks and Smart Hand-held Devices for use in Smart Cities
PublicationIn relation to smart city planning and management, processing huge amounts of generated data and execution of non-lightweight cryptographic algorithms on resource constraint devices at disposal, is the primary focus of researchers today. To enable secure exchange of data between cloud networks and mobile devices, in particular smart hand held devices, this paper presents Blockchain based approach that disperses a public/free key...
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Machine learning applied to bi-heterocyclic drugs recognition
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PERFORMANCE COMPARISON OF MACHINE LEARNING ALGORITHMS FOR PREDICTIVE MAINTENANCE
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Machine Learning for Sensorless Temperature Estimation of a BLDC Motor
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Machine Learning Modelling and Feature Engineering in Seismology Experiment
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The use of machine learning for face regions detection in thermograms
PublicationThe aim of this study is to analyse the methods of detecting characteristic points of the face in thermographic images. As part of the implementation an extensive analysis of scientific publications covering similar issues both for the analysis of images made in visible light and thermographic images was carried out. On the basis of this analysis, 3 models were selected and then they were implemented and tested on the basis of...
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Low Cost Hexacopter Autonomous Platform for Testing and Developing Photogrammetry Technologies and Intelligent Navigation Systems
PublicationLow-cost solutions for autonomous aerial platforms are being intensively developed and used within geodetic community. Unmanned aerial vehicles are becoming very popular and widely used for photogrammetry and remote sensing applications. Today’s market offers an affordable price components for unmanned solution with significant quality and accuracy growth. Every year market offers a new solutions for autonomous platforms with better...
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Computer Networks EN 2022
e-Learning CoursesThe student becomes familiar with the network layered logical architectures, classifies the basic problems of network communication and identifies and analyzes selected protocols and mechanisms of LAN and WAN (IP) networks.
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Computer Networks EN 2023
e-Learning CoursesThe student becomes familiar with the network layered logical architectures, classifies the basic problems of network communication and identifies and analyzes selected protocols and mechanisms of LAN and WAN (IP) networks.
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Domain segmentation for low-cost surrogate-assisted multi-objective design optimisation of antennas
PublicationAbstract: Information regarding the best possible design trade-offs of an antenna structure can be obtained through multiobjective optimisation (MO). Unfortunately, MO is extremely challenging if full-wave electromagnetic (EM) simulation models are used for performance evaluation. Yet, for the majority of contemporary antennas, EM analysis is the only tool that ensures reliability. This study introduces a procedure for accelerated...
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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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Air Pollution, Oxidative Stress, and the Risk of Development of Type 1 Diabetes
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ANN for human pose estimation in low resolution depth images
PublicationThe paper presents an approach to localize human body joints in 3D coordinates based on a single low resolution depth image. First a framework to generate a database of 80k realistic depth images from a 3D body model is described. Then data preprocessing and normalization procedure, and DNN and MLP artificial neural networks architectures and training are presented. The robustness against camera distance and image noise is analysed....