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Search results for: AIR POLLUTION, LOW-COST SENSOR CALIBRATION, MACHINE LEARNING, DATA PRE-PROCESSING, NEURAL NETWORKS
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Air Pollution, Oxidative Stress, and the Risk of Development of Type 1 Diabetes
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Low-cost multi-criterial design optimization of compact microwave passives using constrained surrogates and dimensionality reduction
PublicationDesign of contemporary microwave circuits is a challenging task. Typically, it has to take into account several performance requirements and constraints. The design objectives are often conflicting and their simultaneous improvement may not be possible; instead, compromise solutions are to be sought. Representative examples are miniaturized microwave passives where reduction of the circuit size has a detrimental effect on its electrical...
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CMOS implementation of an analogue median filter for image processing in real time
PublicationAn analogue median filter, realised in a 0.35 μm CMOS technology, is presented in this paper. The key advantages of the filter are: high speed of image processing (50 frames per second), low-power operation (below 1.25 mW under 3.3 V supply) and relatively high accuracy of signal processing. The presented filter is a part of an integrated circuit for image processing (a vision chip), containing: a photo-sensor matrix, a set of...
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FFT analysis of temperature modulated semiconductor gas sensor response for the prediction of ammonia concentration under humidity interference
PublicationThe increasing environmental contamination forces the need to design reliable devices for detecting of the volatile compounds present in the air. For this purpose semiconductor gas sensors, which have been widely used for years, are often utilized. Although they have many advantages such as low price and quite long life time, they still lack of long term stability and selectivity. Namely, environmental conditions have significant...
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Inverse surrogate modeling for low-cost geometry scaling of microwave and antenna structures
PublicationPurpose–The purpose of this paper is to investigate strategies for expedited dimension scaling ofelectromagnetic (EM)-simulated microwave and antenna structures, exploiting the concept of variable-fidelity inverse surrogate modeling.Design/methodology/approach–A fast inverse surrogate modeling technique is described fordimension scaling of microwave and antenna structures. The model is established using referencedesigns obtained...
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Near Field Coupled Wireless Microwave Sensor
PublicationThis paper presents a wireless planar microwave sensor operating at industrial scientific and medical (ISM) frequency for the detection of dielectric materials. The microwave sensor consists of a reader (ground defected microstrip coupled line) and a passive tag where a complementary split-ring resonator (CSRR) is made on the commercially available copper-foil. The CSRR is a peel-off type tag that is excited using the near field...
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Electrical and noise responses of carbon nanotube networks enhanced by UV light for detection of organic gases (ethanol, acetone)
Open Research DataCarbon nanotube networks of different optical transparencies were investigated via resistance and 1/f noise measurements for detection of ethanol and acetone. The sensor resistive and noise responses were collected for dark and UV-assisted conditions, revealing the improvement in sensor sensitivity and limit of detection after applying UV light (275...
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The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing
PublicationRubbers combine the flexibility with mechanical strength, supporting myriad applications, but suffer from inherent flammability. Formulation and production of flame-retardant rubber composites (FRRCs) have intensively been practiced over years, but not comprehensively reviewed. This necessity has outlined collecting, analyzing, screening, classifying, and interpreting the literature with the aim of classifying the FRRCs. We quantified...
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Bożena Kostek prof. dr hab. inż.
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The Use of Artificial Neural Networks and Decision Trees to Predict the Degree of Odor Nuisance of Post-Digestion Sludge in the Sewage Treatment Plant Process
PublicationThis paper presents the application of artificial neural networks and decision trees for the prediction of odor properties of post-fermentation sludge from a biological-mechanical wastewater treatment plant. The input parameters were concentrations of popular compounds present in the sludge, such as toluene, p-xylene, and p-cresol, and process parameters including the concentration of volatile fatty acids, pH, and alkalinity in...
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Sounding Mechanism of a Flue Organ Pipe—A Multi-Sensor Measurement Approach
PublicationThis work presents an approach that integrates the results of measuring, analyzing, and modeling air flow phenomena driven by pressurized air in a flue organ pipe. The investigation concerns a Bourdon organ pipe. Measurements are performed in an anechoic chamber using the Cartesian robot equipped with a 3D acoustic vector sensor (AVS) that acquires both acoustic pressure and air particle velocity. Also, a high-speed camera is employed...
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Low-cost 3D Printed Circularly Polarized Lens Antenna for 5.9 GHz V2X Applications
PublicationThis paper presents design and realization of a circularly polarized antenna consisting of a linearly polarized patch antenna and a 3D printed lens, at the same time performing the functions of wave collimator and a polarizer. The antenna is dedicated for 802.11p systems, as a part of road infrastructure, with operation bandwidth 5.85 - 5.925 GHz. Its realised gain and axial ratio at center frequency 5.9 GHz are 14.3 dBi and 2.17...
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Monitoring Parkinson's disease patients employing biometric sensors and rule-based data processing
PublicationArtykuł prezentuje automatyczny system wykrywania pogorszenia zdrowia pacjentów z chorobą Parkinsona opracowany w ramach projektu PERFORM.The paper presents how rule-based processing can be applied to automatically evaluate the motor state of Parkinson's Disease patients. Automatic monitoring of patients by using biometric sensors can provide assessment of the Parkinson's Disease symptoms. All data on PD patients' state are compared...
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Low-cost multi-objective design of compact microwave structures using domain patching
PublicationA good compromise between size and electrical performance is an important design consideration for compact microwave structures. Comprehensive information about size/performance trade-offs can be obtained through multi-objective optimization. Due to considerable electromagnetic (EM) cross-couplings in highly compressed layouts, the design process has to be conducted at the level of high-fidelity EM analysis which is computationally...
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The computational methods in the development of a novel multianalyte calibration technique for potentiometric integrated sensors systems
PublicationIn recent years, integration and miniaturization of ion-selective electrodes (ISEs) have brought many benefits resulting in the possibility of simultaneous determination of the ions concentration in small volume samples. One of the key problems related to the preparation of potentiometric integrated sensors systems (PISSs) is a calibration procedure due to the necessity to calibrate each particular sensor separately. The main aim...
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Distributed Trust Management Model for Wireless Sensor Networks
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Localization in wireless sensor networks based on zigbee platform
PublicationW artykule porównano dwie różne metody lokalizacji w sieciach sensorów bezprzewodowych. Jedną z metod jest implementacja sprzętowa algorytmu w układzie nadawczo odbiorczym CC2431. Drugą metodą jest implementacja programowa. Wyniki testów przeprowadzonych na otwartym terenie oraz w pomieszczeniach zamkniętych zostały przedstawione i porównane w pracy.
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Pattern matching localization in ZigBee wireless sensor networks.
PublicationLokalizacja typu Pattern matching w sieciach sensorów bezprzewodowych ZigBee.Prezentacja metod implementacji algorytmów lokalizacji. Praktyczne zastosowanie i testowanie lokalizacji sieci ZigBee.
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Sensor data fusion techniques for environment modelling
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Marcin Sikorski prof. dr hab. inż.
PeopleMarcin Sikorski is a professor at the Department of Informatics in Management at the Faculty of Management and Economics of the Gdańsk University of Technology. Earlier he had numerous fellowships in academic institutions, among others in Germany (Universities in Bonn and in Heidelberg), Switzerland (ETH Zurich), the Netherlands (TU Eindhoven) and the USA (Harvard University). Professor Sikorski is a representative of Poland in...
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Neural networks in the diagnostics of induction motor rotor cages.
PublicationW środowisku Lab VIEW została stworzona aplikacja służąca do pomiaru, prezentacji i zapisu przebiegów widma prądu stojana z uwzględnieniem potrzeb pomiarowych występujących podczas badania wirników silników indukcyjnych przy użyciu sieci neuronowych. Utworzona na bazie zbioru uczącego sieć Kohonena z powodzeniem rozwiązała stawiany przed nią problem klasyfikacji widm prądu stojana, a co za tym idzie również diagnozy stanu...
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Applications of neural networks and perceptual masking to audio restoration
PublicationOmówiono zastosowania algorytmów uczących się w dziedzinie rekonstruowania nagrań fonicznych. Szczególną uwagę zwrócono na zastosowanie sztucznych sieci neuronowych do usuwania zakłócających impulsów. Ponadto opisano zastosowanie inteligentnego algorytmu decyzyjnego do sterowania maskowaniem perceptualnym w celu redukowania szumu.
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Application of neural networks for turbine rotor trajectory investigation.
PublicationW pracy przedstawiono rezultaty badań sieci neuronowych przewidujących trajektorię wirnika turbinowego uzyskanych ze stanowiska turbiny modelowej. Badania wykazały, iż sieci neuronowe wydają się być z powodzeniem zastosowane do przewidywania trajektorii ruchu wirnika turbiny. Najważniejszym zadaniem wydaje się poprawne określenie wektorów sygnałów wejściowych oraz wyjściowych jak również prawidłowe stworzenie sieci neuronowej....
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Problems in toxicity analysis - application of fuzzy neural networks
PublicationPraca dotyczy zastosowania sztucznych sieci neuronowych do przygotowywania danych do szacowania toksyczności (wody powierzchniowe). Przygotowanie to polega na sztucznym zagęszczaniu zbioru danych, które następnie mogą być wykorzystane do szacowania/modelowania wartości toksyczności na ich podstawie.
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Artificial Neural Networks in Microwave Components and Circuits Modeling
PublicationArtykuł dotyczy wykorzystania sztucznych sieci neuronowych (SNN) w projektowaniu i optymalizacji układów mikrofalowych.Zaprezentowano podstawowe zasady i założenia modelowania z użyciem SNN. Możliwości opisywanej metody opisano wykorzystując przykładowyprojekt anteny łatowej. Przedstawiono różne strategie modelowania układów, które wykorzystują możliwości opisywanej metody w połączeniu zwiedzą mikrofalową. Porównano również dokładność...
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An Approach to Data Reduction and Integrated Machine Classification
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Exploiting multi-interface networks: Connectivity and Cheapest Paths
PublicationLet G = (V,E) be a graph which models a set of wireless devices (nodes V) that can communicate by means of multiple radio interfaces, according to proximity and common interfaces (edges E). The problem of switching on (activating) the minimum cost set of interfaces at the nodes in order to guarantee the coverage of G was recently studied. A connection is covered (activated) when the endpoints of the corresponding edge share at...
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Low-Cost Multi-Objective Optimization Yagi-Uda Antenna in Multi-Dimensional Parameter Space
PublicationA surrogate-based technique for fast multi-objective optimization of a multi-parameter planar Yagi-Uda antenna structure is presented. The proposed method utilizes response surface approximation (RSA) models constructed using training samples obtained from evaluation of the low-fidelity antenna model. Utilization of the RSA models allowsfor fast determination of the best possible trade-offs between conflicting objectives in multi-objective...
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Electronic Noses for Indoor Air Quality Assessment
PublicationThis chapter presents a proposal of the use of electronic noses in the monitoring of indoor air quality. The main focus is put on the detailed characteristics of today’s indoor air quality control methods, the types of pollution in the air, and the development of electronic noses for air testing. Currently, scientists seek methodological and structural solutions that would enable real-time online indoor air control. It has been...
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Low-cost multi-objective optimization of antennas using Pareto front exploration and response features
PublicationIn the paper, a procedure for low-cost multi-objective optimization of antenna structures is presented. Our approach is based on exploration of the Pareto front representing the best possible trade-offs between conflicting objectives, here, the structure size and its electrical performance. Starting from the design representing the best in-band reflection level, subsequent Pareto-optimal designs are identified through local constrained...
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Low-cost multi-objective optimization and experimental validation of UWB MIMO antenna
PublicationPurpose–The purpose of this paper is to validate methodologies for expedited multi-objective designoptimization of complex antenna structures both numerically and experimentally.Design/methodology/approach–The task of identifying the best possible trade-offs between theantenna size and its electrical performance is formulated as multi-objective optimization problem.Algorithmic frameworks are described for finding Pareto-optimal...
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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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Investigation of Parallel Data Processing Using Hybrid High Performance CPU + GPU Systems and CUDA Streams
PublicationThe paper investigates parallel data processing in a hybrid CPU+GPU(s) system using multiple CUDA streams for overlapping communication and computations. This is crucial for efficient processing of data, in particular incoming data stream processing that would naturally be forwarded using multiple CUDA streams to GPUs. Performance is evaluated for various compute time to host-device communication time ratios, numbers of CUDA streams,...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublicationMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Game theory-based virtual machine migration for energy sustainability in cloud data centers
PublicationAs the demand for cloud computing services increases, optimizing resource allocation and energy consumption has become a key factor in achieving sustainability in cloud environments. This paper presents a novel approach to address these challenges through an optimized virtual machine (VM) migration strategy that employs a game-theoretic approach based on particle swarm optimization (PSO) (PSO-GTA). The proposed approach leverages...
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Low-Cost Unattended Design of Miniaturized 4 × 4 Butler Matrices with Nonstandard Phase Differences
PublicationDesign of Butler matrices dedicated to Internet of Things and 5th generation (5G) mobile systems—where small size and high performance are of primary concern—is a challenging task that often exceeds capabilities of conventional techniques. Lack of appropriate, unified design approaches is a serious bottleneck for the development of Butler structures for contemporary applications. In this work, a low-cost bottom-up procedure for...
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Dynamic Re-Clustering Leach-Based (Dr-Leach) Protocol for Wireless Sensor Networks
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublicationMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Theoretical and Economic Evaluation of Low-Cost Deep Eutectic Solvents for Effective Biogas Upgrading to Bio-Methane
PublicationThis paper presents the theoretical screening of 23 low-cost deep eutectic solvents (DESs) as absorbents for effective removal of the main impurities from biogas streams using a conductor-like screening model for real solvents (COSMO-RS). Based on thermodynamic parameters, i.e., the activity coefficient, excess enthalpy, and Henry’s constant, two DESs composed of choline chloride: urea in a 1:2 molar ratio (ChCl:U 1:2), and choline...
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Neural Architecture Search for Skin Lesion Classification
PublicationDeep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture. This is a tedious and time-consuming process that requires expert knowledge. Different tasks need very different architectures to obtain satisfactory results. The group of methods called the neural architecture search (NAS) helps to find effective architecture...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Self-Organising map neural network in the analysis of electromyography data of muscles acting at temporomandibular joint.
PublicationThe temporomandibular joint (TMJ) is the joint that via muscle action and jaw motion allows for necessary physiological performances such as mastication. Whereas mandible translates and rotates [1]. Estimation of activity of muscles acting at the TMJ provides a knowledge of activation pattern solely of a specific patient that an electromyography (EMG) examination was carried out [2]. In this work, a Self-Organising Maps (SOMs)...
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Systemy z Uczeniem Maszynowym / Systems with Machine Learning 2022/2023
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Low-Cost Open-Hardware System for Measurements of Antenna Far-Field Characteristics in Non-Anechoic Environments
PublicationExperimental validation belongs to the most important steps in the development of antenna structures. Measurements are normally performed in expensive, dedicated facilities such as anechoic chambers, or open-test sites. A high cost of their construction might not be justified when the main goal of antenna verification boils down to demonstration of the measurement procedure, or rough validation of the simulation models used for...
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublicationTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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Processing of LiDAR and Multibeam Sonar Point Cloud Data for 3D Surface and Object Shape Reconstruction
PublicationUnorganised point cloud dataset, as a transitional data model in several applications, usually contains a considerable amount of undesirable irregularities, such as strong variability of local point density, missing data, overlapping points and noise caused by scattering characteristics of the environment. For these reasons, further processing of such data, e.g. for construction of higher order geometric models of the topography...
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Data processing methods for dynamic medical thermography.
PublicationArtykuł przedstawia zastosowanie nowej metody syntezy obrazów w termografii dla potrzeb opisu ilościowego właściwości termicznych tkanek. Opis taki umożliwia różnicowanie przypadków medycznych. Metodę zastosowania dla licznych pomiarów fantomowych i in vitro w eksperymentach na zwierzętach (świnia domowa). Przedstawiono i omówiono rezultaty prac.
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Neural network approach to 2D Kalman filtering in image processing
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Low-Cost Embedded Control System for Environmental Monitoring
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An advanced low-cost sensorless induction motor drive
PublicationW artykule przedstawiono układ sterowania silnikiem asynchronicznym klatkowym pracujący bez pomiaru prędkości obrotowej. Układ zrealizowano na tanim procesorze stałoprzecinkowym. aspekty praktyczne realizacji układu rozpatrzono na podstawie uzyskanych wyników z symulacji i eksperymentu.