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Wyniki wyszukiwania dla: AIR QUALITY, POLLUTANT DETECTION, NITROGEN DIOXIDE, SENSOR CORRECTION, MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS
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Szymon Zaporowski mgr inż.
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Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublikacjaThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...
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Power quality conditioners with minimum number of current sensor requirement
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Vapor correction of FTIR spectra – A simple automatic least squares approach
PublikacjaFTIR spectroscopy is one of the best techniques to study intermolecular interactions. However, such an application requires high quality spectra with as little noise as possible, which are often difficult to obtain. One of the main sources of unwanted interference is water vapor. Here a robust method is proposed for automatic, fast and reliable vapor correction of FTIR spectra. The presented least squares approach of vapor subtraction...
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Application of a fuzzy neural network for river water quality prediction
PublikacjaMonitoring i modelowanie zmian w jakości wód powierzchniowych stanowią jeden z kluczowych elementów monitoringu i zarządzania ochroną środowiska na skalę globalną. Kontrolowanie tak złożonych i nieliniowych w swojej charakterystyce obiektów, jakimi są rzeki, jest trudnym zadaniem. Zazwyczaj do tego celu wykorzystuje się modele matematyczne, jednak czasem wymagają one bardzo dużej ilości danych, lub czas oczekiwania na odpowiedź...
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Quality assessment of mobile host services in IP networks
PublikacjaW pracy opisano podstawowe protokoły wspierające komunikację stacji ruchomych w sieciach IP. Przedmiotem zainteresowania były w szczególności rozwiązania MIP oraz Calkular IP i HAWAII - wspierające mobilność w skali makro bądź mikro. Przeprowadzono badania symulacyjne wskazujące na przydatność powyższych protokołów w przypadku różnych konfiguracji sieci.
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Can Evaluation Patterns Enable End Users to Evaluate the Quality of an e-learning System? An Exploratory Study.
PublikacjaThis paper presents the results of an exploratory study whose main aim is to verify if the Pattern-Based (PB) inspection technique enables end users to perform reliable evaluation of e-learning systems in real work-related settings. The study involved 13 Polish and Italian participants, who did not have an HCI background, but used e-learning platforms for didactic and/or administrative purposes. The study revealed that the participants...
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Super-resolved Thermal Imagery for High-accuracy Facial Areas Detection and Analysis
PublikacjaIn 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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Neural Network Subgraphs Correlation with Trained Model Accuracy
PublikacjaNeural Architecture Search (NAS) is a computationally demanding process of finding optimal neural network architecture for a given task. Conceptually, NAS comprises applying a search strategy on a predefined search space accompanied by a performance evaluation method. The design of search space alone is expected to substantially impact NAS efficiency. We consider neural networks as graphs and find a correlation between the presence...
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Modeling and optimizing the removal of cadmium by Sinapis alba L. from contaminated soil via Response Surface Methodology and Artificial Neural Networks during assisted phytoremediation with sewage sludge
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Design Optimization of an Anisotropic Magnetoresistance Sensor for Detection of Magnetic Nanoparticles
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Extended Hopfield models of neural networks for combinatorial multiobjective optimization problems
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Neural Networks Based on Ultrafast Time-Delayed Effects in Exciton Polaritons
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Use of Neural Networks in Diagnostics of Rolling-Element Bearing of the Induction Motor
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Automatic singing voice recognition employing neural networks and rough sets
PublikacjaCelem prac opisanych w referacie jest automatyczne rozpoznawanie głosów śpiewaczych. Do tego celu utworzona została baza nagrań próbek śpiewu profesjonalnego i amatorskiego. Próbki poddane zostały parametryzacji parametrami zaproponowanymi przez autorów ściśle do tego celu. Sposób wyznaczenia parametrów i ich interpretacja fizyczna przedstawione są w referacie. Parametry wprowadzane są do systemów decyzyjnych, klasyfikatorów opartych...
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Neural Networks in the Diagnostics Process of Low-Power Solar Plant Devices
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Musical phrase representation and recognition by means of neural networks and rough sets.
PublikacjaW artykule przedstawiono podstawowe definicje dotyczące frazy muzycznej. W eksperymentach posłużono się zapisem parametrycznym. W celu wzmocnienia procesu rozpoznawania wykorzystano kodowanie entropijne muzyki. W eksperymentach klasyfikacji oparto się o sztuczne sieci neuronowe i metodę zbiorów przybliżonych. Słowa kluczowe: fraza muzyczna, klasyfikacja, sztuczne sieci neuronowe, metoda zbiorów przybliżonych
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Comparison of effectiveness of musical sound separation algorithms employing neural networks.
PublikacjaNiniejszy referat przedstawia kilka algorytmów służących do separacji dźwięków instrumentów muzycznych. Zaproponowane podejście do dekompozycji miksów dźwiękowych opiera się na założeniu, że wysokość dźwięków w miksie jest znana, tzn. wejściem dla algorytmów jest przebieg zmian wysokości dźwięków składowych miksu. Proces estymacji fazy i amplitudy składowych harmonicznych wykorzystuje dopasowywanie zespolonych przebiegów harmonicznych...
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Estimation of musical sound separation algorithm effectiveness employing neural networks.
PublikacjaŚlepa separacja dźwięków sygnałów muzycznych zawartych w zmiksowanym materiale jest trudnym zadaniem. Jest to spowodowane tym, że dźwięki znajdujące się w relacjach harmonicznych mogą zawierać kolidujące składowe sinusoidalne (składowe harmoniczne). Ewaluacja wyników separacji jest również problematyczna, gdyż analiza błędu energetycznego często nie odzwierciedla subiektywnej jakości odseparowanych sygnałów. W tej publikacji zostały...
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Optimization of a three-bed adsorption chiller by genetic algorithms and neural networks
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Implementing artificial intelligence in forecasting the risk of personal bankruptcies in Poland and Taiwan
PublikacjaResearch background: The global financial crisis from 2007 to 2012, the COVID-19 pandemic, and the current war in Ukraine have dramatically increased the risk of consumer bankruptcies worldwide. All three crises negatively impact the financial situation of households due to increased interest rates, inflation rates, volatile exchange rates, and other significant macroeconomic factors. Financial difficulties may arise when the...
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Evaluation of the prediction ability of air pollutants based on the electronic nose responses
PublikacjaElectronic noses are able to perform on-line measurements of the toxic volatile compounds in air. Due to their low cost and compact size they can be placed in the areas exposed to pollution, outside the laboratory. Those advantages, on the other side, force the need for development of the reliable sensors data analysis procedures. One of the most important issues connected with electronic noses is the lack of stability of the gas...
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Taking decisions in the diagnostic intelligent systems on the basis information from an artificial neural network
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Artificial Neural Network (ANN)-Based Voltage Stability Prediction of Test Microgrid Grid
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Anna Zielińska-Jurek prof. dr hab. inż.
OsobyResearch work on photocatalysis by Prof. Anna Zielinska-Jurek started in 2006 at Gdansk University of Technology (Poland), including 3-month research stay at Hokkaido University, Training School “Environmental Applications of TiO2 Photocatalysis” at the University of Oulu in Finland granted by COST Program and Training School “NanoBiophotonics” at the Beckmann Institute, Urbana-Champaign in the USA granted by University of Illinois....
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A method to monitor urinary carbon dioxide in patients with septic shock
PublikacjaSevere sepsis and septic shock are life-threatening conditions with mortality rates exceeding 31% (Levy et al., 2012) [1]. Septicemia was the most expensive US hospital condition in 2011 (Torio and Andrews, 2006)[2]. Urinary carbon dioxide may provide rapid, clinically useful information about a patient’s status, empowering physicians to intervene earlier and improve septic shock mortality. The objective of this paper is to validate...
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E-learning courses
Kursy OnlineStrona zawiera zbiór kursów prowadzonych metodą e-learning. Kursy te są skierowane do studentów I stopnia kierunku informatyka na VII semestrze profilu Bazy danych, do studentów na kierunku informatyka na II semestrze studiów II stopnia na specjalności ZAD i ISI.
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Obtaining a Well-Trained Artificial Intelligence Algorithm from Cross-Validation in Endoscopy
PublikacjaThe article shortly discusses endoscopic video analysis problems and artificial intelligence algorithms supporting it. The most common method of efficiency testing of these algorithms is to perform intensive cross-validation. This allows for accurately evaluate their performance of generalization. One of the main problems of this procedure is that there is no simple and universal way of obtaining a specific instance of a well-trained...
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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publikacja—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
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Lessons learned from developing an Industry 4.0 mobile process management system supported by Artificial Intelligence
PublikacjaResearch, development and innovation (RDI) projects are undertaken in order to improve existing, or develop new, more efficient products and services. Moreover, the goal of innovation is to produce new knowledge through research, and disseminating it through education and training. In this line of thinking, this paper reports and discusses the lessons learned from the undertaken project, regarding three areas: machine learning...
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Modeling in Machine Design
Kursy OnlineThe course is meant to show the students how to build calculation models in machine design
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Measures of region failure survivability for wireless mesh networks
PublikacjaWireless mesh networks (WMNs) are considered as a promising alternative to wired local, or metropolitan area networks. However, owing to their exposure to various disruptive events, including natural disasters, or human threats, many WMN network elements located close to the failure epicentre are frequently in danger of a simultaneous failure, referred to as a region failure. Therefore, network survivability, being the ability...
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Permeation passive sampling as a tool for the evaluation of indoor air quality
PublikacjaOkreślono stężenie średnie ważone w czasie wybranych lotnych związków organicznych w powietrzu ośmiu pomieszczeniach mieszkalnych na terenie miasta Gdańska. Do pobierania próbek analitów z powietrza wewnętrznego zastosowano permeacyjny dozymetr pasywny typu pudełkowego oraz technikę dynamiczną (urządzenie przepływowe z rurką sorpcyjną). Porównano wyniki uzyskane w wyniku zastosowania w/w technik pobierania próbek analitów.
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Study on transmission quality in cellular 4G and 5G networks between 2019–2021: Impact of the COVID-19 pandemic on the level of provided services by operating base transceiver stations
PublikacjaThe COVID-19 pandemic has significantly limited user mobility, not least among students. Remote learning had a particular impact on resource allocation in relation to using terrestrial cellular networks, especially 4G systems in urban agglomerations. This paper presents the results of a quality evaluation of an outdoor environment, carried out between 2019 and 2021 on the campus of a technical university. Annual studies are conducted...
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LOS and NLOS identification in real indoor environment using deep learning approach
PublikacjaVisibility 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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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublikacjaRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublikacjaThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
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EFFICIENCY OF GAS MIXTURES DETECTION BY RESISTIVE GAS SENSORS
PublikacjaResistive gas sensors are very popular and are commonly used to detect various gases and their mixtures. Their main disadvantage is very limited selectivity. Practical use of gas sensors in environmental applications (e.g., in sewage systems to protect workers, in air conditioning systems to monitor atmosphere quality) requires determination of concentration of a few mixed gases at the same time. We would like to present recent...
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Neural Architecture Search for Skin Lesion Classification
PublikacjaDeep 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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Evaluation of the Commercial Electrochemical Gas Sensors for the Monitoring of CO in Ambient Air
PublikacjaAir pollution is a growing concern of civilized world, which has a significant impact on human health and the environment. Recent studies highlight that the exposure to polluted air can increase the incidence of diseases and deteriorate the quality of life. Hence, it is necessary to develop tools for real-time air quality monitoring. For air pollution monitoring a wide range of stationary gas and particulate analysers can be used....
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Nitrogen removal in vertical flow constructed wetlands: influence of bed depth and high nitrogen loadings
PublikacjaThe aim of the study was to evaluate the nitrogen removal and its effects on the plant’s growth and leaves morphology. using two subsurface vertical flow (VF bed), with different depths (0.24 m2 × 0.70 m; 0.24 m2 × 0.35 m) and nitrogen load increments. The VF bed were planted with Vetiveria zizanioides, filled with light expanded clay aggregates (Leca®NR 10/20) and fed in parallel mode with synthetic wastewater. High ammonium nitrogen...
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The new analyzer based on single pellistor sensor for determination of hydrogen and methane in air
PublikacjaW artykule przedstawiono rezultaty niedawnych badań nad konstrukcją prostego i selektywnego analizatora do monitoringu stężenia gazów wybuchowych w powietrzu. Opisano konstrukcję takiego urządzenia i wyniki prób laboratoryjnych dla gazowych mieszanin wzorcowych.
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Monitoring Regenerative Heat Exchanger in Steam Power Plant by Making Use of the Recurrent Neural Network
PublikacjaArtificial Intelligence algorithms are being increasingly used in industrial applications. Their important function is to support operation of diagnostic systems. This paper pesents a new approach to the monitoring of a regenerative heat exchanger in a steam power plant, which is based on a specific use of the Recurrent Neural Network (RNN). The proposed approach was tested using real data. This approach can be easily adapted to...
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Application of artificial intelligence into/for control of flexible manufacturing cell
PublikacjaThe application of artificial intelligence in technological processes control is usually limited. One problem is how to respond to changes in the environment of manufacturing system. A way to overcome the above shortcoming is to use fuzzy logic for representation of the inexact information. In this paper fundamentals of artificial intelligence and fuzzy logic are introduced from a theoretical point of view. Still more the fuzzy...
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Resource constrained neural network training
PublikacjaModern 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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Electrochemical sensor for measurement of volatile organic compounds employing square wave perturbation voltage
PublikacjaThe paper presents the results of investigation on a prototype sensor for measurement of benzaldehyde in air. Sensitivity and limit of quantification of the sensor were determined for different internal electrolyte using the square wave voltammetry (SWV) as a detection technique. The working and counter electrodes were made of platinum. Ionic liquids 1-hexyl, 3-methylimidazolium chloride,1-hexyl, 3-methylimidazolium bis (trifluoromethanesulfonyl)...
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Machine Learning and data mining tools applied for databases of low number of records
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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