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Wyniki wyszukiwania dla: artificial dets
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CANADIAN MODERN LANGUAGE REVIEW-REVUE CANADIENNE DES LANGUES VIVANTES
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Bulletin du CIETA (Centre International d'études des textiles anciens)
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Discours social: analyse du discours et sociocritique des textes
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Schweizer Beiträge zur Kulturgeschichte und Archäologie des Mittelalters, Basel
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Canadian Biosystems Engineering / Le Genie des biosystems au Canada
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STAPS-Sciences et Techniques des Activites Physiques et Sportives
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Bulletin de la Societe Royale des Sciences de Liege
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Orient - Deutsche Zeitschrift für Politik und Wirtschaft des Orients
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Revue Roumaine des Sciences Techniques-Serie Electrotechnique et Energetique
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Revue d'Elevage et de Medecine Veterinaire des Pays Tropicaux
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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis 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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Kazimierz Darowicki prof.dr hab. inż.
OsobyProf. dr hab. inż. Kazimierz Darowicki studia wyższe ukończył w czerwcu 1981 roku. Już w marcu 1981 roku został zatrudniony na Wydziale Chemicznym Politechniki Gdańskiej. Na Wydziale Chemicznym przeszedł kolejne szczeble rozwoju do stanowiska profesora zwyczajnego i kierownika Katedry Elektrochemii, Korozji i Inżynierii Materiałowej włącznie. W działalności naukowej reprezentuje nauki techniczne, a jego specjalność naukowa i zawodowa...
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Deep eutectic solvents microbial toxicity: Current state of art and critical evaluation of testing methods
PublikacjaDeep eutectic solvents (DESs) were described at the beginning of 21st century and they consist of a mixture of two or more solid components, which gives rise to a lower melting point compared to the starting materials. Over the years, DESs have proved to be a promising alternative to traditional organic solvents and ionic liquids (ILs) due to their low volatility, low inflammability, easy preparation, and usually low cost of compounds...
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Diverse roles, advantages and importance of deep eutectic solvents application in solid and liquid-phase microextraction techniques – A review
PublikacjaDeep eutectic solvents (DESs) are an emerging class of promising green solvents used as an alternative to traditional organic solvents in various scientific fields. The high biodegradability, biocompatibility, eco-friendliness, tunable properties, and presence of active groups in DESs make them the preferred solvent in a variety of solid- and liquid-phase microextraction techniques. Aside from these benefits, the use of DESs in...
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Optymalizacja treningu i wnioskowania sieci neuronowych
PublikacjaSieci neuronowe są jedną z najpopularniejszych i najszybciej rozwijających się dziedzin sztucznej inteligencji. Ich praktyczne wykorzystanie umożliwiło szersze użycie komputerów w wielu obszarach komunikacji, przemysłu i transportu. Dowody tego są widoczne w elektronice użytkowej, medycynie, a nawet w zastosowaniach militarnych. Wykorzystanie sztucznej inteligencji w wielu przypadkach wymaga jednak znacznej mocy obliczeniowej,...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublikacjaArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
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Ireneusz Kreja dr hab. inż.
OsobyAbsolwent klasy matematycznej I Liceum Ogólnokształcącego w Gdańsku im. Mikołaja Kopernika (1974). Absolwent Wydziału Budownictwa Lądowego Politechniki Gdańskiej (1979). Od 1979 pracuje na PG. W 1989 uzyskał doktorat (z wyróżnieniem), na Wydziale Budownictwa Lądowego, a w 2008 habilitował się (również z wyróżnieniem) na Wydziale Inżynierii Lądowej i Środowiska PG. Od 2011 jest profesorem PG. Na Politechnice Gdańskiej pełnił funkcje:...
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Magdalena Maria Popowska dr
OsobyAbsolwentka Uniwersytetu im Adama Mickiewicza w Poznaniu oraz Ecole Supérieure de Commerce w Rouen. Pracownik badawczo dydaktyczny, autorka i recenzentka wielu artykułów publikowanych w czasopismach krajowych i międzynarodowych. Przez wiele lat odpowiedzialna za procesy internacjonalizacji, w latach 2008-2016 jako prodziekan ds. międzynarodowych i publicznych, a 2016-2020 jako pełnomocnik dziekana ds. współpracy międzynarodowej....
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General concept of reduction process for big data obtained by interferometric methods
PublikacjaInterferometric sonar systems apply the phase content of the sonar signal to measure the angle of a wave front returned from the seafloor or from a target. It collect a big data – datasets that are so large or complex that traditional data processing application software is inadequate to deal with them. The recording a large number of data is associated with the difficulty of their efficient use. So data have to be reduced. The main...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublikacjaBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublikacjaNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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An agent-based framework for distributed learning
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Deep learning approach for delamination identification using animation of Lamb waves
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach
PublikacjaShip imaging position plays an important role in visual navigation, and thus significant focuses have been paid to accurately extract ship imaging positions in maritime videos. Previous studies are mainly conducted in the horizontal ship detection manner from maritime image sequences. This can lead to unsatisfied ship detection performance due to that some background pixels maybe wrongly identified as ship contours. To address...
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
PublikacjaHigh-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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Instance segmentation of stack composed of unknown objects
PublikacjaThe article reviews neural network architectures designed for the segmentation task. It focuses mainly on instance segmentation of stacked objects. The main assumption is that segmentation is based on a color image with an additional depth layer. The paper also introduces the Stacked Bricks Dataset based on three cameras: RealSense L515, ZED2, and a synthetic one. Selected architectures: DeepLab, Mask RCNN, DEtection TRansformer,...
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Interpretation and modeling of emotions in the management of autonomous robots using a control paradigm based on a scheduling variable
PublikacjaThe paper presents a technical introduction to psychological theories of emotions. It highlights a usable ideaimplemented in a number of recently developed computational systems of emotions, and the hypothesis thatemotion can play the role of a scheduling variable in controlling autonomous robots. In the main part ofthis study, we outline our own computational system of emotion – xEmotion – designed as a key structuralelement in...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublikacjaThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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Super-resolved Thermal Imagery for High-accuracy Facial Areas Detection and Analysis
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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Quantitative Analysis of Biofilm Formed on Vascular Prostheses by Staphylococcus Epidermidis with Different ica and aap Genetic Status
PublikacjaOBJECTIVES: This study aims to examine biofilm formed on vascular prostheses by Staphylococcus epidermidis with different ica and aap genetic status, and to evaluate the effect of antibiotic-modified prostheses on bacterial colonization. METHODS: Biofilm formation was determined using fluorescence microscopy imaging. Quantitative analysis was conducted using the biofilm coverage ratio (BCR) calculations. RESULTS: Our investigations...
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Neural network simulator's application to reference performance determination of turbine blading in the heat-flow diagnostics.
PublikacjaIn the paper, the possibility of application of artificial neural networks to perform the fluid flow calculations through both damaged and undamaged turbine blading was investigated. Preliminary results are presented and show the potentiality of further development of the method for the purpose of heat-flow diagnostics.
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A Perspective on Missing Aspects in Ongoing Purification Research towards Melissa officinalis
PublikacjaMelissa officinalis L. is a medicinal plant used worldwide for ethno-medical purposes. Today, it is grown everywhere; while it is known to originate from Southern Europe, it is now found around the world, from North America to New Zealand. The biological properties of this medicinal plant are mainly related to its high content of phytochemical (bioactive) compounds, such as flavonoids, polyphenolic compounds, aldehydes, glycosides...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublikacjaAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
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Modeling of Ice Phenomena in the Mouth of the Vistula River
PublikacjaThe mouth of the Vistula River, which is a river outlet located in tideless area, is analyzed. The Vistula River mouth is a man-made, artificial channel which was built in the 19th century in order to prevent the formation of ice jams in the natural river delta. Since the artificial river outlet was constructed, no severe ice-related flood risk situations have ever occurred. However, periodic ice-related phenomena still have an impact...
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A system for acoustic field measurement employing cartesian robot
PublikacjaA system setup for measurements of acoustic field, together with the results of 3D visualisations of acoustic energy flow are presented in the paper. Spatial sampling of the field is performed by a Cartesian robot. Automatization of the measurement process is achieved with the use of a specialized control system. The method is based on measuring the sound pressure (scalar) and particle velocity (vector) quantities. The aim of the...
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Statistical evaluation of the changes in cellulose properties caused by the stepwise solvent exchange and esterification
PublikacjaThe objective of the research was to empirically confirm the changes in cellulose reactivity caused by the pre-treatment with solvents of different polarity. Therefore, 5 solvents varying in their polar component of surface tension from 0 to 4.6 mN/m were chosen. Their impact on the biopolymer properties was carefully analysed concerning chemical structure, crystallinity and surface characteristics. It was revealed that the length...
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g-C3N4 for Photocatalytic Degradation of Parabens: Precursors Influence, the Radiation Source and Simultaneous Ozonation Evaluation
PublikacjaGraphitic carbon nitride (g-C3N4) is a promising catalyst for contaminants of emerging concern removal applications, especially as a visible-light-driven material. In this study, g-C3N4 catalysts were effectively synthesized through a simple thermal polymerization method, using melamine, urea, and thiourea as precursors to elucidate the influence of these compounds on the final product’s photocatalytic performance. The degradation...
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Displacements of bones during bending test of first metatarsophalangeal joint after arthrodesis with medially or dorsally positioned locking plate and lag screw.
Dane BadawczeThe Dataset contains the values of displacements of bone control points during the bending test of first metatarsophalangeal (MTP1) joint specimens after arthrodesis.
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International Conference on Artificial Neural Networks and Genetic Algorithms
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International Conference on Artificial Intelligence: Methodology, Systems, Applications
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International Work-Conference on Artificial and Natural Neural Networks
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Piotr Paradowski dr
OsobyDr Piotr Paradowski's areas of expertise in quantitative social science methods include truncated and censored models, quantile regressions, survival analysis, panel data models, discrete regressions and qualitative choice models, instrumental variable estimation, and hierarchical modeling. He is also an expert in statistical matching and statistical methods to handle missing data. In addition, he conducts research on income and...
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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublikacjaA problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...
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Simulating Power Generation from Photovoltaics in the Polish Power System Based on Ground Meteorological Measurements—First Tests Based on Transmission System Operator Data
PublikacjaThe Polish power system is undergoing a slow process of transformation from coal to one that is renewables dominated. Although coal will remain a fundamental fuel in the coming years, the recent upsurge in installed capacity of photovoltaic (PV) systems should draw significant attention. Owning to the fact that the Polish Transmission System Operator recently published the PV hourly generation time series in this article, we aim...
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PRĄDY WYRÓWNAWCZE W UZIOMACH FUNDAMENTOWYCH I SZTUCZNYCH
PublikacjaW artykule omówiono zasady wykonywania uziomów fundamentowych i sztucznych. Przedstawiono wyniki pomiarów prądów w instalacji zawierającej stal zbrojeniową w fundamencie, połączoną z układem uziomu sztucznego w ziemi wykonanym z stali ocynkowanej.
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Ontology Engineering Aspects in the Intelligent Systems Development
PublikacjaThe ontology engineering encompasses both, artificial intelligence methods and software engineering discipline. The paper tries to address a selection of aspects pertaining to development activities such as choice of the environmental framework, functionality description, specification methods and roles definition. Authors refer to the ontology development projects they were involved in.
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Make lighting healthier
PublikacjaLife on Earth evolved in day-and-night cycles. Plants and animals, including insects such as the fruit fly, have a biological clock that controls their circadian rhythms — as the 2017 winners of the Nobel Prize in Physiology or Medicine showed. Now, humans’ increasing reliance on artificial lighting is changing those rhythms.
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Deep eutectic solvents in analytical sample preconcentration Part B: Solid-phase (micro)extraction
PublikacjaOne of the key challenges of modern analytical chemistry is the monitoring of trace amounts of contaminants using sensitive and selective instrumental techniques. Due to the variety and complexity of some samples, it is often necessary to properly prepare a sample and to perform a preconcentration of trace amounts of analytes. In line with the principles of Green Analytical Chemistry (GAC), it is important for an analytical procedure...