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Wyniki wyszukiwania dla: ARTIFICIAL SWEETENERS
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An odor-sensing system - powerful technique for foodstuff studies
PublikacjaThis work examines gas sensor array technology combined with multivariate data processing methods and demonstrates a promising potential for rapid, non-destructive analysis of food. Main attention is focused on detailed description of sensor used in e-nose instruments, construction, and principle of operation of these systems. Moreover, this paper briefly reviews the progress in the field of artificial olfaction and future trends...
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Deep Learning Basics 2023/24
Kursy OnlineA course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.
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Idea zastosowania sztucznej inteligencji w prognozowaniu wpływu drgań komunikacyjnych na odpowiedź dynamiczną budynków mieszkalnych
PublikacjaW poniższym artykule autorzy analizują wpływ drgań komunikacyjnych na budynki mieszkalne oraz metodykę pomiarową według PN-85 B-02170 [1]. Problemem badawczym jest opracowanie prostej metody prognozowania wpływu drgań na budynki mieszkalne w taki sposób, aby nie było konieczne przeprowadzanie pracochłonnych i kosztownych pomiarów polowych. W tym celu wykonano analizę przy użyciu algorytmów opartych na sztucznej inteligencji oraz...
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International Conference on Hybrid Artificial Intelligence Systems
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Pacific Rim International Conference on Artificial Intelligence
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National Conference of the American Association for Artificial Intelligence
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Conference on Artificial Neural Networks and Expert systems
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International Conference on Artificial Intelligence and Soft Computing
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International Conference on Distributed Computing and Artificial Intelligence
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Australian Conference on Artificial Life and Computational Intelligence
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International Conference on Artificial Intelligence in Science and Technology
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International Conference on Modelling Decisions for Artificial Intelligence
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Florida Artificial Intelligence Research Society Conference
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International Conference on Artificial Intelligence and Pattern Recognition
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Cold-Active beta-Galactosidases: Sources, Biochemical Properties and Their Biotechnological Potential
Publikacjabeta-D-Galactosidases have been studied extensively in terms of their application to a variety of industrial technologies. To date, considerable research efforts have been devoted to characterization of new cold-active beta-D-galactosidases which were isolated directly from selected species of bacteria and yeasts, as well as with the use of metagenomic approaches. This chapter will provide a review of current research towards cold-active...
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Deep learning in the fog
PublikacjaIn the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...
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Intelligence Augmentation and Amplification: Approaches, Tools, and Case Studies
PublikacjaMost experts agree that truly intelligent artificial system is yet to be developed. The main issue that still remains a challenge is imposing trust and explainability into such systems. However, is full replication of human intelligence really desirable key aim in intelligence related technology and research? This is where the concept of augmented intelligence comes into play. It is an alternative conceptualization of artificial...
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Oleksandr Melnychenko dr hab.
OsobyOleksandr Melnychenko pracuje na stanowisku profesora w grupie pracowników naukowo-dydaktycznych Katedry Finansów na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej; jest tłumaczem przysięgłym języka ukraińskiego; przedsiębiorcą z wieloletnim doświadczeniem prowadzenia własnej działalności i zarządzania finansami firm; ma doświadczenie pracy w banku komercyjnym na stanowisku zajmującym się współpracą banku z systemami płatniczymi,...
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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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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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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 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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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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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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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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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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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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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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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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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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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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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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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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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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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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Arsalan Muhammad Soomar Doctoral Student
OsobyHi, I'm Arsalan Muhammad Soomar, an Electrical Engineer. I received my Master's and Bachelor's Degree in the field of Electrical Engineering from Mehran University of Engineering and Technology, Jamshoro, Sindh, Pakistan. Currently enrolled as a Doctoral student at the Gdansk University of Technology, Gdansk, Poland. Also worked in Yellowlite. INC, Ohio as a Solar Design Engineer. HEADLINE Currently Enrolled as a Doctoral...
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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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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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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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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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Unlocking creativity with new technologies
PublikacjaArtificial intelligence, augmented and virtual reality, Internet of Things and digital twins are just a few concepts related to the fourth industrial revolution that is happening right before our eyes. The key question asked by managers in the aerosol sector recently is: what does all this new technology mean to me?
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LIGHT POLLUTION IN THE CONTEXT OF THREATS TO THE WILDLIFE CORRIDORS
PublikacjaAccess to remote sensing night-time imagery allows for modeling of light pollution Increasingly, data on the propagation of artificial light are a source of interesting information for different fields of science and affect the planning of economic development. The article presents the problem of light pollution in the context of threats to the wildlife corridors in Poland. Wildlife corridors are areas that allow safe migration...
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Impact of AI-Based Tools and Urban Big Data Analytics on the Design and Planning of Cities
PublikacjaWide access to large volumes of urban big data and artificial intelligence (AI)-based tools allow performing new analyses that were previously impossible due to the lack of data or their high aggregation. This paper aims to assess the possibilities of the use of urban big data analytics based on AI-related tools to support the design and planning of cities. To this end, the author introduces a conceptual framework to assess the...