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Search results for: artificial intelligence
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Advanced Course on Artificial Intelligence
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Conference on Artificial Intelligence for Applications
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International Conference on Artificial Intelligence
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Argentine Symposium on Artificial Intelligence
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Conference in Uncertainty in Artificial Intelligence
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Portuguese Conference on Artificial Intelligence
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International Symposium on Artificial Intelligence and Mathematics
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International Conference on Artificial Intelligence and Statistics
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SGAI International Conference on Artificial Intelligence
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International Conference on Artificial Intelligence and Law
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International Conference on Artificial Intelligence in Education
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International Joint Conference on Artificial Intelligence
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Logics in Artificial Intelligence, European Conference
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International Conference on Tools with Artificial Intelligence
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International Workshop on Artificial Intelligence and Statistics
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Australian Joint Conference on Artificial Intelligence
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International Conference on Agents and Artificial Intelligence
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Australasian Joint Conference on Artificial Intelligence
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Super-resolved Thermal Imagery for High-accuracy Facial Areas Detection and Analysis
PublicationIn 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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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-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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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
PublicationPreplaced-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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Interpretation and modeling of emotions in the management of autonomous robots using a control paradigm based on a scheduling variable
PublicationThe 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
PublicationThis 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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Instance segmentation of stack composed of unknown objects
PublicationThe 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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Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach
PublicationShip 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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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublicationBiometric 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
PublicationNowadays, 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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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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International Conference on Artificial Intelligence and Soft Computing
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International Conference on Distributed Computing and Artificial 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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International Conference on Artificial Intelligence: Methodology, Systems, Applications
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Fluent Editor and Controlled Natural Language in Ontology Development
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Awareness evaluation of patients in vegetative state employing eye-gaze tracking system
PublicationApplication of eye-gaze tracking system to awareness evaluation is demonstrated. Hitherto awareness evaluation methods are presented. The assumptions of proposed method based on analysis of visual activity of patients in vegetative state are demonstrated. The eye-gaze tracking system ''Cyber-Eye'' developed at the Multimedia Systems Department employed to conducted experiments is presented. Research described in the paper indicates...
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Monitoring Regenerative Heat Exchanger in Steam Power Plant by Making Use of the Recurrent Neural Network
PublicationArtificial 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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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublicationIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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Evolutionary Algorithm for Selecting Dynamic Signatures Partitioning Approach
PublicationIn the verification of identity, the aim is to increase effectiveness and reduce involvement of verified users. A good compromise between these issues is ensured by dynamic signature verification. The dynamic signature is represented by signals describing the position of the stylus in time. They can be used to determine the velocity or acceleration signal. Values of these signals can be analyzed, interpreted, selected, and compared....
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TOWARDS EXPLAINABLE CLASSIFIERS USING THE COUNTERFACTUAL APPROACH - GLOBAL EXPLANATIONS FOR DISCOVERING BIAS IN DATA
PublicationThe paper proposes summarized attribution-based post-hoc explanations for the detection and identification of bias in data. A global explanation is proposed, and a step-by-step framework on how to detect and test bias is introduced. Since removing unwanted bias is often a complicated and tremendous task, it is automatically inserted, instead. Then, the bias is evaluated with the proposed counterfactual approach. The obtained results...
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Optimizing control by robustly feasible model predictive control and application to drinking water distribution systems
PublicationThe paper considers optimizing Model Predictive Control (MPC) for nonlinear plants with output constraints under uncertainties. Although the MPC technology can handle the constraints in the model by solving constraint model based optimization task, satisfying the plant output constraints under the model uncertainty still remains a challenge. The paper proposes Robustly Feasible MPC (RFMPC), which achieves feasibility of the outputs...
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International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems
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International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing
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Australian Conference on Artificial Life and Computational Intelligence
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International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming for Combinatorial Optimization Problems
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International FLINS Conference on Robotics and Artificial Intelligence (International Fuzzy Logic and Intelligent technologies in Nuclear Science Conference)
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Ireneusz Czarnowski Prof.
PeopleIRENEUSZ CZARNOWSKI is a graduate of the Faculty of Electrical Engineering at Gdynia Maritime University. He gained a doctoral degree in the field of computer science at Poznan University of Technology and a postdoctoral degree in the field of computer science at Wroclaw University of Science and Technology. Since 1998 is associated with Gdynia Maritime University, currently is a professor of computer science in the Department...
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Olgun Aydin dr
PeopleOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Principal Machine Learning Engineer in Nike, and works as Assistant Professor in Gdansk University of Technology in Poland. Dr. Aydin is part of editorial board of "Journal of Artificial Intelligence and Data Science" Dr. Aydin served as Vice-Chairman of Why R? Foundation and is member of Polish Artificial Intelligence Society. Olgun is...
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Intelligence Augmentation and Amplification: Approaches, Tools, and Case Studies
PublicationMost 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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Piotr Szczuko dr hab. inż.
PeoplePiotr Szczuko received his M.Sc. degree in 2002. His thesis was dedicated to examination of correlation phenomena between perception of sound and vision for surround sound and digital image. He finished Ph.D. studies in 2007 and one year later completed a dissertation "Application of Fuzzy Rules in Computer Character Animation" that received award of Prime Minister of Poland. His interests include: processing of audio and video, computer...
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Jerzy Balicki dr hab. inż.
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Kazimierz Orłowski prof. dr hab. inż.
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Computational intelligence methods in production management
PublicationThis chapter presents a survey of selected computational intelligence methods used in production management. This group of methods includes, among others, approaches based on the artificial neural networks, the evolutionary algorithms, the fuzzy logic systems and the particle swarm optimization mechanisms. From the abovementioned methods particularly noteworthy are the evolutionary and the particle swarm algorithms, which are successfully...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublicationThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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Experience-based Intelligence Augmentation with Decisional DNA: Upcoming direction
PublicationIntelligence amplification systems and technologies have gained significant interest from academia and industry during the past few decades. One of the main reasons behind this trend is the fact that most experts agree that truly intelligent artificial system is yet to be developed. The question increasing often asked is this: Is full replication of human intelligence desirable key aim in intelligence related technology and research?...
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Patryk Ziółkowski dr inż.
PeoplePatryk Ziolkowski is a graduate of the Faculty of Civil and Environmental Engineering at the Gdansk University of Technology, specializing in Building and Engineering Structures. He works as an Assistant Professor at the Department of Engineering Structures. He participated in international projects, including projects for the Ministry of Transportation of the State of Alabama (2015), he is also the winner of a grant from the Kosciuszko...
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Hybrid System for Ship-Aided Design Automation
PublicationA hybrid support system for ship design based on the methodology of CBR with some artificial intelligence tools such as expert system Exsys Developer along with fuzzy logic, relational Access database and artificial neural network with backward propagation of errors.
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Emotions Embodied in the SVC of an Autonomous Driver System
PublicationA concept of embodied intelligence (EI) is considered. None of such implementations can be fully identified with artificial intelligence. Projects that dare to approach AI and EI should be based on both the AI concepts (symbolic and sub-symbolic), in solving real problems of perception and decision-making. Therefore, the EI, in this paper, is understood as a methodology that uses all available resources and algorithms from the...
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Computational Intelligence - 2023
e-Learning CoursesWidening the students knowledge about the selected methods of artificial intelligence
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Computational Intelligence 2022
e-Learning CoursesWidening the students knowledge about the selected methods of artificial intelligence
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Computational Intelligence - sem. 2022/23
e-Learning CoursesWidening the students knowledge about the selected methods of artificial intelligence
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Computational Intelligence - 2023/2024 sem.
e-Learning CoursesWidening the students knowledge about the selected methods of artificial intelligence
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Computational Intelligence - sem. 2023/2024
e-Learning CoursesWidening the students knowledge about the selected methods of artificial intelligence
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Deep learning in the fog
PublicationIn 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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Impact of AI-Based Tools and Urban Big Data Analytics on the Design and Planning of Cities
PublicationWide 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...
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublicationThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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Jan Cudzik dr inż. arch.
PeopleJan Cudzik (Ph.D. Eng. Arch.) is an assistant professor at the Department of Urban Architecture and Waterside Spaces at the Faculty of Architecture of the Gdańsk University of Technology and the head of the Laboratory of Digital Technologies and Materials of the Future. He is researching kinematic architecture, digital techniques in architectural design, digital fabrication, and forms of artificial intelligence in architecture...
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From Individual to Collective: Intelligence Amplification with Bio-Inspired Decisional DNA and its Extensions
PublicationIn nature, deoxyribonucleic acid (DNA) contains the genetic instructions used in the development and functioning of all known living organisms. The idea behind our vision is to develop an artificial system, an architecture that would support discovering, adding, storing, improving and sharing information and knowledge among agents and organizations through experience. We propose a novel Knowledge Representation (KR) approach in...
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Andrzej Stateczny prof. dr hab. inż.
PeopleProf. Dr. Andrzej Stateczny is a Professor of Gdansk Technical University Poland and President of Marine Technology Ltd. His research interests are mainly centered on navigation, hydrography and geoinformatics. Current RF research activities include radar navigation, comparative navigation, hydrography, artificial intelligence methods focused on image processing and multisensory data fusion. He has been the Principal Investigator...
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Wykorzystanie sztucznych sieci neuronowych do szacowania wpływu drgań na budynki jednorodzinne
PublicationW artykule przedstawiono metodę prognozowania wpływu drgań na budynki mieszkalne z wykorzystaniem sztucznych sieci neuronowych. Drgania komunikacyjne mogą doprowadzić do uszkodzenia elementów konstrukcyjnych, a nawet do awarii budynku. Najczęstszym efektem są jednak rysy, pękanie tynku i wypraw. Metody oparte na sztucznej inteligencji są przybliżone, ale stanowią wystarczająco dokładną i ekonomiczną alternatywę dla tradycyjnych...
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Ontology Engineering Aspects in the Intelligent Systems Development
PublicationThe 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
PublicationArtificial 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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Idea zastosowania sztucznej inteligencji w prognozowaniu wpływu drgań komunikacyjnych na odpowiedź dynamiczną budynków mieszkalnych
PublicationW 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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Big Data Paradigm Developed in Volunteer Grid System with Genetic Programming Scheduler
PublicationArtificial intelligence techniques are capable to handle a large amount of information collected over the web. In this paper, big data paradigm has been studied in volunteer and grid system called Comcute that is optimized by a genetic programming scheduler. This scheduler can optimize load balancing and resource cost. Genetic programming optimizer has been applied for finding the Pareto solu-tions. Finally, some results from numerical...
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Tacjana Niksa-Rynkiewicz dr inż.
PeopleTacjana Niksa-Rynkiewicz - doctor of science in the field of computer science (2011). The doctoral dissertation concerned issues related to the development of Artificial Intelligence methods, and more precisely the generalization of triangular norms in fuzzy neural systems. Currently, he is a researcher (assistant professor) at the Gdańsk University of Technology. He develops his skills and conducts research in the use of methods...
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Optymalizacja treningu i wnioskowania sieci neuronowych
PublicationSieci 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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Remote Sensing in Vessel Detection and Navigation
PublicationThe Special Issue (SI) “Remote Sensing in Vessel Detection and Navigation” highlighted a variety of topics related to remote sensing with navigational sensors. The sequence of articles included in this Special Issue is in line with the latest scientific trends. The latest developments in science, including artificial intelligence, were used. The 15 papers (from 23 submitted) were published.
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Diagnostic Accuracy of Liquid Biopsy in Endometrial Cancer
PublicationBackground: Liquid biopsy is a minimally invasive collection of a patient body fluid sample. In oncology, they offer several advantages compared to traditional tissue biopsies. However, the potential of this method in endometrial cancer (EC) remains poorly explored. We studied the utility of tumor educated platelets (TEPs) and circulating tumor DNA (ctDNA) for preoperative EC diagnosis, including histology determination. Methods:...
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The application of neural networks in forecasting the influence of traffic-induced vibrations on residential buildings
PublicationTraffic-induced vibrations may cause the cracking of plaster, damage to structural elements and, in extreme cases, may even lead to the structural collapse of residential buildings. The aim of this article is to analyse the effectiveness of a method of forecasting the impact of vibrations on residential buildings using the concept of artificial intelligence. The article presents several alternative forecasting systems for which...
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Sztuczna inteligencja w onkologii - nowe narzędzia do diagnostyki i medycyny spersonalizowanej
Publicationstatnie dekady doprowadziły do rozwoju zaawansowanych technologii badawczych, cechujących się wysoką przepustowością. Zmienia to oblicze medycyny, doprowadzając do generowania ogromnej ilości danych. Z każdym kolejnym rokiem przybywa pacjentów onkologicznych, a zebrane informacje o pacjentach przekraczają możliwości lekarzy i naukowców w zakresie samodzielnej analizy tzw. big data. Właśnie dlatego świat nauki coraz częściej zwraca...
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Radar and Sonar Imaging and Processing
PublicationThe 21 papers (from 61 submitted) published in the Special Issue “Radar and Sonar Imaging Processing” highlighted a variety of topics related to remote sensing with radar and sonar sensors. The sequence of articles included in the SI dealt with a broad profile of aspects of the use of radar and sonar images in line with the latest scientific trends. The latest developments in science, including artificial intelligence, were used.
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Sensors and System for Vehicle Navigation
PublicationIn recent years, vehicle navigation, in particular autonomous navigation, has been at the center of several major developments, both in civilian and defense applications. New technologies, such as multisensory data fusion, big data processing, or deep learning, are changing the quality of areas of applications, improving the sensors and systems used. Recently, the influence of artificial intelligence on sensor data processing and...
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Chemiresistive gas sensors based on carbon nanotubes - fabrication and application
PublicationMany types of sensors have been invented to identify and quantify chemical contamination in the gas phase. Sensors based on carbon nanotubes are particularly attractive because of their wide range of applicaions and potential use in electronic nose that can be controlled using algorithms of Artificial Intelligence. Sensor functions, fabrication and selected applications are reviewed and discussed with focus on chemiresistors. Drawbacks...
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Waldemar Korłub dr inż.
PeopleWaldemar Korłub obtained an Eng. degree in 2011, MSc.Eng. degree in 2012 and PhD in Computer Science in 2017 granted by the Faculty of Electronics, Telecommunications and Informatics at Gdansk University of Technology. His research interests include: distributed systems mainly grid and cloud computing platforms, autonomous systems capable of self-optimization, self-management, self-healing and self-protection, artificial intelligence...
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Metody sztucznej inteligencji do wspomagania bankowych systemów informatycznych
PublicationW pracy opisano zastosowania nowoczesnych metod sztucznej inteligencji do wspomagania bankowych systemów informatycznych. Wykorzystanie w systemach informatycznych algorytmów ewolucyjnych, harmonicznych, czy sztucznych sieci neuronowych w połączeniu z nowoczesną technologią mikroprocesorową umożliwiają zasadniczy wzrost konkurencyjności banku. Dlatego w pracy omówiono wybrane zastosowania bankowe ze szczególnym uwzględnieniem zbliżeniowych...
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Marine and Cosmic Inspirations for AI Algorithms
PublicationArtificial Intelligence (AI) is a scientific area that currently sees an enormous growth. Various new algorithms and methods are developed and many of them meets practical, successful applications. Authors of new algorithms draw different inspirations. Probably the most common one is the nature. For example, Artificial Neural Networks were inspired by the structure of human brain and nervous system while the classic Genetic Algorithm...
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THE ROLE OF INFERENCE IN MOBILE MEDICAL APPLICATION DESIGN
PublicationIn the early 21st century, artificial intelligence began to be used to process medical information. However, before this happened, predictive models used in healthcare could only consider a limited number of variables, and only in properly structured and organised medical data. Today, advanced tools based on machine learning techniques - which, using artificial neural networks, can explore extremely complex relationships - and...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublicationDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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Radar and Sonar Imaging and Processing (2nd Edition)
PublicationThe 14 papers (from 29 submitted) published in the Special Issue “Radar and Sonar Imaging Processing (2nd Edition)” highlight a variety of topics related to remote sensing with radar and sonar sensors. The sequence of articles included in the SI deal with a broad profile of aspects of the use of radar and sonar images in line with the latest scientific trends, in which the latest developments in science, including artificial intelligence,...
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Application of Intuitionistic Fuzzy Sets to the assessment of technical university students
PublicationThe article proposes application of artificial intelligence methods to assess students of technical universities. The level of achieved educational goals can be assessed using measurements based on the idea of Fuzzy Intuitionistic Sets (IFS). A classification algorithm was developed and an exemplary distribution of the criteria values using IFS was presented. The application of the proposed approach in online education can enrich...
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Michał Czubenko dr inż.
PeopleMichał Czubenko is a distinguished 2009 graduate of the Faculty of Electronics, Telecommunications, and Informatics at Gdańsk University of Technology, specializing in the discipline of automatic control and robotics. Currently, he serves as an adjunct in the Department of Robotics and Decision Systems at the same institution. In 2012, he embarked on a three-month internship at Kingston University London, broadening his horizons...
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Society 4.0: Issues, Challenges, Approaches, and Enabling Technologies
PublicationThis guest edition of Cybernetics and Systems is a broadening continuation of our last year edition titled “Intelligence Augmentation and Amplification: Approaches, Tools, and Case Studies”. This time we cover research perspective extending towards what is known as Society 4.0. Bob de Vit brought the concept of Society 4.0 to life in his book “Society 4.0 – resolving eight key issues to build a citizens society”. From the Systems...
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Representing and Managing Experiential Knowledge with Decisional DNA and its Drimos® Extension
PublicationThe Semantic Web concept is proposing a future concept of the WorldWideWeb (WWW) where both humans and man-made systems are able to interconnect and exchange knowledge. One of the challenges of Semantic Web is smart and trusted accommodation of knowledge in artificial systems so it can be unified, enhanced, reused, shared, communicated and distributed with added aptitude. Our research represents an important component of addressing...
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Towards detecting programmers’ stress on the basis of keystroke dynamics
PublicationThe article describes the idea of detecting stress among programmers on the basis of keystroke dynamics. An experiment with a group of students of artificial intelligence classes was performed. Two samples of keystroke data were recorded for each case, the first while programming without stress, the second under time pressure. A number of timing and frequency parameters were calculated for each sample. Then statistical analysis...
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Signature Partitioning Using Selected Population-Based Algorithms
PublicationDynamic signature is a biometric attribute which is commonly used for identity verification. Artificial intelligence methods, especially population-based algorithms (PBAs), can be very useful in the dynamic signature verification process. They are able to, among others, support selection of the most characteristic descriptors of the signature or perform signature partitioning. In this paper, we focus on creating the most characteristic...