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Search results for: ARTIFICIAL INTELLIGENCE TRAINING
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ON EGNOS MONITORING IN LOCAL CONDITIONS
PublicationAny SBAS system should deliver to the user corrections to pseudoranges as well as information about the system integrity. In theory, as soon as the system is permanently monitored by RIMS stations, it is impossible to deliver the fault information to the user. However many observations shows that accuracy of EGNOS service in the same time are different in different places, which shows the influence of local conditions on them....
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Accuracy and Availability of EGNOS - Results of Observations
PublicationAccording to SBAS concept the user should receive timely the correct information about the system integrity and corrections to the pseudoranges measurements, which leads to better accuracyof coordinates. In theory the whole system is permanently monitored by RIMS stations, so it is impossible to deliver the faulty information to the user. The quality of the system is guaranteed inside the border of the system coverage however in...
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Ionospheric scintillations computation using real-time GPS observations
PublicationThe following paper presents the results of quasi-real-time determination of the values of phase scintillations indices at the period of ionospheric disturbances that occurred as a consequence of the Sun flares observed on March 7 and 9, 2012. Double-frequency observations with 1-second measurement interval from the EPN (EUREF Permanent Network) network sites located at high latitudes were used for the analysis. To determine the phase...
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Parallel immune system for graph coloring
PublicationThis paper presents a parallel artificial immune system designed forgraph coloring. The algorithm is based on the clonal selection principle. Each processor operates on its own pool of antibodies and amigration mechanism is used to allow processors to exchange information. Experimental results show that migration improves the performance of the algorithm. The experiments were performed using a high performance cluster on a set...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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From a Point Cloud to a 3D Model - an Exercise for Users of AutoCAD and Revit
PublicationThe paper presents a proposal of the topic of an exercise for students of building faculties as part of classes on 3D modelling. The task consists in creating a three-dimensional model based on the measurement obtained with the Leica P30 laser scanner. Due to the maximum number of points in the cloud in the presented programs, the output files must be properly cleared and reduced. The point cloud was pre-processed in Cyclone software....
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Endoscopic Videos Deinterlacing and On-Screen Text and Light Flashes Removal and Its Influence on Image Analysis Algorithms' Efficiency
PublicationIn this article, deinterlacing and removing on- screen text and light flashes methods on endoscopic video images are discussed. The research is intended to improve disease recognition algorithms' performance. In the article, four configurations of deinterlacing methods and another four configurations of text and flashes removal methods are described and examined. The efficiency of endoscopic video analysis algorithms is measured...
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Previous Opinions is All You Need - Legal Information Retrieval System
PublicationWe present a system for retrieving the most relevant legal opinions to a given legal case or question. To this end, we checked several state-of-the-art neural language models. As a training and testing data, we use tens of thousands of legal cases as question-opinion pairs. Text data has been subjected to advanced pre-processing adapted to the specifics of the legal domain. We empirically chose the BERT-based HerBERT model to perform...
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The detection of Alternaria solani infection on tomatoes using ensemble learning
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Parametrization and Correlation Analysis Applied to Music Mood Classification .
PublicationThe paper presents a study on music mood categorization. First, a review of music mood models is presented. Then, the preparation of a set of music excerpts to be used in the experiments and music parametrization is described. Next, some listening tasks performed to obtain mood descriptors are introduced. Finally,the correlation between mood descriptors and features extracted from parameters is discussed. The paper concludes with...
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Model of Rules for IT Organization Evolution
PublicationThe aim of this paper is to introduce the Model of Rules for IT Organization Evolution which shall be in compliance with the Generic IT Organization Evolution Model. Due to its general nature, a set of practical adjustments is proposed in order to adapt the Generic Model to the IT Service Management domain. Further, two sets of rules describing the evolution of the IT Service Management area are defined based on two types of rules...
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Implementation of Business Processes in Smart Cities Technology
PublicationThe goal of the paper is to present the results of studies concerning the development of a method of implementation of business processes in Smart Cities systems. The method has been developed during studies carried out within the building of a Smart Cities system for Gdańsk, and is based on basic development project management mechanisms (drawing from best practices, and in particular from the RUP methodology) and business-oriented...
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Ontology of the Design Pattern Language for Smart Cities Systems
PublicationThe paper presents the definition of the design pattern language of Smart Cities in the form of an ontology. Since the implementation of a Smart City system is difficult, expensive and closely linked with the problems concerning a given city, the knowledge acquired during a single implementation is extremely valuable. The language we defined supports the management of such knowledge as it allows for the expression of a solution...
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Model of an Integration Bus of Data and Ontologies of Smart Cities Processes
PublicationThis paper presents a model of an integration bus used in the design of Smart Cities system architectures. The model of such a bus becomes necessary when designing high-level architectures, within which the silo processes of the organization should be seen from the perspective of its ontology. For such a bus to be used by any city, a generic solution was proposed which can be implemented as a whole or in part depending on the requirements...
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High-Level Model for the Design of KPIs for Smart Cities Systems
PublicationThe main goal of the paper is to build a high-level model for the design of KPIs. Currently, the development and processes of cities have been checked by KPI indicators. The authors realized that there is a limited usability of KPIs for both the users and IT specialists who are preparing them. Another observation was that the process of the implementation of Smart Cities systems is very complicated. Due to this the concept of a...
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Smart Cities System Design Method Based on Case Based Reasoning
PublicationThe objective of this paper is to present the results of research carried out to develop a design method for Smart Cities systems. The method is based on the analysis of design cases of Smart Cities systems in cities, the selection of the city appropriate to the requirements for implementation and application. The Case Based Reasoning method was used to develop the proposed design methodology, along with mechanisms of the conversion...
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Designing Aggregate KPIs as a Method of Implementing Decision-Making Processes in the Management of Smart Cities
PublicationThe aim of the paper is to present a concept of measuring the performance of city management processes by use of a concept of aggregate KPIs. In the management of organizations and, as a consequence of the use of a common design framework also in the management of cities, silo KPIs are commonly used to show the statuses of the processes of organizations/cities. Thus the question arises as to what extent aggregate KPIs, as proposed...
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A CNN based coronavirus disease prediction system for chest X-rays
PublicationCoronavirus disease (COVID-19) proliferated globally in early 2020, causing existential dread in the whole world. Radiography is crucial in the clinical staging and diagnosis of COVID-19 and offers high potential to improve healthcare plans for tackling the pandemic. However high variations in infection characteristics and low contrast between normal and infected regions pose great challenges in preparing radiological reports....
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Deep neural networks for human pose estimation from a very low resolution depth image
PublicationThe work presented in the paper is dedicated to determining and evaluating the most efficient neural network architecture applied as a multiple regression network localizing human body joints in 3D space based on a single low resolution depth image. The main challenge was to deal with a noisy and coarse representation of the human body, as observed by a depth sensor from a large distance, and to achieve high localization precision....
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Control of the cultivation of cartilages for using in the biobearings.
PublicationBiotribologiczne charakterystyki biołożysk są zależne od procesu hodowli żywej tkanki chrząstki w bioreaktorze. Z kolei proces ten, jest wielowymiarowym procesem dynamicznym sterowanym za pomocą odpowiedniego układu automatycznej regulacji. Praca przedstawia prawo i algorytm sterowania takiego procesu. W tym celu zastosowano sztuczne sieci neuronowe (Artificial Neural Networks - ANN) i zaprezentowano wyniki obliczeń.
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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublicationHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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The relationship between architectural detail and light in contemporary architecture
PublicationThe paper deals with the influence of modern artificial and natural lighting technology on contemporary architecture, especially in relation to architectural detail. Advanced complex lighting systems have an increasing importance in contemporary design solutions. Light itself, and the effect of its actions, and characteristic parts of the sophisticated lighting systems, play an essential role as independent architectural elements,...
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Implementing SP4CE Learning Rooms concept and AUTODESK online certification in the preparation of a new generation of engineers.
PublicationIn academia, educators do not always cope with rapidly changing technologies. Yet keeping up with new trends is essential to graduates’ success in a competitive job market. In the article, the author will answer the question of how Autodesk University Open Educational Resources and Certiport exams including GMetrix can enhance students’ academic progress and prepare them for future career. The concept of co-operation between Authorized...
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Electrostatic Zipping Actuators—Analysis of the Pull-In Effect Depending on the Geometry Parameters
PublicationContinuous work on a new generation of actuators, referred to as artificial muscles, resulted in the initiation of work on electrostatic zipping actuators, the concept of which is derived from micro electro-mechanical devices. Despite partial knowledge of their basic operating parameters, a question remains whether electrostatic zipping actuators are able to meet the expectations in the context of generated forces and control possibilities....
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Joanna Rymaszewska prof. dr hab. n. med.
PeopleCV Joanna Rymaszewska Wroclaw University of Science and Technology, Wroclaw, Poland +48 601 98 26 24, joanna.rymaszewska@pwr.edu.pl orcid.org/0000-0001-8985-3592 2023 → Professor of Wroclaw University of Science and Technology (WUST), Poland 2011 → 2023 Professor of Wroclaw Medical University (WMU), PL 2016 → 2022 Head of the Department of Psychiatry, Wroclaw Medical University 2016 → 2022 Head of the Clinic of Psychiatry,...
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The experience of movement in orbital space architecture: A narrative of weightlessness
PublicationBased upon a combination of architectural theories, the knowledge of space environment, and psychology of isolated and confined environments, this qualitative research aims to study orbital space settlement in a way to get the built space congenial to the human experience of movement. In this sense, sensors, self-propulsion or mechanical actuators, the inhabitant’s mental and visual capacity for movement, as well as the represented...
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The experience of movement in orbital space architecture: A narrative of weightlessness
PublicationBased upon a combination of architectural theories, the knowledge of space environment, and psychology of isolated and confined environments, this qualitative research aims to study orbital space settlement in a way to get the built space congenial to the human experience of movement. In this sense, sensors, self-propulsion or mechanical actuators, the inhabitant’s mental and visual capacity for movement, as well as the represented...
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Cost‐efficient performance‐driven modelling of multi‐band antennas by variable‐fidelity electromagnetic simulations and customized space mapping
PublicationElectromagnetic (EM) simulations have become an indispensable tool in the design of contemporary antennas. EM‐driven tasks, for example, parametric optimization, entail considerable computational efforts, which may be reduced by employing surrogate models. Yet, data‐driven modelling of antenna characteristics is largely hindered by the curse of dimensionality. This may be addressed using the recently reported domain‐confinement...
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Professional activity and women entrepreneurship in Poland – Europe 2020 Strategy perspective
PublicationThe level of economic activity of women in Poland is the lowest among Baltic Sea Region countries. The analysis of Europe 2020 targets, shows that at least 3 of the 5 main objectives relate, more or less, to women (e.g. participation in labor market). The objective concerning social inclusion assumes the increase in the employment rate of men and women (aged 20-64) in Poland up to 71%. To achieve this goal, support programs to...
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Computer experiments with a parallel clonal selection algorithm for the graph coloring problem
PublicationArtificial immune systems (AIS) are algorithms that are based on the structure and mechanisms of the vertebrate immune system. Clonal selection is a process that allows lymphocytes to launch a quick response to known pathogens and to adapt to new, previously unencountered ones. This paper presents a parallel island model algorithm based on the clonal selection principles for solving the Graph Coloring Problem. The performance of...
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Clonal selection algorithm for vehicle routing
PublicationOver the years several successful computing techniques have been inspired by biological mechanisms. Studies of the mechanisms that allow the immune systems of vertebratesto adapt and learn have resulted in a class of algorithms called artificial immune systems. Clonal selection is a process that allows lymphocytes to launch a quick response to known pathogens and to adapt to new, previously unencountered ones. This paper presents...
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Superkomputery do wspomagania procesów gospodarczych ze szczególnym uwzględnieniem sektora bankowego
PublicationW artykule omówiono wykorzystanie superkomputerów do wspomagania procesów gospodarczych ze szczególnym uwzględnieniem sektora bankowego. Odniesiono się do wybranych projektów wspierających rozwój gospodarczy w oparciu o superkomputery. W szczególności zaproponowano zastosowanie HPC do implementacji wybranych metod sztucznej inteligencji w bankowości, w tym oceny ryzyka wybranych przedsięwzięć. Zaproponowane podejście umożliwia...
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Anna Lis dr hab. inż.
PeopleAnna Lis has been the head of the Department of Management in Industry, Faculty of Economics and Management GUT since 2019. In 2005 she obtained Ph.D. degree in the field of Economic Sciences, in the discipline Management Sciences, 2019 – the degree of habilitated doctor in the field of Social Sciences, in the discipline of Management and Quality Studies. In the years 2004-2009 she was employed at the Faculty of Production Engineering...
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Gender as a Moderator of the Double Bias of Mistakes – Knowledge Culture and Knowledge Sharing Effects
PublicationThere is no learning without mistakes. The essence of the double bias of mistakes is the contradiction between an often-declared positive attitude towards learning from mistakes, and negative experiences when mistakes occur. Financial and personal consequences, shame, and blame force desperate employees to hide their mistakes. These adverse outcomes are doubled in organizations by the common belief that managers never make mistakes,...
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Tagged images with bees
Open Research DataImages taken from bee hive with tagged bees. The images are prepared for training yolo5 deep neural network (supplied with the data).
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Video of LEGO bricks on conveyor belt - flags and signs
Open Research DataThe set contains videos of LEGO bricks (flags and signs) moving on a white conveyor belt. The images were prepared for training neural network for recognition of LEGO bricks. The bricks were separated as much as possible and in most cases they should not overlap. The images were taken from different sides by stationary camera located over the final...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublicationThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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A Method for Optimising the Blade Profile in Kaplan Turbine
PublicationThis paper introduces a method of blade profile optimisation for Kaplan-type turbines, based on modelling the interaction between rotor and stator blades. Rotor and stator blade geometry is described mathematically by means of a midline curve and thickness distribution. Genetic algorithms are then used to find a global optimum that minimises the loss coefficient. This allows for variety of possible blade shapes and configurations....
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Determination of chlorine concentration using single temperature modulated semiconductor gas sensor
PublicationA periodic temperature modulation using sinusoidal heater voltage was applied to a commercial SnO2 semiconductor gas sensor. Resulting resistance response of the sensor was analyzed using a feature extraction method based on Fast Fourier Transformation (FFT). The amplitudes of the higher harmonics of the FFT from the dynamic nonlinear responses of measured gas were further utilized as an input for Artificial Neural...
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Learning and memory processes in autonomous agents using an intelligent system of decision-making
PublicationThis paper analyzes functions and structures of the memory that is an indispensable part of an Intelligent System of Decision-making (ISD), developed as a universal engine for autonomous robotics. A simplified way of processing and coding information in human cognitive processes is modelled and adopted for the use in autonomous systems. Based on such a knowledge structure, an artificial model of reality representation and a model...
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Knowledge representation of motor activity of patients with Parkinson’s disease
PublicationAn approach to the knowledge representation extraction from biomedical signals analysis concerning motor activity of Parkinson disease patients is proposed in this paper. This is done utilizing accelerometers attached to their body as well as exploiting video image of their hand movements. Experiments are carried out employing artificial neural networks and support vector machine to the recognition of characteristic motor activity...
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Comparison of modelling and measurement results of spectra emitted by a programmable lamp
PublicationNowadays artificial light with an optimized spectrum is used in many different applications. For instance, it is widely used in museums and exhibitions to illuminate the art. Moreover, such light stimulates the growth of plants, or can be applied in industry and healthcare. To achieve the best results for each application, the adjusting of a dedicated spectrum is required, which is a complicated task. The ongoing research is focused...
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Hybrid of Neural Networks and Hidden Markov Models as a modern approach to speech recognition systems
PublicationThe aim of this paper is to present a hybrid algorithm that combines the advantages ofartificial neural networks and hidden Markov models in speech recognition for control purpos-es. The scope of the paper includes review of currently used solutions, description and analysis of implementation of selected artificial neural network (NN) structures and hidden Markov mod-els (HMM). The main part of the paper consists of a description...
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Local Texture Pattern Selection for Efficient Face Recognition and Tracking
PublicationThis paper describes the research aimed at finding the optimal configuration of the face recognition algorithm based on local texture descriptors (binary and ternary patterns). Since the identification module was supposed to be a part of the face tracking system developed for interactive wearable computer, proper feature selection, allowing for real-time operation, became particularly important. Our experiments showed that it is...
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Auditory-visual attention stimulator
PublicationNew approach to lateralization irregularities formation was proposed. The emphasis is put on the relationship between visual and auditory attention stimulation. In this approach hearing is stimulated using time scale modified speech and sight is stimulated by rendering the text of the currently heard speech. Moreover, displayed text is modified using several techniques i.e. zooming, highlighting etc. In the experimental part of...
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Collaborative Data Acquisition and Learning Support
PublicationWith the constant development of neural networks, traditional algorithms relying on data structures lose their significance as more and more solutions are using AI rather than traditional algorithms. This in turn requires a lot of correctly annotated and informative data samples. In this paper, we propose a crowdsourcing based approach for data acquisition and tagging with support for Active Learning where the system acts as an...
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AITP - AI Thermal Pedestrians Dataset
PublicationEfficient pedestrian detection is a very important task in ensuring safety within road conditions, especially after sunset. One way to achieve this goal is to use thermal imaging in conjunction with deep learning methods and an annotated dataset for models training. In this work, such a dataset has been created by capturing thermal images of pedestrians in different weather and traffic conditions. All images were manually annotated...
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Evaluating Performance and Accuracy Improvements for Attention-OCR
PublicationIn this paper we evaluated a set of potential improvements to the successful Attention-OCR architecture, designed to predict multiline text from unconstrained scenes in real-world images. We investigated the impact of several optimizations on model’s accuracy, including employing dynamic RNNs (Recurrent Neural Networks), scheduled sampling, BiLSTM (Bidirectional Long Short-Term Memory) and a modified attention model. BiLSTM was...
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Discussing daylight simulations in a proposal for online daylighting education.
PublicationThere is increasing interest concerning daylighting in the building sector. However, such knowledge is difficult to penetrate the curricula of architects and designers as existing educational programmes often do not provide sufficient training on BPS. This also leads to superficial use of daylight simulations. This paper presents a proposal for a needs-based education package on daylighting design, that mixes modular eLearning...
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AffecTube — Chrome extension for YouTube video affective annotations
PublicationThe shortage of emotion-annotated video datasets suitable for training and validating machine learning models for facial expression-based emotion recognition stems primarily from the significant effort and cost required for manual annotation. In this paper, we present AffecTube as a comprehensive solution that leverages crowdsourcing to annotate videos directly on the YouTube platform, resulting in ready-to-use emotion-annotated...