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Wyniki wyszukiwania dla: LEARNING-BY-DOING METHOD
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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublikacjaLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
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Application of Wavelet Transform and Fractal Analysis for Esophageal pH-Metry to Determine a New Method to Diagnose Gastroesophageal Reflux Disease
PublikacjaIn this paper, a new method for analysing gastroesophageal reflux disease (GERD) is shown. This novel method uses wavelet transform (WT) and wavelet-based fractal analysis (WBFA) on esophageal pH-metry measurements. The esophageal pH-metry is an important diagnostic tool supporting the physician’s work in diagnosing some forms of reflux diseases. Interpreting the results of 24-h pH-metry monitoring is time-consuming, and the conclusions...
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Developing students' spatial skills and teaching the history of architecture through structural drawing
PublikacjaThe method of “structural drawing" is used in teaching history of architecture in the Architectural Faculty of Gdańsk University of Technology. It is addressed to students of the first semester of study – so to the architectural beginners. There are three main goals of the structural drawing method used in that educational course: (1) developing the students’ spatial skills; (2) training architectural drawing ability; (3) teaching...
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Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublikacjaMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
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An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublikacjaSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
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Halucynacje chatbotów a prawda: główne nurty debaty i ich interpretacje
PublikacjaGeneratywne systemy sztucznej inteligencji (SI) są w stanie tworzyć treści medialne poprzez zastosowanie uczenia maszynowego do dużych ilości danych szkoleniowych. Te nowe dane mogą obejmować tekst (np. Bard firmy Google, LLaMa firmy Meta lub ChatGPT firmy OpenAI) oraz elementy wizualne (np. Stable Diffusion lub DALL-E OpenAI) i dźwięk (np. VALL-E firmy Micro- soft). Stopień zaawansowania tych treści może czynić je nieodróżnialnymi...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublikacjaPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublikacjaAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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Adaptacyjny system sterowania ruchem drogowym
PublikacjaAdaptacyjny system sterowania ruchem drogowym to rodzaj systemu sterowania, który dynamicznie, w czasie rzeczywistym, dostosowuje swoje parametry w oparciu o bieżące warunki ruchu drogowego. Celem niniejszej rozprawy jest sprawdzenie wpływu wybranych cech systemu, zbudowanego w oparciu o zaprojektowane i zbudowane z udziałem autora inteligentne znaki drogowe, na wybrane parametry mające wpływ na bezpieczeństwo i płynność ruchu....
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Finite Element Method
Kursy OnlineItem Name : Finite Element Method- Abaqus learning Field of study : Civil Engineering Faculty : Faculty of Civil and Environmental Engineering Education level : Second degree studies Form of studies : Full-time studies Year of studies : 1 Study semester : 2 Start of the semester : November 2021 Academic year of the course : 2021/2022 Form of classes : Lecture, Laboratory
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ZEUS Concept and Its Wider European Application
PublikacjaThe objectives of the ZEUS project and the resulting concept of an integrated system of transport safety are recapitulated in the article. The context for transport safety management that has evolved since this became a concern of the European Union under the Treaty of Union in 1993 is outlined, and some issues related to applying the ZEUS concept across Europe are discussed. It is concluded that there is scope for exploring ways...
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Comparison of Compact Reduced Basis Method with Different Model Order Reduction Techniques
PublikacjaDifferent strategies suitable to compare the performance of different model order reduction techniques for fast frequency sweep in finite element analysis in Electromagnetics are proposed and studied in this work. A Frobenius norm error measure is used to describe how good job a reduced-order model is doing with respect to the true system response. In addition, the transfer function correct behavior is monitored by studying the...
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A MODEL FOR FORECASTING PM10 LEVELS WITH THE USE OF ARTIFICIAL NEURAL NETWORKS
PublikacjaThis work presents a method of forecasting the level of PM10 with the use of artificial neural networks. Current level of particulate matter and meteorological data was taken into account in the construction of the model (checked the correlation of each variable and the future level of PM10), and unidirectional networks were used to implement it due to their ease of learning. Then, the configuration of the network (built on the...
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Improvement of electrochemical action of zinc-rich paints by addition of nanoparticulate zinc
PublikacjaThe influence of nanosized particles on electrochemical action of standard zinc-rich paints by means of SEM as well as potential and impedance measurements has been investigated. The motivation for doing this was to obtain additional electrical connection between the spherical microparticles themselves and zinc particles and steel substrate. Overall zinc content was at the level of 92% by weight. Samples with different concentration...
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Smart Innovation Management in Product Life Cycle
PublikacjaThe present paper proposes a framework for smart innovation management of the product using a Smart Knowledge Management System comprising Set of Experience Knowledge Structure (SOEKS) and Decisional DNA. This proposed system will allow the entrepreneurs and organizations to perform the innovation process technically and quickly as this framework will store knowledge as well as experiences of the past innovations done in various...
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Karol Flisikowski dr inż.
OsobyKarol Flisikowski jest profesorem uczelni w Katedrze Statystyki i Ekonometrii, Wydziału Zarządzania i Ekonomii Politechniki Gdańskiej. Jest odpowiedzialny jest za prowadzenie zajęć ze statystyki opisowej i matematycznej (w języku polskim i angielskim), a także badań naukowych w zakresie statystyki społecznej. Był uczestnikiem wielu konferencji o zasięgu krajowym, jak i międzynarodowym, gdzie prezentował wyniki prowadzonych przez...
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Numerical modeling of quantum dynamical processes
PublikacjaIn this dissertation I present a high-precision (15, 18 or 33 decimal places) C++ implementation of quantum dynamics time propagation algorithms for both time-independent and time-dependent Hamiltonian with an inhomogeneous source term. Moreover I present an extension of both algorithms for time propagation to handle arbitrary number of coupled electronic levels. I have performed a careful validation of these implementations comparing...
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Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate-blood pressure coupling quantified by entropy-based indices
PublikacjaWe introduce an entropy-based classification method for pairs of sequences (ECPS) for quantifying mutual dependencies in heart rate and beat-to-beat blood pressure recordings. The purpose of the method is to build a classifier for data in which each item consists of two intertwined data series taken for each subject. The method is based on ordinal patterns and uses entropy-like indices. Machine learning is used to select a subset...
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Improving Effectiveness of SVM Classifier for Large Scale Data
PublikacjaThe paper presents our approach to SVM implementation in parallel environment. We describe how classification learning and prediction phases were pararellised. We also propose a method for limiting the number of necessary computations during classifier construction. Our method, named one-vs-near, is an extension of typical one-vs-all approach that is used for binary classifiers to work with multiclass problems. We perform experiments...
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Wyróżniki modelu biznesu przedsiębiorstwa inteligentnego
PublikacjaBurzliwa zmiana środowiska biznesowego wpływa na ludzi tak, że generują oczekiwania na wyroby i usługi zaspokajające ich dotychczasowe i nowe potrzeby w coraz większym stopniu. W ten sposób przed menedżerami powstają wciąż nowe, bardziej skomplikowane i wysublimowane wymagania. W takich uwarunkowaniach prowadzenia biznesu sukces osiąga to przedsiębiorstwo, które jest inteligentne. W takiej perspektywie celem badań było wyłonienie...
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Do mistakes acceptance foster innovation? Polish and US cross-country study of tacit knowledge sharing in IT
PublikacjaAbstract Purpose – This study aims to understand and compare how the mechanism of innovative processes in the information technology (IT) industry – the most innovative industry worldwide – is shaped in Poland and the USA in terms of tacit knowledge awareness and sharing driven by a culture of knowledge and learning, composed of a learning climate and mistake acceptance. Design/methodology/approach – Study samples were drawn from...
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Designing Intelligent Factory: Conceptual Framework and Empirical Validation
PublikacjaThis paper presents a framework for monitoring, analysing and decision making for a smart manufacturing environment. We maintain that this approach could play a vital role in developing an architecture and implementation of Industry 4.0. The proposed model has features like experience based knowledge representation and semantic analysis of engineering objects and manufacturing process. It is also capable of continuous real time...
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Kernel PCA in Application to Leakage Detection in Drinking Water Distribution System
PublikacjaMonitoring plays an important role in advanced control of complex dynamic systems. Precise information about system's behaviour, including faults detection, enables efficient control. Proposed method- Kernel Principal Component Analysis (KPCA), a representative of machine learning, skilfully takes full advantage of the well known PCA method and extends its application to nonlinear case. The paper explains the general idea of KPCA...
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GROUPS OF GERMAN DOMESTIC APPLIANCE MANUFACTURERS ACCORDING TO NEW PRODUCT DEVELOPMENT PRACTICES
PublikacjaFinding the best way to develop new products has been always a hot topic for practitioners and academics. However, so far only a few of these kinds of studies have concentrated on a single industry. In this paper, we group German domestic appliance manufacturers with regards to their new product development (NPD) practices to discover their attitude to NPD effort. By conducting a survey we found that three different groups of manufacturers...
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublikacjaThe 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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Rethinking non-governmental organizations – at the crossroad of economics and civil society
PublikacjaThe article aims to close the existing knowledge gaps, show why non‑governmental organizations are founded and maintained, and elaborate and systematize the existing knowledge through an analysis of the existing subdisciplines within economics, laying the groundwork for the economics of non‑governmental organizations. The article was written based on a structured literature review with an approach similar to the grounded theory...
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Creating a radiological database for automatic liver segmentation using artificial intelligence.
PublikacjaImaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.
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Visual and auditory attention stimulator for assisting pedagogical therapy . Stymulator uwagi wzrokowej i słuchowej do wspomagania terapii pedagogicznej
PublikacjaVisual and auditory attention stimulator provides a system developed in order to improve reading skills using simultaneous presentation of text in its visual form and in transformed auditory form accompanied by related movie material. The described research employed 40 children at the age of 8 13 years having difficulties in learning of reading, who were diagnosed as having developmental dyslexia. It was shown that application...
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Visual and Auditory Attention Stimulator for Assisting Pedagogical Therapy
PublikacjaVisual and auditory attention stimulator provides a system developed in order to improve reading skills using simultaneous presentation of text in its visual form and in transformed auditory form accompanied by related movie material. The described research employed 40 children at the age of 8 13 years having difficulties in learning of reading, who were diagnosed as having developmental dyslexia. It was shown that application...
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New methodology for calculating cost-efficiency of different ways of voting: is internet voting cheaper?
PublikacjaNew ways of voting in elections are being sought by electoral administrations worldwide who want to reverse declining voter turnouts without increasing electoral budgets. This paper presents a novel approach to cost accounting for multi-channel elections based on local elections in Estonia. By doing so, it addresses an important gap in the academic literature in this field. The authors confirm that internet voting was most cost-efficient...
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Quantitative Storytelling in the Making of a Composite Indicator
PublikacjaThe reasons for and against composite indicators are briefly reviewed, as well as the available theories for their construction. After noting the strong normative dimension of these measures—which ultimately aim to ‘tell a story’, e.g. to promote the social discovery of a particular phenomenon, we inquire whether a less partisan use of a composite indicator can be proposed by allowing more latitude in the framing of its construction....
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JamesBot - an intelligent agent playing StarCraft II
PublikacjaThe most popular method for optimizing a certain strategy based on a reward is Reinforcement Learning (RL). Lately, a big challenge for this technique are computer games such as StarCraft II which is a real-time strategy game, created by Blizzard. The main idea of this game is to fight between agents and control objects on the battlefield in order to defeat the enemy. This work concerns creating an autonomous bot using reinforced...
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Tacit knowledge influence on intellectual capital and innovativeness in the healthcare sector: A cross-country study of Poland and the US
PublikacjaThis study provides empirical proof that whole organizational innovativeness is rooted in tacit knowledge due to its potency of human capital creation and, that a learning culture composed of a learning climate and mistakes acceptance component fosters human capital development. The main practical implication is that if the IC components are externally rather than internally determined in the particular organization embedded in...
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Kriging-assisted hybrid reliability design and optimization of offshore wind turbine support structure based on a portfolio allocation strategy
PublikacjaIn recent years, offshore wind power generation technology has developed rapidly around the world, making important contributions to the further development of renewable energy. When designing an Offshore Wind Turbine (OWT) system, the uncertainties in parameters and different types of constraints need to be considered to find the optimal design of these systems. Therefore, the Reliability-Based Design Optimization (RBDO) method...
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Weighted Clustering for Bees Detection on Video Images
PublikacjaThis work describes a bee detection system to monitor bee colony conditions. The detection process on video images has been divided into 3 stages: determining the regions of interest (ROI) for a given frame, scanning the frame in ROI areas using the DNN-CNN classifier, in order to obtain a confidence of bee occurrence in each window in any position and any scale, and form one detection window from a cloud of windows provided by...
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A new multi-process collaborative architecture for time series classification
PublikacjaTime series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...
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Emotion recognition and its application in software engineering
PublikacjaIn this paper a novel application of multimodal emotion recognition algorithms in software engineering is described. Several application scenarios are proposed concerning program usability testing and software process improvement. Also a set of emotional states relevant in that application area is identified. The multimodal emotion recognition method that integrates video and depth channels, physiological signals and input devices...
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Towards more inclusive qualitative research: the practice of interviewing neurominorities
PublikacjaManagement scholars increasingly focus their efforts on the development of neurodivergent human capital and the promotion of inclusive employment and decent work. However, it may be argued that existing research still suffers from the lack of a comprehensive appreciation of what neurominorities may find difficult in the research process or how they interpret what the researchers are doing. In the light of only fragmented advice...
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The KLC Cultures' Synergy Power, Trust, and Tacit Knowledge for Organizational Intelligence
PublikacjaThis paper examines the impact of knowledge, learning, and collaboration culturessynergy (the KLC approach) on organizational adaptability. The SEM analysis method was applied to verify the critical assumption of this paper: that the KLC approach and trust support knowledge-sharing processes (tacit and explicit) and are critical for organizational intelligence activation.Specifically, the empirical evidence, based on a 640-case...
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Narratives on cutting down trees on private land. A comparison of urban and rural municipalities in Poland using the Q-deliberation method
PublikacjaIncreased development in rural and urban areas leads to a decrease in tree cover and reduces the ecosystem services that trees provide. Municipal authorities must consider managing trees on private land to ensure that residents have access to trees and green spaces. In doing so, they must frequently confront conflicting stakeholder views, which are driven by diverse public and private interests and impacted by the type of landscape...
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Optimising approach to designing kernel PCA model for diagnosis purposes with and without a priori known data reflecting faulty states
PublikacjaFault detection plays an important role in advanced control of complex dynamic systems since precise information about system condition enables efficient control. Data driven methods of fault detection give the chance to monitor the plant state purely based on gathered measurements. However, they especially nonlinear, still suffer from a lack of efficient and effective learning methods. In this paper we propose the two stages learning...
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Two Stage SVM and kNN Text Documents Classifier
PublikacjaThe paper presents an approach to the large scale text documents classification problem in parallel environments. A two stage classifier is proposed, based on a combination of k-nearest neighbors and support vector machines classification methods. The details of the classifier and the parallelisation of classification, learning and prediction phases are described. The classifier makes use of our method named one-vs-near. It is...
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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublikacjaThis paper contains research results of the diagnostics of induction motor bearings based on measurement of the supply current with usage of artificial neural networks. Bearing failure amount is greater than 40% of all engine failures, which makes their damage-free operation crucial. Tests were performed on motors with intentionally made bearings defects. Chapter 2 introduces the concept of artificial neural networks. It presents...
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Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA
PublikacjaIn this paper, we propose a novel intrusion detection approach using past driving experience and the neural knowledge DNA for in-vehicle information system security. The neural knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for classifying malicious vehicle control commands...
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Pupil detection supported by Haar feature based cascade classifier for two-photon vision examinations
PublikacjaThe aim of this paper is to present a novel method, called Adaptive Edge Detection (AED), of extraction of precise pupil edge coordinates from eye image characterized by reflections of external illuminators and laser beams. The method is used for monitoring of pupil size and position during psychophysical tests of two-photon vision performed by dedicated optical set-up. Two-photon vision is a new phenomenon of perception of short-pulsed...
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The KLC Cultures, Tacit Knowledge, and Trust Contribution to Organizational Intelligence Activation
PublikacjaIn this paper, the authors address a new approach to three organizational, functional cultures: knowledge culture, learning culture, and collaboration culture, named together the KLC cultures. Authors claim that the KLC approach in knowledge-driven organizations must be designed and nourished to leverage knowledge and intellectual capital. It is suggested that they are necessary for simultaneous implementation because no one of...
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Rozwijanie kreatywności ucznia w procesie kształtowania umiejętności językowych. Innowacja pedagogiczna z elementami neurodydaktyki w edukacji wczesnoszkolnej
PublikacjaThis text is a ready-to-use pedagogical innovation program combining teaching English and classes developing creativity in early childhood education. Classes developing creativity are a unique opportunity to implement innovative solutions and ideas to develop language competencies and key competencies, which can be difficult during a standard English lesson. The...
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Active Control of Highly Autocorrelated Machinery Noise in Multivariate Nonminimum Phase Systems
PublikacjaIn this paper, a novel multivariate active noise control scheme, designed to attenuate disturbances with high autocorrelation characteristics and preserve background signals, is proposed. The algorithm belongs to the class of feedback controllers and, unlike the popular feedforward FX-LMS approach, does not require availability of a reference signal. The proposed approach draws its inspiration from the iterative learning control...
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Virtual reality tools in teaching the conservation and history of Polish architecture
PublikacjaVirtual reality and its impact on teaching conservation and architectural history is the subject of this article. During the COVID-19 crisis in 2020, the education of students of architecture was transferred by Gdańsk University of Technology (GUT), Gdańsk, Poland, to distance learning. This method has provided academics an opportunity to examine the impact of virtual reality and remote education on architectural history and conservation....
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Analyzing Preconditions to Introduce Internet Voting in Portugal: Insights from the Estonian Model
PublikacjaInternet voting has been trialed or introduced for several countries, including Norway, Portugal, United States, United Kingdom and Switzerland as an additional voting channel to increase voter turnout and, also to modernize the electoral process. However, only Estonia has successful introduced internet voting, deploying e-enabled elections in general governmental levels. This paper aims to provide an exploratory study on the Estonian...