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Wyniki wyszukiwania dla: artificial intelligence.
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Neural network training with limited precision and asymmetric exponent
PublikacjaAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
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Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems
PublikacjaThe rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. The significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance...
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Condition-Based Monitoring of DC Motors Performed with Autoencoders
PublikacjaThis paper describes a condition-based monitoring system estimating DC motor degradation with the use of an autoencoder. Two methods of training the autoencoder are evaluated, namely backpropagation and extreme learning machines. The root mean square (RMS) error in the reconstruction of successive fragments of the measured DC motor angular-frequency signal, which is fed to the input of autoencoder, is used to determine the health...
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Adam Dąbrowski dr inż.
OsobyAdam Dąbrowski uzyskał stopień doktora nauk inżynieryjno-technicznych w dyscyplinie inżynieria mechaniczna na Politechnice Gdańskiej oraz ukończył studia II stopnia na kierunku mechatronika na Technische Universität Hamburg a także double degree Engineering and Management of Space Systems na Hochschule Bremen. Posiada doświadczenie przemysłowe (Instytut Lotnictwa w Warszawie, SICK AG w Hamburgu, Blue Dot Solutions w Gdańsku, Niemieckie...
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Interactive Decision Making, Inżynieria Środowiska, Environmental Engineering, 2023/2024 (summer semester)
Kursy OnlineThe course is designed for students of MSc Studies in Environmental Engineering (studies in Polish and English) Person responsible for the subject, carrying out lectures and tutorials: mgr inż. Agata.Siemaszko; agata.siemaszko@pg.edu.pl The person conducting the lectures and tutorials: dr inż. Anna Jakubczyk-Gałczyńska; anna.jakubczyk@pg.edu.pl The course is conducted using the Project-Based Learning (PBL) method. It provides...
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Łukasz Szeremeta
OsobyMoje obecne obszary badawcze to zagadnienia związane z grafami własności, cheminformatyką i Semantic Web. Interesuję się również najnowszymi zastosowaniami sztucznej inteligencji.
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Bożena Kostek prof. dr hab. inż.
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublikacjaThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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Optimal Design of Transmitarray Antennas via Low-Cost Surrogate Modelling
PublikacjaOver the recent years, reflectarrays and transmitarrays have been drawing a considerable attention due to their attractive features, including a possibility of realizing high gain and pencil-like radiation patterns without the employment of complex feeding networks. Among the two, transmitarrays seem to be superior over reflectarrays in terms of achieving high radiation efficiency without the feed blockage. Notwithstanding, the...
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Application of unmanned USV surface and AUV underwater maritime platforms for the monitoring of offshore structures at sea
PublikacjaThe operation of offshore structures at sea requires the implementation of advanced systems for their permanent monitoring. There is a set of novel technologies that could be implemented to deliver a higher level of effective and safe operation of these systems. A possible novel solution may be the application of a new maritime unmanned (USV) surface and underwater vehicles/platforms (AUV). Application of such vehicles/platforms...
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The study on the appearance of deformation defects in the yacht lamination process using an AI algorithm and expert knowledge
PublikacjaThis article describes the application of the A-priori algorithm for defining the rule-based relationships between individual defects caused during the lamination process, affecting the deformation defect of the yacht shell. The data from 542 yachts were collected and evaluated. For the proper development of the algorithm, a technological process of the yacht lamination supported by expert decisions was described. The laminating...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublikacjaCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
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ChatGPT Application vis-a-vis Open Government Data (OGD): Capabilities, Public Values, Issues and a Research Agenda
PublikacjaAs a novel Artificial Intelligence (AI) application, ChatGPT holds pertinence not only for the academic, medicine, law, computing or other sectors, but also for the public sector-case in point being the Open Government Data (OGD) initiative. However, though there has been some limited (as this topic is quite new) research concerning the capabilities ChatGPT in these sectors, there has been no research about the capabilities it...
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How Machine Learning Contributes to Solve Acoustical Problems
PublikacjaMachine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task...
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The potential interaction of environmental pollutants and circadian rhythm regulations that may cause leukemia
PublikacjaTumor suppressor genes are highly affected during the development of leukemia, including circadian clock genes. Circadian rhythms constitute an evolutionary molecular machinery involving many genes, such as BMAL1, CLOCK, CRY1, CRY2, PER1, PER2, REV-ERBa, and RORA, for tracking time and optimizing daily life during day-night cycles and seasonal changes. For circulating blood cells many of these genes coordinate their proliferation,...
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Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
PublikacjaFiber-reinforced concrete (FRC) is extensively used in diverse structural engineering applications, and its mechanical properties are crucial for designing and evaluating its performance. The compressive, flexural, splitting tensile, and shear strengths of FRCs are among the most important attributes, which have been discussed more extensively than other properties. The accurate prediction of these properties, which are required...
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Enhancing Customer Engagement in Social Media with AI – a Higher Education case study
PublikacjaPurpose. The study aims to demonstrate the importance of artificial intelligence (AI) and examples of tools based on it in the process of enhancing (building, measuring, and managing) customer engagement (CE) in social media in the higher education industry. CE is one of the current essential non-financial indicators of company performance in Digital Marketing strategy. The article presents a decision support system (DSS) based...
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Forecasting risks and challenges of digital innovations
PublikacjaForecasting and assessment of societal risks related to digital innovation systems and services is an urgent problem, because these solutions usually contain artificial intelligence algorithms which learn using data from the environment and modify their behaviour much beyond human control. Digital innovation solutions are increasingly deployed in transport, business and administrative domains, and therefore, if abused by a malicious...
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Development of cluster analysis methodology for identification of model rainfall hyetographs and its application at an urban precipitation field scale
PublikacjaDespite growing access to precipitation time series records at a high temporal scale, in hydrology, and particularly urban hydrology, engineers still design and model drainage systems using scenarios of rainfall temporal distributions predefined by means of model hyetographs. This creates the need for the availability of credible statistical methods for the development and verification of already locally applied model hyetographs....
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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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The Impact of Generative AI and ChatGPT on Creating Digital Advertising Campaigns
PublikacjaThe use of AI-based solutions is currently discussed in relation to various industries. The proliferation of tools based on generative artificial intelligence (GAI), including the emergence of ChatGPT, has resulted in testing as a first step and implementations in further areas of business life, including marketing, as a second step. Still only a few studies have analysed and evaluated specific solutions for different areas of...
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Identification of High-Value Dataset determinants: is there a silver bullet for efficient sustainability-oriented data-driven development?
PublikacjaOpen Government Data (OGD) are seen as one of the trends that has the potential to benefit the economy, improve the quality, efficiency, and transparency of public administration, and change the lives of citizens, and the society as a whole facilitating efficient sustainability-oriented data-driven services. However, the quick achievement of these benefits is closely related to the “value” of the OGD, i.e., how useful, and reusable...
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Influence of algorithmic management practices on workplace well-being – evidence from European organisations
PublikacjaPurpose Existing literature on algorithmic management practices –defined as autonomous data-driven decision making in people's management by adoption of self-learning algorithms and artificial intelligence – suggests complex relationships with employees' well-being in the workplace. While the use of algorithms can have positive impacts on people-related decisions, they may also adversely influence job autonomy, perceived justice...
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Macro-nutrients recovery from liquid waste as a sustainable resource for production of recovered mineral fertilizer: Uncovering alternative options to sustain global food security cost-effectively
PublikacjaGlobal food security, which has emerged as one of the sustainability challenges, impacts every country. As food cannot be generated without involving nutrients, research has intensified recently to recover unused nutrients from waste streams. As a finite resource, phosphorus (P) is largely wasted. This work critically reviews the technical applicability of various water technologies to recover macro-nutrients such as P, N, and...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublikacjaThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Smart Embedded Systems with Decisional DNA Knowledge Representation
PublikacjaEmbedded systems have been in use since the 1970s. For most of their history embedded systems were seen simply as small computers designed to accomplish one or a few dedicated functions; and they were usually working under limited resources i.e. limited computing power, limited memories, and limited energy sources. As such, embedded systems have not drawn much attention from researchers, especially from those in the artificial...
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Mohsan Ali Master of Science in Computer Science
OsobyMohsan Ali is a researcher at the University of the Aegean. He won the Marie-Curie Scholarship in 2021 in the field of open data ecosystem (ODECO) to pursue his PhD degree at the University of the Aegean. Currently, he is working on the technical interoperability of open data in the information systems laboratory; this position is funded by ODECO. His areas of expertise are open data, open data interoperability, data science, natural...
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Marek Czachor prof. dr hab.
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Dariusz Dąbrowski dr hab. inż.
OsobyDariusz Dąbrowski ukończył studia w Instytucie Okrętowym Politechniki Gdańskiej, a w 1987 roku podjął pracę na tej uczelni na stanowisku asystenta w Zakładzie Organizacji Przemysłu Okrętowego w ówczesnym Instytucie Organizacji i Projektowania Systemów Produkcyjnych. W 1990 roku wyjechał na stypendium TEMPUS, UE, i spędził 14 miesięcy na Uniwersytecie w Sheffield, gdzie uczestniczył w programie Master of Business Administration...
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Sathwik Prathapagiri
OsobySathwik was born in 2000. In 2022, he completed his Master’s of Science in Biological Sciences and Bachelor’s of Engineering in Chemical Engineering in an integrated dual degree program from Birla Institute Of Technology And Science, Pilani, India. During his final year, he worked as a research intern under Dr Giri P Krishnan at Bazhenov lab, University of California San Diego school of medicine to pursue his Master’s Thesis on...
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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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Tomasz Deręgowski dr inż.
OsobyTomasz Deręgowski jest adiunktem w Katedrze Informatyki w Zarządzaniu na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej, oraz kierownikiem Departamentu Inżynierii Platform Danych, pracującego nad rozwiązaniami Big Data, uczenia maszynowego i inżynierii danych w Nordea Bank AB - największej Skandynawskiej instytucji finansowej. Wcześniej pracował przez 15 lat w branży IT jako programista, lider zespołu, kierownik programu...
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AFarCloud Zagregowane rolnictwo w chmurze
ProjektyProjekt realizowany w Katedra Inżynierii Mikrofalowej i Antenowej zgodnie z porozumieniem 783221 — AFarCloud z dnia 2018-05-17
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Nina Rizun dr
OsobyNina Rizun jest adiunktem na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej. W październiku 1999 r. uzyskała stopień doktora nauk technicznych za specjalizacją Gospodarka przedsiębiorstwa i organizacja produkcji. W latach 1993–2000 pracowała na Wydziale Informatyki Ekonomicznej w Akademji Metalurgicznej, Dnipro, Ukraina. W latach 2000–2016 – na Wydziale Cybernetyki Ekonomicznej i Metod Matematycznych na Uniwersytecie Alfreda...
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Andrzej Chybicki dr inż.
OsobyZ wykształcenia informatyk, absolwent Wydziału Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej, doktor nauk technicznych w dziedzinie informatyka specjalizujący się w przetwarzaniau danych przestrzennych w rozproszonych systemach informatycznych. Ukierunkowany na wykorzystywanie osiągnięć i wiedzy zakresu prowadzonych badań w przemyśle. Współpracował z szeregiem podmiotów przemysłu informatycznego, geodezyjnego...
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Jacek Rumiński prof. dr hab. inż.
OsobyWykształcenie i kariera zawodowa 2022 2016 2002 1995 1991-1995 Tytuł profesora Habilitacja Doktor nauk technicznych Magister inżynier Prezydent RP, dziedzina nauk inżynieryjno-technicznych, dyscyplina: inzyniera biomedyczna Politechnika Gdańska, Biocybernetyka i inżyniera biomedyczna, tematyka: „Metody wyodrębniania sygnałów i parametrów z różnomodalnych sekwencji obrazów dla potrzeb diagnostyki i wspomagania...
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Milena Sobotka
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Marek Galewski dr hab. inż.
OsobyMgr inż. - 2002r. - Politechnika Gdańska; Wydział Elektroniki, Telekomunikacji i Informatyki; Automatyka i RobotykaDr inż. - 2007r. - Politechnika Gdańska; Wydział Mechaniczny; Budowa i eksploatacja maszynDr hab. inż. - 2016r. - Politechnika Gdańska; Wydział Mechaniczny; Budowa i eksploatacja maszyn Dotychczasowe i planowane obszary badań: Redukcja drgań podczas obróbki frezowaniem i toczeniem Zastosowanie zmiennej prędkości...
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Digital Interaction and Machine Intelligence. Proceedings of MIDI’2021 – 9th Machine Intelligence and Digital Interaction Conference, December 9-10, 2021, Warsaw, Poland
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Modified nanodiamond particle size studies by means of dynamic light scattering technique
PublikacjaThe Methods Utilizing the Phenomena of Light Scattering to Measure Particle Size distribution in different solvent, such as deionise water and alcohol and also to study the various structural formation when nanodiamond solution is placed on silicon surface. The purpose of this research project is divided into two parts to configure the measurement units for examining modified nanodiamond particles, examination...
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Modified nanodiamond particle size studies by means of dynamic light scattering technique
PublikacjaThe Methods Utilizing the Phenomena of Light Scattering to Measure Particle Size distribution in different solvent, such as deionise water and alcohol and also to study the various structural formation when nanodiamond solution is placed on silicon surface. The purpose of this research project is divided into two parts to configure the measurement units for examining modified nanodiamond particles, examination...
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Medical Image Dataset Annotation Service (MIDAS)
PublikacjaMIDAS (Medical Image Dataset Annotation Service) is a custom-tailored tool for creating and managing datasets either for deep learning, as well as machine learning or any form of statistical research. The aim of the project is to provide one-fit-all platform for creating medical image datasets that could easily blend in hospital's workflow. In our work, we focus on the importance of medical data anonimization, discussing the...
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Cognitum Ontorion: Knowledge Representation and Reasoning System
PublikacjaAt any point of human activity, knowledge and expertise are a key factors in understanding and solving any given problem. In present days, computer systems have the ability to support their users in an efficient and reliable way in gathering and processing knowledge. In this chapter we show how to use Cognitum Ontorion system in this areas. In first section, we identify emerging issues focused on how to represent and inference...
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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublikacjaOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
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AUTOMATIC LEARNING OF STRATEGY AND RULES IN CARD GAMES USING IMAGE FROM CAMERA
PublikacjaBelow work tries to answer a question: if it is possible to replace real human with computer system in social games. As a subject for experiments, card games were chosen, because they require a lot of player interaction (playing and taking cards), while their rules are easy to present in form of clear list of statements. Such a system, should allow real players to play without constant worrying about guiding or helping computer...
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Adjusting Game Difficulty by Recreating Behavioral Trees of Human Player Actions
PublikacjaThis paper presents a proposition of a method for adjusting game difficulty to the current level of player's skills in one-on-one games. The method is based on recognition of human player's actions and recording of those actions in the form of behavioral trees. Such trees are later used to drive behaviors of computer-controlled opponents so that human player has beat hit own strategy and improve on it, to win subsequent games....
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Possible uses of crisis situation aiding system in virtual world simulation
PublikacjaMany of the real world crisis situations like spreading fire, hostile units attack, flood, and etc. are commonly used in computer games where a simulation of extensive virtual world is crucial. This paper presents some ideas for possible uses of existing crisis situation aiding system in such environments. Moreover, it shows how this kind of system can be taught during subsequent games with a large number of players. As an example...
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Smart experience engineering to support collaborative design problems based on constraints modelling
PublikacjaEngineering design is a knowledge intensive process. Experts' experiences from different product life-cycle stages play a key role in problem solving during design decision making by linking up knowledge to find better solutions for a specific design problem. Different approaches have been used to support Collaborative and Concurrent Product Design, such as Constraint Satisfaction Problem (CSP) modelling. Additionally, due to the...
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Machine Learning and Deep Learning Methods for Fast and Accurate Assessment of Transthoracic Echocardiogram Image Quality
PublikacjaHigh-quality echocardiogram images are the cornerstone of accurate and reliable measurements of the heart. Therefore, this study aimed to develop, validate and compare machine learning and deep learning algorithms for accurate and automated assessment of transthoracic echocardiogram image quality. In total, 4090 single-frame two-dimensional transthoracic echocardiogram...