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Wyniki wyszukiwania dla: ARTIFICIAL INTELLIGENCE
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Emotion Recognition Based on Facial Expressions of Gamers
PublikacjaThis article presents an approach to emotion recognition based on facial expressions of gamers. With application of certain methods crucial features of an analysed face like eyebrows' shape, eyes and mouth width, height were extracted. Afterwards a group of artificial intelligence methods was applied to classify a given feature set as one of the following emotions: happiness, sadness, anger and fear.The approach presented in this...
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Signature Partitioning Using Selected Population-Based Algorithms
PublikacjaDynamic 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...
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Przegląd metod szybkiego prototypowania algorytmów uczenia maszynowego w FPGA
PublikacjaW artykule opisano możliwe do wykorzystania otwarte narzędzia wspomagające szybkie prototypowanie algorytmów uczenia maszynowego (ML) i sztucznej inteligencji (AI) przy użyciu współczesnych platform FPGA. Przedstawiono przykład szybkiej ścieżki przy realizacji toru wideo wraz z implementacją przykładowego algorytmu prze-twarzania w trybie na żywo.
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Controlled grafting of vinylic monomers on polyolefins: a robust mathematical modeling approach
PublikacjaExperimental and mathematical modeling analyses were used for controlling melt free-radical grafting of vinylic monomers on polyolefins and, thereby, reducing the disturbance of undesired cross-linking of polyolefins. Response surface, desirability function, and artificial intelligence methodologies were blended to modeling/optimization of grafting reaction in terms of vinylic monomer content, peroxide initiator concentration,...
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Multi-criteria Differential Evolution for Optimization of Virtual Machine Resources in Smart City Cloud
PublikacjaIn a smart city, artificial intelligence tools support citizens and urban services. From the user point of view, smart applications should bring computing to the edge of the cloud, closer to citizens with short latency. However, from the cloud designer point of view, the trade-off between cost, energy and time criteria requires the Pareto solutions. Therefore, the proposed multi-criteria differential evolution can optimize virtual...
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A survey of neural networks usage for intrusion detection systems
PublikacjaIn recent years, advancements in the field of the artificial intelligence (AI) gained a huge momentum due to the worldwide appliance of this technology by the industry. One of the crucial areas of AI are neural networks (NN), which enable commer‐ cial utilization of functionalities previously not accessible by usage of computers. Intrusion detection system (IDS) presents one of the domains in which neural networks are widely tested...
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AI-powered Digital Transformation: Tools, Benefits and Challenges for Marketers – Case Study of LPP
PublikacjaThe article aims to show the role (benefits and challenges) of AI-powered digital marketing tools for marketers in the age of digital transformation. The considerations were related to the Polish market and a case study of LPP, a Polish clothing retailer. The starting point for this study was the analysis of the literature on the concept of artificial intelligence (AI) with reference to digital marketing. In the next steps, the...
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Love your mistakes!—they help you adapt to change. How do knowledge, collaboration and learning cultures foster organizational intelligence?
PublikacjaPurpose: The study aims to determine how the acceptance of mistakes is related to adaptability to change in a broad organizational context. Therefore it explores how knowledge, collaboration, and learning culture (including “acceptance of mistakes”) might help organizations overcome their resistance to change. Methodology: The study uses two sample groups: students aged 18–24 (330 cases) and employees aged >24 (326 cases) who work...
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I, Robot: between angel and evil
PublikacjaThe boosting of most digital innovations within recent technology progress by artificial intelligence (AI) constitutes a growing topic of interest. Besides its technical aspects, increasing research activity may be observed in the domain of security challenges, and therefore of responsibility related to the controlled or hypothetically uncontrolled or autonomous emergence of AI solutions. Consequently, responsibility and ethics...
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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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AI in the creation of the satellite maps
PublikacjaSatellite and aerial imagery acquisition is a very useful source of information for remote monitoring of the Earth’s surface. Modern satellite and aerial systems provide data about the details of the site topography, its characteristics due to different criteria (type of terrain, vegetation cover, soil type and moisture content), or even information about emergency situations or disasters. The paper proposes and discusses the process...
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A New, Reconfigurable Circuit Offering Functionality of AND and OR Logic Gates for Use in Algorithms Implemented in Hardware
PublikacjaThe paper presents a programmable (using a 1-bit signal) digital gate that can operate in one of two OR or AND modes. A circuit of this type can also be implemented using conventional logic gates. However, in the case of the proposed circuit, compared to conventional solutions, the advantage is a much smaller number of transistors necessary for its implementation. Circuit is also much faster than its conventional counterpart. The...
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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublikacjaMachine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...
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General concept of reduction process for big data obtained by interferometric methods
PublikacjaInterferometric sonar systems apply the phase content of the sonar signal to measure the angle of a wave front returned from the seafloor or from a target. It collect a big data – datasets that are so large or complex that traditional data processing application software is inadequate to deal with them. The recording a large number of data is associated with the difficulty of their efficient use. So data have to be reduced. The main...
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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...
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Oleksandr Melnychenko dr hab.
OsobyOleksandr Melnychenko pracuje na stanowisku profesora w grupie pracowników naukowo-dydaktycznych Katedry Finansów na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej; jest tłumaczem przysięgłym języka ukraińskiego; przedsiębiorcą z wieloletnim doświadczeniem prowadzenia własnej działalności i zarządzania finansami firm; ma doświadczenie pracy w banku komercyjnym na stanowisku zajmującym się współpracą banku z systemami płatniczymi,...
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Metaheurystyki sztucznej inteligencji w wybranych grach komputerowych
PublikacjaW pracy omówiono trzy metaheurystyki sztucznej inteligencji, które mogą stać się źródłem inspiracji dla projektantów gier komputerowych. Pokazano, w jaki sposób zastosowano algorytm mrówkowy, algorytm genetyczny i algorytm tabu search w grach komputerowych zaprojektowanych przez studentów Politechniki Gdańskiej. W szczególności, odniesiono się do problematyki wyznaczania trajektorii przemieszczających się obiektów...
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Data Acquisition in a Manoeuver Auto-negotiation System
PublikacjaTypical approach to collision avoidance systems with artificial intelligence support is that such systems assume a central communication and management point (such as e.g. VTS station), usually located on shore. This approach is, however, not applicable in case of an open water encounter. Thus, recently a new approach towards collision avoidance has been proposed, assuming that all ships in the encounter, either restricted or open...
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Zdzisław Kowalczuk prof. dr hab. inż.
OsobyW 1978 ukończył studia w zakresie automatyki i informatyki na Wydziale Elektroniki Politechniki Gdańskiej, następnie rozpoczął pracę na macierzystej uczelni. W 1986 obronił pracę doktorską, w 1993 habilitował się na Politechnice Śląskiej na podstawie pracy Dyskretne modele w projektowaniu układów sterowania. W 1996 mianowany profesorem nadzwyczajnym, w 2003 otrzymał tytuł profesora nauk technicznych. W 2006 założył i od tego czasu...
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Algorithmic Human Resources Management - Perspectives and Challenges
PublikacjaTheoretical background: Technology – most notably processes of digitalisation, the use of artificial intelligence, machine learning, big data and prevalence of remote work due to pandemic – changes the way organizations manage human resources. One of the increasing trends is the use of so-called “algorithmic management”. It is notably different than previous e-HRM or HRIS (human resources information systems) applications, as it...
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Krzysztof Goczyła prof. dr hab. inż.
OsobyKrzysztof Goczyła, profesor zwyczajny Politechniki Gdańskiej, informatyk, specjalista z inżynierii oprogramowania, inżynierii wiedzy i baz danych. Ukończył studia wyższe na Wydziale Elektroniki Politechniki Gdańskiej w 1976 r. jako magister inżynier elektronik w specjalności automatyka. Na Politechnice Gdańskiej pracuje od 1976. Na Wydziale Elektroniki PG w 1982 r. uzyskał doktorat z informatyki, a w 1999 r. habilitację. W 2012...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Deep Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Sensors and Sensor’s Fusion in Autonomous Vehicles
PublikacjaAutonomous vehicle 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, and deep learning are changing the quality of areas of applications, improving the sensors and systems used. New ideas such as 3D radar, 3D sonar, LiDAR, and others are based on autonomous vehicle revolutionary development. The Special...
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How digital technology affects working conditions in globally fragmented production chains: Evidence from Europe
PublikacjaThis paper uses a sample of over 9 million workers from 22 European countries to study the intertwined relationship between digital technology, cross-border production links and working conditions. We compare the social consequences of technological change exhibited by three types of innovation: computerisation (software), automation (robots) and artificial intelligence (AI). To fully quantify work-related wellbeing, we propose...
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Electronic nose algorithm design using classical system identification for odour intensity detection
PublikacjaThe two elements considered crucial for constructing an efficient environmental odour intensity monitoring systems are sensors and algorithms typically addressed to as electronic nose sensor (e-nose). Due to operational complexity of biochemical sensors developed in human bodies algorithms based on computational methods of artificial intelligence are typically considered superior to classical model based approaches in development...
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How personality traits, sports anxiety, and general imagery could influence the physiological response measured by SCL to imagined situations in sports?
Dane BadawczeThe data were collected to understand how individual differences in personality (e.g. neuroticism), general imagery, and situational sports anxiety are linked to arousal measuring with skin conductance level (SCL) in situational imagery (as scripted for sport-related scenes). Thirty persons participated in the study, aged between 14 and 42 years, with...
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Pedestrian detection in low-resolution thermal images
PublikacjaOver one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...
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Addressing Challenges in AI-based Systems Development: A Proposal of Adapted Requirements Engineering Process
Publikacja[Context] Present-day IT systems are more and more dependent on artificial intelligence (AI) solutions. Developing AI-based systems means facing new challenges, not known for more conventional systems. Such challenges need to be identified and addressed by properly adapting the existing development and management processes. [Objective] In this paper, we focus on the requirements engineering (RE) area of IT projects and aim to propose...
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A note on the affective computing systems and machines: a classification and appraisal
PublikacjaAffective computing (AfC) is a continuously growing multidisciplinary field, spanning areas from artificial intelligence, throughout engineering, psychology, education, cognitive science, to sociology. Therefore, many studies have been devoted to the aim of addressing numerous issues, regarding different facets of AfC solutions. However, there is a lack of classification of the AfC systems. This study aims to fill this gap by reviewing...
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublikacjaDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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Digital Innovations and Smart Solutions for Society And Economy: Pros and Cons
PublikacjaRecent developments in artificial intelligence (AI) may involve significant potential threats to personal data privacy, national security, and social and economic stability. AI-based solutions are often promoted as “intelligent” or “smart” because they are autonomous in optimizing various processes. Be-cause they can modify their behavior without human supervision by analyzing data from the environ-ment, AI-based systems may be...
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Automatic Rhythm Retrieval from Musical Files
PublikacjaThis paper presents a comparison of the effectiveness of two computational intelligence approaches applied to the task of retrieving rhythmic structure from musical files. The method proposed by the authors of this paper generates rhythmic levels first, and then uses these levels to compose rhythmic hypotheses. Three phases: creating periods, creating simplified hypotheses and creating full hypotheses are examined within this study....
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Communication as a Factor Limiting University-Business Cooperation
PublikacjaObjective - Despite the broad extent of the scientific activity dealing with university-business cooperation, Poland has yet to develop a satisfactory cooperation strategy that takes business needs into account. This issue is still relevant due to the need for continuous improvement and resulting benefits aimed at improving enterprise competitiveness. Methodology/Technique - Authors of this article attempt to select an overriding...
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Project-Based Collaborative Research and Training Roadmap for Manufacturing Based on Industry 4.0
PublikacjaThe importance of the economy being up to date with the latest developments, such as Industry 4.0, is more evident than ever before. Successful implementation of Industry 4.0 principles requires close cooperation of industry and state authorities with universities. A paradigm of such cooperation is described in this paper stemming from university partners with partly overlapping and partly complementary areas of expertise in manufacturing....
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Roman Śmierzchalski prof. dr hab. inż.
OsobyUrodził się w 1956 r. w Gdyni. Jest absolwentem Wydziału Elektrycznego Politechniki Gdańskiej (1979). W 1989 r. uzyskał stopień doktora, w roku 1999 stopień doktora habilitowanego, a w roku 2014 tytuł profesora. W latach 1980–2009 był pracownikiem naukowo-dydaktycznym Akademii Morskiej w Gdyni. Od 2009 jest r. pracownikiem naukowo-dydaktycznym Politechniki Gdańskiej. Jego zainteresowania naukowe obejmują: sterowanie i automatykę,...
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Spotkanie politechnicznego klubu sztucznej inteligencji
WydarzeniaPierwsze w tym roku akademickim spotkanie klubu AI Bay – Zatoka Sztucznej Inteligencji, który działa na Politechnice Gdańskiej odbędzie się w Gmachu B Wydziału Elektroniki, Telekomunikacji i Informatyki (Audytorium 1P).
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PPAM 2022
WydarzeniaThe PPAM 2022 conference, will cover topics in parallel and distributed computing, including theory and applications, as well as applied mathematics.
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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublikacjaRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
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Viability of decisional DNA in robotics
PublikacjaThe Decisional DNA is an artificial intelligence system that uses prior experiences to shape future decisions. Decisional DNA is written in the Set Of Experience Knowledge Structure (SOEKS) and is capable of capturing and reusing a broad range of data. Decisional DNA has been implemented in several fields including Alzheimer’s diagnosis, geothermal energy and smart TV. Decisional DNA is well suited to use in robotics due to the...
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APPLICATION OF APRIORI ALGORITHM IN THE LAMINATION PROCESS IN YACHT PRODUCTION
PublikacjaThe article specifies the dependence of defects occurring in the lamination process in the production of yachts. Despite great knowledge about their genesis, they cannot be completely eliminated. Authentic data obtained through cooperation with one of the Polish yacht shipyards during the years 2013–2017 were used for the analysis. To perform a simulation, the sample size was observed in 1450 samples, consisting of 6 models of...
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From Knowledge based Vision Systems to Cognitive Vision Systems: A Review
PublikacjaComputer vision research and applications have their origins in 1960s. Limitations in computational resources inherent of that time, among other reasons, caused research to move away from artificial intelligence and generic recognition goals to accomplish simple tasks for constrained scenarios. In the past decades, the development in machine learning techniques has contributed to noteworthy progress in vision systems. However,...
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Spatial Visualization Based on Geodata Fusion Using an Autonomous Unmanned Vessel
PublikacjaThe visualization of riverbeds and surface facilities on the banks is crucial for systems that analyze conditions, safety, and changes in this environment. Hence, in this paper, we propose collecting, and processing data from a variety of sensors—sonar, LiDAR, multibeam echosounder (MBES), and camera—to create a visualization for further analysis. For this purpose, we took measurements from sensors installed on an autonomous, unmanned...
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Machine Learning and Electronic Noses for Medical Diagnostics
PublikacjaThe need for noninvasive, easy-to-use, and inexpensive methods for point-of-care diagnostics of a variety of ailments motivates researchers to develop methods for analyzing complex biological samples, in particular human breath, that could aid in screening and early diagnosis. There are hopes that electronic noses, that is, devices based on arrays of semiselective or nonselective chemical sensors, can fill this niche. Electronic...
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Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublikacjaThe rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...
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Social media for e-learning of citizens in smart city
PublikacjaThe rapid development of social media can be applied for citizens’ e-learning in a smart city. Big cities have to cope with several open issues like a growing population or a traffic congestion. Especially, a home and public space is supposed to be used in more efficient way. Sustainable homes and buildings can be planned with using some modern techniques. Even currently, there is a huge problem with a lack of key resources like...
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Garnizon district in Gdansk, Poland
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Seestadt Aspern, Vienna, Austria
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Västra Hamnen, Malmö, Sweden.
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Hammarby-Sjöstad, Stockholm, Sweden.
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Pilestredet Park, Oslo, Norway.
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / King’s Cross, London, UK.
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / Oceanhamnen, Helsingborg, Sweden
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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Case Study NEB Atlas / part II - Autodesk Forma analysis / La Courrouze district in Rennes, France
Dane BadawczeThe data present the results of the work on the analysis of modern settlements. The goal of this part of the research was to analyze housing estates already in place in various European cities. Analyses were performed in real time using artificial intelligence, and responses were searched for sun hours, daylight potential, noise, wind, and microclimate....
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The impact of the AC922 Architecture on Performance of Deep Neural Network Training
PublikacjaPractical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...
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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublikacjaObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
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Automatic Watercraft Recognition and Identification on Water Areas Covered by Video Monitoring as Extension for Sea and River Traffic Supervision Systems
PublikacjaThe article presents the watercraft recognition and identification system as an extension for the presently used visual water area monitoring systems, such as VTS (Vessel Traffic Service) or RIS (River Information Service). The watercraft identification systems (AIS - Automatic Identification Systems) which are presently used in both sea and inland navigation require purchase and installation of relatively expensive transceivers...
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Optimisation of turbine shaft heating process under steam turbine run-up conditions
PublikacjaAn important operational task for thermal turbines during run-up and run-down is to keep the stresses in the structural elements at a right level. This applies not only to their instantaneous values, but also to the impact of them on the engine lifetime. The turbine shaft is a particularly important element. The distribution of stresses depends on geometric characteristics of the shaft and its specific locations. This means a groove manufactured...
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Global energy transition: From the main determinants to economic challenges regions
PublikacjaDynamic global energy transition has been accelerating for the last decade. Interestingly, the energy transition is multidimensional and concerns both the dimensions of technique/ technology and the economic, social, institu-tional, and legal spheres (Shuguang et al., 2022; Tzeremes et al., 2022; Ram-zan et al., 2022; Tzeremes et al., 2022). The literature also points to the signif-icant impact of the digitization of the global...
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Błażej Prusak dr hab.
OsobyBłażej Prusak jest kierownikiem Katedry Finansów na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej oraz redaktorem naczelnym czasopisma Research on Enterprise in Modern Economy - theory and practice (REME)/Przedsiębiorstwo we współczesnej gospodarce - teoria i praktyka, a także członkiem komitetów redakcyjnych takich czasopism jak: Intellectual Economics; Przestrzeń. Ekonomia. Społeczeństwo; Akademia Zarządzania. Jest autorem...
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Abdalraheem Ijjeh Ph.D. Eng.
OsobyThe primary research areas of interest are artificial intelligence (AI), machine learning, deep learning, and computer vision, as well as modeling physical phenomena (i.e., guided waves in composite laminates). The research interests described above are utilized for SHM and NDE applications, namely damage detection and localization in composite materials.
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublikacjaBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Comparison and Analysis of Service Selection Algorithms
PublikacjaIn Service Oriented Architecture, applications are developed by integration of existing services in order to reduce development cost and time. The approach, however, requires algorithms that select appropriate services out of available, alternative ones. The selection process may consider both optimalization requirements, such as maximalization of performance, and constraint requirements, such minimal security or maximum development...
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Spectrum-based modal parameters identification with Particle Swarm Optimization
PublikacjaThe paper presents the new method of the natural frequencies and damping identification based on the Artificial Intelligence (AI) Particle Swarm Optimization (PSO) algorithm. The identification is performed in the frequency domain. The algorithm performs two PSO-based steps and introduces some modifications in order to achieve quick convergence and low estimation error of the identified parameters’ values for multi-mode systems....
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To Survive in a CBRN Hostile Environment: Application of CAVE Automatic Virtual Environments in First Responder Training
PublikacjaThis paper is of a conceptual nature and focuses on the use of a specific virtual reality environment in civil-military training. We analyzed the didactic potential of so-called CAVE automatic virtual environments for First Responder training, a type of training that fills the gap between First Aid training and the training received by emergency medical technicians. Since real training involves live drills based on unexpected situations,...
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How high-tech solutions support the fight against IUU and ghost fishing: a review of innovative approaches, methods, and trends
PublikacjaIllegal, Unreported, and Unregulated fishing is a major threat to human food supply and marine ecosystem health. Not only is it a cause of significant economic loss but also its effects have serious long-term environmental implications, such as overfishing and ocean pollution. The beginning of the fight against this problem dates since the early 2000s. From that time, a number of approaches and methods have been developed and reported....
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Machine learning approach to packaging compatibility testing in the new product development process
PublikacjaThe paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing...
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Metal–Organic Frameworks (MOFs) for Cancer Therapy
PublikacjaMOFs exhibit inherent extraordinary features for diverse applications ranging from catalysis, storage, and optics to chemosensory and biomedical science and technology. Several procedures including solvothermal, hydrothermal, mechanochemical, electrochemical, and ultrasound techniques have been used to synthesize MOFs with tailored features. A continued attempt has also been directed towards functionalizing MOFs via “post-synthetic...
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(eng)aging! 2021 Technologie wspierające aktywność i niezależność seniorów w państwach V4
ProjektyProjekt realizowany w Katedra Inteligentnych Systemów Interaktywnych zgodnie z porozumieniem 22020301/1 z dnia 2021-01-08
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Ontology-Aided Software Engineering
PublikacjaThis thesis is located between the fields of research on Artificial Intelligence (AI), Knowledge Representation and Reasoning (KRR), Computer-Aided Software Engineering (CASE) and Model Driven Engineering (MDE). The modern offspring of KRR - Description Logic (DL) [Baad03] is considered here as a formalization of the software engineering Methods & Tools. The bridge between the world of formal specification (governed by the mathematics)...
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How Can We Identify Electrophysiological iEEG Activities Associated with Cognitive Functions?
PublikacjaElectrophysiological activities of the brain are engaged in its various functions and give rise to a wide spectrum of low and high frequency oscillations in the intracranial EEG (iEEG) signals, commonly known as the brain waves. The iEEG spectral activities are distributed across networks of cortical and subcortical areas arranged into hierarchical processing streams. It remains a major challenge to identify these activities in...
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Adjusting the Stiffness of Supports during Milling of a Large-Size Workpiece Using the Salp Swarm Algorithm
PublikacjaThis paper concerns the problem of vibration reduction during milling. For this purpose, it is proposed that the standard supports of the workpiece be replaced with adjustable stiffness supports. This affects the modal parameters of the whole system, i.e., object and its supports, which is essential from the point of view of the relative tool–workpiece vibrations. To reduce the vibration level during milling, it is necessary to...
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Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych
PublikacjaAutomation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...
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Klasyfikacja sygnału EKG przy użyciu konwolucyjnych sieci neuronowych
PublikacjaAutomation and improvement of diagnostic process is a vital element of medicine development and patient’s condition self-control. For a long time different ECG signal classification methods exist and are successfully applied, nevertheless their accuracy is not always satisfying enough. The lack of identification of an existing abnormality, which is very similar to a normal heartbeat is the biggest issue - for example premature...
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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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Predicting emotion from color present in images and video excerpts by machine learning
PublikacjaThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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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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Digital Transformation of Terrestrial Radio: An Analysis of Simulcasted Broadcasts in FM and DAB+ for a Smart and Successful Switchover
PublikacjaThe process of digitizing radio is far from over. It is an important interdisciplinary aspect, involving Big Data and AI (Artificial Intelligence) when it comes to classifying and handling content, and an organizational challenge in the Industry 4.0 concept. There exist several methods for delivering audio signals, including terrestrial broadcasting and internet streaming. Among them, the DAB+ (Digital Audio Broadcasting plus)...
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Explainable machine learning for diffraction patterns
PublikacjaSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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Smart metering - social risk perception and risk governance (10h, 2 ECTS credits)
Kursy OnlineThe goal of the course is to broaden the understanding of technology-related risks and to present the concepts of social risk perception and risk governance in the context of smart metering technology. In current phase of technological development – known as the fourth industrial revolution – rapid and profound changes are setting up new and particularly destabilizing risks. In more and more complex technological systems that constitute...
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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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Tomasz Korol dr hab. inż.
OsobyWykształcenie Politechnika Gdańska, Wydział Zarządzania i Ekonomii (2001) University of Applied Sciences Stralsund (1999) Stopień naukowy Doktor habilitowany – Politechnika Gdańska, Wydział Zarządzania i Ekonomii (2015) Doktor – Politechnika Gdańska, Wydział Zarządzania i Ekonomii (2004) Zatrudnienie Politechnika Gdańska: profesor uczelni (od 2019); profesor nadzwyczajny (2017-2019); adiunkt (2004-2016); asystent (2001-2004) I-Shou...
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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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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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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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Arsalan Muhammad Soomar Doctoral Student
OsobyHi, I'm Arsalan Muhammad Soomar, an Electrical Engineer. I received my Master's and Bachelor's Degree in the field of Electrical Engineering from Mehran University of Engineering and Technology, Jamshoro, Sindh, Pakistan. Currently enrolled as a Doctoral student at the Gdansk University of Technology, Gdansk, Poland. Also worked in Yellowlite. INC, Ohio as a Solar Design Engineer. HEADLINE Currently Enrolled as a Doctoral...
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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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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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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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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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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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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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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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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...