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Search results for: ENGINEERING EDUCATION, SMART GRID SYSTEMS, CHALLENGE-BASED LEARNING
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Interactive Technology and Smart Education
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublicationBreast 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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Online Learning Based on Prototypes
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Global Journal of Engineering Education
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Appraisal of the Faculty of Mechanical Engineering of Gdańsk University of Technology in view of domestic education standards
PublicationOpisano doświadczenia Wydziału Mechanicznego Politechniki Gdańskiej wyniesione z akredytacji kierunku studiów: mechanika i budowa maszyn. Skoncentrowano się na przedstawieniu procedury sporządzania raportu samooceny i jego weryfikacji przez komisję zewnętrzną.
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Investor focused placement and sizing of photovoltaic grid-connected systems in Pakistan
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Decisional-DNA-Based Digital Twin Implementation Architecture for Virtual Engineering Objects
PublicationDigital twin (DT) is an enabling technology that integrates cyber and physical spaces. It is well-fitted for manufacturing setup since it can support digitalized assets and data analytics for product and process control. Conventional manufacturing setups are still widely used all around the world for the fabrication of large-scale production. This article proposes a general DT implementation architecture for engineering objects/artifacts...
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Biomedical engineering of polysaccharide-based tissue adhesives: Recent advances and future direction
PublicationTissue adhesives have been widely used for preventing wound leaks, sever bleeding, as well as for enhancing drug delivery and biosensing. However, only a few among suggested platforms cover the circumstances required for high-adhesion strength and biocompatibility, without toxicity. Antibacterial properties, controllable degradation, encapsulation capacity, detectability by image-guided procedures and affordable price are also...
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Learning Health Systems
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublicationAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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Operating systems (Data Engineering) - 2023/24
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International Journal of Game-Based Learning
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Interdisciplinary Journal of Problem-Based Learning
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Deep learning-based waste detection in natural and urban environments
PublicationWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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Port-Based Modelling of Distributed-Lumped Parameter Systems
PublicationThere in the paper is presented an uniform, port-based approach to modelling of both lumped and distributed parameter systems. Port-based model of the distributed system has been defined by application of bond graph methodology and distributed transfer function method (DTFM). The approach proposed combines versatility of port-based modelling and accuracy of distributed transfer function method. The concise representation of lumped-distributed...
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Systemy z Uczeniem Maszynowym / Systems with Machine Learning 2022/2023
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A compact smart resistive sensor based on a microcontroller
PublicationPrzedstawiono nowe rozwiązanie inteligentnego czujnika rezystancyjnego bazującego na mikrokontrolerze, w którym czujnik rezystancyjny jest elementem składowym filtra anty-aliazingowego przetwornika A/C. Procedura pomiaru temperatury obejmuje pobudzenie filtra dwoma impulsami prostokątnymi o zadanym czasie trwania oraz próbkowanie jego odpowiedzi czasowej. Następnie na podstawie wartości pomierzonych próbek napięcia wyznaczana jest...
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Tomasz Maria Boiński dr inż.
PeopleI’m associated with the University since the year 2000 when I started my studies in Computer Science on the Faculty of Electronics, Telecommunications and Informatics. After graduating with honors in 2005, I applied for doctoral studies. During his studies and immediately afterward I was involved in cooperation with Hogart from Warsaw, in the implementation of business solutions in Gdynia company Elektronika SA (Infor FMS SunSystems)...
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Polyurethane based hybrid ciprofloxacin-releasing wound dressings designed for skin engineering purpose
PublicationPurpose Even in the 21st century, chronic wounds still pose a major challenge due to potentially inappropriate treatment options, so the latest wound dressings are hybrid systems that enable clinical management, such as a hybrid of hydrogels, antibiotics and polymers. These wound dressings are mainly used for chronic and complex wounds, which can easily be infected by bacteria. Materials and methods Six Composite Porous Matrices...
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Implementing decisional trust: a first approach for smart reliable systems
PublicationIn this article, we introduce the necessary elements that must be integrated in order to achieve a decisional technology that is trustworthy. Thus, we refer to such technology as decisional trust. For us, decisional trust can be achieved through the use of elements such as the decisional DNA, reflexive ontologies, and security models; and therefore, we present in this article a framework that was used for the implementation of...
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Paweł Czarnul dr hab. inż.
PeoplePaweł Czarnul obtained a D.Sc. degree in computer science in 2015, a Ph.D. in computer science granted by a council at the Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology in 2003. His research interests include:parallel and distributed processing including clusters, accelerators, coprocessors; distributed information systems; architectures of distributed systems; programming mobile devices....
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Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning
PublicationMy doctoral dissertation is intended as the compound of four publications considering: structure and randomness in planning and reinforcement learning, continuous control with ensemble deep deterministic policy gradients, toddler-inspired active representation learning, and large-scale deep reinforcement learning costs.
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublicationMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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A consensus-based approach to the distributed learning
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An agent-based framework for distributed learning
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Krzysztof Goczyła prof. dr hab. inż.
PeopleKrzysztof Goczyła, full professor of Gdańsk University of Technology, computer scientist, a specialist in software engineering, knowledge engineering and databases. He graduated from the Faculty of Electronics Technical University of Gdansk in 1976 with a degree in electronic engineering, specializing in automation. Since then he has been working at Gdańsk University of Technology. In 1982 he obtained a doctorate in computer science...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Evaluation of Supply Chain Management Systems Used in Civil Engineering
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Editorial: Information and knowledge engineering for intelligent systems. Part II
PublicationW pracy omówiono najnowsze dokonania w zakresie inzynierii i zarządzania wiedzą i informacją z perspektywy ich możliwych zastosowań w konstruowaniu systemów inteligentnych
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Editorial: Information and knowledge engineering for intelligent systems. Part I
PublicationW pracy omówiono najnowsze dokonania w zakresie inzynierii i zarządzania wiedzą i informacją z perspektywy ich możliwych zastosowań w konstruowaniu systemów inteligentnych
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Research - based technology education – the EDURES partnership experience
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Biopolymer based nanomaterials in drug delivery systems: A review
PublicationDrug delivery systems (DDS) are used to achieve a higher therapeutic effects of a pharmaceutical drug or natural compound in a specific diseased site with minimal toxicological effect and these systems consists of liposomes, microspheres, gels, prodrugs and many. Nanotechnology is a rapidly developing multi-disciplinary science that ensures the fabrication of the polymers to nanometer scale for various medical applications. Uses...
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Band engineering of BiOBr based materials for photocatalytic wastewater treatment via advanced oxidation processes (AOPs) – A review
PublicationSemiconductor based photocatalysts have been an efficient technology for water and wastewater remediation, addressing the concepts of green chemistry and sustainable development. Owing to narrow and suitable band structure, BiOBr is a promising candidate for efficient wastewater treatment via photocatalysis. Enhancement of photocatalytic properties can be obtained by various techniques like doping, element rich strategy, facet...
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Model-based testing for execution algorithms in the simulation of cyber-physical systems
PublicationThe understanding of simulation semantics of a hybrid system is a challenge for computational engineers as it requires expertise in computer science, engineering, numerical methods, and mathematics at once. The testing methods for the execution of a simulation are being researched but not yet applied on the industrial level. Consequently, the semantics of the simulation becomes a critical artifact in the system development process....
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Decisional DNA Based Conceptual Framework for Smart Manufacturing
PublicationThis paper presents the conceptual framework for systematic knowledge representation, storage and reuse of manufacturing information in a production scenario. This knowledge structure is designed for three levels in a manufacturing set up viz. first at the engineering objects level, second at process and finally at factory level. Virtual engineering object (VEO) deals with knowledge at the individual object/component/machine level...
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Lucyna Nyka prof. dr hab. inż. arch.
PeopleLucyna Nyka (Ph.D., D.Sc., Prof.) is a Professor at the Faculty of Architecture, Gdańsk University of Technology, in 2008-2016 a Vice-Dean for Research, and since 2016 – Dean of the Faculty of Architecture. Her research interests focus on issues concerning water-related architecture and urban landscapes. She is the author and co-author of many projects focused on urban renewal. She was an author of the EU-founded (Audiovisual...
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Performance Analysis of Interaction between Smart Glasses and Smart Objects Using Image-Based Object Identification
PublicationWe propose the use of smart glasses to collaborate with smart objects in the Internet of Things environment. Particularly we are focusing on new interaction methods and the analysis of acceptable reaction times in the process of object recognition using smart glasses. We evaluated the proposed method using user studies and experiments with three different smart glasses: Google Glass, Epson Moverio, and the developed eGlasses platform....
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Michał Grochowski dr hab. inż.
PeopleProfessor and a Head of the Department of Intelligent Control and Decision Support Systems at Gdansk University of Technology (GUT). He is also a Member of the Board of the Digital Technologies Center of GUT. He received his M.Sc. degree in Control Engineering in 2000 from the Electrical and Control Engineering Faculty at the GUT. In 2004 he received a Ph.D. degree in Automatic Control and Robotics from this...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublicationComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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Systems Engineering
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Hybrid design approach in education using a progressive rule-based digital design development. Sopot College experiences.
PublicationBudynek sam w sobie może być uznany za hybrydę inżynierii i Beaux-Arts. Obecnie istnieje wiele narzędzi, które mogą pomóc architektom w opracowaniu i optymalizowu ich innowacyjnych koncepcje. Artykuł opisuje projekt hybrydowego podejścia opartego na połączeniu tradycyjnej architekturze i Komputerowego projektowania na podstawie programu studiów w Sopocie College, Wydział Architektury. Artykuł bada dziedzinie współpracy i interakcji...
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ADAPTATION OF ENGINEERING FEA-BASED ALGORITHMS TO LCF FAILURE AND MATERIAL DATA PREDICTION IN OFFSHORE DESIGN
PublicationThere is an ever growing industrial demand for quantitative assessment of fatigue endurance of critical structural details. Although FEA-based calculations have become a standard in engineering design, problems involving the Low-To-Medium cycle range (101-104) remain challenging. This paper presents an attempt to optimally choose material data, meshing density and other algorithm settings in the context of recent design of the...