Search
Gdańsk University of Technology
Among the 1 000 best universities in the world
Gdańsk University of Technology is one fo the 8 Polish universities classified in the prestigious Academic Ranking of World Universities (ARWU), also known as the Shanghai Ranking. Each year, ARWU ranks over 2 000 universities and publishes a list of top 1 000 best ones. Gdańsk University of Technology was classified in the 801-900 range in 2021.
The highest standards in Europe for conducting research
In 2017, the European Commission granted Gdańsk Tech the right to use the prestigious HR Excellence in Research logo. Gdańsk University of Technology was thus recognized as an institution that creates some of the best working and development conditions for researchers in Europe.
One of the best universities in Poland
Gdańsk University of Technology is the second-best research university in Poland in the ‘Initiative of Excellence - Research University’ competition of the Ministry of Science and Higher Education. It is here where inventions used in Poland and around the world are created - communication with the use of eyes, an ecological medicine for osteoporosis, biodegradable materials and many more.
Publications
Filters
total: 40169
displaying 1000 best results Help
Catalog Publications
Year 2024
-
Active Kriging-based conjugate first-order reliability method for highly efficient structural reliability analysis using resample strategy
PublicationEfficient structural reliability analysis method is crucial to solving reliability analysis of complex structural problems. High-computational cost and low-failure probability problems greatly limit the efficiency in structural reliability analysis problems, causing the safety and reliability of the structure to be questioned. In this work, a highly efficient structural reliability analysis method coupling active Kriging algorithm...
-
Active Learning on Ensemble Machine-Learning Model to Retrofit Buildings Under Seismic Mainshock-Aftershock Sequence
PublicationThis research presents an efficient computational method for retrofitting of buildings by employing an active learning-based ensemble machine learning (AL-Ensemble ML) approach developed in OpenSees, Python and MATLAB. The results of the study shows that the AL-Ensemble ML model provides the most accurate estimations of interstory drift (ID) and residual interstory drift (RID) for steel structures using a dataset of 2-, to 9-story...
-
Activity-based payments: alternative (anonymous) online payment model
PublicationElectronic payments are the cornerstone of web-based commerce. A steady decrease in cash usage has been observed, while various digital payment technologies are taking over. They process sensitive personal information raising concerns about its potentially illicit usage. Several payment models that confront this challenge have been proposed. They offer varying levels of anonymity and readiness for adoption. The aim of this study...
-
Actual and reference evapotranspiration for a natural, temperate zone fen wetland – Upper Biebrza case study
PublicationEvapotranspiration is the key and predominant component of the water balance in wetlands. Direct evapotranspiration measurements are challenging in wetlands due to their remoteness and high surface water level. This article describes the actual (ETa and reference evapotranspiration (ET0) from a cultivated wet meadow located in the Biebrza National Park – the largest national park in north-east Poland, Central Europe. The data were...
-
Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublicationIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
-
Adaptacyjny system oświetlania dróg oraz inteligentnych miast
PublicationPrzedmiotem rozprawy jest zbadanie praktycznej możliwości wykrywania w czasie rzeczywistym anomalii w systemie oświetlenia drogowego w oparciu o analizę danych ze inteligentnych liczników energii. Zastosowanie inteligentnych liczników energii elektrycznej (Smart Meter) w systemach oświetlenia drogowego stwarza nowe możliwości w zakresie automatycznej diagnostyki takich niepożądanych zjawisk jak awarie lamp, odstępstwa od harmonogramu...
-
Adaptacyjny system sterowania ruchem drogowym
PublicationAdaptacyjny system sterowania ruchem drogowym to rodzaj systemu sterowania, który dynamicznie, w czasie rzeczywistym, dostosowuje swoje parametry w oparciu o bieżące warunki ruchu drogowego. Celem niniejszej rozprawy jest sprawdzenie wpływu wybranych cech systemu, zbudowanego w oparciu o zaprojektowane i zbudowane z udziałem autora inteligentne znaki drogowe, na wybrane parametry mające wpływ na bezpieczeństwo i płynność ruchu....
-
Adaptive Hounsfield Scale Windowing in Computed Tomography Liver Segmentation
PublicationIn computed tomography (CT) imaging, the Hounsfield Unit (HU) scale quantifies radiodensity, but its nonlinear nature across organs and lesions complicates machine learning analysis. This paper introduces an automated method for adaptive HU scale windowing in deep learning-based CT liver segmentation. We propose a new neural network layer that optimizes HU scale window parameters during training. Experiments on the Liver Tumor...
-
Adaptive Hyperparameter Tuning within Neural Network-based Efficient Global Optimization
PublicationIn this paper, adaptive hyperparameter optimization (HPO) strategies within the efficient global optimization (EGO) with neural network (NN)-based prediction and uncertainty (EGONN) algorithm are proposed. These strategies utilize Bayesian optimization and multiarmed bandit optimization to tune HPs during the sequential sampling process either every iteration (HPO-1itr) or every five iterations (HPO-5itr). Through experiments using...
-
Adaptive Optimal Discrete-Time Output-Feedback Using an Internal Model Principle and Adaptive Dynamic Programming
PublicationIn order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming (ADP) technique based on the internal model principle (IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback, merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization...
-
Adaptive Sampling for Non-intrusive Reduced Order Models Using Multi-Task Variance
PublicationNon-intrusive reduced order modeling methods (ROMs) have become increasingly popular for science and engineering applications such as predicting the field-based solutions for aerodynamic flows. A large sample size is, however, required to train the models for global accuracy. In this paper, a novel adaptive sampling strategy is introduced for these models that uses field-based uncertainty as a sampling metric. The strategy uses...
-
Additive manufacturing of Proton-Conducting Ceramics by robocasting with integrated laser postprocessing
PublicationA hybrid system combining robocasting and NIR laser postprocessing has been designed to fabricate layers of mixed proton-electron conducting Ba0.5La0.5Co1-xFexO3-δ ceramic. The proposed manufacturing technique allows for the control of the geometry and microstructure and shortens the fabrication time to a range of a few minutes. Using 5 W laser power and a scanning speed of 500 mm⋅s− 1, sintering of a round-shaped layer with an...
-
Addressing challenges of BiVO4 light-harvesting ability through vanadium precursor engineering and sub-nanoclusters deposition for peroxymonosulfate-assisted photocatalytic pharmaceuticals removal
PublicationIn this study, we present a complex approach for increasing light utilisation and peroxymonosulfate (PMS) activation in BiVO4-based photocatalyst. This involves two key considerations: the design of the precursor for BiVO4 synthesis and interface engineering through CuOx sub-nanoclusters deposition. The designed precursor of ammonium methavanadate (NH4VO3, NHV) leads to reduction in particle size, better dispersion and improved light...
-
Addressing the Weaknesses of Multi-Criteria Decision-Making Methods using Python
PublicationThe book aims to draw attention to the weaknesses in Multi-Criteria Decision-Making (MCDM) methods and provide insights to improve the decision-making process. By addressing these weaknesses, it seeks to enhance the accuracy and effectiveness of MCDM methods in selecting the best alternatives in various fields. The book covers popular MCDM methods such as TOPSIS, ELECTRE, VIKOR, and PROMETHEE. It compares traditional methods with...
-
Adjusted SpikeProp algorithm for recurrent spiking neural networks with LIF neurons
PublicationA problem related to the development of a supervised learning method for recurrent spiking neural networks is addressed in the paper. The widely used Leaky-Integrate-and-Fire model has been adopted as a spike neuron model. The proposed method is based on a known SpikeProp algorithm. In detail, the developed method enables gradient descent learning of recurrent or multi-layer feedforward spiking neural networks. The research included...
-
Adoption of the F-statistic of Fisher-Snedecor distribution to analyze importance of impact of modifications of injector opening pressure of a compression ignition engine on specific enthalpy value of exhaust gas flow
PublicationThis article analyzes the effect of modifications of injector opening pressure on the operating values of a compression ignition engine, including the temperature of the fumes. A program of experimental investigation is described, considering the available test stand and measurement capabilities. The structure of the test stand on which the experimental measurements were conducted is presented. The method of introducing real modifications...
-
Advanced Bayesian study on inland navigational risk of remotely controlled autonomous ship
PublicationThe arise of autonomous ships has necessitated the development of new risk assessment techniques and methods. This study proposes a new framework for navigational risk assessment of remotely controlled Maritime Autonomous Surface Ships (MASS). This framework establishes a set of risk influencing factors affecting safety of navigation of a remotely-controlled MASS. Next, model parameters are defined based on the risk factors, and...
-
Advanced nanomaterials and metal-organic frameworks for catalytic bio-diesel production from microalgal lipids – A review
PublicationIncreasing energy demands require exploring renewable, eco-friendly (green), and cost-effective energy resources. Among various sources of biodiesel, microalgal lipids are an excellent resource, owing to their high abundance in microalgal biomass. Transesterification catalyzed by advanced materials, especially nanomaterials and metal-organic frameworks (MOFs), is a revolutionary process for overcoming the energy crisis. This review...
-
Advanced seismic control strategies for smart base isolation buildings utilizing active tendon and MR dampers
PublicationThis paper investigates the seismic behaviour of a five-storey shear building that incorporates a base isolation system. Initially, the study considers passive base isolation and employs a multi-objective archived-based whale optimization algorithm called MAWOA to optimize the parameters of base isolation. Subsequently, a novel model is proposed, which incorporates an interval type-2 Takagi-Sugeno fuzzy logic controller (IT2TSFLC)...
-
Advanced Sensor for Non-Invasive Breast Cancer and Brain Cancer Diagnosis Using Antenna Array with Metamaterial-Based AMC
PublicationMicrowave imaging techniques can identify abnormal cells in early development stages. This study introduces a microstrip patch antenna coupled with artificial magnetic conductor (AMC) to realize improved sensor for non-invasive (early-stage) breast cancer and brain cancer diagnosis. The frequency selectivity of the proposed antenna has been increased by the presence of AMC by creating an additional resonance at 2.276 GHz associated...
-
Advanced ultra super critical power plants: role of buttering layer
PublicationDissimilar metal welded (DMW) joint plays a crucial role in constructing and maintaining ultra-supercritical (USC) nuclear power plants while presenting noteworthy environmental implications. This research examines different welding techniques utilized in DMWJ, specifically emphasizing materials such as P91. The study investigates the mechanical properties of these materials, the impact of alloying elements, the notable difficulties...
-
Advances and Trends in Non-Conventional, Abrasive and Precision Machining 2021
PublicationIn the modern, rapidly evolving industrial landscape, the quest for machining and production processes consistently delivering superior quality and precision is more pronounced than ever. This necessity and imperative are driven by the increasing complexity in the design and manufacturing of mechanical components, an evolution in lockstep with the swift advancements in material science. The real challenge of this evolution lies...
-
Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method
PublicationElectrochemical impedance spectroscopy (EIS) is widely used in electrochemistry, energy sciences, biology, and beyond. Analyzing EIS data is crucial, but it often poses challenges because of the numerous possible equivalent circuit models, the need for accurate analytical models, the difficulties of nonlinear regression, and the necessity of managing large datasets within a unified framework. To overcome these challenges, non-parametric...
-
Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublicationThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
-
Advancing sustainable hybrid bitumen systems: A compatibilization solution by functionalized polyolefins for enhanced crumb rubber content in bitumen
PublicationPolymer waste pollution has a profound effect on the environment and, consequently, on the lifestyle of hu- mankind. The massive production and disposal of cross-linked polymers clearly exemplify the challenges of recycling. Increasing efforts are being undertaken to introduce recycled polymers, especially crumb rubber (CR), into asphalt formulations. Due to the rather poor processability and phase separation associated with CR- modified...
-
Advancing sustainable wastewater management: A comprehensive review of nutrient recovery products and their applications
PublicationWastewater serves as a vital resource for sustainable fertilizer production, particularly in the recovery of nitrogen (N) and phosphorus (P). This comprehensive study explores the recovery chain, from technology to final product reuse. Biomass growth is the most cost-effective method, valorizing up to 95 % of nutrients, although facing safety concerns. Various techniques enable the recovery of 100 % P and up to 99 % N, but challenges...
-
Advancing Urban Transit: Gepard and CAR projects - Innovations in Trolleybus Technology
PublicationThe Gepard project in Gdynia, Poland, revolutionized the city's trolleybus network with the introduction of “Trolleybus 2.0” vehicles and an innovative charging system. “Trolleybus 2.0” vehicles combine features of traditional trolleybuses and electric buses boasting traction batteries for autonomous driving and dual legal approval. Statistical analysis of energy consumption informed the development of a hybrid charging concept,...
-
AGREEMIP: The Analytical Greenness Assessment Tool for Molecularly Imprinted Polymers Synthesis
PublicationMolecular imprinting technology is well established in areas where a high selectivity is required, such as catalysis, sensing, and separations/sample preparation. However, according to the Principles of Green Chemistry, it is evident that the various steps required to obtain molecularly imprinted polymers (MIPs) are far from ideal. In this regard, greener alternatives to the synthesis of MIPs have been proposed in recent years....
-
Agri-food waste biosorbents for volatile organic compounds removal from air and industrial gases – A review
PublicationApproximately 1.3 billion metric tons of agricultural and food waste is produced annually, highlighting the need for appropriate processing and management strategies. This paper provides an exhaustive overview of the utilization of agri-food waste as a biosorbents for the elimination of volatile organic compounds (VOCs) from gaseous streams. The review paper underscores the critical role of waste management in the context of a...
-
AI-Powered Cleaning Robot: A Sustainable Approach to Waste Management
PublicationThe world is producing a massive amount of single use waste, especially plastic waste made from polymers. Such waste is usually distributed in large areas within cities, near roads, parks, forests, etc. It is a challenge to collect them efficiently. In this work, we propose a Cleaning Robot as an autonomous vehicle for waste collection, utilizing the Nvidia Jetson Nano platform for precise arm movements guided by computer...
-
Algebraic periods and minimal number of periodic points for smooth self-maps of 1-connected 4-manifolds with definite intersection forms
PublicationLet M be a closed 1-connected smooth 4-manifolds, and let r be a non-negative integer. We study the problem of finding minimal number of r-periodic points in the smooth homotopy class of a given map f: M-->M. This task is related to determining a topological invariant D^4_r[f], defined in Graff and Jezierski (Forum Math 21(3):491–509, 2009), expressed in terms of Lefschetz numbers of iterations and local fixed point indices of...
-
Alginate-based sorbents in miniaturized solid phase extraction techniques - Step towards greenness sample preparation
PublicationIn response to growing concerns about environmental degradation, one of the main areas of research activity in recent years has been to make sample preparation methods more sustainable and eco-friendly. The increasing greenness of this step can be achieved by minimizing the usage of reagents, automating individual stages, saving energy and time, and using non-toxic, biodegradable substances. Therefore, the use of natural materials...
-
Algorithmic Human Resources Management
PublicationThe rapid evolution of Digital Human Resources Management has introduced a transformative era where algorithms play a pivotal role in reshaping the landscape of workforce management. This transformation is encapsulated in the concepts of algorithmic management and algorithmic Human Resource Management (HRM). The integration of advanced analytics, predictive and prescriptive analytics and the power of Artificial Intelligence (AI)...
-
Alphitobius diaperinus larvae (lesser mealworm) as human food – An approval of the European Commission – A critical review
PublicationDue to the increasing threat of climate change and the need for sustainable food sources, human consumption of edible insects or entomophagy has gained considerable attention globally. The larvae of Alphitobius diaperinus Panzer (Coleoptera: Tenebrionidae), also known as the lesser mealworm, have been identified as a promising candidate for mass-rearing as a food source based the on evaluation on several aspects such as the production...
-
An absorbing set for the Chialvo map
PublicationThe classical Chialvo model, introduced in 1995, is one of the most important models that describe single neuron dynamics. In order to conduct effective numerical analysis of this model, it is necessary to obtain a rigorous estimate for the maximal bounded invariant set. We discuss this problem, and we correct and improve the results obtained by Courbage and Nekorkin (2010). In particular, we provide an explicit formula for an...
-
An Adaptive Network Model for a Double Bias Perspective on Learning from Mistakes within Organizations
PublicationAlthough making mistakes is a crucial part of learning, it is still often being avoided in companies as it is considered as a shameful incident. This goes hand in hand with a mindset of a boss who dominantly believes that mistakes usually have negative consequences and therefore avoids them by only accepting simple tasks. Thus, there is no mechanism to learn from mistakes. Employees working for and being influenced by such a boss...
-
An Analysis of Airline GRI and SDG Reporting
PublicationThis study aims to increase our understanding of the Global Reporting Initiative’s (GRI) topic-specific disclosures and the sustainable development goals (SDGs) addressed in the global passenger airline industry’s sustainability reporting (SR). Based on a quantitative content analysis of the industry’s sustainability reports from the financial year 2019 (FY19), this study reveals that airlines focused more on reporting environmental...
-
An analytical approach to determine the health benefits and health risks of consuming berry juices
PublicationFood products composition analysis is a prerequisite for verification of product quality, fulfillment of regulatory enforcements, checking compliance with national and international food standards, contracting specifications, and nutrient labeling requirements and providing quality assurance for use of the product for the supplemen- tation of other foods. These aspects also apply to the berry fruit and berry juice. It also must...
-
An ANN-Based Method for On-Load Tap Changer Control in LV Networks with a Large Share of Photovoltaics—Comparative Analysis
PublicationThe paper proposes a new local method of controlling the on-load tap changer (OLTC) of a transformer to mitigate negative voltage phenomena in low-voltage (LV) networks with a high penetration of photovoltaic (PV) installations. The essence of the method is the use of the load compensation (LC) function with settings determined via artificial neural network (ANN) algorithms. The proposed method was compared with other selected...
-
An annotated timeline of sensitivity analysis
PublicationThe last half a century has seen spectacular progresses in computing and modelling in a variety of fields, applications, and methodologies. Over the same period, a cross-disciplinary field known as sensitivity analysis has been making its first steps, evolving from the design of experiments for laboratory or field studies, also called ‘in-vivo’, to the so-called experiments ‘in-silico’. Some disciplines were quick to realize the...
-
An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
-
An Efficient PEEC-Based Method for Full-Wave Analysis of Microstrip Structures
PublicationThis article introduces an efficient method for the equivalent circuit characterization and full-wave analysis of microstrip structures, leveraging the full-wave partial element equivalent circuit (PEEC). In particular, the multilayered Green's function is evaluated using the discrete complex-image method (DCIM) and employed to establish the mixed potential integral equations. The proposed strategy considers time delays for the...
-
An Example of Using Low-Cost LiDAR Technology for 3D Modeling and Assessment of Degradation of Heritage Structures and Buildings
PublicationThis article examines the potential of low-cost LiDAR technology for 3D modeling and assessment of the degradation of historic buildings, using a section of the Koszalin city walls in Poland as a case study. Traditional terrestrial laser scanning (TLS) offers high accuracy but is expensive. The study assessed whether more accessible LiDAR options, such as those integrated with mobile devices such as the Apple iPad Pro, can serve...
-
An image processing approach for fatigue crack identification in cellulose acetate replicas
PublicationThe cellulose acetate replication technique is an important method for studying material fatigue. However, extracting accurate information from pictures of cellulose replicas poses challenges because of distortions and numerous artifacts. This paper presents an image processing procedure for effective fatigue crack identification in plastic replicas. The approach employs thresholding, adaptive Gaussian thresholding, and Otsu binarization...
-
An improvement of body surface area formulas using the 3D scanning technique
PublicationObjectives: Body surface area (BSA) is one of the major parameters used in several medical fields. However, there are concerns raised about its usefulness, mostly due to the ambiguity of its estimation. Material and Methods: Authors have conducted a voluntary study to investigate BSA distribution and estimation in a group of 179 adult people of various sex, age, and physique. Here, there is provided an extended analysis of the...
-
An Innovative Floating System with a Savonius Rotor as a Horizontal-Axis Wind Turbine
PublicationIn this project, an innovative wind turbine was designed for a floating plant. A large Savonius rotor was replaced with a double-rotor wind turbine implemented as a horizontal-axis turbine. This double rotor was positioned on the tip of a thrust plate and fixed to the deck of a catamaran. Simple 2D numerical simulations were performed to confirm the effectiveness of the concept. An analysis of the floating system configuration...
-
An Innovative New Approach to Light Pollution Measurement by Drone
PublicationThe study of light pollution is a relatively new and specific field of measurement. The current literature is dominated by articles that describe the use of ground and satellite data as a source of information on light pollution. However, there is a need to study the phenomenon on a microscale, i.e., locally within small locations such as housing estates, parks, buildings, or even inside buildings. Therefore, there is an important...
-
An intelligent cellular automaton scheme for modelling forest fires
PublicationForest fires have devastating consequences for the environment, the economy and human lives. Understanding their dynamics is therefore crucial for planning the resources allocated to combat them effectively. In a world where the incidence of such phenomena is increasing every year, the demand for efficient and accurate computational models is becoming increasingly necessary. In this study, we perform a revision of an initial proposal...
-
An inverse algorithm for contact heat conduction problems with an interfacial heat source based on a first-order thermocouple model
PublicationInverse problems of contact heat conduction with an interfacial heat source are common in various fields of science, engineering and technology. In this study, an algorithm for their solution is developed based on an inverse parametric optimisation method with an impulse response function describing the heat partition and contact heat transfer. A first-order thermocouple model with a time constant parameter is embedded in the impulse...
-
An optimized dissolved oxygen concentration control in SBR with the use of adaptive and predictive control schemes
PublicationThis paper addresses the problem of optimizing control of the aeration process in a water resource recovery facility (WRRF) using sequencing batch reactor (SBR), one that affects the efficiency of wastewater treatment by stimulating metabolic reactions of microorganisms through dissolved oxygen (DO) level control, and accounts for the predominant part of operating costs. Two independent approaches to DO control algorithm design...