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Search results for: VOCATIONAL TRAINING, INNOVATIVE TRAINING MASTER BSR, ERASMUS+
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Pedestrian detection in low-resolution thermal images
PublicationOver 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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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublicationIn remote sensing images, change detection (CD) is required in many applications, such as: resource management, urban expansion research, land management, and disaster assessment. Various deep learning-based methods were applied to satellite image analysis for change detection, yet many of them have limitations, including the overfitting problem. This research proposes the Feature Weighted Attention (FWA) in Bidirectional Long...
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The Effectiveness of Basic Resuscitation Activities Carried out by Combat Paramedics of the Police, as Exemplified by Polish Counterterrorist Units
PublicationThe tasks carried out by Police officers are often accompanied by dangerous situations that threaten the life and health of the people involved, the police themselves, and bystanders. It concerns especially counter-terrorism police units whose activities are aimed at terrorists and particularly dangerous criminals, and their course is violent and aggressive. In conjunction with the inability to bring civilian rescue services into...
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Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening
PublicationFamilial hypercholesterolemia (FH) is a highly undiagnosed disease. Among FH patients, the onset of premature coronary artery disease is 13 times higher than in the general population. Early diagnosis and treatment is essential to prevent cardiovascular diseases and their complications, and to prolong life. One of the clinical criteria of FH is the occurrence of a corneal arcus (CA) among patients, especially those under 45 years...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Magnetic Signature Description of Ellipsoid-Shape Vessel Using 3D Multi-Dipole Model Fitted on Cardinal Directions
PublicationThe article presents a continuation of the research on the 3D multi-dipole model applied to the reproduction of magnetic signatures of ferromagnetic objects. The model structure has been modified to improve its flexibility - model parameters determined by optimization can now be located in the cuboid contour representing the object's hull. To stiffen the model, the training dataset was expanded to data collected from all four cardinal...
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Reduced-Cost Two-Level Surrogate Antenna Modeling using Domain Confinement and Response Features
PublicationElectromagnetic (EM) simulation tools have become indispensable in the design of contemporary antennas. Still, the major setback of EM-driven design is the associated computational overhead. This is because a single full-wave simulation may take from dozens of seconds up to several hours, thus, the cost of solving design tasks that involve multiple EM analyses may turn unmanageable. This is where faster system representations (surrogates)...
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Graph Representation Integrating Signals for Emotion Recognition and Analysis
PublicationData reusability is an important feature of current research, just in every field of science. Modern research in Affective Computing, often rely on datasets containing experiments-originated data such as biosignals, video clips, or images. Moreover, conducting experiments with a vast number of participants to build datasets for Affective Computing research is time-consuming and expensive. Therefore, it is extremely important to...
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Assessing the attractiveness of human face based on machine learning
PublicationThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks
PublicationIn this paper, the optical linear sensor, a representative of low-resolution sensors, was investigated in the multiclass recognition of near-field hand gestures. The recurrent neural network (RNN) with a gated recurrent unit (GRU) memory cell was utilized as a gestures classifier. A set of 27 gestures was collected from a group of volunteers. The 27 000 sequences obtained were divided into training, validation, and test subsets....
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Performance-Based Nested Surrogate Modeling of Antenna Input Characteristics
PublicationUtilization of electromagnetic (EM) simulation tools is mandatory in the design of contemporary antenna structures. At the same time, conducting designs procedures that require multiple evaluations of the antenna at hand, such as parametric optimization or yield-driven design, is hindered by a high cost of accurate EM analysis. To certain extent, this issue can be addressed by utilization of fast replacement models (also referred...
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Reliable data-driven modeling of high-frequency structures by means of nested kriging with enhanced design of experiments
PublicationData-driven (or approximation) surrogate models have been gaining popularity in many areas of engineering and science, including high-frequency electronics. They are attractive as a way of alleviating the difficulties pertinent to high computational cost of evaluating full-wave electromagnetic (EM) simulation models of microwave, antenna, and integrated photonic components and devices. Carrying out design tasks that involve massive...
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sp2-rich dendrite-like carbon nanowalls as effective electrode for environmental monitoring of explosive nitroaromatic
PublicationNitroaromatic compounds are commonly used explosive materials that pose a risk to human health and ecosystems due to their acute toxicity and carcinogenicity. Nitroaromatics have numerous pathways into the environment via discarded munitions (e.g. into the Baltic Sea after World War II), after use in mining operations, and in industrial run-off from factories producing these compounds (which are produced across the world to date)....
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EMBOA - affective loop in Socially Assistive Robotics as an intervention tool for children with autism
e-Learning CoursesThe aim of the training course "Intensive programmes for higher education learner" within the EMBOA project is to familiarise participants with the use of social robots as an intervention tool for children with autism, emotion recognition and the combination of both methods. Students will be informed about the guidelines and results of the project.
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[AiU] Contemporary research methodology, evaluation and preservation of historic architecture
e-Learning CoursesThis course is compulsory for PhD students assigned to Architecture and Urbanism tracks at Doctoral School at Gdańsk University of Technology. The course is conducted by prof. Sandro Parrinello, Department of Civil Engineering and Architecture of University of Pavia Course type: workshops Total hours of training: 30 teaching hours Classes in hybrid mode (classes conducted online and at the GdańskTech)
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[AiU]20232024_Challenges and Perspectives in Contemporary Architecture and Urbanism
e-Learning CoursesThis course is compulsory for PhD students assigned to Architecture and Urbanism tracks at Doctoral School at Gdańsk University of Technology. The course is conducted by Prof. Marichela Sepe, DICEA / Sapienza University Rome Course type: workshops Total hours of training: 15 teaching hours Classes in online mode (classes conducted online)
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[AiU] 20232024_Sustainable Design and Environmental Changes
e-Learning CoursesThis course is compulsory for PhD students assigned to Architecture and Urbanism tracks at Doctoral School at Gdańsk University of Technology. The course is conducted by Prof. Marichela Sepe, DICEA / Sapienza University Rome Course type: workshops Total hours of training: 15 teaching hours Classes in online mode (classes conducted online)
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Dr. Asmaa Mahfoud Al-Hakimi PhD
PeopleDr. ASMA’A MAHFOUD HEZAM AL-HAKIMY from Yemen was born in Egypt 9th October. Received Diploma in Computer Programming in 2006 from University of Science and Technology Sanaa Yemen. Received Bachelor’s Degree in Computer Studies in 2008 from NORTHUMBRIA Newcastle University UK. Received master’s degree in Software Engineering in 2011 from STAFFORDSHIRE University, UK. Received PhD in Software Engineering from Universiti Putra Malaysia....
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Koncepcja logistycznego usprawnienia magazynu cross-dockowego przedsiębiorstwa X
PublicationCelem artykułu jest przedstawienie koncepcji logistycznego usprawnienia magazynu cross- -dockowego przedsiębiorstwa X. W oparciu o informacje dotyczące stanu faktycznego maga- zynu zostały przeprowadzone badania procesów magazynowych. Po przeprowadzeniu identyfikacji problemów zostały zaproponowane usprawnienia wybranego procesu magazynowego, które polegały na propozycji zmiany sposobu zagospodarowania magazynu. Do tego...
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Rzeczywistość rozszerzona – potencjał w kształceniu (przyszłych) pomorskich inżynierów
PublicationEdukacja młodzieży w zakresie nauk eksperymentalnych – takich jak chemia i fizyka – stanowi obecnie w obliczu ograniczeń zaplecza dydaktycznego w szkołach ogromne wyzwanie. Placówki edukacyjne nie posiadają często odpowiednich laboratoriów, lecz dysponują pracowniami komputerowymi. W ramach Projektu EDUAR, współfinansowanego przez NCBiR, przeprowadzono badania w 20 szkołach – po 10 z obszarów wiejskich i miejskich, podczas których...
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Intermolecular Interactions as a Measure of Dapsone Solubility in Neat Solvents and Binary Solvent Mixtures
PublicationDapsone is an effective antibacterial drug used to treat a variety of conditions. However, the aqueous solubility of this drug is limited, as is its permeability. This study expands the available solubility data pool for dapsone by measuring its solubility in several pure organic solvents: N-methyl-2-pyrrolidone (CAS: 872-50-4), dimethyl sulfoxide (CAS: 67-68-5), 4-formylmorpholine (CAS: 4394-85-8), tetraethylene pentamine (CAS:...
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On Inadequacy of Sequential Design of Experiments for Performance-Driven Surrogate Modeling of Antenna Input Characteristics
PublicationDesign of contemporary antennas necessarily involves electromagnetic (EM) simulation tools. Their employment is imperative to ensure evaluation reliability but also to carry out the design process itself, especially, the adjustment of antenna dimensions. For the latter, traditionally used parameter sweeping is more and more often replaced by rigorous numerical optimization, which entails considerable computational expenses, sometimes...
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Variable‐fidelity modeling of antenna input characteristics using domain confinement and two‐stage Gaussian process regression surrogates
PublicationThe major bottleneck of electromagnetic (EM)-driven antenna design is the high CPU cost of massive simulations required by parametric optimization, uncertainty quantification, or robust design procedures. Fast surrogate models may be employed to mitigate this issue to a certain extent. Unfortunately, the curse of dimensionality is a serious limiting factor, hindering the construction of conventional data-driven models valid over...
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Three-dimensional modeling and automatic analysis of the human nasal cavity and paranasal sinuses using the computational fluid dynamics method
PublicationPurpose The goal of this study was to develop a complete workflow allowing for conducting computational fluid dynam- ics (CFD) simulation of airflow through the upper airways based on computed tomography (CT) and cone-beam computed tomography (CBCT) studies of individual adult patients. Methods This study is based on CT images of 16 patients. Image processing and model generation of the human nasal cavity and paranasal sinuses...
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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublicationThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
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Comparability of Raman Spectroscopic Configurations: A Large Scale Cross-Laboratory Study
PublicationThe variable configuration of Raman spectroscopic platforms is one of the major obstacles in establishing Raman spectroscopy as a valuable physicochemical method within real-world scenarios such as clinical diagnostics. For such real world applications like diagnostic classification, the models should ideally be usable to predict data from different setups. Whether it is done by training a rugged model with data from many setups...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublicationRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
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How to teach architecture? – Remarks on the edge of Polish transformation processes after 1989
PublicationThe political changes in Poland after 1989 have resulted in a whole range of dynamic processes including the transformation of space. Until that time the established institutional framework for spatial, urban and architectural planning policy was based on uniform provisions of the so-called planned economy. The same applied to the training of architects, which was based on a unified profile of education provided at the state’s...
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublicationIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
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Global Design Optimization of Microwave Circuits Using Response Feature Inverse Surrogates
PublicationModern microwave design has become heavily reliant on full-wave electromagnetic (EM) simulation tools, which are necessary for accurate evaluation of microwave components. Consequently, it is also indispensable for their development, especially the adjustment of geometry parameters, oriented towards performance improvement. However, EM-driven optimization procedures incur considerable computational expenses, which may become impractical...
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Development of an AI-based audiogram classification method for patient referral
PublicationHearing loss is one of the most significant sensory disabilities. It can have various negative effects on a person's quality of life, ranging from impeded school and academic performance to total social isolation in severe cases. It is therefore vital that early symptoms of hearing loss are diagnosed quickly and accurately. Audiology tests are commonly performed with the use of tonal audiometry, which measures a patient's hearing...
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Low-Cost Modeling of Microwave Components by Means of Two-Stage Inverse/Forward Surrogates and Domain Confinement
PublicationFull-wave electromagnetic (EM) analysis is one of the most important tools in the design of modern microwave components and systems. EM simulation permits reliable evaluation of circuits at the presence of cross-coupling effects or substrate anisotropy, as well as for accounting for interactions with the immediate environment. However, repetitive analyses required by EM-driven procedures, such as parametric optimization or statistical...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublicationNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Expedited Acquisition of Database Designs for Reduced-Cost Performance-Driven Modeling and Rapid Dimension Scaling of Antenna Structures
PublicationFast replacement models have been playing an increasing role in high-frequency electronics, including the design of antenna structures. Their role is to improve computational efficiency of the procedures that normally entail large numbers of expensive full-wave electromagnetic (EM) simulations, e.g., parametric optimization or uncertainty quantification. Recently introduced performance-driven modeling methods, such as the nested...
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The congruence of mental models in entrepreneurial teams – implications for performance and satisfaction in teams operating in an emerging economy
PublicationPurpose – The paper aims to explore the relationship between the congruence of mental models held by the members of entrepreneurial teams operating in an emerging economy (Poland) and entrepreneurial outcomes (performance and satisfaction). Design/methodology/approach – The data obtained from 18 nascent and 20 established entrepreneurial teams was analysed to answer hypotheses. The research was quantitative and was conducted using...
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Embedded gas sensing setup for air samples analysis
PublicationThis paper describes a measurement setup (eNose) designed to analyze air samples containing various volatile organic compounds (VOCs). The setup utilizes a set of resistive gas sensors of divergent gas selectivity and sensitivity. Some of the applied sensors are commercially available and were proposed recently to reduce their consumed energy. The sensors detect various VOCs at sensitivities determined by metal oxide sensors’ technology...
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Computationally-Efficient Statistical Design and Yield Optimization of Resonator-Based Notch Filters Using Feature-Based Surrogates
PublicationModern microwave devices are designed to fulfill stringent requirements pertaining to electrical performance, which requires, among others, a meticulous tuning of their geometry parameters. When moving up in frequency, physical dimensions of passive microwave circuits become smaller, making the system performance increasingly susceptible to manufacturing tolerances. In particular, inherent inaccuracy of fabrication processes affect...
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A Parallel Corpus-Based Approach to the Crime Event Extraction for Low-Resource Languages
PublicationThese days, a lot of crime-related events take place all over the world. Most of them are reported in news portals and social media. Crime-related event extraction from the published texts can allow monitoring, analysis, and comparison of police or criminal activities in different countries or regions. Existing approaches to event extraction mainly suggest processing texts in English, French, Chinese, and some other resource-rich...
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Marking the Allophones Boundaries Based on the DTW Algorithm
PublicationThe paper presents an approach to marking the boundaries of allophones in the speech signal based on the Dynamic Time Warping (DTW) algorithm. Setting and marking of allophones boundaries in continuous speech is a difficult issue due to the mutual influence of adjacent phonemes on each other. It is this neighborhood on the one hand that creates variants of phonemes that is allophones, and on the other hand it affects that the border...
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Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublicationOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...
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[NF] Physics research methods. Part III
e-Learning CoursesKurs realizowany wspólnie dla doktorantów szkoły doktorskiej i studiów doktoranckich The course is conducted jointly for PhD students of the doctoral school and doctoral studies Franco Bagnoli, University of Florence, Italy - "Thermodynamics, Statistical Mechanics, and Kinetic Gas Theory https://enauczanie.pg.edu.pl/moodle/course/view.php?id=5259 Course type: lecture Total hours of training (part III): 15 teaching hours
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[NF] Physics research methods. Part II.
e-Learning CoursesKurs realizowany wspólnie dla doktorantów szkoły doktorskiej i studiów doktoranckich The course is conducted jointly for PhD students of the doctoral school and doctoral studies Franco Bagnoli, University of Florence, Italy - "Thermodynamics, Statistical Mechanics, and Kinetic Gas Theory with a computational perspective. https://enauczanie.pg.edu.pl/moodle/course/view.php?id=5259 Course type: lecture Total hours of training...
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[soft skills] Scientific databases and information skills
e-Learning Courses{mlang pl} Dyscyplina: wszystkie dyscypliny Zajęcia obowiązkowe dla doktorantów I roku Prowadzący: Liczba godzin: 5 Forma zajęć: wykład {mlang} {mlang en} Discipline: all disciplines Obligatory course for 1st-year PhD students Academic teacher: Total hours of training: 5 teaching hours Course type: lecture {mlang} Soft skills Area II - researcher's workshop "Scientific databases and information skills" The training...
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Jakub Miler dr inż.
PeopleAcademic career: 2000: Master of Science - Gdansk University of Technology, Faculty of Electronics, Telecommunications and Informatics, thesis "Computer system for supporting risk management in a software engineering project", supervisor prof. Janusz Górski 2005: PhD - Gdansk University of Technology, Faculty of Electronics, Telecommunications and Informatics, thesis "A Method of Software Project Risk Identification and Analysis",...
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Wykorzystanie metafor w identyfikacji i kształtowaniu postaw przedsiębiorczych
PublicationEdukacja przedsiębiorcza odgrywa coraz większą rolę w promowaniu i kształtowaniu zachowań oraz kompetencji przedsiębiorczych młodego pokolenia. W tym kontekście szczególnie podkreśla się znaczenie wykorzystywania nowych, interaktywnych metod i form kształcenia, niezwykle istotnych dla jednego z aspektów edukacji przedsiębiorczej, jakim jest kształcenie kreatywności i proaktywności. Zastosowanie metafor spełnia wymagania stawiane...
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Agata Pierścieniak dr hab. inż.
PeopleAgata Pierscieniak is a graduate of the Wrocław University of Technology, Faculty of Computer Science and Management (1992). She obtained her Ph.D. degree in the field of Economic Sciences in 2004 from the Warsaw University of Life Sciences, while her post-doc (habilitated doctor) degree in the discipline of Management Sciences, in 2016, was from the Warsaw School of Economics.During the years 1998-2018, she worked at the University...
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[Soft Skills] Workshop in research ethics gr.2 AEEITK, ITIT, IMe
e-Learning Courses{mlang pl} Dyscyplina: Wszystkie dyscypliny Zajęcia obowiązkowe dla doktorantów III roku Prowadzący: A. Karalus Liczba godzin: 5 {mlang} {mlang en} Discipline: All disciplines Obligatory course for 3rd year PhD students Academic teacher: A. Karalus Total hours of training: 5 teaching hours {mlang}
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[Soft Skills] Workshop in research ethics gr.3 NCh, IMa, NF
e-Learning Courses{mlang pl} Dyscyplina: Wszystkie dyscypliny Zajęcia obowiązkowe dla doktorantów III roku Prowadzący: A. Karalus Liczba godzin: 5 {mlang} {mlang en} Discipline: All disciplines Obligatory course for 3rd year PhD students Academic teacher: A. Karalus Total hours of training: 5 teaching hours {mlang}
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[Soft Skills] Workshop in research ethics gr.1 AIU_ILGIT_IŚGIE_EIF
e-Learning Courses{mlang pl} Dyscyplina: Wszystkie dyscypliny Zajęcia obowiązkowe dla doktorantów III roku Prowadzący: A. Karalus Liczba godzin: 5 {mlang} {mlang en} Discipline: All disciplines Obligatory course for 3rd year PhD students Academic teacher: A. Karalus Total hours of training: 5 teaching hours {mlang}
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Rapid tolerance‐aware design of miniaturized microwave passives by means of confined‐domain surrogates
PublicationThe effects of uncertainties, primarily manufacturing tolerances but also incomplete information about operating conditions or material parameters, can be detrimental to the performance of microwave components. Quantification of such effects is essential to ensure a meaningful evaluation of the structure, in particular, its reliability under imperfect fabrication procedures. The improvement of the circuit robustness can be achieved...