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Wyniki wyszukiwania dla: training methods
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From Creative Thinking Techniques to Innovative Design Solutions - The Educators' Perspective
PublikacjaThe article presents a structure and basic tasks of a new original academic course, which was inaugurated in 2015 at the Faculty of Architecture in Gdańsk University of Technology and organized for the first year students of Spatial Planning.The title of the course was ‘Garden Cities and the Gardens in the Cities. A Course with Elements of Training Creativity’. The aim of the course was to encourage the participants to develop...
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OBTAINING FLUID FLOW PATTERN FOR TURBINE STAGE WITH NEURAL MODEL.
PublikacjaIn the paper possibility of applying neural model to obtaining patterns of proper operation for fluid flow in turbine stage for fluid-flow diagnostics is discussed. Main differences between Computational Fluid Dynamics (CFD) solvers and neural model is given, also limitations and advantages of both are considered. Time of calculations of both methods was given, also possibilities of shortening that time with preserving the accuracy...
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Modification and Optimization of the United-Residue (UNRES) Potential Energy Function for Canonical Simulations. I. Temperature Dependence of the Effective Energy Function and Tests of the Optimization Method with Single Training Proteins
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Learning sperm cells part segmentation with class-specific data augmentation
PublikacjaInfertility affects around 15% of couples worldwide. Male fertility problems include poor sperm quality and low sperm count. The advanced fertility treatment methods like ICSI are nowadays supported by vision systems to assist embryologists in selecting good quality sperm. Computer-Assisted Semen Analysis (CASA) provides quantitative and qualitative sperm analysis concerning concentration, motility, morphology, vitality, and fragmentation....
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Expedited Acquisition of Database Designs for Reduced-Cost Performance-Driven Modeling and Rapid Dimension Scaling of Antenna Structures
PublikacjaFast 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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To Work or Not to Work… in a Multicultural Team?
PublikacjaThe main goal of the article is to present research findings regarding student’s attitude to working in a multicultural team (MCT). Research participants of different cultural background completed the research survey. Their willingness to work in MCT was measured together with factors that influence it. These include factors related to both team members and the task structure. Research findings indicate that the respondents preferred...
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Dataset Related Experimental Investigation of Chess Position Evaluation Using a Deep Neural Network
PublikacjaThe idea of training Articial Neural Networks to evaluate chess positions has been widely explored in the last ten years. In this paper we investigated dataset impact on chess position evaluation. We created two datasets with over 1.6 million unique chess positions each. In one of those we also included randomly generated positions resulting from consideration of potentially unpredictable chess moves. Each position was evaluated...
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublikacjaThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublikacjaIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublikacjaThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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BETWEEN IDEA AND INTERPRETATION - DESIGN PROCESS AUGMENTATION
PublikacjaThe following paper investigates the idea of reducing the human digital intervention to a minimum during the advanced design process. Augmenting the outcome attributes beyond the designer's capabilities by computational design methods, data collection, data computing and digital fabrication, altogether imitating the human design process. The primary technical goal of the research was verification of restrictions and abilities used...
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Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks
PublikacjaThe presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods....
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublikacjaBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Vident-synth: a synthetic intra-oral video dataset for optical flow estimation
Dane BadawczeWe introduce Vident-synth, a large dataset of synthetic dental videos with corresponding ground truth forward and backward optical flows and occlusion masks. It can be used for:
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News that Moves the Market: DSEX-News Dataset for Forecasting DSE Using BERT
PublikacjaStock market is a complex and dynamic industry that has always presented challenges for stakeholders and investors due to its unpredictable nature. This unpredictability motivates the need for more accurate prediction models. Traditional prediction models have limitations in handling the dynamic nature of the stock market. Additionally, previous methods have used less relevant data, leading to suboptimal performance. This study...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany 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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Psychosocial risks associated with the profession of train driver
PublikacjaExcellent competencies as well as a good physical and mental health are required in train drivers’ profession. Despite the changes in the structure of employment the train drivers above 46 years and job tenure longer than 30 years are the largest group. The generation gap is becoming more pronounced, and its fulfilment will not be easy. It is related not only to training of new personnel but also promotion of healthy work environment...
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublikacjaSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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MagMax: Leveraging Model Merging for Seamless Continual Learning
PublikacjaThis paper introduces a continual learning approach named MagMax, which utilizes model merging to enable large pre-trained models to continuously learn from new data without forgetting previously acquired knowledge. Distinct from traditional continual learning methods that aim to reduce forgetting during task training, MagMax combines sequential fine-tuning with a maximum magnitude weight selection for effective knowledge integration...
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Design-Oriented Constrained Modeling of Antenna Structures
PublikacjaFast surrogate models are crucially important to reduce the cost of design process of antenna structures. Due to curse of dimensionality, standard (data-driven) modeling methods exhibit serious limitations concerning the number of independent geometry parameters that can be handled but also (and even more importantly) their parameter ranges. In this work, a design-oriented modeling framework is proposed in which the surrogate is...
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Reduced-Cost Constrained Modeling of Microwave and Antenna Components: Recent Advances
PublikacjaElectromagnetic (EM) simulation models are ubiquitous in the design of microwave and antenna components. EM analysis is reliable but CPU intensive. In particular, multiple simulations entailed by parametric optimization or uncertainty quantification may considerably slow down the design processes. In order to address this problem, it is possible to employ fast metamodels. Here, the popular solution approaches are approximation...
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Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing
PublikacjaDeveloping signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....
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Data librarian and data steward – new tasks and responsibilities of academic libraries in the context of Open Research Data implementation in Poland
PublikacjaThesis/Objective – The policy of Open Access (OA) for researching resources in Europe has been implemented for more than 10 years. The first recommendations concerning providing OA to scientific materials were defined during the implementation of the 7th Framework Programme. Introducing another set of recommendations concerning OA to research data was the next stage. The recommendations were transformed into obligations under the...
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International Conference on IT Based Higher Education and Training
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International Conference on Cybercrime Forensics Education and Training
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Fault detection in the marine engine using a support vector data description method
PublikacjaFast detection and correct diagnosis of any engine condition changes are essential elements of safety andenvironmental protection. Many diagnostic algorithms significantly improve the detection of malfunctions.Studies on diagnostic methods are rarely reported and even less implemented in the marine engine industry.To fill this gap, this paper presents the Support Vector Data Description (SVDD) method as applied to thefault detection...
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Normalization of face illumination using basic knowledge and information extracted from a single image
PublikacjaThis paper presents a method for face image normalization that can be applied to the extraction of illumination invariant facial features or used to remove bad lighting effects and produce high-quality, photorealistic results. Most of the existing approaches concentrate on separating the constant albedo from the variable light intensity; that concept, however, is based on the Lambertian model, which fails in the presence of specularities...
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Deep Instance Segmentation of Laboratory Animals in Thermal Images
PublikacjaIn this paper we focus on the role of deep instance segmentation of laboratory rodents in thermal images. Thermal imaging is very suitable to observe the behaviour of laboratory animals, especially in low light conditions. It is an non-intrusive method allowing to monitor the activity of animals and potentially observe some physiological changes expressed in dynamic thermal patterns. The analysis of the recorded sequence of thermal...
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublikacjaBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
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Accelerated multi-objective design optimization of antennas by surrogate modeling and domain segmentation
PublikacjaMulti-objective optimization yields indispensable information about the best possible design trade-offs of an antenna structure, yet it is challenging if full-wave electromagnetic (EM) analysis is utilized for performance evaluation. The latter is a necessity for majority of contemporary antennas as it is the only way of achieving acceptable modeling accuracy. In this paper, a procedure for accelerated multi-objective design of...
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Design-oriented computationally-efficient feature-based surrogate modelling of multi-band antennas with nested kriging
PublikacjaDesign of modern antenna structures heavily depends on electromagnetic (EM) simulation tools. EM analysis provides reliable evaluation of increasingly complex designs but tends to be CPU intensive. When multiple simulations are needed (e.g., for parameters tuning), the aggregated simulation cost may become a serious bottleneck. As one possible way of mitigating the issue, the recent literature fosters utilization of faster representations,...
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QUEUE I
WydarzeniaFaculty of Applied Physics and Mathematics of Gdańsk Tech invites international students to the next summer school - Quantum and Molecules I (QUEUE I), organized within the ScienceApp project.
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Dimensionality-Reduced Antenna Modeling with Stochastically Established Constrained Domain
PublikacjaOver the recent years, surrogate modeling methods have become increasingly widespread in the design of contemporary antenna systems. On the one hand, it is associated with a growing awareness of numerical optimization, instrumental in achieving high-performance structures. On the other hand, considerable computational expenses incurred by massive full-wave electromagnetic (EM) analyses, routinely employed as a major design tool,...
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Recent advances in high-frequency modeling by means of domain confinement and nested kriging
PublikacjaDevelopment of modern high-frequency components and circuits is heavily based on full-wave electromagnetic (EM) simulation tools. Some phenomena, although important from the point of view of the system performance, e.g., EM cross-coupling effects, feed radiation in antenna arrays, substrate anisotropy, cannot be adequately accounted for using simpler means such as equivalent network representations. Consequently, the involvement...
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A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks
PublikacjaThe visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases...
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Rapid Design Centering of Multi-Band Antennas Using Knowledge-Based Inverse Models and Response Features
PublikacjaAccounting for manufacturing tolerances as well as uncertainties concerning operating conditions and material parameters is one of the important yet often neglected aspects of antenna development. Appropriate quantification of uncertainties allows for estimating the fabrication yield but also to carry out robust design (e.g., yield maximization). For reliability reasons, statistical analysis should be executed at the accuracy level...
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Vident-real: an intra-oral video dataset for multi-task learning
Dane BadawczeWe introduce Vident-real, a large dataset of 100 video sequences of intra-oral scenes from real conservative dental treatments performed at the Medical University of Gdańsk, Poland. The dataset can be used for multi-task learning methods including:
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Webquest- dobra praktyka w e-Learningu
PublikacjaW dobie informatyzacji i pokonywania barier wdrażania e-technologii na uczelniach wyższych uważa się, że jedną z najczęściej stosowanych aktywizujących technik nauczania wśród nauczycieli akademickich jest metoda projektu (ang. project-based learning). W niniejszym opracowaniu proponuje się zastosowanie w procesie edukacji na wyższej uczelni, metody webquest. Jest ona dużo rzadziej stosowana w praktyce. Opracowano ją w oparciu...
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Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublikacjaLine heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the...
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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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Platforma edX - nowe podejście do kursów online
PublikacjaWspółczesne metody nauczania na odległość zmieniają się dynamicznie. Powstają światowe konsorcja podejmujące starania zapewnienia dostępu do edukacji na najwyższym poziomie z wykorzystaniem Internetu. Jedną z takich prób jest platforma edX. Jej rozwój zapoczątkowały niemal 2 lata temu MIT i Harvard. Obecnie zespół liczy już 30 uczelni z całego świata. Renoma ośrodków naukowych biorących udział w projekcie przyciągnęła już ponad...
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sp2-rich dendrite-like carbon nanowalls as effective electrode for environmental monitoring of explosive nitroaromatic
PublikacjaNitroaromatic 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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Rapid Design of 3D Reflectarray Antennas by Inverse Surrogate Modeling and Regularization
PublikacjaReflectarrays (RAs) exhibit important advantages over conventional antenna arrays, especially in terms of realizing pencil-beam patterns without the employment of the feeding networks. Unfortunately, microstrip RA implementations feature narrow bandwidths, and are severely affected by losses. A considerably improved performance can be achieved for RAs involving grounded dielectric layers, which are also easy to manufacture using...
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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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Performance-Based Nested Surrogate Modeling of Antenna Input Characteristics
PublikacjaUtilization 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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Graph Representation Integrating Signals for Emotion Recognition and Analysis
PublikacjaData 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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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublikacjaTreatment 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
PublikacjaThe 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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Feature Weighted Attention-Bidirectional Long Short Term Memory Model for Change Detection in Remote Sensing Images
PublikacjaIn 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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Leszek Ziemczonek dr
OsobyUniversity education 1973-1978 – Nicolaus Copernicus University in Toruń, University of Gdańsk in Gdańsk, Mathematical Physics, M. Sc. 1979 – Diploma of Postgraduate Studies, Pedagogics 1989 – Institute of Physics, Polish Academy of Sciences in Warsaw, Theoretical Physics, Ph. D. 2010-2012 – Diploma of Postgraduate Studies, Mathematics Training: · 09.1983 – Trieste (Italy) – International Centre for Theoretical Physics...