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Learning from Imbalanced Data Using Over-Sampling and the Firefly Algorithm
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Deep learning approach for delamination identification using animation of Lamb waves
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Deep learning super-resolution for the reconstruction of full wavefield of Lamb waves
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OmicSelector: automatic feature selection and deep learning modeling for omic experiments
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A Prototype of Educational Agent in Distance Learning Environment - Virtual Student Assistant
PublikacjaW zdalnym nauczaniu pojawia się wiele systemów wspierających, z których niezwykle ciekawym przykładem są agenty edukacyjne. Wśród wielu rodzajów agentów edukacyjnych wyróżnia się osobistych asystentów, których rolą jest organizacyjna pomoc osobie zdobywającej wiedzę. Artykuł jest poświęcony zaimplementowanemu na Wydziale ETI Politechniki Gdańskiej prototypowi agenta edukacyjnego o nazwie WAS (Wirtualny Asystent Studenta). Pokazana...
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The Role of Dopaminergic Genes in Probabilistic Reinforcement Learning in Schizophrenia Spectrum Disorders
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Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publikacjaconvolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...
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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
PublikacjaGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Deep learning approach on surface EEG based Brain Computer Interface
PublikacjaIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublikacjaThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublikacjaObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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A Note on Knowledge Management Education: Towards Implementing Active Learning Methods
PublikacjaKnowledge Management as an area of education is still a big challenge for teachers and practitioners. Nevertheless, there are several useful teaching methods in active education, especially oriented towards courses where innovation and delivering dynamic knowledge are critical. The goal of the paper is to present and discuss criteria relevant in the selection of active educational methods supporting knowledge management courses....
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Analysis of network infrastructure and QoS requirements for modern remote learning systems.
PublikacjaW referacie przedstawiono różne modele zdalnego nauczania. Podjęto próbę oceny wymagań nakładanych na infrastrukturę sieci. Ponadto przedstawiono mechanizmy QoS spotykane w sieciach teleinformatycznych oraz dokonano oceny możliwości ich współpracy w systemach edukacji zdalnej
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Developing ICT-rich lifelong learning opportunities trough EU-projects.
PublikacjaArtykuł opisuje doświadczenia Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej od 1997 roku we wdrażaniu kształcenia na odległość. Głównym zadaniem CEN PG jest tworzenie dostępu do materiałów, skryptów, kursów i środowiska internetowego w sieciach LAN i WAN. Udostępniane moduły kursowe zostały opracowane głównie w międzynarodowych zespołach projektowych w wyniku realizowanych unijnych programów Leonardo da Vinci, Socrates...
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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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Different Ways to Apply a Measurement Instrument of E-Nose Type to Evaluate Ambient Air Quality with Respect to Odour Nuisance in a Vicinity of Municipal Processing Plants
PublikacjaThis review paper presents different ways to apply a measurement instrument of e-nose type to evaluate ambient air with respect to detection of the odorants characterized by unpleasant odour in a vicinity of municipal processing plants. An emphasis was put on the following applications of the electronic nose instruments: monitoring networks, remote controlled robots and drones as well as portable devices. Moreover, this paper presents...
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Minimization of a ship's magnetic signature under external field conditions using a multi-dipole model
PublikacjaThe paper addresses the innovative issue of minimizing the ship's magnetic signature under any external field conditions, i.e., for arbitrary values of ambient field modulus and magnetic inclination. Varying values of the external field, depending on the current geographical location, affect only the induced part of ship's magnetization. A practical problem in minimizing the ship signature is separating permanent magnetization...
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Comparing Apples and Oranges: A Mobile User Experience Study of iOS and Android Consumer Devices
PublikacjaWith the rapid development of wireless networks and the spread of broadband access around the world, the number of active mobile user devices continues to grow. Each year more and more terminals are released on the market, with the smartphone being the most popular among them. They include low-end, mid-range, and of course high-end devices, with top hardware specifications. They do vary in build quality, utilized type of material,...
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THE METHOD OF ANALYSIS OF DAMAGE REINFORCED CONCRETE BEAMS USING TERRESTRIAL LASER SCANNING
PublikacjaThe authors present an analysis of the possibility to assess deformations and mode of failure of R-C beams using terrestrial laser scanning. As part of experiments carried out at the Regional Laboratory of Construction (at Gdansk University of Technology), reinforced concrete beams were subjected to destruction by bending and by shear. The process of press impact on the reinforced concrete beam was recorded using terrestrial laser...
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AN ENERGY APPROACH TO THE FATIGUE LIFE OF SHIP PROPULSION SYSTEMS
PublikacjaThe conducted research investigations aimed to carry out an identification of the constructional materials fatigue state of the ship propulsions’ rotational mechanical units for diagnostic purposes. The fatigue cracks of the elements transmitting mechanical energy streams from the propulsion engines to the ship propellers or to the generators of the ship’s electric power station stand for a primary reason for the secondary, usually...
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POSSIBILITIES OF ELECTRICAL ENERGY GENERATION IN PHOTOVOLTAIC SYSTEMS INSTALLED IN CENTRAL EUROPE
PublikacjaNowadays, fossil fuels are the main sources of energy from which electricity is obtained. But these sources will not last forever, so in due course renewable energies will have to replace them in this role. One of these new sources is solar energy. To generate electricity from sunlight, solar (photovoltaic - PV) cells and modules are used. The increasing interest in PV cells and modules worldwide is due mainly to the fact that...
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Patch size setup and performance/cost trade-offs in multi-objective EM-driven antenna optimization using sequential domain patching
PublikacjaPurpose This paper aims to assess control parameter setup and its effect on computational cost and performance of deterministic procedures for multi-objective design optimization of expensive simulation models of antenna structures. Design/methodology/approach A deterministic algorithm for cost-efficient multi-objective optimization of antenna structures has been assessed. The algorithm constructs a patch connecting extreme Pareto-optimal...
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On deterministic procedures for low-cost multi-objective design optimization of miniaturized impedance matching transformers
PublikacjaPurpose This paper aims to investigate deterministic strategies for low-cost multi-objective design optimization of compact microwave structures, specifically, impedance matching transformers. The considered methods involve surrogate modeling techniques and variable-fidelity electromagnetic (EM) simulations. In contrary to majority of conventional approaches, they do not rely on population-based metaheuristics, which permit lowering...
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Analysis and Risk Evaluation on the Case of Alteration, Revitalization and Conversion of a Historic Building in Gdańsk
PublikacjaEach investment plan, including the one concerning a building, is exposed to the consequences of various types of threats taking place. Therefore, in the case of some large-scale, atypical and complicated building ventures, some actions included in the procedure of risk management should be taken. This will allow for the risk to be eliminated or limited. While preparing a building venture, an investor does not possess full information...
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublikacjaTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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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
PublikacjaNitrous 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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Investigating the disease- modifying properties of sclerotiorin in Alzheimer's therapy using acetylcholinesterase inhibition
PublikacjaAlzheimer's disease (AD) is a progressive neurodegenerative disorder caused due to the damage and loss of neurons in specific brain regions. It is the most common form of dementia observed in older people. The symptoms start with memory loss and gradually cause the inability to speak and do day-to-day activities. The cost of caring for those affected individuals is huge and is probably beyond most developing countries capability....
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Computational analysis of an infinite magneto-thermoelastic solid periodically dispersed with varying heat flow based on non-local Moore–Gibson–Thompson approach
PublikacjaIn this investigation, a computational analysis is conducted to study a magneto-thermoelastic problem for an isotropic perfectly conducting half-space medium. The medium is subjected to a periodic heat flow in the presence of a continuous longitude magnetic field. Based on Moore–Gibson–Thompson equation, a new generalized model has been investigated to address the considered problem. The introduced model can be formulated by combining...
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Tuning Ferulic Acid Solubility in Choline-Chloride- and Betaine-Based Deep Eutectic Solvents: Experimental Determination and Machine Learning Modeling
PublikacjaDeep eutectic solvents (DES) represent a promising class of green solvents, offering particular utility in the extraction and development of new formulations of natural compounds such as ferulic acid (FA). The experimental phase of the study undertook a systematic investigation of the solubility of FA in DES, comprising choline chloride or betaine as hydrogen bond acceptors and six different polyols as hydrogen bond donors....
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublikacjaThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Structural Factors Affecting Cytotoxic Activity of (E)-1-(Benzo[d ][1,3]oxathiol-6-yl)-3-phenylprop-2-en-1-one Derivatives
PublikacjaDerivatives of (E)-1-(5-alkoxybenzo[d][1,3]oxathiol-6-yl)-3-phenylprop-2-en-1-one (1) demonstrated exceptionally high in vitro cytotoxic activity, with IC50 values of the most active derivatives in the nanomolar range. To identify structural fragments necessary for the activity, several analogs deprived of selected fragments were prepared, and their cytotoxic activity was tested. It was found that the activity depends on combined effects...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublikacjaRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Clinical Course and Severity of COVID-19 in 940 Infants with and without Comorbidities Hospitalized in 2020 and 2021: The Results of the National Multicenter Database SARSTer-PED
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Robust-adaptive dynamic programming-based time-delay control of autonomous ships under stochastic disturbances using an actor-critic learning algorithm
PublikacjaThis paper proposes a hybrid robust-adaptive learning-based control scheme based on Approximate Dynamic Programming (ADP) for the tracking control of autonomous ship maneuvering. We adopt a Time-Delay Control (TDC) approach, which is known as a simple, practical, model free and roughly robust strategy, combined with an Actor-Critic Approximate Dynamic Programming (ACADP) algorithm as an adaptive part in the proposed hybrid control...
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Traditional smoking and e-smoking among medical students and students-athletes – popularity and motivation
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Avaliação das propriedades de impulso e freqüência em sistemas de aterramento
PublikacjaBezpieczne uziemienia projektowane dla celów ochrony odgromowej powinny odprowadzać prądy wyładowań atmosferycznych przy możliwie niewielkim spadku napięcia. Dla oceny ich skuteczności należy brać pod uwagę nie tylko ich rezystancję, lecz przede wszystkim impedancję. W pracy porównano wyniki symulacji komputerowych i pomiarów na obiektach rzeczywistych impedancji uziemień mierzonych przy wymuszeniach udarowych oraz wysokoczęstotliwościowych.
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Mesh-based internet on the Baltic sea for improving e-navigation services. A case study
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Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublikacjaThe awareness and practical benefits of behavioral modeling methods have been steadily growing in the antenna engineering community over the last decade or so. Undoubtedly, the most important advantage thereof is a possibility of a dramatic reduction of computational expenses associated with computer-aided design procedures, especially those relying on full-wave electromagnetic (EM) simulations. In particular, the employment of...
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images
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Improved estimation of dynamic modulus for hot mix asphalt using deep learning
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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Effects of mutual learning in physical education to improve health indicators of Ukrainian students
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Simulation Method for Scheduling Linear Construction Projects Using the Learning– Forgetting Effect
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Comparison of Deep Neural Network Learning Algorithms for Mars Terrain Image Segmentation
PublikacjaThis paper is dedicated to the topic of terrain recognition on Mars using advanced techniques based on the convolutional neural networks (CNN). The work on the project was conducted based on the set of 18K images collected by the Curiosity, Opportunity and Spirit rovers. The data were later processed by the model operating in a Python environment, utilizing Keras and Tensorflow repositories. The model benefits from the pretrained...
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublikacjaTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems
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Learning from Imbalanced Data Streams Based on Over-Sampling and Instance Selection
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Machine Learning and data mining tools applied for databases of low number of records
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