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Wyniki wyszukiwania dla: BLENDED E-LEARNING
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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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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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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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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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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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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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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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Jacek Krenz dr hab. inż. arch.
OsobyUr. 11 maja 1948 w Poznaniu – polski architekt, malarz, profesor Wydziału Architektury Politechniki Gdańskiej, Wydziału Architektury, Inżynierii i Sztuki Sopockiej Szkoły Wyższej, W latach 70. członek Grupy Kadyńskiej, skupiającej plastyków i architektów związanych z Międzynarodowymi Plenerami "Ceramika dla architektury" w Kadynach. W roku 1980 uzyskał stopień doktora, a w 1997 – doktora habilitowanego. Prowadzi badania na temat...
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e-Technologie w Kształceniu Inżynierów
WydarzeniaPolitechnika Gdańska i Akademia Górniczo-Hutnicza organizują VI Krajową Konferencję "e-Technologie w Kształceniu Inżynierów”. Celem konferencji jest popularyzacja najnowszych technologii w edukacji inżynierskiej.
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Gdansk 2020, Grunwaldzka (E) street - video data - pedestrian, bicycles, vehicles
Dane BadawczeGdansk 2020, Grunwaldzka (E) street - video data - pedestrian, bicycles, vehicles
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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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Mesh-based internet on the Baltic sea for improving e-navigation services. A case study
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Traditional smoking and e-smoking among medical students and students-athletes – popularity and motivation
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Phononic engineering of silicon using “dots on the fly” e-beam lithography and plasma etching
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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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Emilia Miszewska dr inż.
OsobyEmilia Miszewska urodziła się w 1986 roku w Gdańsku. Ukończyła Szkołę Podstawową nr 17 w Gdańsku z klasami sportowymi o profilu pływanie oraz Liceum Sportowe nr 11 im. Janusza Kusocińskiego w Gdańsku. W 2005 roku rozpoczęła jednolite studia magisterskie na Wydziale Inżynierii Lądowej i Środowiska, które ukończyła w roku 2011, broniąc pracę dyplomową pt. „Analiza i opracowanie wytycznych zabezpieczenia pożarowego oraz planu...
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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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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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Koncepcja zapewnienia interoperacyjności w rozproszonych systemach uczelnianychW : Perspektywy Rozwoju e-Uczelni w Kontekście Globalnej Informatyzacji; - e-uczelnia, konferencja krajowa; 14-15 maja 2009, Gdańsk. - [skrypt prezentacji]
Publikacja...
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UV-Vis-Induced Degradation of Phenol over Magnetic Photocatalysts Modified with Pt, Pd, Cu and Au Nanoparticles
PublikacjaThe combination of TiO2 photocatalyst and magnetic oxide nanoparticles enhances the separation and recoverable properties of nanosized TiO2 photocatalyst. Metal-modified (Me = Pd, Au, Pt, Cu) TiO2/SiO2@Fe3O4 nanocomposites were prepared by an ultrasonic-assisted sol-gel method. All prepared samples were characterized by X-ray powder diffraction (XRD) analysis, Brunauer-Emmett-Teller (BET) method, X-ray photoelectron spectroscopy...
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Copper(I) halide cluster-based coordination polymers modulated by chiral ditopic dithiodianthranilide ligands: synthesis, crystal structure and photoluminescence
PublikacjaReaction of copper(I) halides with chiral dithiodianthranilidesmdtaandbdtaafforded polymeric complexeswhere polynuclear CuX clusters were linked together by ditopic bridging ligands into 1D chains or 2D layerstructures. In the case of racemic ligands double stranded chain polymers were formed where the Cu4X4(X = I or Br) cores are connected by enantiomeric pairs of the ditopic ligands. In contrast, a homochiralmdtaligand created...
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Amygdalin: Toxicity, Anticancer Activity and Analytical Procedures for Its Determination in Plant Seeds
PublikacjaAmygdalin (D-Mandelonitrile 6-O--D-glucosido--D-glucoside) is a natural cyanogenic glycoside occurring in the seeds of some edible plants, such as bitter almonds and peaches. It is a medically interesting but controversial compound as it has anticancer activity on one hand and can be toxic via enzymatic degradation and production of hydrogen cyanide on the other hand. Despite numerous contributions on cancer cell lines, the clinical...
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A palatal prosthesis from archaeological research in the St Francis of Assisi church in Cracow (Poland)
PublikacjaThe hard palate is a septum that not only prevents food from entering between the oral and nasal cavity, but also plays an important role during breathing or speech. The presence of cavities within it negatively affects the comfort of life of people with this type of impairment. Hence, in the literature one can find examples of the use of hard palate prostheses to restore the separation between the nasal and oral cavity. During...
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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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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublikacjaThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublikacjaNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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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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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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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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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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Nondestructive Chicken Egg Fertility Detection Using CNN-Transfer Learning Algorithms
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Embracing ChatGPT for Enhanced English as a Foreign Language Learning and Teaching: Teachers’ Attitudes
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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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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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublikacjaHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublikacjaIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Development and Optimization of Deep Learning Systems for MRI Analysis in Alzheimer's Disease Monitoring
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublikacjaThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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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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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors 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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Czy e-demokracja i rozwiązania znane ze świata biznesu są właściwymi kierunkami zmian politycznych w Polsce?
PublikacjaCEL NAUKOWY: Celem artykułu jest przedstawienie wybranych problemów systemu demokratycznego w Polsce oraz zaproponowanie kierunków rozwoju, poprawiających jego działanie. PROBLEM i METODY BADAWCZE: Problem badawczy dotyczył sprawdzenia czy wdrożenie założeń nowoczesnych koncepcji organizacyjnych i rozwiązań teleinformatycznych może przyczynić się do sprawniejszego sprawowania demokratycznej władzy, a także podwyższenia...
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IM - e-test 2018/19
Kursy Online -
Szablon e-Kursu dla KIDiT
Kursy OnlineNazwa kursu (2020/2021), kurs przeznaczony dla: Nazwa i kod przedmiotu: Nazwa przedmiotu zgodna z moja PG (np. PG_00044591) Kierunek studiów: Transport Poziom kształcenia: I stopnia - inżynierskie Rok akademicki realizacji przedmiotu: 2020/2021 Forma studiów: stacjonarne Rok studiów: 2 Semestr: 4 (letni)