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Search results for: learning about natural phenomena
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn 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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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublicationHuman-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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Szymon Zaporowski mgr inż.
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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
PublicationThe 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
PublicationNowadays, 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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Integrating Statistical and Machine‐Learning Approach for Meta‐Analysis of Bisphenol A‐Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival
PublicationBisphenols are important environmental pollutants that are extensively studied due to different detrimental effects, while the molecular mechanisms behind these effects are less well understood. Like other environmental pollutants, bisphenols are being tested in various experimental models, creating large expression datasets found in open access storage. The meta‐analysis of such datasets is, however, very complicated for various...
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Leszek Ziemczonek dr
PeopleUniversity 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...
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Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublicationThe use of metal halide perovskites in photocatalytic processes has been attempted because of their unique optical properties. In this work, for the first time, Pb-free Bi-based perovskites of the Cs3Bi2X9 type (X = Cl, Br, I, Cl/Br, Cl/I, Br/I) were synthesized and subjected to comprehensive morphological, structural, and surface analyses, and photocatalytic properties in the phenol degradation reaction were examined. Furthermore,...
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Edyta Gołąb-Andrzejak dr hab.
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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CHEMISTRY OF NATURAL COMPOUNDS
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A natural deep eutectic solvent - protonated L-proline-xylitol - based stationary phase for gas chromatography
PublicationThe paper presents a new kind of stationary phase for gas chromatography based on deep eutectic solvents (DES) in the form of a mixture of L-proline (protonated with hydrochloric acid) as a hydrogen bond acceptor (HBA) and xylitol as a hydrogen bond donor (HBD) in a molar ratio of HBA:HBD 5:1. DES immobilized on a silanized chromatographic support was tested by gas chromatography (GC) in order to determine its resolving power for...
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Impact of Climate Change on Water Sources and River‐Floodplain Mixing in the Natural Wetland Floodplain of Biebrza River
PublicationThe origins of river and floodplain waters (groundwater, rainfall, and snowmelt) and their extent during overbank flow events strongly impact ecological processes such as denitrification and vegetation development. However, the long-term sensitivity of floodplain water signatures to climate change remains elusive. We examined how the integrated hydrological model HydroGeoSphere and the Hydraulic Mixing-Cell method could help us...
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Possibility of thermal imaging use in studies of natural convection heat transfer on the example of an isothermal vertical plate
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Phenolics occurrence in surface water of the Dniester river basin (West Ukraine): natural background and industrial pollution
PublicationW pracy przedstawiono wyniki badań poziomu fenoli w wodach rzecznych pochodzących ze zlewni Dniestru. Określono zarówno poziom tła naturalnego tych związków w wodzie rzecznej (na poziomie 0,012 mg/l) jak i poziom stężeń tych związków w części zlewni podlegającej antropopresji. Główne źródła emisji antropogenicznej są związane z przemysłem petrochemicznym. Poziom stężenia sumy fenoli w wodzie rzecznej na obszarach objętych wpływem...
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Simultaneous determination of non-steroidal anti-inflammatory drugs and natural estrogens in the mussels Mytilus edulis trossulus
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Folic acid-conjugated mesoporous silica particles as nanocarriers of natural prodrugs for cancer targeting and antioxidant action
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Effect of Natural Aging of Biochar on Soil Enzymatic Activity and Physicochemical Properties in Long-Term Field Experiment
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Natural Quercetin Analogues Modulate Oxidative Stress Tolerance and Increase Lifespan Extension of S. cerevisiae ( proceeding)
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Synthesis and structural characterization of novel 2-benzimidazolylthioureas: adducts of natural isothiocyanatesand 2-amino-1-methylbenzimidazole
PublicationNa drodze syntezy chemicznej uzyskano addukty naturalnych izotiocyjanianów - alilu, benzylu i fenyloetylu i 2-amino-1-metylobenzoimidazolu. W następstwie optymalizacji warunków reakcji, poszczególne 2-benzimidazolilotiomoczniki otrzymano produkty z umiarkowanymi wydajnościami. Strukturę molekularną i krystaliczną produktów scharakteryzowano przy użyciu metod spektroskopowych i X-ray. Analiza uzyskanych widm pozwoliła stwierdzić,...
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Possibility of thermal imaging use in studies of natural convection heat transfer on the example of an isothermal vertical plate.
PublicationA new method of infrared (IR) camera use in convective heat transfer studies has been presented. Until now, IR cameras were utilized for temperature field visualizations of flat heated surfaces of solid objects only. Because liquids and gasses do not emit radiation in the infrared range of wave lengths, detection of temperature field in the air was conducted with the use of plastic mesh, which, after heating by hot air, emits infrared...
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Seawater intrusion due to pumping mitigated by natural freshwater flux: a case study in Władysławowo, northern Poland
PublicationThe paper presents a case study of seawater intrusion into a coastal aquifer, caused by a groundwater intake located close to the seashore in Władysławowo, northern Poland. Evolution of the basic hydrogeochemical parameters for the 50-year period from 1964 to 2014 indicates progressing encroachment of saline seawater into the aquifer. However, the spatial pattern of salinity was influenced by the variability of hydraulic gradient...
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Heavy metal accumulation and distribution in Phragmites australis seedlings tissues originating from natural and urban catchment
PublicationThe retention of heavy metal (HM) was studied in root and rhizomes (BLG), stems (ST), and leaves (LF) of Phragmites australis (common reed) seedlings collected from different locations, differing in the scale of anthropogenic interference. The analysis includes the reference samples of sediments in uncontaminated lake Garczonki and contaminated roadside ditch in Cieplewo. The concentrations of Zn, Cu, Pb, Cd, Ni, and Cr were analyzed...
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Ammonium sorption from aqueous solutions by the natural zeolite Transcarpathian clinoptilolite studied under dynamics conditons
PublicationPrzeprowadzone badania z wykorzystaniem wodnych roztworów modelowych amoniaku mogą stanowić podstawę do następujących wniosków:- maksymalna pojemność sorpcyjna klinoptylolitu w stosunku do jonów NH4+ w warunkach dynamicznych jest zdecydowanie wyższa niż w warunkach statycznych,- proces usuwania jonów amonowych podlega intensyfikacji w przypadku zastosowania frakcji zeolitu o mniejszej średnicy ziaren,- istotną rolę w procesie sorpcji...
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Ammonium removal from aqueous solution by natural zeolite, Transcarpathian mordenite, kinetics, equilibrium and column tests.
PublicationOpisano wyniki badań procesu usuwania jonów amonowych z wodnych roztworów modelowych z wykorzystaniem mordenitu-naturalnego zeolitu (w postaci surowej i po odpowiedniej wstępnej obróbce) zarówno w warunkach statycznych jak i dynamicznych. Oszacowano pojemność jonowymienną w stosunku do jonów amonowych (1,64 meq/g) w przypadku, gdy stężenie początkowe analitu było na poziomie 1000 mg/l. Sprawdzono również wpływ na przebieg procesu...
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Influence of input data on airflow network accuracy in residential buildings with natural wind - and stack - driven ventilation.
PublicationW artykule omówiono wpływ danych wejściowych na dokładność modelu przepływu sieciowego powietrza w budynkach mieszkalnych z naturalną i kominową wentylacją. Zastosowano połączony model AFN-BES. Wyniki numeryczne omówiono dla 8 różnych przypadków z różnymi danymi ciśnienia wiatru. Wyniki pokazały, że ogromny wpływ danych wejściowych dotyczących ciśnienia wiatru na wyniki numeryczne.
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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublicationIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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E-LEARNING NA POLITECHNICE GDAŃSKIEJ - HISTORIA ROZWOJU W LATACH 1995-2020
PublicationInternet oraz kształcenie oparte na wykorzystaniu e-technologii stały się nieodłącznym elementem edukacji. Artykuł przedstawia zarys historii rozwoju e-learningu na Politechnice Gdańskiej, przykładowe rozwiązania technologiczne, elementy tworzenia struktur organizacyjnych oraz związanych z legislacją, a także wybrane projekty wykorzystujące szeroko pojęte e-technologie w edukacji akademickiej realizowanej na Uczelni
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Deep learning model for automated assessment of lexical stress of non-native english speakers
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Machine Learning for Control Systems Security of Industrial Robots: a Post-covid-19 Overview
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The Effectiveness of Using a Pretrained Deep Learning Neural Networks for Object Classification in Underwater Video
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Edu Inspiracje WZiE: Active Learning, czyli o mocy aktywnego przetwarzania informacji
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Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines
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Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)
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Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
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Experimental Evaluation of the Agent-Based Population Learning Algorithm for the Cluster-Based Instance Selection
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublicationTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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Open source learning management systems at civil engineering and environmental department: TeleCAD and Moodle.
PublicationW rozdziale zaprezentowano dwa systemy zarządzania kształceniem, służące do przygotowania i prowadzenia e-kursów. Pierwszy z nich TeleCAD został opracowany w ramach projektu Leonardo da Vinci (1998-2001). Ostanie użycie systemu miało miejsce w roku akademickim 2003/2004 i był on wykorzystany w projekcie CURE (V Program Ramowy, 2003-2006). W roku 2003 dzięki wsparciu projektu Leonardo da Vinci EMDEL (2001-2005) Centrum Edukacji...
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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Social learning and knowledge flows in cluster initiatives, In: Sanz S.C., Blanco F.P., Urzelai B. (Eds). Human and Relational Resources (pp. 44-45). the 4th International Conference on Clusters and Industrial Districts CLUSTERING, University of Valencia, Spain, May 23–24 (ISBN: 978-84-09-11926-4).
PublicationPurpose – The purpose of the paper is to explore how learning manifests and knowledge flows in cluster initiatives (CIs) due to interactions undertaken by their members. The paper addresses the research question of how social learning occurs and knowledge flows in CIs. Design/methodology/approach – The qualitative study of four cluster initiatives helped to identify various symptoms of social learning and knowledge flows in...
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Justyna Signerska-Rynkowska dr inż.
PeopleI am currently an assistant professor (adjunct) at Gdansk University of Technology (Department of Differential Equations and Mathematics Applications). My scientific interests include dynamical systems theory, chaos theory and their applications to modeling of biological phenomena, especially to neurosciences. In June 2013 I completed PhD in Mathematics at the Institute of Mathematics of Polish Academy of Sciences (IMPAN) (thesis...
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Effect of Co-Encapsulated Natural Antioxidants with Modified Starch on the Oxidative Stability of β-Carotene Loaded within Nanoemulsions
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Removal of organic compounds from natural underground water in sorption and sono-sorption processes on selected activated carbons
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Open tools for benthic habitat mapping: study of seagrass (posidonia oceanica) in the natural park of Cabo de Gata
PublicationW artykule przedstawiono koncepcję wykorzystania otwartego oprogramowania dostępnego poprzez interfejs WWW służącego do analizy materiału zebranego przez echosondy jednowiązkowe i sonary boczne pod kątem klasyfikacji rozmiaru wystąpienia traw morskich Posidonia Oceanica. Jako przyklad przedstawiono analizę danych z sonaru bocznego zebranych w zatoce Cabo de Gata.
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Effective Targeting of Colon Cancer Cells with Piperine Natural Anticancer Prodrug Using Functionalized Clusters of Hydroxyapatite Nanoparticles
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Three-dimensional hierarchical porous carbon derived from natural resources for highly efficient treatment of polluted water
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