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Derecho Evolving from a Mesocyclone—A Study of 11 August 2017 Severe Weather Outbreak in Poland: Event Analysis and High-Resolution Simulation
PublikacjaThis study documents atmospheric conditions, development, and evolution of a severe weather outbreak that occurred on 11 August 2017 in Poland. The emphasis is on analyzing system morphology and highlighting the importance of a mesovortex in producing the most significant wind damages. A derecho-producing mesoscale convective system (MCS) had a remarkable intensity and was one of the most impactful convective storms in the history...
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On the Role of Polarimetric Decomposition and Speckle Filtering Methods for C-Band SAR Wetland Classification Purposes
PublikacjaPrevious wetlands studies have thoroughly verified the usefulness of data from synthetic aperture radar (SAR) sensors in various acquisition modes. However, the effect of the processing parameters in wetland classification remains poorly explored. In this study, we investigated the influence of speckle filters and decomposition methods with different combinations of filter and decomposition windows sizes on classification accuracy....
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Study on the Positioning Accuracy of the GNSS/INS System Supported by the RTK Receiver for Railway Measurements
PublikacjaCurrently, the primary method for determining the object coordinates is positioning using Global Navigation Satellite Systems (GNSS) supported by Inertial Navigation Systems (INS). The main goal of this solution is to ensure high positioning availability, particularly when access to satellite signals is limited (in tunnels, areas with densely concentrated buildings and in forest areas). The aim of this article is to determine whether...
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A Data-Driven Comparative Analysis of Machine-Learning Models for Familial Hypercholesterolemia Detection
PublikacjaThis study presents an assessment of familial hypercholesterolemia (FH) probability using different algorithms (CatBoost, XGBoost, Random Forest, SVM) and its ensembles, leveraging electronic health record data. The primary objective is to explore an enhanced method for estimating FH probability, surpassing the currently recommended Dutch Lipid Clinic Network (DLCN) Score. The models were trained using the largest Polish cohort...
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Assessing climate change threats and urbanization impacts on surface runoff in Gdańsk (Poland): insights from remote sensing, machine learning and hydrological modeling
PublikacjaThis study investigates the impacts of Land Use/Land Cover (LULC) changes and climate change on surface runoff in Gdańsk, Poland, which is crucial for local LULC planning and urban flood risk management. The analysis employs two primary methodologies: remote sensing and hydrological modeling. Remote sensing was conducted using Google Earth Engine and Land Change Modeler in IDRISI Terrset software to analyze historical (1985–2022)...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublikacjaWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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Comparison of Absorbed and Intercepted Fractions of PAR for Individual Trees Based on Radiative Transfer Model Simulations
PublikacjaThe fraction of absorbed photosynthetically active radiation (fAPAR) is a key parameter for estimating the gross primary production (GPP) of trees. For continuous, dense forest canopies, fAPAR, is often equated with the intercepted fraction, fIPAR. This assumption is not valid for individual trees in urban environments or parkland settings where the canopy is sparse and there are well-defined tree crown boundaries. Here, the distinction...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Ecological and Health Effects of Lubricant Oils Emitted into the Environment
PublikacjaLubricating oils used in machines with an open cutting system, such as a saw or harvester, are applied in forest areas, gardening, in the household, and in urban greenery. During the operation of the device with an open cutting system, the lubricating oil is emitted into the environment. Therefore, the use of an oil base and refining additives of petroleum origin in the content of lubricants is associated with a negative impact...
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Estimation of groundwater recharge in a shallow sandy aquifer using unsaturated zone modeling and water table fluctuation method
PublikacjaQuantification of groundwater recharge is one of the most important issues in hydrogeology, especially in view of the ongoing changes in climate and land use. In this study, we use numerical models of 1D vertical flow in the vadose zone and the water table fluctuation (WTF) analysis to investigate local-scale recharge of a shallow sandy aquifer in the Brda outwash plain in northern Poland. We show that these two methods can be...
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THE METHOD OF MEASURING THE MEMBRANE COVER GEOMETRY USING LASER SCANNING AND SYNCHRONOUS PHOTOGRAMMETRY
PublikacjaThe authors present the experience and results of field studies carried out at the technical acceptance of Forest Opera (name in Polish: Opera Leśna) in Sopot (Poland). An unusual design of covering made in the form of “Sheerfill I” technical fabric membrane required spanned in the form of sails, required the use of terrestrial laser scanning. Such approach allowed for the fast and accurate record of the surface of individual panels...
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublikacjaThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
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Mikrofiltrowany koncentrat soku brzozowego jako innowacyjny, trwały środek spożywczy o wysokiej wartości odżywczej
PublikacjaIntroduction. The forest environment becomes an increasingly popular place of obtaining raw materials, and one of the most promising product is birch sap. The market for bottled birch sap in Poland is monotonous, relying exclusively on pasteurized, acidified and sweetened drinks. A chance to change this situation is to develop a birch sap concentrate obtained by reverse osmosis. It has a sweet taste desired by consumers and particularly...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublikacjaThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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Empirical analysis of tree-based classification models for customer churn prediction
PublikacjaCustomer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublikacjaThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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Environmental Role of Rime Chemistry at Selected Mountain Sites in Poland
PublikacjaThe results of field experiments on fog pollutantdeposition enhanced by local mountain climate, completed by thedendrochronological analysis of the forest response, are presentedin this paper. In spite of their low absolute altitude (1,000-1,600 ma.s.l), the Sudetes and the Silesian Beskid form a noticeable orographicbarrier for the airflow of the humid Atlantic air masses.This results in the increase of cloudiness and fog frequency...
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Total mercury and methylmercury (MeHg) in braised and crude Boletus edulis carpophores during various developmental stages
PublikacjaWe collected and processed Boletus edulis (King Bolete) carpophores grouped in four batches based on their developmental stage (button stage, young—white, large—white, and large—yellow). The study aimed, for the first time, to examine the B. edulis content and effect of braising and to estimate the intake of total mercury (THg) and methylmercury (MeHg) from a single meal based on whole (wet) weight (ww) and dry weight (dw). In...
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AGRARSENSE Inteligentne, cyfrowe komponenty i systemy dla rolnictwa i leśnictwa opartego na danych
ProjektyProjekt realizowany w Katedra Inżynierii Mikrofalowej i Antenowej zgodnie z porozumieniem KDT/2021/7/AGRARSENSE/2023
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AGRARSENSE Inteligentne, cyfrowe komponenty i systemy dla rolnictwa i leśnictwa opartego na danych
ProjektyProjekt realizowany w Katedra Inżynierii Mikrofalowej i Antenowej
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Aleksandra Giełdoń - Paszek dr hab.
OsobyDoktor habilitowany w dziedzinie nauk o sztuce, historyk sztuki. Studiowała historię sztuki na Wydziale Filozoficzno-Historycznym Uniwersytetu Jagiellońskiego w Krakowie. W roku 2002 na Wydziale Historycznym tejże uczelni uzyskała tytuł doktora nauk humanistycznych w zakresie nauk o sztuce na podstawie dysertacji: Malarstwo pejzażowe a szkolnictwo artystyczne w Polsce (do 1939 roku). W roku 2015 została doktorem habilitowanym w...