Search
Search results for: FOREST
-
High-resolution fire danger forecast for Poland based on the Weather Research and Forecasting Model
PublicationDue to climate change and associated longer and more frequent droughts, the risk of forest fires increases. To address this, the Institute of Meteorology and Water Management implemented a system for forecasting fire weather in Poland. The Fire Weather Index (FWI) system, developed in Canada, has been adapted to work with meteorological fields derived from the high-resolution (2.5 km) Weather Research and Forecasting (WRF) model....
-
Reflectance Measurements and iCone Calorimeter Burning Results of Charcoals Derived from Lake Żabińskie (North-Eastern Poland)
Open Research DataThe dataset presents the results of litter burning experiments using an iCone calorimeter to assess the flammability of the major tree species in the Lake Żabińskie catchment (NE Poland) and links this to the heat release during burning to understand the influence of fire and its effects on ecosystems. Samples of litter from Betula pendula, Pinus sylvestris,...
-
Mechanical testing of technical woven fabrics
PublicationThis article presents a review of technical fabrics testing methods used by the authors on the basis of their experience with research on properties of polytetrefluoroethylene-coated fabrics used for Forest Opera in Sopot (Poland). First, the different types of testing methods used for description of mechanical properties (uniaxial tensile tests, biaxial tensile tests and shear tests) of technical woven fabrics are described. The...
-
Vehicle classification based on soft computing algorithms
PublicationExperiments and results regarding vehicle type classification are presented. Three classes of vehicles are recognized: sedans, vans and trucks. The system uses a non-calibrated traffic camera, therefore no direct vehicle dimensions are used. Various vehicle descriptors are tested, including those based on vehicle mask only and those based on vehicle images. The latter ones employ Speeded Up Robust Features (SURF) and gradient images...
-
Nowe stanowiska Dicranum viride (Dicranaceae) w północno-wschodniej Polsce na tle jego rozmieszczenia w województwie podlaskim
PublicationDicranum viride (Sull. & Lesq.) Lindb. is a rare moss species from the Dicranaceae family. It is strictly protected in Poland and is considered as a relic of primeval forests. The plant is also included in Annex II of the Natura 2000 Habitats Directive and Annex I of the Bern Convention. Its populations are threatened by habitat fragmentation and economic use of forest...
-
Analysis of the cyclic load-unload-reload tests of VALMEX aged fabric
PublicationThe paper presents mechanical response of the VALMEX fabric during the cyclic loading-unloading and re-loading experiments. Two types of the aged material used for nearly 20 years as the roofing of the Forest Opera in Sopot (Poland) have been tested. The results have been separately obtained for the warp and fill di-rections. The comparative analysis has revealed that the material aged in service is more durable in the fill di-rection,...
-
‘Interspaces of the house | contextualized. our homes about ourselves’ cykl obrazów [w ramach:] międzynarodowa wystawa zbiorowa | ekspozycja hybrydowa Muestra de Arte Universitario - International MAU-I 2023, 'Interconexiones culturales: mirar cómo miras’
Publicationinterprzestrzenie domu: skontekstowane. nasze domy o nas samych W obrazie domu rodzinnego, z którym się utożsamiamy widzimy samych siebie. Tak też poznajemy naszych sąsiadów i ludzi z dalszych kręgów kulturowych. Sposób zamieszkiwania, tworzone schronienia współtworzą nasz wizerunek. Migracje, przemieszczenia, przenoszenie kulturowego wzorca domu i jego spasowywanie z realiami zastanymi tworzy przestrzeń innowacyjnych rozwiązań....
-
Basic evaluation of limb exercises based on electromyography and classification methods
PublicationSymptoms caused by cerebral palsy or stroke deprive a person partially or even completely of his ability to move. Nowadays we can observe more technologically advanced rehabilitation devices which incorporate biofeedback into the process of rehabilitation of such people. However, there is still a lack of devices that would analyse, assess, and control (independently or with limited support) specialised movement exercises. Here...
-
Preliminary estimation of groundwater recharge on Brda river outwash plain
PublicationEstimation of groundwater recharge is one of the most challenging subjects in hydrogeology. It is a critical factor influencing the pollution migration, assessment of aquifer vulnerability to contamination, small-scale groundwater budget calculation, modeling of nutrient cycling and detailed flow path calculations. In Poland an infiltration rate method is widely used, which depends on a system of rate coefficients referring to...
-
Technical fabrics in costruction of large scale roofs - numerical and experimental aspects
PublicationDesigning and construction of textile hanging roofs is the challenging subject for engineers. This type of structure needs geometrically and very often also physically non-linear calculations. Due to different behaviour of two families of threads (warp and weft), which during deformation can change the angle between their directions, they require special constitutive modelling. Also the loading of hanging roofs is very special....
-
Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation
PublicationTo date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging...
-
Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
-
Personal bankruptcy prediction using machine learning techniques
PublicationIt has become crucial to have an early prediction model that provides accurate assurance for users about the financial situation of consumers. Recent studies have focused on predicting corporate bankruptcies and credit defaults, not personal bankruptcies. Due to this situation, the present study fills the literature gap by comparing different machine learning algorithms to predict personal bankruptcy. The main objective of the...
-
Nowe stanowiska, rozmieszczenie i ochrona buławnika czerwonego Cephalanthera rubra (L.) Rich. (Orchidaceae) w Puszczy Augustowskiej (NE Polska)
PublicationCephalanthera rubra (L.) Rich. is a species under strict protection, very rare in the Suwałki region. In recent years, two sites were discovered in the Wigry National Park. The article presents a description of new localities and the distribution of the red helleborine in the Augustów Primeval Forest.
-
Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublicationIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...
-
A Machine Learning Approach for Estimating Overtime Allocation in Software Development Projects
PublicationOvertime planning in software projects has traditionally been approached with search-based multi-objective optimization algorithms. However, the explicit solutions produced by these algorithms often lack applicability and acceptance in the software industry due to their disregard for project managers' intuitive knowledge. This study presents a machine learning model that learns the preferred overtime allocation patterns from solutions...
-
Concentrations of heavy metals and PCBs in the tissues of European beavers (Castor fiber) captured in northeastern Poland
PublicationEuropean beavers (Castor fiber) from two regions were examined to identify exposure to persistent environmental contaminants. A reference group was comprised of six animals from the Forest Division of Srokowo, and an exposed group was comprised of five animals from the vicinity of a former military airport operated in 1918–1986—both from Warmia land in Poland. 137 Cs in beavers' muscles was considered negligible for the overall...
-
Accumulation of radioisotopes and heavy metals in selected species of mushrooms
PublicationSeven species of forest mushrooms from different regions of Poland (edible: Imleria badia, Cantharellus cibarius, Xerocomus subtomentosus, Suillus luteus and inedible by humans but being food for animals: Paxillus involutus, Tylopilus felleus and Russula emetica) were analyzed for radioisotope activity (Cs-137, K-40, Bi-214 and Pb-210) as well as concentrations of heavy metals (aluminum, chromium, cadmium, manganese, iron, lead,...
-
Ranking Speech Features for Their Usage in Singing Emotion Classification
PublicationThis paper aims to retrieve speech descriptors that may be useful for the classification of emotions in singing. For this purpose, Mel Frequency Cepstral Coefficients (MFCC) and selected Low-Level MPEG 7 descriptors were calculated based on the RAVDESS dataset. The database contains recordings of emotional speech and singing of professional actors presenting six different emotions. Employing the algorithm of Feature Selection based...
-
Data for meta-analysis on interversions reducing car use
Open Research DataThis dataset contains the results of a meta-analysis of reported interventions reducing car use. To standardise intervention effects reported in different scales, the Hedges’ g effect size measure was used (ratio of raw difference in samples’ means and pooled standard deviation). The standardised studies outcomes, along with overall outcome, were...
-
Sztuka jako wartość w procesie rewitalizacji przestrzeni miejskiej na przykładzie wybranych elewacji Drogi Królewskiej w Gdańsku
PublicationCelem niniejszej publikacji jest zwrócenie uwagi na rewitalizację przestrzeni miejskiej za pomocą elementów artystycznych, występujących w elewacjach architektonicznych Głównego Miasta w Gdańsku. Sztuka, która zaistniała w elewacjach odbudowywanego w latach pięćdziesiątych Głównego Miasta, dzięki gdańskim artystom, zaowocowała nowymi relacjami twórczymi pomiędzy architekturą a sztuką. Ze względu na ograniczone ramy artykułu, przedstawiamy...
-
Novel analytical method for detection of orange juice adulteration based on ultra-fast gas chromatography
PublicationThe food authenticity assessment is an increasingly important issue in food quality and safety. The application of an electronic nose based on ultra-fast gas chromatography technique enables rapid analysis of the volatile compounds from food samples. Due to the fact that this technique provides chemical profiling of natural products, it can be a powerful tool for authentication in combination with chemometrics. In this article,...
-
Fuzzy Gaussian Decision Tree
PublicationThe Decision Tree algorithm is one of the first machine learning algorithms developed. It is used both as a standalone model and as an ensemble of many cooperating trees like Random Forest, AdaBoost, Gradient Boosted Trees, or XGBoost. In this work, a new version of the Decision Tree was developed for classifying real-world signals using Gaussian distribution functions and a fuzzy decision process. The research was carried out...
-
Integrated model for the fast assessment of flood volume: Modelling – management, uncertainty and sensitivity analysis
PublicationThe specific flood volume is an important criterion for assessing the performance of sewage networks. It has been shown that its value is greatly influenced by the layout of the sewers in the catchment area, which is usually expressed by a fractal dimension. Currently, only mechanistic models (such as SWMM) enable the determination of the impact of the layout of the sewers on flooding volume, but they require additional and robust...
-
Evaluation of the Influence of Farming Practices and Land Use on Groundwater Resources in a Coastal Multi-Aquifer System in Puck Region (Northern Poland)
PublicationThis study focuses on the modeling of groundwater flow and nitrate transport in a multi-aquifer hydrosystem in northern Poland, adjacent to Puck Bay (Baltic sea). The main goal was to investigate how changes in land use and farming practices may affect groundwater recharge and submarine groundwater discharge (SGD) to the sea and the associated N-NO3 fluxes. An integrated modelling approach has been developed, which couples the...
-
Predictions of cervical cancer identification by photonic method combined with machine learning
PublicationCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
-
Influence of service ageing on polyester-reinforced polyvinyl chloride-coated fabrics reported through mathematical material models
PublicationIn this paper the coupled service (constructional tension) and environmental (sunlight, rainfalls, temperature variations) ageing influence on the polyester-reinforced polyvinyl chloride (PVC)-coated fabric VALMEX is studied. Two cases of the same fabric have been analyzed: one USED for 20 years on the real construction of the Forest Opera in Sopot (Poland), and one kept as a spare material (NOT USED). The following tests have...
-
Surfactants: a real threat to the aquatic geoecosystems of lobelia lakes
PublicationLobelia lakes are valuable elements of the natural environment. They are characterised by low trophy, mainly in-forest location and a high transparency of water. However, similarly to other surface waters, they are subjected to increasing anthropogenic pressures, a good indicator of which is the level of surfactants, also called surface-active agents (SAAs). The aim of the study was to evaluate the intensity of anthropogenic pressures...
-
Enhancing voice biometric security: Evaluating neural network and human capabilities in detecting cloned voices
PublicationThis study assesses speaker verification efficacy in detecting cloned voices, particularly in safety-critical applications such as healthcare documentation and banking biometrics. It compares deeply trained neural networks like the DeepSpeaker with human listeners in recognizing these cloned voices, underlining the severe implications of voice cloning in these sectors. Cloned voices in healthcare could endanger patient safety by...
-
Efficiency of Artificial Intelligence Methods for Hearing Loss Type Classification: an Evaluation
PublicationThe evaluation of hearing loss is primarily conducted by pure tone audiometry testing, which is often regarded as golden standard for assessing auditory function. If the presence of hearing loss is determined, it is possible to differentiate between three types of hearing loss: sensorineural, conductive, and mixed. This study presents a comprehensive comparison of a variety of AI classification models, performed on 4007 pure tone...
-
Offshore benthic habitat mapping based on object-based image analysis and geomorphometric approach. A case study from the Slupsk Bank, Southern Baltic Sea
PublicationBenthic habitat mapping is a rapidly growing field of underwater remote sensing studies. This study provides the first insight for high-resolution hydroacoustic surveys in the Slupsk Bank Natura 2000 site, one of the most valuable sites in the Polish Exclusive Zone of the Southern Baltic. This study developed a quick and transparent, automatic classification workflow based on multibeam echosounder and side-scan sonar surveys to...
-
Comparison of Classification Methods for EEG Signals of Real and Imaginary Motion
PublicationThe classification of EEG signals provides an important element of brain-computer interface (BCI) applications, underlying an efficient interaction between a human and a computer application. The BCI applications can be especially useful for people with disabilities. Numerous experiments aim at recognition of motion intent of left or right hand being useful for locked-in-state or paralyzed subjects in controlling computer applications....
-
Utilizing UAV and orthophoto data with bathymetric LiDAR in google earth engine for coastal cliff degradation assessment
PublicationThis study introduces a novel methodology for estimating and analysing coastal cliff degradation, using machine learning and remote sensing data. Degradation refers to both natural abrasive processes and damage to coastal reinforcement structures caused by natural events. We utilized orthophotos and LiDAR data in green and near-infrared wavelengths to identify zones impacted by storms and extreme weather events that initiated mass...
-
Climate change impact on groundwater resources in sandbar aquifers in southern Baltic coast
PublicationShallow coastal aquifers are vulnerable hydrosystems controlled by many factors, related to climate, seawater‑freshwater interactions and human activity. Given on‑going climate change, sea level rise and increasing human impact, it is especially true for groundwater resources situated in sandbars. We developed numerical models of unsaturated zone water flow for two sandbars in northern Poland: the Vistula Spit and the Hel Spit...
-
Application of multisensoral remote sensing data in the mapping of alkaline fens Natura 2000 habitat
PublicationThe Biebrza River valley (NE Poland) is distinguished by largely intact, highly natural vegetation patterns and very good conservation status of wetland ecosystems. In 2013⿿2014, studies were conducted in the upper Biebrza River basin to develop a remote sensing method for alkaline fen classification ⿿ a protected Natura 2000 habitat (code 7230) ⿿ using remote sensing technologies. High resolution airborne true colour (RGB) and...
-
News that Moves the Market: DSEX-News Dataset for Forecasting DSE Using BERT
PublicationStock 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...
-
From Data to Decision: Interpretable Machine Learning for Predicting Flood Susceptibility in Gdańsk, Poland
PublicationFlood susceptibility prediction is complex due to the multifaceted interactions among hydrological, meteorological, and urbanisation factors, further exacerbated by climate change. This study addresses these complexities by investigating flood susceptibility in rapidly urbanising regions prone to extreme weather events, focusing on Gdańsk, Poland. Three popular ML techniques, Support Vector Machine (SVM), Random Forest (RF), and...
-
Numerical modeling of PFAS movement through the vadose zone: Influence of plant water uptake and soil organic carbon distribution
PublicationIn this study, we investigated the effects of soil organic carbon (SOC) distribution and water uptake by plant roots on PFAS movement in the vadose zone with a deep groundwater table under temperate, humid climate conditions. Two series of numerical simulations were performed with the HYDRUS computer code, representing the leaching of historical PFOS contamination and the infiltration of water contaminated with PFOA, respectively. We...
-
The Concept of Construction of Hybrid Constructed Wetland for Wastewater Treatment in Roztocze National Park
PublicationRoztocze National Park (RNP) is one of 23 national parks in Poland. It was created in 1974 both to protect the natural and cultural heritage as well as to share the park area for science, education and tourism. In caring for the environment, the park removed asbestos coverage, performs thermo-modernization using renewable energy sources by the installation of solar panels and photovoltaic cells on the roofs of buildings, and pellet...
-
Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment 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...
-
Lateral forces determine dimensional accuracy of the narrow‑kerf sawing of wood
PublicationThe shrinking global forest area limits the supply of industrially usable raw resources. This, in combination with the ever‑increasing consumption of timber due to population growth can lead to the lack of a positive balance between the annual volumetric growth and consumption of wood. An important innovation toward increasing environmental and economic sustainability of timber production is to reduce the volume of wood residues...
-
ELECTRICAL CONDUCTIVITY AND pH IN SURFACE WATER AS TOOL FOR IDENTIFICATION OF CHEMICAL DIVERSITY
PublicationIn the present study, the creeks and lakes located at the western shore of Admiralty Bay were analysed. The impact of various sources of water supply was considered, based on the parameters of temperature, pH and specific electrolytic conductivity (SEC25). All measurements were conducted during a field campaign in January-February 2017. A multivariate dataset was also created and a biplot of SEC25 and pH of the investigated waters...
-
RAGN-R: A multi-subject ensemble machine-learning method for estimating mechanical properties of advanced structural materials
PublicationThe utilization of advanced structural materials, such as preplaced aggregate concrete (PAC), fiber-reinforced concrete (FRC), and FRC beams has revolutionized the field of civil engineering. These materials exhibit enhanced mechanical properties compared to traditional construction materials, offering engineers unprecedented opportunities to optimize the design, construction, and performance of structures and infrastructures....
-
Spatial Distribution of Eucalyptus Plantation and its Impact on the Depletion of Groundwater Resources of Tehsil Swat Ranizai, District Malakand
PublicationNative to the continent of Australia, eucalyptus is a tall, evergreen tree belonging to the Myrtaceae family. Malakand district has the largest eucalyptus plantation in the province, covering an area of 22,071.29 ha. The present study aims to evaluate its impact on the groundwater table (GWT) in three selected union councils (UCs) of the study area, i.e., Agra, Totakan, and Kot. Both primary and secondary data support the study....
-
Using creative approaches for discovering biomorphic forms for appropriate human habitation in natural environments. Case study of Kashubian Lake District
PublicationThe research process consisted of studies of natural and cultural conditions of the Kashubian Lake District This is an area of exceptional natural conditions. For centuries, it has seen human habitation with respect to landscape values. Given its extensive forest cover and the lack of heterogeneity of natural conditions, the area has become an interesting inspiration for the author’s original project. The project is aimed at searching...
-
Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublicationIntroduction: Intracranial hemorrhage detection in 3D Computed Tomography (CT) brain images has gained more attention in the research community. The major issue to deal with the 3D CT brain images is scarce and hard to obtain the labelled data with better recognition results. Methods: To overcome the aforementioned problem, a new model has been implemented in this research manuscript. After acquiring the images from the Radiological...
-
The Use of Ultra-Fast Gas Chromatography for Fingerprinting-Based Classification of Zweigelt and Rondo Wines with Regard to Grape Variety and Type of Malolactic Fermentation Combined with Greenness and Practicality Assessment
PublicationIn food authentication, it is important to compare different analytical procedures and select the best method. The aim of this study was to determine the fingerprints of Zweigelt and Rondo wines through headspace analysis using ultra-fast gas chromatography (ultra-fast GC) and to compare the effectiveness of this approach at classifying wines based on grape variety and type of malolactic fermentation (MLF) as well as its greenness...
-
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...
-
Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublicationThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
-
Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublicationNitrous 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...