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Search results for: FOREST AIR
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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,...
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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...
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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...
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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...
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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...
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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...
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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...
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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....
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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...
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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...
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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...
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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...
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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...
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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 20132014, 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...
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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...
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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...
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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...
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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....
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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...
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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...
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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....
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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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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...
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On the Role of Polarimetric Decomposition and Speckle Filtering Methods for C-Band SAR Wetland Classification Purposes
PublicationPrevious 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
PublicationCurrently, 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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Empirical Analysis of Forest Penalizing Attribute and Its Enhanced Variations for Android Malware Detection
PublicationAs a result of the rapid advancement of mobile and internet technology, a plethora of new mobile security risks has recently emerged. Many techniques have been developed to address the risks associated with Android malware. The most extensively used method for identifying Android malware is signature-based detection. The drawback of this method, however, is that it is unable to detect unknown malware. As a consequence of this problem,...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublicationWetlands 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
PublicationThe 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
PublicationIn 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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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublicationThe 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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System of monitoring of the Forest Opera in Sopot structure and roofing
PublicationThe authors present a solution realized in Forest Opera (name in Polish: Opera Leśna) in Sopot (Poland) in connection with the modernization and construction of a new roof. The complicated structure of the roof of the facility and the used covering in form of membrane made of technical fabric required (for security reasons) to install the unit of devices allowing for the continuous geodetic monitoring of the facility. Monitoring...
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THE METHOD OF MEASURING THE MEMBRANE COVER GEOMETRY USING LASER SCANNING AND SYNCHRONOUS PHOTOGRAMMETRY
PublicationThe 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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Ecological and Health Effects of Lubricant Oils Emitted into the Environment
PublicationLubricating 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
PublicationQuantification 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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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublicationIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....
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Mikrofiltrowany koncentrat soku brzozowego jako innowacyjny, trwały środek spożywczy o wysokiej wartości odżywczej
PublicationIntroduction. 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
PublicationThis 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
PublicationCustomer 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
PublicationThe 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...