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Search results for: NUMERICAL PREDICTION
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Sonocatalytic degradation of Bisphenol A from aquatic matrices over Pd/CeO2 nanoparticles: Kinetics study, transformation products, and toxicity
PublicationIn this work, different ratios of palladium – cerium oxide (Pd/CeO2) catalyst were synthesized and characterized, while their sonocatalytic activity was evaluated for the degradation of the xenobiotic Bisphenol A (BPA) from aqueous solutions. Sonocatalytic activity expressed as BPA decomposition exhibited a volcano-type behavior in relation to the Pd loading, and the 0.25Pd/CeO2 catalyst characterized by the maximum Pd dispersion...
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublicationThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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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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Machine Learning and Deep Learning Methods for Fast and Accurate Assessment of Transthoracic Echocardiogram Image Quality
PublicationHigh-quality echocardiogram images are the cornerstone of accurate and reliable measurements of the heart. Therefore, this study aimed to develop, validate and compare machine learning and deep learning algorithms for accurate and automated assessment of transthoracic echocardiogram image quality. In total, 4090 single-frame two-dimensional transthoracic echocardiogram...
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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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Power System Stabilizer as a Part of a Generator MPC Adaptive Predictive Control System
PublicationIn this paper, a model predictive controller based on a generator model for prediction purposes is proposed to replace a standard generator controller with a stabilizer of a power system. Such a local controller utilizes an input-output model of the system taking into consideration not only a generator voltage Ug but also an additional, auxiliary signal (e.g., α, Pg, or ωg). This additional piece of information allows for taking...
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Can Web Search Queries Predict Prices Change on the Real Estate Market?
PublicationThis study aims to explore whether the intensity of internet searches, according to the Google Trends search volume index (SVI), is a predictor of changes in real estate prices. The motivation of this study is the possibility to extend the understanding of the extra predictive power of Google search engine query volume of future housing price change (shift direction) by (i) the introduction of a research approach that combines...
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Time window based features extraction from temperature modulated gas sensors for prediction of ammonia concentration
PublicationElectronic gas recognition systems, in literature commonly referred as electronic noses, enable the recognition of a type and a concentration of various volatile compounds. Typical electronic gas-analyzing device consists of four main elements, namely, gas delivery subsystem, an array of gas sensors, data acquisition and power supply circuits and data analysis software. The commercially available metal-oxide TGS sensors are widely...
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Distributed System For Noise Threat Evaluation Based On Psychoacoustic Measurements
PublicationAn innovative system designed for the continuous monitoring of acoustic climate of urban areas was presentedin the paper. The assessment of environmental threats is performed using online data, acquired through a grid ofengineered monitoring stations collecting comprehensive information about the acoustic climate of urban areas.The grid of proposed devices provides valuable data for the purpose of long and short time acoustic climateanalysis....
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Combining X-ray tomogrpahy imaging and DEM simulations to investigate granular material flow during silo discharging
PublicationEven after few decades of research, the study of particle motion taking place during silo discharging hasn’t been fully addressed, both experimentally and numerically, because of nontrivial behaviors that occur during associated flow patterns. For instance, discrete element method (DEM) has shown good qualitative prediction potential of velocity profile, but, on the other hand, frequently failed to match quantitatively experimental...
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Monitoring strategy for industrially contaminated rivers - A study of all year round behaviour of Klodnica river catchment, upper Silesia, Poland
PublicationThe study was undertaken to thoroughly characterise the contamination of water in industrially influenced river Klodnica, in order to explore monitoring strategies in case of limited analytical capacity. Statistical analysis undertaken after a short study was found to be helpful in reducing monitoring efforts in the future.Klodnica river is located within area of dominating coal mining, metallurgy, and additionally being influenced...
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Verification of agent system for it project management support
PublicationThis article is a continuation of article series telling about research about possibility of using agent system to information technology evaluation. Following article presents full conception of exploiting agent system and shows how it can support some managers works, especially in taking correct management method and information tool for project management. In this article the agent system that based on knowledge and can process...
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Exploring the cocrystallization potential of urea and benzamide
PublicationThe cocrystallization landscape of benzamide and urea interacting with aliphatic and aromatic carboxylic acids was studied both experimentally and theoretically. Ten new cocrystals of benzamide were synthesized using an oriented samples approach via a fast dropped evaporation technique. Information about types of known bi-component cocrystals augmented with knowledge of simple binary eutectic mixtures was used for the analysis...
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Identification of category associations using a multilabel classifier
PublicationDescription of the data using categories allows one to describe it on a higher abstraction level. In this way, we can operate on aggregated groups of the information, allowing one to see relationships that do not appear explicit when we analyze the individual objects separately. In this paper we present automatic identification of the associations between categories used for organization of the textual data. As experimental data...
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublicationBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
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A Simple Neural Network for Collision Detection of Collaborative Robots
PublicationDue to the epidemic threat, more and more companies decide to automate their production lines. Given the lack of adequate security or space, in most cases, such companies cannot use classic production robots. The solution to this problem is the use of collaborative robots (cobots). However, the required equipment (force sensors) or alternative methods of detecting a threat to humans are usually quite expensive. The article presents...
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Genetic variations as predictors of dispositional and dyadic empathy - a couple study
PublicationBiological drivers of empathy have been explored in an interdisciplinary manner for decades. Research that merges the psychological and genetic perspectives of empathy has recently gained interest, and more complex designs and analyses are needed. Empathy is a multidimensional construct that might be regarded both dispositionally (as a personality trait) and contextually (experienced and/or expressed in a particular relationship/situation)....
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Deep learning for ultra-fast and high precision screening of energy materials
PublicationSemiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...
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Behavioral state classification in epileptic brain using intracranial electrophysiology
PublicationOBJECTIVE: Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. APPROACH: Data from seven patients (age [Formula: see text], 4 women) who underwent intracranial depth electrode...
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Ecological bearing systems for water turbines – research and development at Gdansk University of Technology
PublicationIncreasing requirements for environmental protection make it necessary to introduce new materials and designs. Hydroelectric power plants operating in direct contact with water reservoirs and rivers are potentially endangering water cleanliness, hence they should also be modernized in the way minimizing the environmental hazards. A lot of progress in this field has been achieved in last decades, but still there is much work to...
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Small city and a bridge. Landscape perspective
PublicationThe aim of the paper is to present the problems connected with the location of big infrastructure objects; like bridges; in close neighbourhood to the small cities located in valuable environment and landscape; and the ways to minimize the potential threats. The case study of the small town Wyszogrod in central Poland will be presented to illustrate the values of the environment and landscape; which could have been easily destroyed...
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Role of miR-15b/16–2 cluster network in endometrial cancer: An in silico pathway and prognostic analysis
PublicationEndometrial cancer (EC) is the second most common cancer in women. A large number of human cancers exhibit dysregulation of microRNA expression including EC. MiR-15b/16–2 is one of the best-known miRNA clusters that is expressed in many types of cancer tissues. Herein, we analyzed the expression of individual miR-15b/16–2 cluster members, its paralogues, and their target network analysis, as well as their prognostic significance...
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Impacts on human health in the Arctic owing to climate-induced changes in contaminant cycling – The EU ArcRisk project policy outcome
PublicationResults of the EU ArcRisk project on human health impacts in the Arctic owing to climate-induced changes in contaminant cycling are summarized in the context of their policy application. The question on how will climate change affect the transport of selected persistent organic pollutants (POPs) and mercury, both to and within the Arctic has been addressed, as well as the issue of human health impacts of these pollutants in the...
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Data-driven Models for Predicting Compressive Strength of 3D-printed Fiber-Reinforced Concrete using Interpretable Machine Learning Algorithms
Publication3D printing technology is growing swiftly in the construction sector due to its numerous benefits, such as intricate designs, quicker construction, waste reduction, environmental friendliness, cost savings, and enhanced safety. Nevertheless, optimizing the concrete mix for 3D printing is a challenging task due to the numerous factors involved, requiring extensive experimentation. Therefore, this study used three machine learning...
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Multi-GPU-powered UNRES package for physics-based coarse-grained simulations of structure, dynamics, and thermodynamics of protein systems at biological size- and timescales
PublicationCoarse-grained models are nowadays extensively used in biomolecular simulations owing to the tremendous extension of size- and time-scale of simulations. The physics-based UNRES (UNited RESidue) model of proteins developed in our laboratory has only two interaction sites per amino-acid residue (united peptide groups and united side chains) and implicit solvent. However, owing to rigorous physics-based derivation, which enabled...
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Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublicationLand Use and Land Cover (LULC) monitoring is crucial for global transformation, sustainable land control, urban planning, urban growth prediction, and the establishment of climate regulations for long-term development. Remote sensing images have become increasingly important in many environmental planning and land use surveys in recent times. LULC is evaluated in this research using the Sat 4, Sat 6, and Eurosat datasets. Various...
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Effect of temperature and composition on physical properties of deep eutectic solvents based on 2-(methylamino)ethanol – measurement and prediction
PublicationNovel deep eutectic solvents were synthesized using 2-(methylamino)ethanol as hydrogen bond donor with tetrabutylammonium bromide or tetrabutylammonium chloride or tetraethylammonium chloride as hydrogen bond acceptors. Mixtures were prepared at different molar ratios of 1:6, 1:8 and 1:10 salt to alkanolamine and then Fourier Transform Infrared Spectroscopy measurements were performed to confirm hydrogen bonds interactions between...
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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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Sensitivity of the Baltic Sea level prediction to spatial model resolution
Publicationhe three-dimensional hydrodynamic model of the Baltic Sea (M3D) and...
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Indole-Acrylonitrile Derivatives as Potential Antitumor and Antimicrobial Agents—Synthesis, In Vitro and In Silico Studies
PublicationA series of 2-(1H-indol-2-yl)-3-acrylonitrile derivatives, 2a–x, 3, 4a–b, 5a–d, 6a–b, and 7, were synthesized as potential antitumor and antimicrobial agents. The structures of the prepared compounds were evaluated based on elemental analysis, IR, 1H- and 13NMR, as well as MS spectra. X-ray crystal analysis of the representative 2-(1H-indol-2-yl)-3-acrylonitrile 2l showed that the acrylonitrile double bond was Z-configured. All...
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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...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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MutS3: a MutS homologue of unknown biological function
PublicationThe homologues of MutS proteins are widespread among both Prokaryotes and Eukaryotes. MutS designated as MutS1 is a part of MMR (mismatch repair) system which is responsible for removal of mispaired bases and small insertion/deletion loops in DNA. Initially, the only MutS homologues known were those engaged in mismatch repair and these were later designated as MutS1. Subsequently, the MutS2 homologue was distinguished. MutS2 does...
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Thermodynamic Analysis of Negative CO2 Emission Power Plant Using Aspen Plus, Aspen Hysys, and Ebsilon Software
PublicationAbstract: The article presents results of thermodynamic analysis using a zero-dimensional mathematical models of a negative CO2 emission power plant. The developed cycle of a negative CO2 emission power plant allows the production of electricity using gasified sewage sludge as a main fuel. The negative emission can be achieved by the use this type of fuel which is already a “zeroemissive” energy source. Together with carbon capture...
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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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Chicken feather keratin as a source of bioactive peptides useful in prevention of metabolic disorders – in silico and in vitro hydrolysis
PublicationProtein derived bioactive peptides not only serve as nutrients but can also exert drug-like activity, e.g. antidiabetic, antihypertensive, or antimicrobial, to name a few. Most biopeptides have beneficial effects on health that make them attractive for nutraceutical applications. The majority of bioactive peptides have been obtained from food proteins, but protein-rich by-products generated by agriculture...
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Experimental and theoretical study of a vertical tube in shell storage unit with biodegradable PCM for low temperature thermal energy storage applications
PublicationThis article presents the experimental investigations of the coconut oil-based TES module for HVAC applications in the ambient and-sub ambient temperature range. To properly study this problem modular experimental module and test loop were developed. Special attention has been paid to study the physical mechanism of the melting/solidification process for natural substance (coconut oil) which has perspectives to be used in thermal...
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On the differential effect of temperature on the Nusselt-Rayleigh relationship in free convection
PublicationThe aim of and inspiration behind this paper was to explain the reasons, also observed by other researchers, of the discrepancy in the results of experimental free convection, which for small Rayleigh and Nusselt numbers in the initial phase of research can sometimes reach several hundred percent. These discrepancies decrease with increasing heating power and plate surface temperature, in proportion to the increase in Ra and Nu,...
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Mechanics of Micro- and Nano-Size Materials and Structures
PublicationNanotechnology knowledge is always looking to expand its boundaries to achieve the mostsignificant benefit to human life and meet the growing needs of today. In this case, we can refer tomicro- and nanosensors in micro/nano-electromechanical systems (MEMS/NEMS). These electricaldevices can detect minimal physical stimuli up to one nanometer in size. Today, micro/nano-sensordevices are widely used in the...
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Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublicationBackground. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...
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Quality prediction of foil capacitors by acoustic emission signals
PublicationJakość i trwałość kondensatorów foliowych jest zależna od ich warunków pracy (np. nadmiarowego napięcia pracy, temperatury, wilgotności) oraz od potencjalnych defektów wprowadzonych na różnych etapach wytwarzania kondensatorów. Nieustanny nacisk na wzrost jakości wytwarzanych elementów przy jednoczesnej redukcji kosztów wytwarzania oznacza, że nowe, tanie i szybkie metody predykcji jakości tych elementów są mocno poszukiwane. W...
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The hybrid estimation algorithm for wastewater treatment plant robust model predictive control purposes at medium time scale
PublicationThe paper proposes an approach to designing the hybrid estimation algorithm/module (HEA) with moving measurements window for Wastewater Treatment Plant (WWTP) Robust Model Predictive Control (RMPC) purposes at medium time scale. The RMPC uses a dedicated grey-box model of biological reactor for the system outputs prediction purposes. The grey-box model parameters are dependant on the plant operating point. Hence, these parameters...