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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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Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublicationOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublicationNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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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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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublicationOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublicationIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublicationWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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Technological vs. Non-Technological Mindsets: Learning From Mistakes, and Organizational Change Adaptability to Remote Work
PublicationThe permanent implementation of the change in working methods, e.g., working in the virtual space, is problematic for some employees and, as a result, for management leaders. To explore this issue deeper, this study assumes that mindset type: technological vs. non-technological, may influence the organizational adaptability to change. Moreover, the key interest of this research is how non-technological mindsets...
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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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Phyto-mediated photocatalysis: a critical review of in-depth base to reactive radical generation for erythromycin degradation
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Grazing of Native Livestock Breeds as a Method of Grassland Protection in Roztocze National Park, Eastern Poland
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Effect of nitrogen doping on TiOxNythin film formation at reactive high-power pulsed magnetron sputtering
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Synergistic action of extracts from carnivorous plants and synthetic peptides against plant pathoghenic bacteria
Publicationw pracy przedstawiono rezultaty badań nad sprawdzeniem aktywności przeciwbakteryjnej ekstraktów z roślin Drosera capensis i Dionaea muscipula w połączeniu z dwoma syntetycznymi peptydami: CAMEL oraz pexiganan. Najwyższą aktywnością przeciwbakteryjną odznaczał się chloroformowy ekstrakt z D. muscipula z peptydem CAMEL.
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Effects of different hydraulic models on predicting longitudinal profiles of reactive pollutants in activated sludge reactors
PublicationW pracy przedstawiono wpływ dyspersji na prognozowanie stężeń azotu amonowego w komorach osadu czynnego w oczyszczalni ścieków Gdańsk-Wschód. W tym celu wykorzystano jednowymiarowe równanie adwekcji-dyspersji z członem źródłowym (szybkością nitryfikacji). Współczynnik dyspersji został wyznaczony na podstawie pomiarów znacznika fluoroscencyjnego. Model został zweryfikowany w oparciu o pomiary stężeń azotu w 6 sekcjach komory tlenowej...
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Effect of Increased Temperature on Native and Alien Nuisance Cyanobacteria from Temperate Lakes: An Experimental Approach
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Polymer-free cubosomes for simultaneous bioimaging and photodynamic action of photosensitizers in melanoma skin cancer cells
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Grafting and reactive extrusion technologies for compatibilization of ground tyre rubber composites: Compounding, properties, and applications
PublicationChemical modification of ground tyre rubber (GTR) to compatibilize it with the matrix is a well-known approach. Based on our recent review of the surface etching methods used in GTR modification, the purpose of the current work is to take a deeper look into more advanced methods such as grafting and reactive extrusion. While grafting is more efficient in achieving compatibility, however, it usually involves multi-step synthesis...
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Ribes nigrum L. Extract-Mediated Green Synthesis and Antibacterial Action Mechanisms of Silver Nanoparticles
PublicationSilver nanoparticles (Ag NPs) represent one of the most widely employed metal-based engineered nanomaterials with a broad range of applications in different areas of science. Plant extracts (PEs) serve as green reducing and coating agents and can be exploited for the generation of Ag NPs. In this study, the phytochemical composition of ethanolic extract of black currant (Ribes nigrum) leaves was determined. The main components...
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The exposure to UV filters: Prevalence, effects, possible molecular mechanisms of action and interactions within mixtures
PublicationSubstances that can absorb sunlight and harmful UV radiation such as organic UV filters are widely used in cosmetics and other personal care products. Since humans use a wide variety of chemicals for multiple purposes it is common for UV filters to co-occur with other substances either in human originating specimens or in the environment. There is increasing interest in understanding such co-occurrence in form of potential synergy, antagonist,...
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Mangiferin Affects Melanin Synthesis by an Influence on Tyrosinase: Inhibition, Mechanism of Action and Molecular Docking Studies
PublicationMangiferin is a strong antioxidant that presents a wide range of biological activities. The aim of this study was to evaluate, for the first time, the influence of mangiferin on tyrosinase, an enzyme responsible for melanin synthesis and the unwanted browning process of food. The research included both the kinetics and molecular interactions between tyrosinase and mangiferin. The research proved that mangiferin inhibits tyrosinase...
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Możliwości sterowania mocą bierną elektrowni wiatrowej : Reactive power control methods in wind parks
PublicationReferat poświęcony jest zagadnieniu sterowania mocą bierną w elektrowniach wiatrowych. W pierwszej części referatu opisano tło problemu sterowania mocą bierną w parkach wiatrowych, podano powody, dla których moc bierna powinna podlegać regulacji oraz zarysowano metody, które mogą być do niej użyte. W celu sprawdzenia proponowanych metod kompensacji, zbudowano model matematyczny elektrowni wiatrowej, którego poszczególne elementy...
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Analysis of muscles behaviour. Part II. The computational model of muscles group acting on the elbow joint
PublicationThe purpose of this paper is to present the computational model of muscles' group describing the movements of flexion/extension at the elbow joint in the sagittal plane of the body when the forearm is being kept in the fixed state of supination/pronation. The method ofevaluating the muscle forces is discussed in detail. This method is the basis for the quantitative and qualitative verification of the proposed computational model...
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NON-STATIONARY THERMAL SELF-ACTION OF ACOUSTIC BEAMS CONTAINING SHOCK FRONTS IN THERMOCONDUCTING FLUID
PublicationNon-stationary thermal self-action of a periodic or impulse acoustic beam containing shock fronts in a thermoconducting Newtonian fluid is studied. Self-focusing of a saw-tooth periodic and impulse sound is considered, as well as that of a solitary shock wave which propagates with the linear sound speed. The governing equations of the beam radius are derived. Numerical simulations reveal that the thermal conductivity weakens the...
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The Palais–Smale condition for the Hamiltonian action on a mixed regularity space of loops in cotangent bundles and applications
PublicationWe show that the Hamiltonian action satisfies the Palais-Smale condition over a “mixed regular- ity” space of loops in cotangent bundles, namely the space of loops with regularity H^s, s ∈ (1/2, 1), in the baseand H^{1−s} in the fiber direction. As an application, we give a simplified proof of a theorem of Hofer-Viterbo on the existence of closed characteristic leaves for certain contact type hypersufaces in cotangent bundles.
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Low-Voltage LDO Regulator Based on Native MOS Transistor with Improved PSR and Fast Response
PublicationIn this paper, a low-voltage low-dropout analog regulator (ALDO) based on a native n-channel MOS transistor is proposed. Application of the native transistor with the threshold voltage close to zero allows elimination of the charge pump in low-voltage regulators using the pass element in a common drain configuration. Such a native pass transistor configuration allows simplification of regulator design and improved performance,...
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Self-Organising map neural network in the analysis of electromyography data of muscles acting at temporomandibular joint.
PublicationThe temporomandibular joint (TMJ) is the joint that via muscle action and jaw motion allows for necessary physiological performances such as mastication. Whereas mandible translates and rotates [1]. Estimation of activity of muscles acting at the TMJ provides a knowledge of activation pattern solely of a specific patient that an electromyography (EMG) examination was carried out [2]. In this work, a Self-Organising Maps (SOMs)...
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Reactive Sintering of Ground Tire Rubber (GTR) Modified by a Trans-Polyoctenamer Rubber and Curing Additives
PublicationThe proposed method of ground tire rubber (GTR) utilization involves the application of trans-polyoctenamer rubber (TOR), a commercially available waste rubber modifier. The idea was to investigate the influence of various curing additives (sulfur, N-cyclohexyl-2-benzothiazole sulfenamide (CBS), dibenzothiazole disulfide (MBTS) and di-(2-ethyl)hexylphosphorylpolysulfide (SDT)) on curing characteristics, physico-mechanical, thermal,...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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Perceived technostress while learning a new mobile technology: Do individual differences and the way technology is presented matter?
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Night shifts as a learning experience among nursing students across Europe: Findings from a cross-sectional survey
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E-learning jako narzędzie wspierające kształcenie osób 50+. Rozważania w oparciu o projekt MAYDAY
PublicationRozdział przedstawia zalety i wady szkoleń e-learningowych ze szczególnym uwzględnieniem uczestników w wieku 50+, analizę szkolenia przeprowadzonego w ramach projektu MAYDAY oraz wytyczne i rekomendacje do tworzenia kursów e-learnignowych dla osób powyżej 50-go roku życia.
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Bilingual advantage? Literacy and phonological awareness in Polish-speaking early elementary school children learning English simultaneously
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Presentation of Novel Architecture for Diagnosis and Identifying Breast Cancer Location Based on Ultrasound Images Using Machine Learning
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Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublicationIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing
PublicationRubbers combine the flexibility with mechanical strength, supporting myriad applications, but suffer from inherent flammability. Formulation and production of flame-retardant rubber composites (FRRCs) have intensively been practiced over years, but not comprehensively reviewed. This necessity has outlined collecting, analyzing, screening, classifying, and interpreting the literature with the aim of classifying the FRRCs. We quantified...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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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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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublicationLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublicationThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader's behavior must align for the best learning effects....
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An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning
PublicationThis paper investigates computationally the following research hypotheses: (1) Higher flexibility and discretion in organizational culture results in better mistake management and thus better organizational learning, (2) Effective organizational learning requires a transformational leader to have both high social and formal status and consistency, and (3) Company culture and leader’s behavior must align for the best learning effects....
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Decisional DNA for modeling and reuse of experiential clinical assessments in breast cancer diagnosis and treatment
PublicationClinical Decision Support Systems (CDSS) are active knowledge resources that use patient data to generate case specific advice. The fast pace of change of clinical knowledge imposes to CDSS the continuous update of the domain knowledge and decision criteria. Traditional approaches require costly tedious manual maintenance of the CDSS knowledge bases and repositories. Often, such an effort cannot be assumed by medical teams, hence...
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Przydatność białka rybiego w postaci kolagenu lub żelatyny oraz polisacharydu - kapa-karagenu do wytwarzania aktywnych opakowań biodegradowalnych = Usefulness of fish collagen, gelatin and carrageenan for preparation of active biodegradable packages
PublicationSummary - The possibility of use of protein films made of fish collagen or gelatin as well as polysaccharide carrageenan films as carriers of enzymes (lysozyme or lysostaphyne), for preparation of microbiologically active packages, was investigated. It was found that crosslinking of such systems with N-[3(dimethylamino)propyl]-N'-ethylcarboimide (EDC) does not influence the activity of lysozyme immobilized in the films (Table 1)....
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Action Research - przygotowanie sądu do zmiany poprzez uczenie się - współpraca praktyków i badaczy
PublicationW praktyce zarządzanie sądem na ogół jest oddalone od teorii zarządzania. Prezesi sądów rzadko zwracają się do naukowców z prośbą o rozwiązanie ich problemów w zarządzaniu. W sądach brakuje nie tylko stałych form współpracy z naukowcami zajmującymi się zarządzaniem, ale także z innymi interesariuszami. Jedyną formą komunikacji, i to z ograniczoną liczbą interesariuszy, są formalne środki wyznaczone przez procedurę cywilną lub karną....
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Experimental and theoretical studies on the photodegradation of 2-ethylhexyl 4-methoxycinnamate in the presence of reactive oxygen and chlorine species
Publication2-Ethylhexyl 4-methoxycinnamate (EHMC) is one of the most commonly used sunscreen ingredient. In this study we investigated photodegradation of EHMC in the presence of such common oxidizing and chlorinating systems as H2O2, H2O2/HCl, H2O2/UV, and H2O2/HCl/UV. Reaction products were detected by gas chromatography with a mass spectrometric detector (GC-MS). As a result of experimental studies chloro-substituted 4-methoxycinnamic...
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The ability of selected plant essential oils to enhance the action of recommended antibiotics against pathogenic wound bacteria
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Hepatic proteome changes induced by dietary supplementation with two levels of native chicory inulin in young pigs
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