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Novel Complementary Multiple Concentric Split Ring Resonator for Reliable Characterization of Dielectric Substrates with High Sensitivity
PublicationAccurate characterization of dielectric substrates with high sensitivity remains an important challenge in a variety of industrial applications. This paper proposes an innovative strategy to address this challenge by developing and optimizing a unique Complementary Multiple Concentric Split Ring Resonator (CMC-SRR). The major goal is to propose a sensor design with increased sensitivity and reliability for dielectric characterization....
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Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects
PublicationModern machine learning (ML) techniques are making inroads in every aspect of renewable energy for optimizationand model prediction. The effective utilization of ML techniques for the development and scaling up of renewable energy systemsneeds a high degree of accountability. However, most of the ML approaches currently in use are termed black box since their work isdifficult to comprehend. Explainable artificial intelligence (XAI)...
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Adsorption onto zeolites: molecular perspective
Publication2D minerals are among key elements of advanced systems, but the need for understanding their interactions/reactions with materials and systems in which they are involved necessitates tracking their molecular and atomic monitoring. Zeolitic structures are microporous materials formed in the nature through volcanic activities or synthesis. Because of their outstanding physicochemical properties like cation exchange capacity and excellent...
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Porosity and shape of airborne wear microparticles generated by sliding contact between a low-metallic friction material and a cast iron
PublicationThe wear of brakes in transport vehicles is one of the main anthropogenic sources of airborne particulate matter in urban environments. The present study deals with the characterisation of airborne wear microparticles from a low-metallic friction material / cast iron pair used in car brakes. Particles were generated by a pin-on-disc machine in a sealed chamber at sliding velocity of 1.3 m/s and contact pressure of 1.5 MPa. They...
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Some Aspects of Shear Behavior of Soft Soil–Concrete Interfaces and Its Consequences in Pile Shaft Friction Modeling
PublicationThis paper examines the stiffness degradation and interface failure load on soft soil–concrete interface. The friction behavior and its variability is investigated. The direct shear tests under constant normal load were used to establish parameters to hyperbolic interface model which provided a good approximation of the data from instrumented piles. Four instrumented piles were used to obtain reference soil–concrete interface behavior....
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Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift
PublicationWhile recent computer vision algorithms achieve impressive performance on many benchmarks, they lack robustness - presented with an image from a different distribution, (e.g. weather or lighting conditions not considered during training), they may produce an erroneous prediction. Therefore, it is desired that such a model will be able to reliably predict its confidence measure. In this work, uncertainty estimation for the task...
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Selection of effective cocrystals former for dissolution rate improvement of active pharmaceutical ingredients based on lipoaffinity index
PublicationNew theoretical screening procedure was proposed for appropriate selection of potential cocrystal formers possessing the ability of enhancing dissolution rates of drugs. The procedure relies on the training set comprising 102 positive and 17 negative cases of cocrystals found in the literature. Despite the fact that the only available data were of qualitative character, performed statistical analysis using binary classification...
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Experimental and predicted physicochemical properties of monopropanolamine-based deep eutectic solvents
PublicationIn this work, the novel deep eutectic solvents (DESs) based on 3-amino-1-propanol (AP) as hydrogen bond donor (HBD) and tetrabutylammonium bromide (TBAB) or tetrabutylammonium chloride (TBAC) or tetraethylammonium chloride (TEAC) as hydrogen bond acceptors (HBAs) were synthesized with different molar ratios of 1: 4, 1: 6 and 1: 8 salt to AP. Fourier Transform Infrared Spectroscopy measurements were performed to provide an evidence...
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An asymmetrical λ-foot of condensing steam flow in the IMP PAN nozzle
PublicationIn the present paper we have focused on the precise prediction of the spontaneous condensation phenomena in wet steam flow. Novelty of our approach lies on modelling both the moment of initiation of a phase transition, as well as the moment of its reverse progress - called here re-vaporization of the condensate phase. The practical issue is to elaborate of a model of spontaneous condensation/vaporization of water steam flow...
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Endohedral gallide cluster superconductors and superconductivity in ReGa5
PublicationWe present transition metal-embedded (T@Gan) endohedral Ga clusters as a favorable structural motif for superconductivity and develop empirical, molecule-based, electron counting rules that govern the hierarchical architectures that the clusters assume in binary phases. Among the binary T@Gan endohedral cluster systems, Mo8Ga41, Mo6Ga31, Rh2Ga9, and Ir2 Ga9 are all previously known superconductors. The well-known exotic superconductor...
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Experimental and predicted physicochemical properties of monopropanolamine-based deep eutectic solvents
PublicationIn this work, the novel deep eutectic solvents (DESs) based on 3-amino-1-propanol (AP) as hydrogen bond donor (HBD) and tetrabutylammonium bromide (TBAB) or tetrabutylammonium chloride (TBAC) or tetraethylammonium chloride (TEAC) as hydrogen bond acceptors (HBAs) were synthesized with different molar ratios of 1:4, 1:6 and 1:8 salt to AP. Fourier Transform Infrared Spectroscopy measurements were performed to provide an evidence...
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A Comparison of Empirical Correlations of Viscosity and Thermal Conductivity of Water-Ethylene Glycol-Al2O3 Nanofluids
PublicationBecause of their superb thermal conductivity, nanofluids are seen as new generation of cooling mediums in many engineering applications. It is well established that even a small amount of nanoparticles mixed with a base fluid may result in distinct thermal conductivity enhancement. On the other hand, addition of nanoparticles to the base fluid results in its substantial viscosity increase. Therefore, it is very dicult to evaluate...
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Revisiting the estimation of cutting power with different energetic methods while sawing soft and hard woods on the circular sawing machine: a Central European case
PublicationIn the classical approaches, used in Central Europe in practice, cutting forces and cutting power in sawing processes of timber are commonly computed by means of the specific cutting resistance kc. It needs to be highlighted that accessible sources in handbooks and the scientific literature do not provide any data about wood provenance, nor about cutting conditions, in which cutting resistance has been empirically determined. In...
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Exploring the influence of personal factors on physiological responses to mental imagery in sport
PublicationImagery is a well-known technique in mental training which improves performance efficiency and influences physiological arousal. One of the biomarkers indicating the amount of physiological arousal is skin conductance level (SCL). The aim of our study is to understand how individual differences in personality (e.g. neuroticism), general imagery and situational sport anxiety are linked to arousal measuring with SCL in situational...
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Effect of bending-torsion on fracture and fatigue life for 18Ni300 steel specimens produced by SLM
PublicationIn this study, different fracture surfaces caused by fatigue failure were generated from 18Ni300 steel produced by selective laser melting (SLM). Hollow round bars with a transverse hole were tested under bending-torsion to investigate the crack initiation mechanisms and fatigue life. Next, the post-failure fracture surfaces were examined by optical profilometer and scanning electron microscope. The focus is placed on the relationship...
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USING ARTIFICIAL NEURAL NETWORKS FOR PREDICTING SHIP FUEL CONSUMPTION
PublicationIn marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types...
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Analyses of Shear Angle in Orthogonal Cutting of Pine Wood
PublicationThe determination of energy effects for wood machining processes, such as cutting power and cutting forces, is very useful in designing of manufacture process of wooden products. A more accurate prediction of cutting forces requires a correct determination of the shear angle value, which can be determined using various models. In this article, shear angle values for an orthogonal linear cutting process of pine wood are determined. The...
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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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An energetic analysis of a gas turbine with regenerative heating using turbine extraction at intermediate pressure - Brayton cycle advanced according to Szewalski's idea
PublicationIn this paper, a modification of a simple gas turbine into the Brayton cycle with regenerative heating, using turbine extraction at intermediate pressure, is presented. The main concept of the retrofitting is based on the transfer of heat from the turbine exhaust gases to the air entering the combustion chamber. The extracted gas transfers heat to air via the divided regenerative heat exchanger and after that is compressed and...
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SkinDepth - synthetic 3D skin lesion database
Open Research DataSkinDepth is the first synthetic 3D skin lesion database. The release of SkinDepth dataset intends to contribute to the development of algorithms for:
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Consequences of New Approach of Chemical Stability Tests of Active Pharmaceutical Ingredients (APIs)
PublicationThere is a great need of broaden look on stability tests of active pharmaceuticalingredients (APIs) in comparison with current requirements contained in pharmacopeia.By usage of many modern analytical methods the conception of monitoring the changesof APIs during initial stage of their exposure to harmful factors has been developed. Newknowledge must be acquired in terms of identification of each degradation...
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Localization of impulsive disturbances in audio signals using template matching
PublicationIn this paper, a new solution to the problem of elimination of impulsive disturbances from audio signals, based on the matched filtering technique, is proposed. The new approach stems from the observation that a large proportion of noise pulses corrupting audio recordings have highly repetitive shapes that match several typical “patterns”. In many cases a representative set of exemplary pulse waveforms can be extracted from the...
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Online sound restoration system for digital library applications.
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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INFLUENCE OF TIME ON THE BEARING CAPACITY OF PRECAST PILES
PublicationOne of the most popular types of foundations in layered subsoil with very differentiated soil shear strengths are precast piles. One of the reasons is a fact that we can well control the driving process during the installation of these piles. The principles of the assessment of bearing capacity and settlements of the piles given by Eurocode 7, concentrate on two main methods, i.e. Static Pile Load Tests (SPLT) and Dynamic Driving...
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Interaction Between Storm Water Conduit And Surface Flow For Urban Flood Inundation Modelling
PublicationRapid development of urban areas always comes with great side effects. One of them is the occurrence of urban floods. Growth of impervious surfaces in cities leads to increasing run-off values. This together with difficulties connected with sewage modernization in cities marks urban inundations as being one of the most important issues concerning urban water. Accurate prediction of a phenomenon is difficult as it is highly dependent...
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Smooth least absolute deviation estimators for outlier-proof identification
PublicationThe paper proposes to identify the parameters of linear dynamic models based on the original implementation of least absolute deviation estimators. It is known that the object estimation procedures synthesized in the sense of the least sum of absolute prediction errors are particularly resistant to occasional outliers and gaps in the analyzed system data series, while the classical least squares procedure unfortunately becomes...
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An optimized dissolved oxygen concentration control in SBR with the use of adaptive and predictive control schemes
PublicationThis paper addresses the problem of optimizing control of the aeration process in a water resource recovery facility (WRRF) using sequencing batch reactor (SBR), one that affects the efficiency of wastewater treatment by stimulating metabolic reactions of microorganisms through dissolved oxygen (DO) level control, and accounts for the predominant part of operating costs. Two independent approaches to DO control algorithm design...
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Adaptive Hyperparameter Tuning within Neural Network-based Efficient Global Optimization
PublicationIn this paper, adaptive hyperparameter optimization (HPO) strategies within the efficient global optimization (EGO) with neural network (NN)-based prediction and uncertainty (EGONN) algorithm are proposed. These strategies utilize Bayesian optimization and multiarmed bandit optimization to tune HPs during the sequential sampling process either every iteration (HPO-1itr) or every five iterations (HPO-5itr). Through experiments using...
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Modelling and simulation of GPU processing in the MERPSYS environment
PublicationIn this work, we evaluate an analytical GPU performance model based on Little's law, that expresses the kernel execution time in terms of latency bound, throughput bound, and achieved occupancy. We then combine it with the results of several research papers, introduce equations for data transfer time estimation, and finally incorporate it into the MERPSYS framework, which is a general-purpose simulator for parallel and distributed...
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Theoretical calculation of the physico-chemical properties of 1-butyl-4-methylpyridinium based ionic liquids
PublicationACCEPTED MAIonic liquids (ILs) have attracted much attention for their unique physicochemical properties, which can be designed as needed by altering the ion combinations. Besides experimental work, numerous computational studies have been concerned with prediction of physical properties of ILs. The results of molecular dynamics simulations of ILs depend strongly on the proper force field parameterization. Classical force fields...
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On adaptive covariance and spectrum estimation of locally stationary multivariate processes
PublicationWhen estimating the correlation/spectral structure of a locally stationary process, one has to make two important decisions. First, one should choose the so-called estimation bandwidth, inversely proportional to the effective width of the local analysis window, in the way that complies with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive...
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A New Approach for Investigating the Impact of Pesticides and Nutrient Flux from Agricultural Holdings and Land-Use Structures on Baltic Sea Coastal Waters
PublicationKnowledge related to land-use management impacts on the Baltic Sea ecosystem is limited. The constant release of pollutants into water bodies has resulted in water quality degradation. Therefore, only the innovative approaches integrated with research will provide accurate solutions and methods for proper environment management and will enable understanding and prediction of the impacts of land-use in the Baltic Sea region. Modelling...
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Optimization of Saccharification Conditions of Lignocellulosic Biomass under Alkaline Pre-Treatment and Enzymatic Hydrolysis
PublicationPre-treatment is a significant step in the production of second-generation biofuels from waste lignocellulosic materials. Obtaining biofuels as a result of fermentation processes requires appropriate pre-treatment conditions ensuring the highest possible degree of saccharification of the feed material. An influence of the following process parameters were investigated for alkaline pre-treatment of Salix viminalis L.: catalyst concentration...
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Cost-efficient design optimization of compact patch antennas with improved bandwidth
PublicationIn this letter, a surrogate-assisted optimization procedure for fast design of compact patch antennas with enhanced bandwidth is presented. The procedure aims at addressing a fundamental challenge of the design of antenna structures with complex topologies, which is simultaneous adjustment of numerous geometry parameters. The latter is necessary in order to find a truly optimum design and cannot be executed-at the level of high-fidelity...
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Krzysztof Bruniecki dr inż.
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Novel molecules containing structural features of NSAIDs and 1,2,3-triazole ring: Design, synthesis and evaluation as potential cytotoxic agents
PublicationFor the first time the template containing structural features of more than one NSAIDs and the 1,2,3-triazole ring was explored for the identification of potential cytotoxic agents. These new and complex molecules were predicted to be effective inhibitors of PDE4B by molecular modelling studies in silico. The multi-step synthesis of these compounds were carried out starting from the well-known drug nimesulide and involved the use...
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The impact of initial and boundary conditions on severe weather event simulations using a high-resolution WRF model. Case study of the derecho event in Poland on 11 August 2017
PublicationPrecise simulations of severe weather events are a challenge in the era of changing climate. By performing simulations correctly and accurately, these phenomena can be studied and better understood. In this paper, we have verified how different initial and boundary conditions affect the quality of simulations performed using the Weather Research and Forecasting Model (WRF). For our analysis, we chose...
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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...
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Active learning on stacked machine learning techniques for predicting compressive strength of alkali-activated ultra-high-performance concrete
PublicationConventional ultra-high performance concrete (UHPC) has excellent development potential. However, a significant quantity of CO2 is produced throughout the cement-making process, which is in contrary to the current worldwide trend of lowering emissions and conserving energy, thus restricting the further advancement of UHPC. Considering climate change and sustainability concerns, cementless, eco-friendly, alkali-activated UHPC (AA-UHPC)...
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Co-gasification of waste biomass-low grade coal mix using downdraft gasifier coupled with dual-fuel engine system: Multi-objective optimization with hybrid approach using RSM and Grey Wolf Optimizer
PublicationThe looming global crisis over increasing greenhouse gases and rapid depletion of fossil fuels are the motivation factors for researchers to search for alternative fuels. There is a need for more sustainable and less polluting fuels for internal combustion engines. Biomass offers significant potential as a feed material for gasification to produce gaseous fuel. It is carbon neutral, versatile, and abundant on earth. The present...
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Diurnal variability of atmospheric water vapour, precipitation and cloud top temperature across the global tropics derived from satellite observations and GNSS technique
PublicationThe diurnal cycle of convection plays an important role in clouds and water vapour distribution across the global tropics. In this study, we utilize integrated moisture derived from the global navigation satellite system (GNSS), satellite precipitation estimates from TRMM and merged infrared dataset to investigate links between variability in tropospheric moisture, clouds development and precipitation at a diurnal time scale. Over...
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Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
PublicationFiber-reinforced concrete (FRC) is extensively used in diverse structural engineering applications, and its mechanical properties are crucial for designing and evaluating its performance. The compressive, flexural, splitting tensile, and shear strengths of FRCs are among the most important attributes, which have been discussed more extensively than other properties. The accurate prediction of these properties, which are required...
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Application of Feed Forward Neural Networks for Modeling of Heat Transfer Coefficient During Flow Condensation for Low and High Values of Saturation Temperatur
PublicationMost of the literature models for condensation heat transfer prediction are based on specific experimental parameters and are not general in nature for applications to fluids and non-experimental thermodynamic conditions. Nearly all correlations are created to predict data in normal HVAC conditions below 40°C. High temperature heat pumps operate at much higher parameters. This paper aims to create a general model for the calculation...
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Experimental investigations on adiabatic frictional pressure drops of R134a during flow in 5mm diameter channel
PublicationThe article presents detailed two-phase adiabatic pressure drops data for refrigerant R134a at a saturation pressure of 5.5 bar corresponding to the saturation temperature of 19.4 °C. Study cases have been set for a mass flux varying from 100 to 500 kg/m2 s. The frictional pressure drop was characterized for the refrigerant R134a, for vapor qualities ranging from 0 to 1. Long-time thermal stability of test facility allowed to gather...
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Pool boiling of nanofluids on rough and porous coated tubes: experimental and correlation
PublicationThe paper deals with pool boiling of water-Al2O3 and water- Cu nanofluids on rough and porous coated horizontal tubes. Commercially available stainless steel tubes having 10 mm outside diameter and 0.6 mm wall thickness were used to fabricate the test heater. The tube surface was roughed with emery paper 360 or polished with abrasive compound. Aluminium porous coatings of 0.15 mm thick with porosity of about 40% were produced by...
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MRI assessment of ectopic fat accumulation in pancreas, liver and skeletal muscle in patients with obesity, overweight and normal BMI in correlation with the presence of central obesity and metabolic syndrome
PublicationPurpose: Obesity, defined as a body mass index (BMI) exceeding 30 kg/m2, is a serious health problem, which can be called an epidemic on a global scale and is one of the most important causes of preventable death. The aim of this study was to assess ectopic fat accumulation in pancreas, liver and skeletal muscle in patients with obesity, overweight and normal BMI in correlation with metabolic syndrome (MetS). Patients and methods:...
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REVIEW OF WEATHER FORECAST SERVICES FOR SHIP ROUTING PURPOSES
PublicationWeather data is nowadays used in a variety of navigational and ocean engineering research problems: from the obvious ones like voyage planning and routing of sea-going vessels, through the analysis of stability-related phenomena, to detailed modelling of ships’ manoeuvrability for collision avoidance purposes. Apart from that, weather forecasts are essential for passenger cruises and fishing vessels that want to avoid the risk...
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Evaluation and application of data from road weather stations for winter maintenance management
PublicationThe paper presents the analysis of road weather data from meteorological stations located at the Polish national roads of Pomerania District during the impact of winter conditions. Presented issue is particularly important from the point of view the problem of winter maintenance and especially for prediction and assurance of quality of asphalt pavement surface ie. resistance to low temperature cracking or risk of glazed frost....
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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 seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublicationMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...