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Wyniki wyszukiwania dla: ARTIFICIAL IN TELLIGENCE
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Embodying Intelligence in Autonomous and Robotic Systems with the Use of Cognitive Psychology and Motivation Theories
PublikacjaThe article discusses, on a certain level of abstraction and generalization, a coherent anthropological approach to the issue of controlling autonomous robots or agents. A contemporary idea can be based on appropriate modeling of the human mind using the available psychological knowledge. One of the main reasons for developing such projects is the lack of available and effective top-down approaches resulting from the known research...
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Optimized Computational Intelligence Model for Estimating the Flexural Behavior of Composite Shear Walls
PublikacjaThis article presents a novel approach to estimate the flexural capacity of reinforced concrete-filled composite plate shear walls using an optimized computational intelligence model. The proposed model was developed and validated based on 47 laboratory data points and the Transit Search (TS) optimization algorithm. Using 80% of the experimental dataset, the optimized model was selected by determining the unknown coefficients of...
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Corrosion resistance examinations of Ti6Al4V alloy with the use of potentiodynamic method in Ringer`s and artificial saliva solutions
PublikacjaThe research results of corrosion resistance of the Ti6Al4V alloy in the simulated body fluids (SBF) are presented. The polished specimens have shown better corrosion resistance than grinded surfaces in both liquids. The artificial saliva has revealed more aggressive test solution than Ringer`s solution. The pitting tendency has been observed in Ringer`s solution for grinded specimens.
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Designing of an effective structure of system for the maintenance of a technical object with the using information from an artificial neural network
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Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublikacjaOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...
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Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks
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The influence of ILs on TiO2 microspheres activity towards 5-FU removal under artificial sunlight irradiation
PublikacjaIn this work, the effect of various ionic liquids (ILs), namely, choline chloride [Chol][Cl], hexadecylpyridynium chloride [HDPy][Cl], and tributylmethylammonium chloride [TBMA][Cl], on the morphology, surface compo-sition in relation to photocatalytic oxidation of 5-fluorouracil (5-FU) and phenol in the presence of TiO2 pho-tocatalysts under artificial sunlight conditions was investigated. The highest photoactivity towards cytostatic...
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Biotrickling filtration of n-butanol vapors: process monitoring using electronic nose and artificial neural network
PublikacjaBiotrickling filtration is one of the techniques used to reduce odorants in the air. It is based on the aerobic degradation of pollutants by microorganisms located in the filter bed. The research presents the possibility of using the electronic nose prototype combined with artificial neural network for biofiltration process monitoring in terms of reduction in n-butanol concentration and odour intensity of treated air. The study...
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Scheduling with Complete Multipartite Incompatibility Graph on Parallel Machines: Complexity and Algorithms
PublikacjaIn this paper, the problem of scheduling on parallel machines with a presence of incompatibilities between jobs is considered. The incompatibility relation can be modeled as a complete multipartite graph in which each edge denotes a pair of jobs that cannot be scheduled on the same machine. The paper provides several results concerning schedules, optimal or approximate with respect to the two most popular criteria of optimality:...
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Analysis of the Degradation Process of Alginate-Based Hydrogels in Artificial Urine for Use as a Bioresorbable Material in the Treatment of Urethral Injuries
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Modelling relation between oxidation resistance and tribological properties of non-toxic lubricants with the use of artificial neural networks
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Predicting Performance of Lightweight Concrete with Granulated Expanded Glass and Ash Aggregate by Means of Using Artificial Neural Networks
PublikacjaLightweight concrete (LWC) is a group of cement composites of the defined physical, mechanical, and chemical performance. The methods of designing the composition of LWC with the assumed density and compressive strength are used most commonly. The purpose of using LWC is the reduction of the structure’s weight, as well as the reduction of thermal conductivity index. The highest possible strength, durability and low thermal conductivity...
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Mathematical modeling and prediction of pit to crack transition under cyclic thermal load using artificial neural network
PublikacjaThe formation of pitting is a major problem in most metals, which is caused by extremely localized corrosion that creates small holes in metal and subsequently, it changes into cracks under mechanical load, thermo-mechanical stress, and corrosion process factors. This research aims to study pit to crack transition phenomenon of steel boiler heat tubes under cyclic thermal load, and mathematical modeling...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublikacjaDesigning 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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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublikacjaDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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Artificial neural network prophecy of ion exchange process for Cu (II) eradication from acid mine drainage
PublikacjaThe removal of heavy metal ions from wastewater was found to be significant when the cation exchange procedure was used effectively. The model of the cation exchange process was built using an artificial neural network (ANN). The acid mine drainage waste’s Cu(II) ion was removed using Indion 730 cation exchange resin. Experimental data from 252 cycles were recorded. In a column study, 252 experimental observations validated the...
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Editorial: Applied intelligence and knowledge based systems: approaches and case studies - part 2
PublikacjaWydanie Cybernetics and Systems poswiecone zagadnieniom zarzadzania wiedza.
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From Individual to Collective: Intelligence Amplification with Bio-Inspired Decisional DNA and its Extensions
PublikacjaIn nature, deoxyribonucleic acid (DNA) contains the genetic instructions used in the development and functioning of all known living organisms. The idea behind our vision is to develop an artificial system, an architecture that would support discovering, adding, storing, improving and sharing information and knowledge among agents and organizations through experience. We propose a novel Knowledge Representation (KR) approach in...
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Manufacturing collective intelligence by the means of Decisional DNA and virtual engineering objects, process and factory
PublikacjaEngineering collective intelligence is paramount in current industrial times. This research proposes and presents case studies for collective knowledge structures required in the industry field. Knowledge structures such as Set of Experience and Decisional DNA are extended into more advanced knowledge structures for manufacturing processes. These structures are called Virtual Engineering Object, Virtual Engineering Process and...
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Optimal detection observers based on eigenstructure assignment. W: FaultDiagnosis. Models, artificial intelligence, applications. Ed. J. Korbicz, J.M. Kościelny, Z. Kowalczuk, W. Cholewa. Berlin: Springer Verlag**2004 s. 219-259, 7 rys. bibliogr. 41 poz. Optymalne obseratory detekcyjne oparte na strukturze własnej.
PublikacjaPraca dotyczy analitycznych metod syntezy algorytmów detekcji uszkodzeń. De-finiując wektor resztowy jako ważony błąd uzyskanej oceny wyjścia danego o-biektu, poszukuje się takich obserwatorów stanu, dostarczających owych osza-cowań, dla których wektor resztowy jest w możlwie wysokim stopniu niezależnyod niemierzalnych zakłóceń oddziałujących na obiekt oraz od niemierzalnychszumów w torach pomiarowych. Rozważa się algorytmy...
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The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification
PublikacjaDeveloping of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and...
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Artificial neural networks as a tool for selecting the parameters of prototypical under sleeper pads produced from recycled rubber granulate
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A review on application of artificial neural network (ANN) for performance and emission characteristics of diesel engine fueled with biodiesel-based fuels
PublikacjaBiodiesel has been emerging as a potential and promising biofuel for the strategy of reducing toxic emissions and improving engine performance. Computational methods aiming to offer numerical solutions were inevitable as a study methodology which was sometimes considered the only practical method. Artificial neural networks (ANN) were data-processing systems, which were used to tackle many issues in engineering and science, especially...
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Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublikacjaLine heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the...
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublikacjaThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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Applied intelligence and knowledge-based systems: challenges, approaches, nad case studies - part 1
PublikacjaPrzeanalizowano najnowsze kierunki badawcze i rozwojowe w obszarze zastosowań sztucznej inteligencji i systemów opartych na wiedzy
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Hybrid System for Ship-Aided Design Automation
PublikacjaA hybrid support system for ship design based on the methodology of CBR with some artificial intelligence tools such as expert system Exsys Developer along with fuzzy logic, relational Access database and artificial neural network with backward propagation of errors.
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Dynamic electrochemical impedance spectroscopy and polarization studies to evaluate the inhibition effect of benzotriazole on copper-manganese-aluminium alloy in artificial seawater
PublikacjaPrzeprowadzono badania wpływu benzotriazolu (BTA) na korozję nowego typ mosiądzu (CMA) w środowisku syntetycznej wody morskiej przy użyciu dynamicznej elektrochemicznej spektroskopii impedancyjnej (DEIS), techniki polaryzacji rezystancyjnej i ekstrapolacji krzywych Tafela. Wyniki pomiarowe otrzymane przy użyciu tych metod wskazują spadek szybkości korozji wraz ze wzrostem stężenia BTA. Wskazuje to na inhibicyjne własności BTA w...
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Energy Management for PV Powered Hybrid Storage System in Electric Vehicles Using Artificial Neural Network and Aquila Optimizer Algorithm
PublikacjaIn an electric vehicle (EV), using more than one energy source often provides a safe ride without concerns about range. EVs are powered by photovoltaic (PV), battery, and ultracapacitor (UC) systems. The overall results of this arrangement are an increase in travel distance; a reduction in battery size; improved reaction, especially under overload; and an extension of battery life. Improved results allow the energy to be used efficiently,...
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Artificial neural network model of hardness, porosity and cavitation erosion wear of APS deposited Al2O3 -13 wt% TiO2 coatings
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Effect of Melanin on the Stability of Casein Films Exposed to Artificially Accelerated UV Aging
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Application of computational intelligence models in IoMT big data for heart disease diagnosis in personalized health care
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Towards the 4th industrial revolution: networks, virtuality, experience based collective computational intelligence, and deep learning
PublikacjaQuo vadis, Intelligent Enterprise? Where are you going? The authors of this paper aim at providing some answers to this fascinating question addressing emerging challenges related to the concept of semantically enhanced knowledge-based cyber-physical systems – the fourth industrial revolution named Industry 4.0.
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Drill holes decrease cancellous bone strength: A comparative study of 33 paired osteoporotic human and 9 paired artificial bone samples
PublikacjaThis study was designed to compare compressive strength of cancellous bone retrieved from the femoral head in a specimen with and without guide wire hole, with comparison to synthetic bone samples. Femoral heads retrieved from 33 patients who sustained femoral neck fractures and underwent hip arthroplasty were cut into cuboids leaving two matching samples from the same femoral head. Similar samples were prepared from synthetic femurs....
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The Use of Artificial Neural Networks and Decision Trees to Predict the Degree of Odor Nuisance of Post-Digestion Sludge in the Sewage Treatment Plant Process
PublikacjaThis paper presents the application of artificial neural networks and decision trees for the prediction of odor properties of post-fermentation sludge from a biological-mechanical wastewater treatment plant. The input parameters were concentrations of popular compounds present in the sludge, such as toluene, p-xylene, and p-cresol, and process parameters including the concentration of volatile fatty acids, pH, and alkalinity in...
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Application of PSO-artificial neural network and response surface methodology for removal of methylene blue using silver nanoparticles from water samples
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An Impact Analysis of Artificial Light at Night (ALAN) on Bats. A Case Study of the Historic Monument and Natura 2000 Wisłoujście Fortress in Gdansk, Poland
PublikacjaThe artificial light at night (ALAN) present in many cities and towns has a negative impact on numerous organisms that live alongside humans, including bats. Therefore, we investigated if the artificial illumination of the historic Wisłoujście Fortress in Gdańsk, Poland (part of the Natura 2000 network), during nighttime events, which included an outdoor electronic dance music (EDM) festival, might be responsible for increased...
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Artificial Neural Network based fatigue life assessment of riveted joints in AA2024 aluminum alloy plates and optimization of riveted joints parameters
PublikacjaThe objective of this paper is to provide the fatigue life of riveted joints in AA2024 aluminum alloy plates and optimization of riveted joints parameters. At first, the fatigue life of the riveted joints in AA2024 aluminum alloy plates is obtained by experimental tests. Then, an artificial neural network is applied to estimate the fatigue life of riveted lap joints based on the number of lateral and longitudinal holes, punch pressure,...
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Idea zastosowania sztucznej inteligencji w prognozowaniu wpływu drgań komunikacyjnych na odpowiedź dynamiczną budynków mieszkalnych
PublikacjaW poniższym artykule autorzy analizują wpływ drgań komunikacyjnych na budynki mieszkalne oraz metodykę pomiarową według PN-85 B-02170 [1]. Problemem badawczym jest opracowanie prostej metody prognozowania wpływu drgań na budynki mieszkalne w taki sposób, aby nie było konieczne przeprowadzanie pracochłonnych i kosztownych pomiarów polowych. W tym celu wykonano analizę przy użyciu algorytmów opartych na sztucznej inteligencji oraz...
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Cognitive motivations and foundations for building intelligent decision-making systems
PublikacjaConcepts based on psychology fit well with current research trends related to robotics and artificial intelligence. Biology-inspired cognitive architectures are extremely useful in building agents and robots, and this is one of the most important challenges of modern science. Therefore, the widely viewed and far-reaching goal of systems research and engineering is virtual agents and autonomous robots that mimic human behavior in...
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Deep learning in the fog
PublikacjaIn the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...
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Particle swarm optimization–artificial neural network modeling and optimization of leachable zinc from flour samples by miniaturized homogenous liquid–liquid microextraction
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A vector-enzymatic DNA fragment amplification-expression technology for construction of artificial, concatemeric DNA, RNA and proteins for novel biomaterials, biomedical and industrial applications
PublikacjaA DNA fragment amplification/expression technology for the production of new generation biomaterials for scientific, industrial and biomedical applications is described. The technology enables the formation of artificial Open Reading Frames (ORFs) encoding concatemeric RNAs and proteins. It recruits the Type IIS SapI restriction endonuclease (REase) for an assembling of DNA fragments in an ordered head-to-tail-orientation. The...
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Optymalizacja treningu i wnioskowania sieci neuronowych
PublikacjaSieci neuronowe są jedną z najpopularniejszych i najszybciej rozwijających się dziedzin sztucznej inteligencji. Ich praktyczne wykorzystanie umożliwiło szersze użycie komputerów w wielu obszarach komunikacji, przemysłu i transportu. Dowody tego są widoczne w elektronice użytkowej, medycynie, a nawet w zastosowaniach militarnych. Wykorzystanie sztucznej inteligencji w wielu przypadkach wymaga jednak znacznej mocy obliczeniowej,...
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Wykorzystanie sztucznych sieci neuronowych do szacowania wpływu drgań na budynki jednorodzinne
PublikacjaW artykule przedstawiono metodę prognozowania wpływu drgań na budynki mieszkalne z wykorzystaniem sztucznych sieci neuronowych. Drgania komunikacyjne mogą doprowadzić do uszkodzenia elementów konstrukcyjnych, a nawet do awarii budynku. Najczęstszym efektem są jednak rysy, pękanie tynku i wypraw. Metody oparte na sztucznej inteligencji są przybliżone, ale stanowią wystarczająco dokładną i ekonomiczną alternatywę dla tradycyjnych...
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Emotions Embodied in the SVC of an Autonomous Driver System
PublikacjaA concept of embodied intelligence (EI) is considered. None of such implementations can be fully identified with artificial intelligence. Projects that dare to approach AI and EI should be based on both the AI concepts (symbolic and sub-symbolic), in solving real problems of perception and decision-making. Therefore, the EI, in this paper, is understood as a methodology that uses all available resources and algorithms from the...
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Dendron to Central Core S1–S1 and S2–Sn (n>1) Energy Transfers in Artificial Special Pairs Containing Dendrimers with Limited Numbers of Conformations
PublikacjaTwo dendrimers consisting of a cofacial free-base bisporphyrin held by a biphenylene spacer and functionalized with 4-benzeneoxomethane (5-(4-benzene)tri-10,15,20-(4-n-octylbenzene)zinc(II)porphyrin) using either five or six of the six available meso-positions, have been synthesized and characterized as models for the antenna effect in Photosystems I and II. The presence of the short linkers, -CH2O-, and long C8H17 soluble side...
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Evaluation of Immobilization of Selected Peat-Isolated Yeast Strains of the Species Candida albicans and Candida subhashii on the Surface of Artificial Support Materials Used for Biotrickling Filtration
PublikacjaThe paper describes the process of n-butanol abatement by unicellular fungi, able to deplete n-butanol content in gas, by using n-butanol as source of carbon. Isolated and identified fungi species Candida albicans and Candida subhashii were subjected to a viability process via assimilation of carbon from hydrophilic and hydrophobic compounds. The isolates, which exhibited the ability to assimilate carbon, were immobilized on four...
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Artificial neural network based fatigue life assessment of friction stir welding AA2024-T351 aluminum alloy and multi-objective optimization of welding parameters
PublikacjaIn this paper, the fracture behavior and fatigue crack growth rate of the 2024-T351 aluminum alloy has been investigated. At first, the 2024-T351 aluminum alloys have been welded using friction stir welding procedure and the fracture toughness and fatigue crack growth rate of the CT specimens have been studied experimentally based on ASTM standards. After that, in order to predict fatigue crack growth rate and fracture toughness,...
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Metody sztucznej inteligencji do wspomagania bankowych systemów informatycznych
PublikacjaW pracy opisano zastosowania nowoczesnych metod sztucznej inteligencji do wspomagania bankowych systemów informatycznych. Wykorzystanie w systemach informatycznych algorytmów ewolucyjnych, harmonicznych, czy sztucznych sieci neuronowych w połączeniu z nowoczesną technologią mikroprocesorową umożliwiają zasadniczy wzrost konkurencyjności banku. Dlatego w pracy omówiono wybrane zastosowania bankowe ze szczególnym uwzględnieniem zbliżeniowych...