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Search results for: E-LEARING
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Deterministic and statistical size effect during shearing of granular layer
PublicationArtykuł omawia deterministyczny i statystyczny efekt skali w materiałach granulowanych podczas ścinania cienkiej warstwy piasku między dwoma bardzo szorstkimi ścianami. Obliczenia wykonano metodą elementów skończonych na bazie mikropolarnego prawa hipoplastycznego. Pokazano wyniki efektu skali przy zastosowaniu różnych metod redukujących ilość realizacji pól losowych dla początkowego wskaźnika porowatości..
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Effect of cyclic shearing on the evolution of localisation of deformationsin granular bodies.
PublicationOmówiono wpływ cyklicznego ścinania na lokalizację odkształceń stycznych w materiałach granulowanych. Obliczenia wykonano metodą elementów skończonych na bazie mikropolarnego prawa hipoplastycznego dla wąskiej warstwy piasku. Obliczenia wykonano dla różnych amplitud ścinania i różnych początkowych zagęszczeń piasku.
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FE-simulations of direct and simple shearing within a polar hypoplasticity
PublicationW artykule przedstawiono wyniki analizy MES dwóch podstawowych testów w mechanice gruntów, mianowicie testu bezpośredniego ścinania i testu prostego ścinania. Obliczenia wykonano stosując metodę elementów skończonych i mikropolarne hipoplastyczne prawo konstytutywne. Szczególną uwagę zwrócono na wpływ warunków brzegowych na lokalizacje odkształceń.
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FE-analysis of shearing of granular bodies in a direct shear box
PublicationW artykule przedstawiono wyniki numerycznej obszernej analizy testu bezpośredniego ścinania. w materiałach granulowanych. Obliczenia wykonano stosując metodę elementów skończonych i mikropolarne hipoplastyczne prawo konstytutywne. Analizę wykonano dla różnego poziomu obciażenia, długości charakterystycznej, wskaźnika porowatości, długości próbki W analizie uwzględniono lokalizacje odkształceń stycznych.
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Porównanie własności smarnych wody, emulsji oleju w wodzie typu HFA-E oraz oleju Total Azolla 46 jako czynników roboczych w układach hydraulicznych = Comparison of the lubricant property of water oil-in-water emulsion type HFA-E and oil total Azolla 46 as working liquids in hydraulic systems
PublicationW artykule scharakteryzowano i opisano wyniki badań własności smarnych wody destylowanej, 1% emulsji oleju w wodzie typu HFA-E sporządzonej na bazie koncentratu do tworzenia emulsji Isosynth VH110BF, oleju Total Azolla 46 oraz, w celach porównawczych, samego koncentratu Isosynth VH110BF. Przedstawiono również wyniki badań powierzchniowego zużycia zmęczeniowego (pittingu), dla wyżej wymienionych czynników smarnych. Emulsja oleju...
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Bio and slide bearings: their lubrication by non-Newtonian fluids and application in non conventional systems. Vol.3. Tribology processes for cells human joints and micro-bearings
PublicationW niniejszej monografii przedstawiony został aktualny pogląd dotyczący procesu smarowania stawów człowieka od strony mechaniki, a szczególnie hydromechaniki i metod matematycznych. Wyznaczono pola prędkości przepływu lepkiej, odżywczej nie Newtonowskiej cieczy biologicznej, a także powstające siły tarcia w trakcie ruchu cieczy w warstwie granicznej wokoło współpracujących powierzchni. Dodatkowo rozpatrywano przepływy potencjalne...
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The pattern of verbal, visuospatial and procedural learning in Richardson variant of progressive supranuclear palsy in comparison to Parkinson’s disease
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Multimodal learning application with interactive animated character. [Multimodalna aplikacja edukacyjna wykorzystująca interaktywną animowaną postać]
PublicationThe aim of this study is to design a computer application that may assist teachers and therapists in multimodal manner in their work with impaired or disabled children. The application can be operated in many different ways, giving to a child with special educational needs a possibility to learn and train many skills or treat speech disorders. The main stress in this research is on the creation of animated character that will serve...
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Up-regulation of ferritin ubiquitination in skeletal muscle of transgenic rats bearing the G93A hmSOD1 gene mutation
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Universal Predictors of Dental Students’ Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
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A new methodological approach to the noise threat evaluation based on the selected physiological properties of the human hearing system
PublicationA new way of assessment of noise-induced harmful effects on human hearing system is presented in the paper. The method takes into consideration properties of the selected physiological human hearing system. On the basis of the hearing examinations and noise measurements results and psychoacoustical noise dosimeter performance the new indicators of the noise harmfulness were proposed. The evaluation of the proposed indicators were...
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Experimental investigations and prediction of WEDMed surface of nitinol SMA using SinGAN and DenseNet deep learning model
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Synthesis and photochemical properties of unsymmetrical phthalocyanine bearing two 1-adamantylsulfanyl groups at adjacent peripheral positions
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Detection of Cystic Fibrosis Symptoms Based on X-Ray Images Using Machine Learning- Pilot Study
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Early Predictors of Learning a Foreign Language in Pre-school – Polish as a First Language, English as a Foreign Language
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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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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublicationData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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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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Assessment of Failure Occurrence Rate for Concrete Machine Foundations Used in Gas and Oil Industry by Machine Learning
PublicationConcrete machine foundations are structures that transfer loads from machines in operation to the ground. The design of such foundations requires a careful analysis of the static and dynamic effects caused by machine exploitation. There are also other substantial differences between ordinary concrete foundations and machine foundations, of which the main one is that machine foundations are separated from the building structure....
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublicationThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublicationMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Tilting pad thrust bearing with novel material selection - experimental comparison of low and medium speed operation
PublicationThe advances in material engineering led to the development of hard carbon based coatings applied in numerous applications in order to prevent or minimize wear of the parts in contact. With Triondur® coatings, the bearing company Schaeffler has succeeded in halving the friction losses in the valve trains of passenger cars. The coatings are optimized for high abrasive wear protection and low sliding friction moments. Altogether...
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Proposal for calculating the bearing capacity of screw displacement piles in non-cohesive soils based on CPT results
PublicationPrzedstawienie wyników badań terenowych pali przemieszczeniowych wkręcanych, zrealizowanych w ramach projektu badawczego MNiSW. Propozycja dwóch metod obliczania nośności pali przemieszczeniowych wkręcanych w niespoistym podłożu gruntowym na podstawie wyników badań CPT. Metody dostosowano do wytycznych Eurokodu 7. Weryfikacja metod obliczeniowych z wynikami badań terenowych pali.
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Bearing capacity of piles based on static load tests and calculation principles provided by EN 1997-1
PublicationW artykule scharakteryzowano i przeanalizowano ogólne zalecenia Eurokodu 7 dotyczące wyznaczania nośności pali na podstawie próbnych obciążeń statycznych. Porównano je z zaleceniami dotychczasowej polskiej normy PN-83/B-02482. Przedstawiono kilka przykładów interpretacji rzeczywistych wyników próbnych obciążeń pali według zaleceń wyżej wymienionych dwóch norm wraz z analizą porównawczą.
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Towards the 4th industrial revolution: networks, virtuality, experience based collective computational intelligence, and deep learning
PublicationQuo 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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Cloud solutions as a platform for building advanced learning platform, that stimulate the real work environment for project managers
PublicationImproving skills of managers and executives require, that during the transfer of knowledge (in different ways: during studies, trainings, workshops and other forms of education) it is necessary to use tools and solutions that are (or will be) used in real world environments, where people being educated are working or will work. Cloud solutions allow educational entities (universities, training companies, trainers, etc.) to provide...
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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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Experimental Research on Insufficient Water Lubrication of Marine Stern Tube Journal Bearing with Elastic Polymer Bush
PublicationWater-lubricated bearings with polymer bushes are steadily gaining popularity due to their advantages, including environmental friendliness, relatively simple construction and long-term operation. Nevertheless, in practice instances of damage to such bearings occur due to insufficient or absent flow of the lubricating agent. In this study, experimental tests established that elastic polymer bush bearing is capable of operating...
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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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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublicationOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublicationAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublicationIn this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model has been used. The task is to predict simultaneously and independent of each characteristic parameters of a buried object of several radii at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable...
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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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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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Process [Intellectual Output 2] Guidelines for a design process leading to a high-quality Baukultur in the digital age
PublicationThe main aim of the intellectual output “Process” is to identify, explore and evaluate new design processes for shaping the built environment, which are informed, collaborative, and adaptable, allow customization and are generally enabled by the application of digital tools. Further, it aims at creating methodological guidelines for future-oriented design processes leading to a high-quality Baukultur in the digital age. The guidelines...
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Projekt Leonardo da Vinci EMDEL (European Model for Distance Education and Learning) - otwarte szkolenia online.
PublicationW referacie zaprezentowano główne zadania oraz ofertę szkoleniową Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej (CEN PG) w kontekście realizowanych projektów Unii Europejskiej. Przedstawiono projekt Leonardo da Vinci EMDEL - European Model for Distance Education and learning - realizowany przez CEN PG w latach 2001-2005 oraz opisano doświadczenia w zakresie adaptacji i lokalizacji opracowanych przez partnerów projektu...
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Numerical Determination of the Load-Bearing Capacity of a Perforated Thin-Walled Beam in a Structural System with a Steel Grating
PublicationThis article presents the results of numerical simulations of a structural system consisting of steel perforated thin-walled beams and a steel grating. The simulations were conducted using the finite element method. The analysis took into account physical and geometric nonlinearity as well as the contact between the steel grating and the beams. The main goal of the research was to develop load-bearing curves for the main beam in...
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Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublicationThe rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...
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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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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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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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Contribution of non-carbonate inorganic and organic alkalinity to total measured alkalinity in pore waters in marine sediments (Gulf of Gdansk, S-E Baltic Sea)
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Different Ways to Apply a Measurement Instrument of E-Nose Type to Evaluate Ambient Air Quality with Respect to Odour Nuisance in a Vicinity of Municipal Processing Plants
PublicationThis review paper presents different ways to apply a measurement instrument of e-nose type to evaluate ambient air with respect to detection of the odorants characterized by unpleasant odour in a vicinity of municipal processing plants. An emphasis was put on the following applications of the electronic nose instruments: monitoring networks, remote controlled robots and drones as well as portable devices. Moreover, this paper presents...
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Ekspertyza dotycząca oceny stanu technicznego stalowej konstrukcji wiaty na peronie wyspowym linii E-65 na stacji kolejowej w Sopocie
PublicationOpracowanie dot.stanu zachowania zabytkowej wiaty (zasadnicza konstrukcja - stalowa) nad peronem stacji kolejowej w Sopocie z propozycją wykonania prac konserwatorskich.
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Cassirer E. Język i mit. Przyczynek do zagadnienia imion bogów.Przekład, wstęp i opracowanie: Przemysław Parszutowicz.. Wydaw. Marek Drzewiecki,2021
PublicationRozprawa Cassirera pochodzi z najważniejszego bodaj okresu jego twórczości – okresu współpracy z Biblioteką Warburga – i mimo niewielkich rozmiarów jest w dużej mierze reprezentatywna, tak gdy idzie o wykorzystywaną przez niego metodę, jak i o główny obszar jego zainteresowań badawczych. Stanowi bezpośrednie nawiązanie do rozprawy Hermanna Usenera Götternamen. Versuch einer Lehre von der religiösen Begriffsbildung. Pod względem...
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Lasing modes of infinite periodic chain of quantum wires
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QUANTITATIVE EASING POLICY AND ITS IMPACT ON THE GLOBAL ECONOMY
PublicationBased on the analysis of the impact of quantitative easing policies on the global economy, there was concluded that the world’s largest central banks and widespread debt stimulation have created the model of economic growth. This model was based on the productivity growth. The lack of productivity growth in the developed world, the active integration of developing countries (first of all China and India) in the global economy have...