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Wyniki wyszukiwania dla: DEEP REINFORCEMENT LEARNING
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Textile reinforced concrete members subjected to tension, bending, and in-plane loads: Experimental study and numerical analyses
PublikacjaTextile reinforced concrete has raised increasing research interest during the last years, mainly due to its potential to be used for freeform shell structures involving complex load situations. Yet, most experimental work has focused on test setups with primarily uniaxial loading. In the current work, such setups are complemented with a novel test setup of deep beams, including in-plane bending and shear. Further, nonlinear finite...
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Koncepcja systemu wspomagania decyzji nawigatora statku opartego na ewolucyjnym planowaniu manewrów antykolizyjnych
PublikacjaArtykuł przedstawia koncepcję systemu wspomagania decyzji nawigatora statku opartego na wątkach badań prowadzonych wcześniej przez autora. System będzie rozszerzał funkcjonalność systemów dotychczasowych o możliwość szczegółowego planowania bezpiecznej trajektorii statku na wodach zamkniętych, z dużą liczbą statków obcych i ograniczeniami toru wodnego. Artykuł zawiera dyskusję możliwych podejść do planowania manewrów, optymalizacji...
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Akustyczna analiza parametrów ruchu drogowego z wykorzystaniem informacji o hałasie oraz uczenia maszynowego
PublikacjaCelem rozprawy było opracowanie akustycznej metody analizy parametrów ruchu drogowego. Zasada działania akustycznej analizy ruchu drogowego zapewnia pasywną metodę monitorowania natężenia ruchu. W pracy przedstawiono wybrane metody uczenia maszynowego w kontekście analizy dźwięku (ang.Machine Hearing). Przedstawiono metodologię klasyfikacji zdarzeń w ruchu drogowym z wykorzystaniem uczenia maszynowego. Przybliżono podstawowe...
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Distortion of speech signals in the listening area: its mechanism and measurements
PublikacjaThe paper deals with a problem of the influence of the number and distribution of loudspeakers in speech reinforcement systems on the quality of publicly addressed voice messages, namely on speech intelligibility in the listening area. Linear superposition of time-shifted broadband waves of a same form and slightly different magnitudes that reach a listener from numerous coherent sources, is accompanied by interference effects...
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Damage of a post-tensioned concrete bridge – Unwanted cracks of the girders
PublikacjaThe cracking of a post-tensioned T-beam superstructure, which was built using the incremental launching method, is analyzed in the paper. The problem is studied in detail, as specific damage was observed in the form of longitudinal cracks, especially in the mid-height zone of the girder at the interface of two assembly sections. The paper is a case study. A detailed inspection is done and non-destructive testing results of the...
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A note on total reinforcement in graphs
PublikacjaIn this note we prove a conjecture and inprove some results presendet in a recent paper of N. Sridharan, M.D. Elias, V.S.A. Subramanian, Total reinforcement number of a graph, AKCE Int. J. Graphs Comb. 4 (2) (2007) 197-202.
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Alternative way of the main reinforcement anchorage in reinforced short cantilevers
PublikacjaThe results of the experimental investigation of the reinforced corbels and dapped end beams with steel studs were introduced in the work. The efficiency of this type of the reinforcement was compared with the typical reinforcenet applied in reinforced conctrete construcions.
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Federated Learning in Healthcare Industry: Mammography Case Study
PublikacjaThe paper focuses on the role of federated learning in a healthcare environment. The experimental setup involved different healthcare providers, each with their datasets. A comparison was made between training a deep learning model using traditional methods, where all the data is stored in one place, and using federated learning, where the data is distributed among the workers. The experiment aimed to identify possible challenges...
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Influence of effective width of flange on calculation and reinforcement dimensioning of beam of reinforced concrete frame
PublikacjaThe paper analyses the influence of modelling the cross-section of a beam in two-storey reinforced concrete frame of industrial warehouse with dimensions: 18.0 m × 32.0 m using bar elements on the results of bending moments, the value of elastic deflection and the dimensioning of reinforcement due to bending. Six options were considered: a beam as a rectangular section and five T-beam variants with different definitions of effective...
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Assessing the attractiveness of human face based on machine learning
PublikacjaThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublikacjaTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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Lifelong Learning Idea in Architectural Education
PublikacjaThe recent advances in IT and technology are forcing changes in the approach to educating society. In the 20th century, life-long learning was understood as educating adults in order to improve their occupational qualifications. Life-long learning allows the needs of the present-day world to be addressed through providing the individual with education at every stage of his/her life various forms. The search for a new model...
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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublikacjaIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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Knowledge sharing and knowledge hiding in light of the mistakes acceptance component of learning culture- knowledge culture and human capital implications
PublikacjaPurpose: This study examines the micromechanisms of how knowledge culture fosters human capital development. Method: An empirical model was developed using the structural equation modeling method (SEM) based on a sample of 321 Polish knowledge workers employed in different industries. Findings: This study provides direct empirical evidence that tacit knowledge sharing supports human capital, whereas tacit knowledge hiding does...
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Speech Analytics Based on Machine Learning
PublikacjaIn this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...
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Basic sensitivity analysis of a telecommunication tower complementing standard reinforcement design process
PublikacjaThis paper presents straightforward sensitivity assessment of a telecommunication tower. The analysis is set toidentify the elements of the tower which may be reinforced with the greatest structural advantage. As current expertopin ions on structural redesign of similar structures due to a planned addition of extra loads are mainly based ondeterministic computations or engineering intuition,...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublikacjaIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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MANAGING LEARNING PROCESS WITH E-LEARNING TOOL
PublikacjaThis article presents one possibility to employ Moodle, the free e-Leaning platform, to organize learning understood as a process. Behavioral approach and application to massive courses are assumed. A case study is presented, where the introduction of Moodle resulted in better student performance in homework
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A Comparison of STI Measured by Direct and Indirect Methods for Interiors Coupled with Sound Reinforcement Systems
PublikacjaThis paper presents a comparison of STI (Speech Transmission Index) coefficient measurement results carried out by direct and indirect methods. First, acoustic parameters important in the context of public address and sound reinforcement systems are recalled. A measurement methodology is presented that employs various test signals to determine impulse responses. The process of evaluating sound system performance, signals enabling...
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Blended Learning Model for Computer Techniques for Students of Architecture
PublikacjaAbstract: The article summarizes two-year experience of implementing hybrid formula for teaching Computer Techniques at the Faculty of Architecture at the Gdansk University of Technology. Original educational e-materials, consisting of video clips, text and graphics instructions, as well as links to online resources are embedded in the university e-learning educational platform. The author discusses technical constraints associated...
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Problems of reinforcement designing for plates
PublikacjaPrzedstawiono problem projektowania zbrojenia nietrajektorialnego płyt w aspekcie ich odkształcalności. Na podstawie niektórych wyników badań doświadczalnych, przeprowadzonych na żelbetowych płytach skręcanych, zweryfikowano procedury wymiarowania. Analiza wykazuje, że pomimo formalnego zapewnienia nośności przekroju płyt nietrajektorialnie zbrojonych, ich odkształcalność znacznie wzrasta. Aby zapewnić im sztywność na poziomie...
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Verification of selected calculation methods regarding shear strength in beams without web reinforcement
PublikacjaThe purpose of the article was to compare selected calculation methods regarding shear strength in reinforced concrete beams without web reinforcement. Several calculation methods were tested. This included codes: PN-EN 1992-1-1:2008, ACI 318-14 and fib Model Code for Concrete Structures 2010. The analysis also consists of authorial methods published in technical literature. Calculations of shear strengths were made based on experimental...
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublikacjaDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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Social learning in cluster initiatives
PublikacjaPurpose – The purpose of the paper is to portray social learning in cluster initiatives (CIs), namely: 1) to explore, with the lens of the communities of practice (CoPs) theory, in what ways social learning occurs in CIs; 2) to discover how various CoPs emerge and evolve in CIs to facilitate a collective journey in their learning process. Subsequently, the authors address the research questions: In what ways does social learning...
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TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublikacjaTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublikacjaIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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EXPERIMENTAL AND THEORETICAL FLOW OF THE FORCES IN DEEP BEAMS WITH CANTILEVAR
PublikacjaThis article presents the results of experimental research carried out on deep beams with cantilever which was loaded throughout the depth. The main deep beam was directly simply supported on the one side. On the other side the deep beam was suspended in another deep member situated at right angles. All deep beams created a spatial arrangement. The paper is focused on the analysis of the cracks morphology and flow of the internal...
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Experiments and calibration of a bond-slip relation and efficiency factors for textile reinforcement in concrete
PublikacjaTextile reinforcement yarns consist of many filaments, which can slip relative each other. At modelling of the global structural behaviour, interfilament slip in the yarns, and slip between the yarns and the concrete can be considered by efficiency factors for the stiffness and strength of the yarns, and by applying a bond-slip relation between yarns and concrete. In this work, an effective and robust method for calibration of...
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The effect of multiaxial geocomposite reinforcement on fatigue performance and crack propagation delay in double-layered asphalt beams
PublikacjaThe presented study investigates the effect of a recently developed multiaxial geocomposite made of polypropylene geogrid and non-woven fabric on the delay of crack propagation, based on four-point bending tests of large asphalt concrete beams – both for reinforced and non-reinforced specimens. Several approaches are described in this study, including analysis of stiffness modulus decrease and analysis of crack propagation using...
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Model szkolenia "Blended learning" z wykorzystaniem platformy Oracle I-learning.
PublikacjaW artykule zaproponowano modele organizacyjne szkoleń "blended learning", które pokazują możliwości współpracy firm prywatnych z instytucjami edukacyjnymi w dziedzinie e-learningu. W ramach wspólnego eksperymentu firm Oracle, Incenti S.A., WiedzaNet Sp. z o.o. oraz Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej w semestrze letnim roku akademickiego 2003/2004 udostępniony będzie kurs dla studentów Wydziału Inzynierii Lądowej...
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The impact of the AC922 Architecture on Performance of Deep Neural Network Training
PublikacjaPractical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...
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Hybrid all-cellulose reinforcement in polypropylene matrix biocomposites for injection moulding - influence of particle geometry and volume fraction on hybrid effect
PublikacjaThe presented study is focused on evaluation of influence of reinforcement volume fraction and geometry on the occurrence of positive hybrid effect by the hybridisation of man-made cellulose fibres (rayon viscose) with cellulose microparticle fillers applied in polypropylene matrix. Four volume fractions of reinforcement were used at 1:1 combination of short man-made cellulose fibres with cellulose microfillers of different aspect...
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Broadband interference in speech reinforcement systems
PublikacjaArtykuł podejmuje niedoceniany problem wpływu liczby i rozkładu głośników w systemach nagłośnienia, na jakość przekazu głosowego, czyli na zrozumiałość mowy w audytoriach. Superpozycji przesuniętych w czasie szerokopasmowych sygnałów o tym samym kształcie i lekko różnych wielkościach, które docierają do słuchacza z licznych spójnych źródeł, towarzyszy zjawisko interferencji prowadzące do głębokiej modyfikacji odbieranych sygnałów...
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A Closed Bipolar Electrochemical Cell for the Interrogation of BDD Single Particles: Electrochemical Advanced Oxidation
PublikacjaA closed bipolar electrochemical cell containing two conductive boron-doped diamond (BDD) particles of size 250 – 350 m, produced by high-pressure high-temperature (HPHT) synthesis, has been used to demonstrate the applicability of single BDD particles for electrochemical oxidative degradation of the dye, methylene blue (MB). The cell is fabricated using stereolithography 3D printing and the BDD particles are located at either...
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E-learning versus traditional learning - Polish case
PublikacjaE-learning jest współczesnym fenomenem, który pozwala na dostęp do kształcenia i treści edukacyjnych, niezależnie od czasu i miejsca, dla każdego użytkownika. E-learnig tworzy ogromne możliwości dla uczelni akademickich, organizacji, instytucji komercyjnych i szkoleniowych, dostarczając na żądanie kształcenia i szkoleń w wirtualnym środowisku. Student może stworzyć własny plan kształcenia, dostosowując go do swojej pracy i sytuacji...
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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublikacjaIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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FRP-based reinforcement coatings of steel with application prospects in ships and offshore structures: a review
PublikacjaLatest research on novel FRP-based anti-corrosion structural coatings (for enhancing structural capacity and strengthening the coating layer) is discussed with application prospects for ships and offshore structures. In the marine environment, structures constantly face corrosion and fatigue cracks. Combining this with high operational and wave loads, it might cause a structural collapse. Recently, polymer composites have been...
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Explainable machine learning for diffraction patterns
PublikacjaSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublikacjaMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
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Cellulose Nanofibers Isolated from the Cuscuta Reflexa Plant as a Green Reinforcement of Natural Rubber
PublikacjaIn the present work, we used the steam explosion method for the isolation of cellulose nanofiber (CNF) from Cuscuta reflexa, a parasitic plant commonly seen in Kerala and we evaluated its reinforcing efficiency in natural rubber (NR). Fourier Transform Infrared Spectroscopy (FTIR), X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), and Thermogravimetric analysis (TGA) techniques...
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Minimal transverse reinforcement of reinforced concrete members
PublikacjaW pierwszej części pracy omówiono zagadnienia dotyczące minimalnego zbrojenia na ścinanie elementów żelbetowych w kontekście norm europejskich oraz pozaeuropejskich. W drugiej części pracy dokonano analizy wyników badań eksperymentalnych dotyczących nośności elementów bez zbrojenia poprzecznego, które stanowią podstawę do weryfikacji zaleceń normowych w zakresie minimalnego zbrojenia na ścinanie.
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Face with Mask Detection in Thermal Images Using Deep Neural Networks
PublikacjaAs the interest in facial detection grows, especially during a pandemic, solutions are sought that will be effective and bring more benefits. This is the case with the use of thermal imaging, which is resistant to environmental factors and makes it possible, for example, to determine the temperature based on the detected face, which brings new perspectives and opportunities to use such an approach for health control purposes. The...
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Deep Eutectic Solvents and Their Uses for Air Purification
PublikacjaChemical compounds released into the air by the activities of industrial plants and emitted from many other sources, including in households (paints, waxes, cosmetics, disinfectants, plastic (PVC) flooring), may affect the environment and human health. Thus, air purification is an important issue in the context of caring for the condition of the environment. Deep eutectic solvents (DESs) as liquids with environmentally friendly...
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Blended Learning in Teaching Safety of Electrical Installations
PublikacjaBlended learning becomes more commonly used in teaching information technology or other subjects, which involve practice in computer laboratories. In case of subjects with no access to computer rooms blended learning supports lecturing and teaching classes e.g. interactive lessons. The article presents the use of blended learning forms in Gdansk University of Technology in teaching the subject of Safety of Electrical Installations....
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Supramolecular deep eutectic solvents and their applications
PublikacjaIn recent years, the growing awareness of the harmfulness of chemicals to the environment has resulted in the development of green and sustainable technologies. The compromise between economy and environmental requirements is based on the development of new efficient and green solutions. Supramolecular deep eutectic solvents (SUPRADESs), a new deep eutectic solvent (DES) subclass characterized by inclusion properties, are a fresh...
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Discussion:Horizontal stress increase induced by deep vibratory compaction
PublikacjaDeep compaction control of granular material using the results of field tests. The analysis include the CPTU and DMT tests terformed before and after compaction works.
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Magnetic deep eutectic solvents – Fundamentals and applications
PublikacjaMagnetic deep eutectic solvents (MDES), a relatively new subclass of conventional deep eutectic solvents (DES) containing additional paramagnetic components in their structure. MDES exhibit a strong response toward external magnetic fields, thus they can improve many industrial and analytical applications. In addition, this new group of solvents present unique physicochemical properties that can be easily tuned by selecting the...
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Edge-Computing based Secure E-learning Platforms
PublikacjaImplementation of Information and Communication Technologies (ICT) in E-Learning environments have brought up dramatic changes in the current educational sector. Distance learning, online learning, and networked learning are few examples that promote educational interaction between students, lecturers and learning communities. Although being an efficient form of real learning resource, online electronic resources are subject to...