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Search results for: alphafold, blind prediction, capri, casp, deep learning, protein assemblies, protein complexes, protein-protein interaction
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change with Focus on Organizational Culture and Organizational Learning
PublicationTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Open source solution LMS for supporting e-learning/blended learning engineers
PublicationW artykule zaprezentowano darmowe systemy zarządzania kształceniem na odległość wspomagające e-learningowe/mieszane nauczanie inżynierów. Pierwszy system TeleCAD został opracowany w ramach projektu Leonardo da Vinci (1998-2001). System TeleCAD był propozycją w projekcie V Ramowy CURE (2003-2006). W roku 2003 dzięki projektowi Leonardo da Vinci EMDEL (2001-2005) Centrum Edukacji Niestacjonarnej Politechniki Gdańskiej wybrało system...
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Efficient Extraction of Fermentation Inhibitors by Means of Green Hydrophobic Deep Eutectic Solvents
PublicationThe methods for hydrogen yield efficiency improvements, the gaseous stream purification in gaseous biofuels generation, and the biomass pretreatment are considered as the main trends in research devoted to gaseous biofuel production. The environmental aspect related to the liquid stream purification arises. Moreover, the management of post-fermentation broth with the application of various biorefining techniques gains importance....
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Simulation of fluid structure interaction in a novel design of high pressure axial piston hydraulic pump
PublicationA novel type of an axial, piston-driven high pressure hydraulic pump with variable capacity marks a significant improvement in the area of the hydraulic machinery design. Total discharge from hydrostatic forces eliminates a need for a servomechanism, thus simplifying operation, reducing weight and introducing the possibility of the pump displacement control by computer. PWK-type pumps, invented in the Gdansk University of Technology,...
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Closer look into the structures of tetrabutylammonium bromide–glycerol-based deep eutectic solvents and their mixtures with water
PublicationIn recent years, deep eutectic solvents (DES) and it’s mixture with water have become more and more attention as green solvents used in chemistry. However, there are only a few theoretical studies on the mechanisms of pure DES and DES-water complex formation. Therefore, the structural properties of tetrabutylammonium bromide–glycerol-based deep eutectic solvents and their mixtures with water have been investigated by means of Molecular...
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Sensitivity of the Baltic Sea level prediction to spatial model resolution
Publicationhe three-dimensional hydrodynamic model of the Baltic Sea (M3D) and...
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AN INNOVATIVE APPROACH TO PREDICTION ENERGETIC EFFECTS OF WOOD CUTTING PROCESS WITH CIRCULAR-SAW BLADES
PublicationIn the classical approach, energetic effects (cutting forces and cutting power) of wood sawing process are generally calculated on the basis of the specific cutting resistance, which is in the case of wood cutting the function of more or less important factors. The aim of the paper is to present a new calculating model using the application of modern fracture mechanics and to compare cutting parameters of native beech, Bendywood...
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Playback detection using machine learning with spectrogram features approach
PublicationThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Interaction of Acoustic and Thermal Modes in the Gas with Nonequilibrium Chemical Reactions: Possibilities of Acoustic Cooling
PublicationNonlinear generation of thermal mode during propagation of dominative sound in a chemically reacting gas is considered. The dynamic equation of excess temperature associated with the thermal mode is derived. It is instantaneous and includes quadratic nonlinear acoustic source reflecting the nonlinear character of interaction between acoustic and non-acoustic types of gas motion. Both periodic and aperiodic sound may be considered...
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Distance learning trends: introducing new solutions to data analysis courses
PublicationNowadays data analysis of any kind becomes a piece of art. The same happens with the teaching processes of statistics, econometrics and other related courses. This is not only because we are facing (and are forced to) teach online or in a hybrid mode. Students expect to see not only the theoretical part of the study and solve some practical examples together with the instructor. They are waiting to see a variety of tools, tutorials,...
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numerical prediction of vortex generated by hydrofoil
PublicationW pracy przedstawiono wyniki obliczeń programami Fluent i Comet dla płata śruby napędowej. Pola prędkości oraz wirowość za płatem porównano z wynikami pomiarów (LDA- Laser Doppler Anemometry) w tunelu kawitacyjnym Centrum Techik Okrętowych (CTO). Przedstawiono wpływ adaptacji siatki wg różnych kryteriów (lokalnej wirowości lub prędkości) na zgodność wyników obliczeń z danymi eksperymentalnymi.
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Toward Prediction of Environmental Arctic Change
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Bankruptcy Prediction - History, Present and Future.
PublicationW artykule przedstawiono krótką wzmiankę dotyczącą dotychczasowych badań w obszarze zagrożenia przedsiębiorstw upadłością, techniki wykorzystywane do budowy modeli prognozowania upadłości przedsiębiorstw oraz metody stosowane w analizie porównawczej tego typu modeli.
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COMPARISON OF BLOOD PRESSURE PREDICTION METHODS
PublicationIn the paper dierent approaches of predicting blood pressure values are presented. Basically, two methods and theirs modifications are considered. In total, seven algorithms have been examined. Tests have been conducted using both synthetic and clinical data. From our study it follows that none of the examined methods is superior to other.
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublicationA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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Mapping the Structural and Dynamic Determinants of pH-Sensitive Heparin Binding to Granulocyte Macrophage Colony Stimulating Factor
PublicationGranulocyte macrophage colony stimulating factor (GMCSF) is an immunomodulatory cytokine that is harnessed as a therapeutic. GMCSF is known to interact with other clinically important molecules, such as heparin, suggesting that endogenous and administered GMCSF has the potential to modulate orthogonal treatment outcomes. Thus, molecular level characterization of GMCSF and its interactions with biologically active compounds is critical...
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Optimization of parallel implementation of UNRES package for coarse‐grained simulations to treat large proteins
PublicationWe report major algorithmic improvements of the UNRES package for physics-based coarse-grained simulations of proteins. These include (i) introduction of interaction lists to optimize computations, (ii) transforming the inertia matrix to a pentadiagonal form to reduce computing and memory requirements, (iii) removing explicit angles and dihedral angles from energy expressions and recoding the most time-consuming energy/force terms...
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Extremophile Deinococcus geothermalis as potential source of proteolytic enzymes
PublicationAmong many extremozymes, thermophilic enzymes have attracted most attention during the past four decades. Such enzymes are of considerable industrial and biotechnological interest due to the fact that the enzymes are better suited for harsh industrial processes. There are many advantages of conducting industrial processes at high temperature, such as the increased solubility of many polymeric substrates, resulting in decreased...
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Saccharides
PublicationSaccharides are widely distributed in nature as the major component of fruits and vegetables (primarily monosaccharides), milk and malt (mainly disaccharides), and grains (mostly polysaccharides). They are an important source of energy, structural material, as well as flavor and taste factors. Molecules of this class of compounds contain mainly carbon, hydrogen, and oxygen atoms; however, most natural saccha- rides do not have...
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In silico design of telomerase inhibitors.
PublicationTelomerase is a reverse transcriptase enzyme involved in DNA synthesis at the end of linear chromosomes. Unlike in most other cells, telomerase is reactivated most cancerous cells and, therefore, has become a promising new anticancer target. Despite extensive research, direct telomerase inhibitors have yet not been introduced to the clinics because of the complexity of this enzyme. Structures of this protein from simple organisms...
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Amino Acid Based Antimicrobial Agents – Synthesis and Properties
PublicationStructures of several dozen of known antibacterial, antifungal or antiprotozoal agents are based on the amino acid scaffold. In most of them, the amino acid skeleton is of a crucial importance for their antimicrobial activity, since very often they are structural analogs of amino acid intermediates of different microbial biosynthetic pathways. Particularly, some aminophosphonate or aminoboronate analogs of protein amino acids are...
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User -friendly E-learning Platform: a Case Study of a Design Thinking Approach Use
PublicationE-learning systems are very popular means to support the teaching process today. These systems are mainly used by universities as well as by commercial training centres. We analysed several popular e-learning platforms used in Polish universities and find them very unfriendly for the users. For this reason, the authors began the work on the creation of a new system that would be not only useful, but also usable for students, teachers...
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Soil-structure interaction effects on modal parameters of office buildings with different number of stories
PublicationThe paper summarizes the results of a numerical investigation designed to study the soil-structure interaction effects on modal parameters of three office buildings. The reinforced-concrete 4-storey, 8-storey, and 12-storey office buildings, each with additional two levels of embedded basements, represent low, medium, and high-rise structures, respectively. In order to conduct this research, detailed finite-element structure models...
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Solubility advantage of sulfanilamide and sulfacetamide in natural deep eutectic systems: experimental and theoretical investigations
PublicationObjective: The aim of this study was to explore the possibility of using natural deep eutectic solvents (NADES) as solvation media for enhancement of solubility of sulfonamides, as well as gaining some thermodynamic characteristics of the analyzed systems. Significance: Low solubility of many active pharmaceutical ingredients is a well-recognized difficulty in pharmaceutical industry, hence the need for different strategies addressing...
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Electromodulation of monomer and excimer phosphorescence in vacuum-evaporated films of platinum (II) complexes of 1,3-di(2-pyridyl)benzenes
PublicationElectric field-modulated photoluminescence (EML) measurements are presented for vacuum-evaporated films of cyclometallated Pt (II) complexes of 1,3-di(2-pyridyl) benzenes used as triplet emitters in organic light-emitting diodes (OLEDs). The excimer phosphorescence is quenched by the external electric field of 2.5 MV/cm up to 25% but the same effect on monomer phosphorescence is one order of magnitude smaller. The higher quenching...
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Coordination polymers and molecular structures among complexes of mercury(II) halides with selected 1-benzoylthioureas
PublicationSix new 1-benzoyl-3-phenylthiourea and 1-benzoyl-3-(2-methylphenyl)thiourea complexes of mercury( II) were obtained in the reactions of the ligands with HgX2 in methanol (X = Cl, Br, I). Their structures, determined by single-crystal X-ray diffraction analysis, exhibit different stoichiometries and molecular organization. Coordination centers adopt more or less distorted tetrahedral geometry (five structures) or distorted trigonal...
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New uranium(vi) and isothiouronium complexes: synthesis, crystal structure, spectroscopic characterization and a DFT study
PublicationThe crystal structures of S,S′-2,5-dimethylbenzene-1,4-diylbis(methylisothiouronium) diacetate (1_ac), S,S′-2,5-dimethylbenzene-1,4-diylbis(methylisothiouronium) dichloride (1_Cl), 1_U complex, S,S′-naphthalene-1,4-diylbis(methylisothiouronium) dichloride (2_Cl), and 2_U complex were determined for the first time. The supramolecular structures of the compounds obtained are mainly based on hydrogen bonding and ionic interactions...
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Deep convolutional neural network for predicting kidney tumour malignancy
PublicationPurpose: According to the statistics, up to 15-20% of removed solid kidney tumors turn out to be benign in postoperative histopathological examination, despite having been identified as malignant by a radiologist. The aim of the research was to limit the number of unnecessary nephrectomies of benign tumors. Methods or Background: We propose a machine-aided diagnostic system for kidney...
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Sphere Drive and Control System for Haptic Interaction With Physical, Virtual, and Augmented Reality
PublicationA system for haptic interaction with physical, virtual, and augmented realities, founded on drive and measurement elements (DMEs), is considered. The system consists of eight DME rolls equipped with linear actuators, able to measure their angular velocity, drive the sphere, and adjust downforce (pressing the roll against the sphere). Two modeling issues are addressed. Special effort is put in to compensate for various technical...
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Selected issues related to the toxicity of ionic liquids and deep eutectic solvents—a review
PublicationGreen Chemistry plays a more and more important role in implementing rules of sustainable development to prevent environmental pollution caused by technological processes, while simultaneously increasing the production yield. Ionic liquids (ILs) and deep eutectic solvents (DESs) constitute a very broad group of substances. Apart from many imperfections, ILs and DESs have been the most promising discoveries in the world of Green...
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Application of deep eutectic solvents for separation and determination of bioactive compounds in medicinal plants
PublicationThe medicinal plants industry, particularly in regard to products rich in biologically active substances for maintaining health, has grown by leaps and bounds in the last decade, with sales of over-the-counter drugs containing these substances growing by billions of dollars. Attention has thus also been paid to the safety and effectiveness of these medicines. We are currently witnessing a rapid increase in the number of publications...
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Deodorization of model biogas by means of novel non-ionic deep eutectic solvent
PublicationThe paper presents new non-ionic deep eutectic solvent (DES) composed of natural and non-toxic components i.e. guaiacol, camphor and levulinic acid in 1:1:3 molar ratio as a promising absorbent for removal of selected volatile organic compounds (VOCs) including dichloromethane, toluene, hexamethyldisiloxane and propionaldehyde from model biogas. The affi nity of DES for VOCs was determined as vapour-liquid coeffi cients and the...
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VOCs absorption from gas streams using deep eutectic solvents – A review
PublicationVolatile organic compounds (VOCs) are one of the most severe atmospheric pollutants. They are mainly emitted into the atmosphere from anthropogenic sources such as automobile exhaust, incomplete fuel combustion, and various industrial processes. VOCs not only cause hazards to human health or the environment but also adversely affect industrial installation components due to their specific properties, i.e., corrosive and reactivity....
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Enzymatic cross-linking of β-lactoglobulin in solution and at air–water interface: Structural constraints
PublicationEffective and controlled use of cross-linking enzymes in structure engineering of food systems depends on characterization of the favorable conditions for enzyme-substrate complex and the limiting factors for the desired modification. In this respect, we analyzed the susceptibility of bovine β-lactoglobulin (BLG) to enzymatic cross-linking by Trichoderma reesei tyrosinase (TrTyr) and transglutaminase (TG). Changes in BLG molecular...
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Edible black ant Smith (Carebara vidua) as human food – A systematic review
PublicationMeeting food security is one of the major global challenges to ensure sufficient supply of food for current and future generations, considering increasing population growth and climate change issues. Consequently, the consumption of edible insects as an alternative food source has recently gained global attention for combating global food insecurity. The present review aims to provide information on the recent progress in consumption...
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Formation of carboxymethyl cellulose–casein complexes by electrosynthesis
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Deep Eutectic Solvents for Starch Treatment
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Looking through the past: better knowledge retention for generative replay in continual learning
PublicationIn this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained...
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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublicationTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
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Generalized Taylor formula and shell structures for the analysis of the interaction between geosythetics and engineering structures of transportation lines
PublicationThe analysis of the interaction between geosynthetics and engineering structures (e.g. railroad bed, soil foundation, pipeline) assumes that the geosynthetic form elastic membranes or shell laid on different types of foundations. The mathematical description of that problems in continuous domain employs Laplace operator Δ or d’Alembert operator □. In this paper we demonstrate the analysis based on generalize Taylor formula, and...
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Novel anticancer strategy aimed at targeting shelterin complexes by the induction of structural changes in telomeric DNA: hitting two birds with one stone.
PublicationThe ends of chromosomes in mammals are composed of telomeric DNA containing TTAGGG repeats, which bind specific proteins called shelterins. This telomeric DNA together with shelterins form a cap that protects the ends of chromosomes from being recognized as sites of DNA damage and from chromosomal fusions. Many very successful antitumor drugs used in the treatment of cancer patients bind to DNA, some of them with a prominent sequence...
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Social media as an opportunity or a blind alley in social communication and forest education? – Experiences from Poland
PublicationThe article characterizes the experiences, problems, and prospects for the development of forest education on social media, which in Poland has been carried out by the Państwowe Gospodarstwo Leśne Lasy Państwowe (National Forest Holding ‘State...
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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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Two-step mechanism of J-domain action in driving Hsp70 function
PublicationJ-domain proteins (JDPs), obligatory Hsp70 cochaperones, play critical roles in protein homeostasis. They promote key allosteric transitions that stabilize Hsp70 interaction with substrate polypeptides upon hydrolysis of its bound ATP. Although a recent crystal structure revealed the physical mode of interaction between a J-domain and an Hsp70, the structural and dynamic consequences of J-domain action once bound and how Hsp70s...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublicationIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublicationDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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Effect of choline chloride based natural deep eutectic solvents on aqueous solubility and thermodynamic properties of acetaminophen
PublicationIn this work, natural deep eutectic solvents (NADESs) containing choline chloride as hydrogen bond acceptor and 1,2-propanediol, malic acid and tartaric acid as hydrogen bond donors have been synthesized and applied to enhance the aqueous solubility of model sparingly water-soluble drug – acetaminophen. The results indicate that the greatest impact on the solubility of acetaminophen have deep eutectic solvents based on 1,2-propanediol...
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Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries
PublicationIn developed countries, the first studies on forecasting bankruptcy date to the early 20th century. In Central and Eastern Europe, due to, among other factors, the geopolitical situation and the introduced economic system, this issue became the subject of researcher interest only in the 1990s. Therefore, it is worthwhile to analyze whether these countries conduct bankruptcy risk assessments and what their level of advancement is....
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Evaluation of Machine Learning Methods for the Experimental Classification and Clustering of Higher Education Institutions
PublicationHigher education institutions have a big impact on the future of skills supplied on the labour market. It means that depending on the changes in labour market, higher education institutions are making changes to fields of study or adding new ones to fulfil the demand on labour market. The significant changes on labour market caused by digital transformation, resulted in new jobs and new skills. Because of the necessity of computer...
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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublicationMachine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...