Filtry
wszystkich: 728
Wyniki wyszukiwania dla: MOLECULAR MODELING,MOLECULES,NEURAL NETWORKS,SOLVENTS,VISCOSITY
-
Bio‐polyols synthesized by liquefaction of cellulose: Influence of liquefaction solvent molecular weight
PublikacjaCurrently, the plastics industry including polyurethanes is based on the use of petrochemicals. For this reason, scientists are looking for new types of renewable resources for the substitution of petrochemical substances. This work aims to evaluate the effect of polyethylene glycols (PEG) with different molecular mass impact on properties of bio-based polyols synthesized via biomass liquefaction of cellulose. To date, research...
-
Experience-Based Cognition for Driving Behavioral Fingerprint Extraction
PublikacjaABSTRACT With the rapid progress of information technologies, cars have been made increasingly intelligent. This allows cars to act as cognitive agents, i.e., to acquire knowledge and understanding of the driving habits and behavioral characteristics of drivers (i.e., driving behavioral fingerprint) through experience. Such knowledge can be then reused to facilitate the interaction between a car and its driver, and to develop better and...
-
Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublikacjaSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
-
Latest Insights on Novel Deep Eutectic Solvents (DES) for Sustainable Extraction of Phenolic Compounds from Natural Sources
PublikacjaPhenolic compounds have long been of great importance in the pharmaceutical, food, and cosmetic industries. Unfortunately, conventional extraction procedures have a high cost and are time consuming, and the solvents used can represent a safety risk for operators, consumers, and the environment. Deep eutectic solvents (DESs) are green alternatives for extraction processes, given their low or non-toxicity, biodegradability, and reusability....
-
Performance of the AMOEBA Water Model in the Vicinity of QM Solutes: A Diagnosis Using Energy Decomposition Analysis
PublikacjaThe importance of incorporating solvent polarization effects into the modeling of solvation processes has been well-recognized, and therefore a new generation of hybrid quantum mechanics/molecular mechanics (QM/MM) approaches that accounts for this effect is desirable. We present a fully self-consistent, mutually polarizable QM/MM scheme using the AMOEBA force field, in which the total energy of the system is variationally minimized...
-
Optoelectronic system for investigation of cvd diamond/DLC layers growth
PublikacjaDevelopment of the optoelectronic system for non-invasive monitoring of diamond/DLC (Diamond-Like-Carbon) thin films growth during μPA ECR CVD (Microwave Plasma Assisted Electron Cyclotron Resonance Chemical Vapour Deposition) process is described. The system uses multi-point Optical Emission Spectroscopy (OES) and long-working-distance Raman spectroscopy. Dissociation of H2 molecules, excitation and ionization of hydrogen atoms...
-
Machine Learning Algorithm-Based Tool and Digital Framework for Substituting Daylight Simulations In Early- Stage Architectural Design Evaluation
PublikacjaThe aim of this paper is to examine the new method of obtaining the simulation-based results using backpropagation of errors artificial neural networks. The primary motivation to conduct the research was to determine an alternative, more efficient and less timeconsuming method which would serve to achieve the results of daylight simulations. Three daylight metrics: Daylight Factor, Daylight Autonomy and Daylight Glare Probability have...
-
Widespread theta synchrony and high-frequency desynchronization underlies enhanced cognition
PublikacjaThe idea that synchronous neural activity underlies cognition has driven an extensive body of research in human and animal neuroscience. Yet, insufficient data on intracranial electrical connectivity has precluded a direct test of this hypothesis in a whole-brain setting. Through the lens of memory encoding and retrieval processes, we construct whole-brain connectivity maps of fast gamma (30-100 Hz) and slow theta (3-8 Hz) spectral...
-
A Novel IoT-Perceptive Human Activity Recognition (HAR) Approach Using Multi-Head Convolutional Attention
PublikacjaTogether with fast advancement of the Internet of Things (IoT), smart healthcare applications and systems are equipped with increasingly more wearable sensors and mobile devices. These sensors are used not only to collect data, but also, and more importantly, to assist in daily activity tracking and analyzing of their users. Various human activity recognition (HAR) approaches are used to enhance such tracking. Most of the existing...
-
WYKORZYSTANIE SIECI NEURONOWYCH DO SYNTEZY MOWY WYRAŻAJĄCEJ EMOCJE
PublikacjaW niniejszym artykule przedstawiono analizę rozwiązań do rozpoznawania emocji opartych na mowie i możliwości ich wykorzystania w syntezie mowy z emocjami, wykorzystując do tego celu sieci neuronowe. Przedstawiono aktualne rozwiązania dotyczące rozpoznawania emocji w mowie i metod syntezy mowy za pomocą sieci neuronowych. Obecnie obserwuje się znaczny wzrost zainteresowania i wykorzystania uczenia głębokiego w aplikacjach związanych...
-
Creating a radiological database for automatic liver segmentation using artificial intelligence.
PublikacjaImaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.
-
Resource constrained neural network training
PublikacjaModern applications of neural-network-based AI solutions tend to move from datacenter backends to low-power edge devices. Environmental, computational, and power constraints are inevitable consequences of such a shift. Limiting the bit count of neural network parameters proved to be a valid technique for speeding up and increasing efficiency of the inference process. Hence, it is understandable that a similar approach is gaining...
-
New Two-center Ellipsoidal Basis Function Neural Network for Fault Diagnosis of Analog Electronic Circuits
PublikacjaIn the paper a new fault diagnosis-oriented neural network and a diagnostic method for localization of parametric faults in Analog Electronic Circuits (AECs) with tolerances is presented. The method belongs to the class of dictionary Simulation Before Test (SBT) methods. It utilizes dictionary fault signatures as a family of identification curves dispersed around nominal positions by component tolerances of the Circuit Under Test...
-
High frequency oscillations in human memory and cognition: a neurophysiological substrate of engrams?
PublikacjaDespite advances in understanding the cellular and molecular processes underlying memory and cognition, and recent successful modulation of cognitive performance in brain disorders, the neurophysiological mechanisms remain underexplored. High frequency oscillations beyond the classic electroencephalogram spectrum have emerged as a potential neural correlate of fundamental cognitive processes. High frequency oscillations are detected...
-
Molecular dynamics simulations of the growth of poly(chloro-para-xylylene) films
Publikacja -
A unified coarse-grained model of biological macromolecules based on mean-field multipole–multipole interactions
Publikacja -
Study of the Interactions between Neurophysin II and Dipeptide Ligand by Means of Molecular Dynamics
Publikacja -
On the origin of surface imposed anisotropic growth of salicylic and acetylsalicylic acids crystals during droplet evaporation
PublikacjaIn this paper droplet evaporative crystallization of salicylic acid (SA) and acetylsalicylic acid (ASA) crystals on different surfaces, such as glass, polyvinyl alcohol (PVA), and paraffin was studied. The obtained crystals were analyzed using powder X-ray diffraction (PXRD) technique. In order to better understand the effect of the surface on evaporative crystallization, crystals deposited on glass were scraped off. Moreover,...
-
Exploring the cocrystallization potential of urea and benzamide
PublikacjaThe cocrystallization landscape of benzamide and urea interacting with aliphatic and aromatic carboxylic acids was studied both experimentally and theoretically. Ten new cocrystals of benzamide were synthesized using an oriented samples approach via a fast dropped evaporation technique. Information about types of known bi-component cocrystals augmented with knowledge of simple binary eutectic mixtures was used for the analysis...
-
Molecular dynamics of fentanyl bound to μ-opioid receptor
Publikacja -
Binding free energy of selected anticancer compounds to DNA - theoreticalcalculations
PublikacjaPraca dotyczy swobodnej energii wiązania z DNA trzech związków o działaniu przeciwnowotworowym (mitoksantronu i dwóch pochodnych pirymidoakrydyny). Obliczenia wykorzystywały metody Poissona-Boltzmanna (udział elektrostatyczny) i metody SASA (udział nieelektrostatyczny). W wyniku badań zaproponowano struktury kompleksów jakie tworzą badane ligandy z DNA.
-
Instability of 2,2-di(pyridin-2-yl)acetic acid. Tautomerization versus decarboxylation
Publikacja -
Polymerization of chloro-p-xylylenes, quantum-chemical study
PublikacjaThe p-xylylene monomers of parylene N, C and D have similar high polymerization reactivity. For effective copolymerization processes this fact is basically a draw- back and for instance the copolymerization with styrene doesn't go at all (Corley et al. J Pol Sc 13(68):137156, 1954). Substitution of terminal hydrogen atoms by chlorine atoms reduces reactivity dramatically. 7,7,8,8-tetrachloro-p- xylylene and 2,5,7,7,8,8-hexachloro-p-xylylene...
-
A first-principles study of electronic and magnetic properties of 4d transition metals doped in Wurtzite GaN for spintronics applications
PublikacjaWe studied the electronic and magnetic properties of wurtzite GaN (w-GaN) doped with different concentrations of the 4d transition metal ions Nb, Mo, and Ru. We incorporated spin-polarized plane-wave density functional theory within an ultrasoft pseudopotential formalism. The 4d transition metals were doped at different geometrical sites to determine the geometry with the lowest total energy and the one that induced the largest...
-
Ab initio study of phenyl benzoate: structure, conformational analysis, dipole moment, IR and Raman vibrational spectra
Publikacja -
Molecular dynamics study of 4-OH-phenylacetyl- D -Y(Me)FQNRPR-NH 2 selectivity to V1a receptor
Publikacja -
A hypothesis for GPCR activation
Publikacja -
Attaching an alkali metal atom to an alkaline earth metal oxide (BeO, MgO, or CaO) yields a triatomic metal oxide with reduced ionization potential and redirected polarity
Publikacja -
Functionalization of the transition metal oxides FeO, CoO, and NiO with alkali metal atoms decreases their ionization potentials by 3–5 eV
Publikacja -
Computational studies of intermolecular interactions in aqueous solutions of poly(vinylmethylether)
Publikacja -
Molecular dynamics simulations of the growth of poly (chloro-para-xylylene) films.
PublikacjaParylene C, poly(chloro-para-xylylene) is the most widely used member of the parylene family due to its excellent chemical and physical properties. In this work we analyzed the formation of the parylene C film using molecular mechanics and molecular dynamics methods. A five unit chain is necessary to create a stable hydrophobic cluster and to adhere to a covered surface. Two scenarios were deemed to take place. The obtained results...
-
Long range molecular dynamics study of regulation of eukaryotic glucosamine-6-phosphate synthase activity by UDP-GlcNAc
PublikacjaGlucosamine-6-phosphate (GlcN-6-P) synthase catalyses the first and practically irreversible step in hexosamine metabolism. The final product of this pathway, uridine 5' diphospho N-acetyl-D-glucosamine (UDPGlcNAc), is an essential substrate for assembly of bacterialand fungal cell walls. Moreover, the enzyme is involved in phenomenon of hexosamine induced insulin resistance in type II diabetes, which makes it a potential target...
-
Configurations of H 3 + (H2)n clusters and their energies
PublikacjaThe H-3(+) ion plays an important role in low temperature astrophysical and laboratory plasmas. It is considered as the initiator of many ion-molecule chemistries. Also its clusters with H-2 are quite interesting. We study configurations of the H-3(+)(H-2)(n) clusters for n = 1 up to n = 12 as a simple test system. Total energies for these structures, with zero point vibration corrections have been calculated. Stabilization energies...
-
Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate
PublikacjaFast replacement models (or surrogates) have been widely applied in the recent years to accelerate simulation-driven design procedures in microwave engineering. The fundamental reason is a considerable—and often prohibitive—CPU cost of massive full-wave electromagnetic (EM) analyses related to solving common tasks such as parametric optimization or uncertainty quantification. The most popular class of surrogates are data-driven...
-
Badanie dynamiki platform pływających morskich turbin wiatrowych z zastosowaniem metod numerycznej mechaniki płynów
PublikacjaPraca dotyczy badania ruchu platform pływających pod morskie turbiny wiatrowe. Przedstawiono w niej główne metody obliczeń i przedyskutowano ich zastosowanie. Na przykładzie koncepcji konstrukcji 3-kolumnowej platformy typu Spar przedstawiono metodykę wykonywania obliczeń z zastosowaniem programu AQWA opartego na metodzie dyfrakcyjnej, rozszerzonego o współczynniki wynikające z lepkości wyznaczone za pomocą obliczeń RANSE-CFD....
-
On a Method of Efficiency Increasing in Kaplan Turbine
PublikacjaThis paper presents a method of increasing efficiency in Kaplan-type turbine. The method is based on blade profile optimisation together with modelling the interaction between rotor and stator blades. Loss coefficient was chosen as the optimisation criterion, which is related directly to efficiency. Global optimum was found by means of Genetic Algorithms, and Artificial Neural Networks were utilised for approximations to reduce...
-
Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublikacjaThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
-
Classifying Emotions in Film Music - A Deep Learning Approach
PublikacjaThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
-
SegSperm - a dataset of sperm images for blurry and small object segmentation
Dane BadawczeMany deep learning applications require figure-ground segmentation. The performance of segmentation models varies across modalities and acquisition settings.
-
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...
-
Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublikacjaThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...
-
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...
-
Closer look into the structures of tetrabutylammonium bromide–glycerol-based deep eutectic solvents and their mixtures with water
PublikacjaIn 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...
-
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...
-
Document Agents with the Intelligent Negotiations Capability
PublikacjaThe paper focus is on augmenting proactive document-agents with built -in intelligence to enable them to recognize execution context provided by devices visited durning the business process, and to reach collaboration agreement despite of their conflicting requirements. We propose a solution based on neural networks to improve simple multi-issue negotiation between the document and the device, practically with no excessive cost...
-
Automatic music set organizatio based on mood of music / Automatyczna organizacja bazy muzycznej na podstawie nastroju muzyki
PublikacjaThis work is focused on an approach based on the emotional content of music and its automatic recognition. A vector of features describing emotional content of music was proposed. Additionally, a graphical model dedicated to the subjective evaluation of mood of music was created. A series of listening tests was carried out, and results were compared with automatic mood recognition employing SOM (Self Organizing Maps) and ANN (Artificial...
-
Recurrent Neural Network Based Adaptive Variable-Order Fractional PID Controller for Small Modular Reactor Thermal Power Control
PublikacjaThis paper presents the synthesis of an adaptive PID type controller in which the variable-order fractional operators are used. Due to the implementation difficulties of fractional order operators, both with a fixed and variable order, on digital control platforms caused by the requirement of infinite memory resources, the fractional operators that are part of the discussed controller were approximated by recurrent neural networks...
-
Towards Knowledge Sharing Oriented Adaptive Control
PublikacjaIn this paper, we propose a knowledge sharing oriented approach to enable a robot to reuse other robots' knowledge by adapting itself to the inverse dynamics model of the knowledge-sharing robot. The purpose of this work is to remove the heavy fine-tuning procedure required before using a new robot for a task via reusing other robots' knowledge. We use the Neural Knowledge DNA (NK-DNA) to help robots gain empirical knowledge and...
-
Design of new cholinesterase inhibitors based on phosphorus analogs of tacrine as potential anti-Alzheimer’s disease agents
PublikacjaBased on the analysis of the determined free binding energy (using the AutoDock Vina 1.1.2 docking program), the most potent cholinesterase inhibitors were selected. Moreover, studies of 3D visualization of the results of molecular modeling led to the identification of potential sites for the interaction of new potential inhibitors with amino acid residues building active sites of investigated cholinesterases.
-
A compact smart sensor based on a neural classifier for objects modeled by Beaunier's model
PublikacjaA new solution of a smart microcontroller sensor based on a simple direct sensor-microcontroller interface for technical objects modeled by two-terminal networks and by the Beaunier’s model of anticorrosion coating is proposed. The tested object is stimulated by a square pulse and its time voltage response is sampled four times by the internal ADC of microcontroller. A neural classifier based on measurement data classifies the...