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Search results for: NATURAL PIGMENTS
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Ontology-Aided Software Engineering
PublicationThis thesis is located between the fields of research on Artificial Intelligence (AI), Knowledge Representation and Reasoning (KRR), Computer-Aided Software Engineering (CASE) and Model Driven Engineering (MDE). The modern offspring of KRR - Description Logic (DL) [Baad03] is considered here as a formalization of the software engineering Methods & Tools. The bridge between the world of formal specification (governed by the mathematics)...
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IEEE Transactions on Neural Networks and Learning Systems
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Optical Memory and Neural Networks (Information Optics)
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IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
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Journal of Biologically Active Products from Nature
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Soft X-ray Induced Production of Neutral Fragments in High-Rydberg States at the O 1s Ionization Threshold of the Water Molecule
PublicationDissociation of water molecules after soft X-ray absorption can yield neutral fragments in high-Rydberg (HR) states. We have studied the production of such fragments by field ionization and ion time-of-flight (TOF) spectrometry. Neutral HR fragments are created at all resonances below the O 1s ionization potential (IP) and particularly within 1 eV above the O 1s IP. The latter effect is due to the recapture of the O 1s photoelectrons...
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Cost-Efficient Surrogate Modeling of High-Frequency Structures Using Nested Kriging with Automated Adjustment of Model Domain Lateral Dimensions
PublicationSurrogate models are becoming popular tools of choice in mitigating issues related to the excessive cost of electromagnetic (EM)-driven design of high-frequency structures. Among available techniques, approximation modeling is by far the most popular due to its versatility. In particular, the surrogates are exclusively based on the sampled simulation data with no need to involve engineering insight or problem-specific knowledge....
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Ultrasound-Assisted Dispersive Liquid-Liquid Microextraction Using Deep Eutectic Solvents (DESs) for Neutral Red Dye Spectrophotometric Determination
PublicationDeep eutectic solvents (DES), which have low toxicity and are low cost, biodegradable, and easily synthesized, were used for the extraction of neutral red (NR) dye before its spectrophotometric analysis. DES, containing choline chloride as a hydrogen bond acceptor and phenol as a hydrogen bond donor with a molar ratio of 1:2, was used for the extraction of NR dye from aqueous media. The possible interaction of different DESs with...
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Changes on the Surface of the SiO2/C Composite, Leading to the Formation of Conductive Carbon Structures with Complex Nature of DC Conductivity
PublicationSol–gel layers have been the subject of many studies in recent decades. However, very little information exists about layers in which carbon structures are developed in situ. Using the spin-coating method, we obtained thin iron-doped SiO2/C composite films. The results of Raman spectroscopy showed that our samples consisted of graphitic forms and polymers. The latter’s contribution decreases with rising temperature. FTIR and EDS...
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Long Short-Term Memory (LSTM) neural networks in predicting fair price level in the road construction industry
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Optimal Selection of Input Features and an Acompanying Neural Network Structure for the Classification Purposes - Skin Lesions Case Study
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Performance analysis of an rfid-based 3d indoor positioning system combining scene analysis and neural network methods
PublicationThe main purpose of this research is to improve localization accuracy of an active Radio Frequency Identification, RFID tag, in 3D indoor space. The paper presents a new RFID based 3D Indoor Positioning System which shows performance improvement. The proposed positioning system combines two methods: the Scene Analysis technique and Artificial Neural Network. The results of both simulation using Log-Distance Path Loss Model and...
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Modelling relation between oxidation resistance and tribological properties of non-toxic lubricants with the use of artificial neural networks
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Mathematical modeling and prediction of pit to crack transition under cyclic thermal load using artificial neural network
PublicationThe formation of pitting is a major problem in most metals, which is caused by extremely localized corrosion that creates small holes in metal and subsequently, it changes into cracks under mechanical load, thermo-mechanical stress, and corrosion process factors. This research aims to study pit to crack transition phenomenon of steel boiler heat tubes under cyclic thermal load, and mathematical modeling...
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Predicting Performance of Lightweight Concrete with Granulated Expanded Glass and Ash Aggregate by Means of Using Artificial Neural Networks
PublicationLightweight concrete (LWC) is a group of cement composites of the defined physical, mechanical, and chemical performance. The methods of designing the composition of LWC with the assumed density and compressive strength are used most commonly. The purpose of using LWC is the reduction of the structure’s weight, as well as the reduction of thermal conductivity index. The highest possible strength, durability and low thermal conductivity...
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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublicationObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublicationIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublicationAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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Management of Urban Waters with Nature-Based Solutions in Circular Cities—Exemplified through Seven Urban Circularity Challenges
PublicationNature-Based Solutions (NBS) have been proven to effectively mitigate and solve resource depletion and climate-related challenges in urban areas. The COST (Cooperation in Science and Technology) Action CA17133 entitled “Implementing nature-based solutions (NBS) for building a resourceful circular city” has established seven urban circularity challenges (UCC) that can be addressed effectively with NBS. This paper presents the outcomes...
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Artificial neural network prophecy of ion exchange process for Cu (II) eradication from acid mine drainage
PublicationThe removal of heavy metal ions from wastewater was found to be significant when the cation exchange procedure was used effectively. The model of the cation exchange process was built using an artificial neural network (ANN). The acid mine drainage waste’s Cu(II) ion was removed using Indion 730 cation exchange resin. Experimental data from 252 cycles were recorded. In a column study, 252 experimental observations validated the...
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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublicationMalignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublicationMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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Application of neural networks for identification of forcedness having effect on magnitude of turbine rotor vibration using rotor trajectory.
PublicationW pracy dokonano analizy zastosowania sieci neuronowych do wyznaczenia wartości wymuszeń wpływających na wielkość drgań wirnika używając trajektorii jako parametr określający drgania. Badania przeprowadzono na powietrznej, jednostopniowej turbinie modelowej. Przemieszczenia poziome i pionowe wirnika turbiny mierzono przy pomocy systemu pomiarowego i rejestrowano na oscyloskopie cyfrowym. Przeprowadzono pomiary trajektorii ruchu...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublicationDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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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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Longitudinal drug synergy assessment using convolutional neural network image-decoding of glioblastoma single-spheroid cultures
PublicationAbstract Background In recent years, drug combinations have become increasingly popular to improve therapeutic outcomes in various diseases, including difficult to cure cancers such as the brain cancer glioblastoma. Assessing the interaction between drugs over time is critical for predicting drug combination effectiveness and minimizing the risk of therapy resistance. However, as viability readouts of drug combination experiments...
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Model Management for Low-Computational-Budget Simulation-Based Optimization of Antenna Structures Using Nature-Inspired Algorithms
PublicationThe primary objective of this study is investigation of the possibilities of accelerating nature-inspired optimization of antenna structures using multi-fidelity EM simulation models. The primary methodology developed to achieve acceleration is a model management scheme which the level of EM simulation fidelity using two criteria: the convergence status of the optimization algorithm, and relative quality of the individual designs...
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Cost-Efficient Globalized Parameter Optimization of Microwave Components through Response-Feature Surrogates and Nature-Inspired Metaheuristics
PublicationDesign of contemporary microwave devices predominantly utilizes computational models, including both circuit simulators, and full-wave electromagnetic (EM) evaluation. The latter constitutes the sole generic way of rendering accurate assessment of the system outputs that considers phenomena such as cross-coupling or radiation and dielectric losses. Consequently, for reliability reasons, the final tuning of microwave device parameters...
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Investigating the disease- modifying properties of sclerotiorin in Alzheimer's therapy using acetylcholinesterase inhibition
PublicationAlzheimer's disease (AD) is a progressive neurodegenerative disorder caused due to the damage and loss of neurons in specific brain regions. It is the most common form of dementia observed in older people. The symptoms start with memory loss and gradually cause the inability to speak and do day-to-day activities. The cost of caring for those affected individuals is huge and is probably beyond most developing countries capability....
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Journal of Education (Univ. KwaZulu-natal)
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Ewa Głowińska dr inż.
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Łukasz Bugalski dr inż. arch.
PeopleŁukasz Bugalski graduated as an architect and urban planner (2013) and held a Ph.D. (2013-2018) in the same discipline (Gdańsk University of Technology). He has been Marie Skłodowska-Curie Fellow (2017-2020) trained in the critical heritage studies as part of the "CHEurope" project (MSCA Innovative Training Network) conducted at Istituto per i Beni Artistici, Culturali e Naturali della Regione Emilia-Romagna in Bologna. Currently...
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Effect of carbazole and pyrrolidine functionalization of phenanthroline ligand on ground- and excited-state properties of rhenium(I) complexes. Interplay between 3MLCT and 3IL/3ILCT
PublicationNew rhenium(I) tricarbonyl complexes based on the phenanthroline ligand were designed and synthesized to investigate the role of carbazole (cbz) and pyrrolidine (pyrr) substituents in determining thermal, electrochemical and optoelectronic properties. Both pyrr and cbz are electron-releasing substituents, but they differ in the steric hindrance and electron delocalization ability. The impact of pyrr and cbz on ground- and excited-state...
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Impact of blocking layer on DSSC performance based on new dye -indolo[3,2,1-jk]carbazole derivative and N719
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9,9′-bifluorenylidene derivatives as novel hole-transporting materials for potential photovoltaic applications
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Photoelectrochemical and thermal characterization of aromatic hydrocarbons substituted with a dicyanovinyl unit
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Synthesis, ellipsometry and non-linear optical features of substituted 1,3,5-triphenylpyrazolines
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Studying the governing factors on the photo(electro)catalytic activity of surface-modified photocatalysts under visible light illumination
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Excited-state photodynamics of pyrene-containing boronated dyes
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The influence of anchoring group position in ruthenium dye molecule on performance of dye-sensitized solar cells
PublicationThe effect of anchoring group position and, in consequence, the orientation of the ruthenium dye molecule on titania surface on the performance of dye-sensitized solar cells has been studied intensively. Three model ruthenium sensitizing dyes bearing carboxylic anchoring group in ortho, meta or para position were synthesized and well characterized by spectroscopic, electrochemical, photophysical and photochemical measurements....
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AMCA to TAMRA long range resonance energy transfer on a flexible peptide
PublicationFörster resonance energy transfer between 7-amino-4-methyl-3-coumarinylacetic acid, (AMCA, donor) and 5- carboxytetramethylrhodamine, (TAMRA, acceptor) bound to Lys(AMCA)-Gly-Pro-Arg-Ser-Leu-Ser-Gly-Lys (TAMRA)-NH2 peptide is demonstrated by various spectroscopic techniques in glycerol at room temperature. In particular, nonexponential character of fluorescence intensity decay evidences the distance distribution between the donor...
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Improved electrocatalytic response toward hydrogen peroxide reduction of sulfanyl porphyrazine/multiwalled carbon nanotube hybrids deposited on glassy carbon electrodes
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Cationic porphyrazines with morpholinoethyl substituents – Syntheses, optical properties, and photocytotoxicities
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Single-walled carbon nanotube/sulfanyl porphyrazine hybrids deposited on glassy carbon electrode for sensitive determination of nitrites
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Electrochemical and catalytic assessment of peripheral bromoaryl-substituted manganese and iron porphyrazines
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Sulfanyl porphyrazines: Molecular barrel-like self-assembly in crystals, optical properties and in vitro photodynamic activity towards cancer cells
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Photophysical properties and photochemistry of a sulfanyl porphyrazine bearing isophthaloxybutyl substituents
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An enhanced electrochemical nanohybrid sensing platform consisting of reduced graphene oxide and sulfanyl metalloporphyrazines for sensitive determination of hydrogen peroxide and l -cysteine
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Influence of bulky pyrrolyl substitent on the physicochemical properties of porphyrazines
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Phthalocyanines with bulky substituents at non-peripheral positions – Synthesis and physico-chemical properties
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