Filters
total: 3886
-
Catalog
- Publications 3080 available results
- Journals 246 available results
- Conferences 33 available results
- People 60 available results
- Inventions 2 available results
- Projects 8 available results
- Research Teams 3 available results
- e-Learning Courses 63 available results
- Events 6 available results
- Open Research Data 385 available results
displaying 1000 best results Help
Search results for: NATURAL%20LIGHTING
-
Long Short-Term Memory (LSTM) neural networks in predicting fair price level in the road construction industry
Publication -
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,...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
IEEE Transactions on Neural Networks and Learning Systems
Journals -
Optical Memory and Neural Networks (Information Optics)
Journals -
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
Journals -
Journal of Biologically Active Products from Nature
Journals -
The Review of the Selected Challenges for an Incorporation of Daylight Assessment Methods into Urban Planning in Poland
PublicationThe main objectives of this research it to find out if modern daylight assessment and design methods can be useful for urban residential planning in Poland. The study gives a chance to describe and appraise modern daylight design techniques. The other purpose is to illustrate how daylight knowledge could be used as an incentive to rethink the way urban environments are created. Although daylight design is acknowledged in literature...
-
Journal of Education (Univ. KwaZulu-natal)
Journals -
Adaptacyjny system oświetlania dróg oraz inteligentnych miast
PublicationPrzedmiotem rozprawy jest zbadanie praktycznej możliwości wykrywania w czasie rzeczywistym anomalii w systemie oświetlenia drogowego w oparciu o analizę danych ze inteligentnych liczników energii. Zastosowanie inteligentnych liczników energii elektrycznej (Smart Meter) w systemach oświetlenia drogowego stwarza nowe możliwości w zakresie automatycznej diagnostyki takich niepożądanych zjawisk jak awarie lamp, odstępstwa od harmonogramu...
-
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...
-
Ewa Głowińska dr inż.
People -
Elective Seminar: Loft - Before and Nowadays - Creative Contest for Architects and Designers
e-Learning CoursesAs part of the elective seminar, students working in groups of 3 people will prepare architectural and lighting concept for an international competition: "LOFT-BEFORE AND NOWADAYS" organized by the Polish Lighting Industry Association), co-organized by Goczołowie Architekci OVO Grąbczewscy Architects and the SOMA Agency, the organizer of the International LIGHT Fair. More information here about the competition here: https://lightfair.pl/green-shoots-competition/ The...
-
Chang'an Daxue Xuebao (Ziran Kexue Ban)/Journal of Chang'an University (Natural Science Edition)
Journals -
Jiangsu Daxue Xuebao (Ziran Kexue Ban) / Journal of Jiangsu University (Natural Science Edition)
Journals -
Jiefangjun Ligong Daxue Xuebao/Journal of PLA University of Science and Technology (Natural Science Edition)
Journals -
Dongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Southeast University (Natural Science Edition)
Journals -
Radionuclides activity and effective doses referred to geological formations
PublicationNaturally occurring radioactive materials (NORM) are present in Earth’s crust and they caused natural background radiation, variable in different regions. Liquid, gas and solid radionuclides emit three types of radiation – alpha, beta and gamma. Fluctuations of natural radioactivity in different geological formations in the world and in Poland were compared in relation to radiological hazard. Also drilling cuttings from boreholes...
-
Diverse Expression of Selected SMN Complex Proteins in Humans with Sporadic Amyotrophic Lateral Sclerosis and in a Transgenic Rat Model of Familial Form of the Disease
Publication -
Inner-shell fragmentation of molecules into neutral fragments in high-Rydberg states induced by soft X-ray excitation with pulsed-field ionization
PublicationIn the present communication, we will show the results of measurements probing the production of neutral high-Rydberg fragments at the K edges of the molecules containing oxygen and nitrogen atoms. The experiments were performed at the Gas Phase beamline of the Elettra synchrotron radiation laboratory (Trieste, Italy), exploiting a combined soft X-ray excitation with pulsed-field ionization and ion time-of-flight (TOF) spectrometry...
-
Bożena Kostek prof. dr hab. inż.
People -
The Opoka-Rock from the Mesozoic/Neogene Contact Zone in the Bełchatów Lignite Deposit – Characteristics of a Petrographic Nature and as a Raw Material
Publication -
The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification
PublicationDeveloping of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and...
-
Powrót natury do miasta. Zieleń miejska w gdańsku od końca xix do polowy XX wieku
Publicationartykuł zawiera charakterystykę powstającej na przełomie xix i xx wieku zieleni miejskiej w gdańsku; pokazuje dzieje, zakres działalności i osiągnięcia gdańskiego zarządu zieleni oraz postaci z nim związane.
-
TiO2 with Tunable Anatase-to-Rutile Nanoparticles Ratios: How Does the Photoactivity Depend on the Phase Composition and the Nature of Photocatalytic Reaction?
Publication -
Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublicationLine heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the...
-
Genetic and biochemical determinants of serum concentrations of monocyte chemoattractant protein-1, a potential neural tube defect risk factor
Publication -
Novel Potent Muscarinic Receptor Antagonists: Investigation on the Nature of Lipophilic Substituents in the 5- and/or 6-Positions of the 1,4-Dioxane Nucleus
Publication -
Artificial neural networks as a tool for selecting the parameters of prototypical under sleeper pads produced from recycled rubber granulate
Publication -
A review on application of artificial neural network (ANN) for performance and emission characteristics of diesel engine fueled with biodiesel-based fuels
PublicationBiodiesel 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...
-
Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublicationThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
-
A new analyzer based on pellistor sensor with neural network data postprocessing for measurement of hydrocarbons in lower explosive limit range
PublicationW pracy przedstawiono rezultaty pierwszego etapu badań nad nowym typem analizatora do oznaczania stężenia wodoru i lotnych węglowodorów w zakresie dolnej granicy wybuchowości. Analizator ten zbudowano w oparciu o pojedynczy czujnik pelistorowy z układem przetwarzania danych wykorzystującym sztuczną sieć neuronową.
-
Hanna Obarska-Pempkowiak prof. dr hab. inż.
People -
ENVIRONMENTALLY FRIENDLY MATERIALS IN ARCHITECTURE � MODERN TRENDS AND DEVELOPMENT DIRECTIONS
PublicationFor a long time the interest in environmentally friendly materials in architecture is no longer limited to the use of renewable and natural substances such as wood, stone, straw, or reusable materials, such as metals or glass. Today the so-called naturals and the materials compatible with the idea of sustainability constantly appear on the market in new forms. Increasing awareness of the necessity to limit the building sector’s...
-
Intelligent information services 23/24
e-Learning CoursesInformation retrieval Text categorization Natural language processing
-
International Conference on Adaptive and Natural Computing Algorithms
Conferences -
International Joint Conference on Natural Language Processing
Conferences -
Potential energy curves and spectroscopic parameters of the diatomic silver anion and neutral silver dimer
Open Research DataThe process of a two-channel decay of the diatomic silver anion (Ag2-), namely the spontaneous electron ejection giving Ag2 + e- and the dissociation leading to Ag- + Ag is theoretically studied. The ground state potential energy curves (PECs) of the neutral silver dimer and anionic silver diatomic molecule are calculated using the single reference...