Filtry
wszystkich: 16194
-
Katalog
- Publikacje 11212 wyników po odfiltrowaniu
- Czasopisma 511 wyników po odfiltrowaniu
- Konferencje 226 wyników po odfiltrowaniu
- Wydawnictwa 1 wyników po odfiltrowaniu
- Osoby 309 wyników po odfiltrowaniu
- Wynalazki 2 wyników po odfiltrowaniu
- Projekty 24 wyników po odfiltrowaniu
- Laboratoria 1 wyników po odfiltrowaniu
- Aparatura Badawcza 1 wyników po odfiltrowaniu
- Kursy Online 391 wyników po odfiltrowaniu
- Wydarzenia 32 wyników po odfiltrowaniu
- Dane Badawcze 3484 wyników po odfiltrowaniu
wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: AIR POLLUTION, LOW-COST SENSOR CALIBRATION, MACHINE LEARNING, DATA PRE-PROCESSING, NEURAL NETWORKS
-
Analysing and processing of geotagged social media
PublikacjaThe use of location based data analysing tools is an important part of geomarketing strategies among entrepreneurs. One of the key elements of interest is social media data shared by the users. This data is analysed both for its content and its location information, the results help to identify trends represented in the researched regions. In order to verify the possibilities of analysing and processing of geotagged social media...
-
THE COST ANALYSIS OF CORROSION PROTECTION SOLUTIONS FOR STEEL COMPONENTS IN TERMS OF THE OBJECT LIFE CYCLE COST
PublikacjaSteel materials, due to their numerous advantages - high availability, easiness of processing and possibility of almost any shaping are commonly applied in construction for carrying out basic carrier systems and auxiliary structures. However, the major disadvantage of this material is its high corrosion susceptibility, which depends strictly on the local conditions of the facility and the applied type of corrosion protection system....
-
Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublikacjaForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
-
Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublikacjaNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
-
International Journal of Machine Learning and Cybernetics
Czasopisma -
International Journal of Machine Learning and Computing
Czasopisma -
Categorization of emotions in dog behavior based on the deep neural network
PublikacjaThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
-
A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublikacjaComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
-
Monitoring of n-butanol vapors biofiltration process using an electronic nose combined with calibration models
PublikacjaMalodours, by definition, are generally unpleasant, nuisance smells that are a mixture of volatile chemical compounds which can be perceptible even at low concentrations. Due to the more frequent occurrence of odour nuisance associated with the odour sensations, and thus the need to remove them from the air, deodorization techniques are commonly used. Biofiltration is one of the methods of reducing odorants in the air stream. In...
-
Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublikacjaRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
-
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...
-
Low-volume label-free SARS-CoV-2 detection with the microcavity-based optical fiber sensor
PublikacjaAccurate and fast detection of viruses is crucial for controlling outbreaks of many diseases; therefore, to date, numerous sensing systems for their detection have been studied. On top of the performance of these sensing systems, the availability of biorecognition elements specific to especially the new etiological agents is an additional fundamental challenge. Therefore, besides high sensitivity and selectivity, such advantages...
-
Low cost real time UAV stereo photogrammetry modelling technique – accuracy considerations
PublikacjaThe paper presents accuracy considerations regarding three 3D modelling techniques. The tested new consumer type stereo camera (ZED 3D Stereolabs) has been implemented info an aerial mapping system, on board micro air vehicle MAV) and tested object has been mapped using a real-time photogrammetry with original real-time software application. The evaluated results has been compared with model gained with a state of art unmanned...
-
Machine Design 2
Kursy OnlineMachine Design 2, what else?
-
A Simple Neural Network for Collision Detection of Collaborative Robots
PublikacjaDue to the epidemic threat, more and more companies decide to automate their production lines. Given the lack of adequate security or space, in most cases, such companies cannot use classic production robots. The solution to this problem is the use of collaborative robots (cobots). However, the required equipment (force sensors) or alternative methods of detecting a threat to humans are usually quite expensive. The article presents...
-
Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
Publikacja -
Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublikacjaMusic analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...
-
KTaO3-based nanocomposites for air treatment
PublikacjaThe advantage is that photocatalytic methods allow removing VOCs, NOx, SO2, deodorants, and microorganisms at the same system. The new third generation of photoactive materials activated by low powered and low cost irradiation sources (such as LEDs or black fluorescent UV lamps) can be used as photocatalysts in air purification systems. A series of single semiconductors and their nanocomposites combination were prepared using hydrothermal...
-
Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublikacjaRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
-
Toward Intelligent Recommendations Using the Neural Knowledge DNA
PublikacjaIn this paper we propose a novel recommendation approach using past news click data and the Neural Knowledge DNA (NK-DNA). The Neural Knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for news recommendation tasks on the MIND benchmark dataset. By taking advantages of NK-DNA, deep...
-
Szymon Zaporowski mgr inż.
Osoby -
Multianalyte Calibration Methods for Potentiometric Integrated Sensors System for Determination of Ions Concentration in a Body Fluids
PublikacjaIn recent years, integration and miniaturization of ion-selective electrodes (ISEs) have brought many benefits resulting in the possibility of simultaneous determination of the ions concentration in a small sample volume. One of the key problems related to the preparation of integrated sensors systems (ISSs) is a calibration procedure due to the necessity to calibrate each particular sensor separately. The main aim of the research...
-
Efficient sampling of high-energy states by machine learning force fields
Publikacja -
Modular machine learning system for training object detection algorithms on a supercomputer
PublikacjaW pracy zaprezentowano architekturę systemu służącego do tworzenia algorytmów wykorzystujących metodę AdaBoost i służących do wykrywania obiektów (np. twarzy) na obrazach. System został podzielony na wyspecjalizowane moduły w celu umożliwienia łatwej rozbudowy i efektywnego zrównoleglenia implementacji przeznaczonej dla superkomputera. Na przykład, system może być rozszerzony o nowe cechy i algorytmy ich ekstrakcji bez konieczności...
-
POPULATION-BASED MULTI-AGENT APPROACH TO SOLVING MACHINE LEARNING PROBLEMS
Publikacja -
Image Processing in Robotics (2021/2022)
Kursy OnlineFor ISD M.Sc. (II degr.) 2 sem. Participants are to learn image processing algorithms related to transformation, filtration, feature detection (image descriptors), image processing algorithms in robotic industrial systems.
-
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...
-
Analysis of circular polarization antenna design trade‐offs using low‐cost EM‐driven multiobjective optimization
PublikacjaCircular polarization (CP) antennas are vital components of modern communication systems. Their design involves handling several requirements such as low reflection and axial ratio (AR) within the frequency range of interest. Small size is an important criterion for antenna mobility which is normally achieved as a by‐product of performance‐oriented modifications of the structure topology. In this work, multiobjective optimization...
-
Hydrogen degradation of pre-oxidized zirconium alloys
PublikacjaThe presence of the oxide layers on Zr alloys may retard or enhance the hydrogen entry and material degradation, depending on the layer features. This research has been aimed to determine the effects of pre-oxidation of the Zircaloy-2 alloy at a different temperature on hydrogen degradation. The specimens were oxidised in laboratory air at 350°C, 700°C, and 900°C. After, some samples were tensed at 10-5 strain rate and simultaneously...
-
Low-Cost Yield-Driven Design of Antenna Structures Using Response-Variability Essential Directions and Parameter Space Reduction
PublikacjaQuantifying the effects of fabrication tolerances and uncertainties of other types is fundamental to improve antenna design immunity to limited accuracy of manufacturing procedures and technological spread of material parameters. This is of paramount importance especially for antenna design in the industrial context. Degradation of electrical and field properties due to geometry parameter deviations often manifests itself as, e.g.,...
-
Calibration of precipitation estimation algorithm with particular emphasis on the Pomeranian region using high performance computing
PublikacjaFast and accurate precipitation estimation is an important element of remote atmosphere monitoring, as it allows, for example, to correct short-term weather forecasts and the prediction of several types of meteorological threats. The paper presents methodology for calibrating precipitation estimation algorithm based on MSG SEVIRI sensor data, and Optimal Cloud Analysis product available via EumetCast transmission. Calibration is...
-
Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublikacjaA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
-
Machine-aided detection of SARS-CoV-2 from complete blood count
PublikacjaThe current gold standard for SARS-CoV-2 detection methods lacks the functionality to perform population screening. Complete blood count (CBC) tests are a cost-effective way to reach a wide range of people – e.g. according to the data of the Central Statistical Office of Poland from 2016, there are 3,000 blood diagnostic laboratories in Poland, and 46% of Polish people have at least one CBC test per year. In our work, we show...
-
Learning from examples with data reduction and stacked generalization
Publikacja -
Low-Cost Method for Internal Surface Roughness Reduction of Additively Manufactured All-Metal Waveguide Components
PublikacjaIn this study, a novel low-cost polishing method for internal surface roughness reduction of additively manufactured components, developed for waveguide (WG) circuits operating in the millimeter frequency range is proposed. WG components fabricated using powder bed fusion (PBF) generally feature roughness of ten to fifty microns, which influences the increase of roughness-related conductor power losses having a major effect on...
-
Waste tire rubber as low-cost and environmentally-friendly modifier in thermoset polymers – a review
PublikacjaNowadays, waste tire rubber (WTR) management is a growing and serious problem. Therefore, research works focused on the development of cost-effective and environmentally-friendly methods of WTR recycling are fully justified. Incorporation of WTR into polymer matrices and composite materials attracts much attention, because this approach allows sustainable development of industrially applicable waste tires recycling technologies....
-
Reliability of flue gas desulphurisation installations - the essential condition of efficient air pollution control
PublikacjaW celu minimalizacji niekorzystnego wpływu SO2 i SO3 na środowisko naturalne w wielu instalacjach skrubery odsiarczające gaz spalinowy (FGD) stosowane są do usuwania tlenków siarki z gazów wylotowych. Ostre warunki pracy skruberów i dodatkowego osprzętu powodują problemy korozyjne w powszechnie stosowanych materiałach konstrukcyjnych a awarie wywierają długookresowy wpływ na środowisko. Opisano najnowsze doświadczenia związane...
-
Health impacts of indoor air pollution from household solid fuel on children and women
Publikacja -
Review of the Complexity of Managing Big Data of the Internet of Things
PublikacjaTere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...
-
Speed observer of induction machine based on backstepping and sliding mode for low‐speed operation
PublikacjaThis paper presents a speed observer design based on backstepping and slidingmode approaches. The inputs to the observer are the stator current and thevoltage vector components. This observer structure is extended to the integra-tors. The observer stabilizing functions contain the appropriate sliding surfaceswhich result from the Lyapunov function. The rotor angular speed is obtainedfrom the non‐adaptive formula with a sliding...
-
Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublikacjaCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
-
Neural Network Subgraphs Correlation with Trained Model Accuracy
PublikacjaNeural Architecture Search (NAS) is a computationally demanding process of finding optimal neural network architecture for a given task. Conceptually, NAS comprises applying a search strategy on a predefined search space accompanied by a performance evaluation method. The design of search space alone is expected to substantially impact NAS efficiency. We consider neural networks as graphs and find a correlation between the presence...
-
Neural Network-Based Sequential Global Sensitivity Analysis Algorithm
PublikacjaPerforming global sensitivity analysis (GSA) can be challenging due to the combined effect of the high computational cost, but it is also essential for engineering decision making. To reduce this cost, surrogate modeling such as neural networks (NNs) are used to replace the expensive simulation model in the GSA process, which introduces the additional challenge of finding the minimum number of training data samples required to...
-
Artificial Neural Networks for Prediction of Antibacterial Activity in Series of Imidazole Derivatives
Publikacja -
Neural Networks Based on Ultrafast Time-Delayed Effects in Exciton Polaritons
Publikacja -
Analysis of electrical patterns activity in artificial multi-stable neural networks
Publikacja -
Optimization of a three-bed adsorption chiller by genetic algorithms and neural networks
Publikacja -
Extended Hopfield models of neural networks for combinatorial multiobjective optimization problems
Publikacja -
Automatic singing voice recognition employing neural networks and rough sets
PublikacjaCelem prac opisanych w referacie jest automatyczne rozpoznawanie głosów śpiewaczych. Do tego celu utworzona została baza nagrań próbek śpiewu profesjonalnego i amatorskiego. Próbki poddane zostały parametryzacji parametrami zaproponowanymi przez autorów ściśle do tego celu. Sposób wyznaczenia parametrów i ich interpretacja fizyczna przedstawione są w referacie. Parametry wprowadzane są do systemów decyzyjnych, klasyfikatorów opartych...
-
Musical phrase representation and recognition by means of neural networks and rough sets.
PublikacjaW artykule przedstawiono podstawowe definicje dotyczące frazy muzycznej. W eksperymentach posłużono się zapisem parametrycznym. W celu wzmocnienia procesu rozpoznawania wykorzystano kodowanie entropijne muzyki. W eksperymentach klasyfikacji oparto się o sztuczne sieci neuronowe i metodę zbiorów przybliżonych. Słowa kluczowe: fraza muzyczna, klasyfikacja, sztuczne sieci neuronowe, metoda zbiorów przybliżonych