Filters
total: 10602
-
Catalog
- Publications 7962 available results
- Journals 405 available results
- Conferences 163 available results
- Publishing Houses 1 available results
- People 270 available results
- Inventions 1 available results
- Projects 22 available results
- e-Learning Courses 293 available results
- Events 11 available results
- Open Research Data 1474 available results
displaying 1000 best results Help
Search results for: AIR QUALITY, POLLUTANT DETECTION, NITROGEN DIOXIDE, SENSOR CORRECTION, MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS
-
Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublicationMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
-
Michał Grochowski dr hab. inż.
PeopleProfessor and a Head of the Department of Intelligent Control and Decision Support Systems at Gdansk University of Technology (GUT). He is also a Member of the Board of the Digital Technologies Center of GUT. He received his M.Sc. degree in Control Engineering in 2000 from the Electrical and Control Engineering Faculty at the GUT. In 2004 he received a Ph.D. degree in Automatic Control and Robotics from 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...
-
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...
-
Design, Realization and Measurements of Enhanced Performance 2.4 GHz ESPAR Antenna for Localization in Wireless Sensor Networks
PublicationThis paper presents the design, realization and measurements of an Electronically Steerable Parasitic Array Radiator (ESPAR) antenna with enhanced performance of estimating the incoming signal direction. Designed antenna is dedicated for 2.4 GHz ISM applications with emphasis on Wireless Sensor Networks (WSN). Proposed antenna provides different radiation patterns by proper configuration of the parasitic elements. Thus, several...
-
Optimal placement of IMU sensor for the detection of children activity
PublicationIn this paper an investigation to determine the optimal placement of IMU sensors for the purpose of children characteristic activity detection is presented. The article compares four different placement of two IMU sensors on human body. Ten healthy volunteers participated within the study. Data were collected firstly from two wireless 9-axial IMU sensors placed at the left and right wrists, then sensors were placed at lower back...
-
Toward the next generation of air quality monitoring: Mercury
PublicationMercury is a global pollutant that is ubiquitous in the environment. Enrichment of mercury in the biosphere as the result of human activities and subsequent production of methylmercury (MeHg) has resulted in elevated concentrations in fish, wildlife and marine mammals globally. Elemental mercury (Hg0) is the most common form of mercury in the atmosphere, and the form that is most readily transported long distances from its emission...
-
Electrocatalytic gas sensor with reference layer
PublicationIn recent years electrochemical gas sensors based on solid state electrolytes have been intensively developed. They are easy to obtain, use and relative durable. Nasicon is one of the most promising materials, which have been used in construction of gas sensors. Most of these devices work in potentiometric or amperometric mode. However, some works are dedicated to sensors working in electrocatalytic mode. Principle of operation...
-
Mutual Coupling Reduction in Antenna Arrays Using Artificial Intelligence Approach and Inverse Neural Network Surrogates
PublicationThis paper presents a novel approach to reduce undesirable coupling in antenna arrays using custom-designed resonators and inverse surrogate modeling. To illustrate the concept, two stand-ard patch antenna cells with 0.07λ edge-to-edge distance are designed and fabricated to operate at 2.45 GHz. A stepped-impedance resonator is applied between the antennas to suppress their mutual coupling. For the first time, the optimum values...
-
Determination of toxic gases based on the responses of a single electrocatalytic sensor and pattern recognition techniques
PublicationA response from an electrocatalytic gas sensor contains fingerprint information about the type of gas and its concentration. As a result, a single gas sensor can be used for the determination of different gases. However, information about the type of gas and its concentration is hidden in the unique shape of the current–voltage response and it is quite difficult to explore. One of the ways to get precise information about the measured...
-
Investigation of Sensing Mechanism of Nasicon Electrocatalytic Sensors in Nitrogen Dioxide and Ammonia
PublicationW pracy przedstawiono wyniki badań mechanizmu działania czujnika elektrokatalitycznego pracującego w ditlenku azotu i amoniaku.
-
Identification of volatile compounds based on the electrocatalytic gas sensor responses
PublicationMeasured response in case of electrocatalytic gas sensors is in form of a voltamperometric characteristic. Current-voltage (I-V) response shape depends on the gas type and its concentration. Such response contains significantly more information comparing with typical electrochemical sensors, but is quite difficult to analyze. When I-V curve contains current peaks, position of such peaks can be used...
-
Optimal Sensor Placement for Damage Detection
PublicationW pracy przedstawiono dwie konfiguracje czujników PZT do detekcji uszkodzeń w płytach. Omówion zalety i wady obu konfiguracji.
-
Application of passive sampling technique in monitoring research on quality of atmospheric air in the area of Tczew, Poland.
PublicationThis paper presents the results of atmospheric air quality research in Tczew (adjacent to the Vistula River) on the content of BTEX compounds. Analytical procedure applied during the sampling of the analytes from the air used the passive sampling technique (diffusive passive sampler, Radiello®). For determination of BTEX compounds in atmospheric air, two-stage thermal desorption technique combined with gas chromatography (TD-GC-FID)...
-
Investigation of Air Quality beside a Municipal Landfill: The Fate of Malodour Compounds as a Model VOC
PublicationThis paper presents the results of an investigation on ambient air odour quality in the vicinity of a municipal landfill. The investigations were carried out during the spring–winter and the spring seasons using two types of the electronic nose instrument. The field olfactometers were employed to determine the mean odour concentration, which was from 2.1 to 32.2 ou/m3 depending on the measurement site and season of the year. In...
-
The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing
PublicationRubbers combine the flexibility with mechanical strength, supporting myriad applications, but suffer from inherent flammability. Formulation and production of flame-retardant rubber composites (FRRCs) have intensively been practiced over years, but not comprehensively reviewed. This necessity has outlined collecting, analyzing, screening, classifying, and interpreting the literature with the aim of classifying the FRRCs. We quantified...
-
Active Annotation in Evaluating the Credibility of Web-Based Medical Information: Guidelines for Creating Training Data Sets for Machine Learning
PublicationMethods Results Discussion References Abbreviations Copyright Abstract Background: The spread of false medical information on the web is rapidly accelerating. Establishing the credibility of web-based medical information has become a pressing necessity. Machine learning offers a solution that, when properly deployed, can be an effective tool in fighting medical misinformation on the web. Objective: The aim of this study is to...
-
Data on bicycle traffic in Lodz (Poland) paired with weather and air quality data
Open Research DataThe file contains data on bicycle traffic registered by counting stations loacted in Lodz in the years 2016-2019. The data are paired with weather and air quality data from Lodz collected for the same period. The data is described below:
-
Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublicationAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
-
Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
-
Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks
PublicationA method developed for parametrization of EEG signals gathered from participants with acquired brain injuries is shown. Signals were recorded during therapeutic session consisting of a series of computer assisted exercises. Data acquisition was performed in a neurorehabilitation center located in Poland. The presented method may be used for comparing the performance of subjects with acquired brain injuries (ABI) who are involved...
-
Comparison of single best artificial neural network and neural network ensemble in modeling of palladium microextraction
Publication -
Detection of immunological agent by optical fiber sensor: preliminary study
PublicationThe objective of this study is the application of optical methods for detection of immunological agent concentration. As the agent we used the Cyclaid, produced by Apotex Inc. In this article we investigated different Cyclaid concentrations in water. We used a Fabry-Pérot interferometer working in a reflective mode, the measurements were performed with source with central wavelength λ = 1550 nm. The preliminary investigation have...
-
Foundations and Trends in Machine Learning
Journals -
Machine Learning and Knowledge Extraction
Journals -
Machine Learning-Science and Technology
Journals -
Indoor Air Quality: A Bibliometric Study
Publication -
Detecting Lombard Speech Using Deep Learning Approach
PublicationRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
-
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...
-
Currently Commercially Available Chemical Sensors Employed for Detection of Volatile Organic Compounds in Outdoor and Indoor Air
PublicationThe paper presents principle of operation and design of the most popular chemical sensors for measurement of volatile organic compounds (VOCs) in outdoor and indoor air. It describes the sensors for evaluation of explosion risk including pellistors and IR-absorption sensors as well as the sensors for detection of toxic compounds such as electrochemical (amperometric), photoionization and semiconductor with solid electrolyte ones....
-
Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublicationPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
-
Different Ways to Apply a Measurement Instrument of E-Nose Type to Evaluate Ambient Air Quality with Respect to Odour Nuisance in a Vicinity of Municipal Processing Plants
PublicationThis review paper presents different ways to apply a measurement instrument of e-nose type to evaluate ambient air with respect to detection of the odorants characterized by unpleasant odour in a vicinity of municipal processing plants. An emphasis was put on the following applications of the electronic nose instruments: monitoring networks, remote controlled robots and drones as well as portable devices. Moreover, this paper presents...
-
Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance
PublicationIdentification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable...
-
Efficiency of linear and non-linear classifiers for gas identification from electrocatalytic gas sensor
PublicationElectrocatalytic gas sensors belong to the family of electrochemical solid state sensors. Their responses are acquired in the form of I-V plots as a result of application of cyclic voltammetry technique. In order to obtain information about the type of measured gas the multivariate data analysis and pattern classification techniques can be employed. However, there is a lack of information in literature about application of such...
-
Low-volume label-free SARS-CoV-2 detection with the microcavity-based optical fiber sensor
PublicationAccurate 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...
-
Interactive information and decision support system for urban and industrial air quality management based on multi-agent system
PublicationThis article presents conception of interactive information and decision support system for urban and industrial air quality management. The emphasis of the project is on real-time analysis and multi-media information, and the support of distributed and mobile clients through the Internet. The approach integrates meteorological data and forecasts, air quality and emission monitoring, dynamic 3D simulation modelling and forecasting,...
-
Integrating modelling, simulation and data management tools to create a planning support system for the improvement of air quality by urban planning solutions
PublicationThe urbanization pressure requires urban planners, designers, and policy makers to be more responsive to the challenges related to improving the quality of the urban environment and the living conditions of the inhabitants. One of the many environmental issues that need to be taken into account is urban air pollution. As the process of urban ventilation and air pollution dis-persion is significantly affected by the urban layout,...
-
Efficient uncertainty quantification using sequential sampling-based neural networks
PublicationUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
-
Constrained aerodynamic shape optimization using neural networks and sequential sampling
PublicationAerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...
-
Hierarchical 2-step neural-based LEGO bricks detection and labeling
PublicationLEGO bricks are extremely popular and allow the creation of almost any type of construction due to multiple shapes available. LEGO building requires however proper brick arrangement, usually done by shape. With over 3700 different LEGO parts this can be troublesome. In this paper, we propose a solution for object detection and annotation on images. The solution is designed as a part of an automated LEGO bricks arrangement. The...
-
Digits Recognition with Quadrant Photodiode and Convolutional Neural Network
PublicationIn this paper we have investigated the capabilities of a quadrant photodiode based gesture sensor in the recognition of digits drawn in the air. The sensor consisting of 4 active elements, 4 LEDs and a pinhole was considered as input interface for both discrete and continuous gestures. Index finger and a round pointer were used as navigating mediums for the sensor. Experiments performed with 5 volunteers...
-
Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublicationIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
-
Artificial neural network based sensorless control ofinduction motor.
PublicationW artykule przedstawiono bezczujnikowy układ sterowania silnikiem indukcyjnym wykorzystujący sztuczne sieci neuronowe (ANN). Sieć neuronową wykorzystano w regulatorze prędkości silnika. Zaprezentowano wyniki badań symulacyjnych.
-
NIRCa: An artificial neural network-based insulin resistance calculator
Publication -
Properties of an innovative multi-functional finish for the improvement of indoor air quality
PublicationDue to lifestyle changes, people spend most of their time indoors at present; thus, Indoor Air Quality (IAQ) is a matter of utmost importance. Multi-functional and innovative finishes can help to passively improve the IAQ, benefitting the health and comfort of occupants. For this study, reference and pre-mixed commercial mortars are compared to a new multi-functional hydraulic lime mortar for indoor finishes, in which conventional...
-
A framework for Air Quality Management Zones - Useful GIS-based tool for urban planning: Case studies in Antwerp and Gdańsk
PublicationThere is a growing recognition of the importance of proper urban design in the improvement of air flow and pollution dispersion and in reducing human exposure to air pollution. However, a limited number of studies have been published so far focusing on the development of standard procedures which could be applied by urban planners to effectively evaluate urban conditions with respect to air quality. To fill this gap, a new approach...
-
Employment of passive sampling in monitoring indoor air quality in selected residences in a Tri-city area in Poland
PublicationTime-weighted average concentrations of selected volatile compounds were measured in chosen residences in a Tri-City area of Poland by means of passive sampling. The results were compared to those obtained by dynamic technique – sorption tubes filled with Tenax TA sorbent. Results obtained by employing the two techniques were similar. Total volatile organic compound (TVOC) parameters were also determined. An attempt was also...
-
Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublicationIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
-
Electrochemical sensor for measurement of volatile organic compounds in air
PublicationPrzedstawiono rezultaty badań prototypowego czujnika do oznaczania mrówczanu etylu i formaldehydu w powietrzu. Określono czułość wskazań czujnika i jego granice oznaczalności wykorzystując jako techniki detekcyjne pulsową woltamperometrię różnicową (DPV) oraz woltamperometrię fali prostokątnej (SWV). Elektrodę roboczą i przeciwelektrodę stanowiły elektrody z Pt. Elektrolitem wewnętrznym była ciecz jonowa (chlorek 1-heksylo,3-metyloimidazolinowy)....
-
Potentiometric sensor containing set of ion selective electrodes with lipid modified membranes for quality assessment of tested non-alcoholic beverages
PublicationPotentiometric sensors may be a good tool for fast quality control of commercial drinks. In this work, such a sensor, containing a set of ion-selective electrodes with lipid-modified membranes (benzylhexadecyldimethylammonium chloride monohydrate, hexadecylamine, 1-dodecanol, elaidic acid, cholesterol) was used for discrimination and quality control of non-alcoholic beverages, mainly composed of sugar and citric acid. It was found...