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Search results for: AIR POLLUTION, LOW-COST SENSOR CALIBRATION, MACHINE LEARNING, DATA PRE-PROCESSING, NEURAL NETWORKS
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Hardware-Software Implementation of a Sensor Network for CityTraffic Monitoring Using the FPGA- and ASIC-Based Sensor Nodes
PublicationArtykuł opisuje prototypową sieć sensorową do monitorowania ruchu pojazdów w mieście. Węzły sieci sensorowej, wyposażone w kamerę o niskiej rozdzielczości, obserwują ulice i wykrywają poruszające się obiekty. Detekcja obiektów jest realizowana w oparciu o własny algorytm segmentacji obrazów, wykorzystujący podwójne odejmowanie tła, wykrywanie krawędzi i cieni, działający na dedykowanym systemie mikroelektronicznym typu ''System...
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A novel calibration method for RSS-based DoA estimation using ESPAR antennas
PublicationIn this paper, we introduce a new calibration method that can successfully be used in direction of arrival (DoA) estimation using electronically steerable parasitic array radiator (ESPAR) antennas and employing power-pattern cross-correlation (PPCC) algorithm, which relies on received signal strength (RSS) values recorded at the antenna output port. Instead of the commonly used two-step approach, during which ESPAR antenna calibration...
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Evaluation of the prediction ability of air pollutants based on the electronic nose responses
PublicationElectronic noses are able to perform on-line measurements of the toxic volatile compounds in air. Due to their low cost and compact size they can be placed in the areas exposed to pollution, outside the laboratory. Those advantages, on the other side, force the need for development of the reliable sensors data analysis procedures. One of the most important issues connected with electronic noses is the lack of stability of the gas...
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublicationThis work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...
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A universal IT system architecture for servicing, collecting, storing, processing and presenting data from wireless devices
PublicationIn the article we present a universal IT system architecture, which allows one to develop, based on mobile and multiplatform JAVA language, applications capable of working with many different wireless systems in an easy and effective way. Modular system architecture supports efficient data processing and enables convenient presentation of chosen parameters. Additionally, proposed IT system architecture provides easy adoption to...
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublicationWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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Towards neural knowledge DNA
PublicationIn this paper, we propose the Neural Knowledge DNA, a framework that tailors the ideas underlying the success of neural networks to the scope of knowledge representation. Knowledge representation is a fundamental field that dedicates to representing information about the world in a form that computer systems can utilize to solve complex tasks. The proposed Neural Knowledge DNA is designed to support discovering, storing, reusing,...
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Low-Cost Modeling of Microwave Components by Means of Two-Stage Inverse/Forward Surrogates and Domain Confinement
PublicationFull-wave electromagnetic (EM) analysis is one of the most important tools in the design of modern microwave components and systems. EM simulation permits reliable evaluation of circuits at the presence of cross-coupling effects or substrate anisotropy, as well as for accounting for interactions with the immediate environment. However, repetitive analyses required by EM-driven procedures, such as parametric optimization or statistical...
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A New Approach to Capacitive Sensor Measurements Based on a Microcontroller and a Three-Gate Stable RC Oscillator
PublicationA complete smart capacitive sensor solution basedA complete smart capacitive sensor solution based on a microcontroller was developed. This approach includes the development of both the hardware and software. The hardware part comprises an 8-bit microcontroller equipped with two timers/counters and a three-gate stable RC relaxation oscillator. The software part handles system configuration, measurement control, communication control,...
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OBTAINING FLUID FLOW PATTERN FOR TURBINE STAGE WITH NEURAL MODEL.
PublicationIn the paper possibility of applying neural model to obtaining patterns of proper operation for fluid flow in turbine stage for fluid-flow diagnostics is discussed. Main differences between Computational Fluid Dynamics (CFD) solvers and neural model is given, also limitations and advantages of both are considered. Time of calculations of both methods was given, also possibilities of shortening that time with preserving the accuracy...
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Low-cost and reliable geometry scaling of compact microstrip couplers with respect to operating frequency, power split ratio, and dielectric substrate parameters
PublicationA technique for rapid re-design of miniaturised microstrip couplers with respect to operating conditions as well as material parameters of the dielectric substrate is proposed. The dimension scaling process is based on a set of pre-optimised reference designs, obtained for an equivalent circuit model of the coupler at hand. The reference designs are utilised to construct an inverse surrogate model which – upon suitable correction...
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Influence of YARN Schedulers on Power Consumption and Processing Time for Various Big Data Benchmarks
PublicationClimate change caused by human activities can influence the lives of everybody onthe planet. The environmental concerns must be taken into consideration by all fields of studyincludingICT. Green Computing aims to reduce negative effects of IT on the environment while,at the same time, maintaining all of the possible benefits it provides. Several Big Data platformslike Apache Spark orYARNhave become widely used in analytics and...
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Analog multiplier for a low-power integrated image sensor
PublicationArtykuł przedstawia nowe podejście do projektowania tanich niskomocowych zintegrowanych sensorów optycznych. W odróżnieniu od wcześniej stosowanych rozwiązań opartych na masowym przetwarzaniu równoległym, zaproponowany mnożnik macierzowy charakteryzuje się korzystniejszymi cechami. Proponowane rozwiązanie, chociaż mniej elastyczne w sensie liczby możliwych do zaimplementowania algorytmów wstępnej obróbki obrazu, cechuje się znaczącą...
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Analog multiplier for a low-power integrated image sensor
PublicationArtykuł przedstawia nowe podejście do projektowania tanich niskomocowych zintegrowanych sensorów optycznych. W odróżnieniu od wcześniej stosowanych rozwiązań opartych na masowym przetwarzaniu równoległym, zaproponowany mnożnik macierzowy charakteryzuje się korzystniejszymi cechami. Proponowane rozwiązanie, chociaż mniej elastyczne w sensie liczby możliwych do zaimplementowania algorytmów wstępnej obróbki obrazu, cechuje się znaczącą...
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Study of data scheduling methods in the WiMAX Mobile metropolitan area networks
PublicationThe paper discusses basic assumptions of the WiMAX Mobile system. It also presents and analyses the results of simulation tests run for selected data scheduling methods and subcarrier allocation. Based on the test results, the authors have prepared a comparative analysis of two popular data scheduling methods, i.e. WRR and PF, and their own method CDFQ which uses information about the current channel situation for the queuing processes...
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Neural networks based NARX models in nonlinear adaptive control
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Application of neural networks for description of pressure distribution in slide bearing.
PublicationBadano rozkład ciśnienia hydrodynamicznego w łożysku ślizgowym dla wybranych wariantów łożyska. Wykazano, że zastosowanie sieci neuronowych umożliwia opis rozkładu ciśnienia hydrodynamicznego z uwzględnieniem zmian geometrycznych (bezwymiarowa długość - L) i mechanicznych (mimośrodowość względem H) łożyska.
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Identification of slide bearing main parameters using neural networks.
PublicationWykazano, że sieci neuronowe jak najbardziej nadają się do identyfikacji głównych parametrów geometrycznych i ruchowych hydrodynamicznych łożysk ślizgowych.
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Application of Artificial Neural Networks in Investigations of Steam Turbine Cascades
PublicationZaprezentowano wyniki badań numerycznych zastosowania sieci neuronowych przy obliczeniach przepływów w palisadach turbin parowych. Na podstawie uzyskanych wyników wykazano, że sieci neuronowe mogą być używane do szacowania przestrzennego rozkładu parametrów przepływu, takich jak entalpia, entropia, ciśnienie czy prędkość czynnika w kanale przepływowym. Omówiono również zastosowania tego typu metod przy projektowaniu palisad, stopni...
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Prediction of antimicrobial activity of imidazole derivatives by artificial neural networks
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Forecasting of currency exchange rates using artificial neural networks
PublicationW rozdziale tym autor przedstawił wyniki swoich badań nad wykorzystaniem sztucznych sieci neuronowych do prognozowania kursu walut (na przykładzie pary walutowej PLN-USD).Głównym celem badań było porównanie skuteczności przewidywania kursu złotówki w latach 1997 - 2005 przy pomocy różnych rodzajów sieci neuronowych.
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Using neural networks to examine trending keywords in Inventory Control
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Wireless data transmission for fiber optical sensor system
PublicationW artykule opisano możliwość wykorzystania bezprzewodowego systemu transmisji danych do transmisji sygnałów z czujników światłowodowych.
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
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Adding Intelligence to Cars Using the Neural Knowledge DNA
PublicationIn this paper we propose a Neural Knowledge DNA based framework that is capable of learning from the car’s daily operation. The Neural Knowledge DNA is a novel knowledge representation and reasoning approach designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing devices. We examine our framework for drivers' classification based on their driving behaviour. The experimental...
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On deterministic procedures for low-cost multi-objective design optimization of miniaturized impedance matching transformers
PublicationPurpose This paper aims to investigate deterministic strategies for low-cost multi-objective design optimization of compact microwave structures, specifically, impedance matching transformers. The considered methods involve surrogate modeling techniques and variable-fidelity electromagnetic (EM) simulations. In contrary to majority of conventional approaches, they do not rely on population-based metaheuristics, which permit lowering...
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Cleaner energy for sustainable future using hybrid photovoltaics-thermoelectric generators system under non-static conditions using machine learning based control technique
PublicationIn addition to the load demand, the temperature difference between the hot and cold sides of the thermoelectric generator (TEG) module determines the output power for thermoelectric generator systems. Maximum power point tracking (MPPT) control is needed to track the optimal global power point as operating conditions change. The growing use of electricity and the decline in the use of fossil fuels have sparked interest in photovoltaic-TEG...
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Data Compression in Ultrasonic Network Communication via Sparse Signal Processing
PublicationThis document presents the approach of using compressed sensing in signal encoding and information transferring within a guided wave sensor network, comprised of specially designed frequency steerable acoustic transducers (FSATs). Wave propagation in a damaged plate was simulated using commercial FEM-based software COMSOL. Guided waves were excited by means of FSATs, characterized by the special shape of its electrodes, and modeled...
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Asking Data in a Controlled Way with Ask Data Anything NQL
PublicationWhile to collect data, it is necessary to store it, to understand its structure it is necessary to do data-mining. Business Intelligence (BI) enables us to make intelligent, data-driven decisions by the mean of a set of tools that allows the creation of a potentially unlimited number of machine-generated, data-driven reports, which are calculated by a machine as a response to queries specified by humans. Natural Query Languages...
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Music information retrieval—The impact of technology, crowdsourcing, big data, and the cloud in art.
PublicationThe exponential growth of computer processing power, cloud data storage, and crowdsourcing model of gathering data bring new possibilities to music information retrieval (mir) field. Mir is no longer music content retrieval only; the area also comprises the discovery of expressing feelings and emotions contained in music, incorporating other than hearing modalities for helping this issue, users’ profiling, merging music with social...
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General concept of reduction process for big data obtained by interferometric methods
PublicationInterferometric sonar systems apply the phase content of the sonar signal to measure the angle of a wave front returned from the seafloor or from a target. It collect a big data – datasets that are so large or complex that traditional data processing application software is inadequate to deal with them. The recording a large number of data is associated with the difficulty of their efficient use. So data have to be reduced. The main...
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Analysing and processing of geotagged social media
PublicationThe 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...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublicationForecasting 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...
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublicationNowadays, 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...
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THE COST ANALYSIS OF CORROSION PROTECTION SOLUTIONS FOR STEEL COMPONENTS IN TERMS OF THE OBJECT LIFE CYCLE COST
PublicationSteel 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....
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Categorization of emotions in dog behavior based on the deep neural network
PublicationThe 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...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational 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...
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Monitoring of n-butanol vapors biofiltration process using an electronic nose combined with calibration models
PublicationMalodours, 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...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublicationThis 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...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublicationRenal 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...
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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...
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Low cost real time UAV stereo photogrammetry modelling technique – accuracy considerations
PublicationThe 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...
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A Simple Neural Network for Collision Detection of Collaborative Robots
PublicationDue 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...
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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublicationMusic 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...
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Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
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KTaO3-based nanocomposites for air treatment
PublicationThe 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...
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Reliability of flue gas desulphurisation installations - the essential condition of efficient air pollution control
PublicationW 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...
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Health impacts of indoor air pollution from household solid fuel on children and women
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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublicationRemote 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...
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Multianalyte Calibration Methods for Potentiometric Integrated Sensors System for Determination of Ions Concentration in a Body Fluids
PublicationIn 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...