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Wyniki wyszukiwania dla: AIR QUALITY, POLLUTANT DETECTION, NITROGEN DIOXIDE, SENSOR CORRECTION, MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS
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Machine Learning and data mining tools applied for databases of low number of records
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublikacjaIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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Designing RBF Networks Using the Agent-Based Population Learning Algorithm
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The detection of Alternaria solani infection on tomatoes using ensemble learning
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Deep learning-based waste detection in natural and urban environments
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Towards high quality ITO coatings: the impact of nitrogen admixture in HiPIMS discharges
PublikacjaThe paper reports controlled deposition of optically transparent and electrically conductive ITO films prepared by a combination of rf (13.56 MHz) and High Power Impulse Magnetron Sputtering (HiPIMS) systems without any post deposition thermal treatment/annealing. It is shown that (i) reactive admixture of N2 gas to the process and (ii) pressure in the deposition chamber enable to optimize optical properties of ITO films. Furthermore,...
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Carbon dioxide fracturing technologies for shale gas recovery
PublikacjaThis paper presents literature survey on the theoretical and practical aspects of gas production from shale using carbon dioxide fracturing. Development of technical and environmental aspects of carbon dioxide fracturing technologies are also considered. Patents applicable to carbon dioxide fracturing are reviewed.
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublikacjaMalignant 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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Investigation of the temperature modulation parameters on semiconductor gas sensor response
PublikacjaIn this work we present the results of the investigation of the sensing properties of semiconductor gas sensors with a sinusoidally modulated temperature in the presence of synthetic air (SA) and three volatile air pollutants, i.e. NH3, NO2 and SO2. The measurements were performed for different average sensor heater temperatures and the amplitude of the modulation signal. In addition, the extraction of features from the sensor...
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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...
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Identification of defected sensors in an array of amperometric gas sensors
PublikacjaPurpose Amperometric gas sensors are commonly used in air quality monitoring in long-term measurements. Baseline shift of sensor responses and power failure may occur over time, which is an obstacle for reliable operation of the entire system. The purpose of this study is to check the possibility of using PCA method to detect defected samples, identify faulty sensor and correct the responses of the sensor identified as faulty. Design/methodology/approach In...
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Pathways of Nitrogen Removal in Hybrid Treatment Wetlands
PublikacjaHybrid Treatment Wetlands (HTWs) are composed of two or more filters with different modes of flow, allowing the benefits of both types of bed to be combined, resulting in better effluent quality (nitrogen and organic compounds removal). Such a heterogeneous environment creates possibilities for different mechanisms of nitrogen removal. The objective of the present study was to investigate the removal of nitrogen versus a range...
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Adsorption chiller in a combined heating and cooling system: simulation and optimization by neural networks
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Aerodynamic excitations generated in turbine shroud clearance determined bymeans of neural networks
PublikacjaSiły aerodynamiczne generowane w uszczelnieniach turbinowych z reguły opisywane są modelem liniowym. Przy dużych drganiach wirnika sposób ten daje niezbyt dokładne wyniki. Zaproponowano wykorzystanie sieci neuronowych do określania sił ciśnieniowych powstających w uszczelnieniu. Wyniki porównano z badaniami eksperymentalnymi.
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Nitrogen-Doped Diamond Film for Optical Investigation of Hemoglobin Concentration
PublikacjaIn this work we present the fabrication and characterization of a diamond film which can be utilized in the construction of optical sensors for the investigation of biological samples. We produced a nitrogen-doped diamond (NDD) film using a microwave plasma enhanced chemical vapor deposition (MWPECVD) system. The NDD film was investigated with the use of scanning electron microscopy (SEM), atomic force microscopy (AFM) and Raman...
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Diagnostic potential for a serum miRNA neural network for detection of ovarian cancer
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Integrating Statistical and Machine‐Learning Approach for Meta‐Analysis of Bisphenol A‐Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival
PublikacjaBisphenols are important environmental pollutants that are extensively studied due to different detrimental effects, while the molecular mechanisms behind these effects are less well understood. Like other environmental pollutants, bisphenols are being tested in various experimental models, creating large expression datasets found in open access storage. The meta‐analysis of such datasets is, however, very complicated for various...
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Evolution of Animats Following a Moving Target in an Artificial Ecosystem
PublikacjaMany biological animals, even microscopically small, are able to track moving sources of food. In this paper, we investigate the emergence of such behavior in artificial animals (animats) in a 2-dimensional simulated liquid environment. These "predators" are controlled by evolving artificial gene regulatory networks encoded in linear genomes. The fate of the predators is determined only by their ability to gather food and reproduce—no...
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Distance magnetic nanoparticle detection using a magnetoelectric sensor for clinical interventions
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A Development of a Capacitive Voltage Divider for High Voltage Measurement as Part of a Combined Current and Voltage Sensor
PublikacjaThis article deals with the development of capacitive voltage divider for high voltage measurements and presents a method of analysis and optimization of its parameters. This divider is a part of a combined voltage and current sensor for measurements in high voltage power networks. The sensor allows continuous monitoring of the network distribution status and performs a quick diagnosis and location of possible network failures....
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Correction to: Azo group(s) in selected macrocyclic compounds
PublikacjaIn the original publication of the article, a part of Scheme 12 was missed. The correct version of Scheme 12 was provided in this correction article. The original article has also been corrected.
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublikacjaThe paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...
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Studies on the utilization of post-distillation liquid from Solvay process to carbon dioxide capture and storage
PublikacjaIn this work, a method of precipitated calcium carbonate production from the post-distillation liquid created in the Solvay process and waste carbon dioxide was proposed and investigated. Precipitation was carried out in a model solution of calcium chloride containing ammonia at various molar ratios in relation to Ca2+ ions, while gaseous carbon dioxide was supplied to the reactor as a pure gas or as a mixture with air. It was...
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Detection and segmentation of moving vehicles and trains using Gaussian mixtures, shadow detection and morphological processing
PublikacjaSolution presented in this paper combines background modelling, shadow detection and morphological and temporal processing into one system responsible for detection and segmentation of moving objects recorded with a static camera. Vehicles and trains are detected based on their pixellevel difference from the continually updated background model utilizing a Gaussian mixture calculated separately for every pixel. The shadow detection...
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Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublikacjaThe use of metal halide perovskites in photocatalytic processes has been attempted because of their unique optical properties. In this work, for the first time, Pb-free Bi-based perovskites of the Cs3Bi2X9 type (X = Cl, Br, I, Cl/Br, Cl/I, Br/I) were synthesized and subjected to comprehensive morphological, structural, and surface analyses, and photocatalytic properties in the phenol degradation reaction were examined. Furthermore,...
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Near Field Coupled Wireless Microwave Sensor
PublikacjaThis paper presents a wireless planar microwave sensor operating at industrial scientific and medical (ISM) frequency for the detection of dielectric materials. The microwave sensor consists of a reader (ground defected microstrip coupled line) and a passive tag where a complementary split-ring resonator (CSRR) is made on the commercially available copper-foil. The CSRR is a peel-off type tag that is excited using the near field...
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Jakość powietrza wewnętrznego - lotne związki organiczne jako wskaźnik jakości powietrza wewnętrznego = Indoor air quality - volatile organic compounds as an indicator of the quality of indoor air
PublikacjaPomieszczenia zamknięte z jednej strony są barierą chroniącą przed negatywnymi czynnikami środowiska, zmiennymi warunkami pogodowymi - deszczem, wiatrem, niską lub wysoką temperaturą, z drugiej jednak strony - w zamkniętych wnętrzach nastepuje często kumulacja toksycznych związków organicznych i nieorganicznych, co nie pozostaje bez wpływu na ludzkie zdrowie.Głównym celem badań jest oszacowanie jakości powietrza wewnętrznego pod...
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Expedited Machine-Learning-Based Global Design Optimization of Antenna Systems Using Response Features and Multi-Fidelity EM Analysis
PublikacjaThe design of antenna systems poses a significant challenge due to stringent per-formance requirements dictated by contemporary applications and the high com-putational costs associated with models, particularly full-wave electromagnetic (EM) analysis. Presently, EM simulation plays a crucial role in all design phases, encompassing topology development, parametric studies, and the final adjustment of antenna dimensions. The latter...
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An Analysis of Uncertainty and Robustness of Waterjet Machine Positioning Vision System
PublikacjaThe paper presents a new Automatic Waterjet Positioning Vision System (AWPVS) and investigates components of workpiece positioning accuracy. The main purpose of AWPVS is to precisely identify the position and rotation of a workpiece placed on a waterjet machine table. Two webcams form a basis for the system, and constitute its characteristics. The proposed algorithm comprises various image processing techniques to assure a required...
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Optimised Allocation of Hard Quality Sensors for Robust Monitoring of Quality in Drinking Water Distribution Systems
PublikacjaA problem of optimised placement of the hard quality sensors in Drinking Water Distribution Systems for robust quality monitoring is formulated. Two numerical algorithms to solve the problem are derived. The optimality is meant as achieving a desired trade off between the sensor capital and maintenance costs and resulting robust estimation accuracy of the monitoring algorithm. The robust estimation algorithm recently developed...
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Fast-response optoelectronic detection of explosives’ residues from the nitroaromatic compounds detonation: field studies approach
PublikacjaWe are presenting an application of optoelectronic nitrogen dioxide (NO2) analyzer based on cavity enhanced absorption spectroscopy in the detection of traces of explosives after detonation. It has been shown that the analyzer using blue-violet laser is able to detect explosive residues after the detonation of various amounts of nitroaromatic compounds (75g-1kg) with higher efficiency than the HPLC soil sample testing equipment,...
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Food analysis using artificial senses.
PublikacjaNowadays, consumers are paying great attention to the characteristics of food such as smell, taste, and appearance. This motivates scientists to imitate human senses using devices known as electronic senses. These include electronic noses, electronic tongues, and computer vision. Thanks to the utilization of various sensors and methods of signal analysis, artificial senses are widely applied in food analysis for process monitoring...
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Cascade Object Detection and Remote Sensing Object Detection Method Based on Trainable Activation Function
PublikacjaObject detection is an important process in surveillance system to locate objects and it is considered as major application in computer vision. The Convolution Neural Network (CNN) based models have been developed by many researchers for object detection to achieve higher performance. However, existing models have some limitations such as overfitting problem and lower efficiency in small object detection. Object detection in remote...
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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublikacjaThis work proposes a novel adaptive global surrogate modeling algorithm which uses two neural networks, one for prediction and the other for the model uncertainty. Specifically, the algorithm proceeds in cycles and adaptively enhances the neural network-based surrogate model by selecting the next sampling points guided by an auxiliary neural network approximation of the spatial error. The proposed algorithm is tested numerically...
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Adding Intelligence to Cars Using the Neural Knowledge DNA
PublikacjaIn 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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Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
PublikacjaIntroduction: Alzheimer’s Disease (AD) is a degenerative brain disorder characterized by cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the mortality rate through slowing down its progression. The prevention and detection of AD is the emerging research topic for many researchers. The structural Magnetic Resonance Imaging (sMRI) is an extensively used imaging technique in detection of AD, because...
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Element sensor based on microplasma generators
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OBTAINING FLUID FLOW PATTERN FOR TURBINE STAGE WITH NEURAL MODEL.
PublikacjaIn 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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Pathways of nitrogen compounds depletion in hybrid constructed wetlands
PublikacjaHybrid Constructed Wetlands are composed of two or more filters with mixed flow direction of sewage. Apparently in the HCWS the benefits of both types of bed are merged, resulting in better effluent quality (organic and nitrogen componds removal). Such heterogeneous environment creates possibilities for different ways of nitrogen "disappearing". The objective of the present study was to compare the removal of nitrogen with accompanying...
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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublikacjaA problem related to the development of an algorithm designed to find an architecture of artificial neural network used for black-box modelling of dynamic systems with time delays has been addressed in this paper. The proposed algorithm is based on a well-known NeuroEvolution of Augmenting Topologies (NEAT) algorithm. The NEAT algorithm has been adjusted by allowing additional connections within an artificial neural network and...
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The effect of reduced pressure on carbon dioxide flow boiling heat transfer in minichannels
Publikacja. In the paper presented are the results of the study on the effect of reduced pressure on flow boiling heat transfer data in minichannels as well as conventional ones. That effect renders that most of heat transfer correlations fail to return appropriate results of predictions. Mostly they have been developed for the reduced pressures from the range 0.1-0.3. The special correction has been postulated to the in-house model of flow...
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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
PublikacjaIn 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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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...
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Machine Learning for Control Systems Security of Industrial Robots: a Post-covid-19 Overview
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines
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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublikacjaTe feld of Big Data is rapidly developing with a lot of ongoing research, which will likely continue to expand in the future. A crucial part of this is Knowledge Discovery from Data (KDD), also known as the Knowledge Discovery Process (KDP). Tis process is a very complex procedure, and for that reason it is essential to divide it into several steps (Figure 1). Some authors use fve steps to describe this procedure, whereas others...
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A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks
PublikacjaThe visual data acquisition from small unmanned aerial vehicles (UAVs) may encounter a situation in which blur appears on the images. Image blurring caused by camera motion during exposure significantly impacts the images interpretation quality and consequently the quality of photogrammetric products. On blurred images, it is difficult to visually locate ground control points, and the number of identified feature points decreases...