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Search results for: AIR QUALITY, POLLUTANT DETECTION, NITROGEN DIOXIDE, SENSOR CORRECTION, MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS
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Towards high quality ITO coatings: the impact of nitrogen admixture in HiPIMS discharges
PublicationThe 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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Investigation of the temperature modulation parameters on semiconductor gas sensor response
PublicationIn 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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Carbon dioxide fracturing technologies for shale gas recovery
PublicationThis 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
PublicationMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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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
PublicationBisphenols 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
PublicationMany 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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Identification of defected sensors in an array of amperometric gas sensors
PublicationPurpose 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
PublicationHybrid 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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Aerodynamic excitations generated in turbine shroud clearance determined bymeans of neural networks
PublicationSiły 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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Adsorption chiller in a combined heating and cooling system: simulation and optimization by neural networks
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Nitrogen-Doped Diamond Film for Optical Investigation of Hemoglobin Concentration
PublicationIn 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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Correction to: Azo group(s) in selected macrocyclic compounds
PublicationIn 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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Distance magnetic nanoparticle detection using a magnetoelectric sensor for clinical interventions
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Diagnostic potential for a serum miRNA neural network for detection of ovarian cancer
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A Development of a Capacitive Voltage Divider for High Voltage Measurement as Part of a Combined Current and Voltage Sensor
PublicationThis 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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Lead-free bismuth-based perovskites coupled with g–C3N4: A machine learning based novel approach for visible light induced degradation of pollutants
PublicationThe 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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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublicationThe 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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Expedited Machine-Learning-Based Global Design Optimization of Antenna Systems Using Response Features and Multi-Fidelity EM Analysis
PublicationThe 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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Near Field Coupled Wireless Microwave Sensor
PublicationThis 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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Studies on the utilization of post-distillation liquid from Solvay process to carbon dioxide capture and storage
PublicationIn 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
PublicationSolution 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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An Analysis of Uncertainty and Robustness of Waterjet Machine Positioning Vision System
PublicationThe 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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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
PublicationPomieszczenia 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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Food analysis using artificial senses.
PublicationNowadays, 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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Optimised Allocation of Hard Quality Sensors for Robust Monitoring of Quality in Drinking Water Distribution Systems
PublicationA 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
PublicationWe 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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Cascade Object Detection and Remote Sensing Object Detection Method Based on Trainable Activation Function
PublicationObject 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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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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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublicationThis 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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Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
PublicationIntroduction: 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.
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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Pathways of nitrogen compounds depletion in hybrid constructed wetlands
PublicationHybrid 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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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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Neural modelling of dynamic systems with time delays based on an adjusted NEAT algorithm
PublicationA 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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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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Advances in Architectures, Big Data, and Machine Learning Techniques for Complex Internet of Things Systems
PublicationTe 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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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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The effect of reduced pressure on carbon dioxide flow boiling heat transfer in minichannels
Publication. 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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Lifelong Learning Idea in Architectural Education
PublicationThe recent advances in IT and technology are forcing changes in the approach to educating society. In the 20th century, life-long learning was understood as educating adults in order to improve their occupational qualifications. Life-long learning allows the needs of the present-day world to be addressed through providing the individual with education at every stage of his/her life various forms. The search for a new model...
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Correction: Surgeons’ perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey
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Broken Rotor Symptons in the Sensorless Control of Induction Machine
PublicationInverter fed sensorless controlled variable speed drives with induction machine are widely used in the industry applications, also in wind power generation and electric vehicles. On-line self diagnostic systems implementation is needed for early stage fault detection and avoiding a critical fault. Diagnostic algorithms in modern DSP-based controllers can operate simultaneously with control system functions. In the closed-loop controlled...
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Is Artificial Intelligence Ready to Assess an Enterprise’s Financial Security?
PublicationThis study contributes to the literature on financial security by highlighting the relevance of the perceptions and resulting professional judgment of stakeholders. Assessing a company’s financial security using only economic indicators—as suggested in the existing literature—would be inaccurate when undertaking a comprehensive study of financial security. Specifically, indices and indicators based on financial or managerial reporting...
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Guest editorial: learning, scheduling, resource optimization, and evolution in smart artificial systems: challenges and support
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublicationTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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A Novel Method for the Deblurring of Photogrammetric Images Using Conditional Generative Adversarial Networks
PublicationThe 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...
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Musical Instrument Identification Using Deep Learning Approach
PublicationThe work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related to musical instrument identification. It focuses on tasks performed, input type, algorithms employed, and metrics used. The paper starts with the background presentation, i.e., metadata...
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Application of mechanistic and data-driven models for nitrogen removal in wastewater treatment systems
PublicationIn this dissertation, the application of mechanistic and data-driven models in nitrogen removal systems including nitrification and deammonification processes was evaluated. In particular, the influential parameters on the activity of the Nitrospira activity were assessed using response surface methodology (RSM). Various long-term biomass washout experiments were operated in two parallel sequencing batch reactor (SBR) with a different...