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Search results for: COST-EFFICIENT SENSORS
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Cost-Efficient Design Methodology for Compact Rat-Race Couplers
PublicationIn this article, a reliable and low-cost design methodology for simulation-driven optimization of miniaturized rat-race couplers (RRCs) is presented. We exploit a two-stage design approach, where a composite structure (a basic building block of the RRC structure) is first optimized using a pattern search algorithm, and, subsequently, the entire coupler is tuned by means of surrogate-based optimization (SBO) procedure. SBO is executed...
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The applicability of low-cost PM10 sensors for atmospheric air quality monitoring
PublicationDescribed in this work are the results of field tests carried out in the Tricity Agglomeration between 01 April 2018 and 30 June 2018 in order to evaluate the usefulness of low-cost PM10 sensors in atmospheric air quality monitoring. The results were juxtaposed with the results obtained using reference methods. The results were validated based on the measurement uncertainty as described in...
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A Surrounding World Knowledge Acquiring by Using a Low-cost Ultrasound Sensors
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Cost-efficient simulation-driven design of compact impedance matching transformers
PublicationIn this paper, an algorithmic framework for cost-efficient design optimization of miniaturized impedance matching transformers has been presented. Our approach exploits a bottom-up design that involves translating the overall design specifications for the circuit at hand to its elementary building blocks (here, compact microstrip resonant cells, CMRCs), as well as fast surrogate-assisted optimization of the cells followed by simulation-based...
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Cost-Efficient Optical Fronthaul Architectures for 5G and Future 6G Networks
PublicationFifth-generation and Beyond (5GB) wireless networks have introduced new centralized architectures such as cloud radio access network (CRAN), which necessitate extremely high-capacity low latency Fronthaul (FH). CRAN has many advantageous features in terms of cost reduction, performance enhancement, ease of deployment, and centralization of network management. Nevertheless, designing and deploying a cost-efficient FH is still a...
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Accurate Lightweight Calibration Methods for Mobile Low-Cost Particulate Matter Sensors
PublicationMonitoring air pollution is a critical step towards improving public health, particularly when it comes to identifying the primary air pollutants that can have an impact on human health. Among these pollutants, particulate matter (PM) with a diameter of up to 2.5 μ m (or PM2.5) is of particular concern, making it important to continuously and accurately monitor pollution related to PM. The emergence of mobile low-cost PM sensors...
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Cost-efficient design optimization of compact patch antennas with improved bandwidth
PublicationIn this letter, a surrogate-assisted optimization procedure for fast design of compact patch antennas with enhanced bandwidth is presented. The procedure aims at addressing a fundamental challenge of the design of antenna structures with complex topologies, which is simultaneous adjustment of numerous geometry parameters. The latter is necessary in order to find a truly optimum design and cannot be executed-at the level of high-fidelity...
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Efficient list cost coloring of vertices and/or edges of bounded cyclicity graphs
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Efficient List Cost Coloring of Vertices and∕or Edges of Some Sparse Graphs
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Efficient list cost coloring of vertices and/or edges of bounded cyclicity graphs
PublicationW artykule rozważamy listowo-kosztowe kolorowanie wierzchołków i krawędzi grafu w modelu wierzchołkowym, krawędziowym, totalnym i pseudototalnym. Stosujemy programowanie dynamiczne w celu otrzymania algorytmów wielomianowych dla drzew. Następnie uogólniamy to podejście na dowolne grafy z ograniczonymi liczbami cyklomatycznymi i na ich multikolorowania.
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Efficient list cost coloring of vertices and/or edges of some sparse graphs
PublicationRozważane jest kolorowanie wierzchołków i krawędzi grafów w modelach klasycznym, totalnym i pseudototalnym z uwzględnieniem dodatkowego ograniczenia w postaci list dostępnych kolorów. Proponujemy wielomianowy algorytm oparty na paradygmacie programowania dynamicznego dla grafów o strukturze drzewa. Wynik ten można uogólnić na grafy o liczbie cyklomatycznej ograniczonej z góry przez dowolnie wybraną stała.
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Design of Cost-Efficient Optical Fronthaul for 5G/6G Networks: An Optimization Perspective
PublicationCurrently, 5G and the forthcoming 6G mobile communication systems are the most promising cellular generations expected to beat the growing hunger for bandwidth and enable the fully connected world presented by the Internet of Everything (IoE). The cloud radio access network (CRAN) has been proposed as a promising architecture for meeting the needs and goals of 5G/6G (5G and beyond) networks. Nevertheless, the provisioning of cost-efficient...
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A High-Efficient Measurement System With Optimization Feature for Prototype CMOS Image Sensors
PublicationIn this paper, a gray-scale CMOS image sensor (CIS) characterization system with an optimization feature has been proposed. By using a very fast and precise control of light intensity, based on the pulsewidth-modulation method, it is avoided to measure the illuminance every time. These features accelerate the multicriteria CIS optimization requiring many thousands of measurements. The system throughput is 2.5 Gb/s, which allows...
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Rotational Design Space Reduction for Cost-Efficient Multi-Objective Antenna Optimization
PublicationCost-efficient multi-objective design of antenna structures is presented. Our approach is based on design space reduction algorithm using auxiliary single-objective optimization runs and coordinate system rotation. The initial set of Pareto-optimal solutions is obtained by optimizing a response surface approximation model established in the reduced space using coarse-discretization EM simulation data. The optimization engine is...
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Cost-efficient multi-objective design optimization of antennas in highly-dimensional parameter spaces
PublicationMulti-objective optimization of antenna structures in highly-dimensional parameter spaces is investigated. For expedited design, variable-fidelity EM simulations and domain patching algorithm are utilized. The results obtained for a monopole antenna with 13 geometry parameters are compared with surrogate-assisted optimization involving response surface approximation modeling.
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Cost-Efficient Bi-Layer Modeling of Antenna Input Characteristics Using Gradient Kriging Surrogates
PublicationOver the recent years, surrogate modeling has been playing an increasing role in the design of antenna structures. The main incentive is to mitigate the issues related to high cost of electromagnetic (EM)-based procedures. Among the various techniques, approximation surrogates are the most popular ones due to their flexibility and easy access. Notwithstanding, data-driven modeling of antenna characteristics is associated with serious...
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Cost-Efficient EM-Driven Size Reduction of Antenna Structures by Multi-Fidelity Simulation Models
PublicationDesign of antenna systems for emerging application areas such as the Internet of Things (IoT), fifth generation wireless communications (5G), or remote sensing, is a challenging endeavor. In addition to meeting stringent performance specifications concerning electrical and field properties, the structure has to maintain small physical dimensions. The latter normally requires searching for trade-off solutions because miniaturization...
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublicationAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublicationDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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Cost-Efficient Two-Level Modeling of Microwave Passives Using Feature-Based Surrogates and Domain Confinement
PublicationA variety of surrogate modelling techniques has been utilized in high-frequency design over the last two decades. Yet, the curse of dimensionality still poses a serious challenge in setting up re-liable design-ready surrogates of modern microwave components. The difficulty of the model-ing task is only aggravated by nonlinearity of circuit responses. Consequently, constructing a practically usable surrogate model, valid across...
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On Memory-Based Precise Calibration of Cost-Efficient NO2 Sensor Using Artificial Intelligence and Global Response Correction
PublicationNitrogen dioxide (NO2) is a prevalent air pollutant, particularly abundant in densely populated urban regions. Given its harmful impact on health and the environment, precise real-time monitoring of NO2 concentration is crucial, particularly for devising and executing risk mitigation strategies. However, achieving precise measurements of NO2 is challenging due to the need for expensive and cumbersome equipment. This has spurred...
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Variable-Fidelity Simulation Models and Sparse Gradient Updates for Cost-Efficient Optimization of Compact Antenna Input Characteristics
PublicationDesign of antennas for the Internet of Things (IoT) applications requires taking into account several performance figures, both electrical (e.g., impedance matching) and field (gain, radiation pattern), but also physical constraints, primarily concerning size limitation. Fulfillment of stringent specifications necessitates the development of topologically complex structures described by a large number of geometry parameters that...
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On Computationally-Efficient Reference Design Acquisition for Reduced-Cost Constrained Modeling and Re-Design of Compact Microwave Passives
PublicationFull-wave electromagnetic (EM) analysis has been playing a major role in the design of microwave components for the last few decades. In particular, EM tools allow for accurate evaluation of electrical performance of miniaturized structures where strong cross-coupling effects cannot be adequately quantified using equivalent network models. However, EM-based design procedures (parametric optimization, statistical analysis) generate...
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Free-standing TiO2 nanotubes decorated with spherical nickel nanoparticles as a cost-efficient electrocatalyst for oxygen evolution reaction
PublicationHere, we report significant activity towards the oxygen evolution reaction (OER) of spherical nickel nanoparticles (NPs) electrodeposited onto free-standing TiO2 nanotubes (TNT) via cyclic voltammetry. It has been shown that simple manipulation of processing parameters, including scan rate and number of cycles, allows for formation of the NPs in various diameters and amounts. The polarization data with respect to transmission electron...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Cost-Efficient Globalized Parameter Optimization of Microwave Components through Response-Feature Surrogates and Nature-Inspired Metaheuristics
PublicationDesign of contemporary microwave devices predominantly utilizes computational models, including both circuit simulators, and full-wave electromagnetic (EM) evaluation. The latter constitutes the sole generic way of rendering accurate assessment of the system outputs that considers phenomena such as cross-coupling or radiation and dielectric losses. Consequently, for reliability reasons, the final tuning of microwave device parameters...
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Cost‐efficient performance‐driven modelling of multi‐band antennas by variable‐fidelity electromagnetic simulations and customized space mapping
PublicationElectromagnetic (EM) simulations have become an indispensable tool in the design of contemporary antennas. EM‐driven tasks, for example, parametric optimization, entail considerable computational efforts, which may be reduced by employing surrogate models. Yet, data‐driven modelling of antenna characteristics is largely hindered by the curse of dimensionality. This may be addressed using the recently reported domain‐confinement...
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Cost-Efficient Surrogate Modeling of High-Frequency Structures Using Nested Kriging with Automated Adjustment of Model Domain Lateral Dimensions
PublicationSurrogate models are becoming popular tools of choice in mitigating issues related to the excessive cost of electromagnetic (EM)-driven design of high-frequency structures. Among available techniques, approximation modeling is by far the most popular due to its versatility. In particular, the surrogates are exclusively based on the sampled simulation data with no need to involve engineering insight or problem-specific knowledge....
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublicationAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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MEMS Technology Quality Requirements as Applied to Multibeam Echosounder
PublicationSmall, lightweight, power-efficient, and low-cost microelectromechanical system (MEMS) inertial sensors and microcontrollers, available in the market today, help reduce the instability of Multibeam Sonars. Current MEMS inertial measurement units (IMUs) come in many shapes, sizes, and costs — depending on the application and performance required. Although MEMS inertial sensors offer affordable, appropriately scaled units, they are...
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Low-Cost Automated Design of Compact Branch-Line Couplers
PublicationBranch-line couplers (BLCs) are important components of wireless communication systems. Conventional BLCs are often characterized by large footprints which make miniaturization an important prerequisite for their application in modern devices. State-of-the-art approaches to design of compact BLCs are largely based on the use of high-permittivity substrates and multi-layer topologies. Alternative methods involve replacement of transmission-line...
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Multi-Fidelity Local Surrogate Model for Computationally Efficient Microwave Component Design Optimization
PublicationIn order to minimize the number of evaluations of high-fidelity (“fine”) model in the optimization process, to increase the optimization speed, and to improve optimal solution accuracy, a robust and computational-efficient multi-fidelity local surrogate-model optimization method is proposed. Based on the principle of response surface approximation, the proposed method exploits the multi-fidelity coarse models and polynomial interpolation...
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Novel Complementary Multiple Concentric Split Ring Resonator for Reliable Characterization of Dielectric Substrates with High Sensitivity
PublicationAccurate characterization of dielectric substrates with high sensitivity remains an important challenge in a variety of industrial applications. This paper proposes an innovative strategy to address this challenge by developing and optimizing a unique Complementary Multiple Concentric Split Ring Resonator (CMC-SRR). The major goal is to propose a sensor design with increased sensitivity and reliability for dielectric characterization....
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Gas sampling system for matrix of semiconductor gas sensors
PublicationSemiconductor gas sensors are popular commercial sensors applied in numerous gas detection systems. They are reliable, small, rugged and inexpensive. However, there are a few problem limiting the wider use of such sensors. Semiconductor gas sensor usually exhibits a low selectivity, low repeatability, drift of response, strong temperature and moisture influence on sensor properties. Sample flow rate is one of the parameters that...
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Taguchi sensors under temperature modulation
PublicationSemiconductor gas sensors are widely used in gas- analyzing applications for various gas species determination due to their low cost and possibility to detect number of different gases. However, one of the main problems with such sensors is their lack of selectivity. To overcome this issue different ap- proaches can be used. One of them is the operation with sensor temperature modulation combined with dedicated data process- ing...
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Temperature Sensors Based on Polymer Fiber Optic Interferometer
PublicationTemperature measurements are of great importance in many fields of human activities, including industry, technology, and science. For example, obtaining a certain temperature value or a sudden change in it can be the primary control marker of a chemical process. Fiber optic sensors have remarkable properties giving a broad range of applications. They enable continuous real-time temperature control in difficult-to-reach areas, in...
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Chapter 11 – Application of Chemical Sensors and Sensor Matrixes to Air Quality Evaluation
PublicationIndoor and outdoor air quality is one of the key factors influencing human health. However, air quality evaluation is not easy task. Air is a complex system, which is subjected to changes even within short period of time. Progress in analytical methods and analytical tools provides increasingly more reliable information on the condition and quality of indoor and outdoor air. This progress, however, generates an increase in the...
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sp2-rich dendrite-like carbon nanowalls as effective electrode for environmental monitoring of explosive nitroaromatic
PublicationNitroaromatic compounds are commonly used explosive materials that pose a risk to human health and ecosystems due to their acute toxicity and carcinogenicity. Nitroaromatics have numerous pathways into the environment via discarded munitions (e.g. into the Baltic Sea after World War II), after use in mining operations, and in industrial run-off from factories producing these compounds (which are produced across the world to date)....
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Innovations in Wastewater Treatment: Harnessing Mathematical Modeling and Computer Simulations with Cutting-Edge Technologies and Advanced Control Systems
PublicationThe wastewater treatment landscape in Central Europe, particularly in Poland, has undergone a profound transformation due to European Union (EU) integration. Fueled by EU funding and rapid technological advancements, wastewater treatment plants (WWTPs) have adopted cutting-edge control methods to adhere to EU Water Framework Directive mandates. WWTPs contend with complexities such as variable flow rates, temperature fluctuations,...
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Evaluation of the Commercial Electrochemical Gas Sensors for the Monitoring of CO in Ambient Air
PublicationAir pollution is a growing concern of civilized world, which has a significant impact on human health and the environment. Recent studies highlight that the exposure to polluted air can increase the incidence of diseases and deteriorate the quality of life. Hence, it is necessary to develop tools for real-time air quality monitoring. For air pollution monitoring a wide range of stationary gas and particulate analysers can be used....
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Real-time working gas recognition system based on the array of semiconductor gas sensors and portable computer Raspberry PI
PublicationThe gas-analyzing systems based on the array of partially selective gas sensors and pattern-recognition techniques are potentially fast and low-cost alternative for other devices, like gas analysers. They give the possibility of recognition the type and the concentration of measured volatile compounds in their working environment. In this work we present the implementation of gas recognition system, in which the signals from an...
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Low cost electrochemical sensor module for measurement of gas concentration
PublicationThis paper describes a low cost electrochemical sensor module for gas concentration measurement. A module is universal and can be used for many types of electrochemical gas sensors. Device is based on AVR ATmega8 microcontroller. As signal processing circuit a specialized integrated circuit LMP9l000 is used. The proposed equipment will be used as a component of electronic nose system employed for classifying and distinguishing...
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Sensors and System for Vehicle Navigation
PublicationIn recent years, vehicle navigation, in particular autonomous navigation, has been at the center of several major developments, both in civilian and defense applications. New technologies, such as multisensory data fusion, big data processing, or deep learning, are changing the quality of areas of applications, improving the sensors and systems used. Recently, the influence of artificial intelligence on sensor data processing and...
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Sensors and Sensor’s Fusion in Autonomous Vehicles
PublicationAutonomous vehicle navigation has been at the center of several major developments, both in civilian and defense applications. New technologies such as multisensory data fusion, big data processing, and deep learning are changing the quality of areas of applications, improving the sensors and systems used. New ideas such as 3D radar, 3D sonar, LiDAR, and others are based on autonomous vehicle revolutionary development. The Special...
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Metal-Organic Frameworks-Based Sensors for the Detection of Toxins in Food: A Critical Mini-Review on the Applications and Mechanisms
PublicationUsing scientific technologies to detect toxins in food is significant to prevent food safety problems and protect people’s health. Recently, the rise of sensors has made rapid, efficient, and safe detection of food toxins possible. One of the key factors impacting the sensor’s performance is the nanomaterials employed. Metal-organic frameworks (MOFs), with high specific surface area, tunable composition, porous structure, and flexible...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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Fluctuation enhanced gas sensing with WO3-based nanoparticle gas sensors modulated by UV light at selected wavelengths
PublicationThe sensitivity and selectivity of WO3-based gas sensors can be enhanced by UV-irradiation-induced modulation, especially if different wavelengths are employed. We used fluctuation-enhanced gas sensing, based on measurements of resistance fluctuations in the gas sensor, to study the effects of such modulation on the noise intensity for ambient atmospheres of synthetic air without and with additions of small amounts of ethanol,...
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Design of novel highly sensitive sensors for crack detection in metal surfaces: theoretical foundation and experimental validation
PublicationThe application of different types of microwave resonators for sensing cracks in metallic structures has been subject of many studies. While most studies have been focused on improving the sensitivity of planar crack sensors, the theoretical foundation of the topic has not been treated in much detail. The major objective of this study is to perform an exhaustive study of the principles and theoretical foundations for crack sensing...
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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...