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Wyniki wyszukiwania dla: AIR QUALITY MONITORING, NITROGEN DIOXIDE, COST-EFFICIENT SENSORS, SENSOR CORRECTION, MACHINE LEARNING
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublikacjaAir 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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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublikacjaAir 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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On Memory-Based Precise Calibration of Cost-Efficient NO2 Sensor Using Artificial Intelligence and Global Response Correction
PublikacjaNitrogen 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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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublikacjaAir 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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Features extraction from the electrocatalytic gas sensor responses
PublikacjaOne of the types of gas sensors used for detection and identification of toxic-air pollutant is an electrocatalytic gas sensor. The electrocatalytic sensors are working in cyclic voltammetry mode, enable detection of various gases. Their response are in the form of I-V curves which contain information about the type and the concentration of measured volatile compound. However,...
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Electrocatalytic Gas Sensor with Reference Layer
PublikacjaThis paper presents studies of gas sensors prepared in ceramic technology with Nasicon as a solid electrolyte. Sensors work in the voltammetric mode thus based on the excitation of a sensor with a periodic potential signal while current response is recorded. The main aim is to investigate a Bi8Nb2O17 reference layer influence on sensor properties. Sensors I-V characteristics in different concentration of nitrogen dioxide have been...
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Efficiency of linear and non-linear classifiers for gas identification from electrocatalytic gas sensor
PublikacjaElectrocatalytic gas sensors belong to the family of electrochemical solid state sensors. Their responses are acquired in the form of I-V plots as a result of application of cyclic voltammetry technique. In order to obtain information about the type of measured gas the multivariate data analysis and pattern classification techniques can be employed. However, there is a lack of information in literature about application of such...
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Identification of volatile compounds based on the electrocatalytic gas sensor responses
PublikacjaMeasured response in case of electrocatalytic gas sensors is in form of a voltamperometric characteristic. Current-voltage (I-V) response shape depends on the gas type and its concentration. Such response contains significantly more information comparing with typical electrochemical sensors, but is quite difficult to analyze. When I-V curve contains current peaks, position of such peaks can be used...
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Electrocatalytic gas sensor with reference layer
PublikacjaIn recent years electrochemical gas sensors based on solid state electrolytes have been intensively developed. They are easy to obtain, use and relative durable. Nasicon is one of the most promising materials, which have been used in construction of gas sensors. Most of these devices work in potentiometric or amperometric mode. However, some works are dedicated to sensors working in electrocatalytic mode. Principle of operation...
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Extraction and evaluation of gas-flow-dependent features from dynamic measurements of gas sensors array
PublikacjaGas analyzers based on gas sensors are the devices which enable recognition of various kinds of volatile compounds. They have continuously been developed and investigated for over three decades, however there are still limitations which slow down the implementation of those devices in many applications. For example, the main drawbacks are the lack of selectivity, sensitivity...
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EVALUATION OF THE NO2CONCENTRATION PREDICTION POSSIBILITYBASED ON STATIC AND DYNAMIC RESPONSES OF TGS SENSORSAT CHANGING HUMIDITY LEVELS
PublikacjaThe commercially available metal-oxide TGS sensors are widely used in many applications due to thefact that they are inexpensive and considered to be reliable. However, they are partially selective and theirresponses are influenced by various factors,e.g. temperature or humidity level. Therefore, it is importanttodesign a proper analysis system of the sensor responses. In this paper, the results of examinations of eightcommercial...
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An NO2 sensor based on WO3 thin films for automotive applications in the microwave frequency range
PublikacjaA microwave system dedicated to the detection of nitrogen dioxide in the harsh environment of the Norway highways is proposed. An optimized transmission line type of sensor coated with a tungsten trioxide thin film that changes its electrical properties under NO2 gas exposure is developed. The sensors' response (S) is given in °/GHz and it is calculated based on wideband measurements. The advantage of wideband measurements in comparison...
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An electronic nose for quantitative determination of gas concentrations
PublikacjaThe practical application of human nose for fragrance recognition is severely limited by the fact that our sense of smell is subjective and gets tired easily. Consequen tly, there is considerable need for an instrument that can be a substitution of the human sense of smell. Electronic nose devices from the mid 1980s are used in growing number of applications. They comprise an array of several electrochemical gas sensors...
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The applicability of low-cost PM10 sensors for atmospheric air quality monitoring
PublikacjaDescribed 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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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublikacjaAtmospheric 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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Chapter 11 – Application of Chemical Sensors and Sensor Matrixes to Air Quality Evaluation
PublikacjaIndoor 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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Investigation of sensing mechanism of Nasicon electrocatalytic sensors in nitrogen dioxide and ammonia
PublikacjaIn this paper a sensing mechanism of Nasicon electrocatalytic sensor in nitrogen dioxide and ammonia is investigated. Both gases are environmentally hazardous and contain nitrogen atom in the molecule. However, it seems that their sensing mechanism in electrocatalytic sensor could be totally different. Namely, the maximum sensitivity for each gas was obtained at different temperatures. Also, different auxiliary layers are formed...
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SENSORS
Czasopisma -
Evaluation of the Commercial Electrochemical Gas Sensors for the Monitoring of CO in Ambient Air
PublikacjaAir 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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A Surrogate-Assisted Measurement Correction Method for Accurate and Low-Cost Monitoring of Particulate Matter Pollutants
PublikacjaAir pollution involves multiple health and economic challenges. Its accurate and low-cost monitoring is important for developing services dedicated to reduce the exposure of living beings to the pollution. Particulate matter (PM) measurement sensors belong to the key components that support operation of these systems. In this work, a modular, mobile Internet of Things sensor for PM measurements has been proposed. Due to a limited...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublikacjaDue 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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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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Current air quality analytics and monitoring: A review
PublikacjaThis review summarizes the different tools and concepts that are commonly applied in air quality monitoring. The monitoring of atmosphere is extremely important as the air quality is an important problem for large communities. Main requirements for analytical devices used for monitoring include a long period of autonomic operation and portability. These instruments, however, are often characterized by poor analytical performance....
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublikacjaDesigning 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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Electrocatalytic nitrogen dioxide sensor.
PublikacjaOpisano konstrukcję i właściwości elektrokatalitycznego czujnika gazów na bazie domieszkowanego samarem tlenku ceru. Pomiary przeprowadzono w mieszaninie syntetycznego powietrza i dwutlenku azotu. Kształt odpowiedzi prądowo - napięciowej zależy od stężenia NO2.
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Determination of Odor Air Quality Index (OAQII) Using Gas Sensor Matrix
PublikacjaThis article presents a new way to determine odor nuisance based on the proposed odor air quality index (OAQII), using an instrumental method. This indicator relates the most important odor features, such as intensity, hedonic tone and odor concentration. The research was conducted at the compost screening yard of the municipal treatment plant in Central Poland, on which a self-constructed gas sensor array was placed. It consisted...
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Optimised Robust Placement of Hard Quality Sensors for Robust Monitoring of Quality in Drinking Water Distribution Systems
PublikacjaA problem of optimised robust placement of the hard quality sensors in Drinking Water Distribution Systems under several water demand scenarios for robust quality monitoring is formulated. Numerical algorithms to solve the problem are derived. The optimality is meant as achieving at the same time a desired trade off between the sensor capital and maintenance costs and resulting robust estimation accuracy of the monitoring algorithm...
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Long term measurements of PM1, PM2.5, PM10 and NO2 in open-air at Gdansk (Poland) area using low-cost sensors together with the reference results
Dane BadawczeThe measurements results of open-air measurements made using the following low-cost sensors: particulate matter (PM) sensor SPS30 from Sensirion, NO2 electrochemical sensor SGX-7NO2 from SGX Sensortech, NO2 electrochemical sensor 7E4-NO2 from SemaTech, compact MOS air quality sensor MiCS 2714 from SGX Sensortech, BME280 (Bosch) environmental sensor...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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Machine learning applied to acoustic-based road traffic monitoring
PublikacjaThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
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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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Measurement Automation Monitoring
Czasopisma -
Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries
PublikacjaOptical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated...
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...
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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublikacjaMachine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...
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Application of Multiplicative Drift Correction and Component Correction methods on simulated gas sensor array responses
PublikacjaSensor response drift is one of the most challenging problems in gas-analyzing systems. Such systems, commonly called electronic noses, are expected to be reliable and reproducible in the long term. Due to the drift phenomena, electronic noses usability is limited to the relatively short period of time, and frequent recalibrations of device are required. Because it is very hard to fabricate sensors without drift, this phenomenon...
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An optimised placement of the hard quality sensors for a robust monitoring of the chlorine concentration in drinking water distribution systems
PublikacjaThe problem of an optimised placement of the hard quality sensors in drinking water distribution systemsunder several water demand scenarios for a robust monitoring of the chlorine concentration is formulatedin this paper. The optimality is understood as achieving a desired trade off between the sensors and theirmaintenance costs and the accuracy of estimation of the chlorine concentration. The contribution of thiswork is a comprehensive...
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Air Pollution: Monitoring
PublikacjaThe entry presents an overview of the issues in the field of air pollution monitoring. At the beginning, the general objectives of air monitoring, ambient air quality standards for so-called criteria pollutants, and their sources are discussed. In the next part, both analytical methods and instruments for monitoring of ambient air and stack gases are briefly presented. Additionally, other approaches used in air pollution monitoring,...
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TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublikacjaTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
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Application of a Gas Sensor Array to Effectiveness Monitoring of Air Contaminated with Toluene Vapors Absorption Process
PublikacjaThis article demonstrates the application of a gas sensor array to monitor the effectiveness of the absorption process of air stream purification from odorous compounds (toluene vapors). A self-constructed matrix consisting of five commercially available gas sensors was used. Multiple linear regression (MLR) was selected as the statistical technique used to calibrate the matrice. Gas chromatography coupled with a flame ionization...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublikacjaThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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Accurate Lightweight Calibration Methods for Mobile Low-Cost Particulate Matter Sensors
PublikacjaMonitoring 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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Nitrogen dioxide gas-sensing detection with GO modified CuO thin films
PublikacjaGas sensors have been continuously developed over the last few decades for several applications including air quality monitoring, automotive industry and recently for medical use. Gas sensors are usually based on metal oxides (MOXs), such as SnO2, TiO2, ZnO, WO3, CuO. Recently, new materials such as graphene oxide and heterostructures of graphene oxide and metal oxides are utilized for gassensing applications.
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Low cost electrochemical sensor module for measurement of gas concentration
PublikacjaThis 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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Sensitivity to nitrogen dioxide of electrocatalytic gas sensor based on NASICON
PublikacjaW pracy przedstawiono wyniki badań czujnika elektrokatalitycznego na bazie NASICONu.
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublikacjaThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublikacjaThe acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...
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Investigation of Sensing Mechanism of Nasicon Electrocatalytic Sensors in Nitrogen Dioxide and Ammonia
PublikacjaW pracy przedstawiono wyniki badań mechanizmu działania czujnika elektrokatalitycznego pracującego w ditlenku azotu i amoniaku.
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Development of Gas Sensor Array for Methane Reforming Process Monitoring
PublikacjaThe article presents a new method of monitoring and assessing the course of the dry methane reforming process with the use of a gas sensor array. Nine commercially available TGS chemical gas sensors were used to construct the array (seven metal oxide sensors and two electrochemical ones). Principal Component Regression (PCR) was used as a calibration method. The developed PCR models were used to determine the quantitative parameters...
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Machine Learning and Electronic Noses for Medical Diagnostics
PublikacjaThe need for noninvasive, easy-to-use, and inexpensive methods for point-of-care diagnostics of a variety of ailments motivates researchers to develop methods for analyzing complex biological samples, in particular human breath, that could aid in screening and early diagnosis. There are hopes that electronic noses, that is, devices based on arrays of semiselective or nonselective chemical sensors, can fill this niche. Electronic...