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Search results for: AIR QUALITY MONITORING, NITROGEN DIOXIDE, COST-EFFICIENT SENSORS, SENSOR CORRECTION, MACHINE LEARNING
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Potentiometric sensor with lipid-polymer membranes for quality assessment of French red wines
PublicationThe quality of wines resulting from vineyard management is important for consumers due to the taste and price of wines. In this work, the quality of red wines of three vintages has been investigated by potentiometric sensors with six all-solid-state electrodes. Two series of experiments were carried out. The first involved a qualitative analysis of wine of different vintages from freshly opened bottles. The second consisted of...
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Evaluation of the Electronic Nose Used for Monitoring Environmental Pollution
PublicationAir pollution is a one of the major 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. Electronic-nose systems based on sensors are an interesting and promising technology in...
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A measurement method for lossy capacitive relative humidity sensors based on a direct sensor-to-microcontroller interface circuit
PublicationA new time-domain measurement method for determining the capacitance and resistance values of lossy relative humidity capacitive sensors is presented. The method is based on a direct sensor-to-microcontroller interface for microcontrollers with internal analog comparators and timers. The interface circuit consists only of four reference resistors (two reference resistors if a microcontroller includes a voltage reference source),...
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Portable Electronic Nose Based on Electrochemical Sensors for Food Quality Assessment
PublicationThe steady increase in global consumption puts a strain on agriculture and might lead to a decrease in food quality. Currently used techniques of food analysis are often labour-intensive and time-consuming and require extensive sample preparation. For that reason, there is a demand for novel methods that could be used for rapid food quality assessment. A technique based on the use of an array of chemical sensors for holistic analysis...
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MONTE CARLO MODELING OF OPTICAL SENSOR FOR POST-OPERATIVE FREE FLAP MONITORING
PublicationAfter a preliminary study of the currently employed methods in vitality monitoring of the tissue flaps (TRAM, DIEP, SIEA), a usefulness of optical techniques is discussed. It seems that one of the most promising in monitoring tissue flaps blood flow is a near infrared spectrometry (NIRS). However, a special design of a measurement sensor has to be developed. First, basing on the literature study an optical “window” is characterized....
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Assessing the attractiveness of human face based on machine learning
PublicationThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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Robust Monitoring of Water Quality in Drinking Water Distribution System
PublicationThe paper develops a novel open loop set bounded observer for robust estimation of water quality in DWDS based on the advanced nonlinear quality dynamics model including disinfections by-products (DBPs). The observer utilises a cooperativeness of the quality dynamics model and is computationally efficient, hence applicable to on-line quality monitoring. The simulation results illustrate its good and sustainable performance.
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Poland: Quality Monitoring of Therapeutic Processes in a Small Treatment Center for Children
PublicationThis article presents the case of the first ISO 9001:2000-certified small healthcare organization (the Center for Therapy and Rehabilitation) providing therapeutic and rehabilitation services for disabled children in Northern Poland. Elements of the process-oriented healthcare quality system implementation, initial benefits, and the organization's quality system structure and process descriptions are described. Particular attention...
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MACHINE LEARNING
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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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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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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublicationThis study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...
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Influence of terpenes on indoor air quality
PublicationThe aim of this study was to investigate air quality in hairdresser salons, focusing on terpenes determination. Terpenes are known reactive volatile organic compounds that contribute to secondary organic aerosol formation. Those compounds are frequently found in cosmetic products as fragrance agents. Hairdresser salons are special kind of environment, where secondary organic aerosol concentration may be elevated. One hairdresser...
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An application of acoustic sensors for the monitoring of road traffic
PublicationAssessment of road traffic parameters for the developed intelligent speed limit setting decision system constitutes the subject addressed in the paper. Current traffic conditions providing vital data source for the calculation of the locally fitted speed limits are assessed employing an economical embedded platform placed at the roadside. The use of the developed platform employing a low-powered processing unit with a set of microphones,...
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Analytical Techniques Used in Monitoring of Atmospheric Air Pollutants
PublicationThe air pollution monitoring is one of the most pressing environmental problems today. The paper describes common air pollutants, their interaction and impact on the environment, and classifies the techniques and methods applied in air studies. Furthermore, the review characterizes the selected collection and sampling techniques used for gas sample analysis. Finally, the schematic diagrams of typical designs of systems applied...
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Electrical responses of nanostructured ZrS3 as field-effect transistor for nitrogen dioxide, ethanol, and acetone detection enhanced by visible light
Open Research DataSmall-area layers of nanostructured ZrS3 were fabricated and measured in the field-effect transistor configuration. Irradiation with visible light enabled generating photocurrent and increasing the sensitivity to selected ambient gases: nitrogen dioxide, ethanol, and acetone. The data set consists of electrical responses (current vs. voltage characteristics...
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Data on bicycle traffic in Gdansk paired with weather and air quality data
Open Research DataThe file contains data on bicycle traffic registered by counting stations loacted in Gdańsk in the years 2013-2020. The data are paired with weather and air quality data from Gdansk collected for the same period. The data is described below:
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Sztuczny sensor smaku a zmysł smaku
PublicationOmówiono klasy smaku i działanie zmysłu smaku, który odgrywa ogromną rolę w ocenie jakości żywności metodami organoleptycznymi. Metody te nie są w pełni obiektywne, stąd poszukuje się sztucznego sensora smaku. Przedstawiono szereg rozwiązań prowadzących do opracowania sensora smaku na większą skalę. Omówiono wybrane potencjometryczne i woltamperometryczne sensory smaku, a także ich handlowe modele.
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Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublicationThe continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...
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Indoor air quality in public utility environments-a review
PublicationIndoor air quality has been the object of interest for scientists and specialists from the fields of science such as chemistry, medicine and ventilation system design. This results from a considerable number of potential factors, which may influence the quality of the broadly understood indoor air in a negative way. Poor quality of indoor air in various types of public utility buildings may significantly affect an increase in the...
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Evaluation of Ambient Air Odour Quality in Vicinity of Municipal Landfill Using Electronic Nose Technique
PublicationThe paper presents the results of investigation on ambient air quality evaluation with respect to concentration of odorants in a vicinity of municipal landfill. The investigation was carried out with a prototype of electronic nose and a team of panelists utilizing the Nasal Ranger field olfactometers. The prototype was equipped with a set of six semiconductor sensors by FIGARO Co. and one PID-type sensor. Performed measurements...
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Modeling lignin extraction with ionic liquids using machine learning approach
PublicationLignin, next to cellulose, is the second most common natural biopolymer on Earth, containing a third of the organic carbon in the biosphere. For many years, lignin was perceived as waste when obtaining cellulose and hemicellulose and used as a biofuel for the production of bioenergy. However, recently, lignin has been considered a renewable raw material for the production of chemicals and materials to replace petrochemical resources....
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Model-Based Adaptive Machine Learning Approach in Concrete Mix Design
PublicationConcrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete...
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Rengel Cane Sia Doctoral Candidate
PeopleI’m Rengel, born and raised in the Philippines. As an undergraduate I did kinetic modeling on Copper-catalyzed atom transfer radical addition (ATRA). Then I was inspired to do both theoretical and experimental studies, which led me to propose my master’s thesis on Synthesis, Computational, Electrochemical, and Photoconductivity Studies on Naphthalene and its derivatives. This led to a master’s degree in Chemistry in the Mindanao...
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Multimedia industrial and medical applications supported by machine learning
PublicationThis article outlines a keynote paper presented at the Intelligent DecisionTechnologies conference providing a part of the KES Multi-theme Conference “Smart Digital Futures” organized in Rome on June 14–16, 2023. It briefly discusses projects related to traffic control using developed intelligent traffic signs and diagnosing the health of wind turbine mechanisms and multimodal biometric authentication for banking branches to provide...
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UV-Light-Induced Fluctuation Enhanced Sensing by WO3-Based Gas Sensors
PublicationWO3-based gas sensors were investigated under UV-light irradiation and at different working temperatures with the object of achieving superior sensitivity and selectivity. Resistance fluctuations in the WO3 layer were studied together with dc resistance measurements. The data were taken in synthetic air, ethanol, nitrogen dioxide, and mixtures of these gases. We conclude that UV irradiation can easily be applied to enhance the...
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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
PublicationBiochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts,...
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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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A measurement method for capacitive sensors based on a versatile direct sensor-to-microcontroller interface circuit
PublicationIn the paper, there is presented a new time-domain measurement method for determining the capacitance values of capacitive sensors, dedicated, among others, to capacitive relative humidity sensors. The method is based on a versatile direct sensor-to-microcontroller interface for microcontrollers with internal analog comparators (ACs) and with precision voltage reference sources, e.g. digital-to-analog converters (DACs). The reference...
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Decisional DNA (DDNA) Based Machine Monitoring and Total Productive Maintenance in Industry 4.0 Framework
PublicationThe entire manufacturing spectrum is transforming with the advent of Industry 4.0. The features of Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA) were utilized for developing Virtual Engineering Objects (VEO), Virtual Engineering Process (VEP) and Virtual Engineering Factory (VEF), which in turn facilitate the creation of smart factories. In this study, DDNA based Machine Monitoring for Total Maintenance...
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Optical method supported by machine learning for dynamics of C‐reactive protein concentrations changes detection in biological matrix samples
PublicationIn this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern,...
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Ireneusz Czarnowski Prof.
PeopleIRENEUSZ CZARNOWSKI is a graduate of the Faculty of Electrical Engineering at Gdynia Maritime University. He gained a doctoral degree in the field of computer science at Poznan University of Technology and a postdoctoral degree in the field of computer science at Wroclaw University of Science and Technology. Since 1998 is associated with Gdynia Maritime University, currently is a professor of computer science in the Department...
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Journal of Sensors and Sensor Systems
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Data on bicycle traffic in Lodz (Poland) paired with weather and air quality data
Open Research DataThe file contains data on bicycle traffic registered by counting stations loacted in Lodz in the years 2016-2019. The data are paired with weather and air quality data from Lodz collected for the same period. The data is described below:
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The Use of Sensory Analysis Techniques to Assess the Quality of Indoor Air
PublicationThe quality of indoor air is one of the significant elements that influences people's well-being and health inside buildings. Emissions of pollutants, which may cause odor nuisance, are the main reason for people's complaints regarding the quality of indoor air. As a result, it is necessary to perform tests aimed at identifying the sources of odors inside buildings. The article contains basic information on the characteristics...
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Time-domain measurement methods for R, L and C sensors based on aversatile direct sensor-to-microcontroller interface circuit
PublicationtIn the paper new time-domain measurement methods for determining values of resistive (R), inductive(L) and capacitive (C) sensors based on a versatile direct sensor-to-microcontroller interface for microcon-trollers with internal analog-to-digital converters (ADCs) and analog comparators (ACs) are presented.The interface circuit consists of a reference resistor Rrworking as a voltage divider, a given R, L or C sensorand a microcontroller...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublicationA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Multi-sensor monitoring of the corrosion rate and the assessment of the efficiency of a corrosion inhibitor in utility water installations
PublicationThis paper presents an implementation of the monitoring of the corrosion rate and the assessment of the efficiency of a corrosion inhibitor in a utility water installation using an automated corrosion monitoring system. Due to the fact that the corrosion inhibitor was added to water intended for human consumption, it was necessary to build a multi-sensor monitoring system. In order to implement corrosion monitoring using a linear...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Urban Vegetation in Air Quality Management: A Review and Policy Framework
PublicationRecent episodes of high air pollution concentration levels in many Polish cities indicate the urgent need for policy change and for the integration of various aspects of urban development into a common platform for local air quality management. In this article, the focus was placed on the prospects of improving urban air quality through proper design and protection of vegetation systems within local spatial planning strategies....
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Anna Zielińska-Jurek prof. dr hab. inż.
People2018 DSc in technical sciences in the field of chemical technology Chemical Faculty, Gdansk University of Technology, Title: “Functionalized titanium(IV) oxide as a photocatalyst for environmental purification” 2011 Ph. D. in technical sciences in the field of chemical technology Chemical Faculty, Gdansk University of Technology, Title of the dissertation:...
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Concrete mix design using machine learning
PublicationDesigning a concrete mix is a process of synthesizing many components, it is not a simple process and requires extensive technical knowledge. The design process itself focuses on obtaining the required strength of concrete. Very often designing a concrete mix takes into account the need to maintain the proper water-demand and frost-resistance features. The parameters that influence the concrete class most significantly are the...
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Selectivity of amperometric sulfur dioxide sensor.
PublicationW pracy przedstawiono wartości współczynników selektywności amperometrycznego czujnika ditlenku siarki względem siarkowodoru. Obliczenia wykonane zostały w oparciu o krzywe kalibracyjne wyznaczone dla zaprezentowanego wcześniej przez nas amperometrycznego czujnika ditlenku siarki. Analiza krzywych kalibracyjnych pod względem czułości oznaczenia oraz analiza wartości amperometrycznych współczynników selektywności odgrywa dużą pomocniczą...
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Selectivity of amperometric gas sensors in multicomponent gas mixtures
PublicationIn recent years smog and poor air quality became a growing environmental problem. There is a need to continuously monitor the quality of air. The lack of selectivity is one of the most important problems limiting the use of gas sensors for this purpose. In this study, a selectivity of the six amperometric gas sensors is being investigated. Calibration of sensors has been performed in order to find a correlation between concentration...
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Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
PublicationIn recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for...
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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublicationTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
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Explainable machine learning for diffraction patterns
PublicationSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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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...