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Search results for: gas recognition
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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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Gas mixtures recognition using an array of amperometric gas sensors with drifting or faulty sensors
PublicationIn this study, the possibility of using selected methods for diagnostics of performance of matrix composed with six amperometric electrochemical gas sensors is investigated. Measurements of sensor responses in selected concentrations of single toxic gases or gas mixtures were performed and were repeated over time to show sensor drift. Additionally, the studies on the sensors’ drift were performed. The drift has been recognized...
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An electronic nose for quantitative determination of gas concentrations
PublicationThe 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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Identification of volatile compounds based on the electrocatalytic gas sensor responses
PublicationMeasured 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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Features extraction from the electrocatalytic gas sensor responses
PublicationOne 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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Voice command recognition using hybrid genetic algorithm
PublicationAbstract: Speech recognition is a process of converting the acoustic signal into a set of words, whereas voice command recognition consists in the correct identification of voice commands, usually single words. Voice command recognition systems are widely used in the military, control systems, electronic devices, such as cellular phones, or by people with disabilities (e.g., for controlling a wheelchair or operating a computer...
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Pracujący w czasie rzeczywistym system detekcji gazów wykorzystujący przenośny komputer Raspberry PI oraz matrycę półprzewodnikowych czujników gazu
PublicationThe gas-analyzing systems based on the array of partially selective gas sensors and pattern-recognition techniques are potentially fast and lowcost 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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An electronic nose based on the semiconducting and electrochemical gas sensors
PublicationThe 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. Consequently, there is a significant need for an instrument that can be a substitution of the human sense of smell. Development of an electronic nose devices is an active area of research starting from pioneering research of Dodd and Persuad in the mid-1980s. Such systems...
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Determination of toxic gases based on the responses of a single electrocatalytic sensor and pattern recognition techniques
PublicationA response from an electrocatalytic gas sensor contains fingerprint information about the type of gas and its concentration. As a result, a single gas sensor can be used for the determination of different gases. However, information about the type of gas and its concentration is hidden in the unique shape of the current–voltage response and it is quite difficult to explore. One of the ways to get precise information about the measured...
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Extraction and evaluation of gas-flow-dependent features from dynamic measurements of gas sensors array
PublicationGas 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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A calibration model for gas sensor array in varying environmental conditions
PublicationAbstract: Gas-analyzing systems based on gas sensors, commonly referred to as electronic noses, are the systems which enable the recognition of volatile compounds in their working environment and provide the on-line results of analysis. The most commonly used type of sensors in such systems is semiconductor gas sensors. They are considered to be the most reliable in the long-term applications (more than 1 year), however,...
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A calibration model for gas sensor array in varying environmental conditions
PublicationAbstract: Gas-analyzing systems based on gas sensors, commonly referred to as electronic noses, are the systems which enable the recognition of volatile compounds in their working environment and provide the on-line results of analysis. The most commonly used type of sensors in such systems is semiconductor gas sensors. They are considered to be the most reliable in the long-term applications (more than 1 year), however,...
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Time window based features extraction from temperature modulated gas sensors for prediction of ammonia concentration
PublicationElectronic gas recognition systems, in literature commonly referred as electronic noses, enable the recognition of a type and a concentration of various volatile compounds. Typical electronic gas-analyzing device consists of four main elements, namely, gas delivery subsystem, an array of gas sensors, data acquisition and power supply circuits and data analysis software. The commercially available metal-oxide TGS sensors are widely...
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Techniques of acquiring additional features of the responses of individual gas sensors
PublicationGas sensors usually exhibit lack of selectivity, require fre quent calibration, exhibit drift of the response and a lot of factors, such as humidity or ambient temperature, influen ce their performance. Different approaches can be used to overcome this shortcomings. Building arrays of different sensors and usage of pattern recognition methods to analyze responses of elements...
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Application of gamma densitometry and statistical signal analysis to gas phase velocity measurements in pipeline hydrotransport
PublicationThe work presents selected methods of signal analysis used in the processing of data obtained from radiometric probes. The used data came from an exemplary study of a two-phase liquid-gas flow at the laboratory installation. In such rigs many possible transport types may be observed, i.e. slug, plug and bubble flow, and each of them gives different signal-to-noise ratio of recorded data. Therefore, available radiometric methods...
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Application of gamma densitometry and statistical signal analysis to gas phase velocity measurements in pipeline hydrotransport
PublicationThe work presents selected methods of signal analysis used in the processing of data obtained from radiometric probes. The used data came from an exemplary study of a two-phase liquid-gas flow at the laboratory installation. In such rigs many possible transport types may be observed, i.e. slug, plug and bubble flow, and each of them gives different signal-to-noise ratio of recorded data. Therefore, available radiometric methods...
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Application of fuzzy logic to determine the odour intensity of model gas mixtures using electronic nose
PublicationThe paper presents the possibility of application of fuzzy logic to determine the odour intensity of model, ternary gas mixtures (α-pinene, toluene and triethylamine) using electronic nose prototype. The results obtained using fuzzy logic algorithms were compared with the values obtained using multiple linear regression (MLR) model and sensory analysis. As the results of the studies, it was found the electronic nose prototype along...
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Zastosowanie metod eksploracji danych do analizy odpowiedzi czujników gazu
PublicationZagadnienia poruszane w niniejszej rozprawie dotyczą zastosowania metod eksploracji danych do analizy odpowiedzi czujników gazu, umożliwiających poprawną identyfikację składu mieszaniny gazowej w elektronicznych systemach rozpoznawania gazu. Elektroniczne systemy rozpoznawania gazu to urządzenia wykorzystujące czujniki gazu oraz odpowiednio dobrane metody analizy danych pomiarowych, zdolne do określenia składu mierzonej mieszaniny...
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Analysis of odour interactions in model gas mixtures using electronic nose and fuzzy logic
PublicationMeasurement and monitoring of air quality in terms of odour nuisance is an important problem. Although the source of these nuisances is different (e.g. wastewater treatment plants, municipal landfills), their common feature is that they are a complex mixture of odorants with different odour thresholds. An additional problem is occurrence of the odour interactions between mixture components. From a practical point of view, it would...
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Molecularly imprinted polymers for the detection of volatile biomarkers
PublicationIn the field of cancer detection, the development of affordable, quick, and user-friendly sensors capable of detecting various cancer biomarkers, including those for lung cancer (LC), holds utmost significance. Sensors are expected to play a crucial role in the early-stage diagnosis of various diseases. Among the range of options, sensors emerge as particularly appealing for the diagnosis of various diseases, owing to their cost-effectiveness,...
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Determination of long-chain aldehydes using a novel quartz crystal microbalance sensor based on a biomimetic peptide
PublicationThere is an increasingly popular trend aimed at improvement of fundamental metrological parameters of sensors via implementation of materials mimicking biological olfactory systems. This study presents investigation on usefulness of the peptide mimicking HarmOBP7 region as a receptor element of the piezoelectric sensor for selective analysis of long-chain aldehydes. Identification of odorant binding proteins creates new possibilities...
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“Shadow” vs. “Phase 3D” method within endoscopic examinations of marine engines
PublicationA visual investigation of surfaces creating internal, working spaces of marine combustion engines by means of specialized view-finders so called endoscopes is at present almost a basic method of technical diag-nostics. The surface structure of constructional material is visible during investigations like through the magnifying glass (usually with a precisely determined magnification), which makes possible a detection, recognition...
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Blood concentrations of a new psychoactive substance 4-chloromethcathinone (4-CMC) determined in 15 forensic cases
PublicationPurpose: The 4-chloromethcathinone (4-CMC) is a synthetic derivative of cathinone and belongs to new psychoactive substances. Neither data on the effects of 4-CMC on the human body, nor on nontoxic, toxic and lethal concentrations in biological materials have been published in the literature. This paper describes the results of an analysis of the blood concentrations of 4-CMC determined in 15 forensic cases related to nonfatal...
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Conditions for increasing the recognition of degradation in thermal-flow diagnostics, taking into account environmental legal aspects
PublicationThe ever-increasing demand for electricity and the need for conventional sources to cooperate with renewable ones generates the need to increase the efficiency and safety of the generation sources. Therefore, it is necessary to find a way to operate existing facilities more efficiently with full detection of emerging faults. These are the requirements of Polish, European and International law, which demands that energy facilities...
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Emotion Recognition from Physiological Channels Using Graph Neural Network
PublicationIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...
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Limitations of Emotion Recognition from Facial Expressions in e-Learning Context
PublicationThe paper concerns technology of automatic emotion recognition applied in e-learning environment. During a study of e-learning process the authors applied facial expressions observation via multiple video cameras. Preliminary analysis of the facial expressions using automatic emotion recognition tools revealed several unexpected results, including unavailability of recognition due to face coverage and significant inconsistency...
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Mining inconsistent emotion recognition results with the multidimensional model
PublicationThe paper deals with the challenge of inconsistency in multichannel emotion recognition. The focus of the paper is to explore factors that might influence the inconsistency. The paper reports an experiment that used multi-camera facial expression analysis with multiple recognition systems. The data were analyzed using a multidimensional approach and data mining techniques. The study allowed us to explore camera location, occlusions...
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Limitations of Emotion Recognition in Software User Experience Evaluation Context
PublicationThis paper concerns how an affective-behavioural- cognitive approach applies to the evaluation of the software user experience. Although it may seem that affect recognition solutions are accurate in determining the user experience, there are several challenges in practice. This paper aims to explore the limitations of the automatic affect recognition applied in the usability context as well as...
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Accelerometer signal pre-processing influence on human activity recognition
PublicationA study of data pre-processing influence on accelerometer-based human activity recognition algorithms is presented. The frequency band used to filter-out the accelerometer signals and the number of accelerometers involved were considered in terms of their influence on the recognition accuracy.
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Emotion Recognition for Affect Aware Video Games
PublicationIn this paper the idea of affect aware video games is presented. A brief review of automatic multimodal affect recognition of facial expressions and emotions is given. The first result of emotions recognition using depth data as well as prototype affect aware video game are presented
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Language Models in Speech Recognition
PublicationThis chapter describes language models used in speech recognition, It starts by indicating the role and the place of language models in speech recognition. Mesures used to compare language models follow. An overview of n-gram, syntactic, semantic, and neural models is given. It is accompanied by a list of popular software.
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Material for Automatic Phonetic Transcription of Speech Recorded in Various Conditions
PublicationAutomatic speech recognition (ASR) is under constant development, especially in cases when speech is casually produced or it is acquired in various environment conditions, or in the presence of background noise. Phonetic transcription is an important step in the process of full speech recognition and is discussed in the presented work as the main focus in this process. ASR is widely implemented in mobile devices technology, but...
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Interactions with recognized patients using smart glasses
PublicationRecently, different smart glasses solutions have been proposed on the market. The rapid development of this wearable technology has led to several research projects related to applications of smart glasses in healthcare. In this paper we propose a general architecture of the system enabling data integration for the recognized person. In the proposed system smart glasses integrates data obtained for the recognized patient from health...
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Vocalic Segments Classification Assisted by Mouth Motion Capture
PublicationVisual features convey important information for automatic speech recognition (ASR), especially in noisy environment. The purpose of this study is to evaluate to what extent visual data (i.e. lip reading) can enhance recognition accuracy in the multi-modal approach. For that purpose motion capture markers were placed on speakers' faces to obtain lips tracking data during speaking. Different parameterizations strategies were tested...
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Investigation of educational processes with affective computing methods
PublicationThis paper concerns the monitoring of educational processes with the use of new technologies for the recognition of human emotions. This paper summarizes results from three experiments, aimed at the validation of applying emotion recognition to e-learning. An analysis of the experiments’ executions provides an evaluation of the emotion elicitation methods used to monitor learners. The comparison of affect recognition algorithms...
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Adaptive system for recognition of sounds indicating threats to security of people and property employing parallel processing of audio data streams
PublicationA system for recognition of threatening acoustic events employing parallel processing on a supercomputing cluster is featured. The methods for detection, parameterization and classication of acoustic events are introduced. The recognition engine is based onthreshold-based detection with adaptive threshold and Support Vector Machine classifcation. Spectral, temporal and mel-frequency descriptors are used as signal features. The...
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Integration in Multichannel Emotion Recognition
PublicationThe paper concerns integration of results provided by automatic emotion recognition algorithms. It presents both the challenges and the approaches to solve them. Paper shows experimental results of integration. The paper might be of interest to researchers and practitioners who deal with automatic emotion recognition and use more than one solution or multichannel observation.
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Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition
PublicationThe article presents the problem of parameter value selection of the multiclass ``one against all'' approach of an AdaBoost algorithm in tasks of object recognition based on two-dimensional graphical images. AdaBoost classifier with Haar features is still used in mobile devices due to the processing speed in contrast to other methods like deep learning or SVM but its main drawback is the need to assembly the results of binary...
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Gesture-based computer control system
PublicationIn the paper a system for controlling computer applications by hand gestures is presented. First, selected methods used for gesture recognition are described. The system hardware and a way of controlling a computer by gestures are described. The architecture of the software along with hand gesture recognition methods and algorithms used are presented. Examples of basic and complex gestures recognized by the system are given.
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Automatic Classification of Polish Sign Language Words
PublicationIn the article we present the approach to automatic recognition of hand gestures using eGlove device. We present the research results of the system for detection and classification of static and dynamic words of Polish language. The results indicate the usage of eGlove allows to gain good recognition quality that additionally can be improved using additional data sources such as RGB cameras.
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Rough Sets Applied to Mood of Music Recognition
PublicationWith the growth of accessible digital music libraries over the past decade, there is a need for research into automated systems for searching, organizing and recommending music. Mood of music is considered as one of the most intuitive criteria for listeners, thus this work is focused on the emotional content of music and its automatic recognition. The research study presented in this work contains an attempt to music emotion recognition...
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Automatic sound recognition for security purposes
PublicationIn the paper an automatic sound recognition system is presented. It forms a part of a bigger security system developed in order to monitor outdoor places for non-typical audio-visual events. The analyzed audio signal is being recorded from a microphone mounted in an outdoor place thus a non stationary noise of a significant energy is present in it. In the paper an especially designed algorithm for outdoor noise reduction is presented,...
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Influence of accelerometer signal pre-processing and classification method on human activity recognition
PublicationA study of data pre-processing influence on accelerometer-based human activity recognition algorithms is presented. The frequency band used to filter-out the accelerometer signals and the number of accelerometers involved were considered in terms of their influence on the recognition accuracy. In the test four methods of classification were used: support vector machine, decision trees, neural network, k-nearest neighbor.
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Automatic music set organizatio based on mood of music / Automatyczna organizacja bazy muzycznej na podstawie nastroju muzyki
PublicationThis work is focused on an approach based on the emotional content of music and its automatic recognition. A vector of features describing emotional content of music was proposed. Additionally, a graphical model dedicated to the subjective evaluation of mood of music was created. A series of listening tests was carried out, and results were compared with automatic mood recognition employing SOM (Self Organizing Maps) and ANN (Artificial...
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Examining Influence of Distance to Microphone on Accuracy of Speech Recognition
PublicationThe problem of controlling a machine by the distant-talking speaker without a necessity of handheld or body-worn equipment usage is considered. A laboratory setup is introduced for examination of performance of the developed automatic speech recognition system fed by direct and by distant speech acquired by microphones placed at three different distances from the speaker (0.5 m to 1.5 m). For feature extraction from the voice signal...
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Introduction to the special issue on machine learning in acoustics
PublicationWhen we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing...
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Facial emotion recognition using depth data
PublicationIn this paper an original approach is presented for facial expression and emotion recognition based only on depth channel from Microsoft Kinect sensor. The emotional user model contains nine emotions including the neutral one. The proposed recognition algorithm uses local movements detection within the face area in order to recognize actual facial expression. This approach has been validated on Facial Expressions and Emotions Database...
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Employing a biofeedback method based on hemispheric synchronization in effective learning
PublicationIn this paper an approach to build a brain computer-based hemispheric synchronization system is presented. The concept utilizes the wireless EEG signal registration and acquisition as well as advanced pre-processing methods. The influence of various filtration techniques of EOG artifacts on brain state recognition is examined. The emphasis is put on brain state recognition using band pass filtration for separation of individual...
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Hand gesture recognition supported by fuzzy rules and Kalman filters
PublicationThe paper presents a system based on camera and multimediaprojector enabling a user to control computer applications by dynamic hand gestures. Gesture recognition methodology based on representing hand movement trajectory by motion vectors analysed using fuzzy rule-based inference is first given. For effective hand position tracking Kalman filters are employed. The system engineered is developed using J2SE and C++/OpenCV technology....
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Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublicationWith the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...