Relevant bibliographies by topics / Supervision signal

Academic literature on the topic 'Supervision signal'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Supervision signal"

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Li, Teng, Huan Chang, and Jun Wu. "Nonnegative Signal Decomposition with Supervision." Mathematical Problems in Engineering 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/620537.

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This paper presents a novel algorithm to numerically decompose mixed signals in a collaborative way, given supervision of the labels that each signal contains. The decomposition is formulated as an optimization problem incorporating nonnegative constraint. A nonnegative data factorization solution is presented to yield the decomposed results. It is shown that the optimization is efficient and decreases the objective function monotonically. Such a decomposition algorithm can be applied on multilabel training samples for pattern classification. The real-data experimental results show that the proposed algorithm can significantly facilitate the multilabel image classification performance with weak supervision.
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Gao, Hongliang, Xiaoling Li, Chao Gao, and Jie Wu. "Neural Network Supervision Control Strategy for Inverted Pendulum Tracking Control." Discrete Dynamics in Nature and Society 2021 (March 23, 2021): 1–14. http://dx.doi.org/10.1155/2021/5536573.

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This paper presents several control methods and realizes the stable tracking for the inverted pendulum system. Based on the advantages of RBF and traditional PID, a novel PID controller based on the RBF neural network supervision control method (PID-RBF) is proposed. This method realizes the adaptive adjustment of the stable tracking signal of the system. Furthermore, an improved PID controller based on RBF neural network supervision control strategy (IPID-RBF) is presented. This control strategy adopts the supervision control method of feed-forward and feedback. The response speed of the system is further improved, and the overshoot of the tracking signal is further reduced. The tracking control simulation of the inverted pendulum system under three different signals is given to illustrate the effectiveness of the proposed method.
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Kim, Byung-Gyu, and Dong-San Jun. "Artificial Intelligence for Multimedia Signal Processing." Applied Sciences 12, no. 15 (July 22, 2022): 7358. http://dx.doi.org/10.3390/app12157358.

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Weispfenning, Thomas. "Model and Signal Based Supervision of Components of Cars." IFAC Proceedings Volumes 30, no. 8 (June 1997): 479–84. http://dx.doi.org/10.1016/s1474-6670(17)43867-5.

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Tumanyan, Narek T. "Deep Learning Approaches for Voice Emotion Recognition Using Sentiment-Arousal Space." Mathematical Problems of Computer Science 56 (December 14, 2021): 35–47. http://dx.doi.org/10.51408/1963-0077.

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In this paper, we present deep learning-based approaches for the task of emotion recognition in voice recordings. A key component of the methods is the representation of emotion categories in a sentiment-arousal space and the usage of this space representation in the supervision signal. Our methods use wavelet and cepstral features as efficient data representations of audio signals. Convolutional Neural Network (CNN) and Long Short Term Memory Network (LSTM) architectures were used in recognition tasks, depending on whether the audio representation was treated as a spatial signal or as a temporal signal. Various recognition approaches were used, and the results were analyzed.
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Han, Haopeng, Eva Oberacker, Andre Kuehne, Shuailin Wang, Thomas Wilhelm Eigentler, Eckhard Grass, and Thoralf Niendorf. "Multi-Channel RF Supervision Module for Thermal Magnetic Resonance Based Cancer Therapy." Cancers 13, no. 5 (February 28, 2021): 1001. http://dx.doi.org/10.3390/cancers13051001.

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Glioblastoma multiforme (GBM) is the most lethal and common brain tumor. Combining hyperthermia with chemotherapy and/or radiotherapy improves the survival of GBM patients. Thermal magnetic resonance (ThermalMR) is a hyperthermia variant that exploits radio frequency (RF)-induced heating to examine the role of temperature in biological systems and disease. The RF signals’ power and phase need to be supervised to manage the formation of the energy focal point, accurate thermal dose control, and safety. Patient position during treatment also needs to be monitored to ensure the efficacy of the treatment and avoid damages to healthy tissue. This work reports on a multi-channel RF signal supervision module that is capable of monitoring and regulating RF signals and detecting patient motion. System characterization was performed for a broad range of frequencies. Monte-Carlo simulations were performed to examine the impact of power and phase errors on hyperthermia performance. The supervision module’s utility was demonstrated in characterizing RF power amplifiers and being a key part of a feedback control loop regulating RF signals in heating experiments. Electromagnetic field simulations were conducted to calculate the impact of patient displacement during treatment. The supervision module was experimentally tested for detecting patient motion to a submillimeter level. To conclude, this work presents a cost-effective RF supervision module that is a key component for a hyperthermia hardware system and forms a technological basis for future ThermalMR applications.
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Pedrycz, Witold, and George Vukovich. "Fuzzy clustering with supervision." Pattern Recognition 37, no. 7 (July 2004): 1339–49. http://dx.doi.org/10.1016/j.patcog.2003.11.005.

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Rasztovits-Wiech, M., K. Studer, and W. R. Leeb. "Bit error probability estimation algorithm for signal supervision in all-optical networks." Electronics Letters 35, no. 20 (1999): 1754. http://dx.doi.org/10.1049/el:19991176.

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Minarčík, Peter, Hynek Procházka, and Martin Gulan. "Advanced Supervision of Smart Buildings Using a Novel Open-Source Control Platform." Sensors 21, no. 1 (December 29, 2020): 160. http://dx.doi.org/10.3390/s21010160.

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Gathering data and monitoring performance are at the heart of energy efficiency and comfort securing strategies in smart buildings. Therefore, it is crucial to present the obtained data to the user or administrator of such a building in an appropriate form. Moreover, evaluating the data in real time not only helps to maintain comfort, but also allows for a timely response from the user or operator to a possible fault. Continuous online monitoring and analysis of process behaviour, which is referred to as advanced supervision, is addressed in this paper by developing a procedure that will form an artificial operator autonomously supervising process. After introducing several techniques that are used for signal analysis, we propose an approach to advanced supervision of processes in smart buildings or other industrial control systems. The developed procedure is implemented on a control system platform that is particularly suitable for this purpose. Moreover, this platform includes a framework that provides support for the implementation of advanced control techniques and it is based on open-source tools, which is rarely seen in industrial applications. The developed advanced supervision procedure has been tested in simulation as well as in a practical case study using a real two-storey family house.
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Wang, Tiantian, Junjie Liu, Chuan Wan, and Zhi Wang. "Remote supervision strategy based on in-use vehicle OBD data flow." E3S Web of Conferences 268 (2021): 01007. http://dx.doi.org/10.1051/e3sconf/202126801007.

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Test results from many researchers show that NOx emissions from parts of on-road heavy-duty diesels are higher than which been registered. Therefore, CN_VI emission regulations clearly proposes that the heavy-duty diesels should be supervised by a T-BOX which can transmit CAN message from vehicle OBD interface to the remote monitoring platform. Recognition of cheating behaver and calculation method of NOx emission were developed and verified by platform data from on-line vehicle. The modules in the platform can effectively monitor urea consumption rationality, injection system working state, exhaust temperature sensor signal reasonability, NOx sensor signal reasonability and NOx emission level, which can reduce the cost of supervision and governance, improve the effectiveness of regulation and provide basic data for policy making.
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Dissertations / Theses on the topic "Supervision signal"

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Larsson, Emil. "Diagnosis and Supervision of Industrial Gas Turbines." Licentiate thesis, Linköpings universitet, Fordonssystem, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-75985.

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Monitoring of industrial gas turbines is of vital importance, since it gives valuable information for the customer about maintenance, performance, and process health. The performance of an industrial gas turbine degrades gradually due to factors such as environment air pollution, fuel content, and ageing to mention some of the degradation factors. The compressor in the gas turbine is especially vulnerable against contaminants in the air since these particles are stuck at the rotor and stator surface. The loss in compressor performance, due to fouling, can partially be restored by an on-line/off-line compressor wash. If the actual health state of the gas turbine is known, it is possible to efficiently plan the service and maintenance and thereby reduce the environmental impact and the fuel cost for the customer. A thermodynamic gas turbine modeling package, called GTLib, is developed in the equation-based object-oriented modeling language Modelica. Using the GTLib package, a gas turbine model can be constructed. The gas turbine model can be used for performance calculation and as a base when diagnosis tests are generated. These tests can be used in a diagnosis and supervision system to detect compressor fouling and abrupt sensor faults. One of the benefits with using GTLib is the ability to model a lean stoichiometric combustion at different air/fuel ratio. Using the air/fuel ratio concept, an arbitrary number of gas species in the in-coming air can be considered. The number of equations is reduced if the air/fuel ratio concept is considered instead of modeling each gas species separately. The difference in the number of equations is significant if many gas species are considered. When the gas turbine components deteriorate, a mismatch between the nominal performance model and the measurements increase. To handle this, the gas turbine model is augmented with a number of estimation parameters. These estimation parameters are used to detect slow deterioration in the gas turbine components and are estimated with a Constant Gain Extended Kalman Filter (CGEKF). The state estimator is chosen using structural methods before an index reduction of the model is performed. Experimental data is investigated and it is shown that the performance degradation due to compressor fouling can be estimated. After the compressor is washed, the performance of the compressor is partially restored. An abrupt sensor fault of 1% of the nominal value is introduced in the discharge temperature of the compressor. The sensor fault can be detected using the CUSUM algorithm for change detection. Finally, the overall thesis contribution is the calculation chain from a simulation model used for performance calculation to a number of test quantities used in a diagnosis and supervision system. Since the considered gas turbine model is a large non-linear DAE model that has unobservable state variables, the test construction procedure is automatically performed with developed parsers.
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Tayq, Zakaria. "Intégration et supervision des liens Fronthaul dans les réseaux 5G." Thesis, Limoges, 2017. http://www.theses.fr/2017LIMO0092/document.

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Le Cloud RAN a été préconisé pour la 5G. Cependant, sa mise en place rencontre des difficultés notamment sur l'intégration du fronthaul, ce dernier généralement basé sur l’interface CPRI représente le segment situé entre la Digital Unit et la Radio Unit. Vu les contraintes de débit, de latence et de gigue sur cette interface, le multiplexage en longueur est la solution adéquate pour son transport. En revanche, les technologies radio recommandées pour la 5G augmenteront considérablement les débits CPRI, ce qui rend l’utilisation du WDM bas coût très difficile. Cette thèse traite quatre sujets principaux : L'introduction d'un canal de contrôle dans le CPRI permettrait la supervision de l'infrastructure WDM et l'accordabilité en longueurs d'onde des transceivers. L’impact de l’intégration de ce canal de contrôle dans le fronthaul est étudié dans le chapitre II. La radio analogique sur fibre peut améliorer de manière significative l'efficacité spectrale du fronthaul, permettant potentiellement le transport des interfaces 5G. Une étude approfondie sur le gain réel apporté par cette solution est rapportée dans le chapitre III. La compression du CPRI basée sur la quantification uniforme et non uniforme est également une solution pour améliorer l'efficacité spectrale du CPRI. Le chapitre IV démontre expérimentalement les taux de compression réalisables. Enfin, les nouveaux splits fonctionnels sont considérés comme une solution prometteuse pour la 5G. Deux nouvelles interfaces ont été identifiées pour les splits couche haute et couche basse. Une étude théorique et expérimentale de ces nouvelles interfaces est présentée dans le chapitre V
Cloud Radio Access Network (RAN) was identified as a key enabler for 5G. Its deployment is however meeting multiple challenges notably in the fronthaul integration, the latter being the segment located between the Digital Unit and the Radio Unit generally based on CPRI. Giving its bit-rate, latency and jitter constrains, Wavelength Division Multiplexing (WDM) is the most adequate solution for its transport. However, the radio technologies recommended for 5G will drastically increase the CPRI bit-rate making its transport very challenging with low-cost WDM. This thesis deals with four main topics : The introduction of a control channel in the CPRI enables offering the WDM infrastructure monitoring and the wavelength tunability in the transceivers. The study of this control channel integration in the fronthaul link is reported in the second chapter as well as an investigation on the wireless transmission of CPRI. The use of Analog Radio over Fiber (A-RoF) can significantly improve the fronthaul spectral efficiency compared to CPRI-based fronthaul enabling, potentially, the transport of 5G interfaces. A thorough investigation on the actual gain brought by this solution is stated in the third chapter. CPRI compression based on uniform and non-uniform quantization is also a solution to enhance the CPRI spectral efficiency. The fourth chapter describes this solution and experimentally shows the achievable compression rates. Finally, establishing a new functional split in the radio equipment was considered as a promising solution for 5G. Two new interfaces have been identified for high and low layer functional splits. A theoretical and experimental study of these new interfaces is reported in the fifth chapter
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Wacquet, Guillaume. "Classification spectrale semi-supervisée : Application à la supervision de l'écosystème marin." Thesis, Littoral, 2011. http://www.theses.fr/2011DUNK0389/document.

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Dans les systèmes d'aide à la décision, sont généralement à disposition des données numériques abondantes et éventuellement certaines connaissances contextuelles qualitatives, disponibles a priori ou fournies a posteriori par retour d'expérience. Les performances des approches de classification, en particulier spectrale, dépendent de l'intégration de ces connaissances dans leur conception. Les algorithmes de classification spectrale permettent de traiter la classification sous l'angle de coupes de graphe. Ils classent les données dans l'espace des vecteurs propres de la matrice Laplacienne du graphe. Cet espace est censé mieux révéler la présence de groupements naturels linéairement séparables. Dans ce travail, nous nous intéressons aux algorithmes intégrant des connaissances type contraintes de comparaison. L'espace spectral doit, dans ce cas, révéler la structuration en classes tout en respectant, autant que possible, les contraintes de comparaison. Nous présentons un état de l'art des approches spectrales semi-supervisées contraintes. Nous proposons un nouvel algorithme qui permet de générer un sous-espace de projection par optimisation d'un critère de multi-coupes normalisé avec ajustement des coefficients de pénalité dus aux contraintes. Les performances de l'algorithme sont mises en évidence sur différentes bases de données par comparaison à d'autres algorithmes de la littérature. Dans le cadre de la surveillance de l'écosystème marin, nous avons développé un système de classification automatique de cellules phytoplanctoniques, analysées par cytométrie en flux. Pour cela, nous avons proposé de mesurer les similarités entre cellules par comparaison élastique entre leurs signaux profils caractéristiques
In the decision support systems, often, there a huge digital data and possibly some contextual knowledge available a priori or provided a posteriori by feedback. The performances of classification approaches, particularly spectral ones, depend on the integration of the domain knowledge in their design. Spectral classification algorithms address the problem of classification in terms of graph cuts. They classify the data in the eigenspace of the graph Laplacian matrix. The generated eigenspace may better reveal the presence of linearly separable data clusters. In this work, we are particularly interested in algorithms integrating pairwise constraints : constrained spectral clustering. The eigenspace may reveal the data structure while respecting the constraints. We present a state of the art approaches to constrained spectral clustering. We propose a new algorithm, which generates a subspace projection, by optimizing a criterion integrating both normalized multicut and penalties due to the constraints. The performances of the algorithms are demonstrated on different databases in comparison to other algorithms in the literature. As part of monitoring of the marine ecosystem, we developed a phytoplankton classification system, based on flow cytometric analysis. for this purpose, we proposed to characterize the phytoplanktonic cells by similarity measures using elastic comparison between their cytogram signals
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Bechar, Hassane. "Comparaison d'images : Application à la surveillance et au suivi de trajectoire." Nancy 1, 1987. http://www.theses.fr/1987NAN10062.

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L'étude se base sur la comparaison d'une image stockée en mémoire avec celle provenant de la caméra. L'étude s'est effectuée à l'aide d'un dispositif cablé qui donne un résultat visuel et un résultat numérique en temps réel. Un logiciel permet d'obtenir les mêmes résultats mais en temps différé
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Al, Nazer Rouba. "Système de mesure d'impédance électrique embarqué, application aux batteries Li-ion." Phd thesis, Université de Grenoble, 2014. http://tel.archives-ouvertes.fr/tel-00958783.

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La mesure d'impédance électrique en embarqué sur véhicule est un sujet clé pour améliorer les fonctions de diagnostic d'un pack batterie. On cherche en particulier à fournir ainsi des mesures supplémentaires à celles du courant pack et des tensions cellules, afin d'enrichir les indicateurs de vieillissement dans un premier temps, et d'état de santé et de charge dans un second temps. Une méthode classique de laboratoire pour obtenir des mesures d'impédance d'une batterie est la spectroscopie d'impédance électrochimique (ou EIS). Elle consiste à envoyer un signal sinusoïdal en courant (ou tension) de fréquence variable balayant une gamme de fréquences d'intérêt et mesurer ensuite la réponse en tension (ou courant) pour chaque fréquence. Une technique d'identification active basée sur l'utilisation des signaux large bande à motifs carrés est proposée. En particulier, des simulations ont permis de comparer les performances d'identification de différents signaux d'excitation fréquemment utilisés dans le domaine de l'identification et de vérifier les conditions correspondant à un comportement linéaire et invariant dans le temps de l'élément électrochimique. L'évaluation de la qualité d'estimation est effectuée en utilisant une grandeur spécifique : la cohérence. Cette grandeur statistique permet de déterminer un intervalle de confiance sur le module et la phase de l'impédance estimée. Elle permet de sélectionner la gamme de fréquence où la batterie respecte les hypothèses imposées par la méthode d'identification large bande. Afin de valider les résultats, une électronique de test a été conçue. Les résultats expérimentaux permettent de mettre en valeur l'intérêt de cette approche par motifs carrés. Un circuit de référence est utilisé afin d'évaluer les performances en métrologie des méthodes. L'étude expérimentale est ensuite poursuivie sur une batterie Li-ion soumise à un courant de polarisation et à différents états de charge. Des essais comparatifs avec l'EIS sont réalisés. Le cahier de charge établi à l'aide d'un simulateur de batterie Li-ion a permis d'évaluer les performances de la technique large bande proposée et de structurer son utilité pour l'estimation des états de vieillissement et de charge.
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Gamero, Argüello Fco Ignacio (Francisco Ignacio). "Pattern recognition based on qualitative representation of signals. Application to situation assessment of dynamic systems." Doctoral thesis, Universitat de Girona, 2012. http://hdl.handle.net/10803/83670.

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The main focus of situation assessment is to decide on the adequacy of process behaviour with respect to specifications. When is not possible to have a mathematical model to represent the system operation, other non-model-based techniques must be considered. Classification methods are typically proposed as strategies for diagnosis. Here, identification of the functional states is reduced to recognising the current shapes of variables as well-known states, commonly taking advantage of a process expert or past experiences. However, human knowledge is related to concepts and symbols whereas process acquisition systems provide monitoring systems with numerical data. Consequently, these type of knowledge-based decision systems are usually forced to work in a higher level of abstraction using symbolic representations. This thesis deals with the study of classification methods when performing qualitative trends analysis. The aim is to obtain qualitative trends and their classification by means of the extracted knowledge from past experiences. This doctoral dissertation deals with the study of classification methods when performing qualitative trends analysis. The aim is to obtain qualitative trends and their classification by means of the extracted knowledge from past experiences.
El objetivo principal de la evaluación de situaciones es decidir sobre la adecuación del comportamiento del proceso con respecto a las especificaciones. Cuando no es posible tener un modelo matemático para representar el funcionamiento del sistema, otras técnicas deben considerarse. Los métodos de clasificación suelen ser propuestos como estrategias para el diagnóstico. La identificación de los estados funcionales se reduce a reconocer las formas de las variables como estados conocidos, comúnmente adquiriendo conocimiento de un experto o experiencias anteriores. Sin embargo, el conocimiento humano se relaciona con conceptos y símbolos, mientras que los sistemas de adquisición proporcionan datos numéricos. En consecuencia, este tipo de sistemas basados en el conocimiento de decisiones trabajan en un nivel superior de abstracción a través de representaciones simbólicas. Esta tesis aborda el estudio de métodos de clasificación de las tendencias cualitativas. El objetivo es clasificarlas por medio del conocimiento extraído de las experiencias pasadas.
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Somon, Bertille. "Corrélats neuro-fonctionnels du phénomène de sortie de boucle : impacts sur le monitoring des performances." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAS042/document.

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Les mutations technologiques à l’œuvre dans les systèmes aéronautiques ont profondément modifié les interactions entre l’homme et la machine. Au fil de cette évolution, les opérateurs se sont retrouvés face à des systèmes de plus en plus complexes, de plus en plus automatisés et de plus en plus opaques. De nombreuses tragédies montrent à quel point la supervision des systèmes par des opérateurs humains reste un problème sensible. En particulier, de nombreuses évidences montrent que l’automatisation a eu tendance à éloigner l’opérateur de la boucle de contrôle des systèmes, créant un phénomène dit de sortie de boucle (OOL). Ce phénomène se caractérise notamment par une diminution de la conscience de la situation et de la vigilance de l’opérateur, ainsi qu’une complaisance et une sur-confiance dans les automatismes. Ces difficultés déclenchent notamment une baisse des performances de l’opérateur qui n’est plus capable de détecter les erreurs du système et de reprendre la main si nécessaire. La caractérisation de l’OOL est donc un enjeux majeur des interactions homme-système et de notre société en constante évolution. Malgré plusieurs décennies de recherche, l’OOL reste difficile à caractériser, et plus encore à anticiper. Nous avons dans cette thèse utilisé les théories issues des neurosciences, notamment sur le processus de détection d’erreurs, afin de progresser sur notre compréhension de ce phénomène dans le but de développer des outils de mesure physiologique permettant de caractériser l’état de sortie de boucle lors d’interactions avec des systèmes écologiques. En particulier, l’objectif de cette thèse était de caractériser l’OOL à travers l’activité électroencéphalographique (EEG) dans le but d’identifier des marqueurs et/ou précurseurs de la dégradation du processus de supervision du système. Nous avons dans un premier temps évalué ce processus de détection d’erreurs dans des conditions standards de laboratoire plus ou moins complexes. Deux études en EEG nous ont d’abord permis : (i) de montrer qu’une activité cérébrale associée à ce processus cognitif se met en place dans les régions fronto-centrales à la fois lors de la détection de nos propres erreurs (ERN-Pe et FRN-P300) et lors de la détection des erreurs d’un agent que l’on supervise, (complexe N2-P3) et (ii) que la complexité de la tâche évaluée peut dégrader cette activité cérébrale. Puis nous avons mené une autre étude portant sur une tâche plus écologique et se rapprochant des conditions de supervision courantes d’opérateurs dans l’aéronautique. Au travers de techniques de traitement du signal EEG particulières (e.g., analyse temps-fréquence essai par essai), cette étude a mis en évidence : (i) l’existence d’une activité spectrale θ dans les régions fronto-centrales qui peut être assimilée aux activités mesurées en condition de laboratoire, (ii) une diminution de l’activité cérébrale associée à la détection des décisions du système au cours de la tâche, et (iii) une diminution spécifique de cette activité pour les erreurs. Dans cette thèse, plusieurs mesures et analyses statistiques de l’activité EEG ont été adaptées afin de considérer les contraintes des tâches écologiques. Les perspectives de cette thèse ouvrent sur une étude en cours dont le but est de mettre en évidence la dégradation de l’activité de supervision des systèmes lors de la sortie de boucle, ce qui permettrait d’identifier des marqueurs précis de ce phénomène permettant ainsi de le détecter, voire même, de l’anticiper
The ongoing technological mutations occuring in aeronautics have profoundly changed the interactions between men and machines. Systems are more and more complex, automated and opaque. Several tragedies have reminded us that the supervision of those systems by human operators is still a challenge. Particularly, evidences have been made that automation has driven the operators away from the control loop of the system thus creating an out-of-the-loop phenomenon (OOL). This phenomenon is characterized by a decrease in situation awareness and vigilance, but also complacency and over-reliance towards automated systems. These difficulties have been shown to result in a degradation of the operator’s performances. Thus, the OOL phenomenon is a major issue of today’s society to improve human-machine interactions. Even though it has been studied for several decades, the OOL is still difficult to characterize, and even more to predict. The aim of this thesis is to define how cognitive neurosciences theories, such as the performance monitoring activity, can be used in order to better characterize the OOL phenomenon and the operator’s state, particularly through physiological measures. Consequently, we have used electroencephalographic activity (EEG) to try and identify markers and/or precursors of the supervision activity during system monitoring. In a first step we evaluated the error detection or performance monitoring activity through standard laboratory tasks, with varying levels of difficulty. We performed two EEG studies allowing us to show that : (i) the performance monitoring activity emerges both for our own errors detection but also during another agent supervision, may it be a human agent or an automated system, and (ii) the performance monitoring activity is significantly decreased by increasing task difficulty. These results led us to develop another experiment to assess the brain activity associated with system supervision in an ecological environment, resembling everydaylife aeronautical system monitoring. Thanks to adapted signal processing techniques (e.g. trial-by-trial time-frequency decomposition), we were able to show that there is : (i) a fronto-central θ activité time-locked to the system’s decision similar to the one obtained in laboratory condition, (ii) a decrease in overall supervision activity time-locked to the system’s decision, and (iii) a specific decrease of monitoring activity for errors. In this thesis, several EEG measures have been used in order to adapt to the context at hand. As a perspective, we have developped a final study aiming at defining the evolution of the monitoring activity during the OOL. Finding markers of this degradation would allow to monitor its emersion, and even better, predict it
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Huamán, Aliaga Carlos Alberto Junior, and Chumpitaz Yameli Olenka Talla. "Desarrollo de un prototipo de supervisión médica, basado en IOT, para la detección de arritmia de tipo Fibrilación auricular en personas de la tercera edad en estado de reposo, mediante el monitoreo y procesamiento de señales ECG." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2020. http://hdl.handle.net/10757/656502.

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El presente trabajo propone un sistema electrónico de monitoreo continuo de las señales electrocardiográficas de pacientes para la detección de arritmias de tipo Fibrilación auricular y envío de resultados obtenidos para ofrecer una completa supervisión médica que agilice el diagnóstico y atención del paciente. El sistema está compuesto por dos partes, la primera de Hardware y la segunda de Software. En primer lugar, el Hardware del sistema está compuesto por equipos que permiten adquirir las señales electrocardiográficas, realizar el procesamiento y enviar las señales a una base de datos. En segundo lugar, el Software analiza dos parámetros de la señal electrocardiográfica para inferir si el paciente presenta fibrilación auricular y envía una alerta al especialista para la revisión de la señal involucrada. La validación del funcionamiento del sistema se realizó utilizando señales de la base de datos Physionet con una efectividad de 97.3% y señales extraídas de un conjunto de personas con una efectividad del 85.7%.
The present work proposes an electronic system for constant monitoring of the electrocardiographic signals of the patients for the detection of atrial fibrillation and sending the results in order to offer a complete medical supervision that expedites diagnosis and patient care. The system is composed of two parts, the first Hardware and the second Software. First, the system Hardware consists of equipment that allows electrocardiographic signals to be obtained, to process and send the signals to a database. Second, the system Software analyzes 02 parameters of the electrocardiographic signal to conclude if the patient has atrial fibrillation. The validation of the operation of the system is performed using signals from the Physionet database with 97.3% effectiveness and signals extracted from a sample of people with 85.7% effectiveness.
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9

Jiang-YongCheng and 承江永. "A Modified Time-Frequency Transform and Its Application to Power Quality Signal Supervision." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/y76822.

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博士
國立成功大學
電機工程學系
104
Continuous technological advancement has enabled conventional industries to upgrade into high-tech industries. The emphasis on the quality of supplying power has hence becomes more important than ever. Therefore, this study thoroughly investigated power supply quality signals by using an improved time-frequency transform method. This study first proposed Gabor-Wigner transform to investigate high impedance fault detection. In addition to being applicable to non-stationary signals, Gabor-Wigner transform exhibited major advantages such as considerably high time-frequency resolution and capability to overcome the noise problem in Wigner distribution. The method proposed in this dissertation was applied to high impedance fault detection in various situations, including on a cement ground, wet ground, and lawn. The experiment results revealed that this method can correctly detect high impedance faults in various conditions, serving as useful references for the study in the field of high impedance fault detection. Furthermore, the method proposed in this dissertation was applied to investigate various voltage flicker-generated signals such as 5Hz voltage flicker-generated signals, 10Hz voltage flicker-generated signals, voltage flicker-generated signals with harmonic signals, and the voltage flicker-generated signals produced by electric arc furnace operations. Test results of waveforms that were generated from simulations and measurements revealed that the proposed method effectively detected voltage flicker variations in all scenarios, benefiting engineers to grasp the quality information of power operations. The method proposed in this dissertation was also applied to discuss the inter-harmonic signals produced during the simulation and actual experiment. When analyzing the inter-harmonic signals in simulation, this method correctly detected the frequency and the time point of inter-harmonic signal occurrence, and the amplitude of each frequency. Moreover, when analyzing inter-harmonic signals of actual experiments, this method completed with a good detection without committing any misjudgment. Finally, the method proposed in this dissertation was used to investigate signals of voltage sag and voltage interruption as well. The results show that this method can identify the time point, frequency, and amplitude of power sags and interruptions. This method has also exhibited a higher resolution. The outcomes gained from these tests are useful for the improvement of electric power quality study.
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Books on the topic "Supervision signal"

1

Luttrell, Stephen P. Self-supervision in multilayer adaptive networks. [London]: HMSO, 1991.

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Pollock, Steve. Coaching green belt projects for sustainable success. Milwaukee, Wisconsin: ASQ Quality Press, 2015.

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Chritton, M. R. Security system signal supervision. Supt. of Docs., U.S. G.P.O. [distributor], 1991.

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Simon, Gleeson. Part VI Bank Group Supervision, 24 Group Supervision. Oxford University Press, 2018. http://dx.doi.org/10.1093/law/9780198793410.003.0024.

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This chapter discusses banking group supervision. At first glance the necessity for the supervision of banking groups is not obvious. However, banks are now known to be subject to contagion risk. In theory the failure of a company which is a member of a bank group has no effect on the regulated bank. In practice, the failure of a company in a bank group will send a strong signal to the outside world that the group is in difficulty. It would in theory be possible to operate a group bank with such a degree of separation that the market as a whole believed that the bank would genuinely be unaffected by the failure of one of its subsidiaries. However, in practice the market believes that banks are closely connected with the groups of which they are members, and that failures elsewhere in a group will have important knock-on consequences for a group bank.
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Walters, Russell Craig. A distributed in-process supervision of milling based on signal processing machining models. 1993.

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Corporation, National Learning. Supervisor (Signals). National Learning Corp, 2005.

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Cobb, William T. Digital filtering techniques for processing signals utilized in the unmanned supervision of machining. 1994.

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La citta senza nome: Segni e segnali nella metropoli moderna : Atti del 1o Convegno internazionale di studio sull'immagine della citta, Roma, 27-28 ottobre 1994 (Atti e documenti / Supervisione). Edizioni De Luca, 1996.

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Book chapters on the topic "Supervision signal"

1

Dornfeld, D. "Signal Processing for Automatic Supervision." In Automatic Supervision in Manufacturing, 209–50. London: Springer London, 1994. http://dx.doi.org/10.1007/978-1-4471-3458-9_10.

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Ke, Niu, Du Yihang, Niu Chenxu, and Li Panke. "Optimal Design of an Ecological Alarm Display for Automatic Train Supervision System." In Advances in Intelligent Information Hiding and Multimedia Signal Processing, 183–93. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1053-1_17.

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Bryant, Peter T. "Learning." In Augmented Humanity, 225–46. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76445-6_8.

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AbstractHuman and artificial agents are both committed to learning. Evaluation of performance is a key driver. This is the case for adaptive feedback, which is generated from the evaluation of performance outcomes. It is also true for feedforward guidance, which results from real-time monitoring of ongoing processes. Augmented agents will learn in both ways. However, these developments signal a shift from historic patterns of learning from performance, which mainly focus on slower, inter-cyclical feedback cycles. Indeed, much human learning occurs in simple increments and takes years to complete. By comparison, artificial agents learn complex lessons with extraordinary speed and precision. Therefore, if collaborative supervision is poor, artificial learning will be fast and complex, while human learning is relatively sluggish and incremental. Such learning will be distorted, often ambiguous, ambivalent, and potentially dysfunctional. This chapter examines these dilemmas.
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Baqué, François, Olivier Descombin, Olivier Gastaldi, and Yves Vandenboomgaerde. "Aims, Context and Type of Signals Studied." In Supervision and Safety of Complex Systems, 183–90. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118561744.ch9.

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Kebriaee, Javad, Hadi Chahkandi Nejad, and Sadegh Seynali. "Using an Active Learning Semi-supervision Algorithm for Classifying of ECG Signals and Diagnosing Heart Diseases." In Lecture Notes in Electrical Engineering, 69–82. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8672-4_6.

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Paś, Jacek, and Tomasz Klimczak. "Operational System Modelling in a Focused Fire Alarm System with an Open and Signal Detection Circuit Supervising Railway Station Premises." In Advances in Intelligent Systems and Computing, 307–16. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-27687-4_31.

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Barschdorff, D., P. M. Frank, R. Isermann, R. J. Patton, and D. Wach. "SIGNAL AND/OR MODEL BASED DIAGNOSIS." In Fault Detection, Supervision and Safety for Technical Processes 1991, 621. Elsevier, 1992. http://dx.doi.org/10.1016/b978-0-08-041275-7.50100-9.

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Gustafsson, F. "Statistical Signal Processing Approaches to Fault Detection." In Fault Detection, Supervision and Safety of Technical Processes 2006, 24–35. Elsevier, 2007. http://dx.doi.org/10.1016/b978-008044485-7/50006-3.

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Samaan, M., M. Duque, and M. M'Saad. "A REAL TIME SUPERVISION SYSTEM FOR ADAPTIVE CONTROL." In Adaptive Systems in Control and Signal Processing 1989, 397–402. Elsevier, 1990. http://dx.doi.org/10.1016/b978-0-08-035727-0.50072-x.

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Endt, P., C. Rudolph, H. Schwetlick, and D. Filbert. "MULTI-LEVEL SIGNAL ABSTRACTION FOR DIAGNOSING ANALOGUE CIRCUITS." In Fault Detection, Supervision and Safety for Technical Processes 1991, 343–47. Elsevier, 1992. http://dx.doi.org/10.1016/b978-0-08-041275-7.50053-3.

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Conference papers on the topic "Supervision signal"

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Jayawardana, Vindula, Anna Landler, and Cathy Wu. "Mixed Autonomous Supervision in Traffic Signal Control." In 2021 IEEE International Intelligent Transportation Systems Conference (ITSC). IEEE, 2021. http://dx.doi.org/10.1109/itsc48978.2021.9565053.

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Otero, A., P. Felix, F. Palacios, C. Perez-Gandia, and COS Sorzano. "Intelligent alarms for patient supervision." In 2007 IEEE International Symposium on Intelligent Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/wisp.2007.4447555.

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Jin, Gaole, and Raviv Raich. "On surrogate supervision multiview learning." In 2012 IEEE International Workshop on Machine Learning for Signal Processing (MLSP). IEEE, 2012. http://dx.doi.org/10.1109/mlsp.2012.6349759.

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Gfeller, Beat, Christian Frank, Dominik Roblek, Matt Sharifi, Marco Tagliasacchi, and Mihajlo Velimirovic. "Pitch Estimation Via Self-Supervision." In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. http://dx.doi.org/10.1109/icassp40776.2020.9053798.

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Mopuri, Konda Reddy, Vishal B. Athreya, and R. Venkatesh Babu. "Learning Representations with Strong Supervision for Image Search." In 2018 International Conference on Signal Processing and Communications (SPCOM). IEEE, 2018. http://dx.doi.org/10.1109/spcom.2018.8724475.

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Huan Zhang, Zheying Li, and Wenliang Niu. "Mine supervision system data analysis and transmission design." In 2008 9th International Conference on Signal Processing (ICSP 2008). IEEE, 2008. http://dx.doi.org/10.1109/icosp.2008.4697765.

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Li, Zhengxue, and Gaoyun An. "Human-Object Interaction Prediction with Natural Language Supervision." In 2022 16th IEEE International Conference on Signal Processing (ICSP). IEEE, 2022. http://dx.doi.org/10.1109/icsp56322.2022.9965210.

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Li, Bin, Xiaoguang Chen, Zhixin Wang, and Shulin Tan. "Vibration Signal Analysis For Rail Flaw Detection." In 2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS). IEEE, 2019. http://dx.doi.org/10.1109/safeprocess45799.2019.9213353.

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Salem, Sameh, and Asoke Nandi. "Novel Clustering Algorithm (RACAL) and a Partial Supervision Strategy for Classification." In 2006 16th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing. IEEE, 2006. http://dx.doi.org/10.1109/mlsp.2006.275567.

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Yao, Tingting, Shenghua Dai, Pei Wang, and Yue He. "Image based obstacle detection for automatic train supervision." In 2012 5th International Congress on Image and Signal Processing (CISP). IEEE, 2012. http://dx.doi.org/10.1109/cisp.2012.6469703.

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Reports on the topic "Supervision signal"

1

Chritton, M. R., and J. C. Matter. Security system signal supervision. Office of Scientific and Technical Information (OSTI), September 1991. http://dx.doi.org/10.2172/6276408.

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López Boo, Florencia, María de la Paz Ferro, and Pedro Carneiro. ¿Funciona integrar servicios de primera infancia con los servicios de salud?: Evidencia experimental del programa de visitas domiciliarias Cresça Com Seu Filho. Inter-American Development Bank, April 2021. http://dx.doi.org/10.18235/0003230.

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Un desafío clave de la política pública es cómo llevar a escala programas de primera infancia efectivos. Si la entrega de estos programas pudiera hacerse a través de la infraestructura de servicios públicos existentes, esto resultaría no solo escalable sino más costo-eficiente. Este documento es de los primeros en evaluar los impactos de corto plazo de un programa de visitas domiciliarias a escala integrado completamente con los servicios de atención primaria en salud (en este caso, la Estratégia Saúde da Família de Brasil). Nuestra estrategia de identificación explota la aleatorización original del programa Cresça Com Seu Filho en Fortaleza a nivel de agente comunitario de salud (ACS). En la estimación de intención de tratamiento (ITT, por sus siglas en inglés) encontramos un impacto positivo modesto en la calidad del entorno familiar (0.12 desvíos estándar, DE). Este resultado se alinea con el foco del currículo del programa en el cuidado sensible, receptivo y no punitivo de los niños. No encontramos evidencia de impacto en desarrollo infantil, muy probablemente debido a los desafíos con la intensidad y la fidelidad de las visitas. Nuestros resultados apuntan a la importancia de mejorar los sistemas de supervisión y acompañamiento del personal para lograr mejoras en la fidelidad de la intervención, así como en esquemas de motivación intrínseca del recurso humano que, en un contexto de mayor carga laboral, resulta central para el éxito de este tipo de intervenciones.
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