The Experts below are selected from a list of 91578 Experts worldwide ranked by ideXlab platform
Yan Wang - One of the best experts on this subject based on the ideXlab platform.
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Modeling a paper making wastewater treatment process by means of an adaptive network based fuzzy inference system and principal component analysis
Industrial & Engineering Chemistry Research, 2012Co-Authors: Mingzhi Huang, Huiping Zhang, Yan WangAbstract:In this paper, a Predictive Control system based on an adaptive network-based fuzzy inference system (ANFIS) was employed to develop Models for predicting and Controlling the performance of a paper-making wastewater treatment process. The system includes an ANFIS Predictive Model and an ANFIS Controller. In order to improve the network performance, fuzzy subtractive clustering, euclidean distance clustering, and principal component analysis (PCA) were used to identify Model architecture and extract and optimize the fuzzy rule of the Model. For the developed Predictive Model, when predicting, mean absolute percentage error (MAPE) lay 6.06% adopting ANFIS, root mean square normalized error (RMSE) was 24.4485 and R was 0.9731. The Control Model, taking into account the difference between the predicted value of chemical oxygen demand (COD) and the set point, can effectively change the additive dosages. In order to verify the developed Predictive Control Model, a paper-making wastewater treatment process was p...
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Modeling a Paper-Making Wastewater Treatment Process by Means of an Adaptive Network-Based Fuzzy Inference System and Principal Component Analysis
Industrial & Engineering Chemistry Research, 2012Co-Authors: Mingzhi Huang, Huiping Zhang, Jinquan Wan, Yan WangAbstract:In this paper, a Predictive Control system based on an adaptive network-based fuzzy inference system (ANFIS) was employed to develop Models for predicting and Controlling the performance of a paper-making wastewater treatment process. The system includes an ANFIS Predictive Model and an ANFIS Controller. In order to improve the network performance, fuzzy subtractive clustering, euclidean distance clustering, and principal component analysis (PCA) were used to identify Model architecture and extract and optimize the fuzzy rule of the Model. For the developed Predictive Model, when predicting, mean absolute percentage error (MAPE) lay 6.06% adopting ANFIS, root mean square normalized error (RMSE) was 24.4485 and R was 0.9731. The Control Model, taking into account the difference between the predicted value of chemical oxygen demand (COD) and the set point, can effectively change the additive dosages. In order to verify the developed Predictive Control Model, a paper-making wastewater treatment process was p...
Lucile Rapin - One of the best experts on this subject based on the ideXlab platform.
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The ConDialInt Model: Condensation, Dialogality, and Intentionality Dimensions of Inner Speech Within a Hierarchical Predictive Control Framework
Frontiers in Psychology, 2019Co-Authors: Romain Grandchamp, Lucile Rapin, Marion Dohen, Pascal Perrier, Marcela Perrone-bertolotti, Cédric Pichat, Célise Haldin, Emilie Cousin, Jean-philippe Lachaux, Maëva GarnierAbstract:Inner speech has been shown to vary in form along several dimensions. Along condensation, condensed inner speech forms have been described, that are supposed to be deprived of acoustic, phonological and even syntactic qualities. Expanded forms, on the other extreme, display articulatory and auditory properties. Along dialogality, inner speech can be monologal, when we engage in internal soliloquy, or dialogal, when we recall past conversations or imagine future dialogs involving our own voice as well as that of others addressing us. Along intentionality, it can be intentional (when we deliberately rehearse material in short-term memory) or it can arise unintentionally (during mind wandering). We introduce the ConDialInt Model, a neurocognitive Predictive Control Model of inner speech that accounts for its varieties along these three dimensions. ConDialInt spells out the condensation dimension by including inhibitory Control at the conceptualization, formulation or articulatory planning stage. It accounts for dialogality, by assuming internal Model adaptations and by speculating on neural processes underlying perspective switching. It explains the differences between intentional and spontaneous varieties in terms of monitoring. We present an fMRI study in which we probed varieties of inner speech along dialogality and intentionality, to examine the validity of the neuroanatomical correlates posited in ConDialInt. Condensation was also informally tackled. Our data support the hypothesis that expanded inner speech recruits speech production processes down to articulatory planning, resulting in a predicted signal, the inner voice, with auditory qualities. Along dialogality, covertly using an avatar's voice resulted in the activation of right hemisphere homologs of the regions involved in internal own-voice soliloquy and in reduced cerebellar activation, consistent with internal Model adaptation. Switching from first-person to third-person perspective resulted in activations in precuneus and parietal lobules. Along intentionality, compared with intentional inner speech, mind wandering with inner speech episodes was associated with greater bilateral inferior frontal activation and decreased activation Frontiers in Psychology | www.frontiersin.org 1
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An EMG study of the lip muscles during covert auditory verbal hallucinations in schizophrenia.
Journal of speech language and hearing research : JSLHR, 2013Co-Authors: Lucile Rapin, Marion Dohen, Mircea Polosan, Pascal Perrier, Hélène LœvenbruckAbstract:Auditory verbal hallucinations (AVHs) are speech perceptions in the absence of external stimulation. According to an influential theoretical account of AVHs in schizophrenia, a deficit in inner-speech monitoring may cause the patients' verbal thoughts to be perceived as external voices. The account is based on a Predictive Control Model, in which individuals implement verbal self-monitoring. The authors examined lip muscle activity during AVHs in patients with schizophrenia to check whether inner speech occurred. Lip muscle activity was recorded during covert AVHs (without articulation) and rest. Surface electromyography (EMG) was used on 11 patients with schizophrenia. Results showed an increase in EMG activity in the orbicularis oris inferior muscle during covert AVHs relative to rest. This increase was not due to general muscular tension because there was no increase of muscular activity in the forearm muscle. This evidence that AVHs might be self-generated inner speech is discussed in the framework of a Predictive Control Model. Further work is needed to better describe how inner speech is Controlled and monitored and the nature of inner-speech-monitoring-dysfunction. This will lead to a better understanding of how AVHs occur.
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An EMG study of the lip muscles during covert auditory verbal hallucinations in schizophrenia
Journal of Speech Language and Hearing Research, 2013Co-Authors: Lucile Rapin, Marion Dohen, Mircea Polosan, Pascal Perrier, Hélène LœvenbruckAbstract:Purpose: Auditory verbal hallucinations (AVHs) are speech perceptions in the absence of a external stimulation. An influential theoretical account of AVHs in schizophrenia claims that a deficit in inner speech monitoring would cause the verbal thoughts of the patient to be perceived as external voices. The account is based on a Predictive Control Model, in which verbal self-monitoring is implemented. The aim of this study was to examine lip muscle activity during AVHs in schizophrenia patients, in order to check whether inner speech occurred. Methods: Lip muscle activity was recorded during covert AVHs (without articulation) and rest. Surface electromyography (EMG) was used on eleven schizophrenia patients. Results: Our results show an increase in EMG activity in the orbicularis oris inferior muscle, during covert AVHs relative to rest. This increase is not due to general muscular tension since there was no increase of muscular activity in the forearm muscle. Conclusion: This evidence that AVHs might be self-generated inner speech is discussed in the framework of a Predictive Control Model. Further work is needed to better describe how the inner speech monitoring dysfunction occurs and how inner speech is Controlled and monitored. This will help better understanding how AVHs occur.
Yong Xu - One of the best experts on this subject based on the ideXlab platform.
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ICNC - Generalized Predictive Control Model based on support vector machines
2012 8th International Conference on Natural Computation, 2012Co-Authors: Yong XuAbstract:Aiming at nonlinear deControlled plants at large exist in industrial processes, this paper firstly introduces the support vector machine and least squares support vector machine briefly. On this basis, we propose a nonlinear generalized Predictive Control Model based on least squares support vector machines. This method can overcome the classic quadratic programming method for solving support vector machines curse of dimensionality problem, and has a good robustness, suitable for large-scale computing. So use least squares support vector machines as nonlinear Predictive Model have more advantages.
Pascal Perrier - One of the best experts on this subject based on the ideXlab platform.
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The ConDialInt Model: Condensation, Dialogality, and Intentionality Dimensions of Inner Speech Within a Hierarchical Predictive Control Framework
Frontiers in Psychology, 2019Co-Authors: Romain Grandchamp, Lucile Rapin, Marion Dohen, Pascal Perrier, Marcela Perrone-bertolotti, Cédric Pichat, Célise Haldin, Emilie Cousin, Jean-philippe Lachaux, Maëva GarnierAbstract:Inner speech has been shown to vary in form along several dimensions. Along condensation, condensed inner speech forms have been described, that are supposed to be deprived of acoustic, phonological and even syntactic qualities. Expanded forms, on the other extreme, display articulatory and auditory properties. Along dialogality, inner speech can be monologal, when we engage in internal soliloquy, or dialogal, when we recall past conversations or imagine future dialogs involving our own voice as well as that of others addressing us. Along intentionality, it can be intentional (when we deliberately rehearse material in short-term memory) or it can arise unintentionally (during mind wandering). We introduce the ConDialInt Model, a neurocognitive Predictive Control Model of inner speech that accounts for its varieties along these three dimensions. ConDialInt spells out the condensation dimension by including inhibitory Control at the conceptualization, formulation or articulatory planning stage. It accounts for dialogality, by assuming internal Model adaptations and by speculating on neural processes underlying perspective switching. It explains the differences between intentional and spontaneous varieties in terms of monitoring. We present an fMRI study in which we probed varieties of inner speech along dialogality and intentionality, to examine the validity of the neuroanatomical correlates posited in ConDialInt. Condensation was also informally tackled. Our data support the hypothesis that expanded inner speech recruits speech production processes down to articulatory planning, resulting in a predicted signal, the inner voice, with auditory qualities. Along dialogality, covertly using an avatar's voice resulted in the activation of right hemisphere homologs of the regions involved in internal own-voice soliloquy and in reduced cerebellar activation, consistent with internal Model adaptation. Switching from first-person to third-person perspective resulted in activations in precuneus and parietal lobules. Along intentionality, compared with intentional inner speech, mind wandering with inner speech episodes was associated with greater bilateral inferior frontal activation and decreased activation Frontiers in Psychology | www.frontiersin.org 1
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An EMG study of the lip muscles during covert auditory verbal hallucinations in schizophrenia.
Journal of speech language and hearing research : JSLHR, 2013Co-Authors: Lucile Rapin, Marion Dohen, Mircea Polosan, Pascal Perrier, Hélène LœvenbruckAbstract:Auditory verbal hallucinations (AVHs) are speech perceptions in the absence of external stimulation. According to an influential theoretical account of AVHs in schizophrenia, a deficit in inner-speech monitoring may cause the patients' verbal thoughts to be perceived as external voices. The account is based on a Predictive Control Model, in which individuals implement verbal self-monitoring. The authors examined lip muscle activity during AVHs in patients with schizophrenia to check whether inner speech occurred. Lip muscle activity was recorded during covert AVHs (without articulation) and rest. Surface electromyography (EMG) was used on 11 patients with schizophrenia. Results showed an increase in EMG activity in the orbicularis oris inferior muscle during covert AVHs relative to rest. This increase was not due to general muscular tension because there was no increase of muscular activity in the forearm muscle. This evidence that AVHs might be self-generated inner speech is discussed in the framework of a Predictive Control Model. Further work is needed to better describe how inner speech is Controlled and monitored and the nature of inner-speech-monitoring-dysfunction. This will lead to a better understanding of how AVHs occur.
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An EMG study of the lip muscles during covert auditory verbal hallucinations in schizophrenia
Journal of Speech Language and Hearing Research, 2013Co-Authors: Lucile Rapin, Marion Dohen, Mircea Polosan, Pascal Perrier, Hélène LœvenbruckAbstract:Purpose: Auditory verbal hallucinations (AVHs) are speech perceptions in the absence of a external stimulation. An influential theoretical account of AVHs in schizophrenia claims that a deficit in inner speech monitoring would cause the verbal thoughts of the patient to be perceived as external voices. The account is based on a Predictive Control Model, in which verbal self-monitoring is implemented. The aim of this study was to examine lip muscle activity during AVHs in schizophrenia patients, in order to check whether inner speech occurred. Methods: Lip muscle activity was recorded during covert AVHs (without articulation) and rest. Surface electromyography (EMG) was used on eleven schizophrenia patients. Results: Our results show an increase in EMG activity in the orbicularis oris inferior muscle, during covert AVHs relative to rest. This increase is not due to general muscular tension since there was no increase of muscular activity in the forearm muscle. Conclusion: This evidence that AVHs might be self-generated inner speech is discussed in the framework of a Predictive Control Model. Further work is needed to better describe how the inner speech monitoring dysfunction occurs and how inner speech is Controlled and monitored. This will help better understanding how AVHs occur.
Marion Dohen - One of the best experts on this subject based on the ideXlab platform.
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The ConDialInt Model: Condensation, Dialogality, and Intentionality Dimensions of Inner Speech Within a Hierarchical Predictive Control Framework
Frontiers in Psychology, 2019Co-Authors: Romain Grandchamp, Lucile Rapin, Marion Dohen, Pascal Perrier, Marcela Perrone-bertolotti, Cédric Pichat, Célise Haldin, Emilie Cousin, Jean-philippe Lachaux, Maëva GarnierAbstract:Inner speech has been shown to vary in form along several dimensions. Along condensation, condensed inner speech forms have been described, that are supposed to be deprived of acoustic, phonological and even syntactic qualities. Expanded forms, on the other extreme, display articulatory and auditory properties. Along dialogality, inner speech can be monologal, when we engage in internal soliloquy, or dialogal, when we recall past conversations or imagine future dialogs involving our own voice as well as that of others addressing us. Along intentionality, it can be intentional (when we deliberately rehearse material in short-term memory) or it can arise unintentionally (during mind wandering). We introduce the ConDialInt Model, a neurocognitive Predictive Control Model of inner speech that accounts for its varieties along these three dimensions. ConDialInt spells out the condensation dimension by including inhibitory Control at the conceptualization, formulation or articulatory planning stage. It accounts for dialogality, by assuming internal Model adaptations and by speculating on neural processes underlying perspective switching. It explains the differences between intentional and spontaneous varieties in terms of monitoring. We present an fMRI study in which we probed varieties of inner speech along dialogality and intentionality, to examine the validity of the neuroanatomical correlates posited in ConDialInt. Condensation was also informally tackled. Our data support the hypothesis that expanded inner speech recruits speech production processes down to articulatory planning, resulting in a predicted signal, the inner voice, with auditory qualities. Along dialogality, covertly using an avatar's voice resulted in the activation of right hemisphere homologs of the regions involved in internal own-voice soliloquy and in reduced cerebellar activation, consistent with internal Model adaptation. Switching from first-person to third-person perspective resulted in activations in precuneus and parietal lobules. Along intentionality, compared with intentional inner speech, mind wandering with inner speech episodes was associated with greater bilateral inferior frontal activation and decreased activation Frontiers in Psychology | www.frontiersin.org 1
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An EMG study of the lip muscles during covert auditory verbal hallucinations in schizophrenia.
Journal of speech language and hearing research : JSLHR, 2013Co-Authors: Lucile Rapin, Marion Dohen, Mircea Polosan, Pascal Perrier, Hélène LœvenbruckAbstract:Auditory verbal hallucinations (AVHs) are speech perceptions in the absence of external stimulation. According to an influential theoretical account of AVHs in schizophrenia, a deficit in inner-speech monitoring may cause the patients' verbal thoughts to be perceived as external voices. The account is based on a Predictive Control Model, in which individuals implement verbal self-monitoring. The authors examined lip muscle activity during AVHs in patients with schizophrenia to check whether inner speech occurred. Lip muscle activity was recorded during covert AVHs (without articulation) and rest. Surface electromyography (EMG) was used on 11 patients with schizophrenia. Results showed an increase in EMG activity in the orbicularis oris inferior muscle during covert AVHs relative to rest. This increase was not due to general muscular tension because there was no increase of muscular activity in the forearm muscle. This evidence that AVHs might be self-generated inner speech is discussed in the framework of a Predictive Control Model. Further work is needed to better describe how inner speech is Controlled and monitored and the nature of inner-speech-monitoring-dysfunction. This will lead to a better understanding of how AVHs occur.
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An EMG study of the lip muscles during covert auditory verbal hallucinations in schizophrenia
Journal of Speech Language and Hearing Research, 2013Co-Authors: Lucile Rapin, Marion Dohen, Mircea Polosan, Pascal Perrier, Hélène LœvenbruckAbstract:Purpose: Auditory verbal hallucinations (AVHs) are speech perceptions in the absence of a external stimulation. An influential theoretical account of AVHs in schizophrenia claims that a deficit in inner speech monitoring would cause the verbal thoughts of the patient to be perceived as external voices. The account is based on a Predictive Control Model, in which verbal self-monitoring is implemented. The aim of this study was to examine lip muscle activity during AVHs in schizophrenia patients, in order to check whether inner speech occurred. Methods: Lip muscle activity was recorded during covert AVHs (without articulation) and rest. Surface electromyography (EMG) was used on eleven schizophrenia patients. Results: Our results show an increase in EMG activity in the orbicularis oris inferior muscle, during covert AVHs relative to rest. This increase is not due to general muscular tension since there was no increase of muscular activity in the forearm muscle. Conclusion: This evidence that AVHs might be self-generated inner speech is discussed in the framework of a Predictive Control Model. Further work is needed to better describe how the inner speech monitoring dysfunction occurs and how inner speech is Controlled and monitored. This will help better understanding how AVHs occur.