Information processing in sleep-onset insomnia : a test of the neurocognitive model /

The present thesis study is a systematic investigation of information processing at sleep onset, using auditory event-related potentials (ERPs) as a test of the neurocognitive model of insomnia. Insomnia is an extremely prevalent disorder in society resulting in problems with daytime functioning (e.g., memory, concentration, job performance, mood, job and driving safety). Various models have been put forth in an effort to better understand the etiology and pathophysiology of this disorder. One of the newer models, the neurocognitive model of insomnia, suggests that chronic insomnia occurs through conditioned central nervous system arousal. This arousal is reflected through increased information processing which may interfere with sleep initiation or maintenance. The present thesis employed event-related potentials as a direct method to test information processing during the sleep-onset period. Thirteen poor sleepers with sleep-onset insomnia and 1 2 good sleepers participated in the present study. All poor sleepers met the diagnostic criteria for psychophysiological insomnia and had a complaint of problems with sleep initiation. All good sleepers reported no trouble sleeping and no excessive daytime sleepiness. Good and poor sleepers spent two nights at the Brock University Sleep Research Laboratory. The first night was used to screen for sleep disorders; the second night was used to investigate information processing during the sleep-onset period. Both groups underwent a repeated sleep-onsets task during which an auditory oddball paradigm was delivered. Participants signalled detection of a higher pitch target tone with a button press as they fell asleep. In addition, waking alert ERPs were recorded 1 hour before and after sleep on both Nights 1 and 2.As predicted by the neurocognitive model of insomnia, increased CNS activity was found in the poor sleepers; this was reflected by their smaller amplitude P2 component seen during wake of the sleep-onset period. Unlike the P2 component, the Nl, N350, and P300 did not vary between the groups. The smaller P2 seen in our poor sleepers indicates that they have a deficit in the sleep initiation processes. Specifically, poor sleepers do not disengage their attention from the outside environment to the same extent as good sleepers during the sleep-onset period. The lack of findings for the N350 suggest that this sleep component may be intact in those with insomnia and that it is the waking components (i.e., Nl, P2) that may be leading to the deficit in sleep initiation. Further, it may be that the mechanism responsible for the disruption of sleep initiation in the poor sleepers is most reflected by the P2 component. Future research investigating ERPs in insomnia should focus on the identification of the components most sensitive to sleep disruption. As well, methods should be developed in order to more clearly identify the various types of insomnia populations in research contexts (e.g., psychophysiological vs. sleep-state misperception) and the various individual (personality characteristics, motivation) and environmental factors (arousal-related variables) that influence particular ERP components. Insomnia has serious consequences for health, safety, and daytime functioning, thus research efforts should continue in order to help alleviate this highly prevalent condition.

The role of the dopaminergic system in the production of ultrasonic calls in adult rats /

Ultrasonic vocalizations (USV) are emitted by rats in a number of social situations such as aggressive encounters, during sexual behavior, and during play in young rats, situations which are predominantly associated with strong emotional responses. These USV typically involve two distinct types of calls: 22 kHz calls, which are emitted in aversive situations and 50 kHz calls, which are emitted in non-aversive, appetitive situation. The 50 kHz calls are the focus of the present study and to date both the glutamatergic and the dopaminergic systems have been independently implicated in the production of these 50 kHz calls. The present study was conducted to examine a possible relationship between glutamate (GLU) and dopamine (DA) in mediating 50 kHz calls. It was hypothesized that the dopaminergic system plays a mediating role in 50 kHz calls induced by injections ofGLU into the anterior hypothalamic/preoptic area (AHPOA) in adult rats. A total of 68 adult male rats were used in this study. Rats' USV were recorded and analyzed in five experiments that were designed to test the hypothesis: in experiment 1, rats were treated with systemic amphetamine (AMPH) alone; in experiment 2, intra- AHPOA GLU was pretreated with systemic AMPH; in experiment 3, intra-AHPOA GLU was pretreated with intra-AHPOA AMPH; in experiment 4, rats were treated with high and low doses of intra-AHPOA AMPH only; in experiment 5, rats were treated with systemic haloperidol (HAL) as a pretreatment for intra-AHPOA GLU. Analysis of the results indicated that AMPH has a facilitatory effect on 50 kHz USV and that a relationship between DA and GLU in inducing 50 kHz calls does exist. The effect, however, was only observed when DA receptors were antagonized with HAL and was not seen with systemic AMPH pretreatments of intra-AHPOA GLU. The DAGLU relationship at the AHPOA was unclear.

A System for Models of First Order Theories

If you want to know whether a property is true or not in a specific algebraic structure,you need to test that property on the given structure. This can be done by hand, which can be cumbersome and erroneous. In addition, the time consumed in testing depends on the size of the structure where the property is applied. We present an implementation of a system for finding counterexamples and testing properties of models of first-order theories. This system is supposed to provide a convenient and paperless environment for researchers and students investigating or studying such models and algebraic structures in particular. To implement a first-order theory in the system, a suitable first-order language.( and some axioms are required. The components of a language are given by a collection of variables, a set of predicate symbols, and a set of operation symbols. Variables and operation symbols are used to build terms. Terms, predicate symbols, and the usual logical connectives are used to build formulas. A first-order theory now consists of a language together with a set of closed formulas, i.e. formulas without free occurrences of variables. The set of formulas is also called the axioms of the theory. The system uses several different formats to allow the user to specify languages, to define axioms and theories and to create models. Besides the obvious operations and tests on these structures, we have introduced the notion of a functor between classes of models in order to generate more co~plex models from given ones automatically. As an example, we will use the system to create several lattices structures starting from a model of the theory of pre-orders.

Enabling and Measuring Complexity in Evolving Designs using Generative Representations for Artificial Architecture

As the complexity of evolutionary design problems grow, so too must the quality of solutions scale to that complexity. In this research, we develop a genetic programming system with individuals encoded as tree-based generative representations to address scalability. This system is capable of multi-objective evaluation using a ranked sum scoring strategy. We examine Hornby's features and measures of modularity, reuse and hierarchy in evolutionary design problems. Experiments are carried out, using the system to generate three-dimensional forms, and analyses of feature characteristics such as modularity, reuse and hierarchy were performed. This work expands on that of Hornby's, by examining a new and more difficult problem domain. The results from these experiments show that individuals encoded with those three features performed best overall. It is also seen, that the measures of complexity conform to the results of Hornby. Moving forward with only this best performing encoding, the system was applied to the generation of three-dimensional external building architecture. One objective considered was passive solar performance, in which the system was challenged with generating forms that optimize exposure to the Sun. The results from these and other experiments satisfied the requirements. The system was shown to scale well to the architectural problems studied.

Clinician-Perceived Bridges and Barriers to Parental Implementation of Picture Exchange Communication System (PECS): An evaluation.

Picture Exchange Communication System (PECS) is an augmentative and alternative communicative system that improves communication and decreases problem behaviors in children with Developmental Disabilities and Autism. The mediator model is a validated approach that clinicians use to train parents to perform evidence-based interventions. Parental non-adherence to treatment recommendations is a documented problem. This qualitative study investigated clinician-perceived factors that influence parental adherence to PECS recommendations. Three focus groups (n=8) were conducted with Speech Language Pathologists and Behavior Therapists experienced in providing parents with PECS recommendations. Constant comparison analysis was used. In general, clinicians believed that PECS was complex to implement. Thirty-one bridges were identified to overcome complexity. Twenty-two barriers and 6 other factors also impacted parental adherence. Strategies to address these factors were proposed based on a review of the literature. Future research will be performed to validate these findings using parents and a larger sample size.

Development of a New Assessment System to Evaluate Students' English Communicative Capacities in China

The purpose of this study was to develop a new English assessment system to evaluate Chinese students' English communicative capacities. Since there is more interaction with people from English-speaking countries, Chinese people attach more importance to English oral skills, and a lot of Western English teaching methods were introduced into China to improve students' English communicative capacities. However, traditional paper-written examinations, like the English test of higher education entry examination, cannot evaluate it effectively. This study explored the perceptions of two Chinese English-language teachers and two Chinese students about English assessment system. A qualitative research method using telephone interviews was conducted in this study. The findings showed that the most possible ways to assess Chinese students' English communicative capacities were paper-written examination and person-machine conversations, although measures should be taken to improve these two models. On the other hand, the model of person-person conversation was the ideal assessment tool but was hard to achieve at the current stage.

Methoxypyrazine removal in grape juice: Development of a removal system using odorant and pheromone binding proteins coupled with bentonite fining

Multicoloured Asian Lady Beetles (MALB) and 7-spot Lady Beetles that infect vineyards can secrete alkyl-methoxypyrazines when they are processed with the grapes, resulting in wines containing a taint. The main methoxypyrazine associated with this taint is 3-isopropyl-2-methoxypyrazine (IPMP). The wines are described as having aroma and flavours of peanut butter, peanut shells, asparagus and earthy which collectively, have become known as “ladybug taint”. To date, there are no known fining agents used commercially added to juice or wine that are effective in removing this taint. The goal of this project was to use previously identified proteins with an ability to bind to methoxypyrazines at low pH, and subsequently develop a binding assay to test the ability of these proteins to bind to and remove methoxypyrazines from grape juice. The piglet odorant binding protein (plOBP) and mouse major urinary protein (mMUP) were identified, cloned and expressed in the Pichia pastoris expression system. Protein expression was induced using methanol and the proteins were subsequently purified from the induction media using anion exchange chromatography. The purified proteins were freeze-dried and rehydrated prior to use in the methoxypyrazine removal assay. The expression and purification system resulted in yields of approximately 78% of purified plOBP and 62% of purified mMUP from expression to rehydration. Purified protein values were 87 mg of purified plOPB per litre of induction media and 19 mg of purified mMUP per litre of induction medium. In order to test the ability of the protein to bind to the MPs, an MP removal assay was developed. In the assay, the purified protein is incubated with either IPMP or 3-isobutyl-2-methoxypyrazine (IBMP) for two hours in either buffer or grape juice. Bentonite is then used to capture the protein-MP complex and the bentonite-protein-MP complex is then removed from solution by filtration. Residual MP is measured in solution following the MP removal assay and compared to that in the starting solution by Gas Chromatography Mass Spectrometry (GC/MS). GC/MS results indicated that the mMUP was capable of removing IBMP and IPMP from 300 ng/L in buffer pH 4.0, buffer pH 3.5 and Riesling Juice pH 3.5 down to the limit of quantification of the instrument, which is 6ng/L and 2ng/L for IBMP and IPMP, respectively. The results for the plOBP showed that although it could remove some IBMP, it was only approximately 50-70 ng/L more than bentonite treatment followed by filtration, resulting in approximately 100 ng/L of the MPs being left in solution. pIOBP was not able to remove IPMP in buffer pH 3.5 using this system above that removed by bentonite alone. As well, the pIOBP was not able to remove any additional MPs from Chardonnay juice pH 3.5 above that already removed by the bentonite and filtration alone. The mouse MUP was shown to be a better candidate protein for removal of MPs from juice using this system.

Evaluation of a novel transcortical pin-sleeve system in a calf model

Le desserrage des tiges est une complication fréquente des plâtres avec tiges transcorticales (TP) chez les grands animaux, nécessitant souvent leur retrait prématuré avant la guérison des fractures. Les charges excessives centrées sur le cortex à l’interface os-tige proximo-externe et disto-interne causent de l'ostéolyse. En utilisant un modèle de veau nouveau-né, ce projet a évalué un nouveau système de tige-manchon et anneau integré dans un plâtre (PS) optimisé pour réduire la contrainte péri-implant et le stress à l'interface os-implant. On a émis l'hypothèse que les PS se traduiraient par une ostéolyse péri-implant moindre par rapport aux TP. Dix veaux en bonne santé, de 3 semaines d'âge, ont été implantés avec les TP ou PS dans le métacarpe droit, à raison de 2 implants par veau. Les veaux ont été observés quotidiennement pour le confort et la boiterie et ont été euthanasiés à 28 jours. Les données recueillies comprenaient les radiographies à la chirurgie et à l'euthanasie et les mesures histomorphométriques de contact os-implant sur des échantillons non-décalcifiés avec les implants in situ. Les données ont été analysées en utilisant le test de Cochran-Mantel-Haenszel, une valeur de P <0,05 a été considérée comme significative. L'épaisseur corticale était plus importante pour les implants distaux que proximaux pour les deux groupes lors de la chirurgie (P = 0,03), mais était similaire entre les groupes (P > 0,3). Les veaux avec TP ont développé une boiterie plus tôt (au jour 21) que les veaux avec PS (P = 0,04). Histologiquement, il y avait plus de contact direct os-implant cortical pour les implants PS distaux que les implants TP (P = 0,04). La jonction métaphyso-diaphysaire osseuse où les implants proximaux étaient situés est impropre aux deux systèmes; chacun a un minimum de contact os-implant et de l'ostéolyse extensive. Le système PS n'ayant pas causé une ostéolyse importante lorsque implantés dans l'os diaphysaire et peut-être une alternative convenable aux TP pour des fractures comminutives des membres distaux.

In vivo phosphorus spectroscopy in human subjects on a clinical 3T MRI system

Alors que l’Imagerie par résonance magnétique (IRM) permet d’obtenir un large éventail de données anatomiques et fonctionnelles, les scanneurs cliniques sont généralement restreints à l’utilisation du proton pour leurs images et leurs applications spectroscopiques. Le phosphore jouant un rôle prépondérant dans le métabolisme énergétique, l’utilisation de cet atome en spectroscopie RM présente un énorme avantage dans l’observation du corps humain. Cela représente un certain nombre de déEis techniques à relever dus à la faible concentration de phosphore et sa fréquence de résonance différente. L’objectif de ce projet a été de développer la capacité à réaliser des expériences de spectroscopie phosphore sur un scanneur IRM clinique de 3 Tesla. Nous présentons ici les différentes étapes nécessaires à la conception et la validation d’une antenne IRM syntonisée à la fréquence du phosphore. Nous présentons aussi l’information relative à réalisation de fantômes utilisés dans les tests de validation et la calibration. Finalement, nous présentons les résultats préliminaires d’acquisitions spectroscopiques sur un muscle humain permettant d’identiEier les différents métabolites phosphorylés à haute énergie. Ces résultats s’inscrivent dans un projet de plus grande envergure où les impacts des changements du métabolisme énergétique sont étudiés en relation avec l’âge et les pathologies.

Le défi de l’intégration de l’approche par compétences lors de la sélection : conception d’un test de jugement situationnel ciblant le rôle CanMEDS de collaborateur pour la sélection au niveau postdoctoral en médecine

Introduction : L’approche par compétences est maintenant bien ancrée dans l’enseignement au niveau de la formation médicale postdoctorale. Dans ce contexte, un système de sélection également axé sur les compétences pourrait être avantageux. L’objectif principal de ce projet était de concevoir un TJS ciblant le rôle CanMEDS de collaborateur pour la sélection au niveau postdoctoral en médecine interne (MI) et en médecine familiale (MF). Méthodologie : Des entrevues d’incidents critiques ont été réalisées auprès de résidents juniors en MI ou en MF afin de générer les items du TJS. Trois leaders de l’approche par compétences ont révisé le contenu du test. Les items ont été analysés pour identifier la compétence principale du rôle CanMEDS de collaborateur, le contexte ainsi que les membres de l’équipe interprofessionnelle représentés dans les vignettes. La clé de correction a été déterminée par un panel composé de 11 experts. Cinq méthodes de notation ont été comparées. Résultats : Sept entrevues ont été réalisées. Après révision, 33 items ont été conservés dans le TJS. Les compétences clés du rôle CanMEDS de collaborateur, les contextes et les divers membres de l’équipe interprofessionnelle étaient bien distribués au travers des items. La moyenne des scores des experts variait entre 43,4 et 75,6 % en fonction des différentes méthodes de notation. Le coefficient de corrélation de Pearson entre les cinq méthodes de notation variait entre 0,80 et 0,98. Conclusion : Ce projet démontre la possibilité de concevoir un TJS utilisant le cadre CanMEDS comme trame de fond pour l’élaboration de son contenu. Ce test, couplé à une approche globale de sélection basée sur les compétences, pourrait éventuellement améliorer le pouvoir prédictif du processus de sélection au niveau de la formation médicale postdoctorale.

Développement d’outils analytiques pour la détection de biomolécules directement dans des fluides sanguins

Cette thèse porte sur le développement de biocapteurs basés sur la technique de résonance des plasmons de surface (SPR) pour effectuer des analyses directement dans un fluide sanguin n’ayant subi aucune purification ou dilution. L’ensemble des biocapteurs discutés exploiteront un instrument SPR portable développé dans le groupe du professeur Masson. Le premier volet de la thèse portera sur le processus d’interférence lié à l’adsorption non spécifique du sérum à la surface du capteur. L’analyse des biomolécules adsorbées sera effectuée en combinant la SPR à la spectrométrie de masse. Les informations obtenues seront exploitées pour la construction de biocapteurs adaptés à l’analyse en milieu sanguin. Un premier biocapteur développé ciblera la protéine antigène prostatique spécifique (APS) contenue dans le sérum servant de biomarqueur pour dépister le cancer de la prostate. Pour détecter les faibles concentrations de cette protéine directement dans le sérum, un matériel plasmonique microstructuré sera utilisé pour amplifier les signaux obtenus et sera recouvert d’une monocouche peptidique minimisant l’adsorption non spécifique du sérum. L’instrument SPR aura été adapté pour permettre également la détection simultanée de fluorescence. Un test ELISA sera ainsi effectué en parallèle du test SPR. Chacune des techniques fournira un contrôle pour la deuxième, tout en permettant de détecter le biomarqueur au niveau requis pour dépister la maladie. La combinaison des deux méthodes permettra aussi d’élargir la gamme dynamique du test de dépistage. Pour terminer, l’instrument SPR portable sera utilisé dans le cadre de détection de petites biomolécules ayant un potentiel thérapeutique directement dans un échantillon de sang. Des peptides ayant une activité anti-athérosclérotique pourront ainsi être détectés à même un échantillon de sang ni purifié ni dilué, et ce à des concentrations de l’ordre du micromolaire. Une modification de la microfluidique via l’introduction d’une membrane poreuse au cœur de celle-ci sera la clé permettant d’effectuer de telles analyses. La présente thèse met de l’avant de nouvelles stratégies et des modifications instrumentales permettant d’analyser des protéines et des petites molécules directement dans un échantillon non purifié de sérum ou de sang. Les modifications apportées au système fluidique, à l’instrument SPR et au niveau du biocapteur employé permettront d’effectuer des biodétections dans des matrices aussi complexes que les fluides sanguins. Les présents travaux mettent en lumière la capacité d’un instrument SPR/fluorescence portable à faire en 12 minutes la biodétection d’un marqueur du cancer de la prostate directement dans un échantillon de sérum. Finalement, on rapporte ici un des premiers articles où un biocapteur SPR est utilisé à même un échantillon de sang non-purifié pour faire des biodétections.

Design and Development of an Adaptable Frame -Based System for Dravidian Language Processing

This work is aimed at building an adaptable frame-based system for processing Dravidian languages. There are about 17 languages in this family and they are spoken by the people of South India.Karaka relations are one of the most important features of Indian languages. They are the semabtuco-syntactic relations between verbs and other related constituents in a sentence. The karaka relations and surface case endings are analyzed for meaning extraction. This approach is comparable with the borad class of case based grammars.The efficiency of this approach is put into test in two applications. One is machine translation and the other is a natural language interface (NLI) for information retrieval from databases. The system mainly consists of a morphological analyzer, local word grouper, a parser for the source language and a sentence generator for the target language. This work make contributios like, it gives an elegant account of the relation between vibhakthi and karaka roles in Dravidian languages. This mapping is elegant and compact. The same basic thing also explains simple and complex sentence in these languages. This suggests that the solution is not just ad hoc but has a deeper underlying unity. This methodology could be extended to other free word order languages. Since the frame designed for meaning representation is general, they are adaptable to other languages coming in this group and to other applications.

Permutation Entropy Based Analysis of Complex Signals for Characterising Change in System Dynamics

Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

Analysis of System Signals Based on Cross Recurrence Method for System Dynamics Characterization

Natural systems are inherently non linear. Recurrent behaviours are typical of natural systems. Recurrence is a fundamental property of non linear dynamical systems which can be exploited to characterize the system behaviour effectively. Cross recurrence based analysis of sensor signals from non linear dynamical system is presented in this thesis. The mutual dependency among relatively independent components of a system is referred as coupling. The analysis is done for a mechanically coupled system specifically designed for conducting experiment. Further, cross recurrence method is extended to the actual machining process in a lathe to characterize the chatter during turning. The result is verified by permutation entropy method. Conventional linear methods or models are incapable of capturing the critical and strange behaviours associated with the dynamical process. Hence any effective feature extraction methodologies should invariably gather information thorough nonlinear time series analysis. The sensor signals from the dynamical system normally contain noise and non stationarity. In an effort to get over these two issues to the maximum possible extent, this work adopts the cross recurrence quantification analysis (CRQA) methodology since it is found to be robust against noise and stationarity in the signals. The study reveals that the CRQA is capable of characterizing even weak coupling among system signals. It also divulges the dependence of certain CRQA variables like percent determinism, percent recurrence and entropy to chatter unambiguously. The surrogate data test shows that the results obtained by CRQA are the true properties of the temporal evolution of the dynamics and contain a degree of deterministic structure. The results are verified using permutation entropy (PE) to detect the onset of chatter from the time series. The present study ascertains that this CRP based methodology is capable of recognizing the transition from regular cutting to the chatter cutting irrespective of the machining parameters or work piece material. The results establish this methodology to be feasible for detection of chatter in metal cutting operation in a lathe.