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Turner, Lauren. "Helquist's and Snicket's all-seeing eyes panopticism and the archive in A series of unfortunate events /." [Gainesville, Fla.] : University of Florida, 2006. http://purl.fcla.edu/fcla/etd/UFE0014120.
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Barton, Julie Anastasia. "From The bad beginning to an elusive End : knowledge and power in Lemony Snicket's A series of unfortunate events." Thesis, University of East Anglia, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.580565.
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My thesis analyzes A Series of Unfortunate Events by Lemony Snicket (pseudonym of Daniel Handler), a popular children's book series published between 1999 and 2006. I argue that this series challenges and ultimately subverts the traditional hierarchical power relations evident in the dynamic between the adult author and the child reader. As Maria Nikolajeva argues, "nowhere else are power structures as visible as in children's literature, the refined instrument used for centuries to educate, socialize and oppress a particular social group" (2010, 9). The power play between adults and children, between authors and readers, can be seen as an essential defining characteristic of children's literature, and my thesis asserts that this power play is often enacted in terms of knowledge. I argue that this bestselling thirteen-book series provides a distinctive approach to the role of offering knowledge to a child reader, as Daniel Handler ultimately transcends the typical power hierarchy where an adult must' give' or 'grant' knowledge (of any kind) to a child reader. Instead, he uses what I have termed "metateaching" to teach the child reader how to teach herself, thereby dispensing with the need for an adult authority figure. I begin by examining Handler's use of traditional narratological tropes before moving on to the numerous ways in which he subverts them. Handler utilizes a complex form when writing A Series of Unfortunate Events, invoking strategies allied to postmodernism, such as metafictionality and intertextuality, and he complicates the conventional children's literature reader/author relationship by introducing a didactic yet ultimately unreliable narrator in Lemony Snicket.
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Starzecki, Caroline. ""Τhe Wοrld Ιs Quiet Ηere" : La Figure de l'enfant déraciné dans A Series οf Unfοrtunate Events (1999-2006) de Lemοny Snicket." Electronic Thesis or Diss., Normandie, 2024. http://www.theses.fr/2024NORMR097.
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Ce travail étudie, par le biais de la notion de déracinement, l’ensemble littéraire A Series of Unfortunate Events (Les Désastreuses aventures des orphelins Baudelaire, 1999-2006) de l’écrivain américain Daniel Handler, plus connu sous le nom de plume de Lemony Snicket. Dans son sens propre, le déracinement désigne le caractère contraint du déplacement d’un individu loin de son foyer. Même si cet exil est souvent lié aux récits de migration et de guerre, il est également utilisé dans toute oeuvre de jeunesse qui aborde la dépossession physique et psychologique pour métaphoriser le passage de l’enfance à l’adolescence, voire l’âge adulte. Notre étude explore les causes et les conséquences tant pernicieuses que libératrices de cette notion protéiforme dont font l’expérience les trois protagonistes, Violet, Klaus et Sunny Baudelaire. L’arrachage au noyau familial, ainsi que les placements répétés en familles d’accueil, témoignent de l’incapacité des individus et de la société génératrice de violences systémiques à gérer le traumatisme d’orphelin·e·s. Cette expérience aliénante est toutefois reconfigurée à mesure que l’oeuvre devient un cycle, que les protagonistes entament leur (en)quête éclaircissant leur histoire paternelle et personnelle, et que la question de la moralité est abordée. Déployée à l’échelle de l’oeuvre entière, la notion peut être considérée comme un rhizome, au sens infini et dédaléen. Ainsi, la métaphore du déracinement est celle de la transition, difficile mais inévitable. L’analyse de la figure de l’enfant déraciné repose sur les expériences des trois personnages et sur la construction du lectorat, sans cesse déstabilisées par l’auteur-narrateur postmoderne Le jeune lectorat évolue avec les Baudelaire afin de (re)créer des liens et des racines, tant textuels que réels, et à (re)prendre sa place dans le mondeThis study uses the notion of displacement, or uprooting, to study the literary cycle A Series of Unfortunate Events (1999-2006) by American writer Daniel Handler, better known as Lemony Snicket. An individual is displaced when he or she is forced to move away from his or her home(land). Although this specific type of exile is often linked with immigration and war literature, we argue that the notion may be used in any children’s book that deals with physical and psychological dispossession to symbolise the passage from childhood to adolescence, and eventually adulthood. Thematically, Violet, Klaus and Sunny Baudelaire experience uprootedness, and we shall explore the destructive yet emancipating causes and consequences of this Protean notion. The displacement from the family nucleus, as well as the multiple foster care placements they endure, testify to both individual and systemic inability to deal with traumatised orphans. Nonetheless, the books gradually reconfigure this alienating experience, as the series becomes a cycle, as the protagonists embark on their quest, investigate their history, and as moral questions arise. It becomes clear that uprootedness must be considered as a rhizome, with interconnected and infinite layers of meanings. The metaphor of uprootedness becomes that of the transition between childhood and adolescence as one that is difficult yet unstoppable. The study of the figure of the displaced child is concerned not only with the characters’ experiences, but also with the readership’s, who is encouraged to evolve alongside the three Baudelaire children in order to create new roots, both in a textual and real sense, and to (re)claim his/her place in the world
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Sääf, Ida. ""In my experience well-read people are less likely to be evil" : En studie om intertextualitet och kulturellt kapital i Lemony Snickets A series of unfortunare events." Thesis, Stockholms universitet, Institutionen för kultur och estetik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-166066.
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Syftet med studien har varit att se vilka funktioner intertextualiteten i Lemony Snickets serie A series of unfortunate events har och vad författaren uppnår med den. Studien studerar seriens intertextualitet på olika nivåer som bär olika funktioner. Med hjälp av Pierre Bourdieus teori om kulturellt kapital, Aleida Assmanns teori om kulturellt minne och Harold Blooms tankar kring den västerländska kanon diskuteras intertextualitetens nivåer och dess betydelser. Av dessa intertexter kan kulturellt kapital läsas samt en tro om den goda litteraturen och den goda läsningen. Studien lyfter fram Snickets verk som en serie som förhåller sig till barnlitterära traditioner i sin form men använder sig av vuxenlitteraturens referenser för att förhöja statusen av serien såväl som barnboken.
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Stoecker-Sylvia, Zachary. "Mining for frequent events in time series." Link to electronic thesis, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0902104-163011/.
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Hallerberg, Sarah. "Predictability of extreme events in time series." kostenfrei, 2008. http://elpub.bib.uni-wuppertal.de/edocs/dokumente/fbc/physik/diss2008/hallerberg.
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Owsley, Lane M. D. "Classification of transient events in time series /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/5989.
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Santos, Rui Pedro Silvestre dos. "Time series morphological analysis applied to biomedical signals events detection." Master's thesis, Faculdade de Ciências e Tecnologia, 2011. http://hdl.handle.net/10362/10227.
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Dissertation submitted in the fufillment of the requirements for the Degree of Master in Biomedical EngineeringAutomated techniques for biosignal data acquisition and analysis have become increasingly powerful, particularly at the Biomedical Engineering research field. Nevertheless, it is verified the need to improve tools for signal pattern recognition and classification systems, in which the detection of specific events and the automatic signal segmentation are preliminary processing steps. The present dissertation introduces a signal-independent algorithm, which detects significant events in a biosignal. From a time series morphological analysis, the algorithm computes the instants when the most significant standard deviation discontinuities occur, segmenting the signal. An iterative optimization step is then applied. This assures that a minimal error is achieved when modeling these segments with polynomial regressions. The adjustment of a scale factor gives different detail levels of events detection. An accurate and objective algorithm performance evaluation procedure was designed. When applied on a set of synthetic signals, with known and quantitatively predefined events, an overall mean error of 20 samples between the detected and the actual events showed the high accuracy of the proposed algorithm. Its ability to perform the detection of signal activation onsets and transient waveshapes was also assessed, resulting in higher reliability than signal-specific standard methods. Some case studies, with signal processing requirements for which the developed algorithm can be suitably applied, were approached. The algorithm implementation in real-time, as part of an application developed during this research work, is also reported. The proposed algorithm detects significant signal events with accuracy and significant noise immunity. Its versatile design allows the application in different signals without previous knowledge on their statistical properties or specific preprocessing steps. It also brings added objectivity when compared with the exhaustive and time-consuming examiner analysis. The tool introduced in this dissertation represents a relevant contribution in events detection, a particularly important issue within the wide digital biosignal processing research field.
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Dolphin, Maureen Anne Margaret. "The effects of policy events on quota values, a time series analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ34352.pdf.
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Eriksson, Therése, and Abdelnaeim Mohamed Mahmoud. "Waveform clustering - Grouping similar power system events." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-44147.
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Over the last decade, data has become a highly valuable resource. Electrical power grids deal with large quantities of data, and continuously collect this for analytical purposes. Anomalies that occur within this data is important to identify since they could cause nonoptimal performance within the substations, or in worse cases damage to the substations themselves. However, large datasets in the order of millions are hard or even impossible to gain a reasonable overview of the data manually. When collecting data from electrical power grids, predefined triggering criteria are often used to indicate that an event has occurred within the specific system. This makes it difficult to search for events that are unknown to the operator of the deployed acquisition system. Clustering, an unsupervised machine learning method, can be utilised for fault prediction within systems generating large amounts of multivariate time-series data without labels and can group data more efficiently and without the bias of a human operator. A large number of clustering techniques exist, as well as methods for extracting information from the data itself, and identification of these was of utmost importance. This thesis work presents a study of the methods involved in the creation of such a clustering system which is suitable for the specific type of data. The objective of the study was to identify methods that enables finding the underlying structures of the data and cluster the data based on these. The signals were split into multiple frequency sub-bands and from these features could be extracted and evaluated. Using suitable combinations of features the data was clustered with two different clustering algorithms, CLARA and CLARANS, and evaluated with established quality analysis methods. The results indicate that CLARA performed overall best on all the tested feature sets. The formed clusters hold valuable information such as indications of unknown events within the system, and if similar events are clustered together this can assist a human operator further to investigate the importance of the clusters themselves. A further conclusion from the results is that research into the use of more optimised clustering algorithms is necessary so that expansion into larger datasets can be considered.
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Rydell, Sofia. "The use of extreme value theory and time series analysis to estimate risk measures for extreme events." Thesis, Umeå universitet, Institutionen för fysik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-70291.
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In this thesis the main purpose is to use extreme value theory and time series analysis to find modelsfor estimating the two risk measures for potential losses, value at risk and expected shortfall. Focus ison the time horizon needed to obtain predictions that are consistent with the actual outcome of anasset or a portfolio of assets. The extreme value based methods used are the Hill estimator and the peak over threshold method.The Hill estimator is also combined with a time series model. The time series model used is an AR(1)-GARCH(1,1) model. For extreme value theory based models the choice of threshold between the observations belongingto the tail and the observations belonging to the center of the distribution is crucial. In this study thethreshold is set to be 10% of the sample size, by conventional choice. There are additional methodsof choosing the threshold and some of them are presented in this paper. For each models different length of historical data is used when predictions of the risk measures aremade for different assets. The main result is that the best model and appropriate time horizon ofhistorical data to use for estimating value at risk and expected shortfall differs from dataset todataset. However, the methods that combine extreme value theory and time series models are themost flexible ones and those are the ones most likely to capture extreme events. The conditional Hillmethods with shorter time horizons seem preferable when estimating the risk measures for indices,while the Hill estimator with time horizon of three or four years is preferable for foreign exchangerates. In this study only models for single assets are evaluated, but the models could easily beimplemented on a time series of a portfolio. A multivariate case of the extreme value theory existsbut its complexity makes it disadvantageously to implement. So if for example the univariateextreme value models alone are considered inadequate to capture all the relations in a portfolio themodels could be used as a complement to the commonly used model based solely on historicalsimulation and thereby improve the risk analysis.
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Qi, Jing. "Application of Intervention Analysis to Evaluate the Impacts of Special Events on Freeways." FIU Digital Commons, 2008. http://digitalcommons.fiu.edu/etd/71.
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In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.
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Halla, Martin, Julia Schmieder, and Andrea Weber. "Job Displacement, Family Dynamics and Spousal Labor Supply, Discussion Paper Series." IZA - Institute of Labor Economics, 2018. http://epub.wu.ac.at/6509/1/dp11752.pdf.
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We study interdependencies in spousal labor supply and the effectiveness of intrahousehold insurance in a sample of married couples, where the husband loses his job due to a mass layoff or plant closure using data from the Austrian Social Security Database. We show that in our sample of relatively young couples the shock hits households at crucial stages of family formation, which requires careful modeling of the wives' counterfactual lifecycle labor market patterns. In our empirical analysis, we propose three independent control groups of unaffected households to identify the causal effects of husbands' displacement
on wives' labor supply. Our empirical results show that husbands suffer large and persistent employment and earnings losses over the first 5 years after displacement. But wives' labor supply increases only moderately and they respond predominantly at the extensive margin. The implied participation elasticity with respect to the husband's earnings shock is very small, about -0:04. While the wives' earnings gains recover only a tiny fraction of the household income loss, public transfers and taxes are a more important insurance at least
in the short run. In terms of non-labor market related outcomes, we find a small positive effect on the probability of divorce, but no effect of the husband's job displacement on fertility. The presence and ages of children in the household are crucial determinants of the wife's labor supply response. The most responsive group are mothers, who are planning to return to the labor market after a maternity break, while mothers of very young children or wives without children remain unresponsive. We thus conclude that Austria's strong gender identity norms are an explanation for the limited scope of intra-household insurance.
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Zhakiya, Elezhan. "Unsupervised machine learning and k-Means clustering as a way of discovering anomalous events In continuous seismic time series." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117323.
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Thesis: S.M., Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences, 2018.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 51-52).
Unsupervised k-Means clustering was implemented as a method for identifying anomalies in seismic time series. Sliding window approach was used for generating specific subsequences from the overall waveform. Dynamic Time Warping (DTW) was used as the method for comparing seismic subsequences. DTW barycenter averaging (DBA) was used as the method for averaging multiple subsequences within a group of similiar shapes. Clustering is able to discover anomalously shaped parts of a seismic time series in a completely unsupervised fashion, without requiring anyone to input actual times of the events, any predetermiend examples of events, or any other parameters about the signal.
by Elezhan Zhakiya.
S.M.
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Biswas, Debashis. "An Algorithm for Mining Adverse-Event Datasets for Detection of Post Safety Concern of a Drug." Scholarly Repository, 2010. http://scholarlyrepository.miami.edu/oa_theses/17.
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Signal detection from Adverse Event Reports (AERs) is important for identifying and analysing drug safety concern after a drug has been released into the market. A safety signal is defined as a possible causal relation between an adverse event and a drug. There are a number of safety signal detection algorithms available for detecting drug safety concern. They compare the ratio of observed count to expected count to find instances of disproportionate reportings of an event for a drug or combination of events for a drug. In this thesis, we present an algorithm to mine the AERs to identify drugs which show sudden and large changes in patterns of reporting of adverse events. Unlike other algorithms, the proposed algorithm creates time series for each drug and use it to identify start of a potential safety problem. A novel vectorized timeseries utilizing multiple attributes has been proposed here. First a time series with a small time period was created; then to remove local variations of the number of reports in a time period, a time-window based averaging was done. This method helped to keep a relatively long time-series, but eliminated local variations. The steps in the algorithm include partitioning the counts on attribute values, creating a vector out of the partitioned counts for each time period, use of a sliding time window, normalizing the vectors and computing vector differences to find the changes in reporting over time. Weights have been assigned to attributes to highlight changes in the more significant attributes. The algorithm was tested with Adverse Event Reporting System (AERS) datasets from Food and Drug Administation (FDA). From AERS datasets the proposed algorithm identified five drugs that may have safety concern. After searching literature and the Internet it was found that the five drugs the algorithm identified, two were recalled, one was suspended, one had to undergo label change and the other one has a lawsuit pending against it.
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Hawken, Steven. "Methodological Approaches to Studying Risk Factors for Adverse Events Following Routine Vaccinations in the General Population and Vulnerable Subgroups of Individuals Using Health Administrative Data." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31774.
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Objectives: This thesis included 6 manuscripts which focused on the analysis of adverse events following immunization (AEFIs), including general health services utilization (emergency room (ER) visits and hospital admissions) and specific diagnoses (e.g. febrile convulsions). The main objectives of this research were: 1) To demonstrate the utility of the self-controlled case series (SCCS) design coupled with health administrative data for studying the safety of vaccines; 2) Introducing an innovative approach using relative incidence ratios (RIRs) within an SCCS analysis to identify risk factors for AEFIs and to overcome the healthy vaccinee bias; and 3) To demonstrate how SCCS and RIR analyses of health services outcomes in health administrative data can provide important insights into underlying physiological and behavioural mechanisms.
Data Sources: This work utilized Ontario health administrative data housed at the Institute for Clinical Evaluative Sciences (ICES). The study included all children born in Ontario, Canada between 2002 and 2011 (over 1 million children). Vaccinations were identified using OHIP fee for service billing codes for general vaccination. Admissions and ER visits for any reason were identified in the Discharge Abstract Database (DAD) and National Ambulatory Care Reporting System (NACRS). Primary reasons for admissions and ER visits were investigated using ICD-10-CA codes reported in the DAD and NACRS databases.
Statistical Methods: The self-controlled case series design (SCCS) was used to calculate the relative incidence of admissions, ER visits and other AEFIs. To investigate relative incidence for AEFIs across risk groups of interest, as well as addressing the healthy vaccinee effect bias, RIRs were calculated. RIRs are the ratio of incidence ratios in a subgroup of interest relative to a designated reference group.
Results and Conclusions: The combined approach of using the SCCS design and RIRs to identify risk factors and overcome the healthy vaccinee bias proved to be a powerful approach to studying vaccine safety. Future work will be important to characterize the performance and validity of the SCCS + RIR approach in the presence of increasing levels of confounding and differing manifestations of the healthy vaccinee bias, as well as to elucidate the biological and behavioural mechanisms underlying our findings.
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Zelenka, Jaroslav. "Vliv externích událostí na hodnotu tržní kapitalizace společnosti." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-114318.
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This diploma thesis analyses the relationship between external events (i.e. events with impact within the Czech Republic which cannot be influenced by local firms) and the value of market capitalization of companies on Prague Stock Exchange. The analysis of the 1994 to 2012 time series showed that even the most important political, economical and other events specific for the Czech Republic only have marginal impacts on values of companies on the Czech stock market. The impacts of corporate events proved to have much stronger such effects. The most advisable investment recommendation thus seems to be to ignore external events when deciding in which stocks to invest.
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Procházka, Jan. "Vliv domácích a zahraničních ekonomických událostí na sledovanost českého televizního zpravodajství." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-193008.
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This work represents the research of television audience of news programs in Czech Republic during the years 2008 to 2013 in order to capture the possible preference for specific viewers areas of economic events, or information. For the needs of econometric time-series analysis is assembled basic model, which is individually applied to a total of five time series of news programs. Econometric estimates suggest that key events increasing viewership of Czech news programs are riots and demonstrations in the territory of Czech Republic, with a positive effect on the ratings of up to 4.1%, or home catastrophic events that increase viewership up by 4.6%. The world macroeconomic events showed the negative effect of up to 2.4% for viewership of television news.
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Pham, Khoi Minh. "NEURAL NETWORK ON VIRTUALIZATION SYSTEM, AS A WAY TO MANAGE FAILURE EVENTS OCCURRENCE ON CLOUD COMPUTING." CSUSB ScholarWorks, 2018. https://scholarworks.lib.csusb.edu/etd/670.
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Cloud computing is one important direction of current advanced technology trends, which is dominating the industry in many aspects. These days Cloud computing has become an intense battlefield of many big technology companies, whoever can win this war can have a very high potential to rule the next generation of technologies. From a technical point of view, Cloud computing is classified into three different categories, each can provide different crucial services to users: Infrastructure (Hardware) as a Service (IaaS), Software as a Service (SaaS), and Platform as a Service (PaaS). Normally, the standard measurements for cloud computing reliability level is based on two approaches: Service Level Agreements (SLAs) and Quality of Service (QoS). This thesis will focus on IaaS cloud systems’ Error Event Logs as an aspect of QoS in IaaS cloud reliability. To have a better view, basically, IaaS is a derivation of the traditional virtualization system where multiple virtual machines (VMs) with different Operating System (OS) platforms, are run solely on one physical machine (PM) that has enough computational power. The PM will play the role of the host machine in cloud computing, and the VMs will play the role as the guest machines in cloud computing. Due to the lack of fully access to the complete real cloud system, this thesis will investigate the technical reliability level of IaaS cloud through simulated virtualization system. By collecting and analyzing the event logs generated from the virtualization system, we can have a general overview of the system’s technical reliability level based on number of error events occur in the system. Then, these events will be used on neural network time series model to detect the system failure events’ pattern, as well as predict the next error event that is going to occur in the virtualization system.
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Ghawi, Christina. "Forecasting Volume of Sales During the Abnormal Time Period of COVID-19. An Investigation on How to Forecast, Where the Classical ARIMA Family of Models Fail." Thesis, KTH, Matematisk statistik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302396.
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During the COVID-19 pandemic, customer shopping habits have changed. Some industries experienced an abrupt shift during the pandemic outbreak while others navigate in new normal states. For some merchants, the highly-uncertain new phenomena of COVID-19 expresses as outliers in time series of volume of sales. As forecasting models tend to replicate past behavior of a series, outliers complicates the procedure of forecasting; the abnormal events tend to unreliably replicate in forecasts of the subsequent year(s). In this thesis, we investigate how to forecast volume of sales during the abnormal time period of COVID-19, where the classical ARIMA family of models produce unreliable forecasts. The research revolved around three time series exhibiting three types of outliers: a level shift, a transient change and an additive outlier. Upon detecting the time period of the abnormal behavior in each series, two experiments were carried out as attempts for increasing the predictive accuracy for the three extreme cases. The first experiment was related to imputing the abnormal data in the series and the second was related to using a combined model of a pre-pandemic and a post-abnormal forecast. The results of the experiments pointed at significant improvement of the mean absolute percentage error at significance level alpha=0.05 for the level shift when using a combined model compared to the pre-pandemic best-fit SARIMA model. Also, at significant improvement for the additive outlier when using a linear impute. For the transient change, the results pointed at no significant improvement in the predictive accuracy of the experimental models compared to the pre-pandemic best-fit SARIMA model. For the purpose of generalizing to large-scale conclusions of methods' superiority or feasibility for particular abnormal behaviors, empirical evaluations are required. The proposed experimental models were discussed in terms of reliability, validity and quality. By residual diagnostics, it was argued that the models were valid; however, that further improvements can be made. Also, it was argued that the models fulfilled desired attributes of simplicity, scaleability and flexibility. Due to the uncertain phenomena of the COVID-19 pandemic, it was suggested not to take the outputs as long-term reliable solutions. Rather, as temporary solutions requiring more frequent updating of forecasts.Under coronapandemin har kundbeteenden och köpvanor förändrats. I vissa branscher upplevdes ett plötsligt skifte vid pandemiutbrottet och i andra navigerar handlare i nya normaltillstånd. För vissa handlare är förändringarna så pass distinkta att de yttrar sig som avvikelser i tidsserier över försäljningsvolym. Dessa avvikelser komplicerar prognosering. Då prognosmodeller tenderar att replikera tidsseriers tidigare beteenden, tenderas det avvikande beteendet att replikeras i försäljningsprognoser för nästkommande år. I detta examensarbete ämnar vi att undersöka tillvägagångssätt för att estimera försäljningsprognoser under den abnorma tidsperioden av COVID-19, då klassiska tidsseriemodeller felprognoserar. Detta arbete kretsade kring tre tidsserier som uttryckte tre avvikelsertyper: en nivåförskjutning, en övergående förändring och en additiv avvikelse. Efter att ha definierat en specifik tidsperiod relaterat till det abnorma beteendet i varje tidsserie, utfördes två experiment med syftet att öka den prediktiva noggrannheten för de tre extremfallen. Det första experimentet handlade om att ersätta den abnorma datan i varje serie och det andra experimentet handlade om att använda en kombinerad pronosmodell av två estimerade prognoser, en pre-pandemisk och en post-abnorm. Resultaten av experimenten pekade på signifikant förbättring av ett absolut procentuellt genomsnittsfel för nivåförskjutningen vid användande av den kombinerade modellen, i jämförelse med den pre-pandemiskt bäst passande SARIMA-modellen. Även, signifikant förbättring för den additiva avvikelsen vid ersättning av abnorm data till ett motsvarande linjärt polynom. För den övergående förändringen pekade resultaten inte på en signifikant förbättring vid användande av de experimentella modellerna. För att generalisera till storskaliga slutsatser giltiga för specifika avvikande beteenden krävs empirisk utvärdering. De föreslagna modellerna diskuterades utifrån tillförlitlighet, validitet och kvalitet. Modellerna uppfyllde önskvärda kvalitativa attribut såsom enkelhet, skalbarhet och flexibilitet. På grund av hög osäkerhet i den nuvarande abnorma tidsperioden av coronapandemin, föreslogs det att inte se prognoserna som långsiktigt pålitliga lösningar, utan snarare som tillfälliga tillvägagångssätt som regelbundet kräver om-prognosering.
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Marchini, Ben. "Festivals and sustainability : reducing energy related greenhouse gas emissions at music festivals." Thesis, De Montfort University, 2013. http://hdl.handle.net/2086/8840.
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This thesis investigates the potential to reduce greenhouse gas emissions relating to electrical power provision at UK music festivals. It has been carried out in partnership with a number of UK festival organisers and power providers. The thesis provides a literature review of sustainable event management and the associated electrical power provision, before then investigating the existing methodologies for quantifying greenhouse gas emissions at festivals. This review identified a lack of data regarding energy demand at events other than total fuel demand. While energy data does not improve the accuracy of GHG accounting, it provides more detail which can identify opportunities to reduce these emissions. Data was gathered from 73 power systems at 18 music festivals from 2009-2012. This produced typical festival power load profiles for different system types including stages, traders and site infrastructure. These load profiles were characterised using a series of indicators that can create performance benchmarks, in addition to increasing the detail of carbon auditing. Analysis of the load profiles identifies opportunities for emission reduction. These address either the supply or demand for power in order to reduce on site fuel consumption. These opportunities include changes in operating procedure to reduce demand during non-operational periods, utilising low energy equipment on stages, and using a power provision system capable of adjusting power plant supply to meet demand. The work has documented power demand at festivals, and highlighted opportunities for change that can reduce costs and emissions, as well as informing festivals on their practices.
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Monthuy-Blanc, Johana. "Fonctionnement du concept de soi : facteur prévisionnel des symptômes anorexiques." Thèse, Université de Sherbrooke, 2009. http://savoirs.usherbrooke.ca/handle/11143/949.
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This doctoral dissertation examine the specific role of the self-concept and of its different dimensions on the evolution of anorexic symptoms over a period of 140 consecutive days. in two different samples comprising 26 anorexic outpatients and inpatients and in 23 girls without eating disorders (ED). By applying an idiographic approach, the main results show that the level, instability and dynamic of self-concept dimensions, and more precisely of body attractiveness, represent potent predictors of psychological, behavioral (e.g. full score of Eating Disorders Inventory-Adolescent, EDI-A-24) and somatic (e.g. Body Mass Index, BMI) anorexic symptoms over medium (i.e. over a few months), short (i.e. over a few weeks) and very short (i.e. over a few days) periods of time. Moreover, multivariate regression analyses further show that the pattern of association between anorexic symptoms and self concept dimensions remains the same in both samples (anorexic and without ED). Moreover, the results of cross-correlations analyses reveal that anorexic symptoms are as unstable as the dimensions of self-concept, with which they appear to be intertwined. More precisely, body attractiveness, most often a) precedes the drive for thinness, b) is associated to bulimia according to a"vicious circle" phenomenon, and c) fluctuates with according to body dissatisfaction. However body attractiveness was not found to relate to anorexic girls final status at the end of the follow-up period (e.g. deterioration, improvement, stabilization, etc). Finally, the results from a qualitative analysis suggest that social events experienced as positive contribute to the improvement of anorexia nervosa.This appears to be explained by the potential of these events to break through anorectic girls known ego-centered tendencies. Taken as a whole, the 'results highlight the necessity of considering overall of dimensions of self-esteem and the"profiles" of girls with and without ED in preventive and therapeutic interventions for ED.
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Malik, Nishant. "Extremes in events and dynamics : a nonlinear data analysis perspective on the past and present dynamics of the Indian summer monsoon." Phd thesis, Universität Potsdam, 2011. http://opus.kobv.de/ubp/volltexte/2012/5801/.
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To identify extreme changes in the dynamics of the Indian Summer Monsoon (ISM) in the past, I propose a new approach based on the quantification of fluctuations of a nonlinear similarity measure, to identify regimes of distinct dynamical complexity in short time series. I provide an analytical derivation for the relationship of the new measure with the dynamical invariants such as dimension and Lyapunov exponents of the underlying system. A statistical test is also developed to estimate the significance of the identified transitions. Our method is justified by uncovering bifurcation structures in several paradigmatic models, providing more complex transitions compared with traditional Lyapunov exponents. In a real world situation, we apply the method to identify millennial-scale dynamical transitions in Pleistocene proxy records of the south Asian summer monsoon system. We infer that many of these transitions are induced by the external forcing of solar insolation and are also affected by internal forcing on Monsoonal dynamics, i.e., the glaciation cycles of the Northern Hemisphere and the onset of the tropical Walker circulation. Although this new method has general applicability, it is particularly useful in analysing short palaeo-climate records.
Rainfall during the ISM over the Indian subcontinent occurs in form of enormously complex spatiotemporal patterns due to the underlying dynamics of atmospheric circulation and varying topography. I present a detailed analysis of summer monsoon rainfall over the Indian peninsular using Event Synchronization (ES), a measure of nonlinear correlation for point processes such as rainfall. First, using hierarchical clustering I identify principle regions where the dynamics of monsoonal rainfall is more coherent or homogenous. I also provide a method to reconstruct the time delay patterns of rain events. Moreover, further analysis is carried out employing the tools of complex network theory. This study provides valuable insights into the spatial organization, scales, and structure of the 90th and 94th percentile rainfall events during the ISM (June to September). I furthermore analyse the influence of different critical synoptic atmospheric systems and the impact of the steep Himalayan topography on rainfall patterns. The presented method not only helps in visualising the structure of the extremeevent rainfall fields, but also identifies the water vapor pathways and decadal-scale moisture sinks over the region. Furthermore a simple scheme based on complex networks is presented to decipher the spatial intricacies and temporal evolution of monsoonal rainfall patterns over the last six decades. Some supplementary results on the evolution of monsoonal rainfall extremes over the last sixty years are also presented.Um Extremereignisse in der Dynamik des indischen Sommermonsuns (ISM) in der geologischen Vergangenheit zu identifizieren, schlage ich einen neuartigen Ansatz basierend auf der Quantifikation von Fluktuationen in einem nichtlinearen Ähnlichkeitsmaß vor. Dieser reagiert empfindlich auf Zeitabschnitte mit deutlichen Veränderungen in der dynamischen Komplexität kurzer Zeitreihen. Ein mathematischer Zusammenhang zwischen dem neuen Maß und dynamischen Invarianten des zugrundeliegenden Systems wie fraktalen Dimensionen und Lyapunovexponenten wird analytisch hergeleitet. Weiterhin entwickle ich einen statistischen Test zur Schätzung der Signifikanz der so identifizierten dynamischen Übergänge. Die Stärken der Methode werden durch die Aufdeckung von Bifurkationsstrukturen in paradigmatischen Modellsystemen nachgewiesen, wobei im Vergleich zu den traditionellen Lyapunovexponenten eine Identifikation komplexerer dynamischer Übergänge möglich ist. Wir wenden die neu entwickelte Methode zur Analyse realer Messdaten an, um ausgeprägte dynamische Veränderungen auf Zeitskalen von Jahrtausenden in Klimaproxydaten des südasiatischen Sommermonsunsystems während des Pleistozäns aufzuspüren. Dabei zeigt sich, dass viele dieser Übergänge durch den externen Einfluss der veränderlichen Sonneneinstrahlung, sowie durch dem Klimasystem interne Einflussfaktoren auf das Monsunsystem (Eiszeitzyklen der nördlichen Hemisphäre und Einsatz der tropischenWalkerzirkulation) induziert werden. Trotz seiner Anwendbarkeit auf allgemeine Zeitreihen ist der diskutierte Ansatz besonders zur Untersuchung von kurzen Paläoklimazeitreihen geeignet. Die während des ISM über dem indischen Subkontinent fallenden Niederschläge treten, bedingt durch die zugrundeliegende Dynamik der atmosphärischen Zirkulation und topographische Einflüsse, in äußerst komplexen, raumzeitlichen Mustern auf. Ich stelle eine detaillierte Analyse der Sommermonsunniederschläge über der indischen Halbinsel vor, die auf Ereignissynchronisation (ES) beruht, einem Maß für die nichtlineare Korrelation von Punktprozessen wie Niederschlagsereignissen. Mit hierarchischen Clusteringalgorithmen identifiziere ich zunächst Regionen mit besonders kohärenten oder homogenen Monsunniederschlägen. Dabei können auch die Zeitverzögerungsmuster von Regenereignissen rekonstruiert werden. Darüber hinaus führe ich weitere Analysen auf Basis der Theorie komplexer Netzwerke durch. Diese Studien ermöglichen wertvolle Einsichten in räumliche Organisation, Skalen und Strukturen von starken Niederschlagsereignissen oberhalb der 90% und 94% Perzentilen während des ISM (Juni bis September). Weiterhin untersuche ich den Einfluss von verschiedenen, kritischen synoptischen Systemen der Atmosphäre sowie der steilen Topographie des Himalayas auf diese Niederschlagsmuster. Die vorgestellte Methode ist nicht nur geeignet, die Struktur extremer Niederschlagsereignisse zu visualisieren, sondern kann darüber hinaus über der Region atmosphärische Transportwege von Wasserdampf und Feuchtigkeitssenken auf dekadischen Skalen identifizieren.Weiterhin wird ein einfaches, auf komplexen Netzwerken basierendes Verfahren zur Entschlüsselung der räumlichen Feinstruktur und Zeitentwicklung von Monsunniederschlagsextremen während der vergangenen 60 Jahre vorgestellt.
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Beeferman, Leah. "JOURNEYS INTO THE UNKNOWN: A SERIES OF SCIENCE ARCHITECTURE TASKS AND EVENTS, SPACE-BOUND EXPLORATIONS AND FAR-TRAVELS, DISCOVERIES AND MISSES (NEAR AND FAR), IMAGINATIVE SPACE-GAZING AND RELATED INVESTIGATIONS, OBSERVATIONS, ORBITS, AND OTHER REPETITIOUS MONITORING TASKS." VCU Scholars Compass, 2010. http://scholarscompass.vcu.edu/etd/2164.
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This thesis expansively and inclusively puts forth the imaginings, research, processes and experiences behind my two thesis exhibitions, "Journeys into the unknown: a series of science architecture tasks and events, space-bound explorations and far-travels, discoveries and misses (near and far), imaginative space-gazing and related investigations, observations, orbits, and other repetitious monitoring tasks" and "Timed travel: asystematic accounts of regular and geometrical timekeeping, orbital flight, repetitive rotations and other journeys into actual time and slow space." It begins with an abstract interpretation of the dial: a tool not limited to scientific measurement but, instead, a gauge of an object’s overall position and general status. Equal parts scientific information, abstracted and fictionalized instruments and facts, and the personal experiences which provided these concrete informational elements with psychological and metaphorical meaning, this document is as much a record of time as it is an elucidation of my artistic practice and methodology.
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Birkholz, Simon. "Determinism and predictability in extreme event systems." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät, 2016. http://dx.doi.org/10.18452/17495.
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In den vergangenen Jahrzehnten wurden extreme Ereignisse, die nicht durch Gauß-Verteilungen beschrieben werden können, in einer Vielzahl an physikalischen Systemen beobachtet. Während statistische Methoden eine zuverlässige Identifikation von extremen Ereignissen ermöglichen, ist deren Entstehungsmechanismus nicht vollständig geklärt. Das Auftreten von extremen Ereignissen ist nicht vollkommen verstanden, da sie nur selten beobachtet werden können und häufig unter schwer reproduzierbaren Bedingungen auftreten. Deshalb ist es erstrebenswert Experimente zu entwickeln, die eine einfache Beobachtung von extremen Ereignissen erlauben. In dieser Dissertation werden extreme Ereignisse untersucht, die bei Multi-Filamentation von Femtosekundenlaserimpulsen entstehen. In den Experimenten, die in dieser Dissertation vorgestellt werden, werden Multi-Filamente durch Hochgeschwindigkeitskameras analysiert. Die Untersuchung der raum-zeitlichen Dynamik der Multi-Filamente zeigt eine L-förmige Wahrscheinlichkeitsverteilung, Diese Beobachtung impliziert das Auftreten von extremen Ereignissen. Lineare Analyse liefert Hinweise auf die physikalischen Prozesse, die zur Entstehung der extremen Ereignisse führen und nicht-lineare Zeitreihen-Analyse charakterisiert die Dynamik des Systems. Die Analyse der Multi-Filamente wird außerdem auf extreme Ereignisse in Wellen-Messungen und optische Superkontinua angewandt. Die durchgeführten Analysen zeigen Unterschiede in den physikalischen Prozessen, die zur Entstehung von extremen Ereignissen führen. Extreme Ereignisse in optischen Fasern werden durch stochastische Fluktuationen von verstärktem Quantenrauschen dominiert. In Multi-Filamenten und Ozeanwellen resultieren extreme Ereignisse dagegen aus klassischer mechanischer Turbulenz, was deren Vorhersagbarkeit impliziert. In dieser Arbeit wird anhand der von Multi-Filament-Zeitreihen die Vorhersagbarkeit in einem kurzen Zeitfenster vor Auftreten des extremen Ereignisses bewiesen.In the last decades, extreme events, i.e., high-magnitude phenomena that cannot be described within the realm of Gaussian probability distributions have been observed in a multitude of physical systems. While statistical methods allow for a reliable identification of extreme event systems, the underlying mechanism behind extreme events is not understood. Extreme events are not well understood due to their rare occurrence and their onset under conditions that are difficult to reproduce. Thus, it is desirable to identify extreme event scenarios that can serve as a test bed. Optical systems exhibiting extreme events have been discovered to be ideal for such tests, and it is now desired to find more different examples to improve the understanding of extreme events. In this thesis, multifilamentation formed by femtosecond laser pulses is analyzed. Observation of the spatio-temporal dynamics of multifilamentation shows a heavy-tailed fluence probability distribution. This finding implies the onset of extreme events during multifilamentation. Linear analysis gives hints on the processes that drive the formation of extreme events. The multifilaments are also analyzed by nonlinear time series analysis, which provides information on determinism and chaos in the system. The analysis of the multifilament s is compared to an analysis of extreme event time series from ocean wave measurements and the supercontinuum output of an optical fiber. The analysis performed in this work shows fundamental differences in the extreme event mechnaism. While the extreme events in the optical fiber system are ruled by the stochastic changes of amplified quantum noise, in the multifilament and the ocean system extreme events appear as a result of the classical mechanical process of turbulence. This implies the predictability of extreme events. In this work, the predictability of extreme events is proven to be possible in a brief time window before the onset of the extreme event.
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Stuart, Graeme. "Monitoring energy performance in local authority buildings." Thesis, De Montfort University, 2011. http://hdl.handle.net/2086/4964.
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Energy management has been an important function of organisations since the oil crisis of the mid 1970’s led to hugely increased costs of energy. Although the financial costs of energy are still important, the growing recognition of the environmental costs of fossil-fuel energy is becoming more important. Legislation is also a key driver. The UK has set an ambitious greenhouse gas (GHG) reduction target of 80% of 1990 levels by 2050 in response to a strong international commitment to reduce GHG emissions globally. This work is concerned with the management of energy consumption in buildings through the analysis of energy consumption data. Buildings are a key source of emissions with a wide range of energy-consuming equipment, such as photocopiers or refrigerators, boilers, air-conditioning plant and lighting, delivering services to the building occupants. Energy wastage can be identified through an understanding of consumption patterns and in particular, of changes in these patterns over time. Changes in consumption patterns may have any number of causes; a fault in heating controls; a boiler or lighting replacement scheme; or a change in working practice entirely unrelated to energy management. Standard data analysis techniques such as degree-day modelling and CUSUM provide a means to measure and monitor consumption patterns. These techniques were designed for use with monthly billing data. Modern energy metering systems automatically generate data at half-hourly or better resolution. Standard techniques are not designed to capture the detailed information contained in this comparatively high-resolution data. The introduction of automated metering also introduces the need for automated analysis. This work assumes that consumption patterns are generally consistent in the short-term but will inevitably change. A novel statistical method is developed which builds automated event detection into a novel consumption modelling algorithm. Understanding these changes to consumption patterns is critical to energy management. Leicester City Council has provided half-hourly data from over 300 buildings covering up to seven years of consumption (a total of nearly 50 million meter readings). Automatic event detection pinpoints and quantifies over 5,000 statistically significant events in the Leicester dataset. It is shown that the total impact of these events is a decrease in overall consumption. Viewing consumption patterns in this way allows for a new, event-oriented approach to energy management where large datasets are automatically and rapidly analysed to produce summary meta-data describing their salient features. These event-oriented meta-data can be used to navigate the raw data event by event and are highly complementary to strategic energy management.
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Adolf, Janne K. "Contextualizing the Dynamics of Affective Functioning: Conceptual and Statistical Considerations." Doctoral thesis, Humboldt-Universität zu Berlin, 2018. http://dx.doi.org/10.18452/19412.
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Aktuelle Affektforschung betont die Bedeutung mikrolängsschnittlicher Daten für das Verstehen täglichen affektiven Funktionierens, da sie es erlauben affektive Dynamiken und potentiell zugrunde liegende Prozesse zu beschreiben. Dynamische Längsschnittmodelle werden entsprechend attraktiver. In dieser Dissertation komme ich Forderungen nach einer Integration kontextueller Informationen in die Untersuchung täglichen affektiven Funktionierens nach. Speziell modifiziere ich populäre dynamische Modelle so, dass sie kontextuelle Variationen einbeziehen. In einem ersten Beitrag werden Personen als in Kontexte eingebettet begriffen. Der vorgeschlagene Ansatz der festen moderierten Zeitreihenanalyse berücksichtigt systemische Reaktionen auf kontextuelle Veränderungen, indem Veränderungen in allen Parametern eines dynamischen Zeitreihenmodells auf kontextuelle Veränderungen bedingt schätzt werden. Kontextuelle Veränderungen werden als bekannt und assoziierte Parameterveränderungen als deterministisch behandelt. Folglich sind Modellspezifikation und -schätzung erleichtert und in kleineren Stichproben praktikabel. Es sind allerdings Informationen über den Einfluss kontextueller Faktoren erforderlich. Anwendbar auf einzelne Personen erlaubt der Ansatz die uneingeschränkte Exploration interindividueller Unterschiede in kontextualisierten affektiven Dynamiken. In einem zweiten Beitrag werden Personen als mit Kontexten interagierend begriffen. Ich implementiere eine Prozessperspektive auf kontextuelle Schwankungen, die die Dynamiken täglicher Ereignisse über autoregressive Modelle mit Poisson Messfehler abbildet. Die Kombination von Poisson und Gaußscher autoregressiver Modellierung erlaubt eine Formalisierung des dynamischen Zusammenspiels kontextueller und affektiver Prozesse. Die Modelle sind hierarchisch aufgesetzt und erfassen so interindividuelle Unterschiede in intraindividuellen Dynamiken. Die Schätzung erfolgt über simulationsbasierte Verfahren der Bayesschen Statistik.Recent affect research stresses the importance of micro-longitudinal data for understanding daily affective functioning, as they allow describing affective dynamics and potentially underlying processes. Accordingly, dynamic longitudinal models get increasingly promoted. In this dissertation, I address calls for an integration of contextual information into the study of daily affective functioning. Specifically, I modify popular dynamic models so that they incorporate contextual changes. In a first contribution, individuals are characterized as embedded in contexts. The proposed approach of fixed moderated time series analysis accounts for systemic reactions to contextual changes by estimating change in all parameters of a dynamic time series model conditional on contextual changes. It thus treats contextual changes as known and related parameter changes as deterministic. Consequently, model specification and estimation are facilitated and feasible in smaller samples, but information on which and how contextual factors matter is required. Applicable to single individuals, the approach permits an unconstrained exploration of inter-individual differences in contextualized affective dynamics. In a second contribution, individuals are characterized as interacting reciprocally with contexts. Implementing a process perspective on contextual changes, I model the dynamics of daily events using autoregressive models with Poisson measurement error. Combining Poisson and Gaussian autoregressive models can formalize the dynamic interplay between contextual and affective processes. It thereby distinguishes not only unique from joint dynamics, but also affective reactivity from situation selection, evocation, or anticipation. The models are set up as hierarchical to capture inter-individual differences in intra-individual dynamics. Estimation is carried out via simulation-based techniques in the Bayesian framework.
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Seiler, Ralf. "Extraktion von Trends in der Phänologie komplexer Ökosysteme am Beispiel des westafrikanischen Niger Binnendeltas für den Zeitraum 1982‑2006 : Auswertung von NOAA‑AVHRR Zeitreihen." Doctoral thesis, Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2016. http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-160474.
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Die vorliegende Arbeit analysiert die Phänologie photosynthetisch aktiver Vegetation mit Hilfe von NDVI Zeitreihen für einen Zeitraum von 24 Jahren (AVHRR‑GIMMS Daten). Neben einer Datierung des jahreszeitlichen Wechsels zwischen Wachstums-, Reife- und Seneszenzphase wird das Ziel verfolgt, Trends sowohl in phänologischen Ereignissen (Start-of-Season) als auch im NDVI zu identifizieren. Das, in der semi-ariden Sahelregion gelegene, Untersuchungsgebiet weist mit zwei sich teilweise überlagernden Vegetationsperioden eine komplexe Phänologie auf, deren Modellierung durch die sowohl in ihren Zeitpunkten als auch in ihren Ausprägungen hoch variablen Vegetationsabläufe erschwert wird. Vor diesem Hintergrund ist zunächst ein, auf der Fourieranalyse basierender, Ansatz zur flexiblen Glättung der NDVI Zeitreihen entwickelt worden. Um für die Trendanalyse lineare Regressionsverfahren einsetzen zu können, sind die Zeitreihen nach dem Komponentenmodell untergliedert worden (Subtraktion der Saisonfigur). Alternativ kam der saisonale MANN-KENDALL Trendtest zur Anwendung. Die NDVI Zeitreihen wurden ebenfalls auf Änderungen im mehrjährigen Mittelwert (Bruchpunkte) untersucht. Alle Auswertungen sind in einer eigenen Applikation umgesetzt worden. Es konnte gezeigt werden, daß Änderungen im NDVI Niveau eher abrupt als graduell verlaufen. Langfristige Trends weisen nur geringe Anstiege auf. Die Vegetation erholte sich von der Dürre 1984/85 nur im südlichen Teil des Untersuchungsgebietes, im Norden dominieren langfristig negative Trends. Brüche im mean der NDVI Zeitreihen korrelieren mit Brüchen im Abflußverhalten des Niger.
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Crisci, Carolina. "Effets du changement climatique sur les écosystèmes littoraux de la mer Méditerranée nord-occidentale : étude de la relation entre les conditions de température et la réponse biologique pendant les événements de mortalité massive." Thesis, Aix-Marseille 2, 2011. http://www.theses.fr/2011AIX22092.
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FRANKOVÁ, Nikola. "Řada nešťastných příhod Lemony Snicketa a Harry Potter Joanne Rowlingové jako příklady současné angloamerické morální fantasy." Master's thesis, 2018. http://www.nusl.cz/ntk/nusl-385125.
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The thesis deals with the interpretation of Series of Unfortunate Events written by an American author Lemony Snicket and Joanne K. Rowling´s story about Harry Potter. The analysis is focused on the moral and ethical aspects of individual motifs and symbols, as well as on the importance of human values in the behaviour of main characters. Some of the main protagonist were analysed according to their ability to spread good or evil, and therefore their influence on the young reader. The most important aspect was the good will of characters according to the principles of Lévinas' ethics while the self-sacrifice of the heroes is considered the highest moral value.
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Braz, João Guilherme da Costa. "Relatório de estágio realizado na Ocean Events WSL Qualifying Series." Master's thesis, 2020. http://hdl.handle.net/10400.5/20253.
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O presente trabalho é um Relatório de Estágio baseado no estágio curricular
realizado na empresa Ocean Events, promotora e organizadora de eventos da
World Surf League (WSL). As atividades desenvolvidas pelo estagiário foram ao
encontro dos objetivos estabelecidos, sendo o objetivo principal integrar o
departamento operacional na organização e gestão de dois eventos da WSL
Qualifying Series - Pro Santa Cruz e Caparica Surf Fest. O departamento
operacional reúne várias responsabilidades: realização do licenciamento,
supervisão dos protocolos de qualidade e segurança, negociação e contratação
de equipamentos, estruturas e staff, controlo e gestão de montagens e
desmontagens, apoio técnico a patrocinadores e parceiros. Os eventos da WSL
representam o nível mais elevado de competição profissional de surf no mundo,
como tal os padrões de qualidade exigidos à organização dos eventos são
igualmente elevados. O planeamento cuidado e a cooperação de todos os
elementos da equipa refletiram-se no sucesso dos eventos, que foram
observados por milhões de fãs na transmissão mundial em direto.The present work is a Report based on the internship carried out at Ocean Events, promoter and organizer of the events of the World Surf League (WSL). The activities developed by the intern met the established objectives, the main purpose is to integrate the operational department in the organization and management of two WSL Qualifying Series events - Pro Santa Cruz and Caparica Surf Fest. The operational department has several responsibilities: licensing, supervision of quality and safety protocols, negotiation and contracting of equipment, structures and staff, control and management of assembly and disassembly, technical support to sponsors and partners. WSL events represent the highest level of professional surfing competition in the world, so the quality standards required for the organization are equally rigorous. The careful planning and cooperation of all members of the team was reflected in the success of the events, which were observed by millions of fans in the worldwide live broadcast.
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Hallerberg, Sarah [Verfasser]. "Predictability of extreme events in time series / vorgelegt von Sarah Hallerberg." 2008. http://d-nb.info/994083033/34.
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Li, Chao. "Stochastic Simulation Methods for Precipitation and Streamflow Time Series." Thesis, 2013. http://hdl.handle.net/1969.1/149572.
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One major acknowledged challenge in daily precipitation is the inability to model extreme events in the spectrum of events. These extreme events are rare but may cause large losses. How to realistically simulate extreme behavior of daily precipitation is necessary and important. To that end, a hybrid probability distribution is developed. The logic of this distribution is to simulate the low to moderate values by an exponential distribution and extremes by a generalized Pareto distribution. Compared with alternatives, the developed hybrid distribution is capable of simulating the entire range of precipitation amount and is much easier to use. The hybrid distribution is then used to construct a bivariate discrete-continuous mixed distribution, which is used for building a daily precipitation generator. The developed generator can successfully reproduce extreme events. Compared with other widely used generators, the most important advantage of the developed generator is that it is apt at extrapolating values significantly beyond the upper range of observed data.
The major challenge in monthly streamflow simulation is referred to the underrepresentation of inter-annual variability. The inter-annual variability is often related with sustained droughts or periods of high flows. Preserving inter-annual variability is thus of particular importance for the long-term management of water resources systems. To that end, variables conveying such inter-annual signals should be used as covariates. This requires models that must be flexible at incorporating as many covariates as necessary. Keeping this point in mind, a joint conditional density estimation network is developed. Therein, the joint distribution of streamflows of two adjacent months is assumed to follow a specific parametric family. Parameters of the distribution are estimated by an artificial neural network. Due to the seasonal concentration of precipitation or the joint effect of rainfall and snowmelt, monthly streamflow distribution sometimes may exhibit a bimodal shape. To reproduce bimodality, nonparametric models are often preferred. However, the simulated sequences from existing nonparametric models represent too close a resemblance to historical record. To address this issue, while retaining typical merits of nonparametric models, a multi-model regression-sampling algorithm with a few weak assumptions is developed.
Collecting hydrometric data is the first step for building hydrologic models, and for planning, design, operation, and management of water resource systems. In this dissertation, an entropy-theory-based criterion, termed maximum information minimum redundancy, is proposed for hydrometric monitoring network evaluation and design. Compared with existing similar approaches, the criterion is apt at finding stations with high information content, and locating independent stations.
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Chung, Kuang-Yao, and 鍾光耀. "The Risk Data Mining of Time Series Data in Financial Disaster Events─The Applications of Time Series Value at Risk Model." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/31650349073640693074.
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碩士銘傳大學
資訊管理研究所
90
Instead of traditional approach to VaR estimation techniques good for common events but poor for tail one, say variance-covariance and HS, this study is to, this paper attempts to give empirical evidence on the performance of varied VaR models in which VaR will be formed by different methods, especially for EVT with GARCH model. Stress testing will be employed to gauge each of VaR models in the use of daily data as follows: NASDAQ, SGX-DT, MSCI, S&P500 index and TSE from 1997 to 2001; meanwhile the BVaR will be provided as another criteria. The calculation of VaR and BVaR of one, five and ten days is under 99% confidence level. The results show that 1.The EVT model with GARCH-fitted data works better than the model in the use of source data. 2.Among the different distributions of EVT, the estimated VaRs from Fréchet distribution assumption captures most of the major events.
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Martins, Luis Filipe Farias de Sousa. "Structural changes in nonstationary time series econometrics time varying cointegration and modeling catastrophic events /." 2005. http://etda.libraries.psu.edu/theses/approved/WorldWideIndex/ETD-794/index.html.
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Sarkar, Mostofa Ali. "Events identification using Box-Jenkins methodology with application to accelerated durability tests of ground vehicles." 2012. http://hdl.handle.net/1993/8891.
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Durability tests are important to ensure the safety and reliability of a ground vehicle and involve frequently driving a vehicle through a series of events that simulate different road conditions or obstacles encountered during actual driving. Since durability tests are costly in-terms of time and money, accelerated durability lab tests can be used to spot failures before actual road tests. Signals of different events of the actual durability road tests generate three continuous time series data, that can be used to conduct accelerated durability lab tests. The actual analysis of these time series is very challenging because they are (i) of high frequency (ii) very noisy and (iii) inconsistent.
The purpose of this study was to identify the patterns of signals from the noisy and inconsistent time series data collected from the field tests. The Box-Jenkins methodology was used to identify models corresponding to different events. Due to complex structures of the real data, ARMA modelling was considered after testing stationarity of the given time series. While the time series data in vertical direction was used to identify the first three events, the time series in vertical, longitudinal and lateral directions were used to identify other four events.
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Rajabi, Sareh. "Dating tectono-thermal events within the crystalline series of the Himalaya, the Kullu valley, NW India." Phd thesis, 2017. http://hdl.handle.net/1885/148838.
Full textAbstract:
The Greater Himalayan series preserve valuable geological
information revealing a complex
deformational and thermal history since the collision between
India and Eurasia. This research
employed field structural geology, microstructural analysis and
geochronometers such as 40Ar/39Ar
and U–Pb to reconstruct the deformational and thermal history
of the crystalline series within the
Kullu Valley, NW India. Key localities featuring geologically
important structures within and in
the vicinity of the Phojal recumbent fold were studied: an S-type
gneiss (top-gneiss-series) at the
structurally-highest part of the fold, deformed and undeformed
leucogranites intruded into the
crystalline series, and the phyllonites deformed by the Main
Central Thrust.
The sequencing of the thermal and deformational events that have
been preserved within the
microstructure of the Greater Himalaya series in the Kullu Valley
indicates a complex tectonic
history that can be summarised as: i) a leucogranite formation
event in the mid-Eocene; ii) a
deformation event in the late-Eocene; iii) regional Barrovian
metamorphism in the early-
Oligocene; iv) SW-verging recumbent folding in the Oligocene; v)
extensional South Tibetan
Detachment-related shearing in the Oligo-Miocene; vi) an
early-Miocene static thermal event;
and vii) mid-Miocene thrusting over the Main Central Thrust,
followed by regional uplift in the
Pliocene that resulted in the surface exhumation of the series.
This study shows that the tectonic models that have been proposed
for the evolution and
exhumation of the Greater Himalaya might not be applicable to the
NW Himalaya. The tectonic
history revealed by the present study is inconsistent with the
tectonic models involving: i) channel
flow—because the Main Central Thrust and the South Tibetan
Detachment were not coeval in
the NW Himalaya; ii) fold-nappes—because the Main Central
Thrust operated at least 10 Myr
after the recumbent folding; and iii) wedge tectonics—because
the South Tibetan Detachment
was not folded by the Phojal fold.
These models assume that the Himalaya evolved in a purely
compressional tectonic regime since
the continental collision. It is shown in this thesis that the
model of tectonic mode switches is
more applicable to the NW Himalaya—a compressional mode was in
effect until the Oligocene,
then from the late-Oligocene to mid-Miocene a switch to extension
occurred and finally the mode
switched back to compression from the mid-Miocene until the
present day. It appears that the
tectonic history of the crystalline series of the Himalaya has
been controlled mainly by the
kinematics of the subducting Indian plate, whereby a more
dominant convergence induced crustal
shortening, and a more accentuated roll-back stimulated crustal
extension.
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LEONELLI, FRANCESCA ELISA. "Addressing climate variability and extreme events in the ocean with spectral time series analysis and neural network models." Doctoral thesis, 2022. http://hdl.handle.net/11573/1632093.
Full textAbstract:
In the context of the Copernicus Climate Change Service project (C3S) we outline a set of time series analysis methods, showing their application to oceanic essential climate variables, mainly Sea Surface Temperature (SST), both globally and in regions of particular interest, such as the North Atlantic, tropical Pacific and Indian Oceans as well as the Mediterranean basin. The goal is to decompose observations into their main components, to be considered as average conditions, anomaly patterns, slow varying trend components, evaluating main periodicities and studying variability patterns.
We introduce and show the comparison between linear and nonlinear methods for extraction of main features in SST data, where the nonlinear method is obtained with the application of a feed-forward neural network with the architecture of an autoencoder. The Singular Spectral Analysis method (SSA) is shown for extracting the main periodic oscillations in time series, showing both its ability of treating climate indices and usability for spatio-temporal gap-filling of data records, which is typically the case that occurs with when dealing with satellite data.
We also highlight the importance of studying extreme events as defined by SST, that is those events which represent the tails of observations’ probability distribution, known as the Marine Heat Waves (MHWs). We outline their hierarchical characterisation and the detection procedure, presenting results on the global scale but also giving insight of a specific study-case in the Mediterranean basin. Indeed, the Mediterranean Sea has been experiencing a nearly constant positive trend over the last decades, accounting for a total increase of 1.5°C in the satellite era (from 1981 to present), and we analyse how this influences the MHWs detection. Hence we propose a second detection approach, based on first detrending the series, wanting to evaluate the variability itself once decoupled from a changing baseline climate and give comparison of results.
Within the framework of neural networks, we investigate the equivalence of two paradigmatic models, the Hopfield model (HN) and the Boltzmann Machine (BM), firstly when dealing with random centred patterns and secondly also generalising duality to biased patterns. Since HN has a robust statistical mechanics background that enables a clear picture of retrieval capabilities, and BMs constitute the building block of deep neural architectures, this duality gives a route to follow in addressing explainable Artificial Intelligence (AI), which is nowadays an always more demanded feature for such methods, to allow further comprehension of results, as well as increased control and capability of improving these.
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JIN, PEI-JUN, and 金姵君. "The Digital Visual Narrative Analysis of Historical Events from Narrative Critical Perspective - Taking Taiwan History Series as an Example." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/73j5h8.
Full textAbstract:
碩士世新大學
口語傳播學研究所
106
By applying the rhetorical approach of narrative criticism, this study examines seven animated short clips of Taiwanese history series produced by Taiwan Bar Studio. After the studio posted the history-themed clips, the debates and news reports concerning Taiwan’s history and its correlation to the social context have caused people’s attention in society. Therefore, the purpose of this study is to interpret the narrative techniques of the select artifacts by analyzing the settings, events, characters, causal relations and themes. In addition, the researcher examines narrative meanings, relevance, and consistency under the lens of narrative possibility and fidelity proposed by Fisher in his narrative paradigm. The results of this study show that, firstly, the select video clips of Taiwanese history series adopts four narrative techniques: using the sense of humor to draw audience's attention; shaping into the situation to intimate with audience; contrasting to narrative context; and providing the right of interpretation with audience. Secondly, the select video clips show the narrative meanings through the following three aspects: concerning contemporary issues and basing arguments on the issues; confronting parts of the Taiwanese governmental system; and differentiating the chinalized political ideology promoted by the Nationalist Government. Lastly, this study proposes that the select visual artifacts display the results of uncertainty of political standpoints, as well as the exclusion of some historical events resulting in lack of relevance. In short, this study aims to comprehend the narrations, animations, captions, and sound effects in the storytelling of select visual artifacts. Not only arousing public concern on Taiwanese history, the researcher of this study also attempts to explore the further investigations of digital visual narrative.
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Francis, Zharina. "A study of trends of consumer credit with a focus on the increase in unsecured lending in South Africa." Diss., 2016. http://hdl.handle.net/10500/24839.
Full textAbstract:
The objective of this research is to investigate the existence of structural changes in unsecured lending time series data and analyse the impact thereof on trends in consumer demand for unsecured credit spanning the years from 2008 to 2015. This is achieved by identifying dates when structural changes occurred over this period. The identified structural break date is linked to an influential economic event or monetary policy change that took place in South Africa of which the impact on three unsecured credit categories are analysed.
Unsecured credit growth in South Africa has been subjected to intensive scrutiny since the inception of the National Credit Act (Act No. 34 of 2005) by various regulatory bodies. In 2012 the National Credit Regulator (NCR) commissioned a research study into examining the impact that the National Credit Act (Act No. 34 of 2005) has had on the consumer credit market.
The empirical part of this study involved the gathering of time series data on unsecured loans approved, unsecured credit granted per income category and unsecured credit granted from the National Credit Regulator (NCR) database and performing descriptive and econometric analysis. The Zivot-Andrews (1992) and augmented Dickey-Fuller tests determined the break dates which were linked to a significant economic event while the one sample t-test of means compared average loan values before and after the break date.
Results of the study indicate that the break dates determined coincided with economic events and monetary policy changes in South Africa, such as the collapse of African Bank, the implementation of the National Credit Amendment Act, prime interest rate movements and the introduction of a debt counselling program by the government. These events, coupled with stricter lending criteria and no further loans being granted to customers already more than three months in arrears, restrained the uptake of unsecured loans to lower and middle income groups. The introduction of new affordability criteria and increasing interest rates in 2014 further negatively impacted demand for unsecured loans. However, higher income earners had the advantage of being able to apply for higher loan amounts. Findings could be used by monetary policymakers and financial institutions to constantly monitor credit trends, improve credit assessment techniques and review lending criteria.Business Management
M. Com. (Financial Management)
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Seiler, Ralf. "Extraktion von Trends in der Phänologie komplexer Ökosysteme am Beispiel des westafrikanischen Niger Binnendeltas für den Zeitraum 1982‑2006 : Auswertung von NOAA‑AVHRR Zeitreihen." Doctoral thesis, 2013. https://tubaf.qucosa.de/id/qucosa%3A22963.
Full textAbstract:
Die vorliegende Arbeit analysiert die Phänologie photosynthetisch aktiver Vegetation mit Hilfe von NDVI Zeitreihen für einen Zeitraum von 24 Jahren (AVHRR‑GIMMS Daten). Neben einer Datierung des jahreszeitlichen Wechsels zwischen Wachstums-, Reife- und Seneszenzphase wird das Ziel verfolgt, Trends sowohl in phänologischen Ereignissen (Start-of-Season) als auch im NDVI zu identifizieren. Das, in der semi-ariden Sahelregion gelegene, Untersuchungsgebiet weist mit zwei sich teilweise überlagernden Vegetationsperioden eine komplexe Phänologie auf, deren Modellierung durch die sowohl in ihren Zeitpunkten als auch in ihren Ausprägungen hoch variablen Vegetationsabläufe erschwert wird. Vor diesem Hintergrund ist zunächst ein, auf der Fourieranalyse basierender, Ansatz zur flexiblen Glättung der NDVI Zeitreihen entwickelt worden. Um für die Trendanalyse lineare Regressionsverfahren einsetzen zu können, sind die Zeitreihen nach dem Komponentenmodell untergliedert worden (Subtraktion der Saisonfigur). Alternativ kam der saisonale MANN-KENDALL Trendtest zur Anwendung. Die NDVI Zeitreihen wurden ebenfalls auf Änderungen im mehrjährigen Mittelwert (Bruchpunkte) untersucht. Alle Auswertungen sind in einer eigenen Applikation umgesetzt worden. Es konnte gezeigt werden, daß Änderungen im NDVI Niveau eher abrupt als graduell verlaufen. Langfristige Trends weisen nur geringe Anstiege auf. Die Vegetation erholte sich von der Dürre 1984/85 nur im südlichen Teil des Untersuchungsgebietes, im Norden dominieren langfristig negative Trends. Brüche im mean der NDVI Zeitreihen korrelieren mit Brüchen im Abflußverhalten des Niger.