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Approche décentralisée de l'apprentissage constructiviste et modélisation multi-agent du problème d'amorçage de l'apprentissage sensorimoteur en environnement continu : application à l'intelligence ambiante / Bootstrapping sensory-motor patterns for a constructivist learning system in continuous environments based on decentralized multi-agent approach : application to ambient intelligenceMazac, Sébastien 06 October 2015 (has links)
Nous proposons donc un modèle original d'apprentissage constructiviste adapté pour un système d'AmI. Ce modèle repose sur une approche décentralisée, permettant de multiples implémentations convenant à un environnement hétérogène. Dans les environnements réels continus sans modélisation à priori, se pose la question de la modélisation des structures élémentaires de représentation et particulièrement le problème d'amorçage de l'apprentissage sensorimoteur (comme décrit par [Kuipers06]). Dans le cadre du modèle général proposé, nous explicitons ce problème particulier et proposons de le traiter comme une forme d'auto-organisation modélisée par un système multi-agent. Cette approche permet de construire des motifs d'interaction élémentaires à partir des seules données brutes, sur lesquels peut reposer la construction d'une représentation plus élaborée (voir [Mazac14]). Nous présentons enfin une série d'expérimentations illustrant la résolution de ce problème d'amorçage : tout d'abord grâce à un environnement simulé, qui permet de maitriser les régularités de l'environnement et autorise des expérimentations rapides ; ensuite en implémentant ce système d'apprentissage au sein d'un environnement d'AmI réel. Pour cela le modèle est intégré dans le système d'AmI développé par l'entreprise partenaire de cette thèse CIFRE. Puis nous présentons une possible application industrielle des résultats de cette première étape implémentée d'amorçage de l'apprentissage sensorimoteur. Nous concluons par l'analyse des résultats et des perspectives de ce type d'approche pour l'AmI et l'application en général de l'IA aux systèmes réels en environnements continus / The theory of cognitive development from Jean Piaget (1923) is a constructivist perspective of learning that has substantially influenced cognitive science domain. Within AI, lots of works have tried to take inspiration from this paradigm since the beginning of the discipline. Indeed it seems that constructivism is a possible trail in order to overcome the limitations of classical techniques stemming from cognitivism or connectionism and create autonomous agents, fitted with strong adaptation ability within their environment, modelled on biological organisms. Potential applications concern intelligent agents in interaction with a complex environment, with objectives that cannot be predefined. Like robotics, Ambient Intelligence (AmI) is a rich and ambitious paradigm that represents a high complexity challenge for AI. In particular, as a part of constructivist theory, the agent has to build a representation of the world that relies on the learning of sensori-motor patterns starting from its own experience only. This step is difficult to set up for systems in continuous environments, using raw data from sensors without a priori modelling.With the use of multi-agent systems, we investigate the development of new techniques in order to adapt constructivist approach of learning on actual cases. Therefore, we use ambient intelligence as a reference domain for the application of our approach
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Assessment of the benefits and drawbacks of high resolution PET for the imaging of cancer in the headAnton-Rodriguez, Jose January 2018 (has links)
Introduction: In Positron Emission Tomography (PET), the use of resolution modelling (RM) in iterative image reconstruction enables the modelling of aspects of detection which result in mispositioning of measured data and the subsequent blurring of reconstructed images. RM reconstruction can result in significant improvements in spatial resolution, voxel variance and count rate bias and could be a software alternative to detection hardware that is able to achieve higher resolution. Such hardware typically consists of small scintillation crystals, small bore diameters and depth of interaction discrimination, such as for the High Resolution Research Tomograph (HRRT, Siemens), which used a double crystal layer phoswich detector system. However, RM implementation comes with penalties such as slower rates of convergence, potentially higher region of interest variance and Gibbs artefacts. Methods: Assessment of the benefits and drawbacks of RM was done in the first part of this thesis together with the measurement and modelling of spatially varying resolution kernels for different scanner configurations and PET isotopes for the HRRT. It is also unclear as to whether high resolution scanning offers significant advantages over clinical PET-CT scanners for applications in the head. Through direct comparison to our HRRT, we explore whether there are significant advantages of high resolution scanning for an application in the head over clinical PET-CT. For this comparison our Biograph TruePoint TrueV (Siemens) optimised for whole body imaging was used and a novel clinical study using both scanners was set where we scanned Neurofibromatosis 2 (NF2) patients with vestibular schwannomas (VS) using [18F]fluorodeoxyglucose (FDG) and [18F]fluorothymidine (FLT). The clinical objective was to assess if uptake within VS of FLT and FDG could be measured and whether this uptake was predictive of tumour growth. Finally an assessment of the feasibility and impact of reducing the original injected activities in our clinical study was performed using bootstrapping resampling. Conclusions: RM provides greater but additive improvements in image resolution compared to DOI on the HRRT. Isotope specific image based RM could be estimated from published positron range distributions and measurements using fluorine-18. With the clinical project, uptake of FDG and FLT within the VS lesions was observed, these uptake values were correlated to each other, and high uptake was predictive of tumour growth with little differences in predictive power between FLT and FDG. Although there were benefits of the HRRT for imaging small lesions, in our clinical application there was little difference between the two scanners to discriminate lesion growth. Using the PET-CT scanner data and knowledge of lesion location, doses could be reduced to 5-10% without any significant loss of ability to discriminate lesion growth.
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Model-Based Hypothesis Testing in Biomedicine : How Systems Biology Can Drive the Growth of Scientific KnowledgeJohansson, Rikard January 2017 (has links)
The utilization of mathematical tools within biology and medicine has traditionally been less widespread compared to other hard sciences, such as physics and chemistry. However, an increased need for tools such as data processing, bioinformatics, statistics, and mathematical modeling, have emerged due to advancements during the last decades. These advancements are partly due to the development of high-throughput experimental procedures and techniques, which produce ever increasing amounts of data. For all aspects of biology and medicine, these data reveal a high level of inter-connectivity between components, which operate on many levels of control, and with multiple feedbacks both between and within each level of control. However, the availability of these large-scale data is not synonymous to a detailed mechanistic understanding of the underlying system. Rather, a mechanistic understanding is gained first when we construct a hypothesis, and test its predictions experimentally. Identifying interesting predictions that are quantitative in nature, generally requires mathematical modeling. This, in turn, requires that the studied system can be formulated into a mathematical model, such as a series of ordinary differential equations, where different hypotheses can be expressed as precise mathematical expressions that influence the output of the model. Within specific sub-domains of biology, the utilization of mathematical models have had a long tradition, such as the modeling done on electrophysiology by Hodgkin and Huxley in the 1950s. However, it is only in recent years, with the arrival of the field known as systems biology that mathematical modeling has become more commonplace. The somewhat slow adaptation of mathematical modeling in biology is partly due to historical differences in training and terminology, as well as in a lack of awareness of showcases illustrating how modeling can make a difference, or even be required, for a correct analysis of the experimental data. In this work, I provide such showcases by demonstrating the universality and applicability of mathematical modeling and hypothesis testing in three disparate biological systems. In Paper II, we demonstrate how mathematical modeling is necessary for the correct interpretation and analysis of dominant negative inhibition data in insulin signaling in primary human adipocytes. In Paper III, we use modeling to determine transport rates across the nuclear membrane in yeast cells, and we show how this technique is superior to traditional curve-fitting methods. We also demonstrate the issue of population heterogeneity and the need to account for individual differences between cells and the population at large. In Paper IV, we use mathematical modeling to reject three hypotheses concerning the phenomenon of facilitation in pyramidal nerve cells in rats and mice. We also show how one surviving hypothesis can explain all data and adequately describe independent validation data. Finally, in Paper I, we develop a method for model selection and discrimination using parametric bootstrapping and the combination of several different empirical distributions of traditional statistical tests. We show how the empirical log-likelihood ratio test is the best combination of two tests and how this can be used, not only for model selection, but also for model discrimination. In conclusion, mathematical modeling is a valuable tool for analyzing data and testing biological hypotheses, regardless of the underlying biological system. Further development of modeling methods and applications are therefore important since these will in all likelihood play a crucial role in all future aspects of biology and medicine, especially in dealing with the burden of increasing amounts of data that is made available with new experimental techniques. / Användandet av matematiska verktyg har inom biologi och medicin traditionellt sett varit mindre utbredd jämfört med andra ämnen inom naturvetenskapen, såsom fysik och kemi. Ett ökat behov av verktyg som databehandling, bioinformatik, statistik och matematisk modellering har trätt fram tack vare framsteg under de senaste decennierna. Dessa framsteg är delvis ett resultat av utvecklingen av storskaliga datainsamlingstekniker. Inom alla områden av biologi och medicin så har dessa data avslöjat en hög nivå av interkonnektivitet mellan komponenter, verksamma på många kontrollnivåer och med flera återkopplingar både mellan och inom varje nivå av kontroll. Tillgång till storskaliga data är emellertid inte synonymt med en detaljerad mekanistisk förståelse för det underliggande systemet. Snarare uppnås en mekanisk förståelse först när vi bygger en hypotes vars prediktioner vi kan testa experimentellt. Att identifiera intressanta prediktioner som är av kvantitativ natur, kräver generellt sett matematisk modellering. Detta kräver i sin tur att det studerade systemet kan formuleras till en matematisk modell, såsom en serie ordinära differentialekvationer, där olika hypoteser kan uttryckas som precisa matematiska uttryck som påverkar modellens output. Inom vissa delområden av biologin har utnyttjandet av matematiska modeller haft en lång tradition, såsom den modellering gjord inom elektrofysiologi av Hodgkin och Huxley på 1950‑talet. Det är emellertid just på senare år, med ankomsten av fältet systembiologi, som matematisk modellering har blivit ett vanligt inslag. Den något långsamma adapteringen av matematisk modellering inom biologi är bl.a. grundad i historiska skillnader i träning och terminologi, samt brist på medvetenhet om exempel som illustrerar hur modellering kan göra skillnad och faktiskt ofta är ett krav för en korrekt analys av experimentella data. I detta arbete tillhandahåller jag sådana exempel och demonstrerar den matematiska modelleringens och hypotestestningens allmängiltighet och tillämpbarhet i tre olika biologiska system. I Arbete II visar vi hur matematisk modellering är nödvändig för en korrekt tolkning och analys av dominant-negativ-inhiberingsdata vid insulinsignalering i primära humana adipocyter. I Arbete III använder vi modellering för att bestämma transporthastigheter över cellkärnmembranet i jästceller, och vi visar hur denna teknik är överlägsen traditionella kurvpassningsmetoder. Vi demonstrerar också frågan om populationsheterogenitet och behovet av att ta hänsyn till individuella skillnader mellan celler och befolkningen som helhet. I Arbete IV använder vi matematisk modellering för att förkasta tre hypoteser om hur fenomenet facilitering uppstår i pyramidala nervceller hos råttor och möss. Vi visar också hur en överlevande hypotes kan beskriva all data, inklusive oberoende valideringsdata. Slutligen utvecklar vi i Arbete I en metod för modellselektion och modelldiskriminering med hjälp av parametrisk ”bootstrapping” samt kombinationen av olika empiriska fördelningar av traditionella statistiska tester. Vi visar hur det empiriska ”log-likelihood-ratio-testet” är den bästa kombinationen av två tester och hur testet är applicerbart, inte bara för modellselektion, utan också för modelldiskriminering. Sammanfattningsvis är matematisk modellering ett värdefullt verktyg för att analysera data och testa biologiska hypoteser, oavsett underliggande biologiskt system. Vidare utveckling av modelleringsmetoder och tillämpningar är därför viktigt eftersom dessa sannolikt kommer att spela en avgörande roll i framtiden för biologi och medicin, särskilt när det gäller att hantera belastningen från ökande datamängder som blir tillgänglig med nya experimentella tekniker.
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Optimalizace skladových zásob ve společnosti NET4GAS, s.r.o. / Optimization of inventory in NET4GAS, s.r.o.Hynoušová, Zuzana January 2012 (has links)
This thesis deals with optimization of inventory of spare parts and maintenance materials in NET4GAS, s.r.o. The aim of the thesis is to sort the items stored in the company and to propose specific supply methodology for the year 2013. The thesis is divided into two parts. The first, theoretical part includes theoretical knowledge of inventory management together with the methods used in the managing process, it also introduces specific inventory management of spare parts and maintenance materials. The second, practical part describes NET4GAS, s.r.o., its current system of inventory management of spare parts and maintenance materials, it identifies the local current problems in inventory management, it proposes selection of appropriate methods of inventory optimization and it demonstrates their application to real data. For the classification of stored items is selected ABC method. To draw up the supply plan is primarily used bootstrap method (also called bootstrapping), which makes estimates of future consumption of spare parts and maintenance materials. The final section summarizes all the recommendations for improving the current inventory management.
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Účinky vybraných opatření k prevenci malárie: analýza panelových dat / The Effects of Different Malaria Prevention Measures: Panel Data AnalysisPavelková, Adéla January 2020 (has links)
The main aim of this diploma thesis was to explore the topic of malaria preventive measures. Concretely, to study which preventive measures are useful and to see how they are distributed around the world. For international organizations, this is very important as they need to know whether funds allocated for malaria aid are distributed effectively. This study is using manually compounded data from the World Health Organization for all countries threatened by malaria mostly from 2001 to 2018. For this purpose, panel data regression methods using robust standard errors, bootstrapping and cluster analysis were used. The results showed that generally, the most useful preventive measures are indoor-residual sprayings, a combination of sprayings and insecticide-treated nets and rapid diagnostic tests. Furthermore, the effect of the population living in rural areas is significant. Besides, gross domestic product is a very important factor for African countries. The stability analysis - bootstrapping - confirmed our results. However, we examined that insecticide-treated nets are still the most distributed measures. Doing the cluster analysis, we observed that countries on the same continent should not be treated similarly and we emphasized countries that should receive higher attention. Overall, the...
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Relational Intimacy Mediates Sexual Outcomes Associated With Impaired Sexual Function: Examination in a Clinical SampleWitherow, Marta P., Chandraiah, Shambhavi, Seals, Samantha R., Sarver, Dustin E., Parisi, Kathryn E., Bugan, Antal 01 June 2017 (has links)
Background Relational intimacy is hypothesized to underlie the association between female sexual functioning and various sexual outcomes, and married women and women with sexual dysfunction have been generally absent from prior studies investigating these associations, thus restricting generalizability. Aim To investigate whether relational intimacy mediates sexual outcomes (sexual satisfaction, coital frequency, and sexual distress) in a sample of married women with and without impaired sexual functioning presenting in clinical settings. Methods Using a cross-sectional design, 64 heterosexual married women with (n = 44) and without (n = 20) impaired sexual functioning completed a battery of validated measurements assessing relational intimacy, sexual dysfunction, sexual frequency, satisfaction, and distress. Intimacy measurements were combined using latent factor scores before analysis. Bias-corrected mediation models of the indirect effect were used to test mediation effects. Moderated mediation models examined whether indirect effects were influenced by age and marital duration. Outcomes Patients completed the Female Sexual Function Index, the Couple's Satisfaction Index, the Sexual Satisfaction Scale for Women, the Inclusion of the Other in the Self Scale, and the Miller Social Intimacy Test. Results Mediation models showed that impaired sexual functioning is associated with all sexual outcomes directly and indirectly through relational intimacy. Results were predominantly independent of age and marital duration. Clinical Implications Findings have important treatment implications for modifying interventions to focus on enhancing relational intimacy to improve the sexual functioning of women with impaired sexual functioning. Strengths and Limitations The importance of the role relational intimacy plays in broad sexual outcomes of women with impaired sexual functioning is supported in clinically referred and married women. Latent factor scores to improve estimation of study constructs and the use of contemporary mediation analysis also are strengths. The cross-sectional design precludes any causal conclusions and it is unknown whether the results generalize to male partners, partners within other relationship structures, and non-heterosexual couples. Conclusion Greater relational intimacy mitigates the adverse impact of impaired sexual functioning on sexual behavior and satisfaction in women. Witherow MP, Chandraiah S, Seals SR, et al. Relational Intimacy Mediates Sexual Outcomes Associated With Impaired Sexual Function: Examination in a Clinical Sample. J Sex Med 2017;14:843–851.
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Développement précoce de la segmentation des formes sonores : unités rythmiques, voyelles puis consonnes / Early development in segmenting word forms : rhythmic units, vowels and then consonantsNishibayashi, Léo-Lyuki 18 November 2014 (has links)
Les mots étant rarement produits hors contexte phrastique, les enfants vont devoir les extraire du flux de parole pour les apprendre. Les probabilités de transition (Saffran et al., 1996) et les unités rythmiques (Nazzi et al., 2006) seraient cruciales à l'émergence de la segmentation. Les formes sonores segmentées seront par la suite mémorisées en représentations phonétiquement détaillées. Cependant, selon Nespor et al. (2003) les consonnes seraient plus impliquées au niveau lexical que les voyelles, proposant un biais consonantique dans la reconnaissance des formes sonores segmentées. Le premier axe de ma thèse s'intéresse aux capacités précoces de segmentation chez les enfants francophones nés à terme et prématurés afin de déterminer quand elles émergent et dans quelle mesure les unités rythmiques sont impliquées. Le second s'intéresse à l'émergence et à l'origine du biais consonantique. Les résultats montrent que (1) les enfants nés à terme et prématurés sont capables de segmenter la parole en utilisant l'unité syllabique dès 6 mois ; (2) d'un biais vocalique à 6 mois, les enfants francophones, acquièrent un biais consonantique à 8 mois dans la reconnaissance de formes sonores segmentées ; (3) le biais consonantique proviendrait donc de l'acquisition des propriétés acoustiques/phonétiques de la langue maternelle. / Since words are rarely produced in isolation, one of the first steps in acquiring new words is to segment them from continuous speech. Transitional probabilities (Saffran et al., 1996) and rhythmic units (Nazzi et al., 2006) have been proposed to be crucial at segmentation onset. Segmented word forms will then have to be stored as phonetically-specified representations for future recognition. However, Nespor et al. (2003) hypothesized that consonants, more than vowels, are involved at the lexical level, proposing a consonant bias in early word processing.The first part of my dissertation investigates preterm and full-term infants' segmentation abilities to determine when they emerge and to what extent rhythmic units are involved. The second part investigates the emergence and origin of the consonant bias in recognizing segmented word forms with full-term infants. Results show that (1) both preterm and full-term 6-month-olds are able to segment speech by using syllabic units; (2) French-learning infants switch from a vowel bias at 6 months to an adult-like consonant bias in recognizing segmented word forms; (3) the consonant bias emerging between 6 and 8 months of age, it would result from the processing and learning of the acoustic/phonetic properties on the language being acquired.
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Stochastic Modeling of Geometric Mistuning and Application to Fleet Response PredictionHenry, Emily Brooke January 2014 (has links)
No description available.
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Likelihood inference for multiple step-stress models from a generalized Birnbaum-Saunders distribution under time constraintAlam, Farouq 11 1900 (has links)
Researchers conduct life testing on objects of interest in an attempt to determine their life distribution as a means of studying their reliability (or survivability). Determining the life distribution of the objects under study helps manufacturers to identify potential faults, and to improve quality. Researchers sometimes conduct accelerated life tests (ALTs) to ensure that failure among the tested units is earlier than what could result under normal operating (or environmental) conditions. Moreover, such experiments allow the experimenters to examine the effects of high levels of one or more stress factors on the lifetimes of experimental units. Examples of stress factors include, but not limited to, cycling rate, dosage, humidity, load, pressure, temperature, vibration, voltage, etc. A special class of ALT is step-stress accelerated life testing. In this type of experiments, the study sample is tested at initial stresses for a given period of time. Afterwards, the levels of the stress factors are increased in agreement with prefixed points of time called stress-change times. In practice, time and resources are limited; thus, any experiment is expected to be constrained to a deadline which is called a termination time. Hence, the observed information may be subjected to Type-I censoring.
This study discusses maximum likelihood inferential methods for the parameters of multiple step-stress models from a generalized Birnbaum-Saunders distribution under time constraint alongside other inference-related problems. A couple of general inference frameworks are studied; namely, the observed likelihood (OL) framework, and the expectation-maximization (EM) framework. The last-mentioned framework is considered since there is a possibility that Type-I censored data are obtained. In the first framework, the scoring algorithm is used to get the maximum likelihood estimators (MLEs) for the model parameters. In the second framework, EM-based algorithms are utilized to determine the required MLEs. Obtaining observed information matrices under both frameworks is also discussed. Accordingly, asymptotic and bootstrap-based interval estimators for the model parameters are derived. Model discrimination within the considered generalized Birnbaum-Saunders distribution is carried out by likelihood ratio test as well as by information-based criteria. The discussed step-stress models are illustrated by analyzing three real-life datasets. Accordingly, establishing optimal multiple step-stress test plans based on cost considerations and three optimality criteria is discussed. Since maximum likelihood estimators are obtained by numerical optimization that involves maximizing some objective functions, optimization methods used, and their software implementations in R are discussed. Because of the computational aspects are in focus in this study, the benefits of parallel computing in R, as a high-performance computational approach, are briefly addressed. Numerical examples and Monte Carlo simulations are used to illustrate and to evaluate the methods presented in this thesis. / Thesis / Doctor of Science (PhD)
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Ionic Characterization of Laundry Detergents: Implications for Consumer Choice and Inland Freshwater SalinizationMendoza, Kent Gregory 11 April 2024 (has links)
Increased salinity in freshwater systems – also called the Freshwater Salinization Syndrome (FSS) – can have far-ranging implications for the natural and built environment, agriculture, and public health at large. Such risks are clearly on display in the Occoquan Reservoir – a drinking water source for roughly one million people in the northern Virginia/ National Capital Region. Sodium concentrations in the Occoquan Reservoir are approaching levels that can affect taste and health. The Reservoir is also noteworthy as a flagship example of indirect potable reuse, which further adds complexity to understanding the sources of rising levels of sodium and other types of salinity. To help understand the role residential discharges might play in salinization of the Occoquan Reservoir, a suite of laundry detergent products was identified based upon survey data collected in the northern Virginia region. The ionic compositions of these products were then characterized using ion chromatography and inductively coupled plasma-mass spectrometry to quantify select ionic and elemental analytes. Sodium, chloride, and sulfate were consistently found in appreciable amounts. To comparatively characterize the laundry detergents, principal component analysis was employed to identify clusters of similar products. The physical formulation of the products was identified as a marker for their content, with dry formulations (free-flowing and encapsulated powders) being more enriched in sodium and sulfate. This result was corroborated by comparing nonparametric bootstrap intervals for individual analytes. The study's findings suggest an opportunity wherein consumer choice can play a role in mediating residential salt inputs in receiving bodies such as the Occoquan Reservoir. / Master of Science / Many streams, rivers, and other freshwater systems have become increasingly salty in recent decades. A rise in salinity can be problematic, stressing aquatic life, corroding pipes, and even enhancing the release of more pollutants into the water. This phenomenon, called Freshwater Salinization Syndrome, can threaten such systems' ability to serve as sources of drinking water, as is the case for the Occoquan Reservoir in northern Virginia. Serving roughly one million people, the Reservoir is notable for being one of the first in the country to purposely incorporate highly treated wastewater upstream of a drinking water supply. Despite the Reservoir's prominence, the reasons behind its rising salt levels are not well understood. This study sought to understand the role that individual residences could play when household products travel down the drain and are ultimately discharged into the watershed. Laundry detergents are potentially high-salt products. A survey of northern Virginian's laundry habits was conducted to understand local tastes and preferences. Informed by the survey, a suite of laundry detergents was chemically characterized to measure salt and element concentrations. The detergents were found to have notable amounts of sodium, chloride, and sulfate in particular, with sodium being the most abundant analyte in every detergent. However, not all detergents were equally salty; statistical tools revealed that dry formulations (such as powdered and powder-filled pak detergents) contributed more sodium and sulfate, among other things. This study's findings suggest that laundry detergents could be contributing to Freshwater Salinization Syndrome in the Occoquan Reservoir, and that local consumers' choice of detergents could make a difference.
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