Magister Chirurgiae Dentium (MChD) / AIMS AND OBJECTIVES: Most children presenting to dental clinics have pain of varying intensity that usually, has been endured for long periods of time. A study done at Cardiff in the United Kingdom, found that only 15% of children that had dental pain visited the dentist. Therefore, understanding the motivations of patients in seeking health care is vital to the quality of life in the family and community and to the success of any oral health planning process. This study explored factors influencing the time between the initial pain experience and definitive dental treatment, that is, the time lapse. It assessed how factors such as pain, individual and community characteristics affect the timing of dental visits. METHOD: Parents or guardians accompanying children visiting two community dental clinics in Guguletu and Mitchells Plain in the Western Cape were asked to indicate how factors such as severity and duration of pain, efficacy of self-treatment, and impact on parents affected the decision to seek treatment. A total of one hundred and twenty six parents were interviewed using a structured questionnaire. The English questionnaire was translated into Xhosa and Afrikaans and used with the help of interpreters when necessary. Children attending these community dental clinics for treatment on a particular morning were included in the study sample. Children up to thirteen years of age (primary, mixed, and early permanent dentition) comprised the study sample. Only children that had a dental problem were included in the study. Children that were not accompanied by a parent or guardian were excluded. RESULTS: Close to half the children (43 - 45%) had never been to the dentist before. Parents from Mitchells Plain knew earlier of their children's dental problems (most knew14 days before visit) than those from Guguletu where most knew within the last 7 days. However, Guguletu children were presented to the dentist sooner after the painful experience (69.2% within 7 days) than Mitchells Plain where only 48.3% were presented within the same period. It was found that for these communities, the distance from the clinic, the mode of transport, and the fares charged greatly influenced dental attendance. Most families lived within 3km, and walked (more prevalent in Guguletu) or rode a taxi (more prevalent in Mitchells Plain). With taxi the most prevalent mode of transport, money was an important factor of dental attendance. Long queues at the clinic and waiting long for appointments, were cited by parents as the major hindrances to attendance. While a worsening of pain, loss of sleep and sensitivity to chewing hastened dental attendance, parental work commitment and the child's school delayed it. Most families (79%) tried some treatment at home prior to the dental visit. The remedies offered such as Disprin®, direct placement of crushed Disprin® and Panado® were a concern because they were potentially harmful. Both communities were in the low socio-economic class with Guguletu consistently the poorer of the two. They both had disrupted family life as reflected by the low rates of married parents. CONCLUSION: In the presence of pain Guguletu children were presented to the dentist sooner than those of Mitchells Plain. Accessibility of the clinics was a real concern especially in Guguletu. There was rampant inappropriate use of medications such as aspirin and antibiotics. The greatest impact of the child's pain on the parents was on affected sleep. The non-regular attendance pattern of the children closely followed that of the parents.

Bibliography: pages 123-133. / The hypothesis was advanced that comparative interpretation of multi-temporal aerial photographs can be used as a tool in Environmental Impact Analysis (EIA). To test this hypothesis a site, Silwerstroomstrand, approximately 40 kilometres north of Cape Town on the West coast was chosen. An analysis of the site was carried out using aerial photographs taken in 1938, 1960, 1968, 1971, 1977, 1981 and 1983 at scales ranging from 1:7 000 to 1:50 000. Development of the site for recreation began in 1972 and in 1976 for water extraction. Pre-development photographs, 1938, 1960, 1968 and 1971, were stereoscopically compared and the observations were interpreted using a systems approach. From the analysis of the photographs and information on past landuse, the dynamics of the site were described with particular attention to the response of that environment to perturbations such as fire and removal of vegetation. Development actions were analysed to establish any similarity to past perturbations and on the basis of similarities, predictions of probable future responses of the site (and hence impacts) were made. The predicted impacts were compared with: 1. the interpretation of post-development photographs. 2. Impacts identified by a multi-disciplinary panel after a visit to the site. It was found that the major limitation of multi-temporal aerial photographs was the spatial resolution of the early (pre 1970) photographs. However, the capabilities of the tool for quantitative and semi-quantitative data gathering; promoting an understanding of spatial and temporal relationships; monitoring change; communicating information and the fact that it is economical means that it has a positive contribution to make to Environmental Impact Analysis is suggested that the optimal use of the tool of comparative interpretation of multi-temporal aerial photography is to combine it with other tools such as site visits and multi-disciplinary panels.

Seismic inversion is the leading method to map and quantify changes in time-lapse (4D) seismic datasets, with applications ranging from monitoring hydrocarbon-producing fields to geological CO2 storage. However, the process of inverting seismic data for reservoir properties is a notoriously ill-posed inverse problem due to the band-limited and noisy nature of seismic data. This comes with additional challenges for 4D applications, given the inaccuracies in the repeatability of time-lapse acquisition surveys. Consequently, adding prior information to the inversion process in the form of properly crafted regularization terms is essential to obtain geologically meaningful subsurface models and 4D effects. In this thesis, I propose a joint inversion-segmentation algorithm for 4D seismic inversion, which integrates total variation and segmentation priors as a way to counteract the missing frequencies and noise present in 4D seismic data. I validate the algorithm with synthetic and field seismic datasets and benchmark it against state-of-the-art 4D inversion techniques. The proposed algorithm shows three main advantages: 1. it produces high-resolution baseline and monitor acoustic impedance models, 2. by leveraging similarities between multiple seismic datasets, the proposed algorithm mitigates the non-repeatable noise and better highlights the real seismic time-lapse changes, and 3. it simultaneously provides a volumetric classification of the acoustic impedance 4D difference model based on user-defined classes, i.e., percentages of seismic time-lapse changes. Such advantages may enable more robust stratigraphic/structural and quantitative 4D seismic interpretation and provide more accurate inputs for dynamic reservoir simulations.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第24208号 / 工博第5036号 / 新制||工||1786(附属図書館) / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 中北 英一, 准教授 山口 弘誠, 教授 田中 賢治 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Mass loss of alpine glaciers presently account for about half of the cryospheric contribution to the global sea-level rise. Mass balance of alpine glaciers has predominantly been monitored by; (1) glaciological and hydrological methods, and (2) satellite gravimetric methods using data from NASA’s Gravity Recovery and Climate Experiment (GRACE) satellite mission. However, the former can be logistically costly and have large extrapolation errors: measurements taken at monthly temporal scales are expensive and have a spatial resolution of roughly one kilometer. The latter provides monthly mass-balance estimates of aggregates of alpine glaciers, although the spatial resolution (~300 km) is far too coarse for assessing individual glaciers’ mass balance. Ground-based, time-lapse microgravity measurements can potentially overcome some of the disadvantages of the glaciological, hydrological, and satellite gravitational methods for assessing mass changes and their spatial distribution on a single glacier. Gravity models were utilized to predict the gravity signals of the summer-time mass balance, changes in the seasonal snow cover outside of the glacier, and the vertical gravity gradient (VGG) needed for the free-air correction on Wolverine Glacier, AK. The modeled gravity signal of the summer-time mass balance (average of -0.237 mGal) is more than an order of magnitude larger than the uncertainty of conventional relative gravimeters (±0.007 mGal). Therefore, modeling predict that the time-lapse gravitational method could detect the summer-time mass balance on Wolverine Glacier. The seasonal snow effect was shown to have the greatest influence (~ -0.15 mGal) on the outer 100 m boundary of the glacier and minimal effect (~ -0.02 mGal) towards the center, both larger than the uncertainty of relative gravimeters. The VGG has a positive deviation, about -0.1 to -0.2 mGal/m, from the normal VGG (-0.309 mGal/m). Thus, seasonal snow effect and VGG need to be correctly accounted for when processing gravity measurements to derive the residual gravity signal of the glacier mass balance. Accurate measurements of elevation changes, seasonal snow depth, and the VGG should be performed in future gravity surveys of glaciers. / Geology

Optical recording of various brain signals is becoming an indispensable technique for biological studies, accelerated by the development of new or improved biosensors and microscopy technology. A major challenge in leveraging the technique is to identify and quantify the rich patterns embedded in the data. However, existing methods often struggle, either due to their limited signal analysis capabilities or poor performance. Here we present Activity Quantification and Analysis (AQuA2), an innovative analysis platform built upon machine learning theory. AQuA2 features a novel event detection pipeline for precise quantification of intricate brain signals and incorporates a Consensus Functional Unit (CFU) module to explore interactions among potential functional units driving repetitive signals. To enhance efficiency, we developed BIdirectional pushing with Linear Component Operations (BILCO) algorithm to handle propagation analysis, a time-consuming step using traditional algorithms. Furthermore, considering user-friendliness, AQuA2 is implemented as both a MATLAB package and a Fiji plugin, complete with a graphical interface for enhanced usability. AQuA2's validation through both simulation and real-world applications demonstrates its superior performance compared to its peers. Applied across various sensors (Calcium, NE, and ATP), cell types (astrocytes, oligodendrocytes, and neurons), animal models (zebrafish and mouse), and imaging modalities (two-photon, light sheet, and confocal), AQuA2 consistently delivers promising results and novel insights, showcasing its versatility in fluorescent imaging data analysis. / Doctor of Philosophy / Understanding and effectively treating brain diseases requires a deep insight into how the brain operates. A crucial aspect of this exploration involves directly visualizing different signals within the brain, allowing researchers to delve into the functions of brain cells and their interactions. However, as data collection expands rapidly, analyzing this wealth of information presents a significant challenge. Existing methods often fall short due to their limited capacity to analyze signals or their subpar performance, failing to keep pace with current demands. In this work, we introduce Activity Quantification and Analysis (AQuA2), an innovative platform rooted in machine learning principles. AQuA2 features a novel event detection pipeline for accurately quantifying intricate brain signals. Additionally, it incorporates a Consensus Functional Unit (CFU) module, which facilitates the exploration of interactions among potential functional units associated with repetitive signals. To enhance efficiency and usability, we have developed acceleration algorithms and released AQuA2 in two versions: a MATLAB package and a Fiji plugin, each designed to address unique user requirements. AQuA2 has demonstrated its efficacy through real-world applications, effectively quantifying and analyzing signals across various platforms such as biosensors, cell types, animal models, and imaging modalities, with promising outcomes. Furthermore, the utilization of AQuA2 has facilitated the discovery of new insights, thereby augmenting its value. These findings emphasize its versatility as software for comprehensive analysis of diverse fluorescent imaging data, enabling a wide range of scientific inquiries.

People spend a significant amount of time using computers at work, at home, or school. Given users switch tasks and are frequently interrupted or distracted while working, reconstructing working context is inevitable. For example, users sometimes need to revisit an arbitrary task from the past to retrieve necessary information (e.g., webpages, files). In this scenario, retrieving working context can be time-consuming or even impossible; users may rely on their memory and may not be able to retrieve the relevant documents that they used before. Sometimes application provides a chronological history of recently opened documents (files, websites). However, it can be challenging to find the right information they need as there are many and users may not recognize from the text-based data (e.g. web page titles, document file name). Therefore, helping them reconstruct mental context and retrieving relevant applications and files can enhance overall productivity. To that end, the concept of self-tracking, which is widely used in health and fitness, is applied to the context of computer usage. In particular, the idea of using a history of a computer screen can provide visuals that users can associate with existing meta-data (file location, web page URL, time). A user can reconstruct working context from the screen visual that they recognize. The idea of using a visual history of a computer screen activities is tested through the development of ScreenTrack, a program that captures a computer screen regularly and let a user watch a time-lapse video made of computer screenshots, and retrieve applications, files, and web pages from a snapshot of a screen. I hypothesize that the chronological history of computer screen activities can effectively help users navigate visual working context and retrieve information that is associated with a snapshot. Through a controlled user study, it was found that participants were able to retrieve information that they were asked more quickly with ScreenTrack than the control condition with statistical significance (p<0.005). Besides, participants gave positive feedback on the software that they would like to use such software in their computers in various context, but expressed potential concerns of using such software for privacy and computer storage problems. In this thesis, I motivate the need of such software, review the related work, share the design consideration, and introduce design and implementation process, validate the effects of ScreenTrack with a controlled user study. / Master of Science / Nowadays, people spend a significant amount of time using computers at work, at home, or school. Users switch software frequently and are often interrupted or distracted while working. Hence recalling previous working context is inevitable for computer users. Recalling previous working context can take lots of time or even impossible. Because users may rely on their own memory and may not be able to recall and retrieve the relevant documents that they used before. Sometimes software provides a history of recently opened documents (files, websites). However, it can be challenging to find the right information they need as there are many recorded information. And users may not recognize documents of interest from the textual data (e.g. web page titles, document file name). Therefore, helping people restore previous working context and reopening relevant software and files can enhance overall productivity. I designed and developed a software, called ScreenTrack. This software can take pictures of current computer screen regularly and store them. Later, users can watch a video made of stored screenshots. Based on this video, individuals can recall their previous computer activities and reopen closed software, websites, files, and documents from a snapshot. Through a controlled user study, I found that participants were able to retrieve previous computer activities more quickly under the help of ScreenTrack than without ScreenTrack. With ScreenTrack, participants spend 27.1 seconds on average to reopen a previous closed website, 37% faster than without it. Furthermore, participants gave positive feedback on this software that they would like to use ScreenTrack in the future for various purposes, for doing researches and reading papers.

With changing climate, it is necessary to investigate how different plants are af- fected by drought, which is the starting point for this project. The proposed project aims to apply Machine Learning tools to learn predictive patterns of Scots pine seedlings in response to drought conditions by measuring the canopy area and growing rate of the seedlings presented in the time-lapse images. There are 5 different families of Scots Pine researched in this project, therefore 5 different sets of time-lapse images will be used as the data set. The research group has previously created a method for finding the canopy area and computing the growth rate for the different families. Furthermore, the seedlings rotate in an individual pattern each day, which could prove to affect their tolerance to drought according to the research group and is currently not being measured. Therefore, we propose a method using an object detection model, such as Mask R-CNN, to detect and find each seedling’s respective region of interest. With the obtained region of interest, the goal will be to apply an object-tracking algorithm, such as a Dense Optical Flow Algorithm. Using different methods, such as the Shi-Tomasi or Lucas Kanade method, we aim to find feature points and track motion between images to find the direction and velocity of the rotation for each seedling. The tracking algorithms will then be evaluated based on their performance in estimating the rotation features against an annotated sub-set of the time-lapse data set.

Le suivi temporel est un processus d’acquisition et d’analyse d’acquisitions multiples répétées au même endroit sur la même cible à différentes périodes de temps. Cela s’applique bien à l’exploration sismique quand les propriétés de la cible varient au cours du temps comme pour les réservoirs pétroliers. Cette technique de sismique, dite 4D en raison de l’intégration du temps dans la construction des images, permet une détection et une estimation des variations du sous-sol survenues lors de l’évolution en temps du milieu. En particulier, dans l’industrie, le suivi et la surveillance peuvent améliorer notre compréhension d’un réservoir de pétrole/gaz ou d’un site de stockage de CO2. Analyser la sismique 4D peut aider à mieux gérer les programmes de production des réservoirs. Ainsi, des acquisitions répétées permettent de suivre l’évolutiondes fronts de fluide injectés: on peut optimiser les programmes d’injection de fluides pour une récupération améliorée des hydrocarbures (enhanced oil recovery). Plusieurs méthodes ont été développées pour l’imagerie variable dans le temps en utilisant les informations des ondes sismiques. Dans ma thèse, je montre que l’inversion de forme d’onde complété (FWI) peut être utilisée pour cette imagerie. Cette m´méthode offre des images sismiques quantitatives haute résolution. Elle est une technique prometteuse pour reconstruire les petites variations de propriétés physiques macro-échelle du sous-sol. Sur une cible identifiée pour ces imageries 4D, plusieurs informations a priori sont souvent disponibles et peuvent être utilisées pour augmenter la résolution de l’image. J’ai introduit ces informations grâce à la définition d’un modèle a priori dans une approche classique FWI en l’accompagnant de la construction d’un modèle d’incertitudes a priori. On peut réaliser deux reconstructions indépendantes et faire la différence les reconstruits: on parle de différence parallèle. On peut aussi effectuer une différence séquentielle o`u l’inversion de l’ensemble de données de la second acquisition, dite moniteur, se fait `a partir du modèle de base et non plus à partir du modèle utilisé initialement. Enfin, l’approche double-différence conduit à l’inversion des différences entre les deux jeux de données que l’on rajoute aux données synthétiques du modèle de base reconstruit. J’étudie quelle stratégie est à adopter pour obtenir des changements vitesse plus précis et plus robustes. En plus, je propose une imagerie 4D ciblée en construisant un modèle d’incertitude a priori grâce `a une information (si elle existe) sur la localisation potentielle des variations attendues. Il est démontré que l’inversion 4D ciblée empêche l’apparition d’artéfacts en dehors des zones cibles: on évite la contamination des zones extérieures qui pourrait compromettre la reconstruction des changements 4D réels. Une étude de sensibilité, concernant l’échantillonnage en fréquence pour cette imagerie 4D, montre qu’il est nécessaire de faire agir simultanément un grand nombre de fréquences au cours d’un cycle d’inversion. Ce faisant, l’inversion fournit un modèle de base plus précis que l’approche temporelle, ainsi qu’un modèle des variations 4D plus robuste avec moins d’artéfacts. Toutefois, la FWI effectuée dans le domaine temporel semble être une approche plus intéressante pour l’imagerie 4D. Enfin, l’approche d’inversion 4D régularisée avec un modèle a priori est appliquée sur des ensembles de données réelles d’acquisitions sismiques répétées fournis par TOTAL. Cette reconstruction des variations locales s’inscrit dans un projet d’injection de vapeur pour améliorer la récupération des hydro-carbures: Il est possible de reconstituer des variations de vitesse fines causées par la vapeur injectée. / Time-lapse monitoring is the process of acquiring and analysing multiple seismic surveys, repeatedat the same place at different time periods. This seismic technique, called 4D becauseof the integration time in the construction of images, allows detection and estimation of thesubsurface parameter variations occured through a time evolution. Particularly, in industries,the monitoring can improve our understanding of a producing oil/gas reservoir and CO2 storagesite. Analyzing the time-lapse seismics can help to better manage production programsof reservoirs. In addition, repeated surveys can monitor the evolution of injected fluid frontsand can permit to optimize injection programs which are considered for enhanced oil recovery(EOR) techniques.Several methods have been developed for time-lapse imaging using seismic wave information.In my thesis, I show that full waveform inversion (FWI) can be used for time-lapseimaging, since this method delivers high-resolution quantitative seismic images. It is a promisingtechnique to recover small variations of macro-scale physical properties of the subsurface.In time-lapse applications, several sources of prior information are often available and shouldbe used to increase the image reliability and its resolution. I have introduced this informationthrough a definition of a prior model in a classical FWI approach by also considering a prioruncertainty model. In addition, I have suggested a dynamic weighting to reduce the importanceof these prior models in the final convergence. In realistic synthetic cases, I have shownhow the prior model can reduce the sensitivity of FWI to a less accurate initial model. It istherefore possible to obtain a highly accurate baseline model for 4D imaging.Once the baseline reconstruction is achieved, several strategies can be used to assess thephysical parameter changes. We can make two independent reconstructions of baseline andmonitor models and make subtraction of the two reconstructed models. This strategy is calledparallel difference. The sequential difference strategy inverts the monitor dataset starting fromthe recovered baseline model, and not from the model used initially. Finally, the doubledifferencestrategy inverts the difference data between two datasets which are added to thecalculated baseline data computed in the recovered baseline model. I investigate which strategyshould be adopted to get more robust and more accurate time-lapse velocity changes. Inaddition, I propose a target-oriented time-lapse imaging using regularized FWI including priormodel and model weighting, if the prior information exists on the location of expected variations.It is shown that the target-oriented inversion prevents the occurrence of artifacts outsidethe target areas, which could contaminate and compromise the reconstruction of the effectivetime-lapse changes.A sensitivity study, concerning several frequency decimations for time-lapse imaging, showsthat the frequency-domain FWI requires a large number of frequencies inverting simultaneously.By doing so, the inversion provides a more precise baseline model and more robust time-lapsevariation model with less artifacts. However, the FWI performed in the time domain appearsto be a more interesting approach for time-lapse imaging considering all frequency content.Finally, the regularized time-lapse FWI with prior model is applied to the real field timelapsedatasets provided by TOTAL. The reconstruction of local variations is part of a steaminjection project to improve the recovery of hydrocarbons: it is possible to reconstruct thevelocity variations caused by the injected steam.

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