Streams and rivers are examples of vital ecosystems that frequently undergo various environmental and anthropogenic stresses. A core question in population ecology is whether a given population will persist under changing ecological conditions. This thesis consists of three papers and is devoted to the mathematical analysis of responses of river-dwelling species to population persistence threats. The first paper presents a stochastic approach to the 'drift paradox' problem, where the classical reaction-advection-diffusion model is replaced by a birth-death-emigration process. We explore the effects of temporally varying flow on the persistence probability and highlight the importance of the benthic stage for the persistence of stream organisms. The second paper addresses the problem of river network fragmentation through disconnecting structures such as dams. We construct a population matrix model that incorporates the spatial structure of the studied river network and compare structural connectivity to an indicator of population persistence. The third paper adapts the same basic matrix model to examine fish response to disturbances travelling downstream from upstream sites. The study of these three aspects of persistence challenges for river populations contributes to the cumulative effects assessment on river networks.

L'oscillateur optoélectronique (OEO) a été introduit pour la première fois en 1996 par S. Yao et L. Maleki, en tant qu'oscillateur microondes à très faible bruit de phase et obtenu par synthèse directe. Les développements de l'OEO concernent les applications en photonique microondes, télécommunications optiques, radar et traitement du signal. Mais l'OEO devrait aussi pouvoir être utilisé dans le domaine des capteurs. Dans cette thèse nous étudiants plusieurs aspects de l'OEO pour son application à la mesure d'indice de réfraction d'un liquide. Compte tenu de sa structure l'OEO dépend fortement des conditions ambiantes d'utilisation. S'il n'est pas bien optimisé ni contrôlé, il ne peut pas fonctionner correctement sur une longue durée. Nous avons étudié les influences de la température sur le modulateur électrooptique (EOM) et sur le comportement global de l'OEO. Un contrôle de température réduit de façon significative le phénomène de dérive de l'EOM. Afin de la supprimer complètement, nous avons mis au point une instrumentation construite autour d'une carte DSP, permettant de détecter et compenser la dérive du point de fonctionnement optique de l'EOM tout en contrôlant simultanément sa température. Une première technique est basée sur un signal de test, basse fréquence, appliqué à l'électrode DC du modulateur. Une deuxième solution consiste à travailler sur la puissance optique en sortie du modulateur. En combinant les deux on peut profiter des avantages de ces deux méthodes. Utilisant ainsi l'OEO nous avons testé plusieurs configurations pour mesurer l'indice de réfraction de quatre solutions chimiques bien connues, nous avons obtenu une variance de 3 pour mille. Les résultats sont en assez bon accord avec les publications correspondantes. Enfin nous avons aussi introduit une nouvelle méthode pour améliorer les mesures d'indice de réfraction faites à long terme en suivant, grâce à un analyseur vectoriel de réseau, les évolutions au cours du temps du temps de propagation dans la fibre optique. En introduisant à partir de cette mesure une correction aux mesures de la fréquence d'oscillation il est possible de réduire les fluctuations de cette fréquence à seulement 606 Hz, sur une durée de 62 h, ce que l'on peut comparer aux 8 GHz de l'oscillateur. Ainsi le rapport signal à bruit, peut être grandement amélioré lors de la mesure d'indice de réfraction et il doit être possible de diminuer la limite de détection des variations de l'indice de réfraction au cours du temps. / The optoelectronic oscillator (OEO) was first introduced in 1996 by S. Yao and L. Maleki as a very low phase noise microwave oscillator working in direct synthesis. The OEO developments concern applications in microwave photonics, optical telecommunication, radar and high speed signal processing systems but it should also be used in the sensing domain. In this thesis, we study several aspects to apply the OEO to liquid refractive index measurement. Because of its structure the OEO is very dependent on the ambient conditions. If the OEO is not optimized and controlled, it cannot operate well for long duration. We have analyzed the influences of temperature on the electrooptic modulator (EOM) and the global OEO behavior. Temperature control can significantly reduce the drift phenomena of the EOM. In order to totally remove this drift, we have developed a complete digital system, based on a DSP kit, to detect and compensate automatically the EOM optical bias point drift and to control simultaneously its temperature. The first technique is based on a dither signal at low frequency, injected to DC electrode of the EOM. The second one is based on the average optical output power of the EOM. A combination of these two techniques can take advantages from both of them. Using like that the OEO, we have tested several configurations to measure the refractive index of four classical chemical solutions leading to a standard deviation of 3 per thousand. The results are in rather good agreement with previous publications. Finally, we have introduced a new method to improve the long-term refractive index measurement by monitoring, with a vector network analyzer, the variations of the optical delay in the fiber loop of the OEO. Introducing by this way a correction to the long-term frequency measurement it is possible to reduce the oscillation frequency fluctuations to only 606 Hz, compared to the 8 GHz of the oscillator, for a duration of 62 hours. Therefore the signal-to-noise ratio in the refractive index measurement can be enhanced and so the detection resolution of the refractive index variations during time.

Essa dissertação é um trabalho na área de geoestatística aplicada à avaliação de recursos minerais. Esta aplicação pode ser considerada o passo anterior à avaliação das reservas minerais. Os conceitos básicos são fundamentados na geoestatística atual, com amplo uso de recursos de informática. O objetivo principal foi de testar a técnica da krigagem com deriva externa na avaliação de recursos minerais, principalmente no que tange o ganho de resultado com a utilização de mais de uma variável, ou seja, verificar se o uso de variáveis auxiliares pode ser feito de maneira amigável com bom custo/benefício. Foram escolhidos dois depósitos, com geologias distintas entre si, um depósito de metal base com minério saprolítico e outro depósito de calcário. Em cada um foram selecionadas duas variáveis, uma variável principal e outra secundária, no depósito laterítico as variáveis foram \'SiO IND.2\' e Fe e no depósito de calcário as variáveis foram CaO e \'SiO IND.2\'. Foi elaborada a modelagem tridimensional dos depósitos no programa Datamine. Os modelos foram transferidos para o programa Isatis e serviram como base para a estimativa das variáveis. Essa modelagem foi necessária para que se pudesse dar aos blocos estimados a geometria do corpo do minério. A estimativa por krigagem com deriva externa foi comparada à krigagem ordinária, essa comparação serviu para mensurar as diferenças em relação a um método tradicional amplamente usado e divulgado com outro pouco utilizado, ou mesmo difundido. Os resultados mostraram pequenas diferenças entre os blocos estimados por krigagem com deriva externa e por krigagem ordinária. Porém como na mineração podem ocorrer situações de sub-amostragem, por diversos fatores, pode-se afirmar que a krigagem com deriva externa é uma alternativa válida, pois demanda menos esforço na estimativa multivariada do que, por exemplo, a cokrigagem ordinária. / This dissertation is a work on applied geostatistics to evaluation of mineral resources. This application can be considered as the last step to such the task. The basic concepts are based on current geostatistics, with extensive use of informatics resources. The first goal of this work was to test the technique named kriging with external drift in the evaluation of mineral resources, concerning to the resulting gain in the use of more than one variable, mainly whether the use of auxiliary variables con be done in a friendly way. Two deposits were chosen with different geology, a deposit of base metal saprolitic ore and another deposit of limestone. In each deposit two variables were selected, the principal and secondary variable, at lateritic deposit variables were respectively \'SiO IND.2\' and Fe and at the deposit of limestone were CaO and \'SiO IND.2\'. The three-dimensional modeling of the deposits was made in the software Datamine. The models were transferred to the software Isatis and used as the base for interpolate variables. This model was necessary in the way to print in the estimated blocks the geometry of the ore body. Estimates by kriging with external drift was compared to ordinary kriging, ones this comparison was done to measure the differences between a traditional method widely used to another underutilized, or even non widespread. Results showed minor differences between the blocks estimated by bolth methods. But as in mining sub-sampling can occur from several factors, one can say that the kriging with external drift is a reliable alternative since it requires less effort to perform multivariate estimation than those, for example, to perform the ordinary cokriging.

Several industrial, scientific and commercial processes produce open-ended sequences of observations which are referred to as data streams. We can understand the phenomena responsible for such streams by analyzing data in terms of their inherent recurrences and behavior changes. Recurrences support the inference of more stable models, which are deprecated by behavior changes though. External influences are regarded as the main agent actuacting on the underlying phenomena to produce such modifications along time, such as new investments and market polices impacting on stocks, the human intervention on climate, etc. In the context of Machine Learning, there is a vast research branch interested in investigating the detection of such behavior changes which are also referred to as concept drifts. By detecting drifts, one can indicate the best moments to update modeling, therefore improving prediction results, the understanding and eventually the controlling of other influences governing the data stream. There are two main concept drift detection paradigms: the first based on supervised, and the second on unsupervised learning algorithms. The former faces great issues due to the labeling infeasibility when streams are produced at high frequencies and large volumes. The latter lacks in terms of theoretical foundations to provide detection guarantees. In addition, both paradigms do not adequately represent temporal dependencies among data observations. In this context, we introduce a novel approach to detect concept drifts by tackling two deficiencies of both paradigms: i) the instability involved in data modeling, and ii) the lack of time dependency representation. Our unsupervised approach is motivated by Carlsson and Memolis theoretical framework which ensures a stability property for hierarchical clustering algorithms regarding to data permutation. To take full advantage of such framework, we employed Takens embedding theorem to make data statistically independent after being mapped to phase spaces. Independent data were then grouped using the Permutation-Invariant Single-Linkage Clustering Algorithm (PISL), an adapted version of the agglomerative algorithm Single-Linkage, respecting the stability property proposed by Carlsson and Memoli. Our algorithm outputs dendrograms (seen as data models), which are proven to be equivalent to ultrametric spaces, therefore the detection of concept drifts is possible by comparing consecutive ultrametric spaces using the Gromov-Hausdorff (GH) distance. As result, model divergences are indeed associated to data changes. We performed two main experiments to compare our approach to others from the literature, one considering abrupt and another with gradual changes. Results confirm our approach is capable of detecting concept drifts, both abrupt and gradual ones, however it is more adequate to operate on complicated scenarios. The main contributions of this thesis are: i) the usage of Takens embedding theorem as tool to provide statistical independence to data streams; ii) the implementation of PISL in conjunction with GH (called PISLGH); iii) a comparison of detection algorithms in different scenarios; and, finally, iv) an R package (called streamChaos) that provides tools for processing nonlinear data streams as well as other algorithms to detect concept drifts. / Diversos processos industriais, científicos e comerciais produzem sequências de observações continuamente, teoricamente infinitas, denominadas fluxos de dados. Pela análise das recorrências e das mudanças de comportamento desses fluxos, é possível obter informações sobre o fenômeno que os produziu. A inferência de modelos estáveis para tais fluxos é suportada pelo estudo das recorrências dos dados, enquanto é prejudicada pelas mudanças de comportamento. Essas mudanças são produzidas principalmente por influências externas ainda desconhecidas pelos modelos vigentes, tal como ocorre quando novas estratégias de investimento surgem na bolsa de valores, ou quando há intervenções humanas no clima, etc. No contexto de Aprendizado de Máquina (AM), várias pesquisas têm sido realizadas para investigar essas variações nos fluxos de dados, referidas como mudanças de conceito. Sua detecção permite que os modelos possam ser atualizados a fim de apurar a predição, a compreensão e, eventualmente, controlar as influências que governam o fluxo de dados em estudo. Nesse cenário, algoritmos supervisionados sofrem com a limitação para rotular os dados quando esses são gerados em alta frequência e grandes volumes, e algoritmos não supervisionados carecem de fundamentação teórica para prover garantias na detecção de mudanças. Além disso, algoritmos de ambos paradigmas não representam adequadamente as dependências temporais entre observações dos fluxos. Nesse contexto, esta tese de doutorado introduz uma nova metodologia para detectar mudanças de conceito, na qual duas deficiências de ambos paradigmas de AM são confrontados: i) a instabilidade envolvida na modelagem dos dados, e ii) a representação das dependências temporais. Essa metodologia é motivada pelo arcabouço teórico de Carlsson e Memoli, que provê uma propriedade de estabilidade para algoritmos de agrupamento hierárquico com relação à permutação dos dados. Para usufruir desse arcabouço, as observações são embutidas pelo teorema de imersão de Takens, transformando-as em independentes. Esses dados são então agrupados pelo algoritmo Single-Linkage Invariante à Permutação (PISL), o qual respeita a propriedade de estabilidade de Carlsson e Memoli. A partir dos dados de entrada, esse algoritmo gera dendrogramas (ou modelos), que são equivalentes a espaços ultramétricos. Modelos sucessivos são comparados pela distância de Gromov-Hausdorff a fim de detectar mudanças de conceito no fluxo. Como resultado, as divergências dos modelos são de fato associadas a mudanças nos dados. Experimentos foram realizados, um considerando mudanças abruptas e o outro mudanças graduais. Os resultados confirmam que a metodologia proposta é capaz de detectar mudanças de conceito, tanto abruptas quanto graduais, no entanto ela é mais adequada para cenários mais complicados. As contribuições principais desta tese são: i) o uso do teorema de imersão de Takens para transformar os dados de entrada em independentes; ii) a implementação do algoritmo PISL em combinação com a distância de Gromov-Hausdorff (chamado PISLGH); iii) a comparação da metodologia proposta com outras da literatura em diferentes cenários; e, finalmente, iv) a disponibilização de um pacote em R (chamado streamChaos) que provê tanto ferramentas para processar fluxos de dados não lineares quanto diversos algoritmos para detectar mudanças de conceito.

The purpose of this study is to investigate how teachers with different educational and subject backgrounds co-exist within the same framework of the same education. Previous research suggests that this teacher composition should lead to conflict. But it does not provide any explanations as to how these conflicts are expressed or managed. To illustrate how potential conflicts are expressed or managed, 12 teachers from various Swedish police educations have been interviewed. The theoretical basis is a merging between institutional logics and inhabitant institutions, as a way to direct analytical focus to what happens on the micro level, between the teachers in their daily work. This analytical level has often been neglected in previous research, and this study is a way to contribute to the research about academic drift. The results show that police education is populated by teachers whom we can understand as carriers of different logics. Two logics emerged as particularly contrasting, which I chose to name police logic and academy logic. This means that the teachers was carriers of different ideologically colored norm structures. The results also indicated that the police students were carriers of the police logic. Despite this, I saw no clear traces of conflict. One explanation for this was that teachers' interaction patterns were limited by the organization of the education. One consequence of this was that the teachers with different educations and subject matter rarely met, and conflicts were avoided. In the concrete teaching situation, the two logics met and the teachers needed to find some form of co-existence, especially in relation to the police students. Using Erving Goffman´s concept of cooling out, I found three different cooling out strategies that the teachers used. A central result was that the logics were superior to the teachers. The important thing for the students was not who taught, but what was taught, and that the teaching contents, in the students’ view, had clear professional relevance.

In the fall of 2019, a comprehensive idea study was conducted on heat storage in two rock caverns located at Näsudden in Skelleftehamn and was part of the project course "Energiteknik, huvudkurs" at Luleå University of Technology. This idea study investigated the conditions of using waste heat from Boliden AB:s copper smeltery (Rönnskär) and storing this waste heat in two rock caverns and use them as seasonal thermal storage tanks, with the purpose of using the heat in the nearby district heating network, thus replacing some of the oil burned at Rönnskär. To investigate this, the authors of the idea study looked at two different storage cycles of seasonal storage and modeled this in ANSYS Fluent to simulate the heat storage and the heat losses. The results from this idea study showed promising results for using these caverns as heat storage and this work is therefore a continuation of the idea study. Since the study provided a good understanding of the conditions for seasonal storage, some questions arose about how the rock caverns will behave during an intermittent operation, which is the planned mode of operating the caverns in case of deployment. In this thesis, intermittent operation of these caverns are explored and how this effects the temperature in the caverns and its surrondings, the charge/discharge speed, how insulated walls affect the operation and how much oil is replaced. At the beginning of this project a review of the idea study and similar projects was done to gain deeper knowledge about the subject, but also to get a wider grasp on the different problems that could arise during the thesis. Relevant data for the caverns was collected and acquired to get a deeper understanding of its geometry, layout and what kind of modifications are really possible. Further data from the district heating networks of Boliden AB and Skellefteå Kraft was acquired. The available waste heat from Rönnskär was examined and used to calculate the chargeable energy by hour for the caverns, with the limits of Skelleftehamn district heating network in mind. By examining the different steam boiler patterns, the discharge pattern could be calculated. Using CFD, the unknown global heat transfer coefficient between the cavern water and the cavern wall can be determined. This data was then used with a set of differential equations to model the behavior of the caverns in Simulink. This allowed to determine the behavior for the caverns during normal operation, such as how the heat losses evolve, how the temperatures fluctuate, how much heat the caverns can be charged with and how much they can discharge. The results from the simulations showed that the caverns discharge a higher amount of energy when operating intermittently than when operating seasonally. Depending on how the caverns are utilized, different amounts of discharged energy are obtained. This range from 2224,7MWh to 7846,1MWh for the different discharging patterns. The usage also affects the efficiency of the cavern giving the efficiency a range between 19% to 53,9%. The heat losses range from around 20kW to 1000kW, depending on operation. Insulating the cavern walls reduces on average the heat losses by a factor of 5. Operating the caverns intermittently would on average remove a total of 29 ktonne CO2 and 88,74 tonne NOx for its expected lifespan of 30 years. Economically, the rock caverns have good economic potential as they would save about 80 million SEK during their lifetime just from buying less oil. / Hösten 2019 genomfördes en omfattande idéstudie om värmelagring i två bergrum vid Näsudden i Skelleftehamn och var en del av projektkursen "\textit {Energiteknik, huvudkurs}" vid Luleå tekniska universitet. Denna idéstudie undersökte villkoren för att använda spillvärme från Boliden AB:s kopparsmältverk (Rönnskär) och lagra denna värme i bergrummen och använda dem som säsongslagrade ackumulatortankar. Syftet med detta var att använda värmen i det närliggande fjärrvärmenätverket och därmed ersätta en del av den förbrända oljan hos Rönnskär. Författarna utforskade detta genom att undersöka två olika lagringscykler för säsongslagring och modellerade detta i ANSYS Fluent för att simulera värmelagring och värmeförluster. Resultaten från idéstudien visade lovande resultat för säsongsbaserad värmelagring i dessa bergrum och detta arbete är därför en fortsättning av idéstudien. Eftersom studien gav en god förståelse för förhållandena för säsongslagring, uppstod några frågor om hur bergrummen kommer att bete sig under en intermittent drift, vilket är den planerade driften av bergrummen vid en framtida användning. I detta projekt undersöks intermittent drift av dessa bergrum och hur detta påverkar temperaturen i bergrummen och dess omgivning, laddnings- / urladdningshastigheten, hur isolerade väggar påverkar driften och hur oljeförbrukningen reduceras. I början av detta projekt gjordes en genomgång av idéstudien och liknande projekt för att få djupare kunskap om ämnet, men också för att få ett bredare grepp om de olika problem som kan uppstå under arbetets gång. Relevant data för bergrummen samlades in och anskaffades för att få en djupare förståelse för dess geometri, layout och vilken typ av ändringar som verkligen är möjliga. Ytterligare data från fjärrvärmenätverket för Boliden AB och Skellefteå Kraft förvärvades. Den tillgängliga spillvärme från Rönnskär undersöktes och användes för att beräkna den urladdningsbara energin per timme för bergrummen, med begränsningarna i Skelleftehamns fjärrvärmenät i åtanke. Genom att undersöka de olika ångpannmönstren kan urladdningsmönstret beräknas. Med hjälp av CFD kan den okända globala värmeöverföringskoefficienten mellan bergrumsvattnet och bergväggen bestämmas. Denna data användes sedan med en uppsättning differentialekvationer för att modellera driften av bergrummen i Simulink. Detta gjorde det möjligt att bestämma beteendet för bergrummen under normal drift, till exempel hur värmeförlusterna utvecklas, hur temperaturen fluktuerar, hur mycket värme bergrummen kan laddas med och hur mycket de kan ladda ur. Resultaten från simuleringarna visade att bergrummen kan ladda ur en större mängd energi än vid en säsongsbetonad drift. Beroende på hur grottorna utnyttjas erhålls olika mängder urladdad energi. Detta sträcker sig från 2224,7MWh till 7846,1MWh för de olika urladdningsmönstren. Användningen påverkar också grottans effektivitet vilket ger en effektivitet mellan 19% och 53,9%. Värmeförlusterna sträcker sig från cirka 1000 kW till 20kw, beroende på drift. Isolering av bergväggarna minskar i genomsnitt värmeförlusten med en faktor 5. Att använda grottorna intermittent skulle i genomsnitt ersätta totalt 29 kton CO2 och 88,74 ton NOx för den förväntade livslängden på 30 år. Bergrummen har även god ekonomisk potential eftersom de skulle spara cirka 80 miljoner SEK under sin livstid bara från minskade oljekostnader.

L'ère du Big Data a révolutionné la manière dont les données sont créées et traitées. Dans ce contexte, de nombreux défis se posent, compte tenu de la quantité énorme de données disponibles qui doivent être efficacement gérées et traitées afin d’extraire des connaissances. Cette thèse explore la symbiose de l'apprentissage en mode batch et en flux, traditionnellement considérés dans la littérature comme antagonistes, sur le problème de la classification à partir de flux de données en évolution. L'apprentissage en mode batch est une approche bien établie basée sur une séquence finie: d'abord les données sont collectées, puis les modèles prédictifs sont créés, finalement le modèle est appliqué. Par contre, l’apprentissage par flux considère les données comme infinies, rendant le problème d’apprentissage comme une tâche continue (sans fin). De plus, les flux de données peuvent évoluer dans le temps, ce qui signifie que la relation entre les caractéristiques et la réponse correspondante peut changer. Nous proposons un cadre systématique pour prévoir le surendettement, un problème du monde réel ayant des implications importantes dans la société moderne. Les deux versions du mécanisme d'alerte précoce (batch et flux) surpassent les performances de base de la solution mise en œuvre par le Groupe BPCE, la deuxième institution bancaire en France. De plus, nous introduisons une méthode d'imputation évolutive basée sur un modèle pour les données manquantes dans la classification. Cette méthode présente le problème d'imputation sous la forme d'un ensemble de tâches de classification / régression résolues progressivement.Nous présentons un cadre unifié qui sert de plate-forme d'apprentissage commune où les méthodes de traitement par batch et par flux peuvent interagir de manière positive. Nous montrons que les méthodes batch peuvent être efficacement formées sur le réglage du flux dans des conditions spécifiques. Nous proposons également une adaptation de l'Extreme Gradient Boosting algorithme aux flux de données en évolution. La méthode adaptative proposée génère et met à jour l'ensemble de manière incrémentielle à l'aide de mini-lots de données. Enfin, nous présentons scikit-multiflow, un framework open source en Python qui comble le vide en Python pour une plate-forme de développement/recherche pour l'apprentissage à partir de flux de données en évolution. / The Big Data era has revolutionized the way in which data is created and processed. In this context, multiple challenges arise given the massive amount of data that needs to be efficiently handled and processed in order to extract knowledge. This thesis explores the symbiosis of batch and stream learning, which are traditionally considered in the literature as antagonists. We focus on the problem of classification from evolving data streams.Batch learning is a well-established approach in machine learning based on a finite sequence: first data is collected, then predictive models are created, then the model is applied. On the other hand, stream learning considers data as infinite, rendering the learning problem as a continuous (never-ending) task. Furthermore, data streams can evolve over time, meaning that the relationship between features and the corresponding response (class in classification) can change.We propose a systematic framework to predict over-indebtedness, a real-world problem with significant implications in modern society. The two versions of the early warning mechanism (batch and stream) outperform the baseline performance of the solution implemented by the Groupe BPCE, the second largest banking institution in France. Additionally, we introduce a scalable model-based imputation method for missing data in classification. This method casts the imputation problem as a set of classification/regression tasks which are solved incrementally.We present a unified framework that serves as a common learning platform where batch and stream methods can positively interact. We show that batch methods can be efficiently trained on the stream setting under specific conditions. The proposed hybrid solution works under the positive interactions between batch and stream methods. We also propose an adaptation of the Extreme Gradient Boosting (XGBoost) algorithm for evolving data streams. The proposed adaptive method generates and updates the ensemble incrementally using mini-batches of data. Finally, we introduce scikit-multiflow, an open source framework in Python that fills the gap in Python for a development/research platform for learning from evolving data streams.

Bakgrund: Sedan slutet av 1960-talet har flera studier kunnat påvisa drift i aktiepriset efter att ett bolag publicerat en kvartalsrapport, något som benämns som Post-earningsannouncement drift (PEAD). När bolagets resultat varit bättre än det marknaden förväntade sig har aktiepriset fortsatt stiga under en längre period, vilket går emot etablerade hypoteser om en effektiv marknad. Det motsatta har skett när bolaget publicerat ett sämre resultat än vad marknaden förväntat sig. Eftersom den svenska marknaden är relativt outforskad och att den kontinuerligt förändras är det intressant att undersöka om den anomali som nyss beskrivits fortsatt existerar på Stockholmsbörsen, om den går att använda som lönsam investeringsstrategi och huruvida det finns skillnader i aktieprisdrift mellan branscher eftersom det aldrig tidigare studerats. Syfte: Syftet med studien är att analysera huruvida PEAD förekommer på Nasdaq Stockholmsbörsen och om det existerar skillnader i aktieprisdrift mellan branscher under perioden 2014–2018. Studien avser vidare studera om det är möjligt att utforma en lönsam investeringsstrategi baserad på PEAD. Metod: För att uppnå studiens syfte tillämpades en deduktiv ansats och en kvantitativ metod. För att analysera PEAD på Stockholmsbörsen baserades portföljer på Unexpected Earnings (UE) och två modeller benämnda Buy-and-hold-abnormal returns (BHAR) och Calendar-Time regression model (CTP) användes för att illustrera och testa portföljernas avkastning. Resultat: Studiens resultat tyder på att PEAD fortfarande existerar på Stockholmsbörsen, men att resultatet skiljer sig något från tidigare studier. En drift i positiv riktning påvisas i innevarande studie i portföljer av bolag som publicerat såväl bättre som sämre resultat än vad marknaden förväntat sig. I tidigare studier har portföljer av bolag som publicerat sämre resultat än marknaden förväntat sig istället haft en negativ. Vidare visar resultatet att det återfunnits skillnader i drift mellan undersökta branscher och att PEAD sannolikt inte är en lönsam investeringsstrategi. / Background: Since the end of 1960 several studies has indicated a delay in stock price movements after the publishing of a company's interim report. When the earnings of a company were higher than expected, the stock price continued to rise for an extended period, which contradicts the different hypothesis of efficient markets. The opposite effect was observed when the earnings were lower than expected. Due to the limited number of studies regarding PEAD conducted on the Swedish stock market, and the fact that the stock markets are constantly changing, it is interesting to examine and analyze if the anomaly still exists on Stockholmsbörsen. Another point of interest to research is whether it would be possible to earn abnormal returns through a PEAD investment strategy and analyze if there are differences in drift depending on the industry. Aim: The aim of this study is to analyze whether PEAD exists on Nasdaq Stockholmsbörsen and if differences in stock price drift exists between industries during the period 2014-2018. The study further means to study whether it is possible to implement a profitable investment strategy based on PEAD. Methodology: In order to reach the aim of the study a quantitative method and deductive approach were used. In order to analyze PEAD on the Swedish stock market portfolios based on Unexpected Earnings (UE) were formed and two models named Buy-and-hold-abnormal returns (BHAR) and Calendar-Time regression model (CTP) were used in order to illustrate and test the portfolio returns. Results: The results of the study indicated that PEAD exists on Stockholmsbörsen, but that the results differ from previous studies. A positive drift was observed in both the portfolios which were based on positive and negative earnings surprises in relation to the market's expectations. In previous studies the portfolio based on companies which reported negative earnings surprise had a negative drift, which differs from this study’s results. Furthermore, this study’s results indicate that an investment strategy based on PEAD is not profitable and that differences in drift could be observed depending on the industry.

Study of Production Drifts Stability and Assessment of Reinforcement Requirements at LKAB Konsuln Test-Mine Levels 436 and 486 Using Geologic Structures Data, and Modelling Software - Dips and Unwedge:  a Part of dp1 Project (Mine Layout and Technology) of the Sustainable Underground Mining (Sum) Project Oludare Joseph Olufe Global population has been on exponential increase over the past half century. The population explosion is driving massive urbanization and infrastructure developments across the globe, which result in huge demand for metals, especially steel. The trend is forecasted to continue to rise steeply in for the next two decades. This is putting enormous strain on metals mining, especially because new surface economic deposits are rare to come by. Therefore, mining is steadily going deeper in many of the mining destinations across the world.     Mining at great depths present unique challenges, particularly regarding stability of excavations at depths. Rock falls, rock burst, excavation collapse are common occurrences associated with deep mining. In regions with high seismicity potentials the frequency and consequences could be very high. Over the past decade ground instability has become a significant challenge confronting mining at LKAB deep mines. There had been incidents that resulted in long term closure of sections of the mines, with resultant adverse economic impacts. More undesirable is loss of live of personnel.     The study was conducted at the Konsuln test mine levels 436 and 486, aimed to investigate the impacts of geologic structures on excavations instability at depths, at the Kiruna iron ore mines, on one hand.  And on the other hand, evaluate the influence of geologic structures on ground reinforcements at the mine. Structural data were collected and analysed using Dips program to define orientation of major structures. The results were used for wedge analysis and excavations stability modelling using Unwedge program. Important rock mechanical parameters were defined based on data provided, and others based on literatures. A design factor of safety of 1.5 was used.     Results from the study established that structures have significant impact on excavations instability at the Konsuln mine. 100% of the production drifts studied has minimum of four wedges formed in its perimeters. Out of this approximately 37% has factor of safety lower than 1.5. Evaluation of reinforcements (shotcrete and rock bolts) implemented in the mine found that approximately 15% of the total wedges formed in the production drifts has factor of safety less that 1.5 after both shotcrete and rock bolt reinforcements had been implement. Also, approximately 5% of the total wedges has apex height longer the rock bolt length.     It was therefore concluded that structurally induced instability is a major contributor to excavations instability at the Kiruna mine. The study approach presented a new methodology to understand and provide robust solution to ground instability problem at the mine.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第23506号 / 工博第4918号 / 新制||工||1768(附属図書館) / 京都大学大学院工学研究科原子核工学専攻 / (主査)教授 中島 健, 教授 横峯 健彦, 准教授 山本 俊弘 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM