Sound pressure equalization of audio signals using digital signal processors has been a subject of ongoing study for many years. The traditional approach is to equalize sound at a point in a listening environment, but because of its specific dependence on the room frequency response between a source and receiver position, this equalization generally causes the spectral response to worsen significantly at other locations in the room. This work presents both a time-invariant and a time-varying implementation of an adaptive acoustic energy density equalization filter for a one-dimensional sound field. Energy density equalization addresses the aforementioned challenge and others that relate to sound equalization. The theory and real-time implementation of time-invariant sound pressure and energy density equalizers designed using the least-squares method are presented, and their performances are compared. An implementation of a time-varying energy density equalizer is also presented. Time-invariant equalization results based on real-time measurements in a plane-wave tube are presented. A sound pressure equalizer results in a nearly flat spectral magnitude at the point of equalization. However, it causes the frequencies corresponding to spatial nulls at that point to be undesirably boosted elsewhere in the sound field, where those nulls do not exist at the same frequencies. An energy density equalization filter identifies and compensates for all resonances and other global spectral effects of the tube and loudspeaker. It does not attempt to equalize the spatially varying frequency nulls caused by local pressure nodes at the point of equalization. An implementation of a time-varying energy density equalizer is also presented. This method uses the filtered-x filter update to adjust the filter coefficients in real-time to adapt to changes in the sound field. Convergence of the filter over time is demonstrated as the closed end of the tube is opened, then closed once again. Thus, the research results demonstrate that an acoustic energy density filter can be used to time-adaptively equalize global spectral anomalies of a loudspeaker and a one-dimensional sound field.

This thesis is, to my knowledge, the first study utilising data from the Swedish population and housing censuses between 1960 and 1990 merged with other data from the same period in order to estimate extensive margin labour supply responses to changes in municipal tax rate changes. Given that women historically have not faced the same structural labour market preconditions as men, the empirical strategy is designed to allow for an analysis of gender-based heterogeneity in labour supply responses. Using a weighted fixed effects framework, estimates of the average over time between municipal effects of tax rate increases are presented. Using the preferred main model specification, the estimate for the average tax rate elasticity is -0.165 for men and 0.3513 for women. Additionally, an attempt is made to estimate an effect using a difference-in-difference framework, treating the overall largest municipal tax rate changes as a form of quasi-experimental treatment. The results of the main analysis indicate the presence of gender-based heterogeneity in extensive margin labour supply responses during 1960 to 1990 within the administrative region in question.

Torgen har under en väldigt lång tid i människans historia spelat en viktig funktion i människors liv. Stadens öppna platser har fungerat som en social mötesplats och detta ända sedan antikens dagar. Under mitten av 1800-talet fram till vår tid har torgen dessvärre börjat att alltmer tappa fokus som en social katalysator med liv och rörelse. Torgen blev snarare politiska platser och mer en maktsymbol än en mötesplats. Under 1900-talet uppkom andra motkrafter till torgens existens som en social plats. Mycket av detta berodde på bilen, men även på grund av nya levnadsvillkor och estetiska ideal. Som följd av den moderna stadsutvecklingen har dessutom små butiker flyttat från torget för att bilda större enheter.  Men hur kan man transformera ett äldre torg till hur det en gång var eller borde ha varit? Under arbetets gång med detta omgestaltningsförslag av Davidhallstorg har det visat sig att dagens torg till stor del skiljer sig från torgens ursprungliga funktion. Gestaltningen försöker därför lösa problemet med problem som dagens storstadstorg kan ställas inför, såsom alldeles för dominerade av biltrafik och bilens behov och för lite aktiviteter. Förr i tiden ansågs städernas torg vara deras mittpunkter, och de var fulla av liv och rörelse. Arbetet i denna studie har fokuserat på att hitta en mer lämplig design för ett torg i centrala Malmö och därigenom försöka ge det tillbaka mer liv och rörelse som en social mötesplats.  Resultatet visar sig att torg är sociala mötesplatser som måste finnas kvar för att skapa sociala mötesplatser utomhus för människor i storstadsmiljö. Därför är det inte lämpligt eller rekommenderat att ”slösa” bort torgyta till stora bilparkeringar. Studien visar att funktionen som torgen har trots allt är viktig än idag att skapa en bakgrund till formella och informella möten mellan människor, en social mötesplats för människor. Bara för vi lever i nya moderna tider betyder det inte att vi ändå inte är beroende av att möta och umgås med andra människor. Torgen utgör en utmärkt plats för detta. Torg behöver uppdateras med sina ändrade invånare, dvs. återupplivas så att de åter fyller en funktion som passar dagens krav och behov. Gestaltningsförslaget visar på vikten av att låta torgen leva upp tills sin rätta funktion och placera bilen i kanten eller under torget.  Det går inte att glömma bort att bilen trots allt ännu är en stor del av vår vardag. Gestaltningsförslaget försöker hitta en lösning där både människa och maskin kan ta plats och vistas utan att den andra tar över för mycket, detta är av stor vikt. / For a very long time in human history, squares have played an important role in people's lives. The city's open spaces have functioned as a social meeting place since the days of antiquity. During the middle of the 19th century until our time, the squares have unfortunately begun to lose focus more and more as a social catalyst with life and movement. The squares became rather political places and more a symbol of power than a meeting place. During the 20th century, other counterforces arose to the existence of the squares as a social place. Much of this was due to the car, but also due to new living conditions and aesthetic ideals. As a result of modern urban development, small shops have also moved from the square to form larger units. But how can one transform an older square into what it once was or should have been? During the work on this redesign proposal of Davidshallstorg, it has turned out that today's square is largely different from the squares' original function. The design therefore tries to solve the problem with problems that today's metropolitan squares can be faced with, such as being far too dominated by car traffic and the car's needs and too few activities. In the past, the town squares were considered to be their centers, and they were full of life and movement. The work in this study has focused on finding a more suitable design for a square in central Malmö and thereby trying to give it back more life and movement as a social meeting place. The result shows that squares are social meeting places that must remain in order to create social meeting places outdoors for people in a metropolitan environment. Therefore, it is not appropriate or recommended to "waste" square space to large car parks. The study shows that the function that the squares have, after all, is still important today to create a background for formal and informal meetings between people, a social meeting place for people. Just because we live in new modern times does not mean that we are still not dependent on meeting and socializing with other people. The squares are an excellent place for this. Squares need to be updated with their changed inhabitants, ie. revived so that they again fulfill a function that suits today's requirements and needs. The design proposal shows the importance of letting the squares live up to their proper function and placing the car at the edge or under the square. It is not possible to forget that the car is still a big part of our everyday life after all. The design proposal tries to find a solution where both man and machine can take place and stay without the other taking over too much, this is of great importance.

Trygghetsarbete ärnågot som både statliga myndigheter och kommuner intresserar sig för. Kommunernämner gärna i sina översiktsplaner att trygghetsfrämjande åtgärder ska vidtasoch att områden ska utvecklas med hänsyn till tryggheten. Hur dettatrygghetsarbete tar sig form i den fysiska miljön är mindre tydligt och syftetmed denna studie har således varit att ta fram aspekter som går att arbeta medför att främja trygghet. Dessa aspekter har sedan använts för att analyseratorg i Stockholm stad, Nacka kommun och Vaxholm stad för att se hur väl torgensvarar mot dessa aspekter. Aspekterna som tagits fram med hjälp av enlitteraturstudie och den fallstudie som har utförts har sedan legat till grundför att ta fram tips för hur trygga torg kan utformas.Litteraturstudien ledde till att fem aspekter av stor betydelse för trygghetentogs fram: närhet till andra människor, synlighet och överblickbarhet,belysning, grönska och skötsel av allmän plats. Inget av de torg som omfattadesav fallstudien uppnådde samtliga trygghetsaspekter, men vissa uppfyllde fler änandra. Utöver de slutsatser som har dragits kring vilka aspekter som är trygghetsfrämjandeså ledde studien till slutsatser kring vilka torg som uppfyller vilka aspekter.Slutligen ledde studien fram till konkreta förbättringsförslag för trygghetenpå de torg som fallstudien omfattade och handfasta tips för hur torg kanutformas med hänsyn till trygghet / Working with perceived safety is something that both government agencies and municipalities are interested in. Municipalities gladly mention in their general plans that perceived safety actions is something that should be prioritised and that new areas should be developed with regard to the perceived safety. Exactly how these perceived safety actions takes shape in the physical environment is less clear and the purpose has thus been to identify aspects that are possible to work with and that promotes the perceived safety. The identified aspects have then been used to analyse squares in Stockholm stad, Nacka kommun and Vaxholm stad to see how well these places correspond to the these aspects. Tips on how squares that are perceived as safe was then formulated based on the case study and the aspects that was identified in the literature study.The literature study led to the identification of five aspects with great significance to the perceived safety: closeness to other people, visibility and overview, lightning, greenery and maintenance of public space. None of the observed squares fulfill all the aspects, but some fulfill more than others. Other than the conclusions that were drawn concerning which aspects that are promoting for the perceived safety, the study also led to conclusions regarding which squares that fulfill which aspects. Finally the study led to improvement-proposals for perceived safety on the squares of the case study and concrete tips on how squares can be designed with regard to perceived safety.

It is estimated that about 35-40% of adults in the U.S. suffer from insufficient sleep. Chronic sleep deprivation has become a prevalent phenomenon because of contemporary lifestyle and work-related factors. Sleep deprivation can reduce the capabilities and efficiency of attentional performance by impairing perception, increasing effort to maintain concentration, as well as introducing vision disturbance. Thus, it is important to understand the neural mechanisms behind how chronic sleep deprivation impairs sustained attention. In recent years, more attention has been paid to the study of the integration between anatomically distributed and functionally connected brain regions. Functional connectivity has been widely used to characterize brain functional integration, which measures the statistical dependency between neurophysiological events of the human brain. Further, evidence from recent studies has shown the non-stationary nature of brain functional connectivity, which may reveal more information about the human brain. Thus, the objective of this thesis is to investigate the effects of chronic sleep deprivation on sustained attention from the perspective of dynamic functional connectivity. A modified spatial cueing paradigm was used to assess human sustained attention in rested wakefulness and chronic sleep deprivation conditions. Partial least squares approach was applied to distinguish brain functional connectivity for the experimental conditions. With the integration of a sliding-window approach, dynamic patterns of brain functional connectivity were identified in two experimental conditions. The brain was modeled as a series of dynamic functional networks in each experimental condition. Graph theoretic analysis was performed to investigate the dynamic properties of brain functional networks, using network measures of clustering coefficient and characteristics path length. In the chronic sleep deprivation condition, a compensation mechanism between highly clustered organization and ineffective adaptability of brain functional networks was observed. Specifically, a highly clustered organization of brain functional networks was illustrated with a large clustering coefficient. This organization suggested that brain utilizes more connections to maintain attention in the chronic sleep deprivation condition. A smaller impact of clustering coefficient variation on characteristics path lengths indicated an ineffective adaptability of brain functional networks in the chronic sleep deprivation condition. In the rested wakefulness condition, brain functional networks showed the small-world topology in general, with the average small-world topology index larger than one. Small-world topology was identified as an optimal network structure with the balance between local information processing and global integration. Given the fluctuating values of the index over time, small-world brain networks were observed in most cases, indicating an effective adaptability of the human brain to maintain the dominance of small-world networks in the rested wakefulness condition. On the contrary, given that the average small-world topology index was smaller than one, brain functional networks generally exhibited random network structure. From the perspective of dynamic functional networks, even though there were few cases showing small-world brain networks, brain functional networks failed to maintain the dominance of small-world topology in the chronic sleep deprivation condition. In conclusion, to the best of our knowledge this thesis was the first to investigate the effects of chronic sleep deprivation on sustained attention from the perspective of dynamic brain functional connectivity. A compensation mechanism between highly clustered organization and ineffective adaptability of brain functional networks was observed in the chronic sleep deprivation condition. Furthermore, chronic sleep deprivation impaired sustained attention by reducing the effectiveness of brain functional networks' adaptability, resulting in the disrupted dominance of small-world brain networks.

evaluate disruption risks in the supply chain of petroleum production. This methodology is developed to formalise and facilitate the systematic integration and implementation of various models; such as analytical hierarchy process (AHP) and partial least squares structural equation model (PLS-SEM) and various statistical tests. The methodology is validated with the case of Nigeria’s oil industry. The study revealed the need to provide a responsive approach to managing the influence of geopolitical risk factors affecting supply chain in the petroleum production industry. However, the exploration and production risk, and geopolitical risk were identified as concomitant risk factors that impact performance in Nigeria’s oil industry. The research findings show that behavioural-based mechanisms successfully predict the ability of the petroleum industry to manage supply chain risks. The significant implication for this study is that the current theoretical debate on the supply chain risk management creates the understanding of agency theory as a governing mechanism for supply chain risk in the Nigerian oil industry. The systematic approach results provide an insight and objective information for decisions-making in resolving disruption risk to the petroleum supply chain in Nigeria. Furthermore, this study highlights to stakeholders on how to develop supply chain risk management strategies for mitigating and building resilience in the supply chain in the Nigerian oil industry. The developed systematic method is associated with supply chain risk management and performance measure. The approach facilitates an effective way for the stakeholders to plan according to their risk mitigation strategies. This will consistently help the stakeholders to evaluate supply chain risk and respond to disruptions in supply chain. This capability will allow for efficient management of supply chain and provide the organization with quicker response to customer needs, continuity of supply, lower costs of operations and improve return on investment in the Nigeria oil industry. Therefore, the methodology applied provide a new way for implementing good practice for managing disruption risk in supply chain. Further, the systematic approach provides a simplistic modelling process for disruption risk evaluation for researchers and oil industry professionals. This approach would develop a holistic procedure for monitoring and controlling disruption risk in supply chains practices in Nigeria.

Dans ce mémoire, nous nous intéressons à une façon géométrique de voir la méthode du Lasso en régression linéaire. Le Lasso est une méthode qui, de façon simultanée, estime les coefficients associés aux prédicteurs et sélectionne les prédicteurs importants pour expliquer la variable réponse. Les coefficients sont calculés à l’aide d’algorithmes computationnels. Malgré ses vertus, la méthode du Lasso est forcée de sélectionner au maximum n variables lorsque nous nous situons en grande dimension (p > n). De plus, dans un groupe de variables corrélées, le Lasso sélectionne une variable “au hasard”, sans se soucier du choix de la variable. Pour adresser ces deux problèmes, nous allons nous tourner vers le Lasso Linéaire. Le vecteur réponse est alors vu comme le point focal de l’espace et tous les autres vecteurs de variables explicatives gravitent autour du vecteur réponse. Les angles formés entre le vecteur réponse et les variables explicatives sont supposés fixes et nous serviront de base pour construire la méthode. L’information contenue dans les variables explicatives est projetée sur le vecteur réponse. La théorie sur les modèles linéaires normaux nous permet d’utiliser les moindres carrés ordinaires (MCO) pour les coefficients du Lasso Linéaire. Le Lasso Linéaire (LL) s’effectue en deux étapes. Dans un premier temps, des variables sont écartées du modèle basé sur leur corrélation avec la variable réponse; le nombre de variables écartées (ou ordonnées) lors de cette étape dépend d’un paramètre d’ajustement γ. Par la suite, un critère d’exclusion basé sur la variance de la distribution de la variable réponse est introduit pour retirer (ou ordonner) les variables restantes. Une validation croisée répétée nous guide dans le choix du modèle final. Des simulations sont présentées pour étudier l’algorithme en fonction de différentes valeurs du paramètre d’ajustement γ. Des comparaisons sont effectuées entre le Lasso Linéaire et des méthodes compétitrices en petites dimensions (Ridge, Lasso, SCAD, etc.). Des améliorations dans l’implémentation de la méthode sont suggérées, par exemple l’utilisation de la règle du 1se nous permettant d’obtenir des modèles plus parcimonieux. Une implémentation de l’algorithme LL est fournie dans la fonction R intitulée linlasso, disponible au https://github.com/yanwatts/linlasso. / In this thesis, we are interested in a geometric way of looking at the Lasso method in the context of linear regression. The Lasso is a method that simultaneously estimates the coefficients associated with the predictors and selects the important predictors to explain the response variable. The coefficients are calculated using computational algorithms. Despite its virtues, the Lasso method is forced to select at most n variables when we are in highdimensional contexts (p > n). Moreover, in a group of correlated variables, the Lasso selects a variable “at random”, without caring about the choice of the variable. To address these two problems, we turn to the Linear Lasso. The response vector is then seen as the focal point of the space and all other explanatory variables vectors orbit around the response vector. The angles formed between the response vector and the explanatory variables are assumed to be fixed, and will be used as a basis for constructing the method. The information contained in the explanatory variables is projected onto the response vector. The theory of normal linear models allows us to use ordinary least squares (OLS) for the coefficients of the Linear Lasso. The Linear Lasso (LL) is performed in two steps. First, variables are dropped from the model based on their correlation with the response variable; the number of variables dropped (or ordered) in this step depends on a tuning parameter γ. Then, an exclusion criterion based on the variance of the distribution of the response variable is introduced to remove (or order) the remaining variables. A repeated cross-validation guides us in the choice of the final model. Simulations are presented to study the algorithm for different values of the tuning parameter γ. Comparisons are made between the Linear Lasso and competing methods in small dimensions (Ridge, Lasso, SCAD, etc.). Improvements in the implementation of the method are suggested, for example the use of the 1se rule allowing us to obtain more parsimonious models. An implementation of the LL algorithm is provided in the function R entitled linlasso available at https://github.com/yanwatts/linlasso.

Few studies have explored the relative strength of ecogeographic versus lineage-specific effects on a global scale, particularly for poikilotherms, those organisms whose internal temperature varies with their environment. Here, we compile a global dataset of life history traits in Daphnia, at the species-and population-level, and use those data to parse the relative influences of lineage-specific effects and climate. We also compare the thermal response (plasticity) of life history traits and their dependence on climate, temperature, precipitation, and latitude. We found that the mode of evolution for life history traits varies but that the thermal response of life history traits most often follows a random walk model of evolution. We conclude that life history trait evolution in Daphnia is not strongly species-specific but is ecogeographically distinct, suggesting that life history evolution should be understood at the population level for Daphnia and possibly for other poikilotherms.

Data gathering is a constant in human history with ever increasing amounts in quantity and dimensionality. To get a feel for the data, make it interpretable, or find underlying laws it is necessary to fit a function to the finite and possibly noisy data. In this thesis we focus on a method achieving this, namely least squares approximation. Its discovery dates back to around 1800 and it has since then proven to be an indispensable tool which is efficient and has the capability to achieve optimal error when used right. Crucial for the least squares method are the ansatz functions and the sampling points. To discuss them, we gather tools from probability theory, frame subsampling, and $L_2$-Marcinkiewicz-Zygmund inequalities. With that we give results in the worst-case or minmax setting, when a set of points is sought for approximating a class of functions, which we model as a generic reproducing kernel Hilbert space. Further, we give error bounds in the statistical learning setting for approximating individual functions from possibly noisy samples. Here, we include the covariate-shift setting as a subfield of transfer learning. In a natural way a parameter choice question arises for balancing over- and underfitting effect. We tackle this by using the cross-validation score, for which we show a fast way of computing as well as prove the goodness thereof.:1 Introduction 2 Least squares approximation 3 Reproducing kernel Hilbert spaces (RKHS) 4 Concentration inequalities 5 Subsampling of finite frames 6 L2 -Marcinkiewicz-Zygmund (MZ) inequalities 7 Least squares in the worst-case setting 8 Least squares in statistical learning 9 Cross-validation 10 Outlook

Numerical methods for solving partial differential equations are commonplace in the engineering community and their popularity can be attributed to the rapid performance improvement of modern workstations and desktop computers. The ubiquity of computer technology has allowed all areas of engineering to have access to detailed thermal, stress, and fluid flow analysis packages capable of performing complex studies of current and future designs. The rapid pace of computer development, however, has begun to outstrip efforts to reduce analysis overhead. As such, most commercially available software packages are now limited by the human effort required to prepare, develop, and initialize the necessary computational models. Primarily due to the mesh-based analysis methods utilized in these software packages, the dependence on model preparation greatly limits the accessibility of these analysis tools. In response, the so-called meshless or mesh-free methods have seen considerable interest as they promise to greatly reduce the necessary human interaction during model setup. However, despite the success of these methods in areas demanding high degrees of model adaptability (such as crack growth, multi-phase flow, and solid friction), meshless methods have yet to gain notoriety as a viable alternative to more traditional solution approaches in general solution domains. Although this may be due (at least in part) to the relative youth of the techniques, another potential cause is the lack of focus on developing robust methodologies. The failure to approach development from a practical perspective has prevented researchers from obtaining commercially relevant meshless methodologies which reach the full potential of the approach. The primary goal of this research is to present a novel meshless approach called MIMS (Model Integrated Meshless Solver) which establishes the method as a generalized solution technique capable of competing with more traditional PDE methodologies (such as the finite element and finite volume methods). This was accomplished by developing a robust meshless technique as well as a comprehensive model generation procedure. By closely integrating the model generation process into the overall solution methodology, the presented techniques are able to fully exploit the strengths of the meshless approach to achieve levels of automation, stability, and accuracy currently unseen in the area of engineering analysis. Specifically, MIMS implements a blended meshless solution approach which utilizes a variety of shape functions to obtain a stable and accurate iteration process. This solution approach is then integrated with a newly developed, highly adaptive model generation process which employs a quaternary triangular surface discretization for the boundary, a binary-subdivision discretization for the interior, and a unique shadow layer discretization for near-boundary regions. Together, these discretization techniques are able to achieve directionally independent, automatic refinement of the underlying model, allowing the method to generate accurate solutions without need for intermediate human involvement. In addition, by coupling the model generation with the solution process, the presented method is able to address the issue of ill-constructed geometric input (small features, poorly formed faces, etc.) to provide an intuitive, yet powerful approach to solving modern engineering analysis problems.