Many of the ongoing activities towards establishing SDI on a regional, national, and international level are focused on data sharing and dissemination. Next to data access and visualisation, data processing is a third important pillar of GIS which can generate new insights by creating derived data or conducting computational analyses on original data sets. Within today’s largely data-centric SDI, two major challenges were identified that stand in the way of ubiquitous geoprocessing: The ability to use and exchange implementations of geoprocessing functions as freely as geographic data and the ability to describe, communicate and catalogue existing functionality on the Web. This thesis evaluates the moving code approach as an alternative to client–server processing in a distributed SDI. While classical client–server configurations move pieces of data between remote processing services, data services, and clients over the network, moving code setups consider the transfer of portable software components to the location of data or the location of computing resources. To exchange implementations of geoprocessing functions at a larger scale, a Web based code sharing architecture is proposed. For improved descriptions of geoprocessing functions, WPS process descriptions are suggested as an interface description language. They are enhanced by a hierarchical profiling approach that permits different levels of granularity in the functional descriptions.

Climate changes are predicted to increase precipitation intensities and occurrence of extreme rainfall events in the near future. Scandinavia has been identified as one of the most sensitive regions in Europe to such changes; therefore, an increase in the risk for flooding, landslides and soil erosion is to be expected also in Sweden. An increase in the occurrence of extreme weather events will impose greater strain on the built environment and major transport infrastructures such as roads and railways. This research aimed to identify the risk of flooding at the road-stream intersections, crucial locations where water and debris can accumulate and cause failures of the existing drainage facilities. Two regions in southwest of Sweden affected by an extreme rainfall event in August 2014, were used for calibrating and testing a statistical flood prediction model. A set of Physical Catchment Descriptors (PCDs) including road and catchment characteristics was identified for the modelling. Moreover, a GIS-based topographic Index of Sediment Connectivity (IC) was used as PCD. The novelty of this study relies on the adaptation of IC for describing sediment connectivity in lowland areas taking into account contribution of soil type, land use and different patterns of precipitation during the event. A weighting factor for IC was calculated by estimating runoff calculated with SCS Curve Number method, assuming a constant value of precipitation for a given time period, corresponding to the critical event. The Digital Elevation Model of the study site was reconditioned at the drainage facilities locations to consider the real flow path in the analysis. These modifications led to highlight the role of rainfall patterns and surface runoff for modelling sediment delivery in lowland areas. Moreover, it was observed that integrating IC into the statistic prediction model increased its accuracy and performance. The calibrated model was then validated in another area, located in the central part of Sweden, affected by severe rainfall event in August 2004, in order to verify its robustness even in ungauged catchments.

The recent addition to Stockholm’s built environment in the shape of the new Slussen bridge, or Guldbron as most locals call it, has been both a source of controversy and admiration. This reaction is typical of any infrastructure that reshapes our surroundings. However, this interaction is not unidirectional. Similar projects may be affected by the very relations they might trigger in the first place. Building upon the conjunction of crucial concepts from actor-network theory and assemblage thinking, this study intends to identify the co-producing nature of the bridge as a technical artefact and the relations surrounding the project. To that end, I employ a qualitative research technique combining various methods of interviews and observation. The research primarily identifies the desired nature of the bridge and its ability to stabilize relations as a heterogeneous assemblage. Ultimately, the everchanging state of affairs or fluid character of this piece of infrastructure is discussed. The thesis concludes by arguing that the exploration of similar projects from a relational perspective challenges the conceptualization of megaprojects as taken- for-granted entities. Such an understanding brings to the forefront the crucial importance of interactions to define whether a project can be considered as ‘mega’, as opposed to employing a prescribed set of criteria.

Critical infrastructure is a term to define the network of crucial assets for the functioning of a society and modern economies. The complexity of critical infrastructures and the ability to connect smart devices to these networks make them more vulnerable to cyberattacks. One of the cutting events pointing out gaps and importance of the cyber resilience in the nation's infrastructure systems, including Industrial Control Systems (ICS), was the discovery of Stuxnet in 2010, a malicious computer worm attacking Iranian nuclear facilities. The vulnerability of cyber systems was further revealed by a cyberattack on the SCADA system in Ukraine in 2015. This paper uses both a systematic literature strategy base on the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement and co-occurrence analysis by VOSviewer, a tool for visualization of similarities, to explore the specific research domains of cyber resilience for critical infrastructures and to understand the current trend of development and future research orientation. Despite the literature's emphasis on essential industries, the results show that, of all exposure parameters, the organization's sector is most consistently connected with the emergence of cyber resilience traits. The sector is also important in terms of the kind of attack and its effect on data. The attacked entities in the sample have a low level of cyber resilience, as evidenced by the surprisingly low intensity of devoted Cyber Security (CS) operational setting, use of CS structures, the resilience of Prevention, Detection, and Recovery controls (PDR), and organizations' reactions to their stakeholders following cyber attacks. The studied countries do not consistently adopt cyber resilience features. The prevalence of resilience traits, on the other hand, seems to have a beneficial influence on the frequency of litigation and sanctions. Furthermore, improved protection, detection, and recovery measures increase the frequency of responsibilities and expectations to stakeholders following cyber assaults.

One emerging threat to Public Key Infrastructures is the possible development of large-scale quantum computers, which would be able to break the public-key cryptosystems used today. Several possibly post-quantum secure cryptographic algorithms have been proposed but so far they have not been used in many practical settings. The purpose of this thesis was to find post-quantum digital signature algorithms that might be suitable for use in Public Key Infrastructures today. To answer the research question, an extensive literature study was conducted where relevant algorithms were surveyed. Algorithms with high-grade implementations in different cryptographic libraries were benchmarked for performance. Hash-based XMSS and SPHINCS, multivariate-based Rainbow and lattice-based BLISS-B were benchmarked and the results showed that BLISS-B offered the best performance, on par with RSA and ECDSA. All the algorithms did however have relatively large signature sizes and/or key sizes. Support for post-quantum digital signature algorithms in Public Key Infrastructure products could easily be achieved since many algorithms are implemented in cryptographic libraries. The algorithms that could be recommended for use today were SPHINCS for high-security applications and possibly BLISS-B for lower security applications requiring higher efficiency. The biggest obstacles to widespread deployment of post-quantum algorithms was deemed to be lack of standardisation and either inefficient operations compared to classical algorithms, uncertain security levels, or both. / Ett nytt hot mot Public Key Infrastructures är den möjliga utvecklingen av storskaliga kvantdatorer som kan knäcka de asymmetriska kryptosystem som används idag. Ett flertal eventuellt kvantsäkra algoritmer har presenterats men de har än så länge inte sett mycket praktisk användning. Målet med detta examensarbete var att försöka identifiera eventuellt kvantsäkra signaturalgoritmer som skulle kunna lämpa sig för användning i Public Key Infrastructures idag. För att besvara forskningsfrågan gjordes en utredande litteraturstudie där relevanta signaturalgoritmer identifierades. Därefter prestandatestades de algoritmer som var implementerade i kryptografiska bibliotek. De algoritmer som prestandatestades var de hash-baserade algoritmerna XMSS och SPHINCS, flervariabel-baserade Rainbow och gitter-baserade BLISS-B. Resultaten visade att BLISS-B hade bäst prestanda och att prestandan var i nivå med RSA och ECDSA. Samtliga algoritmer hade emellertid relativt stora signatur- och/eller nyckelstorlekar. Eventuellt kvantsäkra algoritmer skulle redan idag kunna stödjas i Public Key Infrastructures eftersom många algoritmer finns implementerade i kryptografiska bibliotek. SPHINCS kunde rekommenderas när hög säkerhet krävs medan BLISS-B möjligtvis skulle kunna användas när lägre säkerhet kan tolereras i utbyte mot bättre prestanda. Största hindren för utbredd användning ansågs vara en brist på standardisering samt ineffektiva operationer jämfört med klassiska algoritmer och/eller tveksamma säkerhetsnivåer.

Yes / The on-going COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2) has posed an extraordinary threat to global public health, wealth and well-being. As the carrier of human life and production, infrastructures need to be upgraded to mitigate and prevent the spread of viral diseases. Developing multifunctional/smart civil engineering materials to fight viruses is a promising approach to achieving this goal. In this perspective, the basic introduction on virus and its structure is provided. Then, the current design principles of antiviral materials and structures are examined. Subsequently, the possibility of developing active/passive antiviral civil engineering materials (including cementitious composites, ceramics, polymers and coatings) is proposed and envisaged. Finally, the future research needs and potential challenges to develop antiviral civil engineering materials are put forward. The proposed strategies to develop multifunctional/smart antiviral civil engineering materials will aid in the construction of smart infrastructures to prevent the spread viruses, thus improving human life and health as well as sustainability of human society. / The authors would like to thank the National Science Foundation of China (51978127, 52178188, and 51908103) and the Fundamental Research Funds for the Central Universities (DUT21RC(3)039) for providing funding to carry out this investigation.

Le pergélisol est omniprésent dans l’Arctique et l’Antarctique, et il est présent en haute altitude partout dans le monde. Les communautés et le développement industriel des régions pergélisolées ont besoin d’infrastructures de transport (routes, aéroports, chemins de fer, etc.), sachant que le transport y revêt une importance vitale au niveau social, économique et politique (Regehr, Milligan et Alfaro 2013). Toutefois, les changements climatiques auront des répercussions sur les infrastructures de transport existantes et futures en Alaska de l’ordre de 282 à 550 M$ (2015 USD), selon les scénarios d’émissions (Melvin et al. 2016). Vu ces conditions, des outils sont nécessaires pour aider les décideurs à prioriser l’entretien, le remplacement et la construction des infrastructures, et potentiellement justifier l’utilisation des stratégies de mitigation pour les remblais sur pergélisol. Des méthodes d’analyse de risque peuvent être utilisées, mais leur application en ingénierie du pergélisol est actuellement limitée. Le risque est un produit du hasard, de la conséquence et de la vulnérabilité pour chacun des dangers considérés. La probabilité et le coût de l’occurrence d’un danger sont respectivement un hasard et une conséquence, tandis que la vulnérabilité corrèle le dommage possible avec la conséquence. Comme il existe peu de données de défaillance pour les installations sur pergélisol, le risque doit être déterminé à l’aide des méthodes d’analyse de fiabilité (premier-ordre deuxièmemoment ou simulations de Monte Carlo), qui intègrent les incertitudes des paramètres d’entrée pour déterminer la variabilité des résultats. Ces méthodes exigent la caractérisation de l’incertitude des variables aléatoires, ce qui peut être difficile en l’absence de données suffisantes, souvent plus que nécessaire dans la pratique actuelle. En outre, ces méthodes d’analyse de fiabilité exigent une fonction d’état limite pour que le danger soit analysé. Les dangers communs qui affectent les remblais sur pergélisol incluent : le tassement, la fissuration, la rupture soudaine, le déplacement latéral du remblai, le drainage et l’accumulation d’eau en pied de remblai, et les glissements de la couche active. Parmi ces dangers, seuls quelques-uns ont des fonctions d’état limite déterminées ou qui peuvent être approfondies par l’auteure. Les dangers associés à ces fonctions d’état limite ou de hasard comprennent : les tassements totaux et différentiels au dégel, la formation d’arche par le positionnement de particules audessus de cavité, les glissements de la couche active, la rupture de la pente du ponceau et l’affaissement de la structure du ponceau. Un programme a été créé sur le logiciel Excel pour calculer le risque des installations linéaires construites sur un remblai de pergélisol en utilisant les méthodes statistiques appliquées aux fonctions d’état limite afin de déterminer les dangers communs aux infrastructures sur pergélisol, ainsi que d'estimer les coûts directs de réparation et les facteurs d’échelle permettant de tenir compte des coûts indirects des dommages causés aux utilisateurs de l’infrastructure et aux communautés concernées. Les calculs des risques sont basés sur les propriétés géotechniques et l’incertitude climatique, telles que caractérisées par des fonctions de densité de probabilité, en utilisant les méthodes statistiques de simulations de Monte Carlo. Une analyse de la fragilité du réchauffement climatique permet de recalculer les dangers à partir des variations des températures de l’air. Les analyses répétées le long de l’infrastructure fournissent un profil de risque actuel ainsi qu'un profil tenant compte du réchauffement climatique. Le programme a servi à déterminer les dangers pour la route d’accès à l’aéroport de Salluit, et l'évaluation des dangers, des risques et de la rentabilité a été effectuée pour l’aéroport international d’Iqaluit / Permafrost is ubiquitous in the Arctic and Antarctic, and present in high elevation regions throughout the world. The communities and industrial development in permafrost regions require transportation infrastructures (roadways, airports, railways, etc.) and, in these regions, transportation is of vital social, economic, and political importance (Regehr, Milligan, and Alfaro 2013). However, warming climate conditions will endanger existing and future transportation infrastructure in Alaska to the tune of $282 to $550 million (2015 USD) depending on future emission scenarios (Melvin et al. 2016). Given these conditions, tools are required to aid decisionmakers in prioritizing infrastructure maintenance, replacement, and construction, and potentially justifying the use of mitigation strategies of permafrost embankments. Risk analysis methods can be used but their existing application to permafrost engineering is limited. Risk is a product of hazard, consequence and vulnerability for each of the dangers under consideration. The probability and costs of a danger’s occurrence is a hazard and the consequence, respectively, while vulnerability correlated the damage with the consequence. Since little failure data is available for permafrost infrastructure, the hazard must be determined from reliability analysis methods (First-Order Second-Moment or Monte Carlo Simulation), which aggregate the uncertainty of input parameters to determine the result’s variation. These methods require the characterization of random variable uncertainty, which can be difficult without sufficient data, often more than the current standard-of-practice. Additionally, the method requires a limit state function for the danger to be analyzed. Common dangers effecting permafrost embankment infrastructure included: settlement, cracking, sudden collapse, lateral embankment spreading, drainage and ponding water, and active layer detachment landslides. Of these dangers, only a few have existing limit state functions or have limit state functions that can be developed by the author. The dangers with limit state functions or hazard functions include: total and differential thaw settlement, particle position bridging over voids, active layer detachment landslides, and culvert gradient and structural failure. A Microsoft Excel-based program was created to calculate the risk for permafrost embankment linear infrastructure, using statistical methods applied to limit state functions to determine hazards for common permafrost dangers, estimated direct costs for the repair of a hazard’s occurrence, and scaling factors to account for the indirect costs of damage to the infrastructure’s users and connected communities. Hazard calculations are based on geotechnical property and climate uncertainty, as characterized by probability density functions, using Monte Carlo Simulation methods. A climate change fragility analysis recalculates the hazard with warming air temperatures. Repeated analyses along the infrastructure provide a risk profile of the infrastructure, now and with a warming climate. The program is used to determine hazard for the Airport Access Road in Salluit, and hazard, risk and cost/benefit assessments were conducted using this program for the Iqaluit International Airport.

Les besoins croissants en infrastructures et les contraintes des finances publiques incitent les gouvernements à travers le monde à explorer différents modes de financement et d’approvisionnement en infrastructures et services publics. Ces dernières décennies, un des modes les plus plébiscités pour financer ces besoins en infrastructures est le partenariat public-privé (PPP). Les défenseurs du PPP le considèrent comme l’instrument de financement des infrastructures qui peut combler les besoins des infrastructures sans mettre à mal les finances publiques, tout en permettant l’efficience, l’efficacité, le contrôle des coûts et le respect des délais dans les projets d’infrastructures. Les rares preuves empiriques sur la performance des PPP à travers le monde sont toutefois mitigées. Au Canada, le PPP est utilisé par le gouvernement fédéral, les gouvernements municipaux et autochtones, et surtout les gouvernements provinciaux. Ce mode de financement et d’approvisionnement a vu son rythme s’accélérer depuis les années 2000 malgré les différentes critiques des universitaires, des professionnels et des médias sur sa performance. Ce paradoxe de l’accélération du rythme des PPP malgré leurs bilans mitigés et les critiques nous ont poussés à chercher à comprendre les raisons du choix des PPP. Une tentative de compréhension des raisons du choix des PPP à travers une analyse des rapports des projets réalisés en mode PPP, l'exploration la littérature scientifique nous a laissé perplexe. Tous les rapports d’optimisation des ressources sur les projets en mode PPP justifient leurs choix par leur capacité à atteindre la performance, bien que des études empiriques sur leurs performances soient peu claires. La rareté des travaux empiriques sur le choix des PPP augmentait notre curiosité intellectuelle sur ce nouvel instrument d’action publique au cœur des politiques d’infrastructures si bien que nous avons jugé pertinent de mener une recherche pour comprendre empiriquement les raisons de leurs choix dans le contexte Canadien. En administration publique, la compréhension du choix des PPP permettrait de faire avancer les connaissances théoriques et pratiques sur les instruments de politiques publiques. Comprendre le choix des PPP devenait pour nous un agenda de recherche stimulant tant au niveau théorique que pratique. Cette étude est ainsi la première à analyser les déterminants du choix des PPP dans le contexte canadien. Cette étude a pour objectif d’identifier et de comprendre les facteurs explicatifs du choix du PPP comme mode de financement et d’approvisionnement en infrastructures et services publics par les gouvernements provinciaux Canadiens pour la période 2002 - 2018. Des pistes d’explications en lien avec des facteurs politiques, les finances publiques et les facteurs économiques ont été explorées et nous ont permis de concevoir un modèle explicatif adapté au contexte canadien que nous avons testé statistiquement. La régression logistique binaire est la méthode statistique utilisée pour mettre en évidence les facteurs explicatifs du choix des PPP par les gouvernants provinciaux Canadiens. Trois régressions avec nos variables politiques, de finances publiques et économiques prises individuellement ont été réalisées dans un premier temps. Ensuite une régression logistique binaire avec nos variables des trois catégories analysées conjointement a été aussi réalisée. Les résultats des analyses statistiques pour chacune de nos catégories montrent que les variables économiques expliquent majoritairement le choix des PPP. Les variables financières et politiques comptent aussi. Les résultats des analyses statistiques montrent que notre modèle qui réunit toutes nos variables a un pouvoir explicatif de 83,2% de la probabilité d’adoption des PPP par les gouvernements provinciaux Canadiens. Le modèle avec toutes les variables explique mieux le choix des PPP que les modèles pour chacune des trois catégories. Le choix des PPP est une combinaison d’explications économiques, financières et politiques. Les résultats montrent que neuf de douze de nos hypothèses sont vérifiées. Des résultats de cette étude, nous pouvons considérer que le gouvernement de droite, le niveau d’endettement de la province, l’existence de règles relatives à la dette dans la province, l’expérience de la province en PPP, la présence d’agences spécialisées en PPP dans la province, les coûts des projets d’infrastructure et le niveau de technicité des infrastructures influencent positivement la probabilité d’adoption d’un PPP par un gouvernement provincial canadien. Le nombre d’employés publics dans la province, le nombre de provinces voisines qui a réalisé les PPP, l’existence d’un fonds PPP quant à eux influencent négativement la probabilité d’adoption d’un PPP par un gouvernement provincial Canadien. Les résultats des analyses statistiques par technicités d’infrastructures, par catégories d’infrastructures et par périodes d’observation montrent que notre modèle explicatif a un fort pouvoir explicatif du choix des PPP par les gouvernements provinciaux canadiens. Cette étude s’inscrit dans les travaux sur la compréhension des instruments d’action publique dans nos sociétés contemporaines. Elle participe à améliorer les connaissances sur les PPP, contribue à enrichir les connaissances théoriques et pratiques sur le choix des PPP, au-delà des débats idéologiques.

In the context of negative consequences following an economic growth paradigm, in the urban sphere, such as uneven urban development, marginalization, gentrification and austerity measures, the present study directs the focus towards the spaces of civic promise. These spaces have the potential to challenge the commoditized and consumerist urban practices and imagine alternative futures. The present paper applies an infrastructural approach to neighborhood art spaces with the purpose of identifying and understanding urban solidarity. Urban solidarity is conceptualized as civic sociality that negotiates difference. To pursue this line of inquiry, the thesis analyzes practices, relations, encounters and socialities that are allowed at Konsthall C, a neighborhood art space located in Hökarängen, a southern suburb of Stockholm, Sweden. The three research questions that guide the thesis are discussing the qualities of the art space, the civic sociality and how it negotiates difference and the dynamics between the qualities of the spaces and the civic social relations manifested in the space. These dynamics reveal that there is not a simple straightforward relationship between the two. Moreover, the importance of the background is reiterated for these types of spaces. Besides this, a nuanced perspective on the types of civic sociality and how it works towards negotiating differences is highlighted.

Condition assessment of civil engineering infrastructure systems is of growing importance as they face aging and degradation due to both human-made activities and environmental factors. Nevertheless, challenges persist in data collection, leading to “data scarcity”, and the need for frequent site visits in inspections, presenting significant obstacles in the assessment of the civil infrastructure systems. This dissertation aims to overcome these challenges by exploring the potential of two emerging technologies: Generative Artificial Intelligence (AI) and Virtual Reality (VR). In tackling the issue of data scarcity, the research question revolves around how Generative AI can be utilized to mitigate data collection-related constraints and increase data availability, thus facilitating health monitoring applications of infrastructure systems. For that, using various Generative AI models, the dissertation works on acceleration response data generation, including data augmentation and domain translation applications on different structures. In addressing the site visit challenge, the dissertation focuses on the use of VR to bring the infrastructure to the experts in a single collaborative immersive environment and investigate its impact on decision-making in inspections. For that, using VR technology, the dissertation develops a Virtual Meeting Environment (VME) integrated with the infrastructure data and models presented through novel immersive visualization techniques. The dissertation further investigates the impact of VME on decision-making in infrastructure inspections through experimentation with engineers. These investigations of the use of Generative AI and VR demonstrate various contributions. Generative AI effectively tackles the need for vast datasets in data-intensive damage detection applications. It also demonstrates its potential in estimating representative response data for various structural conditions across dissimilar infrastructures. VME, on the other hand, offers an increased understanding of the material along with a safer, practical, and cost-effective complementing alternative to traditional in-person site visits. It further reveals how VME improves decision-making in infrastructure inspections.