The thesis aims to examine the impact of climate change on line rating and to investigate the possibility of a potential increase of capacity of an overhead line. The line rating of an overhead line determines how much current can be transmitted in the line. The weather parameters which affect the line rating are ambient temperature, solar radiation, wind speed, and wind direction. If the line rating is adapted to weather conditions, it is important to be able to predict how the weather will change in the future. Therefore, the impact of climate change on weather parameters is investigated. The ambient temperature and solar radiation are expected to change between different scenarios. However, it is unclear how wind speed and wind direction will be affected. Climate scenarios are designed that take these findings into account. The results show that wind speed has, by a large margin from other weather parameters, the largest impact on the dynamic line rating. This is followed by the wind's angle of attack to the conductor, ambient temperature, and finally solar radiation. For the designed climate scenarios, the dynamic line rating is almost the same in each case, which means that the calculated change in ambient temperature and solar radiation has no significant effect on the line rating. To further increase the capacity of the overhead line, the line could be upgraded with a conductor with a larger cross-sectional area.

Sweden's maternal and childcare services have received recognition for maintaining high standards and employing effective risk-reduction strategies, leading to improved childbirth outcomes. However, these services face contemporary challenges exacerbated by evolving public health dynamics, including the increasing prevalence of obesity among Swedish adults, which mirrors trends in maternal healthcare and poses significant risks during pregnancy. Two significant risks during pregnancy are gestational diabetes mellitus (GDM) and preeclampsia. The rise in these pathophysiological conditions emphasizes the necessity for specialized maternal care approaches. In response, there is growing interest in utilizing technological innovations like glucose and blood pressure sensors for enhanced monitoring and proactive healthcare solutions during pregnancy.  This thesis investigates the intersection of maternal healthcare, technological advancements, and public health challenges in Sweden, aiming to identify innovative approaches to maternal care and explore the potential of glucose and blood pressure sensors in improving outcomes. To achieve it, an extensive literature review established a robust foundation, focusing on women's and maternity care trends and the impact of BMI on pregnancy outcomes. Interviews with healthcare professionals from diverse fields provided further insights, leading to an in-depth cause analysis and technology assessment. Subsequently, a mockup was developed based on the gathered information, utilizing JavaScript for program development and incorporating user feedback. Real-world data acquisition was explored using APIs, particularly Dexcom, for glucose monitoring. The design process employed Figma, ensuring visual appeal and functional integration, followed by comprehensive evaluation involving functional, usability, and compatibility testing to refine the mockup interface in alignment with stakeholder expectations.  The results of this study reveal two primary insights into maternal healthcare enhancement: Firstly, through a comprehensive literature review and stakeholder interviews, key challenges and potential solutions were identified, emphasizing the importance of interdisciplinary collaboration. Secondly, developing and evaluating a mockup integrating sensor technology demonstrated promising prospects for real-time monitoring and management, highlighting the potential for improving maternal health outcomes. These findings underscore the importance of integrating self-monitoring technology into maternal healthcare to enhance monitoring capabilities and address contemporary challenges in pregnancy care. / Sveriges mödra- och barnavårdstjänster har fått erkännande för att upprätthålla höga standarder och använda effektiva riskminskningsstrategier, vilket har lett till förbättrade förlossningsresultat. Emellertid möter dessa tjänster samtida utmaningar förvärrade av utvecklande folkhälsodynamik, inklusive den ökande förekomsten av fetma bland svenska vuxna, vilket speglar trender inom mödrahälsovård och innebär betydande risker under graviditeten. Två av dessa risker är graviditetsdiabetes mellitus och preeklampsi. Ökningen av dessa patofysiologiska tillstånd understryker behovet av nyanserade mödravårdsmetoder. Som svar finns det ett växande intresse för att använda teknologiska innovationer som glukos- och blodtryckssensorer för förbättrad övervakning och proaktiva hälsolösningar under graviditeten. Denna avhandling undersöker korsningen mellan mödrahälsovård, tekniska framsteg och folkhälsoutmaningar i Sverige, med målet att identifiera innovativa angreppssätt för mödraomsorg och utforska potentialen hos glukos- och blodtryckssensorer för att förbättra resultat.  För att uppnå detta etablerades en gedigen litteraturgenomgång som fokuserade på trender inom kvinnors och mödravård samt BMI:s påverkan på graviditetsresultat. Intervjuer med vårdpersonal från olika områden gav ytterligare insikter, vilket ledde till en djupgående orsaksanalys och teknisk bedömning. Därefter utvecklades en prototyp baserad på den insamlade informationen, med användning av JavaScript för programutveckling och inkorporering av användarfeedback. Verklig datainsamling utforskades med hjälp av API:er, särskilt Dexcom, för glukosövervakning. Designprocessen använde Figma för visuellt tilltalande och funktionell integration, följt av omfattande utvärderingar som involverade funktions-, användbarhets- och kompatibilitetstester för att förbättra prototypens gränssnitt i linje med intressenternas förväntningar.  Resultaten av denna studie belyser två primära insikter om förbättringar inom mödrahälsovård: För det första identifierades nyckelutmaningar och potentiella lösningar genom en omfattande litteraturgenomgång och intervjuer med intressenter, vilket betonar vikten av tvärvetenskapligt samarbete. För det andra visade utveckling och utvärdering av en prototyp som integrerar sensorteknik lovande framtidsutsikter för realtidsövervakning och hantering, vilket belyser potentialen för att förbättra mödrahälso-resultat. Dessa resultat understryker vikten av att integrera självövervakningsteknik i mödrahälsovård för att förbättra övervakningsmöjligheter och adressera samtida utmaningar inom graviditetsvård.

Organizations use Business Intelligence (BI) systems to monitor how well they are meeting their goals and objectives. Yet, very often BI systems do not include clear models of the organization’s goals or of how to measure whether they are satisfied or not. Several researchers now attempt to integrate goal models into BI systems, but there are still major challenges related to how to get access to the BI data to populate the part of the goal model (often indicators) used to assess goal satisfaction. This thesis explores a new approach to integrate BI systems with goal models. In particular, it explores the integration of IBM Cognos Business Intelligence, a leading BI tool, with an Eclipse-based goal modeling tool named jUCMNav. jUCMNav is an open source graphical editor for the User Requirements Notation (URN), which includes the Use Case Map notation for scenarios and processes and the Goal-oriented Requirement Language for business objectives. URN was recently extended with the concept of Key Performance Indicator (KPI) to enable performance assessment and monitoring of business processes. In jUCMNav, KPIs are currently calculated or modified manually. The new integration proposed in this thesis maps these KPIs to report elements that are generated automatically by Cognos based on the model defined in jUCMNav at runtime, with minimum effort. We are using IBM Cognos Mashup Service, which includes web services that enable the retrieval of report elements at the most granular level. This transformation provides managers and analysts with useful goal-oriented and process-oriented monitoring views fed by just-in-time BI information. This new solution also automates retrieving data from Cognos servers, which helps reducing the high costs usually caused by the amount of manual work required otherwise. The novel approach presented in this thesis avoids manual report generation and minimizes any contract with respect to the location of manually created reports, hence leading to better usability and performance. The approach and its tool support are illustrated with an ongoing example, validated with a case study, and verified through testing.

Organizations use Business Intelligence (BI) systems to monitor how well they are meeting their goals and objectives. Yet, very often BI systems do not include clear models of the organization’s goals or of how to measure whether they are satisfied or not. Several researchers now attempt to integrate goal models into BI systems, but there are still major challenges related to how to get access to the BI data to populate the part of the goal model (often indicators) used to assess goal satisfaction. This thesis explores a new approach to integrate BI systems with goal models. In particular, it explores the integration of IBM Cognos Business Intelligence, a leading BI tool, with an Eclipse-based goal modeling tool named jUCMNav. jUCMNav is an open source graphical editor for the User Requirements Notation (URN), which includes the Use Case Map notation for scenarios and processes and the Goal-oriented Requirement Language for business objectives. URN was recently extended with the concept of Key Performance Indicator (KPI) to enable performance assessment and monitoring of business processes. In jUCMNav, KPIs are currently calculated or modified manually. The new integration proposed in this thesis maps these KPIs to report elements that are generated automatically by Cognos based on the model defined in jUCMNav at runtime, with minimum effort. We are using IBM Cognos Mashup Service, which includes web services that enable the retrieval of report elements at the most granular level. This transformation provides managers and analysts with useful goal-oriented and process-oriented monitoring views fed by just-in-time BI information. This new solution also automates retrieving data from Cognos servers, which helps reducing the high costs usually caused by the amount of manual work required otherwise. The novel approach presented in this thesis avoids manual report generation and minimizes any contract with respect to the location of manually created reports, hence leading to better usability and performance. The approach and its tool support are illustrated with an ongoing example, validated with a case study, and verified through testing.

Organizations use Business Intelligence (BI) systems to monitor how well they are meeting their goals and objectives. Yet, very often BI systems do not include clear models of the organization’s goals or of how to measure whether they are satisfied or not. Several researchers now attempt to integrate goal models into BI systems, but there are still major challenges related to how to get access to the BI data to populate the part of the goal model (often indicators) used to assess goal satisfaction. This thesis explores a new approach to integrate BI systems with goal models. In particular, it explores the integration of IBM Cognos Business Intelligence, a leading BI tool, with an Eclipse-based goal modeling tool named jUCMNav. jUCMNav is an open source graphical editor for the User Requirements Notation (URN), which includes the Use Case Map notation for scenarios and processes and the Goal-oriented Requirement Language for business objectives. URN was recently extended with the concept of Key Performance Indicator (KPI) to enable performance assessment and monitoring of business processes. In jUCMNav, KPIs are currently calculated or modified manually. The new integration proposed in this thesis maps these KPIs to report elements that are generated automatically by Cognos based on the model defined in jUCMNav at runtime, with minimum effort. We are using IBM Cognos Mashup Service, which includes web services that enable the retrieval of report elements at the most granular level. This transformation provides managers and analysts with useful goal-oriented and process-oriented monitoring views fed by just-in-time BI information. This new solution also automates retrieving data from Cognos servers, which helps reducing the high costs usually caused by the amount of manual work required otherwise. The novel approach presented in this thesis avoids manual report generation and minimizes any contract with respect to the location of manually created reports, hence leading to better usability and performance. The approach and its tool support are illustrated with an ongoing example, validated with a case study, and verified through testing.