This thesis presents new tools and techniques developed to address the challenging problem of high-fidelity aerostructural optimization with respect to large numbers of design variables. A new mesh-movement scheme is developed that is both computationally efficient and sufficiently robust to accommodate large geometric design changes and aerostructural deformations. A fully coupled Newton-Krylov method is presented that accelerates the convergence of aerostructural systems and provides a 20% performance improvement over the traditional nonlinear block Gauss-Seidel approach and can handle more flexible structures. A coupled adjoint method is used that efficiently computes derivatives for a gradient-based optimization algorithm. The implementation uses only machine accurate derivative techniques and is verified to yield fully consistent derivatives by comparing against the complex step method. The fully-coupled large-scale coupled adjoint solution method is shown to have 30% better performance than the segregated approach. The parallel scalability of the coupled adjoint technique is demonstrated on an Euler Computational Fluid Dynamics (CFD) model with more than 80 million state variables coupled to a detailed structural finite-element model of the wing with more than 1 million degrees of freedom. Multi-point high-fidelity aerostructural optimizations of a long-range wide-body, transonic transport aircraft configuration are performed using the developed techniques. The aerostructural analysis employs Euler CFD with a 2 million cell mesh and a structural finite element model with 300000 DOF. Two design optimization problems are solved: one where takeoff gross weight is minimized, and another where fuel burn is minimized. Each optimization uses a multi-point formulation with 5 cruise conditions and 2 maneuver conditions. The optimization problems have 476 design variables are optimal results are obtained within 36 hours of wall time using 435 processors. The TOGW minimization results in a 4.2% reduction in TOGW with a 6.6% fuel burn reduction, while the fuel burn optimization resulted in a 11.2% fuel burn reduction with no change to the takeoff gross weight.

This thesis presents new tools and techniques developed to address the challenging problem of high-fidelity aerostructural optimization with respect to large numbers of design variables. A new mesh-movement scheme is developed that is both computationally efficient and sufficiently robust to accommodate large geometric design changes and aerostructural deformations. A fully coupled Newton-Krylov method is presented that accelerates the convergence of aerostructural systems and provides a 20% performance improvement over the traditional nonlinear block Gauss-Seidel approach and can handle more flexible structures. A coupled adjoint method is used that efficiently computes derivatives for a gradient-based optimization algorithm. The implementation uses only machine accurate derivative techniques and is verified to yield fully consistent derivatives by comparing against the complex step method. The fully-coupled large-scale coupled adjoint solution method is shown to have 30% better performance than the segregated approach. The parallel scalability of the coupled adjoint technique is demonstrated on an Euler Computational Fluid Dynamics (CFD) model with more than 80 million state variables coupled to a detailed structural finite-element model of the wing with more than 1 million degrees of freedom. Multi-point high-fidelity aerostructural optimizations of a long-range wide-body, transonic transport aircraft configuration are performed using the developed techniques. The aerostructural analysis employs Euler CFD with a 2 million cell mesh and a structural finite element model with 300000 DOF. Two design optimization problems are solved: one where takeoff gross weight is minimized, and another where fuel burn is minimized. Each optimization uses a multi-point formulation with 5 cruise conditions and 2 maneuver conditions. The optimization problems have 476 design variables are optimal results are obtained within 36 hours of wall time using 435 processors. The TOGW minimization results in a 4.2% reduction in TOGW with a 6.6% fuel burn reduction, while the fuel burn optimization resulted in a 11.2% fuel burn reduction with no change to the takeoff gross weight.

Mobile marketing is a young and still developing strategy in marketing. It thanks its creation and rapid evolution to the growth of mobile devices, such as mobile phones and tablets. This paper's research question, "can mobile marketing be used as a strategy in CRM?" investigates the strength of mobile marketing, its application and use by marketers as their sole or part of their marketing campaign and as strategy in customer relationship management (CRM). The two main components of the research question are mobile marketing and CRM. Mobile marketing is part of the marketing mix, namely promotion. CRM on the other hand is a business strategy which is designed to reduce costs and increase profitability by solidifying customer loyalty. According to Pousstchi and Wiedemann (2006), there are 6 objectives of mobile marketing, and a Mobile campaign is based on 12 critical success factors (CSF) (Scornavacca E., McKenzie J.). These CSFs range from related content, permission, personalisation to time and response time. If mobile marketers take these CSFs into account when creating their mobile marketing, then they raise the success rate of their mobile campaign significantly. Mobile devices are very personal items, people even take them with them when they visit the bathroom. This and the fact that most people have a cellphone and/or other mobile devices, make mobile marketing very appealing to be used as a marketing medium. Mobile marketers have several options, using mobile devices, to reach consumers. Internet plays a critical part, but new technologies such as 3G and Wifi have also eased the way of reaching consumers. SMS and MMS are two other commonly used messaging services in mobile marketing. With all the research of this paper, but with regard to its limitations, this research paper concludes that, if used properly, mobile marketing can be used as a CRM strategy.

Enterprise crowdsourcing transforms the way in which traditional business tasks can be processed by harnessing the collective intelligence and workforce of a large and often diver-sified group of people. At the present time, data and information residing within enterprise crowdsourcing systems and other business applications are insufficiently interlinked and are rarely made publicly available in an open and semantically structured manner – neither to the corporate intranet nor to the World Wide Web (WWW). However, the semantic annotation of enterprise crowdsourcing activities is a promising research and application domain. The Semantic Web and its related technologies, methods and principles for publishing structured data offer an extension of the traditional layout-oriented Web to provide more intelligent and complex services. This technical report describes the efforts toward a universal and lightweight yet powerful Semantic Web vocabulary for the domain of enterprise crowdsourcing. As a methodology for developing the vocabulary, the approach of ontology engineering is applied. To illustrate the purpose and to limit the scope of the ontology, several informal competency questions as well as functional and non-functional requirements are presented. The subsequent con-ceptualization of the ontology applies different sources of knowledge and considers various perspectives. A set of semantic entities is derived from a review of existing crowdsourcing applications and a review of recent crowdsourcing literature. During the domain capture, all partial results of the review are integrated into a consistent data dictionary and structured as a UML data schema. The designed ontology includes 24 classes, 22 object properties and 30 datatype properties to describe the key aspects of a crowdsourcing model (CSM). To demonstrate the technical feasibility, the ontology is implemented using the Web Ontology Language (OWL). Finally, the ontology is evaluated by means of transforming informal to formal competency questions, comparing it to existing semantic vocabularies, and calculat-ing ontology metrics. Evidence is shown that the CSM ontology covers the key representa-tional needs of the enterprise crowdsourcing domain. At the end of the technical report, cur-rent limitations are illustrated and directions for future research are proposed.

The last couple of years have seen a fascinating evolution. While the early Web predominantly focused on human consumption of Web content, the widespread dissemination of social software and Web 2.0 technologies enabled new forms of collaborative content creation and problem solving. These new forms often utilize the principles of collective intelligence, a phenomenon that emerges from a group of people who either cooperate or compete with each other to create a result that is better or more intelligent than any individual result (Leimeister, 2010; Malone, Laubacher, & Dellarocas, 2010). Crowdsourcing has recently gained attention as one of the mechanisms that taps into the power of web-enabled collective intelligence (Howe, 2008). Brabham (2013) defines it as “an online, distributed problem-solving and production model that leverages the collective intelligence of online communities to serve specific organizational goals” (p. xix). Well-known examples of crowdsourcing platforms are Wikipedia, Amazon Mechanical Turk, or InnoCentive. Since the emergence of the term crowdsourcing in 2006, one popular misconception is that crowdsourcing relies largely on an amateur crowd rather than a pool of professional skilled workers (Brabham, 2013). As this might be true for low cognitive tasks, such as tagging a picture or rating a product, it is often not true for complex problem-solving and creative tasks, such as developing a new computer algorithm or creating an impressive product design. This raises the question of how to efficiently allocate an enterprise crowdsourcing task to appropriate members of the crowd. The sheer number of crowdsourcing tasks available at crowdsourcing intermediaries makes it especially challenging for workers to identify a task that matches their skills, experiences, and knowledge (Schall, 2012, p. 2). An explanation why the identification of appropriate expert knowledge plays a major role in crowdsourcing is partly given in Condorcet’s jury theorem (Sunstein, 2008, p. 25). The theorem states that if the average participant in a binary decision process is more likely to be correct than incorrect, then as the number of participants increases, the higher the probability is that the aggregate arrives at the right answer. When assuming that a suitable participant for a task is more likely to give a correct answer or solution than an improper one, efficient task recommendation becomes crucial to improve the aggregated results in crowdsourcing processes. Although some assumptions of the theorem, such as independent votes, binary decisions, and homogenous groups, are often unrealistic in practice, it illustrates the importance of an optimized task allocation and group formation that consider the task requirements and workers’ characteristics. Ontologies are widely applied to support semantic search and recommendation mechanisms (Middleton, De Roure, & Shadbolt, 2009). However, little research has investigated the potentials and the design of an ontology for the domain of enterprise crowdsourcing. The author of this thesis argues in favor of enhancing the automation and interoperability of an enterprise crowdsourcing environment with the introduction of a semantic vocabulary in form of an expressive but easy-to-use ontology. The deployment of a semantic vocabulary for enterprise crowdsourcing is likely to provide several technical and economic benefits for an enterprise. These benefits were the main drivers in efforts made during the research project of this thesis: 1. Task allocation: With the utilization of the semantics, requesters are able to form smaller task-specific crowds that perform tasks at lower costs and in less time than larger crowds. A standardized and controlled vocabulary allows requesters to communicate specific details about a crowdsourcing activity within a web page along with other existing displayed information. This has advantages for both contributors and requesters. On the one hand, contributors can easily and precisely search for tasks that correspond to their interests, experiences, skills, knowledge, and availability. On the other hand, crowdsourcing systems and intermediaries can proactively recommend crowdsourcing tasks to potential contributors (e.g., based on their social network profiles). 2. Quality control: Capturing and storing crowdsourcing data increases the overall transparency of the entire crowdsourcing activity and thus allows for a more sophisticated quality control. Requesters are able to check the consistency and receive appropriate support to verify and validate crowdsourcing data according to defined data types and value ranges. Before involving potential workers in a crowdsourcing task, requesters can also judge their trustworthiness based on previous accomplished tasks and hence improve the recruitment process. 3. Task definition: A standardized set of semantic entities supports the configuration of a crowdsourcing task. Requesters can evaluate historical crowdsourcing data to get suggestions for equal or similar crowdsourcing tasks, for example, which incentive or evaluation mechanism to use. They may also decrease their time to configure a crowdsourcing task by reusing well-established task specifications of a particular type. 4. Data integration and exchange: Applying a semantic vocabulary as a standard format for describing enterprise crowdsourcing activities allows not only crowdsourcing systems inside but also crowdsourcing intermediaries outside the company to extract crowdsourcing data from other business applications, such as project management, enterprise resource planning, or social software, and use it for further processing without retyping and copying the data. Additionally, enterprise or web search engines may exploit the structured data and provide enhanced search, browsing, and navigation capabilities, for example, clustering similar crowdsourcing tasks according to the required qualifications or the offered incentives.

Hintergrund: Bei der Einleitung einer Narkose eines nicht-nüchternen Patienten wird das Relaxanz in unmittelbarer Folge zum Induktionsmittel appliziert. Welches der Hypnotika Propofol, Etomidat oder Methohexital führt am schnellsten zur ausreichend tiefen Narkose? Material/Methoden: Standardisierte Narkoseinduktion, je 20 ASA1/2 Patienten pro Medikament. Bestimmung Schlaftiefe mittels CSI: 1. vor Beginn , nach Midazolamgabe, 2. zwei Min. nach Fentanylgabe, 3. direkt nach Gabe des Hypnotikum (Dauer Injektion 1Min.), 4. nach 1 Min. Propofol 3 mg/kg KG, Etomidat 0,3 mg/kg KG, Methohexital 1 mg/kg KG. Fentanyl 3 µg/kg KG, Midazolam 7,5mg Ergebnisse: CSI direkt nach Injektion bei Methohexital mit 70,80 (+/-13,93) niedriger (p=0,024) als bei Propofol mit 81,05 (+/-10,82) und als bei Etomidat (p=0,026) mit 81,45 (+/-12,04). Abnahme des CSI während der Injektion bei Methohexital mit -9,6 (+/-12,14) größer (p=0,006) als bei Propofol mit –0,1 (+/-8,31). CSI <60 direkt nach Injektion bei Propofol 2x, Etomidat 3x, Methohexital 4x , nach einer Minute Propofol 17x, Etomidat 10x, Methohexital 16x. Schlussfolgerung: Methohexital ermöglicht eine schnellere Narkoseinduktion als Etomidat und Propofol. / Background: Relaxance has to inject close to the narcotics at induction of a patient without empty stomach. Which narcotic will reach the deepest anesthesia rapidly, methohexital, propofol or etomidate? Material/methods: Standard narcotic-induction of 20 ASA 1/2 patients each drug. Measuring the depth of anesthesia with CSI: 1. before starting, after application of midazolam , 2. 2 minutes after injection of fentanyl, 3. after injection of narcotics (injectionperiod 1 minute), 4.after 1 minute propofol 3mg/kg, etomidate 0,3 mg/kg , methohexital 1mg/kg, fentanyl 3 µg/kg, midazolam 7,5 mg Results: CSI after injection of methohexital 70,80 (+/-13,93) less than propofol (p=0,024) with 81,05 (+/-10,82) and etomidate (p=0,026) with 81,45 (+/-12,04).Decline of CSI while injection of methohexital was higher - 9,6 (+/-12,14), with p=0,006 than the decline of CSI while propofolinjection –0,1 (+/-8,31). Reaching CSI < 60 after injection: propofol 2x, etomidate 3x, methohexital 4x , after waiting1 minute: propofol 17x, etomidate 10x, methohexital 16x. Conclusion: Methohexital reaches a sufficient deep anesthesia before the other narcotics.

Authors        Jonathan Kölemo (890303) and Simon Jensen (870212)                         Title              Goodbye to Inbound and Outbound waste - A case study at IKEA’s Distribution                      Centre, Älmhult   Background The DC in Älmhult is working in two administrative teams; Inbound and Outbound. The relationship between and inside the Inbound and Outbound teams are complex and unclear. This increases the risk for bad and unnecessary work. The teams’ are handling tasks regarding planning and scheduling for unloading and loading shipments. The complexity at the DC in Älmhult also makes it difficult for managers to control and understand the whole flow within the two teams. The problem is based on complicated and unsynchronized tasks, poor utilization of IT systems and lack of integration and standardization within the teams work.   Purpose        The purpose with the thesis is to identify wastes within the teams’ work, and thereby provide suggestions for improvements.                 Method         A positivist approach has been used as a scientific perspective throughout the study. The scientific approach is deductive and the research strategy is qualitative. From the theoretical and empirical material an analysis has been designed that eventually lead to a conclusion.   Results            The study shows that both the Inbound and Outbound teams’ processes consist of a number of wastes. By using One-piece-flow, Standardization, Capacity and FIFO theories, the wastes can be reduced or completely eliminated.   Conclusions The most critical wastes have been chosen and by combining the four improvement theories, reductions of unnecessary activities can be made. By implementing the suggested improvements, the number of unnecessary activities can be reduced, and the total process and lead times will decrease. By doing this, the Flow planners can focus on more important activities and the same amount of staff can handle increased throughput of goods.

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Les cellules souches mésenchymateuses (CSM) sont des cellules stromales présentes dans différents types de tissus. En plus de leur capacité à se différencier en plusieurs lignées (chondrocytes, adipocytes et ostéoblastes), les CSM présentent également des propriétés immunosuppressives. Bien que ces mécanismes soient loin d'être entièrement compris, leur capacité immunosuppressive a récemment été démontrée comme étant modulée par des miARN. L'arthrose est la forme la plus courante de maladies articulaires sans traitement curatif et se caractérise principalement par la dégradation du cartilage articulaire, avec des altérations osseuses sous-chondrales et une inflammation synoviale. Les CSM pourraient offrir un potentiel thérapeutique intéressant pour le traitement de l'arthrose.Nos travaux ont montré qu'une injection autologue de CSM d'origine adipeuse (ASC) dans une articulation arthrosique améliore la douleur et les niveaux fonctionnels chez les patients. Nous avons souligné la tolérance immunitaire systémique induite à la suite d'injections intra-articulaires d'ASC. Enfin, nous avons étudié le profil d'expression des miARN des CSM humaines lors de leur stimulation par des cellules mononuclées du sang préalablement activés. Nous avons identifié le miR-29a et le PSAT1 comme de nouveaux candidats pour réguler l'activité immunosuppressive médiée par les CSM. / Mesenchymal Stem Cells (MSCs) are stromal cells present in a number of different tissue types. In addition to their ability to differentiate into multiple lineages (chondrocytes, adipocytes and osteoblasts), MSCs also display immunosuppressive properties. Whilst these mechanisms are far from fully understood, their immunosuppressive capacity has recently been shown to be modulated by miRNAs. OA is the most common form of joint diseases without curative treatment and mainly characterized by the degradation of articular cartilage, with subchondral bone alterations and synovial inflammation. MSC might provide therapeutic potential for treatment of OA.Here, we showed that an autologous injection of adipose-derived MSC (ASC) into an osteoarthritic joint improved pain and function levels in patients. We underscored the systemic immune tolerance induced following intra-articular injections of ASCs. Finally, we investigated the miRNA expression profile of human MSCs upon their stimulation by peripheral blood mononuclear cells. We identified miR-29a and PSAT1 as new candidates to regulate immunosuppressive activity mediated by MSCs.