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The world wide web has gone through several distinct eras since its launch in 1989, going through the eras Web 1.0, Web 2.0, and Web 3.0. There is an upcoming era, Web 4.0, where the web will become seamlessly integrated with people's everyday life. However, creating consumer engagement across platforms has already been recognized as challenging in Web 3.0 (Dolan et al., 2016). A type of storytelling, known for creating engagement is transmedia storytelling (TS). TS is a technique of telling one single story across multiple platforms, and when enjoyed together becomes a full experience. There is limited research conducted on the relationship between TS and the web, which became the problem of this study. The purpose of this study is to explorethe research gap and it was fulfilled by asking two research questions. The first oneestablished an understanding about the relationship between TS and Web 2.0 and 3.0, tounderstand how TS evolves and adapts to the web. Based on the built foundation, the second question aimed to explore the possibilities of TS and Web 4.0, and how they could benefit from each other and grow together. To answer our research questions this paper utilised the method of a multiple-case study that examines two cases, one in Web 2.0, and one in Web 3.0. The data was manually collected, traced and broken down into instances using reverse engineering. To analyse the data, it was rebuilt with visual mapping to understand the connections, and lastly compared to the web characteristics and TS principles. Concluding the findings and analysis, it can be established that TS evolves alongside the web, utilising and adapting to the new characteristics. In Web 2.0, TS relied heavily on offline sources such as DVD’s and TV, while in Web 3.0, it existed solely online. The participatory activity also grew from Web 2.0 to 3.0, where the users were an active part of the campaign evolving in Web 3.0. TS manages to create engagement across platforms, and benefits from new technical innovations. After the individual case reports, and cross-case analysis, it could be concluded that TS has good chances of continuing to adapt in the rise of Web 4.0. This study explored the research gap further, offering valuable insight onthe topic and opening for various further research possibilities, where TS and web cancontinue being investigated.

This thesis is about cyber-security and penetration testing. More specifically it concerns penetration testing of a Hövding bicycle airbag which is a smart alternative to a traditional bicycle helmet. The thesis focuses on exploiting Bluetooth Low Energy, firmware analysis and reverse engineering. The research question is as follows: Is the Hövding bicycle airbag secure against cyber attacks? No previous work has been done with regards to penetration testing the Hövding, despite its popularity. The Hövding’s latest model allows users to connect to their Hövding using a smartphone, with Bluetooth Low Energy as a communication protocol. There is limited research that has been done on exploiting this protocol, which is relatively complex and secure. To answer the research question a number of threats and attacks is identified with the help of the STRIDE model and whose risk is assessed with the DREAD model. These attacks are later executed in a series of penetration tests on the Hövding. The result shows that the Hövding has been securely developed and no vulnerabilities are found. Although no vulnerabilities are found the thesis discusses various approaches that can be useful for further work relating penetration testing similar devices. Regarding further work on the Hövding, there might be some vulnerabilities left to be discovered, perhaps related to hardware hacking or firmware tampering. / I denna avhandling analyseras cybersäkerhet och penetrationstestning. Den behandlar penetrationstestning av Hövdings cykelairbag som är ett uppkopplat alternativ till traditionell cykelhjälm. Fokus är exploatering av Bluetooth Low Energy, analys av fast programvara och baklängeskonstruktion. Frågeställningen lyder: Är Hövdings cykelairbag skyddad mot cyberangrepp? Det finns inga tidigare vetenskapliga arbeten rörande penetrationstestning av Hövdingen, trots dess popularitet. Hövdings senaste modell tillåter användaren att ansluta cykelairbagen till mobil med hjälp av Bluetooth Low Energy-protokollet. Forskning om exploatering av detta protokoll, som är relativt komplext och säkert, är begränsat. För att besvara frågeställningen identifieras hot och attacker med hjälp av STRIDE-modellen vars risk sedan fastställs med DREAD-modellen. Dessa attacker genomförs i en serie penetrationstest på Hövdingen. Resultatet visar att Hövdingen har utvecklats på ett säkert sätt och inga sårbarheter påträffas. Trots att inga sårbarheter påträffas diskuteras olika ansatser som kan vara tillämpliga för framtida penetrationstestning av liknande apparater. Gällande framtida studier av Hövdingen kan det möjligtvis finnas sårbarheter kvar att upptäcka, till exempel inom hårdvaruhackning eller manipulering av fast programvara.

Spezialisierung Theoretische Biologie / Obwohl die Krebstherapie im letzten Jahrhundert große Fortschritte gemacht hat, bleibt die Resistenz gegen medikamentöse Behandlungen ein großes Hindernis im Kampf gegen den Krebs. In dieser Arbeit habe ich ein R-Paket namens STASNet entwickelt, das semi-quantitative Modelle der Signaltransduktion aus Signalisierungs-Störungsantwortdaten unter Verwendung von Least Square Modular Response Analysis-Modellen generiert. Um zu untersuchen, wie gut STASNet die Aktivität von Signalwegen quantifizieren kann, haben wir Perturbationsdaten von einem Paar isogener Darmkrebszelllinien mit und ohne SHP2-Knock-out, einem bekannten Resistenzmechanismus bei dieser Krebsart, verwendet. Ich habe dann untersucht die Resistenz gegen die MEK- und ALK-Hemmung beim Neuroblastom, einem pädiatrischen Krebs mit schlechter Prognose. Ein Wirkstoffscreening zeigte, dass der MEK-Inhibitor Selumetinib ein Panel von Neuroblastom-Zelllinien in drei sensitive und sechs resistente Zelllinien trennte, dass konnte nicht mit einzelnen molekularen Markern erklärt. STASNet-Modelle zeigten, dass die starke Resistenz gegen Selumetinib durch eine starke Rückkopplung von ERK auf MEK oder eine vielschichtige Rückkopplung sowohl auf MEK als auch auf IGF1R getrieben wurde. Aus dem Modell konnte eine kombinatorische Therapie abgeleitet werden, die auf MEK in Kombination mit entweder RAF oder IGF1R abzielt, je nach Art der in der Zelllinie vorhandenen Rückkopplungen. Schließlich ergab die Untersuchung der Wirkung von NF1-KO auf die Signalübertragung, dass der Verlust von NF1 den MAPK-Weg für die Liganden-induzierte Aktivierung hypersensibilisierte, aber das ERK-RAF-Rückkopplung störte. Die Erkenntnisse aus den in dieser Arbeit entwickelten Modellen werden somit dazu beitragen, personalisierte Kombinationen von Inhibitoren zu entwerfen, die als Zweitlinientherapie nach molekularer Untersuchung der Tumorreaktion auf die Erstbehandlung eingesetzt werden könnten. / Cancer therapy has seen immense progress over the last century but resistance to drug treatments remains a major obstacle in the war against cancer. I developed an R package named STASNet to generate models of signal transduction from signalling perturbation-response data using Least Square Modular Response Analysis models. I used these models to study how differences in signal transduction relate to drug resistance and can be used to make predictions about resistance mechanisms and optimal treatments. To show how STASNet can accurately quantify the activity of signalling pathways, I used perturbation data from a pair of isogenic colon cancer cell line with and without SHP2 knock-out, a known resistance mechanism in this cancer type, which showed that MAPK signalling is more affected by SHP2 knock-out than PI3K signalling, confirming the role of SHP2 as a primary MAPK component. I investigated resistance to MEK and ALK inhibition in neuroblastoma, a pediatric cancer with a dismal prognosis. The MEK inhibitor Selumetinib separated a panel of neuroblastoma cell lines into three sensitive and six resistant cell lines that could not be explained with individual molecular markers. STASNet models trained on perturbation-response data from these cell lines revealed that the strong resistance to Selumetinib was driven by a strong feedback from ERK to MEK or a multi-layered feedback to both MEK and IGF1R. This was confirmed by phosphoproteomics and suggested a therapy targeting MEK in combination with either RAF or IGF1R depending on the type of feedback present in the cell line that was confirmed experimentally. Finally, studying the effect of NF1-KO on signalling revealed that the loss of NF1 hyper-sensitized the MAPK pathway to ligand-induced activation but disrupted the ERK-RAF feedback. Those insights to design personalized combinations of inhibitors that could be used as second line therapy after molecularly monitoring the tumor response to the initial treatment.

The market of Android applications is huge, and in 2019, Google Play users worldwide downloaded 84.3 billion mobile applications. With such a big user base, any security issues could have big negative impacts. That is why penetration testing of Android applications is important and it is also why Google has a bug bounty program where people can submit vulnerability reports on their most downloaded applications. The aim of the project was to assess the security of Android applications from the Google Play Security Reward Program by performing penetration tests on the applications. A threat model of Android applications was made where potential threats were identified. A choice was made to focus on the Spotify Application for Android where threats were given ratings based on risks associated with them in the context of the Spotify Application. Penetration tests were made where testing depth was determined by the ratings associated with the attacks.The results of the tests showed that the Spotify Application is secure, and no test showed any real possibility of exploiting the application. The perhaps biggest potential exploit found is a Denial of Service attack that can be made through a malicious application interacting with the Spotify application. The result doesn’t guarantee that the application isn’t penetrable and further testing is needed to give the result more reliability. The methods used in the project can however act as a template for further research into both Spotify and other Android applications. / Marknaden för Android applikationer är enorm och 2019 laddade Google Play användare ner 84.3 miljarder mobil-applikationer. Med en så stor användarbas kan potentiella säkerhetsproblem få stora negativa konsekvenser. Det är därför penetrationstest är viktiga och varför Google har ett bug bounty program där folk kan skicka in sårbarhetsrapporter för deras mest nedladdade applikationer. Målet med projektet är att bedöma säkerheten hos Android applikationer från Google Play Security Reward Program genom utförande av penetrationstester på applikationerna. En hotmodell över Android applikationer skapades, där potentiella hot identifierades. Ett val att fokusera på Spotify för Android gjordes, där hot gavs rankingar baserat på riskerna associerade med dem i kontexten av Spotify applikationen. Penetrationstest gjordes med testdjup avgjort av rankingarna associerade med attackerna.Resultatet av testen visade att Spotify applikationen var säker, och inga test visade på några riktiga utnyttjningsmöjligheter av applikationen. Den kanske största utnyttjningsmöjligheten som hittades var en Denial of Service-attack som kunde göras genom en illvillig applikation som interagerar med Spotify applikationen. Resultaten garanterar inte att applikationen inte är penetrerbar och fortsatt testande behövs för att ge resultatet mer trovärdighet. Metoderna som användes i projektet kan i alla fall agera som en mall för fortsatt undersökning av både Spotify såväl som andra Android applikationer.

Systems biology is an emergent field focused on developing a system-level understanding of biological systems. In the last decade advances in genomics, transcriptomics and proteomics have gathered a remarkable amount data enabling the possibility of a system-level analysis to be grounded at a molecular level. The reverse-engineering of biochemical networks from experimental data has become a central focus in systems biology. A variety of methods have been proposed for the study and identification of the system's structure and/or dynamics. The objective of this dissertation is to introduce and propose solutions to some of the challenges inherent in reverse-engineering of biological systems. First, previously developed reverse engineering algorithms are studied and compared using data from a simulated network. This study draws attention to the necessity for a uniform benchmark that enables an ob jective comparison and performance evaluation of reverse engineering methods. Since several reverse-engineering algorithms require discrete data as input (e.g. dynamic Bayesian network methods, Boolean networks), discretization methods are being used for this purpose. Through a comparison of the performance of two network inference algorithms that use discrete data (from several different discretization methods) in this work, it has been shown that data discretization is an important step in applying network inference methods to experimental data. Next, a reverse-engineering algorithm is proposed within the framework of polynomial dynamical systems over finite fields. This algorithm is built for the identification of the underlying network structure and dynamics; it uses as input gene expression data and, when available, a priori knowledge of the system. An evolutionary algorithm is used as the heuristic search method for an exploration of the solution space. Computational algebra tools delimit the search space, enabling also a description of model complexity. The performance and robustness of the algorithm are explored via an artificial network of the segment polarity genes in the D. melanogaster. Once a mathematical model has been built, it can be used to run simulations of the biological system under study. Comparison of simulated dynamics with experimental measurements can help refine the model or provide insight into qualitative properties of the systems dynamical behavior. Within this work, we propose an efficient algorithm to describe the phase space, in particular to compute the number and length of all limit cycles of linear systems over a general finite field. This research has been partially supported by NIH Grant Nr. RO1GM068947-01. / Ph. D.

Truss-like shapes can occur in topology optimization described by an assembly of finite elements or its boundary represented as a polygon mesh. Such shape description does not cover a common engineering parametrization like the lines of a frame structure and its corresponding cross-section. This article addresses the truss-parametrization of such optimization using curve skeletons and Meta Balls. While the curve skeleton is common in the truss-parametrization, including Meta Balls can lead to an overall implicit and smooth shape description.

Die Konferenz Entwerfen – Entwickeln – Erleben bietet ein besonderes Podium zum Austausch von Wissenschaftlern und Praxisvertretern aus den zentralen Bereichen der Produktentwicklung. Der vorliegende Band enthält Beiträge der EEE2016 unter anderem zu Industrie 4.0, Cyber-Physical Systems und Virtual Reality in vielfältigen Anwendungsbereichen des Maschinenbaus, zu Innovationsmanagement, Konstruktionsmethodik und Product Lifecycle Management sowie zu Reverse Engineering und generativen Verfahren. Die Technische Universität Dresden und technischesdesign.org ermöglichten in Kooperation mit der Gruppe Virtuelle Produktentwicklung der Wissenschaftlichen Gesellschaft für Produktentwicklung (WiGeP) und dem Rat für Formgebung die fachübergreifende Diskussion des Schwerpunkt- Themas inmitten der interdisziplinären Dresdner Wissenschaftslandschaft. In diesem Band sind die Beiträge zur Konstruktionstechnik und zur Virtuellen Produktentwicklung enthalten, ein weiterer Band (ISBN 978-3-95908-061-3, herausgegeben von Jens Krzywinski et al.) fasst die Beiträge zum Industrial Design zusammen.

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Die Konferenz Entwerfen – Entwickeln – Erleben bietet ein besonderes Podium zum Austausch von Wissenschaftlern und Praxisvertretern aus den zentralen Bereichen der Produktentwicklung. Der vorliegende Band enthält Beiträge der EEE2014 unter anderem zu Industrie 4.0, Cyber-Phy­sical Systems und Virtual Reality in vielfältigen Anwendungsbereichen des Maschinenbaus, zu Innovationsmanagement, Konstruktionsmetho­dik und Product Lifecycle Management sowie zu Reverse Engineering und generativen Verfahren. Die Technischen Universität Dresden und technischesdesign.org ermög­lichten in Kooperation mit der Gruppe Virtuelle Produktentwicklung der Wissenschaftlichen Gesellschaft für Produktentwicklung (WiGeP), dem Mathematisch-Physikalischen Salon der Staatlichen Kunstsammlungen Dresden und der Hochschule für Bildende Künste Dresden die fachüber­greifende Diskussion des Schwerpunkt-Themas inmitten der Dresdner Altstadt. In diesem Band sind die Beiträge zur Konstruktionstechnik und zur Virtuellen Produktentwicklung enthalten, ein weiterer Band (http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-144950, herausgegeben von Mario Linke et al.) fasst die Bei­träge zum Technischen Design zusammen.