In this master thesis we investigate implications of the Domain-Wall/Cosmology (DW/C) correspondence on one-point functions of holographic RG-flows. The thesis gives a detailed computation of linearized gauge-invariant Einstein equations in (d+1) dimensions while making the DW/C correspondence explicit. Although holographic renormalization has previously been studied on Lorentzian manifolds, we extend its study to Lorentzian domain-wall solutions with a parameter η. This parameter is introduced to easily travel from domain-walls to cosmologies in the context of the DW/C correspondence. We present the calculation of the vacuum expectation value of general scalar boundary operators of conformal weight Δ dual to a (d+1)-dimensional bulk theory, while still making the DW/C correspondence appear explicitly. Finally, we study the application of these results to holographic RG-flow solutions. In particular, the GPPZ solution is investigated in the framework of the thesis. We find that the vacuum expectation value of the scalar field is invariant under the domain-wall/cosmology correspondence.

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Reklamfilmer blir alltmer anpassade för sociala medier och formatet för nätbaserad reklam har således krympt till endast sex sekunder. Denna studie vill undersöka hur det går att applicera en avancerad berättelsestruktur under dessa sex sekunder och vilka känslor som reklamen försöker väcka hos betraktaren. Denna studie analyserar fyra reklamfilmer från olika produktgrupper för att göra analyserna mer djupgående. Filmerna är inte från samma kategori för att få större variation och täcka en större del av fältet. Studien kommer utgå från Joseph Campbells modell på 17 steg och undersöka vilka steg som syns och vilka som bortfaller/sammankopplas. Utöver att ta reda på vilka steg som finns har studien även fokus på vilka känslor som reklamfilmerna försöker framhäva. Studierna visar att det går att applicera en avancerad berättarstruktur på en bumper-ad på endast sex sekunder, med stor variation av känslostimulans.

Videoinnehåll på internet är en populär källa för informationssökning och underhållning idag. YouTube är den största av de videoplattformar som finns tillgängliga och dess gratisversion finansieras genom reklam. Reklamen i sig innebär ett avbrott i tittarupplevelsen. Tidigare forskning har visat att sådan reklam är ett störande moment och kan orsaka irritation hos tittaren. Därtill väljer många idag att installera insticksprogram i sina webbläsare som blockerar reklamen och hindrar den från att visas. Eftersom att reklamen i dessa fall inte når mottagaren så fungerar inte reklamfinansieringen som tänkt. Denna studie syftar till att undersöka vad hos reklamen som uppfattas som störande och/eller irriterande av tittaren samt hur videoreklam kan utformas för undvika detta. För att besvara frågeställningarna genomfördes en experimentell studie där tio studenter deltog. Resultatet visade att de störande aspekterna relaterar till reklamens tid, dess placering i en video och tittarnas personliga intresse av reklamens innehåll. Slutligen föreslås följande designimplikationer för utformandet av videoreklam: i) reklamklipp bör vara kortare än 15 sekunder för att undvika att uppfattas som irriterande; och att längre reklamklipp bör kunna skippas av användaren; ii) placering av reklamklipp mitt i en vald YouTube-video bör undvikas; iii) reklamklipp bör passa till innehållet av den valda huvudvideon och borde, om möjligt, vara av personligt intresse för tittaren; iv) funktioner såsom att få se kvarvarande tid för ett reklamklipp bör kunna anpassas av tittaren själv, genom dennes användarkonto. / Videos have become a popular source for information gathering and entertainment. YouTube is the biggest video platform available and its free version is funded by ads. The advertisements create an interruption from the viewer experience and research has shown that the ads are disruptive and can cause irritation among the viewers. Many users choose to use plugins in their browsers which block ads to avoid the distraction. Since ad-blockers hinder the ad from reaching the viewer they also hinder the funding of the video platform. This study aims to research what parts of the ads that the user finds disruptive or irritating, and how ads should be designed in order to avoid being perceived as a source of irritation for Swedish viewers. A suggestion will be made on how to design the video ads so that they are as non-disruptive as possible for the user and therefore allowed to be a part of the viewing experience. To answer the questions at hand an experimental study was conducted with ten students. The results showed that the irritating aspects of ads are related to the running times, its placement in a video and the viewers own interest in the content of the ad. Finally, the following implications are suggested for the design of video ads: i) ads should be shorter than 15 seconds to avoid being perceived as irritating; users should be able to skip longer ads; ii) ads showing in the middle of the video should be avoided; iii) ad content should match the content of the video and, if possible, be relevant to the viewer and their interests; iv) features such as showing the time remaining of the ad should be made customisable by the user, through their user account.

Online behavioral targeting (OBT) are customized ad messages based on personal information to enhance advertising effectiveness. Greater personalization typically increases relevance but is also told to cause privacy concerns. This study examines the constructs of advertising engagement and advertising avoidance on Instagram. Using the Critical Incident Technique, it identifies a typology of the three antecedents of both engagement and avoidance: relevance, degree of personalization and traceability of data source. While a high degree of personalization and relevance was found to be prevalent in both engagement and avoidance scenarios, tractability of data source was identified as an ethical boundary for research subjects and a decisive criterium in whether privacy concerns were being raised. The results propose common trigger combinations for both engagement and avoidance scenarios, yet there are cases falling outside the norm with suggests that acceptance and reactions to OBT is a highly complex construct were many external variables and as well as personal character traits might be at play. / Online beteendeinriktning (OBT) är anpassade annonsmeddelanden baserat på personlig information för att förbättra reklameffektiviteten. Större personalisering ökar vanligtvis relevansen men indikerar också att orsaka integritetsproblem. Denna studie undersöker konstruktioner av reklamengagemang och reklamundvikande på Instagram. Med den kritiska incidenttekniken identifieras en typologi av de tre föregångarna för både engagemang och undvikande: relevans, grad av personalisering och spårbarhet av datakällan. Emedan en hög grad av personalisering och relevans befanns vara vanligt i både engagemangs- och undvikelsesscenarier, identifierades datakällans spårbarhet som en etisk gräns för forskningsämnen och ett avgörande kriterium för huruvida integritetshänsyn togs upp eller inte. Resultaten föreslår vanliga utlösarkombinationer för både engagemangs- och undvikelsesscenarier, men det existerar fall som faller utanför normen men antyder att acceptans och reaktioner på OBT är en mycket komplex konstruktion där många externa variabler och personliga karaktärsdrag står på spel.

2020 and 2021 were shocking years for advertising and digital marketing since both Apple and Google announced that they would limit third-party tracking. Google and Apple’s news created turmoil in the marketing business sector since advertisers no longer will be able to target and track the success of their digital ads as efficiently and effectively. In addition, there will be significant changes in the industry since these new privacy rules mean that there will be an inability of personalisation and just-in-time targeting for digital marketing, and advertisers have dubbed this situation the “adpocalypse.”  Both secondary and primary data were collected to answer the research question, how have the new privacy rules and regulations impacted the different steps of the AIDA model in digital media planning for digital advertising. Secondary data has been collected from business journals and academic journals, and the primary data has been collected through in-depth interviews. Further, the research is exploratory and explores the research question to give the reader a greater understanding of the subject area.   The following can be concluded from the research. Internet privacy rules and regulations will impact awareness, and it will be more challenging for companies to create awareness for their product offerings. Awareness will be heavily built on brand recognition, and the strategies for this step will revert to more traditional methods.  Interest would be affected since companies no longer will be able to follow up on their communication strategies as effectively. This research showed that the further down the company’s sales funnel, the more impacted the strategies. Further, desire would be more challenging for companies to create since retargeting, just-in-time targeting, and micro-targeting would no longer be possible in the same manner. Lastly, since action results from desire, this step would be heavily impacted.

Scenario-based testing is a major pillar in the development and effectiveness assessment of automated driving systems. Thereby, test scenarios address different information layers and situations (normal driving, critical situations and accidents) by using different databases. However, the systematic combination of accident and / or normal driving databases into new synthetic databases can help to obtain scenarios that are as realistic as possible. This paper shows how statistical matching (SM) can be applied to fuse different categorical accident and traffic observation databases. Hereby, the fusion is demonstrated in two use cases, each featuring several fusion methods. In use case 1, a synthetic database was generated out of two accident data samples, whereby 78.7% of the original values could be estimated correctly by a random forest classifier. The same fusion using distance-hot-deck reproduced only 67% of the original values, but better preserved the marginal distributions. A real-world application is illustrated in use case 2, where accident data was fused with over 23,000 car trajectories at one intersection in Germany. We could show that SM is applicable to fuse categorical traffic databases. In future research, the combination of hotdeck- methods and machine learning classifiers needs to be further investigated.

This dissertation is devoted to investigation of quantum chaos in the Sachdev-Ye-Kitaev (SYK) and supersymmetric SYK models. First, a unified minimal scheme is developed to classify quantum chaos in the SYK and supersymmetric SYK models and also work out the structure of the energy levels in one periodic table. The SYK with even q-body or supersymmetric SYK with odd q-body interaction, with N even or odd number of sites, are put on an equal footing in the minimal Hilbert space; N (mod 8), q (mod 4) double Bott periodicity, and a reflection relation are identified. Then, exact diagonalizations are performed to study both the bulk energy level statistics and hard-edge behaviors. Excellent agreements between the exact diagonalization results and the symmetry classifications are demonstrated. This compact and systematic method can be transformed to map out more complicated periodic tables of SYK models with more degrees of freedom, tensor models, or symmetry protected topological phases.

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