År 2020 blev världen utsatt av viruset Covid-19, en pandemi som har påverkat mångas liv, allt från företag till människors vardag. Medan restaurangindustrin har påverkats negativt av den ökande mängden hemmasittande, har matleveransindustrin istället ökat. Under samma år publicerade McDonalds, en av världens största restaurangkedjor, två reklamfilmer för deras matleveranstjänst McDelivery, en i Sverige och en i Japan. Då dessa två länders regeringar har tagit liknande aktioner mot pandemin blir förutsättningarna kring reklamerna likartade och därmed mer optimalt för att se kulturella skillnader. Syftet med denna studie är att analysera dessa två reklamfilmer, som publicerades under pandemin, för att se om den kultur som återspeglas i reklamerna följer sina nationers samhällskultur. Beräknandet och systematiseringen av kulturerna i denna studie har förts via Hofstedes 6-D modell, en modell som värderar samhällens kultur i 6 dimensioner. Reklamerna har först genomgått en semiotisk analys för att beskriva dess innehåll, och sedan analyserats av teorier angående storytelling och retorik. Detta har sedan jämförts med teorin bakom de 6 dimensionerna i Hofstedes 6-D modell, samt hur dessa påverkar marknadsföringen. Studien visade att den japanska reklamen förhöll sig relativt väl mot landets värdering i Hofstedes 6-D modell, där endast en av dimensionerna avvek. Den svenska reklamfilmen var däremot mindre lik sin samhällskultur då det var relativt jämnt fördelat i om dimensioner avvek eller stämde överens med varandra. Detta var specifikt inom dimensionen osäkerhetsundvikande där reklamen visade starka värden. / <p>Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet</p>

In the last decade, convolutional neural networks have been used to a large extent for image classification and recognition tasks in a number of fields. For image weather classification, data can be both sparse and unevenly distributed amongst labels in the training set. As a way to improve the performance of the classifier, one often used traditional augmentation techniques to increase the size of the training set and help the classifier to converge towards a desirable solution. This can often be met with varying results, which is why this work intends to investigate another approach of augmentation using image synthesis. The idea is to make use of the fact that most datasets contain at least one label that is well represented. In weather image datasets, this is often the sunny label. CycleGAN is a framework which is capable of image-to-image translation (i.e. synthesizing images to represent a new label) using unpaired data. This makes the framework attractive as it does not put any unnecessary requirements on the data collection. To test the whether the synthesized images can be used as an augmentation approach, training samples in one label was deliberately reduced sequentially and supplemented with CycleGAN synthesized images. The results show adding synthesized images using CycleGAN can be used as an augmentation approach, since the performance of the classifier was relatively unchanged even though the number of images was low. In this case it was as few as 198 training samples in the label that represented foggy weather. Comparing CycleGAN to traditional augmentation techniques, it proved to be more stable as the number of images in the training set decreased. A modification to CycleGAN, which used weight demodulation instead of instance normalization in its generators, removed artifacts that otherwise could appear during training. This improved the visual quality of the synthesized images overall. / <p>Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet</p>

As society strives for an increasing amount of connectivity and digitalization to increase accessibility and productivity, society is also more vulnerable then ever before. Thus, societal, business and personal infrastructure is the most vulnerable it has ever been. Therefore, the need for systems that can digitally catalog all devices within a network and provide information about each and every device, what other devices it is communicating with and its placement within the network, along with providing ways to identify potential threats before it is to late, is at an all time high. This report presents the process of designing, developing and using a system aimed at performing passive asset detection and how it can lead to an increased visibility and knowledge of a network. The system is developed using C++, Python and the graph database Neo4j, which also provides a tool called Bloom to interactively visualize the database using custom Bloom perspectives. It uses direct informational gain to make initial assumptions about a device, subnetwork or network and tries to strengthen these assumptions using indirect information that is gained by passively analyzing traffic, provided over a longer period of time. Data can be supplied using either pcap files or by using the live capture feature and should be recorded at the router closest to the end point devices in each individual subnetwork to work optimally. / <p>Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet</p>

As society strives for an increasing amount of connectivity and digitalization to increase accessibility and productivity, society is also more vulnerable than ever before. Thus, societal, business and personal infrastructure is the most vulnerable it has ever been. Therefore, the need for systems that can digitally catalog all devices within a network and provide information about each and every device, what other devices it is communicating with and its placement within the network, along with providing ways to identify potential threats before it is too late, is at an all time high. This report presents the process of designing, developing and using a system aimed at performing passive asset detection and how it can lead to an increased visibility and knowledge of a network. The system is developed using C++, Python and the graph database Neo4j, which also provides a tool called Bloom to interactively visualize the database using custom Bloom perspectives. It uses direct informational gain to make initial assumptions about a device, subnetwork or network and tries to strengthen these assumptions using indirect information that is gained by passively analyzing traffic, provided over a longer period of time. Data can be supplied using either pcap files or by using the live capture feature and should be recorded at the router closest to the end point devices in each individual subnetwork to work optimally. / <p>Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet</p>

Syftet med denna studie var att utforma ett koncept som visualiserar grafiska riktlinjer för secondhand-butiker i avsikt att tilltala en bredare målgrupp. Studien baserades på en metod innehållande både kvalitativ och kvantitativ datainsamling. Det teoretiska ramverket innefattade teorier relaterade till varumärkesbyggande, designprinciper vid formgivning samt de grundläggande komponenterna inom grafisk identitet för att säkerställa att välgrundade designbeslut tagits. Det grafiska konceptet skapades genom ett iterativt designarbete baserat på resultat från förstudie, fokusgrupper, digitala enkätundersökningar och tematiska analyser. I den avslutande undersökningen av den slutgiltiga designen samlades kvantitativa data in för att ta reda på om arbetets syfte uppnåtts eller ej. Resultatet visade att det är viktigt att orden second hand inkluderas i logotypen. Tydlighet och enkelhet bör ligga i fokus vid framtagandet av grafiska formspråk för secondhand-butiker för att tilltala en bredare målgrupp. Många respondenter efterfrågade att kopplingen till hållbarhet framhävs. Den mest efterfrågade färgen var grön. Övriga färger ska helst upplevas som miljövänliga, positiva, lugna och inbjudande. Studien resulterade i konceptuella visualiserade riktlinjer. Dessa bestod av en logotyp, fyra färger samt typsnitt. Logotypen är i formen av ett runt emblem, innehållande en symbol som kombinerar ett löv och ett löv och ett hjärta för att symbolisera hållbarhet och välgörenhet. / <p>Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet</p>

This is a study where social media users’ reactions and interpretations to different types of content moderation messages. The focus was to try and determine what reactions explanations, explanations by an AI, or explanations by human moderators had on social media users. The goal of the study was to have this study become a pilot study for future research to find a solution to fair and transparent content moderation. The main research question sought to find out what ways do user attitudes differ from content moderation messages if the moderator is human or an AI. It was found that users react more strongly against AI moderation and decision making, showing higher rates of frustration. Providing a reason for moderation increases fairness and transparency rate, regardless of human or AI delivering the decision. / <p>Självständigt Examensarbete (Forskningsartikel)</p>

This report presents the work of a master thesis which aim was to investigate how sonification can be used in the space visualization software OpenSpace to further convey information about the Solar System. A sonification was implemented by using the software SuperCollider and was integrated into OpenSpace using Open Sound Control to send positional data to control the panning and sound level of the sonification. The graphical user interface of OpenSpace was also extended to make the sonification interactive. Evaluations were conducted both online and in the Dome theater to evaluate how well the sonification conveyed information. The outcome of the evaluations shows promising results, which might suggest that sonification has a future in conveying information of the Solar System.

This master thesis report presents the development process and result of an artificial neural network model that can predict if a file has been encrypted. It was developed as a stand alone component that can be implemented in to a backup system. The development process was tested to determine the best possible outcome and it was implemented to a rudimentary backup system. The resulting software was a command line interface that gave the user full access to the training and testing process. The backup system is also implemented in this command line interface for test purposes. The model was successful in identifying encrypted files.

Includes bibliographical references. / One of the recent technological devices that have been introduced in the educational domain is the interactive whiteboard (IWB). IWBs have become established teaching and learning tools, particularly in primary school classrooms in developed English speaking countries and have more recently been deployed in developing countries such as South Africa. The Western Cape Province in South Africa has rolled out a province-wide IWB programme over the last decade, despite limited local research on the pedagogical value of IWBs in South African schools. This research study aims to investigate how the IWB can be used to encourage collaboration amongst the learners in a Grade 6 Technology Education class at a primary school in the Western Cape and specifically to assist the teacher in understanding how her pedagogy needs to change to optimise learner collaboration in association with an IWB. To understand the ways in which the IWB influences the activities in the classroom, Activity Theory is used as a framework to understand the tensions that arise and how the teacher needs to change her pedagogical strategies to successfully resolve these tensions.

Modeled on the master-apprenticeship relationship, student designers gain access to implicit design knowledge mainly through the conversations with their tutors during studio projects. However, intimate design studio tutelage is being challenged by increasing student to staff ratios. If leveraged effectively, technology offers the potential to maximize tutors' time investment in order to allow them to tend to more students. Scaffolding tools (Reiser, 2004) as supplement to teacher support, can assist learners with complex tasks previously out of their reach. This case study is a critical realist inquiry into the use of a scaffolding tool, Cognician Cogs. It seeks to reveal the ways in which and circumstances under which these Cogs scaffold conceptual design in a second year architecture studio project. The study draws upon Cognitive Apprenticeship as a conceptual framework to shed light on design studio practices involving specially developed Cogs. The mixed methodology approach adopted consisting mainly of qualitative data in the form of the project brief, scaffolding tool content, sample design critique conversations and interviews with three tutors and nine students. Supplementary quantitative data included closed survey question responses and Studio work marks collected from the entire class (39). Thematic analysis of the qualitative data was framed by the Vitruvian guiding principles of architecture: 'Firmness', 'Commodity' and 'Delight'. The study revealed that the intended use of the Cogs to cover aspects of Firmness and Commodity only resulted in the over-scaffolding of Firmness and the under-scaffolding of Delight. The students' resulting designs were practically acceptable, but lacked novelty.