Although most brain tumor diagnosis studies have focused on tumor segmentation and localization operations, few studies have focused on tumor detection as a time- and effort-saving process. This study introduces a new network structure for accurate glioma tumor detection and classification using two parallel deep convolutional neural networks (PDCNNs). The proposed structure is designed to identify the presence and absence of a brain tumor in MRI images and classify the type of tumor images as high-grade gliomas (HGGs, i.e., glioblastomas) or low-grade gliomas (LGGs). The introduced PDCNNs structure takes advantage of both global and local features extracted from the two parallel stages. The proposed structure is not only accurate but also efficient, as the convolutional layers are more accurate because they learn spatial features, and they are efficient in the testing phase since they reduce the number of weights, which reduces the memory usage and runtime. Simulation experiments were accomplished using an MRI dataset extracted from the BraTS 2017 database. The obtained results show that the proposed parallel network structure outperforms other detection and classification methods in the literature.

The use of medical images has been continuously increasing, which makes manual investigations of every image a difficult task. This study focuses on classifying brain magnetic resonance images (MRIs) as normal, where a brain tumor is absent, or as abnormal, where a brain tumor is present. A hybrid intelligent system for automatic brain tumor detection and MRI classification is proposed. This system assists radiologists in interpreting the MRIs, improves the brain tumor diagnostic accuracy, and directs the focus toward the abnormal images only. The proposed computer-aided diagnosis (CAD) system consists of five steps: MRI preprocessing to remove the background noise, image segmentation by combining Otsu binarization and K-means clustering, feature extraction using the discrete wavelet transform (DWT) approach, and dimensionality reduction of the features by applying the principal component analysis (PCA) method. The major features were submitted to a kernel support vector machine (KSVM) for performing the MRI classification. The performance evaluation of the proposed system measured a maximum classification accuracy of 100 % using an available MRIs database. The processing time for all processes was recorded as 1.23 seconds. The obtained results have demonstrated the superiority of the proposed system.

Computer-aided diagnosis (CAD) systems have become very important for the medical diagnosis of brain tumors. The systems improve the diagnostic accuracy and reduce the required time. In this paper, a two-stage CAD system has been developed for automatic detection and classification of brain tumor through magnetic resonance images (MRIs). In the first stage, the system classifies brain tumor MRI into normal and abnormal images. In the second stage, the type of tumor is classified as benign (Noncancerous) or malignant (Cancerous) from the abnormal MRIs. The proposed CAD ensembles the following computational methods: MRI image segmentation by K-means clustering, feature extraction using discrete wavelet transform (DWT), feature reduction by applying principal component analysis (PCA). The two-stage classification has been conducted using a support vector machine (SVM). Performance evaluation of the proposed CAD has achieved promising results using a non-standard MRIs database.

The successful early diagnosis of brain tumors plays a major role in improving the treatment outcomes and thus improving patient survival. Manually evaluating the numerous magnetic resonance imaging (MRI) images produced routinely in the clinic is a difficult process. Thus, there is a crucial need for computer-aided methods with better accuracy for early tumor diagnosis. Computer-aided brain tumor diagnosis from MRI images consists of tumor detection, segmentation, and classification processes. Over the past few years, many studies have focused on traditional or classical machine learning techniques for brain tumor diagnosis. Recently, interest has developed in using deep learning techniques for diagnosing brain tumors with better accuracy and robustness. This study presents a comprehensive review of traditional machine learning techniques and evolving deep learning techniques for brain tumor diagnosis. This review paper identifies the key achievements reflected in the performance measurement metrics of the applied algorithms in the three diagnosis processes. In addition, this study discusses the key findings and draws attention to the lessons learned as a roadmap for future research.

The utilization of different types of brain images has been expanding, which makes manually examining each image a labor-intensive task. This study introduces a brain tumor segmentation method that uses two parallel U-Net with an asymmetric residual-based deep convolutional neural network (TPUAR-Net). The proposed method is customized to segment high and low grade glioblastomas identified from magnetic resonance imaging (MRI) data. Varieties of these tumors can appear anywhere in the brain and may have practically any shape, contrast, or size. Thus, this study used deep learning techniques based on adaptive, high-efficiency neural networks in the proposed model structure. In this paper, several high-performance models based on convolutional neural networks (CNNs) have been examined. The proposed TPUAR-Net capitalizes on different levels of global and local features in the upper and lower paths of the proposed model structure. In addition, the proposed method is configured to use the skip connection between layers and residual units to accelerate the training and testing processes. The TPUAR-Net model provides promising segmentation accuracy using MRI images from the BRATS 2017 database, while its parallelized architecture considerably improves the execution speed. The results obtained in terms of Dice, sensitivity, and specificity metrics demonstrate that TPUAR-Net outperforms other methods and achieves the state-of-the-art performance for brain tumor segmentation.

This study was conducted with the purpose of studying how the second generation of immigrants in Sweden experience the representation in western television series and how their reality image of the country overlooked the fictive. The study is analyzed based on postcolonial perspectives and theories that include representation, orientalism and stereotypes. The aim was based on whether or not these interviewees felt represented and if the image of the culture and the country were fairly visualized and how they experienced the series vs reality. The method used to answer the question was qualitative interviews where the results showed that the actual experiences of the interviewees did not match with what was shown in the series. Based on their interpretations a big part of the series was constructed by stereotypes.

The Internet beside providing many advantages has some disadvantages. The full unfamiliarity with cyberspace can bring harms and inconvenience to families. This study attempted to introduce the disadvantages and threats on the Internet and present some countermeasures to decrease such threats and harms. Social networks are currently so epidemic that even many companies and organizations formally supply the internal communication system among their members and employees through this social networks and the number of the users of such networks is increasing daily. The term “information security” covers a broad spectrum of activities in an organization. Information security means preventing the unauthorized access to information and products or apply some changes or delete such information using a series of processes. Such actions can be considered as a protection package against current resources in different situations (e.g., a hacker attacks which occurs a lot) by those in charge of information security. One of the most important issues which is considered as a security challenge in these networks is the security and retention of the data and information shared by users from unauthorized access and unwanted disclosure. In this article the Kuleshov effect from cinema has been deployed to explain and launch a behavioral analysis of online activities.

The demand on a bearing ring grinder, as any other machine tool, is to produce parts as per the specification and desired quality. A failure to achieve the quality can be due to functional issues or mechanical failure modes. Ultimately this results in lower productivity and higher production costs. Despite the increased emphasis on practicing condition-based machine maintenance (CBM) in manufacturing applications, it is still considered a challenge to fully deploy CBM in production machines due to diversity in equipment and variety in machine configurations as well as complex characteristics of failure modes. Although there exists extensive literature on CBM for machine tools and subsystems, the issue remains with realization of a technically capable and cost effective CBM system, specifically for a bearing ring grinder. Therefore, sensor(s) selection, data acquisition setup, data processing and analysis are the essential factors considered in the proposed framework to ensure a systematic and organized CBM implementation. The CBM setup is evaluated against production of bearing rings under different process and failure conditions. A machine type independent data acquisition system is designed to capture both machine and process dynamics. The data gathered from sensors at strategic locations exhibits its effectiveness in capturing the process and condition variations in relation to time and operating modes. The presented results of data analysis support the capability and effectiveness of the proposed framework. The utility of this framework can be extended for any number of scenarios including predictive maintenance or adaptive process optimization where solutions using machine learning and artificial intelligence tools can benefit from high dimensional structured dataset. The proposed framework provides a strong foundation to fast track the adaption of CBM in other production machines having similar subsystems.

The refugee crisis during 2015 developed into a highly debated topic. Morning sofas on television, afternoon broadcasts on radio, evening newspapers' leaflets - the news focus was crystal clear. All written reports at that time included diverse topics, including the size of the refugee migration, the long-term economic effects of the refugee crisis, the politicians' proposals, the negotiations in the EU and the tragic accidents in the Mediterranean. The "migration crisis" became a recurring concept and various news media generated their own works where they clearly gave an overview of how people went through a plethora of nasty and violent events to avoid an inevitable fate in their native countries. Majority of the people who fled in 2015 made their way to Europe across the Mediterranean, often in overcrowded boats capsizing on the high seas. Soon thereafter, the Balkan Peninsula, became the alternative route to EU, reason being the life-threatening challenges which the aforementioned route included. 

Therefore, this essay will look beyond the scope of SVT, TV4, DN, Expressen, Aftonbladet and various Swedish media. The primary focus will be on Kosovo media and its reporting. Greater insight of the methods used by a country who lacks economic growth compared to Sweden, during the biggest challenges of our time, will be the focal point. This study may also be relevant from a societal perspective, as Kosovo, together with other Balkan countries, became important partners for the EU in dealing with the refugee crisis in 2015. 

This study will increase understanding of how a system developer can solve complex problems within organizations by developing a new information technology system (IT-system), with a focus on technical- and organizational interoperability at the integration process. The authors act as system developers through a case study where there is a need for a new IT-system.

In this thesis an abductive approach is used combined with an instrumental case study. The work is split up into four phases:

(1) Identifying problems within the organization by drawing up business models, collecting data through qualitative semi-structured interviews with stakeholders, and the development of a theoretical base. As theoretical frame of reference Integration and interoperability (I & I) is defined, business models are explained, how technical- and operational interoperability differs, how business models are created, agile software development and usability of IT-systems.

(2) Building, intervention and evaluation. The IT-system is built using an iterative and incremental software development process where focus is on solving the identified problems. During the development stage requirements and challenges are identified to create the business model target view. The IT-system is developed to reflect this view where each iteration of the IT-system is revised from flaws discovered during interviews with stakeholders. The first iteration did not fulfill the stakeholders’ requirements and expectations, but later iterations succeeded in this and were implemented within the organization. When the IT-system had been implemented, it was evaluated by the end users to identify if the system developers had succeeded in solving the organizational problems, and to check usability of the IT-system.

(3) Reflection and learning. The result is analyzed and discussed, compared to the theoretical frame of reference and course of action. The result shows that system developers succeeded in identifying complex problems within the organization and managed to create a new IT-system that met stakeholders’ needs, while also solving identified organizational problems.

(4) In the last phase formalization of learning are general concepts compiled that can be used in other projects. In this thesis are eight aspects and principles are identified that can be used by system developers when developing IT-systems.

The Internet of Things (IoT) is an emerging paradigm focusing on the connection of devices, objects, or “things” to each other, to the Internet, and to users. IoT technology is anticipated to become an essential requirement in the development of smart homes, as it offers convenience and efficiency to home residents so that they can achieve better quality of life. Application of the IoT model to smart homes, by connecting objects to the Internet, poses new security and privacy challenges in terms of the confidentiality, authenticity, and integrity of the data sensed, collected, and exchanged by the IoT objects. These challenges make smart homes extremely vulnerable to different types of security attacks, resulting in IoT-based smart homes being insecure. Therefore, it is necessary to identify the possible security risks to develop a complete picture of the security status of smart homes. This article applies the operationally critical threat, asset, and vulnerability evaluation (OCTAVE) methodology, known as OCTAVE Allegro, to assess the security risks of smart homes. The OCTAVE Allegro method focuses on information assets and considers different information containers such as databases, physical papers, and humans. The key goals of this study are to highlight the various security vulnerabilities of IoT-based smart homes, to present the risks on home inhabitants, and to propose approaches to mitigating the identified risks. The research findings can be used as a foundation for improving the security requirements of IoT-based smart homes.

There is currently a huge amount of data being collected about movements of objects. Such data is called spatiotemporal data and paths left by moving-objects are called trajectories. Recently, researchers have been targeting those trajectories for extracting interesting and useful knowledge by means of pattern analysis and data mining. But, it is difficult to analyse huge datasets of trajectories without summarizing them and visualizing them for the knowledge seeker and for the decision makers. Therefore, this research paper focuses on utilizing visual techniques and data mining analysis of trajectory patterns in order to help extract patterns and knowledge in an interactive approach. The research study proposes a research framework which integrates multiple data analysis and visualization techniques in a coherent architecture in support of interactive trajectory pattern visualization for the decision makers. An application case-study of the techniques is conducted on an airport's baggage movement data within the Baggage Handling System (BHS). The results indicate the feasibility of the approach and its methods in visually analysing trajectory patterns in an interactive approach which can support the decision maker. © 2014 Springer International Publishing Switzerland.

Syftet med avhandling är att på ett övergripande plan studera modernismens förändringspotentialer utifrån ett familjeperspektiv. På den teoretiska nivån är syftet att studera familjen som en mediepedagogisk kontext utifrån ett senmodernistiskt förändringsperspektiv. På en mer specifik nivå studeras familjen empiriskt som en domän för medierade relationer och medierad kommunikation beträffande familjens inre dynamik, samt familjens egen konstruktion av sin representation i förhållande till andra aktörer i samhället via hemsidor på internet. Det finns även ett metodologiskt syfte inbyggt i studien genom ett försök att utveckla ett synsätt som tillåter att se internet som ett epistemologiskt fält - en sorts social offentlighet där även privatheten blir synlig och där relationerna konstrueras och reproduceras. Detta sker utifrån en ansats som tar fasta på kritisk metodologi för att på ett reflekterande sätt kunna fånga den vetenskapliga validiteten utan att kompromissa på att se det oväntade i förändringsprocesserna. Avhandlingens första forskningsfråga kretsar kring familjen och internet. Den handlar om hur ungdomar använder internet hemma och om hur väl deras föräldrar är insatta i detta, t ex hur kunskapsauktoriteten respektive relationsauktoriteten ser ut i hemmen. Frågan ställdes år 2000 till cirka hundra svarspersoner och utifrån denna empiriska explorativa undersökning fortsatte forskningsprocessen mot den andra forskningsfrågan, som i sin tur handlade om hur familjer presenterar och representerar sig själva via "familjesidor" på internet, och om det var möjligt att se "olika typer" av familjer utifrån deras självkonstruerade webbsidor. Genom en webbsidestudie söker man sedan svaret på om det är möjligt att upptäcka hur singelfamiljer, kärnfamiljer och familjer med avlidna barn, s k änglafamiljer, konstruerade sina representationer på nätet samt hur innehållet med speciell inriktning på internet, och i belysningen av begrepp som auktoritet, relation och tradition skilde sig på dessa sidor beroende på vilken "kategori av familj" det handlade om. Den här delen av licentiat thesis består av en diskursstudie, där främst Foucaults begrepp används. Dessa empiriska forskningsfrågor tillsammans med den teoretiska basen försöker att hjälpa oss att förstå en del av modernismens förändringsprocesser. En slutsats är att familjer har blivit reflexiva processer och bör studeras som sådana, medan internet och de nya medierna skapar ett relationsteknologiskt landskap som jag benämner i denna studie "den sociala offentligheten" för att betona skillnaden till Habermas "borgerlig offentlighet" eller den senare synlighetsbaserade offentligheten. De metodologiska funderingarna löper som en röd tråd igenom hela studien och en tredje forskningsfråga handlar således om hur den kritiska samhällsvetenskapliga metodologin kan tillämpas inom mediepedagogik, och då särskilt för internetstudier. Mediepedagogiken är disciplinen som kan hantera mediesamhällets medieinnehåll och medietexter utan att förlora sitt fokus på människor som skapar relationer mellan varandra med hjälp av dessa medier. I denna studie har man lagt tonvikten på familjerna, men kunskaperna kan hjälpa oss även att studera andra sociala fenomen och processer där relationer skapas eller upprätthålls med hjälp av medier och relationsteknologin.

Purpose - The aim of this paper is to investigate corporate financial disclosure via Twitter among the top listed 350 companies in the UK as well as identify the determinants of the extent of social media usage to disclose financial information.

Design/methodology/approach – This study applies an unsupervised machine learning technique, namely, Latent Dirichlet Allocation (LDA) topic modeling to identify financial disclosure tweets. Panel, Logistic, and Generalized Linear Model Regressions are also run to identify the determinants of financial disclosure on Twitter focusing mainly on board characteristics.

Findings – Topic modeling results reveal that companies mainly tweet about 12 topics, including financial disclosure, which has a probability of occurrence of about 7 percent. Several board characteristics are found to be associated with the extent of Twitter usage as a financial disclosure platform, among which are board independence, gender diversity, and board tenure.

Originality/value – Extensive literature examines disclosure via traditional media and its determinants, yet this paper extends the literature by investigating the relatively new disclosure channel of social media. This study is among the first to utilize machine learning, instead of manual coding techniques, to automatically unveil the tweets’ topics and reveal financial disclosure tweets. It is also among the first to investigate the relationships between several board characteristics and financial disclosure on Twitter; providing a distinction between the roles of executive versus non-executive directors relating to disclosure decisions.

Ongoing advancements in technology have changed dramatically the disclosure media that companies adopt. Such disclosure media have evolved from the traditional paper-based ones, to the internet as the new platform to disclose information via companies’ designated websites. However, currently the new media for disclosures are the social media. The aim of this paper is to investigate corporate social media accounts for financial disclosure, as well as, identify its determinants. The sample of the study is comprised of the tweets posted on the Twitter accounts belonging to the FTSE 350 constituents. Topic modeling is applied to identify financial disclosure tweets and logistic regression is run to identify the determinants of financial disclosure on Twitter. Results show that companies use Twitter to make corporate disclosures and some board characteristics are found to have a significant relationship with financial disclosure.

Ongoing advancements in technology have changed dramatically the disclosure media that companies adopt. Such disclosure media have evolved from the traditional paper-based ones, to the internet as the new platform to disclose information via companies’ designated websites. However, currently the new media for disclosures are the social media. The aim of this paper is to investigate corporate social media accounts for financial disclosure, as well as, identify its determinants. The sample of the study is comprised of the tweets posted on the Twitter accounts belonging to the FTSE 350 constituents. Topic modeling is applied to identify financial disclosure tweets and logistic regression is run to identify the determinants of financial disclosure on Twitter. Results show that companies use Twitter to make corporate disclosures and some board characteristics are found to have a significant relationship with financial disclosure. 

Gruvindustrin befinner sig i en stor förändring allt eftersom digitaliseringen fortskrider. Digitaliseringen innebär att en mängd nya tekniker börjar implementeras i gruvor runt om i världen. En av dessa tekniker är att de anställda använder smartphones i arbetet. Detta medför dock problem då miljön inom gruvindustrin inte är optimal för de generella designprinciperna som finns att tillgå idag. Denna studie undersöker och utvecklar därför designprinciper som kan användas för mobila applikationer inom gruvindustrin. Studien har teori som behandlar generella designprinciper för mobila applikationer, mobila designmönster samt industri 4.0. Vidare har en kvalitativ studie genomförts i form av intervjuer med respondenter från både gruvindustrin men också personer med mångårig erfarenhet av utveckling av mobila applikationer till gruvindustrin. Kvalitativa studien genomfördes för att öka förståelsen kring kontexten som infinner sig inom gruvindustrin men också använda den expertis som finns inom området för att kunna utveckla relevanta designprinciper som kan vara till användning i praktiken. Den insamlade empirin jämfördes sedan mot teori och med hjälp av studiens analys kunde designprinciper som kan anses vara specifika för gruvindustrin identifieras. Slutsatserna visar att enkelhet är nyckeln till framgång och element såsom automatisk ifyllnad, enkel och snabb navigering, stora ikoner och användning av färger är några av de möjliga lösningar som föreslagits för att ta fram en användarvänlig applikation.   

Commercial organizations are experiencing a growing need to access business-criticaldata in the longer term of their operations. Governmental regulations as well as commercial interestsinfluence this need. Organizations are willing to procure cost-effective services to this end - servicesthat are increasingly based as public or private cloud solutions. With the advent of autonomous cloudservices comes the possibility to assemble (mix and match) preservation services in a workflowbasedservice-oriented solution. Following the interaction with information managers in (three)commercial organizations operating in different markets and after a review of current literature, wehave revealed a lack of comprehensive guidelines and decision support in service selection as part ofpreservation planning. Existing models and frameworks used for assessing the quality of preservationservices either manage performance-based features that service provider’s offer or the technicaldetails of the preservation actions themselves. In this paper we present our preservation-planningframework (Preserv-Qual) that addresses the need for decision support in the selection ofpreservation services that explicitly acknowledge the differences among aspects of information usewithin an organization. We describe the outcome from an evaluation of the framework in threecommercial organisations as a service quality assessment and decision support tool. This papershows how our framework supports the use of existing and proven methods, models and principlesfor service assessment, digital preservation and decision support.

Websites constitute one category of official records and as such should be preserved for the long term in compliance with Swedish legislation. Collaborative Archiving Services Testbed (CAST) supports actors involved in the selective web archiving process, from harvesting to the creation of an information package ready for transfer to a long-term archive at National Archives of Sweden. CAST is developed in compliance with the ISO standards Open Archival Information System (OAIS) and Producer-Archive Interface Methodology Abstract Standard (PAIMAS), and do also consider other well-known and established standards and recommendations in digital preservation area. CAST promotes cooperation, knowledge acquisition and sharing among users in an experimental step-by-step workflow, encouraging a proactive approach resulting in authority websites better adapted to digital preservation recommendations. CAST is developed at LDP Centre, a national competence centre in Sweden, within the digital preservation area.

Det är i dagsläget känt att det finns en stor andel IT-projekt som misslyckas eller är utmanade. För små företag så är det viktigt att gå med ekonomisk vinst, men trots att det finns tidigare forskning på de kritiska framgångsfaktorerna som leder till framgång så är det fortfarande en utmaning att bedriva IT-projekt i allmänhet. Inriktningen i denna studie är att undersöka och skapa en förståelse för vilka framgångsfaktorer som är kritiska för olika projektkaraktärer och projektgenomföranden, samt om det finns fördelar eller nackdelar med dessa.

Slutsatsen är att projektteamet, kommunikation, hantering av förändringar och ledning är framgångsfaktorer som är viktiga i de flesta projektgenomföranden och projektkaraktärer, där hantering av förändringar är viktigare för de små företagen jämfört med förekomsten i litteraturen.

Fördelarna med olika projektkaraktärer handlar både om att kunna hantera de centrala framgångsfaktorer som förekommer, men även att prioritera de projekt som ger vinst och stabilitet under en god ledning. Det är fördelaktigt för små företag att välja större projekt där till exempel kunden har ansvar för ledning och resurshantering och leverantören bara har ansvar för sin enskilda resurs. Genom medvetenhet om de centrala framgångsfaktorer som kännetecknar en specifik projektkaraktär så kan man använda detta i en riskanalys tidigt i projektet, vilket innebär att man kan förutse hur man ska hantera de utmaningar som kan uppstå. Det är även fördelaktigt att tidigt i projektet veta var ansvaret ligger om projektet blir utmanat, samt vad konsekvenserna blir för leverantören och eventuell kund och slutanvändare.

Based on the current situation in the media and the fact that newspapers have cut down on journalists over the last ten to fifteen years, especially those located in small, remote areas, the main purpose of this thesis was to study how all the remaining local editors in rural Västerbotten think of their role and what their driving forces are as well as what challenges and opportunities they face in their everyday work life.

Qualitative interviews were conducted with all the seven local editors who currently work in rural Västerbotten and then analyzed through theories of local journalism and democracy, a media landscape in constant change, journalistic profession and identity.

The results showed that their role is complex and has plenty of contradictions. Their driving forces and ambitions conflict with their work situation. While they are driven by high democratic standards in their work, they feel that they don’t have enough time for investigative journalism as a lot of their time goes to reporting from at least two municipalities each. They also express that the one municipality where they don’t live doesn’t get as much coverage as they would like and is somewhat forgotten.

A lot of them are well known in the place where they live and work and some people feel a close connection to the newspaper because of them. Many of them also have difficulties stepping out of their role in their spare time. At the same time, they express that they don’t have the same contact with readers like they used to. They are close but at the same time distanced from their readers.

Many organisations experience the new general data protection regulation (GDPR) as difficult to understand and are unsure as to how they should formulate and communicate a policy that is complied by the organisation's employees. ePrivacy is a separate regulation that works as a compliment to GDPR and makes the regulation even more complex. The purpose of this study is to identify recommendations to formulate policies that increases likelihood that the policy is complied by the organisation's employees. The study was conducted as a case study with a participating company. In this study a policy has been developed within the context of the GDPR and ePrivacythat was then used in interviews with employees of the participating company. This was done in order to research the policy development process and handling of policies in that company. With this research, the knowledge of factors within policy development that affect the employees likelihood to comply with and be aware of the organisation's policies will increase. The recommendations that are formulated as a result of the study may be usedby developers to increase the likelihood that the organisation's policies are complied with and that the employees are more aware of the policies. The recommendations of the study is that developers should take advantage of user involvement in the policy development process. This gives the employees their chance to affect their own work and their processes themselves which will increase their self efficacy and awareness of policies.

Author: Raffael Antonio

Title: The politics are a joke - a qualitative interview analysis about the view of media consuments on memes and Greta Thunberg.

The purpose of this study is to look closely at the media consumers and their views on political memes and how other consumers and producers on social media are producing Greta Thunberg as a political figure by the help of memes. 

The analysis has been done by qualitative semi-structured interviews with people as regular social media consumers. This was made by an interview guide with semi-structured questions about political memes, politics on social media and how Greta Thunberg is produced by meme creators according to the consumers. 

The results have shown that there are two groups when it comes to Greta Thunberg on social media; the ones who are disliking her and the ones who stand up for her. These groups are based on opinions, political views and different generations which are also seen among the meme creators and what type of memes they made. Those who are disliking Thunberg, do it for different main reasons, such as age, origin of family and political beliefs. 

Memes also matter in this study because of its format in picture and text, which give consumers an idea of the meme creator and its beliefs. Results also show that the behaviour of memes reflect society on different levels, political beliefs as an primary example.

QUEENS (Dynamic Quality User Experience ENabling Mobile Multimedia Services) aims at exploiting and leveraging on the benefits and flexibility provided by a novel dynamic real-time QoE provisioning framework in order to assess and establish a new era of user-centric mobile multimedia applications. To achieve that, QUEENS utilizes and builds on the TEFIS infrastructure (EC ICT FIRE initiative) that provides a unique integrated platform for supporting efficient Future Internet service experiment and development involving different actors and heterogeneous testbeds. The TEFIS tools and facilities for designing, planning and executing QUEENS experiment, along with a QoE-aware mobile multimedia application prototype will be demonstrated, forming the trends of future internet services and experimental procedures

I vår forskning om hästböcker har vi kommit att intressera oss också för hästboksläsarna. I syfte att få kunskap om varför människor läser hästböcker har vi intervjuat cirka 60 unga och vuxna. Ett delresultat utifrån intervjuer med flickor 9-12 och i vissa fall deras (ibland hästintresserade) föräldrar presenteras. Där framkommer att flickorna i många fall är bokslukare, om än tämligen genretrogna. Ett tydligt samband mellan identiteten som hästtjej och läsare framträder, då läsningen ofta har spin-off-effekter på lekmönster. Orsakerna bakom hästboksläsningen handlar om identifikation i termer av ett flickskap som i stallkulturen står utanför normen och som präglas av mod och beslutsamhet, men där även spänning och kunskapsinhämtning nämns. Hästbokens status har höjts i både skolan och på bibliotek, där den tidigare har haft dåligt rykte, något som kan ses som att större uppmärksamhet ägnas åt något som intresserar många flickor.

The International Journal of Computer and Telecommunications Networking (COMNET)

Vol. 3, No. 4

The Journal of the Pattern Recognition Society