Maximizing Influence (IM) in social networks has a considerable role to play in the phenomenon of viral marketing, targeted advertisements and in promoting any campaigns. However, the Influence Maximization Problem is a very challenging research-problem due to it being NP-Hard and scaling with the social networks with millions of nodes and edges becomes very tough due to the computational complexities concerned with it. Recently, solving this problem through the use of community detection based methodology is becoming very popular since, it reduces the search space by dividing the network into smaller and more manageable groups called "communities." As part of the larger research work, we reiterate a framework which has been inspired by collection of different work done by Alfalahi et al. (2013) that we can implement to solve the IM problem and its limitation through community detection and fuzzy logic inspired approach. Since the work is still under development, for this project, we report on understanding the IM field through literature reviews and in communicating a design of IM framework as inspired by the previous works. We also present our version ofthe blueprint (Algorithm design) of the framework as a five step approach. For the purpose of this report, we implement and evaluated the step 1 and step 2 of the framework. Step 1 is about preprocessing the input network with a similarity measure, which according to previous study by Alfalahi et al. (2013a) aids the algorithms in detecting better community structure (clear and accurate distinction of the nodes into communities in networks). We test it to see if it holds true. Step 2 is about implementing the community detection in social network. We benchmarkthree candidate algorithms, chosen based on theirperformance, from the previous studies in community detection fieldand we report onwhich algorithm should we consider to use in the proposed framework through experimentationon the simulated data. We use Normalized Mutual Information (NMI) and Modularity (Q) as evaluation metrics to measure the accuracy of the community detected by the candidate algorithms. Our results show that similarity based preprocessing does not improve the community structure and thus may not be required in the framework. We also found out that Louvain should be the algorithm that use to detect communities in social networks since it outperforms both CNM and Infomap on Q and NMI

With an increasing demand of mobile data traffic, and a growing assumption of continuous Internet connectivity, it is important to investigate the characteristics of mobile cellular networks. The consequence of insufficient capacity will grow as the cloud and other Internet demanding services, not only makes us dependent, but becomes a way of living. The present study aims to identify areas without mobile network coverage in Värmland County in central Sweden. An additional aim is to find statistical relationships between network performance metrics such as throughput, signal strength and latency. With data collected during an eight month period, network characteristics have been investigated for the three Swedish mobile operators, Tre, Telia and Telenor. The performed data analysis show multiple regions where at least one operator is unable to provide sufficient performance and regions strongly overrepresented by a specific operator. Provided analysis also show a correlation between signal strength and key performance metrics, such as throughput and network delay.

As major companies like Spotify, Deezer and Tidal look to improve their music streamingproducts, they repeatedly opt for features that engage with users and lead to a morepersonalised user experience. Automatic playlist continuation enables these platforms tosupport their users with a seamless and smooth interface to enjoy music, own their experience,and discover new songs and artists.This report details a recommender system that enables automatic playlist continuation;providing the recommendation of music tracks to users who are creating new playlists or curatingexisting ones. The recommendation framework given in this report is able to provide accurateand pertinent track recommendation, but also addresses issues of scalability, practicalimplementation and decision transparency, so that commercial enterprises can deploy such asystem more easily and develop a winning strategy for their user experience. Furthermore, therecommender system does not require any rich and varied supply of user data, instead requiringonly basic information as input such as the title of the playlist, the tracks currently in the playlist,and the artists associated with those tracks.To accomplish these goals, the system relies on user-based collaborative filtering; a simple, wellestablishedmethod of recommendation, supported by web-scraping and topic modellingalgorithms that creatively use the supplied data to paint a more holistic image of what kind ofplaylist the user would like. This system was developed using data from the Million PlaylistDataset, released by Spotify in 2018 as part of the Recommender Systems Challenge, evaluatedusing R-precision, normalised discounted cumulative gain, and a proprietary evaluation metriccalled Recommended Song Clicks, that reflects the number of times a user would have to refreshthe list of recommendations provided if the current Spotify user interface was used tocommunicate them. Over an 80:20 train-test split, the scores were: 0.343, 0.224, and 15.73.

No description available.

This thesis uses Chrome Timeline tool, Firefox Canvas Debugger and an FPS module to evaluate performance issues in a motion-based web game built with the framework Phaser. For each issue an explanation of how it is found and a proposed solution is given. The game that is the basis of this work, gains input through a WebGL-based camera module that uses shaders to interpret the data. Some solutions might be specific for this particular project and some may be more generally applicable. A few pointers are given to what can be graphically demanding when developing in JavaScript. The game has different themes and features that are further developed which is done from a performance point of view, there are in total eight different improvements that are discussed. The used tools and metrics are further evaluated e.g. the Timeline tool is considered a useful tool for web developers though it has some drawbacks related to WebGL.

Spotify started to use the cloud-based data warehouse BigQuery in 2016 with a business model of pay-as-you-go. Since then, usage has increased rapidly in volume and amount of users across the organisation which is a result of ease of use compared to previous data warehouse solutions. The technology procurement team lacks an overview of how BigQuery is used across Spotify and a strategy of how to maintain an environment where users make cost informed decisions when designing queries and creating tables. Incidents resulting in unexpected high bills are currently handled by a capacity analyst using billing data which is lacking the granularity of how cost maps to the users of BigQuery. The objective of this research is to provide recommendations on how audit data can enable a data driven cost-effective environment for BigQuery across the matrix formed engineering organisation at Spotify. First an overview of the current usage patterns is presented based on audit data which is modeled with regards to volume, complexity and utilization. Different patterns are identified using K-means clustering, including high-volume consuming squads and underutilized tables. Secondly, recommendations on transparency of audit data for cost-effectiveness are based on insights from cluster analysis, interviews and characteristics of organisation structure. Recommendations include transparency of data consumption to producers to prevent paying for unused resources and transparency to consumers on usage patterns to avoid paying for unexpected bills. Usage growth is recommended to be presented to the technology procurement squad which enables better understanding and mitigates challenges on cost forecasting and control.

Tekniken för att kunna skriva ut 3D-objekt har funnits i många år men först på 2010-talet har 3D-skrivare blivit tillgängliga även för vanliga konsumenter. Det finns dock ett problem: för att kunna använda en 3D-skrivare måste man antingen kunna CAD-mjukvara eller förlita sig på andra människors 3D-modeller. Genom att använda ett system för 3Dkopiering kan ett verkligt objekt istället kopieras. Rapporten behandlar ett kandidatprojekt som genomfördes av sju studenter på datavetenskapliga civilingenjörsutbildningarpå Linköpings universitet 2017. Målet med projektet var att utveckla ett system som kan ta separata punktmoln som indata för att sedan registrera dessa till ett komplett punktmoln. Utifrån detta kompletta punktmoln genereras sedan en 3D-mesh som kan skrivas ut av en 3D-skrivare. Tidigt i projektet var målet att vidareutveckla ett befintligt system. Detta mål om förhandlades med kunden efter att ett flertal fel identifierats med det befintliga systemet. Projektet resulterade i 3DCopy, ett mjukvarusystem som registrerar punktmoln och utifrån dessa genererar en 3D-mesh. / The technology to be able to print 3D objects has been available for many years, but it is only recently that 3D printers have been made available for regular consumers. There is one issue though: to be able to use the 3D printer either knowledge of CAD software or 3D models made by others are needed. By using a system for 3D copying a real object can instead be copied. This report presents a bachelor project that was done by seven students studying engineering programs in computer science or software technology at Linköping University, 2017. The goal of the project was to develop a system that could take several point clouds as input and then register them to a complete point cloud. Then use this point cloud to generate a 3D mesh to be printed on a 3D printer. The 3D printer will then be able to print the object. In the early stages of the project the main focus was to develop an already existing system. This goal was then renegotiated since the existing system contained several errors. The project resulted in 3DCopy, a software system that registers point clouds and from these point clouds generates a 3D mesh.

Trots att användarmedverkan är allmänt erkänd som en kritisk framgångsfaktor vid ERP-implementeringar ger litteraturen en begränsad insyn i huranvändarmedverkan kan samordnas och stödjas inom ERP-implementeringar.Användarmedverkan innebär att användarna är delaktiga vid aktiviteter somframtagning av kravspecifikation, testning av ERP-system och utbildning under ettimplementeringsprojekt. Om fel tillvägagångssätt används vid ERPimplementeringarkan det leda till att användarna uppmanas till att medverka meninte får möjlighet att påverka ett ERP-system. Anledningen till att användare intealltid får medverka kan bero på brist på tid samt resurser. Ifall användarna fårmöjlighet att påverka ökar både acceptans, engagemang och användningsnivån avERP-systemet. Användare måste förstå varför ett ERP-system implementeras ochvilka möjligheter som medföljer eftersom det är användarna som slutligen arbetar idet. Syftet med studien är att bidra med kunskap kring hur användarmedverkan kangenomföras vid ERP-implementeringar och vilken påverkan användarna kan ha påERP-system. För att undersöka hur användare kan medverka vid ERPimplementeringarställdes frågan: “Hur kan användarmedverkan genomföras vid ERP-implementeringar?”Frågeställningen har studerats genom en kvalitativ intervjustudie. Respondenterna istudien kommer från olika företag där de har implementerat ett ERP-system underde senaste fem till åtta åren. Sammanlagt har sju intervjuer genomförts på fem olikaföretag. Resultatet mynnar ut i en beskrivning av hur en ledning kan samordna förbred involvering av användare samt en beskrivning av aktiviteter som användare kanmedverka i vid ERP-implementeringar för att möjliggöra användares engagemangoch påverkan på ERP-systemet. / Despite user participation being widely recognized as a critical success factor in ERP implementations, the literature provides a limited insight into how user participationcan be coordinated and supported in ERP-implementations. User participationimplies that users participate in activities such as preparation of specifications ofrequirements, testing of ERP-systems and training during the implementationproject. If the wrong methods are used in ERP-implementation it can cause the usersto be asked to participate but do not get the opportunity to influence the ERP-system.The reason why users do not always get to participate may be due to lack of time andresources. If users get the opportunity to influence it increases both acceptance,involvement and level of use of the ERP-system. Users must understand why an ERPsystemis implemented and the opportunities that comes with it because it is the userswho ultimately works in the ERP-system. The purpose of the study is to contributeknowledge about how user involvement is performed in ERP-implementations andthe influence that the users can have on ERP-system. In order to research how userscan participate in ERP implementations this studies question is:"How can user participation be performed in ERP implementations?"The issue has been studied by a qualitative interview study. Respondents in the studycome from different companies where they have implemented an ERP-system duringthe past five to eight years. A total of seven interviews were conducted in five differentcompanies. The result leads to a description of how management can coordinatebroad involvement of users and a description of activities that users can participatein ERP implementations to enable user engagement and influence.

No description available.

Sensor networks have diverse structures and generally employ proprietary protocols to gather useful information about the physical world. This diversity generates problems to interact with these sensors since custom APIs are needed which are tedious, error prone and have steep learning curve. In this thesis, I present RESThing, a lightweight REST framework for wireless sensor networks to ease the process of interacting with these sensors by making them accessible over the Web. I evaluate the system and show that it is feasible to support widely used and standard Web protocols in wireless sensor networks. Being able to integrate these tiny devices seamlessly into the global information medium, we can achieve the Web of Things.