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  • 251.
    Kucher, Kostiantyn
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Text Visualization Revisited: The State of the Field in 20192019In: Posters of the 21th EG/VGTC Conference on Visualization (EuroVis '19) / [ed] João M. Pereira and Renata G. Raidou, Eurographics - European Association for Computer Graphics, 2019, p. 29-31Conference paper (Refereed)
    Abstract [en]

    Text and document data visualization is an important research field within information visualization and visual analytics with multiple application domains including digital humanities and social media, for instance. During the past five years, we have been collecting text visualization techniques described in peer-reviewed literature, categorizing them according to a detailed categorization schema, and providing the resulting manually curated collection in an online survey browser. In this poster paper, we present the updated results of analyses of this data set as of spring 2019. Compared to the recent surveys and meta-analyses that mainly focus on particular aspects and problems related to text visualization, our results provide an overview of the current state of the text visualization field and the respective research community in general.

  • 252.
    Kucher, Kostiantyn
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Martins, Rafael Messias
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Analysis of VINCI 2009–2017 Proceedings2018In: Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18), 13-15 August 2018, Växjö, Sweden / [ed] Karsten Klein, Yi-Na Li, and Andreas Kerren, Association for Computing Machinery (ACM), 2018, p. 97-101Conference paper (Refereed)
    Abstract [en]

    Both the metadata and the textual contents of scientific publications can provide us with insights about the development and the current state of the corresponding scientific community. In this short paper, we take a look at the proceedings of VINCI from the previous years and conduct several types of analyses. We summarize the yearly statistics about different types of publications, identify the overall authorship statistics and the most prominent contributors, and analyze the current community structure with a co-authorship network. We also apply topic modeling to identify the most prominent topics discussed in the publications. We hope that the results of our work will provide insights for the visualization community and will also be used as an overview for researchers previously unfamiliar with VINCI.

  • 253.
    Kucher, Kostiantyn
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    Paradis, Carita
    Lund University.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    DoSVis: Document Stance Visualization2018In: Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP '18) / [ed] Alexandru C. Telea, Andreas Kerren, and José Braz, SciTePress, 2018, Vol. 3, p. 168-175Conference paper (Refereed)
    Abstract [en]

    Text visualization techniques often make use of automatic text classification methods. One of such methods is stance analysis, which is concerned with detecting various aspects of the writer’s attitude towards utterances expressed in the text. Existing text visualization approaches for stance classification results are usually adapted to textual data consisting of individual utterances or short messages, and they are often designed for social media or debate monitoring tasks. In this paper, we propose a visualization approach called DoSVis (Document Stance Visualization) that focuses instead on individual text documents of a larger length. DoSVis provides an overview of multiple stance categories detected by our classifier at the utterance level as well as a detailed text view annotated with classification results, thus supporting both distant and close reading tasks. We describe our approach by discussing several application scenarios involving business reports and works of literature. 

  • 254.
    Kucher, Kostiantyn
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    Paradis, Carita
    Lund University.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    The State of the Art in Sentiment Visualization2018In: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 37, no 1, p. 71-96, article id CGF13217Article in journal (Refereed)
    Abstract [en]

    Visualization of sentiments and opinions extracted from or annotated in texts has become a prominent topic of research over the last decade. From basic pie and bar charts used to illustrate customer reviews to extensive visual analytics systems involving novel representations, sentiment visualization techniques have evolved to deal with complex multidimensional data sets, including temporal, relational, and geospatial aspects. This contribution presents a survey of sentiment visualization techniques based on a detailed categorization. We describe the background of sentiment analysis, introduce a categorization for sentiment visualization techniques that includes 7 groups with 35 categories in total, and discuss 132 techniques from peer-reviewed publications together with an interactive web-based survey browser. Finally, we discuss insights and opportunities for further research in sentiment visualization. We expect this survey to be useful for visualization researchers whose interests include sentiment or other aspects of text data as well as researchers and practitioners from other disciplines in search of efficient visualization techniques applicable to their tasks and data. 

  • 255.
    Kucher, Kostiantyn
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Paradis, Carita
    Lund University.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Visual Analysis of Sentiment and Stance in Social Media Texts2018In: EuroVis 2018 - Posters / [ed] Anna Puig and Renata Raidou, Eurographics - European Association for Computer Graphics, 2018, p. 49-51Conference paper (Refereed)
    Abstract [en]

    Despite the growing interest for visualization of sentiments and emotions in textual data, the task of detecting and visualizing various stances is not addressed well by the existing approaches. The challenges associated with this task include development of the underlying computational methods and visualization of the corresponding multi-label stance classification results. In this poster abstract, we describe the ongoing work on a visual analytics platform called StanceVis Prime, which is designed for analysis of sentiment and stance in temporal text data from various social media data sources. Our approach consumes documents from several text stream sources, applies sentiment and stance classification, and provides end users with both an overview of the resulting data series and a detailed view for close reading and examination of the classifiers’ output. The intended use case scenarios for StanceVis Prime include social media monitoring and research in sociolinguistics.

  • 256.
    Kucher, Kostiantyn
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    Paradis, Carita
    Lund University.
    Sahlgren, Magnus
    Swedish Research Institute (RISE SICS).
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    Active Learning and Visual Analytics for Stance Classification with ALVA2017In: ACM Transactions on Interactive Intelligent Systems (TiiS), ISSN 2160-6455, Vol. 7, no 3, article id 14Article in journal (Refereed)
    Abstract [en]

    The automatic detection and classification of stance (e.g., certainty or agreement) in text data using natural language processing and machine learning methods create an opportunity to gain insight into the speakers' attitudes towards their own and other people's utterances. However, identifying stance in text presents many challenges related to training data collection and classifier training. In order to facilitate the entire process of training a stance classifier, we propose a visual analytics approach, called ALVA, for text data annotation and visualization. ALVA's interplay with the stance classifier follows an active learning strategy in order to select suitable candidate utterances for manual annotation. Our approach supports annotation process management and provides the annotators with a clean user interface for labeling utterances with multiple stance categories. ALVA also contains a visualization method to help analysts of the annotation and training process gain a better understanding of the categories used by the annotators. The visualization uses a novel visual representation, called CatCombos, which groups individual annotation items by the combination of stance categories. Additionally, our system makes a visualization of a vector space model available that is itself based on utterances. ALVA is already being used by our domain experts in linguistics and computational linguistics in order to improve the understanding of stance phenomena and to build a stance classifier for applications such as social media monitoring.

  • 257.
    Kucher, Kostiantyn
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Skeppstedt, Maria
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). University of Potsdam, Germany.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Application of Interactive Computer-Assisted Argument Extraction to Opinionated Social Media Texts2018In: Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18) / [ed] Karsten Klein, Yi-Na Li, and Andreas Kerren, Association for Computing Machinery (ACM), 2018, p. 102-103Conference paper (Refereed)
    Abstract [en]

    The analysis of various opinions and arguments in textual data can be facilitated by automatic topic modeling methods; however, the exploration and interpretation of the resulting topics and terms may prove to be difficult to the analysts. Opinions, stances, arguments, topics, terms, and text documents are usually connected with many-to-many relationships for such tasks. Exploratory visual analysis with interactive tools can help the analysts to get an overview of the topics and opinions, identify particularly interesting documents, and describe main themes of various arguments. In our previous work, we introduced an interactive tool called Topics2Themes that was used for topic and theme analysis of vaccination-related discussion texts with a limited set of stance categories. In this poster paper, we describe an application of Topics2Themes to a different genre of data, namely, political comments from Reddit, and multiple sentiment and stance categories detected with automatic classifiers.

  • 258.
    Kurti, Arianit
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Dalipi, Fisnik
    Linnaeus University, Faculty of Technology, Department of Computer Science. Linnaeus University.
    Bridging the Gap between Academia and Industry: Lessons Learned from a Graduate IT Professional Development Program2017In: Abstract Book: 2nd Annual International Conference on Engineering Education & Teaching, 5-8 June 2017, Athens, Greece / [ed] Gregory T. Papanikos, Athens, 2017, p. 27-27Conference paper (Other academic)
    Abstract [en]

    The rapid advances of technologies, constantly brings new demands for new skills and expertise of the professionals in IT industry. There is a constant need for people that have in-depth understanding and know how to develop the new innovative services using these new technologies. In these settings, the real challenge is how to find the right persons with the right education in an industry where the in-thing yesterday may be out-of-date tomorrow? To add to this challenge, universities are still “increasingly stove-piped in highly specialized disciplinary fields” (Hurlburt et al., 2010) as well as there is a lack of flexibility for the professionals to have their competences developed. All this points out the great challenges that universities are facing for alignment between academic development within degree curricula and the requirements that industry demands for their specific needs (Falcone et al. 2014). In this research effort we report our experiences from an ongoing Graduate Professional Development Program where we address these challenges through a co-creation process with IT industry based on open innovation. Through this model we bring together research expertise, academic experience and experts from industry in a collaborative process for developing courses to suit the current needs of IT professionals. As an outcome of this process, the course content is tailor-made, as well as everything else in connection, such as: bite-size modules, adjustable pace, open and online educational resources, as well as a flipped classroom approach to teaching. As a result, we have developed and provided so far five courses that have been very well accepted by the IT professional. Thus, in this paper we aim to provide some insights on approaches for facilitating continuous competence development plans for IT professionals within regular university educational offer. 

  • 259.
    Kühne, Kay
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Interactive Multiscale Visualization of Large, Multi-dimensional Datasets2018Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    This thesis project set out to find and implement a comfortable way to explore vast, multidimensional datasets using interactive multiscale visualizations to combat the ever-growing information overload that the digitized world is generating. Starting at the realization that even for people not working in the fields of information visualization and data science the size of interesting datasets often outgrows the capabilities of standard spreadsheet applications such as Microsoft Excel. This project established requirements for a system to overcome this problem. In this thesis report, we describe existing solutions, related work, and in the end designs and implementation of a working tool for initial data exploration that utilizes novel multiscale visualizations to make complex coherences comprehensible and has proven successful in a practical evaluation with two case studies.

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  • 260.
    Laitinen, Mikko
    et al.
    University of Eastern Finland, Finland.
    Lundberg, Jonas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Levin, Magnus
    Linnaeus University, Faculty of Arts and Humanities, Department of Languages.
    Lakaw, Alexander
    University of Eastern Finland, Finland.
    Revisiting weak ties: Using present-day social media data in variationist studies2017In: Exploring Future Paths for Historical Sociolinguistics / [ed] Tanja Säily, Minna Palander-Collin, Arja Nurmi, Anita Auer, Amsterdam: John Benjamins Publishing Company, 2017, p. 303-325Chapter in book (Refereed)
    Abstract [en]

    This article makes use of big and rich present-day data to revisit the social network model in sociolinguistics. This model predicts that mobile individuals with ties outside a home community and subsequent loose-knit networks tend to promote the diffusion of linguistic innovations. The model has been applied to a range of small ethnographic networks. We use a database of nearly 200,000 informants who send micro-blog messages in Twitter. We operationalize networks using two ratio variables; one of them is a truly weak tie and the other one a slightly stronger one. The results show that there is a straightforward increase of innovative behavior in the truly weak tie network, but the data indicate that innovations also spread under conditions of stronger networks, given that the network size is large enough. On the methodological level, our approach opens up new horizons in using big and often freely available data in sociolinguistics, both past and present.

  • 261.
    Laitinen, Mikko
    et al.
    Linnaeus University, Faculty of Arts and Humanities, Department of Languages. Univ Eastern Finland, Finland.
    Lundberg, Jonas
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    Levin, Magnus
    Linnaeus University, Faculty of Arts and Humanities, Department of Languages.
    Lakaw, Alexander
    Linnaeus University, Faculty of Arts and Humanities, Department of Languages.
    Utilizing Multilingual Language Data in (Nearly) Real Time: The Case of the Nordic Tweet Stream2017In: Journal of universal computer science (Online), ISSN 0948-695X, E-ISSN 0948-6968, Vol. 23, no 11, p. 1038-1056Article in journal (Refereed)
    Abstract [en]

    This paper presents the Nordic Tweet Stream, a cross-disciplinary digital humanities project that downloads Twitter messages from Denmark, Finland, Iceland, Norway and Sweden. The paper first introduces some of the technical aspects in creating a real-time monitor corpus that grows every day, and then two case studies illustrate how the corpus could be used as empirical evidence in studies focusing on the global spread of English. Our approach in the case studies is sociolinguistic, and we are interested in how widespread multilingualism which involves English is in the region, and what happens to ongoing grammatical change in digital environments. The results are based on 6.6 million tweets collected during the first four months of data streaming. They show that English was the most frequently used language, accounting for almost a third. This indicates that Nordic Twitter users choose English as a means of reaching wider audiences. The preference for English is the strongest in Denmark and the weakest in Finland. Tweeting mostly occurs late in the evening, and high-profile media events such as the Eurovision Song Contest produce considerable peaks in Twitter activity. The prevalent use of informal features such as univerbated verb forms (e.g., gotta for (HAVE) got to) supports previous findings of the speech-like nature of written Twitter data, but the results indicate that tweeters are pushing the limits even further.

  • 262. Laitinen, Mikko
    et al.
    Lundberg, Jonas
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Levin, Magnus
    Linnaeus University, Faculty of Arts and Humanities, Department of Languages.
    Martins, Rafael Messias
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    The Nordic Tweet Stream: A Dynamic Real-Time Monitor Corpus of Big and Rich Language Data2018In: DHN 2018 Digital Humanities in the Nordic Countries 3rd Conference: Proceedings of the Digital Humanities in the Nordic Countries 3rd Conference Helsinki, Finland, March 7-9, 2018 / [ed] Eetu Mäkelä, Mikko Tolonen, Jouni Tuominen, CEUR-WS.org , 2018, p. 349-362Conference paper (Refereed)
    Abstract [en]

    This article presents the Nordic Tweet Stream (NTS), a cross-disciplinarycorpus project of computer scientists and a group of sociolinguists interestedin language variability and in the global spread of English. Our research integratestwo types of empirical data: We not only rely on traditional structured corpusdata but also use unstructured data sources that are often big and rich inmetadata, such as Twitter streams. The NTS downloads tweets and associatedmetadata from Denmark, Finland, Iceland, Norway and Sweden. We first introducesome technical aspects in creating a dynamic real-time monitor corpus, andthe following case study illustrates how the corpus could be used as empiricalevidence in sociolinguistic studies focusing on the global spread of English tomultilingual settings. The results show that English is the most frequently usedlanguage, accounting for almost a third. These results can be used to assess howwidespread English use is in the Nordic region and offer a big data perspectivethat complement previous small-scale studies. The future objectives include annotatingthe material, making it available for the scholarly community, and expandingthe geographic scope of the data stream outside Nordic region.

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  • 263.
    Lamberg-Liszkay, János
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Lisauskas, Tadas
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    An alternative roaming model inLoRaWAN2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    LoRaWAN is an open networking technology designed for IoT devices that al-lows wireless data transmission over longer ranges than some other wireless tech-nologies, like Wi-Fi or Bluetooth, for devices that are constrained in terms of size,price, and available power. The current design of roaming among networks in LoRaWANis heavily inspired by that of mobile networks, as the use of roaming agreementsis mandated. Roaming agreements create unnecessary administrative overhead thathinders deployments. A roaming model that is quicker and simpler to deploy couldsave money for current users, and could even attract new users to the technology.To circumvent the necessity of roaming agreements, a new, scalable and agreement-less roaming model should be proposed. In this thesis project a literature survey isconducted, investigating similar technologies to find hints or inspiration for a newroaming model. It is found that the broker software architecture pattern put in thecontext of roaming in LoRaWAN suits the requirements quite well, so the new roam-ing model has been developed based on that. A software simulation has been imple-mented to gather data regarding the scalability of the model. It has been found thatthe proposed model is both scalable, and agreement-less.

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    An alternative roaming model inLoRaWAN
  • 264.
    Landmér Pedersen, Jesper
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Weighing Machine Learning Algorithms for Accounting RWISs Characteristics in METRo: A comparison of Random Forest, Deep Learning & kNN2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    The numerical model to forecast road conditions, Model of the Environment and Temperature of Roads (METRo), laid the foundation of solving the energy balance and calculating the temperature evolution of roads. METRo does this by providing a numerical modelling system making use of Road Weather Information Stations (RWIS) and meteorological projections. While METRo accommodates tools for correcting errors at each station, such as regional differences or microclimates, this thesis proposes machine learning as a supplement to the METRo prognostications for accounting station characteristics. Controlled experiments were conducted by comparing four regression algorithms, that is, recurrent and dense neural network, random forest and k-nearest neighbour, to predict the squared deviation of METRo forecasted road surface temperatures. The results presented reveal that the models utilising the random forest algorithm yielded the most reliable predictions of METRo deviations. However, the study also presents the promise of neural networks and the ability and possible advantage of seasonal adjustments that the networks could offer.

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  • 265.
    Larsson, David
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Tearing down the walls hindering colorblind developers: Assistance tool for colorblind developers2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Out in the world, there are over a million colorblind developers and a lot more that are aspiring developers. Amongst them are colorblind developers that are hindered by their color blindness. Hindered in such ways as they do not have the confidence to design an application, due to them not being able to interpret colors in a similar way as other developers. There is also a fear of “can I be colorblind and be a programmer/web designer?”. With these walls stopping potential developers from advancing or doing certain things, we could lose out on some great developers for the future. In order to tackle this, I am creating a tool for colorblind developers to generate color schemes and mock color schemes in applications. As well as giving them a tool to look up RGB/HEX-values and receive the name of the color matching.

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  • 266.
    Larsson, Robin
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    ROP for fun and profit2020Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [sv]

    Minneskorruptionsfel, till exempel stackbaserade överskridningssårbarheter imjukvara, har sedan 1990-talet uppmärksammats som ett kroniskt IT-säkerhetsproblem och kostar samhället mycket pengar och stora resurser.Uppsatsenundersökergenomkontrolleradeexperimentomexploateringsmetoden Return Oriented Programming kan användas för attutnyttja minneskorruptionsfel av typen stackbaserad buffertöverskridning påoperativsystemet Ubuntu Linux 18.04.3 64-bit. Experimenten påvisar attReturn Oriented Programming kan användas för att exploatera stackbaseradebufferöverskridningssårbarheter och att de skyddsmekanismer som finnsimplementerade i målsystemet är forcerbara. Det innebär att än idag finnsingen slutgiltig lösning implementerad för att stoppa exploatering avminneskorruptionsfel av denna typ.

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    ROP for fun and profit
  • 267.
    Lee, Songho
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Current practices for DNS Privacy: Protection towards pervasive surveillance2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Current usage of the DNS system is a significant loophole of Internet users' privacy, as all queries and answers for resolving web address are not protected in most cases. The report elaborates which Internet users' privacy interests exist, and presents the current technologies to enhance DNS Privacy through a systematic literature review. The report also explores the limitations of the current practices and presents several proposals such as DNS-over-Tor and methods to change the trusted recursive resolver to mitigate current limitations periodically.

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  • 268.
    Leifsdóttir, Petra Íris
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Programmering med BBC micro:bit i grundskolan: En studie som syftar till att underlätta programmeringsundervisningen för högstadielärare2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    As of 2018 the Swedish Government has decided that there should be programming in elementary school. The programming should take place in the subjects of mathematics and technics There weren’t a lot of prepared teachers when the law took effect which has made it difficult for the teachers to follow it.

    In this project I have made a prototype to try to increase the competence in programming for the teachers. Since there is another project in Kronobergs län, Make it happen, that focuses on the use of BBC micro:bit in school I chose to make the prototype for BBC micro:bit and microPython programming to keep in line with that project.

    The results indicate that a cloud-based tool that contains both an editor and a Swedish documentation might ease the teaching in elementary schools. For more reliable results however I would need to keep developing the prototype to give it more functionalities and a better documentation that contains more information about microPython. There is also need for more user-testing on the targeted group to make the instrument more reliable.

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  • 269.
    Lennartsson, Alexander
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Melander, Hilda
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Comparison of systems to detect rogue access points2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    A hacker might use a rogue access point to gain access to a network, this poses athreat to the individuals connected to it. The hacker might have the potential to leakcorporate data or steal private information. The detection of rogue access points istherefore of importance to prevent any damage to both businesses and individuals.Comparing different software that detects rogue access points increases the chanceof someone finding a solution that suits their network. The different type of softwarethat are compared are intrusion detection systems, wireless scanners and a Ciscowireless lan controller. The parameters that are being compared are; cost, compat-ibility, detection capability and implementation difficulty. In order to obtain resultssome of the parameters require testing. As there are three types of software, threeexperiment environments should be conducted. Our research indicates that alreadyexisting network equipment or the size of the network affects the results from theexperiments.

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    Comparison of systems to detect rogue access points
  • 270.
    Li, Jian-De
    et al.
    Natl Chung Hsing Univ, Taiwan.
    Kuo, Chun-Hao
    Natl Chiao Tung Univ, Taiwan.
    Lu, Guan-Ruei
    Natl Chiao Tung Univ, Taiwan.
    Wang, Sying-Jyan
    Natl Chung Hsing Univ, Taiwan.
    Li, Katherine Shu-Min
    Natl Sun Yat Sen Univ, Taiwan.
    Ho, Tsung-Yi
    Natl Tsing Hua Univ, Taiwan.
    Chen, Hung-Ming
    Natl Chiao Tung Univ, Taiwan.
    Hu, Shiyan
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Co-placement optimization in sensor-reusable cyber-physical digital microfluidic biochips2019In: Microelectronics Journal, ISSN 0959-8324, Vol. 83, p. 185-196Article in journal (Refereed)
    Abstract [en]

    Digital microfluidic biochips (DMFBs) facilitate modern healthcare applications. One of the most important applications is point-of-care (POC) clinical diagnosis which is directly related to human health. However, biochemical experiments are usually error-prone, which makes monitoring intermediate results during bioassay execution be required to ensure the correctness of POC clinical diagnosis. To tackle this problem, cyber-physical digital microfluidic biochips with integrated sensors have been proposed and have attracted attention recently. In order to fully utilize the sensors for detection, the reusability of sensors should be taken into consideration during the module placement stage of cyber-physical DMFBs synthesis flow. Moreover, excessive actuation of electrodes may cause reliability degradation and this issuse should also be taken care of during module placement stage. In order to deal with the aforementioned problems, this paper presents the first co-optimization method for both module and sensor placement. Experimental results show that the proposed method can effectively minimize bioassay completion time while meeting all constraints from sensors and electrodes.

  • 271.
    Lincke, Alisa
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    A Computational Approach for Modelling Context across Different Application Domains2020Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

     Nowadays, people use a wide range of devices (e.g., mobile phones, smart watches, tablets, activity bands, laptops) to access different digital applications and services. The ubiquitous distribution of these devices allows them to be used across different settings, in different situations, and in a large number of different domains. These devices contain a variety of hardware features (e.g., sensors, Internet connectivity, camera, low energy Bluetooth connectivity) that allow for gathering diverse data types that can be used in many application domains. Among other areas, they could be utilized in mobile learning situations (e.g., for data collection in science education, field trips), to support mobile health (e.g., for health data collection, monitoring the health states of patients, monitoring for changes in health conditions and/or detection of emergency situations), and to provide personalised recommendations (e.g., for recommending services based on the user’s location and time). These devices help to capture the current contextual situation of the user, which could make applications more personalised in order to generate novel services and to deliver a better user experience. However, most applications lack capturing the user’s context situation or have been often limited to the user’s current location and time. Therefore, new ways of conceptualising and processing contextual information are necessary in order to support the development of personalised and contextualised applications and services. Substantial research in the field of contextualisation has explored aspects related to computational modelling of context focusing on just one specific application domain. Most of the existing context models do not address the issue of generalization as being a core feature of the model. Thus, the model is to a particular application domain or scenario. The main goal of this thesis is to conceptualise, design and validate an approach for a unified context model and to investigate its applicability in different application domains. This thesis presents the state of the art of recent approaches used for context modelling and it introduces a rich context model as an approach for modelling context in a domain-independent way. Reusability and flexibility of the proposed rich context model are illustrated by showing several applications domains (e.g., mobile learning, recommender systems, data analytics, eHealth) in which the model has been tested. This work explains the promising potential of using rich context models to support the personalization of services that are tied to the user’s current context. The results and outcomes of this work pave the way for new opportunities and further research related to the integration and combination of the proposed rich context model with machine learning techniques.

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  • 272.
    Lincke, Alisa
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Fellman, Daniel
    Umeå University, Sweden.
    Jansen, Marc
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). Umeå University, Sweden.
    Milrad, Marcelo
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Berge, Elias
    Hypocampus AB, Sweden.
    Jonsson, Bert
    Umeå University, Sweden.
    Correlating Working Memory Capacity with Learners´ Study Behavior in a Web-Based Learning Platform2019In: Proceedings of the  27th International Conference on Computers in Education Conference Proceedings, Asia-Pacific Society for Computers in Education, 2019, Vol. 1, p. 90-92Conference paper (Refereed)
    Abstract [en]

    Cognitive pre-requisites should be taken into consideration when providing personalized and adaptive digital content in web-based learning platforms. In order to achieve this it should be possible to extract these cognitive characteristics based on students´ study behavior. Working memory capacity (WMC) is one of the cognitive characteristics that affect students’ performance and their academic achievements. However, traditional approaches to measuring WMC are cognitively demanding and time consuming. In order to simplify these measures, Chang et al. (2015) proposed an approach that can automatically identify students’ WMC based on their study behavior patterns. The intriguing question is then whether there are study behavior characteristics that correspond to the students’ WMC? This work explores to what extent it is possible to map individual WMC data onto individual patterns of learning by correlating working memory capacity with learners´ study behavior in an adaptive web-based learning system. Several machine learning models together with a rich context model have been applied to identify the most relevant study behavior characteristics and to predict students’ WMC. The evaluation was performed based on data collected from 122 students during a period of 2 years using a web-based learning platform. The initial results show that there is no linear correlation with learners´ study behavior and their WMC.

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  • 273.
    Lincke, Alisa
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Jansen, Marc
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Milrad, Marcelo
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Berge, Elias
    Hypocampus, Sweden.
    Using Data Mining Techniques to Assess Students’ Answer Predictions2019In: ICCE 2019 - 27th International Conference on Computers in Education, Proceedings: Volume 1 / [ed] Chang M.,So H.-J.,Wong L.-H.,Yu F.-Y.,Shih J.-L.,Boticki I.,Chen M.-P.,Dewan A.,Haklev S.,Koh E.,Kojiri T.,Li K.-C.,Sun D.,Wen Y, Kenting, Taiwan: Asia-Pacific Society for Computers in Education, 2019, Vol. 1, p. 42-50Conference paper (Refereed)
    Abstract [en]

    Estimating students´ knowledge and performance, modeling their learning behaviors, and discovering and analyzing their different characteristics are some of the main tasks in the field of research called educational data mining (EDM). According to Chounta (2017), the predicted probabilities that a student will answer a question correctly can provide some insights into the student´s knowledge. Based on this point of departure, the main objective of this paper is to apply different data mining techniques to predict the probabilities that students will answer questions correctly by using their interaction records with a web-based learning platform called Hypocampus. Five different machine learning algorithms and a rich context model were used on the Hypocampus dataset. The results of our evaluation indicate that the gradient-boosted tree and the XGboost algorithms are best in predicting the correctness of the student’s answer

  • 274.
    Lincke, Alisa
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Lozano Prieto, David
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Herault, Romain Christian
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Forsgärde, Elin-Sofie
    Linnaeus University, Faculty of Health and Life Sciences, Department of Health and Caring Sciences.
    Milrad, Marcelo
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Visualizing learners’ navigation behaviour using 360 degrees interactive videos2019In: Proceedings of the 15th International Conference on Web Information Systems and Technologies / [ed] Alessandro Bozzon, Francisco Domínguez Mayo & Joaquim Filipe, Vienna: SciTePress, 2019, Vol. 1, p. 358-364Conference paper (Refereed)
    Abstract [en]

    The use of 360-degrees interactive videos for educational purposes in the medical field has increased in recent years, as well as the use of virtual reality in general. Learner’s navigation behavior in 360-degrees interactive video learning environments has not been thoroughly explored yet. In this paper, a dataset of interactions generated by 80 students working in 16 groups while learning about patient trauma treatment using 360-degrees interactive videos is used to visualize learners’ navigation behavior. Three visualization approaches were designed and implemented for exploring users’ navigation paths and patterns of interaction with the learning materials are presented and discussed. The visualization tool was developed to explore the issues above and it provides a comprehensive overview of the navigation paths and patterns. A user study with four experts in the information visualization field has revealed the advantages and drawbacks of our solution. The paper concludes by providing some suggestions for improvements of the proposed visualizations.

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  • 275.
    Lincke, Alisa
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Lundberg, Jenny
    Thunander, Maria
    Lund University .
    Milrad, Marcelo
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Lundberg, Jonas
    Jusufi, Ilir
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Diabetes Information in Social Media2018In: Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18) / [ed] Karsten Klein, Yi-Na Li, and Andreas Kerren, ACM Publications, 2018, p. 104-105Conference paper (Refereed)
    Abstract [en]

    Social media platforms have created new ways for people to communicate and express themselves. Thus, it is important to explore how e-health related information is generated and disseminated in these platforms. The aim of our current efforts is to investigate the content and flow of information when people in Sweden use Twitter to talk about diabetes related issues. To achieve our goals, we have used data mining and visualization techniques in order to explore, analyze and cluster Twitter data we have collected during a period of 10 months. Our initial results indicate that patients use Twitter to share diabetes related information and to communicate about their disease as an alternative way that complements the traditional channels used by health care professionals.

  • 276.
    Lindahl, Daniel
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Ledsagande av seniorer i samband med webben: Identifiering av tillvägagångssätt att bistå seniorer i utförandet av uppgifter på webben2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    The web can be used in multiple purposes and can create a value both at work and in the

    personal life of people. Today computers, internet and IT in general are commonly used in

    multiple professions. IT has also become a part of the Swedish educational system where it

    happens that the schools provides the students with a computer with including programs to

    conduct their studies. Most swedes today gets some kind of computer habit from either work or

    education, something that certain seniors have missed out on. People above the age of 75 is by

    margin the age-group (taking in to account twelve years and older) that most seldom uses

    internet in Sweden. When asked why a common answer is “it is too hard”.

    This study aims to find out in what ways the use of the web can be made easier for seniors (in

    this study defined as 75 years of age and older). For starters the study focused on finding out

    what seniors can get out of using internet and the web. That was done by literature searching

    and a number of interviews. It showed that seniors who actually uses the web one way or the

    other uses for example internet banking, mail and news by computer, smartphone and/or tablet.

    These three areas (internet banking, mail and news) was used as a Centre in the user tests who

    was conducted in order to find out how seniors can be assisted in their interaction with the web.

    A browser extension was formed suited to the three areas mentioned above. Browser extensions

    is a sort of a local program/extension to install in your browser to personally have access to

    external functionality, such as blocking advertisement. The browser extension formed in this

    study gave the users browser graphic elements with the purpose to help the user solve a number

    of predetermined tasks. Three concepts was tested in the study. In the context of this study a

    concept is the way that the graphic assist is formed.

    User tests was conducted with and without the browser extension as an assist in order to see if

    there was a difference in the results. When tests was conducted with the browser extension the

    concepts was rotated so that all three concepts was tested on equal basis. The test persons who

    conducted the tests with the browser extension also got the opportunity to give anonymous

    feedback on the concepts through an inquiry that was filled out after conducted test. The result

    of the user tests and the inquiry indicates that seniors would appreciate a step by step guide for

    tasks on the web. According to the results of this study seniors conducts everyday tasks both

    quicker and with more success when there is a step by step list or highlighted headlines and

    buttons describing said task.

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  • 277.
    Lindwall, Katrin
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Sjökvist, Jan
    Xplorator.
    Green, Rebecka (Illustrator)
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Maker Tour - Mot nya höjder: Make IT flow, del 22018Other (Other (popular science, discussion, etc.))
    Abstract [sv]

    Utmaningarna är en del av projektet Maker tour - Mot nya höjder ( tidigare Mot nya höjder). Projektets mål är att öka intresset för naturvetenskap, teknik och matematik bland skolelever.

    Läs gärna mer på http://motnyahojder.com/

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    Make IT flow, del 2
  • 278. Lindwall, Katrin
    et al.
    Sjökvist, Jan
    Xplorator, Sweden.
    Maker tour: mot nya höjder: make IT shine HT-182018Other (Other (popular science, discussion, etc.))
    Abstract [sv]

    Utmaningarna är en del av projektet Maker tour - Mot nya höjder (tidigare Mot nya höjder). Projektets mål är att öka intresset för naturvetenskap, teknik och matematik bland skolelever.

    Download full text (pdf)
    Make IT shine
  • 279.
    Lindwall, Katrin
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Sjökvist, Jan
    Xplorator, Sweden.
    Maker tour: mot nya höjder: make space HT-192019Other (Other (popular science, discussion, etc.))
    Abstract [sv]

    Utmaningarna är en del av projektet Maker tour - Mot nya höjder (tidigare Mot nya höjder). Projektets mål är att öka intresset för naturvetenskap, teknik och matematik bland skolelever.

    Download full text (pdf)
    Maker tour - Mot nya höjder: Make space, del2
  • 280. Lindwall, Katrin
    et al.
    Sjökvist, Jan
    Xplorator, Sweden.
    Maker tour: mot nya höjder: make space VT-192019Other (Other (popular science, discussion, etc.))
    Abstract [sv]

    Utmaningarna är en del av projektet Maker tour - Mot nya höjder (tidigare Mot nya höjder). Projektets mål är att öka intresset för naturvetenskap, teknik och matematik bland skolelever. 

    Läs mer på: http://motnyahojder.com/

    Download full text (pdf)
    Make space, del 1
  • 281.
    Lindwall, Katrin
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Sjökvist, Jan
    Xplorator.
    Mot nya höjder: ASE - astronautbesök & rymdresan 20152014Other (Other (popular science, discussion, etc.))
    Abstract [sv]

    Utmaningarna är en del av projektet Mot nya höjder (från 2018 Maker tour  - Mot nya höjder). Projektets mål är att öka intresset för naturvetenskap, teknik och matematik bland skolelever.

    Läs gärna mer på www.motnyahojder.com

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    1. Mot nya höjder - En rymdresa
  • 282.
    Lindwall, Katrin
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Sjökvist, Jan
    Xplorator.
    Mot nya höjder: Make IT flow hösten 2017!2017Other (Other (popular science, discussion, etc.))
    Abstract [sv]

    Utmaningarna är en del av projektet Mot nya höjder ( från 2018 Maker tour - Mot nya höjder). Projektets mål är att öka intresset för naturvetenskap, teknik och matematik bland skolelever.

    Läs gärna mer på www.motnyahojder.com 

    Download full text (pdf)
    Mot nya höjder - Make IT flow
  • 283.
    Lindwall, Katrin
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Sjökvist, Jan
    Xplorator.
    Mot nya höjder: Make IT happen våren 20162016Other (Other (popular science, discussion, etc.))
    Abstract [sv]

    Utmaningarna är en del av projektet Mot nya höjder ( från 2018 Maker tour - Mot nya höjder). Projektets mål är att öka intresset för naturvetenskap, teknik och matematik bland skolelever.

    Läs gärna mer på www.motnyahojder.com 

    Download full text (pdf)
    Mot nya höjder - Make IT happen
  • 284.
    Lindwall, Katrin
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Sjökvist, Jan
    Xplorator.
    Mot nya höjder: Make IT Move våren 2017!2017Other (Other (popular science, discussion, etc.))
    Abstract [sv]

    Utmaningarna är en del av projektet Mot nya höjder ( från 2018 Maker tour - Mot nya höjder). Projektets mål är att öka intresset för naturvetenskap, teknik och matematik bland skolelever.

    Läs gärna mer på www.motnyahojder.com 

    Download full text (pdf)
    Mot nya höjder - Make IT move
  • 285.
    Lindwall, Katrin
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Sjökvist, Jan
    Xplorator.
    Mot nya höjder: Make sound happen hösten 2016!2016Other (Other (popular science, discussion, etc.))
    Abstract [sv]

    Utmaningarna är en del av projektet Mot nya höjder ( från 2018 Maker tour - Mot nya höjder). Projektets mål är att öka intresset för naturvetenskap, teknik och matematik bland skolelever.

    Läs gärna mer på www.motnyahojder.com 

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    Mot nya höjder - Make sound happen
  • 286.
    Lozano Prieto, David
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Data analysis and advanced visualization of 360degrees video dataset2020Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Recent trends in the use of 360degrees videos have led to a proliferation of studies that point to its potential in different application domains. A notable example of this potential is shown in the development of tools for educating and evaluating students in multiple disciplines. A search of the literature revealed there is a lack of research in the visualization of users’ navigation patterns and behavior while watching a 360degree interactive video in educational scenarios. There is a need for analyzing this behavior in order to help the teachers to evaluate their learners, and also understand how they are using this educational tool. To address this necessity, the creation of an approach was proposed. To gather for the approach’s technical requirements, meetings with nursing teachers and experts in the visualization field were conducted. This approach turned into the second version of Xcalpel (Xcalpel2.0) which was developed as the solution to this problem. To visualize users’ navigation behavior, an interaction dataset from 16 groups of medical students was used in this application. Two user studies were performed focusing on the interactions of the user with the application, having the user experience as one of the main factors for its evaluation, regarding media technology standards. The first user study was performed with two nursing teachers stressing the pedagogical value that the approach adds to the educational experience, and a second one was performed with four visualization experts in order to evaluate the visualization approaches from a technical point of view. The initial outcome from those sessions showed that Xcalpel2.0 achieves the set requirement and objectives. These results also allow seeing the advantages and drawbacks that the application presents, while knowing which developed visualization approaches are more suitable for solving the detected necessity. The aspect of the comparison between 360degrees video users had been successfully implemented, as well as the analysis and visualization of the navigation patterns in a 360 space, which makes out of Xcalpel2.0 a useful tool for assessing the performance into an interactive 360degrees video in educational scenarios.

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  • 287.
    Lozano Prieto, David
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Data analysis and visualization of the 360degrees interactional datasets2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Nowadays, there has been an increasing interest in using 360degrees video in medical education. Recent efforts are starting to explore how nurse students experience and interact with 360degrees videos. However, once these interactions have been registered in a database, there is a lack of ways to analyze these data, which generates a necessity of creating a reliable method that can manage all this collected data, and visualize the valuable insights of the data. Hence, the main goal of this thesis is to address this challenge by designing an approach to analyze and visualize this kind of data. This will allow teachers in health care education, and medical specialists to understand the collected data in a meaningful way. To get the most suitable solution, several meetings with nursing teachers took place to draw the first draft structure of an application which acts as the needed approach. Then, the application was used to analyze collected data in a study made in December. Finally, the application was evaluated through a questionnaire that involved a group of medical specialists related to education. The initial outcome from those testing and evaluations indicate that the application successfully achieves the main goals of the project, and it has allowed discussing some ideas that will help in the future to improve the 360degrees video experience and evaluation in the nursing education field providing an additional tool to analyze, compare and assess students. 

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  • 288.
    Luckert, Michael
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    Schaefer-Kehnert, Mortiz
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    Löwe, Welf
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    Ericsson, Morgan
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    Wingkvist, Anna
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    A Classifier to Determine Whether a Document is Professionally or Machine Translated2016In: PERSPECTIVES IN BUSINESS INFORMATICS RESEARCH, BIR 2016, Springer, 2016, p. 339-353Conference paper (Refereed)
    Abstract [en]

    In an increasingly networked world, the availability of high quality translations is critical for success, especially in the context of international competition. International companies need to provide well translated, high quality technical documentation not only to be successful in the market but also to meet legal regulations. We seek to evaluate translation quality, specifically concerning technical documentation, and formulate a method to evaluate the translation quality of technical documents both when we do have access to the original documents and when we do not. We rely on state-of-the-art machine learning algorithms and translation evaluation metrics in the context of a knowledge discovery process. Our evaluation is performed on a sentence level where each sentence is classified as either professionally translated or machine translated. The results for each sentence is then combined to evaluate the full document. The research is based on a database that contains 22,327 sentences and 32 translation evaluation attributes, which are used to optimize Decision Trees that are used to evaluate translation quality. Our method achieves an accuracy of 70.48% on sentence level for texts in the database and can accurately classify documents with at least 100 sentences.

  • 289.
    Lundberg, Jenny
    et al.
    Linnaeus University, Faculty of Technology, Department of Media Technology.
    Billore, Soniya
    Linnaeus University, School of Business and Economics, Department of Marketing.
    Axelsson, Clara
    Linnaeus University, Faculty of Health and Life Sciences, Department of Medicine and Optometry.
    Diabetes Among Children (DAC): project - Exploring opportunities with support from mobile applications in a cross cultural Indo-Swedish study2017In: BIOSTEC 2017: Final Program and Book of Abstracts, Portugal, 2017, p. 85-, article id 89Conference paper (Refereed)
    Abstract [en]

    In this paper we present opportunities and challenges to meet the worldwide challenge of diabetes. Diabetes has devastating long term complications that cause very great personal suffering and social costs locally and globally. The prevalence of diabetes is increasing globally as an epidemic and affects 415 million people today which is expected to increase to 642 million is 2040. Int this paper we explore the possibilities to join an Indo-Swedish collaboration. we present a research framework for mobile applicaiton development between Sweden and India. the scientific frameowrk is elaborated and this paper ends with speciifc challenges and future work.

  • 290.
    Lundberg, Jenny
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Media Technology.
    Billore, Soniya
    Linnaeus University, School of Business and Economics, Department of Marketing.
    Axelsson, Clara
    Linnaeus University, Faculty of Health and Life Sciences, Department of Medicine and Optometry.
    Diabetes Among Children (DAC) Project - Exploring Opportunities with Support from Mobile Applications in a Cross Cultural Indo-Swedish Study2017In: Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies, Vol 5: HEALTHINF / [ed] VanDenBroek, EL Fred, A Gamboa, H Vaz, M, SciTePress, 2017, p. 407-412Conference paper (Refereed)
    Abstract [en]

    In this paper we present opportunities and challenges to meet the worldwide challenge of diabetes. Diabetes has devastating long-term complications that cause very great personal suffering and social costs locally and globally. The prevalence of diabetes is increasing globally as an epidemic and affects 415 million people today, which is expected to increase to 642 million in 2040. In this paper we explore possibilities to join in Indo-Swedish R&D collaboration. We present and motivate the research purpose. Furthermore we present a research framework for mobile application development between Sweden and India. The scientific framework is elaborated and this paper ends with specific challenges and further work.

  • 291.
    Lundberg, Jenny
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Claesson, Lena
    Blekinge Institute of Technology.
    Early Signs of Diabetes Explored from an Engineering Perspective2019In: Smart Industry & Smart Education / [ed] Auer, ME Langmann, R, Springer, 2019, p. 22-31Conference paper (Refereed)
    Abstract [en]

    Undetected diabetes is a global issue, estimated to over 200 million persons affected. Engineering opportunities in capturing early signs of diabetes has a potential due to the complexity to interpret early signs and link it to diabetes. Persons with untreated diabetes are doubled in risk of getting cardiovascular diseases and may also suffer other consequent diseases. In Sweden, approximately 450 thousand have diabetes where 80-90% are of type 2 with 1/4 unaware of it, i.e. approx. 100 thousand. Screening approaches, searching specifically for diabetes in persons not showing symptoms has been initiated with positive results. However, some general drawbacks of screening such as false sense of security are an issue. In this publication, we focus upon in home measurements and empowering of the individual in identifying early signs of diabetes. The methods in this publication are to gather data, evaluate and give suggestion if clinical test to confirm or reject diabetes. In home measurements, education process with companies for innovation possibilities.

  • 292.
    Lundberg, Jonas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Fast and Precise Points-to Analysis2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Many software engineering applications require points-to analysis. These client applications range from optimizing compilers to integrated program development environments (IDEs) and from testing environments to reverse-engineering tools. The software engineering applications are often user-interactive, or used in an edit-compile cycle, and need the points-to analysis to be fast and precise.

    In this compilation thesis, we present a new context- and flow-sensitive approach to points-to analysis that is both fast and precise. This is accomplished by a new SSA-based flow-sensitive dataflow algorithm (Paper 1) and a new context-sensitive analysis (Paper 2). Compared to other well-known analysis approaches our approach is faster in practice, on average, twice as fast as the call string approach and by an order of magnitude faster than the object-sensitive technique. In fact, it shows to be only marginally slower than a context-insensitive baseline analysis. At the same time, it provides higher precision than the call string technique and is similar in precision to the object-sensitive technique. We confirm these statements with experiments in Paper 2.

    Paper 3 is a systematic comparison of ten different variants of context-sensitive points-to analysis using different call-depths  for separating the contexts. Previous works indicate that analyses with a call-depth  only provides slightly better precision than context-insensitive analysis and they find no substantial precision improvement when using a more expensive analyses with call-depth . The hypothesis in Paper 3 is that substantial differences between the context-sensitive approaches show if (and only if) the precision is measured by more fine-grained metrics focusing on individual objects (rather than methods and classes) and references between them. These metrics are justified by the many applications requiring such detailed object reference information.

    The main results in Paper 3 show that the differences between different context-sensitive analysis techniques are substantial, also the differences between the context-insensitive and the context-sensitive analyses with call-depth are substantial. The major surprise was that increasing the call-depth  did not lead to any substantial precision improvements. This is a negative result since it indicates that, in practice, we cannot get a more precise points-to analysis by increasing the call-depth. Further investigations show that substantial precision improvements can be detected for but they occur at such a low detail level that they are unlikely to be of any practical use.

  • 293.
    Lundberg, Jonas
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Laitinen, Mikko
    Linnaeus University, Faculty of Arts and Humanities, Department of Languages. University of Eastern Finland, Finland.
    Twitter trolls: A linguistic profile of anti-democratic discourse2020In: Language sciences (Oxford), ISSN 0388-0001, E-ISSN 1873-5746, article id 101268Article in journal (Refereed)
    Abstract [en]

    ThisThis article focuses on anti-democratic discourse and investigates the linguistic profile of Twitter trolls. The troll data consist of some 3.5 million messages in English obtained through Twitter in late 2018. These data originate from potentially state-backed information operations aimed at sowing discord in Western societies. The baseline data, against which the troll data are compared, contain circa 4.4 million messages in English drawn from the Nordic Tweet Stream corpus. A machine learning application that enables us to select genuine personal messages in this corpus is used to prune the data. The empirical part investigates frequency-based characteristics of the two datasets. We utilize a set of automatically-extracted word-list information and the observed frequencies of personal pronouns. Our empirical findings show considerable quantitative differences so that the troll data are shorter, make use of a smaller number of lexical types and tokens, and resemble more formal registers, while the personal messages are more spoken-like. The results could be used to improve automated detection systems whose purpose is to identify troll accounts. article focuses on anti-democratic discourse and investigates the linguistic profile of Twitter trolls. The troll data consist of some 3.5 million messages in English obtained through Twitter in late 2018. These data originate from potentially state-backed information operations aimed at sowing discord in Western societies. The baseline data, against which the troll data are compared, contain circa 4.4 million messages in English drawn from the Nordic Tweet Stream corpus. A machine learning application that enables us to select genuine personal messages in this corpus is used to prune the data. The empirical part investigates frequency-based characteristics of the two datasets. We utilize a set of automatically-extracted word-list information and the observed frequencies of personal pronouns. Our empirical findings show considerable quantitative differences so that the troll data are shorter, make use of a smaller number of lexical types and tokens, and resemble more formal registers, while the personal messages are more spoken-like. The results could be used to improve automated detection systems whose purpose is to identify troll accounts.

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  • 294.
    Lundqvist, Johan
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). 1994.
    Integrerade valideringsverktyg i webbläsaren: En studie om dess effekt hos människor som lär sig grunderna i HTML2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    This thesis presents the effect of an integrated validation tool applied on people learning the basics of HTML. Prior research show that students who are beginning to learn web development often write code containing validation errors and even hand in final submissions containing them. This thesis has collected data from 28 participants who voluntary agreed to participate. All participants studied basic web technology at university level. Three different methods were applied to gather a wide variety of data: experiment, survey and focus group. In order to collect data from the experiments, a tool called RawHTML was developed and used by the participants. Using RawHTML, a user could receive instant feedback weather or not the current website contained validation errors. This eliminates the participant’s use for external validation programs found on the web. To measure the effect of the tool the participants was split into a test group and a control group. The feedback of whether the website contained validation errors was not available for the control group.

    The result shows that using an integrated validation tool in the browser may have a positive impact on the user’s learning. The participants in both test groups performed better when calculating repeated validation errors from one update to another, compared to both control groups. The number of participants handing in their final submissions containing validation errors was lower in the test group compared with the control group.

    Data gathered from the focus group and surveys indicated that the participants in the test groups appreciated RawHTMLs helpfulness, as the tool conveyed the feedback in such a way that the participants could rectify the errors that occurred. RawHTML’s main strength, according to the test group, was the direct feedback shown when updating a web page. The result of this thesis may in turn lead to new and improved validation tools, having beginners as its target group.

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  • 295.
    Lyrå, Martin
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Digitalisering av skogsskötsel med GNSS: Kostnadseffektiv kartläggning med Arduino &Real-Time Kinematic2019Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [sv]

    Det finns en efterfrågan på hög-precisa GNSS-enheter i skogshantering som utförs av skogsinspektörer, skogsägare, och plantskolor. Problemet är att en genomsnittlig enhet kostar 30 000 SEK och uppåt.

    Därför söker man efter en billigare lösning med samma noggrannhet. Lösningen bör vara tillgänglig och lätt då det är önskvärt att monterasystemet på ett planteringsrör eller stav.

    Lösningen bestod av Arduino och U-Blox:s NEO-M8P-2 monterat på kretskort från SparkFun. Kommunikation mellan enheterna realiserades meden NTRIP-program som tredje part. Med Bluetooth för NTRIP-klienten och LTE (mobiltelefoni) för NTRIP-servern kommunicerade en rover och en basstation med nätet, för att överföra hämta och skicka korrigeringsdata från stationen till rovern.

    Lösningen lyckades med att uppnå grundligt resultat och några förväntningar. Man lyckades med att ta fram en lösning som kostar mindre än 6000 SEK, eller 2500 SEK om man väljer bort basstationen och endast behållermottagaren; rovern.

    Alla målen och förväntningar för resultat kunde inte uppfyllas på grund av problem och utmaningar i både lösningen och komplikationer orsakade avfaktorer utanför projektets ram.

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  • 296.
    Mahdavi-Hezavehi, Sara
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science. Univ Groningen, Netherlands ; Room 576 Bernoulliborg, Netherlands.
    Durelli, Vinicius H. S.
    Univ Groningen, Netherlands ; Room 576 Bernoulliborg, Netherlands ; Univ Sao Paulo, Brazil.
    Weyns, Danny
    Linnaeus University, Faculty of Technology, Department of Computer Science. Katholieke Univ Leuven, Belgium.
    Avgeriou, Paris
    Univ Groningen, Netherlands ; Room 576 Bernoulliborg, Netherlands.
    A systematic literature review on methods that handle multiple quality attributes in architecture-based self-adaptive systems2017In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 90, p. 1-26Article, review/survey (Refereed)
    Abstract [en]

    Context: Handling multiple quality attributes (QAs) in the domain of self-adaptive systems is an understudied research area. One well-known approach to engineer adaptive software systems and fulfill QAs of the system is architecture-based self-adaptation. In order to develop models that capture the required knowledge of the QAs of interest, and to investigate how these models can be employed at runtime to handle multiple quality attributes, we need to first examine current architecture-based self-adaptive methods. Objective: In this paper we review the state-of-the-art of architecture-based methods for handling multiple QAs in self-adaptive systems. We also provide a descriptive analysis of the collected data from the literature. Method: We conducted a systematic literature review by performing an automatic search on 28 selected venues and books in the domain of self-adaptive systems. As a result, we selected 54 primary studies which we used for data extraction and analysis. Results: Performance and cost are the most frequently addressed set of QAs. Current self-adaptive systems dealing with multiple QAs mostly belong to the domain of robotics and web-based systems paradigm. The most widely used mechanisms/models to measure and quantify QAs sets are QA data variables. After QA data variables, utility functions and Markov chain models are the most common models which are also used for decision making process and selection of the best solution in presence of many alternatives. The most widely used tools to deal with multiple QAs are PRISM and IBM's autonomic computing toolkit. KLAPER is the only language that has been specifically developed to deal with quality properties analysis. Conclusions: Our results help researchers to understand the current state of research regarding architecture-based methods for handling multiple QAs in self-adaptive systems, and to identity areas for improvement in the future. To summarize, further research is required to improve existing methods performing tradeoff analysis and preemption, and in particular, new methods may be proposed to make use of models to handle multiple QAs and to enhance and facilitate the tradeoffs analysis and decision making mechanism at runtime. (C) 2017 Published by Elsevier B.V.

  • 297.
    Martin, Manu
    et al.
    ManoMotion AB, Sweden.
    Nguyen, Thang
    ManoMotion AB, Sweden.
    Yousefi, Shahrouz
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Li, Bo
    ManoMotion AB, Sweden.
    Comprehensive features with randomized decision forests for hand segmentation from color images in uncontrolled indoor scenarios2019In: Multimedia tools and applications, ISSN 1380-7501, E-ISSN 1573-7721, Vol. 78, no 15, p. 20987-21020Article in journal (Refereed)
    Abstract [en]

    Hand segmentation is an integral part of many computer vision applications, especially gesture recognition. Training a classifier to classify pixels into hand or background using skin color as a feature is one of the most popular methods for this purpose. This approach has been highly restricted to simple hand segmentation scenarios since color feature alone provides very limited information for classification. Meanwhile there have been a rise of segmentation methods utilizing deep learning networks to exploit multi-layers of complex features learned from image data. Yet a deep neural network requires a large database for training and a powerful computational machine for operations due to its complexity in computations. In this work, the development of comprehensive features and optimized uses of these features with a randomized decision forest (RDF) classifier for the task of hand segmentation in uncontrolled indoor environments is investigated. Newly designed image features and new implementations are provided with evaluations of their hand segmentation performances. In total, seven image features which extract pixel or neighborhood related properties from color images are proposed and evaluated individually as well as in combination. The behaviours of feature and RDF parameters are also evaluated and optimum parameters for the scenario under consideration are identified. Additionally, a new dataset containing hand images in uncontrolled indoor scenarios was created during this work. It was observed from the research that a combination of features extracting color, texture, neighborhood histogram and neighborhood probability information outperforms existing methods for hand segmentation in restricted as well as unrestricted indoor environments using just a small training dataset. Computations required for the proposed features and the RDF classifier are light, hence the segmentation algorithm is suited for embedded devices equipped with limited power, memory, and computational capacities.

  • 298.
    Martins, Rafael Messias
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Berge, Elias
    Hypocampus, Sweden.
    Milrad, Marcelo
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Masiello, Italo
    Linnaeus University, Faculty of Social Sciences, Department of Pedagogy and Learning.
    Visual Learning Analytics of Multidimensional Student Behavior in Self-regulated Learning2019In: Transforming Learning with Meaningful Technologies / [ed] Scheffel M., Broisin J., Pammer-Schindler V., Ioannou A., Schneider J., Springer, 2019, p. 737-741Conference paper (Refereed)
    Abstract [en]

    In Self-Regulated Learning (SLR), the lack of a predefined, formal learning trajectory makes it more challenging to assess students’ progress (e.g. by comparing it to specific baselines) and to offer relevant feedback and scaffolding when appropriate. In this paper we describe a Visual Learning Analytics (VLA) solution for exploring students’ datasets collected in a Web-Based Learning Environment (WBLE). We employ mining techniques for the analysis of multidimensional data, such as t-SNE and clustering, in an exploratory study for identifying patterns of students with similar study behavior and interests. An example use case is presented as evidence of the effectiveness of our proposed method, with a dataset of learning behaviors of 6423 students who used an online study tool during 18 months.

  • 299.
    Martins, Rafael Messias
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Efficient Dynamic Time Warping for Big Data Streams2019In: Proceedings of the IEEE International Conference on Big Data (Big Data '18): Workshop on Real-time & Stream Analytics in Big Data & Stream Data Management / [ed] Abe, N; Liu, H; Pu, C; Hu, X; Ahmed, N; Qiao, M; Song, Y; Kossmann, D; Liu, B; Lee, K; Tang, J; He, J; Saltz, J, IEEE, 2019, p. 2924-2929Conference paper (Refereed)
    Abstract [en]

    Many common data analysis and machine learning algorithms for time series, such as classification, clustering, or dimensionality reduction, require a distance measurement between pairs of time series in order to determine their similarity. A variety of measures can be found in the literature, each with their own strengths and weaknesses, but the Dynamic Time Warping (DTW) distance measure has occupied an important place since its early applications for the analysis and recognition of spoken word. The main disadvantage of the DTW algorithm is, however, its quadratic time and space complexity, which limits its practical use to relatively small time series. This issue is even more problematic when dealing with streaming time series that are continuously updated, since the analysis must be re-executed regularly and with strict running time constraints. In this paper, we describe enhancements to the DTW algorithm that allow it to be used efficiently in a streaming scenario by supporting an append operation for new time steps with a linear complexity when an exact, error-free DTW is needed, and even better performance when either a Sakoe-Chiba band is used, or when a sliding window is the desired range for the data. Our experiments with one synthetic and four natural data sets have shown that it outperforms other DTW implementations and the potential errors are, in general, much lower than another state-of-the-art approximated DTW technique.

  • 300.
    Martins, Rafael Messias
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    Simaki, Vasiliki
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science. Lund University.
    Kucher, Kostiantyn
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    Paradis, Carita
    Lund University.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    StanceXplore: Visualization for the Interactive Exploration of Stance in Social Media2017Conference paper (Refereed)
    Abstract [en]

    The use of interactive visualization techniques in Digital Humanities research can be a useful addition when traditional automated machine learning techniques face difficulties, as is often the case with the exploration of large volumes of dynamic—and in many cases, noisy and conflicting—textual data from social media. Recently, the field of stance analysis has been moving from a predominantly binary approach—either pro or con—to a multifaceted one, where each unit of text may be classified as one (or more) of multiple possible stance categories. This change adds more layers of complexity to an already hard problem, but also opens up new opportunities for obtaining richer and more relevant results from the analysis of stancetaking in social media. In this paper we propose StanceXplore, a new visualization for the interactive exploration of stance in social media. Our goal is to offer DH researchers the chance to explore stance-classified text corpora from different perspectives at the same time, using coordinated multiple views including user-defined topics, content similarity and dissimilarity, and geographical and temporal distribution. As a case study, we explore the activity of Twitter users in Sweden, analyzing their behavior in terms of topics discussed and the stances taken. Each textual unit (tweet) is labeled with one of eleven stance categories from a cognitive-functional stance framework based on recent work. We illustrate how StanceXplore can be used effectively to investigate multidimensional patterns and trends in stance-taking related to cultural events, their geographical distribution, and the confidence of the stance classifier. 

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