1. |
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2. |
- Chatterjee, Bapi, 1982
(author)
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Lock-free Concurrent Search
- 2017
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Doctoral thesis (other academic/artistic)abstract
- The contemporary computers typically consist of multiple computing cores with high compute power. Such computers make excellent concurrent asynchronous shared memory system. On the other hand, though many celebrated books on data structure and algorithm provide a comprehensive study of sequential search data structures, unfortunately, we do not have such a luxury if concurrency comes in the setting. The present dissertation aims to address this paucity. We describe novel lock-free algorithms for concurrent data structures that target a variety of search problems. (i) Point search (membership query, predecessor query, nearest neighbour query) for 1-dimensional data: Lock-free linked-list; lock-free internal and external binary search trees (BST). (ii) Range search for 1-dimensional data: A range search method for lock-free ordered set data structures - linked-list, skip-list and BST. (iii) Point search for multi-dimensional data: Lock-free kD-tree, specially, a generic method for nearest neighbour search. We prove that the presented algorithms are linearizable i.e. the concurrent data structure operations intuitively display their sequential behaviour to an observer of the concurrent system. The lock-freedom in the introduced algorithms guarantee overall progress in an asynchronous shared memory system. We present the amortized analysis of lock-free data structures to show their efficiency. Moreover, we provide sample implementations of the algorithms and test them over extensive micro-benchmarks. Our experiments demonstrate that the implementations are scalable and perform well when compared to related existing alternative implementations on common multi-core computers. Our focus is on propounding the generic methodologies for efficient lock-free concurrent search. In this direction, we present the notion of help-optimality, which captures the optimization of amortized step complexity of the operations. In addition to that, we explore the language-portable design of lock-free data structures that aims to simplify an implementation from programmer’s point of view. Finally, our techniques to implement lock-free linearizable range search and nearest neighbour search are independent of the underlying data structures and thus are adaptive to similar data structures.
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3. |
- Liu, Yuanhua, 1971, et al.
(author)
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Considering the importance of user profiles in interface design
- 2009
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In: User Interfaces. ; , s. 23-
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Book chapter (other academic/artistic)abstract
- User profile is a popular term widely employed during product design processes by industrial companies. Such a profile is normally intended to represent real users of a product. The ultimate purpose of a user profile is actually to help designers to recognize or learn about the real user by presenting them with a description of a real user’s attributes, for instance; the user’s gender, age, educational level, attitude, technical needs and skill level. The aim of this chapter is to provide information on the current knowledge and research about user profile issues, as well as to emphasize the importance of considering these issues in interface design. In this chapter, we mainly focus on how users’ difference in expertise affects their performance or activity in various interaction contexts. Considering the complex interaction situations in practice, novice and expert users’ interactions with medical user interfaces of different technical complexity will be analyzed as examples: one focuses on novice and expert users’ difference when interacting with simple medical interfaces, and the other focuses on differences when interacting with complex medical interfaces. Four issues will be analyzed and discussed: (1) how novice and expert users differ in terms of performance during the interaction; (2) how novice and expert users differ in the perspective of cognitive mental models during the interaction; (3) how novice and expert users should be defined in practice; and (4) what are the main differences between novice and expert users’ implications for interface design. Besides describing the effect of users’ expertise difference during the interface design process, we will also pinpoint some potential problems for the research on interface design, as well as some future challenges that academic researchers and industrial engineers should face in practice.
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4. |
- Wilhelmsson, Kenneth, 1976
(author)
-
Huvudansatser för parsningsmetoder. Om programutvecklingens förutsättningar i en svensk kontext
- 2016
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Reports (other academic/artistic)abstract
- Syftet med denna text var att ge en inblick i området (syntaktisk) parsning. Tanken var att ge en bild av utvecklingen som var 1) fri från alltför tekniska detaljer, då området är programmeringstekniskt, och 2) beskriven ur ett svenskt perspektiv. Bakgrunden till valet av ämne till texten, som var tänkt att finnas med i antologin Text och kontext, var att parsning är relativt okänt för många personer verksamma inom närliggande områden, samtidigt som det är ett absolut nyckelbegrepp för den som ägnar sig åt datorlingvistik eller språkteknologi. Målet var alltså att ge en ganska allmän utifrånblick på några centrala sidor av utvecklingen, samtidigt som det tydligt är så att den som själv arbetat med utveckling kan ha starka åsikter och preferenser rörande metodval, något som i ärlighetens namn kanske inte heller denna text är lösgjord från. Hur ska det göras? Konsten att utveckla automatisk syntaxanalys av naturlig text kan läras ut från ett flertal perspektiv. Det kan t.ex. ske med fokus på användandet av en viss grammatikformalism, med fokus på beräkningssnabbhet, med fokus på entydiggörande av möjliga ambiguiteter. Tolkningsval kan göras med hjälp av antingen handskrivna regler eller inhämtad statistik. En sorts huvudtema i denna text är hur metoder för parsning på senare år uppvisar förändringar som kanske kan förklaras med att programmen har fått andra användningsområden och att metoderna har anpassats därefter (en annan tolkning är att flera senare system inte längre gör parsning i strikt mening). När detta tänkta ”kapitel” var färdigt fick det kommentaren att det inte var anpassat för antologins målgrupp. Det fick skrivas en annan kapiteltext, men det kom samtidigt ett förslag att publicera texten om parsning här som denna rapport.
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5. |
- Wilhelmsson, Kenneth, 1976
(author)
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Autentiska och artificiella frågor till svensk text Automatisk frågegenerering jämfört med användares frågor för informationsåtkomst : Authentic and artificial questions to Swedish text Automatically generated questions versus user-generated questions for information access
- 2015
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Other publication (other academic/artistic)abstract
- Informationssökning mot ostrukturerade datakällor som fri text är ett av de områden där användargränssnitt med fri formulering i naturligt språk har tagits fram. I ett sådant, eventuellt AI-betonat, system kan några grundläggande svårigheter från användarperspektivet märkas. En sådan svårighet är att en användare inte känner till huruvida en fråga som hon avser att ställa egentligen kan besvaras av den aktuella texten. Denna svårighet, tillsammans med andra, som de kraftiga variationsmöjligheterna för formen för ett giltigt svar på en ställd fråga, riskerar att leda till att användarintrycken av systemtypen blir negativa. De moment som behöver ingå i ett sådant frågebaserat informationssystems funktionssätt måste på något sätt inbegripa en mappning av frågeled i frågan (t.ex. när) till den form och grammatisk funktion som svaret i texten måste ha (för frågan när normalt ett tidsadverbial). Bland annat denna iakttagelse inbjuder till användning av automatisk frågegenerering (question generation, QG). Frågegenerering innebär att frågor som en naturlig text besvarar initialt utvinns av ett program som samlar in dem i explicit form. Tanken för användning i informationssökning är att en användare i gränssnittet enbart ska kunna ställa just dessa frågor, vilka faktiskt besvaras av texten. Denna studie gäller just de frågor som ett automatiskt frågegenereringssystem för svenska kan, och genom vidare utveckling, skulle kunna generera för godtycklig digital svensk text. Även om mängden automatiskt genererade frågor och frågeformuleringar kan bli mycket stor, utrymmesmässigt många gånger större än ursprungstexten, så är det tydligt att den beskrivna metoden för frågegenerering för svenska inte kan och troligen inte heller kommer att kunna förmås att skapa alla de frågor och frågeformuleringar som en vanlig användare skulle anse att en viss text besvarar. Men hur väl fungerar då automatiskt genererade frågor i detta sammanhang? Denna uppsats kretsar kring en användarundersökning där undersökningsdeltagare har ombetts att formulera frågor som texter besvarar, och som anses vara relevanta frågor. Den resulterande samlingen frågor undersöktes och kategoriserades. Resultatet av undersökningens huvudfråga visar att bara 20-25 % av användarnas frågeformuleringar skulle kunna genereras direkt automatiskt med aktuell ansats – utan vissa informationstekniska förbättringar. Uppsatsen föreslår viss ny terminologi för detta outforskade område, bl.a. för att skilja mellan de olika grader av processkrav som generering av olika frågeslag från text kräver.
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6. |
- Munappy, Aiswarya Raj, 1990, et al.
(author)
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On the Trade-off Between Robustness and Complexity in Data Pipelines
- 2021
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In: Quality of Information and Communications Technology. - Cham : Springer. - 9783030853464 - 9783030853471 ; 1439, s. 401-415
-
Conference paper (peer-reviewed)abstract
- Data pipelines play an important role throughout the data management process whether these are used for data analytics or machine learning. Data-driven organizations can make use of data pipelines for producing good quality data applications. Moreover, data pipelines ensure end-to-end velocity by automating the processes involved in extracting, transforming, combining, validating, and loading data for further analysis and visualization. However, the robustness of data pipelines is equally important since unhealthy data pipelines can add more noise to the input data. This paper identifies the essential elements for a robust data pipeline and analyses the trade-off between data pipeline robustness and complexity.
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7. |
- Amundin, Mats, et al.
(author)
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A proposal to use distributional models to analyse dolphin vocalisation
- 2017
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In: Proceedings of the 1st International Workshop on Vocal Interactivity in-and-between Humans, Animals and Robots, VIHAR 2017. - 9782956202905 ; , s. 31-32
-
Conference paper (peer-reviewed)abstract
- This paper gives a brief introduction to the starting points of an experimental project to study dolphin communicative behaviour using distributional semantics, with methods implemented for the large scale study of human language.
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8. |
- Blanch, Krister, 1991
(author)
-
Beyond-application datasets and automated fair benchmarking
- 2023
-
Licentiate thesis (other academic/artistic)abstract
- Beyond-application perception datasets are generalised datasets that emphasise the fundamental components of good machine perception data. When analysing the history of perception datatsets, notable trends suggest that design of the dataset typically aligns with an application goal. Instead of focusing on a specific application, beyond-application datasets instead look at capturing high-quality, high-volume data from a highly kinematic environment, for the purpose of aiding algorithm development and testing in general. Algorithm benchmarking is a cornerstone of autonomous systems development, and allows developers to demonstrate their results in a comparative manner. However, most benchmarking systems allow developers to use their own hardware or select favourable data. There is also little focus on run time performance and consistency, with benchmarking systems instead showcasing algorithm accuracy. By combining both beyond-application dataset generation and methods for fair benchmarking, there is also the dilemma of how to provide the dataset to developers for this benchmarking, as the result of a high-volume, high-quality dataset generation is a significant increase in dataset size when compared to traditional perception datasets. This thesis presents the first results of attempting the creation of such a dataset. The dataset was built using a maritime platform, selected due to the highly dynamic environment presented on water. The design and initial testing of this platform is detailed, as well as as methods of sensor validation. Continuing, the thesis then presents a method of fair benchmarking, by utilising remote containerisation in a way that allows developers to present their software to the dataset, instead of having to first locally store a copy. To test this dataset and automatic online benchmarking, a number of reference algorithms were required for initial results. Three algorithms were built, using the data from three different sensors captured on the maritime platform. Each algorithm calculates vessel odometry, and the automatic benchmarking system was utilised to show the accuracy and run-time performance of these algorithms. It was found that the containerised approach alleviated data management concerns, prevented inflated accuracy results, and demonstrated precisely how computationally intensive each algorithm was.
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9. |
- Yun, Yixiao, 1987, et al.
(author)
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Maximum-Likelihood Object Tracking from Multi-View Video by Combining Homography and Epipolar Constraints
- 2012
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In: 6th ACM/IEEE Int'l Conf on Distributed Smart Cameras (ICDSC 12), Oct 30 - Nov.2, 2012, Hong Kong. - 9781450317726 ; , s. 6 pages-
-
Conference paper (peer-reviewed)abstract
- This paper addresses problem of object tracking in occlusion scenarios, where multiple uncalibrated cameras with overlapping fields of view are used. We propose a novel method where tracking is first done independently for each view and then tracking results are mapped between each pair of views to improve the tracking in individual views, under the assumptions that objects are not occluded in all views and move uprightly on a planar ground which may induce a homography relation between each pair of views. The tracking results are mapped by jointly exploiting the geometric constraints of homography, epipolar and vertical vanishing point. Main contributions of this paper include: (a) formulate a reference model of multi-view object appearance using region covariance for each view; (b) define a likelihood measure based on geodesics on a Riemannian manifold that is consistent with the destination view by mapping both the estimated positions and appearances of tracked object from other views; (c) locate object in each individual view based on maximum likelihood criterion from multi-view estimations of object position. Experiments have been conducted on videos from multiple uncalibrated cameras, where targets experience long-term partial or full occlusions. Comparison with two existing methods and performance evaluations are also made. Test results have shown effectiveness of the proposed method in terms of robustness against tracking drifts caused by occlusions.
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10. |
- Dodig-Crnkovic, Gordana, 1955
(author)
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Cognitive Architectures Based on Natural Info-Computation
- 2022
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In: Studies in Applied Philosophy, Epistemology and Rational Ethics. - Cham : Springer. - 2192-6255 .- 2192-6263. ; , s. 3-13, s. 3-13
-
Book chapter (peer-reviewed)abstract
- At the time when the first models of cognitive architectures have been proposed, some forty years ago, understanding of cognition, embodiment and evolution was substantially different from today’s. So was the state of the art of information physics, information chemistry, bioinformatics, neuroinformatics, computational neuroscience, complexity theory, self-organization, theory of evolution, as well as the basic concepts of information and computation. Novel developments support a constructive interdisciplinary framework for cognitive architectures based on natural morphological computing, where interactions between constituents at different levels of organization of matter-energy and their corresponding time-dependent dynamics, lead to complexification of agency and increased cognitive capacities of living organisms that unfold through evolution. Proposed info-computational framework for naturalizing cognition considers present updates (generalizations) of the concepts of information, computation, cognition, and evolution in order to attain an alignment with the current state of the art in corresponding research fields. Some important open questions are suggested for future research with implications for further development of cognitive and intelligent technologies.
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11. |
- Schötz, Susanne, et al.
(author)
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Phonetic Characteristics of Domestic Cat Vocalisations
- 2017
-
In: Proceedings of the 1st International Workshop on Vocal Interactivity in-and-between Humans, Animals and Robots, VIHAR 2017. - 9782956202905 ; , s. 5-6
-
Conference paper (peer-reviewed)abstract
- The cat (Felis catus, Linneaus 1758) has lived around or with humans for at least 10,000 years, and is now one of the most popular pets of the world with more than 600 millionindividuals. Domestic cats have developed a more extensive, variable and complex vocal repertoire than most other members of the Carnivora, which may be explained by their social organisation, their nocturnal activity and the long period of association between mother and young. Still, we know surprisingly little about the phonetic characteristics of these sounds, and about the interaction between cats and humans.Members of the research project Melody in human–cat communication (Meowsic) investigate the prosodic characteristics of cat vocalisations as well as the communication between human and cat. The first step includes a categorisation of cat vocalisations. In the next step it will be investigated how humans perceive the vocal signals of domestic cats. This paper presents an outline of the project which has only recently started.
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12. |
- Mohseni, Zeynab (Artemis)
(author)
-
Development of Visual Learning Analytic Tools to Explore Performance and Engagement of Students in Primary, Secondary, and Higher Education
- 2024
-
Doctoral thesis (other academic/artistic)abstract
- Schools and educational institutions collect large amounts of data about students and their learning, including text, grades, quizzes, timestamps, and other activities. However, in primary and secondary education, this data is often dispersed across different digital platforms, lacking standardized methods for collection, processing, analysis, and presentation. These issues hinder teachers and students from making informed decisions or strategic and effective use of data. This presents a significant obstacle to progress in education and the effective development of Educational Technology (EdTech) products. Visual Learning Analytics (VLA) tools, also known as Learning Analytics Dashboards (LADs), are designed to visualize student data to support pedagogical decision-making. Despite their potential, the effectiveness of these tools remains limited. Addressing these challenges requires both technical solutions and thoughtful design considerations, as explored in Papers 1 through 5 of this thesis. Paper 1 examines the design aspects of VLA tools by evaluating higher education data and various visualization and Machine Learning (ML) techniques. Paper 2 provides broader insights into the VLA landscape through a systematic review, mapping key concepts and research gaps in VLA and emphasizing the potential of VLA tools to enhance pedagogical decisions and learning outcomes. Meanwhile, Paper 3 delves into a technical solution (data pipeline and data standard) considering a secure Swedish warehouse, SUNET. This includes a data standard for integrating educational data into SUNET, along with customized scripts to reformat, merge, and hash multiple student datasets. Papers 4 and 5 focus on design aspects, with Paper 4 discussing the proposed Human-Centered Design (HCD) approach involving teachers in co-designing a simple VLA tool. Paper 5 introduces a scenario-based framework for Multiple Learning Analytics Dashboards (MLADs) development, stressing user engagement for tailored LADs that facilitate informed decision-making in education. The dissertation offers a comprehensive approach to advancing VLA tools, integrating technical solutions with user-centric design principles. By addressing data integration challenges and involving users in tool development, these efforts aim to empower teachers in leveraging educational data for improved teaching and learning experiences.
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13. |
- Bayram, Firas, et al.
(author)
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DQSOps : Data Quality Scoring Operations Framework for Data-Driven Applications
- 2023
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In: EASE '23: Proceedings of the 27<sup>th</sup> International Conference on Evaluation and Assessment in Software Engineering. - : Association for Computing Machinery (ACM). - 9798400700446 ; , s. 32-41
-
Conference paper (peer-reviewed)abstract
- Data quality assessment has become a prominent component in the successful execution of complex data-driven artificial intelligence (AI) software systems. In practice, real-world applications generate huge volumes of data at speeds. These data streams require analysis and preprocessing before being permanently stored or used in a learning task. Therefore, significant attention has been paid to the systematic management and construction of high-quality datasets. Nevertheless, managing voluminous and high-velocity data streams is usually performed manually (i.e. offline), making it an impractical strategy in production environments. To address this challenge, DataOps has emerged to achieve life-cycle automation of data processes using DevOps principles. However, determining the data quality based on a fitness scale constitutes a complex task within the framework of DataOps. This paper presents a novel Data Quality Scoring Operations (DQSOps) framework that yields a quality score for production data in DataOps workflows. The framework incorporates two scoring approaches, an ML prediction-based approach that predicts the data quality score and a standard-based approach that periodically produces the ground-truth scores based on assessing several data quality dimensions. We deploy the DQSOps framework in a real-world industrial use case. The results show that DQSOps achieves significant computational speedup rates compared to the conventional approach of data quality scoring while maintaining high prediction performance.
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14. |
- Nilsson, R. Henrik, 1976, et al.
(author)
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Mycobiome diversity: high-throughput sequencing and identification of fungi.
- 2019
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In: Nature reviews. Microbiology. - : Springer Science and Business Media LLC. - 1740-1534 .- 1740-1526. ; 17, s. 95-109
-
Research review (peer-reviewed)abstract
- Fungi are major ecological players in both terrestrial and aquatic environments by cycling organic matter and channelling nutrients across trophic levels. High-throughput sequencing (HTS) studies of fungal communities are redrawing the map of the fungal kingdom by hinting at its enormous - and largely uncharted - taxonomic and functional diversity. However, HTS approaches come with a range of pitfalls and potential biases, cautioning against unwary application and interpretation of HTS technologies and results. In this Review, we provide an overview and practical recommendations for aspects of HTS studies ranging from sampling and laboratory practices to data processing and analysis. We also discuss upcoming trends and techniques in the field and summarize recent and noteworthy results from HTS studies targeting fungal communities and guilds. Our Review highlights the need for reproducibility and public data availability in the study of fungal communities. If the associated challenges and conceptual barriers are overcome, HTS offers immense possibilities in mycology and elsewhere.
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15. |
- Wilhelmsson, Kenneth
(author)
-
Automatic Question Generation from Swedish Documents as a Tool for Information Extraction
- 2011
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In: Proceedings of the 18th Nordic Conference of Computational Linguistics NODALIDA 2011. ; , s. 323-326
-
Conference paper (peer-reviewed)abstract
- An implementation of automatic question generation (QG) from raw Swedish text is presented. QG is here chosen as an alternative to natural query systems where any query can be posed and no indication is given of whether the current text database includes the information sought for. The program builds on parsing with grammatical functions from which corresponding questions are generated and it incorporates the article database of Swedish Wikipedia. The pilot system is meant to work with a text shown in the GUI and auto-completes user input to help find available questions. The act of question generation is here described together with early test results regarding the current produced questions.
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16. |
- Lu, Zhihan, et al.
(author)
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Multimodal Hand and Foot Gesture Interaction for Handheld Devices
- 2014
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In: ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP). - : Association for Computing Machinery (ACM). - 1551-6857 .- 1551-6865. ; 11:1
-
Journal article (peer-reviewed)abstract
- We present a hand-and-foot-based multimodal interaction approach for handheld devices. Our method combines input modalities (i.e., hand and foot) and provides a coordinated output to both modalities along with audio and video. Human foot gesture is detected and tracked using contour-based template detection (CTD) and Tracking-Learning-Detection (TLD) algorithm. 3D foot pose is estimated from passive homography matrix of the camera. 3D stereoscopic and vibrotactile are used to enhance the immersive feeling. We developed a multimodal football game based on the multimodal approach as a proof-of-concept. We confirm our systems user satisfaction through a user study.
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17. |
- Bergström, Gustav, et al.
(author)
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Evaluating the layout quality of UML class diagrams using machine learning
- 2022
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In: Journal of Systems and Software. - : Elsevier BV. - 0164-1212. ; 192
-
Journal article (peer-reviewed)abstract
- UML is the de facto standard notation for graphically representing software. UML diagrams are used in the analysis, construction, and maintenance of software systems. Mostly, UML diagrams capture an abstract view of a (piece of a) software system. A key purpose of UML diagrams is to share knowledge about the system among developers. The quality of the layout of UML diagrams plays a crucial role in their comprehension. In this paper, we present an automated method for evaluating the layout quality of UML class diagrams. We use machine learning based on features extracted from the class diagram images using image processing. Such an automated evaluator has several uses: (1) From an industrial perspective, this tool could be used for automated quality assurance for class diagrams (e.g., as part of a quality monitor integrated into a DevOps toolchain). For example, automated feedback can be generated once a UML diagram is checked in the project repository. (2) In an educational setting, the evaluator can grade the layout aspect of student assignments in courses on software modeling, analysis, and design. (3) In the field of algorithm design for graph layouts, our evaluator can assess the layouts generated by such algorithms. In this way, this evaluator opens up the road for using machine learning to learn good layouting algorithms. Approach.: We use machine learning techniques to build (linear) regression models based on features extracted from the class diagram images using image processing. As ground truth, we use a dataset of 600+ UML Class Diagrams for which experts manually label the quality of the layout. Contributions.: This paper makes the following contributions: (1) We show the feasibility of the automatic evaluation of the layout quality of UML class diagrams. (2) We analyze which features of UML class diagrams are most strongly related to the quality of their layout. (3) We evaluate the performance of our layout evaluator. (4) We offer a dataset of labeled UML class diagrams. In this dataset, we supply for every diagram the following information: (a) a manually established ground truth of the quality of the layout, (b) an automatically established value for the layout-quality of the diagram (produced by our classifier), and (c) the values of key features of the layout of the diagram (obtained by image processing). This dataset can be used for replication of our study and others to build on and improve on this work. Editor's note: Open Science material was validated by the Journal of Systems and Software Open Science Board.
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18. |
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19. |
- Petersson, Jesper, 1974, et al.
(author)
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Off the record: The invisibility work of doctors in a patient-accessible electronic health record information service.
- 2021
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In: Sociology of health & illness. - : Wiley. - 1467-9566 .- 0141-9889. ; 43:5, s. 1270-1285
-
Journal article (peer-reviewed)abstract
- In this article, we draw on Michael Lipsky's work on street-level bureaucrats and discretion to analyse a real case setting comprising an interview study of 30 Swedish doctors regarding their experiences of changes in clinical work following patients being given access to medical records information online. We introduce the notion of invisibility work to capture how doctors exercise discretion to preserve the invisibility of their work, in contrast to the well-established notion of invisible work, which denotes work made invisible by parties other than those performing it. We discuss three main forms of invisibility work in relation to records: omitting information, cryptic writing and parallel note writing. We argue that invisibility work is a way for doctors to resolve professional tensions arising from the political decision to provide patients with online access to record information. Although invisibility work is understood by doctors as a solution to government-initiated visibility, we highlight how it can create difficulties for doctors concerning accountability towards patients, peers and authorities.
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20. |
- Ali, Muhaddisa Barat, 1986
(author)
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Deep Learning Methods for Classification of Gliomas and Their Molecular Subtypes, From Central Learning to Federated Learning
- 2023
-
Doctoral thesis (other academic/artistic)abstract
- The most common type of brain cancer in adults are gliomas. Under the updated 2016 World Health Organization (WHO) tumor classification in central nervous system (CNS), identification of molecular subtypes of gliomas is important. For low grade gliomas (LGGs), prediction of molecular subtypes by observing magnetic resonance imaging (MRI) scans might be difficult without taking biopsy. With the development of machine learning (ML) methods such as deep learning (DL), molecular based classification methods have shown promising results from MRI scans that may assist clinicians for prognosis and deciding on a treatment strategy. However, DL requires large amount of training datasets with tumor class labels and tumor boundary annotations. Manual annotation of tumor boundary is a time consuming and expensive process. The thesis is based on the work developed in five papers on gliomas and their molecular subtypes. We propose novel methods that provide improved performance. The proposed methods consist of a multi-stream convolutional autoencoder (CAE)-based classifier, a deep convolutional generative adversarial network (DCGAN) to enlarge the training dataset, a CycleGAN to handle domain shift, a novel federated learning (FL) scheme to allow local client-based training with dataset protection, and employing bounding boxes to MRIs when tumor boundary annotations are not available. Experimental results showed that DCGAN generated MRIs have enlarged the original training dataset size and have improved the classification performance on test sets. CycleGAN showed good domain adaptation on multiple source datasets and improved the classification performance. The proposed FL scheme showed a slightly degraded performance as compare to that of central learning (CL) approach while protecting dataset privacy. Using tumor bounding boxes showed to be an alternative approach to tumor boundary annotation for tumor classification and segmentation, with a trade-off between a slight decrease in performance and saving time in manual marking by clinicians. The proposed methods may benefit the future research in bringing DL tools into clinical practice for assisting tumor diagnosis and help the decision making process.
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21. |
- Isaksson, Martin, et al.
(author)
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Adaptive Expert Models for Federated Learning
- 2023
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In: <em>Lecture Notes in Computer Science </em>Volume 13448 Pages 1 - 16 2023. - Cham : Springer Science and Business Media Deutschland GmbH. - 9783031289958 ; 13448 LNAI, s. 1-16
-
Conference paper (peer-reviewed)abstract
- Federated Learning (FL) is a promising framework for distributed learning when data is private and sensitive. However, the state-of-the-art solutions in this framework are not optimal when data is heterogeneous and non-IID. We propose a practical and robust approach to personalization in FL that adjusts to heterogeneous and non-IID data by balancing exploration and exploitation of several global models. To achieve our aim of personalization, we use a Mixture of Experts (MoE) that learns to group clients that are similar to each other, while using the global models more efficiently. We show that our approach achieves an accuracy up to 29.78% better than the state-of-the-art and up to 4.38% better compared to a local model in a pathological non-IID setting, even though we tune our approach in the IID setting. © 2023, The Author(s)
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22. |
- Lv, Zhihan, Dr. 1984-, et al.
(author)
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Editorial : 5G for Augmented Reality
- 2022
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In: Mobile Networks and Applications. - : Springer. - 1383-469X .- 1572-8153.
-
Journal article (peer-reviewed)
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23. |
- Nugent, Christopher, et al.
(author)
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Improving the Quality of User Generated Data Sets for Activity Recognition
- 2016
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In: Ubiquitous Computing and Ambient Intelligence, UCAMI 2016, PT II. - Amsterdam : Springer Publishing Company. - 9783319487991 - 9783319487984 ; , s. 104-110
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Conference paper (peer-reviewed)abstract
- It is fully appreciated that progress in the development of data driven approaches to activity recognition are being hampered due to the lack of large scale, high quality, annotated data sets. In an effort to address this the Open Data Initiative (ODI) was conceived as a potential solution for the creation of shared resources for the collection and sharing of open data sets. As part of this process, an analysis was undertaken of datasets collected using a smart environment simulation tool. A noticeable difference was found in the first 1-2 cycles of users generating data. Further analysis demonstrated the effects that this had on the development of activity recognition models with a decrease of performance for both support vector machine and decision tree based classifiers. The outcome of the study has led to the production of a strategy to ensure an initial training phase is considered prior to full scale collection of the data.
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24. |
- Helldin, Tove, et al.
(author)
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Situation Awareness in Telecommunication Networks Using Topic Modeling
- 2018
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In: 2018 21st International Conference on Information Fusion, FUSION 2018. - : IEEE. - 9780996452762 - 9780996452779 - 9781538643303 ; , s. 549-556
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Conference paper (peer-reviewed)abstract
- For an operator of wireless telecommunication networks to make timely interventions in the network before minor faults escalate into issues that can lead to substandard system performance, good situation awareness is of high importance. Due to the increasing complexity of such networks, as well as the explosion of traffic load, it has become necessary to aid human operators to reach a good level of situation awareness through the use of exploratory data analysis and information fusion techniques. However, to understand the results of such techniques is often cognitively challenging and time consuming. In this paper, we present how telecommunication operators can be aided in their data analysis and sense-making processes through the usage and visualization of topic modeling results. We present how topic modeling can be used to extract knowledge from base station counter readings and make design suggestions for how to visualize the analysis results to a telecommunication operator.
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25. |
- Norlund, Tobias, 1991, et al.
(author)
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Transferring Knowledge from Vision to Language: How to Achieve it and how to Measure it?
- 2021
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In: Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, pp. 149-162, Punta Cana, Dominican Republic. - : Association for Computational Linguistics.
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Conference paper (peer-reviewed)abstract
- Large language models are known to suffer from the hallucination problem in that they are prone to output statements that are false or inconsistent, indicating a lack of knowledge. A proposed solution to this is to provide the model with additional data modalities that complements the knowledge obtained through text. We investigate the use of visual data to complement the knowledge of large language models by proposing a method for evaluating visual knowledge transfer to text for uni- or multimodal language models. The method is based on two steps, 1) a novel task querying for knowledge of memory colors, i.e. typical colors of well-known objects, and 2) filtering of model training data to clearly separate knowledge contributions. Additionally, we introduce a model architecture that involves a visual imagination step and evaluate it with our proposed method. We find that our method can successfully be used to measure visual knowledge transfer capabilities in models and that our novel model architecture shows promising results for leveraging multimodal knowledge in a unimodal setting.
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