| 1. |
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| 2. |
- Chatterjee, Bapi, 1982
(författare)
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Lock-free Concurrent Search
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)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.
(författare)
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Considering the importance of user profiles in interface design
- 2009
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Ingår i: User Interfaces. ; , s. 23-
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Bokkapitel (övrigt vetenskapligt/konstnärligt)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
(författare)
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Huvudansatser för parsningsmetoder. Om programutvecklingens förutsättningar i en svensk kontext
- 2016
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Rapport (övrigt vetenskapligt/konstnärligt)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
(författare)
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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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Annan publikation (övrigt vetenskapligt/konstnärligt)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.
(författare)
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On the Trade-off Between Robustness and Complexity in Data Pipelines
- 2021
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Ingår i: Quality of Information and Communications Technology. - Cham : Springer. - 9783030853464 - 9783030853471 ; 1439 CCIS, s. 401-415
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Konferensbidrag (refereegranskat)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.
(författare)
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A proposal to use distributional models to analyse dolphin vocalisation
- 2017
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Ingår i: Proceedings of the 1st International Workshop on Vocal Interactivity in-and-between Humans, Animals and Robots, VIHAR 2017. - 9782956202905 ; , s. 31-32
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Konferensbidrag (refereegranskat)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
(författare)
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Beyond-application datasets and automated fair benchmarking
- 2023
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)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.
(författare)
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Maximum-Likelihood Object Tracking from Multi-View Video by Combining Homography and Epipolar Constraints
- 2012
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Ingår i: 6th ACM/IEEE Int'l Conf on Distributed Smart Cameras (ICDSC 12), Oct 30 - Nov.2, 2012, Hong Kong. - 9781450317726 ; , s. 6 pages-
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Konferensbidrag (refereegranskat)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
(författare)
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Cognitive Architectures Based on Natural Info-Computation
- 2022
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Ingår i: Studies in Applied Philosophy, Epistemology and Rational Ethics. - Cham : Springer. - 2192-6255 .- 2192-6263. ; , s. 3-13, s. 3-13
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Bokkapitel (refereegranskat)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.
(författare)
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Phonetic Characteristics of Domestic Cat Vocalisations
- 2017
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Ingår i: Proceedings of the 1st International Workshop on Vocal Interactivity in-and-between Humans, Animals and Robots, VIHAR 2017. - 9782956202905 ; , s. 5-6
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Konferensbidrag (refereegranskat)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)
(författare)
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Development of Visual Learning Analytic Tools to Explore Performance and Engagement of Students in Primary, Secondary, and Higher Education
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)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.
(författare)
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DQSOps : Data Quality Scoring Operations Framework for Data-Driven Applications
- 2023
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Ingår i: 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
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Konferensbidrag (refereegranskat)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.
(författare)
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Mycobiome diversity: high-throughput sequencing and identification of fungi.
- 2019
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Ingår i: Nature reviews. Microbiology. - : Springer Science and Business Media LLC. - 1740-1534 .- 1740-1526. ; 17, s. 95-109
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Forskningsöversikt (refereegranskat)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
(författare)
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Automatic Question Generation from Swedish Documents as a Tool for Information Extraction
- 2011
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Ingår i: Proceedings of the 18th Nordic Conference of Computational Linguistics NODALIDA 2011. ; , s. 323-326
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Konferensbidrag (refereegranskat)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.
(författare)
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Multimodal Hand and Foot Gesture Interaction for Handheld Devices
- 2014
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Ingår i: ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP). - : Association for Computing Machinery (ACM). - 1551-6857 .- 1551-6865. ; 11:1
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Tidskriftsartikel (refereegranskat)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.
(författare)
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Evaluating the layout quality of UML class diagrams using machine learning
- 2022
-
Ingår i: Journal of Systems and Software. - : Elsevier BV. - 0164-1212. ; 192
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Tidskriftsartikel (refereegranskat)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.
(författare)
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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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Ingår i: Sociology of health & illness. - : Wiley. - 1467-9566 .- 0141-9889. ; 43:5, s. 1270-1285
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Tidskriftsartikel (refereegranskat)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
(författare)
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Deep Learning Methods for Classification of Gliomas and Their Molecular Subtypes, From Central Learning to Federated Learning
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)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.
(författare)
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Adaptive Expert Models for Federated Learning
- 2023
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Ingår i: <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
-
Konferensbidrag (refereegranskat)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. |
- Zhang, Chi, et al.
(författare)
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Spatial-Temporal-Spectral LSTM: A Transferable Model for Pedestrian Trajectory Prediction
- 2023
-
Ingår i: IEEE Transactions on Intelligent Vehicles. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2379-8858 .- 2379-8904.
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Tidskriftsartikel (refereegranskat)abstract
- Predicting the trajectories of pedestrians is critical for developing safe advanced driver assistance systems and autonomous driving systems. Most existing models for pedestrian trajectory prediction focused on a single dataset without considering the transferability to other previously unseen datasets. This leads to poor performance on new unseen datasets and hinders leveraging off-the-shelf labeled datasets and models. In this paper, we propose a transferable model, namely the “Spatial-Temporal-Spectral (STS) LSTM” model, that represents the motion pattern of pedestrians with spatial, temporal, and spectral domain information. Quantitative results and visualizations indicate that our proposed spatial-temporal-spectral representation enables the model to learn generic motion patterns and improves the performance on both source and target datasets. We reveal the transferability of three commonly used network structures, including long short-term memory networks (LSTMs), convolutional neural networks (CNNs), and Transformers, and employ the LSTM structure with negative log-likelihood loss in our model since it has the best transferability. The proposed STS LSTM model demonstrates good prediction accuracy when transferring to target datasets without any prior knowledge, and has a faster inference speed compared to the state-of-the-art models. Our work addresses the gap in learning knowledge from source datasets and transferring it to target datasets in the field of pedestrian trajectory prediction, and enables the reuse of publicly available off-the-shelf datasets.
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| 23. |
- Lv, Zhihan, Dr. 1984-, et al.
(författare)
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Editorial : 5G for Augmented Reality
- 2022
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Ingår i: Mobile Networks and Applications. - : Springer. - 1383-469X .- 1572-8153.
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Tidskriftsartikel (refereegranskat)
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| 24. |
- Nugent, Christopher, et al.
(författare)
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Improving the Quality of User Generated Data Sets for Activity Recognition
- 2016
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Ingår i: Ubiquitous Computing and Ambient Intelligence, UCAMI 2016, PT II. - Amsterdam : Springer Publishing Company. - 9783319487991 - 9783319487984 ; , s. 104-110
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Konferensbidrag (refereegranskat)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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| 25. |
- Helldin, Tove, et al.
(författare)
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Situation Awareness in Telecommunication Networks Using Topic Modeling
- 2018
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Ingår i: 2018 21st International Conference on Information Fusion, FUSION 2018. - : IEEE. - 9780996452762 - 9780996452779 - 9781538643303 ; , s. 549-556
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Konferensbidrag (refereegranskat)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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| 26. |
- Norlund, Tobias, 1991, et al.
(författare)
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Transferring Knowledge from Vision to Language: How to Achieve it and how to Measure it?
- 2021
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Ingår i: 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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Konferensbidrag (refereegranskat)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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| 27. |
- Fu, Keren, et al.
(författare)
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Deepside: A general deep framework for salient object detection
- 2019
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Ingår i: Neurocomputing. - : Elsevier BV. - 0925-2312 .- 1872-8286. ; 356, s. 69-82
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Tidskriftsartikel (refereegranskat)abstract
- Deep learning-based salient object detection techniques have shown impressive results compared to con- ventional saliency detection by handcrafted features. Integrating hierarchical features of Convolutional Neural Networks (CNN) to achieve fine-grained saliency detection is a current trend, and various deep architectures are proposed by researchers, including “skip-layer” architecture, “top-down” architecture, “short-connection” architecture and so on. While these architectures have achieved progressive improve- ment on detection accuracy, it is still unclear about the underlying distinctions and connections between these schemes. In this paper, we review and draw underlying connections between these architectures, and show that they actually could be unified into a general framework, which simply just has side struc- tures with different depths. Based on the idea of designing deeper side structures for better detection accuracy, we propose a unified framework called Deepside that can be deeply supervised to incorporate hierarchical CNN features. Additionally, to fuse multiple side outputs from the network, we propose a novel fusion technique based on segmentation-based pooling, which severs as a built-in component in the CNN architecture and guarantees more accurate boundary details of detected salient objects. The effectiveness of the proposed Deepside scheme against state-of-the-art models is validated on 8 benchmark datasets.
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| 28. |
- Rexhepi, Hanife, 1984-, et al.
(författare)
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Cancer patients’ information seeking behavior related to online electronic healthcare records
- 2021
-
Ingår i: Health Informatics Journal. - : Sage Publications. - 1460-4582 .- 1741-2811. ; 27:3, s. 1-12
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Tidskriftsartikel (refereegranskat)abstract
- Patients’ online access to their EHR together with the rapid proliferation of medical information on the Internet has changed how patients use information to learn about their health. Patients’ tendency to turn to the Internet to find information about their health and care is well-documented. However, little is known about patients’ information seeking behavior when using online EHRs. By using information horizons as an analytical tool this paper aims to investigate the information behavior of cancer patients who have chosen to view their EHRs (readers) and to those who have not made that option (non-readers). Thirty interviews were conducted with patients. Based on information horizons, it seems that non-reading is associated with living in a narrower information world in comparison to readers. The findings do not suggest that the smallness would be a result of active avoidance of information, or that it would be counterproductive for the patients. The findings suggest, however, that EHRs would benefit from comprehensive linking to authoritative health information sources to help users to understand their contents. In parallel, healthcare professionals should be more aware of their personal role as a key source of health information to those who choose not to read their EHRs.
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| 29. |
- Mallozzi, Piergiuseppe, 1990, et al.
(författare)
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A runtime monitoring framework to enforce invariants on reinforcement learning agents exploring complex environments
- 2019
-
Ingår i: RoSE 2019, IEEE/ACM 2nd International Workshop on Robotics Software Engineering, p.5-12. - : IEEE. - 9781728122496
-
Konferensbidrag (refereegranskat)abstract
- © 2019 IEEE. Without prior knowledge of the environment, a software agent can learn to achieve a goal using machine learning. Model-free Reinforcement Learning (RL) can be used to make the agent explore the environment and learn to achieve its goal by trial and error. Discovering effective policies to achieve the goal in a complex environment is a major challenge for RL. Furthermore, in safety-critical applications, such as robotics, an unsafe action may cause catastrophic consequences in the agent or in the environment. In this paper, we present an approach that uses runtime monitoring to prevent the reinforcement learning agent to perform 'wrong' actions and to exploit prior knowledge to smartly explore the environment. Each monitor is de?ned by a property that we want to enforce to the agent and a context. The monitors are orchestrated by a meta-monitor that activates and deactivates them dynamically according to the context in which the agent is learning. We have evaluated our approach by training the agent in randomly generated learning environments. Our results show that our approach blocks the agent from performing dangerous and safety-critical actions in all the generated environments. Besides, our approach helps the agent to achieve its goal faster by providing feedback and shaping its reward during learning.
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| 30. |
- Falkman, Göran, 1968-, et al.
(författare)
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SOMWeb - Towards an Infrastructure for Knowledge Sharing in Oral Medicine
- 2005
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Ingår i: Connecting Medical Informatics and Bio-Informatics: Proceedings of MIE2005 - The XIXth International Congress of the European Federation for Medical Informatics. - Amsterdam : IOS Press. - 1586035495 ; 116, s. 527-32, s. 527-532
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Konferensbidrag (refereegranskat)abstract
- In a net-based society, clinicians can come together for cooperative work and distance learning around a common medical material. This requires suitable techniques for cooperative knowledge management and user interfaces that are adapted to both the group as a whole and to individuals. To support distributed management and sharing of clinical knowledge, we propose the development of an intelligent web community for clinicians within oral medicine. This virtual meeting place will support the ongoing work on developing a digital knowledge base, providing a foundation for a more evidence-based oral medicine. The presented system is founded on the use and development of web services and standards for knowledge modelling and knowledge-based systems. The work is conducted within the frame of a well-established cooperation between oral medicine and computer science.
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| 31. |
- Ge, Chenjie, 1991, et al.
(författare)
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Co-Saliency-Enhanced Deep Recurrent Convolutional Networks for Human Fall Detection in E-Healthcare
- 2018
-
Ingår i: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. - 1557-170X. ; 2018-July, s. 1572-1575
-
Konferensbidrag (refereegranskat)abstract
- This paper addresses the issue of fall detection from videos for e-healthcare and assisted-living. Instead of using conventional hand-crafted features from videos, we propose a fall detection scheme based on co-saliency-enhanced recurrent convolutional network (RCN) architecture for fall detection from videos. In the proposed scheme, a deep learning method RCN is realized by a set of Convolutional Neural Networks (CNNs) in segment-levels followed by a Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), to handle the time-dependent video frames. The co-saliency-based method enhances salient human activity regions hence further improves the deep learning performance. The main contributions of the paper include: (a) propose a recurrent convolutional network (RCN) architecture that is dedicated to the tasks of human fall detection in videos; (b) integrate a co-saliency enhancement to the deep learning scheme for further improving the deep learning performance; (c) extensive empirical tests for performance analysis and evaluation under different network settings and data partitioning. Experiments using the proposed scheme were conducted on an open dataset containing multicamera videos from different view angles, results have shown very good performance (test accuracy 98.96%). Comparisons with two existing methods have provided further support to the proposed scheme.
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| 32. |
- Gerken, Jan, 1991, et al.
(författare)
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Equivariance versus augmentation for spherical images
- 2022
-
Ingår i: Proceedings of Machine Learning Resaerch. ; , s. 7404-7421
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Konferensbidrag (refereegranskat)abstract
- We analyze the role of rotational equivariance in convolutional neural networks (CNNs) applied to spherical images. We compare the performance of the group equivariant networks known as S2CNNs and standard non-equivariant CNNs trained with an increasing amount of data augmentation. The chosen architectures can be considered baseline references for the respective design paradigms. Our models are trained and evaluated on single or multiple items from the MNIST- or FashionMNIST dataset projected onto the sphere. For the task of image classification, which is inherently rotationally invariant, we find that by considerably increasing the amount of data augmentation and the size of the networks, it is possible for the standard CNNs to reach at least the same performance as the equivariant network. In contrast, for the inherently equivariant task of semantic segmentation, the non-equivariant networks are consistently outperformed by the equivariant networks with significantly fewer parameters. We also analyze and compare the inference latency and training times of the different networks, enabling detailed tradeoff considerations between equivariant architectures and data augmentation for practical problems.
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| 33. |
- Martinsson, John, et al.
(författare)
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Automatic blood glucose prediction with confidence using recurrent neural networks
- 2018
-
Ingår i: CEUR Workshop Proceedings. - : CEUR. ; 2148, s. 64-68
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Konferensbidrag (refereegranskat)abstract
- Low-cost sensors continuously measuring blood glucose levels in intervals of a few minutes and mobile platforms combined with machine-learning (ML) solutions enable personalized precision health and disease management. ML solutions must be adapted to different sensor technologies, analysis tasks and individuals. This raises the issue of scale for creating such adapted ML solutions. We present an approach for predicting blood glucose levels for diabetics up to one hour into the future. The approach is based on recurrent neural networks trained in an end-to-end fashion, requiring nothing but the glucose level history for the patient. The model outputs the prediction along with an estimate of its certainty, helping users to interpret the predicted levels. The approach needs no feature engineering or data pre-processing, and is computationally inexpensive.
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| 34. |
- Kucher, Kostiantyn, et al.
(författare)
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Visual Analysis of Online Social Media to Open Up the Investigation of Stance Phenomena
- 2016
-
Ingår i: Information Visualization. - : Sage Publications. - 1473-8716 .- 1473-8724. ; 15:2, s. 93-116
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Tidskriftsartikel (refereegranskat)abstract
- Online social media are a perfect text source for stance analysis. Stance in human communication is concerned with speaker attitudes, beliefs, feelings and opinions. Expressions of stance are associated with the speakers' view of what they are talking about and what is up for discussion and negotiation in the intersubjective exchange. Taking stance is thus crucial for the social construction of meaning. Increased knowledge of stance can be useful for many application fields such as business intelligence, security analytics, or social media monitoring. In order to process large amounts of text data for stance analyses, linguists need interactive tools to explore the textual sources as well as the processed data based on computational linguistics techniques. Both original texts and derived data are important for refining the analyses iteratively. In this work, we present a visual analytics tool for online social media text data that can be used to open up the investigation of stance phenomena. Our approach complements traditional linguistic analysis techniques and is based on the analysis of utterances associated with two stance categories: sentiment and certainty. Our contributions include (1) the description of a novel web-based solution for analyzing the use and patterns of stance meanings and expressions in human communication over time; and (2) specialized techniques used for visualizing analysis provenance and corpus overview/navigation. We demonstrate our approach by means of text media on a highly controversial scandal with regard to expressions of anger and provide an expert review from linguists who have been using our tool.
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| 35. |
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| 36. |
- Wilhelmsson, Kenneth, 1976
(författare)
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Om förutsättningarna för språkligt datorstöd på ordnivån och uppåt
- 2017
-
Ingår i: Text och kontext - perspektiv på textanalys / Karin Helgesson, Hans Lundqvist, Anna Lyngfelt, Andreas Nord & Åsa Wengelin (red.). - Malmö : Gleerups. - 9789140693648 ; , s. 207-228
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 37. |
- Sanli, Kemal, et al.
(författare)
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Metagenomic Sequencing of Marine Periphyton: Taxonomic and Functional Insights into Biofilm Communities
- 2015
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Ingår i: Frontiers in Microbiology. - : Frontiers Media SA. - 1664-302X. ; 6:1192
-
Tidskriftsartikel (refereegranskat)abstract
- Periphyton communities are complex phototrophic, multispecies biofilms that develop on surfaces in aquatic environments. These communities harbor a large diversity of organisms comprising viruses, bacteria, algae, fungi, protozoans and metazoans. However, thus far the total biodiversity of periphyton has not been described. In this study, we use metagenomics to characterize periphyton communities from the marine environment of the Swedish west coast. Although we found approximately ten times more eukaryotic rRNA marker gene sequences compared to prokaryotic, the whole metagenome-based similarity searches showed that bacteria constitute the most abundant phyla in these biofilms. We show that marine periphyton encompass a range of heterotrophic and phototrophic organisms. Heterotrophic bacteria, including the majority of proteobacterial clades and Bacteroidetes, and eukaryotic macro-invertebrates were found to dominate periphyton. The phototrophic groups comprise Cyanobacteria and the alpha-proteobacterial genus Roseobacter, followed by different micro- and macro-algae. We also assess the metabolic pathways that predispose these communities to an attached lifestyle. Functional indicators of the biofilm form of life in periphyton involve genes coding for enzymes that catalyze the production and degradation of extracellular polymeric substances, mainly in the form of complex sugars such as starch and glycogen-like meshes together with chitin. Genes for 278 different transporter proteins were detected in the metagenome, constituting the most abundant protein complexes. Finally, genes encoding enzymes that participate in anaerobic pathways, such as denitrification and methanogenesis, were detected suggesting the presence of anaerobic or low-oxygen micro-zones within the biofilms.
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| 38. |
- Buckland, Philip I., 1973-, et al.
(författare)
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The Strategic Environmental Archaeology Database : a resource for international, multiproxy and transdisciplinary studies of environmental and climatic change
- 2015
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Konferensbidrag (refereegranskat)abstract
- Climate and environmental change are global challenges which require global data and infrastructure to investigate. These challenges also require a multi-proxy approach, integrating evidence from Quaternary science and archaeology with information from studies on modern ecology and physical processes among other disciplines. The Strategic Environmental Archaeology Database (SEAD http://www.sead.se) is a Swedish based international research e-infrastructure for storing, managing, analysing and disseminating palaeoenvironmental data from an almost unlimited number of analysis methods. The system currently makes available raw data from over 1500 sites (>5300 datasets) and the analysis of Quaternary fossil insects, plant macrofossils, pollen, geochemistry and sediment physical properties, dendrochronology and wood anatomy, ceramic geochemistry and bones, along with numerous dating methods. This capacity will be expanded in the near future to include isotopes, multi-spectral and archaeo-metalurgical data. SEAD also includes expandable climate and environment calibration datasets, a complete bibliography and extensive metadata and services for linking these data to other resources. All data is available as Open Access through http://qsead.sead.se and downloadable software. SEAD is maintained and managed at the Environmental Archaeology Lab and HUMlab at Umea University, Sweden. Development and data ingestion is progressing in cooperation with The Laboratory for Ceramic Research and the National Laboratory for Wood Anatomy and Dendrochronology at Lund University, Sweden, the Archaeological Research Laboratory, Stockholm University, the Geoarchaeological Laboratory, Swedish National Historical Museums Agency and several international partners and research projects. Current plans include expanding its capacity to serve as a data source for any system and integration with the Swedish National Heritage Board's information systems. SEAD is partnered with the Neotoma palaeoecology database (http://www.neotomadb.org) and a new initiative for building cyberinfrastructure for transdisciplinary research and visualization of the long-term human ecodynamics of the North Atlantic funded by the National Science Foundation (NSF).
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| 39. |
- Chatterjee, Bapi, 1982
(författare)
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Efficient Implementation of Concurrent Data Structures on Multi-core and Many-core Architectures
- 2015
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Synchronization of concurrent threads is the central problem in order to design efficient concurrent data-structures. The compute systems widely available in market are increasingly becoming heterogeneous involving multi-core Central Processing Units (CPUs) and many-core Graphics Processing Units (GPUs). This thesis contributes to the research of efficient synchronization in concurrent data-structures in more than one way. It is divided into two parts. In the first part, a novel design of a Set Abstract Data Type (ADT) based on an efficient lock-free Binary Search Tree (BST) with improved amortized bounds of the time complexity of set operations - Add, Remove and Contains, is presented. In the second part, a comprehensive evaluation of concurrent Queue implementations on multi-core CPUs as well as many-core GPUs are presented. Efficient Lock-free BST -To the best of our knowledge, the lock-free BST presented in this thesis is the first to achieve an amortized complexity of O(H(n)+c) for all Set operations where H(n) is the height of a BST on n nodes and c is the contention measure. Also, the presented lock-free algorithm of BST comes with an improved disjoint-access-parallelism compared to the previously existing concurrent BST algorithms. This algorithm uses single-word compare-and-swap (CAS) primitives. The presented algorithm is linearizable. We implemented the algorithm in Java and it shows good scalability. Evaluation of concurrent data-structures - We have evaluated the performance of a number of concurrent FIFO Queue algorithms on multi-core CPUs and many-core GPUs. We studied the portability of existing design of concurrent Queues from CPUs to GPUs which are inherently designed for SIMD programs. We observed that in general concurrent queues offer them to efficient implementation on GPUs with faster cache memory and better performance support for atomic synchronization primitives such as CAS. To the best of our knowledge, this is the first attempt to evaluate a concurrent data-structure on GPUs.
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| 40. |
- Homem, Irvin, 1985-
(författare)
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Advancing Automation in Digital Forensic Investigations
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Digital Forensics is used to aid traditional preventive security mechanisms when they fail to curtail sophisticated and stealthy cybercrime events. The Digital Forensic Investigation process is largely manual in nature, or at best quasi-automated, requiring a highly skilled labour force and involving a sizeable time investment. Industry standard tools are evidence-centric, automate only a few precursory tasks (E.g. Parsing and Indexing) and have limited capabilities of integration from multiple evidence sources. Furthermore, these tools are always human-driven.These challenges are exacerbated in the increasingly computerized and highly networked environment of today. Volumes of digital evidence to be collected and analyzed have increased, and so has the diversity of digital evidence sources involved in a typical case. This further handicaps digital forensics practitioners, labs and law enforcement agencies, causing delays in investigations and legal systems due to backlogs of cases. Improved efficiency of the digital investigation process is needed, in terms of increasing the speed and reducing the human effort expended. This study aims at achieving this time and effort reduction, by advancing automation within the digital forensic investigation process.Using a Design Science research approach, artifacts are designed and developed to address these practical problems. Summarily, the requirements, and architecture of a system for automating digital investigations in highly networked environments are designed. The architecture initially focuses on automation of the identification and acquisition of digital evidence, while later versions focus on full automation and self-organization of devices for all phases of the digital investigation process. Part of the remote evidence acquisition capability of this system architecture is implemented as a proof of concept. The speed and reliability of capturing digital evidence from remote mobile devices over a client-server paradigm is evaluated. A method for the uniform representation and integration of multiple diverse evidence sources for enabling automated correlation, simple reasoning and querying is developed and tested. This method is aimed at automating the analysis phase of digital investigations. Machine Learning (ML)-based triage methods are developed and tested to evaluate the feasibility and performance of using such techniques to automate the identification of priority digital evidence fragments. Models from these ML methods are evaluated in identifying network protocols within DNS tunneled network traffic. A large dataset is also created for future research in ML-based triage for identifying suspicious processes for memory forensics.From an ex ante evaluation, the designed system architecture enables individual devices to participate in the entire digital investigation process, contributing their processing power towards alleviating the burden on the human analyst. Experiments show that remote evidence acquisition of mobile devices over networks is feasible, however a single-TCP-connection paradigm scales poorly. A proof of concept experiment demonstrates the viability of the automated integration, correlation and reasoning over multiple diverse evidence sources using semantic web technologies. Experimentation also shows that ML-based triage methods can enable prioritization of certain digital evidence sources, for acquisition or analysis, with up to 95% accuracy.The artifacts developed in this study provide concrete ways to enhance automation in the digital forensic investigation process to increase the investigation speed and reduce the amount of costly human intervention needed.
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| 41. |
- Dodig-Crnkovic, Gordana, 1955
(författare)
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On the Foundations of Computing. Computing as the Fourth Great Domain of Science
- 2023
-
Ingår i: Global Philosophy. - 2948-152X .- 2948-1538. ; 33:16
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Tidskriftsartikel (refereegranskat)abstract
- This review essay analyzes the book by Giuseppe Primiero, On the foundations of computing. Oxford: Oxford University Press (ISBN 978-0-19-883564-6/hbk; 978-0-19-883565-3/pbk). xix, 296 p. (2020). It gives a critical view from the perspective of physical computing as a foundation of computing and argues that the neglected pillar of material computation (Stepney) should be brought centerstage and computing recognized as the fourth great domain of science (Denning).
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| 42. |
- Aramrattana, Maytheewat, 1988-, et al.
(författare)
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Team Halmstad Approach to Cooperative Driving in the Grand Cooperative Driving Challenge 2016
- 2018
-
Ingår i: IEEE transactions on intelligent transportation systems (Print). - Piscataway, N.J. : Institute of Electrical and Electronics Engineers Inc.. - 1524-9050 .- 1558-0016. ; 19:4, s. 1248-1261
-
Tidskriftsartikel (refereegranskat)abstract
- This paper is an experience report of team Halmstad from the participation in a competition organised by the i-GAME project, the Grand Cooperative Driving Challenge 2016. The competition was held in Helmond, The Netherlands, during the last weekend of May 2016. We give an overview of our car’s control and communication system that was developed for the competition following the requirements and specifications of the i-GAME project. In particular, we describe our implementation of cooperative adaptive cruise control, our solution to the communication and logging requirements, as well as the high level decision making support. For the actual competition we did not manage to completely reach all of the goals set out by the organizers as well as ourselves. However, this did not prevent us from outperforming the competition. Moreover, the competition allowed us to collect data for further evaluation of our solutions to cooperative driving. Thus, we discuss what we believe were the strong points of our system, and discuss post-competition evaluation of the developments that were not fully integrated into our system during competition time. © 2000-2011 IEEE.
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| 43. |
- Ge, Chenjie, 1991, et al.
(författare)
-
Enlarged Training Dataset by Pairwise GANs for Molecular-Based Brain Tumor Classification
- 2020
-
Ingår i: IEEE Access. - 2169-3536 .- 2169-3536. ; 8:1, s. 22560-22570
-
Tidskriftsartikel (refereegranskat)abstract
- This paper addresses issues of brain tumor subtype classification using Magnetic Resonance Images (MRIs) from different scanner modalities like T1 weighted, T1 weighted with contrast-enhanced, T2 weighted and FLAIR images. Currently most available glioma datasets are relatively moderate in size, and often accompanied with incomplete MRIs in different modalities. To tackle the commonly encountered problems of insufficiently large brain tumor datasets and incomplete modality of image for deep learning, we propose to add augmented brain MR images to enlarge the training dataset by employing a pairwise Generative Adversarial Network (GAN) model. The pairwise GAN is able to generate synthetic MRIs across different modalities. To achieve the patient-level diagnostic result, we propose a post-processing strategy to combine the slice-level glioma subtype classification results by majority voting. A two-stage course-to-fine training strategy is proposed to learn the glioma feature using GAN-augmented MRIs followed by real MRIs. To evaluate the effectiveness of the proposed scheme, experiments have been conducted on a brain tumor dataset for classifying glioma molecular subtypes: isocitrate dehydrogenase 1 (IDH1) mutation and IDH1 wild-type. Our results on the dataset have shown good performance (with test accuracy 88.82%). Comparisons with several state-of-the-art methods are also included.
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| 44. |
- Rajashekarappa, Mohan, et al.
(författare)
-
A Data-Driven Approach to Air Leakage Detection in Pneumatic Systems
- 2021
-
Ingår i: 2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing). - : IEEE. - 9781665401319 - 9781665401302 - 9781665429795
-
Konferensbidrag (refereegranskat)abstract
- During the transition phase of traditional manufacturing companies towards smart factories, they are likely to experience challenges like lack of prehistoric data recordings or events on which the machine learning models need to be trained. This paper introduces a novel approach of artificially induced anomalies for data labelling. Moreover, for newly installed systems or a setup, which has not seen any kind of malfunction yet, the combination of artificially induced anomalies by experiments and machine learning model help to proactively prepare for any kind of future hindrance of the production systems. Two experiments were performed for detection of air leakage. The first one was designed to identify 'sensitive feature' and understand the behaviour of the sensor readings with respect to different state of the machine. The second one was performed to capture more data points pertaining to leaking state of machine on a normal production day since the first one was conducted on a maintenance break). RUSBoosted bagged trees model was built as a supervised machine-learning model, which was yielded 98.73% accuracy, 99.40% precision, recall of 99.21%, and F1 score of 99.30% on test data for detecting pneumatic leakage. As a conclusion, previously unknown hidden patterns and insights regarding temperature feature along with a standardized and systematic methodology are the important deliverables of this study.
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| 45. |
- Bainomugisha, Engineer, et al.
(författare)
-
Message from Chairs of SEiA 2018
- 2018
-
Ingår i: Proceedings - International Conference on Software Engineering. - New York, NY, USA : ACM. - 0270-5257. ; 2018, s. x-xi
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)
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| 46. |
- Javed, Muhammad, et al.
(författare)
-
Safe and secure platooning of Automated Guided Vehicles in Industry 4.0
- 2021
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Ingår i: Journal of systems architecture. - Sweden : Elsevier B.V.. - 1383-7621 .- 1873-6165. ; 121
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Tidskriftsartikel (refereegranskat)abstract
- Automated Guided Vehicles (AGVs) are widely used for materials transportation. Operating them in a platooned manner has the potential to improve safety, security and efficiency, control overall traffic flow and reduce resource usage. However, the published studies on platooning focus mainly on the design of technical solutions in the context of automotive domain. In this paper we focus on a largely unexplored theme of platooning in production sites transformed to the Industry 4.0, with the aim of providing safety and security assurances. We present an overall approach for a fault- and threat tolerant platooning for materials transportation in production environments. Our functional use cases include the platoon control for collision avoidance, data acquisition and processing by considering range, and connectivity with fog and cloud levels. To perform the safety and security analyses, the Hazard and Operability (HAZOP) and Threat and Operability (THROP) techniques are used. Based on the results obtained from them, the safety and security requirements are derived for the identification and prevention/mitigation of potential platooning hazards, threats and vulnerabilities. The assurance cases are constructed to show the acceptable safety and security of materials transportation using AGV platooning. We leveraged a simulation-based digital twin for performing the verification and validation as well as finetuning of the platooning strategy. Simulation data is gathered from digital twin to monitor platoon operations, identify unexpected or incorrect behaviour, evaluate the potential implications, trigger control actions to resolve them, and continuously update assurance cases. The applicability of the AGV platooning is demonstrated in the context of a quarry site. © 2021 The Authors
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| 47. |
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| 48. |
- Taheri, Javid, et al.
(författare)
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Using Machine Learning to Predict the Exact Resource Usage of Microservice Chains
- 2023
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Ingår i: 16th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2023<em></em>. - New York : Association for Computing Machinery, Inc. - 9798400702341
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Konferensbidrag (refereegranskat)abstract
- Cloud computing offers a wide range of services, but it comes with some challenges. One of these challenges is to predict the resource utilization of the nodes that run applications and services. This is especially relevant for container-based platforms such as Kubernetes. Predicting the resource utilization of a Kubernetes cluster can help optimize the performance, reliability, and cost-effectiveness of the platform. This paper focuses on how well different resources in a cluster can be predicted using machine learning techniques. The approach consists of three main steps: data collection and extraction, data pre-processing and analysis, and resource prediction. The data collection step involves stressing the system with a load-generator (called Locust) and collecting data from Locust and Kubernetes with the use of Prometheus. The data pre-processing and extraction step involves extracting relevant data and transforming it into a suitable format for the machine learning models. The final step involves applying different machine learning models to the data and evaluating their accuracy. The results illustrate that different machine learning techniques can predict resources accurately.
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| 49. |
- Lv, Zhihan, Dr. 1984-, et al.
(författare)
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5G for mobile augmented reality
- 2022
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Ingår i: International Journal of Communication Systems. - : John Wiley & Sons. - 1074-5351 .- 1099-1131. ; 35:5
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 50. |
- Abarenkov, Kessy, et al.
(författare)
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Protax-fungi: A web-based tool for probabilistic taxonomic placement of fungal internal transcribed spacer sequences
- 2018
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Ingår i: New Phytologist. - : Wiley. - 0028-646X .- 1469-8137. ; 220:2, s. 517-525
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Tidskriftsartikel (refereegranskat)abstract
- © 2018 New Phytologist Trust. Incompleteness of reference sequence databases and unresolved taxonomic relationships complicates taxonomic placement of fungal sequences. We developed Protax-fungi, a general tool for taxonomic placement of fungal internal transcribed spacer (ITS) sequences, and implemented it into the PlutoF platform of the UNITE database for molecular identification of fungi. With empirical data on root- and wood-associated fungi, Protax-fungi reliably identified (with at least 90% identification probability) the majority of sequences to the order level but only around one-fifth of them to the species level, reflecting the current limited coverage of the databases. Protax-fungi outperformed the Sintax and Rdb classifiers in terms of increased accuracy and decreased calibration error when applied to data on mock communities representing species groups with poor sequence database coverage. We applied Protax-fungi to examine the internal consistencies of the Index Fungorum and UNITE databases. This revealed inconsistencies in the taxonomy database as well as mislabelling and sequence quality problems in the reference database. The according improvements were implemented in both databases. Protax-fungi provides a robust tool for performing statistically reliable identifications of fungi in spite of the incompleteness of extant reference sequence databases and unresolved taxonomic relationships.
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