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| 2. |
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Discrete Geometry and Mathematical Morphology : First International Joint Conference, DGMM 2021, Uppsala, Sweden, May 24–27, 2021, Proceedings
- 2021
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Samlingsverk (redaktörskap) (refereegranskat)abstract
- This book constitutes the proceedings of the First IAPR International Conference on Discrete Geometry and Mathematical Morphology, DGMM 2021, which was held during May 24-27, 2021, in Uppsala, Sweden.The conference was created by joining the International Conference on Discrete Geometry for computer Imagery, DGCI, with the International Symposium on Mathematical Morphology, ISMM.The 36 papers included in this volume were carefully reviewed and selected from 59 submissions. They were organized in topical sections as follows: applications in image processing, computer vision, and pattern recognition; discrete and combinatorial topology; discrete geometry - models, transforms, visualization; discrete tomography and inverse problems; hierarchical and graph-based models, analysis and segmentation; learning-based approaches to mathematical morphology; multivariate and PDE-based mathematical morphology, morphological filtering.The book also contains 3 invited keynote papers.
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| 3. |
- Cheraghchi, M., et al.
(författare)
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Approximating Linear Threshold Predicates
- 2010
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Ingår i: Lecture Notes in Computer Science. 13th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2010 and 14th International Workshop on Randomization and Computation, RANDOM 2010, Barcelona, 1-3 September 2010. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 0302-9743 .- 1611-3349. - 9783642153686 ; 6302, s. 110-123
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Konferensbidrag (refereegranskat)abstract
- We study constraint satisfaction problems on the domain {-1,1}, where the given constraints are homogeneous linear threshold predicates. That is, predicates of the form sgn(w1 x1+⋯+wn x n ) for some positive integer weights w 1, ..., w n . Despite their simplicity, current techniques fall short of providing a classification of these predicates in terms of approximability. In fact, it is not easy to guess whether there exists a homogeneous linear threshold predicate that is approximation resistant or not. The focus of this paper is to identify and study the approximation curve of a class of threshold predicates that allow for non-trivial approximation. Arguably the simplest such predicate is the majority predicate sgn(x 1+⋯+xn ), for which we obtain an almost complete understanding of the asymptotic approximation curve, assuming the Unique Games Conjecture. Our techniques extend to a more general class of "majority-like" predicates and we obtain parallel results for them. In order to classify these predicates, we introduce the notion of Chow-robustness that might be of independent interest.
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| 4. |
- Hedin, Daniel, 1978, et al.
(författare)
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A Principled Approach to Tracking Information Flow in the Presence of Libraries
- 2017
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Berlin, Heidelberg : Springer Berlin Heidelberg. - 1611-3349 .- 0302-9743. - 9783662544549 ; 10204, s. 49-70
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Konferensbidrag (refereegranskat)abstract
- There has been encouraging progress on information flow control for programs in increasingly complex programming languages, tracking the propagation of information from input sources to output sinks. Yet, programs are typically deployed in an environment with rich APIs and powerful libraries, posing challenges for information flow control when the code for these APIs and libraries is either unavailable or written in a different language.This paper presents a principled approach to tracking information flow in the presence of libraries. With the goal to strike the balance between security and precision, we present a framework that explores the middle ground between the “shallow”, signature-based modeling of libraries and the “deep”, stateful approach, where library models need to be supplied manually. We formalize our approach for a core language, extend it with lists and higher-order functions, and establish soundness results with respect to the security condition of noninterference.
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| 7. |
- Kristoffersson, Annica, 1980-, et al.
(författare)
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Sense of presence in a robotic telepresence domain
- 2011
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Ingår i: Universal access in human-computer interaction: users diversity, PT 2. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783642216626 ; , s. 479-487
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Konferensbidrag (refereegranskat)abstract
- Robotic telepresence offers a means to connect to a remote location via traditional telepresence with the added value of moving and actuating in that location. Recently, there has been a growing focus on the use of robotic telepresence to enhance social interaction among elderly. However for such technology to be accepted it is likely that the experienced presence when using such a system will be important. In this paper, we present results obtained from a training session with a robotic telepresence system when used for the first time by healthcare personnel. The study was quantitative and based on two standard questionnaires used for presence namely, the Temple Presence Inventory (TPI) and the Networked Minds Social Presence Intentory. The study showed that overall the sense of social richness as perceived by the users was high. The users also had a realistic feeling regarding their spatial presence.
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| 8. |
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Interactive Storytelling : 16th International Conference on Interactive Digital Storytelling, ICIDS 2023, Kobe, Japan, November 11–15, 2023, Proceedings, Part I
- 2023
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Proceedings (redaktörskap) (refereegranskat)abstract
- This two-volume set LNCS 14383 and LNCS 14384 constitutes the refereed proceedings of the 16th International Conference on Interactive Digital Storytelling, ICIDS 2023, held in Kobe, Japan, during November 11–15, 2023.The 30 full papers presented in this book together with 11 short papers were carefully reviewed and selected from 101 submissions. Additionally, the proceedings includes 22 Late Breaking Works. The papers focus on topics such as: theory, history and foundations; social and cultural contexts; tools and systems; interactive narrative design; virtual worlds, performance, games and play; applications and case studies; and late breaking works.
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| 9. |
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Interactive Storytelling : 16th International Conference on Interactive Digital Storytelling, ICIDS 2023, Kobe, Japan, November 11–15, 2023, Proceedings, Part II
- 2023
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Proceedings (redaktörskap) (refereegranskat)abstract
- This two-volume set LNCS 14383 and LNCS 14384 constitutes the refereed proceedings of the 16th International Conference on Interactive Digital Storytelling, ICIDS 2023, held in Kobe, Japan, during November 11–15, 2023.The 30 full papers presented in this book together with 11 short papers were carefully reviewed and selected from 101 submissions. Additionally, the proceedings includes 22 Late Breaking Works. The papers focus on topics such as: theory, history and foundations; social and cultural contexts; tools and systems; interactive narrative design; virtual worlds, performance, games and play; applications and case studies; and late breaking works.
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| 10. |
- Matić, Teodora, et al.
(författare)
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Unsupervised Learning from Motion Sensor Data to Assess the Condition of Patients with Parkinson’s Disease
- 2019
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Ingår i: AIME 2019. - Cham : Springer. - 9783030216429 - 9783030216412 ; , s. 420-424
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Konferensbidrag (refereegranskat)abstract
- Parkinson’s disease (PD) is a chronic neurodegenerative disorder that predominantly affects the patient’s motor system, resulting in muscle rigidity, bradykinesia, tremor, and postural instability. As the disease slowly progresses, the symptoms worsen, and regular monitoring is required to adjust the treatment accordingly. The objective evaluation of the patient’s condition is sometimes rather difficult and automated systems based on various sensors could be helpful to the physicians. The data in this paper come from a clinical study of 19 advanced PD patients with motor fluctuations. The measurements used come from the motion sensors the patients wore during the study. The paper presents an unsupervised learning approach applied on this data with the aim of checking whether sensor data alone can indicate the patient’s motor state. The rationale for the unsupervised approach is that there was significant inter-physician disagreement on the patient’s condition (target value for supervised machine learning). The input to clustering came from sensor data alone. The resulting clusters were matched against the physicians’ estimates showing relatively good agreement.
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