| 1. |
- 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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| 2. |
- 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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| 3. |
- 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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| 4. |
- 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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| 5. |
- Bergström, Gustav, et al.
(författare)
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Evaluating the layout quality of UML class diagrams using machine learning
- 2022
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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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| 6. |
- Brunetta, Carlo, 1992
(författare)
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Cryptographic Tools for Privacy Preservation
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Data permeates every aspect of our daily life and it is the backbone of our digitalized society. Smartphones, smartwatches and many more smart devices measure, collect, modify and share data in what is known as the Internet of Things. Often, these devices don’t have enough computation power/storage space thus out-sourcing some aspects of the data management to the Cloud. Outsourcing computation/storage to a third party poses natural questions regarding the security and privacy of the shared sensitive data. Intuitively, Cryptography is a toolset of primitives/protocols of which security prop- erties are formally proven while Privacy typically captures additional social/legislative requirements that relate more to the concept of “trust” between people, “how” data is used and/or “who” has access to data. This thesis separates the concepts by introducing an abstract model that classifies data leaks into different types of breaches. Each class represents a specific requirement/goal related to cryptography, e.g. confidentiality or integrity, or related to privacy, e.g. liability, sensitive data management and more. The thesis contains cryptographic tools designed to provide privacy guarantees for different application scenarios. In more details, the thesis: (a) defines new encryption schemes that provide formal privacy guarantees such as theoretical privacy definitions like Differential Privacy (DP), or concrete privacy-oriented applications covered by existing regulations such as the European General Data Protection Regulation (GDPR); (b) proposes new tools and procedures for providing verifiable computation’s guarantees in concrete scenarios for post-quantum cryptography or generalisation of signature schemes; (c) proposes a methodology for utilising Machine Learning (ML) for analysing the effective security and privacy of a crypto-tool and, dually, proposes a secure primitive that allows computing specific ML algorithm in a privacy-preserving way; (d) provides an alternative protocol for secure communication between two parties, based on the idea of communicating in a periodically timed fashion.
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| 7. |
- Rafiq, Y., et al.
(författare)
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Learning to Share: Engineering Adaptive Decision-Support for Online Social Networks
- 2017
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Ingår i: PROCEEDINGS OF THE 2017 32ND IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING (ASE'17). - 1527-1366. - 9781538626849 ; , s. 280-285
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Some online social networks (OSNs) allow users to define friendship-groups as reusable shortcuts for sharing information with multiple contacts. Posting exclusively to a friendship-group gives some privacy control, while supporting communication with (and within) this group. However, recipients of such posts may want to reuse content for their own social advantage, and can bypass existing controls by copy-pasting into a new post; this cross-posting poses privacy risks. This paper presents a learning to share approach that enables the incorporation of more nuanced privacy controls into OSNs. Specifically, we propose a reusable, adaptive software architecture that uses rigorous runtime analysis to help OSN users to make informed decisions about suitable audiences for their posts. This is achieved by supporting dynamic formation of recipient-groups that benefit social interactions while reducing privacy risks. We exemplify the use of our approach in the context of Facebook.
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| 8. |
- Tsaloli, Georgia, 1993
(författare)
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Secure and Privacy-Preserving Cloud-Assisted Computing
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Smart devices such as smartphones, wearables, and smart appliances collect significant amounts of data and transmit them over the network forming the Internet of Things (IoT). Many applications in our daily lives (e.g., health, smart grid, traffic monitoring) involve IoT devices that often have low computational capabilities. Subsequently, powerful cloud servers are employed to process the data collected from these devices. Nevertheless, security and privacy concerns arise in cloud-assisted computing settings. Collected data can be sensitive, and it is essential to protect their confidentiality. Additionally, outsourcing computations to untrusted cloud servers creates the need to ensure that servers perform the computations as requested and that any misbehavior can be detected, safeguarding security. Cryptographic primitives and protocols are the foundation to design secure and privacy-preserving solutions that address these challenges. This thesis focuses on providing privacy and security guarantees when outsourcing heavy computations on sensitive data to untrusted cloud servers. More concretely, this work: (a) provides solutions for outsourcing the secure computation of the sum and the product functions in the multi-server, multi-client setting, protecting the sensitive data of the data owners, even against potentially untrusted cloud servers; (b) provides integrity guarantees for the proposed protocols, by enabling anyone to verify the correctness of the computed function values. More precisely, the employed servers or the clients (depending on the proposed solution) provide specific values which are the proofs that the computed results are correct; (c) designs decentralized settings, where multiple cloud servers are employed to perform the requested computations as opposed to relying on a single server that might fail or lose connection; (d) suggests ways to protect individual privacy and provide integrity. More pre- cisely, we propose a verifiable differentially private solution that provides verifiability and avoids any leakage of information regardless of the participa- tion of some individual’s sensitive data in the computation or not.
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| 9. |
- 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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| 10. |
- John, Meenu Mary, et al.
(författare)
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Towards an AI-driven business development framework: A multi-case study
- 2023
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Ingår i: Journal of Software: Evolution and Process. - : Wiley. - 2047-7481 .- 2047-7473. ; 35:6
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Tidskriftsartikel (refereegranskat)abstract
- Artificial intelligence (AI) and the use of machine learning (ML) and deep learning (DL) technologies are becoming increasingly popular in companies. These technologies enable companies to leverage big quantities of data to improve system performance and accelerate business development. However, despite the appeal of ML/DL, there is a lack of systematic and structured methods and processes to help data scientists and other company roles and functions to develop, deploy and evolve models. In this paper, based on multi-case study research in six companies, we explore practices and challenges practitioners experience in developing ML/DL models as part of large software-intensive embedded systems. Based on our empirical findings, we derive a conceptual framework in which we identify three high-level activities that companies perform in parallel with the development, deployment and evolution of models. Within this framework, we outline activities, iterations and triggers that optimize model design as well as roles and company functions. In this way, we provide practitioners with a blueprint for effectively integrating ML/DL model development into the business to achieve better results than other (algorithmic) approaches. In addition, we show how this framework helps companies solve the challenges we have identified and discuss checkpoints for terminating the business case.
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