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  • 1.
    Abdelraouf, Hussein
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    LARGE LANGUAGE MODELS ADAPTED TO SWEDISH OF THE 1920S2023Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Large Language Models typically perform best when there is a lot of data to train on. An interesting question is how such models perform in less dominant languages (e.g., Swedish) and over domains of historical interest where less modern words and phrasings are used. Specifically, how can existing language models for current usage be adapted to get the best question-answering results when applied over such historical domains? In this Master's thesis, we will use domain adaption on three different pre-trained Swedish NLP language models: BERT base Swedish Cased SQuAD Experimental, GPT-SW3, and IBM Watson. We will fine-tune these models on the specific domain of Vasaloppet's 100-year-old articles to evaluate if the models will have difficulties predicting results from a Swedish source that is a century old. We will evaluate how well these models perform on question answering and report results and lessons learned. 

  • 2. Abdulla, Parosh Aziz
    et al.
    Högberg, Johanna
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Kaati, Lisa
    Bisimulation minimization of tree automata2007Inngår i: International Journal of Foundations of Computer Science, ISSN 0129-0541, Vol. 18, nr 4, s. 699-713Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We extend an algorithm by Paige and Tarjan that solves the coarsest stable refinement problem to the domain of trees. The algorithm is used to minimize nondeterministic tree automata (NTA) with respect to bisimulation. We show that our algorithm has an overall complexity of $O(\hat{r} m \log n)$, where $\hat{r}$ is the maximum rank of any symbol in the input alphabet, m is the total size of the transition table, and n is the number of states.

  • 3. Abdulla, Parosh Aziz
    et al.
    Katti, Lisa
    Högberg, Johanna
    Umeå universitet, Teknisk-naturvetenskaplig fakultet, Institutionen för datavetenskap.
    Bisimulation minimization of tree automata2006Inngår i: Implementation and Application of Automata : 11th International Conference, CIAA 2006, 2006, s. 699-713Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We extend an algorithm by Paige and Tarjan that solves the coarsest stable refinement problem to the domain of trees. The algorithm is used to minimize nondeterministic tree automata (NTA) with respect to bisimulation. We show that our algorithm has an overall complexity of O ((r) over cap log n), where (r) over cap is the maximum rank of any symbol in the input alphabet, m is the total size of the transition table, and n is the number of states.

  • 4.
    Abedan Kondori, Farid
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Yousefi, Shahrouz
    Ostovar, Ahmad
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Liu, Li
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
    Li, Haibo
    A Direct Method for 3D Hand Pose Recovery2014Inngår i: 22nd International Conference on Pattern Recognition, 2014, s. 345-350Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper presents a novel approach for performing intuitive 3D gesture-based interaction using depth data acquired by Kinect. Unlike current depth-based systems that focus only on classical gesture recognition problem, we also consider 3D gesture pose estimation for creating immersive gestural interaction. In this paper, we formulate gesture-based interaction system as a combination of two separate problems, gesture recognition and gesture pose estimation. We focus on the second problem and propose a direct method for recovering hand motion parameters. Based on the range images, a new version of optical flow constraint equation is derived, which can be utilized to directly estimate 3D hand motion without any need of imposing other constraints. Our experiments illustrate that the proposed approach performs properly in real-time with high accuracy. As a proof of concept, we demonstrate the system performance in 3D object manipulation. This application is intended to explore the system capabilities in real-time biomedical applications. Eventually, system usability test is conducted to evaluate the learnability, user experience and interaction quality in 3D interaction in comparison to 2D touch-screen interaction.

  • 5.
    Abedin, Md Reaz Ashraful
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Bensch, Suna
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hellström, Thomas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Self-supervised language grounding by active sensing combined with Internet acquired images and text2017Inngår i: Proceedings of the Fourth International Workshop on Recognition and Action for Scene Understanding (REACTS2017) / [ed] Jorge Dias George Azzopardi, Rebeca Marf, Málaga: REACTS , 2017, s. 71-83Konferansepaper (Fagfellevurdert)
    Abstract [en]

    For natural and efficient verbal communication between a robot and humans, the robot should be able to learn names and appearances of new objects it encounters. In this paper we present a solution combining active sensing of images with text based and image based search on the Internet. The approach allows the robot to learn both object name and how to recognise similar objects in the future, all self-supervised without human assistance. One part of the solution is a novel iterative method to determine the object name using image classi- fication, acquisition of images from additional viewpoints, and Internet search. In this paper, the algorithmic part of the proposed solution is presented together with evaluations using manually acquired camera images, while Internet data was acquired through direct and reverse image search with Google, Bing, and Yandex. Classification with multi-classSVM and with five different features settings were evaluated. With five object classes, the best performing classifier used a combination of Pyramid of Histogram of Visual Words (PHOW) and Pyramid of Histogram of Oriented Gradient (PHOG) features, and reached a precision of 80% and a recall of 78%.

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  • 6.
    Abedin, Reaz Ashraful
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Autonomous Object Category Learning for Service Robots Using Internet Resources2016Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    With the developments in the field of Artificial Intelligence (AI), robots are becoming smarter, more efficient and capable of doing more dififcult tasks than before. Recent progress in Machine Learning has revolutionized the field of AI. Rather than performing pre-programmed tasks, nowadays robots are learning things, and becoming more autonomous along the way. However, in most of the cases, robots need a certain level of human assistance to learn something. To recognize or classify daily objects is a very important skill that a service robot should possess. In this research work, we have implemented a fully autonomous object category learning system for service robots, where the robot uses internet resources to learn object categories. It gets the name of an unknown object by performing reverse image search in the internet search engines, and applying a verification strategy afterwards. Then the robot retrieves a number of images of that object from internet and use those to generate training data for learning classifiers. The implemented system is tested in actual domestic environment. The classification performance is examined against some object categories from a benchmark dataset. The system performed decently with 78:40% average accuracy on ve object categories taken from the benchmark dataset and showed promising results in real domestic scenarios. There are existing research works that deal with object category learning for robots using internet images. But those works use Human-in-the-loop models, where humans assist the robot to get the object name for using it as a search cue to retrieve training images from internet. Our implemented system eliminates the necessity of human assistance by making the task of object name determination automatic. This facilitates the whole process of learning object categories with full autonomy, which is the main contribution of this research.

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  • 7. Adams, R.
    et al.
    Fincher, S.
    Pears, A.
    Börstler, Jürgen
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Bousted, J.
    Dalenius, P.
    Eken, G.
    Heyer, T.
    Jacobsson, A.
    Lindberg, V.
    Molin, B.
    Moström, J.-E.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Wiggberg, M.
    What is the Word for Engineering in Swedish: Swedish Students' Conceptions of their Discipline2007Rapport (Annet vitenskapelig)
  • 8.
    Adewole, Kayode S.
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Department of Computer Science, University of Ilorin, Ilorin, Nigeria.
    Torra, Vicenç
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    DFTMicroagg: a dual-level anonymization algorithm for smart grid data2022Inngår i: International Journal of Information Security, ISSN 1615-5262, E-ISSN 1615-5270, Vol. 21, s. 1299-1321Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The introduction of advanced metering infrastructure (AMI) smart meters has given rise to fine-grained electricity usage data at different levels of time granularity. AMI collects high-frequency daily energy consumption data that enables utility companies and data aggregators to perform a rich set of grid operations such as demand response, grid monitoring, load forecasting and many more. However, the privacy concerns associated with daily energy consumption data has been raised. Existing studies on data anonymization for smart grid data focused on the direct application of perturbation algorithms, such as microaggregation, to protect the privacy of consumers. In this paper, we empirically show that reliance on microaggregation alone is not sufficient to protect smart grid data. Therefore, we propose DFTMicroagg algorithm that provides a dual level of perturbation to improve privacy. The algorithm leverages the benefits of discrete Fourier transform (DFT) and microaggregation to provide additional layer of protection. We evaluated our algorithm on two publicly available smart grid datasets with millions of smart meters readings. Experimental results based on clustering analysis using k-Means, classification via k-nearest neighbor (kNN) algorithm and mean hourly energy consumption forecast using Seasonal Auto-Regressive Integrated Moving Average with eXogenous (SARIMAX) factors model further proved the applicability of the proposed method. Our approach provides utility companies with more flexibility to control the level of protection for their published energy data.

    Fulltekst (pdf)
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  • 9.
    Adewole, Kayode S.
    et al.
    Department of Computer Science and Media Technology, Malmö University, Sweden; Department of Computer Science, University of Ilorin, Ilorin, Nigeria.
    Torra, Vicenç
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Energy disaggregation risk resilience through microaggregation and discrete Fourier transform2024Inngår i: Information Sciences, ISSN 0020-0255, E-ISSN 1872-6291, Vol. 662, artikkel-id 120211Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Progress in the field of Non-Intrusive Load Monitoring (NILM) has been attributed to the rise in the application of artificial intelligence. Nevertheless, the ability of energy disaggregation algorithms to disaggregate different appliance signatures from aggregated smart grid data poses some privacy issues. This paper introduces a new notion of disclosure risk termed energy disaggregation risk. The performance of Sequence-to-Sequence (Seq2Seq) NILM deep learning algorithm along with three activation extraction methods are studied using two publicly available datasets. To understand the extent of disclosure, we study three inference attacks on aggregated data. The results show that Variance Sensitive Thresholding (VST) event detection method outperformed the other two methods in revealing households' lifestyles based on the signature of the appliances. To reduce energy disaggregation risk, we investigate the performance of two privacy-preserving mechanisms based on microaggregation and Discrete Fourier Transform (DFT). Empirically, for the first scenario of inference attack on UK-DALE, VST produces disaggregation risks of 99%, 100%, 89% and 99% for fridge, dish washer, microwave, and kettle respectively. For washing machine, Activation Time Extraction (ATE) method produces a disaggregation risk of 87%. We obtain similar results for other inference attack scenarios and the risk reduces using the two privacy-protection mechanisms.

    Fulltekst (pdf)
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  • 10.
    Adewole, Kayode Sakariyah
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Department of Computer Science, University of Ilorin, Ilorin, Nigeria.
    Torra, Vicenç
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Privacy issues in smart grid data: from energy disaggregation to disclosure risk2022Inngår i: Database and expert systems applications: 33rd international conference, DEXA 2022, Vienna, Austria, August 22–24, 2022, proceedings, part I / [ed] Christine Strauss; Alfredo Cuzzocrea; Gabriele Kotsis; A Min Tjoa; Ismail Khalil, Springer, 2022, s. 71-84Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The advancement in artificial intelligence (AI) techniques has given rise to the success rate recorded in the field of Non-Intrusive Load Monitoring (NILM). The development of robust AI and machine learning algorithms based on deep learning architecture has enabled accurate extraction of individual appliance load signature from aggregated energy data. However, the success rate of NILM algorithm in disaggregating individual appliance load signature in smart grid data violates the privacy of the individual household lifestyle. This paper investigates the performance of Sequence-to-Sequence (Seq2Seq) deep learning NILM algorithm in predicting the load signature of appliances. Furthermore, we define a new notion of disclosure risk to understand the risk associated with individual appliances in aggregated signals. Two publicly available energy disaggregation datasets have been considered. We simulate three inference attack scenarios to better ascertain the risk of publishing raw energy data. In addition, we investigate three activation extraction methods for appliance event detection. The results show that the disclosure risk associated with releasing smart grid data in their original form is on the high side. Therefore, future privacy protection mechanisms should devise efficient methods to reduce this risk.

  • 11.
    Adewole, Kayode Sakariyah
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Department of Computer Science and Media Technology, Malmö University, Malmö, Sweden; Department of Computer Science, University of Ilorin, Ilorin, Nigeria.
    Torra, Vicenç
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Department of Computer Science and Media Technology, Malmö University, Malmö, Sweden.
    Privacy protection of synthetic smart grid data simulated via generative adversarial networks2023Inngår i: Proceedings of the 20th international conference on security and cryptography, SECRYPT 2023 / [ed] DiVimercati, SD; Samarati, P, SciTePress, 2023, s. 279-286Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The development in smart meter technology has made grid operations more efficient based on fine-grained electricity usage data generated at different levels of time granularity. Consequently, machine learning algorithms have benefited from these data to produce useful models for important grid operations. Although machine learning algorithms need historical data to improve predictive performance, these data are not readily available for public utilization due to privacy issues. The existing smart grid data simulation frameworks generate grid data with implicit privacy concerns since the data are simulated from a few real energy consumptions that are publicly available. This paper addresses two issues in smart grid. First, it assesses the level of privacy violation with the individual household appliances based on synthetic household aggregate loads consumption. Second, based on the findings, it proposes two privacy-preserving mechanisms to reduce this risk. Three inference attacks are simulated and the results obtained confirm the efficacy of the proposed privacy-preserving mechanisms.

    Fulltekst (pdf)
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  • 12.
    Adlerborn, Björn
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Parallel Algorithms and Library Software for the Generalized Eigenvalue Problem on Distributed Memory Computer Systems2016Licentiatavhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    We present and discuss algorithms and library software for solving the generalized non-symmetric eigenvalue problem (GNEP) on high performance computing (HPC) platforms with distributed memory. Such problems occur frequently in computational science and engineering, and our contributions make it possible to solve GNEPs fast and accurate in parallel using state-of-the-art HPC systems. A generalized eigenvalue problem corresponds to finding scalars y and vectors x such that Ax = yBx, where A and B are real square matrices. A nonzero x that satisfies the GNEP equation is called an eigenvector of the ordered pair (A,B), and the scalar y is the associated eigenvalue. Our contributions include parallel algorithms for transforming a matrix pair (A,B) to a generalized Schur form (S,T), where S is quasi upper triangular and T is upper triangular. The eigenvalues are revealed from the diagonals of S and T. Moreover, for a specified set of eigenvalues an associated pair of deflating subspaces can be computed, which typically is requested in various applications. In the first stage the matrix pair (A,B) is reduced to a Hessenberg-triangular form (H,T), where H is upper triangular with one nonzero subdiagonal and T is upper triangular, in a finite number of steps. The second stage reduces the matrix pair further to generalized Schur form (S,T) using an iterative QZ-based method. Outgoing from a one-stage method for the reduction from (A,B) to (H,T), a novel parallel algorithm is developed. In brief, a delayed update technique is applied to several partial steps, involving low level operations, before associated accumulated transformations are applied in a blocked fashion which together with a wave-front task scheduler makes the algorithm scale when running in a parallel setting. The potential presence of infinite eigenvalues makes a generalized eigenvalue problem ill-conditioned. Therefore the parallel algorithm for the second stage, reduction to (S,T) form, continuously scan for and robustly deflate infinite eigenvalues. This will reduce the impact so that they do not interfere with other real eigenvalues or are misinterpreted as real eigenvalues. In addition, our parallel iterative QZ-based algorithm makes use of multiple implicit shifts and an aggressive early deflation (AED) technique, which radically speeds up the convergence. The multi-shift strategy is based on independent chains of so called coupled bulges and computational windows which is an important source of making the algorithm scalable. The parallel algorithms have been implemented in state-of-the-art library software. The performance is demonstrated and evaluated using up to 1600 CPU cores for problems with matrices as large as 100000 x 100000. Our library software is described in a User Guide. The software is, optionally, tunable via a set of parameters for various thresholds and buffer sizes etc. These parameters are discussed, and recommended values are specified which should result in reasonable performance on HPC systems similar to the ones we have been running on.

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  • 13.
    Adlerborn, Björn
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Karlsson, Lars
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Kågström, Bo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Distributed one-stage Hessenberg-triangular reduction with wavefront scheduling2018Inngår i: SIAM Journal on Scientific Computing, ISSN 1064-8275, E-ISSN 1095-7197, Vol. 40, nr 2, s. C157-C180Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A novel parallel formulation of Hessenberg-triangular reduction of a regular matrix pair on distributed memory computers is presented. The formulation is based on a sequential cacheblocked algorithm by K degrees agstrom et al. [BIT, 48 (2008), pp. 563 584]. A static scheduling algorithm is proposed that addresses the problem of underutilized processes caused by two-sided updates of matrix pairs based on sequences of rotations. Experiments using up to 961 processes demonstrate that the new formulation is an improvement of the state of the art and also identify factors that limit its scalability.

  • 14.
    Adlerborn, Björn
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Kjelgaard Mikkelsen, Carl Christian
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Karlsson, Lars
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Kågström, Bo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Towards Highly Parallel and Compute-Bound Computation of Eigenvectors of Matrices in Schur Form2017Rapport (Annet vitenskapelig)
    Abstract [en]

    In this paper we discuss the problem of computing eigenvectors for matrices in Schur form using parallel computing. We develop a new parallel algorithm and report on the performance of our MPI based implementation. We have also implemented a new parallel algorithm for scaling during the backsubstitution phase. We have increased the arithmetic intensity by interleaving the compution of several eigenvectors and by merging the backward substitution and the back-transformation of the eigenvector computation.

    Fulltekst (pdf)
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  • 15.
    Adlerborn, Björn
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Kågström, Bo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Karlsson, Lars
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Distributed one-stage Hessenberg-triangular reduction with wavefront scheduling2016Rapport (Annet vitenskapelig)
    Abstract [en]

    A novel parallel formulation of Hessenberg-triangular reduction of a regular matrix pair on distributed memory computers is presented. The formulation is based on a sequential cache-blocked algorithm by Kågstrom, Kressner, E.S. Quintana-Ortí, and G. Quintana-Ortí (2008). A static scheduling algorithm is proposed that addresses the problem of underutilized processes caused by two-sided updates of matrix pairs based on sequences of rotations. Experiments using up to 961 processes demonstrate that the new algorithm is an improvement of the state of the art but also identifies factors that currently limit its scalability.

    Fulltekst (pdf)
    fulltext
  • 16.
    Adlerborn, Björn
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Kågström, Bo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Kressner, Daniel
    A parallel QZ algorithm for distributed memory HPC systems2014Inngår i: SIAM Journal on Scientific Computing, ISSN 1064-8275, E-ISSN 1095-7197, Vol. 36, nr 5, s. C480-C503Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Appearing frequently in applications, generalized eigenvalue problems represent one of the core problems in numerical linear algebra. The QZ algorithm of Moler and Stewart is the most widely used algorithm for addressing such problems. Despite its importance, little attention has been paid to the parallelization of the QZ algorithm. The purpose of this work is to fill this gap. We propose a parallelization of the QZ algorithm that incorporates all modern ingredients of dense eigensolvers, such as multishift and aggressive early deflation techniques. To deal with (possibly many) infinite eigenvalues, a new parallel deflation strategy is developed. Numerical experiments for several random and application examples demonstrate the effectiveness of our algorithm on two different distributed memory HPC systems.

  • 17.
    Adlerborn, Björn
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Kågström, Bo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Kressner, Daniel
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Parallel Variants of the Multishift QZ Algorithm with Advanced Deflation Techniques2007Inngår i: Applied Parallel Computing - State of the Art in Scientific Computing: 8th International Workshop, PARA 2006, Springer , 2007, s. 117-126Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The QZ algorithm reduces a regular matrix pair to generalized Schur form, which can be used to address the generalized eigenvalue problem. This paper summarizes recent work on improving the performance of the QZ algorithm on serial machines and work in progress on a novel parallel implementation. In both cases, the QZ iterations are based on chasing chains of tiny bulges. This allows to formulate the majority of the computation in terms of matrix-matrix multiplications, resulting in natural parallelism and better performance on modern computing systems with memory hierarchies. In addition, advanced deflation strategies are used, specifically the so called aggressive early deflation, leading to a considerable convergence acceleration and consequently to a reduction of floating point operations and computing time.

  • 18.
    Adlerborn, Björn
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Kågström, Bo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Högpresterande beräkningscentrum norr (HPC2N).
    Kressner, Daniel
    SB–MATHICSE–ANCHP, EPF Lausanne.
    PDHGEQZ user guide2015Rapport (Annet vitenskapelig)
    Abstract [en]

    Given a general matrix pair (A,B) with real entries, we provide software routines for computing a generalized Schur decomposition (S, T). The real and complex conjugate pairs of eigenvalues appear as 1×1 and 2×2 blocks, respectively, along the diagonals of (S, T) and can be reordered in any order. Typically, this functionality is used to compute orthogonal bases for a pair of deflating subspaces corresponding to a selected set of eigenvalues. The routines are written in Fortran 90 and targets distributed memory machines.

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  • 19.
    af Geijerstam, Klas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    CONGESTION-CONTROLLED AUTOTUNING OF OPENMP PROGRAMS2019Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
    Abstract [en]

    Parallelisation is becoming more and more important as the single core performance increase is stagnating while the amount of cores is increasing with every new generation of hardware. ŒThe traditional approach of manual parallelisation has an alternative in parallel frameworks, such as OpenMP, which can simplify the creation of parallel code. Optimising this code can, however, be cumbersome and difficult. Automating the optimisation or tuning of parallel code and computations is a very interesting alternative to manually optimising algorithms and programs. Previous work has shown that intricate systems can eff‚ectively autotune parallel programs with potentially the same eff‚ectiveness as human experts. ThŒis study suggests using an approach with the main algorithm used inspired from the congestion control algorithms from computer networks, namely AIMD. By applying the algorithm on top of an OpenMP program the parallel parameters such as grain size can be controlled. TheŒe simpli€ed algorithm is shown to be able to achieve a 19% speedup compared to a naive static parallel implementation

    Fulltekst (pdf)
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  • 20.
    af Geijerstam, Klas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Online graph based latency estimation of microservice applications in a FAAS environment2021Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Function-as-a-Service (FaaS) is an increasingly common platform for many kinds of applications and services, replacing the need to maintain and setup hardware or virtual machines to host functionality in the cloud. The billing model for FaaS is commonly based on actual usage, which makes the ability to estimate the performance and latency of an application before invoking it valuable. This thesis evaluates if previously defined algorithms for offline latency estimation, can be adapted to work with online data. Performing online estimation of latency potentially enables cheaper estimations, as no extra executions are neccessary, and latency estimation of applications and functions that can not be executed spu- riously. The experiments show that for a set of test applications, the previously defined algorithms can achieve greater than 95% accuracy, and that a non-graph based estimation using exponential moving average can achieve greater than 98% accuracy. 

    Fulltekst (pdf)
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  • 21.
    Afzaal, Qasim
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ahmad, Usman
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Audio Video Streaming Solution for Bambuser2012Independent thesis Advanced level (degree of Master (One Year)), 10 poäng / 15 hpOppgave
    Abstract [en]

    Audio/Video streaming has widely been used in different applications but the social communication applications have especially raised its usage. The aim of this thesis is to design and develop an improved Audio/Video streaming solution for a Swedish company Bambuser and can easily be extended with new features where necessary. Currently Bambuser is using the Flash Media Server (FMS) for streaming the media, but it is license based and adds the extra cost to the company's budget. It does not support a wide range of platforms (e.g. OpenBSD and various Linux distributions) and also has limited options for the streaming. There is no real time monitoring and controlling functionality, which can show the status of essential services to the user, needed for the streaming (for example if the camera is working, microphone is turned on, battery power status. etc.).

    In order to solve these issues the GStreamer is used, which is an Open source multimedia streaming framework. The GStreamer environment was tested on different Linux distributions. The research and implementation includes the creation of the streaming pipeline and analyzing which options (i.e. GStreamer elements and plugins) are required to stream the media. It also includes the testing of different pipeline parameters (for example video rate, audio rate etc.) and noting their effects in a real working environment. Python binding with GStreamer is used to have better control over the pipeline. Another requirement of this project was to add the functionality of monitoring and control that shows the status of essential services to the user. Implementation of this part is done by using server and client side coding. Further improvements and suggestions are also proposed in this report.

    Fulltekst (pdf)
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  • 22.
    Agarwal, Ayush
    et al.
    Department of Information Technology, Delhi Technological University, Delhi, India.
    Chivukula, Aneesh Sreevallabh
    School of Computer Science, FEIT, University of Technology Sydney, Sydney, Australia.
    Bhuyan, Monowar H.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Jan, Tony
    School of Computer Science, FEIT, University of Technology Sydney, Sydney, Australia.
    Narayan, Bhuva
    School of Communication, FASS, University of Technology Sydney, Sydney, Australia.
    Prasad, Mukesh
    School of Communication, FASS, University of Technology Sydney, Sydney, Australia.
    Identification and Classification of Cyberbullying Posts: A Recurrent Neural Network Approach Using Under-Sampling and Class Weighting2020Inngår i: ICONIP 2020: Neural Information Processing: 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 18–22, 2020, Proceedings, Part V, Thailand: Springer Berlin/Heidelberg, 2020, s. 113-120Konferansepaper (Fagfellevurdert)
    Abstract [en]

    With the number of users of social media and web platforms increasing day-by-day in recent years, cyberbullying has become a ubiquitous problem on the internet. Controlling and moderating these social media platforms manually for online abuse and cyberbullying has become a very challenging task. This paper proposes a Recurrent Neural Network (RNN) based approach for the identification and classification of cyberbullying posts. In highly imbalanced input data, a Tomek Links approach does under-sampling to reduce the data imbalance and remove ambiguities in class labelling. Further, the proposed classification model uses Max-Pooling in combination with Bi-directional Long Short-Term Memory (LSTM) network and attention layers. The proposed model is evaluated using Wikipedia datasets to establish the effectiveness of identifying and classifying cyberbullying posts. The extensive experimental results show that our approach performs well in comparison to competing approaches in terms of precision, recall, with F1 score as 0.89, 0.86 and 0.88, respectively.

  • 23.
    Ahlman Bohm, Jacob
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Minimizing initial margin requirements using computational optimization2023Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Trading contracts with future commitments requires posting a collateral, called initial margin requirement, to cover associated risks. Differences in estimating those risks and varying risk appetites can however lead to identical contracts having different initial margin requirements at different market places. This creates a potential for minimizing those requirements by reallocating contracts.

    The task of minimizing the requirement is identified as a black-box optimization problem with constraints. The aim of this project was to investigate that optimization problem, how it can best be tackled, and comparing different techniques for doing so. Based on the results and obstacles encountered along the way, some guidelines are then outlined to provide assistance for whomever is interested in solving this or similar problems.

    The project consisted both of a literature study to examine existing knowledge within the subject of optimization, and an implementation phase to empirically test how well that knowledge can be put to use in this case. During the latter various algorithms were tested in a number of different scenarios. Focus was put on practical aspects that could be important in a real situation, such as how much they could decrease the initial margin requirement, execution time, and ease of implementation.

    As part of the literature study, three algorithms were found which were evaluated further: simulated annealing, differential evolution, and particle swarm optimization. They all work without prior knowledge of the function to be optimized, and are thus suitable for black-box optimization.

    Results from the implementation part showed largely similar performance between all three algorithms, indicating that other aspects such as ease of implementation or parallelization potential can be more important to consider when choosing which one to use. They were all well able to optimize different portfolios in a number of different cases. However, in more complex situations they required much more time to do so, showing a potential need to speed up the process.

    Fulltekst (pdf)
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  • 24.
    Ahlqvist, Emil
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Implementing a Resume Database with Online Learning to Rank2015Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Learning to Rank is a research area within Machine Learning. It is mainly used in Information Retrieval and has been applied to, among other systems, web search engines and in computational advertising. The purpose of the Learning to Rank model is to rank a list of items, placing the most relevant at the top of the list, according to the users' requirements. Online Learning to Rank is a type of this model, that learns directly from the users' interactions with the system.

    In this thesis a resume database is implemented, where the search engine applies an Online Learning to Rank algorithm, to rank consultant's resumes, when queries with required skills and competences are issued to the system. The implementation of the Resume Database and the ranking algorithm, as well as an evaluation, is presented in this report. Results from the evaluation indicates that the performance of the search engine, with the Online Learning to Rank algorithm, could be desirable in a production environment.

    Fulltekst (pdf)
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  • 25.
    Ahlskog, Johanna
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Human-Multi-Drone Interaction in Search and Rescue Systems under High Cognitive Workload2024Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Unmanned Aerial Vehicles (UAV), often referred to as drones, have seen increased use in search and rescue (SAR) missions. Traditionally, these missions involve manual control of each drone for aerial surveillance. As UAV autonomy progresses, the next phase in drone technology consists of a shift to autonomous collaborative multi-drone operations, where drones function collectively in swarms. A significant challenge lies in designing user interfaces that can effectively support UAV pilots in their mission without an overload of information from each drone and of their surroundings.

    This thesis evaluates important human factors, such as situational awareness (SA) and cognitive workload, within complex search and rescue scenarios, with the goal of increasing trust in multi-drone systems through the design and testing of various components. Conducting these user studies aims to generate insights for the future design of multi-drone systems.

    Two prototypes were developed with a multi-drone user interface, and simulated a stressful search and rescue mission with high cognitive workload. In the second prototype, a heatmap guided UAV pilots based on the lost person model. The prototypes were tested in a conducted user study with experienced UAV pilots in different SAR organizations across Sweden.

    The results showed variability in SA while monitoring drone swarms, depending on user interface components and SA levels. The prototypes caused significant cognitive workload, slightly reduced in the heatmap-equipped prototype. Furthermore, there was a marginal increase in trust observed in the prototype with the heatmap. Notably, a lack of manual control raised challenges for the majority of participants and many desired features were suggested by participants. These early expert insights can serve as a starting point for future development of multi-drone systems.

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  • 26.
    Ahmad, Farooq
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Lindgren, Helena
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Selection of foundational ontology for collaborative knowledge modeling in healthcare domain2010Inngår i: Artificial intelligence: methodology, systems, and applications / [ed] Dicheva, Darina; Dochev, Danail, Springer Berlin/Heidelberg, 2010, s. 261-262Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Ontology design is an important process for structuring knowledge to be reused in different projects in the health domain. In this paper, we describe an ontology design for the collaborative knowledge building system ACKTUS to be used for developing personalized knowledge applications for different domains. Different foundational ontologies were compared with respect to selected criteria considered vital for the project, such as modularity and descriptiveness.

  • 27.
    Ahmad, Sabtain
    et al.
    Vienna University of Technology, Vienna, Austria.
    Aral, Atakan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. University of Vienna, Vienna, Austria.
    Hierarchical federated transfer learning: a multi-cluster approach on the computing continuum2023Inngår i: 2023 international conference on machine learning and applications (ICMLA), IEEE, 2023, s. 1163-1168Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Federated Learning (FL) involves training models over a set of geographically distributed users. We address the problem where a single global model is not enough to meet the needs of geographically distributed heterogeneous clients. This setup captures settings where different groups of users have their own objectives however, users based on geographical location or task similarity, can be grouped together and by inter-cluster knowledge they can leverage the strength in numbers and better generalization in order to perform more efficient FL. We introduce a Hierarchical Multi-Cluster Computing Continuum for Federated Learning Personalization (HC3FL) to cluster similar clients and train one edge model per cluster. HC3FL incorporates federated transfer learning to enhance the performance of edge models by leveraging a global model that captures collective knowledge from all edge models. Furthermore, we introduce dynamic clustering based on task similarity to handle client drift and to dynamically recluster mobile (non-stationary) clients. We evaluate the HC3FL approach through extensive experiments on real-world datasets. The results demonstrate that our approach effectively improves the performance of edge models compared to traditional FL approaches.

  • 28.
    Ahmad, Sabtain
    et al.
    Institute of Information Systems Engineering, Vienna University of Technology, Vienna, Austria.
    Uyanık, Halit
    Department of Computer Engineering, Istanbul Technical University, Istanbul, Turkey.
    Ovatman, Tolga
    Department of Computer Engineering, Istanbul Technical University, Istanbul, Turkey.
    Sandıkkaya, Mehmet Tahir
    Department of Computer Engineering, Istanbul Technical University, Istanbul, Turkey.
    De Maio, Vincenzo
    Institute of Information Systems Engineering, Vienna University of Technology, Vienna, Austria.
    Brandić, Ivona
    Institute of Information Systems Engineering, Vienna University of Technology, Vienna, Austria.
    Aral, Atakan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Sustainable environmental monitoring via energy and information efficient multi-node placement2023Inngår i: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 10, nr 24, s. 22065-22079Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The Internet of Things is gaining traction for sensing and monitoring outdoor environments such as water bodies, forests, or agricultural lands. Sustainable deployment of sensors for environmental sampling is a challenging task because of the spatial and temporal variation of the environmental attributes to be monitored, the lack of the infrastructure to power the sensors for uninterrupted monitoring, and the large continuous target environment despite the sparse and limited sampling locations. In this paper, we present an environment monitoring framework that deploys a network of sensors and gateways connected through low-power, long-range networking to perform reliable data collection. The three objectives correspond to the optimization of information quality, communication capacity, and sustainability. Therefore, the proposed environment monitoring framework consists of three main components: (i) to maximize the information collected, we propose an optimal sensor placement method based on QR decomposition that deploys sensors at information- and communication-critical locations; (ii) to facilitate the transfer of big streaming data and alleviate the network bottleneck caused by low bandwidth, we develop a gateway configuration method with the aim to reduce the deployment and communication costs; and (iii) to allow sustainable environmental monitoring, an energy-aware optimization component is introduced. We validate our method by presenting a case study for monitoring the water quality of the Ergene River in Turkey. Detailed experiments subject to real-world data show that the proposed method is both accurate and efficient in monitoring a large environment and catching up with dynamic changes.

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  • 29.
    Ahmed, Istiak
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    An ensemble learning approach based on decision trees and probabilistic argumentation2020Independent thesis Advanced level (degree of Master (Two Years)), 20hpOppgave
    Abstract [en]

    This research discusses a decision support system that includes different machine learning approaches (e.g. ensemble learning, decision trees) and a symbolic reasoning approach (e.g. argumentation). The purpose of this study is to define an ensemble learning algorithm based on formal argumentation and decision trees. Using a decision tree algorithmas a base learning algorithm and an argumentation framework as a decision fusion technique of an ensemble architecture, the proposed system produces outcomes. The introduced algorithm is a hybrid ensemble learning approach based on a formal argumentation-based method. It is evaluated with sample data sets (e.g. an open-access data set and an extracted data set from ultrasound images) and it provides satisfactory outcomes. This study approaches the problem that is related to an ensemble learning algorithm and a formal argumentation approach. A probabilistic argumentation framework is implemented as a decision fusion in an ensemble learning approach. An open-access library is also developed for the user. The generic version of the library can be used in different purposes.

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  • 30.
    Ahmetaj, Shqiponja
    et al.
    TU Wien, Vienna, Austria; WU Wien, Vienna, Austria.
    David, Robert
    WU Wien, Vienna, Austria; Semantic Web Company, Vienna, Austria.
    Polleres, Axel
    WU Wien, Vienna, Austria; Complexity Science Hub Vienna, Vienna, Austria.
    Šimkus, Mantas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. TU Wien, Vienna, Austria.
    Repairing SHACL constraint violations using answer set programming2022Inngår i: The Semantic Web –ISWC 2022: 21st International Semantic Web Conference, Virtual Event, October 23–27, 2022 : Proceedings / [ed] Ulrike Sattler; Aidan Hogan; Maria Keet; Valentina Presutti; João Paulo A. Almeida; Hideaki Takeda; Pierre Monnin; Giuseppe Pirrò; Claudia d’Amato, Springer, 2022, s. 375-391Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The Shapes Constraint Language (SHACL) is a recent W3C recommendation for validating RDF graphs against shape constraints to be checked on target nodes of the data graph. The standard also describes the notion of validation reports for data graphs that violate given constraints, which aims to provide feedback on how the data graph can be fixed to satisfy the constraints. Since the specification left it open to SHACL processors to define such explanations, a recent work proposed the use of explanations in the style of database repairs, where a repair is a set of additions to or deletions from the data graph so that the resulting graph validates against the constraints. In this paper, we study such repairs for non-recursive SHACL, the largest fragment of SHACL that is fully defined in the specification. We propose an algorithm to compute repairs by encoding the explanation problem – using Answer Set Programming (ASP) – into a logic program, the answer sets of which correspond to (minimal) repairs. We then study a scenario where it is not possible to simultaneously repair all the targets, which may be often the case due to overall unsatisfiability or conflicting constraints. We introduce a relaxed notion of validation, which allows to validate a (maximal) subset of the targets and adapt the ASP translation to take into account this relaxation. Our implementation in Clingo is – to the best of our knowledge – the first implementation of a repair generator for SHACL.

  • 31.
    Ahmetaj, Shqiponja
    et al.
    TU Wien, Austria.
    Löhnert, Bianca
    TU Wien, Austria.
    Ortiz, Magdalena
    TU Wien, Austria.
    Šimkus, Mantas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. TU Wien, Austria.
    Magic Shapes for SHACL Validation2022Inngår i: Proceedings of the VLDB Endowment, E-ISSN 2150-8097, Vol. 15, nr 10, s. 2284-2296Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A key prerequisite for the successful adoption of the Shapes Constraint Language (SHACL)—the W3C standardized constraint language for RDF graphs—is the availability of automated tools that efficiently validate targeted constraints (known as shapes graphs) over possibly very large RDF graphs. There are already significant efforts to produce optimized engines for SHACL validation, but they focus on restricted fragments of SHACL. For unrestricted SHACL, that is SHACL with unrestricted recursion and negation, there is no validator beyond a proof-of-concept prototype, and existing techniques are inherently incompatible with the goal-driven approaches being pursued by existing validators. Instead they require a global computation on the entire data graph that is not only computationally very costly, but also brittle, and can easily result in validation failures due to conflicts that are irrelevant to the validation targets. To address these challenges, we present a ‘magic’ transformation— based on Magic Sets as known from Logic Programming—that transforms a SHACL shapes graph S into a new shapes graph S′ whose validation considers only the relevant neighbourhood of the targeted nodes. The new S′ is equivalent to S whenever there are no conflicts between the constraints and the data, and in case the validation of S fails due to conflicts that are irrelevant to the target, S′ may still admit a lazy, target-oriented validation. We implement the algorithm and run preliminary experiments, showing our approach can be a stepping stone towards validators for full SHACL, and that it can significantly improve the performance of the only prototype validator that currently supports full recursion and negation.

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  • 32.
    Ahmetaj, Shqiponja
    et al.
    Technical University of Vienna, Wien, Austria.
    Ortiz, Magdalena
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Oudshoorn, Anouk M.
    Technical University of Vienna, Wien, Austria.
    Šimkus, Mantas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Reconciling SHACL and ontologies: semantics and validation via rewriting2023Inngår i: Proceedings of the 36th international workshop on Description Logics (DL 2023) / [ed] Oliver Kutz; Carsten Lutz; Ana Ozaki, CEUR-WS , 2023Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This extended abstract summarizes our recent work [1] on SHACL validation in the presence of OWL 2 QL ontologies. To overcome the challenge posed by the non-monotonic behavior of SHACL constraints, we propose a new intuitive validation semantics and a rewriting algorithm that embeds the effects of the ontological axioms into the SHACL constraints. We analyze the complexity of validation in this setting.

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  • 33.
    Ahmetaj, Shqiponja
    et al.
    Tu Wien, Austria.
    Ortiz, Magdalena
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Oudshoorn, Anouk
    Tu Wien, Austria.
    Šimkus, Mantas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Reconciling SHACL and ontologies: semantics and validation via rewriting2023Inngår i: ECAI 2023 / [ed] Kobi Gal; Ann Nowé; Grzegorz J. Nalepa; Roy Fairstein; Roxana Rădulescu, IOS Press, 2023, s. 27-35Konferansepaper (Fagfellevurdert)
    Abstract [en]

    OWL and SHACL are two prominent W3C standards for managing RDF graphs, the data model of the Web. They are used for different purposes and make different assumptions about the completeness of data: SHACL is used for expressing integrity constraints on complete data, while OWL allows inferring implicit facts from incomplete data; SHACL reasoners perform validation, while OWL reasoners do logical inference. Integrating these two tasks into one uniform approach is a relevant but challenging problem. The SHACL standard envisions graph validation in combination with OWL entailment, but it does not provide technical guidance on how to realize this. To address this problem, we propose a new intuitive semantics for validating SHACL constraints with OWL 2 QL ontologies based on a suitable notion of the chase. We propose an algorithm that rewrites a set of recursive SHACL constraints (with stratified negation) and an OWL 2 QL ontology into a stand-alone set of SHACL constraints that preserves validation for every input graph, which can in turn be evaluated using an off-the-shelf SHACL validator. We show that validation in this setting is EXPTIME-complete in combined complexity, but only PTIME-complete in data complexity, i.e., if the constraints and the ontology are fixed.

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  • 34. Aichroth, Patrick
    et al.
    Weigel, Christian
    Kurz, Thomas
    Stadler, Horst
    Drewes, Frank
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Björklund, Johanna
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Schlegel, Kai
    Berndl, Emanuel
    Perez, Antonio
    Bowyer, Alex
    Volpini, Andrea
    MICO - MEDIA IN CONTEXT2015Inngår i: 2015 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 2015Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The abundance of digital content requires cost-effective technologies to extract the hidden meaning from media objects. However, current approaches fail to deal with the challenges related to cross-media analysis, metadata publishing, querying and recommendation that are necessary to overcome this challenge. In this paper, we describe the EU project MICO (Media in Context) which aims to provide the necessary technologies based on open-source software (OSS) core components.

  • 35.
    Aili, Henrik
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Using MPI One-Sided Communication for Parallel Sudoku Solving2023Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
    Abstract [en]

    This thesis investigates the scalability of parallel Sudoku solving using Donald Knuth’s Dancing Links and Algorithm X with two different MPI communication methods: MPI One-Sided Communication and MPI Send-Receive. The study compares the performance of the two communication approaches and finds that MPI One-Sided Communication exhibits better scalability in terms of speedup and efficiency. The research contributes to the understanding of parallel Sudoku solving and provides insights into the suitability of MPI One-Sided Communication for this task. The results highlight the advantages of using MPI One-Sided Communication over MPI Send-Receive, emphasizing its superior performance in parallel Sudoku solving scenarios. This research lays the foundation for future investigations in distributed computing environments and facilitates advancements in parallel Sudoku solving algorithms.

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  • 36.
    Aimaiti, Nuerrennisahan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    A Comparison of Rotation Parameterisations for Bundle Adjustment2015Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Bundle Adjustment is an iterative process where 3D information is estimated from 2D image measurements. Typically, the position of object points are estimated simultaneously with the position and orientation of the cameras. While the object points and camera positions have a straightforward "natural" parameterisation, several possibilities exist for the rotation. In this thesis, seven parameterisation of the rotation were investigated; Euler angles (two variants), the Rodriguez representation, the axis-and-angle representation, unit quaternions, and two variants of the direction cosine matrix (DCM). The Euler and Rodriguez parameterisation are common in photogrammetry and each has three parameters. The other parameterisations have more parameters and one or more constraint between them.

    The parameterisations were analyzed with respect to singularities, i.e. well-defined rotations that do not have any bounded and/or unique set of parameters. Four bundle adjustment experiments were setup, each corresponding to a singularity for one or more parameterisations. A fitth, singularity-free, experiment was also added. The experiments were perturbation studies that investigated the convergence properties of each parameterisation. The unconstrained parameterisations were solved by a damped and undamped Gauss-Newton algorithm, whereas the parameterisations with constraints were solved using damped and undamped algorithms based on the Gauss-Helmert estimation model.

    As expected, the parameterisations corresponding to the constructed singularity had higher failure rates and required more iterations and execution time than the others when it did converge. Excluding their singular cases, the Euler xyz and Rodriguez representations were the fastest with about 37% of the dcm. Of the singularity-free parameterisation, the unit quaternion was the fastest with 79% of the dcm.

    Surprisingly, the undamped bundle algorithms converged more often and faster than the damped bundle algorithms, even close to singularities. However, the undamped convergence was to a higher degree associated with numerical warnings and convergence toward angular values outside the nominal 2 range.

    The results suggest that if singularities are not expected, the Euler xyz and Rodriguez representations are the best of the tested parameterisations. Otherwise, the unit quaternion is the best. As an alternative to the latter case, the switching algorithm by Singla may be used, at the expense of a more complex algorithm.

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  • 37.
    Aimaiti, Nuerrennisahan
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Yan, Xu
    Umeå universitet, Samhällsvetenskapliga fakulteten, Institutionen för informatik.
    Gestire-based Interaction and Implication for the Future2011Independent thesis Advanced level (degree of Master (One Year)), 10 poäng / 15 hpOppgave
    Abstract [en]

    Currently there exists an advanced and natural form of interaction, named gesture-based interaction. It has been applied in some fields successfully, especially in the form of game applications. Although people are filled with wonder at the new interaction, it has not replaced the traditional interaction, like keyboard and mouse. From the user experience point of view, gesture-based interaction has advantages which traditional interactive form cannot offer, but also shortcomings which people seem dissatisfied with. This thesis focuses on expressing user experience of gesture-based interaction by conducting interview method. Finally, this paper presents a new design and tries to find implications for its practical usage in the future.

    Fulltekst (pdf)
    fulltext
  • 38.
    Ait-Mlouk, Addi
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Agouti, Tarik
    Cadi Ayyad university.
    DM-MCDA: A web-based platform for data mining and multiple criteria decision analysis: A case study on road accident2019Inngår i: SoftwareX, E-ISSN 2352-7110, Vol. 10, artikkel-id 100323Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Today's ultra-connected world is generating a huge amount of data stored in databases and cloud environment especially in the era of transportation. These databases need to be processed and analyzed to extract useful information and present it as a valid element for transportation managers for further use, such as road safety, shipping delays, and shipping optimization. The potential of data mining algorithms is largely untapped, this paper shows large-scale techniques such as associations rule analysis, multiple criteria analysis, and time series to improve road safety by identifying hot-spots in advance and giving chance to drivers to avoid the dangers. Indeed, we proposed a framework DM-MCDA based on association rules mining as a preliminary task to extract relationships between variables related to a road accident, and then integrate multiple criteria analysis to help decision-makers to make their choice of the most relevant rules. The developed system is flexible and allows intuitive creation and execution of different algorithms for an extensive range of road traffic topics. DM-MCDA can be expanded with new topics on demand, rendering knowledge extraction more robust and provide meaningful information that could help in developing suitable policies for decision-makers.

    Fulltekst (pdf)
    fulltext
  • 39.
    Ait-Mlouk, Addi
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Jiang, Lili
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    A Web-Based Platform for Mining and Ranking Association Rules2020Inngår i: ECIR 2020: Advances in Information Retrieval / [ed] Lecture Notes in Computer Science, vol 12036. Springer, Springer, 2020, s. 443-448Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this demo, we introduce an interactive system, which effectively applies multiple criteria analysis to rank association rules. We first use association rules techniques to explore the correlations between variables in given data (i.e., database and linked data (LD)), and secondly apply multiple criteria analysis (MCA) to select the most relevant rules according to user preferences. The developed system is flexible and allows intuitive creation and execution of different algorithms for an extensive range of advanced data analysis topics. Furthermore, we demonstrate a case study of association rule mining and ranking on road accident data.

  • 40.
    Ait-Mlouk, Addi
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Jiang, Lili
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    KBot: a Knowledge graph based chatBot for natural language understanding over linked data2020Inngår i: IEEE Access, E-ISSN 2169-3536, Vol. 8, s. 149220-149230Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    With the rapid progress of the semantic web, a huge amount of structured data has become available on the web in the form of knowledge bases (KBs). Making these data accessible and useful for end-users is one of the main objectives of chatbots over linked data. Building a chatbot over linked data raises different challenges, including user queries understanding, multiple knowledge base support, and multilingual aspect. To address these challenges, we first design and develop an architecture to provide an interactive user interface. Secondly, we propose a machine learning approach based on intent classification and natural language understanding to understand user intents and generate SPARQL queries. We especially process a new social network dataset (i.e., myPersonality) and add it to the existing knowledge bases to extend the chatbot capabilities by understanding analytical queries. The system can be extended with a new domain on-demand, flexible, multiple knowledge base, multilingual, and allows intuitive creation and execution of different tasks for an extensive range of topics. Furthermore, evaluation and application cases in the chatbot are provided to show how it facilitates interactive semantic data towards different real application scenarios and showcase the proposed approach for a knowledge graph and data-driven chatbot.

    Fulltekst (pdf)
    fulltext
  • 41.
    Ait-Mlouk, Addi
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Vu, Xuan-Son
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Jiang, Lili
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    WINFRA: A Web-Based Platform for Semantic Data Retrieval and Data Analytics2020Inngår i: Mathematics, E-ISSN 2227-7390, Vol. 8, nr 11, artikkel-id 2090Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Given the huge amount of heterogeneous data stored in different locations, it needs to be federated and semantically interconnected for further use. This paper introduces WINFRA, a comprehensive open-access platform for semantic web data and advanced analytics based on natural language processing (NLP) and data mining techniques (e.g., association rules, clustering, classification based on associations). The system is designed to facilitate federated data analysis, knowledge discovery, information retrieval, and new techniques to deal with semantic web and knowledge graph representation. The processing step integrates data from multiple sources virtually by creating virtual databases. Afterwards, the developed RDF Generator is built to generate RDF files for different data sources, together with SPARQL queries, to support semantic data search and knowledge graph representation. Furthermore, some application cases are provided to demonstrate how it facilitates advanced data analytics over semantic data and showcase our proposed approach toward semantic association rules.

    Fulltekst (pdf)
    fulltext
  • 42.
    Alaa, Alaqra
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    The Thing about gaming experience2013Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Despite the increasing popularity in the academic and practical fields of digital gaming, little has been explored and documented about gaming experience, especially firsthand account. This study uses Bruno Latour’s concept of the Thing while investigating digital gaming experience from frequent gamers’ standpoint using focus groups methodology. Additionally in-depth interviews were conducted with developers in order to gain a business perspective on the status of digital games development with regard to gamers. From the findings, Reality, Game, and Player were identified as agencies and their associations with the experiences of the gamers were gathered in making the Thing about gaming experience a matter of concern providing new meanings and further understandings of the abstract sets of experiences.

    Fulltekst (pdf)
    fulltext
  • 43.
    Alaqra, Alaa
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Cell-phone Travel Planner GUI for SpaceTime2010Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
    Abstract [en]

    Global positioning systems have been having an increasing interest recently and been integrated and used in many applications to service positioning, navigation and travel planning. This project has set to design and test an interface of a travel planner for cell phones. A pre-study was made to investigate other travel planners to help the design of this application that has targeted a user friendly interface that people can use regardless of their background. A special feature, carpooling, has been introduced to ease the environmental, economical, and social aspects of navigation. The test was done as walk-through mockup images case scenarios. The test subjects were pleased with the interface’s friendliness, invoked carpooling issues, presented contradictory opinions regarding the interface's design, and offered future integration with other applications suggestions all of which were discussed. Overall, the test results were positive and few problems with the overall design were identified. A future study with more participants and a deeper analysis of the interface would be one way to further investigate the proposed interface.

    Fulltekst (pdf)
    FULLTEXT01
  • 44.
    Aldahir, Abdulsalam
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    EVALUATION OF THE PERFORMANCE OF WEBGPU IN A CLUSTER OF WEB-BROWSERS FOR SCIENTIFIC COMPUTING2022Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
    Abstract [en]

    The development and wide spread of Internet browsers and technologies make them a tool that can be used for many scientific problems. This raises the question of whether Internet browsers, together with WebGPU and WebRTC, can be used to do scalable computing in a distributed cluster. This thesis answers the question by implementing a peer-to-peer cluster and testing it with two problems, Matrix multiplication and Mandelbrot sets generation. The experimental results show that computing embarrassingly parallel problems are scalable with more than 75% efficiency.

    Fulltekst (pdf)
    fulltext
  • 45.
    Aler Tubella, Andrea
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Barsotti, Flavia
    Strategy Office, ING Analytics, ING Bank, Amsterdam, Netherlands; Institute for Advanced Study (IAS), University of Amsterdam, Amsterdam, Netherlands.
    Koçer, Rüya Gökhan
    Strategy Office, ING Analytics, ING Bank, Amsterdam, Netherlands.
    Mendez, Julian Alfredo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ethical implications of fairness interventions: what might be hidden behind engineering choices?2022Inngår i: Ethics and Information Technology, ISSN 1388-1957, E-ISSN 1572-8439, Vol. 24, nr 1, artikkel-id 12Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The importance of fairness in machine learning models is widely acknowledged, and ongoing academic debate revolves around how to determine the appropriate fairness definition, and how to tackle the trade-off between fairness and model performance. In this paper we argue that besides these concerns, there can be ethical implications behind seemingly purely technical choices in fairness interventions in a typical model development pipeline. As an example we show that the technical choice between in-processing and post-processing is not necessarily value-free and may have serious implications in terms of who will be affected by the specific fairness intervention. The paper reveals how assessing the technical choices in terms of their ethical consequences can contribute to the design of fair models and to the related societal discussions.

    Fulltekst (pdf)
    fulltext
  • 46.
    Aler Tubella, Andrea
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Coelho Mollo, Dimitri
    Umeå universitet, Humanistiska fakulteten, Institutionen för idé- och samhällsstudier.
    Dahlgren, Adam
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Devinney, Hannah
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Dignum, Virginia
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ericson, Petter
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Jonsson, Anna
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Kampik, Timotheus
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. SAP Signavio, Germany.
    Lenaerts, Tom
    Université Libre de Bruxelles, Belgium; University of California, Berkeley, USA.
    Mendez, Julian Alfredo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Nieves, Juan Carlos
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    ACROCPoLis: a descriptive framework for making sense of fairness2023Inngår i: FAccT '23: Proceedings of the 2023 ACM conference on fairness, accountability, and transparency, ACM Digital Library, 2023, s. 1014-1025Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Fairness is central to the ethical and responsible development and use of AI systems, with a large number of frameworks and formal notions of algorithmic fairness being available. However, many of the fairness solutions proposed revolve around technical considerations and not the needs of and consequences for the most impacted communities. We therefore want to take the focus away from definitions and allow for the inclusion of societal and relational aspects to represent how the effects of AI systems impact and are experienced by individuals and social groups. In this paper, we do this by means of proposing the ACROCPoLis framework to represent allocation processes with a modeling emphasis on fairness aspects. The framework provides a shared vocabulary in which the factors relevant to fairness assessments for different situations and procedures are made explicit, as well as their interrelationships. This enables us to compare analogous situations, to highlight the differences in dissimilar situations, and to capture differing interpretations of the same situation by different stakeholders.

    Fulltekst (pdf)
    fulltext
  • 47.
    Aler Tubella, Andrea
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Dignum, Virginia
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    The Glass Box Approach: Verifying Contextual Adherence to Values2019Inngår i: AISafety 2019: Proceedings of the Workshop on Artificial Intelligence Safety 2019co-located with the 28th International Joint Conference on Artificial Intelligence (IJCAI-19) / [ed] Huáscar Espinoza, Han Yu, Xiaowei Huang, Freddy Lecue, Cynthia Chen, José Hernández-Orallo, Seán Ó hÉigeartaigh, Richard Mallah, CEUR-WS , 2019Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Artificial Intelligence (AI) applications are beingused to predict and assess behaviour in multiple domains, such as criminal justice and consumer finance, which directly affect human well-being. However, if AI is to be deployed safely, then people need to understand how the system is interpreting and whether it is adhering to the relevant moral values. Even though transparency is often seen as the requirement in this case, realistically it might notalways be possible or desirable, whereas the needto ensure that the system operates within set moral bounds remains.

    In this paper, we present an approach to evaluate the moral bounds of an AI system based on the monitoring of its inputs and outputs. We place a ‘Glass Box’ around the system by mapping moral values into contextual verifiable norms that constrain inputs and outputs, in such a way that if these remain within the box we can guarantee that the system adheres to the value(s) in a specific context. The focus on inputs and outputs allows for the verification and comparison of vastly different intelligent systems–from deep neural networks to agent-based systems–whereas by making the context explicit we exposethe different perspectives and frameworks that are taken into account when subsuming moral values into specific norms and functionalities. We present a modal logic formalisation of the Glass Box approach which is domain-agnostic, implementable, and expandable.

    Fulltekst (pdf)
    fulltext
  • 48.
    Aler Tubella, Andrea
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Mora-Cantallops, Marçal
    Dpto. Ciencias de la Computación, Universidad de Alcalá, Madrid, Alcalá de Henares, Spain.
    Nieves, Juan Carlos
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    How to teach responsible AI in Higher Education: challenges and opportunities2024Inngår i: Ethics and Information Technology, ISSN 1388-1957, E-ISSN 1572-8439, Vol. 26, nr 1, artikkel-id 3Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In recent years, the European Union has advanced towards responsible and sustainable Artificial Intelligence (AI) research, development and innovation. While the Ethics Guidelines for Trustworthy AI released in 2019 and the AI Act in 2021 set the starting point for a European Ethical AI, there are still several challenges to translate such advances into the public debate, education and practical learning. This paper contributes towards closing this gap by reviewing the approaches that can be found in the existing literature and by interviewing 11 experts across five countries to help define educational strategies, competencies and resources needed for the successful implementation of Trustworthy AI in Higher Education (HE) and to reach students from all disciplines. The findings are presented in the form of recommendations both for educators and policy incentives, translating the guidelines into HE teaching and practice, so that the next generation of young people can contribute to an ethical, safe and cutting-edge AI made in Europe.

    Fulltekst (pdf)
    fulltext
  • 49.
    Aler Tubella, Andrea
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Theodorou, Andreas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Dignum, Frank
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Dignum, Virginia
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Governance by glass-box: implementing transparent moral bounds for AI behaviour2019Inngår i: Proceedings of the 28th International Joint Conference on Artificial Intelligence, 2019, s. 5787-5793Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    Artificial Intelligence (AI) applications are being used to predict and assess behaviour in multiple domains which directly affect human well-being. However, if AI is to improve people’s lives, then people must be able to trust it, by being able to understand what the system is doing and why. Although transparency is often seen as the requirementin this case, realistically it might not always be possible, whereas the need to ensure that the system operates within set moral bounds remains.

    In this paper, we present an approach to evaluate the moral bounds of an AI system based on the monitoring of its inputs and outputs. We place a ‘Glass-Box’ around the system by mapping moral values into explicit verifiable norms that constrain inputs and outputs, in such a way that if these remain within the box we can guarantee that the system adheres to the value. The focus on inputs and outputs allows for the verification and comparison of vastly different intelligent systems; from deep neural networks to agent-based systems.

    The explicit transformation of abstract moral values into concrete norms brings great benefits interms of explainability; stakeholders know exactly how the system is interpreting and employing relevant abstract moral human values and calibrate their trust accordingly. Moreover, by operating at a higher level we can check the compliance of the system with different interpretations of the same value.

  • 50.
    Aler Tubella, Andrea
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Theodorou, Andreas
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Dignum, Virginia
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Michael, Loizos
    Contestable Black Boxes2020Inngår i: Rules and Reasoning. RuleML+RR 2020. / [ed] V. Gutiérrez-Basulto, T. Kliegr, A. Soylu, M. Giese, D. Roman, Springer, 2020, s. 159-167Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The right to contest a decision with consequences on individuals or the society is a well-established democratic right. Despite this right also being explicitly included in GDPR in reference to automated decision-making, its study seems to have received much less attention in the AI literature compared, for example, to the right for explanation. This paper investigates the type of assurances that are needed in the contesting process when algorithmic black boxes are involved, opening new questions about the interplay of contestability and explainability. We argue that specialised complementary methodologies to evaluate automated decision-making in the case of a particular decision being contested need to be developed. Further, we propose a combination of well-established software engineering and rule-based approaches as a possible socio-technical solution to the issue of contestability, one of the new democratic challenges posed by the automation of decision making.

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