| 1. |
- Małyszko, Jolanta, et al.
(författare)
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Do we know more about hypertension in Poland after the May Measurement Month 2017? - Europe
- 2019
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Ingår i: European Heart Journal, Supplement. - : Oxford University Press (OUP). - 1520-765X .- 1554-2815. ; 21, s. 97-100
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Forskningsöversikt (refereegranskat)abstract
- Elevated blood pressure (BP) is a worldwide burden, leading to over 10 million deaths yearly. May Measurement Month (MMM) is a global initiative organized by the International Society of Hypertension aimed at raising awareness of hypertension and the need for BP screening. An opportunistic cross-sectional survey of volunteers aged ≥18 was carried out in May 2017. BP measurement, the definition of hypertension and statistical analysis followed the globally approved MMM17 Study Protocol. In Poland 5834 (98.9%, Caucasian) individuals were screened. After multiple imputation, 2601 (35.3%) had hypertension. Of individuals not receiving anti-hypertensive medication, 976 (20.6%) were hypertensive. Of individuals receiving anti-hypertensive medication, 532 (49.1%) had uncontrolled BP. In the crude screened group, 81.4% declared to not receive any anti-hypertensive treatment, while the remaining 18.6% were on such medications. In overweight and obese patients both systolic and diastolic BP were significantly higher than in normal weight and underweight subjects. In addition, BP measured on Sundays was significantly lower than on Mondays. MMM17 was one of the largest recent BP screening campaigns in Poland. We found that over 1/3 of participants were hypertensive. Almost half of the treated subjects had uncontrolled BP. These results suggest that opportunistic screening can identify substantial numbers with raised BP.
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| 2. |
- Borg, Markus, et al.
(författare)
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Ergo, SMIRK is safe : a safety case for a machine learning component in a pedestrian automatic emergency brake system
- 2023
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Ingår i: Software quality journal. - : Springer. - 0963-9314 .- 1573-1367. ; 31:2, s. 335-
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Tidskriftsartikel (refereegranskat)abstract
- Integration of machine learning (ML) components in critical applications introduces novel challenges for software certification and verification. New safety standards and technical guidelines are under development to support the safety of ML-based systems, e.g., ISO 21448 SOTIF for the automotive domain and the Assurance of Machine Learning for use in Autonomous Systems (AMLAS) framework. SOTIF and AMLAS provide high-level guidance but the details must be chiseled out for each specific case. We initiated a research project with the goal to demonstrate a complete safety case for an ML component in an open automotive system. This paper reports results from an industry-academia collaboration on safety assurance of SMIRK, an ML-based pedestrian automatic emergency braking demonstrator running in an industry-grade simulator. We demonstrate an application of AMLAS on SMIRK for a minimalistic operational design domain, i.e., we share a complete safety case for its integrated ML-based component. Finally, we report lessons learned and provide both SMIRK and the safety case under an open-source license for the research community to reuse. © 2023, The Author(s).
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| 4. |
- Borg, Markus, et al.
(författare)
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Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language Practice
- 2022
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Ingår i: Proceedings - 1st International Conference on AI Engineering - Software Engineering for AI, CAIN 2022. - New York, NY, USA : Institute of Electrical and Electronics Engineers Inc.. - 9781450392754 ; , s. 22-32
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Konferensbidrag (refereegranskat)abstract
- Due to the migration megatrend, efficient and effective second-language acquisition is vital. One proposed solution involves AI-enabled conversational agents for person-centered interactive language practice. We present results from ongoing action research targeting quality assurance of proprietary generative dialog models trained for virtual job interviews. The action team elicited a set of 38 requirements for which we designed corresponding automated test cases for 15 of particular interest to the evolving solution. Our results show that six of the test case designs can detect meaningful differences between candidate models. While quality assurance of natural language processing applications is complex, we provide initial steps toward an automated framework for machine learning model selection in the context of an evolving conversational agent. Future work will focus on model selection in an MLOps setting.
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| 6. |
- Nilsson Tengstrand, Sara, et al.
(författare)
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Challenges of Adopting SAFe in the Banking Industry – A Study Two Years After Its Introduction
- 2021
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Ingår i: XP 2021: Agile Processes in Software Engineering and Extreme Programming.Lecture Notes in Business Information Processing book series (LNBIP, volume 419). - Cham : Springer Science and Business Media Deutschland GmbH. - 1865-1356 .- 1865-1348. - 9783030780975 ; , s. 157-171
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Konferensbidrag (refereegranskat)abstract
- The Scaled Agile Framework (SAFe) is a framework for scaling agile methods in large organizations. We have found several experience reports and white papers describing SAFe adoptions in different banks, which indicates that SAFe is being used in the banking industry. However, there is a lack of academic publications on the topic, the banking industry is missing in the scientific reports analyzing SAFe transformations. To fill this gap, we present a study on the main challenges with a SAFe transformation at a large full-service bank. We identify the challenges in the bank under study and compare the findings with experience reports from other banks, as well as with research on SAFe transformations in other domains. Many of the challenges reported in this paper overlap with the generic SAFe challenges, including management and organization, education and training, culture and mindset, requirements engineering, quality assurance, and systems architecture. However, we also report some novel challenges specific to the banking domain, e.g., the risk of jeopardizing customer relations, stability, and trust of external stakeholders. This study validates several SAFe-related challenges reported in previous work in the banking context. It also brings up some novel challenges specific to the banking industry. Therefore, we believe our results are particularly useful to practitioners responsible for SAFe transformations at other banks. © 2021, The Author(s).
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| 7. |
- Röding, Magnus, et al.
(författare)
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Machine learning-accelerated small-angle X-ray scattering analysis of disordered two- and three-phase materials
- 2022
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Ingår i: Frontiers in Materials. - : Frontiers Media S.A.. - 2296-8016. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- Small-angle X-ray scattering (SAXS) is a useful technique for nanoscale structural characterization of materials. In SAXS, structural and spatial information is indirectly obtained from the scattering intensity in the spectral domain, known as the reciprocal space. Therefore, characterizing the structure requires solving the inverse problem of finding a plausible structure model that corresponds to the measured scattering intensity. Both the choice of structure model and the computational workload of parameter estimation are bottlenecks in this process. In this work, we develop a framework for analysis of SAXS data from disordered materials. The materials are modeled using Gaussian Random Fields (GRFs). We study the case of two phases, pore and solid, and three phases, where a third phase is added at the interface between the two other phases. Further, we develop very fast GPU-accelerated, Fourier transform-based numerical methods for both structure generation and SAXS simulation. We demonstrate that length scales and volume fractions can be predicted with good accuracy using our machine learning-based framework. The parameter prediction executes virtually instantaneously and hence the computational burden of conventional model fitting can be avoided. Copyright © 2022 Röding, Tomaszewski, Yu, Borg and Rönnols.
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| 15. |
- Tomaszewski, Piotr, et al.
(författare)
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Machine Learning-Assisted Analysis of Small Angle X-ray Scattering
- 2021
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Ingår i: 2021 Swedish Workshop on Data Science (SweDS).
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Konferensbidrag (refereegranskat)abstract
- Small angle X-ray scattering (SAXS) is extensively used in materials science as a way of examining nanostructures. The analysis of experimental SAXS data involves mapping a rather simple data format to a vast amount of structural models. Despite various scientific computing tools to assist the model selection, the activity heavily relies on the SAXS analysts’ experience, which is recognized as an efficiency bottleneck by the community. To cope with this decision-making problem, we develop and evaluate the open-source, Machine Learning-based tool SCAN (SCattering Ai aNalysis) to provide recommendations on model selection. SCAN exploits multiple machine learning algorithms and uses models and a simulation tool implemented in the SasView package for generating a well defined set of datasets. Our evaluation shows that SCAN delivers an overall accuracy of 95%-97%. The XGBoost Classifier has been identified as the most accurate method with a good balance between accuracy and training time. With eleven predefined structural models for common nanostructures and an easy draw-drop function to expand the number and types training models, SCAN can accelerate the SAXS data analysis workflow.
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| 16. |
- Tomaszewski, Piotr
(författare)
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Software Development Productivity : Evaluation and Improvement for Large Industrial Projects
- 2006
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Software development productivity can be improved by introducing improvements in many areas. In this thesis we investigate technology and process driven productivity improvements, i.e., productivity improvements that have sources in changes of technologies or in changes in development processes. The technology driven productivity improvement discussed in this thesis is the change of server platform from a standard general purpose platform to a specialized fault-tolerant platform. We discuss productivity implications of introducing such a platform as well as suggest ways of making the platform introduction process cost efficient. The process changes, which we discuss in this thesis, include improvements of fault detection processes as well as changes of the entire development process. We analyze the implications of introducing new technology by performing case studies, in which we describe, analyze, and quantify the impact of the new platform on software development productivity. We show that there is a significant productivity decrease connected with introducing a new platform. We also show that the initial low productivity can be overcome by experience and maturity. We suggest a number of improvements for both the platform introduction process and the mature development on the specialized platform. Since some productivity decrease after introducing new technology is to a large extent unavoidable, we look for ways of minimizing it. We show that it is possible to minimize it by introducing the specialized platform gradually. We present an example of a hybrid architecture, which combines the specialized and the standard platforms. We show that such architecture is able to provide good technical characteristics for a significantly lower cost as compared to developing the entire application on the specialized platform. As a process improvement suggestion we propose introducing fault prediction models with the goal of increasing the efficiency of fault detection. We suggest and evaluate several such models that are available at different stages of a software development process. The models are evaluated using data from a number of large software systems. Their predictions are also compared with the predictions made by human experts. We show that introducing our fault prediction models is likely to result in an improvement of fault detection efficiency. Another process related productivity improvement suggestion evaluated by us is the change of the development process. We present a case study in which we evaluate a new process concept. One of the goals of that process is to improve the company’s productivity.
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| 17. |
- Tomaszewski, Piotr
(författare)
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Software Development Productivity Issues in Large Telecommunication Applications
- 2005
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The high non-functional requirements of telecommunication applications increase their complexity. Introducing a new and specialized technology is often seen as a way of meeting these high non-functional requirements. An example of such a technology is a software platform that provides high performance and availability. The change of technology can, however, impact another important factor of a successful software development – the cost. The cost is mostly affected by the low development productivity when using the new technology. Therefore it is a challenging task to introduce the new technology in a cost-efficient manner. This thesis investigates the software development cost implications of introducing a specialized technology. We present case studies in which we describe, analyse, and quantify the impact of the new platform on software development productivity. By comparing with UNIX development productivity we establish the initial productivity cost of introducing the new platform. We show that there is a significant difference in the productivity between UNIX and the new platform. We analyse and describe the reasons for this difference. By comparing the productivity in early and mature software development on the new platform we investigate which of the problems that cause the initial low productivity tend to disappear with time. We quantify the impact of experience and maturity on the productivity improvement. Based on our findings, we suggest a number of improvements for both the platform introduction process and the mature development on the specialized platform. The initial high development cost on the specialized platform is, however, an unavoidable issue that the organization must face. Therefore we look for a way of decreasing that cost. We show that it is possible to decrease the cost if we introduce the specialized platform gradually, instead of developing the entire application on it. We present an example of a hybrid architecture, which combines the specialized and the standard platforms. We evaluate it with respect to availability, reliability, performance, and cost. We find that such an architecture is able to provide good technical characteristics for a significantly lower cost as compared to developing the entire application on the specialized platform.
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| 18. |
- Tomaszewski, Piotr, et al.
(författare)
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Software Development Productivity on a New Platform : an Industrial Case Study
- 2005
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Ingår i: Information and Software Technology. - : Elsevier. - 0950-5849 .- 1873-6025. ; 47:4, s. 257-269
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Tidskriftsartikel (refereegranskat)abstract
- The high non-functional requirements on mobile telecommunication applications call for new solutions. An example of such a solution can be a software platform that provides high performance and availability. The introduction of such a platform may, however, affect the development productivity. In this study, we present experiences from research carried out at Ericsson. The purpose of the research was productivity improvement and assessment when using the new platform. In this study, we quantify and evaluate the current productivity level by comparing it with UNIX development. The comparison is based on two large, commercially, available systems. We reveal a factor of four differences in productivity. Later, we decompose the problem into two issues: code writing speed and average amount of code necessary to deliver a certain functionality. We assess the impact of both these issues. We describe the nature of the problem by identifying factors that affect productivity and estimating their importance. To the issues identified we suggest a number of remedies. The main methods used in the study are interviews and historical data research. (C) 2004 Elsevier B.V. All rights reserved.
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| 19. |
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| 21. |
- Tomaszewski, Piotr, et al.
(författare)
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The Accuracy of Fault Prediction in Modified Code –Statistical Model vs. Expert Estimation
- 2006
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Konferensbidrag (refereegranskat)abstract
- Fault prediction models still seem to be more popular in academia than in industry. In industry expert estimations of fault proneness are the most popular methods of deciding where to focus the fault defection efforts. In this paper we present a study in which we empirically evaluate the accuracy of fault prediction offered by statistical models as compared to expert estimations. The study is industry based It involves a large telecommunication system and experts that were involved in the development of this system. Expert estimations are compared to simple prediction models built on another large system, also from the telecommunication domain. We show that the statistical methods clearly outperform the expert estimations. As the main reason for the superiority of the statistical models we see their ability to cope with large datasets, which results in their ability to perform reliable predictions for larger number of components in the system, as well as the ability to perform prediction at a more fine-grain level, e.g., at the class instead of at the component level.
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| 22. |
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| 23. |
- Wohlin, Claes, et al.
(författare)
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The success factors powering industry-academia collaboration
- 2011
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Ingår i: IEEE Software. - : IEEE Computer Society. - 0740-7459 .- 1937-4194. ; 29:2, s. 67-73
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Tidskriftsartikel (refereegranskat)abstract
- Collaboration between industry and academia supports improvement and innovation in industry and helps to ensure industrial relevance in academic research. This article presents an exploratory study of the factors for successful collaboration between industry and academia in software research.
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