| 1. |
- Babu, Md Abu Ahammed, 1994, et al.
(författare)
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Impact of Image Data Splitting on the Performance of Automotive Perception Systems
- 2024
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Ingår i: Lecture Notes in Business Information Processing. - 1865-1356 .- 1865-1348. ; 505 LNBIP, s. 91-111
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Konferensbidrag (refereegranskat)abstract
- Context: Training image recognition systems is one of the crucial elements of the AI Engineering process in general and for automotive systems in particular. The quality of data and the training process can have a profound impact on the quality, performance, and safety of automotive software. Objective: Splitting data between train and test sets is one of the crucial elements in this process as it can determine both how well the system learns and generalizes to new data. Typical data splits take into consideration either randomness or timeliness of data points. However, in image recognition systems, the similarity of images is of equal importance. Methods: In this computational experiment, we study the impact of six data-splitting techniques. We use an industrial dataset with high-definition color images of driving sequences to train a YOLOv7 network. Results: The mean average precision (mAP) was 0.943 and 0.841 when the similarity-based and the frame-based splitting techniques were applied, respectively. However, the object-based splitting technique produces the worst mAP score (0.118). Conclusion: There are significant differences in the performance of object detection methods when applying different data-splitting techniques. The most positive results are the random selections, whereas the most objective ones are splits based on sequences that represent different geographical locations.
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| 2. |
- Borg, Markus, et al.
(författare)
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Agility in Software 2.0 – Notebook Interfaces and MLOps with Buttresses and Rebars
- 2022
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Ingår i: International Conference on Lean and Agile Software DevelopmentLASD 2022: Lean and Agile Software Development pp 3-16. - Cham : Springer Science and Business Media Deutschland GmbH. - 1865-1356 .- 1865-1348. - 9783030942373 ; , s. 3-16
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Konferensbidrag (refereegranskat)abstract
- Artificial intelligence through machine learning is increasingly used in the digital society. Solutions based on machine learning bring both great opportunities, thus coined “Software 2.0,” but also great challenges for the engineering community to tackle. Due to the experimental approach used by data scientists when developing machine learning models, agility is an essential characteristic. In this keynote address, we discuss two contemporary development phenomena that are fundamental in machine learning development, i.e., notebook interfaces and MLOps. First, we present a solution that can remedy some of the intrinsic weaknesses of working in notebooks by supporting easy transitions to integrated development environments. Second, we propose reinforced engineering of AI systems by introducing metaphorical buttresses and rebars in the MLOps context. Machine learning-based solutions are dynamic in nature, and we argue that reinforced continuous engineering is required to quality assure the trustworthy AI systems of tomorrow.
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| 3. |
- Borg, Markus, et al.
(författare)
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The AIQ Meta-Testbed : Pragmatically Bridging Academic AI Testing and Industrial Q Needs
- 2021
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Ingår i: Lecture Notes in Business Information Processing. - Cham : Springer Science and Business Media Deutschland GmbH. - 1865-1348 .- 1865-1356. - 9783030658533 ; 404, s. 66-77
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Tidskriftsartikel (refereegranskat)abstract
- AI solutions seem to appear in any and all application domains. As AI becomes more pervasive, the importance of quality assurance increases. Unfortunately, there is no consensus on what artificial intelligence means and interpretations range from simple statistical analysis to sentient humanoid robots. On top of that, quality is a notoriously hard concept to pinpoint. What does this mean for AI quality? In this paper, we share our working definition and a pragmatic approach to address the corresponding quality assurance with a focus on testing. Finally, we present our ongoing work on establishing the AIQ Meta-Testbed.
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| 4. |
- Eriksson, Kristina M., 1976-, et al.
(författare)
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A Case Study Initiating Discrete Event Simulation as a Tool for Decision Making in I4.0 Manufacturing
- 2021
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Ingår i: Lecture Notes in Business Information Processing. - Cham : Springer Science+Business Media B.V.. - 1865-1348 .- 1865-1356. ; 414 LNBIP, s. 84-96
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Tidskriftsartikel (refereegranskat)abstract
- Smart manufacturing needs to handle increased uncertainty by becoming more responsive and more flexible to reconfigure. Advances in technology within industry 4.0 can provide acquisition of large amounts of data, to support decision making in manufacturing. Those possibilities have brought anew attention to the applicability of discrete event simulation for production flow modelling when moving towards design of logistics systems 4.0. This paper reports a study investigating challenges and opportunities for initiation of discrete event simulation, as a tool for decision making in the era of industry 4.0 manufacturing. The research has been approached through action research in combination with a real case study at a manufacturing company in the energy sector. The Covid-19 pandemic fated that adjusted and new ways of communication, collaboration, and data collection, in relation to the methods, had to be explored and tried. Throughout the study, production data, such as processing times, have been collected and analyzed for discrete event simulation modelling. The complexity of introducing discrete event simulation as a new tool for decision making is highlighted, where we emphasize the human knowledge and involvement yet necessary to understand and to draw conclusions from the data. The results also demonstrate that the data analysis has given valuable insights into production characteristics, that need addressing. Thus, revealing opportunities for how the initiative of introducing discrete event simulation as an anew tool in the wake of industry 4.0, can act as a catalyst for improved decision making in future manufacturing. © 2021, Springer Nature Switzerland AG.
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| 5. |
- Green, Rolf, 1991, et al.
(författare)
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Autonomously Improving Systems in Industry : A Systematic Literature Review
- 2021
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Ingår i: Software Business. - Cham : Springer. - 9783030672911 - 9783030672928 ; 407, s. 30-45
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Konferensbidrag (refereegranskat)abstract
- A significant amount of research effort is put into studying machine learning (ML) and deep learning (DL) technologies. Real-world ML applications help companies to improve products and automate tasks such as classification, image recognition and automation. However, a traditional “fixed” approach where the system is frozen before deployment leads to a sub-optimal system performance. Systems autonomously experimenting with and improving their own behavior and performance could improve business outcomes but we need to know how this could actually work in practice. While there is some research on autonomously improving systems, the focus on the concepts and theoretical algorithms. However, less research is focused on empirical industry validation of the proposed theory. Empirical validations are usually done through simulations or by using synthetic or manually alteration of datasets. The contribution of this paper is twofold. First, we conduct a systematic literature review in which we focus on papers describing industrial deployments of autonomously improving systems and their real-world applications. Secondly, we identify open research questions and derive a model that classifies the level of autonomy based on our findings in the literature review.
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| 6. |
- Gren, Lucas, 1984
(författare)
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Understanding work practices of autonomous agile teams: A social-psychological review
- 2020
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Ingår i: Agile Processes in Software Engineering and Extreme Programming – Workshops. XP 2020. Lecture Notes in Business Information Processing. - Cham : Springer, Cham. - 1865-1348 .- 1865-1356. - 9783030588571
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Konferensbidrag (refereegranskat)abstract
- The purpose of this paper is to suggest additional aspects of social psychology that could help when making sense of autonomous agile teams. To make use of well-tested theories in social psychology and instead see how they replicated and differ in the autonomous agile team context would avoid reinventing the wheel. This was done, as an initial step, through looking at some very common agile practices and relate them to existing findings in social-psychological research. The two theories found that I argue could be more applied to the software engineering context are social identity theory and group socialization theory. The results show that literature provides social-psychological reasons for the popularity of some agile practices, but that scientific studies are needed to gather empirical evidence on these under-researched topics. Understanding deeper psychological theories could provide a better understanding of the psychological processes when building autonomous agile team, which could then lead to better predictability and intervention in relation to human factors.
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| 7. |
- Gren, Lucas, 1984, et al.
(författare)
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What an Agile Leader Does: The Group Dynamics Perspective
- 2020
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Ingår i: Lecture Notes in Business Information Processing. - Cham : Springer International Publishing. - 1865-1356 .- 1865-1348. - 9783030493912 ; 383 LNBIP, s. 178-194
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Konferensbidrag (refereegranskat)abstract
- When large industrial organizations change to (or start with) an agile approach to operations, managers and some employees are supposed to be “agile leaders” often without being given a clear definition of what that comprises when building agile teams. An inductive thematic analysis was used to investigate what 15 appointed leaders actually do and perceive as challenges regarding group dynamics working with an agile approach. Team maturity, Team design, and Culture and mindset were all categories of challenges related to group dynamics that the practitioners face and manage in their work-life that are not explicitly mentioned in the more process-focused agile transformation frameworks. The results suggest that leader mitigation of these three aspects of group dynamics is essential to the success of an agile transformation.
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| 8. |
- Hyrynsalmi, Sami, et al.
(författare)
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Quō vādis, Data Business?: A Study for Understanding Maturity of Embedded System Companies in Data Economy
- 2022
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Ingår i: Lecture Notes in Business Information Processing. - Cham : Springer International Publishing. - 1865-1356 .- 1865-1348. ; 463 LNBIP, s. 141-148, s. 141-148
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Konferensbidrag (refereegranskat)abstract
- Data has been claimed to be the new oil of the 21st century as it has seen to be able both to improve the existing products and services as well as to create new revenue streams for its utilizing company with a secondary customers base. However, while there is active streams of research for developing machine learning and data science methods, considerably less has been done to understand and characterize data business activities in the software-intensive companies. This study uses a multiple case study approach in the software-intensive embedded system domain. Four large international embedded system companies were selected as the case study subjects. The objective is to understand how the case companies are developing their activities for successful utilization of the data. The study identifies six distinct stages with their own challenges. In addition, this study serves as a starting for further work for supporting software-intensive embedded system companies to start data business.
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| 9. |
- John, Meenu Mary, et al.
(författare)
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Architecting AI Deployment: A Systematic Review of State-of-the-Art and State-of-Practice Literature
- 2021
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Ingår i: Lecture Notes in Business Information Processing. - Cham : Springer International Publishing. - 1865-1356 .- 1865-1348. ; 407, s. 14-29, s. 14-29
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Konferensbidrag (refereegranskat)abstract
- Companies across domains are rapidly engaged in shifting computational power and intelligence from centralized cloud to fully decentralized edges to maximize value delivery, strengthen security and reduce latency. However, most companies have only recently started pursuing this opportunity and are therefore at the early stage of the cloud-to-edge transition. To provide an overview of AI deployment in the context of edge/cloud/hybrid architectures, we conduct a systematic literature review and a grey literature review. To advance understanding of how to integrate, deploy, operationalize and evolve AI models, we derive a framework from existing literature to accelerate the end-to-end deployment process. The framework is organized into five phases: Design, Integration, Deployment, Operation and Evolution. We make an attempt to analyze the extracted results by comparing and contrasting them to derive insights. The contribution of the paper is threefold. First, we conduct a systematic literature review in which we review the contemporary scientific literature and provide a detailed overview of the state-of-the-art of AI deployment. Second, we review the grey literature and present the state-of-practice and experience of practitioners while deploying AI models. Third, we present a framework derived from existing literature for the end-to-end deployment process and attempt to compare and contrast SLR and GLR results.
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| 10. |
- Kaili, Michalis, 1997, et al.
(författare)
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Improving the Representation Choices of Privacy Policies for End-Users
- 2023
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Ingår i: Lecture Notes in Business Information Processing. - 1865-1356 .- 1865-1348. ; 494 LNBIP, s. 42-59
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Konferensbidrag (refereegranskat)abstract
- Privacy policies provide users the possibility to get informed about how their data are being used by specific services and vendors. Unfortunately their texts are usually long and users are not devoting the required time to read them and understand their content. Tools that bring the privacy policies closer to the users can assist towards enhancing users’ privacy awareness. In this work, we are presenting the updated version of Privacy Policy Beautifier, our approach and accompanying tool that offers various representations of the privacy policy text, as a way to assist the users in better understanding the policy, devoting less time to explore its main content. Text highlighting, text summarization, word cloud, GDPR terms presence/absence are the techniques employed for the representations. The updated version of Privacy Policy Beautifier has been evaluated for its enhanced features via the participation of 32 users with promising results.
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