Linköping University

About: Linköping University is a education organization based out in Linköping, Sweden. It is known for research contribution in the topics: Population & Thin film. The organization has 15671 authors who have published 50013 publications receiving 1542189 citations.

Shorthand writing on stylus keyboard

Abstract: We propose a method for computer-based speed writing, SHARK (shorthand aided rapid keyboarding), which augments stylus keyboarding with shorthand gesturing. SHARK defines a shorthand symbol for each word according to its movement pattern on an optimized stylus keyboard. The key principles for the SHARK design include high efficiency stemmed from layout optimization, duality of gesturing and stylus tapping, scale and location independent writing, Zipf's law, and skill transfer from tapping to shorthand writing due to pattern consistency. We developed a SHARK system based on a classic handwriting recognition algorithm. A user study demonstrated the feasibility of the SHARK method.

Overview of 5G Security Challenges and Solutions

Abstract: 5G networks will use novel technological concepts to meet the requirements of broadband access everywhere, high user and device mobility, and connectivity of massive number of devices (e.g., the Internet of Things) in an ultra-reliable and affordable way. Software defined networking and network functions virtualization leveraging the advances in cloud computing such as mobile edge computing are the most sought out technologies to meet these requirements. However, securely using these technologies and providing user privacy in future wireless networks are the new concerns. Therefore, this article provides an overview of the security challenges in clouds, software defined networking, and network functions virtualization, and the challenges of user privacy. Henceforth, this article presents solutions to these challenges and future directions for secure 5G systems.

MABA-MABA or Abracadabra? Progress on Human–Automation Co-ordination

Abstract: In this paper we argue that substitution-based function allocation methods (such as MABA-MABA, or Men-Are-Better-At/Machines-Are-Better-At lists) cannot provide progress on human–automation co-ordination. Quantitative ‘who does what’ allocation does not work because the real effects of automation are qualitative: it transforms human practice and forces people to adapt their skills and routines. Rather than re-inventing or refining substitution-based methods, we propose that the more pressing question on human–automation co-ordination is ‘How do we make them get along together?’