Rethinking the Concept of Long-Run Economic Growth

This paper argues that growth theory needs a more general “regularity” concept than that of exponential growth. This offers the possibility of considering a richer set of parameter combinations than in standard growth models. Allowing zero population growth in the Jones (1995) model serves as our illustration of the usefulness of a general concept of “regular growth”.exponential growth, arithmetic growth, regular growth, semi-endogenous growth, knife-edge restrictions

Rethinking the Concept of Long-Run Economic Growth

This paper argues that growth theory needs a more general “regularity” concept than that of exponential growth. This opens up for considering a richer set of parameter combinations than in standard growth models. Allowing zero population growth in the Jones (1995) model serves as our illustration of the usefulness of a general concept of “regular growth”.exponential growth; arithmetic growth; regular growth; semi-endogenous growth; knife-edge restrictions

When Economic Growth is Less than Exponential

This paper argues that growth theory needs a more general notion of “regularity” than that of exponential growth. We suggest that paths along which the rate of decline of the growth rate is proportional to the growth rate itself deserve attention. This opens up for considering a richer set of parameter combinations than in standard growth models. And it avoids the usual oversimplistic dichotomy of either exponential growth or stagnation. Allowing zero population growth in three different growth models (the Jones R&D-based model, a learning-by-doing model, and an embodied technical change model) serve as illustrations that a continuum of “regular” growth processes fill the whole range between exponential growth and complete stagnation.quasi-arithmetic growth; regular growth; semi-endogenous growth; knife-edge restrictions; learning by doing; embodied technical change

Transferring Human Factors Knowledge from Aviation to Development of a Warning System for Landslide

There is a successful history of transferring knowledge from aviation to other domains such as medicine (Thomas & Helmreich, 2002). In this study the ICAO multistage alerting service (2008) served as model for the specification of an early warning system for landslide. The early warning system is designed to monitor mass-movement data provided by GPS sensors, and to generate warnings and alarms to the National Alarm- and Warning Center of Styria, Austria. For the human factors specification of the new system a qualitative analysis was performed. Results are discussed with regard to applicability of human factors guidelines from aviation to development of systems for regional alarming centers which initiate and supervise disaster management activities

Transferring Human Factors Knowledge from Aviation to Development of a Warning System for Landslide

There is a successful history of transferring knowledge from aviation to other domains such as medicine (Thomas & Helmreich, 2002). In this study the ICAO multistage alerting service (2008) served as model for the specification of an early warning system for landslide. The early warning system is designed to monitor mass-movement data provided by GPS sensors, and to generate warnings and alarms to the National Alarm- and Warning Center of Styria, Austria. For the human factors specification of the new system a qualitative analysis was performed. Results are discussed with regard to applicability of human factors guidelines from aviation to development of systems for regional alarming centers which initiate and supervise disaster management activities

Establishing Dynamic Secure Sessions for ECQV Implicit Certificates in Embedded Systems

Be it in the IoT or automotive domain, implicit certificates are gaining ever more prominence in constrained embedded devices. They present a resource-efficient security solution against common threat concerns. The computational requirements are not the main issue anymore. The focus is now placed on determining a good balance between the provided security level and the derived threat model. A security aspect that often gets overlooked is the establishment of secure communication sessions, as most design solutions are based only on the use of static key derivation, and therefore, lack the perfect forward secrecy. This leaves the transmitted data open for potential future exposures by having keys tied to the certificates rather than the communication sessions. We aim to patch this gap, by presenting a design that utilizes the Station to Station (STS) protocol with implicit certificates. In addition, we propose potential protocol optimization implementation steps and run a comprehensive study on the performance and security level between the proposed design and the state-of-the-art key derivation protocols. In our comparative study, we show that with a slight computational increase of 20\% compared to a static ECDSA key derivation, we are able to mitigate many session-related security vulnerabilities that would otherwise remain open.Comment: Accepted copy for Publication at the Design, Automation and Test in Europe (DATE) Conference 202

Automist - A Tool for Automated Instruction Set Characterization of Embedded Processors

The steadily increasing performance of mobile devices also implies a rise in power consumption. To counteract this trend it is mandatory to accomplish software power optimizations based on accurate power consumption models characterized for the processor. This paper presents an environment for automated instruction set characterization based on physical power measurements. Based on a detailed instruction set description a testbench generator creates all needed test programs for a complete characterization. Afterwards those programs are executed by the processor and the energy consumption is measured. For an accurate energy measurement a high performance sampling technique has been established, which can be either clock or energy driven

Lost in folding space? Comparing four variants of the thermodynamic model for RNA secondary structure prediction

Janssen S, Schudoma C, Steger G, Giegerich R. Lost in folding space? Comparing four variants of the thermodynamic model for RNA secondary structure prediction. BMC Bioinformatics. 2011;12(1): 429.BACKGROUND:Many bioinformatics tools for RNA secondary structure analysis are based on a thermodynamic model of RNA folding. They predict a single, "optimal" structure by free energy minimization, they enumerate near-optimal structures, they compute base pair probabilities and dot plots, representative structures of different abstract shapes, or Boltzmann probabilities of structures and shapes. Although all programs refer to the same physical model, they implement it with considerable variation for different tasks, and little is known about the effects of heuristic assumptions and model simplifications used by the programs on the outcome of the analysis.RESULTS:We extract four different models of the thermodynamic folding space which underlie the programs RNAfold, RNAshapes, and RNAsubopt. Their differences lie within the details of the energy model and the granularity of the folding space. We implement probabilistic shape analysis for all models, and introduce the shape probability shift as a robust measure of model similarity. Using four data sets derived from experimentally solved structures, we provide a quantitative evaluation of the model differences.CONCLUSIONS:We find that search space granularity affects the computed shape probabilities less than the over- or underapproximation of free energy by a simplified energy model. Still, the approximations perform similar enough to implementations of the full model to justify their continued use in settings where computational constraints call for simpler algorithms. On the side, we observe that the rarely used level 2 shapes, which predict the complete arrangement of helices, multiloops, internal loops and bulges, include the "true" shape in a rather small number of predicted high probability shapes. This calls for an investigation of new strategies to extract high probability members from the (very large) level 2 shape space of an RNA sequence. We provide implementations of all four models, written in a declarative style that makes them easy to be modified. Based on our study, future work on thermodynamic RNA folding may make a choice of model based on our empirical data. It can take our implementations as a starting point for further program development