Software Ecosystem Orchestration: The Perspective of Complementors

Software ecosystems (SECOs) driven by platform business models have changed how consumer software is produced and marketed. Also in the enterprise software segment, value networks in the form of SECOs are replacing traditional business models and linear value chains. These SECOs involve three main types of actors: platform sponsor, complementors, and customers. Platform sponsor strategies have been researched broadly, but not the view of complementors. Further, there are few studies of real-world SECOs. In our research, we have investigated the complementor’s perspective on SECOs and their partnership with the platform sponsor. Through exploratory qualitative research using a practical case from the enterprise software industry, we have developed a partner management framework comprising the complementors ’ value creation process, goals, enablers, and instruments. The model can be used generally to gain a better understanding of complementors, and by platform sponsors to improve their partner management processes

Operations System vs. Operating System: Towards a Ground System Supporting Satellite Application Programming

The term operating system refers to a software component, which traditionally controls the resources and the processes of a computer, and by providing the appropriate interfaces allows for the implementation of custom user applications. This is a common definition, working very well for ordinary computer systems. Yet, what if the operating system and a corresponding application are physically separated, because the computer is within a satellite in space, while the user program is executed on ground? Then, capabilities must be created to connect both, which is of course complicated by the natural boundaries in satellite communication, for example the limited satellite contact times. Over the past decades, several systems have been developed, which are capable of managing satellite resources and the mission schedule from ground. Although this covers quite well the purpose of an operating system, other terms have evolved in this domain: operations system, ground system, mission control system, ground data handling, etc. The problem though is, those systems primarily focus on the exchange of data and satellite TM/TC, rather than the actual control process. This creates an artificial barrier between ground and space, which harms the development capabilities for ground based satellite applications. This paper introduces a novel approach for an operations system architecture, which can be considered as a ground extension of the satellite’s operating system. This approach shall not break with the existing conventions and definitions, especially in terms of operating systems, but shall introduce a new view on satellite operations. In a layered, functional software architecture, the operating system is the lowest layer between the hardware and the application. Through the definition of the appropriate interfaces in the ground system, a software architecture can be created that actively supports outsourcing parts of the satellite control process to ground. The proposed approach has great potential for various applications in satellite operations. It supports the implementation of automatic system control processes, the implementation of custom payload applications, and the integration of respective activities into the satellite schedule. As applications and operators interact with a verified schedule, and operations is thus no longer limited to low-level commanding, the approach further reduces the risk of the mission being jeopardized by human mistake

Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries

Deep ensembles (DE) have been successful in improving model performance by learning diverse members via the stochasticity of random initialization. While recent works have attempted to promote further diversity in DE via hyperparameters or regularizing loss functions, these methods primarily still rely on a stochastic approach to explore the hypothesis space. In this work, we present Multi-Symmetry Ensembles (MSE), a framework for constructing diverse ensembles by capturing the multiplicity of hypotheses along symmetry axes, which explore the hypothesis space beyond stochastic perturbations of model weights and hyperparameters. We leverage recent advances in contrastive representation learning to create models that separately capture opposing hypotheses of invariant and equivariant functional classes and present a simple ensembling approach to efficiently combine appropriate hypotheses for a given task. We show that MSE effectively captures the multiplicity of conflicting hypotheses that is often required in large, diverse datasets like ImageNet. As a result of their inherent diversity, MSE improves classification performance, uncertainty quantification, and generalization across a series of transfer tasks.Comment: Camera Ready Revision. ICML 202

Ongoing outbreaks of hepatitis A among men who have sex with men (MSM), Berlin, November 2016 to January 2017 – linked to other German cities and European countries

Since 14 November 2016, 38 cases of hepatitis A have been notified in Berlin; of these, 37 were male and 30 reported to have sex with men (MSM). Median age of MSM cases is 31 years (range: 24–52 years). Phylogenetic analysis revealed three distinct sequences, linking cases in Berlin to those in other German cities and to clusters recognised in other European countries in 2016