Eindhoven University of Technology

About: Eindhoven University of Technology is a education organization based out in Eindhoven, Noord-Brabant, Netherlands. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 22309 authors who have published 52936 publications receiving 1584164 citations. The organization is also known as: Technische Hogeschool Eindhoven & TU/e.

Throughput Analysis of Synchronous Data Flow Graphs

Abstract: Synchronous Data Flow Graphs (SDFGs) are a useful tool for modeling and analyzing embedded data flow applications, both in a single processor and a multiprocessing context or for application mapping on platforms. Throughput analysis of these SDFGs is an important step for verifying throughput requirements of concurrent real-time applications, for instance within design-space exploration activities. Analysis of SDFGs can be hard, since the worst-case complexity of analysis algorithms is often high. This is also true for throughput analysis. In particular, many algorithms involve a conversion to another kind of data flow graph, the size of which can be exponentially larger than the size of the original graph. In this paper, we present a method for throughput analysis of SDFGs, based on explicit state-space exploration and we show that the method, despite its worst-case complexity, works well in practice, while existing methods often fail. We demonstrate this by comparing the method with state-ofthe- art cycle mean computation algorithms. Moreover, since the state-space exploration method is essentially the same as simulation of the graph, the results of this paper can be easily obtained as a byproduct in existing simulation tools.

Gender and Tenure Diversity in GitHub Teams

Abstract: Software development is usually a collaborative venture. Open Source Software (OSS) projects are no exception; indeed, by design, the OSS approach can accommodate teams that are more open, geographically distributed, and dynamic than commercial teams. This, we find, leads to OSS teams that are quite diverse. Team diversity, predominantly in offline groups, is known to correlate with team output, mostly with positive effects. How about in OSS? Using GitHub, the largest publicly available collection of OSS projects, we studied how gender and tenure diversity relate to team productivity and turnover. Using regression modeling of GitHub data and the results of a survey, we show that both gender and tenure diversity are positive and significant predictors of productivity, together explaining a sizable fraction of the data variability. These results can inform decision making on all levels, leading to better outcomes in recruiting and performance.

Catalytic Depolymerization of Lignin in Supercritical Ethanol

Abstract: One-step valorization of soda lignin in supercritical ethanol using a CuMgAlOx catalyst results in high monomer yield (23 wt?%) without char formation. Aromatics are the main products. The catalyst combines excellent deoxygenation with low ring-hydrogenation activity. Almost half of the monomer fraction is free from oxygen. Elemental analysis of the THF-soluble lignin residue after 8 h reaction showed a 68?% reduction in O/C and 24?% increase in H/C atomic ratios as compared to the starting Protobind P1000 lignin. Prolonged reaction times enhanced lignin depolymerization and reduced the amount of repolymerized products. Phenolic hydroxyl groups were found to be the main actors in repolymerization and char formation. 2D HSQC NMR analysis evidenced that ethanol reacts by alkylation and esterification with lignin fragments. Alkylation was found to play an important role in suppressing repolymerization. Ethanol acts as a capping agent, stabilizing the highly reactive phenolic intermediates by O-alkylating the hydroxyl groups and by C-alkylating the aromatic rings. The use of ethanol is significantly more effective in producing monomers and avoiding char than the use of methanol. A possible reaction network of the reactions between the ethanol and lignin fragments is discussed.

Measuring the bullwhip effect in the supply chain

Abstract: Increased demand variability in supply chains (the bullwhip effect) has been discussed in the literature. The practical measurement of this effect, however, entails some problems that have not received much attention in the literature and that have to do with the aggregation of data, incompleteness of data, the isolation of demand data for defined supply chains that are part of a greater supply web. This paper discusses these conceptual measurement problems and discusses experiences in dealing with some of these problems in an industrial project. Also presents empirical results of measurements of the bullwhip effect in two supply chains.