Saxony's capital Dresden: On the way to become Eastern Germany's first Innovative Milieu?

In this paper, the chances of Saxonys capital city Dresden to become Eastern Germanys first high-tech-region is discussed. A presentation of the theoretical background of innovative milieux is followed by an overview of the regions universities, R&D institutes and other facilities relevant for milieu formation. Afterwards, the establishment of high-tech enterprises in the Dresden area is analyzed. The paper concludes giving a view of the regions further development potential. --

Territorial innovation dynamics: a knowledge based perspective

A great deal of studies has focused on the role played by geographical location on the emergence and the building of localised learning capacities (Maskell, Malmberg, 1999). In this perspective, empirical studies have demonstrated that innovation dynamics of clusters results from the quality of interactions and coordination inside the cluster as well as interactions with external, often global, networks. In this context, knowledge exchange between firms and institutions are claimed to be the main drivers of spatial agglomeration (Canals et al, 2008). Hence, cluster policies have followed the main idea that geographic proximity facilitates collective innovation in so far as firms can capture knowledge externalities more easily. This idea is in fact very attractive but contains some limits (Suire et Vicente, 2007): if some clusters are successful others seem to decline. Therefore, in order to understand the territorial dynamics of clusters, the analysis of the specific nature of knowledge and information flows within a cluster is crucial. The objective of the paper is to enhance the analysis of the role of cognitive and relational dimensions of interactions on territorial dynamics of innovation. We focus on the key sub process of innovation: knowledge creation, which is above all a social process based on two key complex social mechanisms: the exchange and the combination of knowledge (Nahapiet and Goshal, 1996). We suggest building a theoretical framework that hinges on these two key mechanisms. In this perspective, we mobilise Boisot's I-Space model (Boisot, 1998) for the diffusion and exchange of knowledge and suggest completing the model by introducing the concept of architectural knowledge (Henderson and Clark, 1990) so as to take the complexity of the combination process into consideration. This analysis is conducted through the illustrative analysis of three different case studies. We will draw upon the case of Aerospace Valley Pole of Competitiveness (PoC), The Secured Communicating Solutions PoC, and Fabelor Competence Cluster. The cases show that the existence of architectural knowledge is pivotal to territorial innovation.Architectural Knowledge, I-Space Model, Territorial Innovation, Geographical Clusters, Knowledge Management

Enhancement of polar phases in PVDF by forming PVDF/SiC nanowire composite

Different contents of silicon carbide (SiC) nanowires were mixed with Poly(vinylidene fluoride) (PVDF) to facilitate the polar phase crystallization. It was shown that the annealing temperature and SiC content affected on the phase and crystalline structures of PVDF/SiC samples. Furthermore, the addition of SiC nanowire enhanced the transformation of non-polar α phase to polar phases and increased the relative fraction of β phase in PVDF. Due to the nucleating agent mechanism of SiC nanowires, the ion-dipole interaction between the negatively charged surface of SiC nanowires and the positive CH2 groups in PVDF facilitated the formation of polar phases in PVDF

Optimum Selection of DNN Model and Framework for Edge Inference

This paper describes a methodology to select the optimum combination of deep neuralnetwork and software framework for visual inference on embedded systems. As a first step, benchmarkingis required. In particular, we have benchmarked six popular network models running on four deep learningframeworks implemented on a low-cost embedded platform. Three key performance metrics have beenmeasured and compared with the resulting 24 combinations: accuracy, throughput, and power consumption.Then, application-level specifications come into play. We propose a figure of merit enabling the evaluationof each network/framework pair in terms of relative importance of the aforementioned metrics for a targetedapplication. We prove through numerical analysis and meaningful graphical representations that only areduced subset of the combinations must actually be considered for real deployment. Our approach can beextended to other networks, frameworks, and performance parameters, thus supporting system-level designdecisions in the ever-changing ecosystem of embedded deep learning technology.Ministerio de Economía y Competitividad (TEC2015-66878-C3-1-R)Junta de Andalucía (TIC 2338-2013)European Union Horizon 2020 (Grant 765866

Territorial innovation dynamics and integration of SMEs into the collaborative innovation projects of French competitiveness poles: the underlying mechanisms

Geographical clusters are nowadays considered as a relevant factor for competitiveness, thanks to their innovative capabilities. In this context, public policies based on this approach are flourishing all over the world. The French “Pole of competitiveness” (PoC) policy (Politique des pôles de compétitivité) is one of these initiatives. It is the new French industrial policy aiming at reinforcing the specializations of the economy and the attractiveness of territories by fostering the development of R&D projects, bringing together multinationals, universities, and particularly Small-Middle-Sized-Enterprises (SMEs). Precisely, significant research suggests that in order to innovate SMEs need to cooperate and they are also vital for the functioning, and survival of innovative milieux. Consequently, their integration is a key issue for French PoC' success. However, the call for projects shows that despite their efforts, French Poles of Competitiveness are not totally successful: a gap remains especially between the massive financial investments helping SMEs innovate and the expected results. Yet, this issue is only analysed by focusing on intrinsic weaknesses of SMEs' management or on the complexities of existing support programmes supporting SMEs' innovation. This is insufficient. Innovation dynamics are different from a cluster to another and many failures of innovation policies come from the lack of identification of these specificities. Therefore, this paper aims are threefold: it aims at introducing the French PoC, indeed, the French PoC policy is the main new policy gathering all the nation's innovation programmes. But few papers are explaining how they work. It aims at identifying the territorial innovation dynamics within PoC and how they work, and then combine this analysis with the intrinsic features of SMEs management, to better understand how they get involved in these dynamics. It finally aims at presenting the preliminary results of the first stage of research: the analysis of a specific French PoC, the “Secured Communicating Solutions”(SCS) PoC as well as the further research questions they raise for the next stage of research.clusters, interaction, knowledge management, SMEs

VLSI Revisited - Revival in Japan

This paper describes the abundance of semiconductor consortia that have come into existence in Japan since the mid-1990s. They clearly reflect the ambition of the government - through its reorganized ministry METI and company initiatives - to regain some of the industrial and technological leadership that Japan has lost. The consortia landscape is very different in Japan compared with EU and the US. Outside Japan the universities play a much bigger and very important role. In Europe there has emerged close collaboration, among national government agencies, companies and the EU Commission in supporting the IT sector with considerable attention to semiconductor technologies. Another major difference, and possibly the most important one, is the fact that US and EU consortia include and mix partners from different areas of the semiconductor landscape including wafer makers, material suppliers, equipment producers and integrated device makers.semiconductors, Hitachi, Sony, Toshiba, Elpida, Renesas, Sematech, VLSI, JESSI, MEDEA, ASPLA, MIRAI, innovation system