Emerging Trends in Technological Innovation: First IFIP WG by Patrícia Macedo, Luis M. Camarinha-Matos (auth.), Luis M.

By Patrícia Macedo, Luis M. Camarinha-Matos (auth.), Luis M. Camarinha-Matos, Pedro Pereira, Luis Ribeiro (eds.)

This publication constitutes the refereed court cases of the 1st IFIP WG 5.5/SOCOLNET Doctoral convention on Computing, electric and business structures, DoCEIS 2010, held in Costa de Caparica, Portugal, in February 2010.

The sixty two revised complete papers have been conscientiously chosen from various submissions. They conceal a large spectrum of issues starting from collaborative firm networks to microelectronics.The papers are prepared in topical sections on firm networks and strategic alignment; info structures; collaborative networks aid; threat evaluate and choice help; evolvable manufacturing unit automation; cooperative robots; robots and manipulation; Petri nets established modeling; telecommunications; sensorial belief; sign processing; power structures; devoted strength platforms; electric equipment; electronics layout and try out; and digital circuits.

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Additional resources for Emerging Trends in Technological Innovation: First IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2010, Costa de Caparica, Portugal, February 22-24, 2010. Proceedings

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In order to provide a systematic way of assessing the willingness to collaborate, a tool named Intentions Query Mechanism (IQM) was 1 The scale used in this example is inverted to ensure that the right side always reflects a positive attitude. Assessment of the Willingness to Collaborate in Enterprise Networks 21 developed. From the description of a collaboration opportunity, this tool selects the a set of possible questions to be asked, in order to assess willingness to collaborate. The approach used to develop the IQM is based on a Prolog knowledge-base, which manages an experts’ repository of questions.

As mentioned, the ET-DRN algorithm gradually reduces the dimension of the space of objects using the Euler method. The ET-DRN considers the influence of all attributes on the arrangement of objects (sample points in the Euler method). In each step of the hierarchical clustering, the ET-DRN rearranges the objects of the intervals calculated in the previous step. In each interval, the optimal arrangement is that closest objects settle beside each other, where the measure of closeness of two objects is the L2 norm of their unreduced attributes.

Specifically, the strength of each control belief cbi is weighted by the perceived power ppi, and the products are aggregated using the following equation: PBCb = 1 n × (# scale) 2 n ∑ π [(cb , v )]× π [( pp , v )] i =1 i 2 i 2 i i (3) Definition 11 (Organization’s willingness to collaborate) – According to TPB, intention to collaborate can be taken as a direct measure of the willingness to collaborate. Intention is based on the attitude toward the behavior (Definition 4), the social influences (Definition 7), and perceived behavioral control (Definition 10).

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