Evolution of Supply Chain Collaboration: Implications for the Role of Knowledge

Increasingly, research across many disciplines has recognized the shortcomings of the traditional “integration prescription” for inter-organizational knowledge management. This research conducts several simulation experiments to study the effects of different rates of product change, different demand environments, and different economies of scale on the level of integration between firms at different levels in the supply chain. The underlying paradigm shifts from a static, steady state view to a dynamic, complex adaptive systems and knowledge-based view of supply chain networks. Several research propositions are presented that use the role of knowledge in the supply chain to provide predictive power for how supply chain collaborations or integration should evolve. Suggestions and implications are suggested for managerial and research purposes

The view from elsewhere: perspectives on ALife Modeling

Many artificial life researchers stress the interdisciplinary character of the field. Against such a backdrop, this report reviews and discusses artificial life, as it is depicted in, and as it interfaces with, adjacent disciplines (in particular, philosophy, biology, and linguistics), and in the light of a specific historical example of interdisciplinary research (namely cybernetics) with which artificial life shares many features. This report grew out of a workshop held at the Sixth European Conference on Artificial Life in Prague and features individual contributions from the workshop's eight speakers, plus a section designed to reflect the debates that took place during the workshop's discussion sessions. The major theme that emerged during these sessions was the identity and status of artificial life as a scientific endeavor

BPM News - Folge 3

Die BPM-Kolumne des EMISA-Forums berichtet über aktuelle Themen, Projekte und Veranstaltungen aus dem BPM-Umfeld. Schwerpunkt der vorliegenden Kolumne bildet das Thema Standardisierung von Prozessbeschreibungssprachen und -notationen im Allgemeinen und BPEL4WS (Business Process Execution Language for Web Services) im Speziellen. Hierzu liefert Jan Mendling von der Wirtschaftsuniversität Wien in aktuelles Schlagwort. Des weiteren erhalten Leser eine Zusammenfassung zweier im ersten Halbjahr 2006 veranstalteten Workshops zu den Themen „Flexibilität prozessorientierter Informationssysteme“ und „Kollaborative Prozesse“ sowie einen BPM Veranstaltungskalender für die 2. Jahreshälfte 2006

Activity driven modeling of time varying networks

Network modeling plays a critical role in identifying statistical regularities and structural principles common to many systems. The large majority of recent modeling approaches are connectivity driven. The structural patterns of the network are at the basis of the mechanisms ruling the network formation. Connectivity driven models necessarily provide a time-aggregated representation that may fail to describe the instantaneous and fluctuating dynamics of many networks. We address this challenge by defining the activity potential, a time invariant function characterizing the agents' interactions and constructing an activity driven model capable of encoding the instantaneous time description of the network dynamics. The model provides an explanation of structural features such as the presence of hubs, which simply originate from the heterogeneous activity of agents. Within this framework, highly dynamical networks can be described analytically, allowing a quantitative discussion of the biases induced by the time-aggregated representations in the analysis of dynamical processes.Comment: 10 pages, 4 figure

ASCR/HEP Exascale Requirements Review Report

This draft report summarizes and details the findings, results, and recommendations derived from the ASCR/HEP Exascale Requirements Review meeting held in June, 2015. The main conclusions are as follows. 1) Larger, more capable computing and data facilities are needed to support HEP science goals in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of the demand at the 2025 timescale is at least two orders of magnitude -- and in some cases greater -- than that available currently. 2) The growth rate of data produced by simulations is overwhelming the current ability, of both facilities and researchers, to store and analyze it. Additional resources and new techniques for data analysis are urgently needed. 3) Data rates and volumes from HEP experimental facilities are also straining the ability to store and analyze large and complex data volumes. Appropriately configured leadership-class facilities can play a transformational role in enabling scientific discovery from these datasets. 4) A close integration of HPC simulation and data analysis will aid greatly in interpreting results from HEP experiments. Such an integration will minimize data movement and facilitate interdependent workflows. 5) Long-range planning between HEP and ASCR will be required to meet HEP's research needs. To best use ASCR HPC resources the experimental HEP program needs a) an established long-term plan for access to ASCR computational and data resources, b) an ability to map workflows onto HPC resources, c) the ability for ASCR facilities to accommodate workflows run by collaborations that can have thousands of individual members, d) to transition codes to the next-generation HPC platforms that will be available at ASCR facilities, e) to build up and train a workforce capable of developing and using simulations and analysis to support HEP scientific research on next-generation systems.Comment: 77 pages, 13 Figures; draft report, subject to further revisio

Enabling e-Research in combustion research community

Abstract This paper proposes an application of the Collaborative e-Science Architecture (CeSA) to enable e-Research in combustion research community. A major problem of the community is that data required for constructing modelling might already exist but scattered and improperly evaluated. That makes the collection of data for constructing models difficult and time-consuming. The decentralised P2P collaborative environment of the CeSA is well suited to solve this distributed problem. It opens up access to scattered data and turns them to valuable resources. Other issues of the community addressed here are the needs for computational resources, storages and interoperability amongst different data formats can also be addressed by the use of Grid environment in the CeSA