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Business process management is a challenging task that requires business processes being described, executed, monitored and continuously enhanced. This process management lifecycle requires business as well as IT people working together, whereby the view on business process is quite different on both sides. One important means for bridging the gap between both consists in having a modeling notation that can be easily understood but also has a precise semantics and can be used as a basis for workflow execution. Although existing approaches like BPMN and EPCs aim at being such as notation they are already very activity oriented and do not consider the underlying motivations of processes. Introducing the goal oriented process modeling notation (GPMN) a new language is presented that has the objective of bringing together both sides by establishing higher-level modeling concepts for workflows. This results in an increased intelligibility of workflow descriptions for business people and greater consideration for the way processes are described on the business side. The core idea of the approach consists in introducing different kinds of goals and goal relationships in addition to the established activity-centered behavior model. The applicability of the approach is further illustrated with an example workflow from Daimler AG.

The ability to describe business processes as executable models has always been one of the fundamental premises of workflow management. Yet, the tacit nature of human knowledge is often an obstacle to eliciting accurate process models. On the other hand, the result of process modeling is a static plan of action, which is difficult to adapt to changing procedures or to different business goals. In this article, we attempt to address these problems by approaching workflow management with a combination of learning and planning techniques. Assuming that processes cannot be fully described at build-time, we make use of learning techniques, namely Inductive Logic Programming (ILP), in order to discover workflow activities and to describe them as planning operators. These operators will be subsequently fed to a partial-order planner in order to find the process model as a planning solution. The continuous interplay between learning, planning and execution aims at arriving at a feasible plan by successive refinement of the operators. The approach is illustrated in two simple scenarios. Following a discussion of related work, the paper concludes by presenting the main challenges that remain to be solved.

A material that has both negative permittivity and permeability is termed as left-handed material. The properties of Left Handed Material (LHM), such as negative refraction, have been simulated numerically by beam propagation method. The results are consistent with other works reported in the literature. It is shown that the Poynting vector and the phase velocity of the electromagnetic wave are indeed anti-parallel, confirming that the left-handed material does not violate the causality condition. It is conventional to simulate the phase restoring mechanism in a left-handed medium by showing (negative) refraction at an interface between an LHM and a conventional material. In this paper, we show for the first time, a simulation using BPM for the case of multiple-slit interference using Gaussian beam. The interference for two to three sources with different separations is used to show that the LHM can restore the phase and reverse the diffraction and interference effects.