816 research outputs found
Business Process Model Reasoning: From Workflow to Case Management
AbstractExisting limitations and problems in the current life-cycle of software applications is expected to encourage new development paradigms. New technological trends, aimed at responding to current needs, such as flexibility, dynamics, scalability and creativity will drive the envisaged changes. This article describes the various types of business processes, ranging from structured workflows to semi-structured flexible business processes, and methods to model each type of business process. Development of business process models based on the knowledge economy, changing corporate strategy and organization design, and agile enterprise paradigm requires BPMS technology to support weakly structured business activities and emerging ad-hoc tasks. Increasingly, organizations are expanding the use of BPM beyond their initial focus on structured processes into more challenging, cross-boundary processes that include more unstructured components. Case management technology allows the modeling of cases in which a business goal is achieved by taking decisions in the context of documents and other content objects. Case management is considered dynamic because it focuses on unstructured and ad- hoc processes. It is likewise a continuing process that involves people, information, processes, and technical tools. Furthermore, it is adaptive and adaptable because it can be used by non-technical users and is versatile in its applications in different situations. With the use of case management, circuitous business processes, fragmented communication, repetitive operations, missing documents, and long approval times can be permanently abolished
Self-similar turbulent dynamo
The amplification of magnetic fields in a highly conducting fluid is studied
numerically. During growth, the magnetic field is spatially intermittent: it
does not uniformly fill the volume, but is concentrated in long thin folded
structures. Contrary to a commonly held view, intermittency of the folded field
does not increase indefinitely throughout the growth stage if diffusion is
present. Instead, as we show, the probability-density function (PDF) of the
field strength becomes self-similar. The normalized moments increase with
magnetic Prandtl number in a powerlike fashion. We argue that the
self-similarity is to be expected with a finite flow scale and system size. In
the nonlinear saturated state, intermittency is reduced and the PDF is
exponential. Parallels are noted with self-similar behavior recently observed
for passive-scalar mixing and for map dynamos.Comment: revtex, 4 pages, 5 figures; minor changes to match published versio
Non-conservation of the valley density and its implications for the observation of the valley Hall effect
We show that the conservation of the valley density in a multi-valley
insulator is broken in an unexpected way by an electric field, such as the one
that is used to drive the valley Hall effect. This observation explains how a
fully gapped insulator (i.e., one without edge states that cross the Fermi
level) can support a valley Hall current in the bulk and yet show no valley
density accumulation at the edges. If the insulator is not fully gapped, either
because there are edge states crossing the Fermi level or because carriers are
introduced in the conduction or valence band, then valley density accumulation
at the edges is possible, paving the way to a direct observation of the valley
Hall effect. However, the magnitude of the accumulation depends crucially on
the inclusion of the anomalous electric field term in the continuity equation
that relates valley current and density.Comment: 5 pages + 6 pages of supplemental material, 4 figure
Non-conservation of the valley density and its implications for the observation of the valley Hall effect
We show that the conservation of the valley density in multi-valley and time-reversal-invariant insulators is broken in an unexpected way by the electric field that drives the valley Hall effect. This implies that fully-gapped insulators can support a valley Hall current in the bulk and yet show no valley density accumulation on the edges. Thus, the valley Hall effect cannot be observed in such systems. If the system is not fully gapped then valley density accumulation at the edges is possible and can result in a net generation of valley density. The accumulation has no contribution from undergap states and can be expressed as a Fermi surface average, for which we derive an explicit formula. We demonstrate the theory by calculating the valley density accumulations in an archetypical valley-Hall insulator: a gapped graphene nanoribbon. Surprisingly, we discover that a net valley density polarization is dynamically generated for some types of edge terminations
Astrocytes mediate analogous memory in a multi-layer neuron-astrocyte network
Modeling the neuronal processes underlying short-term working memory remains the focus of many theoretical studies in neuroscience. In this paper, we propose a mathematical model of a spiking neural network (SNN) which simulates the way a fragment of information is maintained as a robust activity pattern for several seconds and the way it completely disappears if no other stimuli are fed to the system. Such short-term memory traces are preserved due to the activation of astrocytes accompanying the SNN. The astrocytes exhibit calcium transients at a time scale of seconds. These transients further modulate the efficiency of synaptic transmission and, hence, the firing rate of neighboring neurons at diverse timescales through gliotransmitter release. We demonstrate how such transients continuously encode frequencies of neuronal discharges and provide robust short-term storage of analogous information. This kind of short-term memory can store relevant information for seconds and then completely forget it to avoid overlapping with forthcoming patterns. The SNN is inter-connected with the astrocytic layer by local inter-cellular diffusive connections. The astrocytes are activated only when the neighboring neurons fire synchronously, e.g., when an information pattern is loaded. For illustration, we took grayscale photographs of people’s faces where the shades of gray correspond to the level of applied current which stimulates the neurons. The astrocyte feedback modulates (facilitates) synaptic transmission by varying the frequency of neuronal firing. We show how arbitrary patterns can be loaded, then stored for a certain interval of time, and retrieved if the appropriate clue pattern is applied to the input
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