15,219 research outputs found
Classes of random walks on temporal networks with competing timescales
Random walks find applications in many areas of science and are the heart of
essential network analytic tools. When defined on temporal networks, even basic
random walk models may exhibit a rich spectrum of behaviours, due to the
co-existence of different timescales in the system. Here, we introduce random
walks on general stochastic temporal networks allowing for lasting
interactions, with up to three competing timescales. We then compare the mean
resting time and stationary state of different models. We also discuss the
accuracy of the mathematical analysis depending on the random walk model and
the structure of the underlying network, and pay particular attention to the
emergence of non-Markovian behaviour, even when all dynamical entities are
governed by memoryless distributions.Comment: 16 pages, 5 figure
Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction
The paper reviews product data technology initiatives in the construction sector and provides a synthesis of related ICT industry needs. A comparison between (a) the data centric characteristics of Product Data Technology (PDT) and (b) ontology with a focus on semantics, is given, highlighting the pros and cons of each approach. The paper advocates the migration from data-centric application integration to ontology-based business process support, and proposes inter-enterprise collaboration architectures and frameworks based on semantic services, underpinned by ontology-based knowledge structures. The paper discusses the main reasons behind the low industry take up of product data technology, and proposes a preliminary roadmap for the wide industry diffusion of the proposed approach. In this respect, the paper stresses the value of adopting alliance-based modes of operation
Towards the Development of a Simulator for Investigating the Impact of People Management Practices on Retail Performance
Often models for understanding the impact of management practices on retail
performance are developed under the assumption of stability, equilibrium and
linearity, whereas retail operations are considered in reality to be dynamic,
non-linear and complex. Alternatively, discrete event and agent-based modelling
are approaches that allow the development of simulation models of heterogeneous
non-equilibrium systems for testing out different scenarios. When developing
simulation models one has to abstract and simplify from the real world, which
means that one has to try and capture the 'essence' of the system required for
developing a representation of the mechanisms that drive the progression in the
real system. Simulation models can be developed at different levels of
abstraction. To know the appropriate level of abstraction for a specific
application is often more of an art than a science. We have developed a retail
branch simulation model to investigate which level of model accuracy is
required for such a model to obtain meaningful results for practitioners.Comment: 24 pages, 7 figures, 6 tables, Journal of Simulation 201
Biology of Applied Digital Ecosystems
A primary motivation for our research in Digital Ecosystems is the desire to
exploit the self-organising properties of biological ecosystems. Ecosystems are
thought to be robust, scalable architectures that can automatically solve
complex, dynamic problems. However, the biological processes that contribute to
these properties have not been made explicit in Digital Ecosystems research.
Here, we discuss how biological properties contribute to the self-organising
features of biological ecosystems, including population dynamics, evolution, a
complex dynamic environment, and spatial distributions for generating local
interactions. The potential for exploiting these properties in artificial
systems is then considered. We suggest that several key features of biological
ecosystems have not been fully explored in existing digital ecosystems, and
discuss how mimicking these features may assist in developing robust, scalable
self-organising architectures. An example architecture, the Digital Ecosystem,
is considered in detail. The Digital Ecosystem is then measured experimentally
through simulations, with measures originating from theoretical ecology, to
confirm its likeness to a biological ecosystem. Including the responsiveness to
requests for applications from the user base, as a measure of the 'ecological
succession' (development).Comment: 9 pages, 4 figure, conferenc
Modelling and simulation framework for reactive transport of organic contaminants in bed-sediments using a pure java object - oriented paradigm
Numerical modelling and simulation of organic contaminant reactive transport in the environment is being increasingly
relied upon for a wide range of tasks associated with risk-based decision-making, such as prediction of contaminant
profiles, optimisation of remediation methods, and monitoring of changes resulting from an implemented remediation
scheme. The lack of integration of multiple mechanistic models to a single modelling framework, however, has
prevented the field of reactive transport modelling in bed-sediments from developing a cohesive understanding of
contaminant fate and behaviour in the aquatic sediment environment. This paper will investigate the problems involved
in the model integration process, discuss modelling and software development approaches, and present preliminary
results from use of CORETRANS, a predictive modelling framework that simulates 1-dimensional organic contaminant
reaction and transport in bed-sediments
Digital Ecosystems: Ecosystem-Oriented Architectures
We view Digital Ecosystems to be the digital counterparts of biological
ecosystems. Here, we are concerned with the creation of these Digital
Ecosystems, exploiting the self-organising properties of biological ecosystems
to evolve high-level software applications. Therefore, we created the Digital
Ecosystem, a novel optimisation technique inspired by biological ecosystems,
where the optimisation works at two levels: a first optimisation, migration of
agents which are distributed in a decentralised peer-to-peer network, operating
continuously in time; this process feeds a second optimisation based on
evolutionary computing that operates locally on single peers and is aimed at
finding solutions to satisfy locally relevant constraints. The Digital
Ecosystem was then measured experimentally through simulations, with measures
originating from theoretical ecology, evaluating its likeness to biological
ecosystems. This included its responsiveness to requests for applications from
the user base, as a measure of the ecological succession (ecosystem maturity).
Overall, we have advanced the understanding of Digital Ecosystems, creating
Ecosystem-Oriented Architectures where the word ecosystem is more than just a
metaphor.Comment: 39 pages, 26 figures, journa
Ecosystem-Oriented Distributed Evolutionary Computing
We create a novel optimisation technique inspired by natural ecosystems,
where the optimisation works at two levels: a first optimisation, migration of
genes which are distributed in a peer-to-peer network, operating continuously
in time; this process feeds a second optimisation based on evolutionary
computing that operates locally on single peers and is aimed at finding
solutions to satisfy locally relevant constraints. We consider from the domain
of computer science distributed evolutionary computing, with the relevant
theory from the domain of theoretical biology, including the fields of
evolutionary and ecological theory, the topological structure of ecosystems,
and evolutionary processes within distributed environments. We then define
ecosystem- oriented distributed evolutionary computing, imbibed with the
properties of self-organisation, scalability and sustainability from natural
ecosystems, including a novel form of distributed evolu- tionary computing.
Finally, we conclude with a discussion of the apparent compromises resulting
from the hybrid model created, such as the network topology.Comment: 8 pages, 5 figures. arXiv admin note: text overlap with
arXiv:1112.0204, arXiv:0712.4159, arXiv:0712.4153, arXiv:0712.4102,
arXiv:0910.067
Trend-based analysis of a population model of the AKAP scaffold protein
We formalise a continuous-time Markov chain with multi-dimensional discrete state space model of the AKAP scaffold protein as a crosstalk mediator between two biochemical signalling pathways. The analysis by temporal properties of the AKAP model requires reasoning about whether the counts of individuals of the same type (species) are increasing or decreasing. For this purpose we propose the concept of stochastic trends based on formulating the probabilities of transitions that increase (resp. decrease) the counts of individuals of the same type, and express these probabilities as formulae such that the state space of the model is not altered. We define a number of stochastic trend formulae (e.g. weakly increasing, strictly increasing, weakly decreasing, etc.) and use them to extend the set of state formulae of Continuous Stochastic Logic. We show how stochastic trends can be implemented in a guarded-command style specification language for transition systems. We illustrate the application of stochastic trends with numerous small examples and then we analyse the AKAP model in order to characterise and show causality and pulsating behaviours in this biochemical system
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