176,954 research outputs found
Modeling functional requirements using tacit knowledge: a design science research methodology informed approach
The research in this paper adds to the discussion linked to the challenge of capturing and modeling tacit knowledge throughout software development projects. The issue emerged when modeling functional requirements during a project for a client. However, using the design science research methodology at a particular point in the project helped to create an artifact, a functional requirements modeling technique, that resolved the issue with tacit knowledge. Accordingly, this paper includes research based upon the stages of the design science research methodology to design and test the artifact in an observable situation, empirically grounding the research undertaken. An integral component of the design science research methodology, the knowledge base, assimilated structuration and semiotic theories so that other researchers can test the validity of the artifact created. First, structuration theory helped to identify how tacit knowledge is communicated and can be understood when modeling functional requirements for new software. Second, structuration theory prescribed the application of semiotics which facilitated the development of the artifact. Additionally, following the stages of the design science research methodology and associated tasks allows the research to be reproduced in other software development contexts. As a positive outcome, using the functional requirements modeling technique created, specifically for obtaining tacit knowledge on the software development project, indicates that using such knowledge increases the likelihood of deploying software successfully
A Mathematical Approach to Order Book Modeling
Motivated by the desire to bridge the gap between the microscopic description
of price formation (agent-based modeling) and the stochastic differential
equations approach used classically to describe price evolution at macroscopic
time scales, we present a mathematical study of the order book as a
multidimensional continuous-time Markov chain and derive several mathematical
results in the case of independent Poissonian arrival times. In particular, we
show that the cancellation structure is an important factor ensuring the
existence of a stationary distribution and the exponential convergence towards
it. We also prove, by means of the functional central limit theorem (FCLT),
that the rescaled-centered price process converges to a Brownian motion. We
illustrate the analysis with numerical simulation and comparison against market
data
An empirical behavioral model of price formation
Although behavioral economics has demonstrated that there are many situations
where rational choice is a poor empirical model, it has so far failed to
provide quantitative models of economic problems such as price formation. We
make a step in this direction by developing empirical models that capture
behavioral regularities in trading order placement and cancellation using data
from the London Stock Exchange. For order placement we show that the
probability of placing an order at a given price is well approximated by a
Student distribution with less than two degrees of freedom, centered on the
best quoted price. This result is surprising because it implies that trading
order placement is symmetric, independent of the bid-ask spread, and the same
for buying and selling. We also develop a crude but simple cancellation model
that depends on the position of an order relative to the best price and the
imbalance between buying and selling orders in the limit order book. These
results are combined to construct a stochastic representative agent model, in
which the orders and cancellations are described in terms of conditional
probability distributions. This model is used to simulate price formation and
the results are compared to real data from the London Stock Exchange. Without
adjusting any parameters based on price data, the model produces good
predictions for the magnitude and functional form of the distribution of
returns and the bid-ask spread
Ontology based Scene Creation for the Development of Automated Vehicles
The introduction of automated vehicles without permanent human supervision
demands a functional system description, including functional system boundaries
and a comprehensive safety analysis. These inputs to the technical development
can be identified and analyzed by a scenario-based approach. Furthermore, to
establish an economical test and release process, a large number of scenarios
must be identified to obtain meaningful test results. Experts are doing well to
identify scenarios that are difficult to handle or unlikely to happen. However,
experts are unlikely to identify all scenarios possible based on the knowledge
they have on hand. Expert knowledge modeled for computer aided processing may
help for the purpose of providing a wide range of scenarios. This contribution
reviews ontologies as knowledge-based systems in the field of automated
vehicles, and proposes a generation of traffic scenes in natural language as a
basis for a scenario creation.Comment: Accepted at the 2018 IEEE Intelligent Vehicles Symposium, 8 pages, 10
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