248,114 research outputs found
Occupant behaviour in naturally ventilated and hybrid buildings
Adaptive thermal comfort criteria for building occupants are now becoming established. In this paper we illustrate their use in the prediction of occupant behaviour and make a comparison with a non-adaptive temperature threshold approach. A thermal comfort driven adaptive behavioural model for window opening is described and its use within dynamic simulation illustrated for a number of building types. Further development of the adaptive behavioural model is suggested including use of windows, doors, ceiling fans, night cooling, air conditioning and heating, also the setting of opportunities and constraints appropriate to a particular situation. The integration in dynamic simulation of the thermal adaptive behaviours together with non-thermally driven behaviours such as occupancy, lights and blind use is proposed in order to create a more complete model of occupant behaviour. It is further proposed that this behavioural model is implemented in a methodology that includes other uncertainties (e.g. in internal gains) so that a realistic range of occupant behaviours is represented at the design stage to assist in the design of robust, comfortable and low energy buildings
The adaptive nature of liquidity taking in limit order books
In financial markets, the order flow, defined as the process assuming value
one for buy market orders and minus one for sell market orders, displays a very
slowly decaying autocorrelation function. Since orders impact prices,
reconciling the persistence of the order flow with market efficiency is a
subtle issue. A possible solution is provided by asymmetric liquidity, which
states that the impact of a buy or sell order is inversely related to the
probability of its occurrence. We empirically find that when the order flow
predictability increases in one direction, the liquidity in the opposite side
decreases, but the probability that a trade moves the price decreases
significantly. While the last mechanism is able to counterbalance the
persistence of order flow and restore efficiency and diffusivity, the first
acts in opposite direction. We introduce a statistical order book model where
the persistence of the order flow is mitigated by adjusting the market order
volume to the predictability of the order flow. The model reproduces the
diffusive behaviour of prices at all time scales without fine-tuning the values
of parameters, as well as the behaviour of most order book quantities as a
function of the local predictability of order flow.Comment: 40 pages, 14 figures, and 2 tables; old figure 12 removed. Accepted
for publication on JSTA
Improving the adaptability of simulated evolutionary swarm robots in dynamically changing environments
One of the important challenges in the field of evolutionary robotics is the development of systems that can adapt to a changing environment. However, the ability to adapt to unknown and fluctuating environments is not straightforward. Here, we explore the adaptive potential of simulated swarm robots that contain a genomic encoding of a bio-inspired gene regulatory network (GRN). An artificial genome is combined with a flexible agent-based system, representing the activated part of the regulatory network that transduces environmental cues into phenotypic behaviour. Using an artificial life simulation framework that mimics a dynamically changing environment, we show that separating the static from the conditionally active part of the network contributes to a better adaptive behaviour. Furthermore, in contrast with most hitherto developed ANN-based systems that need to re-optimize their complete controller network from scratch each time they are subjected to novel conditions, our system uses its genome to store GRNs whose performance was optimized under a particular environmental condition for a sufficiently long time. When subjected to a new environment, the previous condition-specific GRN might become inactivated, but remains present. This ability to store 'good behaviour' and to disconnect it from the novel rewiring that is essential under a new condition allows faster re-adaptation if any of the previously observed environmental conditions is reencountered. As we show here, applying these evolutionary-based principles leads to accelerated and improved adaptive evolution in a non-stable environment
Integration of an adaptive infotainment system in a vehicle and validation in real driving scenarios
More services, functionalities, and interfaces are increasingly being incorporated into current vehicles and may overload the driver capacity to perform primary driving tasks adequately. For this reason, a strategy for easing driver interaction with the infotainment system must be defined, and a good balance between road safety and driver experience must also be achieved. An adaptive Human Machine Interface (HMI) that manages the presentation of information and restricts drivers’ interaction in accordance with the driving complexity was designed and evaluated. For this purpose, the driving complexity value employed as a reference was computed by a predictive model, and the adaptive interface was designed following a set of proposed HMI principles. The system was validated performing acceptance and usability tests in real driving scenarios. Results showed the system performs well in real driving scenarios. Also, positive feedbacks were received from participants endorsing the benefits of integrating this kind of system as regards driving experience and road safety.Postprint (published version
A Framework for Evaluating Model-Driven Self-adaptive Software Systems
In the last few years, Model Driven Development (MDD), Component-based
Software Development (CBSD), and context-oriented software have become
interesting alternatives for the design and construction of self-adaptive
software systems. In general, the ultimate goal of these technologies is to be
able to reduce development costs and effort, while improving the modularity,
flexibility, adaptability, and reliability of software systems. An analysis of
these technologies shows them all to include the principle of the separation of
concerns, and their further integration is a key factor to obtaining
high-quality and self-adaptable software systems. Each technology identifies
different concerns and deals with them separately in order to specify the
design of the self-adaptive applications, and, at the same time, support
software with adaptability and context-awareness. This research studies the
development methodologies that employ the principles of model-driven
development in building self-adaptive software systems. To this aim, this
article proposes an evaluation framework for analysing and evaluating the
features of model-driven approaches and their ability to support software with
self-adaptability and dependability in highly dynamic contextual environment.
Such evaluation framework can facilitate the software developers on selecting a
development methodology that suits their software requirements and reduces the
development effort of building self-adaptive software systems. This study
highlights the major drawbacks of the propped model-driven approaches in the
related works, and emphasise on considering the volatile aspects of
self-adaptive software in the analysis, design and implementation phases of the
development methodologies. In addition, we argue that the development
methodologies should leave the selection of modelling languages and modelling
tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition,
self-adaptive application, context oriented software developmen
Towards homeostatic architecture: simulation of the generative process of a termite mound construction
This report sets out to the theme of the generation of a ‘living’,
homeostatic and self-organizing architectural structure. The main research
question this project addresses is what innovative techniques of design,
construction and materials could prospectively be developed and eventually
applied to create and sustain human-made buildings which are mostly
adaptive, self-controlled and self-functioning, without option to a vast supply
of materials and peripheral services. The hypothesis is that through the
implementation of the biological building behaviour of termites, in terms of
collective construction mechanisms that are based on environmental stimuli,
we could achieve a simulation of the generative process of their adaptive
structures, capable to inform in many ways human construction. The essay
explicates the development of the 3-dimensional, agent-based simulation of
the termite collective construction and analyzes the results, which involve
besides physical modelling of the evolved structures. It finally elucidates the
potential of this emerging and adaptive architectural performance to be
translated to human practice and thus enlighten new ecological engineering
and design methodologies
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