184 resultados para Mean-Reverting Jump-Diffusion
Resumo:
The UK Construction Industry has been criticized for being slow to change and adopt innovations. The idiosyncrasies of participants, their roles in a social system and the contextual differences between sections of the UK Construction Industry are viewed as being paramount to explaining innovation diffusion within this context. Three innovation diffusion theories from outside construction management literature are introduced, Cohesion, Structural Equivalence and Thresholds. The relevance of each theory, in relation to the UK Construction Industry, is critically reviewed using literature and empirical data. Analysis of the data results in an explanatory framework being proposed. The framework introduces a Personal Awareness Threshold concept, highlights the dominant role of Cohesion through the main stages of diffusion, together with the use of Structural Equivalence during the later stages of diffusion and the importance of Adoption Threshold levels.
Resumo:
This paper presents in detail a theoretical adaptive model of thermal comfort based on the “Black Box” theory, taking into account factors such as culture, climate, social, psychological and behavioural adaptations, which have an impact on the senses used to detect thermal comfort. The model is called the Adaptive Predicted Mean Vote (aPMV) model. The aPMV model explains, by applying the cybernetics concept, the phenomena that the Predicted Mean Vote (PMV) is greater than the Actual Mean Vote (AMV) in free-running buildings, which has been revealed by many researchers in field studies. An Adaptive coefficient (λ) representing the adaptive factors that affect the sense of thermal comfort has been proposed. The empirical coefficients in warm and cool conditions for the Chongqing area in China have been derived by applying the least square method to the monitored onsite environmental data and the thermal comfort survey results.
What do we mean when we refer to Bacteroidetes populations in the human gastrointestinal microbiota?
Resumo:
Recent large-scale cloning studies have shown that the ratio of Bacteroidetes to Firmicutes may be important in the obesity-associated gut microbiota, but the species these phyla represent in this ecosystem has not been examined. The Bacteroidetes data from the recent Turnbaugh study were examined to determine those members of the phylum detected in human faecal samples. In addition, FISH analysis was performed on faecal samples from 17 healthy, nonobese donors using probe Bac303, routinely used by gut microbiologists to enumerate BacteroidesPrevotella populations in faecal samples, and another probe (CFB286) whose target range has some overlap with that of Bac303. Sequence analysis of the Turnbaugh data showed that 23/519 clones were chimeras or erroneous sequences; all good sequences were related to species of the order Bacteroidales, but no one species was present in all donors. FISH analysis demonstrated that approximately one-quarter of the healthy, nonobese donors harboured high numbers of Bacteroidales not detected by probe Bac303. It is clear that Bacteroidales populations in human faecal samples have been underestimated in FISH-based studies. New probes and complementary primer sets should be designed to examine numerical and compositional changes in the Bacteroidales during dietary interventions and in studies of the obesity-associated microbiota in humans and animal model systems.
Resumo:
Objective: To examine the interpretation of the verbal anchors used in the Borg rating of perceived exertion (RPE) scales in different clinical groups and a healthy control group. Design: Prospective experimental study. Setting: Rehabilitation center. Participants: Nineteen subjects with brain injury, 16 with chronic low back pain (CLBP), and 20 healthy controls. Interventions: Not applicable. Main Outcome Measures: Subjects used a visual analog scale (VAS) to rate their interpretation of the verbal anchors from the Borg RPE 6-20 and the newer 10-point category ratio scale. Results: All groups placed the verbal anchors in the order that they occur on the scales. There were significant within-group differences (P > .05) between VAS scores for 4 verbal anchors in the control group, 8 in the CLBP group, and 2 in the brain injury group. There was no significant difference in rating of each verbal anchor between the groups (P > .05). Conclusions: All subjects rated the verbal anchors in the order they occur on the scales, but there was less agreement in rating of each verbal anchor among subjects in the brain injury group. Clinicians should consider the possibility of small discrepancies in the meaning of the verbal anchors to subjects, particularly those recovering from brain injury, when they evaluate exercise perceptions.
OFDM joint data detection and phase noise cancellation based on minimum mean square prediction error
Resumo:
This paper proposes a new iterative algorithm for orthogonal frequency division multiplexing (OFDM) joint data detection and phase noise (PHN) cancellation based on minimum mean square prediction error. We particularly highlight the relatively less studied problem of "overfitting" such that the iterative approach may converge to a trivial solution. Specifically, we apply a hard-decision procedure at every iterative step to overcome the overfitting. Moreover, compared with existing algorithms, a more accurate Pade approximation is used to represent the PHN, and finally a more robust and compact fast process based on Givens rotation is proposed to reduce the complexity to a practical level. Numerical Simulations are also given to verify the proposed algorithm. (C) 2008 Elsevier B.V. All rights reserved.
Resumo:
An analysis of Stochastic Diffusion Search (SDS), a novel and efficient optimisation and search algorithm, is presented, resulting in a derivation of the minimum acceptable match resulting in a stable convergence within a noisy search space. The applicability of SDS can therefore be assessed for a given problem.
Resumo:
An information processing paradigm in the brain is proposed, instantiated in an artificial neural network using biologically motivated temporal encoding. The network will locate within the external world stimulus, the target memory, defined by a specific pattern of micro-features. The proposed network is robust and efficient. Akin in operation to the swarm intelligence paradigm, stochastic diffusion search, it will find the best-fit to the memory with linear time complexity. information multiplexing enables neurons to process knowledge as 'tokens' rather than 'types'. The network illustrates possible emergence of cognitive processing from low level interactions such as memory retrieval based on partial matching. (C) 2007 Elsevier B.V. All rights reserved.