Modelling capability and affordance as properties of human/machine resource systems

Understanding how and why the capability of one set of business resources, its structural arrangements and mechanisms compared to another works can provide competitive advantage in terms of new business processes and product and service development. However, most business models of capability are descriptive and lack formal modelling language to qualitatively and quantifiably compare capabilities, Gibson’s theory of affordance, the potential for action, provides a formal basis for a more robust and quantitative model, but most formal affordance models are complex and abstract and lack support for real-world applications. We aim to understand the ‘how’ and ‘why’ of business capability, by developing a quantitative and qualitative model that underpins earlier work on Capability-Affordance Modelling – CAM. This paper integrates an affordance based capability model and the formalism of Coloured Petri Nets to develop a simulation model. Using the model, we show how capability depends on the space time path of interacting resources, the mechanism of transition and specific critical affordance factors relating to the values of the variables for resources, people and physical objects. We show how the model can identify the capabilities of resources to enable the capability to inject a drug and anaesthetise a patient.

Complex extreme learning machine applications in terahertz pulsed signals feature sets

This paper presents a novel approach to the automatic classification of very large data sets composed of terahertz pulse transient signals, highlighting their potential use in biochemical, biomedical, pharmaceutical and security applications. Two different types of THz spectra are considered in the classification process. Firstly a binary classification study of poly-A and poly-C ribonucleic acid samples is performed. This is then contrasted with a difficult multi-class classification problem of spectra from six different powder samples that although have fairly indistinguishable features in the optical spectrum, they also possess a few discernable spectral features in the terahertz part of the spectrum. Classification is performed using a complex-valued extreme learning machine algorithm that takes into account features in both the amplitude as well as the phase of the recorded spectra. Classification speed and accuracy are contrasted with that achieved using a support vector machine classifier. The study systematically compares the classifier performance achieved after adopting different Gaussian kernels when separating amplitude and phase signatures. The two signatures are presented as feature vectors for both training and testing purposes. The study confirms the utility of complex-valued extreme learning machine algorithms for classification of the very large data sets generated with current terahertz imaging spectrometers. The classifier can take into consideration heterogeneous layers within an object as would be required within a tomographic setting and is sufficiently robust to detect patterns hidden inside noisy terahertz data sets. The proposed study opens up the opportunity for the establishment of complex-valued extreme learning machine algorithms as new chemometric tools that will assist the wider proliferation of terahertz sensing technology for chemical sensing, quality control, security screening and clinic diagnosis. Furthermore, the proposed algorithm should also be very useful in other applications requiring the classification of very large datasets.

Ventilation performance in a passage between two non-parallel buildings

A great number of studies on wind conditions in passages between slab-type buildings have been conducted in the past. However, wind conditions under different structure and configuration of buildings is still unclear and studies existed still can’t provide guidance on urban planning and design, due to the complexity of buildings and aerodynamics. The aim of this paper is to provide more insight in the mechanism of wind conditions in passages. In this paper, a simplified passage model with non-parallel buildings is developed on the basis of the wind tunnel experiments conducted by Blocken et al. (2008). Numerical simulation based on CFD is employed for a detailed investigation of the wind environment in passages between two long narrow buildings with different directions and model validation is performed by comparing numerical results with corresponding wind tunnel measurements.

IMF control of cusp proton emission intensity and dayside convection: implications for component and anti-parallel reconnection

We study a brightening of the Lyman-alpha emission in the cusp which occurred in response to a short-lived southward turning of the interplanetary magnetic field (IMF) during a period of strongly enhanced solar wind plasma concentration. The cusp proton emission is detected using the SI-12 channel of the FUV imager on the IMAGE spacecraft. Analysis of the IMF observations recorded by the ACE and Wind spacecraft reveals that the assumption of a constant propagation lag from the upstream spacecraft to the Earth is not adequate for these high time-resolution studies. The variations of the southward IMF component observed by ACE and Wind allow for the calculation of the ACE-to-Earth lag as a function of time. Application of the derived propagation delays reveals that the intensity of the cusp emission varied systematically with the IMF clock angle, the relationship being particularly striking when the intensity is normalised to allow for the variation in the upstream solar wind proton concentration. The latitude of the cusp migrated equatorward while the lagged IMF pointed southward, confirming the lag calculation and indicating ongoing magnetopause reconnection. Dayside convection, as monitored by the SuperDARN network of radars, responded rapidly to the IMF changes but lagged behind the cusp proton emission response: this is shown to be as predicted by the model of flow excitation by Cowley and Lockwood (1992). We use the numerical cusp ion precipitation model of Lockwood and Davis (1996), along with modelled Lyman-_ emission efficiency and the SI-12 instrument response, to investigate the effect of the sheath field clock angle on the acceleration of ions on crossing the dayside magnetopause. This modelling reveals that the emission commences on each reconnected field line 2–2.5min after it is opened and peaks 3–5 min after it is opened. We discuss how comparison of the Lyman-alpha intensities with oxygen emissions observed simultaneously by the SI-13 channel of the FUV instrument offers an opportunity to test whether or not the clock angle dependence is consistent with the “component” or the “anti-parallel” reconnection hypothesis.

Towards a parallel computationally efficient approach to scaling up data stream classification

Advances in hardware technologies allow to capture and process data in real-time and the resulting high throughput data streams require novel data mining approaches. The research area of Data Stream Mining (DSM) is developing data mining algorithms that allow us to analyse these continuous streams of data in real-time. The creation and real-time adaption of classification models from data streams is one of the most challenging DSM tasks. Current classifiers for streaming data address this problem by using incremental learning algorithms. However, even so these algorithms are fast, they are challenged by high velocity data streams, where data instances are incoming at a fast rate. This is problematic if the applications desire that there is no or only a very little delay between changes in the patterns of the stream and absorption of these patterns by the classifier. Problems of scalability to Big Data of traditional data mining algorithms for static (non streaming) datasets have been addressed through the development of parallel classifiers. However, there is very little work on the parallelisation of data stream classification techniques. In this paper we investigate K-Nearest Neighbours (KNN) as the basis for a real-time adaptive and parallel methodology for scalable data stream classification tasks.

Increased dietary α-linolenic acid has sex-specific effects upon eicosapentaenoic acid status in humans: re-examination of data from a randomised, placebo-controlled, parallel study

Background: There is a metabolic pathway by which mammals can convert the omega-3 (n-3) essential fatty acid α-linolenic acid (ALA) into longer-chain n-3 polyunsaturated fatty acids (LC n-3 PUFA) including eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). As far as we know there are currently no studies that have specifically examined sex differences in the LC n-3 PUFA response to increased dietary ALA intake in humans, although acute studies with isotope-labelled ALA identified that women have a significantly greater capacity to synthesise EPA and DHA from ALA compared to men. Findings: Available data from a placebo-controlled, randomised study were re-examined to identify whether there are sex differences in the LC n-3 PUFA response to increased dietary ALA intake in humans. There was a significant difference between sexes in the response to increased dietary ALA, with women having a significantly greater increase in the EPA content of plasma phospholipids (mean +2.0% of total fatty acids) after six months of an ALA-rich diet compared to men (mean +0.7%, P = 0.039). Age and BMI were identified as predictors of response to dietary ALA among women. Conclusions: Women show a greater increase in circulating EPA than men during increased dietary ALA consumption. Further understanding of individual variation in the response to dietary ALA could inform nutrition advice, with recommendations being specifically tailored according to habitual diet, sex, age and BMI.

Application of complex extreme learning machine to multiclass classification problems with high dimensionality: a THz spectra classification problem

We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.

A parallel formulation for the simulation of a generic branch predictor

A parallel formulation for the simulation of a branch prediction algorithm is presented. This parallel formulation identifies independent tasks in the algorithm which can be executed concurrently. The parallel implementation is based on the multithreading model and two parallel programming platforms: pthreads and Cilk++. Improvement in execution performance by up to 7 times is observed for a generic 2-bit predictor in a 12-core multiprocessor system.

Bit-index sort: a fast non-comparison integer sorting algorithm for permutations

This paper describes a fast integer sorting algorithm, herein referred as Bit-index sort, which is a non-comparison sorting algorithm for partial per-mutations, with linear complexity order in execution time. Bit-index sort uses a bit-array to classify input sequences of distinct integers, and exploits built-in bit functions in C compilers supported by machine hardware to retrieve the ordered output sequence. Results show that Bit-index sort outperforms in execution time to quicksort and counting sort algorithms. A parallel approach for Bit-index sort using two simultaneous threads is included, which obtains speedups up to 1.6.

Revisiting the ‘Venturi effect’ in passage ventilation between two non-parallel buildings

A recent study conducted by Blocken et al. (Numerical study on the existence of the Venturi effect in passages between perpendicular buildings. Journal of Engineering Mechanics, 2008,134: 1021-1028) challenged the popular view of the existence of the ‘Venturi effect’ in building passages as the wind is exposed to an open boundary. The present research extends the work of Blocken et al. (2008a) into a more general setup with the building orientation varying from 0° to 180° using CFD simulations. Our results reveal that the passage flow is mainly determined by the combination of corner streams. It is also shown that converging passages have a higher wind-blocking effect compared to diverging passages, explained by a lower wind speed and higher drag coefficient. Fluxes on the top plane of the passage volume reverse from outflow to inflow in the cases of α=135°, 150° and 165°. A simple mathematical expression to explain the relationship between the flux ratio and the geometric parameters has been developed to aid wind design in an urban neighborhood. In addition, a converging passage with α=15° is recommended for urban wind design in cold and temperate climates since the passage flow changes smoothly and a relatively lower wind speed is expected compared with that where there are no buildings. While for the high-density urban area in (sub)tropical climates such as Hong Kong where there is a desire for more wind, a diverging passage with α=150° is a better choice to promote ventilation at the pedestrian level.

Rotational aesthetics: Michael Bay and contemporary cinema’s machine movement

Digital imaging technologies enable a mastery of the visual that in recent mainstream cinema frequently manifests as certain kinds of spatial reach, orientation and motion. In such a context Michael Bay’s Transformers franchise can be framed as a digital re-tooling of a familiar fantasy of vehicular propulsion, US car culture writ large in digitally crafted spectacles of diegetic speed, the vehicular chase film ‘2.0’. Movement is central to these films, calling up Scott Bukatman’s observation that in spectacular visual media ‘movement has become more than a tool of bodily knowledge; it has become an end in itself’ (2003: 125). Not all movements and not all instances of vehicular propulsion are the same however. How might we evaluate what is at stake in a film’s assertion of movement as an end in itself, and the form that assertion takes, its articulations of diegetic velocity, corporeality, and spatial penetration? Deploying an attentiveness towards the specificity of aesthetic detail and affective impact in Bay’s delineation of movement, this essay suggests that the franchise poses questions about the relationship of human movement to machine movement that exceed their narrative basis. Identifying a persistent rotational trope in the franchise that in its audio-visual articulation combines oddly anachronistic elements (evoking the mechanical rather than the digital), the article argues that the films prioritise certain fantasies of transformation and spatial penetration, and certain modes of corporeality, as one response to contemporary debates about digital technologisation, sustainable energy, and cinematic spectacle. In this way the franchise also represents a particular moment in a more widely discernible preoccupation in contemporary cinema with what we might call a ‘rotational aesthetics’ of action, a machine movement made possible by the digital, but which invokes earlier histories and fantasies of animation, propulsion, mechanization and mechanization to particular ends.

A parallel data assimilation model for oceanographic observations

In this paper we describe the development of a program that aims at the optimal integration of observed data in an oceanographic model describ

GHASP: an H alpha kinematic survey of spiral and irregular galaxies - IX. The near-infrared, stellar and baryonic Tully-Fisher relations

We studied, for the first time, the near-infrared, stellar and baryonic Tully-Fisher relations for a sample of field galaxies taken from a homogeneous Fabry-Perot sample of galaxies [the Gassendi HAlpha survey of SPirals (GHASP) survey]. The main advantage of GHASP over other samples is that the maximum rotational velocities were estimated from 2D velocity fields, avoiding assumptions about the inclination and position angle of the galaxies. By combining these data with 2MASS photometry, optical colours, HI masses and different mass-to-light ratio estimators, we found a slope of 4.48 +/- 0.38 and 3.64 +/- 0.28 for the stellar and baryonic Tully-Fisher relation, respectively. We found that these values do not change significantly when different mass-to-light ratio recipes were used. We also point out, for the first time, that the rising rotation curves as well as asymmetric rotation curves show a larger dispersion in the Tully-Fisher relation than the flat ones or the symmetric ones. Using the baryonic mass and the optical radius of galaxies, we found that the surface baryonic mass density is almost constant for all the galaxies of this sample. In this study we also emphasize the presence of a break in the NIR Tully-Fisher relation at M(H,K) similar to -20 and we confirm that late-type galaxies present higher total-to-baryonic mass ratios than early-type spirals, suggesting that supernova feedback is actually an important issue in late-type spirals. Due to the well-defined sample selection criteria and the homogeneity of the data analysis, the Tully-Fisher relation for GHASP galaxies can be used as a reference for the study of this relation in other environments and at higher redshifts.