Managing ICT costs in e-commerce organizations with the time-driven activity-based costing model: a note

As online business activities continue to grow, it is important for organizations to understand the implications of being an e-commerce organization and the appropriateness of applying existing business techniques to e-commerce organizations. This paper examines issues in managing information and communication technologies (ICT) costs in e-commerce organizations and the potentials of the Time-Driven Activity-Based Costing (TDABC) model as a solution to these issues. The reliance on ICT in value creation, the unique natures of ICT costs and the need to maintain updated costing models present new challenges to e-commerce organizations in management of ICT costs. The TDABC model, as a variant of the Activity-Based Costing (ABC) model, inherits the strengths of activity-based paradigm and has unique features that can provide additional benefits to e-commerce organizations.

A review of computational fluid dynamics applications in pressure-driven membrane filtration

Ongoing advances in computational performance and numerics have led to computational fluid dynamics (CFD) becoming a ubiquitous modelling tool. However, CFD methods have only been adopted to simulate pressure-driven membrane filtration systems relatively recently. This paper reviews various approaches to describing the behaviour of these systems using CFD, beginning with the hydrodynamics of membrane channels, including discussion of laminar, turbulent, and transition flow regimes, with reference to the effects of osmotic pressure, concentration polarisation, and cake formation. The use of CFD in describing mass transfer through the membrane itself is then discussed, followed by some concluding comments on commercial membrane simulation packages and future research directions in membrane CFD. © 2013 Springer Science+Business Media Dordrecht.

Sunlight-driven synthesis of anisotropic silver nanoparticles

Photoinduced shape conversion of silver nanoparticles was realized using sunlight. The silver seeds were transformed to silver nanoprisms under sunlight when the concentration of citrate was low (≤5.0×10-4M). Nevertheless, sunlight converted the obtained silver nanoprisms to silver nanodecahedrons when the concentration of citrate in reaction system was increased. It was found that the ultraviolet light from sunlight played a vital role in the shape conversion from nanoprism to nanodecahedron. Lighting power density did not influence the shape conversion except for reaction rate. Besides, the silver nanodecahedrons were synthesized in the mixed solution of AgNO3 and citrate in absence of silver seeds through irradiation by simulated sunlight. The mechanism on the sunlight induced synthesis of silver nanoparticles was discussed. Anisotropic silver nanoparticles including nanoprisms and nanodecahedrons were obtained through controlling the citrate concentration and irradiation time by sunlight from green light source.

Polyoxometalate-based hybrid organogels prepared from a triblock copolymer via charge-driven assembly

We report a novel approach for the preparation of polyoxometalate-based hybrid organogels from a triblock copolymer via charge-induced assembly. The triblock copolymer used is poly(4-vinyl pyridine)-block-poly(ethylene glycol)-block-poly(4-vinyl pyridine) (4VPm-EGn-4VP m), and polyoxometalate (POM) is phosphotungstic acid (HPW). The ionic interaction between the pyridine groups of the 4VPm-EG n-4VPm and HPW drives the assembly of the triblock copolymer to form solvophobic cores. The PEG middle blocks connect and stabilize the different cores to form hybrid organogels. The structures of POM remain unchanged in these hybrid organogels, and the properties of POMs can be preserved, which has been confirmed by the existence of photo-reduction properties of POM in the hybrid organogels. © 2014 the Partner Organisations.

Intervention-driven predictive framework for modeling healthcare data

Assessing prognostic risk is crucial to clinical care, and critically dependent on both diagnosis and medical interventions. Current methods use this augmented information to build a single prediction rule. But this may not be expressive enough to capture differential effects of interventions on prognosis. To this end, we propose a supervised, Bayesian nonparametric framework that simultaneously discovers the latent intervention groups and builds a separate prediction rule for each intervention group. The prediction rule is learnt using diagnosis data through a Bayesian logistic regression. For inference, we develop an efficient collapsed Gibbs sampler. We demonstrate that our method outperforms baselines in predicting 30-day hospital readmission using two patient cohorts - Acute Myocardial Infarction and Pneumonia. The significance of this model is that it can be applied widely across a broad range of medical prognosis tasks. © 2014 Springer International Publishing.

Representing images using curvilinear feature driven subdivision surfaces.

This paper presents a subdivision-based vector graphics for image representation and creation. The graphics representation is a subdivision surface defined by a triangular mesh augmented with color attribute at vertices and feature attribute at edges. Special cubic B-splines are proposed to describe curvilinear features of an image. New subdivision rules are then designed accordingly, which are applied to the mesh and the color attribute to define the spatial distribution and piecewise-smoothly varying colors of the image. A sharpness factor is introduced to control the color transition across the curvilinear edges. In addition, an automatic algorithm is developed to convert a raster image into such a vector graphics representation. The algorithm first detects the curvilinear features of the image, then constructs a triangulation based on the curvilinear edges and feature attributes, and finally iteratively optimizes the vertex color attributes and updates the triangulation. Compared with existing vector-based image representations, the proposed representation and algorithm have the following advantages in addition to the common merits (such as editability and scalability): 1) they allow flexible mesh topology and handle images or objects with complicated boundaries or features effectively; 2) they are able to faithfully reconstruct curvilinear features, especially in modeling subtle shading effects around feature curves; and 3) they offer a simple way for the user to create images in a freehand style. The effectiveness of the proposed method has been demonstrated in experiments.

3D Intervertebral disc localization and segmentation from MR images by data-driven regression and classification

In this paper we propose a new fully-automatic method for localizing and segmenting 3D intervertebral discs from MR images, where the two problems are solved in a unified data-driven regression and classification framework. We estimate the output (image displacements for localization, or fg/bg labels for segmentation) of image points by exploiting both training data and geometric constraints simultaneously. The problem is formulated in a unified objective function which is then solved globally and efficiently. We validate our method on MR images of 25 patients. Taking manually labeled data as the ground truth, our method achieves a mean localization error of 1.3 mm, a mean Dice metric of 87%, and a mean surface distance of 1.3 mm. Our method can be applied to other localization and segmentation tasks.

On the determination of the number of factors using information criteria with data-driven penalty

As is well known, when using an information criterion to select the number of common factors in factor models the appropriate penalty is generally indetermine in the sense that it can be scaled by an arbitrary constant, c say, without affecting consistency. In an influential paper, Hallin and Liška (J Am Stat Assoc102:603–617, 2007) proposes a data-driven procedure for selecting the appropriate value of c. However, by removing one source of indeterminacy, the new procedure simultaneously creates several new ones, which make for rather complicated implementation, a problem that has been largely overlooked in the literature. By providing an extensive analysis using both simulated and real data, the current paper fills this gap.

Securitising participation in the Philippines: KALAHI and community-driven participation

Participatory approaches to development have been implemented increasingly. One form is the World Bank’s community-driven development (CDD) programme. Participation has, also, become increasingly securitised since 2001. One instance of these trends was the Kapit-Bisig Laban sa Kahirapan (KALAHI) project in the Philippines. This paper examines the implementation of CDD and the problems of its securitisation, using the Philippines as a case study. A composite conceptual framework is advanced that draws upon the international analyses of development. Adapting the concepts of securitisation and de-politicisation, it argues that a new hegemonic-development framework has appeared: the Securitised-Washington consensus. The analysis assesses these trends through the examples of KALAHI and Philippine politics and economics. It suggests that securitised CDD projects result in token efforts at political reform and poverty alleviation that often are contradicted by counter-trends towards development decline and militarisation. Unless these deep-rooted problems are confronted, localised participation is likely to remain ineffectual.

A modelling study of transient, buoyancy-driven exchange flow over a descending barrier

Results are presented from a series of model studies of the transient exchange flow resulting from the steady descent of an impermeable barrier separating initially-quiescent fresh and saline water bodies having density ρ0 and ρ0 + (Δρ)0, respectively. A set of parametric laboratory experiments has been carried out (i) to determine the characteristic features of the time-dependent exchange flow over the barrier crest and (ii) to quantify the temporal increase in the thickness and spatial extent of the brackish water reservoir formed behind the barrier by the outflowing, partly-mixed saline water. The results of the laboratory experiments have been compared with the predictions of a theoretical model adapted from the steady, so-called maximal exchange flow case and good qualitative agreement between theory and experiment has been demonstrated. The comparisons indicate that head losses of between 7% and 3% are applicable to the flow over the ridge crest in the early and late stages, respectively, of the barrier descent phase, with these losses being attributed to mixing processes associated with the counterflowing layers of fresh and saline water in the vicinity of the ridge crest. The experimental data show (and the theoretical model predictions confirm) that (i) the dimensionless time of detection tdet (g′/Hb)1/2 of the brackish water pool fed by the dense outflow increases (at a given distance from the barrier) with increasing values of the descent rate parameter g'Hb/(dhb/dt)2 and (ii) the normalised thickness δ(x,t)/Hb of the pool at a given reference station increases monotonically with increasing values of the modified time (t - tdet)/(Hb/g′) 1/2, with the rate of thickening decreasing with increasing values of the descent rate parameter g'Hb (dhb/dt)2. Here, g′ = (g/ρ0) (Δρ)0 is the modified gravitational acceleration, Hb is the mean depth of the water and dhb/dt denotes the rate of descent of the barrier height hb with elapsed time t after the two water bodies are first brought into contact. © 2004 Kluwer Academic Publishers.

Localization and degmentation of 3D intervertebral discs in MR Images by data driven estimation

This paper addresses the problem of fully-automatic localization and segmentation of 3D intervertebral discs (IVDs) from MR images. Our method contains two steps, where we first localize the center of each IVD, and then segment IVDs by classifying image pixels around each disc center as foreground (disc) or background. The disc localization is done by estimating the image displacements from a set of randomly sampled 3D image patches to the disc center. The image displacements are estimated by jointly optimizing the training and test displacement values in a data-driven way, where we take into consideration both the training data and the geometric constraint on the test image. After the disc centers are localized, we segment the discs by classifying image pixels around disc centers as background or foreground. The classification is done in a similar data-driven approach as we used for localization, but in this segmentation case we are aiming to estimate the foreground/background probability of each pixel instead of the image displacements. In addition, an extra neighborhood smooth constraint is introduced to enforce the local smoothness of the label field. Our method is validated on 3D T2-weighted turbo spin echo MR images of 35 patients from two different studies. Experiments show that compared to state of the art, our method achieves better or comparable results. Specifically, we achieve for localization a mean error of 1.6-2.0 mm, and for segmentation a mean Dice metric of 85%-88% and a mean surface distance of 1.3-1.4 mm.

A suite of visual languages for model-driven development of statistical surveys and services

Objective: To provide statistician end users with a visual language environment for complex statistical survey design and implementation. Methods: We have developed, in conjunction with professional statisticians, the Statistical Design Language (SDL), an integrated suite of visual languages aimed at supporting the process of designing statistical surveys, and its support environment, SDLTool. SDL comprises five diagrammatic notations: survey diagrams, data diagrams, technique diagrams, task diagrams and process diagrams. SDLTool provides an integrated environment supporting design, coordination, execution, sharing and publication of complex statistical survey techniques as web services. SDLTool allows association of model components with survey artefacts, including data sets, metadata, and statistical package analysis scripts, with the ability to execute elements of the survey design model to implement survey analysis. Results: We describe three evaluations of SDL and SDLTool: use of the notation by expert statistician to design and execute surveys; useability evaluation of the environment; and assessment of several generated statistical analysis web services. Conclusion: We have shown the effectiveness of SDLTool for supporting statistical survey design and implementation. Practice implications: We have developed a more effective approach to supporting statisticians in their survey design work.