A flexible,object-centric approach for business process modelling

Mainstream business process modelling techniques often promote a design paradigm wherein the activities that may be performed within a case, together with their usual execution order, form the backbone on top of which other aspects are anchored. This Fordist paradigm, while effective in standardised and production-oriented domains, breaks when confronted with processes in which case-by-case variations and exceptions are the norm. We contend that the effective design of flexible processes calls for a substantially different modelling paradigm. Motivated by requirements from the human services domain, we explore the hypothesis that a framework consisting of a small set of coordination concepts, combined with established object-oriented modelling principles, provides a suitable foundation for designing highly flexible processes. Several human service delivery processes have been designed using this framework, and the resulting models have been used to realise a system to support these processes in a pilot environment.     

Effects of soil composition and mineralogy on remote sensing of crop residue cover

The management of crop residues (non-photosynthetic vegetation) in agricultural fields influences soil erosion and soil carbon sequestration. Remote sensing methods can efficiently assess crop residue cover and related tillage intensity over many fields in a region. Although the reflectance spectra of soils and crop residues are often similar in the visible, near infrared, and the lower part of the shortwave infrared (400-1900 nm) wavelength region, specific diagnostic chemical absorption features are evident in the upper shortwave infrared (1900-2500 nm) region. Two reflectance band height indices used for estimating residue cover are the Cellulose Absorption Index (CAI) and the Lignin-Cellulose Absorption (LCA) index, both of which use reflectances in the upper shortwave infrared (SWIR). Soil mineralogy and composition will affect soil spectral properties and may limit the usefulness of these spectral indices in certain areas. Our objectives were to (1) identify minerals and soil components with absorption features in the 2000 nm to 2400 nm wavelength region that would affect CAI and LCA and (2) assess their potential impact on remote sensing estimates of crop residue cover. Most common soil minerals had CAI values ≤ 0.5, whereas crop residues were always > 0.5, allowing for good contrast between soils and residues. However, a number of common soil minerals had LCA values > 0.5, and, in some cases, the mineral LCA values were greater than those of the crop residues, which could limit the effectiveness of LCA for residue cover estimation. The LCA of some dry residues and live corn canopies were similar in value, unlike CAI. Thus, the Normalized Difference Vegetation Index (NDVI) or similar method should be used to separate out green vegetation pixels. Mineral groups, such as garnets and chlorites, often have wide ranges of CAI and LCA values, and thus, mineralogical analyses often do not identify individual mineral species required for precise CAI estimation. However, these methods are still useful for identifying mineral soils requiring additional scrutiny. Future advanced multi- and hyperspectral remote sensing platforms should include CAI bands to allow for crop residue cover estimation.     

Fast Object Segmentation by Growing Minimal Paths from a Single Point on 2D or 3D Images

In this paper, we present a new method for segmenting closed contours and surfaces. Our work builds on a variant of the minimal path approach. First, an initial point on the desired contour is chosen by the user. Next, new keypoints are detected automatically using a front propagation approach. We assume that the desired object has a closed boundary. This a-priori knowledge on the topology is used to devise a relevant criterion for stopping the keypoint detection and front propagation. The final domain visited by the front will yield a band surrounding the object of interest. Linking pairs of neighboring keypoints with minimal paths allows us to extract a closed contour from a 2D image. This approach can also be used for finding an open curve giving extra information as stopping criteria. Detection of a variety of objects on real images is demonstrated. Using a similar idea, we can extract networks of minimal paths from a 3D image called Geodesic Meshing. The proposed method is applied to 3D data with promising results.

Characterising and exploiting workloads of highly interactive video-on-demand

This paper presents a detailed characterisation of user behaviour for a series of interactive video experiments over a 12 month period, in which we served popular sporting and musical content. In addition to generic VCR-like features, our custom-built video-on-demand application provides advanced interactivity features such as bookmarking. The dramatic impact of such functionality on how users consume content is studied and analysed. We discuss in detail how this user behaviour can be exploited by content distributors to improve user experience. Specifically, we study how simple dynamic bookmark placement and interactivity-aware content pre-fetching and replication can reduce the impact of highly interactive media on CDN performance.     

Ahead of time static analysis for automatic generation of debugging interfaces to the Linux kernel

The Linux kernel does not export a stable, well-defined kernel interface, complicating the development of kernel-level services, such as device drivers and file systems. While there does exist a set of functions that are exported to external modules, this set of functions frequently changes, and the functions have implicit, ill-documented preconditions. No specific debugging support is provided. We present Diagnosys, an approach to automatically constructing a debugging interface for the Linux kernel. First, a designated kernel maintainer uses Diagnosys to identify constraints on the use of the exported functions. Based on this information, developers of kernel services can then use Diagnosys to generate a debugging interface specialized to their code. When a service including this interface is tested, it records information about potential problems. This information is preserved following a kernel crash or hang. Our experiments show that the generated debugging interface provides useful log information and incurs a low performance penalty.     

SEBS elastomers for fabrication of microfluidic devices with reduced drug absorption by injection molding and extrusion

The majority of microfluidic devices used for cell culture, including Organ-on-a-Chips (Organ Chips), are fabricated using polydimethylsiloxane (PDMS) polymer because it is flexible, optically clear, and easy to mold. However, PDMS possesses significant challenges for high volume manufacturing and its tendency to absorb small hydrophobic compounds limits its usefulness as a material in devices used for drug evaluation studies. Here, we demonstrate that a subset of optically clear, elastomeric, styrenic block copolymers based on styrene-ethylene-butylene-styrene exhibit reduced absorption of small hydrophobic molecules and drug compounds compared to PDMS and that they can be fabricated into microfluidic devices with fine features and the flexibility required for Organ Chips using mass production techniques of injection molding and extrusion.     

Simultaneous automated design of structured QFT controller and prefilter using nonlinear programming

This paper describes a nonlinear programming‐based robust design methodology for controllers and prefilters of a predefined structure for the linear time‐invariant systems involved in the quantitative feedback theory. This controller and prefilter synthesis problem is formulated as a single optimization problem with a given performance optimization objective and constraints enforcing stability and various specifications usually enforced in the quantitative feedback theory. The focus is set on providing constraints expression that can be used in standard nonlinear programming solvers. The nonlinear solver then computes in a single‐step controller and prefilter design parameters that satisfy the prescribed constraints and maximizes the performance optimization objective. The effectiveness of the proposed approach is demonstrated through a variety of difficult design cases like resonant plants, open‐loop unstable plants, and plants with variation in the time delay. Copyright © 2016 John Wiley & Sons, Ltd.     

On the performance of high-gain observers with gain adaptation under measurement noise

We address the problem of state observation for a system whose dynamics may involve poorly known, perhaps even nonlocally Lipschitz functions and whose output measurement may be corrupted by noise. It is known that one way to cope with all these uncertainties and noise is to use a high-gain observer with a gain adapted on-line. The proposed method, while presented for a particular case, relies on a “generic” analysis tool based on the study of differential inequalities involving quadratic functions of the error system in two coordinate frames plus the gain adaptation law. We establish that, for bounded system solutions, the estimated state and the gain are bounded. Moreover, we provide an upper bound for the mean value of the error signals as a function of the observer parameters. Since due to perturbations the gain adaptation law may drive the observer/plant interconnection to nearby boundary of its stability region, oscillatory behavior may emerge. To overcome this issue, we suggest an adaptive procedure based on a space averaging technique involving several copies of the observer.