Alignment model for trunk road network maintenance outsourcing

Road maintenance outsourcing is now the foremost strategy by which road authorities procure maintenance works. Despite growing application of road maintenance outsourcing, there are conflicting estimates on the effective­ness of road maintenance outsourcing and shortage of appropriate models to align over optimistic expectations of road authorities from road maintenance outsourcing with substantiated benefits. This paper investigates the efficacy of road maintenance outsourcing. In this paper, the different variants of road maintenance outsourcing and road maintenance works are evaluated with a SWOT analysis and a comprehensive literature review respectively. In addition, a road main­tenance outsourcing alignment model based on a decision tree and Balance Score Card is proposed and illustrated with a Nigerian trunk road network authority as a case study. The result of the SWOT analysis and comprehensive literature review establishes fresh insight into road maintenance outsourcing dynamics. The presented road maintenance outsourc­ing alignment model provides adequate pathways that could assist road authorities identify the most appropriate road maintenance outsourcing variant for road maintenance procurement. In addition it aligns actual benefits and expectations of road maintenance outsourcing and facilitates development of SMART metrics for effective assessment of road main­tenance outsourcing. The proposed model is applicable across other infrastructures. First published online: 01 Sep 201

Journal publishing with Acrobat: the CAJUN project

The publication of material in electronic form should ideally preserve, in a unified document representation, all of the richness of the printed document while maintaining enough of its underlying structure to enable searching and other forms of semantic processing. Until recently it has been hard to find a document representation which combined these attributes and which also stood some chance of becoming a de facto multi-platform standard. This paper sets out experience gained within the Electronic Publishing Research Group at the University of Nottingham in using Adobe Acrobat software and its underlying PDF (Portable Document Format) notation. The CAJUN project1 (CD-ROM Acrobat Journals Using Networks) began in 1993 and has used Acrobat software to produce electronic versions of journal papers for network and CD-ROM dissemination. The paper describes the project's progress so far and also gives a brief assessment of PDF's suitability as a universal document interchange standard

Optimization of graded multilayer designs for astronomical x-ray telescopes

We developed a systematic method for optimizing the design of depth-graded multilayers for astronomical hard-x-ray and soft-γ-ray telescopes based on the instrument’s bandpass and the field of view. We apply these methods to the design of the conical-approximation Wolter I optics employed by the balloon-borne High Energy Focusing Telescope, using W/Si as the multilayer materials. In addition, we present optimized performance calculations of mirrors, using other material pairs that are capable of extending performance to photon energies above the W K-absorption edge (69.5 keV), including Pt/C, Ni/C, Cu/Si, and Mo/Si

Characterising the tumour morphological response to therapeutic intervention:an ex vivo model

In cancer, morphological assessment of histological tissue samples is a fundamental part of both diagnosis and prognosis. Image analysis offers opportunities to support that assessment through quantitative metrics of morphology. Generally, morphometric analysis is carried out on two dimensional tissue section data and so only represents a small fraction of any tumour. We present a novel application of three-dimensional (3D) morphometrics for 3D imaging data obtained from tumours grown in a culture model. Minkowski functionals, a set of measures that characterise geometry and topology in n-dimensional space, are used to quantify tumour topology in the absence of and in response to therapeutic intervention. These measures are used to stratify the morphological response of tumours to therapeutic intervention. Breast tumours are characterised by estrogen receptor (ER) status, human epidermal growth factor receptor (HER)2 status and tumour grade. Previously, we have shown that ER status is associated with tumour volume in response to tamoxifen treatment ex vivo. Here, HER2 status is found to predict the changes in morphology other than volume as a result of tamoxifen treatment ex vivo. Finally, we show the extent to which Minkowski functionals might be used to predict tumour grade.Minkowski functionals are generalisable to any 3D data set, including in vivo and cellular systems. This quantitative topological analysis can provide a valuable link among biomarkers, drug intervention and tumour morphology that is complementary to existing, non-morphological measures of tumour response to intervention and could ultimately inform patient treatment

Anomaly Detection Methods to Improve Supply Chain Data Quality and Operations

Supply chain operations drive the planning, manufacture, and distribution of billions of semiconductors a year, spanning thousands of products across many supply chain configurations. The customizations span from wafer technology to die stacking and chip feature enablement. Data quality drives efficiency in these processes and anomalies in data can be very disruptive, and at times, consequential. Developing preventative measures that automate the detection of anomalies before they reach downstream execution systems would result in significant efficiency gain for the organization. The purpose of this research is to identify an effective, actionable, and computationally efficient approach to highlight anomalies in a sparse and highly variable supply chain data structure. This research highlights the application of ensemble unsupervised learning algorithms for anomaly detection on supply chain demand data. The outlier detection algorithms explored include Angle-Based Outlier Detection, Isolation Forest, Local Outlier Factor and K-Nearest Neighbors. The application of an ensemble technique on unconstrained forecast signal, which is traditionally a consistent demand line, demonstrated a dramatic decrease in false positives. The application of the ensemble technique to the sales-order netted demand forecast, a signal that is irregular in structure, the algorithm identifies true anomalous observations relative to historical observations across time. The research team concluded that assessing an outlier is not limited to the most recent forecast’s observations but must be considered in the context of historical demand patterns across time