Adaptive linear combination of heuristic orderings in constructing examination timetables

In this paper, we investigate adaptive linear combinations of graph coloring heuristics with a heuristic modifier to address the examination timetabling problem. We invoke a normalisation strategy for each parameter in order to generalise the specific problem data. Two graph coloring heuristics were used in this study (largest degree and saturation degree). A score for the difficulty of assigning each examination was obtained from an adaptive linear combination of these two heuristics and examinations in the list were ordered based on this value. The examinations with the score value representing the higher difficulty were chosen for scheduling based on two strategies. We tested for single and multiple heuristics with and without a heuristic modifier with different combinations of weight values for each parameter on the Toronto and ITC2007 benchmark data sets. We observed that the combination of multiple heuristics with a heuristic modifier offers an effective way to obtain good solution quality. Experimental results demonstrate that our approach delivers promising results. We conclude that this adaptive linear combination of heuristics is a highly effective method and simple to implement.

A composite pollen-based stratotype for inter-regional evaluation of climatic events in New Zealand over the past 30,000 years (NZ-INTIMATE project)

Our review of paleoclimate information for New Zealand pertaining to the past 30,000 years has identified a general sequence of climatic events, spanning the onset of cold conditions marking the final phase of the Last Glaciation, through to the emergence to full interglacial conditions in the early Holocene. In order to facilitate more detailed assessments of climate variability and any leads or lags in the timing of climate changes across the region, a composite stratotype is proposed for New Zealand. The stratotype is based on terrestrial stratigraphic records and is intended to provide a standard reference for the intercomparison and evaluation of climate proxy records. We nominate a specific stratigraphic type record for each climatic event, using either natural exposure or drill core stratigraphic sections. Type records were selected on thebasis of having very good numerical age control and a clear proxy record. In all cases the main proxy of the type record is subfossil pollen. The type record for the period from ca 30 to ca 18 calendar kiloyears BP (cal. ka BP) is designated in lake-bed sediments from a small morainic kettle lake (Galway tarn) in western South Island. The Galway tarn type record spans a period of full glacial conditions (Last Glacial Coldest Period, LGCP) within the Otira Glaciation, and includes three cold stadials separated by two cool interstadials. The type record for the emergence from glacial conditions following the termination of the Last Glaciation (post-Termination amelioration) is in a core of lake sediments from a maar (Pukaki volcanic crater) in Auckland, northern North Island, and spans from ca 18 to 15.64±0.41 cal. ka BP. The type record for the Lateglacial period is an exposure of interbedded peat and mud at montane Kaipo bog, eastern North Island. In this high-resolution type record, an initial mild period was succeeded at 13.74±0.13 cal. ka BP by a cooler period, which after 12.55±0.14 cal. ka BP gave way to a progressive ascent to full interglacial conditions that were achieved by 11.88±0.18 cal. ka BP. Although a type section is not formally designated for the Holocene Interglacial (11.88±0.18 cal. ka BP to the present day), the sedimentary record of Lake Maratoto on the Waikato lowlands, northwestern North Island, is identified as a prospective type section pending the integration and updating of existing stratigraphic and proxy datasets, and age models. The type records are interconnected by one or more dated tephra layers, the ages of which are derived from Bayesian depositional modelling and OxCal-based calibrations using the IntCal09 dataset. Along with the type sections and the Lake Maratoto record, important, well-dated terrestrial reference records are provided for each climate event. Climate proxies from these reference records include pollen flora, stable isotopes from speleothems, beetle and chironomid fauna, and glacier moraines. The regional composite stratotype provides a benchmark against which to compare other records and proxies. Based on the composite stratotype, we provide an updated climate event stratigraphic classification for the New Zealand region. © 2013 Elsevier Ltd.

A simple disc wind model for broad absorption line quasars

Approximately 20 per cent of quasi-stellar objects (QSOs) exhibit broad, blue-shifted absorption lines in their ultraviolet spectra. Such features provide clear evidence for significant outflows from these systems, most likely in the form of accretion disc winds. These winds may represent the ‘quasar’ mode of feedback that is often invoked in galaxy formation/evolution models, and they are also key to unification scenarios for active galactic nuclei (AGN) and QSOs. To test these ideas, we construct a simple benchmark model of an equatorial, biconical accretion disc wind in a QSO and use a Monte Carlo ionization/radiative transfer code to calculate the ultraviolet spectra as a function of viewing angle. We find that for plausible outflow parameters, sightlines looking directly into the wind cone do produce broad, blue-shifted absorption features in the transitions typically seen in broad absorption line (BAL) QSOs. However, our benchmark model is intrinsically X-ray weak in order to prevent overionization of the outflow, and the wind does not yet produce collisionally excited line emission at the level observed in non-BAL QSOs. As a first step towards addressing these shortcomings, we discuss the sensitivity of our results to changes in the assumed X-ray luminosity and mass-loss rate, Ṁwind. In the context of our adopted geometry, Ṁwind ∼ Ṁacc is required in order to produce significant BAL features. The kinetic luminosity and momentum carried by such outflows would be sufficient to provide significant feedback.

Forecasting Death Rates Using Exogenous Determinants

Mortality models used for forecasting are predominantly based on the statistical properties of time series and do not generally incorporate an understanding of the forces driving secular trends. This paper addresses three research questions: Can the factors found in stochastic mortality-forecasting models be associated with real-world trends in health-related variables? Does inclusion of health-related factors in models improve forecasts? Do resulting models give better forecasts than existing stochastic mortality models? We consider whether the space spanned by the latent factor structure in mortality data can be adequately described by developments in gross domestic product, health expenditure and lifestyle-related risk factors using statistical techniques developed in macroeconomics and finance. These covariates are then shown to improve forecasts when incorporated into a Bayesian hierarchical model. Results are comparable or better than benchmark stochastic mortality models.

Evaluation of Corrosion Fatigue Behaviour of Laser-welded NiTi Alloys using Bending Rotation Fatigue Test in Simulated Body Fluid

Shape memory NiTi alloys have been used extensively for medical device applications such as orthopedic, dental, vascular and cardiovascular devices on account of their unique shape memory effect (SME) and super-elasticity (SE). Laser welding is found to be the most suitable method used to fabricate NiTi-based medical components. However, the performance of laser-welded NiTi alloys under corrosive environments is not fully understood and a specific focus on understanding the corrosion fatigue behaviour is not evident in the literature. This study reveals a comparison of corrosion fatigue behaviour of laser-welded and bare NiTi alloys using bending rotation fatigue (BRF) test which was integrated with a specifically designed corrosion cell. The testing environment was Hanks’ solution (simulated body fluid) at 37.5oC. Electrochemical impedance spectroscopic (EIS) measurement was carried out to monitor the change of corrosion resistance at different periods during the BRF test. Experiments indicate that the laser-welded NiTi alloy would be more susceptible to the corrosion fatigue attack than the bare NiTi alloy. This finding can serve as a benchmark for the product designers and engineers to determine the factor of safety of NiTi medical devices fabricated using laser welding.

A function-based treatment package aiming at decreasing self-injurious behaviour and tantrums.

Self-injurious and aggressive behaviours have often been identified as the cause for students’ lack of academic progress, parental distress, health risks and teachers´ low satisfaction levels. Functional analysis has been identified in the research literature as the benchmark of effective treatments for disruptive and/or inappropriate behaviours. The present study was completed with a girl diagnosed with ASD. An experimental functional analysis was conducted identifying the function of self-injurious behaviours and tantrums to be escaping from tasks. A treatment package was consequently put in place integrating several components that aimed at reducing overall levels of inappropriate behaviours. Results showed a clear and meaningful improvement in the student´s overall health and academic progress, as well as in parental involvement, teachers’ satisfaction and school inclusion. These outcomes are discussed in the light of evidence-based experimental procedures based on applied behaviour analysis and more specifically on the functional-analytic literature, which, if put in place consistently, can bring valuable positive changes in the quality of life of individuals with ASD.

Resonantly Enhanced Multi-Photon Ionization Spectrum of the Neutral Green Fluorescent Protein Chromophore

The photophysics of the green fluorescent protein is governed by the electronic structure of the chromophore at the heart of its β-barrel protein structure. We present the first two-color, resonance-enhanced, multiphoton ionization spectrum of the isolated neutral chromophore in vacuo with supporting electronic structure calculations. We find the absorption maximum to be 3.65 ± 0.05 eV (340 ± 5 nm), which is blue-shifted by 0.5 eV (55 nm) from the absorption maximum of the protein in its neutral form. Our results show that interactions between the chromophore and the protein have a significant influence on the electronic structure of the neutral chromophore during photoabsorption and provide a benchmark for the rational design of novel chromophores as fluorescent markers or photomanipulators.

Fair charging strategies for EVs connected to a low-voltage distribution network

The development of smart grid technologies and appropriate charging strategies are key to accommodating large numbers of Electric Vehicles (EV) charging on the grid. In this paper a general framework is presented for formulating the EV charging optimization problem and three different charging strategies are investigated and compared from the perspective of charging fairness while taking into account power system constraints. Two strategies are based on distributed algorithms, namely, Additive Increase and Multiplicative Decrease (AIMD), and Distributed Price-Feedback (DPF), while the third is an ideal centralized solution used to benchmark performance. The algorithms are evaluated using a simulation of a typical residential low voltage distribution network with 50% EV penetration. © 2013 IEEE.

MSC-clustering and forward stepwise regression for virtual metrology in highly correlated input spaces

Increasingly semiconductor manufacturers are exploring opportunities for virtual metrology (VM) enabled process monitoring and control as a means of reducing non-value added metrology and achieving ever more demanding wafer fabrication tolerances. However, developing robust, reliable and interpretable VM models can be very challenging due to the highly correlated input space often associated with the underpinning data sets. A particularly pertinent example is etch rate prediction of plasma etch processes from multichannel optical emission spectroscopy data. This paper proposes a novel input-clustering based forward stepwise regression methodology for VM model building in such highly correlated input spaces. Max Separation Clustering (MSC) is employed as a pre-processing step to identify a reduced srt of well-conditioned, representative variables that can then be used as inputs to state-of-the-art model building techniques such as Forward Selection Regression (FSR), Ridge regression, LASSO and Forward Selection Ridge Regression (FCRR). The methodology is validated on a benchmark semiconductor plasma etch dataset and the results obtained are compared with those achieved when the state-of-art approaches are applied directly to the data without the MSC pre-processing step. Significant performance improvements are observed when MSC is combined with FSR (13%) and FSRR (8.5%), but not with Ridge Regression (-1%) or LASSO (-32%). The optimal VM results are obtained using the MSC-FSR and MSC-FSRR generated models. © 2012 IEEE.

Machine Learning for Predictive Maintenance: A Multiple Classifiers Approach

In this paper a multiple classifier machine learning methodology for Predictive Maintenance (PdM) is presented. PdM is a prominent strategy for dealing with maintenance issues given the increasing need to minimize downtime and associated costs. One of the challenges with PdM is generating so called ’health factors’ or quantitative indicators of the status of a system associated with a given maintenance issue, and determining their relationship to operating costs and failure risk. The proposed PdM methodology allows dynamical decision rules to be adopted for maintenance management and can be used with high-dimensional and censored data problems. This is achieved by training multiple classification modules with different prediction horizons to provide different performance trade-offs in terms of frequency of unexpected breaks and unexploited lifetime and then employing this information in an operating cost based maintenance decision system to minimise expected costs. The effectiveness of the methodology is demonstrated using a simulated example and a benchmark semiconductor manufacturing maintenance problem.

On Regression Methods for Virtual Metrology in Semiconductor Manufacturing

Virtual metrology (VM) aims to predict metrology values using sensor data from production equipment and physical metrology values of preceding samples. VM is a promising technology for the semiconductor manufacturing industry as it can reduce the frequency of in-line metrology operations and provide supportive information for other operations such as fault detection, predictive maintenance and run-to-run control. The prediction models for VM can be from a large variety of linear and nonlinear regression methods and the selection of a proper regression method for a specific VM problem is not straightforward, especially when the candidate predictor set is of high dimension, correlated and noisy. Using process data from a benchmark semiconductor manufacturing process, this paper evaluates the performance of four typical regression methods for VM: multiple linear regression (MLR), least absolute shrinkage and selection operator (LASSO), neural networks (NN) and Gaussian process regression (GPR). It is observed that GPR performs the best among the four methods and that, remarkably, the performance of linear regression approaches that of GPR as the subset of selected input variables is increased. The observed competitiveness of high-dimensional linear regression models, which does not hold true in general, is explained in the context of extreme learning machines and functional link neural networks.

Automated tumour annotation and analysis for molecular pathology using TissueMark (R)

Objective: Molecular pathology relies on identifying anomalies using PCR or analysis of DNA/RNA. This is important in solid tumours where molecular stratification of patients define targeted treatment. These molecular biomarkers rely on examination of tumour, annotation for possible macro dissection/tumour cell enrichment and the estimation of % tumour. Manually marking up tumour is error prone. Method: We have developed a method for automated tumour mark-up and % cell calculations using image analysis called TissueMark® based on texture analysis for lung, colorectal and breast (cases=245, 100, 100 respectively). Pathologists marked slides for tumour and reviewed the automated analysis. A subset of slides was manually counted for tumour cells to provide a benchmark for automated image analysis. Results: There was a strong concordance between pathological and automated mark-up (100 % acceptance rate for macro-dissection). We also showed a strong concordance between manually/automatic drawn boundaries (median exclusion/inclusion error of 91.70 %/89 %). EGFR mutation analysis was precisely the same for manual and automated annotation-based macrodissection. The annotation accuracy rates in breast and colorectal cancer were 83 and 80 % respectively. Finally, region-based estimations of tumour percentage using image analysis showed significant correlation with actual cell counts. Conclusion: Image analysis can be used for macro-dissection to (i) annotate tissue for tumour and (ii) estimate the % tumour cells and represents an approach to standardising/improving molecular diagnostics.

ELM-induced transient tungsten melting in the JET divertor

The original goals of the JET ITER-like wall included the study of the impact of an all W divertor on plasma operation (Coenen et al 2013 Nucl. Fusion 53 073043) and fuel retention (Brezinsek et al 2013 Nucl. Fusion 53 083023). ITER has recently decided to install a full-tungsten (W) divertor from the start of operations. One of the key inputs required in support of this decision was the study of the possibility of W melting and melt splashing during transients. Damage of this type can lead to modifications of surface topology which could lead to higher disruption frequency or compromise subsequent plasma operation. Although every effort will be made to avoid leading edges, ITER plasma stored energies are sufficient that transients can drive shallow melting on the top surfaces of components. JET is able to produce ELMs large enough to allow access to transient melting in a regime of relevance to ITER.

Transient W melt experiments were performed in JET using a dedicated divertor module and a sequence of I-P = 3.0 MA/B-T = 2.9 T H-mode pulses with an input power of P-IN = 23 MW, a stored energy of similar to 6 MJ and regular type I ELMs at Delta W-ELM = 0.3 MJ and f(ELM) similar to 30 Hz. By moving the outer strike point onto a dedicated leading edge in the W divertor the base temperature was raised within similar to 1 s to a level allowing transient, ELM-driven melting during the subsequent 0.5 s. Such ELMs (delta W similar to 300 kJ per ELM) are comparable to mitigated ELMs expected in ITER (Pitts et al 2011 J. Nucl. Mater. 415 (Suppl.) S957-64).

Although significant material losses in terms of ejections into the plasma were not observed, there is indirect evidence that some small droplets (similar to 80 mu m) were released. Almost 1 mm (similar to 6 mm(3)) of W was moved by similar to 150 ELMs within 7 subsequent discharges. The impact on the main plasma parameters was minor and no disruptions occurred. The W-melt gradually moved along the leading edge towards the high-field side, driven by j x B forces. The evaporation rate determined from spectroscopy is 100 times less than expected from steady state melting and is thus consistent only with transient melting during the individual ELMs. Analysis of IR data and spectroscopy together with modelling using the MEMOS code Bazylev et al 2009 J. Nucl. Mater. 390-391 810-13 point to transient melting as the main process. 3D MEMOS simulations on the consequences of multiple ELMs on damage of tungsten castellated armour have been performed.

These experiments provide the first experimental evidence for the absence of significant melt splashing at transient events resembling mitigated ELMs on ITER and establish a key experimental benchmark for the MEMOS code.

Accelerating integer-based fully homomorphic encryption using Comba multiplication

Fully Homomorphic Encryption (FHE) is a recently developed cryptographic technique which allows computations on encrypted data. There are many interesting applications for this encryption method, especially within cloud computing. However, the computational complexity is such that it is not yet practical for real-time applications. This work proposes optimised hardware architectures of the encryption step of an integer-based FHE scheme with the aim of improving its practicality. A low-area design and a high-speed parallel design are proposed and implemented on a Xilinx Virtex-7 FPGA, targeting the available DSP slices, which offer high-speed multiplication and accumulation. Both use the Comba multiplication scheduling method to manage the large multiplications required with uneven sized multiplicands and to minimise the number of read and write operations to RAM. Results show that speed up factors of 3.6 and 10.4 can be achieved for the encryption step with medium-sized security parameters for the low-area and parallel designs respectively, compared to the benchmark software implementation on an Intel Core2 Duo E8400 platform running at 3 GHz.