A decision support framework for prioritization of engineering asset management activities under uncertainty

Engineers and asset managers must often make decisions on how to best allocate limited resources amongst different interrelated activities, including repair, renewal, inspection, and procurement of new assets. The presence of project interdependencies and the lack of sufficient information on the true value of an activity often produce complex problems and leave the decision maker guessing about the quality and robustness of their decision. In this paper, a decision support framework for uncertain interrelated activities is presented. The framework employs a methodology for multi-criteria ranking in the presence of uncertainty, detailing the effect that uncertain valuations may have on the priority of a particular activity. The framework employs employing semi-quantitative risk measures that can be tailored to an organisation and enable a transparent and simple-to-use uncertainty specification by the decision maker. The framework is then demonstrated on a real world project set from a major Australian utility provider.

Complex Symbolic Sequence Encodings for Predictive Monitoring of Business Processes

This paper addresses the problem of predicting the outcome of an ongoing case of a business process based on event logs. In this setting, the outcome of a case may refer for example to the achievement of a performance objective or the fulfillment of a compliance rule upon completion of the case. Given a log consisting of traces of completed cases, given a trace of an ongoing case, and given two or more possible out- comes (e.g., a positive and a negative outcome), the paper addresses the problem of determining the most likely outcome for the case in question. Previous approaches to this problem are largely based on simple symbolic sequence classification, meaning that they extract features from traces seen as sequences of event labels, and use these features to construct a classifier for runtime prediction. In doing so, these approaches ignore the data payload associated to each event. This paper approaches the problem from a different angle by treating traces as complex symbolic sequences, that is, sequences of events each carrying a data payload. In this context, the paper outlines different feature encodings of complex symbolic sequences and compares their predictive accuracy on real-life business process event logs.

Conjoint use of Dibenzosilole and Indan-1,3-dione Functionalities to Prepare an Efficient Non-Fullerene Acceptor for Solution-Processable Bulk-Heterojunction Solar Cells

A solution-processable, non-fullerene electron acceptor, 2,2′-(((5,5-dioctyl-5 H-dibenzo[b,d]silole-3,7-diyl)bis(thiophene-5,2-diyl))bis(methanylylidene))bis(1 H-indene-1,3(2 H)-dione) (called N5) comprised of dibenzosilole and 1,3-indanedione building blocks was designed, synthesized, and fully characterized. N5 is highly soluble in various organic solvents, has high thermal stability, and has energy levels matching those of archetypal donor poly(3-hexylthiophene). Solution-processable, bulk-heterojunction solar cells afforded promising power conversion efficiency of 2.76 % when N5 was used as a non-fullerene electron acceptor along with the conventional donor polymer poly(3-hexylthiophene). As per our knowledge, the material reported herein is the first example in the literature where synchronous use of such building blocks is demonstrated in the design an efficient, non-fullerene acceptor.

‘Blind Faith’. An experiment with narrative agency in game design

This paper reports on the current field of narrative-based game design through case study analysis with a particular focus on balancing high narrative agency with low production resources.

Application of simulated annealing to data distribution for all-to-all comparison problems in homogeneous systems

Distributed systems are widely used for solving large-scale and data-intensive computing problems, including all-to-all comparison (ATAC) problems. However, when used for ATAC problems, existing computational frameworks such as Hadoop focus on load balancing for allocating comparison tasks, without careful consideration of data distribution and storage usage. While Hadoop-based solutions provide users with simplicity of implementation, their inherent MapReduce computing pattern does not match the ATAC pattern. This leads to load imbalances and poor data locality when Hadoop's data distribution strategy is used for ATAC problems. Here we present a data distribution strategy which considers data locality, load balancing and storage savings for ATAC computing problems in homogeneous distributed systems. A simulated annealing algorithm is developed for data distribution and task scheduling. Experimental results show a significant performance improvement for our approach over Hadoop-based solutions.

Using genetic algorithm in profile-based assignment of applications to virtual machines for greener data centers

The increase in data center dependent services has made energy optimization of data centers one of the most exigent challenges in today's Information Age. The necessity of green and energy-efficient measures is very high for reducing carbon footprint and exorbitant energy costs. However, inefficient application management of data centers results in high energy consumption and low resource utilization efficiency. Unfortunately, in most cases, deploying an energy-efficient application management solution inevitably degrades the resource utilization efficiency of the data centers. To address this problem, a Penalty-based Genetic Algorithm (GA) is presented in this paper to solve a defined profile-based application assignment problem whilst maintaining a trade-off between the power consumption performance and resource utilization performance. Case studies show that the penalty-based GA is highly scalable and provides 16% to 32% better solutions than a greedy algorithm.

A penalty-based genetic algorithm for the migration cost-aware virtual machine placement problem in cloud data centers

In the past few years, the virtual machine (VM) placement problem has been studied intensively and many algorithms for the VM placement problem have been proposed. However, those proposed VM placement algorithms have not been widely used in today's cloud data centers as they do not consider the migration cost from current VM placement to the new optimal VM placement. As a result, the gain from optimizing VM placement may be less than the loss of the migration cost from current VM placement to the new VM placement. To address this issue, this paper presents a penalty-based genetic algorithm (GA) for the VM placement problem that considers the migration cost in addition to the energy-consumption of the new VM placement and the total inter-VM traffic flow in the new VM placement. The GA has been implemented and evaluated by experiments, and the experimental results show that the GA outperforms two well known algorithms for the VM placement problem.

A Strength Pareto Evolutionary Algorithm for live migration of multiple interdependent virtual machines in data centers

Although live VM migration has been intensively studied, the problem of live migration of multiple interdependent VMs has hardly been investigated. The most important problem in the live migration of multiple interdependent VMs is how to schedule VM migrations as the schedule will directly affect the total migration time and the total downtime of those VMs. Aiming at minimizing both the total migration time and the total downtime simultaneously, this paper presents a Strength Pareto Evolutionary Algorithm 2 (SPEA2) for the multi-VM migration scheduling problem. The SPEA2 has been evaluated by experiments, and the experimental results show that the SPEA2 can generate a set of VM migration schedules with a shorter total migration time and a shorter total downtime than an existing genetic algorithm, namely Random Key Genetic Algorithm (RKGA). This paper also studies the scalability of the SPEA2.

Prototyping the self-authored video interview : Challenges and opportunities

Self-authored video- where participants are in control of the creation of their own footage- is a means of creating innovative design material and including all members of a family in design activities. This paper describes our adaptation to this process called Self Authored Video Interviews (SAVIs) that we created and prototyped to better understand how families engage with situated technology in the home. We find the methodology produces unique insights into family dynamics in the home, uncovering assumptions and tensions unlikely to be discovered using more conventional methods. The paper outlines a number of challenges and opportunities associated with the methodology, specifically, maximising the value of the insights gathered by appealing to children to champion the cause, and how to counter perceptions of the lingering presence of researchers.

Using mobile technology to motivate adolescents with type 1 diabetes mellitus: A systematic review of recent literature

Introduction Behavioural interventions have been shown to improve outcomes in patients with type 1 diabetes mellitus (T1DM). There are a small number of studies that suggest text-messages (TM), native mobile applications (NMAs), and other mobile tools may be useful platforms for delivering behavioural interventions to adolescents. Aim The aim of this study was to explore, by way of a systematic review of available literature, (a) the outcomes of interventions using mobile technology for youth with T1DM and (b) what mobile technologies, functional design elements and aesthetic design elements have the best evidence to support their use. Methods A search of six online databases returned 196 unique results, of which 13 met the inclusion criteria. Results Four studies were randomised controlled trials (RCTs), and all others prospective cohort studies. TM (10) was the most common intervention technology, while NMAs were used in four studies. The most common outcome measured was HbA1c (9); however, only three studies showed a significant decrease. Similarly, the results reported for other outcome measures were mixed. The studies included in this review suggest that interventions which have data collection and clinician support functionality may be more effective in improving adherence and glycaemic control, but more evidence is needed. Further, the evidence base supporting the use of NMAs in T1DM management for adolescents is weak, with most studies adopting TM as the intervention tool. Overall, the studies lack adequate descriptions of their methodology, and better quality studies are required to inform future intervention design.

An algorithm for constructing Hjelmslev planes

Projective Hjelmslev planes and affine Hjelmslev planes are generalisations of projective planes and affine planes. We present an algorithm for constructing projective Hjelmslev planes and affine Hjelmslev planes that uses projective planes, affine planes and orthogonal arrays. We show that all 2-uniform projective Hjelmslev planes, and all 2-uniform affine Hjelmslev planes can be constructed in this way. As a corollary it is shown that all $2$-uniform affine Hjelmslev planes are sub-geometries of $2$-uniform projective Hjelmslev planes.

The interleukin 1 gene cluster contains a major susceptibility locus for ankylosing spondylitis

Ankylosing spondylitis (AS) is a common and highly heritable inflammatory arthropathy. Although the gene HLA-B27 is almost essential for the inheritance of the condition, it alone is not sufficient to explain the pattern of familial recurrence of the disease. We have previously demonstrated suggestive linkage of AS to chromosome 2q13, a region containing the interleukin 1 (IL-1) family gene cluster, which includes several strong candidates for involvement in the disease. In the current study, we describe strong association and transmission of IL-1 family gene cluster single-nucleotide polymorphisms and haplotypes with AS.

The chromosome 16q region associated with ankylosing spondylitis includes the candidate gene tumour necrosis factor receptor type 1-associated death domain (TRADD)

Objective: To replicate and refine the reported association of ankylosing spondylitis (AS) with two nonsynonymous single nucleotide polymorphisms (nsSNPs) on chromosome 16q22.1. Methods: Firstly, 730 independent UK patients with AS were genotyped for rs9939768 and rs6979 and allele frequencies were compared with 2879 previously typed historic disease controls. Secondly, the two data sets were combined in meta-analyses. Finally, 5 tagging SNPs, located between rs9939768 and rs6979, were analysed in 1604 cases and 1020 controls. Results: The association of rs6979 with AS was replicated, p=0.03, OR=1.14 (95% CI 1.01 to 1.28), and a trend for association with rs9939768 detected, p=0.06, OR=1.25 (95% CI 0.99 to 1.57). Meta-analyses revealed association of both SNPs with AS, p=0.0008, OR=1.31 (95% CI 1.12 to 1.54) and p=0.0009, OR=1.15 (95% CI 1.06 to 1.23) for rs9939768 and rs6979, respectively. New associations with rs9033 and rs868213 (p=0.00002, OR=1.23 (95% CI 1.12 to 1.36) and p=0.00002 OR=1.45 (95% CI 1.22 to 1.72), respectively, were identified. Conclusions: The region on chromosome 16 that has been replicated in the present work is interesting as the highly plausible candidate gene, tumour necrosis factor receptor type 1 (TNFR1)-associated death domain (TRADD), is located between rs9033 and rs868213. It will require additional work to identify the primary genetic association(s) with AS.

Efficacy and safety of adalimumab in patients with non-radiographic axial spondyloarthritis: Results of a randomised placebo-controlled trial (ABILITY-1)

Purpose: To evaluate the efficacy and safety of adalimumab in patients with non-radiographic axial spondyloarthritis (nr-axSpA). Methods: Patients fulfilled Assessment of Spondyloarthritis international Society (ASAS) criteria for axial spondyloarthritis, had a Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) score of ≥ 4, total back pain score of ≥ 4 (10 cm visual analogue scale) and inadequate response, intolerance or contraindication to non-steroidal anti-inflammatory drugs (NSAIDs); patients fulfilling modified New York criteria for ankylosing spondylitis were excluded. Patients were randomised to adalimumab (N=91) or placebo (N=94). The primary endpoint was the percentage of patients achieving ASAS40 at week 12. Efficacy assessments included BASDAI and Ankylosing Spondylitis Disease Activity Score (ASDAS). MRI was performed at baseline and week 12 and scored using the Spondyloarthritis Research Consortium of Canada (SPARCC) index. Results: Significantly more patients in the adalimumab group achieved ASAS40 at week 12 compared with patients in the placebo group (36% vs 15%, p<0.001). Significant clinical improvements based on other ASAS responses, ASDAS and BASDAI were also detected at week 12 with adalimumab treatment, as were improvements in quality of life measures. Inflammation in the spine and sacroiliac joints on MRI significantly decreased after 12 weeks of adalimumab treatment. Shorter disease duration, younger age, elevated baseline C-reactive protein or higher SPARCC MRI sacroiliac joint scores were associated with better week 12 responses to adalimumab. The safety profile was consistent with what is known for adalimumab in ankylosing spondylitis and other diseases. Conclusions: In patients with nr-axSpA, adalimumab treatment resulted in effective control of disease activity, decreased inflammation and improved quality of life compared with placebo. Results from ABILITY-1 suggest that adalimumab has a positive benefit-risk profile in active nr-axSpA patients with inadequate response to NSAIDs.

Prospective meta-analysis of interleukin 1 gene complex polymorphisms confirms associations with ankylosing spondylitis

Objectives: The aim of the current study was to determine the contribution of interleukin (IL) 1 gene cluster polymorphisms previously implicated in susceptibility for ankylosing spondylitis (AS) to AS susceptibility in different populations worldwide. Methods: Nine polymorphisms in the IL1 gene cluster members IL1A (rs2856836, rs17561 and rs1894399), IL1B (rs16944), IL1F10 (rs3811058) and IL1RN (rs419598, the IL1RA VNTR, rs315952 and rs315951) were genotyped in 2675 AS cases and 2592 healthy controls recruited in 12 different centres in 10 countries. Association of variants with AS was tested by Mantel-Haenszel random effects analysis. Results: Strong association was observed with three single nucleotide polymorphisms (SNPs) in the IL1A gene (rs2856836, rs17561, rs1894399, p = 0.0036, 0.000019 and 0.0003, respectively). There was no evidence of significant heterogeneity of effects between centres, and no evidence of non-combinability of findings. The population attributable risk fraction of these variants in Caucasians is estimated at 4-6%. Conclusions: This study confirms that IL1A is associated with susceptibility to AS. Association of the other IL1 gene complex members could not be excluded in specific populations. Prospective meta-analysis is a useful tool in confirmation studies of genes associated with complex genetic disorders such as AS, providing sufficiently large sample sizes to produce robust findings often not achieved in smaller individual cohorts.