Fast and accurate business process drift detection

Business processes are prone to continuous and unexpected changes. Process workers may start executing a process differently in order to adjust to changes in workload, season, guidelines or regulations for example. Early detection of business process changes based on their event logs – also known as business process drift detection – enables analysts to identify and act upon changes that may otherwise affect process performance. Previous methods for business process drift detection are based on an exploration of a potentially large feature space and in some cases they require users to manually identify the specific features that characterize the drift. Depending on the explored feature set, these methods may miss certain types of changes. This paper proposes a fully automated and statistically grounded method for detecting process drift. The core idea is to perform statistical tests over the distributions of runs observed in two consecutive time windows. By adaptively sizing the window, the method strikes a trade-off between classification accuracy and drift detection delay. A validation on synthetic and real-life logs shows that the method accurately detects typical change patterns and scales up to the extent it is applicable for online drift detection.

Improved Kalman filter initialisation using neurofuzzy estimation

It is traditional to initialise Kalman filters and extended Kalman filters with estimates of the states calculated directly from the observed (raw) noisy inputs, but unfortunately their performance is extremely sensitive to state initialisation accuracy: good initial state estimates ensure fast convergence whereas poor estimates may give rise to slow convergence or even filter divergence. Divergence is generally due to excessive observation noise and leads to error magnitudes that quickly become unbounded (R.J. Fitzgerald, 1971). When a filter diverges, it must be re initialised but because the observations are extremely poor, re initialised states will have poor estimates. The paper proposes that if neurofuzzy estimators produce more accurate state estimates than those calculated from the observed noisy inputs (using the known state model), then neurofuzzy estimates can be used to initialise the states of Kalman and extended Kalman filters. Filters whose states have been initialised with neurofuzzy estimates should give improved performance by way of faster convergence when the filter is initialised, and when a filter is re started after divergence

Wide-area damping control for inter-area oscillations using inverse filtering technique

In this study, a non-linear excitation controller using inverse filtering is proposed to damp inter-area oscillations. The proposed controller is based on determining generator flux value for the next sampling time which is obtained by maximising reduction rate of kinetic energy of the system after the fault. The desired flux for the next time interval is obtained using wide-area measurements and the equivalent area rotor angles and velocities are predicted using a non-linear Kalman filter. A supplementary control input for the excitation system, using inverse filtering approach, to track the desired flux is implemented. The inverse filtering approach ensures that the non-linearity introduced because of saturation is well compensated. The efficacy of the proposed controller with and without communication time delay is evaluated on different IEEE benchmark systems including Kundur's two area, Western System Coordinating Council three-area and 16-machine, 68-bus test systems.

Choosing appropriate contract methods for design-build projects

For design-build (DB) projects, owners normally use lump sum and Guaranteed Maximum Price (GMP) as the major contract payment provisions. However, there was a lack of empirical studies to compare the project performance within different contract types and investigate how different project characteristics affect the owners’ selection of contract arrangement. Project information from Design-build Institute of America (DBIA) database was collected to reveal the statistical relationship between different project characteristics and contract types and to compare project performance between lump sum and GMP contract. The results show that lump sum is still the most frequently used contract method for DB projects, especially in the public sector. However, projects using GMP contract are more likely to have less schedule delay and cost overrun as compared to those with lump sum contract. The chi-square tests of cross tabulations reveal that project type, owner type, and procurement method affect the selection of contract types significantly. Civil infrastructure rather than industrial engineering project tends to use lump sum more frequently; and qualification-oriented contractor selection process resorts to GMP more often compared with cost-oriented process. The findings of this research contribute to the current body of knowledge concerning the effect of associated project characteristics on contract type selection. Overall, the results of this study provide empirical evidence from real DB projects that can be used by owners to select appropriate contract types and eventually improve future project performance.

EVERSUN: A phase 2 trial of alternating sunitinib and everolimus as first-line therapy for advanced renal cell carcinoma

Background We hypothesised that alternating inhibitors of the vascular endothelial growth factor receptor (VEGFR) and mammalian target of rapamycin pathways would delay the development of resistance in advanced renal cell carcinoma (aRCC). Patients and methods A single-arm, two-stage, multicentre, phase 2 trial to determine the activity, feasibility, and safety of 12-week cycles of sunitinib 50 mg daily 4 weeks on / 2 weeks off, alternating with everolimus 10 mg daily for 5 weeks on / 1 week off, until disease progression or prohibitive toxicity in favourable or intermediate-risk aRCC. The primary end point was proportion alive and progression-free at 6 months (PFS6m). The secondary end points were feasibility, tumour response, overall survival (OS), and adverse events (AEs). The correlative objective was to assess biomarkers and correlate with clinical outcome. Results We recruited 55 eligible participants from September 2010 to August 2012. Demographics: mean age 61, 71% male, favourable risk 16%, intermediate risk 84%. Cycle 2 commenced within 14 weeks for 80% of participants; 64% received ≥22 weeks of alternating therapy; 78% received ≥22 weeks of any treatment. PFS6m was 29/55 (53%; 95% confidence interval [CI] 40% to 66%). Tumour response rate was 7/55 (13%; 95% CI 4% to 22%, all partial responses). After median follow-up of 20 months, 47 of 55 (86%) had progressed with a median progression-free survival of 8 months (95% CI 5–10), and 30 of 55 (55%) had died with a median OS of 17 months (95% CI 12–undefined). AEs were consistent with those expected for each single agent. No convincing prognostic biomarkers were identified. Conclusions The EVERSUN regimen was feasible and safe, but its activity did not meet pre-specified values to warrant further research. This supports the current approach of continuing anti-VEGF therapy until progression or prohibitive toxicity before changing treatment.

RNASeqBrowser: A genome browser for simultaneous visualization of raw strand specific RNAseq reads and UCSC genome browser custom tracks

Background Strand specific RNAseq data is now more common in RNAseq projects. Visualizing RNAseq data has become an important matter in Analysis of sequencing data. The most widely used visualization tool is the UCSC genome browser that introduced the custom track concept that enabled researchers to simultaneously visualize gene expression at a particular locus from multiple experiments. Our objective of the software tool is to provide friendly interface for visualization of RNAseq datasets. Results This paper introduces a visualization tool (RNASeqBrowser) that incorporates and extends the functionality of the UCSC genome browser. For example, RNASeqBrowser simultaneously displays read coverage, SNPs, InDels and raw read tracks with other BED and wiggle tracks -- all being dynamically built from the BAM file. Paired reads are also connected in the browser to enable easier identification of novel exon/intron borders and chimaeric transcripts. Strand specific RNAseq data is also supported by RNASeqBrowser that displays reads above (positive strand transcript) or below (negative strand transcripts) a central line. Finally, RNASeqBrowser was designed for ease of use for users with few bioinformatic skills, and incorporates the features of many genome browsers into one platform. Conclusions The features of RNASeqBrowser: (1) RNASeqBrowser integrates UCSC genome browser and NGS visualization tools such as IGV. It extends the functionality of the UCSC genome browser by adding several new types of tracks to show NGS data such as individual raw reads, SNPs and InDels. (2) RNASeqBrowser can dynamically generate RNA secondary structure. It is useful for identifying non-coding RNA such as miRNA. (3) Overlaying NGS wiggle data is helpful in displaying differential expression and is simple to implement in RNASeqBrowser. (4) NGS data accumulates a lot of raw reads. Thus, RNASeqBrowser collapses exact duplicate reads to reduce visualization space. Normal PC’s can show many windows of NGS individual raw reads without much delay. (5) Multiple popup windows of individual raw reads provide users with more viewing space. This avoids existing approaches (such as IGV) which squeeze all raw reads into one window. This will be helpful for visualizing multiple datasets simultaneously. RNASeqBrowser and its manual are freely available at http://www.australianprostatecentre.org/research/software/rnaseqbrowser webcite or http://sourceforge.net/projects/rnaseqbrowser/ webcite

Dementia and the population health approach: Promise, pitfalls and progress. An Australian perspective

The increasing prevalence of dementia in Australia (and worldwide) over the next few decades poses enormous social, health and economic challenges. In the absence of a cure, strategies to prevent, delay the onset of, or reduce the impact of dementia are required to contain a growing disease burden, and health and care costs. A population health approach has the potential to substantially reduce the impact of dementia. Internationally, many countries have started to adopt population health strategies that incorporate elements of dementia prevention. The authors examine some of the elements of such an approach and barriers to its implementation. International dementia frameworks and strategies were reviewed to identify options utilized for a population health approach to dementia. Internationally and nationally, dementia frameworks are being developed that include population health approaches. Most of the frameworks identified included early diagnosis and intervention, and increasing community awareness as key objectives, while several included promotion of the links between a healthy lifestyle and reduced risk for dementia. A poor evidence base (especially for illness prevention), diagnostic and technical limitations, and policy and implementation issues are significant barriers in maximizing the promise of population health approaches in this area. The review and analysis of the population health approach to dementia will inform national and jurisdictional policy development.

Framework for assessing the influence of critical infrastructure interdependencies in post-disaster reconstruction management

Due to ever increasing climate instability, the number of natural disasters affecting society and communities is expected to increase globally in the future, which will result in a growing number of casualties and damage to property and infrastructure. Such damage poses crucial challenges for recovery of interdependent critical infrastructures. Post-disaster reconstruction is a complex undertaking as it is not only closely linked to the well-being and essential functioning of society, but also requires a large financial commitment. Management of critical infrastructure during post-disaster recovery needs to be underpinned by a holistic recognition that the recovery of each individual infrastructure system (e.g. energy, water, transport and information and communication technology) can be affected by the interdependencies that exist between these different systems. A fundamental characteristic of these interdependencies is that failure of one critical infrastructure system can result in the failure of other interdependent infrastructures, leading to a cascade of failures, which can impede post-disaster recovery and delay the subsequent reconstruction process. Consequently, there is a critical need for developing a holistic strategy to assess the influence of infrastructure interdependencies, and for incorporating these interdependencies into a post-disaster recovery strategy. This paper discusses four key dimensions of interdependencies that need to be considered in a post-disaster reconstruction planning. Using key concepts and sub-concepts derived from the notion of interdependency, the paper examines how critical infrastructure interdependencies affect the recovery processes of damaged infrastructures.

Assessing specific deterrence effects of increased speeding penalties using four measures of recidivism

Traffic law enforcement sanctions can impact on road user behaviour through general and specific deterrence mechanisms. The manner in which specific deterrence can influence recidivist behaviour can be conceptualised in different ways. While any reduction in speeding will have road safety benefits, the ways in which a ‘reduction’ is determined deserves greater methodological attention and has implications for countermeasure evaluation more generally. The primary aim of this research was to assess the specific deterrent impact of penalty increases for speeding offences in Queensland, Australia, in 2003 on two cohorts of drivers detected for speeding prior to and after the penalty changes were investigated. Since the literature is relatively silent on how to assess recidivism in the speeding context, the secondary research aim was to contribute to the literature regarding ways to conceptualise and measure specific deterrence in the speeding context. We propose a novel way of operationalising four measures which reflect different ways in which a specific deterrence effect could be conceptualised: (1) the proportion of offenders who re-offended in the follow up period; (2) the overall frequency of re-offending in the follow up period; (3) the length of delay to re-offence among those who re-offended; and (4) the average number of re-offences during the follow up period among those who re-offended. Consistent with expectations, results suggested an absolute deterrent effect of penalty changes, as evidenced by significant reductions in the proportion of drivers who re-offended and the overall frequency of re-offending, although effect sizes were small. Contrary to expectations, however, there was no evidence of a marginal specific deterrent effect among those who re-offended, with a significant reduction in the length of time to re-offence and no significant change in the average number of offences committed. Additional exploratory analyses investigating potential influences of the severity of the index offence, offence history, and method of detection revealed mixed results. Access to additional data from various sources suggested that the main findings were not influenced by changes in speed enforcement activity, public awareness of penalty changes, or driving exposure during the study period. Study limitations and recommendations for future research are discussed with a view to promoting more extensive evaluations of penalty changes and better understanding of how such changes may impact on motorists’ perceptions of enforcement and sanctions, as well as on recidivist behaviour.

Channel selection in the short-time modulation domain for distant speech recognition

Automatic speech recognition from multiple distant micro- phones poses significant challenges because of noise and reverberations. The quality of speech acquisition may vary between microphones because of movements of speakers and channel distortions. This paper proposes a channel selection approach for selecting reliable channels based on selection criterion operating in the short-term modulation spectrum domain. The proposed approach quantifies the relative strength of speech from each microphone and speech obtained from beamforming modulations. The new technique is compared experimentally in the real reverb conditions in terms of perceptual evaluation of speech quality (PESQ) measures and word error rate (WER). Overall improvement in recognition rate is observed using delay-sum and superdirective beamformers compared to the case when the channel is selected randomly using circular microphone arrays.

The influence of critical infrastructure interdependencies on post-disaster reconstruction: Elements of infrastructure interdependency that impede the post-disaster recovery effort

The importance of developing effective disaster management strategies has significantly grown as the world continues to be confronted with unprecedented disastrous events. Factors such as climate instability, recent urbanization along with rapid population growth in many cities around the world have unwittingly exacerbated the risks of potential disasters, leaving a large number of people and infrastructure exposed to new forms of threats from natural disasters such as flooding, cyclones, and earthquakes. With disasters on the rise, effective recovery planning of the built environment is becoming imperative as it is not only closely related to the well-being and essential functioning of society, but it also requires significant financial commitment. In the built environment context, post-disaster reconstruction focuses essentially on the repair and reconstruction of physical infrastructures. The reconstruction and rehabilitation efforts are generally performed in the form of collaborative partnerships that involve multiple organisations, enabling the restoration of interdependencies that exist between infrastructure systems such as energy, water (including wastewater), transport, and telecommunication systems. These interdependencies are major determinants of vulnerabilities and risks encountered by critical infrastructures and therefore have significant implications for post-disaster recovery. When disrupted by natural disasters, such interdependencies have the potential to promote the propagation of failures between critical infrastructures at various levels, and thus can have dire consequences on reconstruction activities. This paper outlines the results of a pilot study on how elements of infrastructure interdependencies have the potential to impede the post-disaster recovery effort. Using a set of unstructured interview questionnaires, plausible arguments provided by seven respondents revealed that during post-disaster recovery, critical infrastructures are mutually dependent on each other’s uninterrupted availability, both physically and through a host of information and communication technologies. Major disruption to their physical and cyber interdependencies could lead to cascading failures, which could delay the recovery effort. Thus, the existing interrelationship between critical infrastructures requires that the entire interconnected network be considered when managing reconstruction activities during the post-disaster recovery period.

Systems modelling of the socio-technical aspects of residential electricity use and network peak demand

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

The window of opportunity: A relevant concept for axial spondyloarthritis

The window of opportunity is a concept critical to rheumatoid arthritis treatment. Early treatment changes the outcome of rheumatoid arthritis treatment, in that response rates are higher with earlier disease-modifying anti-rheumatic drug treatment and damage is substantially reduced. Axial spondyloarthritis is an inflammatory axial disease encompassing both nonradiographic axial spondyloarthritis and established ankylosing spondylitis. In axial spondyloarthritis, studies of magnetic resonance imaging as well as tumor necrosis factor inhibitor treatment and withdrawal studies all suggest that early effective suppression of inflammation has the potential to reduce radiographic damage. This potential would suggest that the concept of a window of opportunity is relevant not only to rheumatoid arthritis but also to axial spondyloarthritis. The challenge now remains to identify high-risk patients early and to commence treatment without delay. Developments in risk stratification include new classification criteria, identification of clinical risk factors, biomarkers, genetic associations, potential antibody associations and an ankylosing spondylitis-specific microbiome signature. Further research needs to focus on the evidence for early intervention and the early identification of high-risk individuals.

Whole exome sequencing is an efficient and sensitive method for detection of germline mutations in patients with phaeochromcytomas and paragangliomas

Background Genetic testing is recommended when the probability of a disease-associated germline mutation exceeds 10%. Germline mutations are found in approximately 25% of individuals with phaeochromcytoma (PCC) or paraganglioma (PGL); however, genetic heterogeneity for PCC/PGL means many genes may require sequencing. A phenotype-directed iterative approach may limit costs but may also delay diagnosis, and will not detect mutations in genes not previously associated with PCC/PGL. Objective To assess whether whole exome sequencing (WES) was efficient and sensitive for mutation detection in PCC/PGL. Methods Whole exome sequencing was performed on blinded samples from eleven individuals with PCC/PGL and known mutations. Illumina TruSeq™ (Illumina Inc, San Diego, CA, USA) was used for exome capture of seven samples, and NimbleGen SeqCap EZ v3.0 (Roche NimbleGen Inc, Basel, Switzerland) for five samples (one sample was repeated). Massive parallel sequencing was performed on multiplexed samples. Sequencing data were called using Genome Analysis Toolkit and annotated using annovar. Data were assessed for coding variants in RET, NF1, VHL, SDHD, SDHB, SDHC, SDHA, SDHAF2, KIF1B, TMEM127, EGLN1 and MAX. Target capture of five exome capture platforms was compared. Results Six of seven mutations were detected using Illumina TruSeq™ exome capture. All five mutations were detected using NimbleGen SeqCap EZ v3.0 platform, including the mutation missed using Illumina TruSeq™ capture. Target capture for exons in known PCC/PGL genes differs substantially between platforms. Exome sequencing was inexpensive (<$A800 per sample for reagents) and rapid (results <5 weeks from sample reception). Conclusion Whole exome sequencing is sensitive, rapid and efficient for detection of PCC/PGL germline mutations. However, capture platform selection is critical to maximize sensitivity.

Narrow linewidth DFB waveguide laser fabricated via ultrafast laser inscription

Linewidth measurement of a femtosecond laser direct-written distributed feedback (DFB) waveguide laser (WGL) is reported. The WGL was fabricated in Yb-doped phosphate glass using the femtosecond laser direct-write technique. The linewidth was measured using a loss-compensated recirculating delayed self-heterodyne interferometer. By recirculating the output signal in a 10.2-km fiber delay loop, the linewidth was measured to be 35.4±1.4 kHz at a delay time of 306 μs , which is comparable with that of narrow-linewidth fiber DFB lasers.