Towards Automated Data-Driven Model Creation for Cloud Computing Simulation

The increasing complexity and scale of cloud computing environments due to widespread data centre heterogeneity makes measurement-based evaluations highly difficult to achieve. Therefore the use of simulation tools to support decision making in cloud computing environments to cope with this problem is an increasing trend. However the data required in order to model cloud computing environments with an appropriate degree of accuracy is typically large, very difficult to collect without some form of automation, often not available in a suitable format and a time consuming process if done manually. In this research, an automated method for cloud computing topology definition, data collection and model creation activities is presented, within the context of a suite of tools that have been developed and integrated to support these activities.

Secure data networks for electrical distribution applications

Smart Grids are characterized by the application of information communication technology (ICT) to solve electrical energy challenges. Electric power networks span large geographical areas, thus a necessary component of many Smart Grid applications is a wide area network (WAN). For the Smart Grid to be successful, utilities must be confident that the communications infrastructure is secure. This paper describes how a WAN can be deployed using WiMAX radio technology to provide high bandwidth communications to areas not commonly served by utility communications, such as generators embedded in the distribution network. A planning exercise is described, using Northern Ireland as a case study. The suitability of the technology for real-time applications is assessed using experimentally obtained latency data.

A novel forward gene selection algorithm for microarray data

This paper investigates the gene selection problem for microarray data with small samples and variant correlation. Most existing algorithms usually require expensive computational effort, especially under thousands of gene conditions. The main objective of this paper is to effectively select the most informative genes from microarray data, while making the computational expenses affordable. This is achieved by proposing a novel forward gene selection algorithm (FGSA). To overcome the small samples' problem, the augmented data technique is firstly employed to produce an augmented data set. Taking inspiration from other gene selection methods, the L2-norm penalty is then introduced into the recently proposed fast regression algorithm to achieve the group selection ability. Finally, by defining a proper regression context, the proposed method can be fast implemented in the software, which significantly reduces computational burden. Both computational complexity analysis and simulation results confirm the effectiveness of the proposed algorithm in comparison with other approaches

An exploration of integrated data on the social dynamics of suicide among women

The gender based nature of suicide related behaviour is largely accepted.However, studies which report exclusively on female fatal suicides are rare.Here we demonstrate how female fatal suicide has effectively been ‘othered’ and appears ‘incidental’ in studies which compare female behaviour with that of their male counterparts. We highlight how recent studies of suicide have tended to be dominated by male only approaches,which increasingly link issues of masculinity with male death by suicide.Drawing on data collected from the GP and Coroner’s office, we then apply the Sociological Autopsy approach to a cohort of 78 deaths recorded as suicides in the UK between 2007 and 2009. By focusing on females in isolation from males, we demonstrate that as in male suicide only studies,it is similarly possible to draw out issues associated with the feminine identity which can be linked to death by suicide. We identify that bereavement, sexual violence and motherhood could all be linked to the lives and help-seeking of the females who died. In closing, we suggest are orientation towards sociological analytic approaches of female suicide may help to produce further reductions in the rate of female death by suicide.

Freshwater Reservoir Effects on the Re-Dating of the Eurasian Steppe Cultures: New Data for the Prehistoric Sites of Kazakhstan and South of Siberia

Freshwater reservoir effects (FRE) can cause a major problem with radiocarbon dating human skeletal material in the Eurasian steppe. Recent research has demonstrated that, for the Eneolithic to Early Bronze Age sites of North-Eastern Kazakhstan, the maximum fish-herbivore freshwater reservoir offset observed equals 301±47 14C yrs, as such indicating that 14C dates from aquatic and human samples from the area apparently need to be interpreted with caution as they are likely to be affected by the offset. The current paper presents the new data on the FRE of the Eneolithic to the Early Iron Age sites of Kazakhstan and South of Siberia.

Knowledge stocks, knowledge flows and innovation: Evidence from matched patents and innovation panel data

Successful innovation depends on knowledge – technological, strategic and market related. In this paper we explore the role and interaction of firms’ existing knowledge stocks and current knowledge flows in shaping innovation success. The paper contributes to our understanding of the determinants of firms’ innovation outputs and provides new information on the relationship between knowledge stocks, as measured by patents, and innovation output indicators. Our analysis uses innovation panel data relating to plants’ internal knowledge creation, external knowledge search and innovation outputs. Firm-level patent data is matched with this plant-level innovation panel data to provide a measure of firms’ knowledge stock. Two substantive conclusions follow. First, existing knowledge stocks have weak negative rather than positive impacts on firms’ innovation outputs, reflecting potential core-rigidities or negative path dependencies rather than the accumulation of competitive advantages. Second, knowledge flows derived from internal investment and external search dominate the effect of existing knowledge stocks on innovation performance. Both results emphasize the importance of firms’ knowledge search strategies. Our results also re-emphasize the potential issues which arise when using patents as a measure of innovation.

Open Source Telecommunications Framework for Time-Series Data from Smart Grid Sensors.

This paper presents a framework for a telecommunications interface which allows data from sensors embedded in Smart Grid applications to reliably archive data in an appropriate time-series database. The challenge in doing so is two-fold, firstly the various formats in which sensor data is represented, secondly the problems of telecoms reliability. A prototype of the authors' framework is detailed which showcases the main features of the framework in a case study featuring Phasor Measurement Units (PMU) as the application. Useful analysis of PMU data is achieved whenever data from multiple locations can be compared on a common time axis. The prototype developed highlights its reliability, extensibility and adoptability; features which are largely deferred from industry standards for data representation to proprietary database solutions. The open source framework presented provides link reliability for any type of Smart Grid sensor and is interoperable with existing proprietary database systems, and open database systems. The features of the authors' framework allow for researchers and developers to focus on the core of their real-time or historical analysis applications, rather than having to spend time interfacing with complex protocols.

Adjuvant bisphosphonate treatment in early breast cancer: meta-analyses of individual patient data from randomised trials

BACKGROUND: Bisphosphonates have profound effects on bone physiology, and could modify the process of metastasis. We undertook collaborative meta-analyses to clarify the risks and benefits of adjuvant bisphosphonate treatment in breast cancer.

METHODS: We sought individual patient data from all unconfounded trials in early breast cancer that randomised between bisphosphonate and control. Primary outcomes were recurrence, distant recurrence, and breast cancer mortality. Primary subgroup investigations were site of first distant recurrence (bone or other), menopausal status (postmenopausal [combining natural and artificial] or not), and bisphosphonate class (aminobisphosphonate [eg, zoledronic acid, ibandronate, pamidronate] or other [ie, clodronate]). Intention-to-treat log-rank methods yielded bisphosphonate versus control first-event rate ratios (RRs).

FINDINGS: We received data on 18 766 women (18 206 [97%] in trials of 2-5 years of bisphosphonate) with median follow-up 5·6 woman-years, 3453 first recurrences, and 2106 subsequent deaths. Overall, the reductions in recurrence (RR 0·94, 95% CI 0·87-1·01; 2p=0·08), distant recurrence (0·92, 0·85-0·99; 2p=0·03), and breast cancer mortality (0·91, 0·83-0·99; 2p=0·04) were of only borderline significance, but the reduction in bone recurrence was more definite (0·83, 0·73-0·94; 2p=0·004). Among premenopausal women, treatment had no apparent effect on any outcome, but among 11 767 postmenopausal women it produced highly significant reductions in recurrence (RR 0·86, 95% CI 0·78-0·94; 2p=0·002), distant recurrence (0·82, 0·74-0·92; 2p=0·0003), bone recurrence (0·72, 0·60-0·86; 2p=0·0002), and breast cancer mortality (0·82, 0·73-0·93; 2p=0·002). Even for bone recurrence, however, the heterogeneity of benefit was barely significant by menopausal status (2p=0·06 for trend with menopausal status) or age (2p=0·03), and it was non-significant by bisphosphonate class, treatment schedule, oestrogen receptor status, nodes, tumour grade, or concomitant chemotherapy. No differences were seen in non-breast cancer mortality. Bone fractures were reduced (RR 0·85, 95% CI 0·75-0·97; 2p=0·02).

INTERPRETATION: Adjuvant bisphosphonates reduce the rate of breast cancer recurrence in the bone and improve breast cancer survival, but there is definite benefit only in women who were postmenopausal when treatment began.

FUNDING: Cancer Research UK, Medical Research Council.

Individual Participant Data (IPD) Meta-analyses of Randomised Controlled Trials: Guidance on Their Use

Jayne Tierney and colleagues offer guidance on how to spot a well-designed and well-conducted individual participant data meta-analysis.

Summary Points 

• Systematic reviews are most commonly based on aggregate data extracted from publications or obtained from trial investigators. 

• Systematic reviews involving the central collection and analysis of individual participant data (IPD) usually are larger-scale, international, collaborative projects that can bring about substantial improvements to the quantity and quality of data, give greater scope in the analyses, and provide more detailed and robust results. 

• The process of collecting, checking, and analysing IPD is more complex than for aggregate data, and not all IPD meta-analyses are done to the same standard, making it difficult for researchers, clinicians, patients, policy makers, funders, and publishers to judge their quality. 

• Following our step-by-step guide will help reviewers and users of IPD meta-analyses to understand them better and recognise those that are well designed and conducted and so help ensure that policy, practice, and research are informed by robust evidence about the effects of interventions.

How individual participant data meta-analyses have influenced trial design, conduct, and analysis

OBJECTIVES: To demonstrate how individual participant data (IPD) meta-analyses have impacted directly on the design and conduct of trials and highlight other advantages IPD might offer.

STUDY DESIGN AND SETTING: Potential examples of the impact of IPD meta-analyses on trials were identified at an international workshop, attended by individuals with experience in the conduct of IPD meta-analyses and knowledge of trials in their respective clinical areas. Experts in the field who did not attend were asked to provide any further examples. We then examined relevant trial protocols, publications, and Web sites to verify the impacts of the IPD meta-analyses. A subgroup of workshop attendees sought further examples and identified other aspects of trial design and conduct that may inform IPD meta-analyses.

RESULTS: We identified 52 examples of IPD meta-analyses thought to have had a direct impact on the design or conduct of trials. After screening relevant trial protocols and publications, we identified 28 instances where IPD meta-analyses had clearly impacted on trials. They have influenced the selection of comparators and participants, sample size calculations, analysis and interpretation of subsequent trials, and the conduct and analysis of ongoing trials, sometimes in ways that would not possible with systematic reviews of aggregate data. We identified additional potential ways that IPD meta-analyses could be used to influence trials.

CONCLUSIONS: IPD meta-analysis could be better used to inform the design, conduct, analysis, and interpretation of trials.