A systematic design of interval type-2 fuzzy logic system using extreme learning machine for electricity load demand forecasting

This paper presents a novel design of interval type-2 fuzzy logic systems (IT2FLS) by utilizing the theory of extreme learning machine (ELM) for electricity load demand forecasting. ELM has become a popular learning algorithm for single hidden layer feed-forward neural networks (SLFN). From the functional equivalence between the SLFN and fuzzy inference system, a hybrid of fuzzy-ELM has gained attention of the researchers. This paper extends the concept of fuzzy-ELM to an IT2FLS based on ELM (IT2FELM). In the proposed design the antecedent membership function parameters of the IT2FLS are generated randomly, whereas the consequent part parameters are determined analytically by the Moore-Penrose pseudo inverse. The ELM strategy ensures fast learning of the IT2FLS as well as optimality of the parameters. Effectiveness of the proposed design of IT2FLS is demonstrated with the application of forecasting nonlinear and chaotic data sets. Nonlinear data of electricity load from the Australian National Electricity Market for the Victoria region and from the Ontario Electricity Market are considered here. The proposed model is also applied to forecast Mackey-glass chaotic time series data. Comparative analysis of the proposed model is conducted with some traditional models such as neural networks (NN) and adaptive neuro fuzzy inference system (ANFIS). In order to verify the structure of the proposed design of IT2FLS an alternate design of IT2FLS based on Kalman filter (KF) is also utilized for the comparison purposes.

Training of interval type-2 fuzzy logic system using extreme learning machine for load forecasting

Extreme learning machine (ELM) is originally proposed for single- hidden layer feed-forward neural networks (SLFN). From the functional equivalence of fuzzy logic systems and SLFN, the fuzzy logic systems can be interpreted as a special case of SLFN under some mild conditions. Hence the fuzzy logic systems can be trained using SLFN's learning algorithms. Considering the same equivalence, ELM is utilized here to train interval type-2 fuzzy logic systems (IT2FLSs). Based on the working principle of the ELM, the parameters of the antecedent of IT2FLSs are randomly generated while the consequent part of IT2FLSs is optimized using Moore-Penrose generalized inverse of ELM. Application of the developed model to electricity load forecasting is another novelty of the research work. Experimental results shows better forecasting performance of the proposed model over the two frequently used forecasting models.

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 or http://sourceforge.net/projects/rnaseqbrowser/.

Evaporation, seepage and water quality management in storage dams: a review of research methods

One of the most significant sources of water wastage in Australia is loss from small storage dams, either by seepage or evaporation. Over much of Australia, evaporative demand routinely exceeds precipitation. This paper outlines first, methodologies and measurement techniques to quantify the rate of evaporative loss from fresh water storages. These encompass high-accuracy water balance monitoring; determination of the validity of alternative estimation equations, in particular the FAO56 Penman- Monteith ETo methodology; and the commencement of CFD modeling to determine a 'dam factor' in relation to practical atmospheric measurement techniques. Second, because the application of chemical monolayers is the only feasible alternative to the high cost of physically covering the storages to retard evaporation, the use of cetyl alcohol-based monolayers is reviewed, and preliminary research on their degradation by photolytic action, by wind break-up and by microbial degradation reported. Similarly, preliminary research on monolayer visualisation techniques for field application is reported; and potential enhancement of monolayers by other chemicals and attendant water quality issues are considered.

Hybrid model for the training of interval type-2 fuzzy logic system

In this paper, a hybrid training model for interval type-2 fuzzy logic system is proposed. The hybrid training model uses extreme learning machine to tune the consequent part parameters and genetic algorithm to optimize the antecedent part parameters. The proposed hybrid learning model of interval type-2 fuzzy logic system is tested on the prediction of Mackey-Glass time series data sets with different levels of noise. The results are compared with the existing models in literature; extreme learning machine and Kalman filter based learning of consequent part parameters with randomly generated antecedent part parameters. It is observed that the interval type-2 fuzzy logic system provides improved performance with the proposed hybrid learning model.

Using meta-synthesis to support application of qualitative methods findings in practice: a discussion of meta-ethnography, narrative synthesis, and critical interpretive synthesis

Meta-synthesis refers to a range of approaches by which existing qualitative studies in healthcare can bereviewed and compared. There is increasing use of meta-synthesis to ensure the clinical applicability offindings from qualitative studies, in healthcare generally, and in the creative arts therapies specifically.Qualitative method research can sometimes lack immediate clinical relevance, as such studies usuallyfocus on the experiences of a small number of participants. Additionally, the results are often presented ingreat detail; finely elaborated, and described conceptually. Findings reported in this way can be engaging,and even emotionally compelling, however the utility of these outcomes for clinical practice can belimited. Meta-synthesis of multiple studies aims to ensure that findings from qualitative methods studiescan be more easily, and effectively, applied in health and social care programs. Three approaches to metasynthesisare briefly presented here; meta-ethnography, narrative synthesis, and critical interpretivesynthesis. A procedure for presentation of meta-synthesis reviews is provided.

Accuracy and usefulness of select methods for assessing complete collection of 24-hour urine: a systematic review.

Twenty-four-hour urine collection is the recommended method for estimating sodium intake. To investigate the strengths and limitations of methods used to assess completion of 24-hour urine collection, the authors systematically reviewed the literature on the accuracy and usefulness of methods vs para-aminobenzoic acid (PABA) recovery (referent). The percentage of incomplete collections, based on PABA, was 6% to 47% (n=8 studies). The sensitivity and specificity for identifying incomplete collection using creatinine criteria (n=4 studies) was 6% to 63% and 57% to 99.7%, respectively. The most sensitive method for removing incomplete collections was a creatinine index <0.7. In pooled analysis (≥2 studies), mean urine creatinine excretion and volume were higher among participants with complete collection (P<.05); whereas, self-reported collection time did not differ by completion status. Compared with participants with incomplete collection, mean 24-hour sodium excretion was 19.6 mmol higher (n=1781 specimens, 5 studies) in patients with complete collection. Sodium excretion may be underestimated by inclusion of incomplete 24-hour urine collections. None of the current approaches reliably assess completion of 24-hour urine collection.

Online versus postal data collection methods: an examination of issues and a comparison of results

New communications technologies often allow new ways of conducting market research. Determining the advantages of a new data collection method over established alternatives is difficult without thorough comparative testing. Computer-mediated marketing research is one such example of a new technology that has been enthusiastically embraced by marketing organisations and those servicing them. While researchers using the Internet (Net) and World Wide Web (Web) in its early years reported benefits such as high response levels, there is little in the way of comparative evidence to support any claimed advantages. This paper reports on the outcomes of three separate studies in which members (subscribers) of various organisations have been surveyed using both postal and online (email invitation and HTML Web form) data collection methods. The conclusion here is that it would be unwise to assume that one method can be directly substituted for another and obtain the same response. Differences in both the response pattern and demographic profile of respondents between the groups are consistently noticed, such as to warrant further examination of the methods used in online marketing research, and to suggest the need for further study.

Assessment methods in social work education: a review of the literature

Student assessment is an important component of social work education, and consumes considerable effort on behalf of both students and staff members. Social work educators in higher education face the challenge of constructing assessment methods, which encourage the development of reflective and critical learning, as well as enabling students to demonstrate acquisition of required knowledge and/or skills. While there is now a substantial literature on field education, the assessment of classroom-based units has warranted less attention. This paper examines the range of assessment methods reported in the social work education literature, the evidence which supports the use of these methods and issues associated with the identified assessment methods.

Methods of construction of OWA operators from data

This paper investigates the problem of obtaining the weights of the ordered weighted aggregation (OWA) operators from observations. The problem is formulated as a restricted least squares and uniform approximation problems. We take full advantage of the linearity of the problem. In the former case, a well known technique of non-negative least squares is used. In a case of uniform approximation, we employ a recently developed cutting angle method of global optimisation. Both presented methods give results superior to earlier approaches, and do not require complicated nonlinear constructions. Additional restrictions, such as degree of orness of the operator, can be easily introduced

Assessment of embodied energy analysis methods for the Australian construction industry

Environmental assessment of buildings typically focuses on operational energy consumption in an attempt to minimise building energy consumption. Whilst the operation of Australian buildings accounts for around 20% of total energy consumption nationally, the energy embodied in these buildings represents up to 20 times their annual operational energy. Many previous studies, now shown to be incomplete in system boundary or unreliable, have provided much lower values for the embodied energy of buildings and their products. Many of these studies have used traditional embodied energy analysis methods, such as process analysis and input-output (1-0) analysis. More recently, hybrid embodied energy analysis methods have been developed, combining these two traditional methods. These hybrid methods need to be compared and validated, as these too have been considered to have several limitations. This paper aims to evaluate a recently developed hybrid method for the embodied energy analysis of the Australian construction industry, relative to traditional methods. Recent improvements to this hybrid method include the use of more recent 1-0 data and th.fl inclusion of capital energy data. These significant systemic changes mean that a previous assessment of the methods needs to be reviewed. It was found that the incompleteness associated with process analysis has increased from 49% to 87%. These findings suggest that current best-practice methods of embodied energy analysis are sufficiently accurate for most typical applications. This finding is strengthened by recent improvements to the 1-0 model.

Non-smooth optimization methods for computation of the conditional value-at-risk and portfolio optimization

We examine numerical performance of various methods of calculation of the Conditional Value-at-risk (CVaR), and portfolio optimization with respect to this risk measure. We concentrate on the method proposed by Rockafellar and Uryasev in (Rockafellar, R.T. and Uryasev, S., 2000, Optimization of conditional value-at-risk. Journal of Risk, 2, 21-41), which converts this problem to that of convex optimization. We compare the use of linear programming techniques against a non-smooth optimization method of the discrete gradient, and establish the supremacy of the latter. We show that non-smooth optimization can be used efficiently for large portfolio optimization, and also examine parallel execution of this method on computer clusters.

Self-rated preparedness of Australian prevocational hospital doctors for emergencies

Objective: To determine perceived preparedness of Australian hospital-based prevocational doctors for resuscitation skills and management of emergencies, and to identify differences between doctors who perceive themselves well prepared and those who perceive themselves poorly prepared for emergencies, in demographics and exposure to desired learning methods.

Methods: Questionnaire consisting of a mix of graded Likert scales and free-text answers distributed to 36 Australian hospitals for secondary distribution to hospital medical officers.

Results: From 2607 questionnaires posted, 470 (18.1%) were returned. Thirty-one per cent (95% confidence interval [CI] 26–35%) felt well prepared for resuscitation and management of emergencies, 41% (CI 37–45%) felt adequately prepared and 28% (CI 24–32%) felt they were not well prepared. Those who felt well prepared reported that they had experienced more exposure to a range of educational methods, including consultant contact, supervisor feedback, clinical skills, high fidelity simulator sessions and unit meetings. Well-prepared and poorly prepared doctors had similar opinions of the usefulness of various learning methods, but the poorly prepared group more frequently expressed a desire for increased exposure to contact with registrars and consultants, clinical skills sessions and hospital and unit meetings. There were no differences in gender, age or country of origin (Australia vs international medical graduates) between those who felt well or poorly prepared.

Conclusions: Many prevocational hospital doctors feel inadequately prepared for the management of emergencies. Perceived preparedness is associated with more exposure to particular educational activities. Increasing exposure to learning of emergencies in undergraduate and prevocational years could reduce the number of junior doctors who feel poorly prepared for emergencies.

Examination of EMG normalisation methods for the study of the posterior and posterolateral neck muscles in healthy controls

The purpose of this study was to examine the reliability of normalisation methods used in the study of the posterior and posterolateral neck muscles in a group of healthy controls. Six asymptomatic male subjects performed a total of 12 maximum voluntary isometric contractions (MVIC) and 60%-submaximal isometric contractions (60%-MVIC) against the torque arm of an isokinetic dynamometer whilst surface and intramuscular electromyography (EMG) was recorded unilaterally from representative posterior and posterolateral locations. Reliability was calculated using intra-class correlation coefficient (ICC), relative standard error of measurement (%SEM) and relative coefficient of variation (%CV). Maximal torque output was found to be highly reliable in the directions of extension and right lateral bending when the first of three MVIC contractions was excluded. When averaged across contraction direction, high reliability was found for both surface (MVIC: ICC = 0.986, %SEM = 7.5, %CV = 9.2; 60%-MVIC: ICC = 0.975, %SEM = 10, %CV = 13.7) and intramuscular (MVIC: ICC = 0.910, %SEM = 20, %CV = 19.1; 60%-MVIC: ICC = 0.952, %SEM = 16.5, %CV = 13.5) electrodes. Intramuscular electrodes displayed the least reliability in right lateral bending. The use of visual feedback markedly increased the reliability of 60%-MVIC contractions.

Assessing cost-effectiveness in obesity (ACE-Obesity) : an overview of the ACE approach, economic methods and cost results

Background : The aim of the ACE-Obesity study was to determine the economic credentials of interventions which aim to prevent unhealthy weight gain in children and adolescents. We have reported elsewhere on the modelled effectiveness of 13 obesity prevention interventions in children. In this paper, we report on the cost results and associated methods together with the innovative approach to priority setting that underpins the ACE-Obesity study.

Methods : The Assessing Cost-Effectiveness (ACE) approach combines technical rigour with 'due process' to facilitate evidence-based policy analysis. Technical rigour was achieved through use of standardised evaluation methods, a research team that assembles best available evidence and extensive uncertainty analysis. Cost estimates were based on pathway analysis, with resource usage estimated for the interventions and their 'current practice' comparator, as well as associated cost offsets. Due process was achieved through involvement of stakeholders, consensus decisions informed by briefing papers and 2nd stage filter analysis that captures broader factors that influence policy judgements in addition to cost-effectiveness results. The 2nd stage filters agreed by stakeholders were 'equity', 'strength of the evidence', 'feasibility of implementation', 'acceptability to stakeholders', 'sustainability' and 'potential for side-effects'.

Results : The intervention costs varied considerably, both in absolute terms (from cost saving [6 interventions] to in excess of AUD50m per annum) and when expressed as a 'cost per child' estimate (from <AUD1.0 [reduction of TV advertising of high fat foods/high sugar drinks] to >AUD31,000 [laparoscopic adjustable gastric banding for morbidly obese adolescents]). High costs per child reflected cost structure, target population and/or under-utilisation.

Conclusions : The use of consistent methods enables valid comparison of potential intervention costs and cost-offsets for each of the interventions. ACE-Obesity informs policy-makers about cost-effectiveness, health impact, affordability and 2nd stage filters for important options for preventing unhealthy weight gain in children. In related articles cost-effectiveness results and second stage filter considerations for each intervention assessed will be presented and analysed.