Sector-specific regimes

This Chapter considers a number of sector-specific access regimes that apply to infrastructure that exhibits natural monopoly characteristics. With the exception of Pt XIC of the CCA which regulates access to telecommunications infrastructure, they adopt the same form of negotiate-arbitrate model found in Pt IIIA of the CCA. In the event of a failure to negotiate commercial terms and conditions of access they allow the regulator to impose cost based (building block)tariffs. The regulator's decisions are subject to merits review and/or judicial review. The Chapter is divided into four Parts: • Part I considers access regulation in the electricity sector; • Part II considers access regulation in the gas sector; • Part III considers access regulation in the telecommunications sector; and • Part N considers access regulation in relation to port and rail bulk supply chains.

A review on degradation models in reliability analysis

With increasingly complex engineering assets and tight economic requirements, asset reliability becomes more crucial in Engineering Asset Management (EAM). Improving the reliability of systems has always been a major aim of EAM. Reliability assessment using degradation data has become a significant approach to evaluate the reliability and safety of critical systems. Degradation data often provide more information than failure time data for assessing reliability and predicting the remnant life of systems. In general, degradation is the reduction in performance, reliability, and life span of assets. Many failure mechanisms can be traced to an underlying degradation process. Degradation phenomenon is a kind of stochastic process; therefore, it could be modelled in several approaches. Degradation modelling techniques have generated a great amount of research in reliability field. While degradation models play a significant role in reliability analysis, there are few review papers on that. This paper presents a review of the existing literature on commonly used degradation models in reliability analysis. The current research and developments in degradation models are reviewed and summarised in this paper. This study synthesises these models and classifies them in certain groups. Additionally, it attempts to identify the merits, limitations, and applications of each model. It provides potential applications of these degradation models in asset health and reliability prediction.

A review on reliability models with covariates

Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Suitable mathematical models that are capable of predicting Time-to-Failure (TTF) and the probability of failure in future time are essential. In traditional reliability models, the lifetime of assets is estimated using failure time data. However, in most real-life situations and industry applications, the lifetime of assets is influenced by different risk factors, which are called covariates. The fundamental notion in reliability theory is the failure time of a system and its covariates. These covariates change stochastically and may influence and/or indicate the failure time. Research shows that many statistical models have been developed to estimate the hazard of assets or individuals with covariates. An extensive amount of literature on hazard models with covariates (also termed covariate models), including theory and practical applications, has emerged. This paper is a state-of-the-art review of the existing literature on these covariate models in both the reliability and biomedical fields. One of the major purposes of this expository paper is to synthesise these models from both industrial reliability and biomedical fields and then contextually group them into non-parametric and semi-parametric models. Comments on their merits and limitations are also presented. Another main purpose of this paper is to comprehensively review and summarise the current research on the development of the covariate models so as to facilitate the application of more covariate modelling techniques into prognostics and asset health management.

Difference-based meta-analytic procedures for between-participant and/or within-participant designs : a tutorial review for sports and exercise scientists

The aim of this paper is to provide a contemporary summary of statistical and non-statistical meta-analytic procedures that have relevance to the type of experimental designs often used by sport scientists when examining differences/change in dependent measure(s) as a result of one or more independent manipulation(s). Using worked examples from studies on observational learning in the motor behaviour literature, we adopt a random effects model and give a detailed explanation of the statistical procedures for the three types of raw score difference-based analyses applicable to between-participant, within-participant, and mixed-participant designs. Major merits and concerns associated with these quantitative procedures are identified and agreed methods are reported for minimizing biased outcomes, such as those for dealing with multiple dependent measures from single studies, design variation across studies, different metrics (i.e. raw scores and difference scores), and variations in sample size. To complement the worked examples, we summarize the general considerations required when conducting and reporting a meta-analysis, including how to deal with publication bias, what information to present regarding the primary studies, and approaches for dealing with outliers. By bringing together these statistical and non-statistical meta-analytic procedures, we provide the tools required to clarify understanding of key concepts and principles.

Intermittent drying of food products : a critical review

Drying is very energy intensive process and consumes about 20-25% of the energy used by food processing industry. The energy efficiency of the process and quality of dried product are two key factors in food drying. Global energy crisis and demand for quality dried food further challenge researchers to explore innovative techniques in food drying to address these issues. Intermittent drying is considered one of the promising solutions for improving energy efficiency and product quality without increasing the capital cost of the drier. Intermittent drying has already received much attention. However, a comprehensive review of recent progresses and overall assessment of energy efficiency and product quality in intermittent drying is lacking. The objective of this article is to discuss, analyze and evaluate the recent advances in intermittent drying research with energy efficiency and product quality as standpoint. Current available modelling techniques for intermittent drying are reviewed and their merits and demerits are analyzed. Moreover, intermittent application of ultrasound, infrared (IR) and microwave in combined drying technology have been reviewed and discussed. In this review article the gaps in the current literature are highlighted, some important future scopes for theoretical and experimental studies are identified and the direction of further research is suggested.