With increasing harmonic pollution in the power system, real-time monitoring and analysis of harmonic variations have become important. Because of limitations associated with conventional algorithms, particularly under supply-frequency drift and transient situations, a new approach based on non-linear leastsquares parameter estimation has been proposed as an alternative solution for high-accuracy evaluation. However, the computational demand of the algorithm is very high and it is more appropriate to use Hopfield type feedback neural networks for real-time harmonic evaluation. The proposed neural network implementation determines simultaneously the supply-frequency variation, the fundamental-amplitude/phase variation as well as the harmonics-amplitude/phase variation. The distinctive feature is that the supply-frequency variation is handled separately from the amplitude/phase variations, thus ensuring high computational speed and high convergence rate. Examples by computer simulation are used to demonstrate the effectiveness of the implementation. A set of data taken on site was used as a real application of the system.

Health care workers may therefore consider any area within at least 0.4 m of a patient using such oxygen masks to be a potential nosocomial hazard zone.

Purpose The Contingency Outsourcing Relationship (CORE) model originated from the Four Outsourcing Relationship Types (FORT) model and the CORE model is used in the globalized facility management (FM) industry while the FORT model is originally used in the global information technology industry. The purpose of this paper is to analyze the CORE model through the rankings of relationship between a client and a globalized FM service provider from the perspective of the FM service provider in one of the four categories (i.e. in-house, technical expertise, commitment and common goals) and the application of this model with the aid of artificial neural networks (ANNs). Design/methodology/approach A quantitative methodology using a survey is used to analyze the four types of outsourcing categories. First, the background theory and a set of rules of the CORE is introduced and discussed regarding the proper ways to identify the rankings collected from the survey. Findings The study reveals that an interesting understanding of the outsourcing categories can be systematically implemented into the FM outsourcing relationships through the methodology of scientific artificial intelligence. FM outsourcing categorization may help to define the appropriate relationship; as either not too aggressive or too passive. Originality/value The outcome generated from the ANN can be considered a strong and solid reference to assess and define the existing outsourcing relationships between the stakeholders and the service providers with the goal to assign an outsourcing category to the service provider based on the learnt rules.

No abstract

Adding an exercise programme after functional multidisciplinary rehabilitation compared with usual care does not offer significant long-term benefits in quality of life and direct and indirect costs.

The Contingency Outsourcing Relationship (CORE) model originated from the Four Outsourcing Relationship Types (FORT) model; the CORE model is used in the globalized Facility Management (FM) industry, while the FORT model is originally used in the global information technology industry. The purpose of this paper is to thoroughly analyse the simulated case studies of the four different categories (i.e., in-house, technical expertise, commitment and common goals) of the CORE model from the perspective of the various clients. This study builds on the previous work on the outsourcing relationships between a client and a globalized FM service provider. It further explores the application of this model with the aid of artificial neural networks (ANNs) towards a sustainable future. A quantitative methodology through a survey is used to analyse eight outsourcing strategies for the four outsourcing relationships. A set of revised rules of the CORE is introduced and discussed regarding the approaches to investigate the four simulated outsourcing relationship systems. The study further reveals that an interesting understanding of the four outsourcing categories can be systematically and efficiently implemented into the FM outsourcing relationships through the methodology of scientific Artificial Intelligence (AI). It is concluded that FM outsourcing categorization may help to define the appropriate relationships. This further detailed outcome generated from the ANN can be clearly considered a strong and solid reference to define and explain the existing outsourcing relationships between the stakeholders and the service providers with the aim to assign an outsourcing category to the FM relationship between the client and service provider based on the learnt rules.

No abstract

If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation.