Protecting Schrodinger cat states using feedback

A feedback model based on direct photodetection and micromaser-like atomic injection is proposed for the preservation of quantum coherence in a cavity. We show that in this way it is possible to slow down significantly the decoherence of Schrodinger cat states.

A survey of Australian consumers' attitudes towards UHT milk

A telephone survey was conducted in Melbourne and Brisbane to obtain a profile of milk consumption in Australia and determine consumers' attitudes regarding UHT milk. It was anticipated that this survey would reveal the reasons for the low level of UHT milk consumption in Australia. Pasteurised milk was the main milk type used by more than 80% of respondents. For UHT milk this figure was much lower (approximately 10%), even though two thirds of respondents had tried UHT milk. Factors that were found to influence UHT milk consumption included existing milk consumption habits, consumer perception, flavour and price. The majority of non-users of UHT milk stated habit of using other milk type as their main reason for not using UHT milk. Other reasons included poor nutritional value, poor flavour and not real/pure milk, indicating a negative consumer perception of the product. The flavour of UHT milk was identified as a problem, with nearly half of UHT milk users considering it to be worse than the flavour of pasteurised milk. However, a small proportion of UHT milk users preferred the flavour of UHT milk, with the majority of them stating that it was creamier, richer and/or stronger than the flavour of pasteurised milk. Prior to post-farmgate deregulation, price was shown to discourage consumers from using UHT milk. At the time of the survey, post-farmgate prices in Victoria were deregulated resulting in UHT milk being priced below that of pasteurised milk in some instances. This was believed to contribute to a significantly higher market share of the product in Melbourne than in Brisbane.

Service quality and consumers' experience: Towards an interpretive approach

As marketers and researchers we understand quality from the consumer's perspective, and throughout contemporary service quality literature there is an emphasis on what the consumer is looking for, or at least that is the intention. Through examining the underlying assumptions of dominant service quality theories, an implicit dualistic ontology is highlighted (where subject and object are considered independent) and argued to effectively negate the said necessary consumer orientation. This fundamental assumption is discussed, as are the implications, following a critical review of dominant service quality models. Consequently, we propose an alternative approach to service quality research that aims towards a more genuine understanding of the consumer's perspective on quality experienced within a service context. Essentially, contemporary service quality research is suggested to be limited in its inherent third-person perspective and the interpretive, specifically phenomenographic, approach put forward here is suggested as a means of achieving a first-person perspective on service quality.

Consumers' perceived risk: Sources versus consequences

In this study, we examine an important factor that affects consumers' acceptance of business-to-commerce (B2C) electronic commerce - perceived risk. The objective of this paper is to examine the definition of perceived risk in the context of B2C electronic commerce. The paper highlights the importance of perceived risk and the interwoven relation between perceived risk and trust. It discusses the problem of defining perceived risk in prior B2C research. This study proposes a new classification of consumers' perceived risk based on sources. It highlights the importance of identifying the sources of consumer's risk perceptions in addition to the consequences dimensions. Two focus group discussion sessions were conducted to verify the proposed classification. Results indicate that Internet consumers perceive three sources of risk in B2C electronic commerce: technology, vendor, and product. © 2003 Elsevier B.V. All rights reserved.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

Data mining contributions to characterize MV consumers and to improve the suppliers-consumers settlements

This paper deals with the establishment of a characterization methodology of electric power profiles of medium voltage (MV) consumers. The characterization is supported on the data base knowledge discovery process (KDD). Data Mining techniques are used with the purpose of obtaining typical load profiles of MV customers and specific knowledge of their customers’ consumption habits. In order to form the different customers’ classes and to find a set of representative consumption patterns, a hierarchical clustering algorithm and a clustering ensemble combination approach (WEACS) are used. Taking into account the typical consumption profile of the class to which the customers belong, new tariff options were defined and new energy coefficients prices were proposed. Finally, and with the results obtained, the consequences that these will have in the interaction between customer and electric power suppliers are analyzed.

Intelligent management of end consumers loads including electric vehicles through a SCADA system

The large penetration of intermittent resources, such as solar and wind generation, involves the use of storage systems in order to improve power system operation. Electric Vehicles (EVs) with gridable capability (V2G) can operate as a means for storing energy. This paper proposes an algorithm to be included in a SCADA (Supervisory Control and Data Acquisition) system, which performs an intelligent management of three types of consumers: domestic, commercial and industrial, that includes the joint management of loads and the charge/discharge of EVs batteries. The proposed methodology has been implemented in a SCADA system developed by the authors of this paper – the SCADA House Intelligent Management (SHIM). Any event in the system, such as a Demand Response (DR) event, triggers the use of an optimization algorithm that performs the optimal energy resources scheduling (including loads and EVs), taking into account the priorities of each load defined by the installation users. A case study considering a specific consumer with several loads and EVs is presented in this paper.

MV producers and consumers agents characterization with DSM techniques

This paper consist in the establishment of a Virtual Producer/Consumer Agent (VPCA) in order to optimize the integrated management of distributed energy resources and to improve and control Demand Side Management DSM) and its aggregated loads. The paper presents the VPCA architecture and the proposed function-based organization to be used in order to coordinate the several generation technologies, the different load types and storage systems. This VPCA organization uses a frame work based on data mining techniques to characterize the costumers. The paper includes results of several experimental tests cases, using real data and taking into account electricity generation resources as well as consumption data.