84 resultados para limit sets
Resumo:
For most data stream applications, the volume of data is too huge to be stored in permanent devices or to be thoroughly scanned more than once. It is hence recognized that approximate answers are usually sufficient, where a good approximation obtained in a timely manner is often better than the exact answer that is delayed beyond the window of opportunity. Unfortunately, this is not the case for mining frequent patterns over data streams where algorithms capable of online processing data streams do not conform strictly to a precise error guarantee. Since the quality of approximate answers is as important as their timely delivery, it is necessary to design algorithms to meet both criteria at the same time. In this paper, we propose an algorithm that allows online processing of streaming data and yet guaranteeing the support error of frequent patterns strictly within a user-specified threshold. Our theoretical and experimental studies show that our algorithm is an effective and reliable method for finding frequent sets in data stream environments when both constraints need to be satisfied.
Resumo:
The issue of credit card debt has become an increasing concern in recent years. In Australia, for example, there is currently $42.5 billion worth of outstanding debt on credit cards, with $30 billion (over 70 per cent) bearing interest. Further, in 2001, Visa reported that 32 per cent of consumers had not paid their card off in the previous 12 months, which suggests that interest-bearing debt in Australia is held by approximately only 113 of credit card borrowers. An important element of credit card marketing is the use of psychological manipulations to encourage consumers to take-up credit. In this article, we examine the use of language and imagery in unsolicited credit card limit increase offers, and how these might influence consumers' decisions to increase their credit card limit. The analysis found that the use of terms that focused on the benefits of credit card use, such as "choice", "freedom", and "peace of mind" were used consistently to convince consumers to increase their credit card limit, whereas the use the of terms that could be considered more pragmatic and with direct reference to the nature of the product, such as "debt", "repayment" and "loan", were rarely used. Similarly, the use of colour, text changes, and images, were used which may have an influence over a consumer's ability to rationally consider whether the increase is appropriate for them. The paper concludes by recommending that government and representative bodies need to take into account the psychological manipulations used by credit card providers when developing consumer policy and codes of ethics.
Resumo:
Consumer Action commissioned Dr Paul Harrison, Deakin Business School, Deakin University and Marta Massi, School of Marketing and Communication, Lumsa University (Rome), to study the psychological aspects of one form of credit marketing – unsolicited credit card limit-increase offers (UCCLIOs). The researchers studied 21 UCCLIO letters – 17 provided by consumers and four provided by banks – and applied theories developed from previous research in the fields of marketing, consumer behavior, behavioural economics and cognitive psychology, to describe likely ways in which UCCLIO’s influenced consumer behavior and decision making. The researchers make some recommendations from a behavioural perspective based on their findings, and Consumer Action proposes how these findings might be applied to consumer policy.
Resumo:
The links between the built environment and sustainability issues such as fossil fuel consumption and climate change is clear. In developed countries buildings contribute around half of all carbon dioxide emissions and offer considerable scope for a significant contribution to sustainability through ecologically aware design and increased energy efficiency (BRE, 1996). The Australian commercial stock emits 12% of all greenhouse gas emissions however the commercial property market has some inherent barriers to sustainability (DSE, 2005). A substantial proportion of the stock is owned by institutional investors who are unconvinced by the need to improve their stock and pass on running costs to tenants (Callender & Key, 1997). As capital values are not greatly affected by sustainability, owners react by doing little or nothing and the effect is to limit sustainability related investment and undermine efforts to deliver sustainability in the sector.
Furthermore the efficiency of buildings declines over time and whilst energy efficiency is important to new design, the existing stock must be improved if urban built environment greenhouse gas emissions are to be reduced. Much of the property and surveying research has previously adopted an illustrative case study approach advocating the benefits of ESD and energy efficiency in existing buildings. This research adopts a radically different approach and profiles the entire office stock of a global CBD, namely Melbourne, which is seeking to become a carbon neutral city by 2020. The research also employs scenario forecasting to model future changes to the stock over a fifteen year period. This paper sets out the rationale for the research and establishes the methodological approach adopted by the research team.
Resumo:
The Australian commercial stock emits 12% of all greenhouse gas emissions however the commercial property market has some inherent barriers to sustainability (DSE, 2005). A substantial proportion of the stock is owned by institutional investors who are unconvinced by the need to improve their stock and pass on running costs to tenants (Callender & Key, 1997). The links between the built environment and sustainability issues such as fossil fuel consumption and climate change is clear. In developed countries buildings contribute around half of all carbon dioxide emissions and offer considerable scope for a significant contribution to sustainability through ecologically aware design and increased energy efficiency (BRE, 1996). As capital values are not greatly affected by sustainability, owners react by doing little or nothing and the effect is to limit sustainability-related investment and undermine efforts to deliver sustainability in the sector. Facility managers are in an influential position to help address sustainability issues via an increased awareness of energy efficiency and CO2 emissions.
Even though the efficiency of buildings is primarily focused on new stock, with an existing churn replacement rate of approximately 2-3% the existing stock must be improved if urban built environment greenhouse gas emissions are to be reduced – clearly the management of existing stock must therefore contribute to substantial savings in energy use. Much of the property and surveying research has previously adopted an illustrative case study approach advocating the benefits of ESD and energy efficiency in existing buildings. This research adopts a radically different approach and profiles the entire office stock of a global CBD, namely Melbourne, which is seeking to become a carbon neutral city by 2020 (City of Melbourne, 2003). The research also employs scenario forecasting to model future changes to the stock over a fifteen year period. This paper sets out the rationale for the research and establishes the methodological approach adopted by the research team. The results provides a unique insight into the variations between different building types and grades of office buildings, which in turn will allow facility managers to gain a better understanding of where gains in energy efficiency can be made.
Resumo:
In previous paper, we introduced a concept of multi-soft sets and used it for finding reducts. However, the comparison of the proposed reduct has not been presented yet, especially with rough-set based reduct. In this paper, we present matrices representation of multi-soft sets. We define AND and OR operations on a collection of such matrices and apply it for finding reducts and core of attributes in a multi-valued information system. Finally, we prove that our proposed technique for reduct is equivalent to Pawlak’s rough reduct.
Resumo:
Background: Constraint-based modeling of reconstructed genome-scale metabolic networks has been successfully applied on several microorganisms. In constraint-based modeling, in order to characterize all allowable phenotypes, network-based pathways, such as extreme pathways and elementary flux modes, are defined. However, as the scale of metabolic network rises, the number of extreme pathways and elementary flux modes increases exponentially. Uniform random sampling solves this problem to some extent to study the contents of the available phenotypes. After uniform random sampling, correlated reaction sets can be identified by the dependencies between reactions derived from sample phenotypes. In this paper, we study the relationship between extreme pathways and correlated reaction sets.
Results: Correlated reaction sets are identified for E. coli core, red blood cell and Saccharomyces cerevisiae metabolic networks respectively. All extreme pathways are enumerated for the former two metabolic networks. As for Saccharomyces cerevisiae metabolic network, because of the large scale, we get a set of extreme pathways by sampling the whole extreme pathway space. In most cases, an extreme pathway covers a correlated reaction set in an 'all or none' manner, which means either all reactions in a correlated reaction set or none is used by some extreme pathway. In rare cases, besides the 'all or none' manner, a correlated reaction set may be fully covered by combination of a few extreme pathways with related function, which may bring redundancy and flexibility to improve the survivability of a cell. In a word, extreme pathways show strong complementary relationship on usage of reactions in the same correlated reaction set.
Conclusion: Both extreme pathways and correlated reaction sets are derived from the topology information of metabolic networks. The strong relationship between correlated reaction sets and extreme pathways suggests a possible mechanism: as a controllable unit, an extreme pathway is regulated by its corresponding correlated reaction sets, and a correlated reaction set is further regulated by the organism's regulatory network.
Resumo:
This paper discusses results from an international study of continuous improvement in product innovation. The empirical research is based upon a theoretical model of continuous product innovation (CPI) that identifies contingencies, behaviours, levers and performances relevant to improving product innovation processes. As successful knowledge management is widely recognised as a key capability for firms to successfully develop CPI, companies have been classified according to identified contingencies and the impact of these contingencies on key knowledge management criteria. Comparative analysis of the identified groups of companies has demonstrated important differences between the learning behaviours found present in the two groups thus identified, and in the levers used to develop and support these behaviours. The selection of performance measures by the two groups has highlighted further significant differences in the way the two groups understand and measure their CPI processes. Finally, the paper includes a discussion of appropriate mechanisms for firms with similar contingency sets to improve their approaches to organisational learning and product innovation.
Resumo:
In this work we introduce a new construction method of Atanassov's intuitionistic fuzzy sets (A-IFSs) from fuzzy sets. We use A-IFSs in image processing. We propose a new image magnification algorithm using A-IFSs. This algorithm is characterized by its simplicity and its efficiency.
Resumo:
Missing data imputation is a key issue in learning from incomplete data. Various techniques have been developed with great successes on dealing with missing values in data sets with homogeneous attributes (their independent attributes are all either continuous or discrete). This paper studies a new setting of missing data imputation, i.e., imputing missing data in data sets with heterogeneous attributes (their independent attributes are of different types), referred to as imputing mixed-attribute data sets. Although many real applications are in this setting, there is no estimator designed for imputing mixed-attribute data sets. This paper first proposes two consistent estimators for discrete and continuous missing target values, respectively. And then, a mixture-kernel-based iterative estimator is advocated to impute mixed-attribute data sets. The proposed method is evaluated with extensive experiments compared with some typical algorithms, and the result demonstrates that the proposed approach is better than these existing imputation methods in terms of classification accuracy and root mean square error (RMSE) at different missing ratios.