An optimal strategy for extracting probabilistic rules by combining rough sets and genetic algorithm

This paper proposes an optimal strategy for extracting probabilistic rules from databases. Two inductive learning-based statistic measures and their rough set-based definitions: accuracy and coverage are introduced. The simplicity of a rule emphasized in this paper has previously been ignored in the discovery of probabilistic rules. To avoid the high computational complexity of rough-set approach, some rough-set terminologies rather than the approach itself are applied to represent the probabilistic rules. The genetic algorithm is exploited to find the optimal probabilistic rules that have the highest accuracy and coverage, and shortest length. Some heuristic genetic operators are also utilized in order to make the global searching and evolution of rules more efficiently. Experimental results have revealed that it run more efficiently and generate probabilistic classification rules of the same integrity when compared with traditional classification methods.

The rough sets feature selection for trees recognition in color aerial images using genetic algorithms

Selecting a set of features which is optimal for a given task is the problem which plays an important role in a wide variety of contexts including pattern recognition, images understanding and machine learning. The concept of reduction of the decision table based on the rough set is very useful for feature selection. In this paper, a genetic algorithm based approach is presented to search the relative reduct decision table of the rough set. This approach has the ability to accommodate multiple criteria such as accuracy and cost of classification into the feature selection process and finds the effective feature subset for texture classification . On the basis of the effective feature subset selected, this paper presents a method to extract the objects which are higher than their surroundings, such as trees or forest, in the color aerial images. The experiments results show that the feature subset selected and the method of the object extraction presented in this paper are practical and effective.

The reduction subset based on rough sets applied to texture classification

The rough set is a new mathematical approach to imprecision, vagueness and uncertainty. The concept of reduction of the decision table based on the rough sets is very useful for feature selection. The paper describes an application of rough sets method to feature selection and reduction in texture images recognition. The methods applied include continuous data discretization based on Fuzzy c-means and, and rough set method for feature selection and reduction. The trees extractions in the aerial images were applied. The experiments show that the methods presented in this paper are practical and effective.

Methodological shifts in ratio-based modelling of corporate collapse

The year 1968 saw a major shift from univariate to multivariate methodological approaches to ratio-based modelling of corporate collapse. This was facilitated by the introduction of a new statistical tool called Multiple Discriminant Analysis (MDA). However, it did not take long before other statistical tools were developed. The primary objective for developing these tools was to enable deriving models that would at least do as good a job asMDA, but rely on fewer assumptions. With the introduction of new statistical tools, researchers became pre-occupied with testing them in signalling collapse. lLTUong the ratio-based approaches were Logit analysis, Neural Network analysis, Probit analysis, ID3, Recursive Partitioning Algorithm, Rough Sets analysis, Decomposition analysis, Going Concern Advisor, Koundinya and Purl judgmental approach, Tabu Search and Mixed Logit analysis. Regardless of which methodological approach was chosen, most were compared to MDA. This paper reviews these various approaches. Emphasis is placed on how they fared against MDA in signalling corporate collapse.

An illustration of variable precision rough set theory : The gender classification of the European barn swallow (Hirundo rustica)

This paper introduces a new technique in the investigation of object classification and illustrates the potential use of this technique for the analysis of a range of biological data, using avian morphometric data as an example. The nascent variable precision rough sets (VPRS) model is introduced and compared with the decision tree method ID3 (through a ‘leave n out’ approach), using the same dataset of morphometric measures of European barn swallows (Hirundo rustica) and assessing the accuracy of gender classification based on these measures. The results demonstrate that the VPRS model, allied with the use of a modern method of discretization of data, is comparable with the more traditional non-parametric ID3 decision tree method. We show that, particularly in small samples, the VPRS model can improve classification and to a lesser extent prediction aspects over ID3. Furthermore, through the ‘leave n out’ approach, some indication can be produced of the relative importance of the different morphometric measures used in this problem. In this case we suggest that VPRS has advantages over ID3, as it intelligently uses more of the morphometric data available for the data classification, whilst placing less emphasis on variables with low reliability. In biological terms, the results suggest that the gender of swallows can be determined with reasonable accuracy from morphometric data and highlight the most important variables in this process. We suggest that both analysis techniques are potentially useful for the analysis of a range of different types of biological datasets, and that VPRS in particular has potential for application to a range of biological circumstances.

Analysis on relationship between extreme pathways and correlated reaction sets

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.

A causal analysis for the expenditure data of business travelers

Determining the causal relation among attributes in a domain
is a key task in the data mining and knowledge discovery. In this
paper, we applied a causal discovery algorithm to the business traveler
expenditure survey data [1]. A general class of causal models is adopted in
this paper to discover the causal relationship among continuous and discrete variables. All those factors which have direct effect on the expense
pattern of travelers could be detected. Our discovery results reinforced
some conclusions of the rough set analysis and found some new conclusions which might significantly improve the understanding of expenditure behaviors of the business traveler.

The application of rough set and Kohonen network to feature selection for object extraction

Selecting a set of features which is optimal for a given task is a problem which plays an important role in a wide variety of contexts including pattern recognition, images understanding and machine learning. The paper describes an application of rough sets method to feature selection and reduction in texture images recognition. The proposed methods include continuous data discretization based on Kohonen neural network and maximum covariance, and rough set algorithms for feature selection and reduction. The experiments on trees extraction from aerial images show that the methods presented in this paper are practical and effective.

Objective grading of fabric pilling with wavelet texture analysis

A new objective fabric pilling grading method based on wavelet texture analysis was developed. The new method created a complex texture feature vector based on the wavelet detail coefficients from all decomposition levels and horizontal, vertical and diagonal orientations, permitting a much richer and more complete representation of pilling texture in the image to be used as a basis for classification. Standard multi-factor classification techniques of principal components analysis and discriminant analysis were then used to classify the pilling samples into five pilling degrees. The preliminary investigation of the method was performed using standard pilling image sets of knitted, woven and non-woven fabrics. The results showed that this method could successfully evaluate the pilling intensity of knitted, woven and non-woven fabrics by selecting the suitable wavelet and associated analysis scale.

Ecotourism in Costa Rica: an economic framework of analysis

Costa Rica is a small Central American nation that has gained an international reputation as a leader in environmental conservation. This has formed the base for its highly successful and lucrative small-scale ecotourism industry. However, there are threats from high rates of deforestation and expanding large scale tourism that is trading on strong environmental credentials. This paper sets out an ecologically sustainable economic framework to firstly examine the Costa Rican experience, and then analyse lessons for general policy development of any ecotourism industry. The analysis is conducted from a political economy perspective on the trade-offs between small-scale and large-scale tourism.

Values underlying the National Service Framework for coronary heart disease in England : a discourse analysis

OBJECTIVES: The National Service Framework (NSF) for Coronary Heart Disease--published by the English Department of Health in 2000--sets out how those within the health service should seek to prevent and treat coronary heart disease and care for people with the disease. Its prescriptions are partly based on what is known about coronary heart disease and partly on its underlying 'values'. This paper seeks to identify those values.

METHODS:An analysis of the discourses within the text of the NSF based on critical discourse analysis.

RESULTS: Three different discourses can be identified: the managerial, the clinical and the political. The managerial discourse is dominant. Each discourse has its own values. The main 'aspirational' values within the NSF are efficiency, effectiveness, autonomy (choice), universalism and equity. Some aspirational values--particularly equity--appear to be largely rhetorical and lead to few recommendations or prescriptions. Some values that might have been expected to underlie the framework, such as compassion and democracy, are largely absent.

CONCLUSIONS: Discourse analysis provides a more systematic and transparent method of describing the values behind health care policy than the methods that have been used previously.

An integrated model of subnational regional and urban economic development : framework of analysis

The mechanism of subnational regional and urban economic development has been studied extensively by economists, geographers, town planners and other academics. The existing widely varying theories of regional economic development are insufficient on their own in explaining how a region can develop and prosper. Each theory has evaluated a few facets of regional economic development. Research from these different perspectives is narrow and prevents any cross-fertilization of research from these diverse theories. Recognition of multiple factors affecting the development process has led the author to create an integrated model of regional and urban economic development. The essay first sets out to describe and explain this integrated model. Each of the components of this new model draws heavily upon seminal work in the field. This model proposes three rings. Each ring is at a different level of abstraction. The determinants of development described in each ring can influence each and every other determinant of development shown in the three-ring structure. This model recognizes that development in any centre, be it regional or urban, nascent or established, is a composite end result of the complex interplay of all the determinants. The essay then goes on to show how this model can provide a broad holistic approach to regional economic development that can assist researchers in their attempts to understand and link its various theories.

Contractual thinking and responsible government in China: A constructivist framework for analysis*

Responsible government is often seen as contingent on democracy. Yet despite China's continued lack of notable progress in democratization, recent years have witnessed some limited moves towards responsible governance. In the absence of free elections and other institutional arrangements, how can an authoritarian regime become responsible? This paper turns to the role of ideas and culture in general and contractual thinking in particular for an explanation. Contractual thinking, defined as a particular kind of intersubjective understanding between the government and citizens with regard to their mutual interests, is present in both China's contemporary official discourse on "responsible government" and traditional Chinese culture. Taking a constructivist approach, the paper focuses on two interrelated aspects of the role of contractual thinking in the construction of responsible government. First, it examines how contractual thinking, by helping redefine the identity and interest of the government in line with citizens' loyalty, could allow more responsible government behaviour. It then illustrates that in the case of government irresponsibility, contractual thinking sets the discursive context for rightful resistance from citizens as well as for a more sympathetic reading of such resistance by the government, both of which, the paper argues, could facilitate the development of responsible governance.

The valuation of fast food outlets in Australia : methodology, analysis and reliability

Fast food outlets are a significant sub sector of the Hospitality and Tourism Property Market and a specialized form of business. This form of hospitality outlet has experienced significant growth and change in the last 20 years. Their value as an asset is therefore of significant interest to many involved in the tourism and hospitality industry, not least fast food operators or potential operators and their financiers. However, little attention has been given in professional and academic literature to valuation methodology, the analysis of the major components of asset value, and the underlying factors which influence asset value. As such the reliability of the valuation process could justifiably be questioned.
This paper sets out a working definition of a fast food outlet. It investigates the major determinants of value with respect to asset value and examines the accepted methods of valuation of fast food outlets in Australia as well as establishing the methods most commonly used. It clarifies the major components of asset value and examines to what extent these have changed with the changing business environment. In particular it isolates the role of Goodwill in assessing Going Concern Value. Sources of data include a comprehensive literature review and personal interviews with professionals involved in the valuation process. The paper concludes that an efficient valuation process requires that fast food outlets be considered as both a real estate and business investment. The contribution of both tangible and intangible assets to the value of the asset must be identified.

Energy analysis of the construction of office buildings /by Graham J. Treloar

Buildings have a significant impact on the environment due to the energy required for the manufacture of construction materials. The method of assessing the energy embodied in a product is known as energy analysis. Detailed office building embodied energy case studies are very rare. However, there is evidence to suggest that the energy requirements for the construction phase of commercial buildings, including the energy embodied in materials, is a significant component of the life cycle energy requirements. This thesis sets out to examine the current state of energy analysis, determine the national average energy intensities < i.e. embodied energy rates < for building materials and assess the significance of using national average energy intensities for the energy analysis of a case study office building. Likely ranges of variation in the building material embodied energy rates from the national averages are estimated and the resulting distribution for total embodied energy in the case study building simulated. Strategies for improving the energy analysis methods and data are suggested. Detailed energy analysis is shown to be a useful indicative method of quantifying the energy required for the construction of buildings.