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Abstract: In a recent paper Greco et al. (2012) propose a number of properties for measures of rule interestingness. The most fundamental of these properties is that such measures should be Bayesian confirmation measures and this criterion provides the context for the current paper as well. They also propose a number of properties relating to entailment and symmetry in order to discriminate between various confirmation measures which have been proposed in the literature. Working within the same framework of confirmation measures, several limitations of their proposed properties are discussed and a motivation provided for alternative properties. Two new measures of interestingness are proposed and then compared with two other recently proposed measures which also satisfy these properties. [Copyright &y& Elsevier]

Abstract: The limit inferior and limit superior of a bounded sequence of fuzzy real numbers have been introduced by Aytar et al. (2008) [1]. In this paper we give a simplified expressions for limit inferior and limit superior. The expressions is concise and convenient for use. As a straightforward corollary of this expressions, we can easily prove some properties of the limit inferior and limit superior. [Copyright &y& Elsevier]

Abstract: Evolutionary membrane computing is an important research direction of membrane computing that aims to explore the complex interactions between membrane computing and evolutionary computation. These disciplines are receiving increasing attention. In this paper, an overview of the evolutionary membrane computing state-of-the-art and new results on two established topics in well defined scopes (membrane-inspired evolutionary algorithms and automated design of membrane computing models) are presented. We survey their theoretical developments and applications, sketch the differences between them, and compare the advantages and limitations. [Copyright &y& Elsevier]

Abstract: There are mainly two methodologies dealing with uncertainty measurement issue in rough set theory: pure rough set approach and information theory approach. Pure rough set approach is based on the concepts of accuracy, roughness and approximation accuracy proposed by Pawlak. Information theory approach is based on Shannon’s entropy or its variants. Several authors have extended the information theory approach into incomplete information systems. However, there are few studies on extending the pure rough set approach to incomplete information systems. This paper focuses on constructing uncertainty measures in incomplete information systems by pure rough set approach. Three types of definitions of lower and upper approximations and corresponding uncertainty measurement concepts including accuracy, roughness and approximation accuracy are investigated. Theoretical analysis indicates that two of the three types can be used to evaluate the uncertainty in incomplete information systems. Experiments on incomplete real-life data sets have been conducted to test the two selected types (the first type and the third type) of uncertainty measures. Results show that the two types of uncertainty measures are effective. [Copyright &y& Elsevier]

Abstract: The effectiveness of current software development strategies, such as Model-Driven Development (MDD), depends largely on the quality of their primary artefacts, i.e. software models. As the standard modelling language for software systems is the Unified Modelling Language (UML), quality assurance of UML models is a major research field in Computer Science. Understandability, i.e. a model’s ability to be easily understood, is one model quality property that is currently heavily under investigation. In particular, researchers are searching for the factors that determine an UML model’s understandability and are looking for ways to manipulate these factors. This paper presents an empirical study investigating the effect that structural complexity has on the understandability of one particular type of UML model, i.e. the statechart diagram. Based on data collected in a family of three experiments, we have identified three dimensions of structural complexity that affect understandability: (i) the size and control flow complexity of the statechart in terms of features such as the number of states, events, guards and state transitions; (ii) the actions that are performed when entering or leaving a state; (iii) the sequence of actions that is performed while staying within a state. Based on these structural complexity dimensions we have built an understandability prediction model using a regression technique that is specifically recommended for data obtained through a repeated measures design. Our test results show that each of the underlying structural complexity dimensions has a significant impact on the understandability of a statechart diagram. [Copyright &y& Elsevier]

Abstract: This paper provides a representation theorem of lattices using many-valued relations. We show that any many-valued relation can be associated to a unique lattice which is a meet-sublattice of a product of chains. Conversely, to any lattice we can associate a many-valued relation such that its associated lattice is isomorphic to the initial one. Thereby, we obtain a representation theorem of lattices using many-valued relations. Moreover, since several many-valued relations might have the same associated lattice, we give a characterization of the minimal many-valued relation that can be associated to a lattice. We then sketch a polynomial time algorithm which computes such a minimal relation from either a lattice or an arbitrary relation. This representation presents several advantages: it is smaller than the usual binary representation; all known reconstruction algorithms working on binary relation can be used without loss of efficiency; it can be used by existing data mining processes. [Copyright &y& Elsevier]

The temporal aggregate in temporal databases is an extension of the conventional aggregate to include the time on the range condition of aggregation. It is a useful operation for Historical Data Warehouses, Call Data Records, and so on. In this paper, we propose a structure for the temporal aggregation with multiple range-condition attributes, called the ITA-tree, and an aggregate processing method based on the structure. In the ITA-tree, we transform the time interval of a record into a single value, called the T-value. Then, we index records according to their T-values like a B+-tree style. For possible hot-spot situations, we also propose an improvement of the ITA-tree, called the eITA-tree. Through analyses and experiments, we evaluate the performance of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper a modified algorithm is suggested for developing polynomial neural network (PN N) models. Optimal partial description (PD) modeling is introduced at each layer of the PNN expansion, a task accomplished using the orthogonal least squares (OLS) method. Based on the initial PD models determined by the polynomial order and the number of PD inputs, OLS selects the most significant regressor terms reducing the output error variance. The method produces PN N models exhibiting a high level of accuracy and superior generalization capabilities. Additionally, parsimonious models are obtained comprising a considerably smaller number of parameters compared to the ones generated by means of the conventional PNN algorithm. Three benchmark examples are elaborated, including modeling of the gas furnace process as well as the iris and wine classification problems. Extensive simulation results and comparison with other methods in the literature, demonstrate the effectiveness of the suggested modeling approach. [ABSTRACT FROM AUTHOR]

In this paper, two uncertain linguistic aggregation operators called uncertain linguistic ordered weighted averaging (ULOWA) operator and uncertain linguistic hybrid aggregation (ULHA) operator are proposed. An approach to multiple attribute group decision making with uncertain linguistic information is developed based on the ULOWA and the ULHA operators. Finally, a practical application of the developed approach to the problem of evaluating university faculty for tenure and promotion is given. [ABSTRACT FROM AUTHOR]