Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Biomechanical consequences of impairment: A taxonomically valid basis for classification in a unified disability athletics system

Developing a unified classification system to replace four of the systems currently used in disability athletics (i.e., track and field) has been widely advocated. The diverse impairments to be included in a unified system require severed assessment methods, results of which cannot be meaningfully compared. Therefore, the taxonomic basis of current classification systems is invalid in a unified system. Biomechanical analysis establishes that force, a vector described in terms of magnitude and direction, is a key determinant of success in all athletic disciplines. It is posited that all impairments to be included in a unified system may be classified as either force magnitude impairments (FMI) or force control impairments (FCI). This framework would provide a valid taxonomic basis for a unified system, creating the opportunity to decrease the number of classes and enhance the viability of disability athletics.

Associative priming in color naming: Interference and facilitation

In Experiment 1, color-naming interference for target stimuli following associated primes was greater in a group making a lexical decision to the prime than in a group reading the prime silently. High-frequency targets were responded to more quickly than low-frequency targets. In Experiment 2, with subjects naming the prime, there was evidence of associative interference when the prime and the target were grouped temporally but not when the intertrial interval was comparable with the prime-target interval. Associative primes presented at a short (120-msec) prime-target stimulus onset asynchrony facilitated color naming in Experiment 3. Taken together, the results suggest that the effect of faster processing of the base word in a color-naming task is facilitatory and that color-naming priming interference arises when associative prime processing increases conflict between word and color responses by enhancing phonological or articulatory activation of the base word.

Strain-dependent fluid flow defined through rock mass classification schemes

Strain-dependent hydraulic conductivities are uniquely defined by an environmental factor, representing applied normal and shear strains, combined with intrinsic material parameters representing mass and component deformation moduli, initial conductivities, and mass structure. The components representing mass moduli and structure are defined in terms of RQD (rock quality designation) and RMR (rock mass rating) to represent the response of a whole spectrum of rock masses, varying from highly fractured (crushed) rock to intact rock. These two empirical parameters determine the hydraulic response of a fractured medium to the induced-deformations The constitutive relations are verified against available published data and applied to study one-dimensional, strain-dependent fluid flow. Analytical results indicate that both normal and shear strains exert a significant influence on the processes of fluid flow and that the magnitude of this influence is regulated by the values of RQD and RMR.

CysView: protein classification based on cysteine pairing patterns

CysView is a web-based application tool that identifies and classifies proteins according to their disulfide connectivity patterns. It accepts a dataset of annotated protein sequences in various formats and returns a graphical representation of cysteine pairing patterns. CysView displays cysteine patterns for those records in the data with disulfide annotations. It allows the viewing of records grouped by connectivity patterns. CysView's utility as an analysis tool was demonstrated by the rapid and correct classification of scorpion toxin entries from GenPept on the basis of their disulfide pairing patterns. It has proved useful for rapid detection of irrelevant and partial records, or those with incomplete annotations. CysView can be used to support distant homology between proteins. CysView is publicly available at http://research.i2r.a-star.edu.sg/CysView/.

Normal and anomalous classification of category exemplars in schizophrenia

Background Schizophrenia has been associated with semantic memory impairment and previous studies report a difficulty in accessing semantic category exemplars (Moelter et al. 2005 Schizophr Res 78:209–217). The anterior temporal cortex (ATC) has been implicated in the representation of semantic knowledge (Rogers et al. 2004 Psychol Rev 111(1):205–235). We conducted a high-field (4T) fMRI study with the Category Judgment and Substitution Task (CJAST), an analogue of the Hayling test. We hypothesised that differential activation of the temporal lobe would be observed in schizophrenia patients versus controls. Methods Eight schizophrenia patients (7M : 1F) and eight matched controls performed the CJAST, involving a randomised series of 55 common nouns (from five semantic categories) across three conditions: semantic categorisation, anomalous categorisation and word reading. High-resolution 3D T1-weighted images and GE EPI with BOLD contrast and sparse temporal sampling were acquired on a 4T Bruker MedSpec system. Image processing and analyses were performed with SPM2. Results Differential activation in the left ATC was found for anomalous categorisation relative to category judgment, in patients versus controls. Conclusions We examined semantic memory deficits in schizophrenia using a novel fMRI task. Since the ATC corresponds to an area involved in accessing abstract semantic representations (Moelter et al. 2005), these results suggest schizophrenia patients utilise the same neural network as healthy controls, however it is compromised in the patients and the different ATC activity might be attributable to weakening of category-to-category associations.

Expectancy-based associative and identity priming in pronunciation

Evidence for expectancy-based priming in the pronunciation task was provided in three experiments. In Experiments 1 and 2, a high proportion of associatively related trials produced greater associative priming and superior retrieval of primes in a subsequent test of memory for primes, whereas high- and low-proportion groups showed comparable repetition benefits in perceptual identification of previously presented primes. In Experiment 2, the low-proportion condition had few associatively related pairs hut many identity pairs. In Experiment 3, identity priming was greater in a high- than a low-identity proportion group, with similar repetition benefits and prime retrieval responses for the two groups. These results indicate that when the prime-target relationship is salient, subjects strategically vary their processing of the prime according to the nature of the prime-target relationship.

Mild myocardial infarction - A classification problem in epidemiologic studies

In studies assessing the trends in coronary events, such as the World Health Organization (WHO) MONICA Project (multinational MONItoring of trends and determinants of CArdiovascular disease), the main emphasis has been on coronary deaths and non-fatal definite myocardial infarctions (MI). It is, however, possible that the proportion of milder MIs may be increasing because of improvements in treatment and reductions in levels of risk factors. We used the MI register data of the WHO MONICA Project to investigate several definitions for mild non-fatal MIs that would be applicable in various settings and could be used to assess trends in milder coronary events. Of 38 populations participating in the WHO MONICA MI register study, more than half registered a sufficiently wide spectrum of events that it was possible to identify subsets of milder cases. The event rates and case fatality rates of MI are clearly dependent on the spectrum of non-fatal MIs, which are included. On clinical grounds we propose that the original MONICA category ''non-fatal possible MI'' could bt:divided into two groups: ''non fatal probable MI'' and ''prolonged chest pain.'' Non-fatal probable MIs are cases, which in addition to ''typical symptoms'' have electrocardiogram (EGG) or enzyme changes suggesting cardiac ischemia, but not severe enough to fulfil the criteria for non-fatal definite MI In more than half of the MONICA Collaborating Centers, the registration of MI covers these milder events reasonably well. Proportions of non-fatal probable MIs vary less between populations than do proportions of non fatal possible MIs. Also rates of non-fatal probable MI are somewhat more highly correlated with rates of fatal events and non-fatal definite MI. These findings support the validity of the category of non-fatal probable MI. In each center the increase in event rates and the decrease in case-fatality due to the inclusion of non-fatal probable MI was lar er for women than men. For the WHO MONICA Project and other epidemiological studies the proposed category of non-fatal probable MIs can be used for assessing trends in rates of milder MI. Copyright (C) 1997 Elsevier Science Inc.