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).

Improvements in the data partitioning approach for frequent itemsets mining

Frequent Itemsets mining is well explored for various data types, and its computational complexity is well understood. There are methods to deal effectively with computational problems. This paper shows another approach to further performance enhancements of frequent items sets computation. We have made a series of observations that led us to inventing data pre-processing methods such that the final step of the Partition algorithm, where a combination of all local candidate sets must be processed, is executed on substantially smaller input data. The paper shows results from several experiments that confirmed our general and formally presented observations.

Diagnosis of diabetes mellitus: case of different cutoff values: A data mining approach

Objective: An estimation of cut-off points for the diagnosis of diabetes mellitus (DM) based on individual risk factors. Methods: A subset of the 1991 Oman National Diabetes Survey is used, including all patients with a 2h post glucose load >= 200 mg/dl (278 subjects) and a control group of 286 subjects. All subjects previously diagnosed as diabetic and all subjects with missing data values were excluded. The data set was analyzed by use of the SPSS Clementine data mining system. Decision Tree Learners (C5 and CART) and a method for mining association rules (the GRI algorithm) are used. The fasting plasma glucose (FPG), age, sex, family history of diabetes and body mass index (BMI) are input risk factors (independent variables), while diabetes onset (the 2h post glucose load >= 200 mg/dl) is the output (dependent variable). All three techniques used were tested by use of crossvalidation (89.8%). Results: Rules produced for diabetes diagnosis are: A- GRI algorithm (1) FPG>=108.9 mg/dl, (2) FPG>=107.1 and age>39.5 years. B- CART decision trees: FPG >=110.7 mg/dl. C- The C5 decision tree learner: (1) FPG>=95.5 and 54, (2) FPG>=106 and 25.2 kg/m2. (3) FPG>=106 and =133 mg/dl. The three techniques produced rules which cover a significant number of cases (82%), with confidence between 74 and 100%. Conclusion: Our approach supports the suggestion that the present cut-off value of fasting plasma glucose (126 mg/dl) for the diagnosis of diabetes mellitus needs revision, and the individual risk factors such as age and BMI should be considered in defining the new cut-off value.

The association between auditory memory span and speech rate in children from kindergarten to sixth grade

This study reexamined the association between speech rate and memory span in children from kindergarten to sixth grade (N = 152) in order to potentially account for the inconsistencies within the published literature on this topic. Some of the inconsistencies in past research may reflect the different methods adopted in assessing speech rate. In particular, repeating word triples may itself involve memory demands, contaminating the correlation between speech rate and memory span in younger children. Analyses using composite speech rate and memory span measures showed that speech rate for word triples shared variance with memory span that was independent of speech rate for single words. Moreover, speech rate for word triples was largely redundant with age in explaining additional variation in memory span once the effects of speech rate for single words were controlled. (C) 2002 Elsevier Science.

Stability criteria for unsupervised temporal association networks

A biologically realizable, unsupervised learning rule is described for the online extraction of object features, suitable for solving a range of object recognition tasks. Alterations to the basic learning rule are proposed which allow the rule to better suit the parameters of a given input space. One negative consequence of such modifications is the potential for learning instability. The criteria for such instability are modeled using digital filtering techniques and predicted regions of stability and instability tested. The result is a family of learning rules which can be tailored to the specific environment, improving both convergence times and accuracy over the standard learning rule, while simultaneously insuring learning stability.

No Association Between MTHFR A1298C and MTRR A66G Polymorphisms, and MS in an Australian Cohort

Multiple sclerosis (MS) is a complex neurological disease that affects the central nervous system (CNS) resulting in debilitating neuropathology. Pathogenesis is primarily defined by CNS inflammation and demyelination of nerve axons. Methionine synthase reductase (MTRR) is an enzyme that catalyzes the remethylation of homocysteine (Hcy) to methionine via cobalamin and folate dependant reactions. Cobalamin acts as an intermediate methyl carrier between methylenetetrahydrofolate reductase (MTHFR) and Hcy. MTRR plays a critical role in maintaining cobalamin in an active form and is consequently an important determinant of total plasma Hcy (pHcy) concentrations. Elevated intracellular pHcy levels have been suggested to play a role in CNS dysfunction, neurodegenerative, and cerebrovascular diseases. Our investigation entailed the genotyping of a cohort of 140 cases and matched controls for MTRR and MTHFR, by restriction length polymorphism (RFLP) techniques. Two polymorphisms: MTRR A66G and MTHFR A1298C were investigated in an Australian age and gender matched case-control study. No significant allelic frequency difference was observed between cases and controls at the α = 0.05 level (MTRR χ^2 = 0.005, P = 0.95, MTHFR χ^2 = 1.15, P = 0.28). Our preliminary findings suggest no association between the MTRR A66G and MTHFR A1298C polymorphisms and MS.

Effects of temporal association on recognition memory

The influence of temporal association on the representation and recognition of objects was investigated. Observers were shown sequences of novel faces in which the identity of the face changed as the head rotated. As a result, observers showed a tendency to treat the views as if they were of the same person. Additional experiments revealed that this was only true if the training sequences depicted head rotations rather than jumbled views; in other words, the sequence had to be spatially as well as temporally smooth. Results suggest that we are continuously associating views of objects to support later recognition, and that we do so not only on the basis of the physical similarity, but also the correlated appearance in time of the objects.

Variants of temporal defeasible logics for modelling norm modifications

This paper proposes some variants of Temporal Defeasible Logic (TDL) to reason about normative modifications. These variants make it possible to differentiate cases in which, for example, modifications at some time change legal rules but their conclusions persist afterwards from cases where also their conclusions are blocked.

Thermogravimetric determination of the carbon dioxide reactivity of char from some New Zealand coals and its association with the inorganic geochemistry of the parent coal

Thermogravimetrically-determined carbon dioxide reactivities of chars formed from New Zealand coals, ranging in rank from lignite to high volatile bituminous, vary from 0.12 to 10.63 mg/h/mg on a dry, ash-free basis. The lowest rank subbituminous coal chars have similar reactivities to the lignite coal chars. Calcium content of the char shows the strongest correlation with reactivity, which increases as the calcium content increases. High calcium per se does not directly imply a high char reactivity. Organically-bound calcium catalyses the conversion of carbon to carbon monoxide in the presence of carbon dioxide, whereas calcium present as discrete minerals in the coal matrix, e.g., calcite, fails to significantly affect reactivity. Catalytic effects of magnesium, iron, sodium and phosphorous are not as obvious, but can be recognised for individual chars. The thermogravimetric technique provides a fast, reliable analysis that is able to distinguish char reactivity differences between coals, which may be due to any of the above effects. Published by Elsevier Science B.V.

Instantaneous outbursts in underground coal mines: An overview and association with coal type

Instantaneous outbursts in underground coal mines have occurred in at least 16 countries, involving both methane (CH4) and carbon dioxide (CO2). The precise mechanisms of an instantaneous outburst are still unresolved but must consider the effects of stress, gas content and physico-mechanical properties of the coal. Other factors such as mining methods (e.g., development heading into the coal seam) and geological features (e.g., coal seam disruptions from faulting) can combine to exacerbate the problem. Prediction techniques continue to be unreliable and unexpected outburst incidents resulting in fatalities are a major concern for underground coal operations. Gas content thresholds of 9 m(3)/t for CH4 and 6 m(3)/t for CO2 are used in the Sydney Basin, to indicate outburst-prone conditions, but are reviewed on an individual mine basis and in mixed as situations. Data on the sorption behaviour of Bowen Basin coals from Australia have provided an explanation for the conflicting results obtained by coal face desorption indices used for outburst-proneness assessment. A key factor appears to be different desorption rates displayed by banded coals, which is supported by both laboratory and mine-site investigations. Dull coal bands with high fusinite and semifusinite contents tend to display rapid desorption from solid coal, for a given pressure drop. The opposite is true for bright coal bands with high vitrinite contents and dull coal bands with high inertodetrinite contents. Consequently, when face samples of dull, fusinite-or semifusinite-rich coal of small particle size are taken for desorption testing, much gas has already escaped and low readings result. The converse applies for samples taken from coal bands with high vitrinite and/or inertodetrinite contents. In terms of outburst potential, it is the bright, vitrinite-rich and the dull, inertodetrinite-rich sections of a coal seam that appear to be more outburst-prone. This is due to the ability of the solid coal to retain gas, even after pressure reduction, creating a gas content gradient across the coal face sufficient to initiate an outburst. Once the particle size of the coal is reduced, rapid gas desorption can then take place. (C) 1998 Elsevier Science.

A sponge/dinoflagellate association in the haplosclerid sponge Haliclona sp.: cellular origin of cytotoxic alkaloids by Percoll density gradient fractionation

Light-microscopic and electron-microscopic studies of the tropical marine sponge Haliclona sp. (Or der: Haplosclerida Family: Haliclonidae) from Heron Island, Great Barrier Reef, have revealed that this sponge is characterized by the presence of dinoflagellates and by nematocysts. The dinoflagellates are 7-10 mu m in size, intracellular, and contain a pyrenoid with a single stalk, whereas the single chloroplast is branched, curved, and lacks grana. Mitochondria are present, and the nucleus is oval and has distinct chromosomal structure. The dinoflagellates are morphologically similar to Symbiodinium microadriaticum, the common intracellular symbiont of corals, although more detailed biochemical and molecular studies are required to provide a precise taxonomic assignment. The major sponge cell types found in Haliclona sp, are spongocytes, choanocytes, and archaeocytes; groups of dinoflagellates are enclosed within large vacuoles in the archaeocytes. The occurrence of dinoflagellates in marine sponges has previously been thought to be restricted to a small group of sponges including the excavating hadromerid sponges; the dinoflagellates in these sponges are usually referred to as symbionts. The role of the dinoflagellates present in Haliclona sp. as a genuine symbiotic partner requires experimental investigation. The sponge grows on coral substrates, from which it may acquire the nematocysts, and shows features, such as mucus production, which are typical of some excavating sponges. The cytotoxic alkaloids, haliclonacyclamines A and B, associated with Haliclona sp. are shown by Percoll density gradient fractionation to be localized within the sponge cells rather than the dinoflagellates. The ability to synthesize bioactive compounds such as the haliclonacyclamines may help Haliclona sp. to preserve its remarkable ecological niche.