In this thesis we present two new methods for discovering knowledge from ordered datasets using Baldwin’s mass assignment and the Fril programming language. We derive our methods from human observation and knowledge handling computing techniques. We define this combination of observed human behaviour and conventional computing as humanist computing. The first method represents trends in ordered...

This paper represents the rst e ort to apply direct-manipulation (VIS) techniques to spatial data exploration providing mechanisms for visually querying as well as browsing spatial data and for reviewing the visual results for trend discovery. We present a visual query language (SVIQUEL) which allows us to specify the relative spatial position (both topology and direction) between objects using...

The safety of air traffic control (ATC) operations is an important cornerstone for the sustainable development civil aviation industry. In order to clarify risk factors in operation process and achieve digital representation risks operations, starting from ATC incident reports, we fully mine information unspoken rules operations. A perception model based on Latent Dirichlet Allocation (LDA) top...

Cohort studies can be biased by unmeasured confounding. We propose a hybrid ecologic-epidemiologic design called the trend-in-trend design, which requires a strong time trend in exposure, but is unbiased unless there are unmeasured factors affecting outcome for which there are time trends in prevalence that are correlated with time trends in exposure across strata with different exposure trends...

A four stage social network trend mining framework, the IGCV (Identification, Grouping, Clustering and Visualisation) framework, is described. The framework extracts trends from social network data and then applies a sequence of techniques (“tools”) to this data to facilitate interpretation of the identified trends. Of particular note is the visualisation of trend migrations (changes) that feat...

The Rough Set Theory is a common methodology to discover hidden patterns in data. Most software systems and libraries using methods of that theory originated in the mid 1990s and suffer from timeconsuming operations or high communication costs. Today on the other hand there is a perceptible trend for in-database analytics allowing ondemand decision support. While data processing and predictive ...

A role of immunological factors in glioma etiology is suggested by reports of an inverse relationship with history of allergy or autoimmune disease. To test whether single-nucleotide polymorphisms (SNPs) in cytokine genes were related to risk of adult glioma, we genotyped 11 SNPs in seven cytokine genes within a hospital-based study conducted by the National Cancer Institute and an independent,...

Data Mining is the process of automatically searching large volumes of data for patterns and it is also a fairly recent and contemporary topic in computing. Nowadays, pattern discovery is a field within the area of data mining. In general, large volumes of time series data are contained in financial database and these data have some useful but not easy finding patterns in it and many financial ...

Service-Oriented Development (SOD) is currently gaining momentum and has been marked as the future trend in software development. The building blocks of a service-oriented system are services which may be instantiated by web, grid and p2p services. For SOD to prevail there is a need to support the discovery and composition of services. However, this is not an easy task, due to the heterogeneity...

The documented unfavorable changes of physicochemical properties during lead discovery and optimization prompted us to investigate the present practice of medicinal chemistry optimization from a thermodynamic perspective. Basic principles of binding thermodynamics suggest that discriminating between enthalpy-driven and entropy-driven optimizations could be beneficial. We hypothesize that entrop...