An ontological characterization of time-series and state-sequences for data mining

Time-series and sequences are important patterns in data mining. Based on an ontology of time-elements, this paper presents a formal characterization of time-series and state-sequences, where a state denotes a collection of data whose validation is dependent on time. While a time-series is formalized as a vector of time-elements temporally ordered one after another, a state-sequence is denoted as a list of states correspondingly ordered by a time-series. In general, a time-series and a state-sequence can be incomplete in various ways. This leads to the distinction between complete and incomplete time-series, and between complete and incomplete state-sequences, which allows the expression of both absolute and relative temporal knowledge in data mining.

Temporal pattern recognition in video clips detection

Temporal representation and reasoning plays an important role in Data Mining and Knowledge Discovery, particularly, in mining and recognizing patterns with rich temporal information. Based on a formal characterization of time-series and state-sequences, this paper presents the computational technique and algorithm for matching state-based temporal patterns. As a case study of real-life applications, zone-defense pattern recognition in basketball games is specially examined as an illustrating example. Experimental results demonstrate that it provides a formal and comprehensive temporal ontology for research and applications in video events detection.

Deforestation and the spatio-temporal distribution of savannah and forest members of the Simulium damnosum complex in southern Ghana and south-western Togo

Spatio-temporal data on cytotaxonomic identifications of larvae of different members of the Simulium damnosum complex collected from rivers in southern Ghana and south-western Togo from 1975 until 1997 were analysed. When the data were combined, the percentages of savannah blackflies (S. damnosum sensu stricto and S. sirbanum) in the samples were shown to have been progressively increasing since 1975. The increases were statistically significant (P < 0·001), but the rates of increase were not linear. Further analyses were conducted according to the collection seasons and locations of the samples, to account for possible biases such as savannah flies occurring further south in the dry season or a preponderance of later samples from northern rivers having more savannah flies. These analyses showed that the increasing trend was statistically significant (P< 0·0001) only during the periods April to June and October to December. The presence of adult savannah flies carrying infective larvae (L3) indistinguishable from those of Onchocerca volvulus in the study zone was confirmed by examinations of captured flies. The percentages of savannah flies amongst the human-biting populations and the percentages with L3s in the head were higher during dry seasons than wet seasons and the savannah species were found furthest south (5 °25′N) in the dry season. Comparisons of satellite images taken in 1973 and 1990 over a study area in south-western Ghana encompassing stretches of the Tano and Bia rivers demonstrated that there have been substantial increases in urban and savannah areas, at the expense of forest. This was so not only for the whole images but also for subsamples of the images taken at 1, 2, 4, 8 and 16 km distant from sites alongside the River Tano. At every distance from the river, the percentages of pixels classified as urban or savannah have increased in 1990 compared with 1973, while those classified as degraded or dense forest have decreased. The possibility that the proportionate increases in savannah forms of the vectors of onchocerciasis, and hence in the likelihood of the transmission of savannah strains of the disease in formerly forested areas, were related to the decreases in forest cover is discussed.