Deriving explanations from partial temporal information

The representation and manipulation of natural human understanding of temporal phenomena is a fundamental field of study in Computer Science, which aims both to emulate human thinking, and to use the methods of human intelligence to underpin engineering solutions. In particular, in the domain of Artificial Intelligence, temporal knowledge may be uncertain and incomplete due to the unavailability of complete and absolute temporal information. This paper introduces an inferential framework for deriving logical explanations from partial temporal information. Based on a graphical representation which allows expression of both absolute and relative temporal knowledge in incomplete forms, the system can deliver a verdict to the question if a given set of statements is temporally consistent or not, and provide understandable logical explanation of analysis by simplified contradiction and rule based reasoning.

The completeness and soundness of temporal theories

Generally speaking, the term temporal logic refers to any system of rules and symbolism for representing and reasoning about propositions qualified in terms of time. In computer science, particularly in the domain of Artificial Intelligence, there are mainly two known approaches to the representation of temporal information: modal logic approaches including tense logic and hybrid temporal logic, and predicate logic approaches including temporal arguement method and reified temporal logic. On one hand, while tense logic, hybrid temporal logic and temporal argument method enjoy formal theoretical foundations, their expressiveness has been criticised as not power enough for representing general temporal knowledge; on the other hand, although reified temporal logic provides greater expressive power, most of the current systems following the temporal reification lack of complete and sound axiomatic theories. With there observations in mind, a new reified temporal logic with clear syntax and semantics in terms of a sound and complete axiomatic formalism is introduced in this paper, which retains all the expressive power of temporal reification.

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.

Summarising spatial and temporal information in CPR data

The Continuous Plankton Recorder survey provides pan-oceanic data on geographic distribution, species composition, seasonal cycles of abundance, and long-term change during the last 70 years. In this paper we compare and contrast some of the historic data-analytic protocols of the survey, focusing primarily on the various means by which spatio-temporal information in CPR data has been exposed. Relative strengths and limitations are assessed, followed by suggestions for future approaches to the visualisation and summarising of CPR data.

Using historical data to detect temporal changes in the abundances of intertidal species on Irish shores

An historical data set, collected in 1958 by Southward and Crisp, was used as a baseline for detecting change in the abundances of species in the rocky intertidal of Ireland. In 2003, the abundances of each of 27 species was assessed using the same methodologies (ACFOR [which stands for the categories: abundant, common, frequent, occasional and rare] abundance scales) at 63 shores examined in the historical study. Comparison of the ACFOR data over a 45-year period, between the historical survey and re-survey, showed statistically significant changes in the abundances of 12 of the 27 species examined. Two species (one classed as northern and one introduced) increased significantly in abundance while ten species (five classed as northern, one classed as southern and four broadly distributed) decreased in abundance. The possible reasons for the changes in species abundances were assessed not only in the context of anthropogenic effects, such as climate change and commercial exploitation, but also of operator error. The error or differences recorded among operators (i.e. research scientists) when assessing species abundance using ACFOR categories was quantified on four shores. Significant change detected in three of the 12 species fell within the margin of operator error. This effect of operator may have also contributed to the results of no change in the other 15 species between the two census periods. It was not possible to determine the effect of operator on our results, which can increase the occurrence of a false positive (Type 1) or of a false negative (Type 2) outcome

Temporal Variations In Annual Production And Biomass In Estuarine Populations Of 2 Polychaetes Nephtys-Hombergi And Ampharete-Acutifrons

Production rates and production/biomass ratios have been estimated for a large number of macrobenthic species (Hargrave, 1977; Robertson, 1979). The usefulness of such estimates is limited by a lack of information on their temporal and spatial stability; we are aware of only one study (Sarvala, 1980) in which production has been estimated for more than one year. The present study investigates the stability of the production (P), biomass (B) and P/B values of two polychaete species, Nephtys hombergi Savigny and Ampharete acutifrons (Grube), over a 5-year period.