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Don Kulasiri

Bio: Don Kulasiri is an academic researcher from Canterbury of New Zealand. The author has contributed to research in topics: Stochastic differential equation & Medicine. The author has an hindex of 18, co-authored 126 publications receiving 1050 citations. Previous affiliations of Don Kulasiri include American College of Surgeons & Lincoln University (New Zealand).


Papers
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Journal ArticleDOI
TL;DR: In this article, the usefulness of raw meat surface characteristics (geometric and texture) in predicting cooked meat tenderness was investigated, and four feature sets comprising six geometric, four difference histogram, eight co-occurrence and four run length features were generated based on the results of dimensionality reduction.

69 citations

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TL;DR: Insect-sensing systems are not widely studied or accepted as proven biological sensors and further studies are needed to examine additional insect species and to develop better methods of using their olfactory system for detecting odorants of interest.

60 citations

Journal ArticleDOI
TL;DR: The ability of artificial neural network (ANN) models to predict the lamb carcass grades using features extracted from lamb chop images was compared with multivariate statistical model (discriminant function analysis (DFA) with respect to the classification accuracy.

53 citations

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TL;DR: It is concluded that, while time consuming, development of system-specific objective indices may often be the most useful way to compare simulation output and field data when complex biological entities are modelled.

47 citations

Journal ArticleDOI
TL;DR: This study presents a model to represent the transcriptional regulatory network essential for the circadian rhythmicity in Drosophila, and simulates sustained circadian oscillations in mRNA and protein concentrations in constant darkness in agreement with experimental observations.

39 citations


Cited by
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Journal ArticleDOI
TL;DR: Van Kampen as mentioned in this paper provides an extensive graduate-level introduction which is clear, cautious, interesting and readable, and could be expected to become an essential part of the library of every physical scientist concerned with problems involving fluctuations and stochastic processes.
Abstract: N G van Kampen 1981 Amsterdam: North-Holland xiv + 419 pp price Dfl 180 This is a book which, at a lower price, could be expected to become an essential part of the library of every physical scientist concerned with problems involving fluctuations and stochastic processes, as well as those who just enjoy a beautifully written book. It provides an extensive graduate-level introduction which is clear, cautious, interesting and readable.

3,647 citations

Book ChapterDOI
01 Jan 1998
TL;DR: In this paper, the authors explore questions of existence and uniqueness for solutions to stochastic differential equations and offer a study of their properties, using diffusion processes as a model of a Markov process with continuous sample paths.
Abstract: We explore in this chapter questions of existence and uniqueness for solutions to stochastic differential equations and offer a study of their properties. This endeavor is really a study of diffusion processes. Loosely speaking, the term diffusion is attributed to a Markov process which has continuous sample paths and can be characterized in terms of its infinitesimal generator.

2,446 citations

Book ChapterDOI
01 Jan 1997
TL;DR: This chapter introduces the finite element method (FEM) as a tool for solution of classical electromagnetic problems and discusses the main points in the application to electromagnetic design, including formulation and implementation.
Abstract: This chapter introduces the finite element method (FEM) as a tool for solution of classical electromagnetic problems. Although we discuss the main points in the application of the finite element method to electromagnetic design, including formulation and implementation, those who seek deeper understanding of the finite element method should consult some of the works listed in the bibliography section.

1,820 citations

Journal ArticleDOI
TL;DR: A conceptual model of how interdependent environmental factors shape regional-scale variation in local diversity in the deep sea is presented, showing how environmental gradients may form geographic patterns of diversity by influencing local processes such as predation, resource partitioning, competitive exclusion, and facilitation that determine species coexistence.
Abstract: Most of our knowledge of biodiversity and its causes in the deep-sea benthos derives from regional-scale sampling studies of the macrofauna. Improved sampling methods and the expansion of investigations into a wide variety of habitats have revolutionized our understanding of the deep sea. Local species diversity shows clear geographic variation on spatial scales of 100-1000 km. Recent sampling programs have revealed unexpected complexity in community structure at the landscape level that is associated with large-scale oceanographic processes and their environmental consequences. We review the relationships between variation in local species diversity and the regional-scale phenomena of boundary constraints, gradients of productivity, sediment heterogeneity, oxygen availability, hydrodynamic regimes, and catastrophic physical disturbance. We present a conceptual model of how these interdependent environmental factors shape regional-scale variation in local diversity. Local communities in the deep sea may be composed of species that exist as metapopulations whose regional distribution depends on a balance among global-scale, landscape-scale, and small-scale dynamics. Environmental gradients may form geographic patterns of diversity by influencing local processes such as predation, resource partitioning, competitive exclusion, and facilitation that determine species coexistence. The measurement of deep-sea species diversity remains a vital issue in comparing geographic patterns and evaluating their potential causes. Recent assessments of diversity using species accumulation curves with randomly pooled samples confirm the often-disputed claim that the deep sea supports higher diversity than the continental shelf. However, more intensive quantitative sampling is required to fully characterize the diversity of deep-sea sediments, the most extensive habitat on Earth. Once considered to be constant, spatially uniform, and isolated, deep-sea sediments are now recognized as a dynamic, richly textured environment that is inextricably linked to the global biosphere. Regional studies of the last two decades provide the empirical background necessary to formulate and test specific hypotheses of causality by controlled sampling designs and experimental approaches.

680 citations