Computer modelling and estimation of recruitment patterns of non-branching coral colonies at three sites in Wakatobi Marine Park, S.E. Sulawesi, Indonesia; implications for coral reef conservation

We have studied growth and estimated recruitment of massive coral colonies at three sites, Kaledupa, Hoga and Sampela, separated by about 1.5 km in the Wakatobi Marine National Park, S.E. Sulawesi, Indonesia. There was significantly higher species richness (P<0.05), coral cover (P<0.05) and rugosity (P<0.01) at Kaledupa than at Sampela. A model for coral reef growth has been developed based on a rational polynomial function, where dx/dt is an index of coral growth with time; W is the variable (for example, coral weight, coral length or coral area), up to the power of n in the numerator and m in the denominator; a1……an and b1…bm are constants. The values for n and m represent the degree of the polynomial, and can relate to the morphology of the coral. The model was used to simulate typical coral growth curves, and tested using published data obtained by weighing coral colonies underwater in reefs on the south-west coast of Curaçao [‘Neth. J. Sea Res. 10 (1976) 285’]. The model proved an accurate fit to the data, and parameters were obtained for a number of coral species. Surface area data was obtained on over 1200 massive corals at three different sites in the Wakatobi Marine National Park, S.E. Sulawesi, Indonesia. The year of an individual's recruitment was calculated from knowledge of the growth rate modified by application of the rational polynomial model. The estimated pattern of recruitment was variable, with little numbers of massive corals settling and growing before 1950 at the heavily used site, Sampela, relative to the reef site with little or no human use, Kaledupa, and the intermediate site, Hoga. There was a significantly greater sedimentation rate at Sampela than at either Kaledupa (P<0.0001) or Hoga (P<0.0005). The relative mean abundance of fish families present at the reef crests at the three sites, determined using digital video photography, did not correlate with sedimentation rates, underwater visibility or lack of large non-branching coral colonies. Radial growth rates of three genera of non-branching corals were significantly lower at Sampela than at Kaledupa or at Hoga, and there was a high correlation (r=0.89) between radial growth rates and underwater visibility. Porites spp. was the most abundant coral over all the sites and at all depths followed by Favites (P<0.04) and Favia spp. (P<0.03). Colony ages of Porites corals were significantly lower at the 5 m reef flat on the Sampela reef than at the same depth on both other reefs (P<0.005). At Sampela, only 2.8% of corals on the 5 m reef crest are of a size to have survived from before 1950. The Scleractinian coral community of Sampela is severely impacted by depositing sediments which can lead to the suffocation of corals, whilst also decreasing light penetration resulting in decreased growth and calcification rates. The net loss of material from Sampela, if not checked, could result in the loss of this protective barrier which would be to the detriment of the sublittoral sand flats and hence the Sampela village.

Modelling the cabling of rope systems

This paper presents a theoretical model of the torsional characteristics of parallel multi-part rope systems. In such systems, the ropes may cable, or wrap around each other, depending on the combination of applied torque, rope tension, length and spacing between the rope parts. Cabling constitutes a failure that might be retrievable but as such can seriously affect the performance of the rope system. The torsional characteristics of the system are very different before and after cabling, and theoretical models are given for both situations. Laboratory tests were performed on both two and four rope systems, with measurements being made of torque at rotations from 0 to 360 deg. Tests were run with different rope spacings, tensions and lengths and the results compared with predictions from the theoretical model. The conclusion from the test results was that the theoretical model predicts both the pre- and post-cabling torsional behaviour with an acceptable level of accuracy.

Semiotic modelling for complex enterprise systems

An enterprise is viewed as a complex system which can be engineered to accomplish organisational objectives. Systems analysis and modelling will enable to the planning and development of the enterprise and IT systems. Many IT systems design methods focus on functional and non-functional requirements of the IT systems. Most methods are normally capable of one but leave out other aspects. Analysing and modelling of both business and IT systems may often have to call on techniques from various suites of methods which may be placed on different philosophic and methodological underpinnings. Coherence and consistency between the analyses are hard to ensure. This paper introduces the Problem Articulation Method (PAM) which facilitates the design of an enterprise system infrastructure on which an IT system is built. Outcomes of this analysis represent requirements which can be further used for planning and designing a technical system. As a case study, a finance system, Agresso, for e-procurement has been used in this paper to illustrate the applicability of PAM in modelling complex systems.

Modelling complex systems for project planning - A semiotics motivated method

A large and complex IT project may involve multiple organizations and be constrained within a temporal period. An organization is a system comprising of people, activities, processes, information, resources and goals. Understanding and modelling such a project and its interrelationship with relevant organizations are essential for organizational project planning. This paper introduces the problem articulation method (PAM) as a semiotic method for organizational infrastructure modelling. PAM offers a suite of techniques, which enables the articulation of the business, technical and organizational requirements, delivering an infrastructural framework to support the organization. It works by eliciting and formalizing (e. g. processes, activities, relationships, responsibilities, communications, resources, agents, dependencies and constraints) and mapping these abstractions to represent the manifestation of the "actual" organization. Many analysts forgo organizational modelling methods and use localized ad hoc and point solutions, but this is not amenable for organizational infrastructures modelling. A case study of the infrared atmospheric sounding interferometer (IASI) will be used to demonstrate the applicability of PAM, and to examine its relevancy and significance in dealing with the innovation and changes in the organizations.

A hyperstable neural network for the modelling and control of nonlinear systems

A multivariable hyperstable robust adaptive decoupling control algorithm based on a neural network is presented for the control of nonlinear multivariable coupled systems with unknown parameters and structure. The Popov theorem is used in the design of the controller. The modelling errors, coupling action and other uncertainties of the system are identified on-line by a neural network. The identified results are taken as compensation signals such that the robust adaptive control of nonlinear systems is realised. Simulation results are given.

Using modelling tools to optimise the calculation and subsequent reduction of cable distortion parameters with application to oil well logging systems

This paper discusses how the use of computer-based modelling tools has aided the design of a telemetry unit for use with oil well logging. With the aid of modern computer-based simulation techniques, the new design is capable of operating at data rates of 2.5 times faster than previous designs.

The role of closed ecological systems in carbon cycle modelling

Acquiring a mechanistic understanding of the role of the biotic feedbacks on the links between atmospheric CO2 concentrations and temperature is essential for trustworthy climate predictions. Currently, computer based simulations are the only available tool to estimate the global impact of the biotic feedbacks on future atmospheric CO2 and temperatures. Here we propose an alternative and complementary approaches by using materially closed and energetically open analogue/physical models of the carbon cycle. We argue that there is potential in using a materially closed approach to improve our understanding of the magnitude and sign of many biotic feedbacks, and that recent technological advance make this feasible. We also suggest how such systems could be designed and discuss the advantages and limitations of establishing physical models of the global carbon cycle.

Modelling phosphorus dynamics in multi-branch river systems: A study of the Black River, Lake Simcoe, Ontario, Canada

High rates of nutrient loading from agricultural and urban development have resulted in surface water eutrophication and groundwater contamination in regions of Ontario. In Lake Simcoe (Ontario, Canada), anthropogenic nutrient contributions have contributed to increased algal growth, low hypolimnetic oxygen concentrations, and impaired fish reproduction. An ambitious programme has been initiated to reduce phosphorus loads to the lake, aiming to achieve at least a 40% reduction in phosphorus loads by 2045. Achievement of this target necessitates effective remediation strategies, which will rely upon an improved understanding of controls on nutrient export from tributaries of Lake Simcoe as well as improved understanding of the importance of phosphorus cycling within the lake. In this paper, we describe a new model structure for the integrated dynamic and process-based model INCA-P, which allows fully-distributed applications, suited to branched river networks. We demonstrate application of this model to the Black River, a tributary of Lake Simcoe, and use INCA-P to simulate the fluxes of P entering the lake system, apportion phosphorus among different sources in the catchment, and explore future scenarios of land-use change and nutrient management to identify high priority sites for implementation of watershed best management practises.

Modelling and inverting complex-valued Wiener systems

We develop a complex-valued (CV) B-spline neural network approach for efficient identification and inversion of CV Wiener systems. The CV nonlinear static function in the Wiener system is represented using the tensor product of two univariate B-spline neural networks. With the aid of a least squares parameter initialisation, the Gauss-Newton algorithm effectively estimates the model parameters that include the CV linear dynamic model coefficients and B-spline neural network weights. The identification algorithm naturally incorporates the efficient De Boor algorithm with both the B-spline curve and first order derivative recursions. An accurate inverse of the CV Wiener system is then obtained, in which the inverse of the CV nonlinear static function of the Wiener system is calculated efficiently using the Gaussian-Newton algorithm based on the estimated B-spline neural network model, with the aid of the De Boor recursions. The effectiveness of our approach for identification and inversion of CV Wiener systems is demonstrated using the application of digital predistorter design for high power amplifiers with memory

Complex-valued b-spline neural networks for modelling and inverse of wiener systems

Communication signal processing applications often involve complex-valued (CV) functional representations for signals and systems. CV artificial neural networks have been studied theoretically and applied widely in nonlinear signal and data processing [1–11]. Note that most artificial neural networks cannot be automatically extended from the real-valued (RV) domain to the CV domain because the resulting model would in general violate Cauchy-Riemann conditions, and this means that the training algorithms become unusable. A number of analytic functions were introduced for the fully CV multilayer perceptrons (MLP) [4]. A fully CV radial basis function (RBF) nework was introduced in [8] for regression and classification applications. Alternatively, the problem can be avoided by using two RV artificial neural networks, one processing the real part and the other processing the imaginary part of the CV signal/system. A even more challenging problem is the inverse of a CV