Prediction of sediment,particulate nutrient and dissolved nutrient concentrations in a dry tropical river to provide input to a mechanistic coastal water quality model

A Generalised Additive Modelling (GAM) approach is applied to prediction of both particulate and dissolved nutrient concentrations in a wet-tropical river (the Fitzroy River, Queensland, Australia). In addition to covariant terms considered in previous work (i.e. flow, discounted flow and a rising-falling limb term), we considered several new potential covariates: meteorological and hydrological variables that are routinely monitored, available in near-real time, and were considered to have potential predictive power. Of the additional terms considered, only flows from three tributaries of the Fitzroy River (namely, the Nogoa, Comet and Isaac Rivers) were found to significantly improve the model. Inclusion of one or more of these additional flow terms greatly improved results for dissolved nitrogen and dissolved phosphorus concentrations, which were not otherwise amenable to prediction. In particular, the Nogoa sub-catchment, dominated by pasture for cattle, was found to be important in determining dissolved inorganic nitrogen and phosphorus concentrations reaching the river mouth. This insight may direct further research, including future refinement of processed-based catchment models. The GAMs described here are used to provide near real-time river boundary conditions for a complex coupled hydrodynamic and biogeochemical model of the Great Barrier Reef Lagoon, and can be coupled with a forecasting hydrological model to allow integrated forecasting simulations of the catchment to coast system.     

Quasi-static and dynamic crushing behaviors of aluminum and steel tubes with a cutout

Tubular members are commonly used as an energy absorber in engineering structures and many such members have a cutout. In this study, the crushing behaviors of tubes with a cutout are characterized and the effects of cutout on the energy absorption capabilities of these tubes are quantified. Systematic parametric studies were carried out to study the effect of material properties, including yield and ultimate strength of material, strain rate effect, location of cutout, tube length and impact speed on the crushing behaviors and energy absorption capacity of aluminum and steel tubes. First, a numerical model was constructed with a commercial explicit finite element code. It will be first proven that the numerical simulation can produce sufficiently accurate results in an economic manner. Subsequently, the crushing behavior of aluminum and steel tubes with a cutout was experimentally characterized and their energy absorption capacity was evaluated in terms of mean crushing force, peak crushing force and specific energy absorption (SEA). Tubes of various lengths with a cutout located at different locations, subject to both quasi-static and dynamic impact loadings were considered. For steel tubes, the numerical simulation investigated the influence of the strain rate effect and variation in strain hardening ratio of the material. Empirical equations describing the mean and peak crushing forces of aluminum and steel tubes with a cutout were developed using linear and nonlinear regression methods applied to the results obtained from the numerical and experimental studies.     

Pupils' recall of an interactive storybook on CD-ROM

Abstract This small-scale study compares two groups of Year 4 (8/9 year-old) pupils either reading or playing an interactive storybook . The study considered pupils' recall of propositions, which formed the story setting and episodes, and of micro-propositions and characters' names, and pupils' responses to inferential items derived from the 'interactive storybook'. The study indicates that, whether reading or playing, pupils' recall of the story setting was sound, but pupils who had read the interactive storybook demonstrated greater recall of the story event structure than those who had engaged in interactive picture-play. Pupils who had played the interactive storybook demonstrated significantly greater recall of micro-propositions and names.     

Quality of manual data collection in Java software: an empirical investigation

Data collection, both automatic and manual, lies at the heart of all empirical studies. The quality of data collected from software informs decisions on maintenance, testing and wider issues such as the need for system re-engineering. While of the two types stated, automatic data collection is preferable, there are numerous occasions when manual data collection is unavoidable. Yet, very little evidence exists to assess the error-proneness of the latter. Herein, we investigate the extent to which manual data collection for Java software compared with its automatic counterpart for the same data. We investigate three hypotheses relating to the difference between automated and manual data collection. Five Java systems were used to support our investigation. Results showed that, as expected, manual data collection was error-prone, but nowhere near the extent we had initially envisaged. Key indicators of mistakes in manual data collection were found to be poor developer coding style, poor adherence to sound OO coding principles, and the existence of relatively large classes in some systems. Some interesting results were found relating to the collection of public class features and the types of error made during manual data collection. The study thus offers an insight into some of the typical problems associated with collecting data manually; more significantly, it highlights the problems that poorly written systems have on the quality of visually extracted data.     

Bivariate Scientific Function Finding in a Sampled,Real-Data Testbed

This article reports the results of a study of domain-independent function finding based on a collection of several hundred real scientific data sets. Prior studies have introduced the controversial idea of discovering functional relationships of interest to scientists directly from the data they collect. The evidence presented here supports the view that this is sometimes possible, but it also suggests how often purely data-driven discovery is not possible and how much more difficult it may be than has often been assumed. Experience with sampled examples of real scientific data suggests as well that emphasis on search in prior studies may have been misplaced. For the function-finding problems studied here, scientists typically propose only a handful of different functional relationships. The difficulty is not in searching through a large space of relationships but in evaluating a few common ones to determine if they are likely to be of scientific interest.     

Systematic analyses and comparison of development performance and product quality of Incremental Process and Agile Process

ContextAlthough Agile software development models have been widely used as a base for the software project life-cycle since 1990s, the number of studies that follow a sound empirical method and quantitatively reveal the effect of using these models over Traditional models is scarce.ObjectiveThis article explains the empirical method of and the results from systematic analyses and comparison of development performance and product quality of Incremental Process and Agile Process adapted in two projects of a middle-size, telecommunication software development company. The Incremental Process is an adaption of the Waterfall Model whereas the newly introduced Agile Process is a combination of the Unified Software Development Process, Extreme Programming, and Scrum.MethodThe method followed to perform the analyses and comparison is benefited from the combined use of qualitative and quantitative methods. It utilizes; GQM Approach to set measurement objectives, CMMI as the reference model to map the activities of the software development processes, and a pre-defined assessment approach to verify consistency of process executions and evaluate measure characteristics prior to quantitative analysis.ResultsThe results of the comparison showed that the Agile Process had performed better than the Incremental Process in terms of productivity (79%), defect density (57%), defect resolution effort ratio (26%), Test Execution V&V Effectiveness (21%), and effort prediction capability (4%). These results indicate that development performance and product quality achieved by following the Agile Process was superior to those achieved by following the Incremental Process in the projects compared.ConclusionThe acts of measurement, analysis, and comparison enabled comprehensive review of the two development processes, and resulted in understanding their strengths and weaknesses. The comparison results constituted objective evidence for organization-wide deployment of the Agile Process in the company.     

Epileptic seizure classification in EEG signals using second-order difference plot of intrinsic mode functions

Epilepsy is a neurological disorder which is characterized by transient and unexpected electrical disturbance of the brain. The electroencephalogram (EEG) is a commonly used signal for detection of epileptic seizures. This paper presents a new method for classification of ictal and seizure-free EEG signals. The proposed method is based on the empirical mode decomposition (EMD) and the second-order difference plot (SODP). The EMD method decomposes an EEG signal into a set of symmetric and band-limited signals termed as intrinsic mode functions (IMFs). The SODP of IMFs provides elliptical structure. The 95% confidence ellipse area measured from the SODP of IMFs has been used as a feature in order to discriminate seizure-free EEG signals from the epileptic seizure EEG signals. The feature space obtained from the ellipse area parameters of two IMFs has been used for classification of ictal and seizure-free EEG signals using the artificial neural network (ANN) classifier. It has been shown that the feature space formed using ellipse area parameters of first and second IMFs has given good classification performance. Experimental results on EEG database available by the University of Bonn, Germany, are included to illustrate the effectiveness of the proposed method.