Bioinformatic workflows : G-PIPE as an implementation

We present G-PIPE, a graphic pipeline generator for PISE that allows the definition of pipelines, parameterization of its component methods, and storage of metadata in XML formats. Our implementation goes beyond macro capacities currently in PISE. As the entire analysis protocol is defined in XML, a complete bioinformatic experiment (linked sets of methods, parameters and results) can be reproduced or shared among users. We also discuss the role of ontologies as as guidance systems in order to provide users with the possibility to define abstract work-flows, and execute them. A relevant baseline ontology is presented. Availability: http://if-web.imb.uq.edu.au

Quantification of allochthonous nutrient input into freshwater bodies by herbivorous waterbirds

1. Waterbirds are considered to import large quantities of nutrients to freshwater bodies but quantification of these loadings remains problematic. We developed two general models to calculate such allochthonous nutrient inputs considering food intake, foraging behaviour and digestive performance of waterbirds feeding in terrestrial habitats: an intake model (IM), mainly based on an allometric relationship for energy requirements and a dropping model (DM), based on allometric relationships for defaecation.

2. Reviewed data of nitrogen (N) and phosphorus (P) content of herbivorous food varied according to diet type (foliage, seeds and roots), season and fertilization. For model parameterization average foliage diet contained 38.20 mg N g⁻¹ and 3.21 mg P g⁻¹ (dry weight), whereas mean faeces composition was 45.02 mg N g⁻¹ and 6.18 mg P g⁻¹.

3. Daily allochthonous nutrient input increased with body mass ranging from 0.29 g N and 0.03 g P in teals Anas crecca to 5.69 g N and 0.57 g P in mute swans Cygnus olor. Results from IM differed from those of DM from ducks to swans by 63–108% for N and by −4 to 23% for P. Model uncertainty was lowest for the IM and mainly caused by variation in estimates of food retention time (RT). In DM food RT and dropping mass determined model uncertainty in similar extent.

4. Exemplarily applying the models to Dutch wetlands resulted in mean annual contribution of herbivorous waterbirds to allochthonous nutrient loading of 382.8 ± 167.1 tonnes N a⁻¹and 34.7 ± 2.3 tonnes P a⁻¹, respectively, which corresponds to annual surface-water loadings of 1.07 kg N ha⁻¹ and 0.10 kg P ha⁻¹.

5. There was a distinct seasonal pattern with peak loadings in January, when bird abundances were highest. Lowest inputs were in August, when bird abundance and nutrient content in food was low and birds foraged less in terrestrial habitats. Three-quarters of all nutrient input was contributed by greater white-fronted goose Anser albifrons, greylag goose Anser anser, wigeon Anas penelope and barnacle goose Branta leucopsis alone.

6. We provide general, easy to use calculation methods for the estimation of allochthonous nutrient inputs by waterbirds, which are applicable to a range of waterbird species, a variety of potential diets and feeding behaviours, and across spatial scales. Such tools may greatly assist in the planning and execution of management actions for wetland nutrient budgets.

Modelling behavioural and fitness consequences of disturbance for geese along their spring flyway

1. For migratory birds the implications of environmental change may be difficult to predict because they use multiple sites during their annual cycle. Moreover, the migrants’ use of these sites may be interdependent. Along the flyway of the Svalbard pink-footed goose Anser brachyrhynchus population, Norwegian farmers use organized scaring to minimize goose use of their grasslands in spring. We assessed the consequences of this practice for regional site use of pink-footed geese along their spring migration route.

2. We used dynamic programming to find the sequence of migratory decisions that maximizes the fitness of female geese during spring migration, assuming scaring impinges on both food-intake rates and predation risk. The parameterization of the model was based on data gathered from individually marked pink-footed geese between 1991 and 2003.

3. The effect of scaring in terms of fitness and site use was most noticeable regarding food-intake rate. Scaring resulted in a redistribution of geese along the flyway. Furthermore, the outcomes of the modelling exercises were highly dependent on whether or not the geese were omniscient or naive: at moderate scaring levels naive geese were predicted to succumb.

4. On a qualitative basis there was good correspondence between the predictions from the model and the empirical evidence gathered to date.

5. Synthesis and applications. Besides highlighting the importance of learning and changing behaviour in an adaptive fashion, our modelling exercise indicated the potential vulnerability of the geese to abrupt environmental change. In addition, the exercise emphasized the interdependence of site use along the migratory flyway. The model supports the necessity for an integrated flyway management approach. In Norway, discussion is ongoing about the future management of the spring conflict between farming interests and geese. Farmers in north and mid-Norway have announced that they will expand the scaring campaign if a long-term solution, including a compensation scheme, is not forthcoming. If scaring on such a large scale is implemented abruptly, it may have severe consequences for the population: management of both the scaring intensity and its geographical extent is urgently required.

Efficient Coxian duration modelling for activity recognition in smart environment with the hidden semi-Markov model

In this paper, we exploit the discrete Coxian distribution and propose a novel form of stochastic model, termed as the Coxian hidden semi-Makov model (Cox-HSMM), and apply it to the task of recognising activities of daily living (ADLs) in a smart house environment. The use of the Coxian has several advantages over traditional parameterization (e.g. multinomial or continuous distributions) including the low number of free parameters needed, its computational efficiency, and the existing of closed-form solution. To further enrich the model in real-world applications, we also address the problem of handling missing observation for the proposed Cox-HSMM. In the domain of ADLs, we emphasize the importance of the duration information and model it via the Cox-HSMM. Our experimental results have shown the superiority of the Cox-HSMM in all cases when compared with the standard HMM. Our results have further shown that outstanding recognition accuracy can be achieved with relatively low number of phases required in the Coxian, thus making the Cox-HSMM particularly suitable in recognizing ADLs whose movement trajectories are typically very long in nature.

Robust nonlinear adaptive backstepping excitation controller design for rejecting external disturbances in multimachine power systems

This paper proposes a new approach to design a robust adaptive backstepping excitation controller for multimachine power systems in order to reject external disturbances. The parameters which significantly affect the stability of power systems (also called stability sensitive parameters) are considered as unknown and the external disturbances are incorporated into the power system model. The proposed excitation controller is designed in such a way that it is adaptive to the unknown parameters and robust to external disturbances. The stability sensitive parameters are estimated through the adaptation laws and the convergences of these adaptation laws are obtained through the negative semi-definiteness of control Lyapunov functions (CLFs). The proposed controller not only provides robustness property against external disturbances but also overcomes the over-parameterization problem of stability sensitive parameters which usually appears in some conventional adaptive methods. Finally, the performance of the proposed controller is tested on a two-area four machine 11-bus power system by considering external disturbances under different scenarios and is compared to that of an existing nonlinear adaptive backstepping controller. Simulation results illustrate the robustness of the proposed controller over an existing one in terms of rejecting external disturbances.

Rule-based extraction of goal-use case models from text

Goal and use case modeling has been recognized as a key approach for understanding and analyzing requirements. However, in practice, goals and use cases are often buried among other content in requirements specifications documents and written in unstructured styles. It is thus a time-consuming and error-prone process to identify such goals and use cases. In addition, having them embedded in natural language documents greatly limits the possibility of formally analyzing the requirements for problems. To address these issues, we have developed a novel rule-based approach to automatically extract goal and use case models from natural language requirements documents. Our approach is able to automatically categorize goals and ensure they are properly specified. We also provide automated semantic parameterization of artifact textual specifications to promote further analysis on the extracted goal-use case models. Our approach achieves 85% precision and 82% recall rates on average for model extraction and 88% accuracy for the automated parameterization.

Robust adaptive backstepping controller design for DC-DC buck converters with external disturbances

In modern power electronic systems, DC-DC converter is one of the main controlled power sources for driving DC systems. But the inherent nonlinear and time-varying characteristics often result in some difficulties mostly related to the control issue. This paper presents a robust nonlinear adaptive controller design with a recursive methodology based on the pulse width modulation (PWM) to drive a DC-DC buck converter. The proposed controller is designed based on the dynamical model of the buck converter where all parameters within the model are assumed as unknown. These unknown parameters are estimated through the adaptation laws and the stability of these laws are ensured by formulating suitable control Lyapunov functions (CLFs) at different stages. The proposed control scheme also provides robustness against external disturbances as these disturbances are considered within the model. One of the main features of the proposed scheme is that it overcomes the over-parameterization problems of unknown parameters which usually appear in some conventional adaptive methods. Finally, the effectiveness of the proposed control scheme is verified through the simulation results and compared to that of an existing adaptive backstepping controller. Simulation results clearly indicate the performance improvement in terms of a faster output voltage tracking response.