A data collection case study supporting requirements oriented prediction and management in software developments

Consider the statement "this project should cost X and has risk of Y". Such statements are used daily in industry as the basis for making decisions. The work reported here is part of a study aimed at providing a rational and pragmatic basis for such statements. Of particular interest are predictions made in the requirements and early phases of projects. A preliminary model has been constructed using Bayesian Belief Networks and in support of this, a programme to collect and study data during the execution of various software development projects commenced in May 2002. The data collection programme is undertaken under the constraints of a commercial industrial regime of multiple concurrent small to medium scale software development projects. Guided by pragmatism, the work is predicated on the use of data that can be collected readily by project managers; including expert judgements, effort, elapsed times and metrics collected within each project.

Nonlinear error dynamics for cycled data assimilation methods

We investigate the error dynamics for cycled data assimilation systems, such that the inverse problem of state determination is solved at tk, k = 1, 2, 3, ..., with a first guess given by the state propagated via a dynamical system model from time tk − 1 to time tk. In particular, for nonlinear dynamical systems that are Lipschitz continuous with respect to their initial states, we provide deterministic estimates for the development of the error ||ek|| := ||x(a)k − x(t)k|| between the estimated state x(a) and the true state x(t) over time. Clearly, observation error of size δ > 0 leads to an estimation error in every assimilation step. These errors can accumulate, if they are not (a) controlled in the reconstruction and (b) damped by the dynamical system under consideration. A data assimilation method is called stable, if the error in the estimate is bounded in time by some constant C. The key task of this work is to provide estimates for the error ||ek||, depending on the size δ of the observation error, the reconstruction operator Rα, the observation operator H and the Lipschitz constants K(1) and K(2) on the lower and higher modes of controlling the damping behaviour of the dynamics. We show that systems can be stabilized by choosing α sufficiently small, but the bound C will then depend on the data error δ in the form c||Rα||δ with some constant c. Since ||Rα|| → ∞ for α → 0, the constant might be large. Numerical examples for this behaviour in the nonlinear case are provided using a (low-dimensional) Lorenz '63 system.

Comparing hybrid data assimilation methods on the Lorenz 1963 model with increasing nonlinearity

We systematically compare the performance of ETKF-4DVAR, 4DVAR-BEN and 4DENVAR with respect to two traditional methods (4DVAR and ETKF) and an ensemble transform Kalman smoother (ETKS) on the Lorenz 1963 model. We specifically investigated this performance with increasing nonlinearity and using a quasi-static variational assimilation algorithm as a comparison. Using the analysis root mean square error (RMSE) as a metric, these methods have been compared considering (1) assimilation window length and observation interval size and (2) ensemble size to investigate the influence of hybrid background error covariance matrices and nonlinearity on the performance of the methods. For short assimilation windows with close to linear dynamics, it has been shown that all hybrid methods show an improvement in RMSE compared to the traditional methods. For long assimilation window lengths in which nonlinear dynamics are substantial, the variational framework can have diffculties fnding the global minimum of the cost function, so we explore a quasi-static variational assimilation (QSVA) framework. Of the hybrid methods, it is seen that under certain parameters, hybrid methods which do not use a climatological background error covariance do not need QSVA to perform accurately. Generally, results show that the ETKS and hybrid methods that do not use a climatological background error covariance matrix with QSVA outperform all other methods due to the full flow dependency of the background error covariance matrix which also allows for the most nonlinearity.

Supporting schools in identifying and safeguarding the needs of disabled children: the challenges for data collection

Conceptualisations of disability that emphasise the contextual and cultural nature of disability and the embodiment of these within a national system of data collection present a number of challenges especially where this process is devolved to schools. The requirement for measures based on contextual and subjective experiences gives rise to particular difficulties in achieving parity in the way data is analysed and reported. This paper presents an account of the testing of a tool intended for use by schools as they collect data from parents to identify children who meet the criteria of disability established in Disability Discrimination Acts (DDAs). Data were validated through interviews with parents and teachers and observations of children and highlighted the pivotal role of the criterion of impact. The findings are set in the context of schools meeting their legal duties to identify disabled children and their support needs in a way that captures the complexity of disabled children’s school lives and provides useful and useable data.

Disability data collection for children's services

Schools need to identify disabled pupils in accordance with their Disability Equality Duty. This research assisted in the development of suitable tools to allow them to identify disabled children in accordance with the definition set out in the Disability Discrimination Act (DDA) by surveying parents and, via the use of purpose-designed activities, the children themselves.

An online platform for real-time sensor data collection, visualization, and sharing

Sharing sensor data between multiple devices and users can be^challenging for naive users, and requires knowledge of programming and use of different communication channels and/or development tools, leading to non uniform solutions. This thesis proposes a system that allows users to access sensors, share sensor data and manage sensors. With this system we intent to manage devices, share sensor data, compare sensor data, and set policies to act based on rules. This thesis presents the design and implementation of the system, as well as three case studies of its use.

Poultry feed metabolizable energy determination using total or partial excreta collection methods

The aim of this work was to compare the efficiency of total (TC) or partial (PC) collection excreta methods to determine metabolizable energy in poultry feeds. A number of 180 12- to 21-day-old broilers were distributed into two treatments of six replicates of 10 birds each. A reference-diet was formulated to supply broiler requirements, and the test-diets consisted of 60% of reference diets and 40% of corn or soybean meal. Celite was added at 1% to the diets as a marker. Excreta and diet samples were analyzed for dry matter, energy, nitrogen, and acid-insoluble ash (AIA). AME of corn determined by partial collection (PC) was higher (3544 kcal/kg) as compared to total collection (TC) (3133 kcal/kg). However, no difference were observed for soybean meal (1797 vs. 1821 kcal/kg) between both methods. Marker recovery rates in the excreta were 101, 111, and 96% for the basal-diet, and the test-diets with corn or soybean meal, respectively. This result indicates the importance of marker recovery rate in the excreta to evaluate feed AME and digestibility.

Errors due to the tropospheric and ionospheric effects on the geographic location of data collection platforms

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Crytallization and high-resolution X-ray diffraction data collection of an Asp49 PLA(2) from Bothrops jararacussu venom both in the presence and absence of Ca2+ ions

Snake venom PLA(2)s have been extensively studied due to their role in mediating and disrupting physiological processes such as coagulation, platelet aggregation and myotoxicity. The Ca2+ ion bound to the putative calcium-binding loop is essential for hydrolytic activity. We report the crystallization in the presence and absence of Ca2+ and X-ray diffraction data collection at 1.60 Angstrom (with Ca2+) and 1.36 Angstrom (without Ca2+) of an Asp49 PLA(2) from Bothrops jararacussu venom. The crystals belong to orthorhombic space group C222(1). Initial refinement and electron density analysis indicate significant conformational. changes upon Ca2+ binding. (C) 2004 Elsevier B.V. All fights reserved.