One-step Estimation of Networked Population Size: Respondent-Driven Capture-Recapture with Anonymity

Population size estimates for hidden and hard-to-reach populations are particularly important when members are known to suffer from disproportion health issues or to pose health risks to the larger ambient population in which they are embedded. Efforts to derive size estimates are often frustrated by a range of factors that preclude conventional survey strategies, including social stigma associated with group membership or members' involvement in illegal activities. This paper extends prior research on the problem of network population size estimation, building on established survey/sampling methodologies commonly used with hard-to-reach groups. Three novel one-step, network-based population size estimators are presented, to be used in the context of uniform random sampling, respondent-driven sampling, and when networks exhibit significant clustering effects. Provably sufficient conditions for the consistency of these estimators (in large configuration networks) are given. Simulation experiments across a wide range of synthetic network topologies validate the performance of the estimators, which are seen to perform well on a real-world location-based social networking data set with significant clustering. Finally, the proposed schemes are extended to allow them to be used in settings where participant anonymity is required. Systematic experiments show favorable tradeoffs between anonymity guarantees and estimator performance. Taken together, we demonstrate that reasonable population estimates can be derived from anonymous respondent driven samples of 250-750 individuals, within ambient populations of 5,000-40,000. The method thus represents a novel and cost-effective means for health planners and those agencies concerned with health and disease surveillance to estimate the size of hidden populations. Limitations and future work are discussed in the concluding section

A FRAMEWORK FOR SOFTWARE RELIABILITY MANAGEMENT BASED ON THE SOFTWARE DEVELOPMENT PROFILE MODEL

Recent empirical studies of software have shown a strong correlation between change history of files and their fault-proneness. Statistical data analysis techniques, such as regression analysis, have been applied to validate this finding. While these regression-based models show a correlation between selected software attributes and defect-proneness, in most cases, they are inadequate in terms of demonstrating causality. For this reason, we introduce the Software Development Profile Model (SDPM) as a causal model for identifying defect-prone software artifacts based on their change history and software development activities. The SDPM is based on the assumption that human error during software development is the sole cause for defects leading to software failures. The SDPM assumes that when a software construct is touched, it has a chance to become defective. Software development activities such as inspection, testing, and rework further affect the remaining number of software defects. Under this assumption, the SDPM estimates the defect content of software artifacts based on software change history and software development activities. SDPM is an improvement over existing defect estimation models because it not only uses evidence from current project to estimate defect content, it also allows software managers to manage software projects quantitatively by making risk informed decisions early in software development life cycle. We apply the SDPM in several real life software development projects, showing how it is used and analyzing its accuracy in predicting defect-prone files and compare the results with the Poisson regression model

One-step estimation of networked population size: Respondent-driven capture-recapture with anonymity

Size estimation is particularly important for populations whose members experience disproportionate health issues or pose elevated health risks to the ambient social structures in which they are embedded. Efforts to derive size estimates are often frustrated when the population is hidden or hard-to-reach in ways that preclude conventional survey strategies, as is the case when social stigma is associated with group membership or when group members are involved in illegal activities. This paper extends prior research on the problem of network population size estimation, building on established survey/sampling methodologies commonly used with hard-to-reach groups. Three novel one-step, network-based population size estimators are presented, for use in the context of uniform random sampling, respondent-driven sampling, and when networks exhibit significant clustering effects. We give provably sufficient conditions for the consistency of these estimators in large configuration networks. Simulation experiments across a wide range of synthetic network topologies validate the performance of the estimators, which also perform well on a real-world location based social networking data set with significant clustering. Finally, the proposed schemes are extended to allow them to be used in settings where participant anonymity is required. Systematic experiments show favorable trade-offs between anonymity guarantees and estimator performance. Taken together, we demonstrate that reasonable population size estimates are derived from anonymous respondent driven samples of 250-750 individuals, within ambient populations of 5,000-40,000. The method thus represents a novel and cost-effective means for health planners and those agencies concerned with health and disease surveillance to estimate the size of hidden populations. We discuss limitations and future work in the concluding section

Proceedings of the Twenty-Third Annual Software Engineering Workshop

The Twenty-third Annual Software Engineering Workshop (SEW) provided 20 presentations designed to further the goals of the Software Engineering Laboratory (SEL) of the NASA-GSFC. The presentations were selected on their creativity. The sessions which were held on 2-3 of December 1998, centered on the SEL, Experimentation, Inspections, Fault Prediction, Verification and Validation, and Embedded Systems and Safety-Critical Systems

Diet, activity and spatial occupancy of leopards in the Soutpansberg Mountains.

Leopards, though broadly distributed, are highly variable in terms of their ecology. Recently, the Soutpansberg Mountains were identified as supporting one of the highest leopard populations in a non-protected area in Africa. This study aims to understand how these mountains can support such a high density of leopards, thus aiding in identifying the conservation potential of this environment and the species in it. Using a combination of camera trap and scat data collected over two years, research into leopard occupancy, diet and activity was conducted. This research represents the first of its kind to use this combination to investigate these factors in the Soutpansberg. The occupancy analysis proved inconclusive in determining which variables influence the occupancy of leopards. It was found that camera trap data can be split into almost any number of sessions (groupings of trap days), which is a valuable finding as no previous study has provided evidence to support their choice of session number. Leopards consumed 22 species of various sizes, with Artiodactyla species like bushbuck and bushpig contributing most to their diet. No livestock were found in the scats, indicating that leopards are preying on livestock at lower levels than landowners perceive. Some species, such as red duiker and common warthog, were consumed less than expected by leopards based on their availability. Activity patterns indicate that leopards are active throughout the day and night, but their diet suggests they may hunt nocturnally as their most commonly consumed prey are active during this time. Evidence of temporal partitioning between leopards and their prey provides viable explanations for prey selection. This study provides knowledge of elements, such as availability of prey and temporal overlap with prey, which make this environment suitable for a high density of leopards. The knowledge gained through this study of the ecology and behaviour of the Soutpansberg’s top predator in relation to its prey should be valuable in future conservation planning there and in similar montane environments

Leopard population dynamics, trophy hunting and conservation in the Soutpansberg Mountains, South Africa

This thesis represents a highly novel attempt to combine capture-recapture camera trapping, GPS telemetry and dietary analysis with anthropological techniques such as participant observation and semi-structured interviews in order to investigate leopard population density and dynamics, human-leopard conflict and the potential and effectiveness of trophy hunting as a conservation tool for leopards in the Soutpansberg Mountains, Limpopo Province, South Africa. Results from camera trapping data show that the Soutpansberg is home to a very high density of leopards (20 per 100km2). This is supported by the small home range of an adult female measured during the study (13.9 km2 95% MCP) suggesting the Soutpansberg is a prey rich area with prey densities high enough to allow leopards to live in large numbers and hold small home ranges. The dispersal movements of a collared sub-adult male indicate that the Soutpansberg may be acting as a population source for sinks beneath the mountains. High levels of human-wildlife conflict exist between leopards and landowners and leopards are frequently persecuted for perceived livestock predation although no evidence of livestock was found in leopard scats. Trophy hunting does not currently work as an effective conservation tool for leopards by providing economic incentives for landowners to reduce illegal hunting and tolerate the wider leopard population. Quotas are not based on accurate population figures of leopards from field studies, females are allowed in hunting off-take and only game farmers that own hunting farms apply for trophy hunting permits. Landowners responsible for the majority of leopard mortalities (cattle and community farmers) do not conduct trophy hunting due to their distrust of the complex and bureaucratic application process. The sustainability of trophy hunting must be improved by basing off-take on accurate population numbers, monitoring harvested populations, encouraging a wider uptake of commercial hunting and reducing illegal harvests

Hibernation ecology and population biology of the hazel dormouse

Detailed knowledge of the ecology and environmental conditions suitable for individual species across the landscape is vital for effective conservation measures. Similarly, understanding demographic factors that influence the structure of animal populations is crucial for understanding species trends. In this thesis, I explore one of the most interesting aspects that distinguishes the hazel dormouse (Muscardinus avellanarius) from other woodland small mammals - its ability to hibernate. Hibernation is a complex strategy with marked trade-offs that shapes the demography and structure of hazel dormouse populations and yet it is one of the least studied facets of their life cycle. Firstly, I introduce relevant background to the thesis. I evaluate different methods to locate hibernacula, investigate dormouse movements before hibernation, their behaviour as they prepare to face months of low activity at low temperatures and fewer foraging opportunities, to the point where they find a suitable place to build a nest to hibernate on the ground. I then examine population structure and estimate overwinter survival of different hazel dormouse populations. Using telemetry, I found that hazel dormice select hibernation sites within their autumnal home range. I investigate the impact of hibernation on body weight of hazel dormice and quantify rates of weight loss in wild animals. With the use of high-resolution airborne LiDAR derived canopy structure and topography, I develop novel models to characterise hazel dormouse hibernaculum locations and predict suitable locations across the landscape. I demonstrate that topography, sky view and canopy height can influence hibernaculum location selection. At the hibernaculum location, I demonstrate how hazel dormouse hibernation nests are built in a similar fashion to their summer nests and that they utilise a range of materials that are available in the immediate vicinity of the selected hibernation site. I quantify hazel dormouse overwinter survival of different populations and find that on average 0.36 (0.29 - 0.44, 95% Confidence Intervals (CI) of the population survives. My findings, based on the existing literature and evidence I collected in the field, suggests that hazel dormice are resourceful, able to cope with diverse habitat characteristics and resources. Conservation efforts should therefore focus on creating, managing and/or enhancing diversity within their habitat by promoting a varied canopy structure that is well connected and made up of assorted tree and shrub species of value to the hazel dormice in order to increase nesting and foraging opportunities through the seasons.People's Trust for Endangered Specie