Distributed Regression in Sensor Networks: Training Distributively with Alternating Projections

Wireless sensor networks (WSNs) have attracted considerable attention in recent years and motivate a host of new challenges for distributed signal processing. The problem of distributed or decentralized estimation has often been considered in the context of parametric models. However, the success of parametric methods is limited by the appropriateness of the strong statistical assumptions made by the models. In this paper, a more flexible nonparametric model for distributed regression is considered that is applicable in a variety of WSN applications including field estimation. Here, starting with the standard regularized kernel least-squares estimator, a message-passing algorithm for distributed estimation in WSNs is derived. The algorithm can be viewed as an instantiation of the successive orthogonal projection (SOP) algorithm. Various practical aspects of the algorithm are discussed and several numerical simulations validate the potential of the approach.Comment: To appear in the Proceedings of the SPIE Conference on Advanced Signal Processing Algorithms, Architectures and Implementations XV, San Diego, CA, July 31 - August 4, 200

Racial Discrimination Among NBA Referees

The NBA provides an intriguing place to test for taste-based discrimination: referees and players are involved in repeated interactions in a high-pressure setting with referees making the type of split-second decisions that might allow implicit racial biases to manifest themselves. Moreover, the referees receive constant monitoring and feedback on their performance. (Commissioner Stern has claimed that NBA referees "are the most ranked, rated, reviewed, statistically analyzed and mentored group of employees of any company in any place in the world.") The essentially arbitrary assignment of refereeing crews to basketball games, and the number of repeated interactions allow us to convincingly test for own-race preferences. We find -- even conditioning on player and referee fixed effects (and specific game fixed effects) -- that more personal fouls are called against players when they are officiated by an opposite-race refereeing crew than when officiated by an own-race crew. These biases are sufficiently large that we find appreciable differences in whether predominantly black teams are more likely to win or lose, based on the racial composition of the refereeing crew.

Where do uncertainties reside within environmental risk assessments? Expert opinion on uncertainty distributions for pesticide risks to surface water organisms

A reliable characterisation of uncertainties can aid uncertainty identification during environmental risk assessments (ERAs). However, typologies can be implemented inconsistently, causing uncertainties to go unidentified. We present an approach based on nine structured elicitations, in which subject-matter experts, for pesticide risks to surface water organisms, validate and assess three dimensions of uncertainty: its level (the severity of uncertainty, ranging from determinism to ignorance); nature (whether the uncertainty is epistemic or aleatory); and location (the data source or area in which the uncertainty arises). Risk characterisation contains the highest median levels of uncertainty, associated with estimating, aggregating and evaluating the magnitude of risks. Regarding the locations in which uncertainty is manifest, data uncertainty is dominant in problem formulation, exposure assessment and effects assessment. The comprehensive description of uncertainty described will enable risk analysts to prioritise the required phases, groups of tasks, or individual tasks within a risk analysis according to the highest levels of uncertainty, the potential for uncertainty to be reduced or quantified, or the types of location-based uncertainty, thus aiding uncertainty prioritisation during environmental risk assessments. In turn, it is expected to inform investment in uncertainty reduction or targeted risk management action

Race for Results: Building a Path to Opportunity for All Children

In this policy report, the Annie E. Casey Foundation explores the intersection of kids, race and opportunity. The report features the new Race for Results index, which compares how children are progressing on key milestones across racial and ethnic groups at the national and state level. The index is based on 12 indicators that measure a child's success in each stage of life, from birth to adulthood, in the areas of early childhood; education and early work; family supports; and neighborhood context. The report also makes four policy recommendations to help ensure that all children and their families achieve their full potential

Combining and Aggregating Environmental Data for Status and Trend Assessments: Challenges and Approaches

Increasingly, natural resource management agencies and nongovernmental organizations are sharing monitoring data across geographic and jurisdictional boundaries. Doing so improves their abilities to assess local-, regional-, and landscape-level environmental conditions, particularly status and trends, and to improve their ability to make short-and long-term management decisions. Status monitoring assesses the current condition of a population or environmental condition across an area. Monitoring for trends aims at monitoring changes in populations or environmental condition through time. We wrote this paper to inform agency and nongovernmental organization managers, analysts, and consultants regarding the kinds of environmental data that can be combined with suitable techniques and statistically aggregated for new assessments. By doing so, they can increase the (1) use of available data and (2) the validity and reliability of the assessments. Increased awareness of the difficulties inherent in combining and aggregating data for local-and regional-level analyses can increase the likelihood that future monitoring efforts will be modified and/or planned to accommodate data from multiple sources