Retrospective studies of operating problems in air transport

An epidemiological model for the study of human errors in aviation is presented. In this approach, retrospective data are used as the basis for formulation of hypotheses as to system factors which may have contributed to such errors. Prospective experimental studies of aviation operations are also required in order to prove or disprove the hypotheses, and to evaluate the effectiveness of intervention techniques designed to solve operational problems in the aviation system

NASA aviation safety reporting system

The origins and development of the NASA Aviation Safety Reporting System (ASRS) are briefly reviewed. The results of the first quarter's activity are summarized and discussed. Examples are given of bulletins describing potential air safety hazards, and the disposition of these bulletins. During the first quarter of operation, the ASRS received 1464 reports; 1407 provided data relevant to air safety. All reports are being processed for entry into the ASRS data base. During the reporting period, 130 alert bulletins describing possible problems in the aviation system were generated and disseminated. Responses were received from FAA and others regarding 108 of the alert bulletins. Action was being taken with respect to 70 of the 108 responses received. Further studies are planned of a number of areas, including human factors problems related to automation of the ground and airborne portions of the national aviation system

Simulation studies of air transport operational problems

An experimental evaluation of the monitored approach procedure for conducting low visibility instrument approaches is described. Four airline crews each flew 16 approaches using the monitored procedure and 16 using a modified standard procedure in a DC-10 simulator under various conditions of visibility, wind shear and turbulence, and radar vectoring scenarios. In terms of system measures of aircrew performance, no major differences were found. Pilot opinion data indicate that there are some desirable characteristics of the monitored procedure, particularly with reference to the increased role of the flight engineer in conducting low visibility approaches. Rationale for developing approach procedures is discussed

Parsimonious Kernel Fisher Discrimination

By applying recent results in optimization transfer, a new algorithm for kernel Fisher Discriminant Analysis is provided that makes use of a non-smooth penalty on the coefficients to provide a parsimonious solution. The algorithm is simple, easily programmed and is shown to perform as well as or better than a number of leading machine learning algorithms on a substantial benchmark. It is then applied to a set of extreme small-sample-size problems in virtual screening where it is found to be less accurate than a currently leading approach but is still comparable in a number of cases

Talk the talk, walk the walk: Defining Critical Race Theory in research

Over the last decade there has been a noticeable growth in published works citing Critical Race Theory (CRT). This has led to a growth in interest in the UK of practical research projects utilising CRT as their framework. It is clear that research on 'race' is an emerging topic of study. What is less visible is a debate on how CRT is positioned in relation to methodic practice, substantive theory and epistemological underpinnings. The efficacy of categories of data gathering tools, both traditional and non-traditional is a discussion point here to explore the complexities underpinning decisions to advocate a CRT framework. Notwithstanding intersectional issues, a CRT methodology is recognisable by how philosophical, political and ethical questions are established and maintained in relation to racialised problematics. This paper examines these tensions in establishing CRT methodologies and explores some of the essential criteria for researchers to consider in utilising a CRT framework. © 2012 Copyright Taylor and Francis Group, LLC

Nonparametric nonlinear model predictive control

Model Predictive Control (MPC) has recently found wide acceptance in industrial applications, but its potential has been much impeded by linear models due to the lack of a similarly accepted nonlinear modeling or databased technique. Aimed at solving this problem, the paper addresses three issues: (i) extending second-order Volterra nonlinear MPC (NMPC) to higher-order for improved prediction and control; (ii) formulating NMPC directly with plant data without needing for parametric modeling, which has hindered the progress of NMPC; and (iii) incorporating an error estimator directly in the formulation and hence eliminating the need for a nonlinear state observer. Following analysis of NMPC objectives and existing solutions, nonparametric NMPC is derived in discrete-time using multidimensional convolution between plant data and Volterra kernel measurements. This approach is validated against the benchmark van de Vusse nonlinear process control problem and is applied to an industrial polymerization process by using Volterra kernels of up to the third order. Results show that the nonparametric approach is very efficient and effective and considerably outperforms existing methods, while retaining the original data-based spirit and characteristics of linear MPC

A Simple Iterative Algorithm for Parsimonious Binary Kernel Fisher Discrimination

By applying recent results in optimization theory variously known as optimization transfer or majorize/minimize algorithms, an algorithm for binary, kernel, Fisher discriminant analysis is introduced that makes use of a non-smooth penalty on the coefficients to provide a parsimonious solution. The problem is converted into a smooth optimization that can be solved iteratively with no greater overhead than iteratively re-weighted least-squares. The result is simple, easily programmed and is shown to perform, in terms of both accuracy and parsimony, as well as or better than a number of leading machine learning algorithms on two well-studied and substantial benchmarks

Ogbu and the debate on educational achievement: an exploration of the links between education, migration, identity and belonging

This paper looks at some of the issues raised by Ogbu’s work in relation to the education of different minority ethnic groups. Ogbu poses questions such as the value attached to education, its links to the future and its measurable outcomes in terms of ‘success’ as experienced by black participants. The desire for better life chances leads families to consider migration to a new country or resettlement within the same country, thus making migration both a local and a global phenomenon. As an example, attention is drawn to the situation facing South Asian children and their families in the UK. In terms of ethnicity and belonging, the wider question that is significant for many countries in the West after ‘Nine-Eleven’ is the education of Muslim children. A consideration of this current situation throws Ogbu’s identification of ‘autonomous minority’ into question. It is argued that a greater understanding of diverse needs has to be accompanied by a concerted effort to confront racism and intolerance in schools and in society, thus enabling all communities to make a useful contribution and to avoid the ‘risk’ of failure and disenchantment

Geographic Information System Data Analysis

Data was collected in order to further NASA Langley Research Center's Geographic Information System(GIS). Information on LaRC's communication, electrical, and facility configurations was collected. Existing data was corrected through verification, resulting in more accurate databases. In addition, Global Positioning System(GPS) points were used in order to accurately impose buildings on digitized images. Overall, this project will help the Imaging and CADD Technology Team (ICTT) prove GIS to be a valuable resource for LaRC

Community response in disasters: an ecological learning framework

Natural disasters are frequently exacerbated by anthropogenic mechanisms and have social and political consequences for communities. The role of community learning in disasters is seen to be increasingly important. However, the ways in which such learning unfolds in a disaster can differ substantially from case to case. This article uses a comparative case study methodology to examine catastrophes and major disasters from five countries (Japan, New Zealand, the UK, the USA and Germany) to consider how community learning and adaptation occurs. An ecological model of learning is considered, where community learning is of small loop (adaptive, incremental, experimental) type or large loop (paradigm changing) type. Using this model, we consider that there are three types of community learning that occur in disasters (navigation, organization, reframing). The type of community learning that actually develops in a disaster depends upon a range of social factors such as stress and trauma, civic innovation and coercion