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For pilots to accept active decision aids during complex flight scenarios, it is essential that the automation work is in synergy with aircrew. To accomplish this, the automation must go well beyond menu and macro selections, where the pilot must explicitly tell the automation what to do and when to do it. It must also transcend "mother may I" approaches, where the automation asks for permission to proceed. To these traditional barriers, the automation needs a sense of how the pilot will react in a given situation and, based on that reaction, how much of the workload could be allocated to the automation at any given time. For this purpose, the authors reviewed the literature on human factors and dynamic function allocation. This literature provided a wealth of information on this topic. Based on the current state of the art in this topic area, the authors developed and tested a dynamic model of pilot trust and workload allocation. This "full degrees of freedom" model transitions human factors theory, as it exists today, into an engineering application. The resulting model can be combined with other information obtained from static and continuous processes to divide the workload and minimize cognitive overload.

The use of the digital computer for the presentation of the topics of empirical model building and regression analysis is discussed. The author concentrates upon a description of computing exercises which are employed to provide the students with experience in model building and evaluation in a controlled situation. The types of exercises given are treated, followed by a discussion of the relative merits and dysfunctional aspects of the time-sharing and batch modes of operation. Details are presented concerning the main programs accessed by the students--the BMD multiple and stepwise regression programs, RPIREG, STEPREG, and LINREG. Finally, there is consideration of the strengths and weakness of the computer-assisted instructional (CAI) approach to these topics. (PB)

The use of the digital computer for the presentation of the topics of empirical model building and regression analysis is discussed. The author concentrates upon a description of computing exercises which are employed to provide the students with experience in model building and evaluation in a controlled situation. The types of exercises given are treated, followed by a discussion of the relative merits and dysfunctional aspects of the time-sharing and batch modes of operation. Details are presented concerning the main programs accessed by the students--the BMD multiple and stepwise regression programs, RPIREG, STEPREG, and LINREG. Finally, there is consideration of the strengths and weakness of the computer-assisted instructional (CAI) approach to these topics. (PB)

The use of the digital computer for the presentation of the topics of empirical model building and regression analysis is discussed. The author concentrates upon a description of computing exercises which are employed to provide the students with experience in model building and evaluation in a controlled situation. The types of exercises given are treated, followed by a discussion of the relative merits and dysfunctional aspects of the time-sharing and batch modes of operation. Details are presented concerning the main programs accessed by the students--the BMD multiple and stepwise regression programs, RPIREG, STEPREG, and LINREG. Finally, there is consideration of the strengths and weakness of the computer-assisted instructional (CAI) approach to these topics. (PB)

Echoing both Bronfenbrenner's ecological theory and Guralnick's systems model of child development, this proposed project is multi-level in that all stakeholders in a child’s immediate environment, family, and school are involved, as well as parties' in the larger community. This project places equal emphasis on children, parents, teachers, or other school-based staff, as well as partners in the community. Launching from findings on character development as a key pillar of healthy and holistic trajectories, the project reviews and revises the character education and wellbeing programs in a primary school in Hong Kong. The overarching aim is to produce an empirical model of character education and wellbeing programs that extends previous literature, embodies the principles of childhood interventions as a whole, and will act as a trailblazing example of how character development can have long-term implications for individual life development and society.

Echoing both Bronfenbrenner's ecological theory and Guralnick's systems model of child development, this proposed project is multi-level in that all stakeholders in a child’s immediate environment, family, and school are involved, as well as parties' in the larger community. This project places equal emphasis on children, parents, teachers, or other school-based staff, as well as partners in the community. Launching from findings on character development as a key pillar of healthy and holistic trajectories, the project reviews and revises the character education and wellbeing programs in a primary school in Hong Kong. The overarching aim is to produce an empirical model of character education and wellbeing programs that extends previous literature, embodies the principles of childhood interventions as a whole, and will act as a trailblazing example of how character development can have long-term implications for individual life development and society.

The inter-temporal consumption flexibility of commercial buildings can be harnessed to improve the energy efficiency of buildings, or to provide ancillary service to the power grid. To do so, a predictive model of the building's thermal dynamics is required. In this paper, we identify a physics-based model of a multi-purpose commercial building including its heating, ventilation and air conditioning system during regular operation. We present our empirical results and show that large uncertainties in internal heat gains, due to occupancy and equipment, present several challenges in utilizing the building model for long-term prediction. In addition, we show that by learning these uncertain loads online and dynamically updating the building model, prediction accuracy is improved significantly.

This dissertation explores the distributional properties of commonly used statistics developed in the course of empirical model building. A review of some of the more noteworthy efforts to investigate the distribution of the coefficient of determination of determination, R-squared, in the best subset regression is given. To overcome the shortcomings of these results, a permutation test based on Fisher's randomization test is developed to provide a practical basis for assessing the statistical significance of a regression in such situations. An investigation is made into the distributional properties of the multiple correlation coefficient in the choice of a transformation of the dependent variable. The study investigates the possibility that pedestrian use of transformations, such as y* = (y+c) to the p, may lead to an inflationary effect on the sample correlation. A practical management science application of the statistical procedures developed in this study is explored in the area of parametric cost estimation. (Author)

In the context of multiple linear regression, when a subset of k-out-of-p predictor variables is to be selected for the purpose of predicting the response at some known point in the predictor variables' space, the width of the resulting prediction interval gives an indication of the precision with which the response is predicted and, thus, it may provide a suitable selection criterion. A review of commonly used selection criteria is given, with special emphasis on those which deal with the problem of prediction. The Mahalanobis distance is one of the quantities affecting the width of the prediction interval, and it is studied in some detail. The effects of adding a new variable to a model are investigated and a monotonicity theorem is derived. The influence of an observation on the width of the prediction interval, as measured by the effected change when that observation is set aside, is also investigated and an equivalence beteween observation deletions and variable augmentation is shown.