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This report of a multidisciplinary study of Scottish farmers' attitudes, goals, and behavior describes scales developed specifically for this population and explains how they can be used to find correlations among attitudes, objectives, and implementation. The article contains 113 references. (SK)

The interrelationship between personality and intelligence was investigated in several studies using data from a survey of 210 Scottish farmers. Evidence was found for increased differentiation of neuroticism and openness at higher levels of ability. There was no support for the hypothesis that intelligence affects the correlation between extraversion and conscientiousness. (SLD)

Time-Correlated Single Photon Counting and Burst Illumination Laser data can be used for range profiling and target classification. In general, the problem is to analyze the response from a histogram of either photon counts or integrated intensities to assess the number, positions, and amplitudes of the reflected returns from object surfaces. The goal of our work is a complete characterization of the 3D surfaces viewed by the laser imaging system. The authors present a unified theory of pixel processing that is applicable to both approaches based on a Bayesian framework, which allows for careful and thorough treatment of all types of uncertainties associated with the data. We use reversible jump Markov chain Monte Carlo (RJMCMC) techniques to evaluate the posterior distribution of the parameters and to explore spaces with different dimensionality. Further, we use a delayed rejection step to allow the generated Markov chain to mix better through the use of different proposal distributions. The approach is demonstrated on simulated and real data, showing that the return parameters can be estimated to a high degree of accuracy. We also show some practical examples from both near and far-range depth imaging. Index Terms--Three-dimensional reconstruction, burst illumination laser, delayed rejection, Lidar, photon counting, reversible jump MCMC.

We describe two algorithms for designing and training neural-network classifiers. The first, the linear programming slab algorithm (LPSA), is motivated by the problem of reconstructing digital signals corrupted by passage through a dispersive channel and by additive noise. It constructs a multilayer perceptron (MLP) to separate two disjoint sets by using linear programming methods to identify network parameters. The second, the perceptron learning slab algorithm (PLSA), avoids the computational costs of linear programming by using an error-correction approach to identify parameters. Both algorithms operate in highly constrained parameter spaces and are able to exploit symmetry in the classification problem. Using these algorithms, we develop a number of procedures for the adaptive equalization of a complex linear 4-quadrature amplitude modulation (QAM) channel, and compare their performance in a simulation study. Results are given for both stationary and time-varying channels, the latter based on the COST 207 GSM propagation model. Index Terms - Adaptive equalizers, complex spaces, fading channels, multilayer perceptions, multisurface method, neural networks, pattern classification, piecewise linear classifier, slab, time-varying channels.

This paper describes some studies of the interrelationship of personality and intelligence using data from a survey of Scottish farmers. (N = 210). Subjects completed the NEO Five Factor Inventory, [...]

We investigate the validity of the classification of farmers into two or more distinct types on the basis of attitudes, objectives, and values. Factor analysis of data from a survey of farm pluriactivity in Scotland (N=472) shows that attributes ascribed to 'yeoman' and 'entrepreneur' types emerge as separate factors rather than as a single bipolar factor. No clustering of the factor scores corresponding to distinct types is found. We also present correlations of the factor scores with attitudes to on- and off-farm pluriactivity and with observables such as age and off-farm employment. The desirability of analyzing survey data by methods which do not make assumptions about typology is discussed.

An analysis is made of the differentiation hypothesis advanced by C. Spearman that the influence of general intelligence on abilities possibly varies with intelligence quotient levels and/or age and is greater at lower ability levels. Data studied were obtained from the Differential Aptitude Test results of over 10,500 Irish schoolchildren aged 14-17. Results confirm Spearman's differentiation hypothesis.

This paper investigates the classification capabilities of perceptrons which incorporate a single hidden layer of nodes from a theoretical viewpoint. In particular, we consider the question of determining whether a given set can be realized as the decision region of such a network. Our main theoretic result demonstrates that the realizability of a set can be determined by restricting attention to any neighborhood of its boundary. This result is then used to identify general classes of realizable sets and an example is given which shows that even though the realizability of a set might be readily discerned, the construction of an appropriate perceptron architecture may be complicated.