A comparison of search functions and other navigational tools provided on government websites

This paper reports the outcomes of a study that evaluated the effectiveness of search functions compared to other navigational tools available on government websites. The study used an observation exercise triangulated with a post observation interview. Results suggest that while there wasn't any significant difference in effectiveness between search functions and other navigational tools, the skill with which the search function is implemented and participants' familiarity with the website, are fundamental determinants of users' opinions. Implications of the findings for research and practice are discussed.

The eight variable homogeneous degree three bent functions

We determine the affine equivalence classes of the eight variable degree three homogeneous bent functions using a new algorithm. Our algorithm applies to general bent functions and can systematically determine the automorphism groups. We provide a partial verification of the computer enumeration of bent functions by Meng et al.

Determination of yield and erosion damage functions using subjectively elicited data: application to small holder tea in Sri Lanka

Tea has been Sri Lanka's major export earner for several decades. However, soil erosion on tea-producing land has had considerable on-site and off-site effects. This study quantifies soil erosion impacts for smallholder tea farms in Sri Lanka by estimating a yield damage function and an erosion damage function using a subjective elicitation technique. The Mitscherlich-Spillman type of function was found to yield acceptable results. The study indicates that high rates of soil erosion require earlier adoption of soil conservation measures than do low rates of erosion. Sensitivity analysis shows the optimum year to change to a conservation practice is very sensitive to the discount rate but less sensitive to the cost of production and price of tea.

Smoothing Lipschitz functions

This paper describes a new approach to multivariate scattered data smoothing. It is assumed that the data are generated by a Lipschitz continuous function f, and include random noise to be filtered out. The proposed approach uses known, or estimated value of the Lipschitz constant of f, and forces the data to be consistent with the Lipschitz properties of f. Depending on the assumptions about the distribution of the random noise, smoothing is reduced to a standard quadratic or a linear programming problem. We discuss an efficient algorithm which eliminates the redundant inequality constraints. Numerical experiments illustrate applicability and efficiency of the method. This approach provides an efficient new tool of multivariate scattered data approximation.

Myth and Society: Functions, Uses, and Abuses of Myth in Society

In this work, I will discuss the integral role that myth has in society and then, after presenting several examples of this thesis, I will examine how the integral nature of myth lends itself to certain societal abuses. These abuses often result in unjust social constructs that eventually become attributed to the myth. I would like to proceed in defense of myth; that is, that these constructs are not to be attributed to the myths themselves, rather, society has taken myth and applied it to suit its purposes, ignoring the context in which the myths originated. Hopefully this will raise society's current attitudes toward myth to a level of respect, and will also help to clear myth of its reputation as the origin of injustice and domination.

Standardizing anthropometric measures in children and adolescents with new functions for egen

A new function for egen has been developed to allow transformation of child anthropometric data to z-scores using the LMS method and the reference data available from the 1990 British Growth Reference and the 2000 US CDC Growth Reference. An additional function allows for children to be categorized according to body mass index (weight/height ²) using international cutoff points recommended by the Childhood Obesity Working Group of the International Obesity Taskforce. Copyright 2004 by StataCorp LP.

Multi-wavelets from B-spline super-functions with approximation order

Approximation order is an important feature of all wavelets. It implies that polynomials up to degree p−1 are in the space spanned by the scaling function(s). In the scalar case, the scalar sum rules determine the approximation order or the left eigenvectors of the infinite down-sampled convolution matrix H determine the combinations of scaling functions required to produce the desired polynomial. For multi-wavelets the condition for approximation order is similar to the conditions in the scalar case. Generalized left eigenvectors of the matrix H_f; a finite portion of H determines the combinations of scaling functions that produce the desired superfunction from which polynomials of desired degree can be reproduced. The superfunctions in this work are taken to be B-splines. However, any refinable function can serve as the superfunction. The condition of approximation order is derived and new, symmetric, compactly supported and orthogonal multi-wavelets with approximation orders one, two, three and four are constructed.

Estimating money demand functions for South Asian countries

In this paper, we estimate a money demand function for a panel of five South Asian countries. We find that the money demand and its determinants, namely real income, real exchange rate and short-term domestic and foreign interest rates are cointegrated both for individual countries as well as for the panel, and panel long-run elasticities provide robust evidence of statistically significant relationships between money demand and its determinants. Our test for panel Granger causality suggests short-run causality running from all variables, except foreign interest rate, to money demand, and we find evidence that except for Nepal money demand functions are stable.

Deterministic versus stochastic quantitative microbial Risk Assessment models for wastewater irrigation of food crops

Reuse of wastewater to irrigate food crops is being practiced in many parts of the world and is becoming more commonplace as the competition for, and stresses on, freshwater resources intensify. But there are risks associated with wastewater irrigation, including the possibility of transmission of pathogens causing infectious disease, to both workers in the field and to consumers buying and eating produce irrigated with wastewater. To manage these risks appropriately we need objective and quantitative estimates of them. This is typically achieved through one of two modelling approaches: deterministic or stochastic. Each parameter in a deterministic model is represented by a single value, whereas in stochastic models probability functions are used. Stochastic models are theoretically superior because they account for variability and uncertainty, but they are computationally demanding and not readily accessible to water resource and public health managers. We constructed models to estimate risk of enteric virus infection arising from the consumption of wastewater-irrigated horticultural crops (broccoli, cucumber and lettuce), and compared the resultant levels of risk between the deterministic and stochastic approaches. Several scenarios were tested for each crop, accounting for different concentrations of enteric viruses and different lengths of environmental exposure (i.e. the time between the last irrigation event and harvest, when the viruses are liable to decay or inactivation). In most situations modelled the two approaches yielded similar estimates of risk (within 1 order-of-magnitude). The two methods diverged most markedly, up to around 2 orders-of-magnitude, when there was large uncertainty associated with the estimate of virus concentration and the exposure period was short (1 day). Therefore, in some circumstances deterministic modelling may offer water resource managers a pragmatic alternative to stochastic modelling, but its usefulness as a surrogate will depend upon the level of uncertainty in the model parameters.

Predictors of timely doctoral student completions by type of attendance: the utility of a pragmatic approach

Federal government changes to the funding of doctoral students have focused the attention of university management on their completion rates. The aims of this paper are to inform the allocation of institutional resources in a manner that improves the likelihood of timely doctoral completions and to highlight a process that can also be used for analyses of other key indicators of progression and attrition. The analyses and model development used national data readily available to all universities, which are collected in a standard approach through the Graduate Destinations Survey (GDS). The findings show that the most important variable for timely completion was attendance (full-time compared with part-time), whereby in terms of full-time equivalent (FTE) years of study, part-time students were far more likely to complete quickly than full-time students. For the full-time students, the key predictors of timely completion were residency, field of study and English-speaking background (ESB). The timeliness of part-time students was predicted by field of study and ESB. This study confirms that there is considerable variation by discipline for timely doctoral completions. The pragmatic application and prospective test of the derived models present a variety of opportunities for research student administrators. For example, those full-time students scoring highly represented a concentration of timely graduates more than 7.5 times higher than the lowest-scoring group - almost an order of magnitude of difference. In short, university management could gain tremendous value from more widely using the data available.