Economic, social and cultural influences on the status and wellbeing of Indian rural wives

Examines the status and well being of wives in rural India using results from interviews. Surveys were conducted in three villages in the southwest of West Bengal and in three villages in the west of Orissa. The survey in West Bengal contained a large proportion of Santal tribals and the Oriyan survey was dominated by Kondh tribals. The relationships between variables representing economic, social and cultural factors are compared with ‘dependent’ variables representing the status of wives within their family and their wellbeing. Wellbeing is indicated by whether the basic needs of wives for food and medical care are met. Status of wives is indicated by their ‘control’ over family resources, whether or not they are restricted in joining social groups and in working outside their home, and the extent of their involvement in family decision-making. Cultural factors are found to be the dominant influence on the status of wives. Family income and other economic factors are found to be associated cross sectionally with greater restrictions on wives within their family. Nevertheless, the higher in the economic status of the household, the more likely are the basic needs of wives to be met.

Polytomous item response theory models

Polytomous Item Response Theory Models provides a unified, comprehensive introduction to the range of polytomous models available within item response theory (IRT). It begins by outlining the primary structural distinction between the two major types of polytomous IRT models. This focuses on the two types of response probability that are unique to polytomous models and their associated response functions, which are modeled differently by the different types of IRT model. It describes, both conceptually and mathematically, the major specific polytomous models, including the Nominal Response Model, the Partial Credit Model, the Rating Scale model, and the Graded Response Model. Important variations, such as the Generalized Partial Credit Model are also described as are less common variations, such as the Rating Scale version of the Graded Response Model. Relationships among the models are also investigated and the operation of measurement information is described for each major model. Practical examples of major models using real data are provided, as is a chapter on choosing an appropriate model. Figures are used throughout to illustrate important elements as they are described.

Transformations of taste: Americanisation, generational change and Australian cultural consumption

Researchers within the field of cultural imperialism as well as the more recently developed globalisation paradigm have tended to dwell upon the economic or corporate dimensions of global cultural flows and have been largely indifferent to the domain of the everyday cultural tastes and forms of cultural consumption that exist in particular national contexts. This article seeks to redress this focus through an examination of one particular instance of cultural imperialism, the widely held belief in ?he Americanisation of Australian society. Using data from a major research project inquiring into Australian everyday culture the article focuses on the changes in cultural tastes and preferences that are evident in three generational cohorts: contemporary young adults, a segment of the 'baby-boom' generation now in middle age, and a group of older Australians born in the years following World War I and the 1920s. The article documents a trend in which overseas influences, particularly those originating from America, appear to be increasingly shaping Australians' tastes in a wide range of cultural domains. Nevertheless, despite these changes in cultural taste Australians of ail ages retain a strong sense of a distinctive national identity. Such findings have implications for an understanding of cultural globalisation as a process of hybridisation and intermixing.

Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

Capillary network models for transport in packed beds: Considerations of pore aspect ratio

The conventional analysis for the estimation of the tortuosity factor for transport in porous media is modified here to account for the effect of pore aspect ratio. Structural models of the porous medium are also constructed for calculating the aspect ratio as a function of porosity. Comparison of the model predictions with the extensive data of Currie (1960) for the effective diffusivity of hydrogen in packed beds shows good agreement with a network model of randomly oriented intersecting pores for porosities upto about 50 percent, which is the region of practical interest. The predictions based on this network model are also found to be in better agreement with the data of Currie than earlier expressions developed for unconsolidated and grainy media.