Robo-CAMAL : anchoring in a cognitive robot

The CAMAL architecture (Computational Architectures for Motivation,Affect and Learning) provides an excellent framework within which to explore and investigate issues relevant to cognitive science and artificial intelligence. This thesis describes a small sub element of the CAMAL architecture that has been implemented on a mobile robot. The first area of investigation within this research relates to the anchoring problem. Can the robotic agent generate symbols based on responses within its perceptual systems and can it reason about its environment based on those symbols? Given that the agent can identify changes within its environment, can it then adapt its behaviour and alter its goals to mirror the change in its environment? The second area of interest involves agent learning. The agent has a domain model that details its goals, the actions it can perform and some of the possible environmental states it may encounter. The agent is not provided with the belief-goal-action combinations in order to achieve its goals. The agent is also unaware of the effect its actions have upon its environment. Can the agent experiment with its behaviour to generate its own belief-goal-action combinations that allow it to achieve its goals? A second related problem involves the case where the belief-goal-action combination is pre-programmed. This is when the agent is provided with several different methods with which to achieve a specific goal. Can the agent learn which combination is the best? This thesis will describe the sub-element of the CAMAL architecture that was developed for a robot (robo-CAMAL). It will also demonstrate how robo-CAMAL solves the anchoring problem, and learns how to act and adapt in its environment

Issues in the construction of wealth indices for the measurement of socio-economic position in low-income countries

BACKGROUND: Epidemiological studies often require measures of socio-economic position (SEP). The application of principal components analysis (PCA) to data on asset-ownership is one popular approach to household SEP measurement. Proponents suggest that the approach provides a rational method for weighting asset data in a single indicator, captures the most important aspect of SEP for health studies, and is based on data that are readily available and/or simple to collect. However, the use of PCA on asset data may not be the best approach to SEP measurement. There remains concern that this approach can obscure the meaning of the final index and is statistically inappropriate for use with discrete data. In addition, the choice of assets to include and the level of agreement between wealth indices and more conventional measures of SEP such as consumption expenditure remain unclear. We discuss these issues, illustrating our examples with data from the Malawi Integrated Household Survey 2004-5. METHODS: Wealth indices were constructed using the assets on which data are collected within Demographic and Health Surveys. Indices were constructed using five weighting methods: PCA, PCA using dichotomised versions of categorical variables, equal weights, weights equal to the inverse of the proportion of households owning the item, and Multiple Correspondence Analysis. Agreement between indices was assessed. Indices were compared with per capita consumption expenditure, and the difference in agreement assessed when different methods were used to adjust consumption expenditure for household size and composition. RESULTS: All indices demonstrated similarly modest agreement with consumption expenditure. The indices constructed using dichotomised data showed strong agreement with each other, as did the indices constructed using categorical data. Agreement was lower between indices using data coded in different ways. The level of agreement between wealth indices and consumption expenditure did not differ when different consumption equivalence scales were applied. CONCLUSION: This study questions the appropriateness of wealth indices as proxies for consumption expenditure. The choice of data included had a greater influence on the wealth index than the method used to weight the data. Despite the limitations of PCA, alternative methods also all had disadvantages

Child Mortality in Rural Malawi: HIV Closes the Survival Gap between the Socio-Economic Strata

BACKGROUND: As HIV-related deaths increase in a population the usual association between low socioeconomic status and child mortality may change, particularly as death rates from other causes decline. METHODS/PRINCIPAL FINDINGS: As part of a demographic surveillance system in northern Malawi in 2002-6, covering a population of 32,000, information was collected on socio-economic status of the households. Deaths were classified as HIV/AIDS-related or not by verbal autopsy. Poisson regression models were used to assess the association of socio-economic indicators with all-cause mortality, AIDS-mortality and non-AIDS mortality among children. There were 195 deaths in infants, 109 in children aged 1-4 years, and 38 in children aged 5-15. All-cause child mortality in infants and 1-4 year olds was similar in households with higher and lower socio-economic status. In infants 13% of deaths were attributed to AIDS, and there were no clear trends with socio-economic status for AIDS or non-AIDS causes. For 1-4 year olds 27% of deaths were attributed to AIDS. AIDS mortality was higher among those with better built houses, and lowest in those with income from farming and fishing, whereas non-AIDS mortality was higher in those with worse built houses, lowest in those with income from employment, and decreased with increasing household assets. CONCLUSIONS/SIGNIFICANCE: In this population, since HIV infection among adults was initially more common among the less poor, childhood mortality patterns have changed. The usual gap in survival between the poor and the less poor has been lost, but because the less poor have been disproportionately affected by HIV, rather than because of relative improvement in the survival of the poorest

Global report on preterm birth and stillbirth (4 of 7): delivery of interventions

<p>Abstract</p> <p>Background</p> <p>The efficacious interventions identified in the previous article of this report will fail unless they are delivered at high and equitable coverage. This article discusses critical delivery constraints and strategies.</p> <p>Barriers to scaling up interventions</p> <p>Achieving universal coverage entails addressing major barriers at many levels. An overarching constraint is the lack of political will, resulting from the dearth of preterm birth and stillbirth data and the lack of visibility. Other barriers exist at the household and community levels, such as insufficient demand for interventions or sociocultural barriers; at the health services level, such as a lack of resources and trained healthcare providers; and at the health sector policy and management level, such as poorly functioning, centralized systems. Additional constraints involve weak governance and accountability, political instability, and challenges in the physical environment.</p> <p>Strategies and examples</p> <p>Scaling up maternal, newborn and child health interventions requires strengthening health systems, but there is also a role for focused, targeted interventions. Choosing a strategy involves identifying appropriate channels for reaching high coverage, which depends on many factors such as access to and attendance at healthcare facilities. Delivery channels vary, and may include facility- and community-based healthcare providers, mass media campaigns, and community-based approaches and marketing strategies. Issues related to scaling up are discussed in the context of four interventions that may be given to mothers at different stages throughout pregnancy or to newborns: (1) detection and treatment of syphilis; (2) emergency Cesarean section; (3) newborn resuscitation; and (4) kangaroo mother care. Systematic reviews of the literature and large-scale implementation studies are analyzed for each intervention.</p> <p>Conclusion</p> <p>Equitable and successful scale-up of preterm birth and stillbirth interventions will require addressing multiple barriers, and utilizing multiple delivery approaches and channels. Another important need is developing strategies to discontinue ineffective or harmful interventions. Preterm birth and stillbirth interventions must also be placed in the broader maternal, newborn and child health context to identify and prioritize those that will help improve several outcomes at the same time. The next article discusses advocacy challenges and opportunities.</p

Robo-CAMAL : anchoring in a cognitive robot

The CAMAL architecture (Computational Architectures for Motivation,Affect and Learning) provides an excellent framework within which to explore and investigate issues relevant to cognitive science and artificial intelligence. This thesis describes a small sub element of the CAMAL architecture that has been implemented on a mobile robot. The first area of investigation within this research relates to the anchoring problem. Can the robotic agent generate symbols based on responses within its perceptual systems and can it reason about its environment based on those symbols? Given that the agent can identify changes within its environment, can it then adapt its behaviour and alter its goals to mirror the change in its environment? The second area of interest involves agent learning. The agent has a domain model that details its goals, the actions it can perform and some of the possible environmental states it may encounter. The agent is not provided with the belief-goal-action combinations in order to achieve its goals. The agent is also unaware of the effect its actions have upon its environment. Can the agent experiment with its behaviour to generate its own belief-goal-action combinations that allow it to achieve its goals? A second related problem involves the case where the belief-goal-action combination is pre-programmed. This is when the agent is provided with several different methods with which to achieve a specific goal. Can the agent learn which combination is the best? This thesis will describe the sub-element of the CAMAL architecture that was developed for a robot (robo-CAMAL). It will also demonstrate how robo-CAMAL solves the anchoring problem, and learns how to act and adapt in its environment