A framework for state-based time-series analysis and prediction

Time-series analysis and prediction play an important role in state-based systems that involve dealing with varying situations in terms of states of the world evolving with time. Generally speaking, the world in the discourse persists in a given state until something occurs to it into another state. This paper introduces a framework for prediction and analysis based on time-series of states. It takes a time theory that addresses both points and intervals as primitive time elements as the temporal basis. A state of the world under consideration is defined as a set of time-varying propositions with Boolean truth-values that are dependent on time, including properties, facts, actions, events and processes, etc. A time-series of states is then formalized as a list of states that are temporally ordered one after another. The framework supports explicit expression of both absolute and relative temporal knowledge. A formal schema for expressing general time-series of states to be incomplete in various ways, while the concept of complete time-series of states is also formally defined. As applications of the formalism in time-series analysis and prediction, we present two illustrating examples.

The food multimix concept: potential of an innovative food based approach on nutritional status in pregnant women in resource-poor communities

RATIONALE & OBJECTIVES: The food multimix (FFM)concept states that limited food resources can be combined using scientific knowledge to meet nutrient needs of vulnerable groups at low cost utilizing the ‘nutrient strengths’ of individual or candidate foods in composite recipes within a cultural context. METHODS: The method employed the food-to-food approach for recipe development using traditional food ingredients. Recipes were subjected to proximate and micronutrient analysis and optimized to meet at tleast 40% of recommended daily intakes. End products including breads, porridge and soup were developed. RESULTS: FMM products were employed in a feeding trial among 120 healthy pregnant women in Gauteng, South Africa resulting in improvements in serum iron levels from baseline values of 14.59 (=/-7.67) umol/L and 14.02 (=/-8.13) umol/L for control and intervention groups (p=0.71), to 16.03 (=/-5.67) umol/L and 18.66 (=/-9.41) umol/L (p=0.19). The increases from baseline to post-intervention were however statistically significant within groups. Similarly Mean Cell Volume values improved from baseline as well as serum ferritin and transferritin levels. CONCLUSION: The FMM concept has potential value in feeding programs for vulnerable groups including pregnant and lactating mothers.