Representing complex knowledge in an intelligent machine tutor

Knowledge representation remains a serious issue for researchers of intelligent tutoring systems. Two areas of knowledge representation that are particularly difficult are domain and teaching knowledge. This article discusses and gives example solutions to these knowledge engineering issues and also addresses issues that relate to up-scaling existing intelligent tutoring technology to practical levels so that tutoring systems can be brought into the real world.     

Enrichment of Antioxidant Capacity and Vitamin E in Pita Made from Barley

This study aimed to enhance total antioxidant and vitamin E content of pita bread, by replacing 50% of the standard baker's flour with flours milled from covered (WI2585 and Harrington) or hulless (Finniss) barley genotypes, previously shown to have high antioxidant and vitamin E levels at harvest. Pita breads were made from either 100% baker's flour (control) or 50% malt flour, whole‐grain flour, or flour from barley grains pearled at 10%, 15%, and 20% grain weight. Antioxidant capacity and vitamin E content of flours and pitas were determined by their ability to scavenge 2,2‐diphenyl‐1‐picrylhydrazyl radicals and high performance liquid chromatography, respectively. The physical and sensory properties of the pitas were also assessed. All pitas made from either whole grain or pearled barley flour had a higher antioxidant capacity and most also had higher vitamin E content than standard pita. The antioxidant and vitamin E levels were reduced in pearled compared to whole grains, however the extent of that reduction varied among genotypes. The greatest antioxidant and vitamin E levels were found in pita made from malt flour or Finniss whole grain flour. Furthermore, sensory analysis suggested these pitas were acceptable to consumers and retained similar physical and sensory properties to those in the control pita.     

Integrative chemical product design strategies: Reflecting industry trends and challenges

A review of integrative product design strategies is motivated by current trends and challenges faced by the chemical processing industry. The transition in the chemical process industry towards more complex formulated and structured products challenges existing approaches and scientific tools that are well suited for bulk chemical design and properties estimation (Charpentier and McKenna, 2004, Favre et al., 2002). Moreover, the ensuing market challenges, brought on by dominant global trends, demand efficient product design approaches that seek to balance technical specifications and market requirements with the business performance objectives. Integrative approaches to product design are therefore repositioned as useful strategies that simultaneously enhance technical performance and efficiency in design execution. The discussion of the integrative product design strategies is supported by findings of a recent industry benchmark study involving 15 chemical manufacturers.     

Emotional responses to taste and smell stimuli: Self-reports,physiological measures,and a potential role for individual and genetic factors

Taste and olfaction elicit conscious feelings by direct connection with the neural circuits of emotions that affects physiological responses in the body (e.g., heart rate and skin conductance). While sensory attributes are strong determinants of food liking, other factors such as emotional reactions to foods may be better predictors of consumer choices even for products that are equally-liked. Thus, important insights can be gained for understanding the full spectrum of emotional reactions to foods that inform the activities of product developers and marketers, eating psychologist and nutritionists, and policy makers. Today, self-reported questionnaires and physiological measures are the most common tools applied to study variations in emotional perception. The present review discusses these methodological approaches, underlining their different strengths and weaknesses. We also discuss a small, emerging literature suggesting that individual differences and genetic variations in taste and smell perception, like the genetic ability to perceive the bitter compound PROP, may also play a role in emotional reactions to aromas and foods.     

Column breakthrough studies for the removal and recovery of phosphate by lime-iron sludge: Modeling and optimization using artificial neural network and adaptive neuro-fuzzy inference system

Increases in the treatment of water to meet the growing water demand ultimately result in unmanageable quantities of residuals, the handling, and disposal of which is a major environmental issue. Consequently, research into beneficial reuse of water treatment residuals continues unabated. This study investigated the applicability of lime-iron sludge for phosphate adsorption by fixed-bed column adsorption. Laboratory-scale experiments were conducted at varying flow rates and bed depths. Fundamental and empirical models(Thomas, Yan,Bohart-Adams, Yoon-Nelson, and Wolboroska) as well as artificial intelligence techniques(Artificial neural network(ANN) and Adaptive neuro-fuzzy inference system(ANFIS)) were used to simulate experimental breakthrough curves and predict column dynamics. Increase in flow rate resulted in reduced adsorption capacity.However, adsorption capacity was not affected by bed depth. ANN was superior in predicting breakthrough curves and predicted breakthrough times with high accuracy(R~20.9962). Na OH(0.5 mol·L~(-1)) was successfully used to regenerate the adsorption bed. After nine cyclic adsorption/desorption runs, only a marginal decrease in adsorption and desorption efficiencies of 10% and 8% respectively was observed. The same regenerate Na OH solution was reused for all desorption cycles. After nine cycles the eluent desorbed a total of 1550 mg phosphate exhibiting potential for further reuse.