Comprehension is an important cognitive state for learning. Human tutors recognise comprehension and non-comprehension states by interpreting learner non-verbal behaviour (NVB). Experienced tutors adapt pedagogy, materials and instruction to provide additional learning scaffold in the context of perceived learner comprehension. Near real-time assessment for e-learner comprehension of on-screen information could provide a powerful tool for both adaptation within intelligent e-learning platforms and appraisal of tutorial content for learning analytics. However, literature suggests that no existing method for automatic classification of learner comprehension by analysis of NVB can provide a practical solution in an e-learning, on-screen, context. This paper presents design, development and evaluation of COMPASS, a novel near real-time comprehension classification system for use in detecting learner comprehension of on-screen information during e-learning activities. COMPASS uses a novel descriptive analysis of learner behaviour, image processing techniques and artificial neural networks to model and classify authentic comprehension indicative non-verbal behaviour. This paper presents a study in which 44 undergraduate students answered on-screen multiple choice questions relating to computer programming. Using a front-facing USB web camera the behaviour of the learner is recorded during reading and appraisal of on-screen information. The resultant dataset of non-verbal behaviour and question-answer scores has been used to train artificial neural network (ANN) to classify comprehension and non-comprehension states in near real-time. The trained comprehension classifier achieved normalised classification accuracy of 75.8%.
Water treatment processes produce water with low turbidity and colour. It is also now becoming necessary to reduce DOC (Dissolved Organic Carbon) so that less chlorine is lost in a distribution system and less THMs (trihalomethanes) are formed. Enhanced coagulation (exceeding other requirements) at pH of about 5-6 is known to significantly reduce DOC so that acceptable water quality can be achieved at the tap. In this paper, models are integrated to project the impact of water treatment on water quality through the entire distribution system. A DOC removal model, which predicts DOC resulting from a given coagulant, its dose and the coagulation pH, is used to simulate the treatment. By linking this model of DOC removal with models of chlorine decay and THM formation, the impact of treatment on chlorine and THM concentrations in a distribution system can be simulated. This method was applied in a case study with relatively high initial DOC. It was shown that more DOC can be removed by using ferric coagulant than the current practice achieves. This would result in an improved chlorine profile and a substantial reduction in THM concentrations.
Abstract:The Peerless Jenny King treatment system is a series of four sulfate reducing bioreactor cells installed to treat acid mine drainage in the Upper Tenmile Creek Superfund Site located in the Rimini Mining District, near Helena MT. The system consists of a wetland pretreatment followed by the four cells connected in a serpentine manner. The mining impacted water flows from the wetland through each cell before discharge. Sulfate reducing bioreactors mitigate acidity and metal contamination through the microbial production of sulfide. The produced biogenic sulfide precipitates metals, and the microbial process of reducing sulfate to sulfide produces alkalinity.The health of the entire microbial community present in such systems is important for remediation to be effective. Classes of microbes generally present in such systems include fermenters, methanogens and sulfate reducers. The health can be measured in terms of active microbial populations and positive interactions between populations for the support of sulfate reduction. The goal of this research is to measure the activity of each class utilizing analyses that quantify the groups by their function, as opposed to the traditional molecular techniques of identifying bacteria. Gas chromatography, HPLC-DAD, and ICP-AES are used to identify and quantify the end products of metabolism. The microbial activity can then be characterized and changes can be monitored over time. Results from 2005 sampling of Cell 3 within the system indicate that the activity of sulfate reducing bacteria is much higher than the numbers present would indicate. These results combined with those from 2006 sampling indicate that methanogenesis is a minor process within this cell. The calculation of the stoichiometry of carbon utilization by SRB is much higher than what would be predicted from known stoichiometric ratios of carbon used per sulfate reduced.
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