Triadic interaction in clinical task-based interviews with mathematics teachers

A clinical task-based interview can be seen as a situation where the interviewer–interviewee interaction on a task is regulated by a system of explicit and implicit norms, values, and rules. This paper describes how documenting and mapping triadic interaction among the interviewer, the interviewee, and the knowledge negotiated can be used to increase procedural replicability of the interview and accuracy of drawn conclusions about the interviewee’s thinking process. Excerpts from interviews with 25 inservice mathematics teachers working on a task to make up a problem whose solution requires division of two fractions are discussed. The excerpts illustrate the relationship between methodological decisions taken by the interviewer during the interview and the applicability of the interview output to the research questions. A divergent analysis of the interviews with these teachers, which spanned over two years and were conducted by four interviewers, is used to offer a framework for analyzing data collected in clinical task-based interviews.     

Defining the nature of blended learning through its depiction in current research

ABSTRACT

Blended learning has been a feature of higher education practice and research for almost two decades. This article takes stock of current blended learning research, contributing to the growing number of meta-analyses of higher education and blended learning research more generally, through a review of ninety-seven articles relating to blended learning in higher education published in fifteen journals between 2012 and mid-2017. The review focused on where and when the articles were published; their provenance, scale, scope; methodological approach; the broad research themes; and definition of blended learning used. The review shows that despite its ubiquity, blended learning’s definition is all-encompassing; its spread is global but research is dominated by key players; it is of technical interest; and its research is small-scale, individually focused, seeking to evidence the benefits of blended learning. The article concludes with recommendations of how higher education research could provide institutions with evidence to ensure their ‘best of blends’.     

基于核密度估计多样性采集的背景建模算法

1IntroductionBackground subtraction methods are extensively ex-ploited for moving object detection in videos in manyapplications ,such as traffic monitoring[1],human mo-tion capture[2]and video surveillance[3]. The centralidea behind such methods is to segment foreground ini mage sequences taken from a fixed camera by com-paring each newframe to a model of the scene back-ground . Therefore , correctly and efficiently modelingand updating the background model is one of the mostchallenging aspec…     

Conversion of CO<Subscript>2</Subscript> to useful substances with composite iron,nickel, and copper catalysts

Composite materials of Fe/Al₂O₃, which consist of small particles of iron supported by thermally stable alumina even at 500–700 °C, have been widely used in the water-gas shift reaction for natural gas reforming. Therefore, Fe/Al₂O₃ is one of the promising candidates for re-transformation of exhausted CO₂ into fuels such as alcohols and hydrocarbons. The development of a CO₂ reforming system using the composite materials of Fe/Al₂O₃ through CO₂ reduction to CO, dissociation of water into hydrogen, and methanol synthesis has been investigated. It was found that dry and steam (i.e. wet) reforming of CO₂ produced almost the same amount of CO. At a temperature above 500 °C, maximal and saturated yields of CO and H₂ from CO₂ and water were obtained. However, this CO₂ reforming system requires higher-pressure conditions from several tens to hundreds standard atmospheric pressure in order to achieve high yield and selectivity for methanol production. In this study we developed the modified CO₂ reforming system by the utilization of Ni and/or Cu instead of Fe in order to obtain other types of useful products such as CO, CH₄, and carbon, more efficiently and selectively under atmospheric pressure. When Ni or Cu was used, conversion of CO₂ was reduced to 76%, while 9% of methane was detected in the case of Ni. On the other hand, though the CO₂ conversion reduced half of the Fe, the selectivity of CO from CO₂ increased to 95% in the case of Cu.     

Numerical investigation of cavitating flow behind the cone of a poppet valve in water hydraulic system

Computational Fluid Dynamics (CFD) simulations of cavitating flow through water hydraulic poppet valves were performed using advanced RNGk-epsilon turbulence model. The flow was turbulent, incompressible and unsteady, for Reynolds numbers greater than 43000. The working fluid was water, and the structure of the valve was simplified as a two dimensional axisymmetric geometrical model. Flow field visualization was numerically achieved. The effects of inlet velocity, outlet pressure, opening size as well as poppet angle on cavitation intensity in the poppet valve were numerically investigated. Experimental flow visualization was conducted to capture cavitation images near the orifice in the poppet valve with 30° poppet angle using high speed video camera. The binary cavitating flow field distribution obtained from digital processing of the original cavitation image showed a good agreement with the numerical result. Project supported by the National Natural Science Foundation of China (No. 59835160) and Scientific Research Foundation for Returned Overseas Chinese Scholars, State Education Ministry of China (No. 50175097)     

Filtration of micro-particles within multi-fiber arrays by adhesive DEM-CFD simulation

A 3D multi-time scale discrete element method-computational fluid dynamic (DEM-CFD) coupling approach was applied to investigate the filtration of micron-sized particles by different types of fiber arrays. Both the pressure drop and the filtration efficiency were examined to indicate the filtration performance of the fiber arrays. Fibers that were uniformly arrayed in a parallel or staggered manner were compared. Results showed that the staggered array showed a better performance than the parallel array in terms of both pressure drop and filtration efficiency. Further, we compared the performance of different staggered arrays, i.e. a regular case, one densified in the front layers and another densified in the back layers. The front densified array was found to enter the clogging and cake filtration stage in the shortest time, leading to the highest filtration efficiency, but the highest pressure drop. The back densified array still achieved a much higher filtration efficiency, despite a much lower pressure drop comparable to that of the regular array. The results suggest that the two kinds of densified arrays may be suited for different purposes, e.g. baghouse filters or breathing masks.     

A novel multi-objective optimization method for the pressurized reservoir in hydraulic robotics

The pressurized reservoir is a closed hydraulic tank which plays a significant role in enhancing the capabilities of hydraulic driven robotics. The spring pressurized reservoir adopted in this paper requires comprehensive performance, such as weight, size, fluid volume, and pressure, which is hard to balance. A novel interactive multi-objective optimization approach, the feasible space tightening method, is proposed, which is efficient in solving complicated engineering design problems where multiple objectives are determined by multiple design variables. This method provides sufficient information to the designer by visualizing the performance trends within the feasible space as well as its relationship with the design variables. A step towards the final solution could be made by raising the threshold on performance indicators interactively, so that the feasible space is reduced and the remaining solutions are more preferred by the designer. With the help of this new method, the preferred solution of a spring pressurized reservoir is found. Practicability and efficiency are demonstrated in the optimal design process, where the solution is determined within four rounds of interaction between the designer and the optimization program. Tests on the designed prototype show good results.