Preparing Higher Education Tutors for Delivering Online Courses

This paper identifies that academic staff need to be suitably prepared to deliver wholly online courses, and outlines the steps taken towards achieving this, at one Higher Education institution in the UK. E-learning, whether partially (blended) or wholly online, is not simply about the technology, but also requires an understanding of the pedagogical considerations, and the skills that are needed, to effectively facilitate them. Through the use of a formal questionnaire, and collation of informal comments made on a social network, evaluation is made of a staff development course designed specifically to promote effective facilitation of high quality online courses. The results determined that the course is fit for purpose and achieves its aims. Future cohorts are already over-subscribed as a result of positive commentary by participants. Further developments will be made, based upon constructive feedback by participants. Whilst possibly not unique, this course demonstrates action being taken in an educational institution to recognise that effective online delivery requires specific knowledge and skills that are different from those used in the traditional classroom

Ion Exchange Nutrient Recovery from Municipal Wastewater

Nitrogen and phosphorus discharge is regulated due to eutrophication. Typically ammonium-nitrogen is removed through nitrification which requires energy and phosphorus (P) is removed by metal salt addition to precipitate P. A more sustainable approach may be to implement nutrient recovery to form fertilizers. Most nitrogen fertilizer is formed through the energy intensive Haber-Bosch process. Phosphate rock, a limited resource, is mined for P fertilizer. Discharge regulations and the fertilizer production costs provide an economic driver for recovery. The current project used anionic and cationic ion exchange (IX) to concentrate the nutrients with recovery by struvite precipitation. Previous work lacks direct comparison of anion media, treatment of real wastewater with 2 IX columns in series, evaluation of regeneration characteristics and struvite precipitation from combined regenerants. During batch testing, Dow-Cu removed 76% of P while Dow-FeCu and LayneRT™ showed removal of \u3e60%. These three media were tested in column mode using filtered municipal wastewater secondary effluent dosed with nutrients. Phosphate removal before breakthrough (PO4-P effluent\u3e0.075 mg/l) for LayneRT™, Dow-FeCu, and Dow-Cu was 2.00, 1.49, and 0.46 g P/LBV, respectively. Desorption of \u3e89% occurred for all 3 resins. Dow-FeCu provided the best conditions: effective removal, efficient regeneration at neutral pH and high (560 mg/l) regenerant P concentration. Natural zeolite was used for cation exchange. During ammonium exchange batch tests, NaCl solution with pH\u3c13 was optimal for regeneration of zeolite. Column testing of zeolite was conducted using effluent from the\u3eLayneRT™ column. Capacity during IX cycle 1 and 2 before breakthrough (NH4-N effluent \u3e 1.5 mg/l) was 3.9 and 6.1 g N/LBV, respectively; performance variability is due to the difference in influent cation concentrations. Desorption was 74% and 68% in cycle 1 and 2, respectively. Struvite was precipitated from zeolite and anion regenerant with 71%, 13%, and 74% P removal for LayneRT™, Dow-Cu, and Dow-FeCu regenerants, respectively. Struvite precipitation was limited by Mg. Precipitates contained impurities such as Al3+, Ca2+, and Fe2+. The IX-recovery process removed greater than 98% P and 95% N and formed solids containing 13% P and 2% N

A summary of the published data on host plants and morphology of immature stages of Australian jewel beetles (Coleoptera: Buprestidae) : with additional new records

A summary is given of the published host plant and descriptive immature stage morphology data for 671 species and 11 subspecies in 54 genera of Australian jewel beetles (Coleoptera: Buprestidae). New host data for 155 species and 3 subspecies in 17 genera including the first published data for 75 species are included

Atmospheric dispersion study of deicing salt applied to roads: first progress report

"April 2000"--Cover."Prepared for Illinois Dept. of Transportation, Illinois State Toll Highway Authority.

A Rigorous Evaluation of Family Finding in North Carolina

Child Trends evaluated Family Finding services in nine North Carolina counties through a rigorous impact evaluation and an accompanying process study. The impact evaluation involved random assignment of eligible children to a treatment or control group. The treatment group received Family Finding services in addition to traditional child welfare services, whereas the control group received traditional child welfare services only. Eligible children were in foster care; were 10 or older at the time of referral; did not have a goal of reunification; and lacked an identified permanent placement. The accompanying process study examined program outputs, outcomes, and linkages between the project components and other contextual factors

Beyond College Enrollment: Exploring the Relationship Between Historically Underrepresented Students’ Prior Participation in College Access Programs and Undergraduate Success

College access programs (CAPs) have proliferated throughout the United States to address disparities in college enrollment between White, higher-income students, and racial/ethnic minority and lower-income students. While CAPs have helped to reduce such disparities, considerable challenges remain. U.S. higher education leaders are facing renewed urgency to address this issue because racial/ethnic minority and lower-income groups are now the fastest growing segments of the population, and because educational attainment – acquisition of a college degree – is increasingly important to national economic growth and individual well-being. However, to date, only a few researchers have examined CAPs’ influence on participants beyond college enrollment, so there is a knowledge gap regarding the kinds of systems and supports needed to help members of these populations achieve a college degree. This study examines the relationship between CAP participation and the undergraduate experiences and outcomes of CAP alumni who enrolled in college. The primary data for this study consisted of individual interviews with 24 alumni from five CAPs in the New York City metropolitan area who subsequently attended college. The CAPs varied by primary funding source. Four to six participants per site were college juniors or seniors, recent college graduates, or individuals who enrolled in college but withdrew before graduating and never returned. The data highlighted the following key themes and implications: (1) CAPs in this study were largely successful in helping alumni enroll in colleges and universities known to be selective; (2) While the CAPs exerted helpful influences, alumni nonetheless faced serious challenges through the college years, such as meeting academic demands and navigating barriers of bigotry and intolerance that are deeply embedded on many campuses; and (3) CAPs in this study influenced alumni’s post-college aspirations, directions, and trajectories regarding career choices, and family and community uplift. Drawing on these findings, this study proposed a model of the psychosocial, academic, and sociocultural resources that appear to contribute to the undergraduate experiences, outcomes, and post-college trajectories of CAP alumni. The study concludes with implications for practice, policy and further research

Bayesian learning for multi-agent coordination

Multi-agent systems draw together a number of significant trends in modern technology: ubiquity, decentralisation, openness, dynamism and uncertainty. As work in these fields develops, such systems face increasing challenges. Two particular challenges are decision making in uncertain and partially-observable environments, and coordination with other agents in such environments. Although uncertainty and coordination have been tackled as separate problems, formal models for an integrated approach are typically restricted to simple classes of problem and are not scalable to problems with tens of agents and millions of states.We improve on these approaches by extending a principled Bayesian model into more challenging domains, using Bayesian networks to visualise specific cases of the model and thus as an aid in deriving the update equations for the system. One approach which has been shown to scale well for networked offline problems uses finite state machines to model other agents. We used this insight to develop an approximate scalable algorithm applicable to our general model, in combination with adapting a number of existing approximation techniques, including state clustering.We examine the performance of this approximate algorithm on several cases of an urban rescue problem with respect to differing problem parameters. Specifically, we consider first scenarios where agents are aware of the complete situation, but are not certain about the behaviour of others; that is, our model with all elements but the actions observable. Secondly, we examine the more complex case where agents can see the actions of others, but cannot see the full state and thus are not sure about the beliefs of others. Finally, we look at the performance of the partially observable state model when the system is dynamic or open. We find that our best response algorithm consistently outperforms a handwritten strategy for the problem, more noticeably as the number of agents and the number of states involved in the problem increase

Sub pixel analysis and processing of sensor data for mobile target intelligence information and verification

This dissertation introduces a novel process to study and analyze sensor data in order to obtain information pertaining to mobile targets at the sub-pixel level. The process design is modular in nature and utilizes a set of algorithmic tools for change detection, target extraction and analysis, super-pixel processing and target refinement. The scope of this investigation is confined to a staring sensor that records data of sub-pixel vehicles traveling horizontally across the ground. Statistical models of the targets and background are developed with noise and jitter effects. Threshold Change Detection, Duration Change Detection and Fast Adaptive Power Iteration (FAPI) Detection techniques are the three methods used for target detection. The PolyFit and FermiFit are two tools developed and employed for target analysis, which allows for flexible processing. Tunable parameters in the detection methods, along with filters for false alarms, show the adaptability of the procedures. Super-pixel processing tools are designed, and Refinement Through Tracking (RTT) techniques are investigated as post-processing refinement options. The process is tested on simulated datasets, and validated with sensor datasets obtained from RP Flight Systems, Inc