Case-Based Learning: Predictive Features in Indexing

Interest in psychological experimentation from the Artificial Intelligence community often takes the form of rigorous post-hoc evaluation of completed computer models. Through an example of our own collaborative research, we advocate a different view of how psychology and AI may be mutually relevant, and propose an integrated approach to the study of learning in humans and machines. We begin with the problem of learning appropriate indices for storing and retrieving information from memory. From a planning task perspective, the most useful indices may be those that predict potential problems and access relevant plans in memory, improving the planner's ability to predict and avoid planning failures. This predictive features hypothesis is then supported as a psychological claim, with results showing that such features offer an advantage in terms of the selectivity of reminding because they more distinctively characterize planning situations where differing plans are appropriate.We present a specific case-based model of plan execution, RUNNER, along with its indices for recognizing when to select particular plans—appropriateness conditions—and how these predictive indices serve to enhance learning. We then discuss how this predictive features claim as implemented in the RUNNER model is then tested in a second set of psychological studies. The results show that learning appropriateness conditions results in greater success in recognizing when a past plan is in fact relevant in current processing, and produces more reliable recall of the related information. This form of collaboration has resulted in a unique integration of computational and empirical efforts to create a model of case-based learning.     

Can twice weekly hemodialysis expand patient access under resource constraints?

The convention of prescribing hemodialysis on a thrice weekly schedule began empirically when it seemed that this frequency was convenient and likely to treat symptoms for a majority of patients. Later, when urea was identified as the main target and marker of clearance, studies supported the prevailing notion that thrice weekly dialysis provided appropriate clearance of urea. Today, national guidelines on hemodialysis from most countries recommend patients receive at least thrice weekly therapy. However, resource constraints in low‐ and middle‐income countries (LMIC) have resulted in a substantial proportion of patients using less frequent hemodialysis in these settings. Observational studies of patients on twice weekly dialysis show that twice weekly therapy has noninferior survival rates compared with thrice weekly therapy. In fact, models of urea clearance also show that twice weekly therapy can meet urea clearance “targets” if patients have significant residual function or if they follow a protein‐restricted diet, as may be common in LMIC. Greater reliance on twice weekly therapy, at least at the start of hemodialysis, therefore has potential to reduce health care costs and increase access to renal replacement therapy in low‐resource settings; however, randomized control trials are needed to better understand long‐term outcomes of twice versus thrice weekly therapy.     

Comparison of paper-and-pencil versus Web administration of the Youth Risk Behavior Survey (YRBS): Participation,data quality,and perceived privacy and anonymity

The Youth Risk Behavior Surveillance System (YRBSS) monitors priority health-risk behaviors among US high school students. To better understand the ramifications of changing the YRBSS from paper-and-pencil to Web administration, in 2008 the Centers for Disease Control and Prevention conducted a study comparing these two modes of administration. Eighty-five schools in 15 states agreed to participate in the study. Within each participating school, four classrooms of students in grades 9 or 10 were randomly assigned to complete the Youth Risk Behavior Survey questionnaire in one of four conditions (in-class paper-and-pencil, in-class Web without programmed skip patterns, in-class Web with programmed skip patterns, and “on your own” Web without programmed skip patterns). Findings included less missing data for the paper-and-pencil condition (1.5% vs. 5.3%, 4.4%, 6.4%; p < .001), less perceived privacy and anonymity among respondents for the in-class Web conditions, and a lower response rate for the “on your own” Web condition than for in-class administration by either mode (28.0% vs. 91.2%, 90.1%, 91.4%; p < .001). Although Web administration might be useful for some surveys, these findings do not favor the use of a Web survey for the YRBSS.     

Factors influencing teachers’ intention to use technology: Model development and test

Among the key players in any effective integration of technology in teaching and learning is the teacher. Despite the research that has been conducted to examine the factors that explain teachers’ intention to use technology, few have developed a model to statistically explain the interactions among these factors and how they influence teachers’ intention to use technology. Five variables (perceived usefulness, perceived ease of use, subjective norm, facilitating conditions, and attitude towards use) and behavioural intention to use technology were used to build a research model in this study and structural equation modelling was used for parameter estimation and model testing. Self-reported data were gathered from 592 teachers from schools in Singapore. Results revealed a good model fit and of the nine hypotheses formulated in this study, eight were supported. Subjective norm was not found to be a significant influence on teachers’ intention to use technology while the other four variables were.     

Indoor robot gardening: design and implementation

This paper describes the architecture and implementation of a distributed autonomous gardening system with applications in urban/indoor precision agriculture. The garden is a mesh network of robots and plants. The gardening robots are mobile manipulators with an eye-in-hand camera. They are capable of locating plants in the garden, watering them, and locating and grasping fruit. The plants are potted cherry tomatoes enhanced with sensors and computation to monitor their well-being (e.g. soil humidity, state of fruits) and with networking to communicate servicing requests to the robots. By embedding sensing, computation, and communication into the pots, task allocation in the system is de-centrally coordinated, which makes the system scalable and robust against the failure of a centralized agent. We describe the architecture of this system and present experimental results for navigation, object recognition, and manipulation as well as challenges that lie ahead toward autonomous precision agriculture with multi-robot teams.     

Effects of combined wrist deviation and forearm rotation on discomfort score

The aim of the study was to examine the pattern of the change in discomfort for combined wrist deviation and forearm rotation as joint angles increased away from neutral in a repetitive task. There were five levels of wrist deviation (neutral, 35% and 55% of the range of motion (ROM) in radial and ulnar deviation) and five levels of forearm rotation (neutral, 30% and 60% of the ROM in pronation and supination). Twenty-five participants performed a repetitive flexion task with a force of 10 N +/- 1 N at a frequency of 15 exertions per min, with replication after 1 week for six of the participants. A visual analogue scale was used for recording the discomfort scores. Repeated measures analysis of covariance with the Greenhouse-Geisser correction, where necessary, was used on transformed values of the discomfort scores. Grip test endurance time at 50% of maximum voluntary contraction was included as a covariate. Wrist deviation (p = 0.007) and forearm rotation (p = 0.001) were found to have significant effects. Interactions of the main factors were not significant and nor was the covariate. Quadratic regression equations were derived and were used to generate iso-discomfort contours, which show a useful area of low discomfort around the central neutral zone of wrist postures, but with steep increases in discomfort at the extreme combinations of wrist ulnar/radial deviation with forearm pronation/supination. Discomfort equations and contours, showing wrist and forearm postures, which are either acceptable or potentially injurious, are useful for the design of industrial tools, machine controls and workspaces. Reference to these can help to reduce the risk of musculoskeletal injury associated with the tasks or tools by avoiding poor postures with unacceptable deviations from neutral posture.     

A Survey of UAS Technologies for Command, Control, and Communication (C3)

The integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) presents many challenges including airworthiness certification. As an alternative to the time consuming process of modifying the Federal Aviation Regulations (FARs), guidance materials may be generated that apply existing airworthiness regulations toward UAS. This paper discusses research to assist in the development of such guidance material. The results of a technology survey of command, control, and communication (C3) technologies for UAS are presented. Technologies supporting both line-of-sight and beyond line-of-sight UAS operations are examined. For each, data link technologies, flight control, and air traffic control (ATC) coordination are considered. Existing protocols and standards for UAS and aircraft communication technologies are discussed. Finally, future work toward developing the guidance material is discussed.     

A technique for monitoring SO2 in combustion exhausts: Use of a non-Nernstian sensing element in combination with an upstream catalytic filter

Detection of sulfur dioxide (SO₂) at high temperature (600–750 °C) in the presence of some interferents found in combustion exhausts (NO₂, NO, CO₂, CO, and hydrocarbon (C₃H₆)) is described. The detection scheme involves use of a catalytic filter in front of a non-Nernstian (mixed-potential) sensing element. The catalytic filter was a Ni:Cr powder bed operating at 850 °C, and the sensing elements were pairs of platinum (Pt) and oxide (Ba-promoted copper chromite ((Ba,Cu)_xCr_yO_z) or Sr-modified lanthanum ferrite (LSF)) electrodes on yttria-stabilized zirconia. The Ni:Cr powder bed was capable of reducing the sensing element response to NO₂, NO, CO, and C₃H₆, but the presence of NO₂ or NO (“NO_x”, at 100 ppm by volume) still interfered with the SO₂ response of the Pt–(Ba,Cu)_xCr_yO_z sensing element at 600 °C, causing approximately a 7 mV (20%) reduction in the response to 120 ppm SO₂ and a response equivalent to about 20 ppm SO₂ in the absence of SO₂. The Pt–LSF sensing element, operated at 750 °C, did not suffer from this NO_x interference but at the cost of a reduced SO₂ response magnitude (120 ppm SO₂ yielded 10 mV, in contrast to 30 mV for the Pt-(Ba,Cu)_xCr_yO_z sensing element). The powder bed and Pt–LSF sensing element were operated continuously over approximately 350 h, and the response to SO₂ drifted downward by about 7%, with most of this change occurring during the initial 100 h of operation.