Recommendations in a heterogeneous service environment

This paper presents novel algorithms which are able to generate recommendations within a heterogeneous service environment. In this work explicitly set preferences as well as implicitly logged viewing behavior are employed to generate recommendations for Digital Video Broadcast (DVB) content. This paper also discusses the similarity between the DVB genres and YouTube categories. In addition it presents results to show the comparison between well known collaborative filtering methods. The outcome of this comparison study is used to identify the most suitable filtering method to use in the proposed environment. Finally the paper presents a novel Personal Program Guide (PPG), which is used as a tool to visualize the generated recommendations within a heterogeneous service environment. This PPG is also capable of showing the linear DVB content and the non-linear YouTube videos in a single view.     

A methodology for user directed search in evolutionary design

A designer should be able to express their intentions with a design tool. This work describes a methodology that enables the architect to directly interact with the encoding of designs they find aesthetically pleasing. Broadening interaction beyond simple evaluation increases the amount of feedback and bias a user can apply to the search. Increased feedback will have the effect of directing the algorithm to more fruitful areas of the search space. We conduct trials on two interfaces for making localised changes to a design in order to evaluate if the user is capable of directing search. In addition, an examination of the locality of changes made by the users provides an insight into how they explore the search space. The results show that a suitably designed interface is capable of directing search and that the participants used different magnitudes of change during directed search.     

How do clinicians reconcile conditions and medications? The cognitive context of medication reconciliation

Medication omissions and dosing failures are frequent during transitions in patient care. Medication reconciliation (MR) requires bridging discrepancies in a patient’s medical history as a setting for care changes. MR has been identified as vulnerable to failure, and a clinician’s cognition during MR remains poorly described in the literature. We sought to explore cognition in MR tasks. Specifically, we sought to explore how clinicians make sense of conditions and medications. We observed 24 anesthesia providers performing a card-sorting task to sort conditions and medications for a fictional patient. We analyzed the spatial properties of the data using statistical methods. Most of the participants (58%) arranged the medications along a straight line (p < 0.001). They sorted medications by organ systems (Friedman’s χ ²(54) = 325.7, p < 0.001). These arrangements described the clinical correspondence between each two medications (Wilcoxon W = 192.0, p < 0.001). A cluster analysis showed that the subjects matched conditions and medications related to the same organ system together (Wilcoxon W = 1917.0, p < 0.001). We conclude that the clinicians commonly arranged the information into two groups (conditions and medications) and assigned an internal order within these groups, according to organ systems. They also matched between conditions and medications according to similar criteria. These findings were also supported by verbal protocol analysis. The findings strengthen the argument that organ-based information is pivotal to a clinician’s cognition during MR. Understanding the strategies and heuristics, clinicians employ through the MR process may help to develop practices to promote patient safety.     

Implementing knowledge building: Analysis of a face‐to‐face discussion by grade‐four students

Abstract:

Researchers say that teachers can implement an educational innovation without adhering to the principles underpinning its design. Such principles may not adequately take typical classroom conditions into account. The goal of this study was to explore tensions between attempts to implement the principles underpinning knowledge building and the influence of contextual factors that compete for the teacher's attention. To this end, we discuss five excerpts from a discussion of the motion of spinning tops held by a class of Grade‐4 students, coming at the end of a five‐month implementation of knowledge building. Each excerpt is followed first by the teacher's perspective and then by the researcher's perspective. Our analysis highlights two tensions that constrain agency, arising from the students’ need for social development and their need to learn scientific concepts. We offer some suggestions for addressing these tensions.     

Hybrid modeling to predict the economic feasibility of mining undiscovered porphyry copper deposits

Few studies attempt to model the economic feasibility of mining undiscovered mineral resources given the sparseness of data; and the coupled, nonlinear, spatial, and temporal relationships among variables. In this study, a type of unsupervised artificial neural network, called a self-organized map (SOM), is trained using data from 203 porphyry copper deposit sites across the world. The sparse data set includes one dependent variable indicating the economic feasibility, and seventy two independent variables from categories describing characteristics of mining method, metallurgy, dimensions, economics, and amount. Analysis of component planes reveals relations and strengths in the underlying SOM multivariate density function which are used to impute missing values. Application of the Davies–Bouldin criteria to k-means clusters of SOM neurons identified 14 regional economic resource units (conceptual models). A best subsets approach applied to median values from these models identified 20 statistically significant combinations of variables. During model fitting by the multiple linear regression technique, only four of the empirical models had variables that were all significant at the 95% confidence level. The best model explained 98% of the variability in economic feasibility and incorporated variables describing distance to natural gas, road, and water; and the total amount of resources. This model was independently validated by comparing predictions of economic feasibility at 68 mine sites not included in the training data. Eighty-four percent of the reported economic feasibility is correctly predicted with 8 false positives and 2 false negative. We demonstrate the application of this model to a permissive copper porphyry tract that crosses a portion of British Columbia and Yukon territories of Canada. The proposed hybrid approach provides an alternative modeling paradigm for translating estimates of contained metal into meaningful societal measures.