Generalized Hamming Distance

Many problems in information retrieval and related fields depend on a reliable measure of the distance or similarity between objects that, most frequently, are represented as vectors. This paper considers vectors of bits. Such data structures implement entities as diverse as bitmaps that indicate the occurrences of terms and bitstrings indicating the presence of edges in images. For such applications, a popular distance measure is the Hamming distance. The value of the Hamming distance for information retrieval applications is limited by the fact that it counts only exact matches, whereas in information retrieval, corresponding bits that are close by can still be considered to be almost identical. We define a Generalized Hamming distance that extends the Hamming concept to give partial credit for near misses, and suggest a dynamic programming algorithm that permits it to be computed efficiently. We envision many uses for such a measure. In this paper we define and prove some basic properties of the Generalized Hamming distance, and illustrate its use in the area of object recognition. We evaluate our implementation in a series of experiments, using autonomous robots to test the measure's effectiveness in relating similar bitstrings.     

An overhead reduction technique for mega-state compression schemes

Many of the most effective compression methods involve complicated models. Unfortunately, as model complexity increases, so does the cost of storing the model itself. This paper examines a method to reduce the amount of storage needed to represent a Markov model with an extended alphabet, by applying a clustering scheme that brings together similar states. Experiments run on a variety of large natural language texts show that much of the overhead of storing the model can be saved at the cost of a very small loss of compression efficiency.     

Emotional experience, expression, and regulation of high-quality Japanese elementary school teachers

The present study investigates the emotional experience, expression, and regulation processes of high-quality Japanese elementary school teachers while they interact with children, in terms of teachers’ emotional competence. Qualitative analysis of interview data demonstrated that teachers had various emotional experiences including self-elicited negative emotions. The major expression patterns were identified as direct staging and the suppression of emotions. Teachers considered emotion expression in front of children as a skill, and their emotion regulation processes involved considering various purposes, appropriately using emotion expression, and ideal teacher images. The findings suggest that high-quality teachers effectively use emotional competence in teaching.     

Scaling Performance Assessments: A Comparison of One-Parameter and Two-Parameter Partial Credit Models

In one study, parameters were estimated for constructed-response (CR) items in 8 tests from 4 operational testing programs using the l-parameter and 2- parameter partial credit (IPPC and 2PPC) models. Where multiple-choice (MC) items were present, these models were combined with the 1-parameter and 3-parameter logistic (IPL and 3PL) models, respectively. We found that item fit was better when the 2PPC model was used alone or with the 3PL model. Also, the slopes of the CR and MC items were found to differ substantially. In a second study, item parameter estimates produced using the IPL-IPPC and 3PL-2PPC model combinations were evaluated for fit to simulated data generated using true parameters known to fit one model combination or ttle other. The results suggested that the more flexible 3PL-2PPC model combination would produce better item fit than the IPL-1PPC combination.     

Concurrent and Separate Grade-Groups Linking Procedures for Vertical Scaling

Reading and Mathematics tests of multiple-choice items for grades Kindergarten through 9 were vertically scaled using the three-parameter logistic model and two different scaling procedures: concurrent and separate by grade groups. Item parameters were estimated using Markov chain Monte Carlo methodology while fixing the grade 4 population abilities to have a standard normal distribution. For the separate grade-groups scaling, grade groupings were linked using the Stocking and Lord test characteristic curve procedure. Abilities were estimated using the maximum-likelihood method. In either content area, scatterplots of item difficulty, discrimination, and ability estimates from the two methods showed consistently strong linear relationships. However, as grade deviated from the base grade of four, the best-fit linear line through the pairs of item discriminations started to rotate away from the identity line. This indicated the discrimination estimates from the separate grade-groups procedure for extreme grades to be, on average, higher than those from the concurrent analysis. The study also observed some systematic change in score variability across grades. In general, the two vertical scaling approaches yielded similar results at more grades in Reading than in Mathematics.     

How prosody marks shifts in footing in classroom discourse

Prosody refers to features of speech such as intonation, volume and pace. In this paper, we examine teacher–student dialogue in an English lesson at a secondary school in England, using Conversation Analysis notation to mark features of prosody. We also make connections with Goffman's theoretical concept of footing. We show that, within an episode of teacher-led plenary discourse, prosody may be used to signal shifts in footing between different kinds of pedagogic activity. We identify: (i) teacher-led IRF (Initiation–Response–Feedback) discussion; (ii) the teacher's modelling of exploratory talk; (iii) a shift to instruction-giving. If teachers are able to model the enquiring tone of exploratory talk, they may in turn encourage more thoughtful contributions from students.     

Evaluation of a static stretching intervention on vascular endothelial function and arterial stiffness

Purpose: Maintenance and enhancement of vascular endothelial function contribute to the prevention of cardiovascular disease and prolong a healthy life expectancy. Given the reversible nature of vascular endothelial function, interventions to improve this function might prevent arteriosclerosis. Accordingly, we studied the effects of a 6-month static stretching intervention on vascular endothelial function (reactive hyperaemia peripheral arterial tonometry index: RH-PAT index) and arterial stiffness (brachial-ankle pulse wave velocity: baPWV) and investigated the reversibility of these effects after a 6-month detraining period following intervention completion. Methods: The study evaluated 22 healthy, non-smoking, premenopausal women aged ≥40 years. Subjects were randomly assigned to the full-intervention (n?=?11; mean age: 48.6?±?2.8 years) or a half-intervention that included a control period (n?=?11; mean age: 46.9?±?3.6 years). Results: Body flexibility and vascular endothelial function improved significantly after 3 months of static stretching. In addition to these improvements, arterial stiffness improved significantly after a 6-month intervention. However, after a 6-month detraining period, vascular endothelial function, flexibility, and arterial stiffness all returned to preintervention conditions, demonstrating the reversibility of the obtained effects. Conclusion: A 3-month static stretching intervention was found to improve vascular endothelial function, and an additional 3-month intervention also improved arterial stiffness. However, these effects were reversed by detraining.     

Simple Bayesian Model for Bitmap Compression

Bitmaps are a useful, but storage voracious, component of many information retrieval systems. Earlier efforts to compress bitmaps were based on models of bit generation, particularly Markov models. While these permitted considerable reduction in storage, the short memory of Markov models may limit their compression efficiency. In this paper we accept the state orientation of Markov models, but introduce a Bayesian approach to assess the state; the analysis is based on data accumulating in a growing window. The paper describes the details of the probabilistic assumptions governing the Bayesian analysis, as well as the protocol for controlling the window that receives the data. We find slight improvement over the best performing strictly Markov models.