A Study of Feature Extraction Using Divergence Analysis of Texture Features

An empirical study of texture analysis for feature extraction and classification of high spatial resolution remotely sensed imagery (10 meters) is presented in terms of specific land cover types. The principal method examined is the use of spatial gray tone dependence (SGTD). The SGTD method reduces the gray levels within a moving window into a two-dimensional spatial gray tone dependence matrix which can be interpreted as a probability matrix of gray tone pairs. Haralick et al (1973) used a number of information theory measures to extract texture features from these matrices, including angular second moment (inertia), correlation, entropy, homogeneity, and energy. The derivation of the SGTD matrix is a function of: (1) the number of gray tones in an image; (2) the angle along which the frequency of SGTD is calculated; (3) the size of the moving window; and (4) the distance between gray tone pairs. The first three parameters were varied and tested on a 10 meter resolution panchromatic image of Maryville, Tennessee using the five SGTD measures. A transformed divergence measure was used to determine the statistical separability between four land cover categories forest, new residential, old residential, and industrial for each variation in texture parameters

Designing electronic collaborative learning environments

Electronic collaborative learning environments for learning and working are in vogue. Designers design them according to their own constructivist interpretations of what collaborative learning is and what it should achieve. Educators employ them with different educational approaches and in diverse situations to achieve different ends. Students use them, sometimes very enthusiastically, but often in a perfunctory way. Finally, researchers study them and—as is usually the case when apples and oranges are compared—find no conclusive evidence as to whether or not they work, where they do or do not work, when they do or do not work and, most importantly, why, they do or do not work. This contribution presents an affordance framework for such collaborative learning environments; an interaction design procedure for designing, developing, and implementing them; and an educational affordance approach to the use of tasks in those environments. It also presents the results of three projects dealing with these three issues

"Author! Author!" : Shakespeare and biography

Original article can be found at: http://www.informaworld.com/smpp/title~content=t714579626~db=all Copyright Informa / Taylor & Francis Group. DOI: 10.1080/17450910902764454Since 1996, not a year has passed without the publication of at least one Shakespeare biography. Yet for many years the place of the author in the practice of understanding literary works has been problematized, and even on occasions eliminated. Criticism reads the “works”, and may or may not refer to an author whose “life” contributed to their meaning. Biography seeks the author in the works, the personality that precedes the works and gives them their characteristic shape and meaning. But the form of literary biography addresses the unusual kind of “life” that puts itself into “works”, and this is particularly challenging where the “works” predominate massively over the salient facts of the “life”. This essay surveys the current terrain of Shakespeare biography, and considers the key questions raised by the medium: can we know anything of Shakespeare's “personality” from the facts of his life and the survival of his works? What is the status of the kind of speculation that inevitably plays a part in biographical reconstruction? Are biographers in the end telling us as much about themselves as they tell us about Shakespeare?Peer reviewe

A blind detection of a large, complex, Sunyaev--Zel'dovich structure

We present an interesting Sunyaev-Zel'dovich (SZ) detection in the first of the Arcminute Microkelvin Imager (AMI) 'blind', degree-square fields to have been observed down to our target sensitivity of 100{\mu}Jy/beam. In follow-up deep pointed observations the SZ effect is detected with a maximum peak decrement greater than 8 \times the thermal noise. No corresponding emission is visible in the ROSAT all-sky X-ray survey and no cluster is evident in the Palomar all-sky optical survey. Compared with existing SZ images of distant clusters, the extent is large (\approx 10') and complex; our analysis favours a model containing two clusters rather than a single cluster. Our Bayesian analysis is currently limited to modelling each cluster with an ellipsoidal or spherical beta-model, which do not do justice to this decrement. Fitting an ellipsoid to the deeper candidate we find the following. (a) Assuming that the Evrard et al. (2002) approximation to Press & Schechter (1974) correctly gives the number density of clusters as a function of mass and redshift, then, in the search area, the formal Bayesian probability ratio of the AMI detection of this cluster is 7.9 \times 10^4:1; alternatively assuming Jenkins et al. (2001) as the true prior, the formal Bayesian probability ratio of detection is 2.1 \times 10^5:1. (b) The cluster mass is MT,200 = 5.5+1.2\times 10^14h-1M\odot. (c) Abandoning a physical model with num- -1.3 70 ber density prior and instead simply modelling the SZ decrement using a phenomenological {\beta}-model of temperature decrement as a function of angular distance, we find a central SZ temperature decrement of -295+36 {\mu}K - this allows for CMB primary anisotropies, receiver -15 noise and radio sources. We are unsure if the cluster system we observe is a merging system or two separate clusters.Comment: accepted MNRAS. 12 pages, 9 figure

LMDA New & Noteworthy, May 2020

Contents include: #LMDA2020 // Conference Countdown; Managing Life and Work in the Time of COVID-19: Thoughts from the LMDA Executive Committee; The Kennedy Center Dramaturgy Intensive: Learn from the best. Work with the best; Regional Events; Your Dramaturgy Ad Here; Pandemic Response: Resources for Artists in the U.S. and Canada (link).https://soundideas.pugetsound.edu/lmdanewsletter/1033/thumbnail.jp