BACKGROUND The localized form of granuloma annulare is usually self-limiting, resolving within 2 years. Generalized granuloma annulare, on the other hand, runs a protracted course, with spontaneous resolution being rare. It is also characterized by a later age of onset, an increased incidence of diabetes mellitus, poor response to therapy, and an increased prevalence of HLA Bw35. OBJECTIVE To...

This paper considers the problem of a generalized model for conflict analysis and resolution. Such a model would be helpful in analyzing and resolving conflict in disputes in both government and industry, where disputes and negotiations about various issues are the norm. The issue here is how to model a combination of situations among agents i) where there are disagreements leading to a conflic...

A new generalized unsupervised competitive learning rule is introduced for adaptive scalar quantization. The rule, called generalized Boundary Adaptation Rule (BARr), minimizes r-th power law distortion Dr in the high resolution case. It is shown by simulations that a fast version of BARr outperforms generalized Lloyd I in minimizing D1 (mean absolute error) and D2 (mean squared error) distorti...

Recognition and classification of Power Quality Distorted Signals (PQDSs) in power systems is an essential duty. One of the noteworthy issues in Power Quality Analysis (PQA) is identification of distorted signals using an efficient scheme. This paper recommends a Time–Frequency Analysis (TFA), for extracting features, so-called "hybrid approach", using incorporation of Multi Resolution Analysis...

Increasing demand for multimedia applications (MMAs) by general-purpose processor (GPP) users leads architects to merge multimedia processing capability into GPPs. To develop a GPP providing high quality multimedia services as well as high performance general computing, thorough understanding of the characteristics of both types of applications is fundamental. This paper presents an comprehensi...

A new generalized unsupervised competitive learning rule is introduced for adaptive scalar quan-tization. The rule, called generalized Boundary Adaptation Rule (BAR r), minimizes r-th power law distortion D r in the high resolution case. It is shown by simulations that a fast version of BAR r outperforms generalized Lloyd I in minimizing D 1 (mean absolute error) and D 2 (mean squared error) di...

• Learned Image Compression Generalized Octave Convolution Outperforms the state-of-the-art deep learning-based methods and traditional codecs such as VVC Recently, image compression approaches based on learning have gradually outperformed existing standards including BPG intra coding. In particular, application of context-adaptive entropy model significantly improves rate-distortion (R-D) perf...

in this paper, we introduce and study the notion of precompacttopological generalized groups and some new results are given.

given a mapping $f:xto x$ we naturally associate to it a monotonic map $gg_f:exp xto exp x$ from the power set of $x$ into itself, thus inducing a generalized topology on $x$. in this paper we investigate some properties of generalized topologies which are defined by such a procedure.