In a binary response regression model, classical residuals are diicult to deene and interpret due to the discrete nature of the response variable. In contrast , Bayesian residuals have continuous-valued posterior distributions which can be graphed to learn about outlying observations. Two deenitions of Bayesian residuals are proposed for binary regression data. Plots of the posterior distributi...

This paper proposes a general associative memory (GAM) system that combines the functions of other typical associative memory (AM) systems. The GAM is a network consisting of three layers: an input layer, a memory layer, and an associative layer. The input layer accepts key vectors, response vectors, and the associative relationships between these vectors. The memory layer stores the input vect...

We present recent progress of high-speed Mach-Zehnder modulator technologies for advanced modulation formats. Multi-level quadrature amplitude modulation signal can be synthesized by using parallel Mach-Zehnder modulators. We can generate complicated multi-level optical signals from binary data streams, where binary modulated signals are vectorially summed in optical circuits. Frequency respons...

The method of generalized estimating equations (GEE) is often used to analyze longitudinal and other correlated response data, particularly if responses are binary. However, few descriptions of the method are accessible to epidemiologists. In this paper, the authors use small worked examples and one real data set, involving both binary and quantitative response data, to help end-users appreciat...

We aim at proposing a Generalized Linear Model (GLM) with binary dependent variable Y , whose link function defined by the Generalized Extreme Value (GEV) distribution. We define this model as GEV regression. The goal of this paper is to overcome the drawbacks shown by the logistic regression in rare events: the probability of rare events is underestimated and the logit link is a symmetric func...

we study the problem of reconstructing binary images from four projections data in a fuzzy environment. given the uncertainly projections,w e want to find a binary image that respects as best as possible these projections. we provide an iterative algorithm based on fuzzy integer programming and linear membership functions.

In phase II cancer trials, tumour response is either the primary or an important secondary endpoint. Tumour response is a binary composite endpoint determined, according to the Response Evaluation Criteria in Solid Tumors, by (1) whether the percentage change in tumour size is greater than a prescribed threshold and (2) (binary) criteria such as whether a patient develops new lesions. Further b...

HOG features are effective for object detection, but their focus on local regions makes them highdimensional features. To reduce the memory required for the HOG features, this paper proposes a new feature, R-HOG, which creates binary codes from the HOG features extracted from two local regions. This approach enables the created binary codes to reflect the relationships between local regions. Co...

Using Spencer-Oatey’s (2004, 2008) Rapport Management approach, this study was conducted to elicit the reprimanding response behavior of native Persian speakers and EFL Learners. The participants of this study were 30 native Persian speakers and 60 EFL learners. To fulfill the purposes of this study, a six-binary situation Interactive Discourse Completion (IDCT) Task was utilized. Emotion Liker...