Performance Measures of State Dependent MMPP/M/1 Queue

In this research work we are concerned with single unit server queue queue with Markov Modulated process in Poisson fashion and the service time follow exponential distribution. The system is framed as a state dependent with the arrival process as Markov Modulated input and service is rendered by a single server with variation in service rate based on the intensity of service state of the system. The rate matrix that is essential to compute the stationary probability vector is obtained and various performance measures are computed using matrix method.

Neurophysiological Correlates of Comprehending Emotional Meaning in Context

Although the neurocognitive mechanisms of nonaffective language comprehension have been studied extensively, relatively less is known about how the emotional meaning of language is processed. In this study, electrophysiological responses to affectively positive, negative, and neutral words, presented within nonconstraining, neutral contexts, were evaluated under conditions of explicit evaluation of emotional content (Experiment 1) and passive reading (Experiment 2). In both experiments, a widely distributed Late Positivity was found to be larger to negative than to positive words (a “negativity bias”). In addition, in Experiment 2, a small, posterior N400 effect to negative and positive (relative to neutral) words was detected, with no differences found between N400 magnitudes to negative and positive words. Taken together, these results suggest that comprehending the emotional meaning of words following a neutral context requires an initial semantic analysis that is relatively more engaged for emotional than for nonemotional words, whereas a later, more extended, attention-modulated process distinguishes the specific emotional valence (positive vs. negative) of words. Thus, emotional processing networks within the brain appear to exert a continuous influence, evident at several stages, on the construction of the emotional meaning of language.

Critical sizing of LRU caches with dependent requests

It was recently proved by Jelenković and Radovanović (2004) that the least-recently-used (LRU) caching policy, in the presence of semi-Markov-modulated requests that have a generalized Zipf's law popularity distribution, is asymptotically insensitive to the correlation in the request process. However, since the previous result is asymptotic, it remains unclear how small the cache size can become while still retaining the preceding insensitivity property. In this paper, assuming that requests are generated by a nearly completely decomposable Markov-modulated process, we characterize the critical cache size below which the dependency of requests dominates the cache performance. This critical cache size is small relative to the dynamics of the modulating process, and in fact is sublinear with respect to the sojourn times of the modulated chain that determines the dependence structure.

Critical sizing of LRU caches with dependent requests

It was recently proved by Jelenković and Radovanović (2004) that the least-recently-used (LRU) caching policy, in the presence of semi-Markov-modulated requests that have a generalized Zipf's law popularity distribution, is asymptotically insensitive to the correlation in the request process. However, since the previous result is asymptotic, it remains unclear how small the cache size can become while still retaining the preceding insensitivity property. In this paper, assuming that requests are generated by a nearly completely decomposable Markov-modulated process, we characterize the critical cache size below which the dependency of requests dominates the cache performance. This critical cache size is small relative to the dynamics of the modulating process, and in fact is sublinear with respect to the sojourn times of the modulated chain that determines the dependence structure.