Microarchitects rely upon simulation to evaluate design alternatives, yet constructing an accurate simulator by hand is a difficult and time-consuming process because simulators are usually written in sequential languages while the system being modeled is concurrent. Structural modeling can mitigate this difficulty by allowing the microarchitect to specify the simulation model in a concurrent, ...

Neural networks are applied to the system identification problems using adaptive algorithms for either parameter or functional estimation of dynamic systems. In this paper the neural networks' sensitivity to input values and connections' weights, is studied. The Reduction-Sigmoid-Amplification (RSA) neurons are introduced and four different models of neural network architecture are proposed and...

A new machine learning framework is introduced in this paper, based on Hidden Markov Model (HMM), designed to provide scheduling in dynamic wireless push systems. In realistic wireless systems, the clients’ intentions change dynamically, hence a cognitive scheduling scheme is needed to estimate the desirability of the connected clients. The proposed scheduling scheme is enhanced with selforgani...

Loops are the largest source of parallelism in many applications. All prior DOALL loop scheduling algorithms such as Self-Scheduling, Guided Self-Scheduling, Trapezoid Self-Scheduling, and Factoring try to achieve workload balance through decreasing chunk sizes. Moreover, they have been analyzed only for shared memory platforms. In this work, the prior loop scheduling methods will be evaluated ...

We present an overview over recent developments of traffic flow models for production networks. Particular emphasis is given to the implementation of service rules for complex systems, involving multiple product types and re entrant loops. A rather general scheduling concept is introduced and demonstrated on some numerical experiments.

This paper investigates the $p$-center location problem on a network in which vertex weights and distances between vertices are uncertain. The concepts of the $alpha$-$p$-center and the expected $p$-center are introduced. It is shown that the $alpha$-$p$-center and the expected $p$-center models can be transformed into corresponding deterministic models. Finally, linear time algorithms for find...

data envelopment analysis (dea) is a technique used to compare efficiency in various sectors such as hospitals, chain stores, and dealerships. it represents a set of linear programming techniques and uses deter-ministic data (inputs and outputs), in stable conditions. the dea technique cannot be used when there is data with indeterministic nature, or when there is an environment with dynamic co...

uncertainty plays a major role in any project evaluation and management process. one of the trickiest parts of any production project work is its cost and time forecasting. since in the initial phases of production projects uncertainty is at its highest level, a reliable method of project scheduling and cash flow generation is vital to help the managers reach successful implementation of the pr...