New techniques for superscalar instruction issuing are presented. It is shown that the data dependency check for both in-order and out-of-order issuing can be performed in O(logw) gate delay using O(w2) primitive gates, where w is the size of the instruction buffer. Furthermore, we present a new counting based technique for assigning instructions to resources. It requires a delay of O(logw+logm...

This paper presents a novel approach for identifying non-robustly unsensitizable paths using the bounded gate delay model. It is shown that many non-robust paths will remain undetected unless the delay values are calculated at the path level rather than considering calculations at the circuit level bounded delay. As an initial step a canonical data structure is generated where each circuit path...

Knowledge Discovery in Databases (KDD), or Data Mining is used to discover interesting or useful patterns and relationships in data, with an emphasis on large volume of observational databases. Among many other types of information (knowledge) that can be discovered in data, patterns that are expressed in terms of features are popular because they can be understood and used directly by people. ...

In this summary we present a method for modeling the distortion-rate characteristics of compressed video sequences. It is assumed that the source coders rely on motion-compensated prediction, and thus error propagation will contribute signiicantly to the degradation of the reconstructed video. Additionally , it is assumed that the information in each video frame can be prioritized and that sour...

with the rapid growth of indoor wireless communication systems, the need to accurately model radio wave propagation inside the building environments has increased. many site-specific methods have been proposed for modeling indoor radio channels. among these methods, the ray tracing algorithm and the finite-difference time domain (fdtd) method are the most popular ones. the ray tracing approach ...

Parameter estimation of large bio-pathway models is an important and difficult problem. To reduce the prohibitive computational cost, one approach is to decompose a large model into components and estimate their parameters separately. However, the decomposed components often share common parts that may have conflicting parameter estimates, as they are computed independently within each componen...

Parameter estimation of large bio-pathway models is an important and difficult problem. To reduce the prohibitive computational cost, one approach is to decompose a large model into components and estimate their parameters separately. However, the decomposed components often share common parts that may have conflicting parameter estimates, as they are computed independently within each componen...

8 This project presents a machine learning based fatigue crack sensor 9 evaluation scheme without using a physical model. A supervised binary 10 classification problem is defined to distinguish damaged steel specimens 11 from intact specimens. Sets of time-series wave propagation data collected 12 by the fatigue crack sensor are utilized for the proposed scheme. In order to 13 apply supervised ...