In this paper, we present a methodology and techniques for generating cycle-accurate macro-models for registertransfer (RT)-level power analysis. The proposed macro-model predicts not only the cycle-by-cycle power consumption of a module, but also the moving average of power consumption and the power profile of the module over time. We propose an exact power function and approximation steps to ...

Osteoporosis is a common disorder characterised mainly by low bone mineral density (BMD), and leading to an increased risk of fracture. We have developed a new device that estimates BMD from ordinary hand radiographs. A crucial element of this method is the reconstruction of the metacarpals. This paper describes how this was solved using the Active Shape Model (ASM). Standard ASM is unable to l...

MzScheme’s continuation marks provide a flexible mechanism for implementing a number of useful language features and tools. We demonstrate the simplicity and utility of continuation marks by adapting them for JavaScript as frame-based stack marks using the Rhino implementation, showing a simple model of their behavior, and using them to build a toy debugger. Along the way, we discover a few int...

this paper presents a macro model to predict unreinforced masonry structures in plane behavior. the model is based on the concept of multilaminate theory. in the past, the method has been used to model behavior of soil, disregarding the cohesion and the tensile strength. regarding its mathematical base, and the possibility of applying in other cases, this method is used to predict the ultimate ...

This paper describes a SAS" macro for the assessing local influence in regression analysis with censored data. The macro allows one to identify those observations that have the greatest local influence on the estimates of the parameters or functions of the parameters of one's model.

An extension of macro tree transducers is introduced with the capability of states to return multiple trees at the same time. Under call-by-value semantics, the new model is strictly more expressive than call-by-value macro tree transducers, and moreover, it has better closure properties under composition.