Euclidean distance geometry and applications

Euclidean distance geometry is the study of Euclidean geometry based on the concept of distance. This is useful in several applications where the input data consists of an incomplete set of distances, and the output is a set of points in Euclidean space that realizes the given distances. We survey some of the theory of Euclidean distance geometry and some of the most important applications: molecular conformation, localization of sensor networks and statics.Comment: 64 pages, 21 figure

Using Message Passing Instead of the GOTO Construct

This report describes research conducted at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for this research was provided in part by the Office of Naval Research of the Department of Defense under Contract N00014-75-C-0522.This paper advocates a programming methodology using message passing. Efficient programs are derived for fast exponentiation, merging ordered sequences, and path existence determination in a directed graph. The problems have been proposed by John Reynolds as interesting ones to investigate because they illustrate significant issues in programming. The methodology advocated here is directed toward the production of programs that are intended to execute efficiently in a computing environment with many processors. The absence of the GOTO construct does not seem to be constricting in any respect in the development of efficient programs using the programming methodology advocated here.MIT Artificial Intelligence Laboratory Department of Defense Advanced Research Projects Agenc

Scheduling Markovian PERT networks with maximum-NPV objective.

We examine project scheduling with net-present-value objective and exponential activity durations, using a continuous-time Markov decision chain. Based on a judicious partitioning of the state space, we achieve a significant performance improvement compared to the existing algorithms.Project scheduling; Net present value; Stochastic activity durations; Exponential distribution;

Computer architecture for efficient algorithmic executions in real-time systems: New technology for avionics systems and advanced space vehicles

Improvements and advances in the development of computer architecture now provide innovative technology for the recasting of traditional sequential solutions into high-performance, low-cost, parallel system to increase system performance. Research conducted in development of specialized computer architecture for the algorithmic execution of an avionics system, guidance and control problem in real time is described. A comprehensive treatment of both the hardware and software structures of a customized computer which performs real-time computation of guidance commands with updated estimates of target motion and time-to-go is presented. An optimal, real-time allocation algorithm was developed which maps the algorithmic tasks onto the processing elements. This allocation is based on the critical path analysis. The final stage is the design and development of the hardware structures suitable for the efficient execution of the allocated task graph. The processing element is designed for rapid execution of the allocated tasks. Fault tolerance is a key feature of the overall architecture. Parallel numerical integration techniques, tasks definitions, and allocation algorithms are discussed. The parallel implementation is analytically verified and the experimental results are presented. The design of the data-driven computer architecture, customized for the execution of the particular algorithm, is discussed