10,436 research outputs found
Verification and validation of simulation models
Simulation Models;econometrics
Natural Notation for the Domestic Internet of Things
This study explores the use of natural language to give instructions that
might be interpreted by Internet of Things (IoT) devices in a domestic `smart
home' environment. We start from the proposition that reminders can be
considered as a type of end-user programming, in which the executed actions
might be performed either by an automated agent or by the author of the
reminder. We conducted an experiment in which people wrote sticky notes
specifying future actions in their home. In different conditions, these notes
were addressed to themselves, to others, or to a computer agent.We analyse the
linguistic features and strategies that are used to achieve these tasks,
including the use of graphical resources as an informal visual language. The
findings provide a basis for design guidance related to end-user development
for the Internet of Things.Comment: Proceedings of the 5th International symposium on End-User
Development (IS-EUD), Madrid, Spain, May, 201
Invigorating Vertical Merger Enforcement
This Feature summarizes why and how vertical merger enforcement should be invigorated. In our modern market system, vigorous vertical merger enforcement is a necessity. Strong enforcement is particularly important in markets where economies of scale and network effects lead to barriers to entry and durable market power. Even when there are parallel vertical mergers, the result may well be an anticompetitive reciprocal dealing, coordinated equilibrium rather than intense competition among efficient integrated firms. Stronger enforcement would involve several steps, including recognition that claims of elimination of double marginalization do not deserve to be silver bullets and that behavioral remedies are generally unable to prevent anticompetitive effects
Understanding Evolutionary Potential in Virtual CPU Instruction Set Architectures
We investigate fundamental decisions in the design of instruction set
architectures for linear genetic programs that are used as both model systems
in evolutionary biology and underlying solution representations in evolutionary
computation. We subjected digital organisms with each tested architecture to
seven different computational environments designed to present a range of
evolutionary challenges. Our goal was to engineer a general purpose
architecture that would be effective under a broad range of evolutionary
conditions. We evaluated six different types of architectural features for the
virtual CPUs: (1) genetic flexibility: we allowed digital organisms to more
precisely modify the function of genetic instructions, (2) memory: we provided
an increased number of registers in the virtual CPUs, (3) decoupled sensors and
actuators: we separated input and output operations to enable greater control
over data flow. We also tested a variety of methods to regulate expression: (4)
explicit labels that allow programs to dynamically refer to specific genome
positions, (5) position-relative search instructions, and (6) multiple new flow
control instructions, including conditionals and jumps. Each of these features
also adds complication to the instruction set and risks slowing evolution due
to epistatic interactions. Two features (multiple argument specification and
separated I/O) demonstrated substantial improvements int the majority of test
environments. Some of the remaining tested modifications were detrimental,
thought most exhibit no systematic effects on evolutionary potential,
highlighting the robustness of digital evolution. Combined, these observations
enhance our understanding of how instruction architecture impacts evolutionary
potential, enabling the creation of architectures that support more rapid
evolution of complex solutions to a broad range of challenges
The Galileo PPS expert monitoring and diagnostic prototype
The Galileo PPS Expert Monitoring Module (EMM) is a prototype system implemented on the SUN workstation that will demonstrate a knowledge-based approach to monitoring and diagnosis for the Galileo spacecraft Power/Pyro subsystems. The prototype will simulate an analysis module functioning within the SFOC Engineering Analysis Subsystem Environment (EASE). This document describes the implementation of a prototype EMM for the Galileo spacecraft Power Pyro Subsystem. Section 2 of this document provides an overview of the issues in monitoring and diagnosis and comparison between traditional and knowledge-based solutions to this problem. Section 3 describes various tradeoffs which must be considered when designing a knowledge-based approach to monitoring and diagnosis, and section 4 discusses how these issues were resolved in constructing the prototype. Section 5 presents conclusions and recommendations for constructing a full-scale demonstration of the EMM. A Glossary provides definitions of terms used in this text
Care 3, Phase 1, volume 1
A computer program to aid in accessing the reliability of fault tolerant avionics systems was developed. A simple mathematical expression was used to evaluate the reliability of any redundant configuration over any interval during which the failure rates and coverage parameters remained unaffected by configuration changes. Provision was made for convolving such expressions in order to evaluate the reliability of a dual mode system. A coverage model was also developed to determine the various relevant coverage coefficients as a function of the available hardware and software fault detector characteristics, and subsequent isolation and recovery delay statistics
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