Unattended network operations technology assessment study. Technical support for defining advanced satellite systems concepts

The results are summarized of an unattended network operations technology assessment study for the Space Exploration Initiative (SEI). The scope of the work included: (1) identified possible enhancements due to the proposed Mars communications network; (2) identified network operations on Mars; (3) performed a technology assessment of possible supporting technologies based on current and future approaches to network operations; and (4) developed a plan for the testing and development of these technologies. The most important results obtained are as follows: (1) addition of a third Mars Relay Satellite (MRS) and MRS cross link capabilities will enhance the network's fault tolerance capabilities through improved connectivity; (2) network functions can be divided into the six basic ISO network functional groups; (3) distributed artificial intelligence technologies will augment more traditional network management technologies to form the technological infrastructure of a virtually unattended network; and (4) a great effort is required to bring the current network technology levels for manned space communications up to the level needed for an automated fault tolerance Mars communications network

Improving expertise-sensitive help systems

Given the complexity and functionality of today’s software, task-specific, system-suggested help could be beneficial for users. Although system-suggested help assists users in completing their tasks quickly, user response to unsolicited advice from their applications has been lukewarm. One such problem is lack of knowledge of system-suggested help about the user’s expertise with the task they are currently doing. This thesis examines the possibility of improving system-suggested help by adding knowledge about user expertise into the help system and eventually designing an expertise-sensitive help system. An expertise-sensitive help system would detect user expertise dynamically and regularly so that systems could recommend help overtly to novices, subtly to average and poor users, and not at all to experts. This thesis makes several advances in this area through a series of four experiments. In the first experiment, we show that users respond differently to help interruptions depending on their expertise with a task. Having established that user response to helpful interruptions varies with expertise level, in the second experiment we create a four-level classifier of task expertise with an accuracy of 90%. To present helpful interruptions differently to novice, poor, and average users, we need to design three interrupting notifications that vary in their attentional draw. In experiment three, we investigate a number of options and choose three icons. Finally, in experiment four, we integrate the expertise model and three interrupting notifications into an expertise-sensitive system-suggested help program, and investigate the user response. Together, these four experiments show that users value helpful interruptions when their expertise with a task is low, and that an expertise-sensitive help system that presents helpful interruptions with attentional draw that matches user expertise is effective and valuable.&#8195

The 1990 progress report and future plans

This document describes the progress and plans of the Artificial Intelligence Research Branch (RIA) at ARC in 1990. Activities span a range from basic scientific research to engineering development and to fielded NASA applications, particularly those applications that are enabled by basic research carried out at RIA. Work is conducted in-house and through collaborative partners in academia and industry. Our major focus is on a limited number of research themes with a dual commitment to technical excellence and proven applicability to NASA short, medium, and long-term problems. RIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at JPL and AI applications groups at all NASA centers

Making intelligent systems team players: Case studies and design issues. Volume 1: Human-computer interaction design

Initial results are reported from a multi-year, interdisciplinary effort to provide guidance and assistance for designers of intelligent systems and their user interfaces. The objective is to achieve more effective human-computer interaction (HCI) for systems with real time fault management capabilities. Intelligent fault management systems within the NASA were evaluated for insight into the design of systems with complex HCI. Preliminary results include: (1) a description of real time fault management in aerospace domains; (2) recommendations and examples for improving intelligent systems design and user interface design; (3) identification of issues requiring further research; and (4) recommendations for a development methodology integrating HCI design into intelligent system design

Toward a Generic Framework for Ubiquitous System

International audienceIn this paper we present a beginning work about industrial applications using WEB technologies. Systems to study are, for example, robot arms in factories, Heating Ventilation and Air-Conditioning (HVAC) systems for commercial center or buildings, water distribution networks or power management consumption systems of corporate. WEB technologies give us new opportunities to collect the data, to analyze correlations of signals and external events, and finally to change in "soft real-time" the parameters of the managed system. But these applications can be strongly influenced by the behaviour of the communication network and its reliability. We describe the key points that we will explore in our further work

Field Guide for Designing Human Interaction with Intelligent Systems

The characteristics of this Field Guide approach address the problems of designing innovative software to support user tasks. The requirements for novel software are difficult to specify a priori, because there is not sufficient understanding of how the users' tasks should be supported, and there are not obvious pre-existing design solutions. When the design team is in unfamiliar territory, care must be taken to avoid rushing into detailed design, requirements specification, or implementation of the wrong product. The challenge is to get the right design and requirements in an efficient, cost-effective manner. This document's purpose is to describe the methods we are using to design human interactions with intelligent systems which support Space Shuttle flight controllers in the Mission Control Center at NASA/Johnson Space Center. Although these software systems usually have some intelligent features, the design challenges arise primarily from the innovation needed in the software design. While these methods are tailored to our specific context, they should be extensible, and helpful to designers of human interaction with other types of automated systems. We review the unique features of this context so that you can determine how to apply these methods to your project Throughout this Field Guide, goals of the design methods are discussed. This should help designers understand how a specific method might need to be adapted to the project at hand

CERN openlab Whitepaper on Future IT Challenges in Scientific Research

This whitepaper describes the major IT challenges in scientific research at CERN and several other European and international research laboratories and projects. Each challenge is exemplified through a set of concrete use cases drawn from the requirements of large-scale scientific programs. The paper is based on contributions from many researchers and IT experts of the participating laboratories and also input from the existing CERN openlab industrial sponsors. The views expressed in this document are those of the individual contributors and do not necessarily reflect the view of their organisations and/or affiliates

Constructing Reliable Computing Environments on Top of Amazon EC2 Spot Instances

Cloud provider Amazon Elastic Compute Cloud (EC2) gives access to resources in the form of virtual servers, also known as instances. EC2 spot instances (SIs) offer spare computational capacity at steep discounts compared to reliable and fixed price on-demand instances. The drawback, however, is that the delay in acquiring spots can be incredible high. Moreover, SIs may not always be available as they can be reclaimed by EC2 at any given time, with a two-minute interruption notice. In this paper, we propose a multi-workflow scheduling algorithm, allied with a container migration-based mechanism, to dynamically construct and readjust virtual clusters on top of non-reserved EC2 pricing model instances. Our solution leverages recent findings on performance and behavior characteristics of EC2 spots. We conducted simulations by submitting real-life workflow applications, constrained by user-defined deadline and budget quality of service (QoS) parameters. The results indicate that our solution improves the rate of completed tasks by almost 20%, and the rate of completed workflows by at least 30%, compared with other state-of-the-art algorithms, for a worse-case scenarioinfo:eu-repo/semantics/publishedVersio