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

A failure diagnosis and impact assessment prototype for Space Station Freedom

NASA is investigating the use of advanced automation to enhance crew productivity for Space Station Freedom in numerous areas, one being failure management. A prototype is described that diagnoses failure sources and assesses the future impacts of those failures on other Freedom entities

IEEE 802.11 user fingerprinting and its applications for intrusion detection

AbstractEasy associations with wireless access points (APs) give users temporal and quick access to the Internet. It needs only a few seconds to take their machines to hotspots and do a little configuration in order to have Internet access. However, this portability becomes a double-edged sword for ignorant network users. Network protocol analyzers are typically developed for network performance analysis. Nonetheless, they can also be used to reveal user’s privacy by classifying network traffic. Some characteristics in IEEE 802.11 traffic particularly help identify users. Like actual human fingerprints, there are also unique traffic characteristics for each network user. They are called network user fingerprints, by tracking which more than half of network users can be connected to their traffic even with medium access control (MAC) layer pseudonyms. On the other hand, the concept of network user fingerprint is likely to be a powerful tool for intrusion detection and computer/digital forensics. As with actual criminal investigations, comparison of sampling data to training data may increase confidence in criminal specification. This article focuses on a survey on a user fingerprinting technique of IEEE 802.11 wireless LAN traffic. We also summarize some of the researches on IEEE 802.11 network characteristic analysis to figure out rogue APs and MAC protocol misbehaviors

Levoamphetamine and Dextroamphetamine: Differential Effect on Aggression and Hyperkinesis in Children and Dogs

In laboratory experiments with hyperkinetic, untrainable dogs and in a comparison of levoamphetamine, dextroamphetamine, and placebo in children, levoamphetamine and dextroamphetamine were found to be approximately equal in calming an aggressive, hostile dog and in benefiting "unsocialized-aggressive" children; dextroamphetamine was more effective than levoamphetamine in calming "nervousness" and hyperactivity in dogs and in overanxious-hyperkinetic children. These data suggest that in the hyperkinetic syndrome, aggression and hostility may be benefited equally by levoamphetamine or dextroamphetamine via a dopaminergic mechanism, while anxiety and overactivity may be benefited significantly only by the dextro isomer via a norepinephrinergic mechanism

The New Normal: Families, Caretakers, and Adults with Autism

Over the last several decades, the clinical prevalence of autism has increased considerably, as has the amount of popular and scientific attention directed towards the condition. However, discussions of autism tend to focus on children and finding a cause and a cure, while the growing numbers of adults diagnosed with autism have received relatively little attention. This dissertation begins with the argument that popular representations of autism are shaped by the idealism of modern medicine, and its overriding search to discover etiologies and treatments for all forms of biological difference that fall within its purview. And yet, for those responsible for adults with autism, management, care, and support are more relevant concerns to everyday experience than are cause and cure. In order to describe and analyze this everyday experience, this dissertation features a three-year ethnographic study of thirteen families with adult members with severe forms of autism. After reviewing pertinent historical and demographic information, the body of the manuscript explores: 1) the process by which caretakers negotiate between different definitions of problem behavior in the face of persistent situational complexity and ambiguity; 2) the contextual dynamics that make it possible for caretakers to perceive as innocent and/or humorous behaviors that are often viewed as atypical by others; and 3) the ways in which the experience of continued atypicality and dependency comes into conflict with popular representations of autism while at the same time highlighting the reality of the ever-looming future and the care and support required after primary caretakers are gone. At the end of the dissertation, I return to the argument that modern medical idealism discourages popular recognition that, in the case of autism, continued atypicality and dependency constitute the condition\u27s usual prognosis. I conclude with a short consideration of how the themes explored in this thesis resonate with the experiences of those living with or alongside other forms of biological difference (e.g. disability, mental illness, Alzehemier\u27s) that are currently incurable

The spread of substance use and delinquency between adolescent twins

This investigation examines the spread of problem behaviors (substance use and delinquency) between twin siblings. A sample of 628 twins (151 male twin pairs and 163 female twin pairs) drawn from the Quebec Newborn Twin Study completed inventories describing delinquency and substance use at ages 13, 14, and 15. A three-wave longitudinal Actor-Partner Interdependence Model (APIM) identified avenues whereby problem behaviors spread from one twin to another. Problems did not spread directly between twins across domains. Instead, two indirect pathways were identified: (1) Problems first spread inter-individually (between twins) within a behavioral domain, then spread intra-individually (within twins) across behavioral domains (e.g., Twin A delinquency Twin B delinquency Twin B substance use); and (2) problems first spread intra-individually (within twins) across behavioral domains, then spread inter-individually (between twins) within a behavioral domain (e.g., Twin A delinquency Twin A substance use Twin B substance use). Controls for genetic effects, gene-environment correlations, friend substance use and delinquency, and parenting behaviors increase confidence in the conclusion that twin siblings uniquely contribute to the spread of problem behaviors during adolescence. Twin sibling influence is a risk factor for illicit substance use, both because substance use by one twin predicts substance use by the other twin, but also because delinquency in one twin predicts delinquency in the other twin, which then gives rise to greater substance use

Discrete event approach to network fault management

Failure diagnosis in large and complex systems such as a communication network is a critical task. An important aspect of network management is fault management, i.e.,determining, locating, isolation, and correcting faults in the network. In the realm of discrete event systems Sampath et al proposed a failure diagnosis approach, and Jiang et al proposed an efficient algorithm for testing diagnosability. In this work, we adopt the framework of the communicating finite state machine (CFSM) of Miller et al for modeling networks and to investigate fault detection, fault identification and fault location using Sampath et al and Jiang et al methods. Our approach provides a systematic way of performing fault diagnosis aspects of network fault management