Automated analysis of bounded response time for two NASA expert systems

1991 ◽  
Author(s):  
Chih-Kan Wang ◽  
Duu-Chung Tsou ◽  
Rwo-Hsi Wang ◽  
James C. Browne ◽  
Aloysius K. Mok
Keyword(s):  
Response Time ◽  
Expert Systems ◽  
Automated Analysis

Automated analysis of bounded response time for two NASA expert systems

1991 ◽  
Vol 16 (5) ◽  
pp. 147-161
Author(s):  
Chih-Kan Wang ◽  
Duu-Chung Tsou ◽  
Rwo-Hsi Wang ◽  
James C. Browne ◽  
Aloysius K. Mok
Keyword(s):  
Response Time ◽  
Expert Systems ◽  
Automated Analysis

scholarly journals A Distributed Approach for Estimating Battery State-Of-Charge in Solar Farms

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4998 ◽  
Author(s):  
MCarmen Romero-Ternero ◽  
David Oviedo-Olmedo ◽  
Alejandro Carrasco ◽  
Joaquín Luque
Keyword(s):  
Response Time ◽  
Expert Systems ◽  
Bayesian Network ◽  
Network Model ◽  
Multiagent System ◽  
State Of Charge ◽  
Bayesian Network Model ◽  
Distributed Sensors ◽  
Distributed Approach ◽  
Battery State Of Charge

A common problem in solar farms is to predict when accumulators stop working optimally and start losing efficiency. This paper proposes and describes how to use Bayesian networks together with expert systems to predict this moment by using a telecontrol multiagent system for monitoring solar farms with distributed sensors, which was developed in a previous work. To this end, a Bayesian network model and its implementation are proposed. The resulting system meets the requirements of telecontrol systems (reliability, flexibility, and response time), yields a solution for the prediction of lifespan batteries, and provides the multiagent system with autonomous intelligent capabilities and integrated learning.

scholarly journals Method for Attack Tree Data Transformation and Import Into IT Risk Analysis Expert Systems

2020 ◽  
Vol 10 (23) ◽  
pp. 8423
Author(s):  
Donatas Vitkus ◽  
Jonathan Salter ◽  
Nikolaj Goranin ◽  
Dainius Čeponis
Keyword(s):  
Expert System ◽  
Risk Analysis ◽  
Expert Systems ◽  
Knowledge Base ◽  
Automated Analysis ◽  
Knowledge Bases ◽  
It Security ◽  
Security Risk ◽  
Attack Tree ◽  
Attack Trees

Information technology (IT) security risk analysis preventatively helps organizations in identifying their vulnerable systems or internal controls. Some researchers propose expert systems (ES) as the solution for risk analysis automation since risk analysis by human experts is expensive and timely. By design, ES need a knowledge base, which must be up to date and of high quality. Manual creation of databases is also expensive and cannot ensure stable information renewal. These facts make the knowledge base automation process very important. This paper proposes a novel method of converting attack trees to a format usable by expert systems for utilizing the existing attack tree repositories in facilitating information and IT security risk analysis. The method performs attack tree translation into the Java Expert System Shell (JESS) format, by consistently applying ATTop, a software bridging tool that enables automated analysis of attack trees using a model-driven engineering approach, translating attack trees into the eXtensible Markup Language (XML) format, and using the newly developed ATES (attack trees to expert system) program, performing further XML conversion into JESS compatible format. The detailed method description, along with samples of attack tree conversion and results of conversion experiments on a significant number of attack trees, are presented and discussed. The results demonstrate the high method reliability rate and viability of attack trees as a source for the knowledge bases of expert systems used in the IT security risk analysis process.

Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time

2016 ◽  
Vol 63 (6) ◽  
pp. 333-342
Author(s):  
Roberto Limongi ◽  
Angélica M. Silva
Keyword(s):  
Response Time ◽  
Short Term Memory ◽  
Estimation Error ◽  
Predictive Coding ◽  
Time Estimation ◽  
Prediction Errors ◽  
Memory Scanning ◽  
Short Term ◽  
Term Memory ◽  
Temporal Prediction

Abstract. The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production – where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

Building More Expert Expert Systems

1986 ◽  
Vol 31 (6) ◽  
pp. 448-449
Author(s):  
Elaine A. Rich
Keyword(s):  
Expert Systems

A Response-Time Investigation of Vehicle Stereotypes

2000 ◽  
Author(s):  
Michael Anthony ◽  
Robert W. Fuhrman
Keyword(s):  
Response Time
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