From Simulation to Runtime Verification and Back: Connecting Single-Run Verification Techniques

Modern safety-critical systems, such as aircraft and spacecraft, crucially depend on rigorous verification, from design time to runtime. Simulation is a highly-developed, time-honored design-time verification technique, whereas runtime verification is a much younger outgrowth from modern complex systems that both enable embedding analysis on-board and require mission-time verification, e.g., for flight certification. While the attributes of simulation are well-defined, the vocabulary of runtime verification is still being formed; both are active research areas needed to ensure safety and security. This invited paper explores the connections and differences between simulation and runtime verification and poses open research questions regarding how each might be used to advance past bottlenecks in the other. We unify their vocabulary, list their commonalities and contrasts, and examine how their artifacts may be connected to push the state of the art of what we can (safely) fly

Hypotension Risk Prediction via Sequential Contrast Patterns of ICU Blood Pressure

© 2013 IEEE. Acute hypotension is a significant risk factor for in-hospital mortality at intensive care units. Prolonged hypotension can cause tissue hypoperfusion, leading to cellular dysfunction and severe injuries to multiple organs. Prompt medical interventions are thus extremely important for dealing with acute hypotensive episodes (AHE). Population level prognostic scoring systems for risk stratification of patients are suboptimal in such scenarios. However, the design of an efficient risk prediction system can significantly help in the identification of critical care patients, who are at risk of developing an AHE within a future time span. Toward this objective, a pattern mining algorithm is employed to extract informative sequential contrast patterns from hemodynamic data, for the prediction of hypotensive episodes. The hypotensive and normotensive patient groups are extracted from the MIMIC-II critical care research database, following an appropriate clinical inclusion criteria. The proposed method consists of a data preprocessing step to convert the blood pressure time series into symbolic sequences, using a symbolic aggregate approximation algorithm. Then, distinguishing subsequences are identified using the sequential contrast mining algorithm. These subsequences are used to predict the occurrence of an AHE in a future time window separated by a user-defined gap interval. Results indicate that the method performs well in terms of the prediction performance as well as in the generation of sequential patterns of clinical significance. Hence, the novelty of sequential patterns is in their usefulness as potential physiological biomarkers for building optimal patient risk stratification systems and for further clinical investigation of interesting patterns in critical care patients

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

Dragon-kings: mechanisms, statistical methods and empirical evidence

This introductory article presents the special Discussion and Debate volume "From black swans to dragon-kings, is there life beyond power laws?" published in Eur. Phys. J. Special Topics in May 2012. We summarize and put in perspective the contributions into three main themes: (i) mechanisms for dragon-kings, (ii) detection of dragon-kings and statistical tests and (iii) empirical evidence in a large variety of natural and social systems. Overall, we are pleased to witness significant advances both in the introduction and clarification of underlying mechanisms and in the development of novel efficient tests that demonstrate clear evidence for the presence of dragon-kings in many systems. However, this positive view should be balanced by the fact that this remains a very delicate and difficult field, if only due to the scarcity of data as well as the extraordinary important implications with respect to hazard assessment, risk control and predictability.Comment: 20 page

Data Mining for Anomaly Detection

The Vehicle Integrated Prognostics Reasoner (VIPR) program describes methods for enhanced diagnostics as well as a prognostic extension to current state of art Aircraft Diagnostic and Maintenance System (ADMS). VIPR introduced a new anomaly detection function for discovering previously undetected and undocumented situations, where there are clear deviations from nominal behavior. Once a baseline (nominal model of operations) is established, the detection and analysis is split between on-aircraft outlier generation and off-aircraft expert analysis to characterize and classify events that may not have been anticipated by individual system providers. Offline expert analysis is supported by data curation and data mining algorithms that can be applied in the contexts of supervised learning methods and unsupervised learning. In this report, we discuss efficient methods to implement the Kolmogorov complexity measure using compression algorithms, and run a systematic empirical analysis to determine the best compression measure. Our experiments established that the combination of the DZIP compression algorithm and CiDM distance measure provides the best results for capturing relevant properties of time series data encountered in aircraft operations. This combination was used as the basis for developing an unsupervised learning algorithm to define "nominal" flight segments using historical flight segments

Viking '75 spacecraft design and test summary. Volume 3: Engineering test summary

The engineering test program for the lander and the orbiter are presented. The engineering program was developed to achieve confidence that the design was adequate to survive the expected mission environments and to accomplish the mission objective

Performance Evaluation of Distributed Security Protocols Using Discrete Event Simulation

The Border Gateway Protocol (BGP) that manages inter-domain routing on the Internet lacks security. Protective measures using public key cryptography introduce complexities and costs. To support authentication and other security functionality in large networks, we need public key infrastructures (PKIs). Protocols that distribute and validate certificates introduce additional complexities and costs. The certification path building algorithm that helps users establish trust on certificates in the distributed network environment is particularly complicated. Neither routing security nor PKI come for free. Prior to this work, the research study on performance issues of these large-scale distributed security systems was minimal. In this thesis, we evaluate the performance of BGP security protocols and PKI systems. We answer the questions about how the performance affects protocol behaviors and how we can improve the efficiency of these distributed protocols to bring them one step closer to reality. The complexity of the Internet makes an analytical approach difficult; and the scale of Internet makes empirical approaches also unworkable. Consequently, we take the approach of simulation. We have built the simulation frameworks to model a number of BGP security protocols and the PKI system. We have identified performance problems of Secure BGP (S-BGP), a primary BGP security protocol, and proposed and evaluated Signature Amortization (S-A) and Aggregated Path Authentication (APA) schemes that significantly improve efficiency of S-BGP without compromising security. We have also built a simulation framework for general PKI systems and evaluated certification path building algorithms, a critical part of establishing trust in Internet-scale PKI, and used this framework to improve algorithm performance