Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models

Background: User behavior models have been widely used to simulate attack behaviors in the security domain. We revised all patents related to response to attack behavior models. How to decide the protected target against multiple models of attack behaviors is studied. Methods: We utilize one perfect rational and three bounded rational behavior models to simulate attack behaviors in cloud computing, and then investigate cloud provider’s response based on Stackelberg game. The cloud provider plays the role of defender and it is assumed to be intelligent enough to predict the attack behavior model. Based on the prediction accuracy, two schemes are built in two situations. Results: If the defender can predict the attack behavior model accurately, a single-objective game model is built to find the optimal protection strategy; otherwise, a multi-objective game model is built to find the optimal protection strategy. Conclusion: The numerical results prove that the game theoretic model performs better in the corresponding situation.

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Behavior Models of Voltage Differencing Inverting Buffered Amplifier and Applications in Circuit Analysis

Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) ◽

10.2174/2352096511666180629151111 ◽

2019 ◽

Vol 12 (4) ◽

pp. 298-303

Author(s):

YongAn LI

Keyword(s):

Large Scale ◽

Vlsi Design ◽

Circuit Analysis ◽

Second Order ◽

Very Large Scale Integration ◽

Behavioral Models ◽

Order Filter ◽

Large Scale Integration ◽

Scale Integration ◽

Behavior Models

Background: The symbolic nodal analysis acts as a pivotal part of the very large scale integration (VLSI) design. Methods: In this work, based on the terminal relations for the pathological elements and the voltage differencing inverting buffered amplifier (VDIBA), twelve alternative pathological models for the VDIBA are presented. Moreover, the proposed models are applied to the VDIBA-based second-order filter and oscillator so as to simplify the circuit analysis. Results: The result shows that the behavioral models for the VDIBA are systematic, effective and powerful in the symbolic nodal circuit analysis.</P>

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Human Handedness and Scalp Hair-Whorl Direction Develop From a Common Genetic Mechanism

Genetics ◽

10.1093/genetics/165.1.269 ◽

2003 ◽

Vol 165 (1) ◽

pp. 269-276

Author(s):

Amar J S Klar

Keyword(s):

Scalp Hair ◽

Single Gene ◽

Monozygotic Twins ◽

Hand Preference ◽

Genetic Mechanism ◽

Internal Organs ◽

Genetic Pathways ◽

Left Hand ◽

Learned Behavior ◽

Random Mixture

Abstract Theories concerning the cause of right- or left-hand preference in humans vary from purely learned behavior, to solely genetics, to a combination of the two mechanisms. The cause of handedness and its relation to the biologically specified scalp hair-whorl rotation is determined here. The general public, consisting of mostly right-handers (RH), shows counterclockwise whorl rotation infrequently in 8.4% of individuals. Interestingly, non-right-handers (NRH, i.e., left-handers and ambidextrous) display a random mixture of clockwise and counterclockwise swirling patterns. Confirming this finding, in another independent sample of individuals chosen because of their counterclockwise rotation, one-half of them are NRH. These findings of coupling in RH and uncoupling in NRH unequivocally establish that these traits develop from a common genetic mechanism. Another result concerning handedness of the progeny of discordant monozygotic twins suggests that lefties are one gene apart from righties. Together, these results suggest (1) that a single gene controls handedness, whorl orientation, and twin concordance and discordance and (2) that neuronal and visceral (internal organs) forms of bilateral asymmetry are coded by separate sets of genetic pathways. The sociological impact of the study is discussed.

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An examination of virtualization's role in contingency planning

Proceedings of the 4th annual conference on Information security curriculum development - InfoSecCD '07 ◽

10.1145/1409908.1409927 ◽

2007 ◽

Cited By ~ 1

Author(s):

Stephen C. Gay

Keyword(s):

Contingency Planning

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Continuing Patient Care during Electronic Health Record Downtime

Applied Clinical Informatics ◽

10.1055/s-0039-1692678 ◽

2019 ◽

Vol 10 (03) ◽

pp. 495-504

Author(s):

Ethan Larsen ◽

Daniel Hoffman ◽

Carlos Rivera ◽

Brian M. Kleiner ◽

Christian Wernz ◽

...

Keyword(s):

Quantitative Analysis ◽

Electronic Health Record ◽

Clinical Laboratory ◽

Normal Operation ◽

Contingency Planning ◽

Health Record ◽

Safety Assurance ◽

Hospital Operations ◽

Recorded Data ◽

Electronic Health

Introduction Electronic health record (EHR) downtime is any period during which the EHR system is fully or partially unavailable. These periods are operationally disruptive and pose risks to patients. EHR downtime has not sufficiently been studied in the literature, and most hospitals are not adequately prepared. Objective The objective of this study was to assess the operational implications of downtime with a focus on the clinical laboratory, and to derive recommendations for improved downtime contingency planning. Methods A hybrid qualitative–quantitative study based on historic performance data and semistructured interviews was performed at two mid-Atlantic hospitals. In the quantitative analysis, paper records from downtime events were analyzed and compared with normal operations. To enrich this quantitative analysis, interviews were conducted with 17 hospital employees, who had experienced several downtime events, including a hospital-wide EHR shutdown. Results During downtime, laboratory testing results were delayed by an average of 62% compared with normal operation. However, the archival data were incomplete due to inconsistencies in the downtime paper records. The qualitative interview data confirmed that delays in laboratory result reporting are significant, and further uncovered that the delays are often due to improper procedural execution, and incomplete or incorrect documentation. Interviewees provided a variety of perspectives on the operational implications of downtime, and how to best address them. Based on these insights, recommendations for improved downtime contingency planning were derived, which provide a foundation to enhance Safety Assurance Factors for EHR Resilience guides. Conclusion This study documents the extent to which downtime events are disruptive to hospital operations. It further highlights the challenge of quantitatively assessing the implication of downtimes events, due to a lack of otherwise EHR-recorded data. Organizations that seek to improve and evaluate their downtime contingency plans need to find more effective methods to collect data during these times.

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