scholarly journals Approbation of the stochastic group virus protection model

2022 ◽  
pp. 62-70
Author(s):  
R. Y. Sharykin
Keyword(s):  
Virtual Machines ◽  
Propagation Speed ◽  
Model Parameters ◽  
System Specification ◽  
Defense System ◽  
Virus Propagation ◽  
Transmission Delays ◽  
Message Transmission ◽  
Object Based ◽  
System Effectiveness

The article discusses the implementation in Java of the stochastic collaborative virus defense model developed within the framework of the Distributed Object-Based Stochastic Hybrid Systems (DOBSHS) model and its analysis. The goal of the work is to test the model in conditions close to the real world on the way to introducing its use in the practical environment. We propose a method of translating a system specification in the SHYMaude language, intended for the specification and analysis of DOBSHS models in the rewriting logic framework, into the corresponding Java implementation. The resulting Java system is deployed on virtual machines, the virus and the group virus alert system are modeled stochastically. To analyze the system we use several metrics, such as the saturation time of the virus propagation, the proportion of infected nodes upon reaching saturation and the maximal virus propagation speed. We use Monte Carlo method with the computation of confidence intervals to obtain estimates of the selected metrics. We perform analysis on the basis of the sigmoid virus propagation graph over time in the presence of the defense system. We implemented two versions of the system using two protocols for transmitting messages between nodes, TCP/IP and UDP. We measured the influence of the protocol type and the associated costs on the defense system effectiveness. To assess the potential of cost reduction associated with the use of different message transmission protocols, we performed analysis of the original DOBSHS model modified to model message transmission delays. We measured the influence of other model parameters important for the next steps towards the practical use of the model. To address the system scalability, we propose a hierarchical approach to the system design to make possible its use with a large number of nodes.

scholarly journals Detection of contributing object to driving operations based on hidden Markov model

2019 ◽  
Vol 16 (5) ◽  
pp. 172988141987679
Author(s):  
Kohjiro Hashimoto ◽  
Tetsuyasu Yamada ◽  
Takeshi Tsuchiya ◽  
Kae Doki ◽  
Yuki Funabora ◽  
...  
Keyword(s):  
Time Series ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Cognitive Performance ◽  
Traffic Accidents ◽  
Hidden Markov ◽  
Model Parameters ◽  
Detection Accuracy ◽  
Cognitive Support ◽  
Object Based

With increase in the number of elderly people in the Japanese society, traffic accidents caused by elderly driver is considered problematic. The primary factor of the traffic accidents is a reduction in their driving cognitive performance. Therefore, a system that supports the cognitive performance of drivers can greatly contribute in preventing accidents. Recently, the development of devices for visually providing information, such as smart glasses or head up display, is in progress. These devices can provide more effective supporting information for cognitive performance. In this article, we focus on the selection problem of information to be presented for drivers to realize the cognitive support system. It has been reported that the presentation of excessive information to a driver reduces the judgment ability of the driver and makes the information less trustworthy. Thus, indiscriminate presentation of information in the vision of the driver is not an effective cognitive support. Therefore, a mechanism for determining the information to be presented to the driver based on the current driving situation is required. In this study, the object that contributes to execution of avoidance driving operation is regarded as the object that drivers must recognize and present for drivers. This object is called as contributing object. In this article, we propose a method that selects contributing objects among the appeared objects on the current driving scene. The proposed method expresses the relation between the time series change of an appeared object and avoidance operation of the driver by a mathematical model. This model can predict execution timing of avoidance driving operation and estimate contributing object based on the prediction result of driving operation. This model named as contributing model consisted of multi-hidden Markov models. Hidden Markov model is time series probabilistic model with high readability. This is because that model parameters express the probabilistic distribution and its statistics. Therefore, the characteristics of contributing model are that it enables the designer to understand the basis for the output decision. In this article, we evaluated detection accuracy of contributing object based on the proposed method, and readability of contributing model through several experiments. According to the results of these experiments, high detection accuracy of contributing object was confirmed. Moreover, it was confirmed that the basis of detected contributing object judgment can be understood from contributing model.

Research on External Storages Management of Virtual Machine

2013 ◽  
Vol 427-429 ◽  
pp. 2305-2308
Author(s):  
Xiao Rui Wang ◽  
Qing Xian Wang
Keyword(s):  
System Design ◽  
Virtual Machine ◽  
Memory Management ◽  
Virtual Machines ◽  
Virtual Memory ◽  
Network Storage ◽  
Design Scheme ◽  
Virtual Memory Management ◽  
Object Based ◽  
Usage Efficiency

To deal with the problem of external storages management in multiple virtual machines environment, a system design scheme of external storages management is proposed with the idea of virtual memory management and protocol of object-based Network storage. Experiments showed that virtual partition could be created and repealed dynamic, the capability of partition could be increased dynamic with practical requirement, and write protection based partition could also be realized, flexibility of external storages management is enhanced greatly and usage efficiency also increased notably.

scholarly journals Coupled Epidemio-Hydrodynamic Modeling to Understand the Spread of a Deadly Coral Disease in Florida

2020 ◽  
Vol 7 ◽  
Author(s):  
Thomas Dobbelaere ◽  
Erinn M. Muller ◽  
Lewis J. Gramer ◽  
Daniel M. Holstein ◽  
Emmanuel Hanert
Keyword(s):  
Causative Agent ◽  
Coral Disease ◽  
Propagation Speed ◽  
Tissue Loss ◽  
Coral Tissue ◽  
Model Parameters ◽  
Dade County ◽  
Coral Mucus ◽  
Disease Threshold ◽  
Neutrally Buoyant

For the last six years, the Florida Reef Tract (FRT) has been experiencing an outbreak of the Stony Coral Tissue Loss Disease (SCTLD). First reported off the coast of Miami-Dade County in 2014, the SCTLD has since spread throughout the entire FRT with the exception of the Dry Tortugas. However, the causative agent for this outbreak is currently unknown. Here we show how a high-resolution bio-physical model coupled with a modified patch Susceptible-Infectious-Removed epidemic model can characterize the potential causative agent(s) of the disease and its vector. In the present study, the agent is assumed to be transported within composite material (e.g., coral mucus, dying tissues, and/or resuspended sediments) driven by currents and potentially persisting in the water column for extended periods of time. In this framework, our simulations suggest that the SCTLD is likely to be propagated within neutrally buoyant material driven by mean barotropic currents. Calibration of our model parameters with field data shows that corals are diseased within a mean transmission time of 6.45 days, with a basic reproduction number slightly above 1. Furthermore, the propagation speed of the disease through the FRT is shown to occur for a well-defined range of values of a disease threshold, defined as the fraction of diseased corals that causes an exponential growth of the disease in the reef site. Our results present a new connectivity-based approach to understand the spread of the SCTLD through the FRT. Such a method can provide a valuable complement to field observations and lab experiments to support the management of the epidemic as well as the identification of its causative agent.

scholarly journals IDENTIFICATION OF A TEMPERATURE DEPENDENT FITZHUGH–NAGUMO MODEL FOR THE BELOUSOV–ZHABOTINSKII REACTION

2011 ◽  
Vol 21 (11) ◽  
pp. 3249-3258 ◽  
Author(s):  
Y. ZHAO ◽  
S. A. BILLINGS ◽  
D. COCA ◽  
Y. GUO ◽  
R. I. RISTIC ◽  
...  
Keyword(s):  
Oscillation Frequency ◽  
Propagation Speed ◽  
Oscillatory Behavior ◽  
Steady States ◽  
Model Parameters ◽  
Good Representation ◽  
Temperature Dependent ◽  
Control Variables ◽  
The Stability ◽  
Belousov Zhabotinskii Reaction

This paper describes the identification of a temperature dependent FitzHugh–Nagumo model directly from experimental observations with controlled inputs. By studying the steady states and the trajectory of the phase of the variables, the stability of the model is analyzed and a rule to generate oscillation waves is proposed. The dependence of the oscillation frequency and propagation speed on the model parameters is then investigated to seek the appropriate control variables, which then become functions of temperature in the identified model. The results show that the proposed approach can provide a good representation of the dynamics of the oscillatory behavior of a Belousov–Zhabotinskii reaction.

scholarly journals Pattern solutions of the Klausmeier model for banded vegetation in semi-arid environments II: patterns with the largest possible propagation speeds

2011 ◽  
Vol 467 (2135) ◽  
pp. 3272-3294 ◽  
Author(s):  
Jonathan A. Sherratt
Keyword(s):  
Spatial Ecology ◽  
Arid Regions ◽  
Order Approximation ◽  
Propagation Speed ◽  
Theoretical Models ◽  
Model Parameters ◽  
Arid Environments ◽  
Ecosystem Level ◽  
Semi Arid ◽  
Banded Vegetation

Pattern formation at the ecosystem level is a rapidly growing area of spatial ecology. The best studied example is vegetation stripes running along contours in semi-arid regions. Theoretical models are a widely used tool for studying these banded vegetation patterns, and one important model is the system of advection–diffusion equations proposed by Klausmeier. The present study is part of a series of papers whose objective is a comprehensive understanding of patterned solutions of the Klausmeier model. The author focuses on the region of parameter space in which the propagation speed of the patterns is close to its maximum possible value. Exploiting the large value of one of the model parameters, a leading order approximation is obtained for the maximum propagation speed, and the author undertakes a detailed investigation of the parameter region in which there are patterns with speeds close to this maximum.

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