scholarly journals RedHerd: Offensive Cyberspace Operations as a Service

Signals ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 619-636
Author(s):  
Giovanni Pecoraro ◽  
Mario D’Amico ◽  
Simon Pietro Romano
Keyword(s):  
Open Source ◽  
Open Systems ◽  
Systems Architecture ◽  
Cost Constraints ◽  
Simulation Based ◽  
Simulation And Training ◽  
Knowledge Requirements ◽  
Service Paradigm ◽  
Cyber Kill Chain ◽  
And Training

Nowadays, time, scope and cost constraints along with knowledge requirements and personnel training constitute blocking restrictions for effective Offensive Cyberspace Operations (OCO). This paper presents RedHerd, an open-source, collaborative and serverless orchestration framework that overcomes these limitations. RedHerd leverages the ‘as a Service’ paradigm in order to seamlessly deploy a ready-to-use infrastructure that can be also adopted for effective simulation and training purposes, by reliably reproducing a real-world cyberspace battlefield in which red and blue teams can challenge each other. We discuss both the design and implementation of the proposed solution, by focusing on its main functionality, as well as by highlighting how it perfectly fits the Open Systems Architecture design pattern, thanks to the adoption of both open standards and wide-spread open-source software components. The paper also presents a complete OCO simulation based on the usage of RedHerd to perform a fictitious attack and fully compromise an imaginary enterprise following the Cyber Kill Chain (CKC) phases.

scholarly journals Predictors of Manual Dexterity in Simulation-Based Cataract Surgery

2020 ◽  
Vol 12 (02) ◽  
pp. e239-e243
Author(s):  
Laura Palazzolo ◽  
Anna Kozlova ◽  
John J. Laudi ◽  
Allison E. Rizzuti
Keyword(s):  
Medical Students ◽  
Video Games ◽  
Cataract Surgery ◽  
Prior Experience ◽  
Musical Instruments ◽  
Fine Motor ◽  
Surgical Simulator ◽  
Technical Ability ◽  
Simulation Based ◽  
And Training

Abstract Introduction The aim of this study is to determine if prior experience with fine motor hobbies influences a surgeon-in-training's performance on a cataract surgical simulator. Materials and Methods Medical students (n = 70) performed navigation, forceps, and capsulorhexis simulations using the Eyesi Ophthalmosurgical Simulator. Participants were surveyed regarding fine motor hobby experiences, including musical instruments, video games, sewing, knitting, origami, painting, crafting, jewelry making, drawing, and extracurricular dissection. Results Medical students with extracurricular dissection experience, including work in research laboratories involving microscopic animal dissection, did significantly better on the forceps simulator task (p = 0.009). Medical students with drawing experience performed better on capsulorhexis (p = 0.031). No other fine motor hobbies were significant for improving simulator scores. Conclusion Drawing and extracurricular dissection lend to improved technical ability on the cataract surgical simulator. This research continues the conversation regarding fine motor hobbies that correlate with microsurgical ability and adds to the growing area of research regarding the selection and training of ophthalmology residents.

scholarly journals PRISMS-Fatigue computational framework for fatigue analysis in polycrystalline metals and alloys

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Mohammadreza Yaghoobi ◽  
Krzysztof S. Stopka ◽  
Aaditya Lakshmanan ◽  
Veera Sundararaghavan ◽  
John E. Allison ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Metals And Alloys ◽  
Analysis Tool ◽  
Computational Framework ◽  
Crystal Plasticity Finite Element ◽  
Polycrystalline Metals ◽  
Simulation Based ◽  
Open Source Framework

AbstractThe PRISMS-Fatigue open-source framework for simulation-based analysis of microstructural influences on fatigue resistance for polycrystalline metals and alloys is presented here. The framework uses the crystal plasticity finite element method as its microstructure analysis tool and provides a highly efficient, scalable, flexible, and easy-to-use ICME community platform. The PRISMS-Fatigue framework is linked to different open-source software to instantiate microstructures, compute the material response, and assess fatigue indicator parameters. The performance of PRISMS-Fatigue is benchmarked against a similar framework implemented using ABAQUS. Results indicate that the multilevel parallelism scheme of PRISMS-Fatigue is more efficient and scalable than ABAQUS for large-scale fatigue simulations. The performance and flexibility of this framework is demonstrated with various examples that assess the driving force for fatigue crack formation of microstructures with different crystallographic textures, grain morphologies, and grain numbers, and under different multiaxial strain states, strain magnitudes, and boundary conditions.

scholarly journals Bernoulli Time Series Modelling with Application to Accommodation Tourism Demand

2021 ◽  
Vol 5 (1) ◽  
pp. 17
Author(s):  
Miguel Ángel Ruiz Reina
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Prognostic Models ◽  
Series Data ◽  
Economic Agents ◽  
Time Series Modelling ◽  
Simulation And Training ◽  
Uncertainty Method ◽  
And Training ◽  
Hotel Accommodation

In this research, a new uncertainty method has been developed and applied to forecasting the hotel accommodation market. The simulation and training of Time Series data are from January 2001 to December 2018 in the Spanish case. The Log-log BeTSUF method estimated by GMM-HAC-Newey-West is considered as a contribution for measuring uncertainty vs. other prognostic models in the literature. The results of our model present better indicators of the RMSE and Ratio Theil’s for the predictive evaluation period of twelve months. Furthermore, the straightforward interpretation of the model and the high descriptive capacity of the model allow economic agents to make efficient decisions.

scholarly journals Corrigendum to ‘Human corpse model for video-assisted thoracoscopic lobectomy simulation and training’

2020 ◽  
Vol 31 (5) ◽  
pp. 753-753
Author(s):  
Andrea Dell’Amore ◽  
Rafael Boscolo-Berto ◽  
Marco Schiavona ◽  
Alessandro Pangoni ◽  
Andrea Porzionato ◽  
...  
Keyword(s):  
Human Corpse ◽  
Video Assisted ◽  
Thoracoscopic Lobectomy ◽  
Simulation And Training ◽  
And Training

scholarly journals Introducing the StataStan Interface for Fast, Complex Bayesian Modeling Using Stan

2017 ◽  
Vol 17 (2) ◽  
pp. 330-342 ◽  
Author(s):  
Robert L. Grant ◽  
Bob Carpenter ◽  
Daniel C. Furr ◽  
Andrew Gelman
Keyword(s):  
Bayesian Inference ◽  
Item Response Theory ◽  
Open Source ◽  
Item Response ◽  
Bayesian Modeling ◽  
Inference Engine ◽  
Software Components ◽  
Statistical Software ◽  
Simulation Based ◽  
Item Response Theory Models

In this article, we present StataStan, an interface that allows simulation-based Bayesian inference in Stata via calls to Stan, the flexible, open-source Bayesian inference engine. Stan is written in C++, and Stata users can use the commands stan and windowsmonitor to run Stan programs from within Stata. We provide a brief overview of Bayesian algorithms, details of the commands available from Statistical Software Components, considerations for users who are new to Stan, and a simple example. Stan uses a different algorithm than bayesmh, BUGS, JAGS, SAS, and MLwiN. This algorithm provides considerable improvements in efficiency and speed. In a companion article, we give an extended comparison of StataStan and bayesmh in the context of item response theory models.

scholarly journals Software tool for naval surface warfare simulation and training

2007 ◽  
Vol 6 (s2) ◽  
pp. S427-S444 ◽  
Author(s):  
Sergiu Dascalu ◽  
Sermsak Buntha ◽  
Daniela Saru ◽  
Narayan Debnath
Keyword(s):  
Software Tool ◽  
Simulation And Training ◽  
Surface Warfare Simulation ◽  
And Training ◽  
Naval Surface Warfare

scholarly journals Simulation and training in anaesthesia

2009 ◽  
Vol 103 (5) ◽  
pp. 770-771 ◽  
Author(s):  
A. Guha ◽  
M.J. Moneypenny ◽  
S.J. Mercer
Keyword(s):  
Simulation And Training ◽  
And Training
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