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About 10,000 papers for “simulation strategy”

Simulation strategy.

Benjamin J. Liebeskind (3282108), Richard W. Aldrich (4870036), Edward M. Marcotte (50526) · Figshare · 2019

<p><b>A.)</b> The distribution of Pearson’s correlation coefficient averaged over 32 co-fractionation experiments on human cell lines. The distribution for gold-standard interacting human protein pairs is barely distinguishable from non-interactors. <b>B.)</b> Error models parameters were manipulated to replicate typical experimental noise. The equilibrium frequencies of the two state, <i>π</i><sub>0</sub> and <i>π</i><sub>1</sub>, can be tuned to replicate class-imbalance. The difference between the means <i>δ</i>, was changed to replicate weak signal. The mixture weights for the positive error model, <i>λ</i><sub>1</sub> and <i>λ</i><sub>2</sub>, set the false negative rate.</p>

Cited by 0Open access

The simulation strategy.

Robert Kirmse (258085), Zhao Qin (258824), Carl M. Weinert (362666) et al. · Figshare · 2015

<p>A) the full atomic model used to fit the parameter of the coarse-grained substrate model. B) the Lennard-Jones potential for the full atomic model and the coarse-grained substrate model as a function of the distance between two particles.</p>

Cited by 0Open access

OP04 Simulation strategy development

Angela Hope · Oral Presentations · 2018

Aim Encourage Leadership and Management thinking processes in development and sustainment of a Simulation Service for the future. Objectives To gain a stance of where an organisation is currently Identify where they would like to be Map the steps required strategically in meeting individual service goals Develop visionary thinking Enhance competency of faculty and quality standards in accordance with regional and national policy and guidelines1 Harness individuality of services regionally. Summary of work undertaken In 2016 a post as lead of clinical skills and simulation at Calderdale and Huddersfield Trust which spanned two hospitals and community settings was introduced. The post was a new initiative2 in order to develop ways of working of an established Sim Suite, functioning successfully under a technician but with no official role identified within the trust and no faculty in place. In order to explore what the service was currently offering, major goals and aspirations were identified as to where the service could reach if a framework for progression and sustainment were initiated. Key persons, communications and stakeholders were also identified. As a starting point a SWOT analysis3 was undertaken, as a rigorous process in identification of key factors which may impact upon the development of a trajectory path when devising a framework guiding the a service through to their vision. The analysis process led to the development of 6 major goals as a pathway in meeting aspirations, incorporating networks of communication,4 resources and funding and supporting policies and guidelines. Impact on practice The key impact on practice would be through a dedicated programme of ensuring appropriate knowledge in developing an expert faculty, addressing recognised quality standards in meeting the needs of the service and users. Ultimately this will impact upon the safety of patients and benefit the clinical organisations and the feeling of safe environment for learning and personal values of faculty. References . Cantillon P, Wood D, Yardley S (Eds.). ABC of learning and teaching in medicine 2001(3rd ed). Wiley, New Jersey. . Public Health England. Facing the facts, Shaping the future: A health and Care workforce strategy for England to20272017. Available at: https://hee.nhs.uk/sites/default/files/documents/Facing%20the%20Facts%2C%20Shaping%20the%20Future%20%E2%80%93%20a%20draft%20health%20and%20care%20workforce%20strategy%20for%20England%20to%202027.pdf [Accessed 19 May 2018]. . Turner S, Harder N. Psychological safe environment: A concept analysis. Clinical Simulation in Nursing 2018. Available at: https://doi.org/10.1016/j.ecns.2018.02.004 [Accessed 16 May 2018]. . Department of Health. A framework for technology enhanced learning2011. Available at: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/215316/dh_131061.pdf [Accessed 16 May 2018].

Cited by 0

Time for a simulation strategy?

Naomi Shiner · Journal of Medical Radiation Sciences · 2023

This editorial evaluates the role of virtual reality alongside traditional simulation learning environments for radiography education. With such rapid uptake in recent years, is it time to consider how simulation can be implemented more strategically?

Cited by 4Open access

Strategy: A Construction Simulation Environment

Brenda McCabe, Kei Sze Ching, Savio Rodrigues · 2000

STRATEGY is a simulation environment that models the construction process for instructional purposes. Several business functions are required during a simulation to improve a student's understanding of the construction industry. General contractors are represented by teams of students. Each team participates in the preparation of estimates, project control, and financial management. Random events are used to represent external effects such as weather, labour strife or material shortages. The session is concluded after a predetermined number of weeks with the most profitable general contractor team recognized for their construction acumen.

Cited by 36

Adversarial Planning Through Strategy Simulation

2008

Abstract — Adversarial planning in highly complex decision domains, such as modern video games, has not yet received much attention from AI researchers. In this paper, we present a planning framework that uses strategy simulation in conjunction with Nash-equilibrium strategy approximation. We apply this framework to an army deployment problem in a real-time strategy game setting and present experimental results that indicate a performance gain over the scripted strategies that the system is built on. This technique provides an automated way of increasing the decision quality of scripted AI systems and is therefore ideally suited for video games and combat simulators.

Cited by 0

Model architecture and simulation strategy.

Christopher B. Massa (2323078), Angela M. Groves (4042409), Smita U. Jaggernauth (4388953) et al. · Figshare · 2017

<p>Simulation of respiratory impedance employs an anatomic description hybridized from CT and plaster cast data from the literature (A). Tree impedance was calculated using airway lengths and radii and a recursive algorithm to traverse the tree (B). Tissue properties incorporated an estimated model base elastance, radial alveolar count, and fiber thickness (C). Simulation strategy employs mechanical data to construct a model of the 8week WT mouse and determines reduction in error by increasing model complexity (D).</p>

Cited by 0Open access

SC40 Developing a simulation strategy

Leah Greene, Chiara Mosley · 2019

<h3>Background</h3> In the UK, simulation-based education (SBE) is a typical component of undergraduate and postgraduate health and social care and medical education programmes. SBE is also embedded in clinical, medical and inter-professional training delivered in hospital education centres and is routinely conducted in-situ in the actual patient care setting (Lopreiato et al, 2016). The spectrum of SBE ranges from role play and procedural simulation to fully immersive interactive simulation (Lopreiato et al, 2016). Regardless of the simulation learning environment (SLE), traditionally SBE has been an evolutionary, reactive process or has been delivered ad-hoc without proper preparation and planning, resulting in sub-optimal clinical skill development and performance (Al-Elq, 2010). A structured Simulation Strategy and associated Action Plan can enable the implementation of SBE in a proactive and effective manner ensuring adequate support to enable successful delivery of educational programmes. <h3>Summary of project</h3> A Simulation Strategy was developed in the Faculty of Health, Psychology and Social Care (HPSC) at Manchester Metropolitan University to describe our current position and vision for future SBE development in line with three core Faculty curriculum themes. The 5-step process included: Establishment of a Faculty Simulation Strategy Group Mapping exercise to identify where simulation existed in HPSC Faculty programmes Agreement on terms of reference Development of a shared Vision, Aims and Strategic Priorities (figure 1) Formulation of an operational Action Plan <h3>Summary of results</h3> The Simulation Strategy outlines strengths, expertise and areas of best practice and focuses on areas of growth, the development and exploitation of innovations and opportunities for the future. The Action Plan operationalises the Strategy, by turning the strategic priorities into actions, with associated timescales, responsibilities and identifies potential challenges. <h3>Discussion, conclusions and recommendations</h3> The development of a Simulation Strategy and Action Plan is a lengthy but essential process for any higher education institution (HEI) or hospital conducting SBE. Identifying current SBE delivery and agreeing terms of reference enables the development of a cohesive and coherent document with shared ownership across the Faculty. Furthermore, the Simulation Strategy and Action Plan supports in-depth asset inventory, future budgeting and staff development processes, enabling effective planning, which supports SBE delivery. <h3>References</h3> Al-Elq A. H. (2010). Simulation-based medical teaching and learning. <i>Journal of Family and Community Medicine</i>, 17(1), 35–40. doi:10.4103/1319-1683.68787 Lopreiato, J. O. (Ed.), Downing, D., Gammon, W., Lioce, L., Sittner, B., Slot, V., Spain, A. E. (Associate Eds.), and the Terminology &amp; Concepts Working Group. (2016). <i>Healthcare Simulation Dictionary</i>. Retrieved from http://www.ssih.org/dictionary.

Cited by 0Open access

TREAT Modeling and Simulation Strategy

Mark D. DeHart · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2015

This report summarizes a four-phase process used to describe the strategy in developing modeling and simulation software for the Transient Reactor Test Facility. The four phases of this research and development task are identified as (1) full core transient calculations with feedback, (2) experiment modeling, (3) full core plus experiment simulation and (4) quality assurance. The document describes the four phases, the relationship between these research phases, and anticipated needs within each phase.

Cited by 0Open access