Cause-effect modeling as a general method for describing and studying phenomena in complex hierarchical systems

Карнаухов, А. В.

doi:10.1134/s0006350906020278

Cited by 4 publications

(3 citation statements)

References 2 publications

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“…Researchers agreed that causeand-effect analysis is effective and useful in identifying the causes and ensure comprehensive coverage related to a problem. [42][43][44][45][46] In the fishbone diagram, the head of the fish is denoted as the summative effect while the fish ribs represent causes contributing to the final effect. 47 The effect is identified, followed by thoroughly recognizing the main causes.…”

Section: Cause-and-effect Analysismentioning

confidence: 99%

Improving merger and acquisition decision-making using fuzzy logic and simulation

Chui

2017

International Journal of Engineering Business Management

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Mergers and acquisitions (M&A) are an internationally adopted expansion strategy, but not every case can be successfully executed nor achieved the intended post-expansion results. Most studies focus on M&A wave or post-M&A integration, yet this article focuses on pre-M&A analysis and planning. An M&A evaluation and prioritization model (MAEPM) is proposed to assist decision makers in a more objective and effective manner so that to implement and execute each M&A deal with the aim of maximizing the success rate rather than any other irrelevant reasons. Risk analysis, fuzzy critical path analysis, cost-benefit evaluation, as well as decision rule and prioritization were developed and integrated, which provide insight into M&A evaluation and serve as indicators. Eleven case studies were conducted to verify the MAEPM and the results generated from the MAEPM were compared with the actual results that confirmed the MAEPM is significant and plausible. The novel MAEPM is confirmed to be reliable that enables firms to select the most winning M&A deal(s) to be made according to the availability of resources and capital and thus enhance the success rate of M&A.

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Section: Cause-and-effect Analysismentioning

confidence: 99%

Improving merger and acquisition decision-making using fuzzy logic and simulation

Chui

2017

International Journal of Engineering Business Management

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“…In this paper we propose the novel approach to introduce modelling concepts and techniques from computer science to arXiv:2104.07320v1 [quant-ph] 15 Apr 2021 quantum error mitigation. In general, models are simplified representations of systems that can help us understand, predict, and therefore possibly control their complex correlations [25]- [27]. They can also be used for communication and reduce information to the essentials with respect to a specific point of view.…”

Section: Introductionmentioning

confidence: 99%

Modelling for Quantum Error Mitigation

Weber

Riebisch

Borras

et al. 2021

2021 IEEE 18th International Conference on Software Architecture Companion (ICSA-C)

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While we expect quantum computers to surpass their classical counterparts in the future, current devices are prone to high error rates and techniques to minimise the impact of these errors are indispensable. There already exists a variety of error mitigation methods addressing this quantum noise that differ in effectiveness, and scalability. But for a more systematic and comprehensible approach we propose the introduction of modelling, in particular for representing cause-effect relations as well as for evaluating methods or combinations thereof with respect to a selection of relevant criteria.

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“…The biomechanical explanation is that a high cadence will typically reduce the flight trajectory of the body centre-of-mass and cause load reduction, while an increased inclination of the foot angle at impact will reduce limb stiffness and likewise cause load reduction. Here, we use a mathematical model to provide the metalanguage that clarifies this cause-effect relationship within the locomotor control system (Karnaukhov, 2006). For example, cadence and foot-strike angle are the input parameters of some function [i.e., F(input) + ɛ = output], while the output is the loading rate, and "ɛ" is a random error due to the inherent nature of an open nondeterministic locomotor system.…”

Section: Introductionmentioning

confidence: 99%

A real-time feedback method to reduce loading rate during running: Effect of combining direct and indirect feedback

Garofolini

Oppici

Taylor

2020

Journal of Sports Sciences

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Impact loading plays a key role in the pathophysiology of running-related injuries. Providing real-time feedback may be an effective strategy to reduce impact loading; however, it is currently unclear what an effective training method to help runners achieve a habitual low loading rate is. We subjected 20 healthy non-runners to a structured sequence of direct and indirect biofeedback designed to facilitate broader exploration of neuro-mechanical workspace for potential movement solutions (indirect feedback on cadence and foot-strike angle) and to refine and converge upon an optimal subset of that space to match the task goal (direct feedback on loading rate). While indirect biofeedback on foot-strike angle yielded a lower impact load than providing direct biofeedback on loading rate, compared to indirect biofeedback on foot-strike angle, providing direct feedback on loading rate statistically increased (+58%, p = 0.007) the range of goal-relevant solutions participants used to lower their impact loading. Results showed that structured feedback was effective in increasing the range of input parameters that match the task goal, hence expanding the size of goal-relevant solutions, which may benefit running performance under changing environmental constraints.

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Cause-effect modeling as a general method for describing and studying phenomena in complex hierarchical systems

Cited by 4 publications

References 2 publications

Improving merger and acquisition decision-making using fuzzy logic and simulation

Improving merger and acquisition decision-making using fuzzy logic and simulation

Modelling for Quantum Error Mitigation

A real-time feedback method to reduce loading rate during running: Effect of combining direct and indirect feedback

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