Types Of Feedback Loops Research Articles

Digital brand image management based on feedback loops

Purpose: is to propose a model for managing a digital brand image brand based on consecutive feedback loops from the image targetaudience. Methods: collection, processing, and analysis of secondary data were carried out on the basis of desk research, synthesis methods, contentanalysis, and systemic, structural and functional data evaluation using an interdisciplinary approach. Results: systemized methodological approaches in Russian and foreign practice by the authors served as the basis for development of a digital brand image management model based on consecutive feedback loops from the image target audience. Within the framework of the proposed model, it is supposed to create systems in a digital environment for providing feedback to the image target audience and monitoring of formed relationships with consumers. The authors' methodological recommendations for implementation of the proposed model are manifested in detailed approaches to organizing the relationship of the image object with the image target audience through different types of feedback loops, methods of monitoring responses and reactions of target consumers, methods of assessing image in a brand's digital environment to close feedback loops. Conclusions and Relevance: loops of feedback from the brand’s image target audience are a causative mechanism of dynamic nature in which the output data of subjective and objective consumer assessment of brand reputation is used as input data for the management and enhancement of the digital image. Setting up a system of feedback from consumers through digital channels on the basis of consecutive loops allows you to correlate planned indicators of the brand image with the actual indicators, as well as identifi cation of the existing problems and introducing timely adjustments to decisions on managing a brand’s digital image.

Patient experiences with patient-reported outcome measures in metastatic breast cancer trials: qualitative interviews

BackgroundPatient-reported outcome (PRO) measures are critical for assessing treatment benefit of anticancer treatments. Although PRO measures have been developed with the intention of capturing patient-centric concepts, a gap exists in understanding the patient experience with these tools. We characterized the experience of patients with metastatic breast cancer (mBC) with PRO measures in an oncology clinical trial setting to determine the importance, relevance, barriers, and facilitators for PRO completion.MethodsThe multicenter, qualitative design included semistructured interviews with 18 women with mBC who completed PRO measures in a clinical trial setting within 1 year of screening. Interviews began with concept elicitation to understand symptom characterization, decision to participate in a clinical trial, pre-trial expectations, and thoughts on study-related questionnaires. Cognitive debriefing was conducted to determine if items in a commonly used PRO instrument were relevant to the patient experience. Qualitative data were analyzed using a constant comparative approach.ResultsParticipants described the need for detailed explanation of PRO measures at study start, including information about how the PRO data will likely be used to support drug development. Respondents who felt connected to clinical trial research were more likely to feel as if the measures adequately captured their experiences. Items that were deemed irrelevant or out of date to the patient experience may cause a respondent to feel marginalized and adds to the overall burden of PRO measure completion. Mode of PRO measure administration (electronic/paper) was important to some, but placement of the instrument completion within a study visit appeared to influence respondent willingness to fully engage with the measures. A lack of any type of feedback loop to allow respondents to learn from the captured PRO data was noted as important but missing from the patient experience.ConclusionsPRO measures need to include content that is relevant to the patient experience over the course of the clinical trial period to be considered meaningful to respondents, and administration techniques also impact engagement. Robust communication strategies that socialize the intent, use, and results of PRO data may enrich the patient experience and support greater adherence to PRO completion in future studies.

Making a difference in the real world. User-centred impact evaluation of an eight-country, community-based early childhood programme

This paper presents a unique approach to the Impact Evaluation of a project that focused on low-threshold intergenerational play-based interactions in order to support young children from marginalised communities in eight European countries. The approach builds upon the work of Fetterman’s Empowerment Evaluation and Patton’s Utilization Focused Evaluation and brings them together to form an adapted model of evaluation. We outline in this paper how these two well developed methods of evaluation have been applied to a real world context, that is, the impact evaluation of a complex international project. Our approach highlights the complexities of differing contexts and allows for surprising and unintended consequences to emerge. It results, through double loop learning, a type of feedback loop with the internal stakeholders and implementers that is useful to the project coordination team, with a view to further upscaling of the initiative. Recommendations for policy at local, national and European Union levels were provided to the project and potential external users. However, the predominant feedback was provided at two crucial points along the way; during a stakeholder mapping exercise and during the further development of monitoring data tools.

Dynamical phase diagram of an auto-regulating gene in fast switching conditions.

While the steady-state behavior of stochastic gene expression with auto-regulation has been extensively studied, its time-dependent behavior has received much less attention. Here, under the assumption of fast promoter switching, we derive and solve a reduced chemical master equation for an auto-regulatory gene circuit with translational bursting and cooperative protein-gene interactions. The analytical expression for the time-dependent probability distribution of protein numbers enables a fast exploration of large swaths of the parameter space. For a unimodal initial distribution, we identify three distinct types of stochastic dynamics: (i) the protein distribution remains unimodal at all times; (ii) the protein distribution becomes bimodal at intermediate times and then reverts back to being unimodal at long times (transient bimodality); and (iii) the protein distribution switches to being bimodal at long times. For each of these, the deterministic model predicts either monostable or bistable behavior, and hence, there exist six dynamical phases in total. We investigate the relationship of the six phases to the transcription rates, the protein binding and unbinding rates, the mean protein burst size, the degree of cooperativity, the relaxation time to the steady state, the protein mean, and the type of feedback loop (positive or negative). We show that transient bimodality is a noise-induced phenomenon that occurs when the protein expression is sufficiently bursty, and we use a theory to estimate the observation time window when it is manifested.

Measurement without management: qualitative evaluation of a voluntary audit & feedback intervention for primary care teams

BackgroundThe use of clinical performance feedback to support quality improvement (QI) activities is based on the sound rationale that measurement is necessary to improve quality of care. However, concerns persist about the reliability of this strategy, known as Audit and Feedback (A&F) to support QI. If successfully implemented, A&F should reflect an iterative, self-regulating QI process. Whether and how real-world A&F initiatives result in this type of feedback loop are scarcely reported. This study aimed to identify barriers or facilitators to implementation in a team-based primary care context.MethodsSemi-structured interviews were conducted with key informants from team-based primary care practices in Ontario, Canada. At the time of data collection, practices could have received up to three iterations of the voluntary A&F initiative. Interviews explored whether, how, and why practices used the feedback to guide their QI activities. The Consolidated Framework for Implementation Research was used to code transcripts and the resulting frameworks were analyzed inductively to generate key themes.ResultsTwenty-five individuals representing 18 primary care teams participated in the study. Analysis of how the A&F intervention was used revealed that implementation reflected an incomplete feedback loop. Participation was facilitated by the reliance on an external resource to facilitate the practice audit. The frequency of feedback, concerns with data validity, the design of the feedback report, the resource requirements to participate, and the team relationship were all identified as barriers to implementation of A&F.ConclusionsThe implementation of a real-world, voluntary A&F initiative did not lead to desired QI activities despite substantial investments in performance measurement. In small primary care teams, it may take long periods of time to develop capacity for QI and future evaluations may reveal shifts in the implementation state of the initiative. Findings from the present study demonstrate that the potential mechanism of action of A&F may be deceptively clear; in practice, moving from measurement to action can be complex.

A systematic development method for cyber-physical machine tools

Machine Tool 4.0 introduces a new generation of machine tools that are smarter, well connected, widely accessible, more adaptive and more autonomous. Cyber-Physical Machine Tools (CPMT), based on recent advancements of the Information and Communication Technology, provides a promising solution for Machine Tool 4.0. This paper proposes a systematic development method for CPMT. Generic system architecture is developed to provide guidelines for advancing existing Computer Numerical Control (CNC) machine tools to CPMT. The proposed architecture allows machine tool, machining processes, real-time machining data and intelligent algorithms to be deeply integrated through various types of networks. The development methodologies for the core of the CPMT, the Machine Tool Cyber Twin (MTCT), are studied and discussed in detail. MTCT enables different types of feedback loops among the physical world, the cyber space and humans to be realized. An MTConnect-based CPMT prototype is developed to validate the proposed CPMT. Experimental results have proved great interoperability, connectivity and extensibility of the proposed CPMT. The potential of implementing artificial intelligence in CPMT is also discussed.

Comparison of operation modes for spin-exchange optically-pumped spin oscillators

The nuclear spin precesses continually when a positive feedback nuclear magnetic resonance field is applied. The characteristics of this behaviour depend not only on the parameters of the spin ensemble but also on the type and parameters of the feedback loop. We theoretically analysed two types of feedback loops which use direct feedback and phase-lock feedback, respectively. We also compared the oscillating frequency of the spin oscillators using rotating and linear magnetic fields, respectively. Some interesting results on the frequency and start-time of the oscillator were found. These findings will be useful to improve the accuracy of fundamental physical theory tests, such as the Lorentz-violation and electron dipole moment (EDM) test, using spin oscillators. And moreover, they are also very useful for achieving a high performance NMR gyroscope.

Efficient stock price prediction using a Self Evolving Recurrent Neuro-Fuzzy Inference System optimized through a Modified Differential Harmony Search Technique

This paper proposes a new Self Evolving Recurrent Neuro-Fuzzy Inference System (SERNFIS) for efficient prediction of highly fluctuating and irregular financial time series data like stock market indices over varying time frames. The network is modeled including the first order Takagi Sugeno Kang (TSK) type fuzzy if then rules with two types of feedback loops. The recurrent structure in the proposed model comes from locally feeding the firing strength of the fuzzy rule back to itself and by including a few time delay components at the output layer. The novelty of the model is based on the fact that the internal temporal feedback loops and time delayed output feedback loops are used for further enhancing the prediction capability of traditional neuro-fuzzy system in handling more dynamic financial time series data. Another recurrent functional link artificial neural network (RCEFLANN) model is also presented for a comparative study. In the second part of the paper a modified differential harmony search (MDHS) technique is proposed for estimating the parameters of the model including the antecedent, consequent and feedback loop parameters. Experimental results obtained by implementing the model on two different stock market indices demonstrate the effectiveness of the proposed model compared to existing models for stock price prediction.

A Robust Technique for Single-Phase Grid Voltage Fundamental and Harmonic Parameter Estimation

This paper reports a frequency-adaptive robust technique for the accurate estimation of the single-phase grid voltage fundamental and harmonic parameters. The technique is based on the discrete Fourier transform and a cascaded delayed signal cancellation strategy. There is no stability issue in the technique, since it does not contain any type of feedback loop. It can also be flexibly configured to estimate the parameters of the fundamental and/or one/multiple harmonic(s) from the grid voltage waveform distorted by various harmonics. Moreover, it does not require evaluation of trigonometric and inverse trigonometric functions for implementing on real-time digital signal processor. However, it needs computationally demanding high-order finite-impulse-response filters. The simulation and real-time experimental results are provided to verify the performance of the proposed technique.

A Symmetric Dual Feedback System Provides a Robust and Entrainable Oscillator

Many organisms have evolved molecular clocks to anticipate daily changes in their environment. The molecular mechanisms by which the circadian clock network produces sustained cycles have extensively been studied and transcriptional-translational feedback loops are common structures to many organisms. Although a simple or single feedback loop is sufficient for sustained oscillations, circadian clocks implement multiple, complicated feedback loops. In general, different types of feedback loops are suggested to affect the robustness and entrainment of circadian rhythms.To reveal the mechanism by which such a complex feedback system evolves, we quantify the robustness and light entrainment of four competing models: the single, semi-dual, dual, and redundant feedback models. To extract the global properties of those models, all plausible kinetic parameter sets that generate circadian oscillations are searched to characterize their oscillatory features. To efficiently perform such analyses, we used the two-phase search (TPS) method as a fast and non-biased search method and quasi-multiparameter sensitivity (QMPS) as a fast and exact measure of robustness to uncertainty of all kinetic parameters.So far the redundant feedback model has been regarded as the most robust oscillator, but our extensive analysis corrects or overcomes this hypothesis. The dual feedback model, which is employed in biology, provides the most robust oscillator to multiple parameter perturbations within a cell and most readily entrains to a wide range of light-dark cycles. The kinetic symmetry between the dual loops and their coupling via a protein complex are found critically responsible for robust and entrainable oscillations. We first demonstrate how the dual feedback architecture with kinetic symmetry evolves out of many competing feedback systems.

Coherent coupling of feedback loops: a design principle of cell signaling networks

It is widely accepted that cell signaling networks have been evolved to be robust against perturbations. To investigate the topological characteristics resulting in such robustness, we have examined large-scale signaling networks and found that a number of feedback loops are present mostly in coupled structures. In particular, the coupling was made in a coherent way implying that same types of feedback loops are interlinked together. We have investigated the role of such coherently coupled feedback loops through extensive Boolean network simulations and found that a high proportion of coherent couplings can enhance the robustness of a network against its state perturbations. Moreover, we found that the robustness achieved by coherently coupled feedback loops can be kept evolutionarily stable. All these results imply that the coherent coupling of feedback loops might be a design principle of cell signaling networks devised to achieve the robustness.

Rigid Body Rate Inference from Attitude Variation

In this paper we research the extraction of the angular rate vector from attitude information without differentiation, in particular from quaternion measurements. We show that instead of using a Kalman filter of some kind, it is possible to obtain good rate estimates, suitable for spacecraft attitude control loop damping, using simple feedback loops, thereby eliminating the need for recurrent covariance computation performed when a Kalman filter is used. This considerably simplifies the computations required for rate estimation in gyro-less spacecraft. Some interesting qualities of the Kalman filter gain are explored, proven and utilized. We examine two kinds of feedback loops, one with varying gain that is proportional to the well known Q matrix, which is computed using the measured quaternion, and the other type of feedback loop is one with constant coefficients. The latter type includes two kinds; namely, a proportional feedback loop, and a proportional-integral feedback loop. The various schemes are examined through simulations and their performance is compared. It is shown that all schemes are adequate for extracting the angular velocity at an accuracy suitable for control loop damping.

Feed-back in solid-state reactions

The role of feed-back in solid-state reactions is discussed. Various types of feed-back loops are considered. Problems arising in studying feed-back in solid-state reactions and the means of their solution are illustrated by suitable examples.

Synthesis of counters with any kind of feedback

Algebraic expressions may be used to describe the analysis of digital counters with various types of feedback loops. It will be shown that such expressions may also be used to advantage in realisation procedures of the synthesis of counters. Design procedures are shown for the synthesis of counters with specified periodic sets of bases.