Feedback Rules Research Articles

Фідбек як інструмент управління розвитком закладів вищої освіти в умовах сьогодення

The research article is devoted to the theoretical aspects of ‘feedback’, particularly in the education system. The problems and prospects of applying feedback in the educational process are outlined. The features of feedback as a tool for managing the development of higher education institutions in today’s conditions are determined. It is emphasized that it is necessary to focus on organizational support for communication management in higher education institutions to develop higher education in Ukraine. It is noted that feedback is one of the most critical and widespread communication tools. It is determined that in managing the development of higher education institutions with the help of feedback, the following theses are achieved: improving the quality of the educational process, satisfaction of higher education students and research and teaching staff, optimization of management decisions, improvement of the communication process of all participants in the educational process, adaptation to changes, support for the development of research and teaching staff, promotion of innovation and development, planning and strategic development, improvement of student life. It is noted that the main tasks of feedback are helping to adapt faster, encouraging growth and development, and provoking changes to achieve the goals. Therefore, feedback is a tool for developing both the employee and the enterprise. The article identifies and characterizes the main types and kinds of feedback. The main types are positive, negative, and constructive feedback. For effective management of the development of higher education institutions, the most effective type of feedback is constructive. Attention is focused on the rules of constructive feedback. Attention is paid to the generally accepted and most optimal method of feedback – The Sandwich Method, which has both positive and negative aspects. Keywords: feedback, types of feedback, management of development of higher education institutions, research and teaching staff, higher education students.

The perils of fiscal feedback rules

This paper introduces a fiscal feedback rule (FFR) in an endogenous growth model with public debt dynamics. We assume that part of the debt burden is covered by tax increases (we name this “sterilization”), while the remaining part is financed by issuing new debt. We show that while low sterilization does not ensure the existence of a long-run steady state, high sterilization can lead to multiple steady states and aggregate instability in the form of local and global indeterminacy, potentially condemning the economy to a low-growth/high-debt trap steady state and long-lasting public debt cycles. By combining econometric estimations and a calibration exercise on developed economies, we highlight that these various perils can occur for empirically plausible values of the sterilization coefficient.

Dynamical complexity in microscale disk-wind systems

Context. Powerful winds at accretion-disk scales have been observed in the past 20 years in many active galactic nuclei (AGN). These are the so-called ultrafast outflows (UFOs). Outflows are intimately related to mass accretion through the conservation of angular momentum, and they are therefore a key ingredient of most accretion disk models around black holes (BHs). At the same time, nuclear winds and outflows can provide the feedback that regulates the joint BH and galaxy growth. Aims. We reconsidered UFO observations in the framework of disk-wind scenarios, both magnetohydrodynamic disk winds and radiatively driven winds. Methods. We studied the statistical properties of observed UFOs from the literature and derived the distribution functions of the ratio ω̄ of the mass-outflow and -inflow rates and the ratio λw of the mass-outflow and the Eddington accretion rates. We studied the links between ω̄ and λw and the Eddington ratio λ = Lbol/LEdd. We derived the typical wind-activity history in our sources by assuming that it can be statistically described by population functions. Results. We find that the distribution functions of ω̄ and λw can be described as power laws above some thresholds, suggesting that there may be many wind subevents for each major wind event in each AGN activity cycle, which is a fractal behavior. We then introduced a simple cellular automaton to investigate how the dynamical properties of an idealized disk-wind system change following the introduction of simple feedback rules. We find that without feedback, the system is overcritical. Conversely, when feedback is present, regardless of whether it is magnetic or radiation driven, the system can be driven toward a self-organized critical state. Conclusions. Our results corroborate the hypothesis that AGN feedback is a necessary key ingredient in disk-wind systems, and following this, in shaping the coevolution of galaxies and supermassive BHs.

Automated Code Review Tool

As software development undergoes continual evolution, the assurance of code quality remains paramount in the development lifecycle. This research paper introduces an innovative Automated Code Review Tool engineered to augment and streamline the code review process. The tool capitalizes on advanced static code analysis, machine learning algorithms, and industry best practices to automate the detection of code quality issues, security vulnerabilities, and compliance with coding standards. The Automated Code Review Tool addresses the inherent challenges of manual code reviews, including human error, time constraints, and inconsistencies. Through automation, developers can expedite the identification and resolution of potential issues, thereby enhancing overall code quality and software reliability. Key features of the tool encompass intelligent pattern recognition, real-time feedback, and customizable rule sets, enabling development teams to tailor the tool to their project-specific requirements. Leveraging machine learning algorithms facilitates the tool's continuous learning from past reviews, thereby adapting to evolving coding practices and emerging security threats. This paper presents the architectural framework and design principles underpinning the Automated Code Review Tool, emphasizing its capacity to foster collaboration among development teams, reduce time-to-market, and ultimately contribute to the development of more robust and secure software. A comprehensive evaluation of the tool's efficacy across diverse development environments is conducted, offering insights into the practical implications of embracing automated solutions in real-world contexts. Keywords: Automated Code Review Tool, Code quality, Static code analysis, Machine learning algorithms, Coding standards, Manual code reviews, Human error, Time constraints, etc.

UNCERTAINTY, LONG‐RUN, AND MONETARY POLICY RISKS IN A TWO‐COUNTRY MACRO MODEL

AbstractWe study the currency risk premium and the forward premium bias in a two‐country New Keynesian model with production, no physical capital, and recursive utility. Monetary policy follows an interest rate feedback rule and exogenous total factor productivity (TFP) growth follows a long‐run risk process with stochastic volatility, which we estimate from data. With cross‐country heterogeneity in TFP and monetary policy, reasonable currency risk premia emerge under complete and incomplete markets but the forward premium bias is trivial. We diagnose the challenge faced by this fairly standard production model to explain the forward premium bias.

An edge detection method of colony image based on mediocrity ant colony algorithm

The colony is one of the important research objects in microbial technology, which can realize the evaluation of food safety level, environmental pollution degree, therapeutic effect of medical drugs, and characteristics of agricultural fungicides. Traditional colony image research requires human visual observation and statistics, which will result in low work efficiency and high work intensity. Colony image edge detection is an important basis for colony image research. Traditional edge detection operators cannot meet the accuracy requirements of the detection results. This paper proposes a Mediocrity Ant Colony Algorithm (MACA) to achieve edge detection of colony images. MACA combines the mediocrity rule, uses empirical functions to establish a pheromone database that can be used as a pheromone update reference table, adopts the Chebyshev distance as a weight that affects pheromone update, and combines heuristic information acquisition with maximum variance classification method and local path weights. The method that jointly affects the ant transition probability incorporates feedback rules for obtaining path weights to improve the edge detection effect. By performing edge detection simulation experiments on six colonies of three types of bacteria, and comparing with the classic edge detection operators and two classic ant colony edge detection algorithms, the detection performance, detection results and running time are proposed. The stability and accuracy of MACA algorithm is better than other methods, and the ideal results of the colony image edge detection by the ant colony algorithm are obtained.

Endogenous growth and monetary policy: How do interest-rate feedback rules shape nominal and real transitional dynamics?

Monetary authorities have followed interest-rate feedback rules in apparently different ways over time and across countries, with the literature distinguishing, in particular, between active and passive monetary policies. We address the transitional-dynamics implications of these different types of monetary policy, in the context of a monetary growth model of R&D and physical capital accumulation. In this setup, well-behaved saddle-path transitional dynamics occurs under both active and (sufficiently) passive monetary policies – a relevant result little emphasised in the literature. We carry out our study from the perspective of a one-off shift in the structural stance of monetary policy (i.e., a change in the long-run inflation target) and a one-off shift in real industrial policy (i.e., an R&D or a manufacturing subsidy). We uncover a new channel through which institutional factors (the characteristics of the monetary-policy rule) influence the economies' convergence behaviour and through which monetary authorities may leverage (transitional) growth triggered by structural shifts.

Evaluation and Comparison of SEA Torque Controllers in a Unified Framework

Series elastic actuators (SEA) with their inherent compliance offer a safe torque source for robots that are interacting with various environments, including humans. These applications have high requirements for the SEA torque controllers, both in the torque response as well as interaction behavior with its environment. To differentiate state of the art torque controllers, this work introduces a unifying theoretical and experimental framework that compares controllers based on their torque transfer behavior, their apparent impedance behavior, and especially the passivity of the apparent impedance (i.e., their interaction stability) as well as their sensitivity to sensor noise. We compare classical SEA control approaches such as cascaded PID controllers and full state feedback controllers with advanced controllers using disturbance observers, acceleration feedback and adaptation rules. Simulations and experiments demonstrate the trade-off between stable interactions, high bandwidths and low noise levels. Based on these trade-offs, an application-specific controller can be designed and tuned, based on desired interaction with the respective environment.

The SZ flux-mass (Y–M) relation at low-halo masses: improvements with symbolic regression and strong constraints on baryonic feedback

ABSTRACT Feedback from active galactic nuclei (AGNs) and supernovae can affect measurements of integrated Sunyaev–Zeldovich (SZ) flux of haloes (YSZ) from cosmic microwave background (CMB) surveys, and cause its relation with the halo mass (YSZ–M) to deviate from the self-similar power-law prediction of the virial theorem. We perform a comprehensive study of such deviations using CAMELS, a suite of hydrodynamic simulations with extensive variations in feedback prescriptions. We use a combination of two machine learning tools (random forest and symbolic regression) to search for analogues of the Y–M relation which are more robust to feedback processes for low masses ($M\lesssim 10^{14}\, \mathrm{ h}^{-1} \, \mathrm{ M}_\odot$); we find that simply replacing Y → Y(1 + M*/Mgas) in the relation makes it remarkably self-similar. This could serve as a robust multiwavelength mass proxy for low-mass clusters and galaxy groups. Our methodology can also be generally useful to improve the domain of validity of other astrophysical scaling relations. We also forecast that measurements of the Y–M relation could provide per cent level constraints on certain combinations of feedback parameters and/or rule out a major part of the parameter space of supernova and AGN feedback models used in current state-of-the-art hydrodynamic simulations. Our results can be useful for using upcoming SZ surveys (e.g. SO, CMB-S4) and galaxy surveys (e.g. DESI and Rubin) to constrain the nature of baryonic feedback. Finally, we find that the alternative relation, Y–M*, provides complementary information on feedback than Y–M.

Distinct cortico-striatal compartments drive competition between adaptive and automatized behavior.

Cortical and basal ganglia circuits play a crucial role in the formation of goal-directed and habitual behaviors. In this study, we investigate the cortico-striatal circuitry involved in learning and the role of this circuitry in the emergence of inflexible behaviors such as those observed in addiction. Specifically, we develop a computational model of cortico-striatal interactions that performs concurrent goal-directed and habit learning. The model accomplishes this by distinguishing learning processes in the dorsomedial striatum (DMS) that rely on reward prediction error signals as distinct from the dorsolateral striatum (DLS) where learning is supported by salience signals. These striatal subregions each operate on unique cortical input: the DMS receives input from the prefrontal cortex (PFC) which represents outcomes, and the DLS receives input from the premotor cortex which determines action selection. Following an initial learning of a two-alternative forced choice task, we subjected the model to reversal learning, reward devaluation, and learning a punished outcome. Behavior driven by stimulus-response associations in the DLS resisted goal-directed learning of new reward feedback rules despite devaluation or punishment, indicating the expression of habit. We repeated these simulations after the impairment of executive control, which was implemented as poor outcome representation in the PFC. The degraded executive control reduced the efficacy of goal-directed learning, and stimulus-response associations in the DLS were even more resistant to the learning of new reward feedback rules. In summary, this model describes how circuits of the dorsal striatum are dynamically engaged to control behavior and how the impairment of executive control by the PFC enhances inflexible behavior.

Asymmetric Markovian control of quantum entanglement

Expanding utilization of entangled states in quantum technologies, such as quantum information, is a motivating force of developing new methods for enhancement and stabilization of quantum entanglement. This study focuses on using asymmetric lawsto control the entangled states of a quantum systemconsistingof two atoms, each confined in a cavity.The effect of asymmetry laws has been explored in three different scenarios. First, the effect of an asymmetric drive Hamiltonian on a closed quantum system, in which neither the cavity nor the atoms exhibit losses, is studied. Here, the eigenvalues and eigenstates of the total system Hamiltonian have been obtained and the time evolution of the system state has been derived. Also, the fidelity of the system in terms of the asymmetric drive Hamiltonian has been derived analytically. In the second scenario, the stationary solution of an open quantum system, which includes losses in a master equation approach, is derived and the concurrence is studied in terms of the asymmetric drive Hamiltonian and coupling constant. The last scenario is devoted to applying feedback rulesto an open quantum system where some heuristic feedback control laws have been proposed. The simulation results show the concurrence boosting in a larger range of driving field and feedback strength when applying the introduced feedback rules.

Liquidity Traps: An Interest-Rate-Based Exit Strategy

This paper analyzes a potential strategy for escaping liquidity traps. The strategy is based on an augmented Taylor-type interest-rate feedback rule and differs from usual specifications in that when inflation falls below a threshold, the central bank temporarily deviates from the traditional Taylor rule by following a deterministic path for the nominal interest rate. This path reaches the intended target for this policy instrument in finite time. The policy we study is designed to raise inflationary expectations over time while at the same time maintaining all of the desirable local properties of the Taylor principle in a neighborhood of the intended inflation target. Importantly, the effectiveness of the potential exit strategy studied in this paper does not rely on the existence of an accompanying fiscalist (or non-Ricardian) fiscal stance.

Investigation of Four-Port Characteristic Dependence on Gate Length for MOSFETs in the Breakdown Region

In this article, gate length-dependent RF four-port characteristics of MOSFETs are investigated in the avalanche regime by using the double feedback and chain rule methods for the first time. The obvious decline of the imaginary part of source input impedance at high drain voltage for short-channel MOSFETs is investigated through the double feedback instead of only the series feedback for the origin of the inductive source impedance. The dominant terms causing the reduction of inductive source impedance due to parallel feedback are determined by this chain rule method. When compared with the conventional analysis due to short-channel effects on the direct-current (DC) characteristics of threshold voltage and substrate current, short-channel MOSFETs resulting in the aspect of RF characteristics are further analyzed by using different gate length MOSFETs. Besides, as gate length reduces, drain-to-source transmission raises significantly in the avalanche regime due to the RF avalanche network according to this analysis. This mechanism results in lower isolation at the breakdown for the shorter gate length MOSFETs. Good agreement of the four-port scattering parameter (S-parameter) between simulation and measurement is obtained for the MOSFETs operating in the both breakdown and saturation regions. The methods can be utilized for other advanced technology nodes and are helpful for the design of RF CMOS amplifiers in the impact ionization region.

Absolutely Stable Spatiotemporal Order in Noisy Quantum Systems.

We introduce a model of nonunitary quantum dynamics that exhibits infinitely long-lived discrete spatiotemporal order robust against any unitary or dissipative perturbation. Ergodicity is evaded by combining a sequence of projective measurements with a local feedback rule that is inspired by Toom's "north-east-center" classical cellular automaton. The measurements in question only partially collapse the wave function of the system, allowing some quantum coherence to persist. We demonstrate our claims using numerical simulations of a Clifford circuit in two spatial dimensions which allows access to large system sizes, and also present results for more generic dynamics on modest system sizes. We also devise explicit experimental protocols realizing this dynamics using one- and two-qubit gates that are available on present-day quantum computing platforms.

High speed visual insect swarm tracker (Hi-VISTA) used to identify the effects of confinement on individual insect flight

Individual insects flying in crowded assemblies perform complex aerial maneuvers by sensing and feeding back neighbor measurements to small changes in their wing motions. To understand the individual feedback rules that permit these fast, adaptive behaviors in group flight, both experimental preparations inducing crowded flight and high-speed tracking systems capable of tracking both body motions and more subtle wing motion changes for multiple insects in simultaneous flight are needed. This measurement capability extends tracking beyond the previous focus on individual insects to multiple insects. This paper describes an experimental preparation that induces crowded insect flight in more naturalistic conditions (a laboratory-outdoor transition tunnel) and directly compares the resulting flight performance to traditional flight enclosures. Measurements are made possible via the introduction of a multi-agent high speed insect tracker called Hi-VISTA, which provides a capability to track wing and body motions of multiple insects using high speed cameras (9000–12 500 fps). Processing steps consist of automatic background identification, data association, hull reconstruction, segmentation, and feature measurement. To improve the biological relevance of laboratory experiments and develop a platform for interaction studies, this paper applies the Hi-VISTA measurement system to Apis mellifera foragers habituated to transit flights through the transparent transition environment. Binary statistical analysis (Welch’s t-test, Cohen’s d effect size) of 95 flight trajectories is presented, quantifying the differences between flights in an unobstructed environment and in a confined tunnel volume. The results indicate that body pitch angle, heading rate, flapping frequency, and vertical speed (heave) are each affected by confinement, and other flight variables show minor or statistically insignificant changes. These results form a baseline as swarm tracking and analysis begins to isolate the effects of neighbors from environmental enclosures, and improve the connection of high speed insect laboratory experiments to outdoor field experiments.

A feedback model applied in a ubiquitous microlearning environment using SECA rules

Understanding learners’ behavior is the key to the success of any learning process. The more we know about them, the more likely we can personalize learning experiences and provide successful feedback. This paper presents a feedback model implemented in a ubiquitous microlearning environment based on contextual and behavioral information and evaluation results. The model uses SECA rules where the Scenario (S) represents the ubiquitous context variables reflecting the learner behavior during the learning process. The Event (E) identifies the probability that a learner fails or passes its evaluation. Condition (C) evaluates the results of the events. Moreover, Action (A) provides feedback to the learner. The proposal is developed through a controlled experiment whereby a microlearning environment can collect data from a ubiquitous context. The feedback model applies an analytics process to find the best context and behavior variables through different classification models. Those models predict whether a learner could fail, determine evaluation results’ causes, and provide feedback. The Random Forest was the model with the best performance. Thus, 94% accuracy, a 97% Recall, a 93% Precision, an F1 score of 95%, and a Jaccard of 91%. Hence, each scenario is defined from a branch of every tree obtained from the Random Forest model personalizing feedback actions applying clustering techniques. Finally, we presented an exemplified set of feedback rules, providing automatic recommendations and improving learner experiences. Thus, the experiment allows analyzing the learner behavior in a ubiquitous microlearning context from a feedback perspective.

КУЛЬТУРА УПРАВЛІННЯ В СУЧАСНИХ УМОВАХ

The article considers the issues of formation management culture at enterprises and organizations, which were formed in conditions of instability, socio-economic crisis, riskiness of conditions not only the functioning but also the existence of staff. The components of the manager's professional culture (professional knowledge; developed skills, abilities necessary for effective and high-quality management functions), as well as components of the manager's communicative competence (perfect command of professional terms, business Ukrainian and foreign languages, various types of interactive communication, rhetoric; open proactive thinking; empathy; ability to accurately assess and manage the communication situation; ability to make informed management decisions, etc.), which is a leading element of his personal and professional culture were considered. The rules of crisis communication are given (1. "Build trust", 2. "Systematic", 3. "Tell the truth", 4. "Express emotions", 5. "Demonstrate a positive attitude", 6. "Communicate about the state of affairs in the country", 7. "Communication with subordinates", 8. "Think about the plan to overcome the crisis"), as well as the rules of effective feedback (1. Choose the right time and constructive attitude; 2. Describe observations; 3. Explain the impact; 4. Suggest an alternative; 5. Agree on an action plan). Necessity of the head’s emotional intelligence development for maintenance of his professionalism growth, stress-resistance and efficiency of relations management in collective was proved. To this end, ways to develop emotional intelligence in modern conditions have been developed: online trainings, selfdevelopment of perception and management own emotions skills, establishing effective feedback, improving communicative competence, conflict prevention, team training, art therapy and mastering mechanisms "fine-tuning" (identification, empathy, attraction, reflection, causal attribution), as well as the method of nonviolent communication (emphasis on empathy, self-experience and honest self-expression), which form the basis for effective communication, especially in modern stressful conditions.

Hybrid Physics-based and Data-driven Model Predictive Control for Multi-Zone Building's Thermal Comfort Under Disjunctive Uncertainty

This paper develops a hybrid approach that utilizes the distributional information of the disjunctive uncertainty sets and incorporates them into the model predictive control (MPC). This approach aims at the multi-zone building control to the thermal comfort, and it's robust to the uncertain weather forecast errors. The control objective is to maintain each zone's temperature and relative humidity within the specified ranges using the minimum cost of energy of the underlying heating system. The hybrid model is constructed using a physics-based and regression method for the temperature and relative humidity of each zone in the building. The uncertainty space is based on historical weather forecast error data, which are captured by a group of disjunctive uncertainty sets using k-means clustering algorithm. Machine learning approaches based on principal component analysis and kernel density estimation are used to construct each basic uncertainty set and reduce the conservatism of resulting robust control action under disturbances. A robust MPC framework is developed based on the proposed hybrid model and data-driven disjunctive uncertainty set. An affine disturbance feedback rule is employed to obtain a tractable approximation of the robust MPC problem. A case study of controlling temperature and relative humidity of a multi-zone building in Ithaca, New York, USA, is presented. The results demonstrate that the proposed hybrid approach can reduce 9.8% to 17.9% of total energy consumption compared to conventional robust MPC approaches. Moreover, the proposed hybrid approach can essentially satisfy the thermal constraints that certainty equivalent MPC and robust MPC largely violate.

Countering the Deleterious Effects of Electromagnetic Pulse

Robot systems like automated shipping swinging robots, wire transducer sensors and even computer indigenous time sensors (amongst others) often use oscillating circuits such as the famous van der Pol system, while this manuscript investigates protection of such sensor circuitry to spurious voltage spikes accompanying an electromagnetic pulse. These spurious voltages can lead to uncontrolled robot motion and even debilitation. A very brief discussion of electromagnetic pulses yields design parameters to evaluate circuit responses to realistic disturbing pulses. Recent research in nonlinear-adaptive methods to protect circuits are described to highlight the proposed novelty: utilization of feedback rules as adaptive mechanisms to modify the otherwise nonlinear feedforwards systems improving the results in recent literature. Feedback is iterated to select adaption parameters that simultaneously produce favorable circuit performance in addition to effective parameter identification inherent in the adaption (to provide meaningful parameter estimates to unspecified future applications). Spurious voltages were rapidly rejected with a mere 0.3% trajectory deviation, stabilizing quickly with a final (steady state) deviation of 0.01%. The demonstrated abilities to reject the deleterious spurious effects are compared to nominal figures of merit for timing accuracy of various computer systems to conclude the proposed methods are effective for some applications, but insufficient for others.

Banks, money, and the zero lower bound on deposit rates

We develop a New Keynesian model where all payments between agents require bank deposits, bank deposits are created through disbursement of bank loans, and banks face convex lending costs. At the zero lower bound on deposit rates (ZLBD), changes in policy rates affect activity through both real interest rates and banks’ net interest margins (NIMs). At empirically plausible credit supply elasticities, the Phillips curve is very flat at the ZLBD. This is because inflation increases NIMs, credit, deposits, and thereby output, while higher NIMs also dampen inflation by relaxing price setters’ credit rationing constraint. At the ZLBD, monetary policy has far larger effects on output relative to inflation, and inflation feedback rules stabilize output less effectively than rules that also respond to credit. For post-COVID-19 policy, this suggests urgency in returning inflation to targets, caution with negative policy rates, and a strong influence of credit conditions on rate setting.