Imitation Model Research Articles

Imitational Modeling of SPP Electrical Equipment in Various Climatic Conditions

Imitational Modeling of SPP Electrical Equipment in Various Climatic Conditions

Imitation and Large Language Models

Imitation and Large Language Models

«Хороший слог» и «новая художественность» в журнальной полемике 1860-1870-х годов

The research aims to determine the mutual influence of the principles of democratic criticism and raznochinets (“mixed-title”) literature in the 1860s-1870s. The work examines the issues related to the denial of artisticity as an important aesthetic criterion, as well as to the attempt to diminish the authority of literature with a “good style”, which “real critics” attributed to “aristocratic” literature. The paper considers the polemics of those years related to the socio-literary definition of the new stage of democratic literature with a social orientation, which was presented in magazines and by writers. The influence of raznochinets prose on the development of new criteria for evaluating literary works is identified, the function of the rhetorical form of a “conversation with the reader” in terms of combining critical and literary discourse is analyzed, using the prose of A. Scheller-Mikhailov, F. Reshetnikov, and I. Fedorov-Omulevsky as examples. As a model for subsequent imitation by fiction writers, the “conversation with the reader” in N. G. Chernyshevsky’s novel “What Is To Be Done?” is considered in comparison with his concept of art in “The Aesthetic Relations of Art to Reality”. Scientific originality is determined by the comparative method, which allows the researcher to reveal the forms of discursive interaction at the level of the concept of criticism and its embodiment in literary practice. As a result, it was found that a “conversation with the reader” as a metatextual manifesto of the author’s program becomes a component in the concept of literature of the post-Gogol period.

Adoption of Imitation Modeling Tools in Industrial Small and Medium Enterprises: Value Creation and Competitive Advantage

Currently, value creation is considered as a major part of strategic planning and a source of competitive advantage. Competition increases and customers ask for higher service level, but resources are always limited. Small and medium enterprises (SMEs) often face the enlarged requirements of rapid changes created by the modern economic tendencies. Therefore, businesses should react promptly and without spending excessive resources (otherwise SMEs may simply stop existing). On this issue, imitation modeling tools give a considerable advantage to SMEs: almost any decisions of strategic or operational management levels can be tested before implementing real business processes. The research question arises at the point of defining the conceptual framework for testing, adopting and implementing new practices (such as digital technologies and projects) with imitation modeling tools. Currently, business excellence often depends on how and at what extent digital solutions transform the traditional way of managing operations. This study is focused on considering many factors influencing logistics business processes in SMEs. The adjusted three-zone model is suggested for achieving operational excellence in industrial SMEs with imitation modeling tools. The suggested approach is based upon the triple bottom line concept, and creates value from several perspectives: economic, social and environmental.

Performance of mathematics students using video learning in flipped and flipped collaborative learning settings

Due to rapid technological advancement that continues to permeate almost all facets of the education sector, video learning has been explored to enhance performance, but most researchers do not incorporate flipped classroom in mathematical videos, which affects the teaching and learning of the subject in Nigeria. This study checked the effectiveness of video learning in flipped and flipped collaborative classroom on mathematics students’ achievement and retention. Using a randomized controlled trial with repeated measures approach, 70 senior secondary school students were purposively sampled from two private secondary schools in Gombe State, Nigeria, out of which they were randomly assigned into two experimental groups: video learning flipped classroom and video learning flipped collaborative classroom (VLFCC). Data was obtained using a 30-item mathematics achievement test, which was validated and pilot-tested (r=0.93). Results were computed using descriptive statistics and two-way mixed design repeated measures analysis of variance. Findings revealed that while the students’ within subject performance improved tremendously in the post-test after the four-week treatment, the students in VLFCC performed better in both achievement (F<sub>[1, 69]</sub>=1,576.362, p=0.000, effect size of (η<sub>p</sub><sup>2</sup>)<sup> </sup>of<sup> </sup>0.954) and retention (F<sub>[1, 69]</sub>=114. 119, p=0.000, with an effect size (η<sub>p</sub><sup>2</sup>) of 0.785. The finding has some implications for it exposes mathematics teachers, researchers, and policy makers to the credence of deploying video learning in flipped collaborative classroom to improve students’ performance by engaging students in collaborative learning in addition to watching pre-class videos, where students discuss in small groups in order to learn through observation, imitation, repetition and behavior modeling, thus making them to learn at their pace in order to construct their own knowledge.

Increase the operational reliability of the electric drive of the weaving machine

The main purpose of this research work is to analyze malfunctions, power consumption, engine overheating and vibrations based on the loadings of electrical circuits through artificial neural networks. The reliability of artificial intelligence systems was proven on the basis of a model-based system depending on the task, and the obtained values were experimentally compared in the electrical operation of existing equipment in general industrial enterprises. An imitation model of the real object was developed. A concept of increasing productivity was set up to identify malfunctions, in contrast to the existing annular method. The article developed an algorithm for increasing the operational reliability of the electrical operation of the weaving machine on the basis of integrated indicators of excitation to determine the probability of failure of electrical operation. The article proposes the possibility of directly processing the diagnostic energy parameters through artificial neural networks. An experimental combination of signals resulted in a model based on input power and torque, and was based on an asynchronous motorized electrical circuit. It has been proven that intellectual reliability can be increased by 3-5% compared to operational reliability in traditional methods.

The Christology of Cyril of Alexandria

Cyril of Alexandria is best known for his teaching on Christ (Christology). Beginning with the wider soteriological framework for Cyril’s teaching on Christ, this study will first establish the core principles and then move to consider contested and controversial aspects of Cyril’s Christology. By drawing attention to Cyril’s frequent statements that the Incarnate Christ acts both “as man” (as a human being) and “as God”, I will offer support for there being two active natures in Cyril’s view of Christ and will propose that Cyril’s Christ acting “as man” opens the way for recognizing the specific human activity of Christ that is intended as a model for human imitation. The study will conclude with considerations on the wider ecumenical impact of Cyril’s Christological doctrine.

Recovery of gestures for persons with severe non-fluent aphasia and limb apraxia: A long-term follow-up study

Persons with severe non-fluent aphasia would benefit from using gestures to substitute for their absent powers of speech. The use of gestures, however, is challenging for persons with aphasia and concomitant limb apraxia. Research on the long-term recovery of gestures is scant, and it is unclear whether gesture performance can show recovery over time. This study evaluated the recovery of emblems and tool use pantomimes of persons with severe non-fluent aphasia and limb apraxia after a left hemisphere stroke. The Florida Apraxia Screening Test-Revised (FAST-R) was used for measurements. The test includes 30 gestures to be performed (i) after an oral request, (ii) with the aid of a pictorial cue, or (iii) as an imitation. The gestures were rated on their degree of comprehensibility. The comprehensibility of gestures after an oral request improved significantly in five out of seven participants between the first (1–3 months after the stroke) and the last (3 years after) examination. Improvement continued for all five in the period between six months and three years. The imitation model did improve the comprehensibility of gestures for all participants, whereas the pictorial cue did so just slightly. The skill of producing gestures can improve even in the late phase post-stroke. Because of this potential, we suggest that gesture training should be systematically included in the rehabilitation of communication for persons with severe non-fluent aphasia.

State Support for Commercialization of Intellectual Activity Results in Socially Significant Industries

The pharmaceutical industry is one of the leaders in terms of the intensity of commercialization of the intellectual activity results (IAR). Its development as a socially significant industry is a priority in the state policy of countries with developing economies, in particular, the countries of the Latin American region (LA). A number of economic conditions for the development of commercialization of the IAR in these countries are similar to the Russian economy. Common barriers to development include dependence on imported substances, inefficient interaction between science and business, lack of public and private investment in R&D, and insufficient development of the intellectual property (IP) institution. At the same time, it is possible to identify common growth drivers: the growth potential of the consumer market, unique natural resources, relatively high scientific potential, and the concentration of R&D in research institutes and universities. The similarity of the conditions helps to suggest that it is possible to adapt the best practices of IAR commercialization formed in the LA, to the Russian economy. The research method used in this article include analyzing published legislative and statistical materials on financial institutions of the LA countries in order to identify problems and experience in overcoming them in the field of commercialization of intellectual property. The analysis of state support for imitation, closed and open models of commercialization of IAR used by pharmaceutical companies in developing economies made it possible to identify successful support mechanisms, as well as positive and negative results of the application of each model. On this basis, as the results of the research recommendations for state support for the commercialization in socially significant industries of the Russian economy are suggested.

Mimicking the Maestro: Exploring the Efficacy of a Virtual AI Teacher in Fine Motor Skill Acquisition

Motor skills, especially fine motor skills like handwriting, play an essential role in academic pursuits and everyday life. Traditional methods to teach these skills, although effective, can be time-consuming and inconsistent. With the rise of advanced technologies like robotics and artificial intelligence, there is increasing interest in automating such teaching processes. In this study, we examine the potential of a virtual AI teacher in emulating the techniques of human educators for motor skill acquisition. We introduce an AI teacher model that captures the distinct characteristics of human instructors. Using a reinforcement learning environment tailored to mimic teacher-learner interactions, we tested our AI model against four guiding hypotheses, emphasizing improved learner performance, enhanced rate of skill acquisition, and reduced variability in learning outcomes. Our findings, validated on synthetic learners, revealed significant improvements across all tested hypotheses. Notably, our model showcased robustness across different learners and settings and demonstrated adaptability to handwriting. This research underscores the potential of integrating Imitation and Reinforcement Learning models with robotics in revolutionizing the teaching of critical motor skills.

Artificial intelligence for COVID-19 spread modeling

Abstract This paper presents classification and analysis of the mathematical models of the spread of COVID-19 in different groups of population such as family, school, office (3–100 people), town (100–5000 people), city, region (0.5–15 million people), country, continent, and the world. The classification covers major types of models (time-series, differential, imitation ones, neural networks models and their combinations). The time-series models are based on analysis of time series using filtration, regression and network methods. The differential models are those derived from systems of ordinary and stochastic differential equations as well as partial differential equations. The imitation models include cellular automata and agent-based models. The fourth group in the classification consists of combinations of nonlinear Markov chains and optimal control theory, derived by methods of the mean-field game theory. COVID-19 is a novel and complicated disease, and the parameters of most models are, as a rule, unknown and estimated by solving inverse problems. The paper contains an analysis of major algorithms of solving inverse problems: stochastic optimization, nature-inspired algorithms (genetic, differential evolution, particle swarm, etc.), assimilation methods, big-data analysis, and machine learning.

The resilience of the regional ecosystems: Healthcare-service organizations, public agents and communities in the times of COVID-19

The aim of this study is to compare regional ecosystems' resilience in terms of their ability to contain the spread of Covid-19. This is carried out through institutional measures as well as through spontaneous community behaviour in order to preserve public health and the institutional actions to strengthen the health-care system in dealing with the pandemic. The discussion is framed through the institutional approach. We develop a twostep method. In the first step, regions have been clustered by considering the kind of response to Covid-19, in terms of formal and informal rules. In the second step a random effect panel regression analysis was performed in order to define the effect of the single response variable to Covid-19 on the resilience index over time. Implications for policy makers are then discussed. The first is that coping with a regional emergency requires taking into account regional specificities. Strictly imitative models risk being inconsistent with the characteristics of the area, resulting in outputs that are not homogeneous. The second involves social capital, which is crucial to the application of the norms. In regions with high social capital there is a sense of solidarity that presents itself in informal rules aimed at reinforcing the formal rules. However, there is no sense of conformity for the sake of conformance to the standard.

СУТНІСТЬ ІМІТАЦІЙНОГО МОДЕЛЮВАННЯ

The article examines the issue of the essence of simulation modeling. As our world grows increasingly complex, understanding and managing intricate systems become more challenging. Imitative modeling offers a way to simplify and study these systems, providing valuable insights into their behavior and interactions. Advancements in technology, particularly in computing power and simulation software, have made imitative modeling more sophisticated and accessible. This technological progress enables more accurate and detailed simulations, enhancing the value and applicability of modeling across various fields. Imitative modeling provides a tool to simulate different scenarios, evaluate options, and optimize outcomes, thus supporting better decision-making processes. Furthermore, imitative modeling drives innovation by identifying new approaches or configurations that optimize performance. Whether it's designing a new product, improving a manufacturing process, or optimizing a supply chain, modeling can help find the best solutions to complex problems. Addressing global challenges such as climate change, environmental sustainability, public health, and urban planning requires informed strategies and policies. Imitative modeling can play a crucial role in this by simulating the impact of different interventions or policies, thereby informing better approaches to tackle these pressing issues. Additionally, imitative modeling serves as a valuable educational tool, helping students understand complex concepts and theories through practical application. It also supports research by providing a framework for hypothesis testing, data analysis, and validation. It is noted that the widespread use of simulation modeling became a reality at a certain stage of the development of information technologies, which include means of collecting, transmitting, processing and storing information. These means include not only computers, but also computational mathematics tools, multi-level programming tools, database management systems, data banks, and others. The simulation model is a complex mathematical and algorithmic structure, which is intended for the study of a certain system. The method, which is based on the creation and analysis of simulation models, is called "machine simulation" or "simulation modeling".

ОСНОВНІ ЕТАПИ ПОБУДОВИ ІМІТАЦІЙНОЇ МОДЕЛІ

The article examines the issue of the essence of simulation modeling. As the complexity of systems and processes across various sectors continues to grow, the ability to construct accurate and effective simulation models becomes increasingly important. Understanding the key stages of building an imitative model is crucial for ensuring the model's validity, reliability, and relevance to real-world scenarios. These stages typically involve problem definition, data collection and analysis, model design, validation, and implementation. Each stage requires careful planning, expertise, and attention to detail to ensure that the model accurately represents the system being studied. In today's fast-paced and competitive environment, organizations and decision-makers rely on simulation models to analyze complex scenarios, evaluate strategies, and make informed decisions. Therefore, having a clear understanding of the key stages of model building is essential for leveraging simulation modeling effectively as a decision-making tool. Furthermore, advancements in computational technologies and software tools have made it easier than ever to build complex simulation models. However, this also introduces challenges related to data quality, model complexity, and validation. Thus, knowledge of the key stages of building an imitative model is crucial for addressing these challenges and ensuring the model's accuracy and reliability. It is noted that the advantages of simulation modeling include the high adequacy of the model to the physical properties of the object, the possibility of a detailed description of complex systems, the research area that exceeds the capabilities of analytical modeling, the absence of restrictions on the display of dependencies in the model, the possibility of evaluating the functioning of the system in different modes, as well as obtaining extensive information about the object. It is emphasized that the sequence of building a simulation model involves the following steps: definition of the problem and its analysis; determination of information requirements; information gathering; proposing hypotheses and accepting assumptions; establishment of the main content of the model; determination of parameters, variables and efficiency criteria; description of the conceptual model and verification of its plausibility; construction of a logical structural diagram (block diagram).

Venture Aging: A Process Model of Legitimacy, Routinization, and Competitor Imitation of Venture Innovation Capabilities

This study proposes a process model that delineates how venture aging results in legitimacy and routinization, and subsequent venture performance. This model addresses the gap between new venture literature and organizational management literature. The resource-based view of the firm and competitive rivalry models are used to develop the theory behind the process model. The model shows that venture aging enhances legitimacy, which is shown to increase competitor attacks and imitation attempts of venture innovation capabilities. Venture routinization increases the inimitability of a venture’s innovation capabilities, which decreases the success of competitors trying to imitate the new venture. The resulting effects on venture performance identify approaches that entrepreneurs can take to increase their chances of successfully navigating the venture aging process. The model assists researchers in further developing the competitive rivalry literature by explaining how factors such as awareness, motivation, and capability of competitors influence venture success.

РАЗРАБОТКА СЦЕНАРИЕВ ДЛЯ ИМИТАЦИОННОГО МОДЕЛИРОВАНИЯ ЭКОСИСТЕМНЫХ УСЛУГ ЛЕСОВ

Sustainable forest management implies the necessity to maintain and uphold the balance between the growing demand for forest ecosystem services and the capabilities present. This issue motivates the development of ways to include various ecosystem services in the forest ecosystem planning and management system, taking into account social, political, environmental, and economic contexts. One of the effective tools for ecosystem service management is imitation modelling, which allows assessing the decision-making risks and consequences. This raises the scientific problem of substantiating possible alternative scenarios for future forested area development for subsequent simulation. This article is aimed at analysing the approaches to creating scenarios for the development of a forest area for local-level imitation modelling and testing a new method based on the development of the existing approaches to solving this problem. In its first part, modern research analysis in the field of imitation scenario development is presented; the second one proposes a new method for compiling scenarios, created within the framework of the POLYFORES project, and also presents the results of its testing at three model sites located in the Nizhny Novgorod Region, the Republic of Karelia, and the Moscow Region. For the forest plots of the Nizhny Novgorod Region, four scenarios for forest area development have been created, aimed at obtaining benefits: 1 – from timber harvesting, 2 – from recreational ecosystem services and food forest resources, 3 – from regulating ecosystem services, 4 – both from timber harvesting, under the conditions of intensified forest growing, and from regulating ecosystem services. For forest plots in the Republic of Karelia, the first scenario describes the situation of meeting the demand for wood, while also preserving the biodiversity and regulating ecosystem services; the second and third scenarios take into account the increased demand for wood, with low and high priorities for environmental conservation. For the forest plots of the Moscow Region, only two scenarios were relevant, with the increasing need of citizens for recreational ecosystem services, and the biodiversity preservation priority in management decision-making either remaining low or increasing. For each scenario, forestry activities corresponding to the management objectives have been developed. The proposed scenarios can be used to obtain information about the impact of various management decisions on providing forest ecosystem services.

DUBIA TEXTS IN THE ACADEMIC EDITION OF TARAS SHEVCHENKO’S WORKS: THE PROBLEM OF AUTHORSHIP

The paper assesses the validity of including several works in the “Dubia” section of the academic edition. Th ere are grounded doubts regarding Shevchenko’s authorship of the poem “I am bored, it is hard — what should I do?” from the manuscript “Kobzar” of 1861, which belonged to Ivan Levchenko. The main warning is that the poem “Polubotok” was also copied into the same manuscript “Kobzar”, but Shevchenko’s authorship in this case has long been disproven. Therefore, Ivan Levchenko cannot be considered an authoritative expert on the poet’s works. It is plausible that an unknown epigone took “Ballad” (“Weary-dreary lags and drags”) as a model for imitation.
 There is no doubt that the poem-dedication “Tribute to Shternberg” on the now unknown copy of “Kobzar” of 1840 belongs to Shevchenko. The sole known text of the poem “I do not grieve, but do not sleep...” was cited by Oleksandr Afanasiev-Chuzhbynskyi in his memoirs about Shevchenko. Since there is no reason to doubt the reliability of this memoirist, who is known for his accuracy and thoroughness, Shevchenko’s authorship should be definitively confirmed. As for the quatrain “Drink the first, you’ll be aroused...”, despite the compelling testimonies of Shevchenko’s authorship, there is still insufficient certainty to include this poem in the main body.
 As a result of the analysis, it is proposed that the poem “I am bored, it is hard — what should I do?..”, as well as the note “Picturesque Ukraine” from the newspaper “Northern Bee” of 1844, be removed from the edition of Shevchenko’s works as not belonging to the poet. The impromptu “Drink the first, you’ll be aroused...” must be left in the “Dubia” section, while the poems “Tribute to Shternberg”, “I do not worry, but do not sleep...” should be unconditionally transferred to the main body.

An imitation model based on the majority

In the voter model, agents possess binary opinions. At each time step, an agent is selected along with a social neighbor and adopts the opinion of that neighbor at the next time step. In this paper, we delve into a variant of the voter model known as an imitation model based on the majority. This model represents a network opinion framework where individuals, situated on the vertex set of a finite connected graph interpreted as a social network, exhibit one of two competing opinions labeled as +1 and −1. The agent alters its opinion solely when the count of social neighbors holding opposing viewpoints exceeds those aligning with the agent’s opinion. We explore the conditions leading to a consensus and investigate the probability of consensus on a finite connected social graph.

Imitative Virtual Reality-Based Modeling of Flying Vehicles Control on a Lunar Station to Investigate an Operator’s Activity in Isolation Experiments

Imitative Virtual Reality-Based Modeling of Flying Vehicles Control on a Lunar Station to Investigate an Operator’s Activity in Isolation Experiments

Simulation of Diffusion Magnetic Resonance Based on Chain Method

Magnetic resonance diffusion imaging is an important tool for pathology research, and the cost of instrument development is extremely high. The construction of simulation models can optimize the parameters of key components of the instrument on the numerical platform, which can greatly reduce the R&D cost and improve the success rate. In this paper, a chain magnetic resonance simulation calculation method is obtained based on equation Bloch-Torrey to simulate the signal change law caused by gradient coding and diffusion characteristics, and MATLAB is used to construct a numerical imitation model and write a simulation program. Based on this calculation method, the diffusion-weighted imaging, diffusion coefficient imaging and diffusion tensor imaging simulation experiments were carried out by using the spin-echo (SE) diffusion-weighted sequence, and the images and results were reconstructed by combining the anti-Fourier transform. Experiments show that the simulated images can accurately reflect the set simulation model, reconstruct the diffusion coefficient and tensor characteristics, and the chain magnetic resonance simulation calculation method deduced in this paper.