Interconnection Model Research Articles

Environmental and socioeconomic interconnection models and algorithms for managing competitively sustainable regional development

The relevance of the work is stipulated by the need to develop a measurement toolkit of energy, environmental, social, and economic processes in the focus of interdisciplinary research. The aim of the research is to form an objective tool for measuring the state of regional systems, taking into account the interrelation of environmental, social, and economic processes. The methodological basis of the work is physical and economic indicators reflecting the interrelation of natural and economic processes. The main hypothesis put forward is that it is possible to build an integral index that objectively describes the model of competitively sustainable development of regions in the context of the interrelation of energy, environmental, social, economic processes. The results of the study have shown that the physical-economic (natural-physical) law operating in economic life, in the economy is the law of conservation of energy (power) flow, and the methodological basis for the construction of an integrated model of regional development should be the requirements arising from the law of conservation of energy (power) flow. The work is the result of theoretical, methodological, and applied research on systemic natural-scientific analysis of development management in socioeconomic systems considered in interaction with the environment. The results of the study contribute to the understanding of methodological possibilities of non-monetary measurement and on this basis the construction of a multilevel complex model in terms of natural-scientific indicators. The analysis of the results of application of the developed models allows to reveal conditions and limitations of energy, ecological, social, economic development of regions.

Life Experiences and Teaching Practices: An Analysis of Role Models in Accountancy

This study seeks to understand the meaning of experiences and knowledge used in the process of professional development of teachers of undergraduate courses in Accountancy in Brazil. It was used as the theoretical basis for the Interconnected Model of Professional Growth of Teachers and the teaching knowledge from Tardif’s perspective. A semi-structured interview with a qualitative and reflective approach was used as a technique to build the narratives. The analyzed excerpts were grouped into four analysis categories: the personal domain, related to the disciplinary knowledge of accounting; the domain of practice and the didactic-pedagogical knowledge; the external domain and experiential knowledge; and the domain of consequence, highlighting the significant results in professional development. From the analyses, it is concluded that teachers develop in teaching through reflection and action on their practice; through the positive relationships of partnership, support, and guidance established with their students; through the careful search for the exchange of experiences with peers and with the professional market; as well as through the personal search for the improvement of their daily teaching practice.

Slagging Characteristics of a Steam Boiler Furnace with Flare Combustion of Solid Fuel When Switching to Composite Slurry Fuel

Two interconnected mathematical models have been developed to describe slagging of a steam boiler furnace at the macro and micro levels. The macro-level model is implemented in Ansys Fluent. Using the fuel characteristics and temperature in the furnace, this model can predict the characteristics of ash formation on heat exchanger tubes when the melting temperature of the mineral part of solid fossil fuel is exceeded. The obtained values of slagging rates are used as initial data in the software implementation of the original Matlab microlevel model. Under conditions of dynamic change in the thickness of the slag layer, this model can evaluate the heat transfer characteristics in the hot gas/slag layer/tube wall/water coolant system. The results showed that switching a coal-fired boiler from a solid fossil fuel to a fuel slurry will improve stability and uninterrupted boiler operation due to a lower slagging rate. The combustion of coal water slurries with petrochemicals compared with coal–water fuel is characterized by higher maximum temperatures in the furnace (13–38% higher) and a lower average growth rate of slag deposits (5% lower), which reduces losses during heat transfer from flue gases to water coolant by 2%.

Examining teachers' learning through a project-based learning lesson study: a case study in China

PurposeThis study explored how teachers change, what teachers learn and how they learn during the implementation of project-based learning through lesson study.Design/methodology/approachIn this study, three university researchers, one doctoral student and six mathematics school teachers formed a lesson study team. Using a qualitative research method, this study employed a locally integrating networking strategy to combine the modified Interconnected Model of Teacher Professional Growth (IMTPG) and Bannister's framework to describe the teachers' knowledge change when participating in a lesson study on project-based learning.FindingsThe research revealed that the school teachers' knowledge about authenticity and assessment in the context of project-based learning was changed after the lesson study and how the changes were triggered.Originality/valueThe study demonstrates how the networking of two different theories—modified IMTPG and Bannister's framework—contributes to a better understanding of the process of teachers' collective practice, as well as the knowledge change in PjBL. This networking was done by combining the two theories, which were superimposed at the domain of practice.

Демаркация идентичности: проблема сохранения суверенитета индивида в цифровом пространстве

Introduction. In the digital age, the individual becomes the bearer and victim of an ambivalent and labile individual identity: a real identity, as an expression of one's own individuality, including personal, group, professional, gender, ethnic, civil, and a virtual identity, as a user of an information resource with an individual digital code. Today, a universal era of active imitation of real life is being formed, the construction of an anonymous individual based on a total upgrade of his identification codes. Theoretical basis of the study. Based on the identification and analysis of individual identity in the digital space, the conceptualization of various approaches to characterizing identity was carried out. It is expressed in the fact that the situational approach characterizes a theoretical construction that describes the ability of a person to form his identity in various situations and, in order to preserve his individuality, deviate from the general norms of group behavior; the intersubjective approach defines the unique place of the individual, his awareness as a consequence of internalization in the existing symbolic organization of the group; the structural-functional approach explicates a fixed set of attributions of an individual, which include his personal traits, functional characteristics and motivational structure. Results and its discussion. In the digital environment, the identification constructs of the individual are reproduced as some instrumental matrices or original operational models of everyday and social communication, models of relationships and interconnections in the plurality of social worlds. At the same time, reflecting social reality, the individual forms his attitude towards it according to the identification construct, and realizing his actions according to these matrices and models, the individual creates a part of reality itself, changes it, transforms it. Considering that an identification construct can be a purposefully formed or involuntarily emerging way of reflecting the reality that dominates an individual, it can be represented as a pragmatic-target result of a direct impact on the subject of an artificially constructed environment (manipulation), or as a consequence of a rational attitude to social reality in the form of a product of social experiences and social feelings determined by the principles and rules of the dominant reality.

Многоуровневые алгоритмы оценки и принятия решений по оптимальному управлению комплексной системой переработки мелкодисперсного рудного сырья

The results of studies aimed at developing multi-level decision-making algorithms for management of energy and resource efficiency, technogenic and environmental safety of a complex multi-stage system for processing fine ore raw materials are presented (MSPFORM). A distinctive feature of such a system is its multidimensionality and multiscale, which manifests itself in the presence of two options for implementing technological processes for processing finely dispersed ore raw materials, the need to take into account the interaction of the aggregates included in the system, as well as the hierarchy of describing the processes occurring in them - mechanical, thermophysical, hydrodynamic, physical and chemical. Such a variety of processes characterizes the interdisciplinarity of research and the complexity of obtaining analytical, interconnected mathematical models. This situation inspired the analyze use of artificial intelligence methods, such as deep machine learning and fuzzy logic, to describe and analyze processes. The scientific component of the research results consists in the developed generalized structure of the MSPFORM, the conceptual basis of multilevel algorithms for evaluating and making decisions on the optimal control of this system, the proposed composition of the parameters and the form of the optimization criterion. The task of the study was to analyze possible options for the processing of ore raw materials, to develop a concept for the construction of the MSPFORM allowing the possibility of optimizing its functioning according to the criterion of energy and resource efficiency while meeting the requirements of environmental safety. The application of evolutionary algorithms for solving the problem of optimizing the MSPFORM according to the criterion of minimum energy consumption is announced and its stages are specified. The structure of the block of neuro-fuzzy analysis of information about the parameters of processes in MSPFORM is presented, which is based on the use of deep recurrent and convolutional neural networks, as well as a fuzzy inference system. The results of a simulation experiment on approbation of the software implementation of this block in the MatLab environment are presented.

Mechanistic model for human brain metabolism and its connection to the neurovascular coupling.

The neurovascular and neurometabolic couplings (NVC and NMC) connect cerebral activity, blood flow, and metabolism. This interconnection is used in for instance functional imaging, which analyses the blood-oxygen-dependent (BOLD) signal. The mechanisms underlying the NVC are complex, which warrants a model-based analysis of data. We have previously developed a mechanistically detailed model for the NVC, and others have proposed detailed models for cerebral metabolism. However, existing metabolic models are still not fully utilizing available magnetic resonance spectroscopy (MRS) data and are not connected to detailed models for NVC. Therefore, we herein present a new model that integrates mechanistic modelling of both MRS and BOLD data. The metabolic model covers central metabolism, using a minimal set of interactions, and can describe time-series data for glucose, lactate, aspartate, and glutamate, measured after visual stimuli. Statistical tests confirm that the model can describe both estimation data and predict independent validation data, not used for model training. The interconnected NVC model can simultaneously describe BOLD data and can be used to predict expected metabolic responses in experiments where metabolism has not been measured. This model is a step towards a useful and mechanistically detailed model for cerebral blood flow and metabolism, with potential applications in both basic research and clinical applications.

Cognitive Model for Assessing the Security of Information Systems for Various Purposes

This article substantiates the relevance of the development of a cognitive model for assessing the security of information systems for various purposes, designed to support decision-making by officials of information security management bodies. The article analyzes scientific papers and research in this area, formulates the requirements for the functional capabilities of the model, and investigates and identifies the most appropriate modeling tools, based on the symmetry property that develops from integrated ontological and neuro-Bayesian models; typical clusters of information systems; tactics and techniques for the implementation of information security threats through the vulnerabilities of objects at various levels of the International Organization of Standardization/Open Systems Interconnection model (the ISO/OSI model); protective influences; and attacking influences. This approach allowed us to identify such objects of influence and their current vulnerabilities and scenarios for the implementation of information security threats; to calculate the joint probability distribution of information security events of various origins; and to simulate the process of operational management of information security.

A comprehensive review of digital twin—part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision- and policy-making, and more, by comprehensively modeling the physical world as a group of interconnected digital models. In a two-part series of papers, we examine the fundamental role of different modeling techniques, twinning enabling technologies, and uncertainty quantification and optimization methods commonly used in digital twins. This second paper presents a literature review of key enabling technologies of digital twins, with an emphasis on uncertainty quantification, optimization methods, open-source datasets and tools, major findings, challenges, and future directions. Discussions focus on current methods of uncertainty quantification and optimization and how they are applied in different dimensions of a digital twin. Additionally, this paper presents a case study where a battery digital twin is constructed and tested to illustrate some of the modeling and twinning methods reviewed in this two-part review. Code and preprocessed data for generating all the results and figures presented in the case study are available on Github.

Experimental identification of individual insect visual tracking delays in free flight and their effects on visual swarm patterns.

Insects are model systems for swarming robotic agents, yet engineered descriptions do not fully explain the mechanisms by which they provide onboard sensing and feedback to support such motions; in particular, the exact value and population distribution of visuomotor processing delays are not yet quantified, nor the effect of such delays on a visually-interconnected swarm. This study measures untethered insects performing a solo in-flight visual tracking task and applies system identification techniques to build an experimentally-consistent model of the visual tracking behaviors, and then integrates the measured experimental delay and its variation into a visually interconnected swarm model to develop theoretical and simulated solutions and stability limits. The experimental techniques include the development of a moving visual stimulus and real-time multi camera based tracking system called VISIONS (Visual Input System Identification from Outputs of Naturalistic Swarms) providing the capability to recognize and simultaneously track both a visual stimulus (input) and an insect at a frame rate of 60-120 Hz. A frequency domain analysis of honeybee tracking trajectories is conducted via fast Fourier and Chirp Z transforms, identifying a coherent linear region and its model structure. The model output is compared in time and frequency domain simulations. The experimentally measured delays are then related to probability density functions, and both the measured delays and their distribution are incorporated as inter-agent interaction delays in a second order swarming dynamics model. Linear stability and bifurcation analysis on the long range asymptotic behavior is used to identify delay distributions leading to a family of solutions with stable and unstable swarm center of mass (barycenter) locations. Numerical simulations are used to verify these results with both continuous and measured distributions. The results of this experiment quantify a model structure and temporal lag (transport delay) in the closed loop dynamics, and show that this delay varies across 50 individuals from 5-110ms, with an average delay of 22ms and a standard deviation of 40ms. When analyzed within the swarm model, the measured delays support a diversity of solutions and indicate an unstable barycenter.

A comprehensive review of digital twin — part 1: modeling and twinning enabling technologies

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision and policy making, and more, by comprehensively modeling the physical world as a group of interconnected digital models. In a two-part series of papers, we examine the fundamental role of different modeling techniques, twinning enabling technologies, and uncertainty quantification and optimization methods commonly used in digital twins. This first paper presents a thorough literature review of digital twin trends across many disciplines currently pursuing this area of research. Then, digital twin modeling and twinning enabling technologies are further analyzed by classifying them into two main categories: physical-to-virtual, and virtual-to-physical, based on the direction in which data flows. Finally, this paper provides perspectives on the trajectory of digital twin technology over the next decade, and introduces a few emerging areas of research which will likely be of great use in future digital twin research. In part two of this review, the role of uncertainty quantification and optimization are discussed, a battery digital twin is demonstrated, and more perspectives on the future of digital twin are shared. Code and preprocessed data for generating all the results and figures presented in the battery digital twin case study in part 2 of this review are available on Github .

A systematic review of the critical success factors for implementing circular economy in construction projects

AbstractThe transition to a circular economy in the construction industry provides enormous opportunities to decouple construction activities, processes, and practices from finite consumption of natural resources and environmental externalities. Circular construction leverages the interconnected models of narrowing, slowing, and closing resource loops to minimize extractive and wasteful use of natural resources, eliminate waste and pollution from the outset, and retain construction products and materials in use for a longer duration. However, construction practitioners have struggled to implement circular economy principles into construction projects successfully. This study systematically reviewed the critical success factors for implementing circular construction projects. The results revealed 51 critical success factors for circular construction projects, clustered into six typologies: technological (n = 10, ∑ = 93, μ = 9.30), supply chain (n = 14, ∑ = 84, μ = 6.00), organizational (n = 9, ∑ = 82, μ = 9.11), institutional (n = 7, ∑ = 43, μ = 6.14), stakeholder success (n = 7, ∑ = 73, μ = 10.43), and management success factors (n = 4, ∑ = 27, μ = 6.75). A Pareto analysis revealed 30 vital critical success factors for circular construction projects. Thus, the study established the first comprehensive set of critical success strategies for circular construction projects and enriches the knowledge of construction organizations and project team members on how best to implement circular economy principles in construction projects.

How EFL Teachers’ Pedagogical Content Knowledge (PCK) Grows Through Collaborative Learning: A Review Based on The Interconnected Model of Professional Growth (IMPG)

Since Shulman (1986b) argued that pedagogical content knowledge (PCK) should be a significant indicator of teacher knowledge for quality teaching, PCK has received enormous attention from researchers in the teacher education field. Nevertheless, little empirical and theoretical attention has been given to English as a Foreign Language (EFL) teachers’ PCK growth in teachers’ collaborative learning activities (Li et al., 2021). In practice, collaborative learning groups for EFL teachers are often adopted as an effective teacher learning activity as it always integrates observations and discussions of real EFL teaching practices such as English teaching pedagogies and subject matters, for example. However, how EFL teachers’ collaborative learning promotes their PCK growth is less explored by empirical or theoretical studies and some teacher professional growth models. Therefore, this review will mainly discuss via existing literature how EFL teachers could increase their PCK in collaborative learning based on one particular teacher professional growth model, called the Interconnected Model of Professional Growth (IMPG) summarized by Clarke and Hollingsworth (2002). Since IMPG only generally summarizes teachers’ professional growth, this article aims to specifically elaborate the various trajectories of EFL teachers’ PCK growth. The significant role of three essential factors, namely, EFL teachers’ initiatives to learn/share, reciprocal mindset, and reflective dialogues in EFL teachers’ PCK development are stated in the paper. Several recommendations are made to EFL teachers, EFL teacher trainers, and EFL education programs.

Intelligent Fault Detection in Hall-Effect Rotary Encoders for Industry 4.0 Applications

Sensors are the foundational components of any smart machine system and are invaluable in all modern technologies. Consequently, faults and errors in sensors can have a significant negative impact on the setup. Intelligent, lightweight, and accurate fault diagnosis and mitigation lie at the crux of modern industries. This study aimed to conceptualize a germane solution in the domain of fault detection, focusing on Hall-effect rotary encoders. Position monitoring through rotary encoders is essential to the safety and seamless functioning of industrial equipment such as lifts and hoists, and commercial systems such as automobiles. This work used multi-strategy learners to accurately diagnose quadrature and offset faults in Hall-effect rotary encoders. The obtained dataset was then run through a lightweight ensemble classifier to train a robust fault detection model. The complete mechanism was simulated through interconnected models simulated in a MATLAB Simulink™ environment. In real time, the developed fault detection algorithm was embedded in an FPGA controller and tested with a 1 kW PMSM drive system. The resulting system is computationally inexpensive and achieves an accuracy of 95.8%, making it a feasible solution for industrial implementation.

Network Uncertainty Quantification for Analysis of Multi-Component Systems

Abstract In order to impact physical mechanical system design decisions and realize the full promise of high-fidelity computational tools, simulation results must be integrated at the earliest stages of the design process. This is particularly challenging when dealing with uncertainty and optimizing for system-level performance metrics, as full-system models (often notoriously expensive and time-consuming to develop) are generally required to propagate uncertainties to system-level quantities of interest. Methods for propagating parameter and boundary condition uncertainty in networks of interconnected components hold promise for enabling design under uncertainty in real-world applications. These methods avoid the need for time consuming mesh generation of full-system geometries when changes are made to components or subassemblies. Additionally, they explicitly tie full-system model predictions to component/subassembly validation data which is valuable for qualification. These methods work by leveraging the fact that many engineered systems are inherently modular, being comprised of a hierarchy of components and subassemblies that are individually modified or replaced to define new system designs. By doing so, these methods enable rapid model development and the incorporation of uncertainty quantification earlier in the design process. The resulting formulation of the uncertainty propagation problem is iterative. We express the system model as a network of interconnected component models, which exchange solution information at component boundaries. We present a pair of approaches for propagating uncertainty in this type of decomposed system and provide implementations in the form of an open-source software library. We demonstrate these tools on a variety of applications and demonstrate the impact of problem-specific details on the performance and accuracy of the resulting UQ analysis. This work represents the most comprehensive investigation of these network uncertainty propagation methods to date.

Thermo-Mechanical Reliability Study of Through Glass Vias in 3D Interconnection.

Three-dimensional (3D) interconnection technology based on glass through vias (TGVs) has been used to integrate passive devices, and optoelectronic devices due to its superior electrical qualities, outstanding mechanical stability, and lower cost. Nevertheless, the performance and reliability of the device will be impacted by the thermal stress brought on by the mismatch of the coefficient of thermal expansion among multi-material structures and the complicated structure of TGV. This paper focuses on thermal stress evolution in different geometric and material parameters and the development of a controlled method for filling polymers in TGV interconnected structures. In addition, a numerical study based on the finite element (FE) model has been conducted to analyze the stress distribution of the different thicknesses of TGV-Cu. Additionally, a TGV interconnected structure model with a polymer buffer layer is given to solve the crack problem appearing at the edge of RDL. Meanwhile, after practical verification, in comparison to the experimental results, the FE model was shown to be highly effective and accurate for predicting the evolution of stress, and several recommendations were made to alleviate stress-related reliability concerns. An improved manufacturing process flow for the TGV interconnected structure was proposed and verified as feasible to address the RDL crack issue based on the aforementioned research. It provides helpful information for the creation of highly reliable TGV connection structures.

Instability risk analysis of distributed renewable energy caused by energy storage balance zone

An energy storage balance zone (ESBZ) is formed by multiple energy storages to suppress fluctuations in distributed renewable energy (DRE). However, the effects of an ESBZ on the dynamic stability of DRE have usually been ignored, resulting in the underestimation of the potential instability risk. In this study, the impact of dynamics of an ESBZ on the small signal stability of DRE under different steady states was analyzed, and the dynamic instability risk clarified. First, a linearized interconnection model of the ESBZ and DRE was established in d-q coordinates, so that the model can be transformed into a single-input and single-output model. Based on this model, the virtual-damping method was used to analyze the influence of the ESBZ on stability of the DRE. It was found that the effects of the ESBZ vary at different steady states. The different power flows of DRE and ESBZ have different effects on DRE stability. Moreover, the increasing number of ESBZs can amplify the effects on the DRE, in the worst case, leading to instability of the DRE. Therefore, a method was proposed to determine the scale of the ESBZ considering the critical stability of the DRE. Finally, in this paper, a distribution-network system with ESBZ and DRE is selected as an example to demonstrate the correctness of the conclusions.

Model Development of Universal Hardware and Software Module for Medical Information System

Medical information systems (MIS) are the object of the research presented. They allow information processing throughout the patient's interaction with medical services - from contacting such institutions to monitoring the patient after rehabilitation. However, for various reasons, during the information process exchange within the framework of MIS, distortions of collected or transmitted data are possible, which leads to wrong medical decisions. Currently, new approaches are being implemented using Software-Defined Networks, but our work proposes an alternative solution designed to work conservatively with existing equipment using established protocols. To solve the stated problem, this study has developed a universal hardware-software module (UHSM) model, which ensures the effective transmission of sophisticated medical information through networks. A distinctive feature of such UHSM is the connection of different medical equipment in various related to MIS information networks, as well as automatic configuration under all current standards. The study demonstrates that for the most effective UHSM functioning, it is essential to consider the existing features arising during the interaction process of devices in the context of modern networks created for information exchange, based on the established communication model of open-system interconnection (OSI). Keywords—classification methods, information coding methods, information networks, knowledge base, medical information system, multilevel approach, structure synthesis of large systems, telemedicine technologies

Accurate Crosstalk Noise Modeling and Analysis of Non-Identical Lossy Interconnections Using Convex Optimization Method

Recent studies on integrated circuits interconnections are mainly concentrated on the analysis of crosstalk and delay, by taking the trade-off between accuracy, speed, and complexity into consideration. The new idea of this paper is to apply the convex optimization method to analyze crosstalk and delay of the lossy coupled interconnections in identical and non-identical forms. For this purpose, a simple and comprehensive model is proposed to cover the functional and dynamic crosstalk in a computationally-effective way. More specifically, various case studies are determined to analyze the transient response of the coupled transmission lines with arbitrary excitation sources in the presence of both capacitive and inductive coupling characteristics. To validate the model, the numerical and Advanced Design System (ADS) simulation results are compared to indicate the desired accuracy. The calculated crosstalk percentage error of the proposed model with respect to ADS and HSPICE are less than 1.03% and 1.19%, respectively. In addition, the computational speed of the proposed method is about twice higher than ADS and HSPICE. The proposed model is extendible to handle <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> coupled lines, making it appropriate to model complex integrated circuit interconnections.

The Role of Frustration in Collective Decision-Making Dynamical Processes on Multiagent Signed Networks

In this article, we consider a collective decision-making process in a network of agents described by a nonlinear interconnected dynamical model with sigmoidal nonlinearities and signed interaction graph. The decisions are encoded in the equilibria of the system. The aim is to investigate this multiagent system when the signed graph representing the community is not structurally balanced and in particular as we vary its frustration, i.e., its distance to structural balance. The model exhibits bifurcations, and a “social effort” parameter, added to the model to represent the strength of the interactions between the agents, plays the role of bifurcation parameter in our analysis. We show that, as the social effort increases, the decision-making dynamics exhibit a pitchfork bifurcation behavior where, from a deadlock situation of “no decision” (i.e., the origin is the only globally stable equilibrium point), two possible (alternative) decision states for the community are achieved (corresponding to two nonzero locally stable equilibria). The value of social effort for which the bifurcation is crossed (and a decision is reached) increases with the frustration of the signed network.