Interconnection Model Research Articles

A Novel GSPN Based Interconnection Model for 5 G and CAN Heterogeneous Networks

A Novel GSPN Based Interconnection Model for 5 G and CAN Heterogeneous Networks

Governance of rural solid waste under a multi-subject governance model

Rural solid waste (RSW) exhibits distinct characteristics compared to municipal solid waste (MSW), such as dispersed distribution, long governance chains, and low recycling value, making it unsuitable to apply the same management measures as MSW. Government-led RSW management results in excessive administrative costs, and the inherent characteristics of RSW reduce market enthusiasm for its management. To address these issues, this paper integrates the “ multi-subject governance “ model with RSW management and establishes a systematic evaluation index system for RSW governance. Utilizing the Best-Worst Method (BWM), key factors were identified. Utilizing the VIKOR method, representative provinces in China were used as case studies to validate the scientific nature of the evaluation indices. The research findings indicate that the multi-subject governance model is an effective approach for RSW management. Key factors influencing RSW management effectiveness include various governmental measures, waste sorting, and a long-term multi-subject governance mechanism. Case analysis reveals a strong correlation between the level of economic development and the effectiveness of RSW management. However, constructing a government-led, multi-subject collaborative urban-rural interconnected RSW management model can effectively address RSW management issues in economically underdeveloped areas. This research provides innovative solutions for RSW management, contributing to high-quality and sustainable development in rural areas.

Distributed Autonomous Economic Control Strategy for the AC/DC Interconnected Microgrid Considering the Regulation Boundary of the Consensus Variable

ABSTRACTThe autonomous economic control for the islanded AC/DC interconnected microgrid has various modes due to the restriction of the feasible regions of inner and inter‐microgrid resources. To properly handle the cooperative relationship between resources with different regulation characteristics and realize the frequency, voltage stability, and economic operation of the AC/DC interconnected microgrid, a distributed control strategy considering the regulation boundary of the consensus variable is proposed. Firstly, the influence of the variable feasible regions on the consensus control objective is analyzed, and the fundamental principle of the consensus control algorithm considering the variable regulation boundary is expounded. Secondly, the trilevel control strategy consisting of the local equipment control and inner and inter‐microgrid cooperative control is constructed. The local equipment control adopts droop control, and the cooperative control adopts consensus control to realize the elimination of the frequency and voltage deviation and the economic dispatch of active power within and between microgrids. Finally, the AC/DC interconnected microgrid model is built based on PSCAD/EMTDC, and the simulation results verify the effectiveness of the proposed control strategy.

Proposed Modbus Extension Protocol and Real-Time Communication Timing Requirements for Distributed Embedded Systems

The general evolution of fieldbus systems has been variously affected by both computer electrical engineering and science. First, the main contribution undoubtedly originated from network IT systems, when the Open Systems Interconnection model was presented. This reference model with seven layers was and remains the foundation for the development of numerous advanced communication protocols. In this paper, the conducted research resulted in a major contribution; specifically, it describes the mathematical model for the Modbus protocol and defines the acquisition cycle model that corresponds to incompletely defined protocols in order to provide a timestamp and achieve temporal consistency for proposed Modbus Extension. The derived technical contribution of the authors is to exemplify the functionality of a typical industrial protocol that can be decomposed to improve the performance of data acquisition systems. Research results in this area have significant implications for innovations in industrial automation networking because of increasing distributed installations and Industrial Internet of Things (IIoT) applications.

Evaluation of power system instability probability considering output randomness of grid-connected converter

Abstract In recent years, there has been a notable increase in the installed capacity of new energy sources. Nevertheless, the random nature of the output power of G-CCs may potentially result in power system instability. This paper presents a closed-loop interconnection model comprising a G-CC as a feedback subsystem and a VSC-HVDC system as a feedforward subsystem. The instability condition of the closed-loop system is derived from the open-loop mode resonance theory. Subsequently, a mathematical model is developed to represent the random output of the G-CC. This approach allows the probability of open-loop mode resonant instability of the power system to be evaluated, as well as the risk of sub-synchronous resonant instability caused by the output randomness of the G-CC. Finally, validation is performed by building a simulation example system and a time-domain simulation system in MATLAB.

Modeling and Analysis of Wide Frequency Band Coaxial TSV Transmission Interconnect.

In this paper, we first build the 3D model of coaxial TSV(CTSV), RDL, and bump of the CTSV interconnect, and extract the equivalent circuit model of each part. Then, we get the S-parameters of the 3D and equivalent circuit model of the CTSV interconnect structure; the validity of the equivalent circuit model is verified by comparing the consistency of the S-parameters. The simulation results show that the maximum errors for the S11 and S21 parameters are 0.4% and 0.18%, respectively, which proves the validity of the equivalent circuit modeling in this paper. Finally, parametric analysis is performed to investigate the effect of different model parameters on the signal-transmission characteristics of the CTSV interconnect.

Adaptation of FDMT to include process-based models and consider regional aspects following radionuclide deposition events

Experience from earlier nuclear accidents has clearly shown the need for maintaining and developing appropriate modelling capabilities. Dealing with complex issues such as human exposure following a nuclear accident necessitates the implementation of a set of interconnected models such as FDMT. FDMT is an integrated module within the two main European decision support systems for radiological emergency preparedness, ARGOS and JRODOS, to simulate the transfer of radionuclides along terrestrial food chains and to predict their activity concentrations in foodstuffs. In order to make the module more fit-for-purpose, FDMT has been implemented in a new modelling platform (ECOLEGO) which provides a high degree of flexibility with regard to conducting developmental work. This paper presents improvements in FDMT further through either the incorporation of new models or further elaboration of existing ones, as well as updates in default parameters. Models have also been made more fit-for-purpose through consideration of regional-specific parameters. Specific improvements include modelling developments related to dry deposition, radioactive particle weathering, radiocaesium transfer influenced by soil characteristics and, for a region-specific case, animal uptake. In addition, the paper presents new pathways and parameters (and updated values) to be considered for making FDMT more adapted for Norwegian conditions. Overall, the improvements made in the present work should significantly reduce the uncertainties associated with the outputs of the FDMT models.

The Guardian Node Slow DoS Detection Model for Real-Time Application in IoT Networks.

The pernicious impact of malicious Slow DoS (Denial of Service) attacks on the application layer and web-based Open Systems Interconnection model services like Hypertext Transfer Protocol (HTTP) has given impetus to a range of novel detection strategies, many of which use machine learning (ML) for computationally intensive full packet capture and post-event processing. In contrast, existing detection mechanisms, such as those found in various approaches including ML, artificial intelligence, and neural networks neither facilitate real-time detection nor consider the computational overhead within resource-constrained Internet of Things (IoT) networks. Slow DoS attacks are notoriously difficult to reliably identify, as they masquerade as legitimate application layer traffic, often resembling nodes with slow or intermittent connectivity. This means they often evade detection mechanisms because they appear as genuine node activity, which increases the likelihood of mistakenly being granted access by intrusion-detection systems. The original contribution of this paper is an innovative Guardian Node (GN) Slow DoS detection model, which analyses the two key network attributes of packet length and packet delta time in real time within a live IoT network. By designing the GN to operate within a narrow window of packet length and delta time values, accurate detection of all three main Slow DoS variants is achieved, even under the stealthiest malicious attack conditions. A unique feature of the GN model is its ability to reliably discriminate Slow DoS attack traffic from both genuine and slow nodes experiencing high latency or poor connectivity. A rigorous critical evaluation has consistently validated high, real-time detection accuracies of more than 98% for the GN model across a range of demanding traffic profiles. This performance is analogous to existing ML approaches, whilst being significantly more resource efficient, with computational and storage overheads being over 96% lower than full packet capture techniques, so it represents a very attractive alternative for deployment in resource-scarce IoT environments.

Dynamics of memristor coupled discrete fractional symmetric neural network model

Neural networks, also known as artificial neural networks (ANNs), represent innovative computational models inspired by the functioning of biological neurons in the human body. Currently, neural network models are employed to address intricate real-world challenges. This article focuses on constructing and dynamically analyzing interconnected symmetric neural network models inspired by the Hopfield type. These models incorporate discrete fractional memristor elements featuring quadratic memductance. The primary objective is to comprehend system characteristics by introducing nonlinearity to the inter-neuron weights in a functional manner. Additionally, the study explores the influence of electromagnetic radiation on neurons. Bifurcation diagrams, considering fractional order and Lyapunov exponents, illustrate the chaotic nature of the interconnected neural network model. The investigation delves into coexisting system states, examining coexisting bifurcations and attractors. The article offers potential for developing bio-inspired, energy-efficient, and adaptive neural network architectures, thereby contributing to advancements in artificial intelligence and neuromorphic applications.

Stabilization of interconnected models with Nitsche's interface conditions using the two-grid approach: A finite element study

In this paper, a stabilized Stokes–Stokes system with Nitsche's type interface conditions is presented. These conditions are commonly employed in many multi-physical fields, including fluid–fluid interaction, fluid–structure interaction, oceanographic modeling, and atmospheric forecasting. For multi-physical domain modeling purposes, Nitsche's interface conditions provide useful benefits over classical conditions via addressing the complicated nature of fluid phase interface mathematical modeling, phase boundary tracking, interface interactions, and mass and energy transportation. It is not easy to find analytical and numerical solutions for models with these characteristics. We use more accurate interface conditions to solve the fluid–fluid interaction model to accomplish this numerically. This is achieved by including new terms at the interface and decoupling the domain through the two-grid technique, which ultimately reduces the main issue into several smaller problems. Comparing this method to existing models, we find that it is computationally feasible because it uses less memory and operates with a coarse grid instead of a fine grid and thus improves convergence rates for complex and nonlinear problems. Furthermore, it shows mesh independence, supports potential parallelization, and is crucial for advanced multigrid techniques. The optimality of the error is confirmed both theoretically and numerically. The numerical experimental section validates the model through three types of numerical experiments.

MÔ HÌNH PHÁT TRIỂN CHUYÊN MÔN GIÁO VIÊN MẦM NON: NGHIÊN CỨU TRƯỜNG HỢP TRÊN MÔ HÌNH STEMSMART

This article presents the STEMsmart early childhood teacher professional development model. The model is developed based on Clarke and Hollingsworth’s Interconnected Model and focuses on early childhood STEM education. The model includes components contributing to teachers’ change in four main domains: (1) Personal domain, (2) External domain, (3) Domain of practice, and (4) Domain of consequence. Initial trials of the model have significantly improved teachers’ knowledge and pedagogical practices related to STEM education. This model needs further research to gather convincing evidence confirming its suitability and effectiveness, providing a basis for scaling up and applying it to develop other professional competencies of early childhood teachers. Keywords: Professional development; early childhood teacher; professional development model; STEMsmart.

Three network design problems for community energy storage

AbstractIn this article, we develop novel mathematical models to optimize utilization of community energy storage (CES) by clustering prosumers and consumers into energy sharing communities/microgrids in the context of a smart city. Three different microgrid configurations are modeled using a unifying mixed‐integer linear programming formulation. These configurations represent three different business models, namely: the island model, the interconnected model, and the Energy Service Companies model. The proposed mathematical formulations determine the optimal households' aggregation as well as the location and sizing of CES. To overcome the computational challenges of treating operational decisions within a multi‐period decision making framework, we also propose a decomposition approach to accelerate the computational time needed to solve larger instances. We conduct a case study based on real power consumption, power generation, and location network data from Cambridge, MA. Our mathematical models and the underlying algorithmic framework can be used in operational and strategic planning studies on smart grids to incentivize the communitarian distributed renewable energy generation and to improve the self‐consumption and self‐sufficiency of the energy sharing community. The models are also targeted to policymakers of smart cities, utility companies, and Energy Service Companies as the proposed models support decision making on renewable energy related projects investments.

Collaborative Planning and Comprehensive Evaluation Method for Energy Storage System and Flexible Interconnection in Distribution Networks Considering Island Operation

Introduction: When the superior power grid fails and loses power, due to the traditional single power supply radial grid structure of low-voltage substation areas, all loads in the lowvoltage substation area will lose power, causing a poor electricity consumption experience for low-voltage users. To enhance the resilience of low-voltage distribution areas against faults and power outages from higher-tier power grids, a collaborative planning and comprehensive evaluation method for grid-forming energy storage systems (GFM-ESS) and flexible interconnection in distribution networks, considering island operation, is proposed. Method: This method integrates GFM-ESS and flexible interconnections, taking islanding operations into account. Firstly, the structure of GFM-ESS and voltage source converters is analyzed. The control modes of GFM-ESS in parallel or off-grid scenarios are also scrutinized. Secondly, minimizing the annual comprehensive cost and the annual power outage load are the objective functions. A bilevel programming model for GFM-ESS and flexible interconnection of lowvoltage distribution networks, considering island operation, has been established. Moreover, a comprehensive evaluation method based on the analytic hierarchy process for proposed lowvoltage distribution network structural schemes is introduced. An evaluation index system is established to assess the rationality of these proposed network structural planning schemes. Finally, the superiority of the proposed collaborative planning method is verified through a comparative analysis of three planning methods. Result: The proposed collaborative planning method can effectively ensure the continuous power supply of low-voltage distribution networks under the fault scenario of the upper power network. Conclusion: Moreover, the rationality of the results obtained from the proposed collaborative planning method is verified through a comprehensive evaluation method of grid structure schemes based on the analytic hierarchy process. The proposed comprehensive evaluation method can determine which two areas are optimal for grid planning. result: The superiority of the proposed collaborative planning method was verified by comparative analysis of three planning methods. And the rationality of the proposed collaborative planning method results was verified by the comprehensive evaluation method of grid structure schemes based on analytic hierarchy process.

Multi-Scale Deep Learning-Based University Financial System: Hardware Design and Database Integration

With the increasing scale of college enrollment and the increasing complexity of college teaching management, college finance department should innovate the traditional financial management mode while adapting to the reform of teaching management, and make use of the openness and real-time characteristics of Internet to improve the quality of college financial management and reduce the risk of college financial management. To this end, this paper designs a university financial system based on multi-scale deep learning. In the hardware design, the system adds multiple sensors and scans all the information in the financial database using a coordinator. In the software design, the weights that can connect the financial information of the same attribute are set by establishing a database form; according to the multilayer perceptual network topology, a full interconnection model based on multi-scale deep learning is designed to realize the system’s deep extraction of data. The experimental results show that the financial risk is based on the risk warning capability for university finance, and compared with the system under the traditional design, the university finance system designed in this time has the most categories of financial information parameters extracted.

Bibliometric and visual analyses of advancements in chronic kidney disease management.

Chronic kidney disease (CKD) is characterized by high incidence, prolonged course, significant health damage, and a heavy societal burden. Understanding the history and content of CKD research is crucial to further its recognition and management, in addition to reducing its individual and societal burdens. This study aimed to assess the management history of CKD to provide a foundation for clinical medical staff to systematically understand its evolution. The Web of Science Core Collection database was screened for CKD management studies published between January 1, 1948, and December 31, 2021. From the search results, we performed statistical descriptions of the publication date, volume, and type. Using VOS-viewer 1.6.19, variables from the included articles were obtained for keyword co-occurrence clustering and sequence analyses to determine research themes, segment phases based on publication volumes over varied timeframes, assess the dynamic progression of CKD management, and anticipate future research trends. In total, 26,133 articles met the inclusion criteria. The analysis revealed 3 stages of CKD management research: the slow development stage (1948-1998), which was initiated by epidemiological studies without ideal clustering; the steady growth stage (1999-2010), which was focused on CKD complication management and quality-of-life research; and the rapid development stage (2011-2022), which was dominated by 7 major clusters, mainly regarding the treatment and management of severe conditions and management patterns. The CKD research journey is comprised of 3 stages, the contents of which form an interconnected research model. Future research should focus on the establishment of management models and the application of intelligent management tools. Furthermore, this work can serve as a reference for the further expansion of research in this field and in improving its management.

An Interconnected Human Resources Model Development of Intercultural Competence in the Educational Activities of a Manager

An Interconnected Human Resources Model Development of Intercultural Competence in the Educational Activities of a Manager

Reduced-order modeling of modular, position-dependent systems with translating interfaces

Many complex mechatronic systems consist of multiple interconnected dynamical subsystems, which are designed, developed, analyzed, and manufactured by multiple independent teams. To support such a design approach, a modular model framework is needed to reduce computational complexity and, at the same time, enable multiple teams to develop and analyze the subsystems in parallel. In such a modular framework, the subsystem models are typically interconnected by means of a static interconnection structure. However, many complex dynamical systems exhibit position-dependent behavior (e.g., induced by translating interfaces) which cannot be captured by such static interconnection models. In this paper, a modular model framework is proposed, which allows to construct an interconnected system model, which captures the position-dependent behavior of systems with translating interfaces, such as linear guide rails, through a position-dependent interconnection structure. Additionally, this framework allows to apply model reduction on subsystem level, enabling a more effective reduction approach, tailored to the specific requirements of each subsystem. Furthermore, we show the effectiveness of this framework on an industrial wire bonder. Here, we show that including a position-dependent model of the interconnection structure (1) enables to accurately model the dynamics of a system over the operating range of the system and, (2) modular model reduction methods can be used to obtain a computationally efficient interconnected system model with guaranteed accuracy specifications.

Nonlinear Characteristic Analysis of Gas-Interconnected Quasi-Zero Stiffness Pneumatic Suspension System: A Theoretical and Experimental Study

Because of significantly changed load and complex and variable driving road conditions of commercial vehicles, pneumatic suspension with lower natural frequencies is widely used in commercial vehicle suspension system. However, traditional pneumatic suspension system is hardly to respond the greatly changed load of commercial vehicles. To address this issue, a new Gas-Interconnected Quasi-Zero Stiffness Pneumatic Suspension (GIQZSPS) is presented in this paper to improve the vibration isolation performance of commercial vehicle suspension systems under frequent load changes. This new structure adds negative stiffness air chambers on traditional pneumatic suspension to reduce the natural frequency of the suspension. It can adapt to different loads and road conditions by adjusting the solenoid valves between the negative stiffness air chambers. Firstly, a nonlinear mechanical model including the dimensionless stiffness characteristic and interconnected pipeline model is derived for GIQZSPS system. By the nonlinear mechanical model of GIQZSPS system, the force transmissibility rate is chosen as the evaluation index to analyze characteristics. Furthermore, a testing bench simulating 1/4 GIQZSPS system is designed, and the testing analysis of the model validation and isolating performance is carried out. The results show that compared to traditional pneumatic suspension, the GIQZSPS designed in the article has a lower natural frequency. And the system can achieve better vibration isolation performance under different load states by switching the solenoid valves between air chambers.

Interoperability Structure of Smart Water Conservancy Based on Internet of Things

Massive smart water conservancy object (WCO) need to be connected for real-time monitoring and control, which produces massive data. Unfortunately, heterogeneous data structures and semantics lead to low interoperability between WCO and management systems. To address this challenge, we propose a novel interoperability structure for a smart water conservancy system based on the Internet of Things (IoT), and the key design includes a smart WCO terminal, interoperability network, special interoperability protocol, WCO information model, and cloud platform. Universal terminal and network are the base of interoperability hardware, and special interoperability protocol and information model for interconnection of WCO are designed for smart water conservancy management system. WCO can be connected to a water conservancy Big Data processing cloud platform for interoperability applications. The application results demonstrate that our proposed WCO’s interoperability structure has obvious advantages than the general IoT at WCO interoperability. The interoperability protocol is reliable, the information model can ease interoperability and security, and the semantic dictionary is very rich and covers all semantic services of WCO.

Evaluation of the digital teacher professional development TARGET-tool for optimizing the motivational climate in secondary school physical education

Given the complexity of teaching, continuing teacher professional development (CPD) is essential for maintaining and enhancing teaching effectiveness, and bridging the gap between ever-evolving theory and practice. Technological advancements have opened new opportunities for digital tools to support CPD. However, the successful integration of such digital tools into practice poses challenges. It requires adherence to CPD prerequisites and acknowledgment of the complexity of the professional development process. This study explored the applicability of the developed digital PE teacher professional development TARGET-tool in a secondary school PE context. We examined the perceived usability of this tool and gained insights into the process of teachers’ professional development as a result of using the tool. Ten PE teachers from different schools implemented the TARGET-tool within their PE context for a period of 4 to 6 weeks. Individual semi-structured interviews and the System Usability Scale provided insights into the perceived usability and the process of teacher professional development. The TARGET-tool demonstrated its potential as an effective tool for supporting teachers’ professional development. Future tool improvements were identified to further optimize the perceived usability, such as simplifying complex features, providing additional support and resources, and improving (data) presentations. Using the Interconnected Model of Professional Growth as a theoretical basis, it was demonstrated how the use of the TARGET-tool engages teachers as active and reflective participants in their professional development and induces changes within the external domain, the domain of practice, the domain of consequences, and the personal domain.