Interconnection Model Research Articles

Innovative Financial Management in Higher Education: A Multi-Scale Deep Learning Approach for Risk Reduction and Quality Enhancement

This paper presents a novel university financial management system leveraging multi-scale deep learning. With rising college enrollment and teaching complexities, traditional financial models require adaptation to mitigate risks and improve management quality. The system integrates hardware and software innovations: multiple sensors enhance data scanning, coordinated by a central coordinator, ensuring comprehensive financial database coverage. Software-wise, a structured database establishes attribute-based financial connections, crucial for weight assignment. Employing a multilayer perceptual network topology, a full interconnection model based on multi-scale deep learning facilitates profound data extraction. Experimental evaluations demonstrate the system's superior financial risk assessment capabilities compared to traditional approaches, extracting a broader spectrum of financial parameters for comprehensive risk warnings. By embracing multi-scale deep learning, this system promises significant advancements in university financial management, enhancing adaptability and risk mitigation in college finance departments.

Proximity Index Value Based Systematized Approximation of Higher-Order Interconnected Power System Model

Proximity Index Value Based Systematized Approximation of Higher-Order Interconnected Power System Model

A Novel Automatic Generation Control Method Based on the Large-Scale Electric Vehicles and Wind Power Integration Into the Grid.

In order to solve the problem of frequency instability of power system due to strong random disturbance caused by large-scale electric vehicles and wind power grid connection, an improved reinforcement learning algorithm, namely, optimistic initialized double Q, is proposed in this article from the perspective of automatic generation control. The proposed algorithm uses the optimistic initialization principle to expand the agent action exploration space, so as to prevent Q-learning from falling into local optimum by greedy strategy; meanwhile, it integrates double Q-learning to solve the problem of overestimation of action value in traditional reinforcement learning based on Q-learning. In the algorithm, the hyperparameter ατ is introduced to improve the learning efficiency, and the reward bτ based on exploration times is introduced to increase the Q value estimation to drive the exploration of the algorithm, so as to obtain the optimal solution. By simulating the two-area load frequency control model integrated with large-scale electric vehicles and the four-area interconnected power grid model integrated with large-scale wind power generation, it is verified that the proposed algorithm can obtain the global optimal solution, thus effectively solvinng the frequency instability caused by strong random disturbance in the grid-connected mode of large-scale wind power generation, and compared with many reinforcement learning algorithms, the proposed algorithm has better control performance.

Geodense section of the lithosphere of the Ukrainian shield along the Shepetivka – Zhytomyr – Dnipro – Volnovakha traverse

Based on the results of transformation of one-dimensional density models using polynomial corrections to reference model AK135 for different domains of mantle of the Ukrainian Shield, a preliminary reconstruction of the Earth’s geodensity structure to depth of 2600 km was performed. The one-dimensional density models are properly correlated with gravitational field and mass of each mantle layer. Based on these constructions, the integration of the horizontally layered model with seismic stratigraphy data and the vertically block model with gravity field calculations to depth of 275 km along the Shepetivka-Zhytomyr-Dnipro-Volnovakha geotraverse was carried out. The results significantly increased the informativeness of data from two methods regarding the features of deep lithospheric tectonics within the Ukrainian Shield. The results of geological interpretation along the geotraverse show that the megablocks of the shield are best reflected in density anomalies, characterized by different densities both horizontally and in depth. The obtained features of the lithospheric structure of the Ukrainian Shield indicate the need for further research of upper and lower mantle to obtain a comprehensive interconnected model of its structure to refine the petrophysical characteristics that affect the formation of the Earth’s crust and mineral resources.

LymphoDose: a lymphocyte dose estimation framework—application to brain radiotherapy

Objective. Severe radiation-induced lymphopenia occurs in 40% of patients treated for primary brain tumors and is an independent risk factor of poor survival outcomes. We developed an in-silico framework that estimates the radiation doses received by lymphocytes during volumetric modulated arc therapy brain irradiation. Approach. We implemented a simulation consisting of two interconnected compartmental models describing the slow recirculation of lymphocytes between lymphoid organs ( M1 ) and the bloodstream ( M2 ). We used dosimetry data from 33 patients treated with chemo-radiation for glioblastoma to compare three cases of the model, corresponding to different physical and biological scenarios: (H1) lymphocytes circulation only in the bloodstream i.e. circulation in M2 only; (H2) lymphocytes recirculation between lymphoid organs i.e. circulation in M1 and M2 interconnected; (H3) lymphocytes recirculation between lymphoid organs and deep-learning computed out-of-field (OOF) dose to head and neck (H&N) lymphoid structures. A sensitivity analysis of the model’s parameters was also performed. Main results. For H1, H2 and H3 cases respectively, the irradiated fraction of lymphocytes was 99.8 ± 0.7%, 40.4 ± 10.2% et 97.6 ± 2.5%, and the average dose to irradiated pool was 309.9 ± 74.7 mGy, 52.6 ± 21.1 mGy and 265.6 ± 48.5 mGy. The recirculation process considered in the H2 case implied that irradiated lymphocytes were irradiated in the field only 1.58 ± 0.91 times on average after treatment. The OOF irradiation of H&N lymphoid structures considered in H3 was an important contribution to lymphocytes dose. In all cases, the estimated doses are low compared with lymphocytes radiosensitivity, and other mechanisms could explain high prevalence of RIL in patients with brain tumors. Significance. Our framework is the first to take into account OOF doses and recirculation in lymphocyte dose assessment during brain irradiation. Our results demonstrate the need to clarify the indirect effects of irradiation on lymphopenia, in order to potentiate the combination of radio-immunotherapy or the abscopal effect.

Price discrimination in mobile gacha games: A comprehensive study of the scarcity–pricing, gachaing–user profiling, and recharging–profiting models

AbstractPrice discrimination (PD) in mobile gacha games differs from that in e‐commerce platforms due to its reliance on the concealed “probability” mechanism, which appears transparent but is actually controlled, making it harder to detect and regulate by society. To confirm the existence of PD in mobile gacha games, a comprehensive analysis of its operational modes was conducted through extensive participatory observation and in‐depth interviews with over 30 domestic gamers, game developers, and data analysis website founders. The study revealed that, contrary to academic definitions, PD does indeed occur in mobile gacha games, characterized by three interconnected models: the scarcity–pricing model, gachaing–user profiling model, and recharging–profiting model. By examining the interrelated models that comprise the PD process, concentrating on China as a special context, and offering insightful information on the effects of PD on consumer behavior and economic platforms, this study makes a noteworthy and novel contribution to the understanding of PD within the realm of mobile gacha games. The research examines the influence of PD on consumer behavior and economic decision‐making processes. Furthermore, the research discusses the difficulties of controlling PD in mobile gacha games, particularly due to the opacity of the “probability” mechanism. In conclusion, recommendations aimed at addressing the issue of PD within the realm of mobile gacha gaming in China are presented, drawing upon Lawrence Lessig's framework on “Four modalities of restraining behavior in cyberspace.”

Transformative Trajectories: Constructing an Ideal Paradigm for Higher Education with AI Integration

To explore the construction of the ideal paradigm of colleges and universities with artificial intelligence technology in the process of higher personnel training. Using the literature research method, this paper expounds from three aspects: origin, positioning and path. Origin: Artificial intelligence is the reality of technological development in the cultivation of higher talents in the new era, and it is a realistic demand in the cultivation of higher talents, which requires political and ideological empowerment. Positioning: Determining the role of artificial intelligence as an "education assistant", and then clarifying it as a "quasi-subject object", is the basic positioning for the introduction of higher talents at this stage. Paths: 1) Build a teacher-student interconnection model supported by "human-machine collaboration"; 2) Build a smart learning and smart teaching model supported by an "algorithm database"; 3) Establish a "people-oriented" assessment and purpose-led mechanism principle, Deeply improve the quality of the cultivation of higher education personnel in our country's high-level colleges and universities, and promote the final formation of its training pattern.

Climatic Modeling of Seawater Intrusion in Coastal Aquifers: Understanding the Climate Change Impacts

The study examines the impacts of climate change and sea level rise on coastal aquifers, focusing on the influence of the components of the water cycle on seawater intrusion, and the evolution of the phenomenon in the future. The simulation of coastal water resources was performed using an integrated modeling system (IMS), designed for agricultural coastal watersheds, which consists of inter-connected models of surface hydrology (UTHBAL), groundwater hydrology (MODFLOW), and seawater intrusion (SEAWAT). Climatic models for the adverse impact scenario (RCP8.5) and the medium impact scenario (RCP4.5) of climate change were used. Transient boundary head conditions were set to the coastal boundary, to dynamically represent the rise in sea level due to climate change. The response of groundwater in the coastal Almyros Basin, located in central Greece, was simulated from 1991 to 2100. The findings indicate that seawater intrusion will be advanced in the future, in both climate change scenarios. The models show varying patterns in groundwater recharge, with varying uncertainty projected into the future, and sensitivity to time in the fluctuation of the components of the water cycle.

P‐9.3: A Typical Interconnect Model for High Bandwidth Video Streaming Transmission in Mixed‐Reality Devices

P‐9.3: A Typical Interconnect Model for High Bandwidth Video Streaming Transmission in Mixed‐Reality Devices

Tracing teachers’ change of pedagogical design capacity through professional development

ABSTRACT Curriculum adaptation is unavoidable, according to both Turkish and international research. Deliberative adaptations, however, are not as simple as they appear, and teachers with low pedagogical design capacity (PDC) may make haphazard adaptations or fail to make the necessary adaptations. Therefore, professional development (PD) is crucial in making teachers’ adaptations more deliberatively and systematically. In this case study, drawing on the interconnected model of professional growth, the change of pathways of four mathematics teachers’ PDC was explored within the context of a PD. The findings revealed that the capacity to use curricular resources, the capacity to use personal resources, and beliefs towards the use of curriculum emerged as three change indicators of PDC. While teachers’ interactions with the facilitator were effective in fostering knowledge change, getting and reflecting on students’ learning outcomes was effective in fostering belief change. The results are discussed in the context of curricular and PD studies.

Probabilistic framework for quantifying infrastructure systems’ resilience against floods

ABSTRACT This manuscript proposes a probabilistic framework to quantitatively assess communities’ resilience by simulating the state and serviceability of their infrastructure systems from the onset of a flood until the end of recovery. It comprises multiple interconnected models. Hazard model characterizes flood parameters (e.g., depth and velocity). Depth-damage curves estimate the damage to infrastructure systems’ components. The HEC-FIA mortality model characterizes the flood-induced casualties. Serviceability models determine the ability of interdependent infrastructure systems to meet the demand during the recovery process. The recovery models estimate the recovery duration and cost of damaged components probabilistically. The Monte Carlo analysis is employed to consider multiple relevant uncertainties, generating distributions of the flood-induced losses under various scenarios. The ratio of total losses to the gross regional product characterizes the community’s resilience. This framework facilitates the assessment of the impact of various resilience enhancement measures, guiding the selection of appropriate measures through a cost-benefit analysis.

Quantum-Secure Signalling Model for L1/L2 Next-Gen Interconnect and Roaming Networks Over IPX for NB-IoT Traffic: A Review

Signalling security is critical for next-generation mobile (NGN) networks to ensure integrity, privacy, and confidentiality of communication protocols. However, recent research on existing 5G standards has uncovered vulnerabilities that could be exploited by emerging surveillance threats such as HiddenArt and Harvest Now Decrypt Later (HNDTL), as well as the prospect of quantum computing threatening to break classical cryptographic techniques. This systematic literature review (SLR) investigates quantum-based signalling solutions to mitigate these threats in interconnect and roaming 5G networks (IRN) over IP eXchange for Narrowband Internet of Things (NB-IoT) traffic. A database search was conducted, studies were selected and compared based on methods, approaches, techniques, and limitations. The SLR found that quantum key distribution (QKD) combined with quantum teleportation (QT) can protect and mitigate threats and attacks on signalling networks when protocols interact and interoperate in carrier networks. QKD techniques can be used for L1 protocols, while secure direct quantum communication can be used for L2 protocols. This study concludes that further studies are needed to integrate different techniques and protocols for L1/L2 signalling networks to create a robust quantum-secure signalling model for global interconnect and roaming NGN.

Unleashing the potential of digital twins: a new era with aeronautics 4.0

Abstract* Introduction The aerospace value chain consists of several processes, and digitizing it first requires an assessment of these processes and their ability to be transferred to the fully integrated digital thread perspective of smart factories. A digital thread refers to the continuous flow of data and information related to a product throughout its life cycle, integrating and connecting all aspects of a product’s journey. Within this framework, digital twin technology, an essential element of Industry 4.0, comprises the implementation of a virtual presentation of a physical object, system, or process. It brings together the digital replica not only of the physical attributes but also of the behavioral performance of the physical twin. Methods To achieve a digital thread perspective for aeronautics, a research agenda is proposed, including all breakpoints in the current value chain through a PESTLE Analysis, which defines the value-added areas targeted by this transition to digital technology. An aeronautics 4.0 model Digital Thread Twin Smart Aeronautics D2TSAero is proposed, which provides a new perspective in the aeronautics field by integrating its main ecosystems into an interconnected model made possible by the integration of digital twin agent instances. Proof of Concept A use case that deals with the dependability management of an aircraft fuel distribution system is presented. Based on these results, we can see that the proposed twin model can help in reducing real system parts down time, and it can also improve the management of maintenance across the system life cycle by offering a single source of trust for all stakeholders involved in the digital thread cycle of the real twin. Conclusion A forward-looking perspective on the future of aeronautics with this integrated approach is presented, summarizing all the discussed points and the importance of digital twins in supporting the digitalization of the field.

An interconnected system of energy

The purpose of this paper is to describe a system of interconnected energy models. These models produce inferences that may enhance our understanding of classical and quantum mechanics. From the formulated models, an empirical test is derived to validate the proposed light projection hypothesis.

The model-as-a-resource paradigm for geoscience digital ecosystems

A long-term goal of environmental science and Earth observation is to enable the creation of a “Model Web” of semantically interconnected data and models. Geospatial models are usually exposed on the Web as services accessible through heterogeneous interfaces. However, such services, which represent instances of the paradigm called Model-as-a-Service (MaaS), cannot be easily exploited beyond their original use as defined by the service provider. To overcome this important limitation and better support transparency, reproducibility, replicability and reusability of the model (following the Open Science paradigm), we investigated the adoption of a Model-as-a-Resource (MaaR) approach, in which a model is considered a generic digital resource that, as such, can play different roles in different potential use cases. The proposed MaaR framework can play an important enabling role in the realization of those digital ecosystems that generate environmental knowledge. The main challenges and opportunities are discussed in the manuscript.

Process-based life cycle inventory framework for assessing the carbon footprint of products from complex production paths: Case of dual-phase automotive strip steel

The production paths of industrial products are usually complex, leading to difficulties and a large workload when conducting traditional process-based life cycle assessment (P-LCA). Existing studies on reducing LCA workload have focused mainly on simplifying the process or combining LCA with correlation methods. For complex production paths that cannot be simplified or changed, the methods have weak generality. To fill in these research gaps, a process-based life cycle inventory (P-LCI) framework for complex production paths is proposed. P-LCI contains accurate classification and definition methods for input, output and unit processes, and an interconnection model for calculating process coefficients according to the complexity of the linkages among processes is proposed. Based on the proposed framework, a case study of the dual-phase automotive strip steel (DP) production process is performed. The results show that the production of 1 kg of DP steel consumes 0.679 kg of molten steel from a basic oxygen furnace plant and 0.557 kg from the another. Coke plants produce the largest carbon footprint (CF) per unit of coke, which is 0.889–1.231 kgCO2e/kg-coke. For the cradle-to-gate lifecycle of DP steels, the BFP has the largest CF at 0.614 kgCO2e/kg-DP, accounting for 26.32%. Through the proposed P-LCI framework, unit processes can be clearly defined, and the interconnection model can be used as the basis for environmental impact analysis. When the production path changes, the model can be flexibly adjusted, and the workload of repeated model construction can be reduced.

Research on optimization of multi-energy coupling source-network-load-storage based on micro energy network

Based on the architecture of the micro energy network system, a “source network load storage” multi-energy coupling hub system for regional energy internet with electricity gas interconnection is proposed. The lowest operating is set as the optimization goal for the operation of the regional energy internet. A dynamic economic scheduling model for regional energy interconnection based on the sky and an optimization scheduling model for regional energy internet are established. A mixed integer linear programming program based on Matlab is written and solved using CPLex. The results show the operation of the “source grid load storage” regional energy internet with multiple energy coupling hubs as the core is lower than that of traditional micro-grids When adding an energy storage system, the daily operating of the micro-grid system is 16.7% less than that of Control Scenario 1 and 14.3% less than that of Control Scenario 2 The proposal of a regional energy internet “source network load storage” multi-energy coupling hub system based on the micro energy network system architecture provides a feasible basis for the planning and construction research of the regional energy internet.

Consumers’ Brand Experiences With Robotic Service Failures: Modeling Appraisal, Attribution, and Psychological Reactance

Due to the stretched capacities of human staff, consumers are increasingly placed in situations where they are “required” to use technology amidst their travel experiences, despite potential service failures in robotic technologies. Yet, research into how robotic service failures could potentially spill over to consumers’ brand experiences, robot experiences, and adoption intention remains unexplored. Drawing on appraisal, attribution, and psychological reactance theories, an interconnected research model of service failure, attribution, and (in)voluntary robot adoption was tested via two experiments. A mixed-design quasi-experiment (Study 1) found a significant interaction effect of service failure and attribution on brand experience in the hotel concierge context. Study 2 provided further evidence for the causal effects in Study 1 by employing a between-subject quasi-experiment in the hotel front desk context with additional measures. Collectively, this research contributes to the literature by highlighting how temporal, situational, and contextual factors in HRI may impact evaluations of brand and robot experiences.

Grain boundaries-dominated migration failure of copper interconnect under multiphysics field: Insight from theoretical modeling and finite element analysis

As the feature size of Cu interconnects in microelectronic devices are miniaturized into micro- and even nano-scale, the effects of grain boundaries (GBs) on the electromigration (EM) failure become more and more obvious. It is of fundamentally importance to investigate the grain boundaries dominated failure mechanism and lifetime of Cu interconnects. In this work, the interconnection models containing different grain boundaries were constructed by using finite element simulations. The simulation results indicate that the current density at Cu grain boundaries is lower, but the current will be increased locally, when it is almost perpendicular to grain boundaries. However, the temperature is higher locally at grain boundaries. In the early stage of atomic diffusion, thermal migration and stress migration also occur near grain boundaries, resulting in significant atomic segregation near grain boundaries, particularly at the intersection of grain boundaries and near the inclined grain boundaries with small angles to the current direction. The atomic diffusion is considerably accelerated as the density of grain boundaries is increased, but is slowed down by poorly connected columnar grain boundaries.

Robust and quantized repetitive tracking control for fractional‐order fuzzy large‐scale systems

SummaryIn this article, the decentralized repetitive tracking controller design for fractional‐order large‐scale Takagi–Sugeno fuzzy system with time delays is developed. We mainly focus on the design of a decentralized repetitive tracking controller based on the Lyapunov stability theory, by which the addressed large‐scale system asymptotically stabilized with performance index. Further, the repetitive control with quantized signal is developed to ensure the good tracking performance with the presence of interconnected model and external disturbances. Specifically, a logarithmic quantizer is used to quantify the control signal which can reduce the data transmission rate in the network. Finally, a numerical example is presented to verify the effectiveness of the proposed controller design technique.