Construction Of Theoretical Model Research Articles

Research on Communication Network Security Based on Narrowband Internet of Things and Encryption Algorithms

With the rapid development of Internet of Things (IoT) technology, Narrowband IoT (NB-IoT) has been widely adopted in smart cities, smart homes, and industrial automation due to its low power consumption, wide coverage, low cost, and high reliability. However, the associated security issues have become a critical factor hindering its further development. This paper aims to explore the security challenges in NB-IoT communication networks using encryption algorithms. Through theoretical analysis and model construction, a comprehensive security solution is proposed. Initially, the paper reviews the fundamental principles and application scenarios of NB-IoT, analyzing the current challenges in network security, including data leakage, device tampering, and man-in-the-middle attacks. Subsequently, a security framework based on lightweight encryption algorithms is introduced, leveraging the strengths of both symmetric and asymmetric encryption to ensure security while reducing computational and communication overheads. Additionally, the application of blockchain technology in NB-IoT security is discussed, enhancing data credibility and system resilience against attacks through its decentralized nature. Theoretical derivations and simulation analyses confirm the effectiveness and feasibility of the proposed security framework. The results demonstrate that this framework significantly enhances the security performance of NB-IoT networks, providing theoretical support and practical guidance for the secure development of IoT.

The application effect of the optimized scheduling model of virtual power plant participation in the new electric power system

To build a comprehensive framework for virtual power plant (VPP) development aligned with market dynamics and to devise effective strategies to foster its growth, this study undertakes several key steps. Firstly, it constructs a VPP development framework based on market conditions, to drive the evolution of new power systems and facilitating energy transformation. Secondly, through a blend of theoretical analysis and model construction, the fundamental principles of VPP are systematically elucidated, and a decision model for the VPP development framework, focusing on price demand response, is formulated. Lastly, an optimal scheduling model for the new power system is developed, with its efficacy validated across three distinct scenarios. The findings underscore the critical importance of integrating energy storage technologies, particularly pumped storage hydropower systems, for achieving balance and optimization within new power systems. Model verification reveals that the incorporation of energy storage power stations significantly enhances system stability and efficiency, particularly in addressing the volatility associated with renewable energy sources. Additionally, the analysis indicates that while the adoption of energy storage technologies may marginally increase overall power generation costs, the total power generation cost declines with the integration of battery storage and pumped storage hydropower stations. This suggests that leveraging energy storage technologies not only enhances system operational reliability but also contributes to reducing the overall cost of power production to a certain extent. In summary, this study presents an economic and environmentally sustainable scheduling model for new power systems within the context of market trading environments. By offering both theoretical insights and practical guidance, it aims to support sustainable development and energy transformation initiatives. Ultimately, the study is poised to foster the adoption of clean energy, facilitate the establishment of smart grids, and bolster the sustainable utilization of energy resources, thereby advancing environmental conservation efforts.

Building College Education Management in the New Era: Theoretical Discussion and Model Construction Based on New Quality Productivity

This study analyses the use of new quality productivity theory in higher education management and develops a framework called the "multi-dimensional collaborative innovation management model" to tackle the challenges of globalisation and information technology. This concept combines the three dimensions of scientific and technological innovation, management innovation, and system innovation to promote effective resource allocation, improve educational quality and efficiency, and increase the education system's adaptability. This study uses mixed-methods research to verify the model's effectiveness in practical educational management as well as to present fresh theoretical perspectives and practical tactics for cultivating high-qualified talents who will satisfy the needs of future society.

Research on Teaching Strategies of Group Reading in Primary Chinese based on Learning Task Group

This paper aims to explore the teaching strategy of group reading in primary school Chinese language education based on learning task groups. Through the construction of theoretical framework or conceptual model, the design and implementation of this teaching strategy are systematically expounded. Firstly, an overview of primary school Chinese language education, group reading teaching, and learning task group theory is provided, laying a theoretical foundation for the subsequent research. Then, the design principles, implementation steps, and preparation of teaching resources for the teaching strategy based on learning task groups are elaborated in detail. In the results section, the impact of this teaching strategy on students' reading levels and learning outcomes is analyzed. Finally, in the discussion and analysis section, the effectiveness of the teaching strategy is analyzed and evaluated, and comparisons with previous studies are made, along with prospects for future research. The conclusion summarizes the main findings of the study and discusses its contributions and implications for primary school Chinese language education, providing suggestions and insights for improving teaching practices.

Assessment of reclaimed water utilization in water-scarce regions of China: A multi-dimensional–multi-agent coupling and nesting perspective

Reclaimed water utilization is a vital strategy for combatting global water scarcity. In China, diverse degrees and types of water scarcity have led to insufficient and unbalanced reclaimed water utilization. To address this problem, this study introduces a novel perspective that considers multi-dimensional (reclaimed water quantity–quality–price) and multi-agent (reclaimed water producers–consumers–government) coupling and nesting to establish a comprehensive framework for evaluating the reclaimed water utilization level (RWUL) in water-scarce regions. This comprehensive framework, comprising theoretical research, model construction, and region selection, is applied to water-scarce regions of China. The findings reveal that the RWUL grades in these regions are generally modest—Grades I to III (lower-level to high-level reclaimed water utilization). The RWUL grades vary based on regional water scarcity combinations. RWUL grades in water-scarce regions characterized by low water quality scarcity (Type C) are lower than those in regions with high water quantity and high water quality scarcity (Type H), low water quantity and high water quality scarcity (Type G), and low water quantity and low water quality (Type D). However, none of these regions achieved Grade IV (higher-level reclaimed water utilization). Consequently, based on the identified main influencing factors of RWUL, this study proposes five region-tailored measures for each water scarcity combination of regions to enhance their RWUL. By offering a comprehensive framework for assessing RWUL in water-scarce regions of China, this study not only identifies the existing shortcomings in reclaimed water utilization but also provides tailored measures for improvement. These insights are essential for policymakers seeking to implement targeted measures that promote reclaimed water utilization in water-scarce regions.

Theoretical Model Construction and Path Exploration of Intelligent Party Building Education in Colleges and Universities

Abstract In the digital transformation era, higher education stands on the cusp of a revolution. This paper dives into the heart of this transformation, presenting a novel model of intelligent party building education that leverages digital technology to forge a new path for learning. Through the lens of ecological construction, we unveil the CFA model and a sophisticated deep knowledge tracking method aimed at enhancing student performance in Civic and Political Sciences. Our journey through empirical analysis and comparative experiments sheds light on the transformative power of digital education techniques. Despite the initial findings suggesting a modest impact of smart party building and teaching methods on knowledge retention (with significance levels of 0.6941 and 0.4963), a deeper exploration reveals a compelling narrative: the synergistic effect of these methods significantly boosts knowledge retention, as demonstrated by an F-value of 5.6941 and a P-value below 0.05. The prowess of Civics teachers, assessed across three dimensions, further narrates the success of this educational innovation, with scores reflecting their deep understanding of the curriculum and a robust theoretical knowledge base. The performance of 32 Civics teachers, with scores ranging from 12 to 24, underscores the efficacy of intelligent party building education in today’s colleges and universities.

Focusing property and optical field modulation of three-core fiber optical tweezers

This work develops a three-core fiber optical tweezers probe with a double cone angle and a tip microlens based on the Lorentz-Mie scattering theory. The primary parameters of the structural probe, such as the cone angle and the thickness of the microlens, are investigated and clarified by theoretical research, model construction, and simulation analysis. The best capture ability is at 44° of second-order cone angle. In order to create a focused light field, the microlens must be thicker than 8 μm. Under the probe framework, we investigated the primary purposes of various core optical powers. We designed a set of optical fiber tweezers control schemes to adjust the capture effect in real time, which enhances the control capability of optical fiber tweezers. We leverage the difference in input optical power between different cores. The focusing effect of the optical field can be changed, enabling real-time control of the captured item, by modifying the incidence angle and power. The power is inversely correlated with the movement of the capture position. The capture point moves 0.1 μm when the optical power is changed to 0.3 W/m.

Quantum Correlation Resource Recycling via Sequential Measurements: Theoretical Models and Optical Experiments

Quantum correlation is a key resource for a variety of quantum information processing and communication tasks, the efficient utilization of which has been a longstanding concern, and it is also one of the main challenges in the application of quantum technology. In this review, we focus on the interaction between quantum measurements and quantum correlations by designing appropriate measurement strategies, specifically exploring the trade-off between information gain and disturbance degree in weak measurements to ensure that quantum correlations from the same source can be shared among multiple independent observers. We introduce the basic knowledge and classification of quantum measurements, investigate the weak measurement scenario, and show the theoretical model construction of quantum correlation recycling in the original works. We summarize the theoretical and experimental development process and the latest progress in this field. Finally, we provide an outlook for more quantum resource applications that can profit from the optimization of quantum measurement strategies.

Construction of theoretical model of academic entrepreneurship behavior map: based on grounded theory analysis

It is worth exploring how “novices in academic entrepreneurship” can more clearly judge their performance in academic entrepreneurship process, self-diagnose the interaction effect between internal and external factors, and improve the effectiveness of entrepreneurial activities. This research takes Chinese academic entrepreneurs as the object, through the qualitative research method of grounded theory analysis, constructs the behavior map of academic entrepreneurship. The main stages of academic entrepreneurship chain are divided, including four stages: starting point, finding technology application, stabilizing technology application, and enterprise mature development. The common decision logic of academic entrepreneurs in each stage is explained. At the same time, the map shows the main influencing factors of academic entrepreneurial behavior and the logic of these factors’ influence on academic entrepreneurial behavior. The above results not only enrich the research theory in the field of academic entrepreneurship process, but also have guiding significance for the practical activities of “novices in academic entrepreneurship”.

Does black-box supplier involvement help buyers' product modular and architectural innovation? The moderating role of product modularity

PurposeIn product modular design tasks, especially in the high-tech manufacturing industry, buyers and supplies play distinct roles, which may have different impacts on product architectural and modular innovation. Prior research has tended to view product innovation as a holistic concept, overlooking the importance of this differentiated influence. This study, from a modular design perspective, aims to clarify the impact of black-box supplier involvement on product architectural and modular innovation, as well as the influence of product modularity on these relationships.Design/methodology/approachBased on the theory of product modular design, this study decomposes product innovation into architectural and modular innovation from the perspective of the product internal structure to conduct in-depth theoretical analysis and model construction. A total of 276 valid questionnaires are collected from typical Chinese high-tech manufacturing firms and used to empirically test the constructed theoretical model using multiple hierarchical regression analysis.FindingsThe results show that black-box supplier involvement positively affects modular innovation and takes an inverted U-shape, as moderated by product modularity. However, the impact of black-box supplier involvement on architectural innovation shows contradictory differences at different modularity levels. Under a low level of product modular design, black-box supplier involvement has a negative impact on architectural innovation, but under a moderate level of modular design, it has a positive impact. After the degree of modular design exceeds a certain threshold, the impact gradually weakens.Practical implicationsThe results provide valuable insights for managers, highlighting the need to avoid oversimplifying the innovation impact of black-box suppliers solely based on overall product innovation. Instead, a more accurate assessment of the innovation contributions of both the buyer and supplier should be based on the degree of architectural and modular innovation. Additionally, the findings suggest that managers should consider the alignment between their company's product modular design features and innovation priorities (i.e. modular innovation or architectural innovation) when determining an appropriate supplier collaborative development strategy.Originality/valueThis study not only reveals the different impacts of black-box supplier involvement on architectural and modular innovation, but also proves the significant synergistic innovation effect of the relationship between black-box supplier involvement and product modularization. It constitutes an enriched and deepened exploration in the existing research on supplier involvement in product innovation.

Neuro-safety science: an emerging discipline to reveal the neural mechanisms of safety problems.

At present, the research of safety science discipline is limited to the level of describing psychology and behaviors, because the cognitive neural mechanisms behind them are unknown. This paper introduces an emerging interdiscipline, namely neuro-safety science, which uses the neuroscientific methods to investigate the neural systems behind safely relevant behaviors. Qualitative methods such as literature review method and theoretical model construction method were adopted for this study. Based on the background of neuro-safety science, the definition of neuro-safety science was defined, its connotation was analyzed, and the research contents from two aspects of theoretical research and practical application research were proposed. Methodology system including research principles, research routes, research procedure and research methods, and the paradigm system of neuro-safety science were put forward. At last, the application research on neuro-safety science was forecasted. This paper opens up a new research perspective for the research of safety science, and provide guidance and reference to develop neuro-safety science.

Spatiotemporal Evolution and Cause Analysis of Innovation Ecosystem Niche Fitness: A Case Study of the Yellow River Basin

In this study, we explore the evolution and formation mechanism of innovation ecosystem niche fitness from three perspectives: theoretical analysis, model construction, and empirical testing. Based on the niche theory, a theoretical framework for the innovation ecosystem is constructed. Spatiotemporal analysis and qualitative comparison methods are employed to estimate the innovation niche fitness of nine provinces located in the Yellow River Basin, and their spatiotemporal characteristics and differences in terms of formation mechanism differences are then explored. The results show that: (1) temporally, from 2000 to 2017, the innovation niche fitness in the Yellow River Basin experienced minor fluctuations. However, since 2017, there has been a considerable increase. Spatially, the midstream and downstream regions, particularly in the provinces of Shandong, Henan, and Sichuan, have a higher innovation fitness. Conversely, the upstream regions of Qinghai, Ningxia, Gansu, and Inner Mongolia display a lower fitness because of the lack of advantages in innovation elements. (2) The innovation niche fitness is heavily influenced by several factors, including the number of industrial enterprises above designated size, R&D personnel, higher education institutions, scientific research institutions, expenditure for technical renovation, sales revenue of new products, total expenditure on R&D, and the total retail sales of consumer goods. (3) Four mechanisms explain high innovation niche fitness, each of which corresponds to different regions. The formation mechanisms of low innovation niche fitness can be categorized into two paths, which have an asymmetric relationship with the formation mechanisms of high innovation niche fitness. Therefore, provinces and regions should focus on these advantages to enhance the innovation niche fitness. Our research will serve as a theoretical reference to enhance the overall innovation capacity of the Yellow River Basin in the future.

Theoretical Research on the Influencing Factors of Collaborative Innovation in the Coal Industry: Based on the Collaborative Innovation in China’s Coal Industry

Purpose - Based on the importance of collaborative innovation in solving existing problems in the Chinese coal industry, this study mainly studies the categories of influencing factors of collaborative innovation in the Chinese coal industry.
 Design/Methodology/Approach - Due to the deep vertical intersection and extensive horizontal correlation of existing problems in the Chinese coal industry, collaborative innovation in the Chinese coal industry requires the use of a ““full factor”” collaborative innovation method. This study mainly comprehensively sorts out and analyzes the categories of influencing factors that affect collaborative innovation in the Chinese coal industry from a theoretical perspective. Based on this, a “pyramid spiral” operational process model for all-factor collaborative innovation in ’China’s coal industry has been constructed.
 Findings - Through theoretical analysis and model construction, this paper finds that the influencing factors of collaborative innovation in ’China’s coal industry are mainly divided into objective resource factors, subjective willingness factors, mode selection factors, and operational mechanism factors. Objective resource factors include research personnel, research funds, research facilities, research policies, and achievement transformation channels; Subjective willingness factors include research environment, resource complementarity, interest-driven, value orientation, etc; The factors for mode selection include the characteristics of scientific research projects, the level of research participants, etc; And the operational mechanism factors include team formation mechanism, mode selection mechanism, knowledge sharing mechanism, and achievement evaluation mechanism.
 Research Implications - This study lays a the oretical foundation for empirical research on the mechanism of the influencing factors of collaborative innovation in the Chinese coal industry. Also, it provides reference for constructing the operational mechanism of collaborative innovation in the Chinese coal industry.

Dynamic modeling and analysis of a vibration-driven robot driven by a conical dielectric elastomer actuator

This article aims to establish a theoretical model of a vibration-driven robot driven by a conical dielectric elastomer actuator and analyze its characteristics, in order to make up for the lack of theoretical model construction and parameter evolution analysis for this type of robot. This article introduces a vibration-driven robot driven by a conical dielectric elastomer actuator, and then establishes its dynamic model based on its electromechanical coupling and viscoelastic characteristics. Subsequently, simulation research is conducted using this model. Overall, this article derived a dynamic equation that can be applied to this type of robot, analyzed its motion characteristics, studied the effects of different parameters on it, and discussed the influence of viscoelasticity on vibration-driven robots. The proposed dynamic model and evolution law of vibration robots can provide theoretical guidance for subsequent control and optimization.

Self-adaptive physics-driven deep learning for seismic wave modeling in complex topography

Solving for the scattered wavefield is a key scientific problem in the field of seismology and earthquake engineering. Physics-informed neural networks (PINNs) developed in recent years have great potential in possibly increasing the flexibility and efficacy of seismic modeling and inversion. Inspired by self-adaptive physics-informed neural networks (SA-PINNs), we introduce a framework for modeling seismic waves in complex topography The relevant theoretical model construction was performed using the one-dimensional (1D) wave equation as an example. Using SA-PINNs and combining them with sparse initial wavefield data formed by the spectral element method (SEM), we carry out a numerical simulation of two-dimensional (2D) SH wave propagation to realize typical cases such as infinite/semi-infinite domain and arc-shaped canyon/hill topography. For complex scattered wavefields, a sequential learning method with time-domain decomposition was introduced in SA-PINNs to improve the scalability and solution accuracy of the network. The accuracy and reliability of the proposed method to simulate wave propagation in complex topography were verified by comparing the displacement seismograms calculated by the SA-PINNs method with those calculated by the SEM. The results show that the SA-PINNs have the advantage of gridless and fine-grained simulation and can realize numerical simulation conditions, such as free surface and side-boundary wavefield transmission.

Light–induced transition of charged carrier transport in symmetric metal–semiconductor–metal contacts

Metal–semiconductor (M–S) contact is a basic element in semiconductor integrated circuit. Recent studies on photodetectors extensively focus on M–S contact owing to the easy fabrication and superior performance. Here, we report a light–induced transition of charged carrier transport in planar Cu/Si–doped GaAs single crystal (Si:GaAs) symmetric double Schottky contacts. Different from conventional photodetector, illumination not only gains the carrier concentration but also changes the charged carrier transport mechanism at Cu/Si:GaAs contact. The light-induced transition of charged carrier transport is reflected by the change of shape of current–voltage (I–V) curve caused by illumination. By the construction of theoretical model and its fitting to experimental data, we point out that carrier transport mechanism at Cu/Si:GaAs contact changes from tunneling effect to thermionic emission by illumination. Among that, photovoltaic effect is the crucial driving force. This study presents a novel mechanism for converting optical signal to electrical signal by tailoring Schottky contact in photodetector, which provide a design prototype to new–type optoelectronic device.

Dynamic ageing research of cross‐linked polyethylene cable insulation based on temporal‐spatial dimension under combined electro‐thermal effect

AbstractDynamic ageing process of cross‐linked polyethylene (XLPE) cable insulation under combined electro‐thermal effect is investigated by the construction of theoretical analysis model and the practice of operation‐simulated ageing test. Firstly, theoretical analysis model is constructed from time and spatial dimensions. From the time dimension, in the light of the impeding trend of internal stress to external stress, the XLPE ageing process of Steady state ‐Transition state ‐Steady state (STS) is proposed to illustrate the dynamic ageing process of XLPE. From the spatial dimension, the insulation is divided into three scales to quantify the ageing. Secondly, to practice the theoretical analysis model, an operation‐simulated ageing test was conducted on two high voltage alternating current cables with service years of 15 and 30 for 540 days. Subsequently, relevant diagnostic measurements were applied to analyse the influence of physicochemical characteristics on the dielectric and heat transfer performances of the cables. The results show that the degradation of the actual operating cable is an extremely slow process. On the one hand, the response in physical changes of morphology counterbalances the external stress, maintaining the stability. On the other hand, once the chemical changes occur, negative feedback mechanism tends to impede the occurrence of further degradation by regulating fields distribution.

Spatiotemporal Evolution and Cause Analysis of Urban Housing Investment Resilience: An Empirical Study of 35 Large and Medium-Sized Cities in China

In this study, we explore the evolution and formation mechanism of urban housing investment resilience from three perspectives: theoretical analysis, model construction, and empirical testing. Based on the three-element theory of investment decision making and urban resilience system theory, a theoretical framework of urban housing investment resilience is constructed. Spatiotemporal analysis and qualitative comparison methods are used to divide 35 large and medium-sized cities into two categories, first-tier and non-first-tier cities, and their spatiotemporal characteristics and differences in terms of formation mechanism differences then explored. The results show that (1) the overall housing investment resilience of the 35 investigated cities is low, with the characteristics of periodic evolution, and there are obvious differences between the first-tier and non-first-tier cities as well as unbalanced development problems. (2) The three internal investment decision factors of returns, costs, and expectations and the five external support factors of economic growth, infrastructure development, labor market, policy regulation, and monetary policy do not, by themselves, constitute the necessary conditions for high levels of urban housing investment resilience, and there are three paths for the development of high levels of housing investment resilience in both first-tier and non-first-tier cities. (3) The twos types of cities have the same conformational path of "return- and cost-driven" but different dedicated conformational paths, including "cost-driven", "expectation- driven", and "return- and expectation-driven", and the core conditions in their driving paths are different, with real estate policy being the core condition in the path of first-tier cities and infrastructure development and labor markets being the core conditions in the path of non-first-tier cities. (4) There is a potential substitution relationship between the three configuration paths of first-tier and non-first-tier cities, and the substitution relationship between the two types of cities is also different. The findings of this study reveal that the complex interaction between the urban resilience system, represented by infrastructure construction, and multiple factors, including the three elements of investment, can have an impact on the resilience of real estate investment.

How the Experience Designs of Sustainable Festive Events Affect Cultural Emotion, Travel Motivation, and Behavioral Intention

Festivals are an important aspect of cultural design. They not only attract a large number of tourists but are also one of the most direct ways of promoting local culture. This study aimed to discover how festival experiences affect cultural feelings, travel motivations, and behavioral intentions. Based on literature research, theoretical model construction, and analysis, this paper begins with an exploration of the literature and designs a structural model to validate consumers’ expectations and conceptions of the 2021 Tainan Chihsi Festival. A total of 238 residents from Taiwan answered the questionnaire. This study used SEM and ANOVA for data analysis. The impact model of the festival experience design presented here can provide reference standards for in-depth research in related fields. Moreover, cultural emotion is a critical component in designing influential festive event experiences that evoke travel motivations and behavioral intentions. Virtual events can emphasize personal elements and educational content. In-person events can emphasize group interaction and entertainment. A combination of virtual and in-person experiences or personal and group exchanges would be ideal. Organizers should consider including emotional elements in their festive events in addition to originality. The inclusion of cultural elements can also foster “shared” experiences between locals and visitors, diversifying urban landscapes and strengthening community interaction. Organizers can plan festive events that align with consumers’ expectations, distinguish festive events from other community events, and add uniqueness and originality to their events.

County Economy, Population, Construction Land, and Carbon Intensity in a Shrinkage Scenario

As the largest ecological background system and basic economic unit in China, counties are of great significance to China’s carbon emission reduction targets. This article conducts theoretical model construction and empirical test research from a contraction perspective, using population and built-up area change as variables and combining indicators of county scale structure in an attempt to find key scale structure elements and representative indicators that affect the carbon emission intensity of counties. By using data from 140 counties in Northeast China during the period of 2015–2020, an empirical study was conducted on population shrinkage clustering, county size structure, and carbon emission intensity. The results show that: (1) population shrinkage significantly increases the carbon intensity of counties, but the contribution of population shrinkage to carbon intensity is scale-heterogeneous, the contribution effect decreases with population size, and the effect on large counties is minimal; (2) population size and industrial structure are the main factors influencing carbon intensity in counties, both have a negative linear elasticity relationship, and GDP per capita is not included in the overall model and is only significant in large counties; (3) the relationship between total construction land and carbon intensity is an inverted U-shaped Kuznets curve, with a critical value of 30 km2, and the total construction land in most counties is below or close to the critical value.