Supervision Mechanism Research Articles

MISP-Fuse: A progressive fusion network guided by Multi-Information supervision

The fusion of infrared and visible images aims to synthesize an image that combines the advantageous characteristics of both image sources. Nevertheless, existing image fusion algorithms often struggle to extract relevant feature information from the source images and find it challenging to balance the significance of different modality information within the source images. This leads to suboptimal fusion results and inadequately serve advanced downstream visual tasks. In order to confront this challenge, a novel image fusion algorithm, denoted as Multiple Information Supervised Progressive Fusion Network (MISP-Fuse), has been proposed. Specifically, MISP-Fuse employs an innovative and robust multi-stage encoder-decoder network called Full Scale Feature Residual network (FSFR) to extract spatial context and detailed feature information corresponding to infrared and visible images. Within this encoder-decoder network, source image feature information is progressively extracted at different stages, which are recombined at multiple scales and distilled for crucial information. Finally, the fusion image is generated through a spatial localization module named as Spatial Localization Network (SLNet). MISP-Fuse incorporates a multi-information supervision mechanism to establish a linkage between different modality information in the infrared and visible source images. It ensures that the resulting fused image not only aligns with human visual perception but also effectively serves advanced downstream visual tasks. The comparative experiments utilizing diverse image fusion benchmark datasets has been conducted. In comparison to other algorithms, MISP-Fuse demonstrated significant enhancements in comprehensive image fusion metrics, including Average Gradient (AG), Sum of Correlated Differences (SCD), and Correlation Coefficient (CC).

Monitoring, Supervising, and Improving Curriculum Systems in Arabic Language Education Study Programs at STAIN Mandailing Natal

This study aims to evaluate the monitoring, supervision, and curriculum improvement system in the Arabic Language Education Study Program at Sekolah Tinggi Agama Islam Negeri Mandailing Natal (STAIN Madina), assessing its effectiveness in enhancing Arabic language competence and supporting Islamic learning. Utilizing a qualitative research design, the study employs a case study methodology, combining interviews, observations, and documentation analysis. The findings reveal that the monev system, involving comprehensive planning, implementation, and reporting, effectively covers graduate competency standards, content standards, process standards, and learning assessment standards. The structured approach, involving multiple stakeholders, ensures thorough evaluation and continuous improvement. However, limitations such as the need for more in-depth internal supervision of content standards and challenges related to human resources and stakeholder engagement were noted. These findings are significant for higher education institutions aiming to enhance their curriculum systems, offering a model for structured monitoring and supervision. Further research is recommended to explore integrated internal supervision mechanisms and long-term effects on student outcomes.

Game analysis on PPP model operation of abandoned mines ecological restoration under the innovation of central government's reward and punishment system in China.

There is a huge funding gap in the abandoned mines ecological restoration in China. It is of great research value to explore how PPP model can better introduce social capital into the low-profit ecological restoration of abandoned mines. Based on the innovation perspective of the central government's reward and punishment system, this paper constructs an evolutionary game model of "local government-social capital", analyzes the interaction and behavior mechanism of core stakeholders in the operation process of abandoned mines ecological restoration PPP mode, and discusses the influence of evolutionary equilibrium strategy and parameters change on evolutionary strategy under different scenarios by Matlab simulation. The research shows that the abandoned mines ecological restoration needs the support of the central government. When the local government lightly punishes the low-quality service of social capital, the central government needs to pay higher costs to promote all parties to actively participate in the operation and supervision of the PPP project. The revenue and cost of government supervision, the operating subsidy for social capital and the cost saved by social capital in providing bad service are the key factors affecting the evolution of the game between government and social capital. Punishment can effectively spur social capital to keep the contract and operate in the project, but the punishment effect will be ineffective without government supervision. Finally, some suggestions are put forward, such as establishing a long-term supervision mechanism and a reasonable income mechanism for PPP projects, increasing penalties for violations, attracting third parties to reduce supervision costs and strengthening communication between the two parties, so as to make the project take into account the economic performance of social capital and the social welfare of government departments, and achieve dual Pareto improvement.

Training of New Professional Farmers in Rural Revitalization: A Reexamination based on Supply and Demand

The rural revitalization strategy is a crucial initiative aimed at promoting the modernization of rural areas, with the cultivation of new professional farmers emerging as a key component in its implementation. This paper conducts an in-depth analysis of the training of new professional farmers from the perspectives of both supply and demand. Addressing issues related to cultivation policies, key players, and training content during the cultivation process, the paper proposes a series of strategies in areas such as top-level design, classification management, cultivation models, content innovation, and supervision mechanisms. In terms of top-level design, the paper emphasizes the importance of defining strategic goals and pathways for cultivation to ensure alignment with the rural revitalization strategy. The strategy combining classification management with precision cultivation aims to implement differentiated training plans that better cater to the specific needs of different regions and rural areas. Reforms in cultivation models and content are advocated to align with the trends in modern agricultural development. Additionally, the establishment of a comprehensive supervision mechanism is recommended to ensure the fairness and transparency of cultivation efforts.

Reflections on the Use of Big Data Analysis to Enhance the Level of Grassroots Supervision Work in the Construction of Smart Customs -- Research on Supervision Scenario Innovation in Digital Government Construction

In the construction of smart customs, how to use the idea of digital government to strengthen the supervision and control of grassroots power has become a new mode indispensable for customs to improve its governance capacity in the era of big data. I study the significance of big data analysis on supervision in the construction of smart customs, the main structural characteristics, the current problems and measures, so as to make a better combination of big data analysis and grass-roots supervision, so as to establish a more efficient and more perfect supervision system, so that the supervision mechanism can run better, and to build a good cage of power.

Incentive-compatible mechanism for manufacturing carbon emission supervision under carbon control policies in China.

Enhance performance in manufacturing carbon emission (MCE) reduction has become a widespread consensus and a necessary part, which cannot be achieved without the joint participation of manufacturing enterprises and supervisory departments. Accordingly, how to coordinate the interests of both sides and design a reasonable incentive-compatible mechanism becomes an urgent task at present. Considering the two subsidy funding channels of peer funds and government finance, this study applies the evolutionary game model to analyze feasible schemes for designing incentive-compatible mechanism of MCE supervision, discusses and simulates the realistic scenarios and influencing factors of incentive-compatible mechanism under the non-subsidized and subsidized schemes. The results show that MCE supervision is in an incentive-incompatible state under the non-subsidized incentive scheme, while in a constrained incentive-compatible state under the subsidized incentive scheme. With the increase of peer funds and penalty coefficient or the decrease of subsidy coefficient, the period of MCE supervision to reach an incentive-compatible state becomes shorter. However, a lower peer fund and penalty coefficient or a higher subsidy coefficient will contribute to a state of incentive-incompatible or a periodic cycle state of "incentive-compatible → incentive-incompatible →incentive-compatible→…" in the MCE supervision.

Does internal control improve enterprise environmental, social, and governance information disclosure? Evidence from China

AbstractEnvironmental, social, and governance (ESG) is a relatively new concept that emphasizes how to contribute to creating sustainable businesses. However, research on factors that influence ESG development is insufficient. This study explores how internal control influence enterprise ESG information disclosure, using 2009–2021 data from China's A‐share listed companies. The findings show a substantial positive correlation between internal control quality and corporate ESG information disclosure. Particularly, the internal control quality significantly affects corporate governance information disclosure. Moreover, the connection between internal control quality and enterprise ESG information disclosure is significantly and positively moderated by media attention. Specifically, negative media evaluations have significant impacts on enterprises. The main findings remain valid even after conducting multiple robustness tests, such as the lag test, propensity score matching, instrumental variable method, and alternative measurements for the key variables. This study widens the theoretical research frontier of internal and external supervision mechanisms.

Research on risk precaution of intellectual property infringement in cross-border e-commerce

Cross-border e-commerce is one of the innovative applications of Internet technology in the field of foreign trade. In recent years, China's cross-border e-commerce business has developed rapidly, but it is also faced with the challenge of intellectual property infringement risk. This paper takes the intellectual property rights in China's cross-border e-commerce as the research object, analyzes the current situation and main types of intellectual property infringement risks, and sums up the reasons why China's International online trade enterprises frequently encounter intellectual property risks from the perspective of infringement. For example, the relevant laws and regulations, the supervision mechanism of export products need to be improved and perfected, and there are differences in the determination of intellectual property infringement liability in different countries. Based on this, this paper intends to put forward relevant improvement paths from the aspects of perfecting relevant laws and norms, strengthening the legal supervision of intellectual property rights, clarifying the imputation principle applicable to tort liability and increasing the intensity of compensation for intellectual property infringement damages, in order to promote the vigorous development of China's foreign trade industry.

Supervision of Non-Profit Organizations (NPO) On Potential Criminal Acts of Money Laundering and Terrorist Financing

The biggest challenge for NPOs is how the purpose of the NPO, to serve the community, can be run by legal corridors and not be used as a medium for money laundering for criminals or terrorism funding. Supervision of NPOs has a very important purpose in the context of preventing terrorism financing and also in the context of preventing money laundering. Therefore, the identification of donor recipients or beneficiaries for NPOs needs to be analyzed by looking at the existing regulatory framework, and whether the regulatory framework can effectively prevent money laundering and terrorism financing. This paper aims to discuss the supervision mechanism of NPOs in mitigating money laundering and terrorism financing, as well as the liability of NPOs if used as a medium for Money Laundering or Terrorist Financing. The research in this paper is Normative Research with Explanatory Descriptive Research Typology. The data analysis technique that the author uses is data analysis with a qualitative approach. Based on the research conducted by the author, it can be concluded that to prevent NPO funding from being misused for money laundering or terrorist financing, by way of supervision of the transaction flow of Mass Organizations as customers by the financial service provider through the identification and verification of donors and recipients or beneficial owner of NPO, and by the risk-based supervision of NPOs conducted by the Ministry that has authority to allow the establishment of NPOs through educating, monitoring and evaluation.

An information entropy-based fuzzy stochastic configuration network for robust data modeling

In data-driven modeling, the generalization performance of a neural network based on the minimum mean square error criterion may be affected when the samples contain noise. To handle uncertain data modeling problems, this study contributes a novel robust data modeling method called information entropy-based fuzzy stochastic configuration networks (IEFSCNs), which incorporates the maximum correntropy criterion (MCC) to reflect the squared error of the training sample set and uses the quantized minimum error entropy (QMEE) criterion to mine the distribution structure of the modeling data and suppress outlier data. Fuzzy systems are designed to generate nodes in the fuzzy transformation layer. A nonlinear enhancement layer is established as a hidden layer to enhance the representational capacity of the target system. The fuzzy transformation and nonlinear enhancement layers are fully connected to determine the outputs of the IEFSCNs. In addition, an incremental parameter learning algorithm is developed based on a supervision mechanism for optimizing the cost function, and its convergence property is demonstrated. Owing to the superiorities of the cost function by synthesizing MCC and QMEE, IEFSCNs can improve the modeling accuracy and reduce noise suppression. The performances are evaluated using various regression and classification tasks. Compared with existing methods, including SCNs, RVFL, F-SCNs, RSC-KDE, RSC-MCC, and SM-RSC, the proposed method demonstrates an effective robust modeling performance by reducing network structure redundancy while enhancing its ability to suppress noisy data.

The Manifestation, Causes, Countermeasures of “Double-Sided Person” in Current China’s University Teachers from the Perspective of Materialist Philosophy and Psychology

In current China, there is “double-sided person” in university teachers. This phenomenon is seriously threatening the development of universities and national undertakings. Therefore, this phenomenon must be effectively addressed. Recently, this phenomenon has received some attention from the academic community and become a hot theoretical theme. Meanwhile, many achievements has been achieved regarding this theme. However, further research are needed on it. Thus, the article conducts research on it from the perspective of materialist philosophy and psychology. From the perspective of materialist philosophy and psychology, this article mainly focuses on the main manifestations, causes, and countermeasures of “double-sided person” in current China’s university teachers. It summarizes the specific manifestations of “double-sided person” above-mentioned, analyzes why it formed and exists, and proposes some practical and effective countermeasures for it. Firstly, the main manifestation of “double-sided person” in current China’s university teachers is that a minority of them are verbally consistent with the theories, lines, guidelines, and strategies of China’s top administrative department, but their actual behavior is inconsistent with those above-mentioned. Then, from the perspective of materialist philosophy, the causes of “double-sided person” above-mentioned are as follows. The internal reason is that the thought qualities of a minority of university teachers are not strong enough. The external reason is that the relevant appointment, assessment, and supervision mechanisms of university teachers are not sound. From the perspective of psychology, the causes are personality distortion caused by cognitive dissonance, personality fission in motivational conflict dilemma, impression manipulation and negative effects of character labels, the accumulation of “mode personality” and the psychological disorder of “marginal individuals”. Last, the main countermeasures are as follows: First, improving the appointment and assessment mechanism of university teachers. Second, strengthening the daily supervision mechanism for university teachers. Third, strengthening the management of university teachers through the legal measures. Fourth, strengthening thought education for university teachers. Fifth, strengthening the governance of cyberspace related to university teachers. Sixth, establishing a unit alliance to address “double-sided person”.

Research on the Integration of Educational Resources in Higher Education Administration

In order to improve the integration of higher education resources, local governments should strengthen the administrative management of higher education and propose measures to promote social governance. Therefore, from the perspective of local autonomy, this paper puts forward the following hypotheses about local government behavior and public policy adjustment: whether local autonomy affects the adjustment of higher education policy, whether the role of local intervention policy and legal improvement overlaps, whether the impact on resource integration is perfect, whether the public supervision mechanism is perfect, whether the public plays a role in promoting the integration of educational resources, and whether local laws and regulations have an impact on the integration of educational resources, the educational environment, and the level of local governance. The results show that the policy intervention of local governments and the improvement of laws and regulations have a great impact on the integration of educational resources, which can optimize the educational structure and form a good educational environment, which is the direct factor of the integration of educational resources. Therefore, local governments should strengthen the introduction of intervention policies, improve laws and regulations, and guide the public to participate in the integration of education.

A study of the impact of staggered boards on corporate financialization: from the perspective of board governance.

The objective of this study is to assess the influence of staggered boards on corporate financialization and the role that incentive and supervision mechanisms play in this process. We employ a total of 20,647 panel data samples of Chinese A-share listed companies over the period 2011-2020 to empirically test the impact of staggered boards on corporate financialization in the Chinese context. The results indicate that implementing staggered boards significantly increases levels of corporate financialization. On the one hand, the implementation of a staggered board structure can exacerbate the speculative mindset and profit-driven behavior among board members, leading management to prioritize financial investments for personal gain. On the other hand, a staggered board system may also amplify managerial laziness, potentially incentivizing them to rely heavily on financial investments in order to swiftly achieve performance targets with minimal effort. Furthermore, both managerial ownership and audit supervision are found to be critical factors in mitigating this positive impact and preventing excessive financial investment behavior. This paper offers guidance on comprehending the applicability of staggered board provisions and mitigating financial risks in enterprises.

Challenges and Countermeasures of Internet Banking Supervision

Due to the continuous innovation of computer technology and the popularization of the Internet, the number of users, transaction volume and economic benefits of cyberbanking have shown a significant growth trend, which has contributed to the rapid development of cyberbanking. Compared with traditional banks, Internet banks utilize information technology in a more diversified way, and their service efficiency has been greatly improved. However, there are still many problems in China's Internet banking, such as failure to build a perfect legal supervision mechanism, ambiguous supervisory model and unclear supervisory content, which affect the safe operation of cyberbanking. Based on this, we should improve the legal system of cyberbanking supervision, explore new cyberbanking supervision model, and clarify the content of cyberbanking supervision, and improve the cyberbanking supervision system, so as to strengthen the legal supervision of cyberbanking and promote the healthy development of cyberbanking.

How does fiscal policy affect the green low-carbon transition from the perspective of the evolutionary game?

The implementation of effective fiscal policy is an inevitable choice to help green low-carbon transition and strengthen the construction of ecological civilization. This paper constructs a dynamic model of the tripartite evolutionary game among the central government, the local government and the high pollution and high carbon emission (Double-high) enterprises. Accordingly, we examine the impact of the central government's regulatory mechanism and local government's implementation intensity on green and low-carbon transition. Taking Comprehensive Demonstration Cities of Energy Conservation and Emission Reduction Fiscal Policies as the entry point of the study, a staggered differences-in-differences model is used for empirical evaluation, which reveals the effect of fiscal policy on green and low-carbon transition. The theoretical modeling shows that the strategies of Double-high enterprises are affected by the interaction between the central government and local governments, and there is diversity in the strategy stability and equilibrium state of each subject. Under the premise that the central government pays attention to the motives of enterprises and local governments, the fiscal subsidies, tax incentives and penalties of local governments, as well as the supervision, reward and punishment mechanisms and transfer payments of the central government, directly shape the impact of fiscal policy on green and low-carbon transition. The empirical results show that effective fiscal policy can promote green low-carbon transition, in which fiscal decentralization has a moderating role. Finally, the paper emphasizes the importance of the leading role of the central government and the implementation capacity of local governments, as well as the key role of internal changes within firms in addressing the relationship between emissions reduction and development.

A Continuous Non-Invasive Blood Pressure Prediction Method Based on Deep Sparse Residual U-Net Combined with Improved Squeeze and Excitation Skip Connections.

Arterial blood pressure (ABP) serves as a pivotal clinical metric in cardiovascular health assessments, with the precise forecasting of continuous blood pressure assuming a critical role in both preventing and treating cardiovascular diseases. This study proposes a novel continuous non-invasive blood pressure prediction model, DSRUnet, based on deep sparse residual U-net combined with improved SE skip connections, which aim to enhance the accuracy of using photoplethysmography (PPG) signals for continuous blood pressure prediction. The model first introduces a sparse residual connection approach for path contraction and expansion, facilitating richer information fusion and feature expansion to better capture subtle variations in the original PPG signals, thereby enhancing the network's representational capacity and predictive performance and mitigating potential degradation in the network performance. Furthermore, an enhanced SE-GRU module was embedded in the skip connections to model and weight global information using an attention mechanism, capturing the temporal features of the PPG pulse signals through GRU layers to improve the quality of the transferred feature information and reduce redundant feature learning. Finally, a deep supervision mechanism was incorporated into the decoder module to guide the lower-level network to learn effective feature representations, alleviating the problem of gradient vanishing and facilitating effective training of the network. The proposed DSRUnet model was trained and tested on the publicly available UCI-BP dataset, with the average absolute errors for predicting systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean blood pressure (MBP) being 3.36 ± 6.61 mmHg, 2.35 ± 4.54 mmHg, and 2.21 ± 4.36 mmHg, respectively, meeting the standards set by the Association for the Advancement of Medical Instrumentation (AAMI), and achieving Grade A according to the British Hypertension Society (BHS) Standard for SBP and DBP predictions. Through ablation experiments and comparisons with other state-of-the-art methods, the effectiveness of DSRUnet in blood pressure prediction tasks, particularly for SBP, which generally yields poor prediction results, was significantly higher. The experimental results demonstrate that the DSRUnet model can accurately utilize PPG signals for real-time continuous blood pressure prediction and obtain high-quality and high-precision blood pressure prediction waveforms. Due to its non-invasiveness, continuity, and clinical relevance, the model may have significant implications for clinical applications in hospitals and research on wearable devices in daily life.

Double‐layer Byzantine fault‐tolerant grouping consensus algorithm based on raft

AbstractAddressing the scalability issues, excessive communication overhead, and challenges in adapting to large‐scale network node environments faced by the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm currently employed in consortium blockchains, this paper proposes a Double Layer Consensus Algorithm Based on RAFT and PBFT Consensus Algorithms (DLCA_R_P). The nodes in the blockchain are initially divided into several groups to form the lower‐layer consensus network. Subsequently, the leaders of these groups constitute the upper‐layer consensus network, creating a dual‐layer consensus network structure. Within the lower‐layer consensus network, the PBFT consensus algorithm is employed for consensus among the groups, while the primary accountants form the upper‐layer RAFT consensus network. The algorithm incorporates a supervision mechanism and a reputation mechanism to enhance the security of the consensus network. Additionally, a grouping mechanism is introduced to transform the consensus network into a dynamic structure. Experimental results analysis demonstrates that compared to traditional PBFT consensus algorithms, DLCA_R_P reduces consensus latency by two orders of magnitude and improves throughput by one order of magnitude in a scenario with 100 nodes. Furthermore, it exhibits significant advantages over other improved algorithms. Thus, the DLCA_R_P consensus algorithm exhibits excellent scalability and can be widely applied in various scenarios within consortium blockchains.

Research on the "multi-agent co-governance" system of unfair competition on internet platforms: Based on the perspective of evolutionary game.

Unfair competition on internet platforms (UCIP) has become a critical issue restricting the platform economy's healthy development. This paper applies evolutionary game theory to study how to utilize multiple subjects' synergy to supervise UCIP effectively. First, the "multi-agent co-governance" mode of UCIP is constructed based on the traditional "unitary supervision" mode. Second, the government and internet platform evolutionary game models are built under two supervision modes. Finally, MATLAB is used to simulate and analyze the evolutionary stage and parameter sensitivity. In addition, we match the model's evolutionary stage with China's supervisory process. The results show that (1) the Chinese government's supervision of UCIP is in the transitional stage from "campaign-style" to "normalization." (2) Moderate government supervision intensity is essential to guide the game system to evolve toward the ideal state. If the supervision intensity is too high, it will inhibit the enthusiasm for supervision. If the supervision intensity is too low, it cannot form an effective deterrent to the internet platforms. (3) When the participation of industry associations and platform users is low, it can only slow down the evolutionary speed of the game system's convergence to the unfavorable state. Nevertheless, it cannot reverse the evolutionary result. (4) Maintaining the participation level of industry associations and platform users above a specific threshold value while increasing punishment intensity will promote the transition of government supervision from the "campaign-style" to the "normalization" stage. This paper provides ideas and references for the Chinese government to design a supervision mechanism for UCIP.

How do industrial land transfer modes impact carbon emissions? An intermediation perspective based on industrial structure.

Industrial land is currently the main carrier and important source of global carbon emissions, and as the world's largest developing country, China's large-scale and diversified industrial land supply has made it the world's largest carbon emitter. Therefore, researching the impact of different supply methods of industrial land on carbon emissions and its impact paths in China can help provide a reference for other countries to reduce carbon emissions from the perspective of urban industrial land management, which is of great significance for effectively promoting global carbon reduction. Based on this, this paper analyses the impact of different supply methods of industrial land on carbon emissions and its urban heterogeneity using the SYS-GMM and chain-mediated effects models for 285 cities in China from 2008 to 2020. The study found that, in general, the impact of different industrial land transfer modes on carbon emission has hysteresis and persistence. Agreement and listing transfer with government intervention can significantly exacerbate carbon emissions, while more market-based bidding and auction transfer can dampen carbon emissions. In terms of intermediary effects, the transfer of industrial land by agreement and listing will inhibit the rationalization and advancement of industrial structure, thus aggravating carbon emissions. The transfer of industrial land by bidding and auction will create barriers to entry and a crowding-out effect, promote the rationalization of industrial structure and the transformation and upgrading of industrial structure and moderate carbon emissions. In terms of city heterogeneity, there is urban heterogeneity in the impact of industrial land transfer on carbon emissions in cities with different economic types. Bidding and auction transfer for industrial land in both economically developed and less developed cities can promote carbon pollution. While the more developed urban economy makes the intermediary effect of industrial structure not significant. In the future, it is necessary to strictly control the scale of industrial land supply; the whole process supervision mechanism of industrial land allocation and differentiated industrial land supply strategies will provide useful experience for many developing countries in allocating industrial land to mitigate carbon emissions, generating effective contributions to global carbon emission reduction.

Analysis of Factors Influencing Employee Performance at the Regional Civil Service Education and Training Agency of Pohuwato Regency

This research aims to analyze the factors influencing employee performance at the Regional Education and Training Personnel Agency of Pohuwato Regency. The sample targeted for the study consists of 33 individuals, all of whom participated as respondents using multiple linear regression. Based on the analysis, it was found that the decision-making mechanism variable has a positive but non-significant effect on employee performance, the management professionalism variable has a positive and significant effect on employee performance, the supervision and control mechanism variable has a positive and significant effect on employee performance, and the decision-making mechanism, management professionalism, and supervision and control mechanisms collectively have an effect on the performance of the Regional Education and Training Personnel Agency of Pohuwato Regency employees.