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Legal governance and banking efficiency

FINANCE RESEARCH LETTERS 2025年 79卷

作者： wang, shuwen Luo, Han Anhui Univ Finance & Econ Sch Law Bengbu 233030 Peoples R China Univ Int Business & Econ Sch Law Beijing 100029 Peoples R China

This study using panel data from 15 middle- and high-income countries between 2000 and 2022. Employing a fixed effects panel model, the analysis also investigates the moderating effect of income inequality on these relationships. The results indicate that the legal environment, corruption control, and regulatory quality all positively contribute to banking efficiency. Moderation analysis reveals that income inequality does not influence the positive effect of the legal environment but strengthens the positive effects of corruption control and regulatory quality. The study suggests that policymakers should prioritize strengthening legal infrastructure and improving regulatory standards to support banking system efficiency.

关键词： Banking efficiency Legal governance Financial development index Legal environment Corruption control Regulatory quality

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I_(ϵ+)LGEA:A Learning-Guided Evolutionary Algorithm Based on I_(ϵ+) Indicator for Portfolio Optimization

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Complex System Modeling and Simulation 2023年第3期3卷 191-201页

作者： Feng wang Zilu Huang shuwen wang School of Computer Science Wuhan UniversityWuhan 430072China Sloan School of Management Massachusetts Institute of TechnologyCambridgeMA 02139USA

Portfolio optimization is a classical and important problem in the field of asset management,which aims to achieve a trade-off between profit and *** portfolio optimization models use traditional risk measurements such as variance,which symmetrically delineate both positive and negative sides and are not practical and *** this paper,a new model with cardinality constraints is first proposed,in which the idiosyncratic volatility factor is used to replace traditional risk measurements and can capture the risks of the portfolio in a more accurate *** new model has practical constraints which involve the sparsity and irregularity of variables and make it challenging to be solved by traditional Multi-Objective Evolutionary Algorithms(MOEAs).To solve the model,a Learning-Guided Evolutionary Algorithm based on I_(ϵ+)indicator(I_(ϵ+)LGEA)is *** I_(ϵ+)LGEA,the I_(ϵ+)indicator is incorporated into the initialization and genetic operators to guarantee the sparsity of solutions and can help improve the convergence of the *** a new constraint-handling method based on I_(ϵ+)indicator is also adopted to ensure the feasibility of *** experimental results on five portfolio trading datasets including up to 1226 assets show that I_(ϵ+)LGEA outperforms some state-of-the-art MOEAs in most cases.

关键词： portfolio optimization evolutionary algorithm sparse solution space indicator-based Evolutionary Algorithm(EA)

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Effects of Psychological Resilience on Online Learning Performance and Satisfaction Among Undergraduates: The Mediating Role of Academic Burnout

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ASIA-PACIFIC EDUCATION RESEARCHER 2025年第1期34卷 395-409页

作者： wang, shuwen wang, Yang Zhao, Li Nanjing Normal Univ Sch Educ Sci 122 Ninghai Rd Nanjing 210097 Jiangsu Peoples R China

Online learning has accentuated the role and interaction of numerous educational and psychological factors among students, especially undergraduates. Psychological resilience, as an evaluative factor of mental health, has been confirmed in previous studies as having an effect on undergraduates' online learning performance and satisfaction. However, the mediating mechanisms should be further explored to fully understand the relationship between psychological resilience and online learning performance, as well as between psychological resilience and online learning satisfaction. To fill this gap, this study proposed a mediation model which included academic burnout as the mediating variable to clarify the relationships among psychological resilience, online learning performance and satisfaction. A total of 807 Chinese undergraduates with long-term experience of online learning voluntarily participated in this study. They completed the self-report measures of psychological resilience, online learning performance and satisfaction, as well as academic burnout. Results showed that in online learning, undergraduates' psychological resilience was negatively related to their academic burnout, psychological resilience was positively related to online learning performance and satisfaction, academic burnout was negatively related to online learning performance and satisfaction, and academic burnout mediated the effect of psychological resilience on online learning performance and satisfaction. The findings of this analysis offer practical guidance implications for undergraduates to improve their online learning, and provide theoretical support for instructors to focus on undergraduates' psychological status.

关键词： Academic burnout Learning performance Learning satisfaction Online learning Psychological resilience

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Do researchers from prestigious universities deserve advantages in research funding? Evidence from the National Natural Science Foundation of China

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SCIENTOMETRICS 2025年第3期130卷 1587-1615页

作者： wang, shuwen Li, Minglu Li, Jianping Wu, Dengsheng Chinese Acad Sci Inst Sci & Dev Beijing Peoples R China Univ Chinese Acad Sci Sch Publ Policy & Management Beijing Peoples R China Natl Nat Sci Fdn China Bur Policy Beijing Peoples R China Univ Chinese Acad Sci Sch Econ & Management Beijing Peoples R China Shenzhen Univ Coll Management Shenzhen Peoples R China

Existing literature underscores the unequal distribution of research funding across universities of varying prestige, yet the mechanisms through which university prestige influences funding success remain underexplored. Specifically, do Principal Investigators (PIs) from universities of differing prestige levels face divergent probabilities of funding success? Is this disparity solely attributable to differences in research capabilities, or does university prestige independently confer advantages, even among PIs with comparable qualifications? This study addresses these questions by analyzing unique application data from the National Natural Science Foundation of China, employing a combination of baseline regression models, matching methods, and panel data techniques. The results indicate that university prestige significantly increases the likelihood of funding success, even when controlling for the applicant's research background. Furthermore, among awarded grants, the prestige of the PI's affiliated university positively influences both academic productivity and scientific impact. Early-career affiliation with prestigious universities is also strongly linked to higher academic output and sustained funding acquisition, suggesting a "richer-get-richer" dynamic. By elucidating the mechanisms behind funding decisions, this study contributes to the theoretical understanding of research funding allocation and provides empirical insights for optimizing funding policy.

关键词： Research funding Matthew effect University prestige Scientific output National Natural Science Foundation of China (NSFC)

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Predictive Modeling of Hospital Readmission: Challenges and Solutions

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2022年第5期19卷 2975-2995页

作者： wang, shuwen Zhu, Xingquan Florida Atlantic Univ Dept Comp & Elect Engn & Comp Sci Boca Raton FL 33431 USA

Hospital readmission prediction is a study to learn models from historical medical data to predict probability of a patient returning to hospital in a certain period, e.g. 30 or 90 days, after the discharge. The motivation is to help health providers deliver better treatment and post-discharge strategies, lower the hospital readmission rate, and eventually reduce the medical costs. Due to inherent complexity of diseases and healthcare ecosystems, modeling hospital readmission is facing many challenges. By now, a variety of methods have been developed, but existing literature fails to deliver a complete picture to answer some fundamental questions, such as what are the main challenges and solutions in modeling hospital readmission;what are typical features/models used for readmission prediction;how to achieve meaningful and transparent predictions for decision making;and what are possible conflicts when deploying predictive approaches for real-world usages. In this paper, we systematically review computational models for hospital readmission prediction, and propose a taxonomy of challenges featuring four main categories: (1) data variety and complexity;(2) data imbalance, locality and privacy;(3) model interpretability;and (4) model implementation. The review summarizes methods in each category, and highlights technical solutions proposed to address the challenges. In addition, a review of datasets and resources available for hospital readmission modeling also provides firsthand materials to support researchers and practitioners to design new approaches for effective and efficient hospital readmission prediction.

关键词： Hospitals Predictive models Data models Computational modeling Diseases Taxonomy Biological system modeling Hospital readmission predictive modeling classification clustering electronic health records

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References Maxwell-based Permanent Magnet Synchronous Motor Short Circuit Faults and Electromagnetic Losses 3

References Maxwell-based Permanent Magnet Synchronous Motor ...

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3rd International Conference on Energy, Power and Electrical Technology, ICEPET 2024

作者： wang, shuwen Zhao, Aiming Shanghai Dianji University School of Electrical Engineering Shanghai China

ISBN: (纸本)9798350352658

Permanent magnet synchronous motor (PMSM) is a type of motor that is widely used in industrial production, possessing the high efficiency of permanent magnet motor and the precise control characteristics of synchronous motor. With the increase of the motor running time and the change of the external environment, it may lead to the damage of the insulation layer of the stator-side windings, resulting in the turn-to-turn short-circuit faults, which will have an adverse effect on the performance of the motor. In this paper, a 15KW water pump PMSM is selected, and the PMSM model is established by Ansys Maxwell finite element analysis software to study and analyse the relationship between stator side winding turn-to-turn short-circuit and electromagnetic loss, and compare the electromagnetic loss waveforms of the motor in normal operation and various turn-to-turn short-circuit conditions, and the analysis results show that the electromagnetic loss increases the most when the number of short-circuit turns is six. When the stator winding is short-circuited for five turns, the stator's iron consumption increases the most. In the case of a six-turn short circuit, the eddy current loss of the permanent magnet grows the most, and the copper consumption of the stator decreases the most. This provides a reference basis for motor short circuit fault diagnosis and preventive maintenance. © 2024 IEEE.

关键词： Stators

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LG-FAL: Locality-customized GSA Federated Active Learning 15

LG-FAL: Locality-customized GSA Federated Active Learning

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15th IEEE International Conference on Knowledge Graph, ICKG 2024

作者： wang, shuwen Zhu, Xingquan Portland State University Department of Computer Science Portland United States Florida Atlantic University Dept. of Electrical Engineering & Computer Science Boca Raton United States

ISBN: (纸本)9798331508821

Federated Learning (FL) is a learning paradigm which constructs machine learning models using decentralized datasets, with the goal of training a globally optimized model while preserving data privacy. In practice, annotating training data for FL is expensive and time-consuming. To solve this problem, researchers proposed to integrate active Learning (AL) strategy as Federated Active Learning (FAL) framework. However, existing research on FAL has two main limitations: (1) In the active learning part, more attention is paid to the global model, while ignoring the local information;(2) In the federated learning part, the popular Federated averaging (FedAvg) method relies on the assumption that the corresponding nodes in distributed neural networks share the same importance when averaging. In this paper, in order to tackle the two limitations, we propose a locality-customized GSA federated active learning (LG-FAL) method. Specifically, (i) both local and global information are taken into consideration to evaluate and select informative data samples to annotate for active learning;(ii) we integrate Gravitational Search Algorithm (GSA) to dynamically average local network parameters into the global parameter, by mimicking the principles of gravity and motion in the universe, for effective federated learning. As a result, LG-FAL can select a small subset of informative samples considering both local and global information, and at the same time, provide an improved trade-off between communication cost and learning accuracy. Experimental results show that LG-FAL significantly outperforms the current state-of-the-art baselines in terms of performance and effectiveness. © 2024 IEEE.

关键词： Federated learning

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Application of SIFT Algorithm based on the Gabor Features in Multi-source Information Image Monitoring

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IEIE Transactions on Smart Processing and Computing 2023年第2期12卷 112-121页

作者： wang, shuwen Cao, Huiqi Liu, Yao School of Electronics and Electrical Engineering Lingnan Normal University Zhanjiang524048 China

Under the background of today’s intelligence, the application of intelligent images is becoming popularized, and the detection of multi-source information images is a valuable research topic. Current image detection methods are insensitive and inaccurate. Therefore, the research combines the SIFT (scale-invariant feature transform) algorithm with the Gabor features and CNN (convolutional neural network (Ed note. Acronyms only need to be defined once.)) to form an improved new algorithm. The algorithm divides the features of the image into several different categories. In each category, the features will be fully identified and extracted, and different levels of feature matching will be performed. The properties of the SIFT algorithm are used to form an operational stacking pyramid and combine the Gabor features and CNN with it. The Gabor filter is formed into a filter bank to obtain parameters, including frequency, scale, and direction in various dimensions. The results are fused to obtain a fusion Gabor descriptor. The high sensitivity of CNN to images, particularly colors, is applied to the algorithm to make monitoring the algorithm more accurate. The experimental results show that the average precision rate, average recall rate, and average precision rate of the improved algorithm are 92.35%, 74.79%, and 82.55%, respectively, which are significantly higher than the other two algorithms used for comparison. The improved algorithm shows better performance and has remarkable advantages that can be applied to the image monitoring of image information. © 2023 Institute of Electronics and Information Engineers. All rights reserved.

关键词： Convolutional neural networks

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Friction stir processing of wire arc additively manufactured Al-Zn-Mg-Cu alloy reinforced with high-entropy alloy particles: Microstructure and mechanical properties

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JOURNAL OF ALLOYS AND COMPOUNDS 2025年 1020卷

作者： Shan, He Li, Yang wang, shuwen Yuan, Tao Chen, Shujun Beijing Univ Technol Inst Intelligent Forming Equipment & Syst Coll Mech & Energy Engn Beijing 100124 Peoples R China State Key Lab Mech Syst & Vibrat Shanghai 200240 Peoples R China

Wire arc additive manufacturing (WAAM) of Al-Zn-Mg-Cu alloys often leads to poor strength and ductility due to microstructure defects, significantly limiting its application. This study employed friction stir processing (FSP) to reduce porosity and break up continuous coarse second phases along the grain boundaries. By adding high-entropy alloy (HEA) particles with good wettability during FSP, Al-Zn-Mg-Cu alloy components with simultaneously improved strength and ductility were produced. The results indicated that the grain structure transformed from columnar to equiaxed and was refined to 2.3 mu m owing to the dynamic recrystallization of FSP and the particle-stimulated nucleation of HEA particles, while the continuous second phase was fragmented into nanoscale precipitates uniformly distributed in the matrix, acting as dislocation movement barriers. The newly formed Ni3Al precipitates second phases ensure good ductility due to its low lattice mismatch with Al matrix. Additionally, the HEA particles maintained strong interfacial bonding with Al matrix, with an interfacial layer thickness of similar to 400 nm. The FSP-HEA treated components showed increased hardness (151.8 HV), ultimate tensile strength (374.3 +/- 20.4 MPa), and elongation (10.6 % +/- 1.6 %) compared to the WAAM as-deposited state. This study provides guidance for the improvement of microstructural defects and the simultaneous enhancement of the strength and ductility of high-strength Al alloy WAAM components.

关键词： Al-Zn-Mg-Cu alloy Wire arc additive manufacturing Friction stir processing High-entropy alloy Particle reinforcement

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The Observed Effects of a Cold Wave on Over-the-Horizon Propagation in Evaporation Ducts Across Multiple Sea Areas

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IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION 2024年第1期72卷 852-861页

作者： Yang, Kunde Yang, Fan wang, shuwen Shi, Yang Zhang, Hao Northwestern Polytech Univ Sch Marine Sci & Technol Xian 710072 Peoples R China Northwestern Polytech Univ Ocean Inst Taicang 215400 Peoples R China Northwestern Polytech Univ Key Lab Ocean Acoust & Sensing Minist Ind & Informat Technol Xian 710072 Peoples R China

An evaporation duct is a persistent phenomenon that is formed by evaporation over the sea surface and influences marine communication and radar detection through its trapping effects. A cold wave is cold air that rapidly intensifies and intrudes a region with strong winds, a dry air mass, and precipitation, which affects the air-sea interactions and eventually affects the propagation of electromagnetic (EM) waves over the sea. However, there are few studies of over-the-horizon (OTH) propagation in evaporation duct during a cold wave. In this article, the path loss (PL) and atmospheric factors of two OTH propagation links over the Bohai Strait and Yellow Sea were observed during a cold wave in November 2021. The cold wave caused PL to decrease over 35.9 and 44.2 dB, respectively, at links over the Bohai Strait and Yellow Sea, as the evaporation duct height (EDH) simulated from the measured data increased 5.9 and 7.6 m. According to the sensitivity analysis, high wind speed (WS) was the main factor promoting seawater evaporation during the cold wave, while a decrease in air temperature (AT) had the opposite effect. These effects of cold wave should be taken into consideration in marine communication and radar detection systems to enable the optimal use.

关键词： Cold air cold wave evaporation duct multiple sea areas over-the-horizon (OTH) propagation

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