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arXiv 2025年

作者： Zhang, Tongliang Zheng, Lijing Wang, Hengtai Peng, Jie Li, Yanjun College of Science North China University of Science and Technology Hebei Tangshan063000 China Hebei Key Laboratory of Data Science and Application North China University of Science and Technology Hebei Tangshan063000 China School of Mathematics and Physics University of South China Hunan Hengyang421001 China Mathematics and Science College Shanghai Normal University Shanghai200234 China Institute of Statistics and Applied Mathematics Anhui University of Finance and Economics Anhui Bengbu233030 China

Let q = 2m. In a recent paper [31], Zhang and Zheng investigated several classes of permutation pentanomials of the form ϵ0xd0+L(ϵ1xd1+ϵ2xd2) over Fq3 (d0 = 1, 2, 4) from some certain linearized polynomial L(x) by using multivariate method and some techniques to determine the number of the solutions of some equations. They proposed an open problem that there are still some permutation pentanomials of that form have not been proven. In this paper, inspired by the idea of [12], we further characterize the permutation property of the pentanomials with the above form over Fq3 (d0 = 1, 2, 4). The techniques in this paper would be useful to investigate more new classes of permutation pentanomials. Copyright © 2025, The Authors. All rights reserved.

关键词： Polynomials

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A new quantile treatment effect model for studying smoking effect on birth weight during Mother's pregnancy

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Journal of Management science and Engineering 2021年第3期6卷 336-343页

作者： Shengfang Tang Zongwu Cai Ying Fang Ming Lin Wang Yanan Institute for Studies in Economics and Fujian Key Laboratory of Statistical Sciences Xiamen UniversityXiamen361005China Department of Economics University of KansasLawrenceKS66045USA Department of Statistics and Data Science School of EconomicsXiamen UniversityXiamen361005China

This paper proposes a new quantile regression model to characterize the heterogeneity for distributional effects of maternal smoking during pregnancy on infant birth weight across different the mother's *** imposing a parametric restriction on the quantile functions of the potential outcome distributions conditional on the mother's age,we estimate the quantile treatment effects of maternal smoking during pregnancy on her baby's birth weight across different age groups of *** results show strongly that the quantile effects of maternal smoking on low infant birth weight are negative and substantially heterogenous across different ages.

关键词： Birth weight Heterogeneity Quantile regression Smoking Treatment effect

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On stochastic control problems with higher-order moments

arXiv

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arXiv 2024年

作者： Wang, Yike Liu, Jingzhen Bensoussan, Alain Yiu, Ka-Fai Cedric Wei, Jiaqin School of Finance Chongqing Technology and Business University Chongqing400067 China China Institute for Actuarial Science Central University of Finance and Economics Beijing100081 China Naveen Jindal School of Management University of Texas at Dallas DallasTX75083 United States Department of Applied Mathematics The Hong Kong Polytechnic University Kowloon Hunghom Hong Kong Key Laboratory of Advanced Theory and Application in Statistics and Data Science MOE School of Statistics East China Normal University Shanghai200241 China

In this paper, we focus on a class of time-inconsistent stochastic control problems, where the objective function includes the mean and several higher-order central moments of the terminal value of state. To tackle the time-inconsistency, we seek both the closed-loop and the open-loop Nash equilibrium controls as time-consistent solutions. We establish a partial differential equation (PDE) system for deriving a closed-loop Nash equilibrium control, which does not include the equilibrium value function and is different from the extended Hamilton-Jacobi-Bellman (HJB) equations as in Björk et al. (finance Stoch. 21: 331-360, 2017). We show that our PDE system is equivalent to the extended HJB equations that seems difficult to be solved for our higher-order moment problems. In deriving an open-loop Nash equilibrium control, due to the non-separable higher-order moments in the objective function, we make some moment estimates in addition to the standard perturbation argument for developing a maximum principle. Then, the problem is reduced to solving a flow of forward-backward stochastic differential equations. In particular, we investigate linear controlled dynamics and some objective functions affine in the mean. The closed-loop and the open-loop Nash equilibrium controls are identical, which are independent of the state value, random path and the preference on the odd-order central moments. By sending the highest order of central moments to infinity, we obtain the time-consistent solutions to some control problems whose objective functions include some penalty functions for *** Codes Primary: 93E20, 91G80, Secondary: 91B08, 49N90 Copyright © 2024, The Authors. All rights reserved.

关键词： Nash equilibrium

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COVID-19 transmission driven by age-group mathematical model in Shijiazhuang City of China

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Infectious Disease Modelling 2023年第4期8卷 1050-1062页

作者： Fengying Wei Ruiyang Zhou Zhen Jin Senzhong Huang Zhihang Peng Jinjie Wang Ximing Xu Xinyan Zhang Jun Xu Yao Bai Xiaoli Wang Bulai Lu Zhaojun Wang Jianguo Xu School of Mathematics and Statistics Fuzhou UniversityFuzhou350116FujianChina Center for Applied Mathematics of Fujian Province Fuzhou UniversityFuzhou350116FujianChina Key Laboratory of Operations Research and Control of Universities in Fujian Fuzhou UniversityFuzhou350116FujianChina Complex Systems Research Center Shanxi UniversityTaiyuan030006ShanxiChina School of Statistics and Data Science ZhiYing Research Center for Health DataNankai University300071TianjinChina Department of Biostatistics School of Public HealthNanjing Medical UniversityNanjing211166JiangsuChina Nankai Institute of Economics Binhai Development InstituteNankai UniversityTianjin300071China Children's Hospital of Chongqing Medical University Chongqing400010China Jinzhou Center for Disease Control and Prevention Jinzhou121000LiaoningChina School of Statistics and Data Science Nankai UniversityTianjin300071China Xi'an Center for Disease Control and Prevention Xi'an710061ShaanxiChina Beijing Center for Disease Control and Prevention Beijing100013China Suzhou Center for Disease Control and Prevention Suzhou215004JiangsuChina State Key Laboratory of Communicable Disease Prevention and Control National Institute for Communicable Disease Control and PreventionChinese Center for Disease Control and PreventionBeijing102206China Institute of Public Health Nankai UniversityTianjin300071China

Background:A COVID-19 outbreak in the rural areas of Shijiazhuang City was attributed to the complex interactions among vaccination,host,and non-pharmaceutical interventions(NPIs).Herein,we investigated the epidemiological characteristics of all reported symptomatic cases by picking Shijiazhuang City,Hebei Province in Northern China as research *** addition,we established an age-group mathematical model to perform the optimal fitting and to investigate the dynamical profiles under three ***:All reported symptomatic cases of Shijiazhuang epidemic(January 2-February 3,2021)were investigated in our *** cases were classified by gender,age group and location,the distributions were analyzed by epidemiological ***,the reported data from Health Commission of Hebei Province was also analyzed by using an age-group mathematical model by two phases and three ***:Shijiazhuang epidemic caused by SARS-CoV-2 wild strain was recorded with the peak 84 cases out of 868 reported symptomatic cases on January 11,2021,which was implemented with strong NPIs by local government and referred as baseline situation in this *** research results showed that R0 under baseline situation ranged from 4.47 to 7.72,and Rt of Gaocheng Distinct took 3.72 with 95%confidence interval from 3.23 to 4.35 on January 9,the declining tendencies of Rt under baseline situation were kept till February 3,the value of Rt reached below 1 on January 19 and remained low value up to February 3 for Gaocheng District and Shijiazhuang City during Shijiazhuang *** indicated Shijiazhuang epidemic was under control on January ***,if the strong NPIs were kept,but remote isolation operated on January 11 was not implemented as of February 9,then the scale of Shijiazhuang epidemic reached 9,482 cases from age group who were 60 years old and over out of 31,017 symptomatic *** investigation also revealed that Shijiazhuang epidemic reache

关键词： COVID-19 Wild strain Non-pharmaceutical interventions Shijiazhuang epidemic Transmission dynamics

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On a fast consistent selection of nested models with possibly unnormalised probability densities

arXiv

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arXiv 2025年

作者： Bian, Rong Chan, Kung-Sik Cheng, Bing Tong, Howell Academy of Mathematics and System Science Chinese Academy of Sciences Beijing China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing China Department of Statistics and Actuarial Science University of Iowa Iowa City United States AMSS Center for Forecasting Science Chinese Academy of Sciences Beijing China State Key Laboratory of Mathematical Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China Department of Statistics London School of Economics and Political Science London United Kingdom Department of Statistics and Data Science Tsinghua University Beijing China Paula and Gregory Chow Institute for Studies in Economics Xiamen University Xiamen China

Models with unnormalized probability density functions are ubiquitous in statistics, artificial intelligence and many other fields. However, they face significant challenges in model selection if the normalizing constants are intractable. Existing methods to address this issue often incur high computational costs, either due to numerical approximations of normalizing constants or evaluation of bias corrections in information criteria. In this paper, we propose a novel and fast selection criterion, T-GIC, for nested models, allowing direct data sampling from a possibly unnormalized probability density function. T-GIC gives a consistent selection under mild regularity conditions and is computationally efficient, benefiting from a multiplying factor that depends only on the sample size and the model complexity. Extensive simulation studies and real-data applications demonstrate the efficacy of T-GIC in the selection of nested models with unnormalized probability densities. Copyright © 2025, The Authors. All rights reserved.

关键词： Normal distribution

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Service-oriented manufacturing:A literature review and future research directions

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Frontiers of Engineering Management 2022年第1期9卷 71-88页

作者： Zhong-Zhong JIANG Guangqi FENG Zelong YI Xiaolong GUO School of Business Administration&Institute of Behavioral and Service Operations Management Northeastern UniversityShenyang 110167China Key Laboratory of Data Analytics and Optimization for Smart Industry(Northeastern University) Ministry of EducationShenyang 110819China Department of Transportation Economics and Logistics Management College of EconomicsShenzhen UniversityShenzhen 518060China Anhui Province Key Laboratory of Contemporary Logistics and Supply Chain International Institute of FinanceSchool of ManagementUniversity of Science and Technology of ChinaHefei 230026China

This study presents a systematic review of the literature on service-oriented manufacturing(SOM).Specifically,we focus on the impact of SOM on firm operating decisions,which distinguishes this work from previous *** study proposes a classification framework for SOM research based on product flow,from its design to its final *** SOM has been studied for many years,most related research remains *** criterion for choosing papers is that they must be relevant to practical *** review aims to provide readers a guide that will facilitate their search for papers in their field of *** importantly,we hope that this review can provide insightful managerial implications for SOM.

关键词： service-oriented manufacturing product-service systems servitization servicing operations management

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Adaptive Robust Multi-View Linex-Based Xgboost Model for Credit Risk Assessment

SSRN

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SSRN 2023年

作者： Tang, Jingjing Zhu, Guorui Li, Jiahui Tian, Yingjie School of Business Administration Faculty of Business Administration Southwestern University of Finance and Economics Chengdu611130 China Institute of Big Data Southwestern University of Finance and Economics Chengdu611130 China School of Economics and Management University of Chinese Academy of Sciences Beijing100190 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China

Credit risk assessment is crucial for financial institutions. The data-driven methods regard the credit risk assessment as the class-imbalanced binary classification task since the non-default samples greatly outnumber default samples. Ensemble learning offers more advantages over traditional single classifier for credit risk assessment. Besides, the credit data can be extracted from multiple sources, such as personal credit data from financial institutions, personal tax payment data from government departments, telecommunications overdue data from public utilities, etc. They are typical multi-view data. How to fully exploit such multi-view and class-imbalanced data is the main challenge for the improvement of the credit risk assessment. This study proposes a cost-sensitive multi-view ensemble learning model called CSMEL. It firstly adapts the loss of XGBoost with the asymmetric LINEX loss function to construct the cost-sensitive base classifier, and then designs a multi-view ensemble learning framework for the combination of base classifiers. The asymmetry of Linex loss contributes to not only assign different weights to the misclassification errors from the non-default and default classes, but also make the base classifiers robust to noises. Extensive experiments on the Corel datasets and Credit risk datasets validate the effectiveness of the CSMEL model. © 2023, The Authors. All rights reserved.

关键词： Public utilities

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Hierarchical Alignment-enhanced Adaptive Grounding Network for Generalized Referring Expression Comprehension 39

Hierarchical Alignment-enhanced Adaptive Grounding Network f...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Wang, Yaxian Ding, Henghui He, Shuting Jiang, Xudong Wei, Bifan Liu, Jun School of Computer Science and Technology Xi'an Jiaotong University China Ministry of Education Key Laboratory of Intelligent Networks and Network Security Xi'an Jiaotong University China Institute of Big Data Fudan University China Shanghai University of Finance and Economics China Nanyang Technological University Singapore School of Continuing Education Xi'an Jiaotong University China Shaanxi Province Key Laboratory of Big Data Knowledge Engineering Xi'an Jiaotong University China

ISBN: (纸本)157735897X

In this work, we address the challenging task of Generalized Referring Expression Comprehension (GREC). Compared to the classic Referring Expression Comprehension (REC) that focuses on single-target expressions, GREC extends the scope to a more practical setting by further encompassing no-target and multi-target expressions. Existing REC methods face challenges in handling the complex cases encountered in GREC, primarily due to their fixed output and limitations in multi-modal representations. To address these issues, we propose a Hierarchical Alignment-enhanced Adaptive Grounding Network (HieA2G) for GREC, which can flexibly deal with various types of referring expressions. First, a Hierarchical Multi-modal Semantic Alignment (HMSA) module is proposed to incorporate three levels of alignments, including word-object, phrase-object, and text-image alignment. It enables hierarchical cross-modal interactions across multiple levels to achieve comprehensive and robust multi-modal understanding, greatly enhancing grounding ability for complex cases. Then, to address the varying number of target objects in GREC, we introduce an Adaptive Grounding Counter (AGC) to dynamically determine the number of output targets. Additionally, an auxiliary contrastive loss is employed in AGC to enhance object-counting ability by pulling in multi-modal features with the same counting and pushing away those with different counting. Extensive experimental results show that HieA2G achieves new state-of-the-art performance on the challenging GREC task and also the other 4 tasks, including REC, Phrase Grounding, Referring Expression Segmentation (RES), and Generalized Referring Expression Segmentation (GRES), demonstrating the remarkable superiority and generalizability of the proposed HieA2G. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Modal analysis

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Hierarchical Alignment-enhanced Adaptive Grounding Network for Generalized Referring Expression Comprehension

arXiv

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arXiv 2025年

In this work, we address the challenging task of Generalized Referring Expression Comprehension (GREC). Compared to the classic Referring Expression Comprehension (REC) that focuses on single-target expressions, GREC extends the scope to a more practical setting by further encompassing notarget and multi-target expressions. Existing REC methods face challenges in handling the complex cases encountered in GREC, primarily due to their fixed output and limitations in multi-modal representations. To address these issues, we propose a Hierarchical Alignment-enhanced Adaptive Grounding Network (HieA2G) for GREC, which can flexibly deal with various types of referring expressions. First, a Hierarchical Multi-modal Semantic Alignment (HMSA) module is proposed to incorporate three levels of alignments, including word-object, phrase-object, and text-image alignment. It enables hierarchical cross-modal interactions across multiple levels to achieve comprehensive and robust multi-modal understanding, greatly enhancing grounding ability for complex cases. Then, to address the varying number of target objects in GREC, we introduce an Adaptive Grounding Counter (AGC) to dynamically determine the number of output targets. Additionally, an auxiliary contrastive loss is employed in AGC to enhance object-counting ability by pulling in multi-modal features with the same counting and pushing away those with different counting. Extensive experimental results show that HieA2G achieves new state-of-the-art performance on the challenging GREC task and also the other 4 tasks, including REC, Phrase Grounding, Referring Expression Segmentation (RES), and Generalized Referring Expression Segmentation (GRES), demonstrating the remarkable superiority and generalizability of the proposed HieA2G. Copyright © 2025, The Authors. All rights reserved.

关键词： Electric grounding

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DiGAN Breakthrough: Advancing diabetic data analysis with innovative GAN-based imbalance correction techniques

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Computer Methods and Programs in Biomedicine Update 2024年 5卷

作者： Zhao, Puyang Liu, Xinhui Yue, Zhiyi Zhao, Qianyu Liu, Xinzhi Deng, Yuhui Wu, Jingjin Department of Biostatistics The University of Texas Health Science Center at Houston Houston TX United States Department of Statistics The London School of Economics and Political Science London United Kingdom Department of Civil and Environmental Engineering Duke University Durham NC United States School of Physics Southeast University Nanjing China Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science Department of Statistics and Data Science BNU-HKBU United International College Zhuhai China

In the rapidly evolving field of medical diagnostics, the challenge of imbalanced datasets, particularly in diabetes classification, calls for innovative solutions. The study introduces DiGAN, a groundbreaking approach that leverages the power of Generative Adversarial Networks (GAN) to revolutionize diabetes data analysis. Marking a significant departure from traditional methods, DiGAN applies GANs, typically seen in image processing, to the realm of diabetes data. This novel application is complemented by integrating the unsupervised Laplacian Score for sophisticated feature selection. The pioneering approach not only surpasses the limitations of existing techniques but also sets a new benchmark in classification accuracy with a 90% weighted F1-score, achieving a remarkable improvement of over 20% compared to conventional methods. Additionally, DiGAN demonstrates superior performance over popular SMOTE-based methods in handling extremely imbalanced datasets. This research, focusing on the integrated use of Laplacian Score, GAN, and Random Forest, stands at the forefront of diabetic classification, offering a uniquely effective and innovative solution to the long-standing data imbalance issue in medical diagnostics. © 2024 The Authors

关键词： Correction techniques Diabetes GAN Imbalanced classification Laplacian score

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