The effectiveness of flight operations and the quality of airport services are directly impacted by airport gate assignment options.In real-world operations,unexpected events such as airfield accidents may lead to the temporary closure of local gates and an infeasible assignment plan.It is urgent to implement gate emergency reassignment under resource constraints.This paper proposes an Epsilon constraint-based column generation optimization algorithm for this problem.In particular,we develop a bi-objective optimization model based on set partitioning with the goal of minimizing assignment plan deviation and increasing solution efficiency.Then,an Epsilon constraint-based column generation optimization algorithm is designed to efficiently obtain high-quality solutions.Numerical experiments are conducted based on real-world operational data from an international airport.The results demonstrate that the proposed method performs well on main metrics such as the bridge boarding rate and flights adjustment efficiency.In particular,the cross-region adjustment proportion of our solution is 52.34%,which is significantly lower than the comparison methods,and effectively improves the airport operational efficiency in emergency scenarios.

Airport disruptions often pose challenges in assigning aircraft to gates, resulting in infeasible planned schedules. In particular, a large number of transfer passengers miss their connections in the context of disruptions, which cause huge economic losses to airlines and serious passengers’ dissatisfaction. This paper proposes a set-partitioning-based model to optimize Aircraft-Gate Reassignment with Transfer Passenger Connections (AGRP-TPC), which incorporates flexible gate-swap and aircraft-delay operations to mitigate the overall impact of disruptions. To efficiently solve the model, we introduce the concepts of additive-transfer and nonstop-transfer to handle passenger connections, and develop a Hierarchical Column-and-Row Generation (HCRG) approach guided by airport terminal space attribute. The column generation and row generation procedures solve iteratively until no new variables and constraints are generated. In addition, a follow-on strategy and a diving heuristic are designed to efficiently obtain high-quality solutions. We evaluate the proposed approach using various instances from a major Chinese international airport. Computational results demonstrate that our approach outperforms the comparison algorithms and produces good solutions within the time limit. Detailed results indicate that our approach effectively reduces overall losses in aircraft-gate reassignment following disruptions, and it can serve as an auxiliary decision-making tool for airport operators and airlines.

Many recent studies have used reinforcement learning methods to investigate the behavior of agents in evolutionary games. Q-learning, in particular, has become a mainstream method during this development. Here we introduce Q-learning agents into the evolutionary prisoner's dilemma game on a square lattice. Specifically, we associate the state space of Q-learning agents with the strategies of their neighbors, and we introduce a neighboring reward information sharing mechanism. We thus provide Q-learning agents with the payoff information of their neighbors, in addition to their strategies, which has not been done in previous studies. Through simulations, we show that considering neighborhood payoff information can significantly promote cooperation in the population. Moreover, we show that for an appropriate strength of neighborhood payoff information sharing, a chessboard pattern emerges on the lattice. We analyze in detail the reasons for the emergence of the chessboard pattern and the increase in cooperation frequency, and we also provide a theoretical analysis based on the pair approximation method. We hope that our research will inspire effective approaches for resolving social dilemmas by means of sharing more information among reinforcement learning agents during evolutionary games.

Scientific collaboration is an essential aspect of the educational field, offering significant reference value in resource sharing and policy making. With the increasing diversity and inter-disciplinary nature of educational research, understanding scientific collaboration within and between various subfields is crucial for its development. This article employs topic modelling to extract educational research topics from publication metadata obtained from 265 scientific journals spanning the period from 2000 to 2021. We construct a multilayer co-authorship network whose layers represent the scientific collaboration in different subfields. The topological properties of the layers are compared, highlighting the differences and common features of scientific collaboration between hot and cold topics, with the main difference being the existence of a significant largest connected component. Further, the cross-layer cooperation behaviour is investigated by studying the structural measures of the multilayer network and reveals authors’ inclination to collaborate with familiar individuals in familiar subfields. Moreover, the relationships between the authors’ features on the network topology and their H-index are investigated. The results emphasize the significance of establishing a clear research direction to enhance the academic reputation of authors, as well as the importance of cross-layer collaboration for expanding their research groups. Finally, based on the above results, we propose a multilayer network generation model of scientific collaboration and verify its validity.

Education is not only a guarantee of personal knowledge, but also a topic of national importance. In this paper, we analyzed the scientific papers published by authors from China and the United States in 239 educational journals over a period of 20 years (2000-2019). We first extracted the topic of each paper via the Latent Dirichlet allocation model, which demonstrated significant differences in specific sub-fields between both countries. Next, we constructed two networks of scientific collaboration among the educators of each country. By analyzing these networks' topological properties, we show both countries' differences and common features. Regarding individuals, Chinese educators collaborate widely, whereas American educators are more likely to collaborate in certain groups. Regarding groups, there exists an optimal team size for producing highly popular papers in both countries. (C) 2021 Published by Elsevier B.V.

The evolutionary ultimatum game is a powerful paradigm to study the evolution of fairness. Most studies to date assume that a player adopts the same strategy against all his/her opponents. Apart from these works, there are also works exploring the evolution of fairness when various psychological and social factors influence strategies, but celebrity has never been considered. In this paper, we introduce the effect of celebrity, under which a player behaves more generous or stingier when faces different opponents. The celebrity of individuals in a social network is defined as their degree, and ordinary people have small degrees while celebrities have large degrees. The result shows that if ordinary people tend to be more generous to celebrities and celebrities are stingier to the ordinary, fairness will be enhanced first and gradually evolves to an over-fair level.

该文分析了高校来华留学生的培养现状和人才培养目标,以北京航空航天大学电子信息工程学院隆德试验班为例,探索探究留学生同班国际化培养模式的特色,从学校学院学科背景、中外学生沟通交流、中国文化主题实践以及联合班级培养模式等四个方面,阐述同班国际化培养模式的积极影响以及对未来趋同化留学生管理模式发展的深远意义.

陨石坑是天体表面最为显著的地形特征,传统陨石坑识别方法主要是对小型陨石坑正负样本的二分类问题研究,且效率和精度均不高.以星体宏观视角下的大型陨石坑作为研究对象,结合图像处理和神经网络等方面的知识,创建了来自不同数据源的陨石坑样本数据库,研究了数据源对网络模型泛化能力的影响,提出了一种效率更高的陨石坑多分类识别方法.在非极大值抑制(NMS)算法基础上,提出了一种精度更高的陨石坑检测算法.经过参数优化和实验验证,构建的基于深度学习的多尺度多分类陨石坑自动识别网络框架取得了较高的准确率,在同源验证集上识别率可达0.985,在异源验证集上识别率可达0.863,并且有效改善了目标检测时检测框冗余及误检测的问题.

受疫情影响,当前大部分的同学们正在进行远程线上听课学习,不同人格类型的同学可能会因为自己的性格因素加剧听课学习中遇到的某类难题、或因为教师线上授课风格不适应使学习效果打折扣. 难道"线上听课与课堂听课效果无二"只是一种愿望?答案当然是否定的.我们建议大家"因人而异",需根据自己的性格特点来谋划、实施.这里我们主要运用MBTI人格类型理论工具帮助同学们制订、调整适合自己的学习计划及方法.

The ultimatum game (UG) is a useful game model for investigating the evolution of fairness. In this paper, considering the similarity between individuals, we introduce a similarity parameter into the spatial UG and focus on the evolution of the average offer and acceptance threshold. Under this mechanism, individuals can be either more generous or stingier to those who they are similar to. The simulation result shows that the fairness of the system decreases when the strategy is affected by the similarity between players. The greater the influence of similarity, the more fairness is decreased. Equal treatment, hence, is the best way to obtain fairness. Our results may provide some critical insights into the effect of similarity and favoritism on fairness among people.

高校思政教育承担着培养合格建设者和可靠接班人的重大使命.正值互联网飞速发展的时代,做好重大突发事件下大学生的网络思政教育尤为重要.结合新冠肺炎疫情背景,来探索重大突发事件下的高校网络思政教育模式及路径,以期可以为有效提升思政工作质量,做好新时代大学生思政教育提供有力借鉴.

国家重大庆典活动是重要的国家仪式,蕴含着爱国主义教育、集体主义教育、理想信念教育等丰富内容.借助参加国家重大庆典活动的有利机会,可以拓宽思想政治教育活动的形式,对学生的思政教育具有重大意义.作为高校辅导员,结合带领学生参加中华人民共和国成立70周年群众游行活动的经历进行了国家重大庆典活动中思想政治教育的探索.

文章分析在校理工科学生在科技创新方面的意识、认知和需求特征,以科研育人质量提升体系政策为指引,充分利用北京航空航天大学科技创新优势,通过发挥学校科研优势反哺教学,构建思政与教学相融的资源供给模式,搭建多维度科研素养平台,因材施教、分类培养,打造个性化发展支持体系,建立多层次条件保障机制,有效推动科学研究与高等教育相结合,形成以科研育人为主要特征的拔尖创新人才培养模式。

Understanding the emergence and maintenance of cooperation in social dilemma has received a lot of attention. In previous research, many scholars found that the reputation mechanism can promote cooperation, and the variation of reputation is consistent. However, in reality, according to both one's current action and past experiences, every individual's impression from others is modified to varying extent everyday. In other words, the length of duration of the same performance influences the diverse scale of their own reputation fluctuation. Therefore, a reputation-based strategy persistence mechanism, in which the increment of current reputation is determined by the persistence of last strategy, is proposed. Moreover, we introduce a parameter α to illustrate the impact of strategy persistence on reputation variation. The results of simulation show that the new mechanism paves the way for cooperation in evolutionary game, and the smaller α is, the better the mechanism performs.

当代青年是与新时代共同前进的一代,是国家的希望、民族的未来.在高校青年群体中,大学生党员在思想、学习和实践中发挥着先锋模范作用,为广大青年学生树立了良好的学习榜样.目前,高校对学生党员的培养尚存在重发展轻教育、重理论轻实践、考核机制不完善和联系群众不够紧密亟待加强等问题,为此高校应构建规范化的党员发展机制,搭建丰富的党员教育实践平台,创建标准化的党员行为规范,开拓多元化的党员培养方法来培养新时代大学生党员,充分发挥大学生党员的榜样表率作用.

Beidou satellite navigation system (BDS) is a global satellite navigation system built by China. It will provide global coverage of all-weather, all-time, high accuracy, high reliability positioning, navigation and timing services around 2020. With the development of BDS application, users’ requirements for accuracy, integrity, availability, continuity have been gradually improved. In BDS service performance specification, only signal-in-space continuity is defined, but no positioning service continuity is defined. In this paper, we first put forward the definition of the positioning service continuity standards, and evaluate the availability and continuity of BDS positioning service by using the records from several receiver sites in China. The results show that the availability of BDS can reach 99.47% and the continuity can reach 0.9991/h. The conclusion of this paper can provide theoretical reference for the civil aviation application of BDS.

Ground-based augmentation system (GBAS) of the Global Navigation Satellite System (GNSS) can use ranging error correction to achieve satellite integrity monitoring. For purposes of integrity monitoring, GBAS uses error overbounding method to calculate protection level (PL). The general error overbounding modeling method is to establish a zero-mean Gaussian model for pseudorange error. However, there are problems such as “thick tail”, “asymmetric” and “zero mean” in practical applications. In this paper, we use the properties of stable distribution to propose a four-parameter stable distribution modeling method. Based on the estimation of the characteristic parameter and the dispersion coefficient, the stable distribution of symmetry parameter and position parameter are estimated at the same time. Simulation analysis shows that the four-parameter stable distribution method improves the accuracy of the protection level calculation.

Heterogeneity has received increasing attention over the past decade, and it is widely considered to have a great effect on promoting cooperation. In our paper, we investigate the influence of heterogeneous investment on the cooperative behavior of the system, which is based on the number of players in different groups in the evolutionary public goods game (PGG). A parameter α is used to tune the heterogeneous investment mechanism: if α>0, cooperators invest more in the groups centered on high-degree nodes, but if α<0, the groups centered on small-degree nodes attract more investment from cooperators. Simulation results and analysis suggest that the cooperation level is enhanced in a large range. For a smaller enhancement factor r in the PGG model, the cooperation frequency decreases monotonously with the increase of α. For a larger r, the highest cooperation level can only be obtained by α=0, which is a non-monotonous phenomenon. By investigating the mean payoffs of nodes of different degrees for different α, it is found that the strategy utilized by hubs is more prominent in the system. Some explanations are provided for the strategy orientation of hubs and show that the investment propensity will change it. Our work may be useful for understanding the influence of individual investment in different groups on the level of cooperation.

Project performance measurement helps monitoring and controlling project processes, and thus improves project outcomes based on a set of indicators, typically lagging and leading indicators. Lagging indicators provide a comprehensive view on project health outcomes. Leading indicators are complementary; they can be used in a proactive way to enable companies to take corrective actions before performance decreases. But applying leading indicators on project management is not well developed because these indicators are difficult to be elaborated and interpreted. However, [Roedler et al., 2010] provided a great contribution to the state of art with a set of 18 leading indicators in the large domain of Systems Engineering. A deep analysis of literature also showed that some specific field of application, such as Civil Engineering, independently developed their own set of leading indicators. This paper thus analyzes and compares both sets of leading indicators in Systems Engineering and in Civil Engineering to point out similarities and differences, and to evaluate whether leading indicators defined in a field could be adapted to the other, with the goal to improve performance measurement by extending the current scope and structure of indicators. Mots cles-indicateurs avances, Ingenierie Systeme, industrie du bâtiment, mesure de la performance de projet.

通识教育鼓励超越具体学科的整体知识观，从而保证学生将来成为各种类型专家的同时，仍不失宽广的视野，更不失健全的人格和自由的品性。要实现这一目标，需要班主任工作与教学工作积极互动，形成相辅相成的互补关系。本文将从学生的个性化发展辅导、创新能力培养、班级学风建设以及落后学生帮扶等四个方面介绍一些经验和思考。