Dynamic airspace sectorization via improved genetic algorithm

This paper deals with dynamic airspace sectorization （DAS） problem by an improved genetic algorithm （iGA）. A graph model is first constructed that represents the airspace static structure. Then the DAS problem is formulated as a graph-partitioning problem to balance the sector workload under the premise of ensuring safety. In the iGA, multiple populations and hybrid coding are applied to determine the optimal sector number and airspace sectorization. The sector constraints are well satisfied by the improved genetic operators and protect zones. This method is validated by being applied to the airspace of North China in terms of three indexes, which are sector balancing index, coordination workload index and sector average flight time index. The improvement is obvious, as the sector balancing index is reduced by 16.5 %, the coordination workload index is reduced by 11.2 %, and the sector average flight time index is increased by 11.4 % during the peak-hour traffic.

Application of camera calibrating model to space manipulator with multi-objective genetic algorithm

The multi-objective genetic algorithm(MOGA) is proposed to calibrate the non-linear camera model of a space manipulator to improve its locational accuracy. This algorithm can optimize the camera model by dynamic balancing its model weight and multi-parametric distributions to the required accuracy. A novel measuring instrument of space manipulator is designed to orbital simulative motion and locational accuracy test. The camera system of space manipulator, calibrated by MOGA algorithm, is used to locational accuracy test in this measuring instrument. The experimental result shows that the absolute errors are [0.07, 1.75] mm for MOGA calibrating model, [2.88, 5.95] mm for MN method, and [1.19, 4.83] mm for LM method. Besides, the composite errors both of LM method and MN method are approximately seven times higher that of MOGA calibrating model. It is suggested that the MOGA calibrating model is superior both to LM method and MN method.

Workspace optimization of parallel robot by using multi-objective genetic algorithm

For the narrow workspace problem of the universal-prismatic-universal(UPU)parallel robotwith fixed orientation,a kind of multi-objective genetic algorithm is studied to optimize the robot’sworkspace.The concept of the effective workspace and its solution method are given.The effectiveworkspace height(EWH)and global condition number index(GCI)of Jacobi matrix are selected asthe optimized objective functions.Setting the robot in two different orientations,the geometric pa-rameters are optimized by the multi-objective genetic algorithm named non-dominated sorting geneticalgorithm II(NSGA-II),and a set of structural parameters is obtained.The optimization results areverified by four indicators with the robot’s moving platform at different orientations.The resultsshow that,after optimization,the fixed-orientation workspace volume,the effective workspace heightand the effective workspace volume increase by 32.4%,17.8%and 72.9%on average,respec-tively.GCI decreases by 6.8%on average.

Optimal reorientation of underactuated spacecraft using genetic algorithm with wavelet approximation

The optimal attitude control of an underactuated spacecraft is investigated in this paper. The flywheels of the spacecraft can somehow only provide control inputs in two independent directions. The dynamic equations are formulated for the spacecraft under a nonholonomic constraint resulting from the constant time-rate of the total angular momentum of the system. The reorientation of such underactuated spacecraft is transformed into an optimal control problem. A genetic algorithm is proposed to derive the control laws of the two flywheels angle velocity inputs. The control laws are approximated by the discrete orthogonal wavelets. The numerical simulations indicate that the genetic algorithm with the wavelet approximation is an effective approach to deal with the optimal reorientation of underactuated spacecraft.

Multi-objective Collaborative Optimization for Scheduling Aircraft Landing on Closely Spaced Parallel Runways Based on Genetic Algorithms

A scheduling model of closely spaced parallel runways for arrival aircraft was proposed,with multi-objections of the minimum flight delay cost,the maximum airport capacity,the minimum workload of air traffic controller and the maximum fairness of airlines′scheduling.The time interval between two runways and changes of aircraft landing order were taken as the constraints.Genetic algorithm was used to solve the model,and the model constrained unit delay cost of the aircraft with multiple flight tasks to reduce its delay influence range.Each objective function value or the fitness of particle unsatisfied the constrain condition would be punished.Finally,one domestic airport hub was introduced to verify the algorithm and the model.The results showed that the genetic algorithm presented strong convergence and timeliness for solving constraint multi-objective aircraft landing problem on closely spaced parallel runways,and the optimization results were better than that of actual scheduling.

FLIGHT DELAY STATE-SPACE MODEL BASED ON GENETIC EM ALGORITHM

Flight delay prediction remains an important research topic due to dynamic nature in flight operation and numerous delay factors.Dynamic data-driven application system in the control area can provide a solution to this problem.However,in order to apply the approach,a state-space flight delay model needs to be established to represent the relationship among system states,as well as the relationship between system states and input/output variables.Based on the analysis of delay event sequence in a single flight,a state-space mixture model is established and input variables in the model are studied.Case study is also carried out on historical flight delay data.In addition,the genetic expectation-maximization（EM）algorithm is used to obtain the global optimal estimates of parameters in the mixture model,and results fit the historical data.At last,the model is validated in Kolmogorov-Smirnov tests.Results show that the model has reasonable goodness of fitting the data,and the search performance of traditional EM algorithm can be improved by using the genetic algorithm.

CALIBRATION OF A 6-DOF SPACE ROBOT USING GENETIC ALGORITHM

The kinematic error model of a 6-DOF space robot is deduced, and the cost function of kinematic parameter identification is built. With the aid of the genetic algorithm （GA） that has the powerful global adaptive probabilistic search ability, 24 parameters of the robot are identified through simulation, which makes the pose （position and orientation） accuracy of the robot a great improvement. In the process of the calibration, stochastic measurement noises are considered. Lastly, generalization of the identified kinematic parameters in the whole workspace of the robot is discussed. The simulation results show that calibrating the robot with GA is very stable and not sensitive to measurement noise. Moreover, even if the robot＇s kinematic parameters are relative, GA still has strong search ability to find the optimum solution.

Space gripper configuration and its dimension synthesis based on genetic algorithm

The special fingers of the gripper on the space robot have been developed based on genetic algorithmfor the space application.Therefore,the symmetrical wedgelike finger composed of the 4-1ink mechanismand the relevant track were designed.To decrease the weight and optimize the kinematics and grip force,the compositive fitness function for dynamics and kinematics was created.The calculation efficiency couldbe improved by novel methods which overcame the problem of too many constraints in the solution space,such as introducing the specialist's experience and punishment function and simplifying the variables.The solutions show that the optimized finger could perform well and the methods were effectual.

An Orthogonal Wavelet Transform Fractionally Spaced Blind Equalization Algorithm Based on the Optimization of Genetic Algorithm

An orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm(WTFSE-GA) is proposed in viewof the lowconvergence rate,large steady-state mean square error and local convergence of traditional constant modulus blind equalization algorithm(CMA).The proposed algorithm can reduce the signal autocorrelation through the orthogonal wavelet transform of input signal of fractionally spaced blind equalizer,and decrease the possibility of CMA local convergence by using the global random search characteristics of genetic algorithm to optimize the equalizer weight vector.The proposed algorithm has the faster convergence rate and smaller mean square error compared with FSE and WT-FSE.The efficiency of the proposed algorithm is proved by computer simulation of underwater acoustic channels.

Strategic Study on the Development of Space Science in China and Proposals for Future Missions

Since 2011,the Chinese Academy of Sciences(CAS)has implemented the Strategic Priority Program on Space Science(SPP).A series of scientific satellites have been developed and launched,such as Dark Matter Particle Explorer(DAMPE),Quantum Experiments at Space Scale(QUESS),Advanced Space-based Solar Observatory(ASO-S),Einstein Probe(EP),and significant scientific outcomes have been achieved.In order to plan the future space science missions in China,CAS has organized the Chinese space science community to conduct medium and long-term development strategy studies,and summarized the major scientific frontiers of space science as“One Black,Two Dark,Three Origins and Five Characterizations”.Five main scientific themes have been identified for China’s future breakthroughs,including the Extreme Universe,Space-Time Ripples,the Panoramic View of the Sun and Earth,the Habitable Planets,and Biological&Physical Science in Space.Space science satellite missions to be implemented before 2030 are proposed accordingly.

Recent Progress in Space Science and Applications on Chinese Space Station in 2022–2024

Chinese Space Station(CSS)has been fully deployed by the end of 2022,and the facility has entered into the application and development phase.It has conducted scientific research projects in various fields,such as space life science and biotechnology,space materials science,microgravity fundamental physics,fluid physics,combustion science,space new technologies,and applications.In this review,we introduce the progress of CSS development and provide an overview of the research conducted in Chinese Space Station and the recent scientific findings in several typical research fields.Such compelling findings mainly concern the rapid solidification of ultra-high temperature alloy melts,dynamics of fluid transport in space,gravity scaling law of boiling heat transfer,vibration fluidization phenomenon of particulate matter,cold atom interferometer technology under high microgravity and related equivalence principle testing,the full life cycle of rice under microgravity and so forth.Furthermore,the planned scientific research and corresponding prospects of Chinese space station in the next few years are presented.

Data Collection and Research on the Vitality of Public Space in Traditional Villages: A Case Study of Cuandixia Village

The optimization and renewal of rural space is the foundation for building livable,business friendly and harmonious countryside.Three types of data on the spatial vitality of traditional villages are collected and analyzed.A street and alley axis map model is established using spatial syntax,and the degree of industry aggregation is quantified using POI data,and the results of syntactic calculation are validated with the help of popular review text preferences.Taking Cuandixia Village as an example,this paper found that its public space nodes have a pattern of one axis and scattered points;the street and alley space is well preserved but slightly lacking in transportation;the user group is single and the form is traditional.This paper could provide corresponding suggestions for stimulating the vitality of public spaces in traditional villages,in order to provide inspiration for the revitalization design of public spaces in traditional villages.

Application Research of Genetic Algorithm on the Whole-Spacecraft Vibration Isolation System

The objective of the whole-spacecraft vibration isolation (WSVI) system is to reduce the launch-induced dynamic loads and the quality control cost of the satellite and its components, and to increase the launch reliability by insertion of isolators between the satellite and the launch vehicle. A niche hybrid genetic algorithm (NHGA) is proposed to optimize stiffness and damping of the isolators. Through the comparison of the frequency response analysis results, it shows that the optimized WSVI system more effectively reduces spacecraft axial / lateral response due to the broadband structure-born launch environment. At the same time, the case of the whole-spacecraft vibration isolation optimization design demonstrates the efficiency and validity of the genetic algorithm.

The Dual of the Two-Variable Exponent Amalgam Spaces (Lq(),lp())(Ω)

Wiener amalgam spaces are a class of function spaces where the function’s local and global behavior can be easily distinguished. These spaces are ex-tensively used in Harmonic analysis that originated in the work of Wiener. In this paper: we first introduce a two-variable exponent amalgam space (Lq(),lp())(Ω). Secondly, we investigate some basic properties of these spaces, and finally, we study their dual.

A Study on the Mental Space of Subjunctive Mood

Cognitive linguistics offers a novel approach to studying and elucidating language phenomena,with the theory of mental spaces being particularly adept at interpreting many“non-canonical”linguistic occurrences and providing a fresh cognitive framework.The subjunctive mood,one of the three primary moods in English,is integral to English grammar.Yet,it remains a contentious topic within the field,with a lack of consensus among different linguistic schools regarding this significant grammatical category.The substantial role of human cognition in the construction and interpretation of the subjunctive mood’s meaning has been infrequently explored.This paper,from a cognitive perspective,employs the theory of mental spaces to discuss the English subjunctive mood,addressing the questions of its theoretical foundation,the reasons for its use,and the methods of its application.

3D MERGE与3D SPACE STIR序列在腰椎间盘突出症检查中的应用比较

目的:对比三维多回波恢复梯度回波(3D MERGE)、三维可变反转角快速自旋回波(3D SPACE STIR)序列在腰椎间盘突出症(LDH)检查中的应用效果。方法:选择2020年1月~2022年11月收治的135例LDH患者,回顾性分析患者临床和磁共振成像(MRI)资料,所有患者均接受常规MRI扫描及3D MERGE、3D SPACE STIR序列扫描,对比3D MERGE、3D SPACE STIR序列测量神经根直径的一致性,评价两种序列的图像质量参数[信噪比(SNR)、对比噪声比(CNR)]、图像清晰度评分。结果:3D MERGE和3D SPACE STIR序列测量的L3~S1神经根直径比较差异无统计学意义(P>0.05),且两组序列测量的L3、L4、L5和S1直径均显示出较高相关性(r=0.957,0.986,0.975,0.972,P<0.05);3D MERGE序列的SNR及CNR均高于3D SPACE STIR序列,神经根显示分级、图像清晰度评分优于3D SPACE STIR序列,差异有统计学意义(P<0.05)。结论:3D MERGE、3D SPACE STIR序列在LDH神经根直径测量中具有极高一致性,3D MERGE序列较3D SPACE STIR序列能够更清晰显示神经跟的解剖形态,图像质量更好。

A Genetic Algorithm for Identifying Overlapping Communities in Social Networks Using an Optimized Search Space

There are currently many approaches to identify the community structure of a network, but relatively few specific to detect overlapping community structures. Likewise, there are few networks with ground truth overlapping nodes. For this reason,we introduce a new network, Pilgrim, with known overlapping nodes, and a new genetic algorithm for detecting such nodes. Pilgrim is comprised of a variety of structures including two communities with dense overlap,which is common in real social structures. This study initially explores the potential of the community detection algorithm LabelRank for consistent overlap detection;however, the deterministic nature of this algorithm restricts it to very few candidate solutions. Therefore, we propose a genetic algorithm using a restricted edge-based clustering technique to detect overlapping communities by maximizing an efficient overlapping modularity function. The proposed restriction to the edge-based representation precludes the possibility of disjoint communities, thereby, dramatically reducing the search space and decreasing the number of generations required to produce an optimal solution. A tunable parameterr allows the strictness of the definition of overlap to be adjusted allowing for refinement in the number of identified overlapping nodes. Our method, tested on several real social networks, yields results comparable to the most effective overlapping community detection algorithms to date.

我国研究生学术素养研究热点分析(2013—2023年)——基于Cite Space的可视化分析研究

从中国知网数据库检索2013—2023年底国内发表的研究生学术素养研究相关文献,共筛选出259篇相关文献。将文献纳入Cite Space中,分别对作者、机构、关键词等进行可视化分析,并通过Excel绘制年发文量折线图,发现年发文量总体呈现下降趋势。发文作者为教育学领域的居多,发文机构大部分来自于各学校研究所等。高频关键词有研究生、学术道德、学术不端、学术规范、学术素养,并形成了“研究生”“学术道德”“学术不端”“治理”“学术规范”“学术素养”“博士生”“道德理论”“中心和导向”9个聚类。研究者近年来对学术素养相关研究整体呈现下降状态;研究机构以及研究人员结构单一,国家机构对学术素养相关研究较少;但关于“研究生”“学术道德”“学术不端”以及“学术理论”的研究仍有较高热度。

国内“大思政课”研究的现状、热点与展望--基于CiteSpace的核心期刊论文可视化分析

“大思政课”是近年的一个新议题。自习近平总书记作出关于“大思政课”的重要论述以来,“大思政课”建设在全国积极推进,成为新时代用党的创新理论铸魂育人的重要抓手。学界对这一领域的研究成果持续涌现。借助Cite Space文献计量软件对中国知网CNKI数据库中2021-2023年间350篇核心期刊论文的发文量、作者、机构、关键词进行可视化分析,近三年学界的研究热点聚焦“大思政课”的本体论、认识论、价值论、方法论以及一体化等方面。未来,学界还应以多学科交叉和多主体融合实现“大思政课”研究的系统化,以理论和实践结合提升“大思政课”研究的科学化,以破解技术遮蔽与AI赋能强化“大思政课”研究的数字化,以研究反哺教学,不断增强“大思政课”立德树人实效。

BIG HANKEL OPERATORS ON HARDY SPACES OF STRONGLY PSEUDOCONVEX DOMAINS

In this article,we investigate the(big) Hankel operator H_(f) on the Hardy spaces of bounded strongly pseudoconvex domains Ω in C^(n).We observe that H_(f ) is bounded on H~p(Ω)(1 <p <∞) if f belongs to BMO and we obtain some characterizations for Hf on H^(2)(Ω) of other pseudoconvex domains.In these arguments,Amar's L^(p)-estimations and Berndtsson's L^(2)-estimations for solutions of the ■_(b)-equation play a crucial role.In addition,we solve Gleason's problem for Hardy spaces H^(p)(Ω)(1 ≤p≤∞) of bounded strongly pseudoconvex domains.