With the new development trend of multi-resource coordinated Earth observation and the new goal of Earth observation application of“short response time,high observation accuracy,and wide coverage”,space-aeronautics ...With the new development trend of multi-resource coordinated Earth observation and the new goal of Earth observation application of“short response time,high observation accuracy,and wide coverage”,space-aeronautics cooperative complex task planning problem has become an urgent problem to be solved.The focus of this problem is to use multiple resources to perform collaborative observations on complex tasks.By analyzing the process from task assignment to receiving task observation results,we propose a multi-layer interactive task planning framework which is composed of a preprocessing method for complex tasks,a task allocation layer,a task planning layer,and a task coordination layer.According to the characteristics of the framework,a hybrid genetic parallel tabu(HGPT)algorithm is proposed on this basis.The algorithm uses genetic annealing algorithm(GAA),parallel tabu(PT)algorithm,and heuristic rules to achieve task allocation,task planning,and task coordination.At the same time,coding improvements,operator design,annealing operations,and parallel calculations are added to the algorithm.In order to verify the effectiveness of the algorithm,simulation experiments under complex task scenarios of different scales are carried out.Experimental results show that this method can effectively solve the problems of observing complex tasks.Meanwhile,the optimization effect and convergence speed of the HGPT is better than that of the related algorithms.展开更多
In recent years,formation control of multi-agent has been a significant research subject in the field of cooperative control.However,previous works have mainly concentrated on formation control for simple point-mass m...In recent years,formation control of multi-agent has been a significant research subject in the field of cooperative control.However,previous works have mainly concentrated on formation control for simple point-mass model and linear model.In contrast,this paper presents a novel cooperative algorithm for multiple air vehicles formation control,which aims to devise a control strategy based on guidance route to achieve precisely coordinated formation control for a group of fixed-wing aircraft in a complex task environment.The proposed method introduces the leader-follower structure for effective organization of the multi-agent coordination.Moreover,the Partial Integrated Formation and Control(PIFC)is adopted to design the control law for Guidance-Route based Formation Control(GRFC).Additionally,the proposed approach designs two guidance-route generation strategies for two special situations to demonstrate the effectiveness of GRFC in complex task environments.Theoretical analysis reveals that the proposed control protocol for guidance command can ensure the overall stability and tracking accuracy of the system.Numerical simulations are performed to illustrate the theoretical results,and verify that the proposed approach can achieve coordinated formation control precisely in a complex task environment.展开更多
Nowadays,collaborative writing has gained much attention of many scholars.And task complexity is a crucial factor that influences second language(L2)writing.However,little research has explored how task complexity aff...Nowadays,collaborative writing has gained much attention of many scholars.And task complexity is a crucial factor that influences second language(L2)writing.However,little research has explored how task complexity affects the quality of L2 collaborative writing.This study investigates the impact of task complexity on syntactic complexity,lexical complexity,and accuracy of the second language collaborative writing.English learners(N=50)in a Chinese university were required to complete two writing tasks collaboratively:a simple task and a complex task.Through analyzing their compositions,we found that task complexity has a significant impact on syntactic complexity and high complexity writing tasks help increase the syntactic complexity of second language collaborative writing.However,task complexity has little impact on lexical complexity and accuracy.The accuracy of writing tasks is largely influenced by the task requirements.The research results may enhance the understanding of collaborative writing and task complexity and provide valuable guidance for the second language teaching.展开更多
It is an urgent problem for robots to operate complex tasks with some unknown motion mechanisms caused by the strong coupling of force and motion. However, humans can perform complex tasks well due to their natural ev...It is an urgent problem for robots to operate complex tasks with some unknown motion mechanisms caused by the strong coupling of force and motion. However, humans can perform complex tasks well due to their natural evolution and postnatal training. A novel biomimetic control method based on a human motion mechanism with high movement adaptability is proposed in this paper. The core is to present a novel variable-parameter compliance controller based on human operation mechanisms with an action-planning method derived from optimization by human motion, and the main contribution is to change the parameters of compliance controller according to human operating intention synchronized with humanoid motion;this change could establish a humanoid map between the force and motion for a seven degree-of-freedom redundant manipulator to deal with the unknown motion mechanism in complex tasks, so the redundant manipulator can operate complex tasks with high performance. Sufficient experiments were performed, and the results validated the effectiveness of the proposed algorithm.展开更多
In the past few years, the notion of task complexity has been receiving substantial attention in the field of second language acquisition. This paper explores task complexity from the cognitive perspective by analyzin...In the past few years, the notion of task complexity has been receiving substantial attention in the field of second language acquisition. This paper explores task complexity from the cognitive perspective by analyzing two studies with Skehan＇s limited capacity hypothesis and Robinson＇s cognition hypothesis. The two studies, namely You-Jin Kim＇s （2012） and Mirdamadi and Jong （2015）, explore on how linguistic complexity affects language performance. Two hypotheses, Skehan＇s limited capacity hypothesis and Robinson＇s cognition hypothesis, explain the two studies from the cognitive perspective by predicting either that increasing task complexity reduces a pool of attentional capacity during task performance or that increasing complex tasks promotes greater accuracy and complexity of speech and writing. It is suggested that language teaching, syllabus designing in particular, should be based on the basis of task complexity.展开更多
Task-Based Language Teaching has witnessed growing interest in the impact of task complexity on Second language(L2)learners’linguistic performance.Within this field,the influence of resource-directing and resource-di...Task-Based Language Teaching has witnessed growing interest in the impact of task complexity on Second language(L2)learners’linguistic performance.Within this field,the influence of resource-directing and resource-dispersing features of cognitive task complexity has attracted much attention.Research on task complexity focuses on the influence of different task features on language learners’production in terms of linguistic complexity,accuracy,fluency and lexis.Within this field,a line of investigation that has attracted much attention is the influence of resource-directing and resource-dispersing features of cognitive task complexity.The review is helpful for better understanding of task complexity and allows to draw some preliminary pedagogical implications that may be useful for task-based syllabus design.展开更多
There are many algorithms for solving complex problems in supervised manner. However, unsupervised tasks are more common in real scenarios. Inspired by the idea of granular computing and the characteristics of human c...There are many algorithms for solving complex problems in supervised manner. However, unsupervised tasks are more common in real scenarios. Inspired by the idea of granular computing and the characteristics of human cognitive process, this paper proposes a complex tasks decomposition mechanism based on Density Peaks Clustering(DPC) to address complex tasks with an unsupervised process, which simulates the multi-granular observation and analysis of human being. Firstly, the DPC algorithm is modified to nullify its essential defects such as the difficulty of locating correct clustering centers and classifying them accurately. Then, the improved DPC algorithm is used to construct the initial decomposition solving space with multi-granularity theory. We also define subtask centers set and the granulation rules to guide the multi-granularity decomposing procedure. These rules are further used to decompose the solving space from coarse granules to the optimal fine granules with a convergent and automated process. Furthermore, comprehensive experiments are presented to verify the applicability and veracity of our proposed method in community-detection tasks with several benchmark complex social networks.The results show that our method outperforms other four state-of-the-art approaches.展开更多
Task-based Language Teaching(TBLT)research has provided ample evidence that cognitive complexity is an important aspect of task design that influences learner’s performance in terms of fluency,accuracy,and syntactic ...Task-based Language Teaching(TBLT)research has provided ample evidence that cognitive complexity is an important aspect of task design that influences learner’s performance in terms of fluency,accuracy,and syntactic complexity.Despite the substantial number of empirical investigations into task complexity in journal articles,storyline complexity,one of the features of it,is scarcely investigated.Previous research mainly focused on the impact of storyline complexity on learners’oral performance,but the impact on learners’written performance is less investigated.Thus,this study aims at investigating the effects of narrative complexity of storyline on senior high school students’written performance,as displayed by its complexity,fluency,and accuracy.The present study has important pedagogical implications.That is,task design and assessment should make a distinction between different types of narrative tasks.For example,the task with single or dual storyline.Results on task complexity may contribute to informing the pedagogical choices made by teachers when prioritizing work with a specific linguistic dimension.展开更多
针对雨雾等复杂天气下无人机图像质量下降导致目标检测效果不佳的问题,提出基于上下文引导和提示学习的目标检测算法CGP-YOLO(context-guided and prompt-based YOLOv8)。构建一个多任务联合学习的检测网络,通过双分支结构达到平衡图像...针对雨雾等复杂天气下无人机图像质量下降导致目标检测效果不佳的问题,提出基于上下文引导和提示学习的目标检测算法CGP-YOLO(context-guided and prompt-based YOLOv8)。构建一个多任务联合学习的检测网络,通过双分支结构达到平衡图像检测和恢复的任务。提出基于提示学习的跨层注意力加权图像去噪分支,指导网络利用退化提示重构清晰的图像;模型主干设计基于上下文的残差采样模块,集成卷积注意力机制,综合目标的局部和全局信息;采用可分离大核多尺度特征提取模块,处理网络多尺度特征;引入小目标的专用检测头,增强小目标的检测精度。实验结果表明,在参数量仅为基线模型60%的情况下,该模型的检测精度提高了2.4个百分点,平均精度(mAP)提高了2.04个百分点,模型检测效果优于其他经典模型,具备卓越的性能。展开更多
基金the National Natural Science Foundation of China(72001212).
文摘With the new development trend of multi-resource coordinated Earth observation and the new goal of Earth observation application of“short response time,high observation accuracy,and wide coverage”,space-aeronautics cooperative complex task planning problem has become an urgent problem to be solved.The focus of this problem is to use multiple resources to perform collaborative observations on complex tasks.By analyzing the process from task assignment to receiving task observation results,we propose a multi-layer interactive task planning framework which is composed of a preprocessing method for complex tasks,a task allocation layer,a task planning layer,and a task coordination layer.According to the characteristics of the framework,a hybrid genetic parallel tabu(HGPT)algorithm is proposed on this basis.The algorithm uses genetic annealing algorithm(GAA),parallel tabu(PT)algorithm,and heuristic rules to achieve task allocation,task planning,and task coordination.At the same time,coding improvements,operator design,annealing operations,and parallel calculations are added to the algorithm.In order to verify the effectiveness of the algorithm,simulation experiments under complex task scenarios of different scales are carried out.Experimental results show that this method can effectively solve the problems of observing complex tasks.Meanwhile,the optimization effect and convergence speed of the HGPT is better than that of the related algorithms.
基金co-supported by the National Natural Science Foundation of China(Nos.61773031 and 61573042)Graduate Innovation Practice Fund of Beihang University,China(No.YCSJ-01-201915)funded by the State Key Laboratory of Software Development Environment,China.
文摘In recent years,formation control of multi-agent has been a significant research subject in the field of cooperative control.However,previous works have mainly concentrated on formation control for simple point-mass model and linear model.In contrast,this paper presents a novel cooperative algorithm for multiple air vehicles formation control,which aims to devise a control strategy based on guidance route to achieve precisely coordinated formation control for a group of fixed-wing aircraft in a complex task environment.The proposed method introduces the leader-follower structure for effective organization of the multi-agent coordination.Moreover,the Partial Integrated Formation and Control(PIFC)is adopted to design the control law for Guidance-Route based Formation Control(GRFC).Additionally,the proposed approach designs two guidance-route generation strategies for two special situations to demonstrate the effectiveness of GRFC in complex task environments.Theoretical analysis reveals that the proposed control protocol for guidance command can ensure the overall stability and tracking accuracy of the system.Numerical simulations are performed to illustrate the theoretical results,and verify that the proposed approach can achieve coordinated formation control precisely in a complex task environment.
文摘Nowadays,collaborative writing has gained much attention of many scholars.And task complexity is a crucial factor that influences second language(L2)writing.However,little research has explored how task complexity affects the quality of L2 collaborative writing.This study investigates the impact of task complexity on syntactic complexity,lexical complexity,and accuracy of the second language collaborative writing.English learners(N=50)in a Chinese university were required to complete two writing tasks collaboratively:a simple task and a complex task.Through analyzing their compositions,we found that task complexity has a significant impact on syntactic complexity and high complexity writing tasks help increase the syntactic complexity of second language collaborative writing.However,task complexity has little impact on lexical complexity and accuracy.The accuracy of writing tasks is largely influenced by the task requirements.The research results may enhance the understanding of collaborative writing and task complexity and provide valuable guidance for the second language teaching.
基金supported by the National Key Research and Development Program of China(Grant No.2018YFB1305300)the Key Program of the National Natural Science Foundation of China(Grant Nos.61733001,U1713215)the National Natural Science Foundation of China(Grant Nos.61573063,61873039)
文摘It is an urgent problem for robots to operate complex tasks with some unknown motion mechanisms caused by the strong coupling of force and motion. However, humans can perform complex tasks well due to their natural evolution and postnatal training. A novel biomimetic control method based on a human motion mechanism with high movement adaptability is proposed in this paper. The core is to present a novel variable-parameter compliance controller based on human operation mechanisms with an action-planning method derived from optimization by human motion, and the main contribution is to change the parameters of compliance controller according to human operating intention synchronized with humanoid motion;this change could establish a humanoid map between the force and motion for a seven degree-of-freedom redundant manipulator to deal with the unknown motion mechanism in complex tasks, so the redundant manipulator can operate complex tasks with high performance. Sufficient experiments were performed, and the results validated the effectiveness of the proposed algorithm.
文摘In the past few years, the notion of task complexity has been receiving substantial attention in the field of second language acquisition. This paper explores task complexity from the cognitive perspective by analyzing two studies with Skehan＇s limited capacity hypothesis and Robinson＇s cognition hypothesis. The two studies, namely You-Jin Kim＇s （2012） and Mirdamadi and Jong （2015）, explore on how linguistic complexity affects language performance. Two hypotheses, Skehan＇s limited capacity hypothesis and Robinson＇s cognition hypothesis, explain the two studies from the cognitive perspective by predicting either that increasing task complexity reduces a pool of attentional capacity during task performance or that increasing complex tasks promotes greater accuracy and complexity of speech and writing. It is suggested that language teaching, syllabus designing in particular, should be based on the basis of task complexity.
文摘Task-Based Language Teaching has witnessed growing interest in the impact of task complexity on Second language(L2)learners’linguistic performance.Within this field,the influence of resource-directing and resource-dispersing features of cognitive task complexity has attracted much attention.Research on task complexity focuses on the influence of different task features on language learners’production in terms of linguistic complexity,accuracy,fluency and lexis.Within this field,a line of investigation that has attracted much attention is the influence of resource-directing and resource-dispersing features of cognitive task complexity.The review is helpful for better understanding of task complexity and allows to draw some preliminary pedagogical implications that may be useful for task-based syllabus design.
基金supported by the National Natural Science Foundation of China (No. 61572091)Chongqing Postgraduate Scientific Research and Innovation Project (No. CYB16106)
文摘There are many algorithms for solving complex problems in supervised manner. However, unsupervised tasks are more common in real scenarios. Inspired by the idea of granular computing and the characteristics of human cognitive process, this paper proposes a complex tasks decomposition mechanism based on Density Peaks Clustering(DPC) to address complex tasks with an unsupervised process, which simulates the multi-granular observation and analysis of human being. Firstly, the DPC algorithm is modified to nullify its essential defects such as the difficulty of locating correct clustering centers and classifying them accurately. Then, the improved DPC algorithm is used to construct the initial decomposition solving space with multi-granularity theory. We also define subtask centers set and the granulation rules to guide the multi-granularity decomposing procedure. These rules are further used to decompose the solving space from coarse granules to the optimal fine granules with a convergent and automated process. Furthermore, comprehensive experiments are presented to verify the applicability and veracity of our proposed method in community-detection tasks with several benchmark complex social networks.The results show that our method outperforms other four state-of-the-art approaches.
文摘Task-based Language Teaching(TBLT)research has provided ample evidence that cognitive complexity is an important aspect of task design that influences learner’s performance in terms of fluency,accuracy,and syntactic complexity.Despite the substantial number of empirical investigations into task complexity in journal articles,storyline complexity,one of the features of it,is scarcely investigated.Previous research mainly focused on the impact of storyline complexity on learners’oral performance,but the impact on learners’written performance is less investigated.Thus,this study aims at investigating the effects of narrative complexity of storyline on senior high school students’written performance,as displayed by its complexity,fluency,and accuracy.The present study has important pedagogical implications.That is,task design and assessment should make a distinction between different types of narrative tasks.For example,the task with single or dual storyline.Results on task complexity may contribute to informing the pedagogical choices made by teachers when prioritizing work with a specific linguistic dimension.
文摘针对雨雾等复杂天气下无人机图像质量下降导致目标检测效果不佳的问题,提出基于上下文引导和提示学习的目标检测算法CGP-YOLO(context-guided and prompt-based YOLOv8)。构建一个多任务联合学习的检测网络,通过双分支结构达到平衡图像检测和恢复的任务。提出基于提示学习的跨层注意力加权图像去噪分支,指导网络利用退化提示重构清晰的图像;模型主干设计基于上下文的残差采样模块,集成卷积注意力机制,综合目标的局部和全局信息;采用可分离大核多尺度特征提取模块,处理网络多尺度特征;引入小目标的专用检测头,增强小目标的检测精度。实验结果表明,在参数量仅为基线模型60%的情况下,该模型的检测精度提高了2.4个百分点,平均精度(mAP)提高了2.04个百分点,模型检测效果优于其他经典模型,具备卓越的性能。
