The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location re...The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.展开更多
Environmental comprehensive management system, called “the bionic community”, can be established in imitation of biome, which can transform the wastes generated in a certain field into the raw materials of other fie...Environmental comprehensive management system, called “the bionic community”, can be established in imitation of biome, which can transform the wastes generated in a certain field into the raw materials of other field. The establishment of the bionic community includes two aspects, i.e., the matching technique and the management system. The main matching technique is the preparation of composite materials made of various wastes. This new kind of material can be divided into four types: polymer matrix, silicate matrix, metal matrix and carbon matrix(or ceramic matrix). The environmental comprehensive management system is formed by organizing a trans-trades joint-management business entity with the products of composite material made of wastes at the core.展开更多
Robots are key to expanding the scope of space applications.The end-to-end training for robot vision-based detection and precision operations is challenging owing to constraints such as extreme environments and high c...Robots are key to expanding the scope of space applications.The end-to-end training for robot vision-based detection and precision operations is challenging owing to constraints such as extreme environments and high computational overhead.This study proposes a lightweight integrated framework for grasp detection and imitation learning,named GD-IL;it comprises a grasp detection algorithm based on manipulability and Gaussian mixture model(manipulability-GMM),and a grasp trajectory generation algorithm based on a two-stage robot imitation learning algorithm(TS-RIL).In the manipulability-GMM algorithm,we apply GMM clustering and ellipse regression to the object point cloud,propose two judgment criteria to generate multiple candidate grasp bounding boxes for the robot,and use manipulability as a metric for selecting the optimal grasp bounding box.The stages of the TS-RIL algorithm are grasp trajectory learning and robot pose optimization.In the first stage,the robot grasp trajectory is characterized using a second-order dynamic movement primitive model and Gaussian mixture regression(GMM).By adjusting the function form of the forcing term,the robot closely approximates the target-grasping trajectory.In the second stage,a robot pose optimization model is built based on the derived pose error formula and manipulability metric.This model allows the robot to adjust its configuration in real time while grasping,thereby effectively avoiding singularities.Finally,an algorithm verification platform is developed based on a Robot Operating System and a series of comparative experiments are conducted in real-world scenarios.The experimental results demonstrate that GD-IL significantly improves the effectiveness and robustness of grasp detection and trajectory imitation learning,outperforming existing state-of-the-art methods in execution efficiency,manipulability,and success rate.展开更多
Imitation models for computing the environmental water pollution level depending on the intensity of pollution sources created by the author over the years are presented. For this purpose, an additive model of a non-s...Imitation models for computing the environmental water pollution level depending on the intensity of pollution sources created by the author over the years are presented. For this purpose, an additive model of a non-stationary random process is considered. For the modeling of its components, models that consider only dilution and self-purification processes are proposed for waste water and three-dimensional turbulent diffusion equations for river waters, and multidimensional Gaussian Markov series are proposed for modeling the random component. The purpose, the capabilities and the peculiarities of such imitation models are discussed taking into account the peculiarities of the water objects. The modular principle of creating imitation models is proposed to facilitate their development and use.展开更多
This article describes a pilot study aiming at generating social interactions between a humanoid robot and adolescents with autism spectrum disorder (ASD), through the practice of a gesture imitation game. The partici...This article describes a pilot study aiming at generating social interactions between a humanoid robot and adolescents with autism spectrum disorder (ASD), through the practice of a gesture imitation game. The participants were a 17-year-old young lady with ASD and intellectual deficit, and a control participant: a preadolescent with ASD but no intellectual deficit (Asperger syndrome). The game is comprised of four phases: greetings, pairing, imitation, and closing. Field educators were involved, playing specific roles: visual or physical inciter. The use of a robot allows for catching the participants’ attention, playing the imitation game for a longer period of time than with a human partner, and preventing the game partner’s negative facial expressions resulting from tiredness, impatience, or boredom. The participants’ behavior was observed in terms of initial approach towards the robot, positioning relative to the robot in terms of distance and orientation, reactions to the robot’s voice or moves, signs of happiness, and imitation attempts. Results suggest a more and more natural approach towards the robot during the sessions, as well as a higher level of social interaction, based on the variations of the parameters listed above. We use these preliminary results to draw the next steps of our research work as well as identify further perspectives, with this aim in mind: improving social interactions with adolescents with ASD and intellectual deficit, allowing for better integration of these people into our societies.展开更多
Aim The particle texture from diesel engine was imitated by use of computer. Methods The theory of fractal geometry and the diffusion limited aggregation model were used to simulate the micron texture. Results The...Aim The particle texture from diesel engine was imitated by use of computer. Methods The theory of fractal geometry and the diffusion limited aggregation model were used to simulate the micron texture. Results The fractal dimensions of granule distribution and corpuscle superficial area are quite conformed with those of measurement. Conclusion The texture parameters of engine particle cluster can be obtained precisely by use of fractal theory.展开更多
UG and imitation are two parallel hypotheses trying to answer how childrens language acquisition is realized. Imitation fails to explain how children acquire language; however, it helps a lot in childrens language acq...UG and imitation are two parallel hypotheses trying to answer how childrens language acquisition is realized. Imitation fails to explain how children acquire language; however, it helps a lot in childrens language acquisition.展开更多
It is of vital importance for modern college English teaching to properly construct an interactive multimedia-internet-based teaching system, the structure of which is clearly elaborated in this paper. An IMITS usuall...It is of vital importance for modern college English teaching to properly construct an interactive multimedia-internet-based teaching system, the structure of which is clearly elaborated in this paper. An IMITS usually consists of hardware, software, teaching and management. At the end of this paper, a conclusion is made that only when all the four parts of IMITS are construct ed such as is demonstrated, can the IMITS exert its full effects in college English teaching.展开更多
One of the assumptions of previous research in evolutionary game dynamics is that individuals use only one rule to update their strategy. In reality, an individual's strategy update rules may change with the envir...One of the assumptions of previous research in evolutionary game dynamics is that individuals use only one rule to update their strategy. In reality, an individual's strategy update rules may change with the environment, and it is possible for an individual to use two or more rules to update their strategy. We consider the case where an individual updates strategies based on the Moran and imitation processes, and establish mixed stochastic evolutionary game dynamics by combining both processes. Our aim is to study how individuals change strategies based on two update rules and how this affects evolutionary game dynamics. We obtain an analytic expression and properties of the fixation probability and fixation times(the unconditional fixation time or conditional average fixation time) associated with our proposed process. We find unexpected results. The fixation probability within the proposed model is independent of the probabilities that the individual adopts the imitation rule update strategy. This implies that the fixation probability within the proposed model is equal to that from the Moran and imitation processes. The one-third rule holds in the proposed mixed model. However, under weak selection, the fixation times are different from those of the Moran and imitation processes because it is connected with the probability that individuals adopt an imitation update rule. Numerical examples are presented to illustrate the relationships between fixation times and the probability that an individual adopts the imitation update rule, as well as between fixation times and selection intensity. From the simulated analysis, we find that the fixation time for a mixed process is greater than that of the Moran process, but is less than that of the imitation process. Moreover, the fixation times for a cooperator in the proposed process increase as the probability of adopting an imitation update increases; however, the relationship becomes more complex than a linear relationship.展开更多
Here,the challenges of sample efficiency and navigation performance in deep rein-forcement learning for visual navigation are focused and a deep imitation reinforcement learning approach is proposed.Our contributions ...Here,the challenges of sample efficiency and navigation performance in deep rein-forcement learning for visual navigation are focused and a deep imitation reinforcement learning approach is proposed.Our contributions are mainly three folds:first,a frame-work combining imitation learning with deep reinforcement learning is presented,which enables a robot to learn a stable navigation policy faster in the target-driven navigation task.Second,the surrounding images is taken as the observation instead of sequential images,which can improve the navigation performance for more information.Moreover,a simple yet efficient template matching method is adopted to determine the stop action,making the system more practical.Simulation experiments in the AI-THOR environment show that the proposed approach outperforms previous end-to-end deep reinforcement learning approaches,which demonstrate the effectiveness and efficiency of our approach.展开更多
Mobile Edge Computing(MEC)is promising to alleviate the computation and storage burdens for terminals in wireless networks.The huge energy consumption of MEC servers challenges the establishment of smart cities and th...Mobile Edge Computing(MEC)is promising to alleviate the computation and storage burdens for terminals in wireless networks.The huge energy consumption of MEC servers challenges the establishment of smart cities and their service time powered by rechargeable batteries.In addition,Orthogonal Multiple Access(OMA)technique cannot utilize limited spectrum resources fully and efficiently.Therefore,Non-Orthogonal Multiple Access(NOMA)-based energy-efficient task scheduling among MEC servers for delay-constraint mobile applications is important,especially in highly-dynamic vehicular edge computing networks.The various movement patterns of vehicles lead to unbalanced offloading requirements and different load pressure for MEC servers.Self-Imitation Learning(SIL)-based Deep Reinforcement Learning(DRL)has emerged as a promising machine learning technique to break through obstacles in various research fields,especially in time-varying networks.In this paper,we first introduce related MEC technologies in vehicular networks.Then,we propose an energy-efficient approach for task scheduling in vehicular edge computing networks based on DRL,with the purpose of both guaranteeing the task latency requirement for multiple users and minimizing total energy consumption of MEC servers.Numerical results demonstrate that the proposed algorithm outperforms other methods.展开更多
Providing autonomous systems with an effective quantity and quality of information from a desired task is challenging. In particular, autonomous vehicles, must have a reliable vision of their workspace to robustly acc...Providing autonomous systems with an effective quantity and quality of information from a desired task is challenging. In particular, autonomous vehicles, must have a reliable vision of their workspace to robustly accomplish driving functions. Speaking of machine vision, deep learning techniques, and specifically convolutional neural networks, have been proven to be the state of the art technology in the field. As these networks typically involve millions of parameters and elements, designing an optimal architecture for deep learning structures is a difficult task which is globally under investigation by researchers. This study experimentally evaluates the impact of three major architectural properties of convolutional networks, including the number of layers, filters, and filter size on their performance. In this study, several models with different properties are developed,equally trained, and then applied to an autonomous car in a realistic simulation environment. A new ensemble approach is also proposed to calculate and update weights for the models regarding their mean squared error values. Based on design properties,performance results are reported and compared for further investigations. Surprisingly, the number of filters itself does not largely affect the performance efficiency. As a result, proper allocation of filters with different kernel sizes through the layers introduces a considerable improvement in the performance.Achievements of this study will provide the researchers with a clear clue and direction in designing optimal network architectures for deep learning purposes.展开更多
This paper reports on a study on the effects of reading-writing integrated tasks on vocabulary learning and explored the differential roles of creative construction and non-creative construction in promoting lexical l...This paper reports on a study on the effects of reading-writing integrated tasks on vocabulary learning and explored the differential roles of creative construction and non-creative construction in promoting lexical learning. Participants were 90 first-year English majors, randomly assigned to two experimental groups(continuation and retelling) and one control group, with 30 students in each group. Results showed that the continuation group generated a substantial amount of creative construction and produced significantly more instances of creative imitation than the retelling group. The continuation group outperformed the retelling group for both receptive and productive vocabulary knowledge gain and retention, but differences were only significant in terms of productive vocabulary retention. Finally, productive vocabulary knowledge retention among the continuation group was significantly and positively correlated with creative imitation(meaning creation coupled with language imitation), but not with linguistic alignment per se. As productive vocabulary knowledge constitutes the learner ’s ability to use lexical knowledge to express ideas in dynamic contexts, the findings afforded evidence that creative imitation could be the answer to the fundamental issue of L2 learning(i.e., mapping static language onto dynamic idea expression). The pedagogical implications as well as future research directions are also discussed.展开更多
The theory of“imitation”in painting occupies a leading position in western art,which originated from the theory of“imitation”in ancient Greece,and has become one of the art theories affecting the world through the...The theory of“imitation”in painting occupies a leading position in western art,which originated from the theory of“imitation”in ancient Greece,and has become one of the art theories affecting the world through the continuous development of later generations.Through the exploration of the source of“imitation”in China and the West,there are some comments on the meaning of“imitation”in Chinese classical painting theory,such as“transfer model writing”and“image form”,which is obvious differences from the west.Traditional Chinese painting is a combination of careful observation of natural things and subjective emotions to express their own aesthetic feelings,and ultimately form a vivid artistic conception.Modern imitation is borrowed from Western imitation.In fact,imitation in traditional painting has its own meaning,which contains Chinese aesthetic thought.“Imitation”aesthetics is unique in traditional Chinese painting and is the most important form of painting art.展开更多
This paper studies imitation learning in nonlinear multi-player game systems with heterogeneous control input dynamics.We propose a model-free data-driven inverse reinforcement learning(RL)algorithm for a leaner to fi...This paper studies imitation learning in nonlinear multi-player game systems with heterogeneous control input dynamics.We propose a model-free data-driven inverse reinforcement learning(RL)algorithm for a leaner to find the cost functions of a N-player Nash expert system given the expert's states and control inputs.This allows us to address the imitation learning problem without prior knowledge of the expert's system dynamics.To achieve this,we provide a basic model-based algorithm that is built upon RL and inverse optimal control.This serves as the foundation for our final model-free inverse RL algorithm which is implemented via neural network-based value function approximators.Theoretical analysis and simulation examples verify the methods.展开更多
The error sources related to the laser rangefinder,GPS and INS are analyzed in details.Several coordinates systems used in airborne laser scanning are set up,and then the basic formula of system is given.This paper em...The error sources related to the laser rangefinder,GPS and INS are analyzed in details.Several coordinates systems used in airborne laser scanning are set up,and then the basic formula of system is given.This paper emphasizes on discussing the kinematic offset correction between GPS antenna phase center and laser fired point.And kinematic time delay influence on laser footprint position,the ranging errors,positioning errors,attitude errors and integration errors of the system are also explored.Finally,the result shows that the kinematic time delay can be neglected as compared with other error sources.The accuracy of the coordinates is not only influenced by the amplitude of the error,but also controlled by the operation parameters such as flight height,scanning angle amplitude and attitude magnitude of the platform.展开更多
Primary impairments of developmental coordination disorder (DCD) include impairments in motor skill, motor learning, and imitation. Such difficulties present challenges for individuals with DCD and may persist into ad...Primary impairments of developmental coordination disorder (DCD) include impairments in motor skill, motor learning, and imitation. Such difficulties present challenges for individuals with DCD and may persist into adulthood, negatively impacting daily life in school, work, and social domains. A better understanding of the neural correlates of motor and imitation impairments in DCD holds the potential for informing development of treatment approaches to address these impairments. Although the disorder is assumed to be of neurological origin, little is known of the brain-based etiology of DCD. In recent years the discovery of a fronto-parietal circuit—known as the mirror neuron system—has enabled researchers to better understand imitation, general motor functions, and aspects of social cognition. Given its involvement in imitation and other motor functions, we propose that dysfunction in the mirror neuron system may underlie the characteristic impairments of DCD. We review literature pertaining to the mirror neuron system and develop a theory of disordered mirror neuron functioning in DCD. Finally, we review the limited neuroimaging literature available on neural correlates of DCD and show that the findings from those investigations are congruent with a mirror neuron system theory of DCD. Future research in this population should be designed to investigate specifically mirror neuron regions in individuals with DCD during skilled motor tasks and imitation in particular.展开更多
In real life, in different industries, we often deal with systems designed for multiple use for performing single-type tasks. Processes taking place at this time are called service of requirements, and the systems the...In real life, in different industries, we often deal with systems designed for multiple use for performing single-type tasks. Processes taking place at this time are called service of requirements, and the systems themselves—Queueing Systems. This article is dedicated to computer software modelling of processes taking place in the systems in question, Markov processes in particular. In this article, by means of Matlab environment, software realization of one of the typical models of queueing service theory-multichannel QS with unreliable recoverable servers and limited number of requirements in the system, is fulfilled. The results of this research are important because it gives the possibility to use received results to determine optimality degree of some real queueing systems that possess Markov property.展开更多
Gesture recognition is topical in computer science and aims at interpreting human gestures via mathematical algorithms. Among the numerous applications are physical rehabilitation and imitation games. In this work, we...Gesture recognition is topical in computer science and aims at interpreting human gestures via mathematical algorithms. Among the numerous applications are physical rehabilitation and imitation games. In this work, we suggest performing human gesture recognition within the context of a serious imitation game, which would aim at improving social interactions with teenagers with autism spectrum disorders. We use an artificial intelligence algorithm to detect the skeleton of the participant, then model the human pose space and describe an imitation learning method using a Gaussian Mixture Model in the Riemannian manifold.展开更多
When discussing the roots of Arab theatre, we find ourselves confronting two main streams of thought. The first one, represented by prominent Arab writers like Najib Mahfuz, Abbas A1-Aqqad, M. Badawi, and other critic...When discussing the roots of Arab theatre, we find ourselves confronting two main streams of thought. The first one, represented by prominent Arab writers like Najib Mahfuz, Abbas A1-Aqqad, M. Badawi, and other critics, rejects the theory that an Arab theatre existed before the mid-19th century. The second stream, represented by prominent scholars like Ali A1-Rai, Ibrahim Hamada and S. Moreh, see modern Arab theatre as part of a continuum, emphasizing of some elements of dramatic manifestations in Arab literary heritage. This paper intends to examine these two streams, their evidences and arguments. Such examination will shed some light on the origin of Arab theatre as a literary genre, and how it was influenced, if any, by Western theatrical heritage. Thus, answering the main question of this paper, whether Arab theatre is original or simply a Western imitation.展开更多
基金supported by the Natural Science Foundation of Fujian Province of China(2025J01380)National Natural Science Foundation of China(No.62471139)+3 种基金the Major Health Research Project of Fujian Province(2021ZD01001)Fujian Provincial Units Special Funds for Education and Research(2022639)Fujian University of Technology Research Start-up Fund(GY-S24002)Fujian Research and Training Grants for Young and Middle-aged Leaders in Healthcare(GY-H-24179).
文摘The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.
基金National Natural Science Foundation ofChina( No.5 9965 0 0 2)
文摘Environmental comprehensive management system, called “the bionic community”, can be established in imitation of biome, which can transform the wastes generated in a certain field into the raw materials of other field. The establishment of the bionic community includes two aspects, i.e., the matching technique and the management system. The main matching technique is the preparation of composite materials made of various wastes. This new kind of material can be divided into four types: polymer matrix, silicate matrix, metal matrix and carbon matrix(or ceramic matrix). The environmental comprehensive management system is formed by organizing a trans-trades joint-management business entity with the products of composite material made of wastes at the core.
基金Supported by National Natural Science Foundation of China(Grant No.52475280)Shaanxi Provincial Natural Science Basic Research Program(Grant No.2025SYSSYSZD-105).
文摘Robots are key to expanding the scope of space applications.The end-to-end training for robot vision-based detection and precision operations is challenging owing to constraints such as extreme environments and high computational overhead.This study proposes a lightweight integrated framework for grasp detection and imitation learning,named GD-IL;it comprises a grasp detection algorithm based on manipulability and Gaussian mixture model(manipulability-GMM),and a grasp trajectory generation algorithm based on a two-stage robot imitation learning algorithm(TS-RIL).In the manipulability-GMM algorithm,we apply GMM clustering and ellipse regression to the object point cloud,propose two judgment criteria to generate multiple candidate grasp bounding boxes for the robot,and use manipulability as a metric for selecting the optimal grasp bounding box.The stages of the TS-RIL algorithm are grasp trajectory learning and robot pose optimization.In the first stage,the robot grasp trajectory is characterized using a second-order dynamic movement primitive model and Gaussian mixture regression(GMM).By adjusting the function form of the forcing term,the robot closely approximates the target-grasping trajectory.In the second stage,a robot pose optimization model is built based on the derived pose error formula and manipulability metric.This model allows the robot to adjust its configuration in real time while grasping,thereby effectively avoiding singularities.Finally,an algorithm verification platform is developed based on a Robot Operating System and a series of comparative experiments are conducted in real-world scenarios.The experimental results demonstrate that GD-IL significantly improves the effectiveness and robustness of grasp detection and trajectory imitation learning,outperforming existing state-of-the-art methods in execution efficiency,manipulability,and success rate.
文摘Imitation models for computing the environmental water pollution level depending on the intensity of pollution sources created by the author over the years are presented. For this purpose, an additive model of a non-stationary random process is considered. For the modeling of its components, models that consider only dilution and self-purification processes are proposed for waste water and three-dimensional turbulent diffusion equations for river waters, and multidimensional Gaussian Markov series are proposed for modeling the random component. The purpose, the capabilities and the peculiarities of such imitation models are discussed taking into account the peculiarities of the water objects. The modular principle of creating imitation models is proposed to facilitate their development and use.
文摘This article describes a pilot study aiming at generating social interactions between a humanoid robot and adolescents with autism spectrum disorder (ASD), through the practice of a gesture imitation game. The participants were a 17-year-old young lady with ASD and intellectual deficit, and a control participant: a preadolescent with ASD but no intellectual deficit (Asperger syndrome). The game is comprised of four phases: greetings, pairing, imitation, and closing. Field educators were involved, playing specific roles: visual or physical inciter. The use of a robot allows for catching the participants’ attention, playing the imitation game for a longer period of time than with a human partner, and preventing the game partner’s negative facial expressions resulting from tiredness, impatience, or boredom. The participants’ behavior was observed in terms of initial approach towards the robot, positioning relative to the robot in terms of distance and orientation, reactions to the robot’s voice or moves, signs of happiness, and imitation attempts. Results suggest a more and more natural approach towards the robot during the sessions, as well as a higher level of social interaction, based on the variations of the parameters listed above. We use these preliminary results to draw the next steps of our research work as well as identify further perspectives, with this aim in mind: improving social interactions with adolescents with ASD and intellectual deficit, allowing for better integration of these people into our societies.
文摘Aim The particle texture from diesel engine was imitated by use of computer. Methods The theory of fractal geometry and the diffusion limited aggregation model were used to simulate the micron texture. Results The fractal dimensions of granule distribution and corpuscle superficial area are quite conformed with those of measurement. Conclusion The texture parameters of engine particle cluster can be obtained precisely by use of fractal theory.
文摘UG and imitation are two parallel hypotheses trying to answer how childrens language acquisition is realized. Imitation fails to explain how children acquire language; however, it helps a lot in childrens language acquisition.
文摘It is of vital importance for modern college English teaching to properly construct an interactive multimedia-internet-based teaching system, the structure of which is clearly elaborated in this paper. An IMITS usually consists of hardware, software, teaching and management. At the end of this paper, a conclusion is made that only when all the four parts of IMITS are construct ed such as is demonstrated, can the IMITS exert its full effects in college English teaching.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.71871171,71871173,and 71832010)
文摘One of the assumptions of previous research in evolutionary game dynamics is that individuals use only one rule to update their strategy. In reality, an individual's strategy update rules may change with the environment, and it is possible for an individual to use two or more rules to update their strategy. We consider the case where an individual updates strategies based on the Moran and imitation processes, and establish mixed stochastic evolutionary game dynamics by combining both processes. Our aim is to study how individuals change strategies based on two update rules and how this affects evolutionary game dynamics. We obtain an analytic expression and properties of the fixation probability and fixation times(the unconditional fixation time or conditional average fixation time) associated with our proposed process. We find unexpected results. The fixation probability within the proposed model is independent of the probabilities that the individual adopts the imitation rule update strategy. This implies that the fixation probability within the proposed model is equal to that from the Moran and imitation processes. The one-third rule holds in the proposed mixed model. However, under weak selection, the fixation times are different from those of the Moran and imitation processes because it is connected with the probability that individuals adopt an imitation update rule. Numerical examples are presented to illustrate the relationships between fixation times and the probability that an individual adopts the imitation update rule, as well as between fixation times and selection intensity. From the simulated analysis, we find that the fixation time for a mixed process is greater than that of the Moran process, but is less than that of the imitation process. Moreover, the fixation times for a cooperator in the proposed process increase as the probability of adopting an imitation update increases; however, the relationship becomes more complex than a linear relationship.
基金National Natural Science Foundation of China,Grant/Award Numbers:61703418,61825305。
文摘Here,the challenges of sample efficiency and navigation performance in deep rein-forcement learning for visual navigation are focused and a deep imitation reinforcement learning approach is proposed.Our contributions are mainly three folds:first,a frame-work combining imitation learning with deep reinforcement learning is presented,which enables a robot to learn a stable navigation policy faster in the target-driven navigation task.Second,the surrounding images is taken as the observation instead of sequential images,which can improve the navigation performance for more information.Moreover,a simple yet efficient template matching method is adopted to determine the stop action,making the system more practical.Simulation experiments in the AI-THOR environment show that the proposed approach outperforms previous end-to-end deep reinforcement learning approaches,which demonstrate the effectiveness and efficiency of our approach.
基金supported in part by the National Natural Science Foundation of China under Grant 61971084 and Grant 62001073in part by the National Natural Science Foundation of Chongqing under Grant cstc2019jcyj-msxmX0208in part by the open research fund of National Mobile Communications Research Laboratory,Southeast University,under Grant 2020D05.
文摘Mobile Edge Computing(MEC)is promising to alleviate the computation and storage burdens for terminals in wireless networks.The huge energy consumption of MEC servers challenges the establishment of smart cities and their service time powered by rechargeable batteries.In addition,Orthogonal Multiple Access(OMA)technique cannot utilize limited spectrum resources fully and efficiently.Therefore,Non-Orthogonal Multiple Access(NOMA)-based energy-efficient task scheduling among MEC servers for delay-constraint mobile applications is important,especially in highly-dynamic vehicular edge computing networks.The various movement patterns of vehicles lead to unbalanced offloading requirements and different load pressure for MEC servers.Self-Imitation Learning(SIL)-based Deep Reinforcement Learning(DRL)has emerged as a promising machine learning technique to break through obstacles in various research fields,especially in time-varying networks.In this paper,we first introduce related MEC technologies in vehicular networks.Then,we propose an energy-efficient approach for task scheduling in vehicular edge computing networks based on DRL,with the purpose of both guaranteeing the task latency requirement for multiple users and minimizing total energy consumption of MEC servers.Numerical results demonstrate that the proposed algorithm outperforms other methods.
文摘Providing autonomous systems with an effective quantity and quality of information from a desired task is challenging. In particular, autonomous vehicles, must have a reliable vision of their workspace to robustly accomplish driving functions. Speaking of machine vision, deep learning techniques, and specifically convolutional neural networks, have been proven to be the state of the art technology in the field. As these networks typically involve millions of parameters and elements, designing an optimal architecture for deep learning structures is a difficult task which is globally under investigation by researchers. This study experimentally evaluates the impact of three major architectural properties of convolutional networks, including the number of layers, filters, and filter size on their performance. In this study, several models with different properties are developed,equally trained, and then applied to an autonomous car in a realistic simulation environment. A new ensemble approach is also proposed to calculate and update weights for the models regarding their mean squared error values. Based on design properties,performance results are reported and compared for further investigations. Surprisingly, the number of filters itself does not largely affect the performance efficiency. As a result, proper allocation of filters with different kernel sizes through the layers introduces a considerable improvement in the performance.Achievements of this study will provide the researchers with a clear clue and direction in designing optimal network architectures for deep learning purposes.
文摘This paper reports on a study on the effects of reading-writing integrated tasks on vocabulary learning and explored the differential roles of creative construction and non-creative construction in promoting lexical learning. Participants were 90 first-year English majors, randomly assigned to two experimental groups(continuation and retelling) and one control group, with 30 students in each group. Results showed that the continuation group generated a substantial amount of creative construction and produced significantly more instances of creative imitation than the retelling group. The continuation group outperformed the retelling group for both receptive and productive vocabulary knowledge gain and retention, but differences were only significant in terms of productive vocabulary retention. Finally, productive vocabulary knowledge retention among the continuation group was significantly and positively correlated with creative imitation(meaning creation coupled with language imitation), but not with linguistic alignment per se. As productive vocabulary knowledge constitutes the learner ’s ability to use lexical knowledge to express ideas in dynamic contexts, the findings afforded evidence that creative imitation could be the answer to the fundamental issue of L2 learning(i.e., mapping static language onto dynamic idea expression). The pedagogical implications as well as future research directions are also discussed.
文摘The theory of“imitation”in painting occupies a leading position in western art,which originated from the theory of“imitation”in ancient Greece,and has become one of the art theories affecting the world through the continuous development of later generations.Through the exploration of the source of“imitation”in China and the West,there are some comments on the meaning of“imitation”in Chinese classical painting theory,such as“transfer model writing”and“image form”,which is obvious differences from the west.Traditional Chinese painting is a combination of careful observation of natural things and subjective emotions to express their own aesthetic feelings,and ultimately form a vivid artistic conception.Modern imitation is borrowed from Western imitation.In fact,imitation in traditional painting has its own meaning,which contains Chinese aesthetic thought.“Imitation”aesthetics is unique in traditional Chinese painting and is the most important form of painting art.
文摘This paper studies imitation learning in nonlinear multi-player game systems with heterogeneous control input dynamics.We propose a model-free data-driven inverse reinforcement learning(RL)algorithm for a leaner to find the cost functions of a N-player Nash expert system given the expert's states and control inputs.This allows us to address the imitation learning problem without prior knowledge of the expert's system dynamics.To achieve this,we provide a basic model-based algorithm that is built upon RL and inverse optimal control.This serves as the foundation for our final model-free inverse RL algorithm which is implemented via neural network-based value function approximators.Theoretical analysis and simulation examples verify the methods.
基金Funded by the National Natural Science Foundation of China(No.40004001)
文摘The error sources related to the laser rangefinder,GPS and INS are analyzed in details.Several coordinates systems used in airborne laser scanning are set up,and then the basic formula of system is given.This paper emphasizes on discussing the kinematic offset correction between GPS antenna phase center and laser fired point.And kinematic time delay influence on laser footprint position,the ranging errors,positioning errors,attitude errors and integration errors of the system are also explored.Finally,the result shows that the kinematic time delay can be neglected as compared with other error sources.The accuracy of the coordinates is not only influenced by the amplitude of the error,but also controlled by the operation parameters such as flight height,scanning angle amplitude and attitude magnitude of the platform.
文摘Primary impairments of developmental coordination disorder (DCD) include impairments in motor skill, motor learning, and imitation. Such difficulties present challenges for individuals with DCD and may persist into adulthood, negatively impacting daily life in school, work, and social domains. A better understanding of the neural correlates of motor and imitation impairments in DCD holds the potential for informing development of treatment approaches to address these impairments. Although the disorder is assumed to be of neurological origin, little is known of the brain-based etiology of DCD. In recent years the discovery of a fronto-parietal circuit—known as the mirror neuron system—has enabled researchers to better understand imitation, general motor functions, and aspects of social cognition. Given its involvement in imitation and other motor functions, we propose that dysfunction in the mirror neuron system may underlie the characteristic impairments of DCD. We review literature pertaining to the mirror neuron system and develop a theory of disordered mirror neuron functioning in DCD. Finally, we review the limited neuroimaging literature available on neural correlates of DCD and show that the findings from those investigations are congruent with a mirror neuron system theory of DCD. Future research in this population should be designed to investigate specifically mirror neuron regions in individuals with DCD during skilled motor tasks and imitation in particular.
文摘In real life, in different industries, we often deal with systems designed for multiple use for performing single-type tasks. Processes taking place at this time are called service of requirements, and the systems themselves—Queueing Systems. This article is dedicated to computer software modelling of processes taking place in the systems in question, Markov processes in particular. In this article, by means of Matlab environment, software realization of one of the typical models of queueing service theory-multichannel QS with unreliable recoverable servers and limited number of requirements in the system, is fulfilled. The results of this research are important because it gives the possibility to use received results to determine optimality degree of some real queueing systems that possess Markov property.
文摘Gesture recognition is topical in computer science and aims at interpreting human gestures via mathematical algorithms. Among the numerous applications are physical rehabilitation and imitation games. In this work, we suggest performing human gesture recognition within the context of a serious imitation game, which would aim at improving social interactions with teenagers with autism spectrum disorders. We use an artificial intelligence algorithm to detect the skeleton of the participant, then model the human pose space and describe an imitation learning method using a Gaussian Mixture Model in the Riemannian manifold.
文摘When discussing the roots of Arab theatre, we find ourselves confronting two main streams of thought. The first one, represented by prominent Arab writers like Najib Mahfuz, Abbas A1-Aqqad, M. Badawi, and other critics, rejects the theory that an Arab theatre existed before the mid-19th century. The second stream, represented by prominent scholars like Ali A1-Rai, Ibrahim Hamada and S. Moreh, see modern Arab theatre as part of a continuum, emphasizing of some elements of dramatic manifestations in Arab literary heritage. This paper intends to examine these two streams, their evidences and arguments. Such examination will shed some light on the origin of Arab theatre as a literary genre, and how it was influenced, if any, by Western theatrical heritage. Thus, answering the main question of this paper, whether Arab theatre is original or simply a Western imitation.
