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21.
Creating the brain and interacting with the brain: an integrated approach to understanding the brain
In the past two decades, brain science and robotics have made gigantic advances in their own fields, and their interactions have generated several interdisciplinary research fields. First, in the ‘understanding the brain by creating the brain’ approach, computational neuroscience models have been applied to many robotics problems. Second, such brain-motivated fields as cognitive robotics and developmental robotics have emerged as interdisciplinary areas among robotics, neuroscience and cognitive science with special emphasis on humanoid robots. Third, in brain–machine interface research, a brain and a robot are mutually connected within a closed loop. In this paper, we review the theoretical backgrounds of these three interdisciplinary fields and their recent progress. Then, we introduce recent efforts to reintegrate these research fields into a coherent perspective and propose a new direction that integrates brain science and robotics where the decoding of information from the brain, robot control based on the decoded information and multimodal feedback to the brain from the robot are carried out in real time and in a closed loop. 相似文献
22.
大坝运行监测易受自然环境和监测条件影响,存在时间和空间上的变异性,监测数据具有不确定性。以云理论的随机性和不确定性分析方法为基础,并与空间数据辐射思想相结合,建立了云滴概率密度分布估计模型,然后导出云概率密度分布函数,依据样本监测数据推求母体空间数据的分布特征,并设计了基于逆向云算法云变换的计算程序。分析陆浑水库1979~1999年测压管监测数据和位移变形数据的云概率密度分布特征和云数字特征,得出了20 a来大坝的数据分布特征和运行状态。监测数据分析结果表明,云概率密度分布估计不仅能有效合理地分析大坝的运行状态,而且能够依据云数字特征来判断监测状态和监测环境的异常变化。
相似文献
23.
Control of self-assembling systems at the micro- and nano-scale provides new opportunities for the engineering of novel materials in a bottom-up fashion. These systems have several challenges associated with control including high-dimensional and stochastic nonlinear dynamics, limited sensors for real-time measurements, limited actuation for control, and kinetic trapping of the system in undesirable configurations. Three main strategies for addressing these challenges are described, which include particle design (active self-assembly), open-loop control, and closed-loop (feedback) control. The strategies are illustrated using a variety of examples such as the design of patchy and Janus particles, the toggling of magnetic fields to induce the crystallization of paramagnetic colloids, and high-throughput crystallization of organic compounds in nanoliter droplets. An outlook of the future research directions and the necessary technological advancements for control of micro- and nano-scale self-assembly is provided. 相似文献
24.
Evidence suggests that transient visual information, such as animations, may be more challenging to learn than static visualizations. However, when a procedural-manipulative task is involved, our evolved embodied cognition seems to reverse this transitory challenge. Hence, for object manipulative tasks, instructional animations may be more suitable than statics. We investigated this argument further by comparing animations with statics using a Lego task shown to university students, by examining three potential moderators of effectiveness: (a) the environment of manipulation (virtual or physical), (b) the quality of visual information (focused or unfocused), and (c) the presence of hands (no hands or with hands). In Experiment 1 we found an advantage of animation over statics, and no differences among the environments. In Experiment 2, we again observed an animation advantage, a small advantage of focused static information compared to unfocused static information, and a positive effect of not showing the hands. 相似文献
25.
BDI模型能够很好地解决在特定环境下的Agent的推理和决策问题,但在动态和不确定环境下缺少决策和学习的能力。强化学习解决了Agent在未知环境下的决策问题,却缺少BDI模型中的规则描述和逻辑推理。针对BDI在未知和动态环境下的策略规划问题,提出基于强化学习Q-learning算法来实现BDI Agent学习和规划的方法,并针对BDI的实现模型ASL的决策机制做出了改进,最后在ASL的仿真平台Jason上建立了迷宫的仿真,仿真实验表明,在加入Q-learning学习机制后的新的ASL系统中,Agent在不确定环境下依然可以完成任务。 相似文献
26.
如何在海量不确定数据集中提高频繁模式挖掘性能是目前研究的热点.传统算法大多是以期望、概率或者权重等单一指标为数据项集支持度,在大数据背景下,同时考虑概率和权重支持度的算法难以兼顾其执行效率.为此,本文提出一种基于Spark的不确定数据集频繁模式挖掘算法(UWEFP),首先,为了同时兼顾数据项的概率和权重,计算一项集的最大概率权重值并进行剪枝;然后,为了减少对数据集的多次扫描,结合Spark框架的优点,设计了一种具有FP-tree特征的新颖的UWEFP-tree结构进行模式树的构建及挖掘;最后在Spark环境下,以UCI数据集进行实验验证.实验结果表明本文的方法在保证挖掘结果的同时,提高了效率. 相似文献
27.
This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning
of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed
Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given
visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample
size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive
experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr
and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood
(ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given
sparse data, while CL-AIC should be chosen given moderate or large data sample sizes. 相似文献
28.
29.
根据某面板堆石坝施工期、蓄水初期以及几年来的沉降观测资料,对坝体填筑材料计算参数进行反馈分析,得出了能够反映坝体实际变形的弹塑性应力变形计算参数,有利于今后建立大坝变形预报模型,更准确地把握大坝实时运行状态。 相似文献
30.
With the proliferation of mobile computing technologies, location based services have been identified as one of the most promising
target application. We classify mobile information service domains based on feature characteristics of the information sources
and different patterns of mobile information access. By carefully examining the service requirements, we identify the dynamic
data management problem that must be addressed for effective location based services in mobile environments. We then devise
a general architecture and cost model for servicing both location independent and location dependent data. Based on the architecture
and cost model, we propose a set of dynamic data management strategies that employs judicious caching, proactive server pushing
and neighborhood replication to reduce service cost and improve response time under changing user mobility and access patterns.
Detail behavior analysis helps us in precisely capturing when and how to apply these strategies. Simulation results suggest
that different strategies are effective for different types of data in response to different patterns of movement and information
access.
Shiow-yang Wu is an associate professor of the Department of Computer Science and Information Engineering at National Dong Hwa University,
Hualien, Taiwan, R.O.C. He received the BS and MS degrees in computer engineering from National Chiao Tung University, Hsinchu,
Taiwan, ROC, and the PhD degree in computer science from the University of Texas at Austin in 1984, 1986, and 1995, respectively.
His research interests include data/knowledge bases, mobile computing, distributed processing, intelligence information systems,
and electronic commerce.
Kun-Ta Wu was born in Taipei, Taiwan, R.O.C., in 1976. He received the B.S. degree in computer science from Soochow University, Taipei,
Taiwan, R.O.C., in 1999 and the M.S. degree in computer science and information engineering from National Dong Hwa University,
Hualien, Taiwan, R.O.C., in 2001.
Currently, he is an Assistant Researcher in the Domestic Division at Science and Technology Information Center, National Science
Council, R.O.C., as a member of Information Gathering and Analysis Group of National Information and Communication Security
Taskforce. His research interests include mobile computing, wireless network and information security. 相似文献