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arXiv 2022年

作者： Huang, Yi-Hua He, Yue Yuan, Yu-Jie Lai, Yu-Kun Gao, Lin Beijing Key Laboratory of Mobile Computing and Pervasive Device Institute of Computing Technology Chinese Academy of Sciences China School of Computer and Control Engineering University of Chinese Academy of Sciences China School of Computer Science & Informatics Cardiff University United Kingdom

3D scene stylization aims at generating stylized images of the scene from arbitrary novel views following a given set of style examples, while ensuring consistency when rendered from different views. Directly applying methods for image or video stylization to 3D scenes cannot achieve such consistency. Thanks to recently proposed neural radiance fields (NeRF), we are able to represent a 3D scene in a consistent way. Consistent 3D scene stylization can be effectively achieved by stylizing the corresponding NeRF. However, there is a significant domain gap between style examples which are 2D images and NeRF which is an implicit volumetric representation. To address this problem, we propose a novel mutual learning framework for 3D scene stylization that combines a 2D image stylization network and NeRF to fuse the stylization ability of 2D stylization network with the 3D consistency of NeRF. We first pre-train a standard NeRF of the 3D scene to be stylized and replace its color prediction module with a style network to obtain a stylized NeRF. It is followed by distilling the prior knowledge of spatial consistency from NeRF to the 2D stylization network through an introduced consistency loss. We also introduce a mimic loss to supervise the mutual learning of the NeRF style module and fine-tune the 2D stylization decoder. In order to further make our model handle ambiguities of 2D stylization results, we introduce learnable latent codes that obey the probability distributions conditioned on the style. They are attached to training samples as conditional inputs to better learn the style module in our novel stylized NeRF. Experimental results demonstrate that our method is superior to existing approaches in both visual quality and long-range consistency. Copyright © 2022, The Authors. All rights reserved.

关键词： Three dimensional computer graphics

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Estimation of environment models using vector field and its application to robot's contact tasks

Estimation of environment models using vector field and its ...

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International Conference on Neural Networks

作者： Zhi-Wei Luo K. Ito M. Yamakita Bio-Mimetic Control Research Center RIKEN Institute of Physical and Chemical Research Nagoya Japan Department of Information and Computer Sciences Toyohashi University of Technology Toyohashi Japan Faculty of Engineering Tokyo Institute of Technology Meguro Tokyo Japan

Earlier biological studies on the isolated spinal cord of the frog suggested that the premotor circuitry of the frog spinal cord is organized in a number of control modules, and the complex posture motion patterns are generated through the vectorial summation of these vector field forms of modules. Motivated by this study, in this paper, the authors suggest that, when a robot is performing the mechanical contact tasks on the uncertain environment, the internal model of the environment may also be represented in the form of a vector field. The authors show that such kind of environment model can be obtained by integrating the information of a robot's position and interaction force. The authors examine the effectiveness of this environment model in the robot's contact tasks via experiment and computer simulation.

关键词： Robots Motion control Biological system modeling Chemical technology Leg Force measurement Application software Biological control systems Isolation technology Spinal cord

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Advanced evaluation method for regional wind power prediction

Advanced evaluation method for regional wind power predictio...

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International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)

作者： Yu Liu Kai Bai Yang Cui Qi Yao North China Electric Power Research Institute Co. Ltd. Smart Grid and New Energy Institute Beijing China North China Electric Power University. School of Control and Computer Engineering Beijing China

ISBN: (纸本)9781509019717

Accurate wind power forecast is an important method for solving the utilization problem of new energy. Forecast evaluation results have been applied to the dynamic dispatch of power systems that utilize large-scale wind power. As the starting point in optimizing regional forecast evaluation, this study first gathered fully diverse power forecast evaluation indexes that are based on a traditional index. Second, a comprehensive evaluation method for regional wind power forecast was proposed using principal component analysis and the information entropy calculation method. Finally, the proposed method was used to evaluate the regional wind power forecast. The case study revealed comprehensive evaluations and increased scientific weight allocation. Results confirmed the correctness and rationality of the proposed method, which can serve as a reference for power systems.

关键词： Decision support systems Indexes Wind power generation Principal component analysis Entropy FAA Resource management

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Carbon-Aware Computing in a Network of Data Centers: A Hierarchical Game-Theoretic Approach

arXiv

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arXiv 2024年

作者： Breukelman, Enno Hall, Sophie Belgioioso, Giuseppe Dörfler, Florian The KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Division of Decision and Control Systems Malvinas väg 10 StockholmSE-100 44 Sweden The Automatic Control Laboratory Department of Electrical Engineering and Information Technology ETH Zurich Physikstrasse 3 Zürich8092 Switzerland

Over the past decade, the continuous surge in cloud computing demand has intensified data center workloads, leading to significant carbon emissions and driving the need for improving their efficiency and sustainability. This paper focuses on the optimal allocation problem of batch compute loads with temporal and spatial flexibility across a global network of data centers. We propose a bilevel game-theoretic solution approach that captures the inherent hierarchical relationship between supervisory control objectives, such as carbon reduction and peak shaving, and operational objectives, such as priority-aware scheduling. Numerical simulations with real carbon intensity data demonstrate that the proposed approach successfully reduces carbon emissions while simultaneously ensuring operational reliability and priority-aware scheduling. © 2024, CC BY-NC-ND.

关键词： Carbon

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TOWARDS RELIABLE DATA-BASED OPTIMAL AND PREDICTIVE control USING EXTENDED DMD

arXiv

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arXiv 2022年

作者： Schaller, Manuel Worthmann, Karl Philipp, Friedrich Peitz, Sebastian Nüske, Feliks Technische Universität Ilmemau Institute of Mathematics Optimization-based Control Group Germany Paderborn University Department of Computer Science Data Science for Engineering Germany Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany

While Koopman-based techniques like extended Dynamic Mode Decomposition are nowadays ubiquitous in the data-driven approximation of dynamical systems, quantitative error estimates were only recently established. To this end, both sources of error resulting from a finite dictionary and only finitely-many data points in the generation of the surrogate model have to be taken into account. We generalize the rigorous analysis of the approximation error to the control setting while simultaneously reducing the impact of the curse of dimensionality by using a recently proposed bilinear approach. In particular, we establish uniform bounds on the approximation error of state-dependent quantities like constraints or a performance index enabling data-based optimal and predictive control with guarantees. Copyright © 2022, The Authors. All rights reserved.

关键词： Dynamic mode decomposition

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Virtual production control system

Virtual production control system

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Haw-Ching Yang Ying-Liang Chen Min-Hsiung Hung Fan-Tien Cheng Institute of System Information and Control National Kaohsiung First University of Science and Technology Kaohsiung Taiwan Institute of Manufacturing Engineering National Cheng Kung University Tainan Taiwan Department of Computer Science Chinese Cultural University Taipei Taiwan

ISBN: (纸本)9781424454471

This work develops a novel virtual production control system (VPCS), which is allocated on a manufacturer side to adjust production pace of a supplier using a short-term demand plan for reducing inventory level. In addition to remotely monitoring production progress of a supplier, the proposed VPCS allows manufacturers to pre-schedule the latest outputs using an integer programming model, to simulate the short-term plan by a stochastic colored timed Petri Nets, and to adjust the production pace of the supplier via the plan. An industrial case study shows that the supplier inventory was reduced by 13.8% over that of the real inventory level with an order-fill rate exceeding 99.6% using the proposed VPCS.

关键词： Materials Programming Predictive models Data preprocessing Capacity planning

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A Dynamic Time Slot Algorithm Based on Throughput Optimization in IEEE 802.11 Wireless Networks

A Dynamic Time Slot Algorithm Based on Throughput Optimizati...

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IEEE International Symposium on Information (IT) in Medicine and Education, ITME

作者： Guonian Jin Shejie Lu Siping Hu Haihong Xu Jinfeng Gao Fang Liu Haitao Wu School of Computer Science and Technology Institute of Engineering and Technology Hubei University of Science and Technology Xianning PR China International Joint Laboratory of Behavior Optimization Control for Smart Robots College of Computer and Artificial Intelligence Huanghuai University Zhumadian PR China

In IEEE 802.11 wireless LAN, as the number of nodes increases, collisions will increase correspondingly, channel utilization will decline, and the total throughput will decline instead of increasing, leading to system performance degradation. Through in-depth analysis of the root cause of this problem, this paper designs a simple and effective algorithm, which uses ARMA filtering algorithm to measure the conditional collision probability and then calculate the number of nodes in the network. The AP tells all nodes in the network in the form of broadcast when the number of nodes in the network changes, after all nodes receive the broadcast sent by the AP, they dynamically adjust the network parameters accordingly. Finally, NS2 simulation software is used to conduct simulation experiments in a variety of network scenarios, and the experimental results verify that the algorithm in this paper is simple and effective, with less changes to IEEE 802.11, and is suitable for use and promotion in wireless networks. It can optimize the network system performance based on the number of nodes, improve the system throughput, and significantly improve the network performance. According to the number and density of nodes, the algorithm reduces the collision probability by dynamically adjusting the timeslot, accordingly increases the total network throughput, and achieves the purpose of effectively improving the network performance.

关键词： Degradation Wireless LAN Heuristic algorithms Wireless networks System performance Software algorithms Throughput

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Iterative Learning control for Network Systems with Communication Delay or Data Dropout

Iterative Learning Control for Network Systems with Communic...

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Joint 48th IEEE Conference on Decision and control and 28th Chinese control Conference

作者： Chunping Liu Jianxin Xu Jun Wu State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang University Department of Mechatronics Engineering Shaoxing College of Arts and Sciences Department of Electrical and Computer Engineering National University of Singapore Hangzhou Qian Jiang expert SUPCON Technology Co.Ltd.SUPCON Park

In this paper,iterative learning control(ILC) is applied to network-based control problems in which communication channels are subject to random transport delay and data *** averaging ILC algorithm is used to overcome the random *** analysis,it is shown that ILC can perform well and achieve asymptotical convergence in ensemble average along the iteration axis,as far as the probability of the transmission delay and data dropout are known a priori.A unique contribution in this work is to illustrate the applicability of ILC to nonlinear systems while both the one-step delay and the data-dropout phenomena are taken into *** analysis and simulations validate the effectiveness of the ILC algorithm for network-based control tasks.

关键词： ILC Iterative Learning control for Network Systems with Communication Delay or Data Dropout dropout

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Design and Analysis of Weather Parameters Using MEMS Technology with Suitable Characteristics for Integration into a Single Chip for Environment Monitoring

Design and Analysis of Weather Parameters Using MEMS Technol...

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Smart Technologies and Systems for Next Generation Computing (ICSTSN), International Conference on

作者： Abdurrashid S. Hassan Vimala A. Juliet G. Pius Agbulu G. Joselin Retna Kumar Raghavendra Reddy N V S Gunasekar Department of Electronics and Control/Instrumentation Engineering SRM Institute of Science and Technology Chennai Tamil Nadu India Department of Mechatronic Engineering School of Engineering Sciences & Technology Chinhoyi University of Technology Chinhoyi Zimbabwe Department of Electronics and Instrumentation Engineering SRM Institute of Science and Technology Chennai Tamil Nadu India Department of Mechanical Engineering RV Institute of Technology and Management Karnataka India Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India

ISBN: (数字)9798350391565

ISBN: (纸本)9798350391572

This study designs and simulates weather parameters using MEMS technology with suitable characteristics for integration into a single chip for environment monitoring. The sensing and heating filament of the temperature sensor was designed using a thin film platinum resistor, examining its ability to experience stability, increase in resistivity, accuracy, and free-contamination. The temperature sensing and heating element are based on platinum RTD (Resistance Temperature Detector) with meander shape and aluminum as the bonding pad connecting the sensor to the external circuit. A capacitive humidity sensor is implemented in consolidation with a piezoresistive pressure sensor with a square membrane. The capacitive humidity sensor with hole pattern at the upper plate and a polyimide serves as water absorbent sandwiched between the electrodes. The simulation analysis was conducted using finite element analysis in COMSOL Multiphysics version 6.0 . It was observed that the temperature increases from -100oC to - 20oC, and 10oC to 50oC respectively as a result of deviation in relative humidity in the troposphere, and atmosphere. The average changes in capacitances were found at 0.0713/%RH, while the pressure was examined to vary from 1050hPa to 5hPa in a step of 200hPa with a sensitivity of 11.50mv/bar.

关键词： Temperature sensors Temperature Platinum Terrestrial atmosphere Humidity Stability analysis Finite element analysis

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An Initial Research:Towards Accurate Pitch Extraction for Speech Synthesis Based on BLSTM

An Initial Research:Towards Accurate Pitch Extraction for Sp...

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2016 IEEE 13th International Conference on Signal Processing（ICSP2016）

作者： Yibin Zheng Zhengqi Wen Bin Liu Ya Li Jianhua Tao National Laboratory of Pattern Recognition Institute of AutomationChinese Academy Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences CAS Center for Excellence in Brain Science and Intelligence Technology Institute of AutomationChinese Academy Sciences

Accurate pitch extraction from speech is important but challenging problem for speech synthesis. However, the additive nature and long-term suprasegmental property of pitch features have not been fully exploited in most of the existing pitch estimators as they are operated frame by frame. As a result, they would cause some inherent discontinuities, such as double/half F0 errors and unvoiced/voiced(U/V) error. This would adversely affect the quality of synthetic speech as well as the expressiveness of the prosody information. In this paper, we explore the novel use of multi-tasks(Task 1: U/V;Task 2: Pitch) bidirectional long short-term memory recurrent neural network(BLSTM) to model the pitch and voicing decision simultaneously in a unified framework. The features used in this study are extracted from the frequency domain. We compute the log-frequency power spectrogram and then normalize to the long-term speech spectrum to attenuate noises. A filter is then used to enhance the harmonicity. Experiments show that the proposed approach substantially outperforms RAPT, which behaves the best in clean condition. Besides, our proposed approach can even work well with a certain level of background noise.

关键词： pitch extraction voicing decision BLSTM logfrequency power spectrogram speech synthesis

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